Miracle-dz/UniFAR-FTUs huggingface dataset:
Sign language word recognition using via-point information and correlation of they bimanual movements

We have studied Japanese sign Language (JSL) recognition system. In our previous research, we focus on only JSL words performed in the movement of the dominant arm and proposed a recognition method using via-points extracted from the trajectory data of the dominant arm as feature points based on the minimum jerk model. In this study, in order to recognize JSL words performed in bimanual movements, we investigated an integration method of the matching result of the both arms. We classified JSL movements into three categories as part of sign language recognition system. And we used a correlation coefficient and difference of the path length between the both arm movements as a factor to classify JSL. As a result of recognition experiment, the recognition rate was 98% or more in 80 words from multiple speakers.
An Improved GaAs FET Nonlinear Model Suitable for Intermodulation Analysis of Amplifiers,Switches and Resistive Mixers

This paper presents an IDS(VGS,VDS)model to represent PHEMT behavior in the reverse )0 ( DS V .The model predicts with high accuracy the measured data as well as higher orders derivatives of the transconductance over a large range of VDS bias.These characteristics are important for the analysis of intermodulation distortion using harmonic balance or Volterra series.Using the improved IDS(VGS,VDS)model along with an empirical model to simulate the nonlinear behavior of gate-source capacitance, CGS,and gate-drain capacitance,CGD,a GaAs FET nonlinear model suitable for intermodulation analysis of amplifiers,switches and resistive mixers is presented
Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data

With vast amount of medical records being digitized in recent years in the form of Electronic Health Records (EHRs), accurate and large scale automated prognosis of diseases has become a possibility. However, most existing works in disease prediction have focused on a single condition or a few related conditions. Such models do not account for the fact that multiple conditions may co-occur in patients and that patient symptoms may be indicative of more than one distinct disease. Further, most learning models do not account for all patient symptoms, physiological test results, nursing notes and any other patient history that may be available in EHRs. For example, medication data, clinical notes, discharge summaries, physiological test results etc. are all indicative of different patient conditions. Modeling such heterogeneous data simultaneously can improve automated prognosis. In this work, we propose to model such heterogeneous data simultaneously for multiple chronic disease prediction. Our prior work on multiple chronic disease prediction using clinical notes, primarily early nursing progress notes have suggested that such data are predictive and useful for prognosis.
Granulocyte macrophage colony-stimulating factor expression in human herpetic stromal keratitis: implications for the role of neutrophils in HSK.

PURPOSE Granulocyte macrophage colony-stimulating factor (GM-CSF) is thought to play a key role in chronic inflammatory diseases by governing the survival and function of infiltrating neutrophils. The objective of this study was to determine the putative role of GM-CSF in the pathogenesis of human herpetic stromal keratitis (HSK). METHODS Primary human corneal fibroblast (HCF) cultures and a telomerase-immortalized human corneal epithelial (HCE) cell line representative of native HCE were stimulated with the known HSK-inducing cytokines interferon (IFN)-gamma, interleukin (IL)-1beta, and tumor necrosis factor (TNF)-alpha. Alternatively, the T-cell cytokine IL-17 was added solely or simultaneously. Human neutrophils were incubated with conditioned medium (CM) of the HCF and HCE stimulated with the aforementioned cytokines, or recombinant GM-CSF, and their viability or activation status was determined by flow cytometry. GM-CSF and IL-8 secretion levels in the CM were determined by ELISA. The antibody-dependent cellular cytotoxicity (ADCC) of neutrophils toward herpes simplex virus (HSV)-infected HCFs was determined by flow cytometry. The expression of GM-CSF was determined in HSK and control corneal buttons by real-time RT-PCR and immunohistology. RESULTS Compared with IFN-gamma, CM of either cell type stimulated with IL-1beta, or in the case of HCE cells, stimulated with TNF-alpha or IL-17, delayed neutrophil apoptosis significantly. Only in HCFs did IL-17 exhibit a synergistic effect with TNF-alpha. The antiapoptotic activity was attributable in part to the GM-CSF secreted by the activated HCFs and HCE cells. GM-CSF stimulation of neutrophils induced their activation and the secretion of IL-8. GM-CSF did not increase significantly the ADCC reaction of neutrophils toward HSV-infected HCFs. Finally, GM-CSF was expressed in corneas of the patients with HSK but not in control subjects. CONCLUSIONS The data suggest that GM-CSF, expressed by cornea-resident cells such as HCFs and HCE cells, may play a role in the immunopathogenesis of HSK by prolonging the survival and modulating the effector function of corneal infiltrating neutrophils.
Simple zeros of the Riemann zeta-function

Assuming the Riemann Hypothesis, Montgomery and Taylor showed that at least 67.25% of the zeros of the Riemann zeta-function are simple. Using Montgomery and Taylor's argument together with an elementary combinatorial argument, we prove that assuming the Riemann Hypothesis at least 67.275% of the zeros are simple.
Key metabolites in tissue extracts of Elliptio complanata identified using 1H nuclear magnetic resonance spectroscopy

We used 1H-NMR to describe the freshwater mussel metabolome. Muscle, digestive gland, mantle and gill tissues yielded profiles with possible biomarkers of physiologic function. These preliminary studies provide evidence for potential use of digestive gland and mantle tissue for studying physiological impacts of location, sex and reproductive condition on Elliptio complanata.
Apomictic and Sexual Germline Development Differ with Respect to Cell Cycle, Transcriptional, Hormonal and Epigenetic Regulation

Seeds of flowering plants can be formed sexually or asexually through apomixis. Apomixis occurs in about 400 species and is of great interest for agriculture as it produces clonal offspring. It differs from sexual reproduction in three major aspects: (1) While the sexual megaspore mother cell (MMC) undergoes meiosis, the apomictic initial cell (AIC) omits or aborts meiosis (apomeiosis); (2) the unreduced egg cell of apomicts forms an embryo without fertilization (parthenogenesis); and (3) the formation of functional endosperm requires specific developmental adaptations. Currently, our knowledge about the gene regulatory programs underlying apomixis is scarce. We used the apomict Boechera gunnisoniana, a close relative of Arabidopsis thaliana, to investigate the transcriptional basis underlying apomeiosis and parthenogenesis. Here, we present the first comprehensive reference transcriptome for reproductive development in an apomict. To compare sexual and apomictic development at the cellular level, we used laser-assisted microdissection combined with microarray and RNA-Seq analyses. Conservation of enriched gene ontologies between the AIC and the MMC likely reflects functions of importance to germline initiation, illustrating the close developmental relationship of sexuality and apomixis. However, several regulatory pathways differ between sexual and apomictic germlines, including cell cycle control, hormonal pathways, epigenetic and transcriptional regulation. Enrichment of specific signal transduction pathways are a feature of the apomictic germline, as is spermidine metabolism, which is associated with somatic embryogenesis in various plants. Our study provides a comprehensive reference dataset for apomictic development and yields important new insights into the transcriptional basis underlying apomixis in relation to sexual reproduction.
A Single Consumption of High Amounts of the Brazil Nuts Improves Lipid Profile of Healthy Volunteers

Background. This study investigates the effects of Brazil nut ingestion on serum lipid profile in healthy volunteers. Methods. Ten healthy subjects were enrolled in the study. Each subject was tested 4 times in a randomized crossover in relation to the ingestion of different serving sizes of the Brazil nut: 0, 5, 20, or 50 g. At each treatment point, peripheral blood was drawn before and at 1, 3, 6, 9, 24, and 48 hours and 5 and 30 days. Blood samples were tested for total cholesterol, high- and low-density lipoprotein cholesterol (HDL-c and LDL-c, resp.), triglycerides, selenium, aspartate and alanine aminotransferases, albumin, total protein, alkaline phosphatase, gamma GT, urea, creatinine, and C-reactive protein. Results. A significant increase of the plasma selenium levels was observed at 6 hours within the groups receiving the nuts. Serum LDL-c was significantly lower, whereas HDL-c was significantly higher 9 hours after the ingestion of 20 or 50 g of nuts. The biochemical parameters of liver and kidney function were not modified by ingestion of nuts. Conclusions. This study shows that the ingestion of a single serving of Brazil nut can acutely improve the serum lipid profile of healthy volunteers.
Recent Developments in the Cohomology of Finite Groups

In this expository paper we describe some recent work in the cohomology of finite groups. In particular, we discuss techniques for calculation and how they apply to key examples from group theory, namely, the sporadic simple groups. We also mention recent theoretical results arising from these calculations and interactions between algebra and topology which occur in the context of finite group cohomology.
Scapula Statistical Shape Model construction based on watershed segmentation and elastic registration

Automated bone segmentation is one of the most challenging problems in medical imaging. The increasingly demanded MR imaging suffers from low contrast and signal-to-noise ratio when it comes to bones. To increase the segmentation robustness, a prior model of the structure could guide the segmentation when explicit information is missing or weakly presented. Statistical Shape Models (SSMs) are efficient examples for such application where a set of dense correspondences between the training samples is to be established. The complexity of the anatomy of the scapula's bone is a real challenge at this level. We present an automated SSM construction approach with an adapted initialization to address the correspondences problem. Our approach is atlas-based where landmarks are matched on each sample using rigid and elastic registration. Our innovation stems from the derivation of a robust SSM based on Watershed segmentation which steers the elastic registration at some critical zones.
Fusion-based Target Tracker for Sector Scan Radar

This paper presents a fusion-based target tracker (FBTT) for tracking a target detected by sector scan radar. The tracker employs two Kalman filters (KF) in dual-path structure. Estimation of target state in minimum mean square sense (MMSS) is obtained through fusing estimations exported from two Kalman filters, respectively. With the framework proposed here, most prevalent maneuvering target tracking algorithms in annular scan radar system can be readily applied for sector scan radar without the overburden of computation. Performance comparison between FBTT and Kalman filter is demonstrated through simulations. Benefit and validity of the proposed method is verified
Number 44 The Technological Structure and Performance of Developing Country Manufactured Exports , 1985-1998

This paper maps recent manufactured export patterns in developing countries, using a new and detailed classification by technology. It argues that export structures, being path-dependent and difficult to change, have implications for growth and development. Low technology products tend to grow the slowest and technology intensive products the fastest. East Asia dominates the scene with 70 percent of developing-world manufactured exports; there is high and rising concentration at the national level. The strategies used to achieve competitiveness differ greatly between countries. Received trade theory cannot explain these patterns without considering learning processes and the policies used to promote them.
Light-Driven Calcium Signals in Mouse Cone Photoreceptors

Calcium mediates various neuronal functions. The complexity of neuronal Ca2+ signaling is well exemplified by retinal cone photoreceptors, which, with their distinct compartmentalization, offer unique possibilities for studying the diversity of Ca2+ functions in a single cell. Measuring subcellular Ca2+ signals in cones under physiological conditions is not only fundamental for understanding cone function, it also bears important insights into pathophysiological processes governing retinal neurodegeneration. However, due to the proximity of light-sensitive outer segments to other cellular compartments, optical measurements of light-evoked Ca2+ responses in cones are challenging. We addressed this problem by generating a transgenic mouse (HR2.1:TN-XL) in which both short- and middle-wavelength-sensitive cones selectively express the genetically encoded ratiometric Ca2+ biosensor TN-XL. We show that HR2.1:TN-XL allows recording of light-evoked Ca2+ responses using two-photon imaging in individual cone photoreceptor terminals and to probe phototransduction and its diverse regulatory mechanisms with pharmacology at subcellular resolution. To further test this system, we asked whether the classical, nitric oxide (NO)-soluble guanylyl-cyclase (sGC)-cGMP pathway could modulate Ca2+ in cone terminals. Surprisingly, NO reduced Ca2+ resting levels in mouse cones, without evidence for direct sGC involvement. In conclusion, HR2.1:TN-XL mice offer unprecedented opportunities to elucidate light-driven Ca2+ dynamics and their (dys)regulation in cone photoreceptors.
Shear-enhanced adhesiveless transfer printing for use in deterministic materials assembly

This letter describes the physics and application of an approach to transfer printing that utilizes targeted shear loading to modulate stamp adhesion in a controlled and repeatable fashion. Experimental measurements of pull-off forces as functions of shear and stamp dimension reveal key scaling properties and provide a means for comparison to theory and modeling. Examples of printed structures in suspended and multilayer configurations demonstrate some capabilities in micro/nanoscale materials assembly.
MODELING ROAD TRAFFIC ACCIDENT REPORTING SYSTEM BY DISCRETE EVENT SIMULATION : A CASE STUDY OF IRAN ’ S ROAD

In this study business process simulation (BPS) is used to evaluate the effect of redesigning police road traffic accident (RTA) reporting system. It is claimed that by integrating information systems to road traffic accident (RTA) reporting system, duration of this process will be shorten and it will lead to more effective utilization of traffic police personnel. A case is studied in this project is road traffic accident (RTA) reporting system in sample of Iran’s road. In this case the simulation was run ten times in a simulated 30 days for the current road traffic accident system and in presence of new police road traffic accident (RTA) reporting systems. KEYWORD: Discrete simulation, Road Traffic Accident, reporting system
PROTECT: a deployed game theoretic system to protect the ports of the United States

While three deployed applications of game theory for security have recently been reported at AAMAS [12], we as a community remain in the early stages of these deployments; there is a continuing need to understand the core principles for innovative security applications of game theory. Towards that end, this paper presents PROTECT, a game-theoretic system deployed by the United States Coast Guard (USCG) in the port of Boston for scheduling their patrols. USCG has termed the deployment of PROTECT in Boston a success, and efforts are underway to test it in the port of New York, with the potential for nationwide deployment. PROTECT is premised on an attacker-defender Stackelberg game model and offers five key innovations. First, this system is a departure from the assumption of perfect adversary rationality noted in previous work, relying instead on a quantal response (QR) model of the adversary's behavior --- to the best of our knowledge, this is the first real-world deployment of the QR model. Second, to improve PROTECT's efficiency, we generate a compact representation of the defender's strategy space, exploiting equivalence and dominance. Third, we show how to practically model a real maritime patrolling problem as a Stackelberg game. Fourth, our experimental results illustrate that PROTECT's QR model more robustly handles real-world uncertainties than a perfect rationality model. Finally, in evaluating PROTECT, this paper for the first time provides real-world data: (i) comparison of human-generated vs PROTECT security schedules, and (ii) results from an Adversarial Perspective Team's (human mock attackers) analysis.
Model for cost evaluation of OSS data integration

As a result of the rapid development in operation support systems (OSSs), OSS development costs have increased due to the separate development of individual systems, and maintenance costs have also risen due to the complex architecture of the entire system. To solve this problem, we previously proposed OSS data integration, which is an approach to integrate data among systems to reduce the cost of OSS development. To quantify the effect of data integration, we propose a model for cost evaluation focusing on software size as a metric based on an OSS software model and software size estimation method.
Online dictionary learning from large-scale binary data

Compressive sensing (CS) has been shown useful for reducing dimensionality, by exploiting signal sparsity inherent to specific domain representations of data. Traditional CS approaches represent the signal as a sparse linear combination of basis vectors from a prescribed dictionary. However, it is often impractical to presume accurate knowledge of the basis, which motivates data-driven dictionary learning. Moreover, in large-scale settings one may only afford to acquire quantized measurements, which may arrive sequentially in a streaming fashion. The present paper jointly learns the sparse signal representation and the unknown dictionary when only binary streaming measurements with possible misses are available. To this end, a novel efficient online estimator with closed-form sequential updates is put forth to recover the sparse representation, while refining the dictionary `on the fly'. Numerical tests on simulated and real data corroborate the efficacy of the novel approach.
Cognitive adjustment and psychological capital influences on expatriate workers’ job performance: An Ethiopian study

This study examined the relationship between cognitive adjustment and expatriates’ performance in the foreign host-country, and the moderating role of psychological capital in this relationship. The expatriates (N = 1 229; female = 32%; mean international tenure = 2.99, SD = 4.44) completed measures of cognitive adjustments (work and non-work related), psychological capital, job-performance, and organisational culture. Results from the data analysis, using the product least square method, indicate expatriates’ cognitive adjustments (work and non-work related) and psychological capital to singularly predict job performance. Psychological capital partly moderated the relationship between cognitive adjustment (work related) and expatriates’ performance.
My Computer Is an Honor Student - but How Intelligent Is It? Standardized Tests as a Measure of AI

Given the well-known limitations of the Turing Test, there is a need for objective tests to both focus attention on, and measure progress towards, the goals of AI. In this paper we argue that machine performance on standardized tests should be a key component of any new measure of AI, because attaining a high level of performance requires solving significant AI problems involving language understanding and world modeling - critical skills for any machine that lays claim to intelligence. In addition, standardized tests have all the basic requirements of a practical test: they are accessible, easily comprehensible, clearly measurable, and offer a graduated progression from simple tasks to those requiring deep understanding of the world. Here we propose this task as a challenge problem for the community, summarize our state-of-the-art results on math and science tests, and provide supporting datasets
Discrete Differential Evolution with local search to solve the Traveling Salesman Problem: Fundamentals and case studies

Traveling salesman problem (TSP) is one of the most difficult problems in the combinatorial optimization area. The goal of TSP is to find one path that can travel between all the nodes (instances) of the graph just once (Hamiltonian tour) in the smallest tour, that is, smallest Euclidian distance. In this context, many other meta-heuristics techniques based on evolutionary algorithms have been propose in literature to solve TSP problems. Differential evolution (DE) is a relatively new simple evolutionary algorithm, which is an effective adaptive approach to global optimization over continuous search spaces. The design principles of DE are simplicity and efficiency. The most distinct feature of DE is that it mutates vectors by adding weighted, random vector differentials to them. Since its invention, DE has been applied with high success on many numerical optimization problems outperforming other more popular meta-heuristics such as the genetic algorithms. Recently, some researchers extended with success the application of DE to complex combinatorial optimization problems with discrete decision variables such as the traveling salesman problem, the machine layout problem, the flow-shop scheduling problem. In this paper, the following discrete DE approaches for the TSP are proposed and evaluated: i) DE approach without local search, ii) DE with local search based on Lin-Kernighan-Heulsgaun (LKH) method, and iii) DE with local search based on variable neighborhood search (VNS) and together with LKH method. Numerical study is carried out using the TSPLIB of test TSP problems. In this context, the computational results are compared with the other results in the recent TSP literature. The obtained results show that LKH method is the best method to reach optimal results for TSPLIB benchmarks, but for largest problems, the ED+VNS improve the quality of obtained results.
AtRAB-H 1 b and AtRAB-H 1 c GTPases , homologues of the yeast Ypt 6 , target reporter proteins to the Golgi when expressed in Nicotiana tabacum and Arabidopsis thaliana

Ypt/Rab GTPases act as key regulators of intracellular traffic through the conformational differences exhibited by their GTP or GDP-bound forms. In this paper, two Arabidopsis Ypt6 homologues, AtRAB-H1 and AtRAB-H1 were characterized and compared. Using a live cell imaging approach, it is shown that yellow fluorescent protein-fusions (YFP) of AtRAB-H1 and AtRAB-H1 locate to the Golgi and to the cytosol in both Nicotiana tabacum and in Arabidopsis thaliana. In addition, YFP-AtRAB-H1 targets an as yet unknown compartment not labelled by YFPAtRAB-H1 or Golgi markers. It is also shown that the subcellular location of YFP-AtRAB-H1 and YFP-AtRAB-H1 is affected by the state of GTP-binding and that expression of a GTP-deficient mutant results in increased apoplastic fluorescence of a secretory form of YFP.