Miracle-dz/UniFAR-FTUs huggingface dataset:
Vicarious Experiences of Major Discrimination and Psychological Distress among Black Men and Women

Racism-related stress frameworks posit that the discriminatory experiences of one’s loved ones may threaten one’s well-being, but relatively few studies have examined how they may impact mental health beyond childhood and adolescence. Using data from the Nashville Stress and Health Study (N = 1,252), the present study assessed the prevalence of vicarious experiences of discrimination among subsamples of Black men (n = 297) and women (n = 330), examined the association between vicarious experiences of discrimination and psychological distress among Black men and women, and evaluated the impact of vicarious discrimination on psychological distress in the context of other stressors. Results suggest that Black women report more vicarious exposure to specific types of discrimination. Furthermore, vicariously experienced discrimination was associated with higher levels of psychological distress among Black women, but not among Black men. Our findings extend the literature on racism-related stress and offer new insights for interventions aimed at reducing racial disparities in mental health.
On Determining Paint by Numbers Puzzles with Nonunique Solutions

Paint by Numbers is a classic logic puzzle in which the squares of a p ×n grid are to be colored in such a way as to display a picture. The decision on which squares to color is determined by sequences of numbers above each column and to the left of each row. The numbers describe how many consecutive squares are to be colored in that row or column, and multiple numbers represent multiple blocks of colored in squares (with at least one uncolored square inbetween blocks.) Certain natural questions arise. For a given p × n grid, how many possible sequences are in a single column or row? For a given grid, how many puzzles are there? How many of these have unique solutions? We will explore these questions as well as connections between Paint by Numbers puzzles, partition theory, and the Fibonacci sequence.
An Assessment of Frequency of Deficiency of Vitamin D among HIV/AIDS Patients

Background: Literature showed that HIV +ve individuals were deficient for vitamin D as well. Vitamin D deficiency is one of the top most commonly observed abnormality and an independent prognostic marker of HIV disease. The scientific groups’ emphases on the likely impact of its dearth on HIV infested populace. One of most communal comorbidities in HIV-1 patients is insufficiency of Vitamin D (Vit D), which is estimated by measuring 25-hydroxyvitamin D (25[OH]D) concentrations. Patients having vitamin D levels < 20ng/ml (50nmol/l) were considered as having vitamin D deficiency. HIV infection & ART (antiretroviral therapy) may create risk factors for insufficiency of vitamin D, it also has a role in slowing down HIV ailment progression. Methods: A descriptive cross-sectional study was conducted at Medicine Department in Services Hospital Lahore from June 22, 2017 to December 22, 2017. 160 Patients with HIV confirmed by ELISA method were selected by non-Probability Consecutive sampling technique. Data was entered in SPSS v23.0 & Chi square test was applied. Results: Out of 160, Frequency of Vitamin D deficiency was 111(69.4%). Results demonstrated that majority of patients 74(46.25%) are having disease for 1-3 years. While 54(33.75%) patients are having the disease for <1 year and 32(20.0%) are having the disease for >3 years. There were no significant differences between Vitamin D deficiency with age, gender and duration of HIV/AIDS (p-values 0.123, 0.136 & 0.634 respectively). Conclusion: Frequency of vitamin D deficiency is very high. This recommends that all HIV positive individuals should be considered for routine screening. Low serum calcium should prompt investigation of 25-OHD levels.
The Quality of Eggs Derived from Japanese Quail Fed with the Fermented and Non-Fermented Rapeseed Meal

The most popular protein source in poultry feed mixtures is soybean. However, cheaper and more available alternative protein sources are being sought, and feed manufacturers more and more often turn their attention to the post-extraction meals of local oil plants, e.g., rapeseed. Therefore, the effect of fermented and non-fermented post-extraction rapeseed meal used as a feed additive for Japanese quails was investigated on the eggs’ quality. The study was performed on 280 females of Japanese quails fed with a mixture without rapeseed meal, with non-fermented post-extraction rapeseed meal (5%, 10% and 15%) and with fermented one (5%, 10% and 15%). During the experiment, eggs were collected from each group four times (every 4 weeks) and evaluated for their quality characteristics. The addition of 10% fermented rapeseed meal had the most beneficial effect on such eggs quality traits as egg weight, specific gravity, yolk index and color and albumen pH. However, in the majority of examined parameters, no significant differences were found between birds fed with soybean meal and those fed with fermented and non-fermented rapeseed meal (morphological elements proportions, yolk weight, albumen height and Haugh’s units, eggshell quality). This supports the thesis that the use of rapeseed meals instead of soybean meals may allow obtaining the proper quality of animal raw materials at a lower cost and with the use of local feed resources.
Sensorimotor Activities and Their Functional Connectivity Elicited by Robot-Assisted Passive Movements of Lower Limbs

Robot-assisted body movements are a useful approach for the rehabilitation of motor dysfunction. Various robots based on end-effector or exoskeleton type have been proposed. However, the effect of these robots on brain activity during assistive lower limb movements remains unclear. In this study, we evaluated brain activity results among robot-assisted passive movements, voluntary active movements, and kinesthetic motor imagery. We measured and compared the brain activities of 21 young, healthy individuals during three experimental conditions associated with lower limb movements (active, passive, and imagery conditions) using functional near-infrared spectroscopy (fNIRS). Our results showed that although different brain areas with significant activity were observed among the conditions, the temporal patterns of the activity in each recording channel and the spatial patterns of functional connectivity showed high similarity between robot-assisted passive movements and voluntary active movements. Conversely, the robot-assisted passive movements did not show any similarity to motor imagery. Overall, these findings suggest that the robotic assistive approach is useful for activating not only afferent processes associated with sensory feedback processing but also motor control-related efferent processes.
Increased mRNA Levels of ADAM17, IFITM3, and IFNE in Peripheral Blood Cells Are Present in Patients with Obesity and May Predict Severe COVID-19 Evolution

Gene expression patterns in blood cells from SARS-CoV-2 infected individuals with different clinical phenotypes and body mass index (BMI) could help to identify possible early prognosis factors for COVID-19. We recruited patients with COVID-19 admitted in Hospital Universitari Son Espases (HUSE) between March 2020 and November 2021, and control subjects. Peripheral blood cells (PBCs) and plasma samples were obtained on hospital admission. Gene expression of candidate transcriptomic biomarkers in PBCs were compared based on the patients’ clinical status (mild, severe and critical) and BMI range (normal weight, overweight, and obesity). mRNA levels of ADAM17, IFITM3, IL6, CXCL10, CXCL11, IFNG and TYK2 were increased in PBCs of COVID-19 patients (n = 73) compared with controls (n = 47), independently of sex. Increased expression of IFNE was observed in the male patients only. PBC mRNA levels of ADAM17, IFITM3, CXCL11, and CCR2 were higher in those patients that experienced a more serious evolution during hospitalization. ADAM17, IFITM3, IL6 and IFNE were more highly expressed in PBCs of patients with obesity. Interestingly, the expression pattern of ADAM17, IFITM3 and IFNE in PBCs was related to both the severity of COVID-19 evolution and obesity status, especially in the male patients. In conclusion, gene expression in PBCs can be useful for the prognosis of COVID-19 evolution.
Comprehensive review of state-of-the-art photovoltaic cooling technologies

Solar energy, an endless source of electrical power and thermal energy, is one of the most promising ways to meet the energy demands of cities in the climate-change era. However, despite being a sustainable system for using solar energy, photovoltaic systems have only a maximum efficiency of 20% due to the inevitable temperature rise on PV cells' surfaces. To maintain Standard Test Conditions, passive, active, or a combination of cooling techniques are employed in order to cool down the surface temperature of the module. In this review paper, we presented a comprehensive classification of all the possible cooling technologies and evaluated the most recent studies of each cooling method to provide a thorough encyclopedia with a holistic consideration of installation configuration of each technique. Following outcomes are the results of the present review: (1) Passive cooling methods have the advantage of being easy to implement and less expensive, despite being generally more efficient. (2) Active cooling techniques are usually more expensive and difficult to install and maintain, making them less likely to be implemented on a large scale. (3) The evaluation indicated that Nano fluid cooling methods recorded the least satisfactory results with temperature reduction up to 2.4°C and electrical efficiency improvement of 9.7% at maximum based the reviewed studies, while (4) using fluid-based active cooling techniques in the form of jet impingement and spectrum filtering showed highly impressive improvements with up to 46°C and 33°C temperature reduction and 53 % and 47.67% enhancement in electrical efficiency, respectively. Suggested research direction for future studies is on less complicated cooling technologies with minimal installation which makes them easier to install and maintain, resulting in more probable applications for both domestic and large-scale implications.
Psychometric Validation of the Portuguese Version of the Modern Homonegativity Scale among Portuguese College Students

The studies focused on analysing attitudes toward homosexuality show that the manifestation of homonegativity has evolved into more modern forms. We therefore propose using instruments that capture subtle aspects in discrimination against gay and lesbian people. The objective of this study is twofold. First, we aim to adapt and validate the Portuguese version of the Modern Homonegativity Scale. Second, we set out to analyse the modern homonegativity shown by Portuguese university students. The scale includes two parallel subscales (MHS-Gay Men and MHS-Lesbian Women), each with 12 items. Six hundred and forty-one Portuguese college students between 18 and 27 years of age participated in the study (Mage = 21.23; SD = 1.88). The results demonstrate the unidimensionality of the scale and a high degree of internal consistency, along with satisfactory fit indices. Those people who identified as male and heterosexual showed greater modern homonegativity. We conclude that the Portuguese version of the MHS is valid and reliable for evaluating modern homonegativity in Portugal.
Effect of Black Soldier Fly (Hermetia illucens L.) Fat on Health and Productivity Performance of Dairy Cows

Simple Summary What is interesting in terms of unlocking the potential of insects is their fuller and more versatile use. Insect larvae contain large amounts of protein and fat. The fat of Hermetia illucens larvae is primarily rich in lauric acid. Lauric acid represents a promising nutritional strategy to improve animal health and productivity. The experimental data we obtained indicate the possibility of using the insect fat for the nutrition of milking cows. The milk production and milk quality of the cows were improved by optimising digestive processes and improving body defenses. The use of fat of Hermetia illucens larvae can serve as an alternative to traditionally used fats of animal and plant origin, as well as preparations of biologically active substances, which will provide a sustainable resource for the diets of agricultural animals in the future. Abstract Due to the intensive development of technologies for obtaining protein, energy feed and biologically active supplements from insects, the feasibility and effectiveness of introducing these products into the rations of farm animals require further study. This research aims to study the possibility and effects of feeding dairy cows fat from the larvae of the black soldier fly (BSFLF). The composition and properties of the BSFLF have been studied. The research of the fatty acid composition of BSFLF showed a high content of saturated fatty acids, including 58.9% lauric acid. The experiment was performed on black-and-white cows at the beginning of lactation (control, D0 (n = 12) vs. experimental D10 (n = 12) and D100 (n = 12) groups, 10 and 100 g/head/day BSFLF, respectively. There was no negative effect of BSFLF feeding on the process of feed digestion. The pH of the rumen content decreased (6.80 ± 0.07 & 6.85 ± 0.09 vs. 7.16 ± 0.06, p < 0.05), with an increase in the number of infusoria (0.27 ± 0.03&0.37 ± 0.09 vs. 0.18 ± 0.03 g/100 mL, p = 0.16); there was an increase in the concentration of VFA in the rumen content of animals of the experimental groups by 2.1 (p < 0.05) and 3.81 (p < 0.01) (8.66 ± 0.46 & 10.37 ± 0.42 vs. 6.56 ± 0.29) mmol/100 mL. The average daily milk yield of Group D10 cows over the experimental period (d17–d177) was slightly higher than the control (by 4.9%, p = 0.24 vs. Group D0). At the same time, Group D100 cows showed a significant increase in natural-fat milk compared to controls (by 8.0%, p < 0.05 vs. Group D0) over the same experiment period. Analysis of the fatty acid composition of the milk of the experimental animals showed some changes in the fatty acid composition of milk under the influence of BSFLF feeding; these changes were especially noticeable in Group D10. Thus, it was found that feeding dairy cows BSFLF at different dosages leads to better indicators of pre-gastric digestion and productivity.
Deep Learning vs Keypoint: Which Feature Set Is Better for Shell Recognition?

The shells of aquatic molluscs are ubiquitous in many coastal areas. While shells have been valued for decorative, cultural and economic reasons for millennia, they also have significant utility as ecological indicators of marine and freshwater biodiversity, pollution and water quality. With tens of thousands of species, shells are difficult to identify manually, necessitating automated approaches. Machine learning and computer vision can be employed to solve this issue. Unfortunately, very few studies have investigating classifying shells using these technologies. This paper presents an end-to-end shell species detection pipeline comprising feature extraction and recognition components. We exhaustively investigate various feature extraction methods, including those using domain knowledge, keypoints, and pretrained deep neural networks. Three classifiers are used to validate the discriminative capabilities of all generated features: support vector machine, random forest, and feed-forward neural network. Using a recently proposed shell dataset, we show that our best model - SVM trained on pretrained VGG16 features achieved 96% accuracy and macro-average F1, outperforming existing benchmarks by more than 13 % in both metrics.
A Novel Session Key Update Scheme for LoRaWAN

This paper proposes a novel Long-range Wide Area Network (LoRaWAN) session key updating scheme to enhance the security of LoRaWAN with cost-effective communication that provides a unique key for each communication session. The scheme consists of three sequential stages, i.e., initialization, keying material preparation, and key updating, on the basis of the truncated Photon-256 algorithm with updatable keying materials. These stages are structured by a set of novel communication protocols. To prove the uniqueness of the key, we validated its sequence bit randomness using the NIST 800-22 and ENT statistical test suites. The validation results show that the key passes all test parameters. Subsequently, the communication protocols were validated by using Scyther tools. We proved that these protocols ensure the security of the LoRaWAN key update scheme and guarantee that active interception does not occur. The analysis was performed by focusing on the security features of data confidentiality, integrity protection, mutual authentication, perfect forward secrecy, and replay attack resistance. Finally, a formal security analysis using GNY logic indicated that the overall security goals are achieved. The proposed scheme’s performance was evaluated in terms of computational cost, communication cost, and storage. The computational cost needed by the scheme is very small, indicating that there is no additional burden on the backend system. The communication cost requires less traffic than previous solutions, yet it offers more robust security for LoRaWAN by producing a new key in every communication session. The scheme needs insignificant additional storage that is considered negligible.
Segmentation and weight prediction of grape ear based on SFNet-ResNet18

ABSTRACT In this paper, the segment and weight prediction problems are investigated for ear of grape based on deep learning technologies. The image datum is collected from ZaoHeiBao grape in a greenhouse by camera. The grape ear target segmentation model is constructed by cross combining three backbone networks (ResNet18, ResNet50, and ResNet101) and four deep learning semantic segmentation networks (SFNet, GCNet, EMANet, and Deeplabv3). The experimental results show that for the SFNet-ResNet18 model, whose structural size is 52.68MB, the mean Intersection over Union (mIoU) is , the mean Pixel Accuracy (mPA) is , and the average segmentation speed of the image ( ) is 0.217s. Therefore, the performance of the SFNet-ResNet18 model outperforms other combined network models and is selected to segment grape ears. Furthermore, on the basis of the segmentation results of grape ears by using the SFNet-ResNet18 model, the grape ear weight is predicted by adopting fractional regression model. The value of is 0.8903, which means that the selected model could accurately predict the weight of grape ears. The proposed method can not only segment the grape ears and accurately predict the weight of the grape ears, but also provide theoretical and technical support for grape yield prediction.
Perirenal Fat Thickness Significantly Associated with Prognosis of Metastatic Renal Cell Cancer Patients Receiving Anti-VEGF Therapy

Although high body mass index (BMI) was reported to associate with a better prognosis for metastatic renal cell cancer (mRCC) patients receiving anti-vascular endothelial growth factor (anti-VEGF) therapy, it is an imperfect proxy for the body composition, especially in Asian patients with a lower BMI. The role of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and perirenal fat thickness (PRFT) in mRCC patients was still unknown. Therefore, a multicenter retrospective study of 358 Chinese mRCC patients receiving anti-VEGF therapy was conducted and their body composition was measured via computed tomography. We parameterized VAT, SAT and PRFT according to their median value and BMI according to Chinese criteria (overweight: BMI ≥ 24). We found VAT, SAT, and PRFT (all p < 0.05) but not BMI, significantly associated with overall survival (OS) and progression-free survival (PFS). Multivariate Cox analysis identified PRFT was the independent predictor of OS and PFS, and IMDC expanded with PRFT showed the highest C-index in predicting OS (OS:0.71) compared with VAT, SAT, and BMI. PRFT could increase the area under the curve of the traditional International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model in OS (70.54% increase to 74.71%) and PFS (72.22% increase to 75.03%). PRFT was introduced to improve the IMDC model and PRFT-modified IMDC demonstrated higher AIC in predicting OS and PFS compared with the traditional IMDC model. Gene sequencing analysis (n = 6) revealed that patients with high PRFT had increased angiogenesis gene signatures (NES = 1.46, p = 0.04) which might explain why better drug response to anti-VEGF therapy in mRCC patients with high PRFT. The main limitation is retrospective design. This study suggests body composition, especially PRFT, is significantly associated with prognosis in Chinese mRCC patients receiving anti-VEGF therapy. PRFT-modified IMDC model proposed in this study has better clinical predictive value.
CNN-based Model for Gender and Age Classification based on Palm Vein Images

Automatically predicting gender and age group from biometrics traits is an essential and challenging task in many real-world applications. There are several works about using machine learning methods to identify human gender or age through the face, iris, or fingerprint, but only limited research about using palm vein patterns. Considering the powerful feature representation ability of Convolutional Neural Networks (CNN) and the advantages of palm vein biometrics, this paper introduces a new CNN-based method for gender and age classification based on palm vein images. Experimental results show that the proposed model is able to learn discriminative features from palm vein images for these tasks, achieving state-of-the-art results on the VERA database by using a shallow CNN architecture. Besides, the obtained results suggest the feasibility of further studies on multi-task identification approaches and the reduction of the penetration rate in massive databases.
THE EFFECT OF PRE-SERVICE TEACHERS' DIGITAL LITERACY LEVELS ON THEIR ATTITUDE FOR DIGITAL WRITING: STRUCTURAL EQUATION MODEL STUDY

In this study, it was aimed to determine the effect of pre-service teachers' digital literacy levels on their attitudes towards writing in the digital environment. In addition, the mean scores of teacher candidates from both scales were examined in terms of different variables. Probability-based random sampling method, which is included in the general survey model, was preferred in the study. The sample of the research consists of 467 teacher candidates who attend Sivas Cumhuriyet University Faculty of Education in the spring semester of the 2021-2022 academic year. The data of the study were obtained by applying the "Digital Literacy Scale" developed by Ng (2012) and adapted into Turkish by Üstündağ, Güneş and Bahçivan (2017) and the "Attitude Scale for Digital Writing" developed by Kırmızı, Kapıkıran and Akkaya (2021). Research data were analyzed using normality tests, independent groups t-test, ANOVA, Scheffe, SEM and CFA statistical methods. In the findings obtained in the research, digital literacy of fathers education status, graduated high school type, time spent on the internet, computer, tablet, smart watch; on the other hand, it has been determined that the attitudes towards writing in the digital environment differ significantly according to the variables of gender, class level, place of residence, mother and father education level, branch, type of high school graduated, time spent on the internet, computer, smart phone, tablet, smart watch. In addition, it was concluded that digital literacy had a positive effect on their attitudes towards writing in the digital environment. Article visualizations: