Miracle-dz/UniFAR-FTUs huggingface dataset:
Discriminative deep transfer metric learning for cross-scenario person re-identification

A novel discriminative deep transfer learning method called DDTML is proposed for Cross-scenario Person Reidentification( Re-ID). Using a deep neural network, DDTML learns a set of hierarchical nonlinear transformations for Cross-scenario Person Re-identification by transferring discriminative knowledge from the source domain to the target domain. Meanwhile, taking account of the inherent characteristics of Re-ID data sets, in order to reduce the distribution divergence between the source data and the target data, DDTML minimizes a new maximum mean discrepancy based on Class Distribution called MMDCD at the top layer of the network. Experimental results on widely used Re-identification datasets show the effectiveness of the proposed classifiers.
Electron-electron interactions and the bandwidth of metals.

A calculation is presented of the self-energy of an electron from the screened exchange energy. Vertex corrections are included. They have a large effect upon the predictions of the width of the occupied energy bands. For aluminum the band-width is predicted to be 0.7 eV wider in the /ital GW/approximation compared to /ital GW/GAMMA which includes vertex corrections. Results using the /ital GW/GAMMA approximation are similar to those of the random-phase approximation.
MIRAGE: calibration radiometry system

The advent of high resolution infrared resistor arrays, has greatly increased the level of fidelity of infrared sensor testing that can be accomplished in the cost effective laboratory environment. However, the sensor output image quality depends on the uniformity of the projector array. In addition to the advanced proprietary design and fabrication process used to create a highly uniform emitter array. Santa Barbara Infrared, Inc. (SBIR) applies a high speed correction algorithm to the incoming data stream that improves the uniformity of the final infrared image. The key to this algorithm is a set of calibrated tables that are measured for each emitter element in the array. SBIR has developed a Calibration Radiometry System (CRS) which is used to quickly perform these high precision measurements for each emitter element. This paper looks at the CRS system, reviews the algorithms used for applying the correction and for making the calibration measurements. It concludes with some initial results showing the effect of the calibration tables derived using the CRS.
Microlens arrays

Microlenses have been with us for a long time as indeed the very word lens reminds us. Many early lenses,including those made by Hooke and Leeuwenhoek in the 17th century were small and resembled lentils. Many languages use the same word for both (French tilentillelt and German "Linse") and the connection is only obscure in English because we use the French word for the vegetable and the German for the optic. Many of the applications for arrays of inicrolenses are also well established. Lippmann's work on integral photography at the turn of the century required lens arrays and stimulated an interest that is very much alive today. At one stage, lens arrays played an important part in high speed photography and various schemes have been put forward to take advantage of the compact imaging properties of combinations of lens arrays. The fact that many of these ingenious schemes have not been developed to their full potential has to a large degree been due to the absence of lens arrays of a suitable quality and cost.
Ranger telerobotic shuttle experiment: a status report

This paper presents an update on the Ranger Telerobotic Shuttle Experiment (RTSX) and associated key robotics technologies within the Ranger program. Ranger TSX will operate from a Spacelab logistics pallet inside the cargo bay of the shuttle and will demonstrate space station and on-orbit servicing operations including extravehicular (EVA) worksite setup, an orbital replacement unit (ORU) exchange, and various task board experiments. The flight system will be teleoperated from the middeck inside the shuttle as well as from a ground control station at NASA Johnson Space Center. This paper addresses the technical and programmatic status of the flight experiment and describes progress on the engineering test unit, Ranger Neutral Buoyancy Vehicle II (RNBVII), currently in fabrication. Also described are associated technologies, which support this effort. These include a flight robot mockup built to practice EVA stowage and Ranger NBV I, a free-flight prototype vehicle.
Unified Analysis of Periodization-Based Sampling Methods for Matérn Covariances

The periodization of a stationary Gaussian random field on a sufficiently large torus comprising the spatial domain of interest is the basis of various efficient computational methods, such as the classical circulant embedding technique using the fast Fourier transform for generating samples on uniform grids. For the family of Matern covariances with smoothness index $\nu$ and correlation length $\lambda$, we analyse the nonsmooth periodization (corresponding to classical circulant embedding) and an alternative procedure using a smooth truncation of the covariance function. We solve two open problems: the first concerning the $\nu$-dependent asymptotic decay of eigenvalues of the resulting circulant in the nonsmooth case, the second concerning the required size in terms of $\nu$, $\lambda$ of the torus when using a smooth periodization. In doing this we arrive at a complete characterisation of the performance of these two approaches. Both our theoretical estimates and the numerical tests provided here show substantial advantages of smooth truncation.
Targeted Estimation of L2 Distance Between Densities and its Application to Geo-spatial Data

We examine the integrated squared difference, also known as the L2 distance (L2D), between two probability densities. Such a distance metric allows for comparison of differences between pairs of distributions or changes in a distribution over time. We propose a targeted maximum likelihood estimator for this parameter based on samples of independent and identically distributed observations from both underlying distributions. We compare our method to kernel density estimation and demonstrate superior performance for our method with regards to confidence interval coverage rate and mean squared error.
Social Aspects and How They Influence MSECO Developers

Mobile software ecosystem (MSECO) is a new software development paradigm for mobile technologies, having three main dimensions, namely: Technical, Business and Social. The literature has a considerable number of studies on Technical and business dimensions, but only a few studies focus on the social aspects of MSECOs. However, the literature has enough to provide evidence that the actors involved, such as developers, are crucial to an MSECO. This study aims to complement earlies studies by describing new social factors that influence developers to work in a MSECO. We conducted a systematic literature review in order to identify these new factors, and a field study in which 20 developers were interviewed to understand how these factors can influence them to join or keep participating in a MSECO. We found that developer become more rigorous to continue participating then to adopt a MSECO.
Augmenting Transfer Learning with Semantic Reasoning

Transfer learning aims at building robust prediction models by transferring knowledge gained from one problem to another. In the semantic Web, learning tasks are enhanced with semantic representations. We exploit their semantics to augment transfer learning by dealing with when to transfer with semantic measurements and what to transfer with semantic embeddings. We further present a general framework that integrates the above measurements and embeddings with existing transfer learning algorithms for higher performance. It has demonstrated to be robust in two real-world applications: bus delay forecasting and air quality forecasting.
Stereotactic radiosurgery versus stereotactic radiotherapy in the management of intracranial meningiomas: a systematic review and meta-analysis.

OBJECTIVEStereotactic radiosurgery (SRS) and stereotactic radiotherapy (SRT) have been used as a primary treatment or adjuvant to resection in the management of intracranial meningiomas (ICMs). The aim of this analysis is to compare the safety and long-term efficacy of SRS and SRT in patients with primary or recurrent ICMs.METHODSA systematic review of the literature comparing SRT and SRS in the same study was conducted using PubMed, the Cochrane Library, Google Scholar, and EMBASE from January 1980 to December 2018. Randomized controlled trials, case-control studies, and cohort studies (prospective and retrospective) analyzing SRS versus SRT for the treatment of ICMs in adult patients (age > 16 years) were included. Pooled and subgroup analyses were based on the fixed-effect model.RESULTSA total of 1736 patients from 12 retrospective studies were included. The treatment modality used was: 1) SRS (n = 306), including Gamma Knife surgery (n = 36), linear accelerator (n = 261), and CyberKnife (n = 9); or 2) SRT (n = 1430), including hypofractionated SRT (hFSRT, n = 268) and full-fractionated SRT (FSRT, n = 1162). The median age of patients at the time of treatment was 59 years. The median follow-up duration after treatment was 35.5 months. The median tumor volumes at the time of treatment with SRS, hFSRT, and FSRT were 2.84 cm3, 5.45 cm3, and 12.75 cm3, respectively. The radiographic tumor control at last follow-up was significantly worse in patients who underwent SRS than SRT (odds ratio [OR] 0.47, 95% confidence interval [CI] 0.27-0.82, p = 0.007) with 7% less volume of tumor shrinkage (OR 0.93, 95% CI 0.61-1.40, p = 0.72). Compared to SRS, the radiographic tumor control was better achieved by FSRT (OR 0.46, 95% CI 0.26-0.80, p = 0.006) than by hFSRT (OR 0.81, 95% CI 0.21-3.17, p = 0.76). Moreover, SRS leads to a significantly higher risk of clinical neurological worsening during follow-up (OR 2.07, 95% CI 1.06-4.06, p = 0.03) and of immediate symptomatic edema (OR 4.58, 95% CI 1.67-12.56, p = 0.003) with respect to SRT. SRT could produce a better progression-free survival at 4-10 years compared to SRS, but this was not statistically significant (p = 0.29). CONCLUSIONSSRS and SRT are both safe options in the management of ICMs. However, SRT carries a better radiographic tumor control rate and a lower incidence of posttreatment symptomatic worsening and symptomatic edema, with respect to SRS. However, further prospective studies are still needed to validate these results.
Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models

Bottom-Up Hidden Tree Markov Model is a highly expressive model for tree-structured data. Unfortunately, it cannot be used in practice due to the intractable size of its state-transition matrix. We propose a new approximation which lies on the Tucker factorisation of tensors. The probabilistic interpretation of such approximation allows us to define a new probabilistic model for tree-structured data. Hence, we define the new approximated model and we derive its learning algorithm. Then, we empirically assess the effective power of the new model evaluating it on two different tasks. In both cases, our model outperforms the other approximated model known in the literature.
Long-wavelength fluctuations and anomalous dynamics in 2-dimensional liquids

Significance Long-wavelength elastic modes, which have an infinitesimal energy cost, destroy the long-range translational order of 2D solids at finite temperatures. Here we demonstrate that these long-wavelength fluctuations also influence the dynamical properties of 2D systems in their normal liquid regimes. Hence, long-wavelength fluctuations make 2- and 3D molecular particulate systems behave differently from high- to very low-temperature regimes. In 2-dimensional systems at finite temperature, long-wavelength Mermin–Wagner fluctuations prevent the existence of translational long-range order. Their dynamical signature, which is the divergence of the vibrational amplitude with the system size, also affects disordered solids, and it washes out the transient solid-like response generally exhibited by liquids cooled below their melting temperatures. Through a combined numerical and experimental investigation, here we show that long-wavelength fluctuations are also relevant at high temperature, where the liquid dynamics do not reveal a transient solid-like response. In this regime, these fluctuations induce an unusual but ubiquitous decoupling between long-time diffusion coefficient D and structural relaxation time τ, where D∝τ−κ, with κ>1. Long-wavelength fluctuations have a negligible influence on the relaxation dynamics only at extremely high temperatures in molecular liquids or at extremely low densities in colloidal systems.
A Value-based Trust Assessment Model for Multi-agent Systems

An agent's assessment of its trust in another agent is commonly taken to be a measure of the reliability/predictability of the latter's actions. It is based on the trustor's past observations of the behaviour of the trustee and requires no knowledge of the inner-workings of the trustee. However, in situations that are new or unfamiliar, past observations are of little help in assessing trust. In such cases, knowledge about the trustee can help. A particular type of knowledge is that of values - things that are important to the trustor and the trustee. In this paper, based on the premise that the more values two agents share, the more they should trust one another, we propose a simple approach to trust assessment between agents based on values, taking into account if agents trust cautiously or boldly, and if they depend on others in carrying out a task.
MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

We introduce a large-scale dataset of math word problems and an interpretable neural math problem solver by learning to map problems to their operation programs. Due to annotation challenges, current datasets in this domain have been either relatively small in scale or did not offer precise operational annotations over diverse problem types. We introduce a new representation language to model operation programs corresponding to each math problem that aim to improve both the performance and the interpretability of the learned models. Using this representation language, we significantly enhance the AQUA-RAT dataset with fully-specified operational programs. We additionally introduce a neural sequence-to-program model with automatic problem categorization. Our experiments show improvements over competitive baselines in our dataset as well as the AQUA-RAT dataset. The results are still lower than human performance indicating that the dataset poses new challenges for future research. Our dataset is available at https://math-qa.github. io/math-QA/
Rapid and regulated degradation of ornithine decarboxylase.

Ornithine decarboxylase (ODC; EC 4.1.1.17), the first and key enzyme in polyamine biosynthesis (Figure 1), turns over extremely rapidly and is one of the most highly regulated enzymes known [1-3]. It is induced by many kinds of growth stimuli, and its suppression by specific inhibitors or mutation inhibits cellular growth and transformation [4,5]. A recent study showed that overexpression of ODC caused cellular transformation, suggesting that ODC should be regarded as a proto-oncogene product [6]. ODC is also induced by other types of stimuli, such
On Policy Evaluation with Aggregate Time-Series Shocks

We propose a general strategy for estimating treatment effects, in contexts where the only source of exogenous variation is a sequence of aggregate time-series shocks. We start by arguing that commonly used estimation procedures tend to ignore the crucial time-series aspects of the data. Next, we develop a graphical tool and a novel test to illustrate the issues of the design using data from influential studies in development economics [Nunn and Qian, 2014] and macroeconomics [Nakamura and Steinsson, 2014]. Motivated by these studies, we construct a new estimator, which is based on the time-series model for the aggregate shock. We analyze the statistical properties of our estimator in the practically relevant case, where both cross-sectional and time-series dimensions are of similar size. Finally, to provide causal interpretation for our estimator, we analyze a new causal model that allows taking into account both rich unobserved heterogeneity in potential outcomes and unobserved aggregate shocks.
Tunneling Anisotropic Magnetoresistance in Ferroelectric Tunnel Junctions

Using a simple quantum-mechanical model, we explore a tunneling anisotropic magnetoresistance (TAMR) effect in ferroelectric tunnel junctions (FTJs) with a ferromagnetic electrode and a ferroelectric barrier layer, which spontaneous polarization gives rise to the Rashba and Dresselhaus spin-orbit coupling (SOC). For realistic parameters of the model, we predict sizable TAMR measurable experimentally. For asymmetric FTJs, which electrodes have different work functions, the built-in electric field affects the SOC parameters and leads to TAMR dependent on ferroelectric polarization direction. The SOC change with polarization switching affects tunneling conductance, revealing a new mechanism of tunneling electroresistance (TER). These results demonstrate new functionalities of FTJs which can be explored experimentally and used in electronic devices.
Effect of driving on coarsening dynamics in phase-separating systems

We consider the Cahn–Hilliard (CH) equation with a Burgers-type convective term that is used as a model of coarsening dynamics in laterally driven phase-separating systems. In the absence of driving, it is known that solutions to the standard CH equation are characterized by an initial stage of phase separation into regions of one phase surrounded by the other phase (i.e. clusters or drops/holes or islands are obtained) followed by the coarsening process, where the average size of the structures grows in time and their number decreases. Moreover, two main coarsening modes have been identified in the literature, namely, coarsening due to volume transfer and due to translation. In the opposite limit of strong driving, the well-known Kuramoto–Sivashinsky equation is recovered, which may produce complicated chaotic spatio-temporal oscillations. The primary aim of the present work is to perform a detailed and systematic investigation of the transitions in the solutions of the convective CH equation for a wide range of parameter values, and, in particular, to understand in detail how the coarsening dynamics is affected by an increase of the strength of the lateral driving force. Considering symmetric two-drop states, we find that one of the coarsening modes is stabilized at relatively weak driving, and the type of the remaining mode may change as driving increases. Furthermore, there exist intervals in the driving strength where coarsening is completely stabilized. In the intervals where the symmetric two-drop states are unstable they can evolve, for example, into one-drop states, two-drop states of broken symmetry or even time-periodic two-drop states that consist of two traveling drops that periodically exchange mass. We present detailed stability diagrams for symmetric two-drop states in various parameter planes and corroborate our findings by selected time simulations.
Octamer transcription factors 1 and 2 each bind to two different functional elements in the immunoglobulin heavy-chain promoter

Immunoglobulin heavy-chain genes contain two conserved sequence elements 5' to the site of transcription initiation: the octamer ATGCAAAT and the heptamer CTCATGA. Both of these elements are required for normal cell-specific promoter function. The present study demonstrates that both the ubiquitous and lymphoid-cell-specific octamer transcription factors (OTF-1 and OTF-2, respectively) interact specifically with each of the two conserved sequence elements, forming either homo- or heterodimeric complexes. This was surprising, since the heptamer and octamer sequence motifs bear no obvious similarity to each other. Binding of either factor to the octamer element occurred independently. However, OTF interaction with the heptamer sequence appeared to require the presence of an intact octamer motif and occurred with a spacing of either 2 or 14 base pairs between the two elements, suggesting coordinate binding resulting from protein-protein interactions. The degeneracy in sequences recognized by the OTFs may be important in widening the range over which gene expression can be modulated and in establishing cell type specificity.
An all‐atom solution‐equilibrated model for human extrinsic blood coagulation complex (sTF–VIIa–Xa): a protein–protein docking and molecular dynamics refinement study

Summary. Tissue factor (TF)‐bound factor (F)VIIa plays a critical role in activating FX, an event that rapidly results in blood coagulation. Despite recent advances in the structural information about soluble TF (sTF)‐bound VIIa and Xa individually, the atomic details of the ternary complex are not known. As part of our long‐term goal to provide a structural understanding of the extrinsic blood coagulation pathway, we built an all atom solution‐equilibrated model of the human sTF–VIIa–Xa ternary complex using protein–protein docking and molecular dynamics (MD) simulations. The starting structural coordinates of sTF–VIIa and Xa were derived from dynamically equilibrated solution structures. Due to the flexible nature of the light‐chain of the Xa molecule, a three‐stage docking approach was employed in which SP (Arg195‐Lys448)/EGF2 (Arg86‐Arg139), EGF1 (Asp46‐Thr85) and GLA (Ala1‐Lys45) domains were docked in a sequential manner. The rigid‐body docking approach of the FTDOCK method in conjunction with filtering based on biochemical knowledge from experimental site‐specific mutagenesis studies provided the strategy. The best complex obtained from the docking experiments was further refined using MD simulations for 3 ns in explicit water. In addition to explaining most of the known experimental site‐specific mutagenesis data pertaining to sTF–VIIa, our model also characterizes likely enzyme‐binding exosites on FVIIa and Xa that may be involved in the ternary complex formation. According to the equilibrated model, the 140s loop of VIIa serves as the key recognition motif for complex formation. Stable interactions occur between the FVIIa 140s loop and the FXa β‐strand B2 region near the sodium‐binding domain, the 160 s loop and the N‐terminal activation loop regions. The helical‐hydrophobic stack region that connects the GLA and EGF1 domains of VIIa and Xa appears to play a potential role in the membrane binding region of the ternary complex. The proposed model may serve as a reasonable structural basis for understanding the exosite‐mediated substrate recognition of sTF–VIIa and to advance understanding of the TFPI‐mediated regulatory pathway of the extrinsic blood coagulation cascade.