Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Remediation in Psychiatric Disorders: State of the Evidence, Future Perspectives, and Some Bold Ideas

Many people with psychiatric disorders experience impairments in cognition. These deficits have a significant impact on daily functioning and sometimes even on the further course of their disease. Cognitive remediation (CR) is used as an umbrella term for behavioral training interventions to ameliorate these deficits. In most but not all studies, CR has proven effective in improving cognition and enhancing everyday functional outcomes. In this paper, after quickly summarizing the empirical evidence, practical advice to optimize the effects of CR interventions is provided. We advocate that CR interventions should be as fun and motivating as possible, and therapists should at least consider using positively toned emotional stimuli instead of neutral stimuli. Participants should be screened for basic processing deficits, which should be trained before CR of higher-order cognitive domains. CR should stimulate metacognition and utilize natural settings to invoke social cognition. Wherever possible, CR tasks should link to tasks that participants face in their everyday life. Therapists should consider that participants might also benefit from positive side effects on symptomatology. Finally, the CR approach might even be utilized in settings where the treatment of cognitive impairments is not a primary target.
Distributed Fiber-Optic Strain Sensing of an Innovative Reinforced Concrete Beam–Column Connection

Distributed fiber-optic sensing (DFOS) technologies have been used for decades to detect damage in infrastructure. One recent DFOS technology, Optical Frequency Domain Reflectometry (OFDR), has attracted attention from the structural engineering community because its high spatial resolution and refined accuracy could enable new monitoring possibilities and new insight regarding the behavior of reinforced concrete (RC) structures. The current research project explores the ability and potential of OFDR to measure distributed strain in RC structures through laboratory tests on an innovative beam–column connection, in which a partial slot joint was introduced between the beam and the column to control damage. In the test specimen, fiber-optic cables were embedded in both the steel reinforcement and concrete. The specimen was tested under quasi-static cyclic loading with increasing displacement demand at the structural laboratory of the Pacific Earthquake Engineering Research (PEER) Center of UC Berkeley. Different types of fiber-optic cables were embedded both in the concrete and the rebar. The influence of the cable coating and cable position are discussed. The DFOS results are compared with traditional measurements (DIC and LVDT). The high resolution of DFOS at small deformations provides new insights regarding the mechanical behavior of the slotted RC beam–column connection, including direct measurement of beam curvature, rebar deformation, and slot opening and closing. A major contribution of this work is the quantification of the performance and limitations of the DFOS system under large cyclic strains. Performance is quantified in terms of non-valid points (which occur in large strains when the DFOS analyzer does not return a strain value), maximum strain that can be reliably measured, crack width that causes cable rupture, and the effect of the cable coating on the measurements. Structural damage indices are also proposed based on the DFOS results. These damage indices correlate reasonably well with the maximum sustained drift, indicating the potential of using DFOS for RC structural damage assessment. The experimental data set is made publicly available.
Contribution to the numerical simulation of turbulent shock-induced separated flows : Application to supersonic over-expanded nozzles flows

Shock-induced flow separation and reattachment are encountered in many configurations, such as supersonic inlets, transonic airfoils or rocket nozzles. These phenomena involve complex interactions of boundary layers with compression or expansion waves and exhibit a low-frequency unsteady behaviour which still requires a clear explanation. This study aims at better identifying the physical mechanisms which drive the global structure of these flows and suggesting improved numerical tools in order to predict these more accurately. The appearance of free and restricted separations in supersonic annular jets occuring in thrust optimised contour nozzles operating in overexpanded conditions is more particularly investigated while various hypothesis are tested to explain the evolution of the associated unsteady asymmetric wall pressure field in function of the nozzle pressure ratio. The numerical strategy proposed relies on a realizable extension of the Detached Eddy Simulation, combined with high order shock capturing schemes and an implicit time integration algorithm. This methodology is applied for a wide range of both constant or transient inflow conditions and leads to identify more accurately the appearance of free and restricted separations and the time-varying morphology of the flow during the transition process. For both regimes, the simulation is carried out for long-enough time to perform reliable statistical analysis and azimuthal expansion of the wall pressure field and thus investigate extensively the possible origins of the side-load activities.
Random Linear Streaming Codes in the Finite Memory Length and Decoding Deadline Regime—Part I: Exact Analysis

Streaming codes take a string of source symbols as input and output a string of coded symbols in real time, which eliminate the queueing delay of traditional block codes and are thus especially appealing for delay sensitive applications. Existing works on streaming code performance either focused on the asymptotic error-exponent analyses, or on the optimal code construction under deterministic adversarial channel models. In contrast, this work analyzes the exact error probability of random linear streaming codes (RLSCs) in the large field size regime over the stochastic i.i. d. symbol erasure channel model. A closed-form expression of the error probability of large-field-size RLSCs is derived under, simultaneously, the finite memory length and decoding deadline constraints. The result is then used to examine the intricate tradeoff between memory length (complexity), decoding deadline (delay), code rate (throughput), and error probability (reliability). Numerical evaluation shows that under the same code rate and error probability requirements, the end-to-end delay of RLSCs is 40–48% of that of the optimal block codes (i.e., MDS codes). This implies that switching from block codes to streaming codes not only eliminates the queueing delay completely (which accounts for the initial 50% of the delay reduction) but also improves the reliability (which accounts for the additional 2–10% delay reduction).
Knowledge, Attitude and Practice of Osteoporosis among Adult Patients in Bashair Hospital, Sudan, 2021

Osteoporosis is a skeletal disorder distinguished by micro architectural deterioration and rapid bone loss at the osseous tissue, increasing the risk for bone fracture especially at the hip, wrist, and spine. Knowledge, Attitude and Practices (KAP) is a quantitative method that provides access to quantitative and qualitative information. The study aimed to assess the level of Knowledge, Attitude and Practice regarding Osteoporosis among adult patients in Bashair University Hospital 202l. Methodology: This was descriptive cross-sectional hospital-based study conducted in Bashair Hospital 2021. 200 participants were chosen. Data were collected using designed interview questionnaire. Statistical package for social sciences version 26 used for analysis. Results: (53.5%) of participants were females. (33.0%) of participants their level of educational is basic school. (45.2%) of the participants had poor knowledge, (40%) of the participants had poor attitude, and (54%) of the participants had moderate practice about Osteoporosis among adult patients. There was a significant relation between age groups and level of educational regarding Knowledge, Attitude and Practice (p≤ .001). There was a significant relation between Knowledge and Attitude (P<.001) and Knowledge and Practice (P<.001). Conclusion: The study concluded that adult patients had poor knowledge, attitude and moderate practice regarding Osteoporosis. Factors such as age, level of educational and gender were significantly influence the level of knowledge, attitude and practice. Recommendation: Upraise the level of awareness; establish screening programs for community population especially in low socioeconomic areas, regular investigations and at least once for bone scanning regarding Osteoporosis.
Tempting the Fate of the furious: cyber security and autonomous cars

ABSTRACT The United Nations Economic Commission for Europe (UN ECE) has developed new aspects of its WP.29 agreement for harmonising vehicle regulations, focusing on the regulation of vehicle manufacturers’ approaches to ensuring vehicle cyber security by requiring implementation of an approved cyber security management system (CSMS). This paper investigates the background, framework and content of WP.29’s cyber security regulation. We provide an overall description of the processes required to become certified, discuss key gaps, issues and the impacts of implementation on stakeholders, and provide recommendations for manufacturers and the authorities who will oversee the operation. Putting the discussion into a broader theoretical framework on risk certification, we explore to the role of non-academic sources to shape public risk perception and to drive, for better or worse, legislative responses.
Adaptive fuzzy observer-based mismatched faults and disturbance design for singular stochastic T-S fuzzy switched systems

This paper deals with the problem of observer-based mismatched faults for switched singular fuzzy systems subject to disturbances. First, in order to obtain the estimation of unmeasurable or partially measurable states, fuzzy adaptive observer is obtained, eliminating the influence of external disturbances and mismatched faults, simultaneously. Second, by constructing appropriate piecewise Lyapunov functions and average dwell time, the switched singular fuzzy stochastic system with external parameter perturbations and faults is guaranteed to be robustly stable Further, by solving the linear matrix inequalities a sufficient condition to maintain the stability of error dynamic system is presented. Finally, to illustrate the proposed method is available, numerical examples are presented.
An International Retrospective Observational Study of Liver Functional Deterioration after Repeat Liver Resection for Patients with Hepatocellular Carcinoma

Simple Summary For 657 cases of segment or less repeat liver resection with results of plasma albumin and bilirubin levels and platelet counts before and 3 months after surgery, the indicators were compared before and after surgery. There were 268 open repeat after open and 224 cases laparoscopic repeat after laparoscopic liver resection. The background factors and liver functional indicators before and after surgery, and the changes were compared between both groups. Plasma levels of albumin (p = 0.006) and total bilirubin (p = 0.01) were decreased, and ALBI score (p = 0.001) indicated worse liver function after surgery. Though laparoscopic group had poorer performance status and liver function, changes of the values and overall survivals were similar between both groups. Plasma levels of albumin and bilirubin and ALBI score could be the liver functional indicators for liver functional deterioration after liver resection. The laparoscopic group with poorer conditions showed a similar deterioration of liver function and overall survival to the open group. Abstract Whether albumin and bilirubin levels, platelet counts, ALBI, and ALPlat scores could be useful for the assessment of permanent liver functional deterioration after repeat liver resection was examined, and the deterioration after laparoscopic procedure was evaluated. For 657 patients with liver resection of segment or less in whom results of plasma albumin and bilirubin levels and platelet counts before and 3 months after surgery could be retrieved, liver functional indicators were compared before and after surgery. There were 268 patients who underwent open repeat after previous open liver resection, and 224 patients who underwent laparoscopic repeat after laparoscopic liver resection. The background factors, liver functional indicators before and after surgery and their changes were compared between both groups. Plasma levels of albumin (p = 0.006) and total bilirubin (p = 0.01) were decreased, and ALBI score (p = 0.001) indicated worse liver function after surgery. Laparoscopic group had poorer preoperative performance status and liver function. Changes of liver functional values before and after surgery and overall survivals were similar between laparoscopic and open groups. Plasma levels of albumin and bilirubin and ALBI score could be the indicators for permanent liver functional deterioration after liver resection. Laparoscopic group with poorer conditions showed the similar deterioration of liver function and overall survivals to open group.
Dynamics of Changes in pH and the Contents of Free Sugars, Organic Acids and LAB in Button Mushrooms during Controlled Lactic Fermentation

The aim of the study was to assess changes in the basic quality parameters induced by controlled lactic fermentation of fruiting bodies of the button mushroom (Agaricus bisporus). Lactiplantibacillus plantarum 299v with documented probiotic properties and L. plantarum EK3, i.e., an isolate obtained from spontaneously fermented button mushrooms, were used as starter strains. The fruiting bodies of fresh, blanched, and fermented mushrooms were analyzed at different stages of the lactic fermentation process. The content of free sugars (high-performance liquid chromatography with charged aerosol detector method; HPLC-CAD) and organic acids (high-performance liquid chromatography with diode array detector method; HPLC-DAD) was determined both in the mushroom fruiting bodies and in the brine. Five free sugars (ribose, trehalose, sucrose, glucose, and fructose), mannitol, and six organic acids (lactic, malic, succinic, citric, acetic, and fumaric acids) were detected in the samples. Lactic acid dominated in the final products. The starter cultures exhibited varying degrees of utilization of available mushroom sugars and sucrose used as an additional substrate. Sucrose was utilized at a higher rate and in greater amounts by the L. plantarum EK3 isolate. This starter culture was characterized by a significantly higher final amount of produced lactic acid, a lower pH value, and higher numbers of LAB (lactic acid bacteria). These important quality parameters largely determine the stability of fermented products. Based on the analysis results and the high scores in the organoleptic evaluation of the fermented mushrooms, the L. plantarum EK3 isolate can be recommended as an appropriate starter culture for lactic fermentation of mushroom fruiting bodies.
An Empirical Study of Gradient-based Explainability Techniques for Self-admitted Technical Debt Detection

Self-Admitted Technical Debt (SATD) is an intentionally introduced software code comment describing potential defects or other technical debt. Currently, deep learning is widely used in fields such as Natural Language Processing. Deep learning can be used for SATD detection, but there is a class imbalance problem and a large number of easily classified SATD instances that may potentially affect the loss value. As a result, we proposed a weighted focal loss function based on particle swarm to address the problem. Meanwhile, there is no empirical research based on local explanations for SATD detection. We have investigated local interpretation models such as Saliency Maps, Integrated Gradients, which are currently widely used in deep learning, and conducted empirical research for shared data sets. The research results show that our proposed weighted focal loss function can achieve the best performance for SATD detection; our model achieves 12.27%, 5.97%, and 5.62% improvement in Precision, Recall, and AUC compared to the baseline model, respectively; Local explanation models, including Saliency Maps and Integrated Gradients can cover nearly half of the manually labeled paradigms; these two interpretation models can also discover potential new paradigms.
Evaluating Oregon’s Justice Reinvestment Act: An Interrupted Time-Series Regression of State-Level Outcomes

Many jurisdictions across the U.S. have adopted justice reinvestment initiatives (JRIs) as a strategy for reducing the use of incarceration and mitigating large correctional budgets. In spite of this widespread adoption, little empirical research has explored the impacts of justice reinvestment policies. In response, this study employed quasiexperimental, interrupted time-series regression analyses using a decade of monthly court and corrections data to assess if JRI legislation in Oregon was effective. Results show decreased prison usage and recidivism, as well as reveal delayed and significant trend changes for felony jail admissions and community corrections populations as a result of the JRI legislations. A course for future research to further advance understanding of reinvestment and resource reallocation is outlined.
DETERMINANTS INFLUENCING CITIZENS' INTENTION TO USE e-Gov IN THE STATE OF KUWAIT: APPLICATION OF UTAUT

Although Kuwait is known to be one of first countries to develop its information technology infrastructure among Arab countries, its e-government adoption and readiness still fell behind competitive countries in the Gulf region. The current study sheds light over determinants that influence citizens’ intention to use e-government services. The study uses UTAUT model to measure the influence of external determinants over the intention to use. Structural Equation Modelling (SEM) is employed to examine the causal relationship between proposed constructs. A survey involving a total of 317 Kuwaiti citizens who e-government services is conducted and confirmatory factor analysis used to test the hypotheses. In line with previous research, the findings show that effort expectancy, facilitating conditions, social influence and performance expectancy are the factors that affect the citizens’ intention to use e-government services in state of Kuwait. The findings of this research are useful for the decision-makers and servicedesigners to improve e-government services and their accessibility to citizens. The adopted model can be used as a guideline for the implementation of e-government services in state of Kuwait.
CFO and CEO Characteristics and Managerial Accounting Techniques (MAT’s) Usage: An Upper-Echelons Perspective

This research examines the relationship between the individual characteristics of the CEO/CFO and the usage of management accounting techniques (MATs). The essence of Upper Echelons Theory (UET) states that top management characteristics can influence the prediction of organizational outcomes. Based on this statement, we hypothesize that CFO/CEO education, experience and the participation of accountants in the processes of strategic decision making are important determinants in the use of MATs. The analysis of MATs was done based on the IFAC (1998) study, by dividing all MATs into four stages: Stage I: Cost determination and financial control (5 units); Stage II: Information on managerial planning and control (8 units); Stage III: Reduction of waste in business resources (4 units); and Stage IV: Creation of value through effective resource use (9 units). Our empirical analysis is based on a survey of 154 small, medium, and large-sized Kosovar manufacturing enterprises. A Chi-squared test, regression analysis, t-test, and determination coefficients are used for the evaluation of the models performed, as well as to prove the importance of the factors and testing the hypotheses raised in the study. The results of the study showed that the experience of CFO and CEO expressed in years had a positive relationship with the frequency of MATs usage, with the exception of the MATs for the fourth Stage, meaning that the less experienced the executive and financial director, the more frequent the use of the MATs of the fourth Stage. Executive and financial directors of business, economics, and engineering fields tend to use MATs of the second, third, and fourth Stage, compared with those in other fields. Positive connections for the estimated coefficients showed that the higher the involvement of accountants in strategic decision-making processes, the more frequent the use of managerial accounting techniques of Stages I, II, II and IV.
The Learning Transfer System Inventory: Competencies and Performance Among Employees in Sabah Hotel Industry

Background: Employees are one of the important elements in the hotel industry as they are the main assets in providing excellent service quality towards the customers. In order to provide an excellent service, employee training is a very prominent factor. Therefore, the training outcomes should be evaluated to ensure that the training contributed to an increase in competencies and employee performance. Objective: The aim of this paper is to examine the relationship between learning transfer, competencies and performance among employees especially in Sabah hotel industry. Results: The main results indicated that secondary influence and motivation have significant relationship with employee performance. The results also revealed that all transferrelated factors have significant relationship with competencies. Besides that, the results showed that competencies as a mediator has mediation effect on the relationship between transfer-related factors (secondary influence; motivation; environment) and employee performance. Conclusion: This study contributes to the theory of the formation of a new model of learning transfer in which contains the elements of human resource outcomes and also the inclusion of a new variable such as reaction; and secondly, the study contributes to the human resource practices by identifying the importance of factors that will enhance learning transfer in the context of Sabah hotel industry.
Development of a machine learning model for river bed load

Abstract. Prediction of bed load sediment transport rates in rivers is a notoriously difficult problem due to inherent variability in river hydraulics and channel morphology. Machine learning (ML) offers a compelling approach to leverage the growing wealth of bed load transport observations towards the development of a data-driven predictive model. We present an artificial neural network (ANN) model for predicting bed load transport rates informed by 8117 measurements from 134 rivers. Inputs to the model were river discharge, flow width, bed slope, and four bed surface sediment sizes. A sensitivity analysis showed that all inputs to the ANN model contributed to a reasonable estimate of bed load flux. At individual sites, the ANN model was able to reproduce observed sediment rating curves with a variety of shapes without site-specific calibration. This ANN model has the potential to be broadly applied to predict bed load fluxes based on discharge and reach properties alone.