Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of inhomogeneities for vortex nucleation in superconductors within time-dependent Ginzburg-Landau theory

We use Time-Dependent Ginzburg-Landau theory to study the nucleation of vortices in type II superconductors in the presence of geometric and material inhomogeneities. The superconducting Meissner state is meta-stable up to a critical magnetic field, known as the superheating field. For a uniform surface and homogenous material, the superheating transition is driven by a non-local critical mode in which an array of vortices simultaneously penetrate the surface. In contrast, we show that even a small amount of disorder localizes the critical mode and can have a significant reduction in the effective superheating field for a particular sample. Our approach uses a finite element method to simulate a cylindrical geometry in 2 dimensions and a film geometry in 2 and 3 dimensions. We combine saddle node bifurcation analysis along with a novel fitting procedure to evaluate the superheating field and identify the unstable mode. We demonstrate agreement with previous results for homogenous geometries, and extend the analysis to include surface roughness and local variations in material properties. We discuss implications for fabrication and performance of superconducting resonant frequency cavities in particle accelerators.
Non-linear structure formation for dark energy models with a Steep Equation of State

We study the non-linear regime of large scale structure formation considering a dynamical dark energy (DE) component determined by a Steep Equation of State parametrization (SEoS), w(z)=w0+wi(z/zT)q1+(z/zT)q. In order to perform the model exploration at low computational cost, we modified the publicly available L-PICOLA code. We incorporate the DE model employing the first and second-order matter perturbations in the Lagrangian frame and the expansion parameter. We analyse deviations of dynamical DE models w.r. t. ΛCDM in the non-linear matter power spectrum, Pk, the halo mass function (HMF), and the two-point correlation function (2PCF) . We investigate the effect of a steep (SEoS-I) and smooth transition (CPL-lim) in the DE equation of state (EoS) . In the former case, we found an overall impact in the Pk at the level of ∼ 2–3% while, for the latter, we found ∼ 3–4% differences w.r. t. ΛCDM at 0z=. The HMF shows the possibility to distinguish between the models at the high mass end. For the best-fit model, dubbed SEoS-II, we observe large deviations from ΛCDM . This is explained by the combined effect of the dynamical DE with the different amount of matter, Ωm0, and the higher value for H0. Regarding the 2PCF, our results are relatively robust with deviations w.r. t. ΛCDM or the order ∼ 1–2 % for SEoS-I and CPL-lim, and more significant deviation for SEoS-II throughout the r range, making SEoS-I a competitive model. Finally, we conclude that the search for viable DE models (like the SEoS) must include non-linear growth constraints.
Unimodal-Uniform Constrained Wasserstein Training for Medical Diagnosis

The labels in medical diagnosis task are usually discrete and successively distributed. For example, the Diabetic Retinopathy Diagnosis (DR) involves five health risk levels: no DR (0), mild DR (1), moderate DR (2), severe DR (3) and proliferative DR (4). This labeling system is common for medical disease. Previous methods usually construct a multi-binary-classification task or propose some re-parameter schemes in the output unit. In this paper, we target on this task from the perspective of loss function. More specifically, the Wasserstein distance is utilized as an alternative, explicitly incorporating the inter-class correlations by pre-defining its ground metric. Then, the ground metric which serves as a linear, convex or concave increasing function w.r. t. the Euclidean distance in a line is explored from an optimization perspective. Meanwhile, this paper also proposes of constructing the smoothed target labels that model the inlier and outlier noises by using a unimodal-uniform mixture distribution. Different from the one-hot setting, the smoothed label endues the computation of Wasserstein distance with more challenging features. With either one-hot or smoothed target label, this paper systematically concludes the practical closed-form solution. We evaluate our method on several medical diagnosis tasks (e.g., Diabetic Retinopathy and Ultrasound Breast dataset) and achieve state-of-the-art performance.
Keeping Self-Interest under Control: Effects of Procedural Fairness and Project Success Rate in a Cost-Reduction Context

In this study, we investigated the effects of procedural fairness (fair and no fair) and success rate on self-interest behavior. We compared a fair procedure condition that provides detail information regarding colleagues’ cost structure and their willingness to sacrifice with an unfair condition without such information. Participants were assigned into two success rate groups: low and high. We expected that individuals who encountered a higher success rate condition were inclined toward a self-interest choice. Ultimately, we hypothesized that procedural fairness and success rate have an interaction effect on self-interest behavior. We conducted a controlled laboratory experiment to investigate individual decision process in a standard costing setting. The participants were 136 undergraduate business students enrolled in management accounting classes at three large private universities that acted to be the managers in a production department. They completed an experimental task on computer. The result of our experiment indicated a mitigating effect of procedural fairness on the individuals’ self-interest behavior once the individuals realized the pressure of cost reduction process. The findings allow concluding that both self-interest and social preferences are guiding motivational factors of individual behavior. The findings indicated that people are willing to pursue organizational goals on the expense of their personal benefits. The results also showed the process of encouraging employees to undertake projects that decrease their current benefit but potentially have future organizational payoff. However, we did not find the interaction effect between procedural fairness and success rate.
Enriching Conversation Context in Retrieval-based Chatbots

Work on retrieval-based chatbots, like most sequence pair matching tasks, can be divided into Cross-encoders that perform word matching over the pair, and Bi-encoders that encode the pair separately. The latter has better performance, however since candidate responses cannot be encoded offline, it is also much slower. Lately, multi-layer transformer architectures pre-trained as language models have been used to great effect on a variety of natural language processing and information retrieval tasks. Recent work has shown that these language models can be used in text-matching scenarios to create Bi-encoders that perform almost as well as Cross-encoders while having a much faster inference speed. In this paper, we expand upon this work by developing a sequence matching architecture that %takes into account contexts in the training dataset at inference time. utilizes the entire training set as a makeshift knowledge-base during inference. We perform detailed experiments demonstrating that this architecture can be used to further improve Bi-encoders performance while still maintaining a relatively high inference speed.
Dissipation and decoherence for generic open quantum systems

We study generic open quantum systems with Markovian dissipation, focusing on a class of stochastic Liouvillian operators of Lindblad form with independent random dissipation channels (jump operators) and a random Hamiltonian. We perform a thorough numerical study, focusing on global spectral features, the spectral gap, and the steady-state purity and statistics. We establish that all properties follow three different regimes as a function of the dissipation strength, whose boundaries depend on the particular observable. Within each regime, we determine the scaling exponents with the dissipation strength and system size. On the analytical side, we compute the average spectral gap at arbitrary dissipation and provide simple closed-form expressions for the asymptotic values at strong and weak dissipation strength. We also consider spectral correlations in generic complex spectra, such as that of the Liouvillian. We introduce and study, both analytically and numerically, the complex ratio of the nearest-neighbor spacing by next-to-nearest-neighbor spacing. Besides the usual level repulsion, we find that complex spacing ratios have a nontrivial angular dependence which offers a distinct signature of quantum chaos. It distinguishes integrable systems, which support the flat ratio distribution characteristic of Poisson statistics, and chaotic dissipative quantum systems, which conform to Random Matrix Theory statistics. We apply this new signature of quantum chaos to random Liouvillians and boundary-driven dissipative spin-chains. The results of this thesis can help understand the long-time dynamics, steady-state properties, and spectral correlations of generic dissipative systems.
Ireland: a new frontier for the zebra mussel Dreissena polymorpha [Pallas]

Zebra mussels are thought to have colonised Ireland about 1993/4 arriving as fouling on the hulls of leisure craft from Britain. The species has spread to at least 57 Irish lakes, either with fouled craft using the inland navigation or with overland movements of craft on trailers or by other means. Zebra mussels have changed the trophic structure of lakes and there have been impacts on some recreational activities and water abstraction. The species may be expected to spread to other Irish lakes. Small craft are recognised as an important vector and further imports of craft to Ireland may result in the introduction of further non-native species.
Monotonicity and phase transition for the VRJP and the ERRW

The vertex-reinforced jump process (VRJP), introduced by Davis and Volkov, is a continuous-time process that tends to come-back to already visited vertices. It is closely linked to the edge-reinforced random walk (ERRW) introduced by Coppersmith and Diaconis in 1986 which is more likely to cross edges it has already crossed. On $\mathbb{Z}^d$ for $d\geq 3$, both models where shown to be recurrent for small enough initial weights (by Sabot, Tarres(2015) and Angel,Crawford,Kozma(2014)) and transient for large enough initial weights (by Disertori,Sabot,Tarres(2015) and Sabot,Tarres(2015)). We show through a coupling of the VRJP for different weights that the VRJP (and the ERRW) exhibits some monotonicity. In particular, we show that increasing the initial weights of the VRJP and the ERRW makes them more transient which means that the recurrence/transience phase transition is necessarily unique. Furthermore, by making the weights go to infinity, we show that the recurrence of the ERRW and the VRJP is implied by the recurrence of a random walk in deterministic electrical network.
Specific in vivo absorption coefficient of chlorophyll a at 675 nm

Spectral absorption of phytoplankton from cultures and natural samples was measured by means of an integrating-sphere photometer. Measurements on suspension yielded specific absorption coefficients for healthy phytoplankton cultures in collimated light at 675 nm between 0.007 and 0.0 13 m2 (mg Chl a) I. These values were independent of cell density and cell wall material. Natural samples of Kiel harbor water yielded specific absorption coefficients at 675 nm of 0.009 and 0.017 m2 (mg Chl a)- I. The specific absorption coefficients in suspension were dependent on the optical properties of the individual cells (packaging effect), decreasing (ca. l/r) with increasing cell size (r radius) and increasing chlorophyll a content per cell as predicted by theory, but are significantly lower than theoretically expected. Comparison with published values shows that specific absorption coefficients of cell suspensions are often overestimated, presumably because of methodological problems.
IMPACT OF INSTITUTIONAL CREDIT ON PRODUCTION EFFICIENCY OF FARMING SECTOR A Case Study of District Faisalabad

The paper highlighted the level of production efficiency of the farming sector in district Faisalabad in the Punjab province of Pakistan. Stochastic Frontier Analysis (SFA) technique was utilized at farm level survey data of 300 farmers for the year 2009. The overall mean efficiency score was 0.84 indicating 16 percent inefficiency of the sample farmers. The SFA estimation method also illustrated the parameters for the inefficiency. Farming experience, education, access to farming credit, herd size and number of cultivation practices showed constructive and significant effect on the farmer's technical efficiency. The variable of credit showed highest coefficient value (-0.14) indicating the importance for the agricultural credit showing that availability of credit to farmers was much more important than any other factor to improve the resource use efficiency in agriculture sector.
A Programmable Approach to Model Compression

Deep neural networks frequently contain far more weights, represented at a higher precision, than are required for the specific task which they are trained to perform. Consequently, they can often be compressed using techniques such as weight pruning and quantization that reduce both model size and inference time without appreciable loss in accuracy. Compressing models before they are deployed can therefore result in significantly more efficient systems. However, while the results are desirable, finding the best compression strategy for a given neural network, target platform, and optimization objective often requires extensive experimentation. Moreover, finding optimal hyperparameters for a given compression strategy typically results in even more expensive, frequently manual, trial-and-error exploration. In this paper, we introduce a programmable system for model compression called Condensa. Users programmatically compose simple operators, in Python, to build complex compression strategies. Given a strategy and a user-provided objective, such as minimization of running time, Condensa uses a novel sample-efficient constrained Bayesian optimization algorithm to automatically infer desirable sparsity ratios. Our experiments on three real-world image classification and language modeling tasks demonstrate memory footprint reductions of up to 65x and runtime throughput improvements of up to 2.22x using at most 10 samples per search. We have released a reference implementation of Condensa at this https URL.
HIPPI-2: A versatile high-precision polarimeter

Abstract We describe the High-Precision Polarimetric Instrument-2 (HIPPI-2) a highly versatile stellar polarimeter developed at the University of New South Wales. Two copies of HIPPI-2 have been built and used on the 60-cm telescope at Western Sydney University’s (WSU) Penrith Observatory, the 8.1-m Gemini North Telescope at Mauna Kea and extensively on the 3.9-m Anglo-Australian Telescope (AAT). The precision of polarimetry, measured from repeat observations of bright stars in the SDSS g′band, is better than 3.5 ppm (parts per million) on the 3.9-m AAT and better than 11 ppm on the 60-cm WSU telescope. The precision is better at redder wavelengths and poorer in the blue. On the Gemini North 8-m telescope, the performance is limited by a very large and strongly wavelength-dependent TP that reached 1000’s of ppm at blue wavelengths and is much larger than we have seen on any other telescope.
Operations strategy optimization based on developed sense and respond methodology

How to make adaptive adjustments on operations strategy in dynamic business environments becomes the very important competitiveness to all kinds of companies. This paper aims to develop sense and respond (S&R) models in agile and dynamic strategic adjustment by introducing scaled critical factor index (SCFI) compared with previous S&R models such as critical factor index (CFI) and balanced critical factor index (BCFI). In addition, the case study in this paper shows the difference among the three S&R models and the advantages of SCFI model. The analysis results show that the SCFI models have contribution to the adaptive operations strategy adjustment based on clear objectives in dynamic and turbulent business environment. Managers can make quick decisions by the analytical models.
An Efficient (t, n)-Threshold Multi-Secret Sharing Scheme

An efficient (t, n) threshold multi-secret sharing scheme is proposed in this paper. This scheme has the same power as Yang et al. 's scheme, in which there are p (p > 1) secrets to be shared among n participants according to (t, n)-threshold access structure. But it uses the fixed ( t -1 )th degree Lagrange interpolation polynomial whenever p les t or p > t while Yang et al.' scheme employs the (t-1), (p-1)th degree Lagrange interpolation polynomial when p les t, p > t, respectively. Thus, the computing time and the storage cost of this scheme is less than that of Yang et al.'s scheme.
The use of motion analysis as a coaching aid to improve the individual technique in sprint hurdles

Biomechanical data are oflen presented as a group average, which may not always help individual athletes to improve their own performance. The purpose of this study was to analyse techniques in sprint hurdles within the athlete and find critical individual aspects, which influence performance. The hurdle clearance of three athletes (eight trials each) were videotaped with four video camera recorders and analysed three-dimensionally. There were several statistically significant correlations between the critical overall horizontal velocity and other variables, especially for one athlete. Such trends in individual performance presented ideas to coaches, athletes and also to researchers, regarding what happened in less successful runs and which technical points were worth individual attention in training.
Decisions in hierarchical production planning: goals, heuristics and bias

An experiment emulates a hierarchical production planning environment with the aim to determine the effect of goal setting on the production scheduler's performance with regard to lot sizing costs. Some heuristics and biases influencing the production scheduler's decision-making were detected. Reiterative behavioral patterns and the use of statistical parametric procedures found that goal setting reduces the production scheduler's cost dispersion, making the results more predictable, but there's no influence on performance. Production schedulers often use representativeness and availability heuristics and, the more frequent biases affecting the production scheduler's decision-making process are related to subjective probability setting and loss aversion.
accination coverage among school children aged 14 – 15 years in the French department of Sarthe Évaluation des couvertures vaccinales chez les élèves de troisième dans le département de la Sarthe

Objectives. – Vaccinations are the main pillar of primary prevention for infectious diseases. To guide and prioritize public health interventions, the egional Health Agency has asked the Prevention, Vaccination, and Screening Center of the Sarthe department to assess vaccination coverage (VC) t the sub-departmental level. The main objective was to measure the VC among school children aged 14–15 years in Sarthe at the sub-departmental evel. Patients and methods. – We conducted a VC evaluation survey at the administrative district level among school children aged 14–15 years in he Sarthe department during the first quarter of the 2015–2016 school year. Results. – Among 2384 randomly selected school children, 1171 were included in the study. At the departmental level, 85% of children were up o date for DTP, 72% for pertussis, 45% for hepatitis B, 31% for meningococcus C, 93% for measles, and 18% of girls had received at least one ose of the HPV vaccine. Vaccination coverage varied by administrative districts. Conclusion. – At the departmental level, all VC were below national goals. Territorial disparities could be explained by sociodemographic ifferences or differences in medical practices. This survey allowed us to identify areas and population groups where the CV rate justified public ealth actions. 2017 Elsevier Masson SAS. All rights reserved.
On the smallness condition in linear inviscid damping: monotonicity and resonance chains

We consider the effects of mixing by smooth bilipschitz shear flows in the linearized Euler equations on T L × R . Here, we construct a model which is closely related to a small high frequency perturbation around Couette flow, which exhibits linear inviscid damping for L sufficiently small, but for which damping fails if L is large. In particular, similar to the instability results for convex profiles for a shear flow being bilipschitz is not sufficient for linear inviscid damping to hold. Instead of an eigenvalue-based argument the underlying mechanism here is shown to be based on a new cascade of resonances moving to higher and higher frequencies in y, which is distinct from the echo chain mechanism in the nonlinear problem.
Bicyclotomic polynomials and impossible intersections

In a recent paper we proved that there are at most finitely many complex numbers t 6= 0, 1 such that the points (2, √ 2(2− t)) and (3, √ 6(3− t)) are both torsion on the Legendre elliptic curve defined by y2 = x(x − 1)(x − t). In a sequel we gave a generalization to any two points with coordinates algebraic over the field Q(t) and even over C(t). Here we reconsider the special case (u, √ u(u− 1)(u− t)) and (v, √ v(v − 1)(v − t)) with complex numbers u and v.
Full-scale biodrying process of municipal solid waste

The paper presents the results obtained in the full-scale waste biodrying reactor. The studied facility includes in the biological stage a rectangular-shaped, galvanized steel reactor equipped with a module for active aeration connected with a stove and a bio-filter for removing odours. The undersize fraction (O th days in the 150 m 3 capasity reactor. Initial moisture content of the untreated waste was 54.65%. Moisture content was declined gradually during biodrying process. Temperature changes during 14th days of biodrying process were monitored with the maximum temperature 70°C. To assess the degree of stabilization of the biodried waste, the determination of the O2 uptake was measured. The oxygen demand of untreated waste was 53.16 mg O 2 /g d.m. and after 14 th days for biodried waste oxygen consumption was 19.78 mg O 2 /g d.m. The results obtained in studies by respirometric dynamic method of oxygen uptake (expressed as O 2 /96h parameter) had been compared to the results performed using the static method, where AT 4 is the applied indicator.