Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis and Molecular Docking Studies of Alkoxy- and Imidazole-Substituted Xanthones as α-Amylase and α-Glucosidase Inhibitors

Current antidiabetic drugs have severe side effects, which may be minimized by new selective molecules that strongly inhibit α-glucosidase and weakly inhibit α-amylase. We have synthesized novel alkoxy-substituted xanthones and imidazole-substituted xanthones and have evaluated them for their in silico and in vitro α-glucosidase and α-amylase inhibition activity. Compounds 6c, 6e, and 9b promoted higher α-glucosidase inhibition (IC50 = 16.0, 12.8, and 4.0 µM, respectively) and lower α-amylase inhibition (IC50 = 76.7, 68.1, and >200 µM, respectively) compared to acarbose (IC50 = 306.7 µM for α-glucosidase and 20.0 µM for α-amylase). Contrarily, derivatives 10c and 10f showed higher α-amylase inhibition (IC50 = 5.4 and 8.7 µM, respectively) and lower α-glucosidase inhibition (IC50 = 232.7 and 145.2 µM, respectively). According to the structure–activity relationship, attaching 4-bromobutoxy or 4′-chlorophenylacetophenone moieties to the 2-hydroxy group of xanthone provides higher α-glucosidase inhibition and lower α-amylase inhibition. In silico studies suggest that these scaffolds are key in the activity and interaction of xanthone derivatives. Enzymatic kinetics studies showed that 6c, 9b, and 10c are mainly mixed inhibitors on α-glucosidase and α-amylase. In addition, drug prediction and ADMET studies support that compounds 6c, 9b, and 10c are candidates with antidiabetic potential.
Oxidative Stress, Reductive Stress and Antioxidants in Vascular Pathogenesis and Aging

This review is focused on the mechanisms that regulate health, disease and aging redox status, the signal pathways that counteract oxidative and reductive stress, the role of food components and additives with antioxidant properties (curcumin, polyphenols, vitamins, carotenoids, flavonoids, etc.), and the role of the hormones irisin and melatonin in the redox homeostasis of animal and human cells. The correlations between the deviation from optimal redox conditions and inflammation, allergic, aging and autoimmune responses are discussed. Special attention is given to the vascular system, kidney, liver and brain oxidative stress processes. The role of hydrogen peroxide as an intracellular and paracrine signal molecule is also reviewed. The cyanotoxins β-N-methylamino-l-alanine (BMAA), cylindrospermopsin, microcystins and nodularins are introduced as potentially dangerous food and environment pro-oxidants.
A Noise Sensitivity Theorem for Schreier Graphs

During the past 15 years, several extensions of the concept of noise sensitivity first coined in~\cite{schramm2000}, has been studied. One such extension was studied in ? , where the definition of noise sensitivity was extended to noise corresponding to any sequence of irreducible and reversible Markov chains. In this paper we focus on the case where the Markov chain is a random walk on a Schreier graph, and show that the Benjamini-Kalai-Schramm theorem, connecting influences to noise sensitivity, holds in this setting. We then apply this result to give an alternative proof of one of the main results from a recent paper on exclusion sensitivity by Broman, Garban and Steif.
The Complex Outgassing of Comets and the Resulting Coma, a Direct Simulation Monte-Carlo Approach

During its journey, when a comet gets within a few astronomical units of the Sun, solar heating liberates gases and dust from its icy nucleus forming a rarefied cometary atmosphere, the so-called coma. This tenuous atmosphere can expand to distances up to millions of kilometers representing orders of magnitude larger than the nucleus size. Most of the practical cases of coma studies involve the consideration of rarefied gas flows under non-LTE conditions where the hydrodynamics approach is not valid. Then, the use of kinetic methods is required to properly study the physics of the cometary coma. The Direct Simulation Monte-Carlo (DSMC) method is the method of choice to solve the Boltzmann equation, giving the opportunity to study the cometary atmosphere from the inner coma where collisions dominate and is in thermodynamic equilibrium to the outer coma where densities are lower and free flow conditions are verified. While previous studies of the coma used direct sublimation from the nucleus for spherically symmetric 1D models, or 2D models with a day/night asymmetry, recent observations of comets showed the existence of local small source areas such as jets, and extended sources via sublimating icy grains, that must be included into cometary models for a realistic representation of the physics of the coma. In this work, we present, for the first time, 1D, 2D, and 3D models that can take into account the full effects of conditions with more complex sources of gas with jets and/or icy grains. Moreover, an innovative work in a full 3D description of the cometary coma using a kinetic method with a realistic nucleus and outgassing is demonstrated. While most of the physical models used in this study had already been developed, they are included in one self-consistent coma model for the first time.
Membranes with Doubly Periodic Loading

This project involves investigation of wave propagation in membrane on which a doubly periodic pressure is applied. As a pre-requisite to this investigation, initially one dimensional version of the problem, i.e., wave propagation in string has been studied. Transmission Line Method is used to study mass-loaded string. Then inhomogeneous 2-D wave equation is formulated by application of plane wave pressure to a membrane and corresponding displacement is calculated. Finally a given doubly periodic pressure is expressed in terms of plane wave form using reciprocal lattice vectors. Also, double Fourier series is obtained. From this expression of applied pressure, corresponding displacement is obtained over a period parallelogram by superposition.
Heterostructured PHI‐PTI/Li+Cl− Carbon Nitrides for Multiple Photocatalytic Applications

Two series of novel carbon nitride photocatalysts, Rho‐CN (“rhodizonate‐doped carbon nitride”) and Rho‐CN‐TC (Rho‐CN treated in potassium thiocyanate melt), are synthesized in a multistep fashion via copolymerization of cyanamide with potassium rhodizonate. The formed ionic carbon nitrides are composed of poly(triazine imide) (PTI/Li+Cl−) and potassium poly(heptazine imide) (K‐PHI) phases and provide a broad absorption range up to 800 nm. The photocatalysts are characterized by several techniques (including diffuse reflectance ultraviolet–visible, powder X‐ray diffraction, Fourier transform infrared, scanning electron microscopy, and electrochemical methods) and studied in a series of photocatalytic reactions, including red light‐promoted benzylamine oxidation, dual photoredox/nickel C–N cross‐coupling, and hydrogen peroxide evolution. The optimal ratio of rhodizonate dopant in its mixture with cyanamide is found to be 0.5 mol%. The performance of the newly synthesized materials is comparable to the activities of the benchmark catalysts K‐PHI and CN‐OA‐m (defective poly(heptazine imide) doped with oxamide), while not requiring more expensive nitrogen sources for preparation, like 5‐aminotetrazole, or multiple oven cycles.
Study on Employee Involvement on the Effectiveness of Organizational Change in Côte d’Ivoire

Change is critical for any organization in this day and age. New technologies, external/internal business environments, crises, and health pandemics can occur at any time. Running a business has become difficult. Employee involvement has been studied by researchers in recent decades and identified as a key outcome for achieving organizational change. Employee involvement was defined by the researchers in three ways. Employee participation is the process by which employees actively participate in decision-making and problem-solving on a daily basis. Empowerment primarily refers to the autonomy and delegation of power to make the right decisions about their work, resulting in employee responsibility and, ultimately, their outcome. Teamwork is defined as two or more people working together to achieve a goal. Because of the uncertainty that can bring about change, teamwork is known to have significant value. Organizational Change refers to an organization's ability to change its business structures, strategies, and habits. These variables may thus have a negative or positive impact on the success of change. To address this research, data was collected from telecommunications companies using a questionnaire, and Smart PLS and structural equation modeling were used to analyze the data. This paper includes conclusions, limitations, and recommendations for future research.
Investigating the influence of AI research topics in the academic, public, and industry spheres

The Artificial Intelligence research field sits at the intersection of several overlapping spheres (academia, industry, media), each with their own logics and commitments. The influence of research within these worlds is studied through a number of bibliometric methods, including citation metrics for measuring influence within academia, and counts of patents and news-media mentions for influence in industry and the media. Using a large-scale, publicly-available dataset of research outputs, we compare the topical content of outputs that are highly influential in each of these worlds. We identify significant differences between the content of influential research in these worlds, indicating that the academic, industry and media worlds value different aspects of the Artificial Intelligence field. These differences provide new insights on the evaluation of research produced within the Artificial Intelligence field.
Relationships between the Intakes of Human Milk Components and Body Composition of Breastfed Infants: A Systematic Review

Human milk provides all of the elements necessary for infant growth and development. Previous studies have reported associations between breastfeeding and a reduced risk of developing obesity and late-onset metabolic disorders; however, the underlying mechanisms are poorly understood. Recently, intakes of human milk components have been associated with infant body composition, which is likely partially implicated in the reduced risk of developing childhood obesity among breastfed infants. In this systematic review, we searched electronic bibliographic databases for studies that explored relationships between the 24 h intakes of human milk macronutrients and bioactive components and infant body composition and/or growth parameters. Of 13 eligible studies, 10 assessed relationships of infant body composition and growth outcomes with human milk macronutrients, while 8 studies assessed relationships with human milk bioactive components. Significant time-dependent relationships with infant anthropometrics and body composition were found for intakes and no relationships for concentrations of several human milk components, such as lactose, total protein, and human milk oligosaccharides, suggesting that measuring concentrations of human milk components without quantifying the intake by the infant may provide a limited understanding. Future studies investigating the effect of human milk components on infant growth and body composition outcomes should consider measuring the actual intake of components and employ standardised methods for measuring milk intake.
In Silico Method for the Screening of Phytochemicals against Methicillin-Resistant Staphylococcus Aureus

Methicillin-resistant Staphylococcus aureus (MRSA) has evolved resistance even against the last resort β-lactam antibiotics. This is because of the acquisition of an additional penicillin-binding protein 2a (PBP2a) which is a resistance determinant in MRSA. Currently, available PBP2a inhibitors are ineffective against life-threatening and fatal infections caused by microorganisms. Therefore, there is an urgent need to screen natural compounds that could overpass the resistance issue alone or in combination with antibacterial drugs. We studied the interactions of different phytochemicals with PBP2a so that crosslinking of peptidoglycans could be inhibited. In structure-based drug designing, in silico approach plays a key role in determining phytochemical interactions with PBP2a. In this study, a total of 284 antimicrobial phytochemicals were screened using the molecular docking approach. The binding affinity of methicillin, -11.241 kcal/mol, was used as the threshold value. The phytochemicals having binding affinities with PBP2a stronger than methicillin were identified, and the drug-likeness properties and toxicities of the screened phytochemicals were calculated. Out of the multiple phytochemicals screened, nine were found as good inhibitors to be PBP2a, among which cyanidin, tetrandrine, cyclomorusin, lipomycin, and morusin showed strong binding potential with the receptor protein. These best-selected phytochemicals were also docked to the allosteric site of PBP2a, and most of the compounds revealed strong interactions with the allosteric site. These compounds were safe to be used as drugs because they did not show any toxicity and had good bioactivity scores. Cyanidin had the highest binding affinity (S-score of -16.061 kcal/mol) with PBP2a and with high gastrointestinal (GI) absorption. Our findings suggest that cyanidin can be used as a drug against MRSA infection either in purified form or that its structure can lead to the development of more potent anti-MRSA medicines. However, experimental studies are required to evaluate the inhibitory potential of these phytochemicals against MRSA.
Presynaptic Congenital Myasthenic Syndromes: Understanding Clinical Phenotypes through In vivo Models

Presynaptic congenital myasthenic syndromes (CMS) are a group of genetic disorders affecting the presynaptic side of the neuromuscular junctions (NMJ). They can result from a dysfunction in acetylcholine (ACh) synthesis or recycling, in its packaging into synaptic vesicles, or its subsequent release into the synaptic cleft. Other proteins involved in presynaptic endplate development and maintenance can also be impaired. Presynaptic CMS usually presents during the prenatal or neonatal period, with a severe phenotype including congenital arthrogryposis, developmental delay, and apnoeic crisis. However, milder phenotypes with proximal muscle weakness and good response to treatment have been described. Finally, many presynaptic genes are expressed in the brain, justifying the presence of additional central nervous system symptoms. Several animal models have been developed to study CMS, providing the opportunity to identify disease mechanisms and test treatment options. In this review, we describe presynaptic CMS phenotypes with a focus on in vivo models, to better understand CMS pathophysiology and define new causative genes.
Enriched Assembly CAD Model Representation Based on Liaison Data Structure

Introduction: In the last decades, mechanical engineering sector has been largely a ected by the advent of digitalization and the increasing potential of technologies to make the production process more e cient in all its phases. In particular, the production of mechanical assemblies usually relies on the use of a digital model of the nal product to analyze, plan, and simulate complex manufacturing operations in an automatic manner, avoiding waste of material, as well as reducing time and costs. The availability of a consistent and expressive digital model of the nal product results thus a crucial condition that enables both a bene cial use and integration of the di erent technologies and the achievement of optimal and feasible results from the modeling, assembly planning, and reuse standpoints. For this purpose, the representation of the 3D model of a real product is commonly provided through commercial Computer-Aided Design (CAD) software by means of which the geometric and topological properties of the components of an assembly are ensured. However, especially when dealing with industrial CAD models of mechanical assemblies, the inclusion and availability of semantic information, i.e. all the non-geometric information, such as category membership, technological data, and functionality, is not given for granted. Also, due to the gathering up of di erent design conventions, components belonging to same class can be modeled according to di erent criteria, or vice versa, components belonging to di erent categories can be quasi-identical in shape, and this generates misleading situations. Moreover, parts can be missing, or else purposely omitted (e.g. fasteners), making even more challenging the parts relations understanding. According to the above considerations, before actually algorithmically addressing assembly tasks, a rst CAD model processing phase is required to infer the necessary data associated with components and their relations and interpret the assembly from the engineering point of view. Performing a complete data extraction is not trivial and usually most of the analysis is limited to low-level information detection (e.g. existence of contact, presence of features, etc.), while high-level information (e.g. type of connection, functionality of parts, etc.) is often neglected or manually provided by experts. This, on the one hand, limits the use of engineering meaningful data, which instead would a ect the CAD model management, on the other hand, avoids the automation of the assembly tasks performance. The authors' research is placed in this context and aims at automatically extracting from CAD models of mechanical assemblies high-level semantic information and, then, leveraging it to address assembly
PLASMA EMISSION BY NONLINEAR ELECTROMAGNETIC PROCESSES

The plasma emission, or electromagnetic (EM) radiation at the plasma frequency and/or its harmonic(s), is generally accepted as the radiation mechanism responsible for solar type II and III radio bursts. Identification and characterization of these solar radio burst phenomena were done in the 1950s. Despite many decades of theoretical research since then, a rigorous demonstration of the plasma emission process based upon first principles was not available until recently, when, in a recent Letter, Ziebell et al. reported the first complete numerical solution of EM weak turbulence equations; thus, quantitatively analyzing the plasma emission process starting from the initial electron beam and the associated beam-plasma (or Langmuir wave) instability, as well as the subsequent nonlinear conversion of electrostatic Langmuir turbulence into EM radiation. In the present paper, the same problem is revisited in order to elucidate the detailed physical mechanisms that could not be reported in the brief Letter format. Findings from the present paper may be useful for interpreting observations and full-particle numerical simulations.
Ectopic Expression of PsnNAC090 Enhances Salt and Osmotic Tolerance in Transgenic Tobacco

The NAC transcription factor family is well known to play vital roles in plant development and stress responses. For this research, a salt-inducible NAC gene, PsnNAC090 (Po-tri.016G076100.1), was successfully isolated from Populus simonii × Populus nigra. PsnNAC090 contains the same motifs at the N-terminal end of the highly conserved NAM structural domain. The promoter region of this gene is rich in phytohormone-related and stress response elements. Transient transformation of the gene in the epidermal cells of both tobacco and onion showed that the protein was targeted to the whole cell including the cell membrane, cytoplasm and nucleus. A yeast two-hybrid assay demonstrated that PsnNAC090 has transcriptional activation activity with the activation structural domain located at 167–256aa. A yeast one-hybrid experiment showed that PsnNAC090 protein can bind to ABA-responsive elements (ABREs). The spatial and temporal expression patterns of PsnNAC090 under salt and osmotic stresses indicated that the gene was tissue-specific, with the highest expression level in the roots of Populus simonii × Populus nigra. We successfully obtained a total of six transgenic tobacco lines overexpressing PsnNAC090. The physiological indicators including peroxidase (POD) activity, superoxide dismutase (SOD) activity, chlorophyll content, proline content, malondialdehyde (MDA) content and hydrogen peroxide (H2O2) content were measured in three transgenic tobacco lines under NaCl and polyethylene glycol (PEG) 6000 stresses. The findings reveal that PsnNAC090 improves salt and osmotic tolerance by enhancing reactive oxygen species (ROS) scavenging and reducing membrane lipid peroxide content in transgenic tobacco. All the results suggest that the PsnNAC090 gene is a potential candidate gene playing an important role in stress response.
The Ascosphaera apis Infection (Chalkbrood Disease) Alters the Gut Bacteriome Composition of the Honeybee

The declining honeybee populations are a significant risk to the productivity and security of agriculture worldwide. Although there are many causes of these declines, parasites are a significant one. Disease glitches in honeybees have been identified in recent years and increasing attention has been paid to addressing the issue. Between 30% and 40% of all managed honeybee colonies in the USA have perished annually over the past few years. American foulbrood (AFB) and European foulbrood (EFB) have been reported as bacterial diseases, Nosema as a protozoan disease, and Chalkbrood and Stonebrood as fungal diseases. The study aims to compare the bacterial community related to the Nosema ceranae and Ascosphaera apis infection on the gut of the honeybee and compare it with the weakly active honeybees. The Nosema-infected honeybees contain the phyla Proteobacteria as the significantly dominant bacterial phyla, similar to the weakly active honeybees. In contrast, the Ascosphaera (Chalkbrood) infected honeybee contains large amounts of Firmicutes rather than Proteobacteria.
A consider unscented particle filter with genetic algorithm for UAV multi-source integrated navigation

The unscented particle filter (UPF) combines the advantages of both the unscented Kalman filter and particle filter (PF) algorithms. However, during the fusion of multi-source information for UAV integrated navigation, the UPF may encounter problems related to measurement biases and particle depletion. These issues can lead to algorithm results that are unsatisfactory or divergent. To address these challenges, a novel approach called the consider unscented particle filter with genetic algorithm (GA-CUPF) is proposed. The GA-CUPF algorithm incorporates covariance and co-covariance of biases into the state estimation covariance through the ‘consider’ method employed by the CUPF, and it should be noted that the biases are not estimated in this process. Moreover, the GA-CUPF algorithm enhances the importance probability density of particles to avoid the degeneracy of PF algorithm and improves particle diversity through the application of selection, crossover, and mutation methods in GA. Simulation results demonstrate that the proposed GA-CUPF algorithm can effectively mitigate the adverse effects of measurement biases and particle depletion that the UPF algorithm faces in the UAV navigation system. Additionally, it significantly improves the accuracy of UAV integrated navigation.