Miracle-dz/UniFAR-FTUs huggingface dataset:
Team VALOR's ESCHER: A Novel Electromechanical Biped for the DARPA Robotics Challenge

The Electric Series Compliant Humanoid for Emergency Response (ESCHER) platform represents the culmination of four years of development at Virginia Tech to produce a full‐sized force‐controlled humanoid robot capable of operating in unstructured environments. ESCHER's locomotion capability was demonstrated at the DARPA Robotics Challenge (DRC) Finals when it successfully navigated the 61 m loose dirt course. Team VALOR, a Track A team, developed ESCHER leveraging and improving upon bipedal humanoid technologies implemented in previous research efforts, specifically for traversing uneven terrain and sustained untethered operation. This paper presents the hardware platform, software, and control systems developed to field ESCHER at the DRC Finals. ESCHER's unique features include custom linear series elastic actuators in both single and dual actuator configurations and a whole‐body control framework supporting compliant locomotion across variable and shifting terrain. A high‐level software system designed using the robot operating system integrated various open‐source packages and interfaced with the existing whole‐body motion controller. The paper discusses a detailed analysis of challenges encountered during the competition, along with lessons learned that are critical for transitioning research contributions to a fielded robot. Empirical data collected before, during, and after the DRC Finals validate ESCHER's performance in fielded environments.
Active learning-based classifier personalization: A case of on-body device localization

In activity recognition, the number of target classes and classification accuracy are insufficient for practical application because accuracy declines in real situations. To address this problem, we consider that acquiring personal data is effective. We propose an active learning system for the accuracy problem and discuss an effective classifier and method to select appropriate data. We demonstrate that a Random Forest classifier using a Least Confident active learning method increases the F-measure the fastest in the combination of classifiers (Naïve Bayes, Support Vector Machine, and Random Forest) and active learning methods (Least Confident, Margin Sampling, and Entropy).
Reduced ATE Interface for High Test Data Compression

This paper presents a study addressing the challenge of interfacing automatic test equipment (ATE) with on-chip decompression logic deployed by system-on-chip designs or modular decompression environments. The ability of the proposed scheme to improve the encoding bandwidth by reusing groups of scan chains for test data storage has been measured on industrial designs and is reported herein.
Learning graphical models from the Glauber dynamics

In this paper we consider the problem of learning undirected graphical models from data generated according to the Glauber dynamics. The Glauber dynamics is a Markov chain that sequentially updates individual nodes (variables) in a graphical model and it is frequently used to sample from the stationary distribution (to which it converges given sufficient time). Additionally, the Glauber dynamics is a natural dynamical model in a variety of settings. This work deviates from the standard formulation of graphical model learning in the literature, where one assumes access to i.i. d. samples from the distribution. Much of the research on graphical model learning has been directed towards finding algorithms with low computational cost. As the main result of this work, we establish that the problem of reconstructing binary pairwise graphical models is computationally tractable when we observe the Glauber dynamics. Specifically, we show that a binary pairwise graphical model on p nodes with maximum degree d can be learned in time f(d)p3 log p, for a function f(d), using nearly the information-theoretic minimum possible number of samples. There is no known algorithm of comparable efficiency for learning arbitrary binary pairwise models from i.i. d. samples.
Inferring Recent Demography from Isolation by Distance of Long Shared Sequence Blocks

Recently it has become feasible to detect long blocks of nearly identical sequence shared between pairs of genomes. These identity-by-descent (IBD) blocks are direct traces of recent coalescence events and, as such, contain ample signal to infer recent demography. Here, we examine sharing of such blocks in two-dimensional populations with local migration. Using a diffusion approximation to trace genetic ancestry, we derive analytical formulas for patterns of isolation by distance of IBD blocks, which can also incorporate recent population density changes. We introduce an inference scheme that uses a composite-likelihood approach to fit these formulas. We then extensively evaluate our theory and inference method on a range of scenarios using simulated data. We first validate the diffusion approximation by showing that the theoretical results closely match the simulated block-sharing patterns. We then demonstrate that our inference scheme can accurately and robustly infer dispersal rate and effective density, as well as bounds on recent dynamics of population density. To demonstrate an application, we use our estimation scheme to explore the fit of a diffusion model to Eastern European samples in the Population Reference Sample data set. We show that ancestry diffusing with a rate of σ≈50−−100 km/gen during the last centuries, combined with accelerating population growth, can explain the observed exponential decay of block sharing with increasing pairwise sample distance.
T lymphocyte reactivity to glutamic acid-alanine-tyrosine in vitro does not reflect antibody response in vivo.

Mechanisms responsible for the differences in humoral immune response to GAT (a random linear amino acid polymer) were investigated in a line of chickens consisting of four sublines homozygous for Ea-B (B1 or B19) and high or low antibody response to GAT (Ir-GATH or Ir-GATL). Previous research provided evidence of chromosomal recombination between the serologically determined regions of the MHC (encoded by B-F and B-G genes) and the gene or genes that control immune response to GAT, but immune response to GAT did not seem to be mediated through differences in B-L gene products. In the present study, proliferation of GAT-primed T lymphocytes indicated that reactivity in vitro was not associated with antibody levels produced in the animal. Cell surface markers were identified by flow cytometry. Lymphocytes from Ea-B19 chickens that were Ir-GATL had a higher percentage of suppressor T (CD8)-positive cells than did lymphocytes from Ir-GATH chickens. The Ea-B1 chickens that were Ir-GATL had a higher percentage of CD4-positive lymphocytes than did chickens that were Ir-GATH. This may indicate that low response to GAT in the Ea-B19 chickens, but not in Ea-B1 chickens, is mediated by CD8-positive cells. The ability of antigen-presenting cells (APC) to process and present GAT to antigen-primed T lymphocytes was tested in vitro. Measurements of lymphocyte proliferation indicated that, within the Ea-B1 blood type, APC from Ir-GATL chickens produced higher (P < .05) stimulation of both GAT low- and GAT high-responder lymphocytes. (ABSTRACT TRUNCATED AT 250 WORDS)
Progress on utilizing hyperthermia for mitigating bacterial infections

Abstract Recovery from systemic or local bacterial infections can be lengthy and costly, with the clinical challenges being further complicated when bacteria acquire resistance to current antibiotics. Hyperthermia offers new mechanisms for removing bacteria via ablation, or sensitising them to chemical agents. The first part of this review provides a background on the bacterial biofilms, their response to hyperthermia, and acquired resistance to antibiotics, followed by the clinical challenges they present in managing infections associated with soft tissues and biomedical implants. The second part of the review discusses the thermal modalities used to combat infections, including radiofrequency, ultrasound, high-intensity focussed ultrasound, microwave thermotherapy, and photothermal and magnetic nanoparticles (NP). The overall aim of this review is to demonstrate the tremendous potential of hyperthermia for mitigating bacterial infections and foster new research ventures to help remedy these challenging occurrences.
Hot corrosion behavior of Cr-modified NiAl coatings on 310 stainless steel produced by a gas tungsten arc cladding process

The microstructure and hot corrosion behavior of Ni/Al–Cr composite claddings produced by gas tungsten arc welding (GTAW) on a 310 stainless steel substrate were studied. The phase analyses and the microstructure of the cladding layers were evaluated using optical microscopy, X-ray diffraction (XRD) and scanning electron microscopy. The influence of Cr addition (0, 5, 10 at% Cr) on the microstructure and hot corrosion behavior of the NiAl coatings was assessed. The cyclic hot corrosion behavior of the base metal and different claddings was investigated at 900°C and in static air, with a 2–3 mg/cm2 Na2SO4–10%NaCl (wt%). It was found that a dendritic microstructure was formed on the clad surfaces. The results of the XRD analyses indicated that a NiAl phase was synthesized in situ during GTAW cladding and the presence of Cr reduced the intensity of diffraction peaks of NiAl. Hot corrosion experiments also revealed that the addition of Cr had a crucial influence on the hot corrosion behavior of NiAl coatings. It was found that the larger the amount of Cr, the superior the resistance of the coatings to hot corrosion. This improvement was attributed to the formation of Al2O3 as a protective oxide layer, as evidenced by XRD patterns. However, the iron containing phases produced as a result of interactions with the substrate were found to be a detrimental factor influencing the corrosion properties of different cladded layers.
Comparative Efficacy of Selected Dust Insecticides for Controlling Cimex lectularius (Hemiptera: Cimicidae)

Abstract Bed bugs, Cimex lectularius L. , are one of the most difficult urban pests to control. Pest management professionals rely heavily on insecticide sprays and dusts to control bed bugs. Dust formulations are considered to provide longer residual control than sprays. However, there are no scientific data available on the comparative efficacy of the commonly used insecticide dusts. We evaluated the efficacy of eight insecticide dust products using three exposure methods: 1) brief exposure—bed bugs crossed a 2.54-cm-wide dust-treated band, 2) forced exposure—bed bugs were continuously exposed to a dust-treated substrate, and 3) choice exposure—bed bugs were given a choice to stay on either dust-treated or untreated substrate. The brief exposure method was the most sensitive in detecting the differences among the insecticides. Only CimeXa (silica gel) dust caused 100% mortality from all three exposure methods. Other tested dusts (1% cyfluthrin, 0.05% deltamethrin, 0.075% zeta-cypermethrin + 0.15% piperonyl butoxide, 1% pyrethrins, 1% 2-phenethyl propionate + 0.4% pyrethrin, 0.25% dinotefuran + 95% diatomaceous earth, 100% diatomaceous earth) caused ≤65% mortality in a brief exposure assay. We also evaluated the horizontal transfer effect of the silica gel dust. Silica gel dust-exposed bed bugs transferred the dust horizontally to unexposed bed bugs resulting in 100% mortality at 4:6 donor: recipient ratio and 88.0 ± 5.0% mortality at 1:5 donor: recipient ratio. The results suggest silica gel is the most promising insecticide dust for controlling C. lectularius.
Some remarks on the fractional Sumudu transform and applications

In this work we study fractional order Sumudu transform. In the development of the definition we use fractional analysis based on the modified Riemann - Liouville derivative, then we name the fra ctional Sumudu transform. We also establish a relationship between fractional Laplace and Sumudu via duality with complex inversion formula for fractional Sumudu transform and apply new definition to solve fractional differential equations.
Scaling-up Split-Merge MCMC with Locality Sensitive Sampling (LSS)

Split-Merge MCMC (Monte Carlo Markov Chain) is one of the essential and popular variants of MCMC for problems when an MCMC state consists of an unknown number of components. It is well known that state-of-the-art methods for split-merge MCMC do not scale well. Strategies for rapid mixing requires smart and informative proposals to reduce the rejection rate. However, all known smart proposals involve expensive operations to suggest informative transitions. As a result, the cost of each iteration is prohibitive for massive scale datasets. It is further known that uninformative but computationally efficient proposals, such as random split-merge, leads to extremely slow convergence. This tradeoff between mixing time and per update cost seems hard to get around.We leverage some unique properties of weighted MinHash, which is a popular LSH, to design a novel class of split-merge proposals which are significantly more informative than random sampling but at the same time efficient to compute. Overall, we obtain a superior tradeoff between convergence and per update cost. As a direct consequence, our proposals are around 6X faster than the state-of-the-art sampling methods on two large real datasets KDDCUP and PubMed with several millions of entities and thousands of clusters.
Expertise in Online Markets

We examine the effect of the presence of knowledgeable buyers (experts) in online markets where auctions with a hard close and posted prices are widely used. We model buyer expertise as the ability to accurately predict the quality, or condition, of an item. In auctions with a hard close, sniping – submitting bids in the last minute – emerges as an equilibrium strategy for experts. We show that non-experts bid more aggressively as the proportion of experts increases. As a consequence, we establish that the auction platform may obtain a higher revenue by (i) enforcing a hard close and allowing sniping, and (ii) withholding information regarding the quality of the item. Moreover, in online markets where both auctions and posted prices are available, we show that the presence of experts allows the sellers of high quality items to signal their quality by choosing to sell via auctions.
Impact of Potential Barriers at Grain Boundaries of Multi Crystalline Silicon Wafers on Inductively Coupled Resistivity Measurements

Base resistance and emitter sheet resistance are two of the most important process control parameters in solar cell manufacturing, which may be measured inductively. On mono-crystalline silicon, measurement accuracy of this contactless inline technique has already been demonstrated. In this work the investigation of measurement accuracy is extended to multi-crystalline silicon (mc-Si) and reveals for base resistance measurements severe measurement artifacts of up to a factor 2 upon chemical standard treatments, such as damage etching and acidic texturization. The investigation identifies potential barriers at grain boundaries as reason for these artifacts which form upon chemical treatments and further increase with storage time after such chemical steps. It is found that these potential barriers vanish almost completely after thermal treatments, such as a standard emitter diffusion. As a consequence, the emitter sheet resistance calculated from the inductive sheet resistances before and after emitter diffusion may be significantly underestimated if the presumed base resistance is overestimated. Taking into account that mc-Si wafers are almost not affected by potential barriers in the as-cut state, we develop a patented procedure which allows reliable emitter sheet resistance measurements in mc-Si wafers irrespective of the presence of potential barriers before diffusion.
Effects of Different Temperatures on the Development of Dermestes Frischii and Dermestes Undulatus (Coleoptera, Dermestidae): Comparison Between Species

Dermestidae could be useful in forensic investigations to assess the PMI as adults and larvae colonize dried remains. We reared two species of Dermestidae (Dermestes frischii and Dermestes undulatus) to understand the effects of different temperatures on the length of their whole life cycle and on their immature stages. Both species were reared at 23°C ± 0.5, RH 75% and at 26°C ± 0.5, 75% RH. Our result shows that the temperature is the main factor that influences the development of those species; in fact, increasing temperature leads to a shorter development cycle (59.8 ± 0.5 and 38.1 ± 0.2 for D. frischii; 50.6 ± 0.6 and 36.2 ± 0.2 for D. undulatus). Furthermore, we found that the number of the molts before the pupa decreases from 5–7 to 5–6 for D. frischii and from 4–6 to 4–5 for D. undulatus, respectively, at 23°C and 26°C.
Landscape heterogeneity reduces coyote predation on white-tailed deer fawns

Coyote (Canis latrans) predation on white-tailed deer (Odocoileus virginianus) fawns in southeastern North America has led to deer population declines in some areas. Research or management efforts initiated in response to coyote predation on fawns have primarily focused on implementation of reduced antlerless deer harvest or coyote control to mitigate population declines. Vegetation characteristics may influence coyote hunting efficiency, but the potential influence of land cover at large scales in the southeastern United States is underexplored. We investigated whether mortality risk was affected by landscape characteristics within fawn home ranges for a sample of 165 fawns on the United States Department of Energy's Savannah River Site (SRS), South Carolina, 2007–2012. We monitored fawns every 8 hours to ≥4 weeks of age and 1–3 times daily to 12 weeks of age. We included only surviving or coyote-predated fawns in the dataset. The most supported model describing hazard ratios included the length of edge (i.e., area where 2 land cover types joined) in fawn home ranges. Probability of coyote predation increased 1.26 times for each 968-m decrease in edge within a fawn's simulated home range (29.1-ha circular buffer) under this model. Further, fawns with the least edge in their home ranges were >2 times more likely to be depredated by a coyote than fawns with the greatest edge availability. Support for other models was relatively low, but informative variables (e.g., mean patch fractal dimension, Shannon's diversity index, mean forest patch size) supported a general trend that as fawn home ranges became more homogeneous and contained larger patches with less edge and fewer cover types, predation risk increased. These findings are consistent with similar work in the midwestern United States, despite landscape differences between regions. The combined weight of evidence suggests maintenance of a heterogeneous landscape consisting of relatively small dispersed patches may reduce fawn losses to coyotes. This information may also be used to identify areas susceptible to greater fawn predation rates across large spatial scales. However, the relatively long forestry rotation lengths and large scale of consistent forest management on the SRS are uncommon in the southeastern United States and the mechanism for the pattern we observed is unclear. Therefore, our results may not be applicable to sites with different forest management practices. © 2017 The Wildlife Society.
Effects of High-Intensity Interval Exercise versus Moderate Continuous Exercise on Glucose Homeostasis and Hormone Response in Patients with Type 1 Diabetes Mellitus Using Novel Ultra-Long-Acting Insulin

Introduction We investigated blood glucose (BG) and hormone response to aerobic high-intensity interval exercise (HIIE) and moderate continuous exercise (CON) matched for mean load and duration in type 1 diabetes mellitus (T1DM). Material and Methods Seven trained male subjects with T1DM performed a maximal incremental exercise test and HIIE and CON at 3 different mean intensities below (A) and above (B) the first lactate turn point and below the second lactate turn point (C) on a cycle ergometer. Subjects were adjusted to ultra-long-acting insulin Degludec (Tresiba/ Novo Nordisk, Denmark). Before exercise, standardized meals were administered, and short-acting insulin dose was reduced by 25% (A), 50% (B), and 75% (C) dependent on mean exercise intensity. During exercise, BG, adrenaline, noradrenaline, dopamine, cortisol, glucagon, and insulin-like growth factor-1, blood lactate, heart rate, and gas exchange variables were measured. For 24 h after exercise, interstitial glucose was measured by continuous glucose monitoring system. Results BG decrease during HIIE was significantly smaller for B (p = 0.024) and tended to be smaller for A and C compared to CON. No differences were found for post-exercise interstitial glucose, acute hormone response, and carbohydrate utilization between HIIE and CON for A, B, and C. In HIIE, blood lactate for A (p = 0.006) and B (p = 0.004) and respiratory exchange ratio for A (p = 0.003) and B (p = 0.003) were significantly higher compared to CON but not for C. Conclusion Hypoglycemia did not occur during or after HIIE and CON when using ultra-long-acting insulin and applying our methodological approach for exercise prescription. HIIE led to a smaller BG decrease compared to CON, although both exercises modes were matched for mean load and duration, even despite markedly higher peak workloads applied in HIIE. Therefore, HIIE and CON could be safely performed in T1DM. Trial Registration ClinicalTrials.gov NCT02075567 http://www.clinicaltrials. gov/ct2/show/NCT02075567
DLocalMotif: a discriminative approach for discovering local motifs in protein sequences

MOTIVATION Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery. RESULTS This article introduces the method DLocalMotif that makes use of positional information and negative data for local motif discovery in protein sequences. DLocalMotif combines three scoring functions, measuring degrees of motif over-representation, entropy and spatial confinement, specifically designed to discriminatively exploit the availability of negative data. The method is shown to outperform current methods that use only a subset of these motif characteristics. We apply the method to several biological datasets. The analysis of peroxisomal targeting signals uncovers several novel motifs that occur immediately upstream of the dominant peroxisomal targeting signal-1 signal. The analysis of proline-tyrosine nuclear localization signals uncovers multiple novel motifs that overlap with C2H2 zinc finger domains. We also evaluate the method on classical nuclear localization signals and endoplasmic reticulum retention signals and find that DLocalMotif successfully recovers biologically relevant sequence properties. AVAILABILITY http://bioinf.scmb. uq.edu. au/dlocalmotif/