Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Tellurium–Lignin Nanoparticles with Enhanced Antibacterial Properties

The surge of antibiotic-resistant bacteria is leading to the loss of effectiveness of antibiotic treatment, resulting in prolonged infections and even death. Against this healthcare threat, antimicrobial nanoparticles that hamper the evolution of resistance mechanisms are promising alternatives to antibiotics. Herein, we used Kraft lignin, a poorly valorized polymer derived from plant biomass, to develop novel hybrid tellurium–lignin nanoparticles (TeLigNPs) as alternative antimicrobial agents. The sonochemically synthesized TeLigNPs are comprised of a lignin matrix with embedded Te clusters, revealing the role of lignin as both a reducing agent and a structural component. The hybrid NPs showed strong bactericidal effects against the Gram-negative Escherichia coli and Pseudomonas aeruginosa, achieving more than 5 log bacteria reduction, while they only slightly inhibited the growth of the Gram-positive Staphylococcus aureus. Exposure of TeLigNPs to human cells did not cause morphological changes or reduction in cell viability. Studies on the antimicrobial mechanism of action demonstrated that the novel TeLigNPs were able to disturb bacterial model membranes and generate reactive oxygen species (ROS) in Gram-negative bacteria.
Co-infection with Severe Fever with Thrombocytopenia Syndrome Virus and Rickettsia japonica after Tick Bite, Japan

Severe fever with thrombocytopenia syndrome was diagnosed in a febrile woman in Japan after a tick bite. However, Rickettsia japonica DNA was retrospectively detected in the eschar specimen, suggesting co-infection from the bite. Establishment of the severe fever with thrombocytopenia syndrome virus infection might have overpowered the R. japonica infection.
Application of distance geometry to protein tertiary structure calculations

A general approach to the problem of molecular conformation is advanced. We describe a formalism that permits experimental and theoretical information to be incorporated into a set of upper and lower bounds on intramolecular distances. Structures (conformations) meeting these bounds can be readily generated and compared with each other. To illustrate the use of the method, we have employed a simple “firehose” model for protein folding to predict the long‐range hydrophobic interactions in a small protein: pancreatic trypsin inhibitor. Models of this type lead to the proper hairpin turns and a reasonable set of long‐range contacts for this protein. Application of the distance geometry method then yields backbone conformations with errors of 4–8 Å compared to the native structure. We discuss both the merits and shortcomings of the firehose model and the relation between distance geometry and energy minimization techniques.
Serological patterns of hepatitis B virus infection among people living with HIV in Ibadan, Nigeria

ABSTRACT Hepatitis B virus (HBV) is a leading cause of liver pathology, which has remained a serious public health challenge in spite of the availability of hepatitis B vaccine discovered about 40 years ago. People living with human immunodeficiency virus (PLHIV) are more at risk of hepatic problems as liver complications appear and progresses faster, owing to their immunocompromised status. This study seeks to determine HBV exposure, serological pattern, and HBV susceptibility among PLHIV. One hundred and fifty PLHIV were enrolled for the study. About 5 mL of blood was collected, processed, and tested for markers of hepatitis B virus: HBsAg, anti-HBs, HBeAg, anti-HBe, and anti-HBc. Twenty-eight (18.7%) had at least one serological marker while 122 (81.3%) tested negative to all the markers. The prevalence of HBsAg in this study was 8.7%, anti-HBs prevalence was 10%, while HBeAg was 2.7%, anti-HBe 6.0%, and anti-HBc 6.7%. Higher HBsAg, HBeAg, and anti-HBc prevalence were observed among the male participants with 13.9%, 5.6%, and 13.9%, respectively, while the female participants had more anti-HBs and anti-HBe of 1.8% and 6.1%, respectively. Age group 51–60 years had the highest prevalence of HBsAg (17.7%), HBeAg (11.8%), and anti-HBe (11.8%) while age group 31–40 years had the highest prevalence of anti-HBs (14.8%) and anti-HBe (9.8%). This study revealed the different serologic patterns of HBV infection among PLHIV and that susceptibility to HBV infection among PLHIV is high.
Modeling and forecasting of COVID-19 infection cases in Iraq

Abstract Nowadays, COVID-19 pandemic has a big effect on the different factors of the life for all the world. The problem of this study is the behavior, and the expected number of infections are not clear and did not studied in Iraq. Consequently, modeling and forecasting of the infection cases have an importance into various sectors of life. Several models have been proposed in last few months for enhancing the precision and efficiency of pandemic modeling and forecasting. The goal of this paper is to find the appropriate model specifying the behavior of the virus and to forecast the expected number of infections in the few period later. Forecasting of COVID-19 infection cases is important to provide an indicator will be used by the public health authorities in Iraq for different purposes. Several models and an original time series of COVID-19 infection cases in Iraq was analyzed to select the appropriate model and use it to forecast the future number of infections and death. The results of analyze this data show that the appropriate model is nonparametric polynomial model, and the forecasted numbers are near the actual numbers.
Allometric analysis of brain cell number in Hymenoptera suggests ant brains diverge from general trends

Many comparative neurobiological studies seek to connect sensory or behavioural attributes across taxa with differences in their brain composition. Recent studies in vertebrates suggest cell number and density may be better correlated with behavioural ability than brain mass or volume, but few estimates of such figures exist for insects. Here, we use the isotropic fractionator (IF) method to estimate total brain cell numbers for 32 species of Hymenoptera spanning seven subfamilies. We find estimates from using this method are comparable to traditional, whole-brain cell counts of two species and to published estimates from established stereological methods. We present allometric scaling relationships between body and brain mass, brain mass and nuclei number, and body mass and cell density and find that ants stand out from bees and wasps as having particularly small brains by measures of mass and cell number. We find that Hymenoptera follow the general trend of smaller animals having proportionally larger brains. Smaller Hymenoptera also feature higher brain cell densities than the larger ones, as is the case in most vertebrates, but in contrast with primates, in which neuron density remains rather constant across changes in brain mass. Overall, our findings establish the IF as a useful method for comparative studies of brain size evolution in insects.
The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy

Chimeric antigen receptor (CAR) T cell therapy is a remarkably effective immunotherapy that relies on in vivo expansion of engineered CAR T cells, after lymphodepletion (LD) by chemotherapy. The quantitative laws underlying this expansion and subsequent tumour eradication remain unknown. We develop a mathematical model of T cell–tumour cell interactions and demonstrate that expansion can be explained by immune reconstitution dynamics after LD and competition among T cells. CAR T cells rapidly grow and engage tumour cells but experience an emerging growth rate disadvantage compared to normal T cells. Since tumour eradication is deterministically unstable in our model, we define cure as a stochastic event, which, even when likely, can occur at variable times. However, we show that variability in timing is largely determined by patient variability. While cure events impacted by these fluctuations occur early and are narrowly distributed, progression events occur late and are more widely distributed in time. We parameterized our model using population-level CAR T cell and tumour data over time and compare our predictions with progression-free survival rates. We find that therapy could be improved by optimizing the tumour-killing rate and the CAR T cells' ability to adapt, as quantified by their carrying capacity. Our tumour extinction model can be leveraged to examine why therapy works in some patients but not others, and to better understand the interplay of deterministic and stochastic effects on outcomes. For example, our model implies that LD before a second CAR T injection is necessary.
Evidence for an Allee effect in a declining fur seal population

Allee effects play an important role in the dynamics of many populations and can increase the risk of local extinction. However, some authors have questioned the weight of evidence for Allee effects in wild populations. We therefore exploited a natural experiment provided by two adjacent breeding colonies of contrasting density to investigate the potential for Allee effects in an Antarctic fur seal (Arctocephalus gazella) population that is declining in response to climate change-induced reductions in food availability. Biometric time-series data were collected from 25 pups per colony during two consecutive breeding seasons, the first of which was among the worst on record in terms of breeding female numbers, pup birth weights and foraging trip durations. In previous decades when population densities were higher, pup mortality was consistently negatively density dependent, with rates of trauma and starvation scaling positively with density. However, we found the opposite, with higher pup mortality at low density and the majority of deaths attributable to predation. In parallel, body condition was depressed at low density, particularly in the poor-quality season. Our findings shed light on Allee effects in wild populations and highlight a potential emerging role of predators in the ongoing decline of a pinniped species.
Thermal oscillations, second sound and thermal resonance in phonon hydrodynamics

Recent observation of second sound in graphite at a temperature above 100 K has aroused a great interest in the study of thermal waves in non-metallic solid materials. In this article, based on the Guyer–Krumhansl model, we investigate the second sound and thermal resonance phenomena in phonon hydrodynamics. The occurrence condition for the second sound is derived. It shows that the smaller the relaxation time of N-scattering of the non-metallic solid with a large relaxation time of R-scattering, the more likely the second sound will occur. For the phonon transport in the non-metallic solid excited by an oscillatory heat source with a single frequency, the occurrence condition for thermal resonance and a formula for calculating the external heat source frequency at resonance are also derived. It is found that the low-dimensional materials with small size are prone to the occurrence of second sound and thermal resonance. These phenomena open up new avenues for thermal management and energy conversion.
Population Status, Habitat Use and Breeding Biology of the Endangered Colombian Horned Lark in an Andean Wetland

The Colombian Horned Lark Eremophila alpestris peregrina is an endemic bird of the Colombian Andean Plateau that is endangered due to habitat loss. Information on the population status, habitat use and reproductive biology of this species is therefore vital. We studied these aspects in the La Copa reservoir, where the largest population of this species is found. First, we determined at which locations around the reservoir it was present. At these locations, we used fixed-width transects to estimate its abundance and densities in different habitats for eight months. We monitored its reproductive biology, through behavioural observations and nest tracing during 12 months. The species was only present in plain areas with sparse short vegetation, using grassland, cropland or a mix of the two. Population densities varied significantly between habitats, being high (5.7 birds/ha) in extensive grasslands and medium to low in mixed cropland-grassland (1.1 birds/ha) and cropland (0.41 birds/ha). These differences may be related to the presence of grazing, flooding dynamics, the density of perennial forbs, the size of the grassland fields and the detrimental effect of toxic pesticides used for crop production. We estimated that 133 to 230 (95% CI) individuals (mostly adults), inhabit the entire reservoir. This is a significant number since it may represent 13–23% of the Colombian Horned Lark population. Finally, we present our data on the reproductive cycle of these larks.
Application of molecular simulation to derive phase diagrams of binary mixtures

The miscibility behavior of three binary mixtures, solvent with solvent, polymer with solvent, and polymer with polymer, was studied by use of a combination of the Flory-Huggins theory and molecular simulation techniques. Fundamental parameters in the Flory-Huggins theory, including the heat of mixing associated with pairwise interactions (Aw12) and the number of possible interaction partners, i.e., coordination number, z, are calculated from molecular simulations. The pair energies (~11, w22, ~12) are obtained by averaging a large number of confiations generated by a Monte Carlo approach which includes the constraints associated with excluded volume. The temperature dependence of the interaction parameter x is obtained with the formalism developed in this study. In all cases, the calculated upper critical solution temperatures compare favorably with experimental values. This approach provides an opportunity to test the Flory- Huggins theory for a number of model binary systems and to characterize their miscibility behavior. This combined approach also facilitates study of the thermodynamic behavior of a binary mixture without possessing specific knowledge or experimental data of the system under investigation.
Does the Breeding Biology of the Eurasian Stone-Curlew Burhinus oedicnemus in South-Western Morocco Differ between Grazed Steppe and Irrigated Farmland?

Abstract. Birds associated with steppe and pseudosteppe habitats are one of the most threatened avian communities in Europe, given their recent decline due to agriculture intensification and land abandonment. Large-scale conversion of natural and rural areas into irrigated farmlands is ongoing in North Africa, but the effects of this habitat modification on steppe bird species are not investigated. In this study, we investigated the breeding biology of the Eurasian Stone-curlew nesting in grazed steppes and irrigated farmlands in south-western Morocco. Breeding data were collected during 2017 and 2018 breeding seasons on 59 nests. Egg volume was significantly higher in grazed steppes than in irrigated farmlands (37.3 ± 2.30 cm3 vs 35.1 ± 2.11 cm3, average ± SD), possibly due to greater food availability in the former habitat. On the other hand, daily nest survival over the incubation period did not differ between habitats and it was quite high (0.85 [95% CI: 0.71–0.93]) also when compared to the data available for other regions. These results suggest that birds nesting in protected areas characterized by traditional pastoralism might find better conditions for reproduction which allow them to lay larger eggs. In addition, the ongoing process of agricultural intensification in the area does not seem to affect the likelihood of nest failure. Our data add to the few available pieces of evidence regarding the effect of breeding habitat on the reproductive biology of the Stone-curlew in the southern range of its distribution. Further data are needed in order to understand the conservation implication of our findings and, in particular, how the observed variability of egg size might affect chick quality and survival.
Visualized Analysis and Optimization Countermeasures of the Current Situation of College Aesthetic Education Research: Metrological analysis based on VOSviewer

Colleges and universities undertake the mission of cultivating outstanding socialist builders and successors. Aesthetic education is an indispensable and important link in college education. It promotes the all-round development of students and contributes to the cultivation of the "whole person". "Being prosperous in poetry, standing in rituals, and becoming happy", the Chinese nation has paid great attention to aesthetic education since ancient times. Since the new era, aesthetic education in colleges and universities has become a cause that attracts much attention. Based on CNKI, this paper uses analysis tools such as VOSviewer to analyze the current situation of the development of aesthetic education in colleges and universities and put forward optimization countermeasure. It analyzes the causes of the status quo from the aspects of knowledge map, hot vocabulary, and co-occurrence, and proposes the optimization of college aesthetic education in combination with related research and development trends. I
How do High-Performance Work Systems affect Work Fatigue: Mediate effect of between Job Responsibility and Role Overload

The explosion in the number of occupational diseases and the frequent occurrence of management incidents such as "sudden programmer death" have led to work fatigue concerns. Based on the hindrance-challenge stress model, this paper introduces role overload and job responsibility as mediate variables to explore the impact of high-performance work systems on work fatigue. This paper analyzes the data of 283 employees from 12 enterprises and finds that high-performance work systems increases work fatigue through role overload, and reduces work fatigue through job responsibility. This article discusses the internal mechanisms of how high-performance work systems affect work fatigue, confirms the adverse effects of high-performance work systems, and provides practical guidance for companies to reduce work fatigue.
Social Relationship Mining Based on Student Data

In recent years, the campus social network mining has been widely concerned by scholars because it is closely related to the physical and mental health development of college students and the university management work. Compared with the typical social network mining tasks, the challenges of campus social network mining mainly lie in the difficulty of data acquisition and unlabeled data. Based on the phenomenon of homogeneity between friends, this paper proposed a social relationship mining method. Firstly, this paper carried out data dimension reduction operation for each student's daily consumption data, and then innovatively carried out the convolution operation for the consumption behavior data after dimension reduction, and finally obtained the characteristics of students' consumption behavior. The Multiple dimensional scaling algorithm is adopted for data dimension reduction, and the convolutional network is an improved Lenet-5 network. Then, the personalized ranking model is developed base on the phenomenon that the distance between friends is less than the distance between non-friends. To solve the problem of unlabeled data, we mined the friends' relationship from the student's library access control system swiping card records, and then taken the mined friends' relationship as the real friends' relationship to train the model. From the experimental results, the social network mining method proposed in this paper performs well.
Affinitention nets: kernel perspective on attention architectures for set classification with applications to medical text and images

Set classification is the task of predicting a single label from a set comprising multiple instances. The examples we consider are pathology slides represented by sets of patches and medical text data represented by sets of word embeddings. State-of-the-art methods, such as the transformer network, typically use attention mechanisms to learn representations of set data, by modeling interactions between instances of the set. These methods, however, have complex heuristic architectures comprising multiple heads and layers. The complexity of attention architectures hampers their training when only a small number of labeled sets is available, as is often the case in medical applications. To address this problem, we present a kernel-based representation learning framework that links learning affinity kernels to learning representations from attention architectures. We show that learning a combination of the sum and the product of kernels is equivalent to learning representations from multi-head multi-layer attention architectures. From our framework, we devise a simplified attention architecture which we term affinitention (affinity-attention) nets. We demonstrate the application of affinitention nets to the classification of the Set-Cifar10 dataset, thyroid malignancy prediction from pathology slides, as well as patient text-message triage. We show that affinitention nets provide competitive results compared to heuristic attention architectures and outperform other competing methods.
Swineherds and Hogs on Ice: Leadership Impacts for State Chief Judges

Chief judges stand as visible leaders of their courts. Analyses of the Supreme Court focus on the role of the chief justice as an institution-builder seeking out public-facing consensus to protect Court legitimacy. Studying the powers of chief judges and political leadership in general is difficult. Analyzing all 50 states over 16 years we find no evidence that the identity of chief judges explains consensus behavior any better than random chance. This is true even among the subset of chief judges with additional institutional powers like opinion assignment. We show that court structures explain consensus, while leader features do not. Being chief judge correlates with an elevated likelihood of being in the majority, particularly in cases decided by one vote. These results add to our understanding of leadership on courts and imply that the office of chief judge at the state level is more symbolic than uniquely powerful.
Improved image classification algorithm based on convolutional neural network

At present, convolutional neural networks are widely used in image classification, but the training effect of the network model with a relatively shallow number of layers is not good, and the model with a deeper network is prone to overfitting problems at the end. This article uses the cat and dog data set, and the selection is relatively mature The VGG16 model was improved. Add a dropout layer and a feature extraction layer to it, and perform L2 regularization on the loss function at the end to deepen the model depth and improve the fit of the entire model. The experimental results show that the improved model can greatly improve the detection accuracy.
Understanding Dogs' Engagement with Interactive Games: Interaction Style, Behaviour and Personality

Dogs are being increasingly exposed to interactive technology aiming to entertain them with playful experiences. However, work that investigates how dogs engage with tangible play interfaces, whether they manifest different interaction patterns and how these might relate to their personality has so far been limited. In this paper, we explore how dogs interact with a novel physical game. Our study involved 60 participants, whose personality was assessed using a standard personality test and whose interactions and behaviours during the game were observed. Findings suggest that dogs' engagement with physical games presents with specific interaction styles and behavioural patterns, and that these might correlate with specific personality characteristics. These engagement modalities could provide a criterion to customise the design of interactive games for dogs and optimise their gaming experience. Additionally, findings suggest the possibility that identifying relevant personality characteristics could help predict dogs' preferred engagement modalities.