dataesr/scientific-paragraphs-categorization huggingface dataset:
Recent African migration to Europe, North America and Oceania While the GBMD is useful to identify long-term migration trends ad patterns, there are less useful for analysing more recent trends in African migration. First, stock data that are very much a 'legacy of the past' that approximate net migration over several decades, which means that recent changes in migration patterns only show up after a long period. Second, the last census round included in the GBMD dates back to 2000. In order to substantiate and complement the preceding analysis, we analyse recent flow data from the DEMIG C2C database, which is particularly useful to uncover recent trends of extra-continental African migration. Figure  8  shows that there has been a recent acceleration and diversification of extra-continental migration from sub-Saharan Africa, particularly to the United States and Canada.
There is indeed some evidence of increasing migration of Africans in search of work, education and business opportunities to fast growing economies such as China  (Ghosh, 2010) , India, Russia, Turkey, Japan, Brazil and Argentina  (Henao, 2009). The role of policies in shaping migration flows in general and in Africa in particular has been understudied, partly due to the lack of appropriate policy data. This section uses new panel data from the DEMIG VISA database (De Haas and Villares-Varela, 2014 forthcoming) to construct measures of relative immigration restrictiveness of African and non-African destinations (broken down by major regional blocks) between 1973 and 2014. This visa restrictiveness index has been calculated by computing the percentage of origin countries that need a travel visa to enter destination country for every year.
Also East Africa is closing. Central Africa's visa restrictiveness index for OECD citizens has been 99 % since the early 2000s. Interestingly, while West Africa has Fig. 13  Visa restrictiveness African countries for nationals African countries, region of destination. Source: DEMIG VISA database opened up to Africans citizens, it has become more closed to free travel of OECD nationals. It is not entirely clear which political processes explain the increasing visa restrictiveness of African countries towards OECD countries (with the exception of Southern Africa). One hypothesis is this partly mirrors the increasing visa restrictiveness of OECD countries for African citizens, suggesting that a certain degree of visa retaliation may have taken place. Figure  15  indeed confirms that there has been a massive trend of OECD countries closing their doors to free travel of African citizens, although there are clear regional differences.
In 1973 OECD countries used to be relatively open towards nationals from Southern Africa and, to a lesser extent, from North Africa with restrictiveness indices of 61 and 73 % respectively. OECD visa restrictiveness for North Africans shot up since 1990 to reach 98 % in 1993, which seems to reflect the Schengen visa imposed for such countries in Europe. By 1995 all African regions had reached. Source: DEMIG VISA database Fig. 15  Visa restrictiveness of OECD countries for nationals from African countries, by region of origin of migrants. Source: DEMIG VISA database OECD visa restrictiveness scores of more than 90 %. For Southern Africans the increase was more gradual, reaching a value of 93 % in 2013. Figures  13  and 14  show that, in overall, African countries have been more restrictive towards nationals from OECD and other non-African countries than towards African nationals.
While all four effects may apply to African migration, the DEMIG VISA data seems to confirm the role of policies in encouraging spatial substitution in the form of diversion away from colonial pattern. Figure  16  shows that until the late 1980s former colonisers were much less restrictive towards migration of the nationals from previous colonial states. By 1988 Fig. 16  Visa restrictiveness of OECD countries for nationals from African countries, by type of link between countries (previous colonial link or not). Source: DEMIG VISA database this gap was largely closed, however, and in 2010 it was completely closed. This can partly explain the diversification of African emigration over the past few decades. So while increasing African emigration has been rooted in structural development trends, destinations seem to have been diversifying not because of a general fading of colonial links, but also partly as a result of closeness of former colonisers parallel to the more favourable immigration opportunities offered (particularly for the skilled) offered by new destinations such as the Canada, the US and Australia.
Acknowledgement The research leading to these results is part of the  DEMIG (Determinants of International Migration)  project and has received funding from the  European Research Council  under the European Community's  Seventh Framework Programme  ( FP7/2007-2013)/ERC Grant Agreement 240940. www. migrationdeterminants. euThe authors would like to thank the DEMIG team members  Mathias Czaika ,  Simona Vezzoli ,  Maria Villares-Varela ,  Katharina Natter  and  Edo Mahendra  for their support and valuable feedback on draft versions of this paper. The authors received the  Rinus Penninx Best Paper Award  for this paper at the 11th Annual IMISCOE Conference, held in Madrid on  27-29 August 2014.
Plasma-liquid interactions represent a growing interdisciplinary area of research involving plasma science, fluid dynamics, heat and mass transfer, photolysis, multiphase chemistry and aerosol science. This review provides an assessment of the state-of-the-art of this multidisciplinary area and identifies the key research challenges. The developments in diagnostics, modeling and further extensions of cross section and reaction rate databases that are necessary to address these challenges are discussed. The review focusses on nonequilibrium plasmas.
The key challenges in this field regarding transport, chemistry, the availability (or lack) of fundamental reaction rates and cross sections, and diagnostics were discussed and identified. This review can trace its origins to discussions originally held at that meeting and Adapted with permission from  [24] , copyright 2014 IOP Publishing. discussions continued by the authors up to the date of submission. Participants of the workshop were given the opportunity to author contributions on topics discussed at the workshop. These contributions were incorporated into sections by the first 9 authors of this manuscript. The final editing was performed by a subgroup of these 9 authors. The goals of this review are to provide the reader with: • An update on the state of the art in the field of nonequilibrium plasma-liquid interactions; • An introductory description of the strongly multidisciplinary topics within the field; • A compilation of key databases and publications; • Identifying the key challenges in the field; • A summary of the necessary advances in diagnostics and models required to address these key challenges; • The critical needs of data for experimentalists and modelers; • Guidelines on possible reference experiments, modeling and diagnostics.
All data sets should be used with caution. However, the recent success of models predicting specific experimental measurements, (for example,  [334] [335] [336] [337] ) can provide additional confidence in the quality of the available data. experimental and theoretical are available  [338] [339] [340] [341] [342]. A typical test of the applicability of data sets of cross sections for electron and ion transport is whether the fundamental datasets can be used to reproduce experimental swarm measurements by using the datasets in solutions of Boltzmann's equation for the velocity distributions. The swarm data are typically Townsend ionization coefficient α, drift velocity w, mobility µ, diffusion coefficient D, and characteristic energy eD/µ derived from measurements of electrons or ions drifting in constant values of E/N (electric field/gas number densities).
Often the initially generated data set of fundamental cross sections does not reproduce experimental swarm data due to there being missing data (e. g. vibrational excitation cross sections) or small inaccuracies to which the derived transport coefficients are very sensitive. It is then typical practice to make small adjustments to the datasets so that the experimental swarm data can reproduced. This then places high importance on the accuracy and availability of experimental swarm data. In addition to the older measured transport data  [343] [344] [345] , newer measurements have been made  [346, 347]. There are several sets of cross sections that were derived based on the swarm (transport) technique  [342, [348] [349] [350] [351] [352]  which are based on several measurements of swarm data  [18, 347, 351, [353] [354] [355].
It is important to complete the cross section set for water-based clusters and to develop accurate models of cluster formation and related transport properties. Those data could be developed by implementing techniques currently used to study general hydration of charged particles. Data for water related ions, both positive and negative, are abundant for humid noble gasses  [374, 375]  and are available for humid air  [376]. General sources of data for ion transport coefficients can be found in  [366, 377, 378]  and in the LXCat database  [349]. These data enable calculations of the transport Plasma Sources Sci. Technol. 25 (2016) 053002 coefficients for relevant ions in some of the gases found in discharges in proximity to liquids. A wide variety of ion-molecule reactions occur in the gas phase containing water vapor  [379] [380] [381] [382] [383] [384] [385] [386]  including detachment reactions that have a number of different channels and a strong energy dependence  [387] [388] [389].
New data or improvements to existing data are needed. However, including every possible reaction is often not practical. A strategy is needed to establish a reliable database for the primary reactions that can be extended to more complex systems adjacent to the liquid surface where the gas may be super-saturated with water vapor and intersects with the ambient gases. This is a region where there are significant gradients in the water content and also in temperature. While there is gas phase data available for ion-molecule reactions for most of the individual constituents in this region  [386, 390] , the accuracy of binary gas phase rate coefficients in this environment is questionable due to the propensity for forming water cluster ions. Descriptions of clustering, hydration and release from the hydrated state can be based on either simpler phenomenological models (effective lifetimes) or on more detailed kinetics.
These reaction mechanisms have met with success in many venues. For example, humid air chemical kinetics models have been used to explain key reaction pathways in water vapor containing discharges  [57, 333, 391]. Most of the plasma chemistry models developed for discharges in contact with liquids and generally in humid atmosphere rely on extensive compilations of data. Most notable are the evaluations of gas phase chemical reactions of neutral species involved in atmosphere chemistry  [392, 393] , databases for positive ion-molecule reactions  [386]  and neutral-neutral chemical reactions in non-thermal humid air plasmas  [394]  and for dry air chemistry  [395]. Further sources of data can be found in the combustion community. Combustion and plasma processes have similarities in their approaches to experiments and modeling.
The combustion community has gained advantage from using standardized reaction mechanisms such as GRIMech, which is essentially a list of community endorsed elementary chemical reactions and associated rate constants, a practice that would also benefit the low temperature plasma community  [400, 401]. While data for the ground-state neutral reactions are relatively well represented in the literature, quantitative data for excited-state reactions is much less extensive. The interpretation of optical emission spectroscopy (OES) requires knowledge of production and quenching rates of the excited species. For example, in addition to electron-impact excitation, electron-ion dissociative recombination is an important channel in the production of excited species  [402]. The data for these processes can be found in databases originally developed for lighting, upper atmospheric chemistry and excimer lasers  [403, 404].
The AOP community also offers a rich source of basic data. This data typically focuses on • OH reactions since they play an important or even dominant role in AOP due to the extreme reactivity and non-selectivity of • OH which can be formed by a number of different mechanisms. Overviews of rate constants used by the AOP community are available  [184, 242]. These datasets have been developed using various approaches. The group contribution method (GCM) used to predict • OH constants in the gas phase  [420] [421] [422]  has emerged as the most accepted method and is implemented in U. S. Environmental Protection Agency software  [423]. However, applying these methods to the liquid phase requires considering changes in functional group properties arising from the close spaced intra-molecular environment, for example, electronic push-pull effects, intermolecular hydrogen bond formation and steric effects.
Acknowledgments This manuscript originated from discussions at the  Lorentz Center Workshop 'Gas/Plasma-Liquid Interface : Transport, Chemistry and Fundamental Data' that took place at the  Lorentz Center, Leiden University  in the Netherlands from August 4, through August 8, 2014, and follow-up discussions since the workshop. All authors acknowledge the support of the  Lorentz Center , the  COST action TD1208  ( Electrical Discharges with Liquids for Future Applications ) and the  Royal Dutch Academy of Sciences  for their financial support. PJB, MJK, DBG and JEF acknowledge the support of the 'Center on Control of  Plasma Kin  etics' of the  United States Department of Energy Office of Fusion Energy Science  ( DE-SC0001319 ). In addition, PJB and BRL acknowledge the support of the  National Science Foundation  ( PHY 1500135  and  CBET 1236225 , respectively).
The sensor is a 1 m long tube that converts the acoustic pressure caused by snow particles impacting the tube into an aeolian snow mass flux integrated over the length of the tube. The second-generation FlowCapt ™ was evaluated in the French Alps by  Trouvil-liez et al. (2015). They reported that the instrument underestimates the aeolian snow mass flux compared to a reference optical sensor (snow particle counter S7;  Sato et al. , 1993) , especially during snowfalls. Nevertheless, the equivocal behaviour of the second-generation FlowCapt ™ does not affect its ability to accurately detect the occurrence of aeolian snow transport. Data were sampled at 15 s intervals, averaged to half-hourly means and stored in a Campbell CR3000 datalogger.
Acknowledgements. This work would not have been possible without the financial and logistical support of the  French Polar Institute IPEV  (program  CALVA-1013 ). The authors would like to thank all the on-site personnel in  Dumont d'Urville and Cap Prud'homme  for providing valuable help in the field, in particular  Philippe Dordhain  for electronic and technical support, as well as the two anonymous reviewers for their constructive remarks that helped to improve the manuscript considerably. Edited by:  X. Fettweis.
D. The case for space The main reasons for performing MAQRO in space are the required quality of the microgravity environment ( < ∼ 10 -9 g), the long free-fall times (100 s), the high number of data points required (up to ∼ 10 4 per measurement Since its original proposal as an M3 mission in 2010  [26] , MAQRO has made significant progress in technology development  [27]  and in its support within the scientific community. In 2013, we formed the MAQRO consortium, now consisting of more than 30 groups from the UK, Germany, Italy, France, Austria, Switzerland, the US, Australia and Sweden. MAQRO benefits from significant technological progress made since 2010. The TRLs of several core technologies increased from initial concepts to TRL 3-5. In particular, research groups within the MAQRO consortium have successfully demonstrated cavity cooling of trapped nanospheres  [28, 29] , feedback cooling  [30, 31] , optical trapping of nanospheres in high vacuum  [32] , and hybrid optical & Paul trapping of nanospheres  [29, 33].
The number of data points was chosen in order to limit the integration time to at most four weeks. Moreover, we assumed our test particle to initially be in a thermal state of a harmonic oscillator -with a mechanical frequency ω = 10 5 rad/s, an average occupation number of 0. 3, and that we can determine the particle position with an accuracy of 100 nm. Because the mechanical frequency for an optically trapped particle only depends on the mass density and the material's dielectric constant, the mechanical frequency is roughly constant for the particles chosen for MAQRO. The occupation number, however, is assumed to be inversely proportional to the mass of the test particle because it depends on the optomechanical coupling achievable. Because testing quantum physics using wave-function expansion was first introduced for the CSL model  [50] , and because the CSL model represents a rather general, heuristic approach to collapse models, we will now discuss the prerequisites for testing the CSL model in the context of MAQRO.
ACKNOWLEDGMENTS AB acknowledges financial support from  NANOQUESTFIT ,  INFN , and the  COST Action   MP1006. AR is supported by the  German Space Agency (DLR)  through Grant No. DLR 50WM1136. LN acknowledges support through  ERC-QMES  (no. 338763 ). RK acknowledges support from the  FFG Austrian Research Promotion Agency  (no. 3589434 ).
Student evaluations of teaching (SET) are widely used in academic personnel decisions as a measure of teaching effectiveness. We show:. SET are biased against female instructors by an amount that is large and statistically significant. The bias affects how students rate even putatively objective aspects of teaching, such as how promptly assignments are graded. The bias varies by discipline and by student gender, among other things. It is not possible to adjust for the bias, because it depends on so many factors. SET are more sensitive to students' gender bias and grade expectations than they are to teaching effectiveness. Gender biases can be large enough to cause more effective instructors to get lower SET than less effective instructors. These findings are based on nonparametric statistical tests applied to two datasets: 23,001 SET of 379 instructors by 4,423 students in six mandatory first-year courses in a fiveyear natural experiment at a French university, and 43 SET for four sections of an online course in a randomized, controlled, blind experiment at a US university.
DATA French natural experiment These data, collected between 2008 and 2013, are a census of 23,001 SET from 4,423 (57% women) first-year students in 1,177 sections at a French university, taught by 379 instructors (34% women). The data are not public, owing to French restrictions on human subjects data. Boring  [5]  describes the data in detail. Key features include the following: (1) All first-year students take the same six mandatory courses: history, macroeconomics, microeconomics, political institutions, political science, and sociology. Each course has one (male) professor who delivers the lectures to groups of approximately 900 students. Courses are divided into sections of 10-24 students, taught by male and female instructors. The instructors have considerable pedagogical freedom. (2) Students enrol in "triads" of sections of these courses (three courses per semester).
SET included an overall score and questions relating to professionalism, respectfulness, care, enthusiasm, communication, helpfulness, feedback, promptness, consistency, fairness, responsiveness, praise, knowledge, and clarity. Forty-seven students in the four sections taught by TAs finished the class, of whom 43 submitted SET. The SET data include the genders and birth years of the students, 2  while the grade data do not. The SET data are not linked to the grade data.
The probability distribution of the number of random permutations assignments for which the test statistic is greater than or equal to its observed value is binomial, with n equal to the number of overall random permutations and p equal to the true p-value. Hence, the standard error of the estimated pvalues is hence no larger than ð1=2Þ= ffiffiffiffiffiffiffi ffi 10 5 p ≈0:0016. Code for all our analyses is at https://github. com/kellieotto/SET-and-Gender-Bias. Results for the French data are given in "The French Natural Experiment" section.
In practice, there are prohibitively many assignments (for instance, there are 23 11 24 11 > 3:3 Â 10 12 possible assignments of 47 students to the 4 TA-led sections that keep constant which students are assigned to each TA). Hence, we estimate p-values by simulation, drawing 10 5 equally likely assignments at random, with one exception, noted below. The distribution of the number of simulated assignments for which the test statistic is greater than or equal to its observed value is binomial with n equal to the number of simulated assignments and p equal to the true p-value. Hence, the standard error of the estimated p-values is hence no larger than ð1=2Þ= ffiffiffiffiffiffiffi ffi 10 5 p ≈0:0016. Code for all our analyses is at https://github. com/kellieotto/SET-and-Gender-Bias. Results for the US data are in section 5.
The dynamics of the optimization process for the shaping remained smooth as in the passive case. The evolution of the OF in the course of the DM setting was similar; that is, the measured parameter continuously increased, whereas the system adjusted the imposed phase pixel by pixel. This was expected because the algorithm is of the coordinate ascent type. Optimization of the mirror structure configuration here takes ~120 s, a duration that is fixed by the slow interface between the camera and the LabVIEW software on the desktop. In an improved setup, a simple photodiode performed the same work within a 50 ms time lapse. We checked that the system gave the same output pattern and phase chart after optimization when starting from various initial conditions. Once an optimization has led to the DM settings corresponding to a given spot, they can be recorded.
This then allows us to address both challenging sea-ice-related research questions that are of interest for a wide range of scientists and stakeholders, and to address questions that are of immediate interest for sea-ice scientists. This contribution describes the aim and design of SIMIP in detail. In particular, we describe the requested sea-ice-related variables that are included in the CMIP6 data request (see https://earthsystemcog. org/projects/wip/ CMIP6DataRequest for details). Our hope is that in doing so, we provide a framework that allows for the detailed, unified, and efficient analysis of sea-ice simulations well beyond CMIP6. We first outline briefly some of the most pressing research questions that we hope to address through SIMIP and place them within the CMIP6 context. We then move on to discuss in more detail the philosophy behind the design of SIMIP, which then will hopefully also allow for a consistent future extension of the SIMIP protocol as sea-ice models become more and more sophisticated.