Miracle-dz/UniFAR-FTUs huggingface dataset:
Principal Component Analysis (PCA) of Molecular Descriptors for Improving Permeation through the Blood–Brain Barrier of Quercetin Analogues

Despite its beneficial pharmacological effects in the brain, partly by modulating inositol phosphate multikinase (IPMK) activity, the therapeutic use of quercetin is limited due to its poor solubility, low oral bioavailability, and low permeability through the blood–brain barrier (BBB). We aimed to identify quercetin analogues with improved BBB permeability and preserved binding affinities towards IPMK and to identify the molecular characteristics required for them to permeate the BBB. Binding affinities of quercetin analogues towards IPMK were determined by molecular docking. Principal component analysis (PCA) was applied to identify the molecular descriptors contributing to efficient permeation through the BBB. Among 34 quercetin analogues, 19 compounds were found to form more stable complexes with IPMK, and the vast majority were found to be more lipophilic than quercetin. Using two distinct in silico techniques, insufficient BBB permeation was determined for all quercetin analogues. However, using the PCA method, the descriptors related to intrinsic solubility and lipophilicity (logP) were identified as mainly responsible for clustering four quercetin analogues (trihydroxyflavones) with the highest BBB permeability. The application of PCA revealed that quercetin analogues could be classified with respect to their structural characteristics, which may be utilized in further analogue syntheses and lead optimization of BBB-penetrating IPMK modulators as neuroprotective agents.
Lead-Free Perovskite Thin Films for Gas Sensing through Surface Acoustic Wave Device Detection

Thin film technology shows great promise in fabricating electronic devices such as gas sensors. Here, we report the fabrication of surface acoustic wave (SAW) sensors based on thin films of (1 − x) Ba(Ti0.8Zr0.2)O3−x(Ba0.7Ca0.3)TiO3 (BCTZ50, x = 50) and Polyethylenimine (PEI). The layers were deposited by two laser-based techniques, namely pulsed laser deposition (PLD) for the lead-free material and matrix assisted pulsed laser evaporation (MAPLE) for the sensitive polymer. In order to assay the impact of the thickness, the number of laser pulses was varied, leading to thicknesses between 50 and 350 nm. The influence of BCTZ film’s crystallographic features on the characteristics and performance of the SAW device was studied by employing substrates with different crystal structures, more precisely cubic Strontium Titanate (SrTiO3) and orthorhombic Gadolinium Scandium Oxide (GdScO3). The SAW sensors were further integrated into a testing system to evaluate the response of the BCTZ thin films with PEI, and then subjected to tests for N2, CO2 and O2 gases. The influence of the MAPLE’s deposited PEI layer on the overall performance was demonstrated. For the SAW sensors based on BCTZ/GdScO3 thin films with a PEI polymer, a maximum frequency shift of 39.5 kHz has been obtained for CO2; eight times higher compared to the sensor without the polymeric layer.
Metabolomics and Transcriptomics Analyses of Curcumin Alleviation of Ochratoxin A-Induced Hepatotoxicity

Ochratoxin A (OTA) is one of the mycotoxins that poses a serious threat to human and animal health. Curcumin (CUR) is a major bioactive component of turmeric that provides multiple health benefits. CUR can reduce the toxicities induced by mycotoxins, but the underlying molecular mechanisms remain largely unknown. To explore the effects of CUR on OTA toxicity and identify the key regulators and metabolites involved in the biological processes, we performed metabolomic and transcriptomic analyses of livers from OTA-exposed mice. We found that CUR can alleviate the toxic effects of OTA on body growth and liver functions. In addition, CUR supplementation significantly affects the expressions of 1584 genes and 97 metabolites. Integrated analyses of transcriptomic and metabolomic data showed that the pathways including Arachidonic acid metabolism, Purine metabolism, and Cholesterol metabolism were significantly enriched. Pantothenic acid (PA) was identified as a key metabolite, the exogenous supplementation of which was observed to significantly alleviate the OTA-induced accumulation of reactive oxygen species and cell apoptosis. Further mechanistical analyses revealed that PA can downregulate the expression level of proapoptotic protein BAX, enhance the expression level of apoptosis inhibitory protein BCL2, and decrease the level of phosphorylated extracellular signal-regulated kinase 1/2 (pERK1/2). This study demonstrated that CUR can alleviate the adverse effects of OTA by influencing the transcriptomic and metabolomic profiles of livers, which may contribute to the application of CUR in food and feed products for the prevention of OTA toxicity.
HOW AND WHEN ISLAMIC WORK ETHIC LEADS TO EMPLOYEE VOICE IN URBAN MUSLIM COMMUNITY?: THE ROLE OF CIVILITY CLIMATE AND ORGANIZATIONAL IDENTIFICATION

The current study uncovers a new paradigm in studying employee voice using a religious approach: Islamic work ethics (IWE). The research model involves a direct relationship between IWE and employee voice, indirectly through civility climate, and a moderate effect of organizational identification in urban Muslim communities, especially in the education sector. A time-lag data-collecting method captured 278 lecturers at various Islamic universities. The PLS-SEM analysis results confirmed most hypotheses: first, the IWE positively relates to civility and employee voice. Second, the result demonstrated that civility climate plays a significant role in encouraging employee voice. However, the study did not find evidence to support civility climate's interplay role in the relationship between IWE and employee voice. Finally, the research confirmed that organizational identification is a crucial predictor and moderator of employee voice. The urban Muslim community is a diverse group, both culturally and ethnically. This diversity creates an environment that fosters positive cultural exchange and critical thought discussions regarding Islamic thought. The study's findings provide valuable insights into the relevance and implementation of IWE in urban Muslim communities, particularly in Indonesia's education sector. The proposed model has practical and theoretical implications for HR practitioners and the study of IWE in modern society and organizations.
Design of Fractional Verhulst Model for Displacement Prediction of Landslide Based on the Optimization of Beetle Antennae Algorithm

Landslides significantly impact economic development and public safety. Aiming at the problem of insufficient prediction accuracy of the displacement data series of the traditional grey Verhulst model, this paper proposes a fractional Verhulst model optimized using the beetle tentacle search algorithm. First, based on the grey Verhulst model, a fractional order operator is introduced to accurately adjust the magnitude between cumulative values, constructing a fractional order-based grey Verhulst model. Expanding the accumulative order range improves prediction performance. Second, the fractional operator is optimized. The beetle antennae search algorithm finds the optimal fractional order between 0 and 1 in the grey Verhulst model, minimizing average relative error. Finally, using Heifangtai landslide group displacement data from Gansu Province, simulation experiments verified that the model has higher fitting accuracy and prediction effect than the traditional grey Verhulst model, Huang's improved Verhulst model, GM (1,1) model, cubic exponential smoothing model, and DGM (2,1) model. The average relative error is 2.949 %. Results show that the beetle antennae search algorithm optimized fractional order grey prediction model significantly improves fitting and prediction effect on data. The optimized fractional Verhulst model is more suitable for predicting landslide displacement deformation.
The Relationship of Mobile-Based Social Network Addiction and Family Communication Patterns, with Behavioral Problems in Secondary School Students: The Mediating Role of Emotional Self-Regulation

Background New technologies offer endless possibilities for students and schools, but as the use of smartphones increases, psychological and behavioral problems may also increase. Objective To investigate the relationship of mobile-based social network addiction and family communication patterns on the one hand, and behavioral problems in students on the other, with a focus on the mediating role of emotional self-regulation. Design This study used a quantitative approach and a cross-sectional design. The participants were 384 students (female/male: 226/168; mean age: 16 ± 1.98) in secondary high schools in Tehran in the academic year 2022–2023. The students were selected using convenience sampling. The data were collected online using the Revised Family Communication Pattern Scale (1994), Mobile-Based Social Network Addiction Questionnaire (2016), Child Behavior Checklist — Adolescent Version (2001), and the Affective Style Questionnaire (2010). The data were analyzed using structural equation modeling with SPSS-25 and AMOS-24 statistical software. Results The study showed that emotional self-regulation plays a mediating role in the relationship between mobile-based social network addiction and internalized and externalized behavioral problems (P ≤ .05). The indirect effect of conversation orientation on internalized and externalized behavioral problems mediated by emotional self-regulation was not significant, but the indirect effect of conformity orientation on internalized and externalized behavioral problems with the mediation of emotional self-regulation was significant (P ≤ .05). Conclusion Based on the findings, it is suggested that school officials and parents should develop emotional self-regulation and communication skills in students and parenting skills in their parents to prevent and reduce potential harm such as internet addiction and behavioral problems in students.
CBOR Object Signing and Encryption (COSE): Structures and Process

Concise Binary Object Representation (CBOR) is a data format designed for small code size and small message size. There is a need for the ability to have basic security services defined for this data format. This document defines the CBOR Object Signing and Encryption (COSE) protocol. This specification describes how to create and process signatures, message authentication codes, and encryption using CBOR for serialization. This specification additionally describes how to represent cryptographic keys using CBOR. This document along with [I-D.ietf-cose-rfc8152bis-algs] obsoletes RFC8152.
The prevalence of Staphylococcus aureus and the emergence of livestock-associated MRSA CC398 in pig production in eastern China

Livestock-associated Staphylococcus aureus (LA-MRSA) has been of increasing concern due to its potential risk to humans. This study investigated the prevalence of MRSA in pig production in Eastern China and determined the genomic characteristics of pig-associated MRSA isolates by whole-genome sequencing (WGS). A total of 1,318 samples were collected from pig farms and pig slaughterhouses, and 150 S. aureus were identified, including 63 MRSA isolates and 87 MSSA isolates. MRSA was detected in all pig farms and pig slaughterhouses. The antimicrobial susceptibility test revealed that all MRSA isolates were multidrug-resistant. The WGS and MLST analysis demonstrated that 56 MRSA isolates belonged to clonal complex (CC) 398, and seven MRSA isolates belonged to CC9. All LA-MRSA isolates were absent of phiSa3 phage containing immune evasion cluster (IEC) and possessed an intact hlb gene. In addition, genes associated with Panton-Valentine leukocidin, typically indicative of human adaptation, were not detected. The analysis of antibiotic resistance genes (ARGs) demonstrated that all MRSA isolates contained multiple ARGs. All MRSA isolates had Plthe mecA gene and at least one tetracycline resistance gene. Both tetM and tetK were detected in all MRSA CC398 isolates, while tetL was detected in all MRSA CC9 isolates. The phenicol resistance gene fexA was detected in 51 MRSA isolates, while the linezolid resistance gene cfr was detected in 60 MRSA isolates. The emergence of LA-MRSA CC398 in four pig farms and one slaughterhouse in this study indicates the spread of this clonal complex in the pig production sector in Eastern China. Further investigations are required to understand the potential transmission routes of LA-MRSA CC398 within the pork production chain in China and to assess the potential risks to humans.
Water ecological requirements of Characeae taxa in eastern Spain

Presence of Characeae taxa is limited by the existence of clear and oligotrophic waters. Some other chemical water parameters can also influence the distribution of taxa, which can thus be used as ecological bioindicators. The area of eastern Spain contains a high diversity of water basins in both coastal and inland habitats that allow the study of ecological gradients. This work aimed to identify the most relevant and significant water chemical parameters that determine the distribution of Characeae taxa, and establish their optima and tolerance ranges for each parameter in eastern Spain. Ninety-six records corresponding to unpublished old and recent samplings of the presence of 17 taxa belonging to the genera Chara, Nitella, Tolypella and Lamprothamnium were related to water parameters that included salinity, pH, electric conductivity, total water hardness, alkalinity, concentrations of Na+, Mg2+, Ca2+, Cl-, and SO42-, and Mg2+/Ca2+ ratio. Principal Component Analysis showed that salinity was the major factor that determined the distribution of Characeae taxa, followed by concentration of Mg2+, Mg2+/Ca2+ ratio and alkalinity. When previously published records from the same area were added, non-parametric tests showed significant differences among taxa only for salinity, water hardness, and Mg2+/Ca2+ ratio. These statistical analyses, along with optima and tolerance ranges for each parameter showed that Characeae taxa, especially Lamprothamnium papulosum and Tolypella spp. , could be used as bioindicators in eastern Spain, although their ecological differentiation is not clear in many cases.
Comptes Rendus Mathématique

We study nonlocal conservation laws with a discontinuous flux function of regularity L ∞ ( R ) in the spatial variable and show existence and uniqueness of weak solutions in C (cid:161) [0, T ]; L 1loc (cid:162) , as well as related maximum principles. We achieve this well-posedness by a proper reformulation in terms of a fixed-point problem. This fixed-point problem itself necessitates the study of existence, uniqueness and stability of a class of discontinuous ordinary di ff erential equations. On the ODE level, we compare the solution type defined here with the well-known Carathéodory and Filippov solutions. Résumé. Nous étudions des lois de conservation non locales avec une fonction de flux discontinue de régularitéspatiale L ∞ ( R )danslavariablespatialeetmontronsl’existenceetl’unicitédesolutionsfaiblesdans
Effective Isolation and Characterization of Mycobacteriophages with the Ability to Lyse Mycobacterium avium subsp. paratuberculosis

Johne’s disease (JD), a chronic infectious enteritis of ruminants, causes major economic losses in the dairy industry globally. This enteritis is caused by Mycobacterium avium subsp. Paratuberculosis (MAP). Currently there is no cure for JD and test-based culling has proved ineffective at preventing the spread. To isolate new mycobacteriophages (mbps) that can potentially be used to control JD transmission and infection on dairy farms, we optimized an isolation protocol by fecal spiking and the testing of different isolation solution compositions. Using this protocol, we successfully enhanced the yield of mbps from spiked fecal samples, elevating it from less than 1% to 59%. With this method, we isolated 14 mbps from 475 environmental samples collected from MAP-positive dairy farms, after in-sample enrichment with MAP and the fast-growing M. smegmatis. The sample sources included soil, manure pits, lactation barns, feces, milk, and drain water. After fingerprinting these mbps by restriction enzyme profiling, we concluded that 12 were distinct and novel. Further characterization of their host range revealed that eight were capable of lysing multiple MAP strains. We also studied the cross-resistance, lysogeny, the effect of pH and their antimycobacterial properties in milk replacer. Each novel mbp showed limited cross-resistance and prophage immunity and showed no reduction in the titer in a range of pHs after 4 h. The novel phages were also able to reduce the mycobacterial counts to zero after 8 h in milk replacer. In conclusion, these novel mbps could be considered to be used in the control strategies of JD on farms.
A Review on Barrier Properties of Cellulose/Clay Nanocomposite Polymers for Packaging Applications

Packaging materials are used to protect consumer goods, such as food, drinks, cosmetics, healthcare items, and more, from harmful gases and physical and chemical damage during storage, distribution, and handling. Synthetic plastics are commonly used because they exhibit sufficient characteristics for packaging requirements, but their end lives result in environmental pollution, the depletion of landfill space, rising sea pollution, and more. These exist because of their poor biodegradability, limited recyclability, etc. There has been an increasing demand for replacing these polymers with bio-based biodegradable materials for a sustainable environment. Cellulosic nanomaterials have been proposed as a potential substitute in the preparation of packaging films. Nevertheless, their application is limited due to their poor properties, such as their barrier, thermal, and mechanical properties, to name a few. The barrier properties of materials play a pivotal role in extending and determining the shelf lives of packaged foods. Nanofillers have been used to enhance the barrier properties. This article reviews the literature on the barrier properties of cellulose/clay nanocomposite polymers. Cellulose extraction stages such as pretreatment, bleaching, and nanoparticle isolation are outlined, followed by cellulose modification methods. Finally, a brief discussion on nanofillers is provided, followed by an extensive literature review on the barrier properties of cellulose/clay nanocomposite polymers. Although similar reviews have been presented, the use of modification processes applied to cellulose, clay, and final nanocomposites to enhance the barrier properties has not been reviewed. Therefore, this article focuses on this scope.
Improving fluorescence lifetime imaging microscopy phasor accuracy using convolutional neural networks

Introduction: Although a powerful biological imaging technique, fluorescence lifetime imaging microscopy (FLIM) faces challenges such as a slow acquisition rate, a low signal-to-noise ratio (SNR), and high cost and complexity. To address the fundamental problem of low SNR in FLIM images, we demonstrate how to use pre-trained convolutional neural networks (CNNs) to reduce noise in FLIM measurements. Methods: Our approach uses pre-learned models that have been previously validated on large datasets with different distributions than the training datasets, such as sample structures, noise distributions, and microscopy modalities in fluorescence microscopy, to eliminate the need to train a neural network from scratch or to acquire a large training dataset to denoise FLIM data. In addition, we are using the pre-trained networks in the inference stage, where the computation time is in milliseconds and accuracy is better than traditional denoising methods. To separate different fluorophores in lifetime images, the denoised images are then run through an unsupervised machine learning technique named “K-means clustering”. Results and Discussion: The results of the experiments carried out on in vivo mouse kidney tissue, Bovine pulmonary artery endothelial (BPAE) fixed cells that have been fluorescently labeled, and mouse kidney fixed samples that have been fluorescently labeled show that our demonstrated method can effectively remove noise from FLIM images and improve segmentation accuracy. Additionally, the performance of our method on out-of-distribution highly scattering in vivo plant samples shows that it can also improve SNR in challenging imaging conditions. Our proposed method provides a fast and accurate way to segment fluorescence lifetime images captured using any FLIM system. It is especially effective for separating fluorophores in noisy FLIM images, which is common in in vivo imaging where averaging is not applicable. Our approach significantly improves the identification of vital biologically relevant structures in biomedical imaging applications.
A Phytosociological Study of a Weed Community in Fallow Land in the Semi-Arid Zone of India

A phytosociological study of weeds carried out at Ajmer in the semi-arid zone of India revealed the presence of Dactyloctenium-Cynodon-Chloris community during the monsoon season and Cynodon-Tribulus-Tephrosia community of weeds during the summer season, growing on coarse and sandy soils and in harmony with all biotic factors. The communities experience high summer and low winter temperatures with rainfall occurring only during the monsoon season (July to September). Other dominant weeds included Achyranthes aspera L. , Amaranthus gracilis Desf. , Tephrosia purpurea (L.) Pers. , and Trianthema portulacastrum L. during the monsoon season, and Boerhavia diffusa L. , Indigofera linifolia (L.) Retz. , and Rhus mysurensis Heyne ex Wight. are dormant during the summer season.
Unsupervised Image Classifier based on Manifold Learning

Currently most of image classification tasks are achieved by supervised learning. High-quality datasets naturally bring difficulties in annotation, and the datasets in real-world applications present a nonlinear structure, and the annotation cost grows exponentially with the number of targets and the difficulty of recognisability. In this context, research about unsupervised image classification is the way to go. Traditional unsupervised learning for classification is mostly based on the Euclidean distance and various paradigms, which is unable to extract the nonlinear structure of the dataset. This shortcoming makes the accuracy of traditional unsupervised image classification drop drastically. In this paper, we propose to first extract the nonlinear structure of the original dataset using the manifold learning method, and then produce pseudo-labels through the agglomerative clustering algorithm. The pseudo-labels obtained in this way can effectively retain the special mathematical structure of the original data with high accuracy. The neural network is trained with these pseudo labels to obtain an unsupervised usable image classifier. The classifier can be trained on small-scale data and then applied to large-scale data sets, thus saving the cost of manual labelling. The experiments are carried out by setting up a control group and two manifold learning groups for the extraction of non-linear structures using LLE and Isomap algorithms respectively. After that, the production of pseudo-labels and the training of neural networks are completed, and the accuracy of the three groups is compared. Finally, it is concluded that the correct rate of the two groups that have gone through the manifold learning algorithm to extract the nonlinear structure is much higher than that of the other one, and the image classifier based on the Isomap algorithm achieves an accuracy of 85% in the test set, which is highly practical.