Miracle-dz/UniFAR-FTUs huggingface dataset:
Complete Bug Report Summarization Using Task-Based Evaluation Miss .

A software project's bug reports provide a rich source of information for software Developer in different tasks like understanding multiple aspects of particular defect when working on the project. For interaction with bug reports developers required some text so, in this topic investigated if it is possible to summarize bug reports automatically so that developers can performs their tasks by deliberating short summaries instead of entire bug report. The proposed system deals with existing conversation-based automated summarizers and found that the quality of generated summaries is similar to summaries produced for email threads and other conversations. It also focused on training a summarizer on a bug report corpus which helps to check summaries that are statistically better than summaries produced by existing conversation-based generators. For bug report duplicate detection tasks, system conduct a task based evaluation so the automatic produced bug reports summaries can help a developer for their tasks and save time of study participant. There was no proofs which show that accuracy is become weaken when summaries were used and that most participants preferred working with summaries to working with original bug reports.
Executive Succession Planning: Barriers and Substitutes in Nonprofit Organizations

Predicted shortages of chief executives combined with growing economic and social significance of the nonprofit sector in an increasingly complex operating environment highlight the need for executive succession planning. Accordingly, our research explores factors that may influence executive succession planning in nonprofit and cooperative forms of organizations. Survey data (N = 242) were analyzed using multiple regression analysis. Results suggest both barriers to and substitutes for executive succession planning that help explain the apparent dearth of succession planning efforts in these organizations. A penchant for continuity was found to be a barrier to such planning, while elements of governance quality and internal development were found to substitute for executive succession planning.
Artroplastia total do joelho em artrite reumatóide e osteoartrose

2RESUMO Os autores apresentam uma analise prospectiva, com seguimento a curto prazo, de 40 pacientes (52 joelhos) submetidos a artroplastia total utilizando a protese condilar total com estabilizacao posterior (sistema InsallBurstein). O estudo foi dividido em dois grupos: artrite reumatoide (26 joelhos) e osteoartrose (26 joelhos), no sentido de estabelecer possiveis diferencas de comportamento da artroplastia entre os dois grupos. O tempo de seguimento pos-operatorio variou de seis a 59 meses (media de 26,33 meses). Os resultados excelentes e bons foram de 92,3% para artrite reumatoide e 80,76% para a osteoartrose. Os resultados insatisfatorios (15,38%) estiveram associados a necrose de pele e discencia de sutura (13,46%), soltura asseptica dos componentes (7,69%), infeccao (3,34%) e instabilidade medial (3,84%). O metodo mostrou-se satisfatorio na eliminacao dos sintomas (dor), na correcao das deformidades e instabilidades e na obtencao de boa capacidade funcional. Nao houve diferencas significantes entre os dois grupos (artrite reumatoide e osteoartrose). SUMMARY
mTOR Signaling and Neural Stem Cells: The Tuberous Sclerosis Complex Model

The mechanistic target of rapamycin (mTOR), a serine-threonine kinase, plays a pivotal role in regulating cell growth and proliferation. Notably, a great deal of evidence indicates that mTOR signaling is also crucial in controlling proliferation and differentiation of several stem cell compartments. Consequently, dysregulation of the mTOR pathway is often associated with a variety of disease, such as cancer and metabolic and genetic disorders. For instance, hyperactivation of mTORC1 in neural stem cells (NSCs) is associated with the insurgence of neurological manifestation characterizing tuberous sclerosis complex (TSC). In this review, we survey the recent contributions of TSC physiopathology studies to understand the role of mTOR signaling in both neurogenesis and tumorigenesis and discuss how these new insights can contribute to developing new therapeutic strategies for neurological diseases and cancer.
Intercolor-Filter Crosstalk Model for Image Sensors With Color Filter Array

A color crosstalk model for an area image sensor with a color filter (CF) array is proposed, which quantifies the crosstalk in a physically intuitive manner by introducing “inter-CF optical crosstalk (inter-CF crosstalk). ” The model separates the structural design originated crosstalk from the CF material itself, revealing the sole characteristics of microstructures on a photodiode. A constrained nonlinear estimation is used to solve the model equation of system matrices with an objective function focusing on matching between the modeled quantum efficiency spectra and measured ones at both the peak and crosstalk regions. The model is applied to 1.1- $\mu \text{m}$ backside-illuminated CMOS image sensors having four different kinds of optical structures on the photodiode of the same design, and successfully provides the ground of comparison with excellent matching between the models and the measurement results.
R-Node: New Pipelined Approach for an Effective Reconfigurable Wireless Sensor Node

The pipeline of reconfiguration is a novel approach that gives a decision making mechanism for any system of tasks when several reconfiguration scenarios are required. These scenarios represent the run-time operations that allow automatic functional modification of the system behavior. In the case of their frequent income, the pipeline follows a specific set of steps in order to figure out the scenarios that need to be applied without altering its own performance. The steps are represented by a sequence of modules. The first module checks the availability of the resources needed by the tasks. The second maintains the stability by rejecting any insupportable flow of software reconfigurations that can destabilize a system. The third module checks the availability of memory for each software reconfiguration request, whereas the fourth verifies the availability of energy for the execution of a new system software configuration. The last module checks the schedulability of this configuration by changing the priorities of the finally accepted tasks in order to reduce their response and blocking times, and to meet their deadlines. The feasibility of the reconfiguration through this approach allows its implementation in wireless sensor nodes. Known by their important requirements in terms of memory and energy, this proposition is adequate when it comes to guaranteeing a maximum lifespan of the nodes. Therefore, the pipeline of reconfiguration is integrated as a middleware within the software architecture of a node. The functionality of this middleware is coordinated by the mean of a set of threads that manage the communication between the pipeline of reconfiguration and the operating system. A tool has been developed within LISI Laboratory to encode this proposition and show its impact on a large range of real devices under diversified scenarios of reconfigurations.
Isolation of state-dependent monoclonal antibodies against the 12-transmembrane domain glucose transporter 4 using virus-like particles

Significance Generating mAbs against the native extracellular epitopes of multispanning membrane proteins is challenging, and as a result, few nonpeptidic mAbs against transporters have ever been isolated. Our approach here using virus-like particles and divergent host species for immunizations provides a means to overcome these challenges. The specific mAbs isolated here recognize native GLUT4 on the cell surface and can distinguish its different conformational states, thus representing some of the only state-specific mAbs ever isolated against any transporter. Epitope mapping of these mAbs revealed their binding sites as well as the mechanisms by which amino acids control the inward-open and outward-open states of GLUT4. Our studies demonstrate a valuable platform to isolate functional mAbs against important multispanning membrane proteins. The insulin-responsive 12-transmembrane transporter GLUT4 changes conformation between an inward-open state and an outward-open state to actively facilitate cellular glucose uptake. Because of the difficulties of generating conformational mAbs against complex and highly conserved membrane proteins, no reliable tools exist to measure GLUT4 at the cell surface, follow its trafficking, or detect the conformational state of the protein. Here we report the isolation and characterization of conformational mAbs that recognize the extracellular and intracellular domains of GLUT4, including mAbs that are specific for the inward-open and outward-open states of GLUT4. mAbs against GLUT4 were generated using virus-like particles to present this complex membrane protein in its native conformation and using a divergent host species (chicken) for immunization to overcome immune tolerance. As a result, the isolated mAbs recognize conformational epitopes on native GLUT4 in cells, with apparent affinities as high as 1 pM and with specificity for GLUT4 across the human membrane proteome. Epitope mapping using shotgun mutagenesis alanine scanning across the 509 amino acids of GLUT4 identified the binding epitopes for mAbs specific for the states of GLUT4 and allowed the comprehensive identification of the residues that functionally control the GLUT4 inward-open and outward-open states. The mAbs identified here will be valuable molecular tools for monitoring GLUT4 structure, function, and trafficking, for differentiating GLUT4 conformational states, and for the development of novel therapeutics for the treatment of diabetes.
Time-dependent and independent effects of thyroid hormone administration following myocardial infarction in rats

Cardiac function is reduced following myocardial infarction (MI) due to myocardial injury and alterations in the viable non-ischemic myocardium, a process known as cardiac remodeling. The current treatments available for patients with acute MI (AMI) reduce infarct size, preserve left ventricular (LV) function and improve survival; however, these treatments do not prevent remodeling, which can lead to heart failure. The aim of the present study was to investigate the effects of thyroid hormone (TH) treatment following MI in an in vivo rat model. A total of 199 rats were separated into 3 groups: Sham operated and 2 different coronary artery ligation (CAL) groups. Rats subjected to CAL were randomly divided into a further 2 groups 24 h following surgery. The first group received standard rat chow (designated the CAL group), while the second group received food containing 0.05% thyroid powder (designated the CALTH group). The mean daily intake of TH per rat was estimated at 3.0 µg T3 and 12 µg T4. Echocardiography was used to monitor the rats. Large-scale analysis confirmed the favorable effects of TH treatment following CAL on various parameters of cardiac function. TH treatment reduced LV dilation, and increased global and regional LV function. The development of cardiac hypertrophy was induced and, thus, wall stress was limited. Furthermore, TH treatment improved cardiac geometry, which manifested as an increased sphericity index. Myocardial function, as well as LV dilatation, following CAL and TH treatment was not closely associated with the extent of injury, indicating a novel therapeutic intervention that may alter the course of LV remodeling that typically leads to post-MI heart failure. Data modelling and regressions may be developed to enable the simulation of the pathophysiological processes that occur following MI, and to predict with accuracy the effects of novel or current treatments that act via the modulation of tissue injury, LV dilation, LV geometry and hypertrophy.
New Horizons in the Treatment of Type 1 Diabetes: More Intense Immunosuppression and Beta Cell Replacement

Since the discovery of autoimmunity as the main pathophysiologic process involved in type 1 diabetes, many attempts have tried to delay or stop beta cell destruction. Most research protocols in humans have investigated the effects of therapeutic agents targeting specific steps of the autoimmune response. In spite of safety and some degree of beta cell preservation, the clinical impact of such approaches was similar to placebo. Recently, research groups have analyzed the effects of a more intense and wider immunologic approach in newly diagnosed type 1 diabetic individuals with the “immunologic reset,” i.e., high-dose immunosuppression followed by autologous hematopoietic stem cell transplantation. This more aggressive approach has enabled the majority of patients to experience periods of insulin independence in parallel with relevant increments in C-peptide levels during mixed meal tolerance test. However, on long-term follow-up, almost all patients resumed exogenous insulin use, with subsequent decrease in C-peptide levels. This has been at least in part explained by persistence of islet-specific T-cell auto-reactivity. Here, we discuss future steps to induce immune tolerance in individuals with type 1 diabetes, with emphasis on risks and possible benefits of a more intense transplant immunosuppressive regimen, as well as strategies of beta cell replacement not requiring immunomodulation.
Prognostic and diagnostic impact of fibrinogen, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio on thymic epithelial tumors outcome

Background Peripheral blood-derived inflammation-based markers, such as Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Fibrinogen have been identified as prognostic markers in various solid malignancies. Here we aimed to investigate the prognostic and diagnostic impact of NLR, PLR, and Fibrinogen in patients with thymic epithelial tumors (TETs). Results Pretreatment Fibrinogen serum concentrations, NLRs and PLRs were highest in patients with TCs and advanced tumor stages. High pretreatment Fibrinogen serum concentration (≥452.5 mg/dL) was significantly associated with worse cause specific survival (CSS; p = 0.001) and freedom from recurrence (FFR; p = 0.043), high NLR (≥4.0) with worse FFR (p = 0.008), and high PLR (≥136.5) with worse CSS (p = 0.032). Longitudinal analysis revealed that compared to patients without tumor recurrence, patients with tumor recurrence had significantly higher NLR (11.8 ± 4.0 vs. 4.70 ± 0.5; p = 0.001) and PLR (410.8 ± 149.1 vs. 228.3 ± 23.7; p = 0.031). Conclusion Overall, Fibrinogen serum concentrations, NLRs, and PLRs were associated with higher tumor stage, more aggressive tumor behavior, recurrence, and worse outcome. Prospective multicenter studies of the diagnostic and prognostic potential of Fibrinogen, NLR, and PLR are warranted. Methods This retrospective analysis included 122 patients with TETs who underwent surgical resection between 1999-2015. Fibrinogen serum concentrations, NLRs, and PLRs were measured in patients preoperatively, postoperatively, and later during follow-up. These markers were analyzed for association with several clinical variables, including tumor stage, tumor subtype, FFR, and CSS and to evaluate their prognostic and diagnostic impact for detecting tumor recurrence.
Software Code Smell Prediction Model Using Shannon, Rényi and Tsallis Entropies

The current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality and reliability of software. Source code of the open source software is easily accessible by any developer, thus frequently modifiable. In this paper, we have proposed a mathematical model to predict the bad smells using the concept of entropy as defined by the Information Theory. Open-source software Apache Abdera is taken into consideration for calculating the bad smells. Bad smells are collected using a detection tool from sub components of the Apache Abdera project, and different measures of entropy (Shannon, Rényi and Tsallis entropy). By applying non-linear regression techniques, the bad smells that can arise in the future versions of software are predicted based on the observed bad smells and entropy measures. The proposed model has been validated using goodness of fit parameters (prediction error, bias, variation, and Root Mean Squared Prediction Error (RMSPE)). The values of model performance statistics (R2, adjusted R2, Mean Square Error (MSE) and standard error) also justify the proposed model. We have compared the results of the prediction model with the observed results on real data. The results of the model might be helpful for software development industries and future researchers.
Psychometric Properties of Dispositional Hope Scale for Brazilian Sport Context

Abstract This study investigated the psychometric properties of the Dispositional Hope Scale (DHS) for the Brazilian sport context. The sample for construct validity consisted of 474 athletes; internal validity was assessed with 101 athletes; and external validity was tested in 81 athletes, from which, were 55 had further participated in the temporal stability assessment. Data analysis was conducted through the following tests: Cronbach’s alpha, Composite Reliability (CR), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Spearman Correlation Coefficient and intraclass correlation. Results had shown that the DHS presents satisfactory internal consistency (.79 ≤ α ≤ .83; .58 ≤ r ≤ .75). The EFA model revealed a two-factor solution to be the most adequate, while CFA confirmed such model (χ2= 59.88; p< .001; χ2/df = 3.15; CFI = .90; AGFI = .94; TLI = .90; RMSEA = .07 CI [.05, .08]). The hope dimensions were positively correlated with Self-esteem (r > .50). Temporal stability was achieved (ICC > .70). It was concluded that the DHS is a valid measure for the assessment of hope in Brazilian sports context; this instrument has potential practical applications for professionals working with Sport Psychology.
Unilateral spatial neglect in the acute phase of ischemic stroke can predict long-term disability and functional capacity

OBJECTIVE: The aim of this study was to assess the relationship between the degree of unilateral spatial neglect during the acute phase of stroke and long-term functional independence. METHODS: This was a prospective study of right ischemic stroke patients in which the independent variable was the degree of spatial neglect and the outcome that was measured was functional independence. The potential confounding factors included sex, age, stroke severity, topography of the lesion, risk factors, glycemia and the treatment received. Unilateral spatial neglect was measured using the line cancellation test, the star cancellation test and the line bisection test within 48 hours of the onset of symptoms. Functional independence was measured using the modified Rankin and Barthel scales at 90 days after discharge. The relationship between unilateral spatial neglect and functional independence was analyzed using multiple logistic regression that was corrected for confounding factors. RESULTS: We studied 60 patients with a median age of 68 (34–89) years, 52% of whom were male and 74% of whom were Caucasian. The risk for moderate to severe disability increased with increasing star cancellation test scores (OR=1.14 [1.03–1.26], p=0.01) corrected for the stroke severity, which was a confounding factor that had a statistically positive association with disability (OR=1.63 [1.13–2.65], p=0.01). The best chance of functional independence decreased with increasing star cancellation test scores (OR=0.86 [0.78–0.96], p=0.006) corrected for the stroke severity, which was a confounding factor that had a statistically negative association with independence (OR=0.66 [0.48–0.92], p=0.017). CONCLUSION: The severity of unilateral spatial neglect in acute stroke worsens the degree of long-term disability and functional independence.
A web-based framework for the evaluation of predictive process monitoring techniques

Business process management (BPM) focuses on optimizations of various activities within the organization, with respect to key performance indicators (KPI). An important task among BPM-related activities is process monitoring which aims to make sure that business processes comply with KPIs. Process monitoring can be performed either offline, using historical data to analyze process execution in the past or online, i.e. analyzing event streams in real-time to identify the problems as soon as they arise. Predictive monitoring is an emerging type of online process monitoring that uses historical data to construct a predictive model using various machine learning methods and then applies this model to a live event stream in order to predict the future performance of ongoing process cases. Various techniques have been proposed to address typical predictive monitoring problems, such as whether this ongoing case will finish on time or what activity will be executed next in the case. Even though many of these techniques have publicly available software implementations, they typically target one specific predictive monitoring problem. Furthermore, due to variations in evaluation procedures (different data splits, different evaluation metrics reported, etc.), users do not have a readily available way to compare predictive accuracy across multiple techniques. Finally, such solutions are targeting experienced users and also consume a lot of users hardware resources to run the simulations. In this thesis, we have built a web application that allows users with various degrees of expertise in the subject to train, validate and compare models to predict multiple KPIs, using a wide range of predictive monitoring techniques proposed in related work. Moreover, the models can be exported for further use. This application runs all of the computations on the server side, thus eliminating the need for the powerful hardware to construct the models. We compare our solution with existing implementations and highlight clear distinctions and differences.
Vital-SCOPE: Design and Evaluation of a Smart Vital Sign Monitor for Simultaneous Measurement of Pulse Rate, Respiratory Rate, and Body Temperature for Patient Monitoring

Consistent vital sign monitoring is critically important for early detection of clinical deterioration of patients in hospital settings. Mostly, nurses routinely measure and document the primary vital signs of all patients 2‐3 times daily to assess their condition. To reduce nurse workload and thereby improve quality of patient care, a smart vital sign monitor named “Vital‐SCOPE” for simultaneous measurement of vital signs was developed. Vital-SCOPE consists of multiple sensors, including a reflective photo sensor, thermopile, and medical radar, to be used in simultaneous pulse rate, respiratory rate, and body temperature monitoring within 10 s. It was tested in laboratory and hospital settings. Bland-Altman and Pearson’s correlation analyses were used to compare the Vital-SCOPE results to those of reference measurements. The mean difference of the respiratory rate between respiratory effort belt and Vital-SCOPE was 0.47 breaths per minute with the 95% limit of agreement ranging from −7.4 to 6.5 breaths per minute. The Pearson’s correlation coefficient was 0.63 ( ). Moreover, the mean difference of the pulse rate between electrocardiogram and Vital-SCOPE was 3.4 beats per minute with the 95% limit of agreement ranging from −13 to 5.8 beats per minute; the Pearson’s correlation coefficient was 0.91 ( ), indicating strong linear relationship.