Miracle-dz/UniFAR-FTUs huggingface dataset:
Engineering Efficient p‐Type TMD/Metal Contacts Using Fluorographene as a Buffer Layer

P‐type transistors based on high work function transition metal dichalcogenide (TMD) monolayers such as MoS2 are to date difficult to produce, owing to the strong Fermi level pinning at the semiconductor/contact metal interfaces. In this work, the potential of halogenated graphenes is demonstrated as a new class of efficient hole injection layers to TMDs such as MoS2 and WSe2 by taking fluorographene (or GF) as a model buffer layer. Using first‐principles computations, two commonly obtained GF stoichiometries, C2F and CF, have been studied as buffer layers between MoS2 and Pt. In particular, for high work function TMDs such as MoS2, it has been shown that C2F forms an ohmic contact, while CF leads to a significant p‐SBH value. On the other hand, for low work function TMDs such as WSe2, both C2F and CF lead to p‐type ohmic contacts. This analysis shows that the ability of these buffer layers to form p‐type contacts depends crucially on the charge redistribution at the GF/metal interface, which is dictated by their chemical interaction and equilibrium geometry. The fundamental electronic structures between the different semiconductor/insulator/metal interfaces which are part of this study have also been investigated.
High-Throughput All-Optical Analysis of Synaptic Transmission and Synaptic Vesicle Recycling in Caenorhabditis elegans

Synaptic vesicles (SVs) undergo a cycle of biogenesis and membrane fusion to release transmitter, followed by recycling. How exocytosis and endocytosis are coupled is intensively investigated. We describe an all-optical method for identification of neurotransmission genes that can directly distinguish SV recycling factors in C. elegans, by motoneuron photostimulation and muscular RCaMP Ca2+ imaging. We verified our approach on mutants affecting synaptic transmission. Mutation of genes affecting SV recycling (unc-26 synaptojanin, unc-41 stonin, unc-57 endophilin, itsn-1 intersectin, snt-1 synaptotagmin) showed a distinct ‘signature’ of muscle Ca2+ dynamics, induced by cholinergic motoneuron photostimulation, i.e. faster rise, and earlier decrease of the signal, reflecting increased synaptic fatigue during ongoing photostimulation. To facilitate high throughput, we measured (3–5 times) ~1000 nematodes for each gene. We explored if this method enables RNAi screening for SV recycling genes. Previous screens for synaptic function genes, based on behavioral or pharmacological assays, allowed no distinction of the stage of the SV cycle in which a protein might act. We generated a strain enabling RNAi specifically only in cholinergic neurons, thus resulting in healthier animals and avoiding lethal phenotypes resulting from knockdown elsewhere. RNAi of control genes resulted in Ca2+ measurements that were consistent with results obtained in the respective genomic mutants, albeit to a weaker extent in most cases, and could further be confirmed by opto-electrophysiological measurements for mutants of some of the genes, including synaptojanin. We screened 95 genes that were previously implicated in cholinergic transmission, and several controls. We identified genes that clustered together with known SV recycling genes, exhibiting a similar signature of their Ca2+ dynamics. Five of these genes (C27B7.7, erp-1, inx-8, inx-10, spp-10) were further assessed in respective genomic mutants; however, while all showed electrophysiological phenotypes indicative of reduced cholinergic transmission, no obvious SV recycling phenotypes could be uncovered for these genes.
Estimation of Antenna Pose in the Earth Frame Using Camera and IMU Data from Mobile Phones

The poses of base station antennas play an important role in cellular network optimization. Existing methods of pose estimation are based on physical measurements performed either by tower climbers or using additional sensors attached to antennas. In this paper, we present a novel non-contact method of antenna pose measurement based on multi-view images of the antenna and inertial measurement unit (IMU) data captured by a mobile phone. Given a known 3D model of the antenna, we first estimate the antenna pose relative to the phone camera from the multi-view images and then employ the corresponding IMU data to transform the pose from the camera coordinate frame into the Earth coordinate frame. To enhance the resulting accuracy, we improve existing camera-IMU calibration models by introducing additional degrees of freedom between the IMU sensors and defining a new error metric based on both the downtilt and azimuth angles, instead of a unified rotational error metric, to refine the calibration. In comparison with existing camera-IMU calibration methods, our method achieves an improvement in azimuth accuracy of approximately 1.0 degree on average while maintaining the same level of downtilt accuracy. For the pose estimation in the camera coordinate frame, we propose an automatic method of initializing the optimization solver and generating bounding constraints on the resulting pose to achieve better accuracy. With this initialization, state-of-the-art visual pose estimation methods yield satisfactory results in more than 75% of cases when plugged into our pipeline, and our solution, which takes advantage of the constraints, achieves even lower estimation errors on the downtilt and azimuth angles, both on average (0.13 and 0.3 degrees lower, respectively) and in the worst case (0.15 and 7.3 degrees lower, respectively), according to an evaluation conducted on a dataset consisting of 65 groups of data. We show that both of our enhancements contribute to the performance improvement offered by the proposed estimation pipeline, which achieves downtilt and azimuth accuracies of respectively 0.47 and 5.6 degrees on average and 1.38 and 12.0 degrees in the worst case, thereby satisfying the accuracy requirements for network optimization in the telecommunication industry.
Adenosine‐to‐inosine RNA editing

Ribonucleic acid (RNA) editing is a mechanism that generates RNA and protein diversity, which is not directly encoded in the genome. The most common type of RNA editing in vertebrates is the conversion of adenosine to inosine in double‐stranded RNA which occurs in the higher eukaryotes. This editing is carried out by the family of adenosine deaminase acting on RNA (ADAR) proteins. The most‐studied substrates of ADAR proteins undergo editing which is very consistent, highly conserved, and functionally important. However, editing causes changes in protein‐coding regions only at a small proportion of all editing sites. The vast majority of editing sites are in noncoding sequences. This includes microRNAs, as well as the introns and 3′ untranslated regions of messenger RNAs, which play important roles in the RNA‐mediated regulation of gene expression. Copyright © 2009 John Wiley & Sons, Inc.
Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points

We propose a method for human activity recognition from RGB data that does not rely on any pose information during test time, and does not explicitly calculate pose information internally. Instead, a visual attention module learns to predict glimpse sequences in each frame. These glimpses correspond to interest points in the scene that are relevant to the classified activities. No spatial coherence is forced on the glimpse locations, which gives the attention module liberty to explore different points at each frame and better optimize the process of scrutinizing visual information. Tracking and sequentially integrating this kind of unstructured data is a challenge, which we address by separating the set of glimpses from a set of recurrent tracking/recognition workers. These workers receive glimpses, jointly performing subsequent motion tracking and activity prediction. The glimpses are soft-assigned to the workers, optimizing coherence of the assignments in space, time and feature space using an external memory module. No hard decisions are taken, i.e. each glimpse point is assigned to all existing workers, albeit with different importance. Our methods outperform the state-of-the-art on the largest human activity recognition dataset available to-date, NTU RGB+D, and on the Northwestern-UCLA Multiview Action 3D Dataset.
Recent Trends on Electrochemical Sensors Based on Ordered Mesoporous Carbon

The past decade has seen an increasing number of extensive studies devoted to the exploitation of ordered mesoporous carbon (OMC) materials in electrochemistry, notably in the fields of energy and sensing. The present review summarizes the recent achievements made in field of electroanalysis using electrodes modified with such nanomaterials. On the basis of comprehensive tables, the interest in OMC for designing electrochemical sensors is illustrated through the various applications developed to date. They include voltammetric detection after preconcentration, electrocatalysis (intrinsically due to OMC or based on suitable catalysts deposited onto OMC), electrochemical biosensors, as well as electrochemiluminescence and potentiometric sensors.
In pursuit of change: Conceptualizing the social work response to LGBTQ microaggressions in health settings

ABSTRACT Despite the emergence of research on microaggressions targeting lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) communities in recent years, there remains an insufficiency of theoretical literature in this area. In this article, we draw on the works of Michel Foucault to conceptualize the effects of microaggressive practices on LGBTQ people accessing health and other social services, and generate insight into strategies these groups use to resist these effects. We emphasize the need for social workers, particularly those in health care settings, to support these communities’ ongoing attempts at challenging the effects of microaggression, and to this end, outline several implications of our analysis for social work practice.
Can chronic stretching change the muscle‐tendon mechanical properties? A review

It is recognized that stretching is an effective method to chronically increase the joint range of motion. However, the effects of stretching training on the muscle‐tendon structural properties remain unclear. This systematic review with meta‐analysis aimed to determine whether chronic stretching alter the muscle‐tendon structural properties. Published papers regarding longitudinal stretching (static, dynamic and/or PNF) intervention (either randomized or not) in humans of any age and health status, with more than 2 weeks in duration and at least 2 sessions per week, were searched in PubMed, PEDro, ScienceDirect and ResearchGate databases. Structural or mechanical variables from joint (maximal tolerated passive torque or resistance to stretch) or muscle‐tendon unit (muscle architecture, stiffness, extensibility, shear modulus, volume, thickness, cross‐sectional area, and slack length) were extracted from those papers. A total of 26 studies were selected, with a duration ranging from 3 to 8 weeks, and an average total time under stretching of 1165 seconds per week. Small effects were seen for maximal tolerated passive torque, but trivial effects were seen for joint resistance to stretch, muscle architecture, muscle stiffness, and tendon stiffness. A large heterogeneity was seen for most of the variables. Stretching interventions with 3‐ to 8‐week duration do not seem to change either the muscle or the tendon properties, although it increases the extensibility and tolerance to a greater tensile force. Adaptations to chronic stretching protocols shorter than 8 weeks seem to mostly occur at a sensory level.
Management of Failed Biceps Tenodesis or Tenotomy: Causation and Treatment

The purpose of this paper is to review the management of long head biceps tendon pathology, with a particular emphasis on a prior failed biceps tenotomy or tenodesis. Failed biceps tenotomy generally results from a lack of thorough preoperative discussion of potential outcomes rather than from technical problems. Patients with unsatisfactory results can be treated with conversion to a biceps tenodesis. Failed biceps tenodesis is usually recognized with persistent pain in the area of the bicipital groove, often caused by either the mechanical failure of the tenodesis or associated shoulder pathology that is not addressed at the time of the primary surgery. Operative treatment options include revision tenodesis or biceps tenotomy. The subpectoral approach provides excellent versatility and ability to meet technical objectives when performing revision tenodesis, by removing the tendon completely from the groove and preserving biceps function.
Functional Structure of Biological Communities Predicts Ecosystem Multifunctionality

The accelerating rate of change in biodiversity patterns, mediated by ever increasing human pressures and global warming, demands a better understanding of the relationship between the structure of biological communities and ecosystem functioning (BEF). Recent investigations suggest that the functional structure of communities, i.e. the composition and diversity of functional traits, is the main driver of ecological processes. However, the predictive power of BEF research is still low, the integration of all components of functional community structure as predictors is still lacking, and the multifunctionality of ecosystems (i.e. rates of multiple processes) must be considered. Here, using a multiple-processes framework from grassland biodiversity experiments, we show that functional identity of species and functional divergence among species, rather than species diversity per se, together promote the level of ecosystem multifunctionality with a predictive power of 80%. Our results suggest that primary productivity and decomposition rates, two key ecosystem processes upon which the global carbon cycle depends, are primarily sustained by specialist species, i.e. those that hold specialized combinations of traits and perform particular functions. Contrary to studies focusing on single ecosystem functions and considering species richness as the sole measure of biodiversity, we found a linear and non-saturating effect of the functional structure of communities on ecosystem multifunctionality. Thus, sustaining multiple ecological processes would require focusing on trait dominance and on the degree of community specialization, even in species-rich assemblages.
Crystallization and melting behavior of multi-walled carbon nanotube-reinforced nylon-6 composites

The crystallization and melting behavior of neat nylon-6 (PA6) and multi-walled carbon nanotubes (MWNTs)/PA6 composites prepared by simple melt-compounding was comparatively studied. Differential scanning calorimetry (DSC) results show two crystallization exotherms (TCC, 1 and TCC, 2) for PA6/MWNTs composites instead of a single exotherm (TCC, 1) for the neat matrix. The formation of the higher-temperature exotherm TCC, 2 is closely related to the addition of MWNTs. X-ray diffraction (XRD) results indicate that only the α-phase crystalline structure is formed upon incorporating MWNTs into PA6 matrix, independently of the cooling rate and annealing conditions. These observations are significantly different from those for PA6 matrix, where the increase in cooling rate or decrease in annealing temperature results in the crystal transformation from α-phase to γ-phase. The crystallization behavior of PA6/MWNTs composites is also significantly different from those reported in PA6/nanoclay systems, probably due to the difference in nanofiller geometry between one-dimensional MWNTs and two-dimensional nanoclay platelets. The nucleation sites provided by carbon nanotubes seem to be favorable to the formation of thermodynamically stable α-phase crystals of PA6. The dominant α-phase crystals in PA6/MWNTs composites may play an important role in the remarkable enhancement of mechanical properties.
Faster tuple lattice sieving using spherical locality-sensitive filters

To overcome the large memory requirement of classical lattice sieving algorithms for solving hard lattice problems, Bai-Laarhoven-Stehle [ANTS 2016] studied tuple lattice sieving, where tuples instead of pairs of lattice vectors are combined to form shorter vectors. Herold-Kirshanova [PKC 2017] recently improved upon their results for arbitrary tuple sizes, for example showing that a triple sieve can solve the shortest vector problem (SVP) in dimension $d$ in time $2^{0.3717d + o(d)}$, using a technique similar to locality-sensitive hashing for finding nearest neighbors. In this work, we generalize the spherical locality-sensitive filters of Becker-Ducas-Gama-Laarhoven [SODA 2016] to obtain space-time tradeoffs for near neighbor searching on dense data sets, and we apply these techniques to tuple lattice sieving to obtain even better time complexities. For instance, our triple sieve heuristically solves SVP in time $2^{0.3588d + o(d)}$. For practical sieves based on Micciancio-Voulgaris' GaussSieve [SODA 2010], this shows that a triple sieve uses less space and less time than the current best near-linear space double sieve.
Genetic Diversity and Domestication Footprints of Chinese Cherry [Cerasus pseudocerasus (Lindl.) G.Don] as Revealed by Nuclear Microsatellites

Chinese cherry [Cerasus pseudocerasus (Lindl.) G.Don] is a commercially important fruit crop in China, but its structure patterns and domestication history remain imprecise. To address these questions, we estimated the genetic structure and domestication history of Chinese cherry using 19 nuclear microsatellite markers and 650 representative accessions (including 118 Cerasus relatives) selected throughout their natural eco-geographical distributions. Our structure analyses detected no genetic contribution from Cerasus relatives to the evolution history of Chinese cherry. A separate genetic structure was detected in wild Chinese cherries and rough geographical structures were observed in cultivated Chinese cherries. One wild (wild Chinese cherry, WC) and two cultivated (cultivated Chinese cherry, CC1 and CC2) genetic clusters were defined. Our approximate Bayesian computation analyses supported an independent domestication history with two domestication events for CC1 and CC2, happening about 3900 and 2200 years ago, respectively. Moderate loss of genetic diversity, over 1000-year domestication bottlenecks and divergent domestication in fruit traits were also detected in cultivated Chinese cherries, which is highly correlated to long-term clonal propagation and different domestication trends and preferences. Our study is the first to comprehensively and systematically investigate the structure patterns and domestication history for Chinese cherry, providing important references for revealing the evolution and domestication history of perennial woody fruit trees.
A study of an omnidirectional robotic cart using passive wheels

This paper presents another type of robotic cart. In recent years there are a variety of power-assisted machines being researched. From them, robotic carts can help older people carry heavy objects easily and efficiently. Because of the similarity of conventional carts, they can be used in a variety of situations. However, robotic carts have the common mechanism that their wheels are driven directly by actuators. Because of that, energy efficiency is low, and those carts cannot move when battery power is low. As a result, older people are burdened by this disadvantage. To counter this, we tried to develop another type of robotic cart that has passive wheels instead of using regular active wheels. By using passive wheels, the robotic cart has high energy efficiency.
Type II transmembrane serine proteases as potential target for anti-influenza drug discovery

ABSTRACT Introduction: The outbreak of an influenza pandemic as well as the continued circulation of seasonal influenza highlights the need for effective antiviral therapies. The emergence of drug-resistant strains further necessitates the development of novel antivirals that target the host factors crucial for viral replication. Area covered: This review summarizes the current understanding of the structural and functional properties of type II transmembrane serine proteases (TTSPs) as a proteolytic activator of influenza virus infection and discusses their potential as antiviral targets. It also explores the experimental evidence accumulated for inhibitors of TTSPs as novel, broad-spectrum antivirals against various influenza virus subtypes. The review also provides an overview of the properties of small molecules, proteins, and peptides that efficiently inhibit the proteolytic activation of the influenza virus. Expert opinion: TTSPs activate a wide range of influenza virus subtypes including avian influenza viruses, both in vitro and in vivo, via proteolytic cleavage of influenza hemagglutinin (HA) into infection-competent fusogenic conformation. Other viruses such as SARS-, MERS-coronaviruses and human metapneumoviruses may use the same host cell proteases for activation, implying that TTSP inhibition might be a novel strategy for developing broad-spectrum antiviral agents for respiratory viral infections.
Lattice Histograms: a Resilient Synopsis Structure

Despite the surge of interest in data reduction techniques over the past years, no method has been proposed to date that can always achieve approximation quality preferable to that of the optimal plain histogram for a target error metric. In this paper, we introduce the lattice histogram: a novel data reduction method that discovers and exploits any arbitrary hierarchy in the data, and achieves approximation quality provably at least as high as an optimal histogram for any data reduction problem. We formulate LH construction techniques with approximation guarantees for general error metrics. We show that the case of minimizing a maximum-error metric can be solved by a specialized, memory-sparing approach; we exploit this solution to design reduced-space heuristics for the general- error case. We develop a mixed synopsis approach, applicable to the space-efficient high-quality summarization of very large data sets. We experimentally corroborate the superiority of LHs in approximation quality over previous techniques with representative error metrics and diverse data sets.
A template-based and pattern-driven approach to situation awareness and assessment in virtual humans

Situation awareness and assessment are fundamental components of rational virtual humans. They are central parts of models of virtual humans and critical elements of efficient reasoning and planning systems. In this paper, we describe our efforts of developing the capability of situation awareness in autonomous, synthetic virtual pilots in a military domain. After briefly describing the motivations of this research, we present an agent architecture that integrates perception, reasoning with situation awareness, and actions. We describe a representation of situations, methods for situation assessment, and applications of situation awareness in information collection, and creating focused attention. The quantitative measure from our experiment shows that by using focused attention based on the ability of situation awareness, the perceptional load of virtual pilots is significantly reduced, reducing pilots’ response time by more than 50 percent.
On the use of skin texture features for gender recognition: An experimental evaluation

Skin appearance is almost universally the object of gender-related expectations and stereotypes. This not with standing, remarkably little work has been done on establishing quantitatively whether skin texture can be used for gender discrimination. We present a detailed analysis of the skin texture of 43 subjects based on two complementary imaging modalities afforded by a visible-light dermoscope and the recently developed Epsilon sensor for capacitive imaging. We consider an array of established texture features in combination with two supervised classification techniques (1-NN and SVM) and a state-of-the-art unsupervised approach (t-SNE). A statistical analysis of the results suggests that skin microtexture carries very little information on gender.