prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What is the electron correlation parameter, $\Gamma_e$?

Read the following text and answer briefly.

Context 1: \section{Introduction}

Ultracold neutral plasmas studied in the laboratory offer access to a regime of plasma physics that scales to describe thermodynamic aspects of important high-energy-density systems, including strongly coupled astrophysical plasmas \cite{VanHorn,Burrows}, as well as terrestrial sources of neutrons \cite{Hinton,Ichimaru_fusion,Atzeni,Boozer} and x-ray radiation \cite{Rousse,Esarey}   Yet, under certain conditions, low-temperature laboratory plasmas evolve with dynamics that are governed by the quantum mechanical properties of their constituent particles, and in some cases by coherence with an external electromagnetic field    

The relevance of ultracold plasmas to such a broad scope of problems in classical and quantum many-body physics has given rise to a great deal of experimental and theoretical research on these systems since their discovery in the late 90s   A series of reviews affords a good overview of progress in the last twenty years \cite{Gallagher,Killian_Science,PhysRept,Lyon}   Here, we focus on the subset of ultracold neutral plasmas that form via kinetic rate processes from state-selected Rydberg gases, and emphasize in particular the distinctive dynamics found in the evolution of molecular ultracold plasmas   

While molecular beam investigations of threshold photoionization spectroscopy had uncovered relevant effects a few years earlier \cite{Scherzer,Alt}, the field of ultracold plasma physics began in earnest with the 1999 experiment of Rolston and coworkers on metastable xenon atoms cooled in a magneto optical trap (MOT) \cite{Killian}   

This work and many subsequent efforts tuned the photoionization energy as a means to form a plasma of very low electron temperature built on a strongly coupled cloud of ultracold ions   Experiment and theory soon established that fast processes associated with disorder-induced heating and longer-time electron-ion collisional rate processes act to elevate the ion temperatures to around one degree Kelvin, and constrain the effective initial electron temperature to a range above 30 K \cite{Kuzmin,Hanson,Laha}   

This apparent limit on the thermal energy of the electrons can be more universally expressed for an expanding plasma by saying that the electron correlation parameter, $\Gamma_e$, does not exceed 0 25, where, 
\begin{equation}
\Gamma_e = \frac{e^2}{4\pi \epsilon_0 a_{ws}}\frac{1}{k_B T_e}
\label{eqn:gamma_e}
\end{equation}
defines the ratio of the average unscreened electron-electron potential energy to the electron kinetic energy   $a_{ws}$ is the Wigner-Seitz radius, related to the electron density by, $\rho_e = 1/(\frac{4}{3} \pi a_{ws}^3)$   These plasmas of weakly coupled electrons and strongly coupled ions have provided an important testing ground for ion transport theory and the study of electron-ion collision physics \cite{Strickler} 

Soon after the initial reports of ultracold plasmas formed by direct photoionization, a parallel effort began with emphasis on the plasma that forms spontaneously by Penning ionization and electron-impact avalanche in a dense ultracold Rydberg gas \cite{Mourachko}   This process affords less apparent control of the initial electron temperature   But, pulsed field-ionization measurements soon established that the photoionized plasma and that formed by the avalanche of a Rydberg gas both evolve to quasi-equilibria of electrons, ions and high-Rydberg neutrals \cite{Rolston_expand,Gallagher}   

Early efforts to understand plasmas formed by Rydberg gas avalanche paid particular attention to the process of initiation   Evolution to plasma in effusive atomic beams was long known for high-Rydberg gases of caesium and well explained by coupled rate equations \cite{Vitrant}   But, low densities and ultracold velocity distributions were thought to exclude Rydberg-Rydberg collisional mechanisms in a MOT   

In work on ultracold Rydberg gases of Rb and Cs, Gallagher, Pillet and coworkers describe the initial growth of electron signal by a model that includes ionization by blackbody radiation and collisions with a background of uncooled Rydberg atoms \cite{Mourachko,Gallagher,Li,Comparat,Tanner}  This picture was subsequently refined to include many-body excitation and autoionization, as well as attractive dipole-dipole interactions \cite{Viteau,Pillet}, later confirmed by experiments at Rice \cite{Mcquillen}   

The Orsay group also studied the effect of adding Rydberg atoms to an established ultracold plasma   They found that electron collisions in this environment completely ionize added atoms, even when selected to have deep binding energies \cite{Vanhaecke}   They concluded from estimates of electron trapping efficiency that the addition of Rydberg atoms does not significantly alter the electron temperature of the plasma   

Tuning pair distributions by varying the wavelength of the excitation laser, Weidem\"uller and coworkers confirmed the mechanical effects of van der Waals interactions on the rates of Penning ionization in ultracold $^{87}$Rb Rydberg gases \cite{Amthor_mech}   They recognized blackbody radiation as a possible means of final-state redistribution, and extended this mechanical picture to include long-range repulsive interactions \cite{Amthor_model}   This group later studied the effects of spatial correlations in the spontaneous avalanche of Rydberg gases in a regime of strong blockade, suggesting a persistence of initial spatial correlations \cite{RobertdeSaintVincent}   

Robicheaux and coworkers have recently investigated the question of prompt many-body ionization from the point of view of Monte Carlo classical trajectory calculations \cite{Goforth}   For atoms on a regular or random grid driven classically by an electromagnetic field, they find that many-body excitation enhances prompt ionization by about twenty percent for densities greater than $5 6 \times 10^{-3}/(n_0^2 a_0)^3$, where $n_0$ is the principal quantum number of the Rydberg gas and $a_0$ is the Bohr radius   They observed that density fluctuations (sampled from the distribution of nearest neighbour distances) have a greater effect, and point to the possible additional influence of secondary electron-Rydberg collisions and the Penning production of fast atoms not considered by the model, but already observed by Raithel and coworkers \cite{Knuffman}   

The Raithel group also found direct evidence for electron collisional $\ell$-mixing in a Rb MOT \cite{Dutta}, and used selective field ionization to monitor evolution to plasma on a microsecond timescale in ultracold $^{85}$Rb $65d$ Rydberg gases with densities as low as $10^8$ cm$^{-3}$ \cite{WalzFlannigan}   Research by our group at UBC has observed very much the same dynamics in the relaxation of Xe Rydberg gases of similar density prepared in a molecular beam \cite{Hung2014}   In both cases, the time evolution to avalanche is well-described by coupled rate equations (see below), assuming an initializing density of Penning electrons determined by Robicheaux's criterion \cite{Robicheaux05}, applied to an Erlang distribution of Rydberg-Rydberg nearest neighbours   

Theoretical investigations of ultracold plasma physics have focused for the most part on the long- and short-time dynamics of plasmas formed by direct photoionization \cite{PhysRept,Lyon}   In addition to studies mentioned above, key insights on the evolution dynamics of Rydberg gases have been provided by studies of Pohl and coworkers exploring the effects of ion correlations and recombination-reionization on the hydrodynamics of plasma expansion \cite{Pohl:2003,PPR}   Further research has drawn upon molecular dynamics (MD) simulations to reformulate rate coefficients for the transitions driven by electron impact between highly excited Rydberg states \cite{PVS}, and describe an effect of strong coupling as it suppresses three-body recombination \cite{Bannasch:2011}   MD simulations confirm the accuracy of coupled rate equation descriptions for systems with $\Gamma$ as large as 0 3   Newer calculations suggest a strong connection between the order created by dipole blockade in Rydberg gases and the most favourable correlated distribution of ions in a corresponding strongly coupled ultracold plasma \cite{Bannasch:2013}   

Tate and coworkers have studied ultracold plasma avalanche and expansion theoretically as well as experimentally   Modelling observed expansion rates, they recently found that $^{85}$Rb atoms in a MOT form plasmas with effective initial electron temperatures determined by initial Rydberg density and the selected initial binding energy, to the extent that these parameters determine the fraction of the excited atoms that ionize by electron impact in the avalanche to plasma \cite{Forest}   This group also returned to the question of added Rydberg atoms, and managed to identify a crossover in $n_0$, depending on the initial electron temperature, that determines whether added Rydberg atoms of a particular initial binding energy act to heat or cool the electron temperature \cite{Crockett}    

Our group has focused on the plasma that evolves from a Rydberg gas under the low-temperature conditions of a skimmed, seeded supersonic molecular beam   In work on nitric oxide starting in 2008 \cite{Morrison2008,Plasma_expan,Morrison_shock,PCCP}, we established an initial kinetics of electron impact avalanche ionization that conforms with coupled rate equation models \cite{Saquet2011,Saquet2012,Scaling,haenelCP} and agrees at early times with the properties of ultracold plasmas that evolve from ultracold atoms in a MOT   We have also observed unique properties of the NO ultracold plasma owing to the fact that its Rydberg states dissociate \cite{Haenel2017}, and identified relaxation pathways that may give rise to quantum effects \cite{SousMBL,SousNJP}   The remainder of this review focuses on the nitric oxide ultracold plasma and the unique characteristics conferred by its evolution from a Rydberg gas in a laser-crossed molecular beam   


\section{Avalanche to strong coupling in a molecular Rydberg gas}

\subsection{The molecular beam ultracold plasma compared with a MOT}

When formed with sufficient density, a Rydberg gas of principal quantum number $n_0>30$ undergoes a spontaneous avalanche to form an ultracold plasma \cite{Li,Morrison2008,RobertdeSaintVincent}   Collisional rate processes combine with ambipolar hydrodynamics to govern the properties of the evolving plasma   For a molecular Rydberg gas, neutral fragmentation, occurs in concert with electron-impact ionization, three-body recombination and electron-Rydberg inelastic scattering   Neutral dissociation combined with radial expansion in a shaped distribution of charged particles, can give rise to striking effects of self-assembly and spatial correlation \cite{Schulz-Weiling2016,Haenel2017}    

The formation of a molecular ultracold plasma requires the conditions of local temperature and density afforded by a high mach-number skimmed supersonic molecular beam   Such a beam propagates at high velocity in the laboratory, with exceedingly well-defined hydrodynamic properties, including a propagation-distance-dependent density and sub-Kelvin temperature in the moving frame \cite{MSW_tutorial}   The low-temperature gas in a supersonic molecular beam differs in three important ways from the atomic gas laser-cooled in a magneto-optical trap (MOT) 

The milli-Kelvin temperature of the gas of ground-state NO molecules entrained in a beam substantially exceeds the sub-100 micro-Kelvin temperature of laser-cooled atoms in a MOT   However, the evolution to plasma tends to erase this distinction, and the two further characteristics that distinguish a beam offer important advantages for ultracold plasma physics:  Charged-particle densities in a molecular beam can exceed those attainable in a MOT by orders of magnitude   A great many different chemical substances can be seeded in a free-jet expansion, and the possibility this affords to form other molecular ultracold plasmas, introduces interesting and potentially important new degrees of freedom governing the dynamics of their evolution 


\subsection{Supersonic molecular beam temperature and particle density}

Seeded in a skimmed supersonic molecular beam, nitric oxide forms different phase-space distributions in the longitudinal (propagation) and transverse coordinate dimensions   As it propagates in $z$, the NO molecules reach a terminal laboratory velocity, $u_{\parallel}$, of about 1400 ${\rm ms^{-1}}$, which varies with the precise seeding ratio   

The distribution of $v_{\parallel}$, narrows to define a local temperature, $T_{\parallel}$, of approximately 0 5 K   The beam forms a Gaussian spatial distribution in the transverse coordinates, $x$ and $y$   In this plane, the local velocity, $v_{\perp}(r)$ is defined for any radial distance almost entirely by the divergence velocity of the beam, $u_{\perp}(r)$   Phase-space sorting cools the temperature in the transverse coordinates, $T_{\perp}$ to a value as low as $\sim 5$ mK \cite{MSW_tutorial}   

The stagnation pressure and seeding ratio determine the local density distribution as a function of $z$   For example, expanding from a stagnation pressure of 500 kPa with a 1:10 seeding ratio, a molecular beam propagates 2 5 cm to a skimmer and then 7 5 cm to a point of laser interaction, where it contains NO at a peak density of $1 6 \times 10^{14}$ cm$^{-3}$   

Here, crossing the molecular beam with a laser beam tuned to the transition sequence, ${\rm X} ~^2 \Pi_{1/2} ~N'' = 1 \xrightarrow{\omega_1} {\rm A} ~^2\Sigma^+ ~N'=0  \xrightarrow{\omega_2} n_0 f(2)$ forms a Gaussian ellipsoidal volume of Rydberg gas in a single selected principal quantum number, $n_0$, orbital angular momentum, $\ell = 3$, NO$^+$ core rotational quantum number, $N^+ = 2$ and total angular momentum neglecting spin, $N=1$   

A typical $\omega_1$ pulse energy of 2 $\mu$J and a Gaussian width of 0 2 mm serves to drive the first step of this sequence in a regime of linear absorption   Overlapping this volume by an $\omega_2$ pulse with sufficient fluence to saturate the second step forms a Rydberg gas ellipsoid with a nominal peak density of $5 \times 10^{12}$ cm$^{-3}$  \cite{Morrison2008,MSW_tutorial}   Fluctuations in the pulse energy and longitudinal mode of $\omega_1$ cause the real density to vary   For certain experiments, we find it convenient to saturate the $\omega_1$ transition, and vary the density of Rydberg gas by delaying $\omega_2$   An $\omega_1$-$\omega_2$ delay, $\Delta t$, reduces the Rydberg gas density by a precise factor, $e^{-\Delta t/\tau}$, where $\tau$ is the 200 ns radiative lifetime of NO ${\rm A} ~^2\Sigma^+ ~N'=0$ \cite{Carter,Hancock} 


\subsection{Penning ionization}

The density distribution of a Rydberg gas defines a local mean nearest neighbour distance, or Wigner-Seitz radius of $ a_{ws} =  \left(3/4 \pi \rho \right)^{1/3} $, where $\rho$ refers to the local Rydberg gas density   For example, a Rydberg gas with a density of $ \rho_0=0 5 \times 10^{12}$ cm$^{-3} $ forms an Erlang distribution \cite{Torquato 1990} of nearest neighbour separations with a mean value of $ 2 a_{ws}=1 6$  $\mu$m   

A semi-classical model \cite{Robicheaux05} suggests that 90 percent of Rydberg molecule pairs separated by a critical distance, $ r_c = 1 8 \cdot 2 n_0^2 a_0 $ or less undergo Penning ionization within 800 Rydberg periods   We can integrate the Erlang distribution from $ r=0 $ to the critical distance $r = r_c$ for a Rydberg gas of given $n_0$, to define the local density of Penning electrons ($ \rho_e$ at $t=0$) produced by this prompt interaction, for any given initial local density, $\rho_0$ by the expression:
\begin{equation}
\rho_e(\rho_0,n_0) = \frac{0 9}{2} \cdot 4 \pi \rho_0 ^2\int_0^{r_{c}} r^2 \mathrm{e}^{-\frac{4\pi}{3}\rho_0 r^3}\mathrm{d}r \quad 
\label{eqn:Erlang}
\end{equation}

Evaluating this definite integral yields an equation in closed form that predicts the Penning electron density for any particular initial Rydberg density and principal quantum number 
\begin{equation}
\rho_e(\rho_0,n_0) =\frac{0 9 \rho_0}{2}(1-\mathrm{e}^{-\frac{4\pi}{3}\rho_0 r_c^3}) \quad 
\label{Eq:PenDens}
\end{equation}
\begin{figure}[h!]
\centering
\includegraphics[scale=0 33]{Penning_Latice pdf}
\caption{Distributions of ion-ion nearest neighbours following Penning ionization and electron-impact avalanche simulated for a predissociating molecular Rydberg gas of initial principal quantum number, $n_0$, from 30 to 80, and density of 10$^{12}$ cm$^{-3}$   Dashed lines mark corresponding values of $a_{ws}$  Calculated by counting ion distances after relaxation to plasma in 10$^6$-particle stochastic simulations  Integrated areas proportional to populations surviving neutral dissociation }
\label{fig:PL}
\end{figure}

Prompt Penning ionization acts on the portion of the initial nearest-neighbour distribution in the Rydberg gas that lies within $r_c$   When a molecule ionizes, its collision partner relaxes to a lower principal quantum number, $n'<n_0/\sqrt{2}$   This close-coupled interaction disrupts the separability of Rydberg orbital configurations in the Penning partner   This causes mixing with core penetrating states that are strongly dissociative   Penning partners are thus very likely to dissociate, leaving a spatially isolated distribution of ions   We refer to the spatial correlation that results as a Penning lattice \cite{Sadeghi:2014}   The extent of this effect varies depending on the local density and the selected initial principal quantum number   Figure \ref{fig:PL} shows the degree to which Rydberg gases with initial principal quantum numbers from 30 to 80 form a Penning lattice for an initial density of $1 \times 10^{12} ~{\rm cm}^{-3}$   

\subsection{Spontaneous electron-impact avalanche}

The electrons produced by prompt Penning ionization start an electron impact avalanche   The kinetics of this process are well described by a set of coupled rate equations that account for state-to-state electron-Rydberg inelastic scattering, electron-impact ionization and three-body ion-electron recombination \cite{PPR,Saquet2011,Saquet2012,Scaling} using detailed rate coefficients,  $k_{ij}$, $k_{i,ion}$ and $k_{i,tbr}$ validated by MD simulations \cite{PVS}   
\begin{eqnarray}
-\frac{d\rho_i}{dt}&=&\sum_{j}{k_{ij}\rho_e\rho_i}-\sum_{j}{k_{ji}\rho_e\rho_j} \nonumber\\
&& +k_{i,ion}\rho_e\rho_i-k_{i,tbr}\rho^3_e 
  \label{level_i}
\end{eqnarray}
\noindent and,
\begin{equation}
\frac{d\rho_e}{dt}=\sum_{i}{k_{i,ion}\rho_e^2}-\sum_{i}{k_{i,tbr}\rho^3_e}
  \label{electron}
\end{equation}

The relaxation of Rydberg molecules balances with collisional ionization to determine an evolving temperature of avalanche electrons to conserve total energy per unit volume  
\begin{equation}
E_{tot}=\frac{3}{2}k_BT_e(t)\rho_e(t)-R\sum_i{\frac{\rho_i(t)}{n_i^2}},
  \label{energy}
\end{equation}
Here, for simplicity, we neglect the longer-time effects of Rydberg predissociation and electron-ion dissociative recombination \cite{Saquet2012} 

Such calculations show that the conversion from Rydberg gas to plasma occurs on a timescale determined largely by the local Penning electron density, or Penning fraction, $P_f = \rho_e/\rho_0$, which depends on the local density of Rydberg molecules and their initial principal quantum number   

Avalanche times predicted by coupled rate equation calculations range widely   For example, in a model developed for experiments on xenon, simulations predict that a Rydberg gas with $n_0 = 42$ at a density of $8 8 \times 10^8 ~{\rm cm}^{-3}$ ($P_f = 6 \times 10^{-5}$) avalanches with a half time of  40 $\mu$s \cite{Hung2014}   At an opposite extreme, rate equations estimate that a Rydberg gas of NO with $n_0=60$ at a density of $1 \times 10^{12} ~{\rm cm}^{-3}$ ($P_f = 0 3$) rises to plasma in about 2 ns \cite{Saquet2012}   

\begin{figure}[h!]
\centering
\includegraphics[width=  49 \textwidth]{SFI_n=49 pdf}
   \caption{Contour plots showing SFI signal as a function the applied field for an $nf(2)$ Rydberg gas with an initial principal quantum number, $n_0=49$   Each frame represents 4,000 SFI traces, sorted by initial Rydberg gas density   Ramp field beginning at 0 and 150 ns (top, left to right), and  300 and 450 ns (bottom) after the $\omega_2$ laser pulse   The two bars of signal most evident at early ramp field delay times represent the field ionization of the $49f(2)$ Rydberg state respectively to NO$^+$ X $^1\Sigma^+$ cation rotational states, $N^+=0$ and 2   The signal waveform extracted near zero applied field represents the growing population of plasma electrons   
   }
\label{fig:SFI}
\end{figure}

Selective field ionization (SFI) probes the spectrum of binding energies in a Rydberg gas   Applied as a function of time after photoexcitation, SFI maps the evolution from a state of selected initial principal quantum number, $n_0$, to plasma \cite{Haenel2017}   Figure \ref{fig:SFI} shows SFI spectra taken at a sequence of delays after the formation of $49f(2)$ Rydberg gases of varying density     

Here, we can see that a $49f(2)$ Rydberg gas with an estimated initial density $\rho_0 = 3 \times 10^{11} ~{\rm cm}^{-3}$ relaxes to plasma on a timescale of about 500 ns   Observations such as these agree well with the predictions of coupled rate-equation calculations   We can understand this variation in relaxation dynamics with $\rho_0$ and $n_0$ quite simply in terms of the corresponding density of prompt Penning electrons these conditions afford to initiate the avalanche to plasma   

Figure \ref{fig:scaled_rise} illustrates this, showing how rise times predicted by coupled rate-equation simulations for a large range of initial densities and principal quantum number match when plotted as a function of time scaled by the ultimate plasma frequency and fraction of prompt Penning electrons   The dashed line gives an approximate account of the scaled rate of avalanche under all conditions of Rydberg gas density and initial principal quantum number in terms of the simple sigmoidal function:

\begin{equation}
\frac{\rho_e}{\rho_0} = \frac{a}{b+e^{-c\tau}},
  \label{scaledEq1}
\end{equation}
where,
\begin{equation}
\tau = t \omega_e P_f^{3/4},
  \label{scaledEq2}
\end{equation}
in which $\omega_e$ is the plasma frequency after avalanche, $P_f$ is the fraction of prompt Penning electrons, and $a = 0 00062$,  $b =   0 00082$ and $c =     0 075$ are empirical coefficients   

\begin{figure}[h!]
\centering
\includegraphics[width=  4 \textwidth]{sim_analytical_density pdf}
   \caption{Rise in fractional electron density as a function of time scaled by the plasma frequency, $\omega_e$ and fraction, $\rho_e(t=0)/\rho_0 = P_f$, of prompt Penning electrons   Simulation results shown for $n_0 = 30$, 50 and 70 with initial densities, $\rho_0 = 10^9,~10^{10},~10^{11},~{\rm and}~10^{12}~{\rm cm}^{-3}$   
   }
\label{fig:scaled_rise}
\end{figure}


\subsection{Evolution to plasma in a Rydberg gas Gaussian ellipsoid}

As outlined above, the local density and principal quantum number together determine the rate at which a Rydberg gas avalanches to plasma   Our experiment crosses a 2 mm wide cylindrically Gaussian molecular beam with a 1 mm diameter TEM$_{00}$ $\omega_1$ laser beam to produce a Gaussian ellipsoidal distribution of molecules excited to the A $^2\Sigma^+$ $v=0, ~N'=0$ intermediate state   A larger diameter $\omega_2$ pulse then drives a second step that forms a Rydberg gas in a single $n_0f(2)$ state with the spatial distribution of the intermediate state   

We model this shaped Rydberg gas as a system of 100 concentric ellipsoidal shells of varying density \cite{haenelCP}   Coupled rate equations within each shell describe the avalanche to plasma   This rate process proceeds from shell to shell with successively longer induction periods, determined by the local density as detailed above   The rising conversion of Rydberg molecules to ions plus neutral dissociation products conserves the particle number in each shell   We assume that local space charge confines electrons to shells, conserving quasi-neutrality   Electrons exchange kinetic energy at the boundaries of each shell, which determines a single plasma electron temperature   

\begin{figure}[h!]
\centering
\includegraphics[width=  5 \textwidth]{shell_model_100}
   \caption{(top frame) Cross-sectional contour diagram in the $x,y$ plane for $z=0$ describing the distribution of ion plus electron density over 100 shells of Gaussian ellipsoid with initial dimensions, $\sigma_x= 0 75$ mm and $\sigma_y= \sigma_z = 0 42$ mm and an initial $n_0 = 50$ Rydberg gas density, $\rho_0 = 2 \times 10^{11}$ cm$^{3}$ after an evolution time of 100 ns   (bottom frame) Curves describing the (dashed) ascending ion and (solid) descending Rydberg gas densities of each shell as functions of evolution time, for $t=20$, 40, 60, 80 and 100 ns   
   }
\label{fig:shell}
\end{figure}

The upper frame of Figure \ref{fig:shell} shows contours of NO$^+$ ion density after 100 ns obtained from a shell-model coupled rate-equation simulation of the avalanche of a Gaussian ellipsoidal Rydberg gas of nitric oxide with a selected initial state, $50f(2)$ and a density of $2 \times 10^{11}$ cm$^{-3}$   Here, we simulate a relaxation that includes channels of predissociation at every Rydberg level and redistributes the energy released to electrons, which determines a uniform rising electron temperature for all shells   

For comparison, the lower frame plots curves describing the ion density of each shell as a function of time from 20 to 100 ns, as determined by applying Eq \ref{scaledEq1} for the local conditions of initial Rydberg gas density   This numerical approximation contains no provision for predissociation   Coupled rate-equation simulations for uniform volumes show that predissociation depresses yield to some degree, but has less effect on the avalanche kinetics \cite{Saquet2012}   Therefore, we can expect sets of numerically estimated shell densities, scaled to agree with the simulated ion density at the elapsed time of 100 ns to provide a reasonable account of the earlier NO$^+$ density profiles as a function of time    


\begin{figure}[h!]
\centering
\includegraphics[width=  4 \textwidth]{Shell_pop}
   \caption{Global population fractions of particles as they evolve in the avalanche of a shell-model ellipsoidal Rydberg gas with the initial principal quantum number and density distribution of Figure \ref{fig:shell}
   }
\label{fig:shell_yields}
\end{figure}

For each time step, the difference, $\rho_0 - \rho_e$ defines the neutral population of each shell   We assign a fraction of this population to surviving Rydberg molecules, such that the total population of NO$^*$ as a function of time agrees with the prediction of the shell-model simulation, as shown in Figure \ref{fig:shell_yields}   We consider the balance of this neutral population to reflect NO$^*$ molecules that have dissociated to form N($^4$S) $+$ O($^3$P)   Figure \ref{fig:shell} plots these surviving Rydberg densities as a function of radial distance for each evolution time   At the initial density of this simulation, note at each time step that a higher density of Rydberg molecules encloses the tail of the ion density distribution in $x$    

\subsection{Plasma expansion and NO$^+$ - NO$^*$ charge exchange as an avenue of quench}

We regard the ions as initially stationary   The release of electrons creates a radial electric potential gradient, which gives rise to a force, $-e\nabla \phi_{k,j}(t)$, that accelerates the ions in shell $j$ in direction $k$ according to \cite{Sadeghi 2012}:

\begin{align}
\frac{-e}{m'}\nabla \phi_{k,j}(t) = & \frac{\partial u_{k,j}(t)}{\partial t} \notag  \\
= & \frac{k_BT_e(t)}{m'\rho_j(t)} \frac{\rho_{j+1}(t) - \rho_j(t)}{r_{k,j+1}(t) - r_{k,j}(t)},
  \label{dr_dt}
\end{align}

\noindent where $\rho_j(t)$ represents the density of ions in shell $j$   

The instantaneous velocity, $u_{k,j}(t)$ determines the change in the radial coordinates of each shell, $r_{k,j}(t)$, 
\begin{equation}
\frac{\partial r_{k,j}(t)}{\partial t}=u_{k,j}(t) = \gamma_{k,j}(t) r_{k,j}(t),
  \label{dr_dt}
\end{equation}
\noindent which in turn determines shell volume and thus its density, $ \rho_j(t)$    
The electron temperature supplies the thermal energy that drives this ambipolar expansion   Ions accelerate and $T_e$ falls according to: 

\begin{equation}
\frac{3k_B}{2}\frac{\partial T_e(t)}{\partial t}= -\frac{m'}{\sum_{j}{N_j}}\sum_{k,j}{N_j u_{k,j}(t)\frac{\partial u_{k,j}(t)}{\partial t}},
  \label{dr_dt}
\end{equation}
\noindent where we define an effective ion mass, $m'$, that recognizes the redistribution of the electron expansion force over all the NO$^+$ charge centres by resonant ion-Rydberg charge exchange, which occurs with a very large cross section \cite{PPR}   
\begin{equation}
m' =\left (1+ \frac{\rho^*_{j}(t)}{ \rho_j(t)}\right) m ,
  \label{dr_dt}
\end{equation}
\noindent in which $\rho^*_{j}(t)$ represents the instantaneous Rydberg density in shell $j$ 

The initial avalanche in the high-density core of the ellipsoid leaves few Rydberg molecules, so this term has little initial effect   Rydberg molecules predominate in the lower-density wings   There, momentum sharing by charge exchange assumes a greater importance   

We see this most directly in the $\omega_2$ absorption spectrum of transitions to states in the $n_0 f(2)$ Rydberg series, detected as the long-lived signal that survives a flight time of 400 $\mu$s to reach the imaging detector   The balance between the rising density of ions and the falling density of Rydberg molecules depends on the initial density of electrons produced by prompt Penning ionization   As clear from Eq \ref{Eq:PenDens}, this Penning fraction depends sensitively on the principal quantum number, and for all principal quantum numbers, on the initial Rydberg gas density   

\begin{figure}[h!]
\centering
\includegraphics[width=  4 \textwidth]{w2_spectra}
   \caption{Double-resonant spectra of nitric oxide Rydberg states in the $nf$ series converging to NO$^+$ $v=0$, $N^+=2$ (designated, $nf(2)$), derived from the late-peak signal obtained after a flight time of 400 $\mu$s by scanning $\omega_2$ for $\omega_1$ tuned to NO A $^2\Sigma^+$ $v=0$, $N'=0$ for initial $nf(2)$ densities from top to bottom of 0 07, 0 10, 0 13, 0 19, 0 27, 0 30, 0 32 and $3 \times 10^{12}$ cm$^{3}$   
  }
\label{fig:w2_spectra}
\end{figure}

Figure \ref{fig:w2_spectra} shows a series of $\omega_2$ late-signal excitation spectra for a set of initial densities   Here, we see a clear consequence of the higher-order dependence of Penning fraction - and thus the NO$^+$ ion - NO$^*$ Rydberg molecule balance - on $n_0$, the $\omega_2$-selected Rydberg gas initial principal quantum number   This Penning-regulated NO$^+$ ion - NO$^*$ Rydberg molecule balance appears necessary as a critical factor in achieving the long ultracold plasma lifetime required to produce this signal   We are progressing in theoretical work that explains the stability apparently conferred by this balance   


\subsection{Bifurcation and arrested relaxation}

Ambipolar expansion quenches electron kinetic energy as the initially formed plasma expands   Core ions follow electrons into the wings of the Rydberg gas   There, recurring charge exchange between NO$^+$ ions and NO$^*$ Rydberg molecules redistributes the ambipolar force of the expanding electron gas, equalizing ion and Rydberg velocities   This momentum matching effectively channels electron energy through ion motion into the overall $\pm x$ motion of gas volumes in the laboratory   The internal kinetic energy of the plasma, which at this point is defined almost entirely by the ion-Rydberg relative motion, falls   Spatial correlation develops, and over a period of 500 ns, the system forms the plasma/high-Rydberg quasi-equilibrium dramatically evidenced by the SFI results in Figure \ref{fig:SFI}   

\begin{figure}[h!]
\centering
\includegraphics[width=  4 \textwidth]{Bifurcation pdf}
   \caption{$x,y$ detector images of ultracold plasma volumes produced by 2:1 aspect ratio ellipsoidal Rydberg gases with selected initial state, $40f(2)$ after a flight time of 402 $\mu$s over a distance of 575 mm   Lower frame displays the distribution in $x$ of the charge integrated in $y$ and $z$   Both images represent the unadjusted raw signal acquired in each case after 250 shots   
   }
\label{fig:bifurcation}
\end{figure}

In the wings, momentum redistribution owing to cycles of ion-Rydberg charge transfer retards radial expansion \cite{Pohl2003,PPR}   By redirecting electron energy from ambipolar acceleration to $\pm x$ plasma motion, NO$^+$ to NO$^*$ charge exchange dissipates electron thermal energy   This redistribution of energy released in the avalanche of the Rydberg gas to plasma, causes the ellipsoidal Rydberg gas to bifurcate \cite{Schulz-Weiling2016,Haenel2017}, forming very long-lived, separating charged-particle distributions   We capture the electron signal from these recoiling volumes on an imaging detector as pictured in Figure \ref{fig:bifurcation}   Here, momentum matching preserves density and enables ions and Rydberg molecules to relax to positions that minimize potential energy, building spatial correlation   

The semi-classical description of avalanche and relaxation outlined above forms an important point of reference from which to interpret our experimental observations   The laser crossed molecular beam illumination geometry creates a Rydberg gas with a distinctively shaped high-density spatial distribution   This initial condition has an evident effect on the evolution dynamics   We have developed semi-classical models that explicitly consider the coupled rate and hydrodynamic processes governing the evolution from Rydberg gas to plasma using a realistic, ellipsoidal representation of the ion/electron and Rydberg densities \cite{haenelCP}   No combination of initial conditions can produce a simulation that conforms classically with the state of arrested relaxation we observe experimentally  


\subsection{A molecular ultracold plasma state of arrested relaxation}

Thus, we find that spontaneous avalanche to plasma splits the core of an ellipsoidal Rydberg gas of nitric oxide  As ambipolar expansion quenches the electron temperature of this core plasma, long-range, resonant charge transfer from ballistic ions to frozen Rydberg molecules in the wings of the ellipsoid quenches the ion-Rydberg molecule relative velocity distribution  This sequence of steps gives rise to a remarkable mechanics of self-assembly, in which the kinetic energy of initially formed hot electrons and ions drives an observed separation of plasma volumes  These dynamics redistribute ion momentum, efficiently channeling electron energy into a reservoir of mass-transport  This starts a process that evidently anneals separating volumes to a state of cold, correlated ions, electrons and Rydberg molecules  

We have devised a three-dimensional spin model to describe this arrested state of the ultracold plasma in terms of two, three and four-level dipole-dipole energy transfer interactions (spin flip-flops), together with Ising interactions that arise from the concerted pairwise coupling of resonant pairs of dipoles \cite{SousMBL,SousNJP}   

The Hamiltonian includes the effects of onsite disorder owing to the broad spectrum of states populated in the ensemble and the unique electrostatic environment of every dipole   Extending ideas developed for simpler systems \cite{Burin1,Sondhi}, one can make a case for slow dynamics, including an arrest in the relaxation of NO Rydberg molecules to predissociating states of lower principal quantum number 

Systems of higher dimension ought to thermalize by energy transfer that spreads from rare but inevitable ergodic volumes (Griffiths regions) \cite{Sarang2, Roeck_griffith, RareRegions_rev, Thermal_inclusions}   However, a feature in the self-assembly of the molecular ultracold plasma may preclude destabilization by rare thermal domains:  Whenever the quenched plasma develops a delocalizing Griffiths region, the local predissociation of relaxing NO molecules promptly proceeds to deplete that region to a void of no consequence 

In summary, the classical dynamics of avalanche and bifurcation appear to create a quenched condition of low temperature and high disorder in which dipole-dipole interactions drive self-assembly to a localized state purified by the predissociation of thermal regions   We suggest that this state of the quenched ultracold plasma offers an experimental platform for studying quantum many-body physics of disordered systems  \\

\section{Acknowledgments}
This work was supported by the US Air Force Office of Scientific Research (Grant No  FA9550-17-1-0343), together with the Natural Sciences and Engineering research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI) and the British Columbia Knowledge Development Fund (BCKDF)  





ground_truth: It is the ratio of the average unscreened electron-electron potential energy to kinetic energy.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What are some reasons for the lack of data sharing in archaeobotany?

Read the following text and answer briefly.

Context 2: Sowing the Seeds of Future Research: Data Sharing, Citation and Reuse in Archaeobotany
Reading: Sowing the Seeds of Future Research: Data Sharing, Citation and Reuse in Archaeobotany
University of Oxford, GB
Lisa is a post-doctoral research fellow at All Souls College, University of Oxford  Her publications include the co-authored volume The Rural Economy of Roman Britain (Britannia Monographs, 2017)  Her research interests are focussed on agricultural practices in the later prehistoric and Roman period and the utilisation of archaeobotanical data to investigate human-plant relationships 
The practices of data sharing, data citation and data reuse are all crucial aspects of the reproducibility of archaeological research  This article builds on the small number of studies reviewing data sharing and citation practices in archaeology, focussing on the data-rich sub-discipline of archaeobotany  Archaeobotany is a sub-discipline built on the time-intensive collection of data on archaeological plant remains, in order to investigate crop choice, crop husbandry, diet, vegetation and a wide range of other past human-plant relationships  Within archaeobotany, the level and form of data sharing is currently unknown  This article first reviews the form of data shared and the method of data sharing in 239 articles across 16 journals which present primary plant macrofossil studies  Second, it assesses data-citation in meta-analysis studies in 107 articles across 20 journals  Third, it assesses data reuse practices in archaeobotany, before exploring how these research practices can be improved to benefit the rigour and reuse of archaeobotanical research 
Keywords: Archaeobotany, Data reuse, Data sharing, Open science
How to Cite: Lodwick, L , 2019  Sowing the Seeds of Future Research: Data Sharing, Citation and Reuse in Archaeobotany  Open Quaternary, 5(1), p 7  DOI: http://doi org/10 5334/oq 62
Accepted on 29 May 2019 Submitted on 25 Mar 2019
Archaeology is a discipline built on the production and analysis of quantitative data pertaining to past human behaviour  As each archaeological deposit is a unique occurrence, ensuring that the data resulting from excavation and analysis are preserved and accessible is crucially important  Currently, there is a general perception of a low level of data sharing and reuse  Such a low level of data availability would prevent the assessment of research findings and the reuse of data in meta-analysis (Kansa & Kansa 2013; Moore & Richards 2015)  As observed across scientific disciplines, there is a major problem in the reproduction of scientific findings, commonly known as the ‘replication crisis’ (Costello et al  2013)  A range of intersecting debates contribute to this, including access to academic findings (open access), open data, access to software and access to methodologies, which can be broadly grouped as open science practices  Without these, the way that scientific findings can be verified and built upon is impaired  Questions of reproducibility have been raised in recent years in archaeology, with considerations of a range of practices which can improve the reproducibility of findings, and a recent call for the application of open science principles to archaeology (Marwick et al  2017)  Discussion has so far focussed on access to grey literature (Evans 2015), data sharing (Atici et al  2013), data citation practices (Marwick & Pilaar Birch 2018) and computational reproducibility (Marwick 2017), with a focus on lithics, zooarchaeological evidence, and archaeological site reports 
Quantitative assessments of current levels of data sharing, data citation and reuse remain limited in archaeology  The focus of evaluation has been on the uptake of large-scale digital archives for the preservation and dissemination of digital data, such as the Archaeology Data Service (ADS), utilised by developer-led and research projects, and recommended for use by many research funders in the UK (Richards 2002; Wright and Richards 2018)  Much less focus has been paid to the data-sharing practices of individuals or small-groups of university-based researchers who may be disseminating their research largely through journal articles  Recent work on the availability of data on lithics assemblages found a low level of data sharing (Marwick & Pilaar Birch 2018) and there are perceptions of low levels of data reuse (Huggett 2018; Kintigh et al  2018)  Within zooarchaeology numerous studies have explored issues of data sharing and reuse (Kansa & Kansa 2013, 2014), and the sub-discipline is seen as one of the most advanced areas of archaeology in regards to open science (Cooper & Green 2016: 273)  Beyond zooarchaeology, however, explicit discussion has remained limited 
This paper assesses data sharing and reuse practices in archaeology through the case study of archaeobotany – a long established sub-discipline within archaeology which has well-established principles of data recording  Archaeobotany is an interesting case study for data sharing in archaeology as it straddles the division of archaeology between scientific and more traditional techniques  Quantitative data on archaeological plant remains are also of interest to a range of other fields, including ecology, environmental studies, biology and earth sciences  The key issues of data sharing and data reuse (Atici et al  2013) have been touched upon in archaeobotany over the past decade within broader discussions on data quality (Van der Veen, Livarda & Hill 2007; Van der Veen, Hill & Livarda 2013)  These earlier studies focussed on the quality and availability of archaeobotanical data from developer-funded excavations in Britain and Cultural Resource Management in North America (Vanderwarker et al  2016: 156)  However, no discussion of data-sharing and reuse in academic archaeobotany occurred  A recent review of digital methods in archaeobotany is the notable exception, with discussions of the challenges and methods of data sharing (Warinner & d’Alpoim Guedes 2014) 
Currently, we have no evidence for the levels of data sharing and reuse within archaeobotany  This article provides the first quantitative assessment of 1) data publication in recent archaeobotanical journal articles 2) data citation in recent archaeobotanical meta-analysis 3) the reuse of archaeobotanical datasets, in order to assess whether practices need to change and how such changes can take place 
2  Data Publication and Re-use Practices in Archaeobotany
2 1  History of data production and publication
Archaeobotanical data falls within the category of observational data in archaeology (Marwick & Pilaar Birch 2018)  Archaeobotanical data is considered as the quantitative assessment of plant macrofossils present within a sample from a discrete archaeological context, which can include species identification, plant part, levels of identification (cf  – confer or “compares to”), and a range of quantification methods including count, minimum number of individuals, levels of abundance and weight (Popper 1988)  Archaeobotanical data is usually entered into a two-way data table organised by sample number  Alongside the counts of individual taxa, other information is also necessary to interpret archaeobotanical data, including sample volume, flot volume, charcoal volume, flot weight, level of preservation, sample number, context number, feature number, feature type and period  Beyond taxonomic identifications, a range of other types of data are increasingly gathered on individual plant macrofossils (morphometric measurements, isotopic values, aDNA) 
Archaeobotanical training places a strong emphasis on recording data on a sample-by-sample basis (Jacomet & Kreuz 1999: 138–139; Jones & Charles 2009; Pearsall 2016: 97–107)  Time-consuming methodologies utilised in the pursuit of accurate sample-level data recording include sub-sampling and splitting samples into size fractions and counting a statistically useful number of items per sample (Van der Veen & Fieller 1982)  The creation of sample-level data means analysis is often undertaken on the basis of individual samples, for instance the assessment of crop-processing stages and weed ecological evidence for crop husbandry practices  The analysis of sample level data also enables archaeobotanical finds to be integrated alongside contextual evidence from archaeological sites  Requirements for the publication of this data are in place in some archaeological guidelines, for instance current Historic England guidelines for archaeological practice in England (Campbell, Moffett & Straker 2011: 8) 
From the earliest archaeobotanical reports, such as Reid’s work at Roman Silchester, the sample from which plant remains were recovered was noted (Lodwick 2017a), but often results were reported as a list of taxa, or long catalogues of detailed botanical descriptions with seed counts, such as Knörzer’s work at Neuss (Knörzer 1970)  Early systematic archaeobotanical reports displayed data within in-text tables, for example Jones’s work at Ashville (Jones 1978) and the two-way data table has been the standard form of reporting archaeobotanical data ever since  Often data tables are presented within book chapters or appendices, but the financial, space and time constraints of book publishing are limiting  Furthermore, there is the perception that specialist data was not necessary for publication (Barker 2001)  Hence, alternative methods of the dissemination of specialist archaeological data were pursued in the later twentieth century 
From the 1980s, archaeobotanical data tables were often consigned to microfiche following a Council for British Archaeology and Department of Environment report (Moore & Richards 2015: 31), with the example of the excavation of Roman Colchester where the contents of all archaeobotanical samples were available on microfiche (Murphy 1992)  An alternative in the 2000s was providing data tables on CD Rom as seen, for instance, in the CD accompanying the study of a Roman farmstead in the Upper Thames Valley (Robinson 2007) or the One Poultry excavations in London (Hill and Rowsome 2011)  Meanwhile, the inception of the Archaeology Data Service, a digital repository for heritage data, in 1996 meant archaeological datasets were increasingly digitally archived, for instance the data from the Channel Tunnel Rail Link Project (Foreman 2018) or a recent large-scale research excavation at Silchester (University of Reading 2018)  In these cases, archaeobotanical data is available to download as a  csv file 
Whilst the data publication strategy of large excavations was shifting, the availability of data from post-excavation assessment reports has remained challenging  So-called ‘grey literature’ results from the initial evaluation stage of developer-funded investigations and accompanying post-excavation assessment often contain a semi-quantitative evaluation of archaeobotanical samples on a scale of abundance  Whilst paper reports were initially deposited with county Historic Environment Records, a process of digitisation focussing on the Roman period has meant many pdfs are now available through the ADS (Allen et al  2018), whilst born-digital reports are now deposited through OASIS (Online AccesS to the Index of archaeological investigationS), as part of the reporting process (Evans 2015), althought the extent to which specialist appendices are included is variable 
These varying ‘publication’ strategies means archaeobotanical data is often available somewhere for recent developer-funded excavations and large-scale developer-funded excavations, even if much of this data is as a printed table or  pdf file (Evans 2015; Evans and Moore 2014)  However, academic journals are typically perceived as the most high-status publication venue for archaeobotanical data, and a crucial publication venue for academics in order to comply with institutional requirements and the norms of career progression  Aside from the problem of access to pay-walled journals by those without institutional subscriptions to all journals, the publication of primary data alongside research articles faces various problems, from the outright lack of inclusion of data, to problematic curation of supplementary data and a lack of peer review of data (Costello et al  2013; Warinner and d’Alpoim Guedes 2014: 155; Whitlock, 2011)  The extent of these problems for archaeobotany is currently unknown  Given the growth in archaeobotanical data production as methodologies are introduced into many new regions and periods over the last decade, it is vital that we know whether the mass of new data being produced is made available and is being reused 
Recent important advances within archaeobotanical data sharing have focussed on the construction of the ARBODAT database, developed by Angela Kreuz at the Kommission für Archäologische Landesforschung in Hessen  The database is used by a range of researchers in Germany, the Czech Republic, France and England (Kreuz & Schäfer 2002)  Data sharing enabled by the use of this database has facilitated research on Neolithic agriculture in Austria, Bulgaria and Germany (Kreuz et al  2005), and Bronze Age agriculture in Europe (Stika and Heiss 2012)  The use of this database makes data integration between specialists easier due to the shared data structure and metadata description, but often the primary archaeobotanical data is not made publicly available 
2 2  Meta-analysis in archaeobotany
Beyond the need to preserve information, a key reason for the formal sharing of archaeobotanical data is in its reuse to facilitate subsequent research  There has been a long-standing concern within archaeobotany with the need to aggregate datasets and identify temporal and spatial patterns  The palaeobotanist Clement Reid maintained his own database of Quaternary plant records in the late nineteenth century (Reid 1899), which formed the foundation of Godwin’s Quaternary database (Godwin 1975)  Mid-twentieth century studies of prehistoric plant use compiled lists of archaeobotanical materials incorporating full references and the location of the archive (Jessen & Helbaek 1944)  The International Work Group for Palaeoethnobotany was itself founded in 1968 in part with the aim to compile archaeobotanical data, first realised through the publication of Progress in Old World Palaeoethnobotany (Van Zeist, Wasylikowa & Behre 1991), and subsequently through the publication of annual lists of new records of cultivated plants (Kroll 1997) 
To take England as an example, regional reviews produced by state heritage authorities have provided catalogues of archaeobotanical datasets in particular time periods and regions (e g  Murphy 1998)  When one archaeobotanist has undertaken the majority of study within a region, pieces of synthesis within books have provided a relatively comprehensive review, for instance in the Thames Valley, UK (Lambrick & Robinson 2009)  Over the last decade regional synthesis has occurred within several funded reviews which produced catalogues of sites with archaeobotanical data (Lodwick 2014; McKerracher 2018; Parks 2012) and a series of funded projects in France have enabled regional synthesis (Lepetz & Zech-Matterne 2017)  However, many of these reviews are not accompanied by an available underlying database, and draw upon reports which are themselves hard to access 
Through the 1990s and 2000s, a series of databases were constructed in order to collate data from sites in a particular region and facilitate synthetic research  However, these databases have all placed the role of data archiving onto later projects specifically funded to collate data, rather than sourcing datasets at the time of publication  Such a model is unsustainable, and is unlikely to result in all available datasets being compiled  The Archaeobotanical Computer Database (ABCD), published in 1996 in the first issue of Internet Archaeology, contained much of the archaeobotanical data from Britain available at the time of publication, largely at the level of individual samples  The database was compiled between 1989 and 1994 and is still accessible through the accompanying online journal publication (Tomlinson & Hall 1996)  The ABCD made major contributions to recent reviews of the Roman and Medieval periods (Van der Veen, Livarda & Hill 2008; Van der Veen, Hill & Livarda 2013)  However, the database could only be centrally updated, with the online resource remaining a static version, lacking much of the new data produced subsequent to the implementation of PPG16 in 1990  The ADEMNES database, created through a research project undertaken at the Universities of Freiburg and Tübingen, contains data from 533 eastern Mediterranean and Near Eastern sites (Riehl & Kümmel 2005)  Kroll has maintained the Archaeobotanical Literature Database to accompany the Vegetation History and Archaeobotany articles (Kroll 2005) now accessible as a database (Kirleis & Schmültz 2018)  Numerous other databases have collated archaeobotanical studies, including the COMPAG project (Fuller et al  2015), the Cultural Evolution of Neolithic Europe project (Colledge 2016), RADAR in the Netherlands (van Haaster and Brinkkemper 1995), BRAIN Botanical Records of Archaeobotany Italian Network (Mercuri et al  2015) and CZAD – Archaeobotanical database of Czech Republic (CZAD 2019) 
The majority of databases have a restricted regional coverage, whilst research-project driven period-specific databases provide overlapping content  Whilst there are a wide range of archaeobotanical databases available, few contain primary datasets (other than the ABCD) which can be downloaded as  csv files  Data which is most commonly available are bibliographic references per site, with some indications of mode of preservation, quantity of archaeobotanical data, and sometimes taxa present  The databases do not inter-relate to each other, and function primarily as bibliographic sources enabling researchers to find comparative sites or to identify published datasets which need to be re-tabulated prior to meta-analysis  The IWGP website curates a list of resources, but otherwise the resources are often disseminated through the archaeobotany jiscmail list 
Beyond the aim of cataloguing archaeobotanical data within a region and period, meta-analysis is often used in archaeobotany to identify spatial and chronological trends in a range of past human activities, for instance crop choice, crop husbandry practices, plant food consumption, the trade in luxury foods or the use of plants in ritual  Meta-analysis can be undertaken on the basis of simple presence/absence data per site, but in order for such analysis to be rigorous and comparable, sample-level data must be utilised  For instance, sample-level data is required for meta-studies, in order to identify high-quality samples of unmixed crops for weed ecology analysis (Bogaard 2004), to assess the importance of context in the evaluation of wild plant foods (Wallace et al  2019), or to use volumetric measurements as a proxy for scale (Lodwick 2017b)  The reuse of archaeobotanical data also extends to include datasets used as “controls” in commonly used forms of statistical analysis, for instance Jones’s weed data from Amorgos, Greece, which is utilised as a control group in discriminant analysis of crop-processing stage (Jones 1984), and ethnographic observations of crop items in different crop-processing stages (Jones 1990) 
2 3  Open data principles and solutions
Debates over issues of data publication and meta-analysis have been on-going across scientific disciplines over the last decade (Editors 2009), and have been summarised within principles of open science, as recently set out in relation to archaeology (Marwick et al  2017)  Open Data is one of the three core principles for promoting transparency in social science (Miguel et al  2014)  The FAIR principles, developed by representatives from academia, industry, funding agencies, industry and publishers, provide four principles which data sharing should meet for use by both humans and machines – Findability, Accessibility, Interoperability, and Reusability (Wilkinson et al  2016)  A recent report assessing the adoption and impact of FAIR principles across academia in the UK included archaeology as a case study (Allen and Hartland 2018: 46)  It reported how the ADS was often used to archive data, but that “The journal itself provides the “story” about the data, the layer that describes what the data is, how it was collected and what the author thinks it means ” The report also raises the problem that smaller projects may not have the funding to utilise the ADS, meaning that other repositories are utilised  Increasingly, archaeological data is made available through a wide range of data repositories (OSF, Mendeley Data, Zenodo, Open Context), university data repositories (e g  ORA-Data), or social networking sites for academics (Academia edu, ResearchGate)  More widely in archaeology, some have observed that archaeological data is rarely published (Kintigh et al  2014), and recent reviews have reported low levels of data sharing (Huggett 2018; Marwick & Pilaar Birch 2018)  A closely related issue is that of data reuse  Responsible reuse of primary data encourages the sharing of primary data (Atici et al  2013), but levels of data reuse in archaeology are thought to remain low (Huggett 2018)  Principles for responsible data citation in archaeology have recently been developed summarising how datasets should be cited (Marwick & Pilaar Birch 2018) 
In order to assess the current status of data sharing, citation and data re-use in archaeobotany, a review was undertaken of the publication of primary data and the publication of meta-analysis in major archaeological journals over the last ten years, building on recent pilot studies within archaeology (Marwick & Pilaar Birch 2018)  The review of academic journals provided a contrast to recent assessments of archaeobotanical data deriving from developer-funded archaeology (Lodwick 2017c; Van der Veen, Hill & Livarda 2013)  Journal articles have been selected as the focus of this study as the provision of online supplementary materials in the majority of journals and the ability to insert hyperlinks to persistent identifiers (eg a DOI) to link to datasets available elsewhere should not limit the publication of data and references  Much archaeobotanical data is also published elsewhere, especially from projects not based in the university sector, that is commercial or community archaeology in the UK  Archaeobotanical datasets emanating from this research are more commonly published through monographs, county journal articles, and unpublished (or grey literature) reports, but these are beyond the scope of the current review 
All journal articles were included which represent the principle reporting of a new archaeobotanical assemblage  The selected journals fall within three groups  First, what is considered the specialist archaeobotanical journal (Vegetation History and Archaeobotany (VHA))  Second, archaeological science journals (Archaeological and Anthropological Sciences, Environmental Archaeology, The Holocene, Journal of Archaeological Science (JAS), Journal of Archaeological Science: Reports (JASR), Journal of Ethnobiology, Quaternary International, Journal of Wetland Archaeology), which can be considered as specialist sub-disciplinary journals which should be maintaining data-quality  Third, general archaeology journals (Antiquity, Journal of Field Archaeology, Oxford Journal of Archaeology, Journal of Anthropological Archaeology, Journal of World Prehistory)  Finally, the broader cross-disciplinary journals PLoS One and Proceedings of the National Academy of Sciences (PNAS) were included  Published articles from the past ten years (2009–2018) have been analysed in order to assess the availability of plant macrofossil data  This ten-year period brackets the period where most archaeological journals have moved online and adopted supplementary materials 
Data citation in synthetic studies has been assessed in the same range of publications  The extent of data reuse ranges from the analysis of whole sample data to the presence/absence of individual crops  The location of a data citation has been assessed in the same range of publications, with the addition of journals where occasional research incorporating archaeobotanical data is featured (Britannia, Journal of Archaeological Research, Ethnobiology Letters, Medieval Archaeology, Proceedings of the Prehistoric Society, World Archaeology)  The underlying dataset for the analysis is available in Lodwick 2019 
4 1  Primary data sharing
Here, the location of primary archaeobotanical data, that is sample level counts of macroscopic plant remains, was assessed for 239 journal articles across 16 journals (Lodwick 2019 Table 1)  Figure 1 shows the results grouped by journal  Overall, only 56% of articles shared their primary data  In, Antiquity, JAS, JASR, PLOS One, Quaternary International and VHA, the highest proportion of publications did not include their primary data, that is to say that the sample-by-sample counts of plant macrofossils was not available  This level of data is comparable to the findings of other pilot studies in archaeology  Marwick and Pilaar Birch found a data sharing rate of 53% from 48 articles published in Journal of Archaeological Science in Feb – May 2017 (Marwick & Pilaar Birch 2018: 7), and confirm previous assertions that data is often withheld in archaeology (Kansa 2012: 499)  This is better than some disciplines, with a 9% data sharing rate on publication found across high impact journal science publications (n = 500) (Alsheikh-Ali et al  2011) and 13% in biology, chemistry, mathematics and physics (n = 4370) (Womack 2015), yet still indicates that nearly half of articles did not include primary data  Primary archaeobotanical data is more likely to be shared in archaeobotanical and archaeological science journals than general archaeology journals  However, within the primary archaeobotanical journal, VHA, 51% of articles do not include their primary data (Figure 1) 
Chart showing the location of primary archaeobotanical data by journal in primary archaeobotanical data publications 
Where primary data was not shared, the data which was available ranged from summary statistics, typically counts or frequencies, reported either by site, site phase, or feature group  Figure 2 summarises these results by year, showing that there is a gradient within articles not sharing their full ‘raw’ data, from those only provided sample counts on one aspect of the archaeobotanical assemblage, to those only presenting data graphically or within discussion  Beyond full data, the most common form of data shared is either summary counts per site or summary counts per feature or phase  Whilst this data does enable some level of reuse, the results of any sample-level data analysis presented within an article cannot be verified, and the data cannot be reused for crop-processing or weed ecology analysis which requires sample level data  Furthermore, such data would have been collected on a sample-by-sample basis, but this information is lost from the resulting publication 
Chart showing the form of archaeobotanical data shared by year in primary archaeobotanical data publications 
The forms in which data are made available vary across journals  The sharing of primary data within an article remains the most common data sharing form in archaeobotany (Figure 1)  Data tables in text require manual handling to extract data, in journals such as VHA, whilst in other journals in-text tables can be downloaded as  csv files  These however would not be citable as a separate dataset  Supplementary datasets are the third most common form of data sharing  Indeed, the use of electronic supplementary material has been advocated recently for by some journals, such as the Journal of Archaeological Science (Torrence, Martinón-Torres & Rehren 2015)  Microsoft Excel spreadsheets are the most common form of supplementary data, followed by  pdfs and then word documents (Figure 1)  Both  xlsx and  docx are proprietary file formats, and not recommended for long term archiving or open science principles  There is no indication of improvement over the last decade in the form of data sharing  In 2018, 50% of articles did not share their primary data, and where the data was shared, it was in proprietary forms ( docx,  xlsx) or those that do not easily facilitate data reuse ( pdf) (Figure 3) 
Chart showing the location of archaeobotanical data from 2009–2018 in primary archaeobotanical data publications 
Just one of the articles included in this review incorporated a dataset archived in a repository (Farahani 2018), in contrast to the substantial growth in data repositories across academic disciplines (Marcial & Hemminger 2010)  Other examples provide the underlying data for monograph publications, such as that of the archaeobotanical data from Gordion, Turkey (Marston 2017a, 2017b), Silchester, UK (Lodwick 2018; University of Reading 2018) and Vaihingen, Germany (Bogaard 2011a; Bogaard, 2011b) 
Several of the journals that have been assessed have research data policies  In the case of Vegetation History and Archaeobotany, sufficient papers have been surveyed to assess the impact of the research data policy on the availability of data  Figure 4 show the proportion of data sharing formats through time just for VHA (note the small sample size)  The introduction of a research data policy in 2016 encouraging data sharing in repositories has not resulted in any datasets being shared in that format  Of the 10 articles published in PLOS One after the introduction of a clear research data policy in 2014, 4 did not contain primary data  However, elsewhere, journals with no research data policy, such as Antiquity, has one of the lower levels of data sharing (Figure 1) 
Chart showing the location of primary archaeobotanical data in Vegetation History and Archaeobotany 
There are various reasons for why a primary dataset may be lacking  The option of providing supplementary datasets has been available in many of the journals here since before the start of the surveyed period (e g  Vegetation History and Archaeobotany in 2004), and so cannot be a reason for the absence of data publication in this journal while it may be a reason in other journals  Reasons suggested for a lack of data sharing within archaeology include technological limitations, and resistance amongst some archaeologists to making their data available due to cautions of exposing data to scrutiny, lost opportunities of analysis before others use it and loss of ‘capital’ of data (Moore & Richards 2015: 34–35)  Furthermore, control over how data tables is presented (taxa ordering, summary data presented) may also contribute to the preferential publishing of data within journal articles  Another factor to consider is the emphasis on the creation of new data through archaeological research (Huvila 2016)  The creation of a new archaeobotanical dataset through primary analysis is a key form of training in archaeobotany, and the perception of the value of the reuse of other previously published archaeobotanical journals may be low, hence not encouraging the sharing of well-documented datasets  Excellent exams of data reuse have resulted in influential studies (Bogaard 2004; Riehl 2008; Wallace et al  2019), and would hopefully encourage further data sharing in the future 
Given that there are numerous examples of meta-analysis which do take place in archaeobotany, it seems likely that the prevalent form of data sharing is through informal data sharing between individual specialists  However, this does not improve access to data in the long term, and is inefficient and time consuming, with large potential for data errors (Kansa & Kansa 2013), and relies on personal networks, which are likely to exclude some researchers  The absence of primary data in many archaeobotanical publications thus inhibits the verification of patterns observed within a dataset, and strongly limits the re-use potential of a dataset 
4 2  Data citation
One of the common arguments for increasing data sharing is an associated increase in the citation of the articles which have data available  Here, the data citation practices of meta-analyses of plant macrofossil data undertaken over the last decade have been reviewed  20 journals were consulted, including a wider range of period-specific journals, and 107 articles were assessed (Lodwick 2019 Table 2)  Data citation was assessed as ‘in text’ or ‘in table’ to refer to when the citation and the bibliographic reference were within the article, as ‘in supplementary data’ when the citation and reference were within the supplementary materials, and as ‘no citation’ when no citation and reference was provided 
21% of articles (n = 22) did not contain any citations to the underlying studies  16% (n = 17) contained citations within supplementary data files  50% of articles (n = 53) contained a citation within a table within the main article, and 14% (n = 15) contained citations within the main text  For the 21% of articles without data citations, the results of these studies could not be reproduced without consulting individual authors  The papers supplying the underlying data also received no credit for producing these datasets  Where articles contain citations within the main article (in text or table), full credit is provided to the underlying studies, a citation link is created through systems such as google scholar, and the study can be easily built upon in the future  Where the citation is provided within supplementary data, the original studies do receive attribution, but are not linked to so easily 
Through time, there is a steady decrease in the proportion of studies without citations to the underlying data, whereby of the 17 meta-analysis articles published in 2018, only one had no data citations  In comparison, in 2009, 3 out of 8 meta-analysis articles contained no data citation (Figure 6)  Overall this is a more positive outlook on the reuse of published data, but the consistent presence of articles lacking data citation indicates that improvements are needed  Reasons for a lack of data citation may include restrictions on word counts imposed by journals, a lack of technical knowledge in making large databases available, or the wish to hold on to a dataset to optimise usage  Considering the type of journal (Figure 5), levels of data citation are worse in general archaeology journals, with sub-disciplinary journals showing slightly better levels of data citation  In particular VHA has a lack of consistency in where data citations are located 
Chart showing the location of data citations in meta-analysis journal articles by journal type 
Chart showing the location of data citations in meta-analysis journal articles from 2009–2018 
4 3  Reuse of archived archaeobotanical datasets
The majority of data citations assessed in the previous section are to articles or book chapters rather than data-sets  The ADS currently hosts 66 data archives which have been tagged as containing plant macro data, deriving mainly from developer-funded excavations but also some research excavations  However, in some of these the plant macro data is contained within a pdf  As, the archiving of archaeobotanical datasets in data repositories is still at an early stage, the reuse of these datasets is assessed here on a case-by-case basis  The archaeobotanical dataset from the Neolithic site of Vaihingen, Germany (Bogaard 2011b) has not been cited on google scholar  Metrics are provided through the ADS, showing this dataset has been downloaded 56 times with 477 individual visits (as of 25/2/19)  The archaeobotanical dataset from Gordion by Marston has no citations on Google Scholar (Marston 2017b), neither does the Giza botanical database (Malleson & Miracle 2018), but these are both very recently archived datasets  In contrast, the Roman Rural Settlement Project dataset, which includes site-level archaeobotanical data, has received greater levels of use, with 12 citations in Google Scholar, over 40,000 file downloads, and over 35,000 visits (Allen et al  2018) and the archaeobotanical computer database (Tomlinson & Hall 1996) has been cited 44 times, and is the major dataset underpinning other highly-cited studies (Van der Veen, Livarda & Hill 2008; Van der Veen, Hill & Livarda 2013)  Whilst there is clearly precedence for the reuse of archaeobotanical databases, current data citation practices within archaeobotany do not yet appear to be formally citing individual datasets, meaning an assessment of the reuse of archived archaeobotanical datasets is challenging 
5  Steps Forward
This review of data sharing, citation, and reuse practices in archaeobotany has found medium levels of data sharing, good levels of data citation, but so far limited levels of reuse of archived data sets  This picture is similar across archaeology, in part attributed to the status of archaeology as a small-science, where data-sharing takes place ad-hoc (Marwick & Pilaar Birch 2018)  Here, recommendations are discussed for improving these data practices within archaeobotany, of applicability more widely in archaeology 
Clearly an important step is improving the sharing of plant macrofossil data  Given the reasonable small size of most archaeobotanical datasets (a  csv file < 1mb), and a lack of ethical conflicts, there seems to be few reasons why the majority of archaeobotanical data couldn’t be shared  In the case of developer-funded derived data, issues of commercial confidentiality could limit the sharing of data  A key stage is establishing why levels of data sharing are not higher  Issues within archaeobotany may include the conflict between having to publish results within excavation monographs, which may take some time to be published, and have limited visibility due to high purchase costs and no digital access, and the need to publish journal articles for career progression within academia  The production of an archaeobotanical dataset is very time-consuming, and interim publication on notable aspects of an assemblage may be considered as a necessary publication strategy  More broadly, one important aspect is issues of equity in access to digital archiving resources (Wright & Richards 2018), such as differential access to funds, training and knowledge  A recent study in Sweden found that we need to know concerns, needs, and wishes of archaeologists in order to improve preservation of archaeological data (Huvila 2016), especially when control of ones data may be linked to perceptions of job security  In order to make improvements in data sharing and reuse across archaeology, we need improved training in data sharing and the reuse of data in higher education (Touchon & McCoy 2016; Cook et al  2018), improved training in data management (Faniel et al  2018), and crucially, the necessary software skills to make the reuse of archived datasets attainable (Kansa & Kansa 2014: 91)  Examples of good practice in archaeobotany are the Vaihingen and Gordion datasets which demonstrate how datasets can be archived in data repositories to accompany a monograph (Bogaard 2011b; Marston 2017b), whilst Farahani (2018) provides an excellent example of a journal article, where the primary data is supplied as a  csv in a cited data repository along with the R script for the analysis 
In tandem with the need to encourage authors to share their data, is the need for journals to create and implement research data policies  Given the existence of research data policies in many of the journals included here, this reflects other findings of the poor enforcement of data policies by journals (Marwick & Pilaar Birch 2018), supporting arguments that journals should not be relied upon to make data accessible, and data should instead by deposited in digital repositries  In order to implement change in data sharing, there is a role to play for learned societies and academic organisation in lobbying funding bodies, prioritising data sharing in research projects  A key step is through journal editorial boards, and the enforcement of any pre-existing research data policies (Nosek et al  2015)  Revi
Context 3: Publications of Kam W  Leong
Publications of Kam W  Leong :chronological alphabetical combined bibtex listing:
K W  Leong, Synthetic mast-cell granules as adjuvants to promote and polarize immunity in lymph nodes (2013) [PDF]
K W  Leong, Tuning Physical Properties of Nanocomplexes through Microfluidics-Assisted Confinement (2013) [PDF]
K W  Leong, Nucleic acid scavengers inhibit thrombosis without increasing bleeding (2013) [PDF]
K W  Leong, Nanotopography as modulator of human mesenchymal stem cell function (2013) [PDF]
K W  Leong, Efficacy of engineered FVIII-producing skeletal muscle enhanced by growth factor-releasing co-axial electrospun fibers (2013) [PDF]
Zhao, F  and Veldhuis, J  J  and Duan, Y  J  and Yang, Y  and Christoforou, N  and Ma, T  and Leong, K  W , Low Oxygen Tension and Synthetic Nanogratings Improve the Uniformity and Stemness of Human Mesenchymal Stem Cell Layer, Molecular Therapy, vol  18 no  5 (2010), pp  1010-1018 [abs]
Kadiyala, I  and Loo, Y  H  and Roy, K  and Rice, J  and Leong, K  W , Transport of chitosan-DNA nanoparticles in human intestinal M-cell model versus normal intestinal enterocytes, European Journal of Pharmaceutical Sciences, vol  39 no  1-3 (2010), pp  103-109 [abs]
Wang, Y  and Quek, C  H  and Leong, K W  and Fang, J , Synthesis and Cytotoxity of Luminescent InP Quantum Dots, MRS Symposium Proceeding, vol  1241E (2010)
Jiang, X  and Zheng, Y  and Chen, H  H  and Leong, K  W  and Wang, T  H  and Mao, H  Q , Dual-Sensitive Micellar Nanoparticles Regulate DNA Unpacking and Enhance Gene-Delivery Efficiency, Adv Mater (2010)
Ho, Y  P  and Leong, K  W , Quantum dot-based theranostics, Nanoscale, vol  2 no  1 (2010), pp  60-68 [PDF] [abs]
Phua, K  and Leong, K  W , Microscale oral delivery devices incorporating nanoparticles, Nanomedicine, vol  5 no  2 (2010), pp  161-163
Grigsby, C  L  and Leong, K  W , Balancing protection and release of DNA: tools to address a bottleneck of non-viral gene delivery, Journal of the Royal Society Interface, vol  7 (2010), pp  S67-S82 [abs]
Chalut, K  J  and Kulangara, K  and Giacomelli, M  G  and Wax, A  and Leong, K  W , Deformation of stem cell nuclei by nanotopographical cues, Soft Matter, vol  6 no  8 (2010), pp  1675-1681 [abs]
Chen, S  and Jones, J  A  and Xu, Y  and Low, H  Y  and Anderson, J  M  and Leong, K  W , Characterization of topographical effects on macrophage behavior in a foreign body response model, Biomaterials, vol  31 no  13 (2010), pp  3479-91 [PDF] [abs]
Yim, E  K  F  and Darling, E  M  and Kulangara, K  and Guilak, F  and Leong, K  W , Nanotopography-induced changes in focal adhesions, cytoskeletal organization, and mechanical properties of human mesenchymal stem cells, Biomaterials, vol  31 no  6 (2010), pp  1299-1306 [PDF] [abs]
Yow, S  Z  and Quek, C  H  and Yim, E  K  F  and Lim, C  T  and Leong, K  W , Collagen-based fibrous scaffold for spatial organization of encapsulated and seeded human mesenchymal stem cells, Biomaterials, vol  30 no  6 (2009), pp  1133-1142 [abs]
Kunder, C  A  and John, A  L  S  and Li, G  J  and Leong, K  W  and Berwin, B  and Staats, H  F  and Abraham, S  N , Mast cell-derived particles deliver peripheral signals to remote lymph nodes, Journal of Experimental Medicine, vol  206 no  11 (2009), pp  2455-2467 [abs]
Ho, Y P  and Chen, H H  and Leong, K W  and Wang, T H , Combining QD-FRET and microfluidics to monitor DNA nanocomplex self-assembly in real-time, J Vis Exp (2009), pp  1432
Kulangara, K  and Leong, K  W , Substrate topography shapes cell function, Soft Matter, vol  5 no  21 (2009), pp  4072-4076 [abs]
Chakraborty, S  and Liao, I  C  and Adler, A  and Leong, K  W , Electrohydrodynamics: A facile technique to fabricate drug delivery systems, Advanced Drug Delivery Reviews, vol  61 no  12 (2009), pp  1043-1054 [abs]
Oney, S  and Lam, R  T  S  and Bompiani, K  M  and Blake, C  M  and Quick, G  and Heidel, J  D  and Liu, J  Y  C  and Mack, B  C  and Davis, M  E  and Leong, K  W  and Sullenger, B  A , Development of universal antidotes to control aptamer activity, Nature Medicine, vol  15 no  10 (2009), pp  1224-1228 [PDF] [abs]
Chen, H  H  and Ho, Y  P  and Jiang, X  and Mao, H  Q  and Wang, T  H  and Leong, K  W , Simultaneous non-invasive analysis of DNA condensation and stability by two-step QD-FRET, Nano Today, vol  4 no  2 (2009), pp  125-134 [PDF] [abs]
Ho, Y  P  and Chen, H  H  and Leong, K  W  and Wang, T  H , The convergence of quantum-dot-mediated fluorescence resonance energy transfer and microfluidics for monitoring DNA polyplex self-assembly in real time, Nanotechnology, vol  20 no  9 (2009), pp  - [abs]
Liao, I  C  and Chen, S  L  and Liu, J  B  and Leong, K  W , Sustained viral gene delivery through core-shell fibers, Journal of Controlled Release, vol  139 no  1 (2009), pp  48-55 [abs]
Lou, Y  L  and Peng, Y  S  and Chen, B  H  and Wang, L  F  and Leong, K  W , Poly(ethylene imine)-g-chitosan using EX-810 as a spacer for nonviral gene delivery vectors, Journal of Biomedical Materials Research Part A, vol  88A no  4 (2009), pp  1058-1068 [abs]
Chew, S  Y  and Mi, R  and Hoke, A  and Leong, K  W , The effect of the alignment of electrospun fibrous scaffolds on Schwann cell maturation, Biomaterials, vol  29 no  6 (2008), pp  653-61 [abs]
Chen, H  H  and Ho, Y  P  and Jiang, X  and Mao, H  Q  and Wang, T  H  and Leong, K  W , Quantitative comparison of intracellular unpacking kinetics of polyplexes by a model constructed from quantum Dot-FRET, Molecular Therapy, vol  16 no  2 (2008), pp  324-332 [abs]
Chan, B  P  and Leong, K  W , Scaffolding in tissue engineering: general approaches and tissue-specific considerations, European Spine Journal, vol  17 (2008), pp  S467-S479 [abs]
Tsurushima, H  and Yuan, X  and Dillehay, L  E  and Leong, K  W , Radiation-inducible caspase-8 gene therapy for malignant brain tumors, International Journal of Radiation Oncology Biology Physics, vol  71 no  2 (2008), pp  517-525 [abs]
Bowman, K  and Sarkar, R  and Raut, S  and Leong, K  W , Gene transfer to hemophilia A mice via oral delivery of FVIII-chitosan nanoparticles, Journal of Controlled Release, vol  132 no  3 (2008), pp  252-259 [abs]
Choi, J  S  and Leong, K  W  and Yoo, H  S , In vivo wound healing of diabetic ulcers using electrospun nanofibers immobilized with human epidermal growth factor (EGF), Biomaterials, vol  29 no  5 (2008), pp  587-96 [abs]
Liao, I  C  and Liu, J  B  and Bursac, N  and Leong, K  W , Effect of Electromechanical Stimulation on the Maturation of Myotubes on Aligned Electrospun Fibers, Cellular and Molecular Bioengineering, vol  1 no  2-3 (2008), pp  133-145 [abs]
Prow, T  W  and Bhutto, I  and Kim, S  Y  and Grebe, R  and Merges, C  and McLeod, D  S  and Uno, K  and Mennon, M  and Rodriguez, L  and Leong, K  and Lutty, G  A , Ocular nanoparticle toxicity and transfection of the retina and retinal pigment epithelium, Nanomedicine-Nanotechnology Biology and Medicine, vol  4 no  4 (2008), pp  340-349 [abs]
Tan, S  C  W  and Pan, W  X  and Ma, G  and Cai, N  and Leong, K  W  and Liao, K , Viscoelastic behaviour of human mesenchymal stem cells, Bmc Cell Biology, vol  9 (2008), pp  - [abs]
Chalut, K  J  and Chen, S  and Finan, J  D  and Giacomelli, M  G  and Guilak, F  and Leong, K  W  and Wax, A , Label-free, high-throughput measurements of dynamic changes in cell nuclei using angle-resolved low coherence interferometry, Biophysical Journal, vol  94 no  12 (2008), pp  4948-4956 [abs]
Haider, M  and Cappello, J  and Ghandehari, H  and Leong, K  W , In vitro chondrogenesis of mesenchymal stem cells in recombinant silk-elastinlike hydrogels, Pharmaceutical Research, vol  25 no  3 (2008), pp  692-699 [abs]
N  Bursac and Y  H  Loo and K  Leong and L  Tung, Novel anisotropic engineered cardiac tissues: Studies of electrical propagation, Biochemical And Biophysical Research Communications, vol  361 no  4 (October, 2007), pp  847 -- 853, ISSN 0006-291X [abs]
Chen, Beiyi and Dang, Jiyoung and Tan, Tuan Lin and Fang, Ning and Chen, Wei Ning and Leong, Kam W  and Chan, Vincent, Dynamics of smooth muscle cell deadhesion from thermosensitive hydroxybutyl chitosan, Biomaterials, vol  28 no  8 (2007), pp  1503 - 1514 [027] [abs]
Chen, B  and Dang, J  and Tan, T  L  and Fang, N  and Chen, W  N  and Leong, K  W  and Chan, V , Dynamics of smooth muscle cell deadhesion from thermosensitive hydroxybutyl chitosan, Biomaterials, vol  28 no  8 (2007), pp  1503-14 [abs]
Park, D  J  and Choi, J  H  and Leong, K  W  and Kwon, J  W  and Eun, H  S , Tissue-engineered bone formation with gene transfer and mesenchymal stem cells in a minimally invasive technique, Laryngoscope, vol  117 no  7 (2007), pp  1267-71 [abs]
Tsurushima, H  and Yuan, X  and Dillehay, L  E  and Leong, K  W , Radioresponsive tumor necrosis factor-related apoptosisinducing ligand (TRAIL) gene therapy for malignant brain tumors, Cancer Gene Therapy, vol  14 no  8 (2007), pp  706-716 [abs]
Chai, C  and Leong, K  W , Biomaterials approach to expand and direct differentiation of stem cells, Molecular Therapy, vol  15 no  3 (2007), pp  467-480 [abs]
Zhang, Y  and Chai, C  and Jiang, X  S  and Teoh, S  H  and Leong, K  W , Fibronectin immobilized by covalent conjugation or physical adsorption shows different bioactivity on aminated-PET, Materials Science & Engineering C-Biomimetic and Supramolecular Systems, vol  27 no  2 (2007), pp  213-219 [abs]
Song, R  J  and Liu, S  Q  and Leong, K  W , Effects of MIP-1 alpha, MIP-3 alpha, and MIP-3 beta on the induction of HIV Gag-specific immune response with DNA vaccines, Molecular Therapy, vol  15 no  5 (2007), pp  1007-1015 [abs]
Yim, E  K  F  and Liao, I  C  and Leong, K  W , Tissue compatibility of interfacial polyelectrolyte complexation fibrous scaffold: Evaluation of blood compatibility and biocompatibility, Tissue Engineering, vol  13 no  2 (2007), pp  423-433 [abs]
Sharma, B  and Williams, C  G  and Kim, T  K  and Sun, D  N  and Malik, A  and Khan, M  and Leong, K  and Elisseeff, J  H , Designing zonal organization into tissue-engineered cartilage, Tissue Engineering, vol  13 no  2 (2007), pp  405-414 [abs]
Chua, K  N  and Tang, Y  N  and Quek, C  H  and Ramakrishna, S  and Leong, K  W  and Mao, H  Q , A dual-functional fibrous scaffold enhances P450 activity of cultured primary rat hepatocytes, Acta Biomaterialia, vol  3 no  5 (2007), pp  643-650 [abs]
Chua, K  N  and Chai, C  and Lee, P  C  and Ramakrishna, S  and Leong, K  W  and Mao, H  Q , Functional nanofiber scaffolds with different spacers modulate adhesion and expansion of cryopreserved umbilical cord blood hematopoietic stem/progenitor cells, Experimental Hematology, vol  35 no  5 (2007), pp  771-781 [abs]
Yim, E  K  F  and Pang, S  W  and Leong, K  W , Synthetic nanostructures inducing differentiation of human mesenchymal stem cells into neuronal lineage, Experimental Cell Research, vol  313 no  9 (2007), pp  1820-1829 [abs]
Chew, S  Y  and Mi, R  F  and Hoke, A  and Leong, K  W , Aligned protein-polymer composite fibers enhance nerve regeneration: A potential tissue-engineering platform, Advanced Functional Materials, vol  17 no  8 (2007), pp  1288-1296 [abs]
Tsurushima, H  and Yuan, X  and Dillehay, L  E  and Leong, K  W , Radio-responsive gene therapy for malignant glioma cells without the radiosensitive promoter: Caspase-3 gene therapy combined with radiation, Cancer Letters, vol  246 no  1-2 (2007), pp  318-323 [abs]
Dang, J M  and Leong, K  W , Myogenic induction of aligned mesenchymal stem cell sheets by culture on thermally responsive electrospun nanofibers, Advanced Materials, vol  19 no  19 (2007), pp  2775-2779
Dai, H  and Jiang, X  and Tan, G  C  and Chen, Y  and Torbenson, M  and Leong, K  W  and Mao, H  Q , Chitosan-DNA nanoparticles delivered by intrabiliary infusion enhance liver-targeted gene delivery, International Journal of Nanomedicine, vol  1 no  4 (2006), pp  507-522 [abs]
Le Visage, C  and Kim, S  W  and Tateno, K  and Sieber, A  N  and Kostuik, J  P  and Leong, K  W , Interaction of human mesenchymal stem cells with disc cells - Changes in extracellular matrix biosynthesis, Spine, vol  31 no  18 (2006), pp  2036-2042
Ong, S  Y  and Dai, H  and Leong, K  W , Inducing hepatic differentiation of human mesenchymal stem cells in pellet culture, Biomaterials, vol  27 no  22 (2006), pp  4087-4097
Bright, C  and Park, Y  S  and Sieber, A  N  and Kostuik, J  P  and Leong, K  W , In vivo evaluation of plasmid DNA encoding OP-1 protein for spine fusion, Spine, vol  31 no  19 (2006), pp  2163-2172
Yim, E  K  and Wan, A  C  and Le Visage, C  and Liao, I  C  and Leong, K  W , Proliferation and differentiation of human mesenchymal stem cell encapsulated in polyelectrolyte complexation fibrous scaffold, Biomaterials, vol  27 no  36 (2006), pp  6111-22 [abs]
Luong-Van, E  and Grondahl, L  and Chua, K  N  and Leong, K  W  and Nurcombe, V  and Cool, S  M , Controlled release of heparin from poly(epsilon-caprolactone) electrospun fibers, Biomaterials, vol  27 no  9 (2006), pp  2042-2050
Dang, J  M  and Leong, K  W , Natural polymers for gene delivery and tissue engineering, Advanced Drug Delivery Reviews, vol  58 no  4 (2006), pp  487-499
Li, J  and Li, X  and Ni, X  P  and Wang, X  and Li, H  Z  and Leong, K  W , Self-assembled supramolecular hydrogels formed by biodegradable PEO-PHB-PEO triblock copolymers and alpha-cyclodextrin for controlled drug delivery, Biomaterials, vol  27 no  22 (2006), pp  4132-4140
Yim, E  K  F  and Wen, J  and Leong, K  W , Enhanced extracellular matrix production and differentiation of human embryonic germ cell derivatives in biodegradable poly(epsilon-caprolactone-co-ethyl ethylene phosphate) scaffold, Acta Biomaterialia, vol  2 no  4 (2006), pp  365-376
Chew, S  Y  and Hufnagel, T  C  and Lim, C  T  and Leong, K  W , Mechanical properties of single electrospun drug-encapsulated nanofibres, Nanotechnology, vol  17 no  15 (2006), pp  3880-3891
Zhang, Y  and Chai, C  and Jiang, X  S  and Teoh, S  H  and Leong, K  W , Co-culture of umbilical cord blood CD34(+) cells with human mesenchymal stem cells, Tissue Engineering, vol  12 no  8



ground_truth: Technological limitations, resistance to exposing data to scrutiny, and desire to hold onto data for personal use.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What are the titles of one of Kam W. Leong's publications in Journal of Controlled Release?

Read the following text and answer briefly.

Context 4:  The best performing model checkpoint was chosen according to the epoch-wise validation macro-F1 score  5 Experiments and Results

Experiments using Large Language Models

For the task of Dialect Identification we have tried various language specific models like XLM-RoBERTa, BERT, ELECTRA, RoBERTa and GPT- 2  The base variant of all these models were used and all the models were used through the Hugging-Face library  The pooler output of these models was passed through a linear layer and the models were fine-tuned 
First, we experimented with different models for Track-1  All the models were trained for 20 epochs with learning rate 1e-6, weight decay 1e-6 and a batch size of 8  We used XLM-RoBERTa as the baseline for all 3 languages  The best performing models for the English language were RoBERTa and BERT whereas GPT-2 was the worst performing 
Similarly the language specific versions of RoBERTa and BERT performed well for the Spanish and Portuguese respectively  Overall the worst performing model was GPT-2 across all 3 languages  The validation F1 scores are present in Table   The two best-performing models for every language were chosen for Track-2 
The same procedure as specified above was used and the F1 scores are present in Table   The train and validation F1 scores for 2-class classification are higher for all models as compared to the F1 score of the same models for 3-class classification  This was mainly due to the poor representation and accuracy of classification of the third class 
We observed symptoms of overfitting in all models after 12-15 epochs and the best validation F1 score was obtained in the range of 4-8 epochs 

LID experiments

The pipeline for dialect identification is divided into two parts as the sentences in the dataset belong to different languages  The stages are described in Section 4  The XLM-RoBERTa we have used for language classification has a test accuracy of 99 6% meaning it correctly classifies all input sentences and hence, can be considered as a perfect classifier 
For the final pipeline we experimented using the two best performing models for each language in Track-1 and Track-2  For both the tracks we experimented with all 8 (2 3 ) possible combinations of models and calculated the validation F1 score for the combined validation dataset which had sentences belonging to all languages 
The validation scores for Track-1 and Track-2 are shown in Table and Table respectively  For both the tracks, the three pipelines with the best validation F1 scores were chosen for submission 

Using 3-way classifier as a 2-way classifier

In Track-1, participants are expected to train a classifier which classifies amongst 9 classes, and in Track-2, participants are expected to train a classifier which classifies amongst 6 classes  These 6 classes are a proper subset of the 9 classes from Track-1  Thus, an intuitive baseline for Track-2 is to use the model finetuned for Track-1, whilst considering only the relevant classes for the latter task 
The classes EN , ES and P T , i e  the classes without any national dialect associated with them are not included in Track-2 as compared to Track-1  Thus, we calculate the predictions for the Track-2 validation dataset using the models for Track-1 and exclude the metrics for Track-1 specific classes to get the metrics for this "adapted" 2-way classification 
We show the results of this experiment in Table and observe that, as expected, the adapted 2-way classification performs worse compared to the explicitly finetuned variant 

Results for Track-1 and Track-2

We now present our experiments and their performance for both tracks  Our experiments for Track-1 are described in Table and our experiments for Track-2 are described in Table   The participants were allowed three submissions for evaluation on the test set, so we submitted predictions using the three systems which performed the best on the validation set 
As mentioned in Section 5 2, we performed 2 3 , i e  a total of 8 experiments using the two best models for each language  We observed that RoBERTa base on English, Spanish BERT base on Spanish and Portuguese BERT base performed the best on the testing set for Track-1  The same combination, with RoBERTa base for English, worked best for Track-2 
All of our submissions were the top submissions for each track, which surpassed the next best competitors by a margin of 4 5% and 5 6% for Track-1 and Track-2 respectively 

Ablation of best submissions

We hereby make some observations of our submissions and other experiments  To assist this, we plot the confusion matrices of our best submissions for Track-1 and Track-2 in Figures respectively  Note that these confusion matrices have their rows (i e  true labels axes) normalized according to the number of samples in the class 
Here are observations from our experiments: 1  BERT-based models outperform other models across all languages: We observe that BERT-based models outperform ELECTRA-based and GPT-2-based models, as shown in Table   We speculate this is because of the inherent architecture of BERT, which combines semantic learning with knowledge retention 
This combination of traits is particularly useful for this task  2  Common labels perform the worst across all languages: We observe that the common labels EN , ES and P T perform the worst, both in the individual as well as the two-stage setup  We hypothesize this is because of the absence of dialect specific words, or words that are specific to the geographical origin of the national dialect (for example, "Yankees" for EN-US and "Oxford" for EN-GB) 
3  English models work better than models of other languages: It can be noted from Figures 4 and 3 that the English models have the best performance across all classes  This can be attributed to two reasons: absence of national dialect specific words and lesser pretraining data in the case of Portuguese 
4  British English is most correctly classified class: We can observe that the Spanish or Portuguese models make equal number of mistakes in the case of either national dialect, in the case of Track-2 (see Figure )  However, in the case of English, the label EN − GB is correctly classified for more than 95% of the cases 
We speculate this is because British English involves slightly distinctive grammar and semantics, which help the model separate it from other classes  5  The proposed 2-step method is scalable for multiple language dialect classification: We can strongly assert that the novel 2-step deep learning method for multilingual dialect classification is a scalable method for the task due to two specific reasons: firstly, the multilingual models (like XLM-RoBERTa) might not have the vocabulary as well as the learning capabilities to learn the minute differences between individual dialects 
Secondly, this system can be quickly expanded for a new language by simply adding a language specific dialect classifier, provided the language identification model supports that particular language 

Conclusion

In this paper we propose a two-stage classification pipeline for dialect identification for multilingual corpora  We conduct thorough ablations on this setup and provide valuable insights  We foresee multiple future directions for this work  The first is to expand this work to many languages and dialects 
Secondly, it is a worthwhile research direction to distill this multi-model setup into a single model with multiple prediction heads  The obvious limitation of this system is the excessive memory consumption due to the usage of language specific models  For low resource languages this system is difficult to train and scale 
We hope that these problems will be addressed by researchers in future works 



ground_truth: Sustained viral gene delivery through core-shell fibers and Gene transfer to hemophilia A mice via oral delivery of FVIII-chitosan nanoparticles.