Miracle-dz/UniFAR-FTUs huggingface dataset:
A Model Study of the Relationship between Sea-Ice Variability and Surface and Intermediate Water Mass Properties in the Labrador Sea

Abstract Sea ice plays an important role in the variability of the Labrador Sea especially in its most western part adjacent to an important region of deep convection. Winter-to-winter re-emergence and propagation of both sea-ice concentration (SIC) and sea surface temperature anomalies have been observed following years of high SIC in this region. They have potentially important links to water mass properties and freshwater and heat transports in the subpolar North Atlantic. This article builds on the results of two precursor papers and presents results from a coupled sea-ice–ocean model study of the interannual variability of sea ice in the Labrador Sea. The relationships between SIC and water column properties in the subpolar North Atlantic are assessed. Winters with high SIC and strong surface cooling are found to be conducive to intensified convection. Surface and mid-depth temperature and salinity anomalies are observed in the Labrador Sea and the northwestern North Atlantic during winters with anomalous Labrador Sea SIC. These anomalies are found to propagate along the major circulation patterns in the subpolar North Atlantic and to persist for up to three years.
Observation of generalized optomechanical coupling and cooling on cavity resonance.

Optomechanical coupling between a light field and the motion of a cavity mirror via radiation pressure plays an important role for the exploration of macroscopic quantum physics and for the detection of gravitational waves (GWs). It has been used to cool mechanical oscillators into their quantum ground states and has been considered to boost the sensitivity of GW detectors, e.g., via the optical spring effect. Here, we present the experimental characterization of generalized, that is, dispersive and dissipative, optomechanical coupling, with a macroscopic (1.5 mm)2-size silicon nitride membrane in a cavity-enhanced Michelson-type interferometer. We report for the first time strong optomechanical cooling based on dissipative coupling, even on cavity resonance, in excellent agreement with theory. Our result will allow for new experimental regimes in macroscopic quantum physics and GW detection.
Identifiability of 2-tree mixtures for group-based models

Phylogenetic data arising on two possibly different tree topologies might be mixed through several biological mechanisms, including incomplete lineage sorting or horizontal gene transfer in the case of different topologies, or simply different substitution processes on characters in the case of the same topology. Recent work on a 2-state symmetric model of character change showed such a mixture model has non-identifiable parameters, and thus it is theoretically impossible to determine the two tree topologies from any amount of data under such circumstances. Here the question of identifiability is investigated for 2-tree mixtures of the 4-state group-based models, which are more relevant to DNA sequence data. Using algebraic techniques, we show that the tree parameters are identifiable for the JC and K2P models. We also prove that generic substitution parameters for the JC mixture models are identifiable, and for the K2P and K3P models obtain generic identifiability results for mixtures on the same tree. This indicates that the full phylogenetic signal remains in such mixtures, and that the 2-state symmetric result is thus a misleading guide to the behavior of other models.
Quantum Damped Harmonic Oscillator Revisited

In this paper we revisit the quantum damped harmonic oscillator and construct an interesting approximate solution in the operator algebra level. Namely, we first give the general solution to the Lindblad form (equation) and next construct an approximate solution to the full equation by use of it. Our method is a milestone to construct the general solution. In this paper we revisit dynamics of a quantum open system. First of all we explain our purpose in a short manner. See [1] as a general introduction to this subject. We consider E-mail address : fujii@yokohama-cu.ac. jp E-mail address : suzukita@aoni.waseda. jp ; i027110@sic.shibaura-it.ac. jp
Lining up on the M1: a Tooth Defect as a Bio-indicator for Environment and Husbandry in Ancient Pigs

AbstractFrom the analysis of five collections of pig mandibles of Neolithic and medieval date, it is argued that the detailed observation of a common developmental tooth defect, i.e., linear enamel hypoplasia, can shed light on the impact of environmental conditions and husbandry practices on ancient swine herding. It is suggested that degradation of forest environment through the Middle Ages, was responsible for an increase of the frequency of LEH in domestic pigs. Conversely, a supposed late medieval shift in pig husbandry, from forest herding to rearing in (semi-)confinement, could have been the cause of a significant decrease in the occurrence of this tooth defect.
Strong linkages between dimethylsulphoniopropionate (DMSP) and phytoplankton community physiology in a large subtropical and tropical Atlantic Ocean data set

We present an extensive data set of dimethylsulphide (DMS, n = 651) and dimethylsulphoniopropionate (DMSP, n = 590) from the Atlantic Meridional Transect program. These data are used to derive representative depth profiles that illustrate observed natural variations and can be used for DMS and DMSP model‐validation in oligotrophic waters. To further understand our data set, we interpret the data with a wide range of accompanying parameters that characterize the prevailing biogeochemical conditions and phytoplankton community physiology, activity, taxonomic composition, and capacity to cope with light stress. No correlations were observed with typical biomarker pigments for DMSP‐producing species. However, strong correlations were found between DMSP and primary production by cells >2 μm in diameter and between DMSP and some photo‐protective pigments. These parameters are measures of mixed phytoplankton communities, so we infer that such associations are likely to be stronger in DMSP‐producing organisms. Further work is warranted to develop links between community parameters, DMS, and DMSP at the global scale.
QUBIC – The Q & U Bolometric Interferometer for Cosmology

This In this paper we briefly describe QUBIC, the Q & U Bolometric Interferometer for Cosmology, a novel ground-based instrument designed to measure the extremely faint polarization anisotropy of the cosmic microwave background at intermediate angular scales. In particular we will describe simulations of the optical combiner and feedhorn array used to generate synthesized beam patterns for each detector on our focal plane. A QUBIC technical demonstrator has been built and is being installed in the observing site at Alto Chorrillos, Argentina with first light expected in 2022.
Sequential path planning for a formation of mobile robots with split and merge

An algorithm for robot formation path planning is presented in this paper. Given a map of the working environment, the algorithm finds a path for a formation taking into account possible split of the formation and its consecutive merge. The key part of the solution works on a graph and sequentially employs an extended version of Dijkstra's graph-based algorithm for multiple robots. It is thus deterministic, complete, computationally inexpensive, and finds a solution for a fixed source node to other node in the graph. Moreover, the presented solution is general enough to be incorporated into high-level tasks like cooperative surveillance and it can benefit from state-of-the-art formation motion planning approaches, which can be used for evaluation of edges of an input graph. The performed experimental results demonstrate behavior of the method in complex environments for formations consisting of tens of robots.
The influence of sea ice physics on simulations of climate change

In this study, we examine the influence of ice dynamics and the sub-grid-scale ice thickness distribution on present-day and climate change simulations in a global coupled ice-ocean-atmosphere model of intermediate complexity. Under present-day conditions the sea-ice physics modifies both the annual mean and seasonal variation of ice-ocean-atmosphere conditions. In models with motionless sea ice, the ice volume increases and undergoes a smaller seasonal cycle. Resolving the ice thickness distribution also increases the ice thickness, but enhances the seasonal cycle. The response of the system to increased atmospheric CO2 forcing is also dependent on the sea ice physics. Simulating ice dynamics and the ice thickness distribution enhances the ice area response. However, the ice volume response is diminished when ice dynamics is included and enhanced when the ice thickness distribution is resolved. The oceanic thermohaline circulation and regional air temperature response to global warming is also dependent on the sea ice parameterizations. Additional simulations were performed to quantify the influence of the albedo feedback mechanism on climate change simulations. When the albedo feedback was inactive, amplified warming was still present (although reduced) at high latitudes due to the poleward retreat of the ice cover and larger ocean-atmosphere heat exchange. In these simulations, the albedo feedback accounted for 17% of the global air temperature increase and over 30% of the Northern Hemisphere ice area and volume decrease.
Response to Comment on "Low-frequency lattice phonons in halide perovskites explain high defect tolerance toward electron-hole recombination"

Recently we proposed that defect tolerance in the hybrid perovskites is due to their characteristic low-frequency lattice phonon modes that decrease the non-adiabatic coupling and weaken the overlap between the free carrier and defect states [Sci. Adv. 6 7, eaaw7453 (2020)]. Kim and Walsh disagree with the interpretation and argue that there are flaws in our employed methodology. Herein we address their concerns and show that their conclusions are not valid due to misunderstandings of nonadiabatic transition.
Spectral Analysis of Randomly Generated Networks with Prescribed Degree Sequences

Network science attempts to capture real-world phenomenon through mathematical models. The underlying model of a network relies on a mathematical structure called a graph. Having seen its early beginnings in the 1950’s, the field has seen a surge of interest over the last two decades, attracting interest from a range of scientists including computer scientists, sociologists, biologists, physicists, and mathematicians. The field requires a delicate interplay between real-world modeling and theory, as it must develop accurate probabilistic models and then study these models from a mathematical perspective. In my thesis, we undertake a project involving computer programming in which we generate random network samples with fixed degree sequences and then record properties of these samples. We begin with a real-world network, from which we extract a sample of at least one-hundred vertices through the use of snowball sampling. We record the degree sequence, D, of this sample and then generate random models with this same degree sequence. To generate these models, we use a well-known graph algorithm, the Havel-Hakimi algorithm, to produce an initial non-random sample GD. We then run a Monte Carlo Markov Chain (MCMC) on the sample space of graphs with this degree sequence beginning at GD in order to produce a random graph in this space. Denote this random graph by HD. Lastly, we compute the eigenvalues of the Laplacian matrix of HD, as these eigenvalues are intricately connected with the structure of the graph. In doing this, we intend to capture local properties of the network captured by the degree sequence alone. The programming of this project is done in Python and Matlab.
Piezoelectric-based in-situ damage detection of composite materials for structural health monitoring systems

Cost-effective and reliable damage detection is critical for the utilization of composite materials. This thesis presents the conclusions of an analytical and experimental survey of candidate methods for in-situ damage detection in composite materials. Finite element results are presented for the application of modal analysis and Lamb wave techniques to quasi-isotropic graphite/epoxy test specimens containing representative damage. These results were then verified experimentally by using piezoelectric patches as actuators and sensors for both sets of experiments. The passive modal analysis method was reliable for detecting small amounts of global damage in a simple composite structures. By comparison, the active Lamb wave method was sensitive to all types of local damage present between the sensor and actuator, provided useful information about damage presence and severity, and presents the possibility of estimating damage type and location. Analogous experiments were also performed for more complex builtup structures such as sandwich beams, stiffened plates and composite cylinders. These techniques have proven suitable for structural health monitoring applications since they can be applied with low power conformable sensors and can provide useful information about the state of a structure during operation. Piezoelectric patches could also be used as multipurpose sensors to test using a variety of methods such as modal analysis, Lamb wave, acoustic emission and strain based methods simultaneously by altering driving frequencies and sampling rates. Guidelines and recommendations drawn from this research are presented to assist in the design of a structural health monitoring system for a vehicle, and provides a detailed example of a SHM system architecture. These systems will be an important component in future designs of air and spacecraft to increase the feasibility of their missions. Thesis Supervisor: S. Mark Spearing Title: Associate Professor of Aeronautics and Astronautics
Data-driven Expansion of Dense Regions – A Cartographic Approach in Literary Geography

Abstract Cartographic visualisation of the literary space is facing a major challenge resulting from different levels of detail within which the textual descriptions of settings are made by authors. Those range between very detailed descriptions within parts of a city to spatially spread events within a country, or long journeys across continents. Depending on the fictional texts, fictional action often concentrates on a few main places, resulting in high information density – in the form of various individual settings. As well, they are also embedded in a larger environment. When interactively analysing or choosing a section to print a literary map with individual spatial elements, the user has to choose a map scale, which will result in the output of either a detailed representation of a main place or the geographical overview of the fictional space having a small level of detail. However, it would be a great advantage to receive as much information as possible from one single map view. In order to achieve this, this paper presents a method that allows increasing the representable amount of information, depending on its density. Our method makes use of the diffusion algorithm that is used to create value-by-area cartograms. This algorithm is applied to an auxiliary density grid derived from the distribution of individual settings of a literary map that are to be displayed. The resulting distortion is subsequently transferred to the data of the literary map. Unlike the usual use of area cartograms, we do not aim to represent a statistical value; instead information density is used to provide space for the depiction of the information itself. Various parameters such as grid resolution, scale factor and a smoothing filter visually influence the final map distortion. On the basis of several map examples taken from the ‘Literary Atlas of Europe’ project database, distortion results generated from the application of different parameters are visually examined. Using this process, we improved the proposed approach and generalised an appropriate initial configuration for the automated generation of distorted maps through the usage of its information density.
AN EXPERIMENTAL STUDY ON EARTHQUAKE FAULT RUPTURE PROPAGATION THROUGH A SANDY SOIL DEPOSIT

This paper presents the results of experimental studies to examine propagation of fault ruptures with particular concern on dip-slip fault. The pattern of rupture propagation through a sandy soil and the location of surface rupture were investigated. The distortion of surface ground accompanied by fault rupture has been examined as well. The 1-g model tests showed that the location of surface fault rupture varied depending on the model thickness due to strongly dilatant behavior of sand under low confinement. However, the increase of confinement at centrifuge models provided no definite variation of the location against the change of model thickness, which suggested the importance of interpretation about the results from small scale sandbox test.
Loss-on-Ignition as an Estimate of Soil Organic Matter1

Loss-on-ignition at 430C of calcareous and noncalcareous soils has been compared with organic matter contents estimated by a wet oxidation method. The presence of CaCO₃ did not affect the magnitude of the ignition-loss and the gravimetric method provides both a reliable and simple estimation of soil organic matter.
On the Complexity of Random Satisfiability Problems with Planted Solutions

The problem of identifying a planted assignment given a random k-SAT formula consistent with the assignment exhibits a large algorithmic gap: while the planted solution can always be identified given a formula with O(n log n) clauses, there are distributions over clauses for which the best known efficient algorithms require nk/2 clauses. We propose and study a unified model for planted k-SAT, which captures well-known special cases. An instance is described by a planted assignment σ and a distribution on clauses with k literals. We define its distribution complexity as the largest r for which the distribution is not r-wise independent (1 ≤ r ≤ k for any distribution with a planted assignment). Our main result is an unconditional lower bound, tight up to logarithmic factors, of Ω(nr/2) clauses for statistical algorithms, matching the known upper bound (which, as we show, can be implemented using a statistical algorithm). Since known approaches for problems over distributions have statistical analogues (spectral, MCMC, gradient-based, convex optimization etc.), this lower bound provides a rigorous explanation of the observed algorithmic gap. The proof introduces a new general technique for the analysis of statistical algorithms. It also points to a geometric paring phenomenon in the space of all planted assignments. We describe consequences of our lower bounds to Feige's refutation hypothesis and to lower bounds on general convex programs that solve planted k-SAT. Our bounds also extend to the planted k-CSP model, defined by Goldreich as a candidate for one-way function, and therefore provide concrete evidence for the security of Goldreich's one-way function and the associated pseudorandom generator when used with a sufficiently hard predicate.
Temperature and moisture regimes in soils mulched with transparent polyethylene

A numerical one-dimensional model was developed in order to study the effect of soil mulching with transparent polyethylene film upon the soil moisture and temperature regimes. Environmental conditions, soil physical characteristics, and optical properties of the cover are considered. Calculated moisture and temperature profiles were compared with observed ones in experimental field plots. It was shown that soil moisture and temperature distributions are significantly influenced by the polyethylene mulch. The results indicate that the numerical model accurately predicts the soil moisture and temperature regimes in two tested soils. In both a Rehovot sand soil and a light clay soil, experimental and calculated results showed that the temperature maxima of the soil increase with increasing soil moisture content. In the light clay soil both the experimental and numerical results showed that the tarping of the soil with transparent polyethylene caused a significant increase in soil moisture in the upper soil layer. At close to air-dry moisture content, the maximum temperature of the light clay soil indicated a much higher value than the wettest mulched plot of the same soil. Physically based explanations are given for the measured and computed results.
Fast resource scheduling in HetNets with D2D support

Resource allocation in LTE networks is known to be an NP-hard problem. In this paper, we address an even more complex scenario: an LTE-based, 2-tier heterogeneous network where D2D mode is supported under the network control. All communications (macrocell, microcell and D2D-based) share the same frequency bands, hence they may interfere. We then determine (i) the network node that should serve each user and (ii) the radio resources to be scheduled for such communication. To this end, we develop an accurate model of the system and apply approximate dynamic programming to solve it. Our algorithms allow us to deal with realistic, large-scale scenarios. In such scenarios, we compare our approach to today's networks where eICIC techniques and proportional fairness scheduling are implemented. Results highlight that our solution increases the system throughput while greatly reducing energy consumption. We also show that D2D mode can effectively support content delivery without significantly harming macrocells or microcells traffic, leading to an increased system capacity. Interestingly, we find that D2D mode can be a low-cost alternative to microcells.
Nanopores -- a Versatile Tool to Study Protein Dynamics.

Proteins are the active working horses in our body. These biomolecules perform all vital cellular functions from DNA replication and general biosynthesis to metabolic signaling and environmental sensing. While static 3D structures are now readily available, observing the functional cycle of proteins - involving conformational changes and interactions - remains very challenging, e.g., due to ensemble averaging. However, time-resolved information is crucial to gain a mechanistic understanding of protein function. Single-molecule techniques such as FRET and force spectroscopies provide answers but can be limited by the required labelling, a narrow time bandwidth, and more. Here, we describe electrical nanopore detection as a tool for probing protein dynamics. With a time bandwidth ranging from microseconds to hours, it covers an exceptionally wide range of timescales that is very relevant for protein function. First, we discuss the working principle of label-free nanopore experiments, various pore designs, instrumentation, and the characteristics of nanopore signals. In the second part, we review a few nanopore experiments that solved research questions in protein science, and we compare nanopores to other single-molecule techniques. We hope to make electrical nanopore sensing more accessible to the biochemical community, and to inspire new creative solutions to resolve a variety of protein dynamics - one molecule at a time.