Miracle-dz/UniFAR-FTUs huggingface dataset:
Fear Perception of the COVID-19 Pandemic in Peru

Introduction: Fear is a natural response to something unknown. In the current scenario, it is important to assess it in relation to the coronavirus disease-19 (COVID-19) pandemic in Latin American countries. Objective: To determine the fear perception according to factors associated with the COVID-19 pandemic in Peru. Methods: An analytical cross-sectional study was conducted based on a virtual questionnaire. The main question was “how much fear people had of COVID-19? ”, using a scale from zero (without fear) to 10 (very fear). This scale was divided into tertiles, and the upper tertile was the reference category (compared to the middle and lower tertiles). Statistical significances between fear perception of COVID-19 and sociodemographic data were calculated. Results: A total of 3887 participants responded the questionnaire about fear perception. In the multivariate analysis was found that women (adjusted prevalence ratio (aPR): 1.37; 95% confidence interval (CI) : 1.26-1.48; p<0.001), people aged 20-29 (aPR: 1.84; 95% CI: 1.06-1.50; p=0.005), 30-39 (aPR: 1.53; 95% CI : 1.28-1.82; p<0.001), 50-59 (aPR: 1.43; 95% CI: 1.12-1.84; p=0.005), and with 60 or more years (aPR: 1.46; 95% CI: 1.03-2.07; p=0.032), as well as respondents who had some risk for complications due to COVID-19 (aPR: 1.49; 95% CI: 1.32-1.69; p<0.001) were very afraid of the disease. On the other hand, people affiliated with evangelical religions (aPR: 0.79; 95% CI: 0.65-0.96; p=0.018), agnostics (aPR: 0.80; 95% CI: 0.68-0.94; p=0.008), atheists (aPR: 0.67; 95% CI: 0.48-0.95; p=0.024), and health professionals (aPR: 0.81; 95% CI: 0.70-0.93; p=0.003) were less afraid of COVID-19. Conclusion: There was a notorious fear perception of the COVID-19 pandemic by the Peruvian population. In this context, the fear was associated with important variables. Thus, the provision of further emotional support services for this population should be considered in the face of the current pandemic.
Prevalence of Obesity in Inguinal Hernia Repair Patients in a Tertiary Care Center

ABSTRACT Introduction: Inguinal hernia is a common surgical problem, with a lifetime risk of 27% in men and 3% in women. Its cumulative incidence is 17.2% and 12.3% in body mass index of <25 kg/m2 and 25-30 kg/m2 respectively. Obesity had been regarded as the risk factor for the development of an inguinal hernia. However, recent epidemiologic studies have suggested the decreased prevalence of inguinal hernia in increased weight and body mass index individuals. The aim of this study is to find out the prevalence of obesity in inguinal hernia repair patients in a tertiary care center. Methods: A descriptive cross-sectional observational study was performed in Bir Hospital from May 2018 to December 2019 after taking ethical approval from the institutional review board of NAMS. Convenient sampling was done with a sample size of 219. Statistical analysis was done using SPSS ver. 23 and Microsoft Excel software by descriptive statistics. Results: The mean body mass index was 22.10 ±3.07 kg/m2. Body mass index Category 18.5 - 22.9 kg/m2 had 133 (61%) male and seven (3.2%) female patients, category ≥30 kg/m2 had four (1.8%) male. Most of inguinal hernia repair patients were farmers 158 (72.5%). Common risk factors noted were smoking 142 (65.1%), heavy work 112 (51.4%), chronic cough 65 (29.8%). Most of the complications occurred in the normal body mass index category and the prevalence of complications decreased as the body mass index increased. The recurrence was found in three (1.4%) inguinal hernia repairs. Conclusions: The majority of inguinal hernia repair patients were non-obese, and complications were less in obese patients.
Microbiological quality of free-range chicken carcasses from a non-regulated slaughter facility in Kenya

This study assessed the microbiological quality of meat from free rage-produced chicken processed in an informal slaughter facility. The total viable counts (TVC), total coliform counts, coagulase positive Staphylococcus aureus, Streptococcus species, Salmonella species and Campylobacter species were used as indicators. A cross-sectional sampling of chicken carcasses at informal slaughter facility was carried out. Whole carcass rinse fluid was prepared from 40 randomly obtained freshly dressed carcasses. Fluid samples were cultured in selective media to isolate and enumerate the specific bacteria. S. aureus was further identified by coagulase test, Streptococci by serotyping into Lancefield groups, Campylobacter by DNA analysis and Salmonella by biochemical tests and serology. Bacterial concentrations in the carcasses were calculated as colony forming units (CFU) per ml and CFU/cm2. The mean carcass CFU/ml concentration was 1.59 × 107, 1.44 ×105, 3.2 × 104 and 1.06 × 104 for TVC, Coliforms, S. aureus and Streptococci, respectively. All the mean concentration values were higher than the limits recommended by the Codex Alimentarius Commission (CAC). Coagulase-positive Staphylococcus was isolated from 12 (30%) carcasses and Streptococci from 35 (87%). Majority Streptococci were Lancefield Group D (48.57%) followed by Group G (17.14%), and Group F (14.28%). Campylobacter genus was identified in 11 carcasses (27.5%) and Campylobacter jejuni in three (7.5%). On the other hand, Salmonella was not isolated from any carcass. The results of the study indicated that the low hygienic standard in non-regulated slaughter houses exposed the chicken meat to microbial contaminants which may pose a risk to the consumers. Improvement of slaughter infrastructure and capacity-building of slaughter personnel is therefore critically required to ensure food safety and enable access to high value markets. Key words: Slaughter, free-range chicken, bacterial quality.
Obstacles to obtaining Informed Consent from the Perspective of Transplant Coordinators: A Qualitative Study

Background: The lack of consent to donate body organs leads to an increase in the death rate of patients on the waiting list for transplantation. Unwillingness of families is known as the main obstacle to organ donation, and the media has an essential role in motivating organ donation. Objectives: This study aimed to explore obstacles to obtaining consent for organ donation from transplant coordinators’ perspective throughout Iran. Methods: In this qualitative study, 13 in-depth semi-structured face-to-face interviews were conducted with transplant coordinators from November 2018 to March 2019. The participants were investigated using a purposive sampling method. The participants’ age and work experience ranged between 32 - 49 years and 6 - 25 years, respectively. Open-ended questions were asked from the participants in a private room. An experienced interviewer explained the study’s objectives to the coordinators, and each interview lasted on average 50 minutes. The interview scripts were analyzed using a content analysis method. Results: The findings highlighted the difficulty of obtaining consent from brain-dead patients’ families. The obstacles could be internal or external. External determinants were healthcare providers’ lack of empathy, inadequate consultation from doctors outside the hospital, media content, and uninformed comments from relatives. Internal determinants were hoping for recovery, denial, and disagreement among family members. Conclusions: The healthcare team should have a better connection with families to obtain organ donation consent from them. Therefore, a training program must be developed for the treatment team so that they show more supportive behavior and improve quality of care in hospitals before and after brain death.
GRATITUDE AND LONELINESS AS PREDICTORS OF SUBJECTIVE WELL-BEING

The main aim of this research is to analyze the role of loneliness found in previous studies as well as to examine the role of gratitude as one of the main factors contributing to subjective well-being. The sample is a convenience sample and consists of 219 respondents (78.99% women). The instruments used in this research were: the Social and Emotional Loneliness Scale for Adults (SELSA; di Tomasso & Spinner, 1993), the Life satisfaction scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985), PANAS (Watson, Clark, & Tellegan, 1988) and The Gratitude Questionnaire (McCullough et al., 2002). The data were analyzed using a hierarchical linear regression where the criterion variables were components of subjective well-being, the predictor in the first step gratitude, and predictors in the second step three types of loneliness. The results of this research show that the only statistically significant predictor of positive affects is gratitude (model 1: β=.281, p<.01; model 2: β=.243. p<.01). Gratitude and loneliness explain 30.1% of the variance of positive affect. When it comes to negative affect, the first model explains 12.6% of the variance, while the second model explains 21.9% of the total variance. Only the second model is statistically significant (p<.05). The only statistically significant predictor is loneliness in the family (β=.143. p=.049). Finally, when it comes to life satisfaction, the first model explains 23.5% of the variance while the second model explains 38.6% of the total variance. When loneliness is added in the second model, an additional 15.1% of the statistically significant explained variance appears (p<.01). The best predictor in this regression analysis is social loneliness (β=-.297, p<.01). Based on these results we can conclude that both gratitude and loneliness are important variables for subjective well-being – but that some are more important for some and some for other aspects of subjective well-being.
The equilibrium crystallisation process of non-crystalline Cu3Au

ABSTRACT The equilibrium crystallisation of non-crystalline Cu3Au has been studied by molecular dynamics method. The results of structure analysis show that the crystallisation kinetics of non-crystalline Cu3Au in the isothermal process is in agreement with the Avrami equation in the temperature range between 400 and 850 K. The time–temperature transformation diagram of crystallisation process presents a typical C-curve with nose temperature about 650 K. In the crystallisation process, there are also many metastable clusters produced in the disordered structure. The metastable polyhedron structure can promote the nucleation and growth process of crystal.
Endoscopic submucosal dissection in colorectal neoplasia performed with a waterjet system-assisted knife: higher en-bloc resection rate than conventional technique

Background/Aims Colorectal endoscopic submucosal dissection (ESD) is burdened by its associated high risk of adverse events and long procedure time. Recently, a waterjet-assisted knife was introduced to simplify and speed up the procedure. The aim of this study was to evaluate the efficacy and safety of waterjet-assisted ESD (WESD) compared to that of the conventional ESD (CESD) technique. Methods The charts of 254 consecutive patients who underwent colorectal ESD between January 2014 and February 2021 for colorectal neoplasms were analyzed. The primary outcome was the en-bloc resection rate. Secondary outcomes were complete and curative resection rates, the need to switch to a hybrid ESD, procedure speed, the adverse event rates, and the recurrence rates. Results Approximately 174 neoplasias were considered, of which, 123 were removed by WESD and 51 by CESD. The en-bloc resection rate was higher in the WESD group (94.3% vs. 84.3%). Complete resection rates and curative resection rates were similar. The need to switch to a hybrid ESD was greater during CESD (39.2% vs. 13.8%). Procedure speed and adverse event rates were similar. During follow-up, one recurrence occurred after a WESD. Conclusions WESD allows a high rate of en-bloc resections and less frequently requires a rescue switch to the hybrid ESD compared to CESD.
Exopolysaccharides Production by Cultivating a Bacterial Isolate from the Hypersaline Environment of Salar de Uyuni (Bolivia) in Pretreatment Liquids of Steam-Exploded Quinoa Stalks and Enzymatic Hydrolysates of Curupaú Sawdust

The halotolerant bacterial strain BU-4, isolated from a hypersaline environment, was identified as an exopolysaccharide (EPS) producer. Pretreatment liquids of steam-exploded quinoa stalks and enzymatic hydrolysates of Curupaú sawdust were evaluated as carbon sources for EPS production with the BU-4 strain, and the produced EPS was characterized using FTIR, TGA, and SEM. Cultivation was performed at 30 °C for 48 h, and the cells were separated from the culture broth by centrifugation. EPS was isolated from the cell pellets by ethanol precipitation, and purified by trichloroacetic acid treatment, followed by centrifugation, dialysis, and freeze-drying. EPS production from quinoa stalks- and Curupaú sawdust-based substrates was 2.73 and 0.89 g L−1, respectively, while 2.34 g L−1 was produced when cultivation was performed on glucose. FTIR analysis of the EPS revealed signals typical for polysaccharides, as well as ester carbonyl groups and sulfate groups. High thermal stability, water retention capacity and gel-forming ability were inferred from SEM and TGA. The capability of the halotolerant isolate for producing EPS from pretreatment liquids and hydrolysates was demonstrated, and characterization of the EPS revealed their broad application potential. The study shows a way for producing value-added products from waste materials using a bacterium from a unique Bolivian ecosystem.
Intravenous Immunoglobulin for Treatment of Patients with COVID-19: A Case-control Study

Background: It seems that the risk of developing complications associated with coronavirus disease 2019 (COVID-19) is higher among individuals with weakened immune systems. Objectives: Therefore, this study was carried out to determine the effectiveness of intravenous immunoglobulin (IVIG) for the treatment of patients not entering the intubation phase compared to those entering the intubation phase. Methods: This descriptive case-control study was performed on 26 patients with COVID-19 referring to Imam Reza hospital in Mashhad, Iran, in March 2020. For subjects with COVID-19 not responding to the standard three-drug protocol (i.e., ribavirin, hydroxychloroquine, and lopinavir/ritonavir), three doses of IVIG (0.4 g/kg/day) were added to the protocol. The patients were divided into two groups of subjects not entering the intubation phase and those entering the intubation phase and compared in terms of different variables. Results: The comparison of laboratory findings showed a significant difference before and after receiving IVIG regarding oxygen saturation (P < 0.005), white blood cell (P = 0.001), hemoglobin level (P = 0.0002), lymphocyte count (P = 0.03), and C-reactive protein (P = 0.001). In general, 53.8% and 46.2% of the patients were discharged and expired, respectively. All the subjects not entering the intubation phase were recovered; nevertheless, only one case entering the intubation phase was recovered, and 92.3% of the patients expired. A significant difference was observed between the patients not entering the intubation phase and those entering the intubation phase in terms of mortality (χ2 = 22.28; P < 0.005). Conclusions: In summary, the obtained results of the current study confirmed the therapeutic effects of IVIG on patients with COVID-19. Moreover, better treatment results, shorter hospital stay, and lower mortality rates were observed among COVID-19 patients who did not enter the intubation phase in comparison with those entering the intubation phase.
Arising of Informal Women's Learn-to-code Communities

Female-focused, grassroots communities purporting to help women learn to code are popping up in a variety of settings, indicating the motivation on the part of the participants to evade male-dominated settings while learning. However, little is known about how these groups function as an activity system. With current technology enabling the forming of virtual communities and the meteoric rise in use of the Salesforce CRM (customer relationship management) platform, a group of women have formed a coaching and learning community designed to help women move from Salesforce administrators to software developers through learning to code. We used activity systems analysis (ASA) to investigate this real-world instance of the larger phenomenon using an ethnographic approach. We used ASA to organize and make sense of the data by first creating a table listing the points on the activity system triangle (subject, rules, object, etc.) and filling in the points of the triangle based on the design of the coaching and learning group as described by participants; this gave us a high-level view of the activity system. To understand the subjects’ point of view of the system, we then created a new column in the table to fill in themes that emerged from our qualitative data analysis organized by dimension of the activity system. This process enabled us to capture the activity and the voices of participants as well as tensions that had emerged in the system. Findings show a range of outcomes, from participants crediting the group as a kickstart to the journey to successfully landing a job as a developer to members stalling in their progress after involvement. Results also show that purposeful tensions of welcoming novice questions and offering unsolicited verbal encouragement built into the activity system create a welcoming, safe environment for women learning to code.
Clustering Nuclear Magnetic Resonance: Machine learning assistive rapid two‐dimensional relaxometry mapping

Low‐field nuclear magnetic resonance (NMR) relaxometry is an attractive approach from point‐of‐care testing medical diagnosis to in situ oil‐gas exploration. One of the problems, however, is the inherently long relaxation time of the (liquid) samples, (and hence low signal‐to‐noise ratio) which causes unnecessarily long repetition time. In this work, a new class of methodology is presented for rapid and accurate object classification using NMR relaxometry with the aid of machine learning. It is demonstrated that the sensitivity and specificity of the classification is substantially improved with higher order of (pseudo)‐dimensionality (e.g., 2D‐ or multi‐dimensional). This new methodology (termed as ‘Clustering NMR’) may be extremely useful for rapid and accurate object classification (in less than a minute) using low‐field NMR.
Effective Training Evaluation: The Role of Factors Influencing the Evaluation of Effectiveness of Employee Training and Development

If an organisation is to develop in today’s highly competitive environment, it cannot do so without continuous training and development of its employees. The benefit to the individual can be assessed by a measurable degree of his knowledge, mastering a certain operation, etc. Evaluating the effectiveness of training is not easy, because very often we work with quantities that are difficult to quantify, and therefore difficult to measure. The prerequisite is the precise definition of educational goals and ensuring the controllability of educational results (training). This article aims to find factors influencing evaluation of effectiveness of employee training and development. The data was obtained from a questionnaire survey in which 207 organisations operating in the Czech Republic participated. The results show that when evaluating the effectiveness of employee training, organisations prefer methods based on subjective evaluation by an evaluator (direct supervisors, colleagues), but also on their own self-evaluation regarding the number of training days. Due to the coronavirus pandemic, current human resources (HR) trends and priorities for 2021 have changed significantly. The systematic process of evaluating employee training effectiveness depends on the business sector (p-value 0.022), on the fact that the organisation is or is not a part of a larger group (p-value 0.000), on (non)existence of an HR department (p-value 0.000), and on the organisation size (p-value 0.000).
Reliable SRAM using NAND-NOR Gate in beyond-CMOS QCA technology

The rise in complementary metal ‐ oxide semiconductor (CMOS) limitations has urged the industry to shift its focus towards beyond ‐ CMOS technologies to stay in race with Moore’s law. Quantum ‐ dot cellular automata (QCA) is considered to be a prominent paradigm among the emerging beyond ‐ CMOS technologies. Since QCA is an emerging technology with no proper layout tools, layout generation from hardware description language (HDL) can be done by implementing circuits using the NAND ‐ NOR logic. In QCA, the NAND ‐ NOR logic is realised by combining a majority gate and an inverter or by using some dedicated structures. The Radius of Effect (RoE) is a critical factor that depends on the permittivity of the material used and it has an influence on the columbic interaction, polarisation and kink energy. Lower Radius of Effect values will have an impact on the performance of the circuit. In this work, a cost ‐ efficient NAND ‐ NOR gate using Single Rotated Cell (SRC) inverter is proposed which can operate with lower Radius of Effect. Using the proposed gate, multiplexer, decoder, and innovative memory cell are implemented. In order to demonstrate the ability to implement larger circuits using NAND ‐ NOR logic and the proposed blocks, a is implemented. QCADesigner is used for the simulation and vali-dation of the proposed designs.
Online Tuning of Hyperparameters in Deep LSTM for Time Series Applications

Deep learning is one of the most remarkable artificial intelligence trends. It stands behind numerous recent achievements in several domains, such as speech processing, and computer vision, to mention a few. Accordingly, these achievements have sparked great attention to employing deep learning in time series modelling and forecasting. It is known that the deep learning algorithms built on neural networks contain multiple hidden layers, which make the computation of deep neural network challenging and, sometimes, complex. The reason for this complexity is that obtaining an outstanding and consistent result from such deep architecture requires optimizing many parameters known as hyperparameters. Doubtless, hyperparameter tuning plays a critical role in improving the performance of deep learning. This paper proposes an online tuning approach for the hyperparameters of deep long short-term memory (DLSTM) model in a dynamic fashion. The proposed approach adapts to learn any time series based application, particularly the applications that contain streams of data. The experimental results show that the dynamic tuning of the DLSTM hyperparameters performs better than the original static tuning fashion.