Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review of Rattlesnake Venoms

Venom components are invaluable in biomedical research owing to their specificity and potency. Many of these components exist in two genera of rattlesnakes, Crotalus and Sistrurus, with high toxicity and proteolytic activity variation. This review focuses on venom components within rattlesnakes, and offers a comparison and itemized list of factors dictating venom composition, as well as presenting their known characteristics, activities, and significant applications in biosciences. There are 64 families and subfamilies of proteins present in Crotalus and Sistrurus venom. Snake venom serine proteases (SVSP), snake venom metalloproteases (SVMP), and phospholipases A2 (PLA2) are the standard components in Crotalus and Sistrurus venom. Through this review, we highlight gaps in the knowledge of rattlesnake venom; there needs to be more information on the venom composition of three Crotalus species and one Sistrurus subspecies. We discuss the activity and importance of both major and minor components in biomedical research and drug development.
Reference-Free Model Predictive Control for Quadrupedal Locomotion

Full-dynamics model predictive control (MPC) has recently been applied to quadrupedal locomotion in semi-unstructured environments. These advances have been fueled by the availability of efficient trajectory optimization (TO) algorithms and inexpensive computational power. The main advantages of full-dynamics MPC are (i) enabling complex locomotion manoeuvres, (ii) considering actuation limits, and (iii) improving robot stability. However, to make the TO problem sufficiently simple to be solved at run time, reference swing foot trajectories are usually tracked in the MPC formulation. These trajectories are often computed independently of the motion of the joints, limiting the approach generality and capability. To address this limitation, we present a full-dynamics MPC formulation that does not require reference swing-foot trajectories, featuring a novel cost function targeting swing foot motion and considering environmental information. Removing the need for reference swing foot trajectories, our approach can also automatically adjust footstep locations, as long as the contact surfaces are predefined. We have validated our MPC formulation through simulations and experiments on the ANYmal B robot. Our approach has similar computational efficiency to state-of-the-art formulations, while displaying superior push-recovery capabilities on various terrains.
Emergence of Extracellular Vesicles as “Liquid Biopsy” for Neurological Disorders: Boom or Bust

Extracellular vesicles (EVs) have emerged as an attractive liquid biopsy approach in the diagnosis and prognosis of multiple diseases and disorders. The feasibility of enriching specific subpopulations of EVs from biofluids based on their unique surface markers has opened novel opportunities to gain molecular insight from various tissues and organs, including the brain. Over the past decade, EVs in bodily fluids have been extensively studied for biomarkers associated with various neurological disorders, such as Alzheimer's disease, Parkinson's disease, schizophrenia, bipolar disorder, major depressive disorders, substance use disorders, human immunodeficiency virus–associated neurocognitive disorder, and cancer/treatment-induced neurodegeneration. These studies have focused on the isolation and cargo characterization of either total EVs or brain cells, such as neuron-, astrocyte-, microglia-, oligodendrocyte-, pericyte-, and endothelial-derived EVs from biofluids to achieve early diagnosis and molecular characterization and to predict the treatment and intervention outcomes. The findings of these studies have demonstrated that EVs could serve as a repetitive and less invasive source of valuable molecular information for these neurological disorders, supplementing existing costly neuroimaging techniques and relatively invasive measures, like lumbar puncture. However, the initial excitement surrounding blood-based biomarkers for brain-related diseases has been tempered by challenges, such as lack of central nervous system specificity in EV markers, lengthy protocols, and the absence of standardized procedures for biological sample collection, EV isolation, and characterization. Nevertheless, with rapid advancements in the EV field, supported by improved isolation methods and sensitive assays for cargo characterization, brain cell–derived EVs continue to offer unparallel opportunities with significant translational implications for various neurological disorders. Significance Statement Extracellular vesicles present a less invasive liquid biopsy approach in the diagnosis and prognosis of various neurological disorders. Characterizing these vesicles in biofluids holds the potential to yield valuable molecular information, thereby significantly impacting the development of novel biomarkers for various neurological disorders. This paper has reviewed the methodology employed to isolate extracellular vesicles derived from various brain cells in biofluids, their utility in enhancing the molecular understanding of neurodegeneration, and the potential challenges in this research field.
Power of Social Media in Political Marketing – An India Based Empirical Study

This study aims to understand the importance of different factors of social media, along with relevant demographic variables of voters to predict a voter’s preferred political brand, in the context of the Indian Lok Sabha elections. To identify the relevant demographic variables, we have gone through previous literature. However, due to the lack of substantial India-based academic literature that could help us to identify the important factors of social media campaign, we referred to US-based academic literature and attempted to obtain the superset of social media impact variables. Thereafter, we conducted focussed group discussions to identify the most important attributes, which we’ve used in our survey study. We have chosen greater Kolkata to conduct the survey. We have used multinomial logistic regression model with voters’ preferred political brand as a dependent variable with four choices. We observed that there is no significant difference between the intercept and final (including all predictors) model and also found that no individual demographic and social media impact variables are significant predictors of voters’ preferred political brand. We also measured comparative effect on different political parties for each independent variable. That would help political marketers to target specific segments with effective communication and campaign plan.
Effect of Buffer Layer on the Physical Properties of Single Domain YBCO Bulk Superconductors

The buffer layer can play an important role in the fabrication of high quality REBCO bulk superconductors, because it can not only prevent the YBCO crystal from contaminating by the NdBCO seeds, but also can improve the successful rate of single domain YBCO bulk superconductors. However, the key problem is how to optimize the buffer layer for fabrication of single domain YBCO bulks, so in this paper, a group of YBCO bulks of 30 mm in diameters have been fabricated by NdBCO crystal seeds assisted with cylindrical buffer layers of diameter D = 13 mm and height H mm, H = 1, 2, 3, 4, 5, 6, 7, 8 mm. Both the levitation force and the trapped field of the samples are increasing first and decreasing then as H increases from 1 mm to 8 mm. The largest levitation force and the trapped field are achieved in the sample fabricated with the buffer layer of height H = 4 mm; The optimal ratio of H/R is about 0.615, nearly equal to the ratio of the YBCO crystal growth rate along the a-axis and c-axis directions. Based on this result, single domain YBCO bulks of φ93 mm have been fabricated by the Y+011 TSIG method. The results indicate that this is effective method for fabrication of high-quality single domain REBCO bulk superconductors.
Effectiveness of Self-Affirmation Interventions in Educational Settings: A Meta-Analysis

School and university can be stressful contexts that can become an important source of identity threats when social prejudices or stereotypes come into play. Self-affirmation interventions are key strategies for mitigating the negative consequences of identity threat. This meta-analysis aims to provide an overview of the effectiveness of self-affirmation interventions in educational settings. A peer-reviewed article search was conducted in January 2023. A total of 144 experimental studies that tested the effect of self-affirmation interventions in educational contexts among high school and university students from different social and cultural backgrounds were considered. The average effect of self-affirmation interventions was of low magnitude (dIG+ = 0.41, z = 16.01, p < 0.00), with a 95% confidence interval whose values tended to lie between 0.36 and 0.45 (SE = 0.0253). In addition, moderators such as identity threat, participants’ age, and intervention procedure were found. Through a meta-analysis of the impact of self-affirmation interventions in educational contexts, this study suggests that interventions are effective, resulting in a small mean effect size. Thus, self-affirmation interventions can be considered useful, brief, and inexpensive strategies to improve general well-being and performance in educational settings.
Molecular Detection of Microsporidia in Cattle in Jahrom, Iran

Background: Microsporidia are eukaryotic, single-celled intracellular parasites that can produce spores. Recently, they have been considered one of the opportunistic pathogens causing chronic diseases. There are more than 140 genera and 1200 species of microsporidia. Many human microsporidia are probably of zoonotic origin and are transmitted by contaminated water with animal feces. Given the zoonotic importance of this parasite and its ability to be transmitted from animals to humans, diagnosing and determining the species of parasite would seem essential for health strategies. Methods: Two hundred fecal samples of slaughtered cows were collected from the Jahrom abattoirs from February 2021 to January 2022 and examined by molecular methods, including polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP-PCR). Results: From the 200 samples examined by PCR, 19 (9.5%) samples tested positive for microsporidia, of which 17 isolates were Enterocytozoon bieneusi and two isolates were Encephalitozoon cuniculi. Conclusion: The results revealed that microsporidia were present in cow feces. In addition, these findings indicated that cows can be considered a source of contamination for microsporidia. Given that this disease is a zoonosis, it is highly important to pay attention to the presence of this parasite in domestic animals that are in contact with humans. Further studies must be performed in different regions and different animals to understand the epizootiology of the pathogen. Eventually, the wide host range of microsporidia necessitates accurate identification of species and genera in all hosts all over the world.
The Effectiveness of a Single Dry Needling Session on Gait and Quality of Life in Multiple Sclerosis: A Double-Blind Randomized Sham-Controlled Pilot Trial

Introduction: Gait disorders are a major cause of disability and reduced health-related quality of life in people with multiple sclerosis (pwMS). Dry needling (DN) has demonstrated positive results to improve gait parameters in patients with stroke. The main aim of this study was to evaluate the effect of a single session of DN in the gait performance of pwMS. Methods: A double-blind parallel randomized sham-controlled pilot trial was conducted. Study participants received a single session of active DN or sham DN in the gastrocnemius medialis muscle. Pre-treatment and immediately post-treatment measurements were taken, as well as at one and four weeks after the intervention. Outcomes related to gait performance (Timed 25-Foot Walk), self-perceived walking capacity (Multiple Sclerosis Walking Scale), risk of falls (Timed Up and Go test), disability level (Expanded Disability Status Score) and quality of life (Multiple Sclerosis Quality of Life-54 questionnaire and Analogic Quality of Life scale) were evaluated. Results: 18 patients who had multiple sclerosis participated in the study. The group who received active DN showed within-group significant statistical differences immediately after treatment for gait performance (p = 0.008) and risk of falls (p = 0.008), as well as for self-perceived walking capacity at one week (p = 0.017) and four weeks (p = 0.011) and quality of life at four weeks (p = 0.014). Regarding the comparison between groups, only significant results were obtained in the physical domain of the quality of life at four weeks (p = 0.014). Conclusions: DN seems to be a promising therapeutic tool for the treatment of gait disorders in pwMS. However, when results were compared with sham DN, no differences were found.
Clean Water Act 20 years later

This volume explores the issues associated with the complex subject of water quality protection in an assessment of the successes and failures of the Clean Water Act over the past twenty years. In addition to examining traditional indicators of water quality, the authors consider how health concerns of the public have been addressed, and present a detailed examination of the ecological health of waters. Taken together, these measures present a far more complete and balanced picture than raw water quality data alone. As well as reviewing past effectiveness, the book includes specific recommendations for the reauthorization of the Act.
Personality Traits and Charismatic Leader: An Innovative Perspective on Leadership

This paper explores the relationship between inherent personality traits and the emergence of charismatic leadership qualities. Drawing from established psychological models, such as the Five Factor Model, we identify key personality traits most associated with charismatic leaders, including extraversion, openness to experience, and emotional intelligence. Using both historical analysis and contemporary case studies, we demonstrate how these traits often manifest in leaders recognized for their charisma. However, we also discuss the role of environmental factors and personal experiences in shaping and amplifying these traits. Furthermore, the potential pitfalls of over-relying on charisma, to the detriment of other leadership qualities, are highlighted. Overall, the research suggests that certain personality traits, such as extraversion and conscientiousness, are associated with charismatic leadership behavior. These traits contribute to the ability of leaders to influence and mobilize others, create a positive group dynamic, and promote environmental management initiatives. Understanding the relationship between personality traits and charismatic leadership can provide valuable insights for organizations in selecting and developing effective leaders. The paper concludes with recommendations for organizations on how to foster and recognize leadership potential by considering a balance of inherent traits, cultivated skills, and contextual understanding.
Lateral pressure equalisation as a principle for designing support surfaces to prevent deep tissue pressure ulcers

When immobile or neuropathic patients are supported by beds or chairs, their soft tissues undergo deformations that can cause pressure ulcers. Current support surfaces that redistribute under-body pressures at vulnerable body sites have not succeeded in reducing pressure ulcer prevalence. Here we show that adding a supporting lateral pressure can counter-act the deformations induced by under-body pressure, and that this ‘pressure equalisation’ approach is a more effective way to reduce ulcer-inducing deformations than current approaches based on redistributing under-body pressure. A finite element model of the seated pelvis predicts that applying a lateral pressure to the soft tissue reduces peak von Mises stress in the deep tissue by a factor of 2.4 relative to a standard cushion — a greater effect than that achieved by using a more conformable cushion. The ratio of peak lateral pressure to peak under-body pressure was shown to regulate deep tissue stress better than under-body pressure alone. By optimising the magnitude and position of lateral pressure, tissue deformations can be reduced to that induced when suspended in a fluid. Our results explain the lack of efficacy in current support surfaces, and suggest a new approach to designing and evaluating support surfaces: ensuring sufficient lateral pressure is applied to counter-act under-body pressure.
Optimization of Random Forest Algorithm for Paddy Growth Stage Classification Using Bayesian Optimization and Oversampling

Remote sensing and machine learning (ML) technologies that have developed very rapidly allow data retrieval and processing for monitoring paddy field conditions with minimal human intervention. One of the machine learning algorithms that is widely used for paddy growth stage classification is Random Forest. This study rebuilt the Random Forest model with datasets derived from a combination of Area Sample Framework (KSA) data and Sentinel-1A imagery attributes. The highest accuracy result by this model is still <60%. Therefore, this study aims to examine how to optimize the Random Forest algorithm in classifying paddy growth stages. The optimization method used is to perform hyperparameter tuning with the Bayesian Optimization method and handle imbalanced data with oversampling techniques. As a result, the f1-score of Random Forest Optimization Model with Bayesian Optimization and oversampling increase in average of 6% and has a trend similar to the Random Forest baseline model with and produces a stable f1-score under varying dataset conditions.
Effect of hemp and basalt fiber on fracture energy of cement-based composites: a comparative study

Fiber-reinforced composites are one of the most used construction materials. Nowadays, some types of fibers like steel, carbon, glass and basalt are commonly used in these composites. However, the production of these fibers consumes natural resources and a high amount of energy. Researchers have started working on natural fibers to reduce commonly used fibers productions’ drawbacks for more sustainable composites. However, the effect of natural fibers on the properties of cement-based composites -especially fracture energy- still needs further research and comparing with the behavior of commonly used fibers. In this study the effect of hemp fiber on the mechanical properties and fracture energy of cement-based fiber-reinforced mortar mixtures was investigated. The results were compared with those of the basalt fiber-reinforced mixtures. The results showed that the flexural strength and fracture energy improved with the use of hemp and basalt fiber compared to the fiber-free mixture. The flexural strength increased up to 10.7% and 19.6% with the inclusion of hemp and basalt fibers, respectively. The mean peak load and fracture energy of hemp fiber-reinforced mortar was higher than those of the fiber-free mixture by 32.2% and 17.9%, respectively. The corresponding values for basalt fiber addition 60.8% and 146.4%.
Self-Supervised Variational Autoencoder for Unsupervised Object Counting from Very-High-Resolution Satellite Imagery: Applications in Dwelling Extraction in FDP Settlement Areas

In supervised learning, deep learning models demand a large corpus of annotated data for object detection and classification tasks. This constrains their utility in humanitarian emergency response. To overcome this problem, we have proposed an unsupervised dwelling counting from very-high-resolution (VHR) satellite imagery by combining a variational autoencoder (VAE) with an anomaly detection approach. When VAE applied in earth observation images for dwelling localization and counting, we observed two critical limitations: 1) the balance between reconstruction and good latent code, where the favor of good reconstruction of dwellings leads to weak anomaly score maps that fail to properly localize dwellings and 2) limited spatiotemporal invariance of the learned latent code. When the model is trained with datasets obtained from different geography and time, it fails to properly localize dwellings. For the first problem, we introduced self-supervision by creating synthetic anomalies. For the second problem, we introduced latent space conditioning. The approach is tested on nine VHR images obtained from six forcibly displaced people settlement areas. Results indicate that combining VAE with an anomaly detection approach has reached an area under the receiver operating characteristic curve value ranging from 0.70 at complex settlements to 0.98 at relatively less complex settlement areas. Similarly, a mean absolute error (MAE) value of 56.67 toward 5.03 is achieved for dwelling counting. Joint training of combined datasets with latent space conditioning and self-supervision enabled the achievement of results better than classical VAE, with improved spatiotemporal transferability of the model with more crisp and strong anomaly maps. Overall implementation code will be available at https://github.com/getch-geohum/SSL-VAE.
Exploring the implications of blocking renin-angiotensin-aldosterone system and fibroblast growth factor 23 in early left ventricular hypertrophy without chronic kidney disease

Background Whether fibroblast growth factor 23 (FGF23) directly induces left ventricular hypertrophy (LVH) remains controversial. Recent studies showed an association between FGF23 and the renin-angiotensin-aldosterone system (RAAS). The aim of this study was to investigate changes in FGF23 levels and RAAS parameters and their influences on LVH. Methods In the first experiment, male C57BL/6J mice were divided into sham and transverse aortic constriction (TAC) groups. The TAC group underwent TAC at 8 weeks of age. At 1, 2, 3, and 4 weeks after TAC, the mice were sacrificed, and blood and urine samples were obtained. Cardiac expressions of FGF23 and RAAS-related factors were evaluated, and cardiac histological analyses were performed. In the second experiment, the sham and TAC groups were treated with vehicle, angiotensin-converting enzyme (ACE) inhibitor, or FGF receptor 4 (FGFR4) inhibitor and then evaluated in the same way as in the first experiment. Results In the early stage of LVH without chronic kidney disease, serum FGF23 levels did not change but cardiac FGF23 expression significantly increased along with LVH progression. Moreover, serum aldosterone and cardiac ACE levels were significantly elevated, and cardiac ACE2 levels were significantly decreased. ACE inhibitor did not change serum FGF23 levels but significantly decreased cardiac FGF23 levels with improvements in LVH and RAAS-related factors, while FGFR4 inhibitor did not change the values. Conclusions Not serum FGF23 but cardiac FGF23 levels and RAAS parameters significantly changed in the early stage of LVH without chronic kidney disease. RAAS blockade might be more crucial than FGF23 blockade for preventing LVH progression in this condition.
Genetic correlations of productive and reproductive traits of Simmental cows in Republic of Serbia

SUMMARY Genetic improvement of milk quantity, of the milk fat and of prolificacy greatly depends on the phenotypic and genetic variability, heritability and correlation between wanted traits, as well as the production level within the population. The research was done on 3.461 first calving cows of Simmental breed under control with lactations concluded within one year. All first calving cows were reared by individual producers – farmers on the territory of Republic of Serbia. Genetic correlations were calculated using the equation of mixed model which included bull-sire, breeding region and calving year and season: Yijklm = ∝ + Bi + Rj + Gk + Sl + eijklm.