Miracle-dz/UniFAR-FTUs huggingface dataset:
Portuguese validation of the Regret Intensity Scale (RIS-10) for measuring the intensity of regret associated with the provision of attention in health

Abstract Objective: The aim of the study was to adapt and validate the Regret Intensity Scale-10 (RIS-10) for Brazilian health professionals. Methods: The validation study took place in two phases, in which the first was the translation of the instruments and the second, the field validation using psychometric properties validity and reliability of the scale with 341 professionals (doctors, nurses and physiotherapists) linked to hospitals. Validity was assessed using content validities (six judges evaluation), criteria (correlation with the Life Satisfaction Scale - SWLS and Self-Reporting Questionnaire 20 -SRQ-20) and construct (exploratory analysis using the rotation method Promax, based on the slope graph and the Kaiser criterion and confirmatory using the structural equation model) after applying the questionnaire to professionals.Reliability was measured by Cronbach's α coefficient and retest test over a maximum period of 30 days. Reproducibility was calculated by intraclass correlation. Results: A total of 341 professionals participated, with an average age of 38.6 ± 9.2 years. The content validity index (CVI) was 1.00, for all items of the scale in the proportion of agreement of the judges. Exploratory factor analysis showed a satisfactory correlation (Kaiser-Meyer-Olkin = 0.88), suggesting a two-factor model, which comprises the main components of the emotion of regret (Factor I - emoticons, Factor II - feelings), accounting for 64% of the total variation of the first factor. In the confirmation, the index standardized root mean squared residual = 0.063 was close to the acceptable and other values were below. The scale correlated positively with SRQ-20 (p < 0.001) and negatively with SLWS (p = 0.003). Reliability showed (Cronbach’s α = 0.863) and test-retest reliability showed lower values than expected. The Bland-Altman graph showed a mean bias of -1.5 with lower and upper limits of 15.8 to 12.8 respectively. Conclusion: The RIS-10 adapted for the population performed adequately in the psychometric properties evaluated for the assessment of the intensity of regret related to the provision of health care.
"Nutritional Therapies for Patients with Physical Disabilities: A Systematic Review"

The aim of this study was designed to evaluate the scientific evidence of studies that refer to nutritional therapies, whether they originate from diet or supplementation, or through directions and their effects on the health of people with physical disabilities. The PubMed and Scopus databases were used. The terms used for the search and its variations were diet* or “nutrition therapy” and disabled persons. This systematic review consisted of 8 articles with experimental and observational design, related to vitamin D and caffeine supplementation, weight loss programs, aspects of the diet of physically disabled individuals and their eating behaviors. The articles showed that vitamin D supplementation increased their serum levels even in the winter; caffeine supplementation provided an ergogenic effect; weight loss programs were effective in assisting the physically disabled as to changing their diet and practicing exercise. Thus, adequate nutritional therapies are effective in improving the health of people with physical disabilities. Abbreviations: PD: Physical Disability; LS: Sedentary Lifestyle; RS: Systematic Review; PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyzes; IU: International Units; SCI: Spinal Cord Injury Nutritional Therapies for Patients with Physical Disabilities: A Systematic Review. Biomed J Sci & Tech Res 37(4)-2021. BJSTR. MS.ID. 006023.
Assay development in leishmaniasis drug discovery: a comprehensive review

ABSTRACT Introduction Cutaneous, muco-cutaneous and visceral leishmaniasis occur due to an infection with the protozoan parasite Leishmania. The current therapeutic options are limited mainly due to extensive toxicity, emerging resistance and variation in efficacy based on species and strain of the Leishmania parasite. There exists a high unmet medical need to identify new chemical starting points for drug discovery to tackle the disease. Areas covered The authors have highlighted the recent progress, limitations and successes achieved in assay development for leishmaniasis drug discovery. Expert opinion It is true that sophisticated and robust phenotypic in vitro assays have been developed during the last decade, however limitations and challenges remain with respect to variation in activity reported between different research groups and success in translating in vitro outcomes in vivo. The variability is not only due to strain and species differences but also a lack of well-defined criteria and assay conditions, e.g. culture media, host cell type, assay formats, parasite form used, multiplicity of infection and incubation periods. Thus, there is an urgent need for more physiologically relevant assays that encompass multi-species phenotypic approaches to identify new chemical starting points for leishmaniasis drug discovery.
Broken rotor bars: their effect on the transient performance of induction machines

Around 10% of failures in cage induction motors are on the rotor. Problems result from defective castings in die-cast rotors, or from high resistance joints as a result of poor welding or brazing in fabricated cages. In such cases uneven bar stress is then unavoidable. Often, however, failure occurs due to fracture of bars caused by fatigue. This is common in machines with uneven and heavy duty cycles, which consequently are subject to high stress in the cage during periods of rapid braking and acceleration. Some success has been achieved in the development of techniques to identify bar failure, or high resistance joints, even on operational machines. The majority of techniques depend upon detecting a twice-slip frequency modulation in speed, torque or stator current by analysing an appropriate frequency spectrum. As yet, there is still no universally effective procedure for the early detection of such conditions. In this contribution, rotor parameters are evaluated allowing for current redistribution in the damaged rotor cage, and for the concomitant changes in resistance which result. Based upon this, a modified model of the induction machine, which includes the effect of broken rotor bars, and which will represent both transient and steady state behaviour, is developed. Experimental and calculated results compare the transient performance of the healthy and faulty machines.
Flying cars and bigots: projecting post-COVID-19 worlds through the atlas of the civic imagination as refuge for hope

ABSTRACT In April 2020, the Civic Imagination Project at the University of Southern California, funded by the MacArthur Foundation, asked participants around the world to share some of their reflections on what the world of 2060 might look like, and what roles the COVID-19 pandemic may have played in transforming how we live and relate to each other. For the past six years, the Civic Imagination Project has been conducting world-building workshops with groups across America and around the world. Our workshops encourage participants to imagine together what the future might look like under the premise that before we can change the world, we have to be able to collectively imagine what a better world looks like. For this paper, our team draws tools from speculative fiction to create a process where communities come together and propose what an alternative world might look like. While it is still too early for any preliminary analysis, we anticipate being able to map responses from many different parts of the world, and in particular, across different regions in the United States. We are interested in the tensions amongst utopian, dystopian, protopian and heterotopian visions at a time of enormous anxiety.
Reduction of common mode currents in PWM inverter motor drives

Modern PWM inverter motor drives are affected by dangerous common mode currents due to the high rate of variation of the modulated voltage. An inexpensive alternative to low pass filters which are normally used to limit common mode currents, consists in reducing such currents by using suitable modulation strategies. In the present paper a new approach for designing PWM strategies is presented able to reduce common mode currents by limiting the amount of variations of the common mode voltage. The main characteristics of the proposed approach are experimentally evaluated on a standard PWM induction motor drive.
N-glycosylation of somatostatin receptor type 2 protects rats from acute pancreatitis

Background The growth hormone inhibitor somatostatin and its analogs are promising therapeutic agents for acute pancreatitis. However, the therapeutic effects remain controversial. Somatostatin analogs preferentially bind to somatostatin receptor 2 (SSTR2), and this study aimed to investigate whether N-glycosylation affects SSTR2 stability, membrane trafficking, and signal transduction. Methods Western blot analysis following PNGase F digestion was performed to confirm N-glycosylation of SSTR2 in rat pancreatic acinar AR42J cells. Rats were subjected to 4 hourly intraperitoneal injections of cerulein (50 µg/kg) plus LPS (5 µg/mL) to induce acute pancreatitis. Mass spectrometry was conducted to identify the glycosylation sites of SSTR2, and immunofluorescent staining was carried out to examine the localization of wild-type and asparagine 9 (N9)Q-mutant SSTR2. Proteasome inhibitor MG132 was employed to assess the stability of SSTR2, and overexpression of wild-type or N9Q-mutant SSTR2 was used to examine the role of N-glycosylation in SSTR2 signal transduction in vitro and its therapeutic effect on pancreatitis in rats. Results SSTR2 protein in AR42J cells was N-glycosylated at the N9 residue. Wild-type SSTR2 localized in the plasma membrane whereas N9Q-mutant SSTR2 was retained in the endoplasmic reticulum (ER). MG132 rapidly restored the ectopic expression of mutant but not wild-type SSTR2 protein in AR42J cells. Overexpression of wild-type but not N9Q-mutant SSTR2 activated NF-κB signaling and facilitated nuclear transportation of p65 in AR42J cells upon cerulein plus LPS stimulation. Furthermore, pretreatment with wild-type but not N9Q-mutant SSTR2-overexpressing vectors significantly ameliorated biochemical parameters and pancreatic histological impairments in rats with pancreatitis. Conclusions N-glycosylation of SSTR2 is essential for membrane localization, stability, and signal transduction of SSTR2 in pancreatic cells, playing a protective role in experimental acute pancreatitis.
Insulin resistance quantified by the value of HOMA-IR and cardiovascular risk in patients with type 2 diabetes

Cardiovascular disease (CVD) is recognized as a leading cause of death worldwide. Obesity, dyslipidemia, insulin resistance (IR), interconnected pathological conditions constitute risk factors that are closely associated with CVD. The aim of the present study was to highlight the association of IR with cardiovascular risk (CVR). The epidemiological, cross-sectional, non-interventional study was conducted over 12 months (2019-2020) within a research grant and included a sample of 400 subjects divided into 2 subgroups: group 1 (control) subjects did not have diabetes (n=200) and group 2 had type 2 diabetes (T2DM) (n=200). The Framingham risk score (FRS) was calculated according to the 2008 general CVD risk model from the Framingham Heart Study. Subsequent to a correlation of the value of homeostasis model assessment of insulin resistance (HOMA-IR) with the degree of CVR, the IR was higher in both groups, and CVR also increased. After being quantified by the Spearman correlation coefficient, the correlation in group 2 was higher at 0.625 compared to group 1 where this coefficient had a value of 0.440. A high FRS (FRS of 20%) was significantly associated with IR. The results therefore show that HOMA-IR is an independent risk factor for high FRS. New therapies focused on decreasing IR may contribute to decreased CVD.
Clock and carrier recovery in high-speed coherent optical communication systems

In this paper, the implementations of clock and carrier recovery in digital domain are analyzed. Hardware implementation details, resources estimation and real-time results are presented. Analog-to-Digital Converters (ADC), operating at 1.25Gsa/s, and a Virtex-6 Field-Programmable Gate Array (FPGA), have been used, allowing the implementation of a real-time Quadrature Phase Shift Keying (QPSK) system operating at 1.25Gb/s. The real-time mode operation is successfully demonstrated over 80 km of Standard Single Mode Fiber (SSMF).
The Effect of Good Corporate Governance on the Market Value of Financial Sector Companies in Indonesia

Corporate governance is an interesting topic to discuss recently. Governance builds trust and predictability, hence generating comfort to investors. Companies that implement good corporate governance are expected to have a good financial performance to minimize agency problems and provide more benefits to shareholders. A corporate governance framework can determine the agency problem and its effect on shareholders' value. This study uses a random effect model estimation method. Good corporate governance in this study is measured with the corporate governance index (CGI) score and formed based on five sub-indexes. The company's market value is calculated by Tobin's Q ratio. The results of statistical tests show a positive relationship between the implementation of good corporate governance and its market value. Furthermore, this research shows how Indonesian banks listed in IDX from 2010 to 2019 implement good corporate governance practices as the index continues to increase every year.
A Comparative Study on Inverse Analysis in A Deep Drawing Process

Inverse analysis (IA) is a systematical means in determining an optimal blank configuration for a deep drawing process. In this paper, IA is explored by using a commercial finite element software package. A number of numerical studies on the effect of blank configurations to the part quality in a deep drawing process were conducted and compared. The quality of the drawing processes is numerically analyzed by using an incremental explicit nonlinear finite element code. The initial blank configuration has shown that it plays an important role in the quality of the product. However, it is observed that if the blank configuration is not greatly deviated from the one obtained from IA, the blank still can result a good product. In conclusion, IA has presented its important role in the systematical design process for deep drawing processes.
Fashion industry perceptions of clothing design for persons with a physical disability: the need for building partnerships for future innovation

ABSTRACT Introduction: Persons with a physical disability may need adapted clothing to facilitate their full participation in society; it is unclear what information designers use to create adapted clothing. Objective: Explore the perspectives of fashion industry representatives regarding adapted clothing and gauge their receptiveness towards academic inquiry. Methods: Semi-structured interviews with five female adapted clothing designers were conducted, transcribed verbatim, coded, and analyzed thematically. Results: Participants felt research (i.e. knowledge and guidance) could benefit the design process and spoke about industry barriers (e.g. time, manufacturing, human and material resources, marketing, level of importance) to designing adapted clothing. Conclusions: Strengthening collaborations with stakeholders (e.g. researchers, designers, consumers, health professionals, caregivers) may add credibility to future adapted clothing designs and bridge the gap between research and practice. Engagement from fashion design trainees could also contribute to growing a more socially responsible industry.
Evaluation of Ofloxacin and Ornidazole as an Adjunct to Scaling and Root Planing in the Treatment of Generalized Chronic Periodontitis: A Randomized Clinical Study

bstrAct Aim and objective: Over the years, treatment for chronic periodontitis is changing owing to an improved understanding of the pathogenesis of the periodontal disease. Tissue invasive properties of periodontal pathogens have necessitated the use of antimicrobial agents as an adjunct to mechanical plaque control in the treatment of periodontitis. Hence, the study aimed to evaluate the efficacy of ofloxacin–ornidazole combination therapy as an adjunct to scaling and root planing in the treatment of generalized chronic periodontitis. Materials and methods: A total of 40 study participants, aged from 25 to 55 years, with generalized chronic periodontitis were selected. They were randomly divided into two groups—Group I: receiving scaling and root planing along with ofloxacin–ornidazole combination therapy and group II: receiving scaling and root planing. Gingival index (GI), sulcular bleeding index (SBI), and probing pocket depth (PPD) scores were recorded at baseline, 14th day, and after 1 month. Results: Both the groups showed a reduction in GI scores, SBI scores, and mean pocket probing depth from baseline to 14th day and 1 month. However, the improvement in scores was better in a group with the ofloxacin–ornidazole combination, than the group with scaling and root planing alone. The intergroup comparison of the gingival indices, SBI, and mean pocket probing depth at baseline, 14th day, and 1 month have shown the statistically significant difference. Conclusion: It can be concluded that ofloxacin–ornidazole combination therapy is well tolerated by the patients, safe, favorable patient compliance, and proved to be effective in patients with generalized chronic periodontitis when used as an adjunct to mechanical plaque control. Clinical significance: Ofloxacin–ornidazole combination can be used as an adjuvant in the treatment of generalized chronic periodontitis.
An inverse technique to evaluate permittivity of material in a cavity

A numerical technique to estimate the dielectric constant and loss factor of a homogeneous dielectric material placed in an arbitrary shaped cavity has been developed. The values of S-parameters are measured experimentally by placing the sample in the cavity. Starting with a trial set of permittivity values, the computation is carried out using the finite-element method (FEM) to match the S-parameters around the fundamental resonance frequency. The FEM routine is run several times while optimizing the values of dielectric constant and conductivity of the sample. During the process of optimization, eight different measures of error between computed and experimental values of complex S-parameters are examined. It is found that there is no single measure of error, which can be minimized to estimate two parameters (dielectric constant and the loss factor), but the combination of errors has to be minimized to get the exact solution. The computer program can generate the solution with an accuracy of less than 0.01% in a few hours on a Pentium-based personal computer.
Optimising power transmission and distribution networks using optical fibre distributed temperature sensing systems

The use of distributed temperature sensing systems for temperature monitoring of buried and sub-sea cables has been well proven in many applications over ten years. Extending the use of these systems to other critical assets will provide an opportunity to manage networks more effectively. Utilising assets in this way reduces the need for reinforcement, releases capital for other infrastructure projects and minimises environmental disturbance.
Supervised Learning Algorithm for Multilayer Spiking Neural Networks with Long-Term Memory Spike Response Model

As a new brain-inspired computational model of artificial neural networks, spiking neural networks transmit and process information via precisely timed spike trains. Constructing efficient learning methods is a significant research field in spiking neural networks. In this paper, we present a supervised learning algorithm for multilayer feedforward spiking neural networks; all neurons can fire multiple spikes in all layers. The feedforward network consists of spiking neurons governed by biologically plausible long-term memory spike response model, in which the effect of earlier spikes on the refractoriness is not neglected to incorporate adaptation effects. The gradient descent method is employed to derive synaptic weight updating rule for learning spike trains. The proposed algorithm is tested and verified on spatiotemporal pattern learning problems, including a set of spike train learning tasks and nonlinear pattern classification problems on four UCI datasets. Simulation results indicate that the proposed algorithm can improve learning accuracy in comparison with other supervised learning algorithms.
Importance of Machine Learning in Making Investment Decision in Stock Market

Executive Summary Predicting stock trends in the financial market is always demanding but satisfying as well. With the growing power of computing and the recent development of graphics processing unit and tensor processing unit, analysts and researchers are applying advanced techniques such as machine learning techniques more and more to predict stock price trends. In recent years, researchers have developed several algorithms to predict stock trends. To assist investors interested in investing in the stock market, preferably for a short period, it has become necessary to review research papers dealing on machine learning and analyse the importance of their findings in the context of how stock price trends generate trading signals. In this article, to achieve the stated task, authors scrutinized more than 50 research papers focusing on various machine learning algorithms with varied levels of input variables and found that though the performance of models measured by root-mean-square error (RMSE) for regression and accuracy score for classification models varied greatly, long short-term memory (LSTM) model displayed higher accuracy amongst the machine and deep learning models reviewed. However, reinforcement learning algorithm performance measured by profitability and Sharpe ratio outperformed all. In general, traders can maximize their profits by using machine learning instead of using technical analysis. Technical analysis is very easy to implement, but the profit based on it can vanish too soon or making a profit using technical analysis is almost difficult because of its simplicity. Hence, studying machine, deep and reinforcement learning algorithms is vital for traders and investors. These findings were based on the literature review consolidated in the result section.