Miracle-dz/UniFAR-FTUs huggingface dataset:
Incivility in the workplace: incidence and impact.

This study extends the literature on interpersonal mistreatment in the workplace by examining the incidence, targets, instigators, and impact of incivility (e.g., disrespect, condescension, degradation). Data were collected from 1,180 public-sector employees, 71% of whom reported some experience of workplace incivility in the previous 5 years. As many as one third of the most powerful individuals within the organization instigated these uncivil acts. Although women endured greater frequencies of incivility than did men, both genders experienced similarly negative effects on job satisfaction, job withdrawal, and career salience. Uncivil workplace experiences were also associated with greater psychological distress; however, indices of psychological and physical health were relatively unaffected. The authors discuss these findings in the context of organizational and cognitive stress theories.
Twitter data collecting tool with rule-based filtering and analysis module

Purpose – It is difficult to build our own social data set because data in social media is generally too vast and noisy. The aim of this study is to specify design and implementation details of the Twitter data collecting tool with a rule‐based filtering module. Additionally, the paper aims to see how people communicate with each other through social networks in a case study with rule‐based analysis.Design/methodology/approach – The authors developed a java‐based data gathering tool with a rule‐based filtering module for collecting data from Twitter. This paper introduces the design specifications and explain the implementation details of the Twitter Data Collecting Tool with detailed Unified Modeling Language (UML) diagrams. The Model View Controller (MVC) framework is applied in this system to support various types of user interfaces.Findings – The Twitter Data Collecting Tool is able to gather a huge amount of data from Twitter and filter the data with modest rules for complex logic. This case study sh.
Performance evaluation of amino acid substitution matrices

Several choices of amino acid substitution matrices are currently available for searching and alignment applications. These choices were evaluated using the BLAST searching program, which is extremely sensitive to differences among matrices, and the Prosite catalog, which lists members of hundreds of protein families. Matrices derived directly from either sequence‐based or structurebased alignments of distantly related proteins performed much better overall than extrapolated matrices based on the Dayhoff evolutionary model. Similar results were obtained with the FASTA searching program. Improved performance appears to be general rather than family‐specific, reflecting improved accuracy in scoring alignments. An implementation of a multiple matrix strategy was also tested. While no combination of three matrices performed as well as the single best matrix, BLOSUM 62, good results were obtained using a combination of sequence‐based and structure‐based matrices. This hybrid set of matrices is likely to be useful in certain situations. Our results illustrate the importance of matrix selection and value of a comprehensive approach to evaluation of protein comparison tools. © 1993 Wiley‐Liss, Inc.
Potential of Rapid Diagnosis for Controlling Drug-Susceptible and Drug-Resistant Tuberculosis in Communities Where Mycobacterium tuberculosis Infections Are Highly Prevalent

ABSTRACT The long-term persistence of Mycobacterium tuberculosis in communities with high tuberculosis prevalence is a serious problem aggravated by the presence of drug-resistant tuberculosis strains. Drug resistance in an individual patient is often discovered only after a long delay, particularly if the diagnosis is based on current culture-based drug sensitivity testing methods. During such delays, the patient may transmit tuberculosis to his or her contacts. Rapid diagnosis of drug resistance would be expected to reduce this transmission and hence to decrease the prevalence of drug-resistant strains. To investigate this quantitatively, a mathematical model was constructed, assuming a homogeneous population structure typical of communities in South Africa where tuberculosis incidence is high. Computer simulations performed with this model showed that current control strategies will not halt the spread of multidrug-resistant tuberculosis in such communities. The simulations showed that the rapid diagnosis of drug resistance can be expected to reduce the incidence of drug-resistant cases provided the additional measure of screening within the community is implemented.
Viable Polioviruses That Encode 2A Proteins with Fluorescent Protein Tags

ABSTRACT The 2A proteins of the Picornaviridae enterovirus genus are small cysteine proteinases that catalyze essential cleavages in the viral polyprotein in cis and in several cellular proteins in trans. In addition, 2A has been implicated in the process of viral RNA replication, independent of its protease functions. We have generated viable polioviruses that encode 2A proteins containing fluorescent protein tag insertions at either of two sites in the 2A protein structure. Viruses containing an insertion of Discosoma sp. red fluorescent protein (DsRed) after residue 144 of 2A, near the C terminus, produced plaques only slightly smaller than wild-type (wt) virus. The polyprotein harboring the 2A-DsRed fusion protein was efficiently and accurately cleaved; fluorescent 2A proteinase retained protease activity in trans and supported translation and replication of viral RNA, both in vitro and in infected cells. Intracellular membrane reorganization to support viral RNA synthesis was indistinguishable from that induced by wt virus. Infected cells exhibited strong red fluorescence from expression of the 2A-DsRed fusion protein, and the progeny virus was stable for three to four passages, after which deletions within the DsRed coding sequence began to accumulate. Confocal microscopic imaging and analysis revealed a portion of 2A-DsRed in punctate foci concentrated in the perinuclear region that colocalized with replication protein 2C. The majority of 2A, however, was associated with an extensive structural matrix throughout the cytoplasm and was not released from infected cells permeabilized with digitonin.
The ClC-3 Chloride Transport Protein Traffics through the Plasma Membrane via Interaction of an N-terminal Dileucine Cluster with Clathrin*

ClC-3 is a ubiquitously expressed chloride transport protein that is present in synaptic vesicles and endosome/lysosome compartments. It is largely intracellular but has been observed at the plasma membrane as well. The aim of this study was to identify the pathways and regulation of ClC-3 trafficking to intracellular sites. At the steady state, ∼94% of transfected ClC-3 was localized intracellularly, and only 6% was at the plasma membrane. Pulse labeling with [35S]methionine and biotinylation demonstrated that about 25% of newly synthesized ClC-3 traffics through the plasma membrane. We used both immunofluorescence microscopy and biotinylation assays to assess the trafficking of ClC-3. Plasma membrane ClC-3 was rapidly endocytosed (t½ ∼ 9 min); a portion entered a recycling pool that returned to the cell surface after internalization, and the remainder trafficked to more distal intracellular compartments. ClC-3 associated with clathrin at the plasma membrane. Coimmunoprecipitation and glutathione S-transferase pulldown assays demonstrated that the N terminus of ClC-3 binds to clathrin. Alanine replacement of a dileucine acidic cluster within the cytosolic N terminus (amino acids 13-19) resulted in a molecule that had decreased endocytosis and increased surface expression. This replacement also abolished interaction with clathrin as assessed both by coimmunoprecipitation and glutathione S-transferase pulldown assays. We conclude that ClC-3 is primarily an intracellular transport protein that is transiently inserted into the plasma membrane where it is rapidly endocytosed. Internalization of ClC-3 depends on the interaction between an N-terminal dileucine cluster and clathrin.
The impact of disease characteristics on multiple sclerosis patients’ quality of life

OBJECTIVES The aim of this study was to assess the quality of life (QoL) of patients with multiple sclerosis (MS), and to investigate the effects of characteristics of MS such as disease course, severity, and relapses on patients’ QoL. METHODS This was a cross-sectional study, in which 171 patients were enrolled. Health-related QoL was assessed using the Persian version of the Multiple Sclerosis Quality of Life-54 questionnaire. To measure patients’ disability status, we used the Expanded Disability Status Scale. Other variables included in the study were disease course and relapses of the disease. RESULTS The average scores for patients’ physical and mental QoL were 60.9±22.3 and 59.5±21.4, respectively. In a bivariate analysis, disease course, severity of the disease, and relapses were significantly associated with the physical and mental health composite scores. In a hierarchal regression analysis, disease course, severity of the disease, and relapses were responsible for 38 and 16% of the variance in physical and mental QoL, respectively. It was also observed that relapses were a strong predictor of both physical and mental QoL. CONCLUSIONS Our results showed that disease characteristics significantly affected both dimensions of QoL. It is therefore suggested that health care providers should be aware of these characteristics of MS to more successfully improve MS patients’ QoL.
Gate capacitances behavior of nanometer FD SOI CMOS devices with HfO/sub 2/ high-k gate dielectric considering vertical and fringing displacement effects using 2-D Simulation

This paper reports the gate-source (drain)/source (drain)-gate capacitance behavior of 100-nm fully depleted silicon-on-insulator CMOS devices with HfO/sub 2/ high-k gate dielectric considering vertical and fringing displacement effects. Based on the two-dimensional simulation results, a unique two-step C/sub S(D)G//C/sub GS/ versus V/sub G/ curve could be identified for the device with the 1.5-nm HfO/sub 2/ gate dielectric due to the vertical and fringing displacement effects.
The structure of the photoreceptor unit of Rhodopseudomonas viridis

The thylakoid membrane of Rhodopseudomonas viridis contains extensive, regular arrays of photoreceptor complexes arranged on a hexagonal lattice with a repeat distance of ˜130 Å. Single membrane sheets were obtained by mild treatment of the thylakoid fraction with the detergent Triton X‐100. Heavy metal shadowing and electron microscopy of isolated thylakoids indicated a strong asymmetry of the membrane, showing a smooth plasmic and a rough exoplasmic side. Fourier processing of rotary‐shadowed specimens showed the different surface relief on both sides of the membrane. Structural units on both sides were roughly circular and showed 6‐fold symmetry at a resolution close to 20 Å. The structural unit was characterised by a central core that seemed to extend through the membrane, protruding on the exoplasmic side. The core was surrounded by a ring showing 12 subunits on the plasmic side. Rotary‐shadowed as well as negatively‐stained membranes indicated a handedness of the structure. Treatment of thylakoid vesicles with higher detergent concentrations yielded a fraction of particles showing the same features as Fourier maps of the structural units. The isolated particles therefore appeared to represent structurally intact units of photosynthesis.
Working Memory , Cognitive Control , and the Prefrontal Cortex : Computational and Empirical Studies

The dominant cognitive theory of working memory (WM) postulates a strict architectural segregation between components responsible for the short-term active maintenance of information and those responsible for the control and coordination of that information. Cognitive neuroscience research has provided strong evidence that the prefrontal cortex (PFC) serves as an important neural substrate of WM. However, the literature is mixed as to whether PFC should be considered a storage or control component. A theory is presented that attempts to resolve this conflict by postulating that PFC represents and actively maintains context information. These maintained representations provide a mechanism of control by serving as a top-down bias on the local competitive interactions that occur during processing. As such, it is suggested that storage and control functions are integrated within PFC. This theory is implemented as connectionist computational model. Simulation studies are described which demonstrate that the model can account for a wide range of behavioral data associated with performance of a simple task paradigm that probes both the storage and control functions of WM. Two neuroimaging studies are then presented which directly test the predictions of the model regarding the role of PFC in context processing. Taken together, the results provide new insights into the relationship between storage and control in WM, and the role of PFC in subserving these functions.
The model law for SF/sub 6/ insulated systems

The variation of probability of the electrical breakdown of gases as a result of varying the interelectrode gap value is considered. The relevant analytical expressions have been obtained by treating the electrical discharge of gases as avalanche processes in real space and, in the sense of Markov processes, in the probability space. Parameters of the theoretical model are determined experimentally, while the whole model is experimentally verified. A rather good agreement between the results obtained experimentally and those anticipated theoretically is achieved for the surface change by a factor of ten concerning and also for the interelectrode gap change by the same factor. The experiments were carried out with the gas SF/sub 6/. The absolute pressure was varied from 0.5 to 7 bars.
Prediction of single neural firings for Hodgkin-Huxley neuron by fitting generalized linear model

At the single neuron level, neural information processing involves the transformation of input stimulation into an output spike train. Here a generalized linear model (GLM) is used to reconstruct the mapping from stimulation to firing trains of single neuron for Hudgkin-Huxley (H-H) model. Firstly, H-H model is stimulated by the white noise to generate the input-output data samples used to construct GLM. Then, the parameters of GLM are estimated according to the maximum likelihood of the spike time serial of spike trains extracted from action potential of H-H. After that, the input-output mapping of spike trains evoked by white noise for H-H is successfully reconstructed. Through comparing the inter spike interval (ISI) and Pearson's correlation coefficient, it also proves that the established GLM provides a good reproduction and prediction of the firing information for H-H. These studies provide us a new insight into coding processes and information tansfer of single neural.
Natural Language Interfaces for Data Analysis with Visualization: Considering What Has and Could Be Asked

Natural language is emerging as a promising interaction paradigm for data analysis with visualization. Designing and implementing Natural Language Interfaces (NLIs) is a challenging task, however. In addition to being able to process and understand natural language expressions, NLIs for data visuailzation must consider other factors including input modalities, providing input affordances, and explaining system results, among others. In this article, we examine existing NLIs for data analysis with visualization, and compare and contrast them based on the tasks they allow people to perform. We discuss open research opportunities and themes for emerging NLIs in the visualization community. We also provide examples from the existing literature in the broader HCI community that may help explore some of the highlighted themes for future work. Our goal is to assist readers to understand the subtleties and challenges in designing NLIs and encourage the community to think further about NLIs for data analysis with visualization.
The Movement-Related Cortical Activities under the Virtual Environment with Force Feedback

Virtual reality (VR) is widely used in the fields of health care. We hypothesis that hand movement with VR simulated scene is similar to actual activity. Nine subjects participated in the study with brain wave monitoring, they used force feedback device to virtual ball catching. We found the brain wave patterns are similar to prior hand movement study, but pattern in the force feedback had longer latency than none force feedback. The results supported virtual reality paradigm can be the part of activity in the real world. We conclude that, movement in the virtual environment and real world had slight difference. Virtual reality can be used as a tool for the motor learning or skill re-acquisition.
Fishing for Clickbaits in Social Images and Texts with Linguistically-Infused Neural Network Models

This paper presents the results and conclusions of our participation in the Clickbait Challenge 2017 on automatic clickbait detection in social media. We first describe linguistically-infused neural network models and identify informative representations to predict the level of clickbaiting present in Twitter posts. Our models allow to answer the question not only whether a post is a clickbait or not, but to what extent it is a clickbait post e.g., not at all, slightly, considerably, or heavily clickbaity using a score ranging from 0 to 1. We evaluate the predictive power of models trained on varied text and image representations extracted from tweets. Our best performing model that relies on the tweet text and linguistic markers of biased language extracted from the tweet and the corresponding page yields mean squared error (MSE) of 0.04, mean absolute error (MAE) of 0.16 and R2 of 0.43 on the held-out test data. For the binary classification setup (clickbait vs. non-clickbait), our model achieved F1 score of 0.69. We have not found that image representations combined with text yield significant performance improvement yet. Nevertheless, this work is the first to present preliminary analysis of objects extracted using Google Tensorflow object detection API from images in clickbait vs. non-clickbait Twitter posts. Finally, we outline several steps to improve model performance as a part of the future work.
Ice-Dammed Lake Drainage Evolution at Russell Glacier, West Greenland

Glaciological and hydraulic factors that control the timing and mechanisms of glacier lake outburst floods (GLOFs) remain poorly understood. This study used measurements of lake level at 15 min intervals and known lake bathymetry to calculate lake outflow during two GLOF events from the northern margin of Russell Glacier, west Greenland. We used measured ice surface elevation, interpolated subglacial topography and likely conduit geometry to inform a melt enlargement model of the outburst evolution. The model was tuned to best-fit the hydrograph rising limb and timing of peak discharge in both events; it achieved Mean Absolute Errors of <5%. About one third of the way through the rising limb, conduit melt enlargement became the dominant drainage mechanism. Lake water temperature, which strongly governed the enlargement rate, preconditioned the high peak discharge and short duration of these floods. We hypothesize that both GLOFs were triggered by ice dam flotation, and localized hydraulic jacking sustained most of their early-stage outflow, explaining the particularly rapid water egress in comparison to that recorded at other ice-marginal lakes. As ice overburden pressure relative to lake water hydraulic head diminished, flow became confined to a subglacial conduit. This study has emphasized the inter-play between ice dam thickness and lake level, drainage timing, lake water temperature and consequently rising stage lake outflow and flood evolution.
Recursive Regularization Filters: Design, Properties, and Applications

Least squares approximation problems that are regularized with specified highpass stabilizing kernels are discussed. For each problem, there is a family of discrete regularization filters (R-filters) which allow an efficient determination of the solutions. These operators are stable symmetric lowpass filters with an adjustable scale factor. Two decomposition theorems for the z-transform of such systems are presented. One facilitates the determination of their impulse response, while the other allows an efficient implementation through successive causal and anticausal recursive filtering. A case of special interest is the design of R-filters for the first- and second-order difference operators. These results are extended for two-dimensional signals and, for illustration purposes, are applied to the problem of edge detection. This leads to a very efficient implementation (8 multiplies+10 adds per pixel) of the optimal Canny edge detector based on the use of a separable second-order R-filter. >
Offline and Online Electric Vehicle Charging Scheduling With V2V Energy Transfer

We propose offline and online scheduling algorithms for the charging of electric vehicles (EVs) in a single charging station (CS). The station has available cheaper, but limited, energy from renewable energy sources (RES). The EVs are capable of and willing to participate in vehicle-to-vehicle (V2V) energy transfers that are used to reduce the charging cost and increase the RES utilization. The algorithms are centralized and aim to minimize the total charging cost for the EVs. We formulate the problem as a mixed integer programming (MIP) one and we solve it optimally assuming full knowledge of the EV demand and energy generation. Later, we propose an online algorithm that iteratively calls the offline one and copes with unknown future interruptions by arriving the EVs and with the inability to predict accurately RES production. In addition, a novel technique called virtual demand is developed that increases the demand of already existing EVs, in order to store renewable energy and later transfer it via V2V to EVs that will arrive at the CS in the future. This technique is used for mitigating the inefficiency due to the uncertainty about future actions that real-time scheduling entails. In a setting with up to 150 EVs and using real data regarding the RES production, our algorithms are shown to have low execution times, while the use of virtual demand increases RES utilization by 12% and reduces cost by 3.3%.