Miracle-dz/UniFAR-FTUs huggingface dataset:
Strengthening Occupational Safety and Health Policy in Malaysia: Exploring the Awareness of Civil Servants

Accident and fatality rates in the workplace are anticipated to rise constantly over the next few years. Extensive occupational safety and health studies have been conducted in various sectors, yet little attention has been paid to the public sector. This study aims to explore civil servants’ awareness on occupational safety and health (OSH). A survey was conducted in a public university to examine the relationship between OSH awareness and the civil servants’ safety understanding, self-preventive attitudes and self-care practices. The findings revealed that the majority of the respondents have a high understanding of OSH. A correlation analysis indicated that safety understanding, self-preventive attitudes and self-care practice have a positive association with OSH awareness. The highest correlation is between self-preventive attitudes and OSH awareness (r = .732, p < .05). The multiple correlation disclosed F (3,128) = 92.93, p < . 000 with an R2 of . 24. A significant linear relationship between safety understanding, self-preventive attitudes and self-care practices predicting the OSH awareness with the strongest correlation is between self-preventive attitudes (β = .29, p < .05). The findings suggest that public organisations focus on implementing the OSH guidelines and regulations to minimise occupational hazards at work.
Implementing the Political Engagement Project in an Introductory Communication Course: An Examination of the Effects on Students’ Political Knowledge, Efficacy, Skills, Behavior, and Ideology

A repeated measures design was employed to assess the effects of participation in the Political Engagement Project (PEP) on measures of students’ political knowledge, efficacy, general interpersonal skills, skills of influence and action, political behavior, concern for political issues, and political ideology. Results demonstrate that students in PEP sections of an introductory communication course show significantly larger pre- to posttest gains on virtually all of the measures. Specifically, mean scores indicated that both experimental groups (PEP without video and PEP with video) reported significantly greater increases, compared to the control group, in political knowledge, efficacy, general interpersonal skills, skills of influence and action, and political behavior. However, the control group produced significantly greater increases on the concern for political issues measure as compared to the PEP with video experimental group, while showing no significant differences to the PEP without video experimental group. Finally, there were no differences over time for any of the groups on a measure of political ideology.
Automatic Traffic State Recognition Based on Video Features Extracted by an Autoencoder

Video surveillance has become an important measure of urban traffic monitoring and control. However, due to the complex and diverse video scenes, traffic data extraction from original videos is a sophisticated and difficult task, and corresponding algorithms are of high complexity and calculation cost. To reduce the algorithm complexity and subsequent computation cost, this study proposed an autoencoder model which effectively reduces the video dimension by optimizing structural parameters; thus several traffic recognition models can conduct image processing work based on dimension-reduced videos. Firstly, an optimal autoencoder model A ∗ with five hidden layers was constructed. Then, it was combined with a linear classifier, support vector machine, deep neural network, DNN linear classification method, and the k-means clustering method; thus, five traffic state recognition models were constructed: A ∗ -Linear, A ∗ -SVM, A ∗ -DNN, A ∗ -DNN_Linear, and A ∗ -k-means. Train and test results show that the accuracy rate and recall rate of A ∗ -linear, A ∗ -SVM, A ∗ -DNN, and A ∗ -DNN_Linear were 94.5%–97.1%, and the F1 score was 94.4%–97.1%; besides, the accuracy rate, recall rate, and F1 score of A ∗ -k-means were all approximately 95%, which suggests that the combination of the autoencoder A ∗ and common classification or clustering methods achieve good recognition performance. Comparison was also implemented among the five models proposed above and four CNN-based models such as AlexNet, LeNet, GoogLeNet, and VGG16, which shows that the five proposed modes achieve F1 scores of 94.4%–97.1%, while the four CNN-based models achieve F1 scores of 16.7%–94%, indicating that the proposed light weight design methods outperform more complex CNN-based models in traffic state recognition.
Role of Platelet Rich Plasma in the Treatment of Foot Ulcers: A Review

An ulcer is a breach in the continuity of epithelium of mucous membrane and skin when an inflamed necrotic tissue sloughs out. Ulcers are caused by various medical conditions. The key to treatment is daily conventional dressing till the formation of healthy granulation tissue, infection control by antibiotics and surgical intervention such as debridement, and if the need arises, amputations. Platelet Rich Plasma (PRP) uses autologous plasma containing growth factors that helps in wound healing. PRP is being used extensively and is under research for wound treatment.
One Year of Recombinant Human Growth Hormone Treatment in Adults with Prader–Willi Syndrome Improves Body Composition, Motor Skills and Brain Functional Activity in the Cerebellum

We compared body composition, biochemical parameters, motor function, and brain neural activation in 27 adults with Prader–Willi syndrome and growth-hormone deficiency versus age-and sex-matched controls and baseline versus posttreatment values of these parameters after one year of recombinant human growth hormone (rhGH) treatment. To study body composition, we analyzed percentage of fat mass, percentage of lean mass, and muscle-mass surrogate variables from dual X-ray absorptiometry. Biochemical parameters analyzed included IGF-I, glucose metabolism, and myokines (myostatin, irisin, and IL6). To explore muscle function, we used dynamometer-measured handgrip strength, the Timed Up and Go (TUG) test, and the Berg Balance Scale (BBS). To study brain activation, we acquired functional magnetic resonance images during three motor tasks of varying complexity. After one year of treatment, we observed an increase in lean mass and its surrogates, a decrease in fat mass, improvements in TUG test and BBS scores, and increased neural activation in certain cerebellar areas. The treatment did not significantly worsen glucose metabolism, and no side-effects were reported. Our findings support the benefits of rhGH treatment in adults with Prader–Willi syndrome and growth-hormone deficiency on body composition and suggest that it may also improve balance and brain neural activation.
Augmentation-Consistent Clustering Network for Diabetic Retinopathy Grading with Fewer Annotations

Diabetic retinopathy (DR) is currently one of the severe complications leading to blindness, and computer-aided, diagnosis technology-assisted DR grading has become a popular research trend especially for the development of deep learning methods. However, most deep learning-based DR grading models require a large number of annotations to provide data guidance, and it is laborious for experts to find subtle lesion areas from fundus images, making accurate annotation more expensive than other vision tasks. In contrast, large-scale unlabeled data are easily accessible, becoming a potential solution to reduce the annotating workload in DR grading. Thus, this paper explores the internal correlations from unknown fundus images assisted by limited labeled fundus images to solve the semisupervised DR grading problem and proposes an augmentation-consistent clustering network (ACCN) to address the above-mentioned challenges. Specifically, the augmentation provides an efficient cue for the similarity information of unlabeled fundus images, assisting the supervision from the labeled data. By mining the consistent correlations from augmentation and raw images, the ACCN can discover subtle lesion features by clustering with fewer annotations. Experiments on Messidor and APTOS 2019 datasets show that the ACCN surpasses many state-of-the-art methods in a semisupervised manner.
Ethnomedicinal Plants in Herbal Remedies Used for Treatment of Skin Diseases by Traditional Healers in Songkhla Province, Thailand

Skin disorders are a worldwide health problem that normally affect human life. A traditional healer is an important expert in researching notable medicinal plants for skin disease treatment. This study aimed to determine the traditional knowledge and the use of medicinal plants for the treatment of skin diseases among traditional healers in the Songkhla province, Thailand. The ethnobotanical information was collected from experienced traditional healers by semi-structured interviews and participant observations. Plant specimens were also collected and identified using the standard taxonomic method. The data were analyzed by interpretation and descriptive statistics. Twenty-five polyherbal formulations for the treatment of skin diseases were obtained from traditional healers with at least 10 years of experience. A total of 66 plant species in 38 families were documented. Leaves and trees were the most commonly employed plant parts and plant habits included in the herbal remedies, respectively. Fabaceae, Rubiaceae, and Zingiberaceae were the majority of the cited families. Oryza sativa L. and Zingiber montanum (J. Koenig) Link ex A.Dietr. were the most preferred plants combined in the prescriptions, which had the highest use value (UV = 0.83). The highest relative frequency of citation was represented by Curcuma longa L. , Eurycoma longifolia Jack, Knema globularia (Lamk.) Warb, and Senna siamea (Lam.) Irwin & Barneby. (0.55 each). This research suggests the importance of traditional healers in the healing of skin diseases with herbal remedies. A variety of medicinal plants are used in the prescriptions for the treatment of skin disorders in the Songkhla province, in the south of Thailand. Pharmacological and toxicological activities as well as phytochemical constituents of polyherbal remedies should be further investigated to scientifically verify further applications of widely practiced herbal medicines.
Environment and Genetic Effects on Wood Quality of Populus

The purpose of the research was to investigate wood properties of new poplar clones from three different environments. Specific gravity, density, and anatomical properties were studied. Impacts of the cottonwood leaf beetle (Chrysomela scripta) on wood properties were investigated on two six-year-old clones in the first study. The results indicated that insect defoliation caused moderate to large decreases in annual growth over the first three years. Clones had different specific gravity and density for protected trees and constant values along the radius regardless of beetle attack. Fiber length was not affected by defoliation. Vessel number and diameter were impacted by defoliation and offsetting changes in vessel numbers and diameters partially cancel out changes in vessel area. Ray area was larger for unprotected trees; one clone responded to defoliation by producing more rays; meanwhile, the other produced fewer but larger rays. The second study dealt with wood properties of eight six-year-old Populus deltoides clones of two families grown under stressful site conditions. There were no differences in growth rate between the two families; however, specific gravity was significantly influenced by family and by clone. Fiber length was affected only by clone and radial position and correlated with growth rate. Clonal averages of fiber length were different closer to the bark suggesting that the earliest selection for fiber length should start after four or five years. The third study analyzed wood variation for four-year-old Populus deltoides trees with exceptional specific gravity and growth rate values. There were significant differences among trees in fiber length and vessel area but not in vessel numbers, vessel diameter, and in ray numbers. The age of the cambium significantly affected all wood properties. The fastest growing tree with high specific gravity had the longest fibers, the highest ray numbers but low vessel area, vessel number, and low vessel diameter representing an unusual combination of traits. Results indicate that trees with similar growth rates can have wide variation in vessel area and that exceptionally fast-growth tree can be achieved with low vessel area.
Reading, Commenting and Sharing of Fake News: How Online Bandwagons and Bots Dictate User Engagement

Do social media users read, comment, and share false news more than real news? Does it matter if the story is written by a bot and whether it is endorsed by many others? We conducted a selective-exposure experiment (N = 171) to answer these questions. Results showed that real articles were more likely to receive “likes” whereas false articles were more likely to receive comments. Users commented more on a bot-written article when it received fewer likes. We explored the psychological mechanisms underlying these findings in Study 2 (N = 284). Data indicate that users’ engagement with online news is largely driven by emotions elicited by news content and heuristics triggered by interface cues, such that curiosity increases consumption of real news, whereas uneasiness triggered by a high number of “likes” encourages comments on fake news.
A Domain-Specific, Model Based Systems Engineering Approach for Cyber-Physical Systems

Model Based Systems Engineering as a scientific discipline tries to address the increasing complexity of today’s cyber-physical systems by utilizing different kinds of models. In practical application, however, this approach is often constrained to SysML-based object modeling. Even though this appears to be a suitable approach for dealing with complexity, various restrictions limit stakeholder acceptance. Considering scientific discussions in the context of modeling shows two different schools of thought. On the one hand, arguments for more formalized and rigorous concepts can be found, where on the other hand, the need for more stakeholder-oriented and easier-to-understand concepts is postulated. As both are reasonable, the question of integration arises. To address this aspect, we developed the concept of Domain Specific Systems Engineering. Our research in this field lasted for nearly a decade, and different aspects have been investigated. This paper contributes a summary of the overall approach that integrates the various aspects investigated so far. Thus, the underlying concepts are explained, and the corresponding modeling stack and tool-chain are described in more detail. Further, the practical experiences from various case studies are summarized, and identified shortcomings are discussed.
Effect of skip-feeding and re-feeding regimes on compensatory growth, body composition, feed utilization, feeding cost and survival of monosex tilapia (Oreochromis niloticus) in pond aquaculture system

Monosex tilapia has great acceptability particularly among the lower income people due to its lower price. However, due to increased feed price the price of tilapia has been increased in recent years. Compensatory growth (CG) of fish that is achieved after a period of feed deprivation can potentially reduce the feed cost. The present study aimed to get CG in tilapia farming so as to reduce the production cost of this popular fish. Tilapia fry of 0.54 g body weight were nursed in hapa for one month and then stocked in earthen ponds where two different restricted feeding regimes were imposed for next two months followed by one month feeding at satiation level. Sampling was done fortnightly to record average weight gain in control and treatment groups. Average individual weight in restricted feeding group (T1) reached to 170.11±4.6 g in a three months experimental period and it did not significantly (p>0.05) differ with the weight gained in control group (182.79±5.32 g) where fish were fed on regular basis. The specific growth rate (SGR) also showed no significant difference (p>0.05) between T1 (SGR 2.66±0.011 % day-1) and control group (SGR 2.69±0.012 % day-1). Feed Conversion Ratio (FCR) in T1 (1.26) was found significantly (p<0.05) lower to that of control group (1.47), hence the per unit production cost was also found significantly lower in T1 (BDT 75 Kg-1) compared to that of control (BDT 88.23 Kg-1). On the other hand no significant difference was evident in biochemical parameters between the control and restricted feeding groups. Thus, this study suggests skip feeding as an appropriate tool to achieving CG in monosex tilapia and to trim down the production cost as well.
The Role of Vitamin D in Supporting Health in the COVID-19 Era

The genomic activity of vitamin D is associated with metabolic effects, and the hormone has a strong impact on several physiological functions and, therefore, on health. Among its renowned functions, vitamin D is an immunomodulator and a molecule with an anti-inflammatory effect, and, recently, it has been much studied in relation to its response against viral infections, especially against COVID-19. This review aims to take stock of the correlation studies between vitamin D deficiency and increased risks of severe COVID-19 disease and, similarly, between vitamin D deficiency and acute respiratory distress syndrome. Based on this evidence, supplementation with vitamin D has been tested in clinical trials, and the results are discussed. Finally, this study includes a biochemical analysis on the effects of vitamin D in the body’s defense mechanisms against viral infection. In particular, the antioxidant and anti-inflammatory functions are considered in relation to energy metabolism, and the potential, beneficial effect of vitamin D in COVID-19 is described, with discussion of its influence on different biochemical pathways. The proposed, broader view of vitamin D activity could support a better-integrated approach in supplementation strategies against severe COVID-19, which could be valuable in a near future of living with an infection becoming endemic.
‘Breathing Out’ under Heat Stress—Respiratory Control of Crop Yield under High Temperature

Respiration and photosynthesis are indispensable plant metabolic processes that are affected by elevated temperatures leading to disruption of the carbon economy of the plants. Increasing global temperatures impose yield penalties in major staple crops that are attributed to increased respiratory carbon loss, through higher maintenance respiration resulting in a shortage of non-structural carbohydrates and an increase in metabolic processes like protein turnover and maintenance of ion concentration gradients. At a cellular level, warmer temperatures lead to mitochondrial swelling as well as downregulation of respiration by increasing the adenosine triphosphate:adenosine diphosphate (ATP:ADP) ratio, the abscisic acid-mediated reduction in ATP transfer to the cytosol, and the disturbance in a concentration gradient of tricarboxylic acid (TCA) cycle intermediates, as well as increasing lipid peroxidation in mitochondrial membranes and cytochrome c release to trigger programmed cell death. In this review, we discuss the mechanistic insight into the heat stress-induced mitochondrial dysfunction that controls dark respiration in plants. Furthermore, the role of hormones in regulating the network of processes that are involved in retrograde signaling is highlighted. We also propose different strategies to reduce carbon loss under high temperature, e.g., selecting genotypes with low respiration rates and using genome editing tools to target the carbon-consuming pathways by replacing, relocating, or rescheduling the metabolic activities.
Use of off-label compounded oral sildenafil in the management of persistent pulmonary hypertension of the newborn: A case report

We report a case of a newborn with persistent pulmonary hypertension (PPHN) due to meconium aspiration syndrome with associated lung collapse. Echocardiogram revealed features of persistent pulmonary hypertension. He was treated with compounded oral sildenafil. Oral sildenafil has proven to be effective and safe in the management of PPHN in neonates with persistent pulmonary hypertension. Therefore, in situations where inhaled nitric oxide is not available it may be used as an alternative therapy in PPHN. Further randomized controlled studies are needed to determine its efficacy and pharmacokinetics.
Smart2charge: smart grid enabled BEV charging infrastructure for rural areas

Wüstenrot aims to become a ”Plus-Energy municipality” as a part of its German Energy Transition (Energiewende) goals. Wüstenrot has already achieved a high share of renewable energy production and is currently making its electricity and heating grid network more efficient by using intelligent monitoring systems. The next stage of the “Plus-Energy” plan is to increase the share of e-mobility in Wüstenrot. A rapid increase in the electrification of individual transport is expected in the coming years and this sector poses great challenges for municipalities in rural areas such as Wüstenrot. The major challenges are building necessary intelligent charging infrastructure, its integration into the current electricity grid and avoid overloading of the electricity grid. The “Smart2Charge” (S2C) project aims to solve those challenges. The objective of the S2C project is to create a reference model for the rapid expansion of e-mobility in rural areas. Firstly, the traffic flow of Wüstenrot is analysed, then secondly the electricity grid is modelled for testing the expansion of charging infrastructure and the application of flexibility measures. Following this, the acceptance of e-mobility in Wüstenrot is studied and finally a business model is created for the e-mobility expansion. The expansion of electric mobility offers a highly interesting new field of activity with services ranging from the provision of charging infrastructure, the development and implementation of booking and billing systems for car sharing services to the implementation and operation of parking guidance systems. Through comprehensive intelligent bi-directional charging management (V2G), there is also the potential to develop an additional service market for the power grid. This paper aims at giving the audience an overview of the project objectives and an insight into current project results.
Classification in Bone Scintigraphy Images Using Convolutional Neural Networks

The main goal of this thesis is to design and implement a convolutional neural network (CNN) to classify whether hotspots in bone scintigraphy images represent cancer metastases, caused by prostate cancer, or some other physiological process. A side task was included, where another CNN was designed and trained to classify whether a bone scintigraphy image image is acquired from the front of the patient (anterior) or from the back (posterior). The CNNs were implemented using the deep learning frameworks Deeplearning4J and Keras, and were trained on labelled data sets provided by Exini Diagnostics AB, Lund, Sweden. The performance of the CNNs were evaluated using various metrics commonly used in machine learning contexts, for instance accuracy and Receiver Operating Characteristics. The ﬁnal trained CNN used for the classiﬁcation of hotspots reached an accuracy of 89% on a test set consisting of images that had not been used for training. The corresponding CNN for the side task reached an accuracy of 99%. These results indicate that CNNs can work well for both classiﬁcation problems. (Less)