Miracle-dz/UniFAR-FTUs huggingface dataset:
Speed regulation strategy and algorithm for the variable-belt-speed energy-saving control of a belt conveyor based on the material flow rate

As an important transportation, the belt conveyor has been widely used and researched. It is urgent to solve the problem of energy saving and consumption reduction of belt conveyor. Aiming at reducing high energy consumption in the rated-speed operation of a belt conveyor, the present paper establishes an energy-saving belt-speed model of a belt conveyor using a polynomial regression-fitting algorithm and a small number of sample observations, and proposes a speed regulation strategy and particle swarm optimization–proportional–integral–derivative algorithm for the variable-belt-speed energy-saving control of a belt conveyor based on the material flow rate. The control strategy and algorithm adjust the running speed of the belt conveyor accurately according to changes in the material flow rate, thus reducing damage of frequent speed regulation to the belt conveyor and saving energy. Simulation analysis of a practical case shows that energy-saving belt-speed model, speed regulation strategy, and algorithm effectively reduce the energy consumption of a belt conveyor, and they thus have high application value in coal, ports, power, mine, metallurgy, chemical, and other industries. Further work in this field can be focused on the prediction of material flow rate of belt conveyor, the controllable adjustment duration of algorithm and the reduction of overshoot.
Comprehensive Study on Enhancing Low-Quality Position-Specific Scoring Matrix with Deep Learning for Accurate Protein Structure Property Prediction: Using Bagging Multiple Sequence Alignment Learning

Accurate predictions of protein structure properties, for example, secondary structure and solvent accessibility, are essential in analyzing the structure and function of a protein. Position-specific scoring matrix (PSSM) features are widely used in the structure property prediction. However, some proteins may have low-quality PSSM features due to insufficient homologous sequences, leading to limited prediction accuracy. To address this limitation, we propose an enhancing scheme for PSSM features. We introduce the "Bagging MSA" (multiple sequence alignment) method to calculate PSSM features used to train our model, adopt a convolutional network to capture local context features and bidirectional long short-term memory for long-term dependencies, and integrate them under an unsupervised framework. Structure property prediction models are then built upon such enhanced PSSM features for more accurate predictions. Moreover, we develop two frameworks to evaluate the effectiveness of the enhanced PSSM features, which also bring proposed method into real-world scenarios. Empirical evaluation of CB513, CASP11, and CASP12 data sets indicates that our unsupervised enhancing scheme indeed generates more informative PSSM features for structure property prediction.
The Relationship of Neuroticism with Sleep Quality: The Mediating Role of Emotional, Cognitive and Metacognitive Factors

ABSTRACT Background Poor sleep quality is associated with a broad range of psychopathology and is a common problem among college students. This study aimed to investigate the mediating role of metacognitive beliefs related to sleep, emotion regulation and a negative cognitive style related to anxiety (looming cognitive style) in the relation between neuroticism and reported sleep quality. Participants Participants were 343 undergraduates from three universities in Tehran (56.3% females, Mean age = 22.01 ± 2.74 years). Method Data were gathered with a questionnaire packet that included the Pittsburgh Sleep Quality Index (PSQI), Metacognitions Questionnaire-Insomnia (MCQ-I), Emotion Regulation Questionnaire (ERQ), Looming Maladaptive Style Questionnaire (LMSQ) and Neuroticism subscale of NEO-PI-R. Results Structural equation modeling analyses supported a proposed model (R2 = 37%) which proposed that neuroticism both directly and indirectly linked to reported sleep quality through metacognitions related to sleep, cognitive reappraisal and looming cognitive style (χ2 = 1194.87, p < .001; CFI = 0.93, NFI = 0.90, RMSEA = 0.065, GFI = 0.92, SRMR = 0.069, IFI = 0.93). Conclusions The results provide evidence for the impact of neuroticism on reported sleep quality through metacognitive, cognitive and emotional factors. The result suggest that special attention should be paid to these factors in the treatment and psychopathology of sleep quality.
Evaluating the risk of manganese-induced neurotoxicity of parenteral nutrition: review of the current literature

ABSTRACT Introduction Several diseases and clinical conditions can affect enteral nutrition and adequate gastrointestinal uptake. In this respect, parenteral nutrition (PN) is necessary for the provision of deficient trace elements. However, some essential elements, such as manganese (Mn) may be toxic to children and adults when parenterally administered in excess, leading to toxic, especially neurotoxic effects. Areas covered Here, we briefly provide an overview on Mn, addressing its sources of exposure, the role of Mn in the etiology of neurodegenerative diseases, and focusing on potential mechanisms associated with Mn-induced neurotoxicity. In addition, we discuss the potential consequences of overexposure to Mn inherent to PN. Expert opinion In this critical review, we suggest that additional research is required to safely set Mn levels in PN, and that eliminating Mn as an additive should be considered by physicians and nutritionists on a case by case basis in the meantime to avoid the greater risk of neurotoxicity by its presence. There is a need to better define clinical biomarkers for Mn toxicity by PN, as well as identify new effective agents to treat Mn-neurotoxicity. Moreover, we highlight the importance of the development of new guidelines and practice safeguards to protect patients from excessive Mn exposure and neurotoxicity upon PN administration.
Grading hypoxic-ischemic encephalopathy in neonatal EEG with convolutional neural networks and quadratic time–frequency distributions

Objective. To develop an automated system to classify the severity of hypoxic-ischaemic encephalopathy injury (HIE) in neonates from the background electroencephalogram (EEG). Approach. By combining a quadratic time–frequency distribution (TFD) with a convolutional neural network, we develop a system that classifies 4 EEG grades of HIE. The network learns directly from the two-dimensional TFD through 3 independent layers with convolution in the time, frequency, and time–frequency directions. Computationally efficient algorithms make it feasible to transform each 5 min epoch to the time–frequency domain by controlling for oversampling to reduce both computation and computer memory. The system is developed on EEG recordings from 54 neonates. Then the system is validated on a large unseen dataset of 338 h of EEG recordings from 91 neonates obtained across multiple international centres. Main results. The proposed EEG HIE-grading system achieves a leave-one-subject-out testing accuracy of 88.9% and kappa of 0.84 on the development dataset. Accuracy for the large unseen test dataset is 69.5% (95% confidence interval, CI: 65.3%–73.6%) and kappa of 0.54, which is a significant ( P<0.001 ) improvement over a state-of-the-art feature-based method with an accuracy of 56.8% (95% CI: 51.4%–61.7%) and kappa of 0.39. Performance of the proposed system was unaffected when the number of channels in testing was reduced from 8 to 2—accuracy for the large validation dataset remained at 69.5% (95% CI: 65.5%–74.0%). Significance. The proposed system outperforms the state-of-the-art machine learning algorithms for EEG grade classification on a large multi-centre unseen dataset, indicating the potential to assist clinical decision making for neonates with HIE.
Genomic features and antimicrobial resistance patterns of Shiga toxin‐producing Escherichia coli strains isolated from food in Chile

Shiga toxin‐producing Escherichia coli (STEC) is a zoonotic pathogen that causes severe illness in humans, often associated with foodborne outbreaks. Antimicrobial resistance among foodborne E. coli has increased over the last decades becoming a public health issue. In this study, the presence and features of STEC were investigated in samples of meat, seafood, vegetables and ready‐to‐eat street‐vended food collected in Chile, using a genomic and microbiological approach. Phenotypic and genotypic antimicrobial resistance profiles were determined, and serotype, phylogroup, sequence type (ST) and phylogenomics were predicted using bioinformatic tools. Three thousand three hundred samples collected in 2019 were screened, of which 18 were positive for STEC strains (0.5%), with stx2a (61.1%) being the predominant stx subtype. The presence of the virulence genes lpfA (100%), iha and ehaA (94.4%), and ehxA, hlyA and saa (83.3%) was confirmed among the STEC strains; the Locus of adhesion and autoaggregation (LAA) was predicted in 14 (77.8%) strains. Strains displayed resistance to colistin (100%), and intermediate resistance to enrofloxacin (11.1%) and chloramphenicol (5.6%). In this regard, mutations in the two‐component regulatory system genes pmrA (S29G), pmrB (D283G) and phoP (I44L), and the presence of the qnrB19 gene were confirmed. STEC strains belonged to ST11231 (38.9%), ST297 and ST58 (16.7% each), and ST1635, ST11232, ST446, ST442 and ST54 (5.6% each), and the most frequently detected serotypes were O113:H21 (44.4%), O130:H11 and O116:H21 (16.7% each), and O174:H21 (11.1%). Strains belonging to the international ST58 showed genomic relatedness with worldwide strains from human and non‐human sources. Our study reports for the first time the genomic profile of STEC strains isolated from food in Chile, highlighting the presence of international clones and sequence types commonly associated with human infections in different geographical regions, as well as the convergence of virulence and resistance in STEC lineages circulating in this country.
A knowledge, attitudes, and practices study on ticks and tick-borne diseases in cattle among farmers in a selected area of eastern Bhutan

Livestock farming plays an important role in supporting the livelihood of resource-poor subsistence farmers in Bhutan. However, ticks and tick-borne diseases (TBDs) are one of the major constraints to livestock farming due to their negative effect on health and production. To date, no study has been conducted in Bhutan to assess farmers’ knowledge, attitude, and practices (KAP) about ticks and TBDs in cattle, although such information is essential in ensuring the development and adoption of effective prevention and control measures. Therefore, a KAP survey was conducted among 246 cattle owners in the Samkhar sub-district of eastern Bhutan in June 2019, using a structured questionnaire. Based on our scoring criteria, 52% [95%CI: 45.5–58.4] had adequate knowledge about ticks as potential vectors of diseases. Logistic regression analysis showed that the individuals who practiced a stall-feeding system of cattle rearing were 2.8 times [OR = 2.8 (95%CI: 1.66–4.78)] more likely to have adequate knowledge than others. Sixty-eight percent [95%CI: 62.5–74.4] had a favorable attitude toward tick prevention and control programs. Men were 1.95 times [OR = 1.95 (95%CI: 1.09–3.55)] more likely to have a favorable attitude than women, and the individuals who practiced a stall-feeding system were 2.59 times [OR = 2.59 95%CI: 1.45–4.78)] more likely to have a favorable attitude than others, after adjusting for the effect of other variables in the model. Overall, only 38% [95%CI 32.5–45] of the respondents reported tick infestation as one of the most important animal health problems, but 100% reported using acaricides to control ticks in cattle. Despite a high level of acaricide usage, the level of knowledge was low among the farmers interviewed. Findings from this study underline the importance of considering identified knowledge gaps and initiating education efforts to improve the adoption of effective tick prevention and control measures among farmers.
Fatigue strength estimation of butt welded joints in magnesium AZ31 alloy using the genetic algorithm

Genetic Algorithm is applied to calculate the substitute structural length (SSL) and obtain the fatigue strength of welded joints in magnesium. Fatigue tests with unnotched and notched specimens of the base material metal (BM), the weld metal (WM) and the heat‐affected zone (HAZ) of magnesium AZ31 (MgAl3) were carried out in order to derive the unknown substitute structural length. Results of fatigue tests with geometrically similar welded joints with full and partial penetration were available. The comparison of the experimental and predicted substitute structural length using Genetic Algorithm Substitute Structural Length Estimation Model (GASLEM) shows that the developed models seem to be capable of predicting the SSL values. Fatigue strength values were also obtained using predicted SSL.
The New Genetic Evidence on Same-Gender Sexuality: Implications for Sexual Fluidity and Multiple Forms of Sexual Diversity

ABSTRACT In September of 2019, the largest-ever (N = 477,522) genome-wide-association study of same-gender sexuality was published in Science. The primary finding was that multiple genes are significantly associated with ever engaging in same-gender sexual behavior, accounting for between 8–25% of variance in this outcome. Yet an additional finding of this study, which received less attention, has more potential to transform our current understanding of same-gender sexuality: Specifically, the genes associated with ever engaging in same-gender sexual behavior differed from the genes associated with one’s relative proportion of same-gender to other-gender behavior. I review recent research on sexual orientation and sexual fluidity to illustrate how these findings speak to longstanding questions regarding distinctions among subtypes of same-gender sexuality (such as mostly-heterosexuality, bisexuality, and exclusive same-gender experience). I conclude by outlining directions for future research on the multiple causes and correlates of same-gender expression.
Androgen receptors in areas of the spinal cord and brainstem: A study in adult male cats

Sex hormones, including androgens and estrogens, play an important role in autonomic, reproductive and sexual behavior. The areas that are important in these behaviors lie within the spinal cord and brainstem. Relevant dysfunctional behavior in patients with altered androgen availability or androgen receptor sensitivity might be explained by the distribution of androgens and their receptors in the central nervous system. We hypothesize that autonomic dysfunction is correlated with the androgen sensitivity of spinal cord and brainstem areas responsible for autonomic functions. In this study, androgen receptor immunoreactive (AR‐IR) nuclei in the spinal cord and brainstem were studied using the androgen receptor antibody PG21 in four uncastrated young adult male cats. A dense distribution of AR‐IR nuclei was detected in the superior layers of the dorsal horn, including lamina I. Intensely stained nuclei, but less densely distributed, were found in lamina X and preganglionic sympathetic and parasympathetic cells of the intermediolateral cell column. Areas in the caudal brainstem showing a high density of AR‐IR nuclei included the area postrema, the dorsal motor vagus nucleus and the retrotrapezoid nucleus. More cranially, the central linear nucleus in the pons contained a dense distribution of AR‐IR nuclei. The mesencephalic periaqueductal gray (PAG) showed a dense distribution of AR‐IR nuclei apart from the most central part of the PAG directly adjacent to the ependymal lining. Other areas in the mesencephalon with a dense distribution of AR‐IR nuclei were the dorsal raphe nucleus, the retrorubral nucleus, the substantia nigra and the ventral tegmental area of Tsai. It is concluded that AR‐IR nuclei are located in specific areas of the central nervous system that are involved in the control of sensory function and autonomic behavior. Furthermore, damage of these AR‐IR areas might explain related dysfunction in humans.
Policy Action Within Urban African Food Systems to Promote Healthy Food Consumption: A Realist Synthesis in Ghana and Kenya

Background: Obesity and nutrition-related non-communicable diseases (NR-NCDs) are increasing throughout Africa, driven by urbanisation and changing food environments. Policy action has been limited - and influenced by high income countries. Socio-economic/political environments of African food systems must be considered in order to understand what policy might work to prevent NR-NCDs, for whom, and under what circumstances. Methods: A realist synthesis of five policy areas to support healthier food consumption in urban Africa: regulating trade/foreign investment; regulating health/nutrition claims/labels; setting composition standards for processed foods; restricting unhealthy food marketing; and school food policy. We drew upon Ghana and Kenya to contextualise the evidence base. Programme theories were generated by stakeholders in Ghana/Kenya. A two-stage search interrogated MEDLINE, Web of Science and Scopus. Programme theories were tested and refined to produce a synthesised model. Results: The five policies operate through complex, inter-connected pathways moderated by global-, national- and local contexts. Consumers and the food environment interact to enable/disable food accessibility, affordability and availability. Consumer relationships with each other and retailers are important contextual influences, along with political/ economic interests, stakeholder alliances and globalized trade. Coherent laws/regulatory frameworks and government capacities are fundamental across all policies. The increasing importance of convenience is shaped by demographic and sociocultural drivers. Awareness of healthy diets mediates food consumption through comprehension, education, literacy and beliefs. Contextualised data (especially food composition data) and inter-sectoral collaboration are critical to policy implementation. Conclusion: Evidence indicates that coherent action across the five policy areas could positively influence the healthiness of food environments and consumption in urban Africa. However, drivers of (un)healthy food environments and consumption reflect the complex interplay of socio-economic and political drivers acting at diverse geographical levels. Stakeholders at local, national, and global levels have important, yet differing, roles to play in ensuring healthy food environments and consumption in urban Africa.
Intrahepatic Cholangiocarcinoma: State of the Art of FGFR Inhibitors

Objective: Intrahepatic cholangiocarcinoma (iCCA), the second most common type of primary liver tumor, has an increasing incidence in the past few decades. iCCA is highly malignant, with a 5-year survival rate of approximately 5-10%. Surgical resection is usually the prescribed treatment for patients with early stage iCCA; however, patients are usually in an advanced stage iCCA upon diagnosis. Currently, targeted therapy combined with chemotherapy and other comprehensive treatment measures have been mainly adopted as palliative treatment measures. As a common candidate of targeted therapy, FGFR inhibitors have demonstrated their unique advantages in clinical trials. At present, the prospect of FGFR targeted therapy is encouraging. The landscape of FGFR inhibitors in iCCA is needed to be showed urgently. Methods: We searched relative reports of clinical trials on FGFR inhibitors in PubMed as well as Web of Science. We also concluded other available clinical trials of FGFR inhibitors (Data were collected from clinicaltrials.gov). Results: Several relatively effective targeted drugs are being used in clinical trials. Some preliminary results indicate the outlook of targeted therapy such as BGJ398, TAS120, and HSP90 inhibitors. Conclusions: In summary, FGFR targeted therapy has broad prospects for the treatment of iCCA.
Symmetric and nonsymmetric tricritical points in liquid sulfur and ‘‘living polymer’’ solutions

The dilute n→0 vector model recently used to model the phase equilibria in sulfur solutions and living polymers possesses a nonsymmetrical tricritical point, of the sort found in three‐ and more‐component solutions, at a small nonzero value of the magnetic field as well as the symmetric tricritical point at zero field. This has interesting consequences for the phase diagrams of both living polymers and sulfur solutions and suggests a resolution of a number of discrepancies between the earlier (zero field) theory of Scott and experiments on sulfur solutions.
Fluorescent and triplet state photoactive J-type phthalocyanine nano assemblies: controlled formation and photosensitizing properties

Cofacial J type nano aggregates, which are both fluorescent and triplet state photoactive, were formed in chloroform via multiple O → Zn2+ coordination bonds between molecules of ZnPc(α-OPh)4, i.e. tetra(α-phenoxy) zinc phthalocyanine. Non photoactive H aggregates, on the other hand, were observed in DMF–water mixtures. The formation, structure and bonding of the J aggregates were examined by TEM, electronic absorption and fluorescence methods. Photophysical studies revealed that the J-aggregates have narrowed absorption and emission bands with peak wavelengths at 740 and 751 nm, which are 50 nm and 43 nm red shifted from the values of the monomers, respectively. The fluorescence decay of the J aggregates is monoexponential with a long lifetime of 2.41 ns, in contrast to J aggregates of other dyes that usually exhibit much shorter, while widely distributed, lifetimes in the ps scale due to the loosely formed structures. The J aggregates emit fluorescence with an efficiency as high as 50% of its monomer. The laser flash photolysis study revealed that both the triplet state and anion species were generated upon photo excitation. The triplet state was formed in a quantum yield of 0.20 and its lifetime is 11 μs, which makes it sufficiently effective to transfer triplet energy and produce singlet oxygen with a yield of 0.23. The J aggregates represent a new category of nano assemblies that have the potential to be utilized in a variety of optoelectronic devices and photodynamic therapy of tumors.
Statistically Designed Extraction of Herbs Using Ultrasound Waves: A Review.

BACKGROUND Extraction is the foremost step to isolate the natural constituents from a medicinal plant and leads the process of development of herbal formulation from bench to bed. INTRODUCTION In the field of extraction, the optimization approach helps in achieving better yield and quality where a response of concern is determined or influenced by various variables. This review aimed at congregating the application of different statistical designs (CCD/BBD) to optimize the Ultrasound assisted extraction (UAE) parameters for the recovery of various plant actives belonging to different categories. METHODOLOGY The literature published during last decade in the various reputed databases (Web of Science, Pubmed, Scopus) was reviewed and compiled to reveal the role of response surface methodology in optimizing the influential parameters involved in the ultrasound assisted extraction of herbs. CONCLUSION From the present investigations, it can be concluded that the different variables such as sonication power, temperature, time, solute to solvent ratio are generally optimized in UAE of herbs. Moreover, it has also been evidenced from the review of published data that the flavonoids/phenolic acids (>50%) leads the race for the extraction of plants using sound waves. It can be said that the statistically designed UAE has vast prospective in bringing about a green mutiny in herbal drug industry and the modeling of various parameters shall be able to absolutely build up a complete drug innovation course (bench to bed).