Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Environmental Heat and Antioxidant Ingestion on Blood Markers of Oxidative Stress in Professional Firefighters Performing Structural Fire Exercises

Objective: Firefighters (FFs) involved in fire suppression have the greatest on-duty risk of cardiovascular disease (CVD), which may be caused by oxidative stress (OS). Methods: Healthy, active FFs performed a victim “search and clear” exercise involving three conditions: (1) no heat, (2) heat + antioxidant, and (3) heat + placebo. Blood samples were analyzed for OS markers glutathione (GSH), oxidized glutathione (GSSG), superoxide dismutase (SOD), catalase (CAT), and advanced oxidation protein products (AOPP). Results: Increased GSH was found during both heat conditions compared with no heat. CAT activity was higher immediately post exercise. AOPP was reduced post exercise. Conclusions: Antioxidant supplementation did not impact the OS response to exercise. Added heat did not cause OS and exercise resulted in reductions in OS markers. These findings can be attributed to the training status of the FFs involved.
Integration of k-means clustering algorithm with network analysis for drug-target interactions network prediction

Prediction of the interactions between drugs and target proteins is an important factor in silico drug discovery. The number of known interactions is very small in comparison to the potential number of interactions. In this paper, a new method is proposed which combines data from both chemical structures and genomic sequence data. This method uses both supervised and unsupervised learning, as well as network analysis techniques. The proposed approach integrates k-means clustering algorithm with Social Network Analysis (SNA) techniques for a novel prediction of drug-target interactions. Here, we demonstrate the performance of our approach in the prediction of drug-target interactions by using four classes of drug-target interaction networks in human; enzymes, ion channels, G protein-coupled receptors (GPCRs), and nuclear receptors. The AUC curve is used to evaluate the accuracy of the proposed approach using three classifiers; Bayes Network, Naive Bayes and SVM. We could identify novel drug-protein interactions using the Bayes network classifier. The reported accuracy for enzymes, ion channels, GPCRs, and nuclear receptors are 98%, 85%, 98.6% and 99.2%.
Flavivirus Receptors: Diversity, Identity, and Cell Entry

Flaviviruses are emerging and re-emerging arthropod-borne pathogens responsible for significant mortality and morbidity worldwide. The genus comprises more than seventy small, positive-sense, single-stranded RNA viruses, which are responsible for a spectrum of human and animal diseases ranging in symptoms from mild, influenza-like infection to fatal encephalitis and haemorrhagic fever. Despite genomic and structural similarities across the genus, infections by different flaviviruses result in disparate clinical presentations. This review focusses on two haemorrhagic flaviviruses, dengue virus and yellow fever virus, and two neurotropic flaviviruses, Japanese encephalitis virus and Zika virus. We review current knowledge on host-pathogen interactions, virus entry strategies and tropism.
Follistatin‐like protein 5 inhibits hepatocellular carcinoma progression by inducing caspase‐dependent apoptosis and regulating Bcl‐2 family proteins

Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors in the world, especially in China. Follistatin‐like protein 5 (FSTL5) is a member of the FSTL family, which is involved in cell proliferation, migration, differentiation, and embryo development. We aimed to investigate the function and underlying mechanism of FSTL5 in HCC. FSTL5 expression was determined by immunohistochemistry staining in a liver cancer tissue microarray (TMA) and the correlation between FSTL5 and the prognosis of HCC patients was analysed. Further proliferation assay, colony formation assay, flow cytometry, and xenograft tumor model were performed to investigate the bioeffects of FSTL5 in HCC in vitro and in vivo. We found that FSTL5 expression was downregulated in HCC tissues and positively correlated with the prognosis of patients with HCC at tumor node metastasis stage I/II. Overexpression of FSTL5 efficiently impaired HCC growth both in vivo and in vitro with an exogenous manner. Mechanistic investigation demonstrated that FSTL5 promoted HCC cell apoptosis in a caspase‐dependent manner and regulated Bcl‐2 family proteins. These results indicate that FSTL5 may be a potential novel target for HCC treatment, and a biomarker for tumor prognosis.
Tree-Based Optimization: A Meta-Algorithm for Metaheuristic Optimization

Designing search algorithms for finding global optima is one of the most active research fields, recently. These algorithms consist of two main categories, i.e., classic mathematical and metaheuristic algorithms. This article proposes a meta-algorithm, Tree-Based Optimization (TBO), which uses other heuristic optimizers as its sub-algorithms in order to improve the performance of search. The proposed algorithm is based on mathematical tree subject and improves performance and speed of search by iteratively removing parts of the search space having low fitness, in order to minimize and purify the search space. The experimental results on several well-known benchmarks show the outperforming performance of TBO algorithm in finding the global solution. Experiments on high dimensional search spaces show significantly better performance when using the TBO algorithm. The proposed algorithm improves the search algorithms in both accuracy and speed aspects, especially for high dimensional searching such as in VLSI CAD tools for Integrated Circuit (IC) design.
A study on M/G/1 retrial queueing system with three different types of customers under working vacation policy

This paper deals with a single server retrial queueing system with working vacations and vacation interruption. There are three different types of customers are considered, which are priority customers, ordinary customers and negative customers. The priority customers do not form any queue and have an exclusive preemptive priority to receive their services over ordinary customers. The negative customer is arriving during the service time of any positive customer, will remove the positive customer from the service. If the interrupted customer is an ordinary customer, he will leave the system. As soon as the orbit becomes empty at the time of service completion, the server goes for a working vacation. The server works at a lower speed during a working vacation period. Using the supplementary variable technique, the steady-state probability generating a function of the system and its orbit are found. Some numerical examples are presented.
Effects of dietary supplemental lysophospholipids and vitamin C on performance, antioxidant enzymes, lipid peroxidation, thyroid hormones and serum metabolites of broiler chickens reared under thermoneutral and high ambient temperature

The effects of dietary supplemental lysophospholipids (LPLs) and vitamin C (VC) on performance, activity of antioxidant enzymes, and thyroid hormones of broiler chickens reared under thermoneutral and high ambient temperatures were evaluated. A total of 1,680 broiler chicks (Cobb 500) in finishing rearing period (days 21-38 of age) were allotted to two groups: thermoneutral (TN) and heat stress (HS). In the TN group, 480 chicks were subjected to four treatments with four replicates (n = 30) and maintained in usual ambient temperature (24 ± 1°C). In HS group, the remaining 1,200 chicks were subjected to four treatments with 10 replicates (n = 30) and exposed to high ambient temperature (34 ± 1°C for 8 hr daily). In both groups, four iso-caloric and iso-nitrogenous experimental diets based on a 2 × 2 factorial arrangements including supplemental LPLs (0 or 1,000 mg/kg) and VC (0 or 500 mg/kg) were formulated and used. Supplemental LPLs decreased (p < 0.05) body weight gain and increased FCR in the TN and HS groups. In the TN group, increased (p < 0.05) serum glucose was observed in chickens fed with dietary supplemental VC. In the HS group, decreased (p < 0.05) total protein concentration was detected in birds fed with supplemental LPLs. In both TN and HS groups, decreased (p < 0.05) uric acid concentration was detected in chicks fed with the VC-supplemented diets. A significant (p < 0.05) interaction between LPLs and VC on lactate concentration in the TN group was observed. In the HS group, decreased breast malondialdehyde concentration was detected in birds fed with the VC-supplemented diet. In the TN group, increased serum total antioxidant status was detected in birds fed with the LPLs-supplemented diet. In conclusion, LPLs improved oxidative stability and increased the antioxidant capacity of the serum. In addition, vitamin C modified heat stress and reduced lipid peroxidation.
Class-Switch Recombination (CSR)/Hyper-IgM (HIGM) Syndromes and Phosphoinositide 3-Kinase (PI3K) Defects

Antibody production and function represent an essential part of the immune response, particularly in fighting bacterial and viral infections. Multiple immunological phenotypes can result in dysregulation of the immune system humoral compartment, including class-switch recombination (CSR) defects associated with hyper-IgM (HIGM) syndromes. The CSR/HIGM syndromes are defined by the presence of normal or elevated plasma IgM levels in the context of low levels of switched IgG, IgA, and IgE isotypes. Recently described autosomal dominant gain-of-function (GOF) mutations in PIK3CD and PIK3R1 cause combined immunodeficiencies that can also present as CSR/HIGM defects. These defects, their pathophysiology and derived clinical manifestations are described in depth. Previously reported forms of CSR/HIGM syndromes are briefly reviewed and compared to the phosphoinositide 3-kinase (PI3K) pathway defects. Diseases involving the PI3K pathway represent a distinctive subset of CSR/HIGM syndromes, presenting with their own characteristic clinical and laboratory attributes as well as individual therapeutic approaches.
Prey selection can cause novel coevolutionary patterns

Many theoretical models have been formulated to better understand the coevolutionary patterns that emerge from antagonistic interactions. In most of these models it is assumed that the attacks by the exploiters are random, so that the effect of victim selection by exploiters on coevolutionary patterns remains unexplored. Here we study an individual-based model for the coevolution of predators and prey in which every individual predator can attack only a small number of prey any given time. We investigate coevolutionary patterns that result from two scenarios: (i) predation occurs at random; (ii) predators select prey according to phenotype matching. We show that both scenarios result in well known similar coevolutionary patterns if population sizes are sufficiently high: symmetrical coevolutionary branching and symmetrical coevolutionary cycling (Red Queen dynamics). However, for small population sizes prey selection can cause other coevolutionary patterns that have not yet been reported. One is the breaking of symmetry of the coevolutionary pattern, where the phenotypes evolve towards one of two evolutionarily stable patterns. As population size increases, the phenotypes oscillate between these two values in a novel form of Red Queen dynamics, the episodic reversal between the two stable patterns. Thus, prey selection causes prey phenotypes to evolve towards more extreme values, which reduces the fitness of both predators and prey, increasing the likelihood of extinction. An analytical approach allows us to show the robustness of our results.
performance limitations for LTI discrete-time systems in the presence of stochastic disturbance

ABSTRACT This paper concerns the fundamental limitations of disturbance rejection for linear time-invariant discrete-time systems under the assumption that the sensor noise is ignorable. The environmental disturbance is modelled as a linear combination of a step signal, a stationary stochastic signal and several sinusoidal signals with different frequencies. Disturbance rejection is measured by the steady-state variance of the residual input of the plant. In studying this problem, it is shown that for minimum phase systems, perfect disturbance rejection can be achieved by minimising the closed-loop sensitivity function. Unlike the minimum phase systems, the performance limitations for non-minimum phase systems are lower bounded by its non-minimum phase zeros, unstable poles and characteristic quantities of the disturbance, where the typical and integral-type control are respectively addressed. Numerical examples are provided to illustrate the utility of the results by analysing the achievable performance.
Collaborative Learning for Extremely Low Bit Asymmetric Hashing

Hashing techniques are in great demand for a wide range of real-world applications such as image retrieval and network compression. Nevertheless, existing approaches could hardly guarantee a satisfactory performance with the extremely low-bit (e.g., 4-bit) hash codes due to the severe information loss and the shrink of the discrete solution space. In this article, we propose a novel Collaborative Learning strategy that is tailored for generating high-quality low-bit hash codes. The core idea is to jointly distill bit-specific and informative representations for a group of pre-defined code lengths. The learning of short hash codes among the group can benefit from the manifold shared with other long codes, where multiple views from different hash codes provide the supplementary guidance and regularization, making the convergence faster and more stable. To achieve that, an asymmetric hashing framework with two variants of multi-head embedding structures is derived, termed as Multi-head Asymmetric Hashing (MAH), leading to great efficiency of training and querying. Extensive experiments on three benchmark datasets have been conducted to verify the superiority of the proposed MAH, and have shown that the 8-bit hash codes generated by MAH achieve 94.3 percent of the MAP11.Mean Average Precision (MAP) score on the CIFAR-10 dataset, which significantly surpasses the performance of the 48-bit codes by the state-of-the-arts in image retrieval tasks.
Slogatron: Advanced Wealthiness Generator

Creating catchy slogans is a demanding and clearly creative job for ad agencies. The process of slogan creation by humans involves finding key concepts of the company and its products, and developing a memorable short phrase to describe the key concept. We attempt to follow the same sequence, but with an evolutionary algorithm. A user inputs a paragraph describing describing the company or product to be promoted. The system randomly samples initial slogans from a corpus of existing slogans. The initial slogans are then iteratively mutated and improved using an evolutionary algorithm. Mutation randomly replaces words in an individual with words from the input paragraphs. Internal evaluation measures a combination of grammatical correctness, and semantic similarity to the input paragraphs. Subjective analysis of output slogans leads to the conclusion that the algorithm certainly outputs valuable slogans. External evaluation found that the slogans were somewhat successful in conveying a message, because humans were generally able to select the correct promoted item given a slogan.
Stat3 activation is critical for pluripotency maintenance

Signal transducer and activator of transcription 3 (Stat3) is a cytoplasmic transcription with many important functions, including regulation of cell proliferation, differentiation, survival, angiogenesis, and immune response. Besides, it plays critical roles in regulating the pluripotency. With the ability of self‐renewal and differentiation, embryonic stem (ES) cells provide an unlimited source for cell transplantation. ES cells can maintain its undifferentiated state with leukemia inhibitory factor, the role which is achieved by the activation of the Stat3 pathway. Moreover, Stat3 activation is necessary for the naïve state maintenance of the ES cells and somatic stem cells reprogramming. This study presents an overview of the critical roles of Stat3 activation in the pluripotency maintenance of ES cells, somatic cell reprogramming, and naïve‐primed pluripotent states conversion of ES cells.
Double Probability Model for Open Set Problem at Image Classification

In this paper an exploratory classiﬁcation, so called open set problem, is investigated. Open set recognition assumes there is incomplete knowledge of the world at training time, and unknown classes can be submitted to an algorithm during testing. For this problem we elaborated a theoretical model, Double Probability Model (DPM), based on likelihoods of a classiﬁer. We developed it with double smoothing solution in order to solve technical diﬃculties avoiding zero values in the predictions. We applied the GMM based Fisher vector for the mathematical representation of the images and the C-SVC with RBF kernel for the classiﬁcation. The last contributions of the paper are new goodness indicators for classiﬁcation in open set problem, the new type of accuracies. The experimental results present that our Double Probability Model helps with classiﬁcation, the accuracy increases by using our proposed model. We compared our method to a state-of-the-art open set recognition solution and the results showed that DPM outperforms existing techniques.
Multiscale wavelet decomposition of time-resolved X-ray diffraction signals in cyclohexadiene

Significance Free electron laser sources of ultrafast X-ray pulses can record movies of chemical reactions by measuring snapshots of the charge density along the reaction path on the femtosecond timescale. Only a few valence electrons typically participate in chemical bond breaking and forming. To separate the valence electron density from the strong background of highly localized core electrons we use a wavelet transform, a powerful tool for filtering, and scaling analysis of signals. The wavelet-processed signal from the cyclohexadiene molecule reported here clearly reveals the valence electron rearrangements in the early steps of the photoinduced pericyclic ring opening reaction, which are not resolved in the bare signal. This multiscale analysis of charge densities should be extremely valuable for disentangling complex reaction pathways. We demonstrate how the wavelet transform, which is a powerful tool for compression, filtering, and scaling analysis of signals, may be used to separate large- and short-scale electron density features in X-ray diffraction patterns. Wavelets can isolate the electron density associated with delocalized bonds from the much stronger background of highly localized core electrons. The wavelet-processed signals clearly reveal the bond formation and breaking in the early steps of the photoinduced pericyclic ring opening reaction of 1,3-cyclohexadiene, which are not resolved in the bare signal.
Taxonomy Meets Neurology, the Case of Amyotrophic Lateral Sclerosis

Recent landmark publications from our research group outline a transformative approach to defining, studying and treating amyotrophic lateral sclerosis (ALS). Rather than approaching ALS as a single entity, we advocate targeting therapies to distinct “clusters” of patients based on their specific genomic and molecular features. Our findings point to the existence of a molecular taxonomy for ALS, bringing us a step closer to the establishment of a precision medicine approach in neurology practice.
Leakage-Resilient Certificateless Key Encapsulation Scheme

The previous adversary models of public key cryptography usually have a nature assumption that permanent/temporary secret (private) keys must be kept safely and internal secret states are not leaked to an adversary. However, in practice, it is difficult to keep away from all possible kinds of leakage on these secret data due to a new kind of threat, called “side-channel attacks”. By sidechannel attacks, an adversary could obtain partial information of these secret data so that some existing adversary models could be insufficient. Indeed, the study of leakage-resilient cryptography resistant to side-channel attacks has received significant attention recently. Up to date, no work has been done on the design of leakage-resilient certificateless key encapsulation (LR-CL-KE) or public key encryption (LR-CL-PKE) schemes under the continual leakage model. In this article, we propose the first LR-CL-KE scheme under the continual leakage model. Moreover, in the generic bilinear group (GBG) model, we formally prove that the proposed LR-CL-KE scheme is semantically secure against chosen ciphertext attacks for both Type I and Type II adversaries.
Thermoplastic Polyurethane Blends With Thermal Energy Storage/Release Capability

In this work innovative the thermal energy storage materials were developed by encapsulating a paraffin having a melting temperature of 6 °C (M6D) in a thermoplastic polyurethane (TPU), and the most important physical properties of the resulting samples were investigated from a thermo-mechanical point of view. Field emission scanning electron microscope (FESEM) micrographs demonstrated a homogeneous microcapsules distribution and good interfacial adhesion with the TPU matrix even at elevated M6D concentrations. With a capsule concentration of 60 wt% it was possible to obtain elevated melting enthalpy values (up to 95 J/g), retaining the energy storage/release properties even after 50 thermal cycles. The hardness and the dimensional stability of the TPU matrix above its glass transition temperature were strongly increased upon M6D addition, but this stiffening effect was associated to a certain embrittlement. The investigated blends could be applied for winter sport application for low temperature thermal energy storage/release materials.
Sex- and Gender-Related Factors Associated With Cardiac Rehabilitation Enrollment: A SECONDARY ANALYSIS AMONG SYSTEMATICALLY REFERRED PATIENTS.

PURPOSE To assess sex- and gender-related factors associated with cardiac rehabilitation (CR) enrollment following acute coronary syndrome among systematically referred patients. METHODS This secondary analysis of a randomized controlled trial used an exploratory approach to examine the TRANSITion process for patients between the coronary care unit and CR (TRANSIT-UC). The present analysis examined the relationship between sex- and gender-related factors and CR enrollment in systematically referred women (n = 35) and men (n = 207). We performed χ and logistic regression analyses to identify statistically significant results. Using the Bonferroni method, a P value of . 002 or less was considered a significant statistical result. A raw difference of 15% or more between enrolled and nonenrolled participants was considered a difference worthy of further investigation. RESULTS Men who were regularly engaged in physical activity prior to their hospitalization and who lived near the CR center showed a statistically higher CR enrollment rate. In women and men, a radial entry site for percutaneous coronary intervention resulted in a clinically significant difference in favor of CR enrollment. In women, 3 sex-related and 9 gender-related variables were associated with a difference of 15% or more between enrolled and nonenrolled participants. CONCLUSION Factors related to CR enrollment in women and men are suggested. As women keep showing a lower rate of CR enrolment, the investigation of these factors in a larger sample of patients may hold valuable insights to improve CR enrolment.