In the process of oil and gas development and production, when the flow rate in the wellbore is large, the materials underground will be eroded, causing the operation to be unable to proceed smoothly and reducing the efficiency of oil and gas production. Therefore, optimizing the anti-erosion coating under high-speed flow conditions in wellbore is a very interesting thing. It can greatly improve operational efficiency. In this paper, laser cladding was used to prepare the new coating used in the PDC drill bit. Then, the effects of tungsten carbide and multi-layer graphene on the microstructure and properties of the tungsten carbide coating were studied. The research results indicate that, for new coatings, 60% tungsten carbide and 0.3% graphene are the optimal ratios. After adding WC, the hardness has significantly improved. However, when the WC content further increases more than 30%, the increase in hardness is relatively small. In addition, when the content of graphene is more than 0.3%, the branched structure became thicker, and not only the segregation of Cr, Si and W became very obvious again, but also the segregation of Fe occurred at the Ni enrichment site. The research results contribute to improving oil and gas production and operational efficiency under high-speed fluid flow conditions in the wellbore.

This paper proposed a three-layer distributed simulation network architecture: 1. Distributed virtual simulation network, 2. Perception and control sub-network, and 3. Collaborative communication service network. This simulation architecture runs on a distributed platform. The platform can provide a unique virtual scenario and several simulation services to verify the individual robot system's basic perception, control, and planning algorithms and the distributed collaborative algorithms of heterogeneous multi-robot systems. Furthermore, we designed a simulation experiment scenario for classical heterogeneous robot systems such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). At last, We gave a rough estimation model of the bandwidth.

Significant Wave Height(SWH) is a crucial parameter in oceanographic research, essential for understanding various marine and atmospheric processes. Traditional methods for obtaining SWH, such as ship-based and buoy measurements, face limitations like limited spatial coverage and high operational costs. With the advancement of Global Navigation Satellite Systems reflectometry(GNSS-R) technology, a new method for retrieving SWH has emerged, demonstrating promising results. This study utilizes Radio occultation sounder(GNOS) data from the FY-3E satellite and incorporates the latest Vision Transformer(ViT) technology to investigate GNSS-R-based SWH retrieval. We designed and evaluated various deep learning models, including ANN-Wave, CNN-Wave, Hybrid-Wave, Trans-Wave, and ViT-Wave. Through comparative training using ERA5 data, the ViT-Wave model was identified as the optimal retrieval model. The ViT-Wave model achieved an Root Mean Square Error(RMSE) accuracy of 0.4052 meters and Mean Absolute Error(MAE) accuracy of 0.2700 meters, significantly outperforming both traditional methods and newer deep learning approaches utilizing Cyclone Global Navigation Satellite Systems(CYGNSS) data. These results underscore the potential of integrating GNSS-R technology with advanced deep learning models to enhance SWH retrieval accuracy and reliability in oceanographic research.

Satellite navigation spoofing is a major challenge in the field of satellite/inertial integrated navigation security. To effectively enhance the anti-spoofing capability of low-cost GNSS/MEMS-SINS integrated navigation system, this paper proposes a method integrating a dual-antenna global navigation satellite system (GNSS) and a micro-inertial measurement unit (MIMU) to determine the two-dimensional (2D) directions of spoofing signal sources. The proposed method evaluates whether the single-difference carrier-phase measurements conform to the corresponding directions given in ephemeris files, and employs the micro-inertial navigation technology to determine the 2D directions of the signal source. Based on a set of short-baseline dual-station measurements, the accuracy of the proposed method in determining the 2D azimuths of satellites in synchronous orbits is verified, and the deviation from the real value is evaluated. The experimental results show that the proposed method can effectively identify the spoofed satellite signals while providing high-precision direction information at three different distances: 100m, 10km, and 36000km.The two-dimensional angles errors do not exceed 0.2 rad, 0.05 rad, and 0.01 rad, respectively.

In this paper, a new type of self-excited thermomechanical oscillator containing an oscillating shape memory alloy (SMA) filament with two symmetrically arranged spheres is investigated. The self-excitation of the oscillations is due to a heater of constant temperature, which causes periodic contractions of the filament when it approaches it. The contracted filament moves away from the heater a distance sufficient to cool it. Under the action of the weight of the spheres, the cooled filament re-approaches the heater, causing the above processes to repeat periodically. On the basis of experimental studies, approximating functions of the heater's heat field distribution are derived. A dynamic model of the oscillator has been created, in which the minor and major hysteresis in the SMA alloy and the distribution of the heat field around the heater have been taken into account. By numerical solutions of the differential equations, the laws of motion of the spheres are obtained. The displacements of the spheres in two perpendicular directions were measured using an experimental system. The obtained experimental results validate the proposed dynamic model and its assumptions with a high degree of confidence. Conclusions are drawn about the stochastic nature of the oscillations due to the hysteresis properties of the SMA and the temperature variation of the natural frequency of the oscillating system.

The high thrust linear motor used for electromagnetic launch is switched with the anti-shunt thyristor as the switch. During the switching process, different current path states will appear, which will lead to changes in motor parameters and current fluctuation. Aiming at the air-core synchronous linear motor with parallel and series power supply, this paper analyzes the change of current path caused by the change of trigger signal of anti-parallel thyristor in the process of sectionalized stator switching. The motor circuit model of the switching process is derived. A new sectionalized stator switching method is proposed to realize the smooth switching of the sectionalized stator powered linear motor. Finally, the correctness of the analysis and modeling is verified by simulation, and the effectiveness of the sectionalized stator switching method is tested by using the test prototype.

(1) Background: Ectopic pregnancy (EP) is when fertilized ovum implanted outside of uterine cavity. The incidence was 1.5% to 2.0% of all pregnancies [1, 2]. EP decreases fertility ability [3]. This study focused on the pregnancy rate after EP and various parameters influencing pregnancy. (2) Methods: The data was extracted from National Health Insurance Research Database (NHIRD) during 2000-2013. The study group enrolled women with one EP history. Those who did not have EP was put into the control group. Chi-square/Fisher exact test was performed on category variable and t-test was used on continue variables. (3) Results: The EP group had a higher cumulative rate of conceive, 41.55% than control group, 37.14% and 1.16 times higher risk in developing pregnancy (P<0.001). The conceiving rate was lower than the control group in the first 5 years, but higher than the control group in the 10th to 14th years. (4) Conclusions: The fecundability after EP is lower at the beginning, but regained after long term follow.

In this paper we report a new development on the numerical model for aluminum-steam combustion. This model is based on diffusion flame of continuum regime and the thermal equilibrium between the particle and the flow field, which can be used to calculate the aluminum particle combustion model for two phase calculation conditions. The model prediction is in good agreement with the experimental data. A new type of vortex combustor was proposed for the combustion of aluminum and steam, and the mathematical model of the two phase reacting flow with in this combustor was established. The turbulence effects are modeled using the Reynolds Stress Model (RSM) with Linear Pressure-Strain approach, and the Eddy-Dissipation model is used to simulate the gas phase combustion. Aluminum particles are injected into the vortex combustor and form a swirling flow around the chamber and their trajectories are traced using the Discrete Phase Model (DPM). The simulation results show that the vortex combustor can achieve high efficient combustion of aluminum and steam. The influencing factors, such as the eccentric distance of the inlet of aluminum particles, particle size and steam inlet diameter, etc., are studied. The work described in this paper represents an attempt to the design of a vortex combustor in order to increase aluminum combustion efficiency.

Tackling the intricacies of network dismantling in complex systems poses significant challenges. This task has relevance across various practical domains, yet traditional approaches focus primarily on singular metrics, such as the number of nodes in the Giant Connected Component (GCC) or average pairwise connectivity. In contrast, we propose a unique metric that concurrently targets nodes with the highest degree and reduces the GCC size. Given the NP-hard nature of optimizing this metric, we introduce MaxShot, an innovative end-to-end solution that leverages graph representation learning and reinforcement learning. Through comprehensive evaluations on both synthetic and real-world datasets, our method consistently outperforms leading benchmarks in accuracy and efficiency. These results highlight MaxShot’s potential as a superior approach to address the network dismantling problem effectively.

Coronavirus disease 2019 (COVID-19) has affected medical practice. More than 7,000,000 patients died worldwide after being infected with COVID-19; however, no specific laboratory markers have yet been established to predict death related to this disease. In contrast, electrocardiographic changes owing to COVID-19 include QT prolongation and ST-T changes; however, there have been no studies on ambulatory electrocardiographic markers of COVID-19. We encountered three patients diagnosed as having COVID-19 who did not have a prior history of significant structural heart diseases. All had abnormalities in ambulatory echocardiogram parameters detected by high-resolution 24-h electrocardiogram monitoring: positive late potentials (LPs) and T-wave alternans (TWA), abnormal heart rate variability (HRV), and heart rate turbulence (HRT). Case 1 involved a 78-year-old woman with a history of chronic kidney disease, Case 2 a 76-year-old man with hypertension and diabetes, and Case 3 a 67-year-old man with renal cancer, lung cancer, and diabetes. None of them had a prior history of significant structural heart disease. Although no significant consistent increases in clinical markers were observed, all three patients died, mainly because of respiratory failure with mild heart failure. LP, TWA, HRV, and HRT were all positive in three cases with no significant structural cardiac disease at the initial phase of admission. There is a possibility that LP, TWA, HRV, and HRT have the potential to be risk stratifiers of COVID-19 pneumonia in the early phase of admission. Further accumulation of data regarding ambulatory electrocardiographic markers in patients with COVID-19 is needed.

The emerging working mode of coordinated trucks and drones has demonstrated significant practical potential in various fields, including logistics and delivery, intelligence surveillance reconnaissance, area monitoring, and patrol. The seamless collaboration between trucks and drones is garnering widespread attention in academia and has emerged as a key technology for achieving efficient and secure transportation. This paper provides a comprehensive and in-depth review of the research status on the routing problem for coordinated trucks and drones, covering aspects such as application background, cooperative modes, configurations, issues have been taken into consideration, and solution methodologies.

The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities, and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantage of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on the continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. Experimental results illustrate that respiration and heartbeat signals can be extracted accurately under different conditions. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications.

System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these issues, we present an Agent-Based Model (ABM) for SoS evolution in the Internet of Vehicles (IoV) , serving as a quantitative analysis tool for SoS research. By integrating multiple complex and rational behaviors of individuals, we aim to simulate real-world scenarios as accurately as possible. To simulate the SoS evolution process, our model employs multiple agents with autonomous interactions and incorporates external environmental variables. Furthermore, we propose three evaluation metrics: evolutionary time, degree of variation, and evolutionary cost, to assess the performance of SoS evolution. Our study demonstrates that enhanced information transparency significantly improves the evolutionary performance of distributed SoS. Conversely, the adoption of uniform standards only brings limited performance enhancement to distributed SoSs. Although our proposed model has limitations, it stands out from other approaches that utilize Agent-Based Modeling to analyze SoS theories. Our model focuses on realistic problem contexts and simulates realistic interaction behaviors. This study enhances the comprehension of SoS evolution processes and provides valuable insights for the formulation of effective evolutionary strategies.

RNAi is considered a major antiviral defense mechanism in insects but its relative importance compared to other antiviral pathways has not been evaluated comprehensively. Here, it is attempted to give an overview of the antiviral defense mechanisms in Drosophila that involve both RNAi and non-RNAi to acquire a sense of their relative importance. While RNAi is considered important in most viral infections, many other pathways can exist that confer antiviral resistance. It is noted that very few direct recognition mechanisms of virus infections have been identified in Drosophila and that the activation of immune pathways may be accomplished indirectly through cell damage incurred by viral replication. In several cases, protection against viral infection can be obtained in RNAi mutants by non-RNAi mechanisms, confirming the variability of the RNAi defense mechanism according to the type of infection and the physiological status of the host. This analysis invites to investigate more systematically the relative contribution of RNAi in the antiviral response and more specifically to ask whether RNAi efficiency is affected when other defense mechanisms predominate. While Drosophila can function as a useful model, this issue may be more critical for economically important insects that are either controlled (agricultural pests and vectors of diseases) or protected from parasite infection (beneficial insects as bees) by RNAi products.

{This study investigates the coordinated behaviors and the underlying collective intelligence in biological groups, particularly those led by informed leaders. By establishing new convergence criteria based on real biological group experiments, this research introduces the concept of a volitional term and heterogeneous networks, constructing a coupled force Cucker-Smale model with informed leaders. The inclusion of the informed leader aspect distinctively characterizes the dynamics of leaders and followers, enabling a more accurate representation of biological group behavior. The paper then proposes the Flock Leadership Hierarchy Network (FLH), a model reflecting real biological interactions. By employing time slicing and rolling time windows, the study methodically analyses group behavior stages, using volatility and convergence time as metrics to examine the relationship between group consistency and interactions. Comparative experiments show the FLH network's superior performance. The Kolmogorov-Smirnov test indicates that the FLH network follows a power-law distribution, highlighting the evolutionary intelligence of biological groups. This research offers new perspectives on the evolution of biological groups, contributing to our understanding of both natural and artificial systems, such as animal migration and autonomous drone operations.

This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER) rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1) formulation of risk assessment hierarchy, (2) representation of both qualitative and quantitative information, (3) elicitation of attribute weights and information reliabilities, (4) aggregation of assessment information using the ER rule and (5) quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

Unmanned aerial vehicle UAV has become an important tool for emergency communication. When disaster happens, the roads in the disaster area always are seriously damaged, and theground infrastructure communication facilities are damaged. Under emergency conditions, UAV can go into key areas as communication nodes to provide communication services for users in the area.But it's difficult for UAV to cover the entire disaster area and the efficient rescue time will be delayed. Therefore, how to make the UAV accurately perceive the regional situation and deployed in the right position is worth studying. In this paper, a virtual simulation environment is established reasonably and deep reinforcement learning algorithm is used to train UAV agents. At the same time, a series of problems such as sparse reward and long training time are still not solved in the development of reinforcement learning algorithms,and the reward function is designed to improve training efficiency. First of all, we set a specific mountain emergency communication scenario, and combined with the specific application of the UAV to carry out virtual simulation, and build a virtual environment. Furthermore, an additional shaped reward function is designed to address the sparse reward problem. Through the improvement of deep Q-learning network DQN algorithm and the reward design based on potential function, the final evaluation index is improved, and the effectiveness of the algorithm is verified. The experimental results demonstrate our work can effectively shorten the training time and increase convergencerate.

Event detection provides a crucial foundation for intelligent text analysis and supports numerous downstream applications. However, existing detection models often fail to meet the high accuracy requirements and typically require a human–machine collaborative detection mode involving “machine detection followed by manual audit and correction.” Analysis reveals that the recall rate of machine detection is a major factor limiting the efficiency of human–machine collaboration. To address this at its root and ensure high recall, an event trigger recommendation task is introduced, and a span-based recommendation model for Chinese, SpETR (Span-based Event Trigger Recommender), is developed. This model integrates confidence information from both trigger identification and event classification stages to recommend candidate triggers and their event types for each event. To enhance recall, a semantic boundary smoothing method is proposed, which assigns soft labels to spans around gold triggers based on semantic completeness and part-of-speech, combined with a modified focal loss function to make the model predictions smoother. Experiments on DuEE and a self-built dataset show that SpETR is most effective when the number of recommendations is set to 3, achieving recall rates of 97.76% and 98.70%, respectively, comprising improvements of 4.30% and 5.22% over the optimal baseline models. In terms of human–machine collaborative detection, SpETR saved 30.6% and 25.8% of time compared to traditional detection models on two datasets, and the average F1 score of the annotation results was also improved by 5.35% and 3.48%, respectively.

A well known technique to enhance the signal to noise ratio (SNR) of repetitive signals is to average them. The coherent parts of the signal add up constructively while the incoherent parts are averaged out. The prerequisite is that the signals are acquired under conditions of high repeatability, i.e.\ the signals must be sufficiently similar. In the present technical note we describe an efficient method for maintaining signal similarity by ensuring spatial and temporal proximity of laser waveform signals obtained by a sensor operated from an airborne platform. The method makes use of a few auxiliary parameters such as laser pulse repetition rate, mirror rotation rate, platform altitude, and flight speed. The method can be extended to be operated in real time.

Begomoviruses, which belong to the Geminiviridae family, are intracellular parasites transmitted by whiteflies to dicotyledonous plants, significantly damaging agronomically relevant crops. These nucleus-replicating DNA viruses need to move intracellularly from the nucleus to the cytoplasm and then, like other plant viruses, spread systemically throughout the plant to cause dis-ease. The transport proteins of begomoviruses play a crucial role in recruiting host components for the movement of viral DNA within and between cells while exhibiting functions that suppress the host's immune defense. Pioneering studies on species of the Begomovirus genus have identified specific viral transport proteins involved in intracellular transport, cell-to-cell movement, and systemic spread. Recent research has primarily focused on viral movement proteins and their interaction with the cellular host transport machinery, significantly expanding our understanding of viral infection pathways. This review focuses on three main aspects: (i) the role of viral transport proteins, specifically movement proteins (MPs) and nuclear shuttle proteins (NSPs), (ii) their ability to recruit host factors for intra- and intercellular viral movement, and (iii) suppress antiviral immunity, with a particular emphasis on bipartite begomoviral movement proteins.

Cotton (Gossypium hirsutum Linn.) is widely cultivated in China. The polyphagous insect Adelphocoris suturalis (Jakovlev) is a serious insect pest in cotton growing regions. Plants have evolved sophisticated systems to cope with herbivore attacks. However, the cotton defense mechanisms induced by A. suturalis feeding have lagged behind. We carried out untargeted proteomic analysis using the iTARQ technique and metabolomics based on LC-MS/MS analysis of cotton leaves fed upon by A. suturalis. Proteomic analysis identified 775 upregulated proteins and 477 downregulated proteins in plants that were infested by A. sututralis compared to the controls. Metabolomic analysis identified 50 differentially expressed metabolites in the positive ion mode and 14 in the negative ion mode compared to the controls. The tryptophan metabolism pathway was significantly changed in both the positive and negative ion mode in the metabolomics analysis. The alpha-linolenic acid pathway was significantly changed in both the proteomic and metabolomics analyses. Furthermore, the result was validated by RT-qPCR analysis of 5 related genes involved in alpha-linolenic acid pathway. These results indicate that tryptophan metabolism and the alpha-linolenic acid pathway may be important in cotton defense against herbivores and would enhance our understanding of plant defenses induced by A. sututrali feeding.

We report a facile route for the green synthesis of trimethylchitosan nitrate-capped silver nanoparticles (TMCN-AgNPs) with positive surface charge. In this synthesis, silver nitrate, glucose, and trimethyl chitosan nitrate (TMCN) were used as silver precursor, reducing agent, and stabilizer, respectively. The reaction was carried out in a stirred basic aqueous medium at room temperature without the use of energy-consuming or expensive equipment. We investigated the effects of the concentrations of NaOH, glucose, and TMCN on the particle size, zeta potential, and formation yield. The AgNPs were characterized by UV-visible spectroscopy, photon correlation spectroscopy, laser Doppler anemometry, transmission electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The catalytic activity of the TMCN-AgNPs was studied by the reduction of 4-nitrophenol using NaBH₄ as a reducing agent. We evaluated the antibacterial effects of the TMCN-AgNPs on Acinetobacter baumannii, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus using the broth microdilution method. The results showed that both gram-positive and gram-negative bacteria were killed by the TMCN-AgNPs at very low concentration (< 6.13 μg/mL). Moreover, the TMCN-AgNPs also showed high antibacterial activity against clinically isolated multidrug-resistant A. baumannii strains, and the minimum inhibitory concentration (MIC) was ≤ 12.25 μg/mL.

The doctoral defense is an important step towards obtaining the doctoral degree. As such, preparing for the event is necessary. Anecdotal evidence highlights that there is a wide variety of ways in which doctoral candidates prepare for the defense. In this work, I want to explore if there is a relation between the way in which a doctoral candidate prepares for the defense and two important aspects of the defense: the outcome of the defense, and the student perception during and after the defense. For this purpose, I first reviewed the literature on the topic of the preparation for the doctoral defense. Then, I carried out an international survey on the doctoral defense and analyzed the data of the 204 completed surveys with respect to the preparation for the defense using quantitative and qualitative methods. The methods I used included the statistical tests of the correlation between on one hand the preparation and on the other hand the defense outcome and student perception. I used inductive thematic analysis of the open-ended survey questions to gain deeper insight in the way candidates prepared for their defense. I found that candidates most often prepare by making their presentation, reading their thesis, and practicing. The most effective measure is the mock defense, followed by a preparatory course. Reading blogs, books, and chapters is a less effective preparation measure. The conclusion of this work is that doctoral candidates need to understand the format of their defense in order to be able to prepare properly, and that universities should explore either individual pathways to the defense or pilots using a mock defense and/or preparatory course to give their doctoral candidates the necessary tools to prepare for their doctoral defense.

Species of the genus Drosophila have served as favorite models in speciation studies; however, genetic factors of interspecific reproductive incompatibility are underinvestigated. Here we performed the analysis of hybrid female sterility by crossing Drosophila melanogaster females and Drosophila simulans males. Using transcriptomic data analysis, molecular, cellular, and genetic approaches, we analyzed differential gene expression, transposable element (TE) activity, piRNA biogenesis, and functional defects of oogenesis in hybrids. Premature germline stem cell loss was the most prominent defect of oogenesis in hybrid ovaries. Due to the differential expression of genes encoding piRNA pathway components, rhino and deadlock, the functional RDCmel complex in hybrid ovaries was not assembled. However, the activity of the RDCsim complex was maintained in hybrids, independent of the genomic origin of piRNA clusters. Despite the identification of a cohort of overexpressed TEs in hybrid ovaries, we found no evidence that their activity can be considered the main cause of hybrid sterility. We revealed a complicated pattern of Vasa protein expression in the hybrid germline, including partial AT-chX piRNA targeting of the vasasim allele and a significant zygotic delay in vasamel expression. We arrived at the conclusion that the hybrid sterility phenotype was caused by intricate multi-locus differences between the species.

Natural host defensins, also sometimes termed antimicrobial peptides, are evolutionarily conserved. They have been studied as antimicrobials, but some pharmaceutical properties, undesirable for clinical use, led to the development of synthetic molecules with constructed peptide arrangements and/or peptides not found in nature. The leading development currently is synthetic small molecule nonpeptide mimetics, whose physical properties capture the characteristics of the natural molecules, and share their biological attributes. We studied brilacidin, an arylamide of this type, for its activity in vitro against fungi (40 clinical isolates, 20 species) that the World Health Organization has highlighted as problem human pathogens. We find antifungal activity at low concentrations for many pathogens, which indicates further screening for activity, particularly in vivo, is justified to evaluate this compound, and other mimetics, as attractive leads for development of effective antifungal agents.

This study employs the reflection symmetry decomposition (RSD) method to extract polarization scattering features from ground object images, aiming to determine the optimal data input scheme for deep learning networks in polarimetric synthetic aperture radar classification. Eight distinct polarizing feature combinations are designed, and the classification accuracy of various approaches is evaluated using the classic convolutional neural networks(CNNs) AlexNet and VGG16. The findings reveal that the commonly employed 6-parameter input scheme, favored by many researchers, lacks the comprehensive utilization of polarization information and warrants attention. Intriguingly, leveraging the complete 9-parameter input scheme based on the polarization coherence matrix results in improved classification accuracy. Furthermore, the input scheme incorporating all 21 parameters from the RSD and polarization coherence matrix notably enhances overall accuracy and the Kappa coefficient compared to the other 7 schemes. This comprehensive approach maximizes the utilization of polarization scattering information from ground objects, emerging as the most effective CNN input data scheme in this study. Additionally, the classification performance using the second and third component total power values (P2 and P3) from the RSD surpasses the approach utilizing surface scattering power value (PS) and secondary scattering power value (PD) from the same decomposition.

This paper addresses the growing concerns surrounding cloud computing security and highlights key strategies for ensuring the privacy and protection of data in information-critical industries. Cloud computing has revolutionized the field of information technology, providing convenience and efficiency in data processing. However, it has also brought to light significant challenges in terms of data security and privacy. Given the rise in cyber threats and the potential risks associated with storing sensitive information on cloud servers, critical industries such as healthcare and banking have been hesitant to adopt cloud computing as a trusted solution for their data needs. This work examines the specific security concerns that these industries face and proposes measures to mitigate them. Further, the paper explores the barriers that hinder the adoption of cloud computing in critical industries and offers solutions to address these concerns.

The multi-UAV target search problem is crucial in the field of autonomous Unmanned Aerial Vehicle (UAV) decision-making. The algorithm design of Multi-agent Reinforcement Learning (MARL) methods has become integral to research on multi-UAV target search, due to its adaptability to the rapid online decision-making required by UAVs in complex, uncertain environments. In non-cooperative target search scenarios, targets may have the ability to escape, complicating UAVs' search efforts and hindering the convergence of the MARL algorithm training. This paper investigates the multi-UAV target search problem in scenarios involving static obstacles and dynamic escape targets, modeling the problem within the framework of Decentralized Partially Observable Markov Decision Process. Based on this model, a Spatio-Temporal Efficient Exploration network and a Global Convolutional Local Ascent mechanism are proposed. Subsequently,we introduce a Multi-UAV Escape Target Search Algorithm Based on MAPPO(ETS-MAPPO) for addressing the escape target search difficulty problem. Simulation results demonstrate that the ETS-MAPPO algorithm outperforms five classical MARL algorithms in terms of the number of target searches,the area coverage rate, and other metrics.

Background/Objectives: Patients with chronic kidney disease (CKD) have an increased risk of cardiovascular disease (CVD). Carotid intima-media thickness (C-IMT) is a non-invasive marker of atherosclerosis. Low omega-3 polyunsaturated fatty acids (PUFA) intake and vitamin D deficiency are potential cardiometabolic risk factors in patients with CKD. The aim of this study was to evaluate dietary intake and status of omega-3 PUFA and vitamin D in pre-dialysis and hemodialysis patients and to examine the link of dietary α-linolenic acid (ALA) and fish consumption with blood pressure and C-IMT in CKD patients. Methods: All 77 selected patients (36 pre-dialysis, 41 on hemodialysis) underwent standardized clinical, nutritional, and laboratory assessments. Repeated 24-hour recalls were performed to assess dietary intake. The fatty acid profile was determined by gas-liquid chromatography. Results: Inadequate vitamin D intake and vitamin D status were found in 95% of patients. PUFAs profiles did not differ between hemodialysis and pre-dialysis participants. Dietary intake of ALA was negatively correlated with systolic blood pressure (SBP) (p=0.007), C-IMT (p=0.002), serum CRP (p=0.044), iPTH (p=0.01) and 25(OH)D3 (p=0.006). ALA intake of more than 0.23 g/daily was associated with lower SBP (p=0.001), serum 25(OH)D3 (p=0.004), and C-IMT (p=0.002). Conclusions: This study contributes to a better understanding of the relationship between dietary ALA intake and C-IMT in CKD. The results of this study could emphasize the significant role of the high prevalence of vitamin D deficiency and inadequate omega-3 PUFA intake and status considering CVD health in CKD patients.

Polarimetric features extracted from polarimetric synthetic aperture radar (PolSAR) images contain abundant scattering information of objects. Utilizing this information for PolSAR image classification can improve accuracy and enhance object monitoring. Although significant progress has been achieved in related research, there are still issues such as insufficient utilization of polarimetric information and features. In this paper, a deep learning classification method based on polarimetric channel power features for PolSAR is proposed. The distinctive characteristic of this method is that the polarimetric features inputted into the deep learning network are the power values of polarimetric channels, where these channels are treated equivalently and contain complete polarimetric information. In terms of experimental comparative study, besides polarimetric power combinations, three different data input schemes were employed as data for the input end of the convolutional neural network (CNN), taking into account existing research. The neural networks utilizes the extracted polarimetric features to classify images, and the classification accuracy analysis is employed to compare the strengths and weaknesses of different input schemes. It is worth mentioning that the polarized characteristics of the data input scheme mentioned in this article have been derived through rigorous mathematical deduction, and each polarimetric feature has clear physical meaning. By testing different data input schemes on the Gaofen-3 (GF-3) PolSAR image, the experimental results show that the method proposed in this article outperforms existing methods and can improve the accuracy of classification to a certain extent, validating the effectiveness of this method in large-scale area classification.

This project designed a set of network security mechanisms for cloud applications in VANETs. At present, cloud computing is one of the government’s development priorities in the industry. We divide cloud into public, private, and hybrid clouds in this project. Vehicles or passengers can access road conditions or public transport information through the public cloud; public transportation can access current driving records and users can access relevant enterprise information on the private cloud and hybrid cloud is a combination of public and private clouds. Both cloud computing or VANETs require network and information security. At present, many researches on VANETs security only focus on message communication, and neglect information storage. Researches on cloud computing security only focus on information protection, and neglect user privacy and anonymity. This project designed a set of network and information security mechanisms in line with the requirements of Confidentiality, Authentication, Non-repudiation, Conditional Anonymity, and Conditional Untraceability. This project primarily needs to achieve the following: 1.an authentication mechanism to verify the identity of each other between the passenger and the vehicle and to verify the identity with Single Sign-On; 2. vehicle or user privacy and anonymity, which need to be able to replace the anonymous ID and related parameters for the vehicle or the user; 3. a private communication mechanism, which enables any vehicle or user to communicate privately; and 4. an information security encryption method, which can encrypt the information on a cloud server to avoid unauthorized access by internal personnel or hackers.

This paper presents an approach to improve the robustness of tip-tilt controllers for fast-steering mirror (FSM)-based laser beam steering (LBS) systems in the presence of dynamic disturbances such as external shocks. To this end, we propose the addition of a disturbance observer (DOB)-based anti-shock controller in parallel to the original linear servo control loop to improve its control performance in the presence of external shocks. To increase the tip-tilt control performance against external shocks, the DOB-based control method, which is an improved control method for eliminating nonperiodic disturbances, is implemented in the original tip-tilt control system. Results indicate that the control error of the DOB-based anti-shock controller decreased, resulting in an efficient improvement in its disturbance-rejection performance.

This study presents an effective control algorithm to improve the robustness of fast steering mirror (FSM)-based laser beam steering systems against dynamic disturbances such as repetitive disturbances resulting from operating conditions. A stable control system must be able to maintain the required high-precision control even when dynamic disturbances affect the FSM system. In this study, an improved control method is proposed using an internal model principle (IMP)-based nonlinear controller with a disturbance observer (DOB) for the FSM system. This IMP-based controller with DOB can attenuate the residual control error signal under dynamic disturbance conditions.

Social biases may concentrate attention of researchers on a small number of well-known molecules/mechanisms leaving others underexplored. In accordance with this view, central to mechanistic toxicology is a narrow range of molecular pathways that are assumed to be involved in significant part of responses to toxicity. It is unclear, however, if there are other molecular mechanisms which play important role in toxicity events but are overlooked by toxicology. To identify overlooked genes sensitive to chemical exposures we used publicly available databases. First, we used data on published chemical-gene interactions for 17,338 genes to estimate their sensitivity to chemical exposures. Next, we extracted data on publication numbers per gene for 19,243 human genes from Find My Understudied Genes database. Threshold were applied to both datasets using our algorithm to identify chemically sensitive and chemically insensitive genes and well-studied and underexplored genes. 1,110 underexplored genes highly sensitive to chemical exposures were used in GSEA and Shiny GO analyses to identify enriched biological categories. Metabolism of fatty acids, amino acids, and glucose were identified as underexplored molecular mechanisms sensitive to chemical exposures. These findings suggest that future effort is needed to uncover the role of xenobiotics in the current epidemics of metabolic diseases.

Keywords: leptophages; Cas system; bacteriophages; Leptospira interrogans

The doctoral defense is an important step in the doctoral journey and an essential requirement for obtaining the doctoral degree. Past research on the doctoral defense has focused solely on national practices. In this work, I investigate the potential link between the doctoral defense format based on its major and minor elements and the perception of the defense by the student. For this purpose, I first reviewed the different defense formats used internationally to extract the different elements of the doctoral defense, as well as the literature on students’ perceptions of the doctoral defense. Then, I carried out an international survey which received 297 responses, of which 204 completed surveys which I used for the analysis in this article. I first analyzed the outcomes of the survey using qualitative and quantitative methods, and then cross-correlated the outcomes of defense format to the outcomes of student perception. From this analysis, I observe that the defense elements that positively impact the students’ perception are: publication of the thesis before the defense, receiving committee feedback before the defense, knowing the recommendation of one or more committee members in advance, having the supervisor present in the audience or as part of the committee, using a dress code, and including a laudatio. The final conclusion of this work is threefold. The first conclusion is that the details of the defense format impact most the students’ perception. The second conclusion is that doctoral students on average value the defense as a positive experience. The third conclusion is that the defense format cannot influence two important aspects of how a student perceives the defense: the student’s inner life and lived experience during the defense, and the behavior of the committee members.

Rock materials failures are accompanied by the co-existence of various failure mechanisms, in-cluding rock fracturing, shearing, and compaction yield. These mechanisms manifest macro-scopically as multiple failure modes and nonlinear strength characteristics related to stress levels. Considering the limitations of current rock mechanics strength theories, which are primarily derived from single failure mechanisms, this study evaluates the applicability of alternative strength theories. Based on the extensional-strain criterion and the PMC (Paul-Mohr-Coulomb) model, a piecewise linear strength model was proposed that is suitable for analyzing multiple failure mechanisms in rocks and revealing the intrinsic mechanisms of multi-mechanism rock material failure. A multiple failure mechanism strength model in the form of inequalities was proposed, using the generalized shear stress, mean stress, and stress Lode angle as parameters. Strength tests conducted on sandstone and granite rock material samples under different stress conditions revealed distinct piecewise linear strength characteristics for both rock types, vali-dating the rationality and applicability of the multiple failure mechanism model. The findings construct a multi-mechanism failure model for rocks, providing enhanced predictive capabilities and aiding in the prevention of rock structural failures.

Immune checkpoint inhibitors (ICI) are a promising form of immunotherapy that has significantly changed the therapeutic landscape for many advanced cancers. They have shown unique clinical benefit against a broad range of tumour types and a strong overall impact on survival in studied patient populations. However, there are still many limitations holding back this immunotherapy from reaching its full potential as a possible curative option for advanced cancer patients. A great deal of research is being undertaken in the hope of driving advancements in this area, building a better understanding of the mechanisms behind immune checkpoint inhibition and ultimately developing more effective, safer, and wider-reaching agents. Taking into account the current literature on this topic, this review aims to explore in depth the basis of the use of ICIs in the treatment of advanced cancers, evaluate its efficacy and safety, consider its current limitations, and finally reflect on what the future holds for this very promising form of cancer immunotherapy.

The intestinal microbiota, comprised of bacteria, archaea, and phages, inhabits the gastrointestinal tract of the organism. Male reproductive sterility is currently a prominent topic in medical research. Increasing research suggests that gut microbiota dysbiosis can result in various reproductive health problems. This article specifically investigates the impact of gut microbiota dysbiosis on male reproductive infertility development. Gut microbiota imbalances can disrupt the immune system and immune cell metabolism, affecting testicular growth and sperm production. This dysfunction can compromise the levels of hormones produced and secreted by the endocrine glands, affecting male reproductive health. Furthermore, imbalance of the gut microbiota can disrupt the gut-brain-reproductive axis, resulting in male reproductive infertility. This article will explore how the imbalance of the gut microbiota impacts male reproductive infertility through immune regulation, endocrine regulation, and interactions of the gut-brain-reproductive axis, concluding with recommendations for prevention and treatment.

Mammalian species possess sophisticated innate immune mechanisms that collectively combat a wide array of viral pathogens. Among these, the well-characterized interferon (IFN) response has been extensively researched; however, the role of antiviral RNA interference (RNAi) in mammals is emerging as an area of significant interest. Previous research has noted that Dicer, an enzyme crucial for processing double-stranded RNA (dsRNA), exhibits reduced activity in vitro, and that the IFN response may overshadow or inhibit the antiviral functions of RNAi in mammalian cells. Consequently, the functional relevance of RNAi in antiviral defense within mammalian somatic cells remains an open question. The evolution of antiviral systems in human populations reflects their substantial advantages, paralleling the evolutionary pressure on genomes encoding such defense mechanisms. While the well-studied protein-guided immune responses in mammals are essential for survival in viral environments, small RNA-mediated antiviral systems, which utilize complementary base pairing to silence non self-genetic material, also play a crucial role. In mammals, evidence suggests that microRNAs (miRNAs) regulate genes integral to antiviral responses, and emerging data indicate that small interfering RNAs (siRNAs), PIWI-interacting RNAs (piRNAs), and transfer RNAs (tRNAs) can directly target virus-derived nucleic acids. This review aims to highlight some of the recent progress in understanding mammalian antiviral RNAi mechanisms.

With the rapid development of intelligent logistics and network environment, it has become an urgent problem to efficiently and accurately handle and analyse the huge amount of uncertain decision information. Traditional decision making methods often fail to make the best use of complex and incomplete information, especially in the field of cyber defence. To address these problems, this paper introduces a new mathematical tool, discrete multidimensional Z-numbers (MZs), for expressing and dealing with uncertainty and reliability in network defence decisions. In this paper, we first introduce the synthesis method of discrete multidimensional Z-numbers, which allows us to consider the uncertainty and reliability of multi-source information in network defence strategy. Then, the hidden probability of MZs is calculated by using the hidden probability model, and the multidimensional Z+−number is proposed, which improves the expressiveness of the model in dealing with information uncertainty. Based on MZs, we define a variety of utility functions and build a multi-attribute group decision framework for network defence around these functions. The MZs provides a novel perspective for analysing and designing response strategies, especially against highly adaptive and covert attacks. The method in this paper is verified by a case of network security assessment of an intelligent logistics company. The results show that this method can significantly improve the accuracy and efficiency of decision making, demonstrating its unique advantages and wide application potential in network defence. This integrated discrete multidimensional Z-number group decision method is not only suitable for intelligent logistics decision making, but also provides an efficient decision support tool for network defence, which helps to improve the intelligence and adaptability of network security defence.

The regulation of cell death is a fundamental issue in cell biology and continues to be intensely investigated worldwide. The significance of research in this field persists because understanding the determinants of cell lifespan directly impacts the maintenance of multicellular organism homeostasis and, consequently, is crucial for addressing biomedical challenges associated with various diseases. It is recognized that the initiation of cell death can be prompted by both specific signals (such as cytokines or hormones) and nonspecific stimuli, including radiation, temperature increase, or oxidants. When these factors affect a cell, numerous signaling pathways are triggered in the cell, leading to neutralization of the effects of their negative effects or, in case of irreparable damage, to cell elimination. This removal of damaged cells occurs through apoptosis or programmed cell death, a highly regulated process. Numerous signaling molecules participate in orchestrating the apoptotic process, many of which also govern other essential functions within the organism. Physiological factors capable of triggering the apoptotic program in cells include nitric oxide (NO), which serves as one of the key signaling molecules regulating the functions of the cardiovascular, nervous, and immune systems of the organism. The unique chemical nature of NO, along with its numerous intracellular targets and physiologically active redox forms, raises questions about the specific mechanisms through which NO exerts its damaging effects on cells. Utilizing pharmacological preparations- such as sources (donors) of exogenous nitric oxide- represents an approach to investigating the initiation and execution of the apoptotic program in sensitive target cells. Furthermore, this approach holds promise as a direction for discovering new selective drugs.

The combination of several therapeutic strategies is often seen as a good way to decrease the resistance rates, since bacteria overcome better single-drug treatments than multi-drug ones. This strategy is especially attractive when several targets and subpopulations are affected, as it is the case of Klebsiella pneumoniae persister cells, a subpopulation of bacteria able to transiently survive antibiotic exposures. This work aims to evaluate the potential of a repurposed anticancer drug, mitomycin C, combined with the K. pneumoniae lytic phage vB_KpnM-VAC13 in vitro and the safety in an in vivo murine model against two clinical isolates of this pathogen, one of them exhibiting an imipenem-persister phenotype. At the same time, we verified the absence of toxicity of mitomycin C at the concentration using the human chondrocyte cell line T/C28a2. The viability of these human cells was checked both by cytotoxicity assays and flow cytometry.

The process of oxygenic photosynthesis is primarily driven by two multiprotein complexes known as photosystem II (PSII) and photosystem I (PSI). PSII facilitates the light–induced reactions of water–splitting and plastoquinone reduction, while PSI functions as the light–driven plastocyanin-ferredoxin oxidoreductase. In contrast to the highly conserved structure of PSII among all oxygen–evolving photosynthetic organisms, the structures of PSI exhibit remarkable variations, especially for photosynthetic organisms that grow in special environments. In this review, we make a concise overview of the recent investigations of PSI from photosynthetic microorganisms including prokaryotic cyanobacteria and eukaryotic algae from the perspective of structural biology. All known PSI complexes contain a highly conserved heterodimeric core; however, their pigment compositions and peripheral light-harvesting proteins are substantially flexible. This structural plasticity of PSI reveals the dynamic adaptation to environmental changes for photosynthetic organisms.

This review aims to explore the intricate relationship between epigenetic mechanisms, stress, and affective disorders, focusing on how early life experiences and coping mechanisms contribute to susceptibility to mood disorders. Epigenetic factors play a crucial role in regulating gene expression without altering the DNA (deoxyribonucleic acid) sequence, and recent research has revealed associations between epigenetic changes and maladaptive responses to stress or psychiatric disorders. A scoping review of 33 studies employing the PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses – Statement) guidelines investigates the role of stress-induced epigenetic mechanisms and coping strategies in affective disorders' occurrence, development, and progression. The analysis encompasses various stress factors, including childhood trauma, work-related stress, and dietary deficiencies, alongside epigenetic changes such as DNA methylation and altered gene expression. Findings indicate that specific stress-related genes frequently exhibit epigenetic changes associated with affective disorders. Moreover, the review examines coping mechanisms in patients with bipolar disorder and major depressive disorder, revealing mixed associations between coping strategies and symptom severity. While active coping is correlated with better outcomes, emotion-focused coping may exacerbate depressive or manic episodes. Overall, this review underscores the complex interplay between genetic predisposition, environmental stressors, coping mechanisms, and affective disorders. Understanding these interactions is essential for developing targeted interventions and personalized treatment strategies for individuals with mood disorders. However, further research is needed to elucidate specific genomic loci involved in affective disorders and the clinical implications of coping strategies in therapeutic settings.

Glycosphingolipids (GSLs), a subtype of glycolipids containing sphingosine, are critical components of vertebrate plasma membranes, playing a pivotal role in cellular signaling and interactions. In human articular cartilage in osteoarthritis (OA), GSL expression is known notably to decrease. This review focuses on the roles of gangliosides, a specific type of GSL, in cartilage degeneration and regeneration, emphasizing their regulatory function in signal transduction. The expression of gangliosides, whether endogenous or augmented exogenously, is regulated at the enzymatic level, targeting specific glycosyltransferases. This regulation has significant implications for the composition of cell surface gangliosides and their impact on signal transduction in chondrocytes and progenitor cells. Different levels of ganglioside expression can influence signaling pathways in various ways, potentially affecting cell properties, including malignancy. Moreover, gene manipulations against gangliosides have been shown to regulate cartilage metabolism and chondrocyte differentiation in vivo and in vitro. This review highlights the potential of targeting gangliosides in the development of therapeutic strategies for osteoarthritis and cartilage injury and addresses promising directions for future research and treatment.

The danger is still very large from cross site scripting attacks. When designing web applications We must follow as much as we can prevention rules and don’t leave any loophole to our programs. Experience is a great factor for programmers to know these attacks and for a trainee programmer is a difficult task to spot all the weak points. In this article we present a tutorial on launching an XSS attack and also we propose simple solutions.

In order to understand the defense response of Sanchezia nobilis to biotic and abiotic stresses, this study investigated the phenomenon of S. nobilis under biotic of feeding by Achatina fulica, and measured the temporal changes of malondialdehyde content, catalase and peroxidase activities under biotic of feeding by Achatina fulica and abiotic stress of garden pruning conditions on S. nobilis. The results showed that: 1) S. nobilis was seriously damaged by A. fulica and the average hourly food intake of A. fulica is 0.22 ± 0.01 g. 2) Leaf cutting stimulation and snail feeding stress significantly affected the content of malondialdehyde, the activities of catalase and peroxidase in the leaves of S. nobilis. 3) Compared with the control group, the snail feeding and leaf cutting stimulated stress could induce the leaf of S. nobilis to synthesize more malondialdehyde under varying durations, and the activities of catalase and peroxidase were significantly enhanced in a short time, and the induction response of snail feeding biological stress was faster than that of leaf cutting stimulated abiotic stress. 4) After the defense enzyme was strengthened, the activities of catalase and peroxidase in the feeding stress group of snails showed a gradual downward trend, while the activities of catalase and peroxidase in the leaf cutting stimulation stress group showed a first upward and then downward trend, indicating that abiotic stress had more lasting effects on plants than biological stress. It can be seen that biotic stress and abiotic stress significantly affect the defense response of plants, and the defense-related substances malondialdehyde, catalase and peroxidase play an important role in plants' response to biotic and abiotic stress. This study has important production guidance significance for carrying out stress resistance breeding or cultivation management of garden plants.

Leptospira, which are known to be important disease-causing agents transmitted between animals and humans, results in significant illness and, in some cases, significant death in human populations. This study aims to examine the genomic structure of Leptospira interrogans serovar Copenhageni strain FDAARGOS_203 to identify the specific genetic factors that contribute to antimicrobial resistance (AMR) and defense against phages. The genome, consisting of two contigs totaling 4,630,574 base pairs, underwent thorough examination for protein-coding sequences, transfer RNA genes, and ribosomal RNA genes. A total of twenty-two antibiotic resistance genes that specifically target essential cellular processes such as cell wall synthesis, DNA replication, and protein synthesis have been identified. Significant among these were gidB, GdpD, and PgsA, each involved in separate aspects of antibiotic resistance. In addition, the investigation explored the defense mechanisms of bacteriophages, revealing the presence of defense islands that contain a range of anti-phage systems, including RM_Type_IV, PrrC, Borvo, CAS_Class1-Subtype-IC, and CAS_Class1-Subtype-IB. This comprehensive genomic analysis enhances our understanding of the molecular mechanisms that determine Leptospira's ability to adapt to various environments. The identified genetic factors linked to AMR and defense against phages not only enhance our scientific comprehension but also provide a basis for focused interventions to reduce the impact of leptospirosis.

The aim of the study is to characterize the U.S. and Lithuanian defense cooperation from 1990–2020 including arms procurements. Findings suggest close defense cooperation between countries at Presidential, Congressional, and Defense Ministry/Secretary levels. The most developed cooperation areas are joint participation in international operations, improvements of the Lithuanian Armed Forces’ capabilities, and an increase of the U.S. military presence in the Baltic region. An analysis of Lithuanian defense procurements between 1990–2020 indicates that the majority of defense armaments were acquired from the U.S. using the Foreign Military Sales venue while other options to obtain armaments were not used.

Despite the expansion of financial institutions and proliferation of mobile financial services, reaching the unbanked and bringing them under formal financial services has become a policy concern in many developing countries. Due to the lack of financial accounts, unbanked people prefer informal, risky, and inconvenient mechanisms for receiving, sending and transferring money. Previous studies rely much on common intervention like no account maintenance and opening fees, easy documentation processes and money subsidies for opening financial accounts. This study aims to examine the impact of the motivational workshop on opening savings accounts through causality among the unbanked people in a setting where the respondents are unbanked despite having all the requirements and many institutional offers for opening savings accounts. We encouraged the unbanked people through a one-hour-long motivational workshop to open saving account. Based on our cross-sectional data and randomized controlled trial experiment among 505 unbanked Village Defense Party (VDP) members at Dhubil Union under Sirajganj in Bangladesh, we have the evidence that motivational workshop positively impacts opening ac-counts by 32.33 percent. However, the account opening rate differs in terms of respondent’s pref-erence for financial institutions. Our study also finds that unbanked people have the highest pref-erence for mobile financial services for opening accounts resulting in 15.33 percent. The result of the study has some policy implications for adopting effective strategies of financial access in many developing countries.

Autoimmune blistering diseases represent a group of chronic severe, disabling, potentially fatal disorders of the skin and/or mucous membranes primarily mediated by pathogenic auto-antibodies. Despite their rarity, these diseases are associated with significant morbidity and mortality, a profound negative impact on the patient’s quality of life and impose a considerable economic burden. Rituximab, an anti CD-20 monoclonal antibody represents the first line of therapy for pemphigus, regardless of its severity as it ensures high rates of rapid, long-lasting complete remission. Nevertheless, disease recurrence is the rule, all patients requiring maintenance therapy with rituximab sooner or later. While innate resistance to rituximab in pemphigus patients is exceptional, acquired resistance is frequent and may develop even in patients with initial complete response to rituximab, representing a real challenge for physicians. We discuss the various resistance mechanisms and their complex interplay, as well as the numerous therapeutic alternatives that may be used to circumvent rituximab resistance. As no therapeutic measure is universally efficient, individualization of rituximab treatment regimen and tailored adjuvant therapies in refractory pemphigus cases are mandatory.

Excessive oxidative stress and exercise-induced fatigue reduce physical performance and can lead to dysfunction in antioxidant systems within muscular and hepatic tissues. Integrating natural substances with exercise may mitigate fatigue via anti-oxidant effects. This study aims to compare and evaluate the effects of exercise and supplementation with Sundarbans honey vs energy drinks on the strength, anxiety physiological profiles, and hepatic antioxidant capacity in mice undergoing extraneous exercise and fatigue. Forty-eight four-week-old Swiss albino mice were randomly assigned to one of eight groups: (1) Control, (2) Speed™ (Sp), (3) Royal Tiger™ (RT), (4) Sundarbans Honey (SH), (5) Exercise (Ex), (6) Exercise + Sundarbans Honey (Ex+SH), (7) Exercise + Speed™ (Ex+Sp), and (8) Exercise + Royal Tiger™ (Ex+RT). Supplements were administered via oral gavage: Sp (2.5 ml/kg BW), RT (2.5 ml/kg BW), and SH (1 g/kg BW), four times a week for 60 days. Mice in the Ex, Ex+SH, Ex+Sp, and Ex+RT groups underwent daily swimming and running. The strength, fatigue, anxiety levels, lipid profiles, and antioxidant biomarkers were evaluated post-treatment. The SH, Ex, and Ex+SH groups exhibited significantly enhanced physical performance (p<0.05). Plasma lipid profiles, including LDL, triglycerides, total cholesterol, and fatigue-related biomarkers (ALP, AST, ALT, LDH, CK, LA, BUN, and glucose) were markedly increased in the Sp and RT groups but decreased in the SH, Ex, and Ex+SH groups compared to control (p<0.05). Exercise-induced fatigue elevated the Nrf2/HO-1 antioxidant defense system in liver tissue. IL-6 levels were reduced in the SH, Ex, and Ex+SH groups (p<0.05). These findings indicate that regular exercise combined with SH supplementation increases strength and improves lipid profiles, reducing exercise-induced oxidative stress and fatigue via modulation of the Nrf2/HO-1 pathway in liver tissue. These results highlight SH supplementation’s potential as a complementary strategy to enhance exercise outcomes and mitigate exercise-induced stress.

Placenta accreta spectrum (PAS) disorders are characterized by abnormal trophoblastic invasion into the myometrium, leading to significant maternal health risks. PAS includes placenta accreta (invasion &lt;50% of the myometrium), increta (invasion &gt;50%), and percreta (invasion through the entire myometrium). The condition is most associated with previous cesarean deliveries, and its incidence increases with the number of cesareans. Other risk factors include advanced maternal age, multiparity, and various uterine surgeries. The increasing global cesarean rates heighten the importance of early PAS diagnosis and management. The study reviewed molecular mechanisms driving PAS, focusing on signaling pathways, genetic expression, biomarkers, and non-coding RNAs involved in trophoblastic invasion. It explored genetic expression and key regulatory processes such as apoptosis, cell proliferation, invasion, and inflammation. The manuscript was compiled from recent scientific literature (2014 – 2024) from the Scopus, PubMed, Google Scholar, and Web of Science databases. Placenta Acreta Spectrum; acreta; increta; percreta; trophoblast invasion; miRNAs, lncRNAs; genetic expression; biomarkers; signaling pathways were the employed keywords to compile relevant literature. The PAS is an important obstetric health problem that challenges maternal health risks associated with abnormal trophoblastic invasion that relies on abnormal placentation, uterine scarring, and impaired decidualization. Identifying new biomarkers like AFP, sFlt-1, β-hCG, PlGF, and PAPP-A aids early detection and management. Understanding genetic expression and non-coding RNAs is crucial for unraveling PAS complexities. Besides, aberrant signaling pathways like Notch, PI3K/Akt, STAT3, and TGF-β offer potential therapeutic targets to modulate trophoblastic invasion. This review underscores the need for interdisciplinary care, early diagnosis, and ongoing research into PAS biomarkers and molecular mechanisms to improve prognosis and quality of life for affected women.

An analysis of the processes of plastic deformation and acoustic relaxation in a high-entropy alloy Al0.5CoCrCuFeNi was carried out. The following have been established: dominant dislocation defects; types of barriers that prevent the movement of dislocations; mechanisms of thermally activated movement of various elements of dislocation lines through barriers at room and low temperatures. Based on modern dislocation theory, quantitative estimates have been obtained for the most important characteristics of dislocations and their interaction with barriers.

This paper explores the ever-changing topic of cybersecurity and provides a summary of the most recent developments. In a time of unparalleled digital revolution and changing threat environments, being aware of new trends is essential to managing risks and protecting important assets. To highlight significant advancements in fields like artificial intelligence and machine learning for threat detection, the proliferation of IoT devices and related security challenges, the emergence of quantum-resistant cryptography, the development of zero trust architectures, and the growing significance of cybersecurity awareness and education, the report synthesizes insights from industry experts, academic research, and real-world case studies. The goal of the report's analysis of these patterns is to provide stakeholders with useful information so they may modify their cybersecurity plans and strengthen defenses against new threats. Cybersecurity plays a significant role in the IT industry.

Considering the worldwide impact of heart failure, it is crucial to develop approaches that can help us comprehend its root cause and make accurate predictions about its outcome. This is essential for lowering the suffering and death rates connected with this widespread illness. Cardiomyopathies frequently result from genetic factors, and the study of heart failure genetics is advancing quickly. Dilated cardiomyopathy (DCM) is the most prevalent kind of cardiomyopathy, encompassing both hereditary and nongenetic abnormalities. It is distinguished by the enlargement of the left ventricle or both ventricles, accompanied by reduced contractility. The discovery of the molecular origins and subsequent awareness of the molecular mechanism is broadening our knowledge of DCM development. Additionally, it emphasizes the complicated nature of DCM and the necessity to formulate several different strategies to address the diverse underlying factors contributing to this disease. Genetic variations that can be transmitted from one generation to another can be a significant contributor to causing family or isolated DCM. Genetic variation also plays a significant role in determining susceptibility for acquired triggers for DCM. The genetic causes of DCM can have a diverse range of phenotypic expressions. It is crucial to select the most probable patients to have advantages from genetic testing. The purpose of this research is to emphasize the significance of identifying genetic DCM, the crucial relationships between genotype and phenotype, and the usefulness of genetic testing in the therapeutic care of both those affected and their relatives. This approach is expected to gain importance once treatment is guided by genotype-specific advice and disease-modifying medications.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Chronic pancreatitis is a progressive fibroinflammatory disorder with no currently satisfactory treatment. Emerging evidence suggests an association between gut microbial dysbiosis and chronic pancreatitis. Although direct causative evidence is lacking, it is hypothesized that the gut microbiota may play a pivotal role in modulating pancreatic function via the gut-pancreas axis. Thus, modulating the gut microbiota through the administration of probiotics or prebiotics may alleviate pancreatic disorders. In this review, we first propose the potential mechanisms by which specific probiotics or prebiotics may ameliorate chronic pancreatitis, including the alleviation of small intestinal bacterial overgrowth (SIBO), facilitation of short-chain fatty acids (SCFAs) production, activation of the glucagon-like peptide 1 receptors (GLP-1Rs) in the pancreas. Since there are currently no probiotics or prebiotics used for the treatment of chronic pancreatitis, we have discussed research in other disease models that use probiotics or prebiotics to modulate pancreatic endocrine and exocrine functions and prevent pancreatic fibrosis. This provides indirect evidence for their potential application in the treatment of chronic pancreatitis. We anticipate that this research will stimulate further investigation into the gut-pancreas axis and the potential therapeutic value of probiotics and prebiotics in chronic pancreatitis.

Obesity has increasingly become a worldwide epidemic, as demonstrated by epidemiological and clinical studies. Obesity may lead to development of a broad spectrum of cardiovascular diseases (CVDs), such as coronary heart disease (CHD), hypertension, heart failure (HF), cerebrovascular disease, atrial fibrillation (AF), ventricular arrhythmias, and sudden cardiac death (SCD). In addition to hypertension, there are other cardiometabolic risk factors (CRFs) such as visceral adiposity, dyslipidemia, insulin resistance, diabetes, elevated levels of fibrinogen, and C-reactive protein and others, all of which increase the risk of CVD events. Mechanisms involved between obesity and CVD mainly include insulin resistance, oxidative stress, inflammation, and adipokines dysregulation, which cause maladaptive structural and functional alterations of the heart, particularly left ventricular (LV) remodeling and diastolic dysfunction. Natural products of plants, provide a diversity of nutrients and different bioactive compounds, including phenolics, flavonoids, terpenoids, carotenoids, anthocyanins, vitamins, minerals, fibers, and others, which possess a wide range of biological activities including antihypertensive, antilipidemic, antidiabetic, and other activities, thus conferring cardiometabolic benefits. In this review, we discussed the main therapeutic interventions using extracts from herbs and plants in preclinical and clinical trials with protective properties targeting CRFs. Molecular mechanisms and therapeutic targets of herbs and plants extracts for the prevention and treatment of CRFs are also reviewed.

The olive tree (Olea europaea L.) is an evergreen tree that occupies 19% of the woody crop area and is cultivated in 67 countries on five continents. The largest olive production is concentrated in the Mediterranean basin, where the olive tree has had an enormous economic, cultural and environmental impact since the 7th century BC. In the Mediterranean region, salinity stands out as one of the main abiotic stress factors significantly affecting agricultural production. Moreover, climate change is expected to lead to increased salinisation in this region, threatening olive productivity. Salt stress causes combined damage by osmotic stress and ionic toxicity, restricting olive growth and interfering with multiple metabolic processes. A large variability in salinity tolerance among olive cultivars has been described. This paper aims to synthesize information from the published literature on olive adaptations to salt stress and its importance in salinity tolerance. The morphological, physiological, biochemical, and molecular mechanisms of olive tolerance to salt stress are reviewed.

The rise in dependency upon information present on web and social networks has increased the importance of content credibility systems. These sys- tems can help the users to make a right decision related to buying a product, utiliz- ing a service and etc. Application areas including social network blogs of different subjects such as health, food, education, politics and product review/ratings some- times suffer incredible and wrong information flow. The content credibility sys- tems can help users to identify the credible information on these various forums. Recently, researchers have proposed certain mechanisms for these systems, out of which reputation based systems have gained most attention. However, reputa- tion systems are vulnerable to reputation based attacks, like Sybil, Slandering, and Whitewash promoting spread of wrong information. The authors have proposed a defense mechanism against these attacks that is based upon Bayesian Model. The proposed defense mechanism provides protection against these attacks so that fake or wrong information could be prevented. The authors evaluated the proposed mechanism in three different scenarios and presented the results in terms of pre- cision, recall and rate of change in rank. The results reveal almost 88%prevention against these attacks in comparison to the baseline systems.

The rapid increase in metabolic diseases occurred in the last three decades in both industrialized and developing countries has been related to the rise in sugar-added foods and sweetened beverages consumption. An emerging topic in the pathogenesis of metabolic diseases related to modern nutrition is the role of Advanced Glycation Endproducts (AGEs). AGEs can be ingested with high temperature processed foods, but also endogenously formed as consequence of a high dietary sugars intake. Animal models of high sugars consumption, in particular fructose, have reported AGEs accumulation in different tissues in association with peripheral insulin resistance and lipid metabolism alterations. The in vitro observation that fructose is one of the most rapid and effective glycating agent when compared to other sugars has prompted the investigation of the in vivo fructose-induced glycation. In particular, the widespread employment of fructose as sweetener has been ascribed by many experimental and observational studies for the enhancement of lipogenesis and intracellular lipid deposition. Indeed, diet-derived AGEs have been demonstrated to interfere with many cell functions such as lipid synthesis, inflammation, antioxidant defences, and mitochondrial metabolism. Moreover, emerging evidences also in humans suggest that this impact of dietary AGEs on different signalling pathways can contribute to the onset of organ damage in liver, skeletal and cardiac muscle, and brain, affecting not only metabolic control, but global health. Indeed, the here reviewed most recent reports on the effects of high sugars consumption and diet-derived AGEs on human health suggest the need to limit the dietary sources of AGEs, including added sugars, to prevent the development of metabolic diseases and related comorbidities.

Long COVID (Post-Acute Sequelae of COVID-19, PASC) is a consequence of infection by SARS-CoV-2 that continues to disrupt the well-being of millions of affected individuals for many months beyond their first infection. While the exact mechanisms underlying PASC remain to be defined, hypotheses regarding the pathogenesis of Long COVID are varied and include (but are not limited to) dysregulated local or systemic inflammatory responses, autoimmune mechanisms, viral-induced hormonal imbalances and long-term persistence of virus and/or fragments of viral RNA or proteins. This review article is based on a comprehensive review of the wide range of symptoms most often observed in long COVID and an attempt to integrate that information into a plausible hypothesis for the pathogenesis of PASC. In particular, it is proposed that longterm dysregulation of the gut in response to viral persistence could lead to the myriad of symptoms observed in PASC.

A case-crossover study examined how PM_2.5 from Asian Dust Storms (ADS) affects the number of emergency room (ER) admissions for cardiovascular diseases (CVDs) and respiratory diseases (RDs). Our data indicated that PM_2.5 concentration from ADS was highly correlated with ER visits for CVDs and RDs. The odds ratios (OR) increased by 2.92 (95% CI: 1.22-5.08) and 1.86 (95% CI: 1.30-2.91) per increase 10 µg/m³ in PM_2.5 levels, for CVDs and RDs, respectively. A 10 µg/m³ increase in PM_2.5 from ADSs was significantly associated with increase in ER visits for CVDs among those 65 years of age and older (an increase of 2.77 in OR) and for females (an increase of 3.09 in OR). In contrast, PM_2.5 levels had a significant impact on RD ER visits among those under 65 years of age (OR=1.77). The risk of ER visits for CVDs increased on the day when the ADS occurred in Taiwan and the day after (lag 0 and lag 1); the corresponding risk increase for RDs only increased on the fifth day after the ADS (lag 5). In Taiwan’s late winter and spring, the severity of ER visits for CVDs and RDs increases. Environmental protection agencies should employ an early warning system for ADS to reduce high-risk groups’ exposure to PM_2.5.

Bandsaw blades are typical band-shaped cutting tools characterized by low stiffness and micro-level cutting depth, resulting in distinct wear mechanisms compared to rigid cutting tools. In this study, the wear curve and wear mechanisms of bandsaw tooth during the bandsawing of Cr12MoV cold-working steel was investigated. The tool life was divided into two stages: a rapid wear stage (Stage I) and a homogeneous wear stage (Stage II). In Stage I, the wear was dominated by chipping although multiple wear mechanisms were found due to the relatively poor manufacturing accuracy compared to rigid cutting tools, which results in remarkable differences among the cutting depths of individual teeth. In Stage II, abrasive and adhesive wear were the primary wear mechanisms instead of chipping, which was related to the microstructure of Cr12MoV. Furthermore, methods for increasing the bandsaw performance were proposed based on the tooth wear mechanisms.

Apple-tree (Malus × domestica Borkh.) belongs to the genus Rosaceae. Due to its adaptability and tolerance to different soil and climatic conditions, it is cultivated worldwide for fresh consump-tion. Therefore, the priorities of apple growers are the high-quality of fruits and stable yield for high production. In total about 90 to 95 percent of fruits should fall or be eliminated from apple trees to avoid overcropping and poor-quality fruits. Several technologies such as handwork, me-chanically or chemical substances are used for fruit and bud elimination. The most profitable in commercial orchards is the use of chemicals for elimination, but due to the European Green Deal more environmentally sustainable solutions are required. Elimination of fruitlets is influenced by several factors. Additionally, the apple trees have the self-elimination mechanism. This is de-termined by apple genotype, physiological futures and genetics. This review focuses on the bio-logical factors and genetics mechanisms in apple yield self-regulation for better understanding the regulatory mechanism of fruitlets abscission for future breeding programs targeted on self-regulating yield apple varieties

The oral mucosa represents a defense between the external environment and the rest of the body and encompasses several antimicrobial and antiviral mechanisms. Oral mucosal cells are constantly bathed in hypotonic saliva (normally one-third tonicity compared to plasma) and are repeatedly exposed to environmental stresses of tonicity, temperature and pH by the drinks we imbibe (e.g. hypotonic: water, tea, coffee; hypertonic: assorted fruit juices, red wines), as well as of diverse microbial and viral flora. In the mouth, the broad-spectrum antiviral mediator MxA (a dynamin-family large GTPase) is constitutively expressed in healthy periodontal tissues, and also induced by Type III interferons (e.g. IFN-λ1). Endogenously induced human MxA and exogenously expressed human GFP-MxA formed membraneless biomolecular condensates in the cytoplasm of oral carcinoma cells (OECM1 cell line). These condensates likely represent storage granules in equilibrium with antivirally active dispersed MxA. Remarkably, cytoplasmic MxA condensates were exquisitely sensitive sensors of hypotonicity – the condensates in oral epithelium disassembled within 1-2 min of exposure of cells to saliva-like one-third hypotonicity, and spontaneously reassembled in the next 4-7 min. OECM1 cells preloaded with calcein-AM (a reporter of cytosolic “macromolecular crowding”) confirmed unquenching and then requenching of calcein fluorescence during this process. Hypertonicity had little effect on MxA condensates. The spontaneous reassembly of GFP-MxA condensates in oral epithelial cells even under continuous saliva-like hypotonicity was slowed by the protein phosphatase inhibitor cyclosporin A (CsA) and by the K-channel blocker tetraethylammonium chloride (TEA) suggestive of the involvement of the volume-sensitive WNK kinase-protein phosphatase (PTP)-K-Cl cotransporter (KCC) pathway in the regulated volume decrease (RVD) during condensate reassembly in oral cells. Thus, physiologically, hypotonic drinks (water, tea, coffee) trigger a rapid deployment of antiviral MxA throughout the cytoplasm of oral epithelial cells, with subsequent salvage of MxA back into storage granules/condensates.

Background/Objectives: Habituation and sensitization are opposite phenomena that play a role in the pathophysiology of episodic migraine and its progression to chronic migraine (CM). There have been just a few studies that have investigated these phenomena in patients with medication overuse headache (MOH) in comparison to those with chronic migraine (CM) and healthy controls (HCs), and the findings have been inconsistent. Methods: We measured and examined visual evoked potentials (VEPs) in 81 patients with MOH and 24 patients with CM, as well as 24 HCs. The VEPs were used to assess sensitization by analyzing the amplitude of the first block (100 sweeps), and to evaluate habituation by measuring the amplitude response decrement after 6 blocks. We further examined patients diagnosed with MOH based on their acute medication type and after a 3-week acute medication withdrawal program. Results: There were no significant differences between groups in terms of the first N1-P1 VEP amplitude block and its habituation. It was found that patients with MOH had a greater drop in the amplitude of the VEP P1-N2 complex after repeated stimulation than patients with CM or HC. The VEPs parameters showed no significant differences based on the specific overused drug and after a 3-week acute medication off. Conclusions: We propose that the results obtained in patients with MOH indicate an abnormal activation of inhibitory circuits in the parieto-occipital region in response to repeated modulatory stimuli.

Reactive oxygen species (ROS) are produced during cellular metabolism and in response to environmental stress. While low levels of ROS play essential physiological roles, excess ROS can damage cellular components, leading to cell death or transformation. ROS can also regulate protein interactions in cancer cells, thereby affecting processes such as cell growth, migration, and angiogenesis. Dysregulated interactions occur via various mechanisms, including amino acid modifications, conformational changes, and alterations in complex stability. Understanding ROS-mediated changes in protein interactions is crucial for targeted cancer therapies. In this review, we examine the role that ROS mechanisms in regulating pathways through protein-protein interactions.

To advance probiotic research, a comprehensive understanding of bacterial interactions with human physiology at the molecular and cellular levels is fundamental. Lacticaseibacillus rhamnosus LGG® is a bacterial strain that has long been recognized for its beneficial effects on human health. Probiotic effector molecules derived from LGG®, including secreted proteins, surface-anchored proteins, polysaccharides, and lipoteichoic acids, that interact with host physiological processes have been identified. In vitro and animal studies have revealed that specific LGG® effector molecules stimulate epithelial cell survival, preserve intestinal barrier integrity, reduce oxidative stress, mitigate excessive mucosal inflammation, enhance IgA secretion, and provide long-term protection through epigenetic imprinting. Pili on the cell surface of LGG® promote adhesion to the intestinal mucosa and ensure close contact to host cells. Extracellular vesicles produced by LGG® recapitulate many of these effects through their cargo of effector molecules. Collectively, the effector molecules of LGG® exert a significant influence on both the gut mucosa and immune system, that promotes intestinal homeostasis and immune tolerance.

Global agriculture has been forced to increase food production to feed the growing human population, while confronting various environmental obstacles such as global warming, resistance to pathogens, and constraints on arable land caused by soil salinity, drought, rising sea level, saltwater intrusion, and urbanization. Regarding abiotic stresses, salinity is a worldwide problem for agricultural production. Many efforts, therefore, have been made to cope with the environmental challenges, however, the progress of salinization, which is mainly caused and accelerated by anthropogenic activities, is likely faster than our progress in finding ways to deal with this problem. In addition, drought represents a global threat to the production of major crops. In addition, pests and pathogens cause significant crop losses and diminish global food security. Among the various strategies that have been investigated and applied in plant science, antimicrobial peptides derived from plants have caught widespread attention from scientists since these peptides exhibit beneficial biological activities. In agricultural science, there have been reports on the roles of antimicrobial peptides with active properties against biotic and abiotic stresses. Non-specific plant lipid transfer proteins, thionins, systemins, defensins, cyclotides, and heveins-like antimicrobial peptides are common antimicrobial peptides that have been found to be involved in the defense system against fungi and insect pests. Based on their potential ability to protect crops from pests, bacteria, and pathogenic fungi, the use of antimicrobial peptide genes in creating transgenic plants has been largely conducted during the last decades, and these studies have obtained positive results against the growth of fungi and bacteria. This review will focus on the latest progress in studies of antimicrobial peptides related to biotic and abiotic stress tolerance in plants. We will also update the current progress in the development of antimicrobial peptide-based transgenic crops.

Candidiasis is considered an emerging public health concern because of the occurrence of drug-resistant Candida strains and the lack of available structurally diverse antifungal drug armamentariums. The indole alkaloid globospiramine from the anticandidal Philippine medicinal plant Voacanga globosa exhibits a variety of biological activities; however, its antifungal properties remain to be explored. In this study, we report the in vitro antifungal activities of globospiramine against Candida albicans and Candida tropicalis and explore its possible target proteins using in silico methods. The colony-forming unit (CFU) viability assay revealed time- and concentration-dependent anticandidal effects of the alkaloid by decreasing almost 50% of the viable CFUs 60 min after treatment. Results of the MIC and MFC assays indicated inhibitory and fungicidal effects of globospiramine against C. albicans (MIC = 8 µg/mL; MFC = 4 µg/mL) and potential fungistatic effects against C. tropicalis at lower concentrations (MIC = 4 µg/mL; MFC &gt; 64 µg/mL). The FAM-FLICA poly-caspase assay showed metacaspase activation in C. albicans cells at concentrations of 16 and 8 µg/mL, which agreed with the MIC and MFC values. Molecular docking and molecular dynamics simulation experiments indicated stable, strong binding of globospiramine with the target proteins 1,3-β-glucan synthase and Als3 adhesin enzymes, which are indirectly involved in apoptotic-driven candidal inhibition.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense industries, because they are exposed to risk already in early stages of development. This paper uses Heterogeneity and Homogeneity analysis between risk factors with Cochran’s Q test and Multidimensional scaling in order to present the complexity of the risk factors relevant to defense SoS, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense SoS shows a need to focus on three main risks faced by defense projects: insufficient human resources, changes in the original specifications, and lack of other (non-human) resources. The paper also presents some recommendations for minimizing risk factors in defense SoS.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense projects based on systems of systems (SoS), because they are exposed to risk already in early stages of development. This paper uses advanced data science tools to present the complexity of the risk factors relevant to defense systems, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense projects based on SoS shows a need to focus on three main risks faced by defense projects: uncertainty, the lack of clearly defined goals, and managing a system under constrained conditions. The paper also presents some recommendations for minimizing risk factors in SoS for defense projects.

Adipose tissue-derived stem cells (ADSCs) represent a subset of mesenchymal stem cells in every adipose compartment throughout the body. ADSCs can differentiate into various cell types, including chondrocytes, osteocytes, myocytes, and adipocytes. Moreover, they exhibit a notable potential to differentiate in vitro into cells from other germinal lineages, including endothelial cells and neurons. ADSCs have a wide range of clinical applications, from breast surgery to chronic wounds. Furthermore, they are a promising cell population for future tissue-engineering uses. Accumulating evidence indicates decreased proliferation and differentiation potential of ADSCs with increasing age, body mass index, diabetes mellitus, metabolic syndrome, or exposure to radiotherapy. Therefore, recent literature thoroughly investigates this cell population's senescence mechanisms and how they can hinder their possible therapeutic applications. This review will discuss the biological mechanisms and the physio-pathological causes behind ADSC senescence and how they can impact cellular functionality. Moreover, we will examine the possible strategies to invert these processes, re-establishing the full regenerative potential of this progenitor population.

Cloud robot is becoming popular and security of cloud robot is important. However, the researches of cloud robot safety are a few. This work develops a security policy to defense DDoS attack of cloud robot. In this policy, complex, but accurate calculation models are deployed on the cloud, simple but efficient calculation models are deployed on the robot. In the cloud, there are master server and standby server. The master server transfers parameters of complex but accurate models to the standby server periodically and the master executes the start-stop backup policy. Specifically, this work proposes and proves an algorithm to dynamically adjust the interval of parameter transfer. According to a PDRA feature of Netflow, when DDoS attacks, the master server sends warning signals to the robot and standby server. The robot runs local models to avoid stopping work until it is connected to the standby server. Then, standby server provides service to the robot until the master server recover. Finally, this work implemented a gesture recognition cloud robot based on convolutional neural network, hidden Markov model and PDRA feature of Netflow to verify the policy. Experiment shows that the security policy to defense DDoS attack for cloud robot is effective.

This study addresses the escalating threat of data theft ransomware, a form of cyberattack that exfiltrates sensitive information from victim networks and demands ransom for its non-disclosure. Unlike traditional crypto-ransomware, data theft ransomware leverages various infiltration techniques to gain unauthorized access and control over critical data assets. The study introduces a novel Moving Target Defense (MTD) framework, specifically designed for the Windows operating system environment, to counter these sophisticated attacks. MTD increases the unpredictability of the system by dynamically altering its configurations, thereby disrupting the adversary's ability to execute successful attacks. Our research includes the development and empirical evaluation of the MTD framework, demonstrating its effectiveness in reducing ransomware operational capabilities through quantitative analysis, qualitative observations, and statistical significance testing. We also explore the challenges and complexities involved in implementing MTD in real-world scenarios and propose strategies to overcome these barriers. The study concludes with recommendations for future research directions and the potential of MTD in enhancing cybersecurity defense mechanisms.

The doctoral defense, which is an essential requirement for the doctoral degree, is considered to have three dimensions: the scholarly dimension, the emotional (affective) dimension, and the cultural dimension. In this work, I explore the link between sociodemographic factors and students’ perception of the doctoral defense. In particular, I focus on gender, ethnicity, and age at time of defense, as well as current position, and field of study. To address the influence of these aspects on the affective dimension of the doctoral defense, I first reviewed the literature on these socio-demographic aspects as well as the affective dimension of the defense. I then carried out an international survey on doctoral defenses, defense formats, and students’ perceptions and analyzed the 204 completed surveys for this study using quantitative and qualitative methods. The analysis included cross-correlations between students’ perceptions and the studied sociodemographic aspects. The main results of these analyses are that gender affects various aspects of the students’ perception of the doctoral defense and long-term perception, and that female candidates experience more issues with their committee. Ethnicity is important as well, although the participations of non-white respondents in this survey was limited. The influence of age at the defense is limited, and only for the youngest and oldest age groups I observe some differences in perception. There is no relation between current position and perception of the candidates during the defense. Finally, field of study is correlated for various aspects of student perception, committee issues, and long-term perception. The conclusion of this work is that socio-demographic aspects, and in particular gender, ethnicity, and field of study, influence how doctoral candidates experience their defense.

Microaggressions are subtle verbal and non-verbal slights based on group membership, and they are ubiquitous in the lives of racial minorities, women, and LGBTQ individuals (Sue, 2010). The goal of the current paper is to introduce a role-playing based exercise on effective responses to microaggressions. The workshop draws on the prejudice responding workshops of Plous (2000) and Lawson, et al. (2010) but integrates research-based strategies. The activity was tested in two groups of undergraduate students, and the findings suggested that both groups felt more prepared to deal with microaggressions after participating.

With the aim of developing an innovative water treatment approach for developing countries in the Global South, we have applied the method of treating a cavitating water stream with a plasma discharge under real conditions. To this end, we have optimised the approach after investigating the effects that occur in the treated medium during such a treatment. Based on the obtained light absorption curves of treated model solutions of titanium oxysulphate and potassium bichromate, it was found that inside the reactor the main role in the destruction of chemical contaminants is played by hydroxide ions, while outside the reactor the main chemical interaction takes place with hydrogen peroxide. The plasma treatment unit was tested in the biological wastewater treatment plants of a health resort on the territory of the Russian Federation (Almetyevsk, Republic of Tatarstan). Water samples taken directly from the tertiary decantation tank were used as real wastewater samples instead of adding chemical reagents for disinfection. It was found that with different modes of operation of the plasma treatment plant, the concentration levels of coliform bacteria, coliphages and Escherichia coli decrease significantly and fall below the limit of permissible concentrations for wastewater discharge. At the same time, the possible effect of the plasma on persistent inorganic compounds was investigated. It was shown that the plasma discharge in the flow of the incoming liquid can almost completely destroy compounds that are difficult to remove, such as hydrogen sulphide and chlorides. In the course of the study, the optimum frequency of the electrical pulses of 68 kHz was selected, which ensures the lowest consumption of electrical energy while maintaining the required efficiency.

Lynch syndrome (LS) is one of the most common hereditary cancer syndrome in human populations, associated with germline variants in MLH1, MSH2/EPCAM, MSH6 and PMS2 genes. The advent of next generation sequencing has proven a significant impact in germline variant detection in the causative genes; however, a large proportion of patients with clinical criteria still receive uncertain or negative results. PMS2 is the least frequent reported gene, associated with up to 15% of LS cases with late-onset disease and low penetrance phenotype; however, the proportion of PMS2-LS cases is considered to be highly underestimated. In this context, we consulted public available databases (ClinVar, LOVD) for missense and intronic PMS2 variants and performed an in silico analysis of the genomic sequence. Splicing bioinformatics tools proven effective in other genes were used to assess both the wild-type DNA sequence and reported genetic variants. Splicing alterations were predicted in silico and using GTEx short-read RNA expression data. Out of the 2384 missense variants discovered, 90% were classified with uncertain significance (VUS). 4.9% of missense variants were shown to have a potential splicing consequence (DS &gt; 0.2) using SpliceAI. As described in the original publication, SpliceAI-visual was proven effective in annotation of short intronic variants (&lt; 50 bp). Four short intronic variants were identified using SpliceAI-visual as potentially splicing disturbing, in spite of using a lower threshold (DS &gt; 0.1). Moreover, we observed that Splicing Regulatory Elements (SREs) may play a fundamental role in alternative splicing in PMS2 gene, ESE motifs being overrepresented in highly expressed exons 5, 11 and 14. Computational analysis performed in our study serves as a valuable filtering step for guiding further RNA sequencing experiments. Additional functional data is necessary to evaluate the significance of our findings.

The observation that certain therapeutic strategies for targeting inflammation benefit patients with distinct immune-mediated inflammatory diseases (IMIDs) is exemplified by the success of TNF blockade in conditions including rheumatoid arthritis, ulcerative colitis and skin psoriasis, albeit only for subsets of individuals with each condition. This suggests intersecting "nodes" in inflammatory networks at a molecular and cellular level may drive and/or maintain IMIDs, being “shared” between traditionally distinct diagnoses without mapping neatly to a single clinical phenotype. In line with this proposition, integrative tumour tissue analyses in oncology have highlighted novel cell states acting across diverse cancers, with important implications for precision medicine. Drawing upon advances in the oncology field, this narrative review will first summarise learnings from the Human Cell Atlas in health as a platform for interrogating IMID tissues. It will then review cross-disease studies to date that inform this endeavour, before considering future directions in the field.

Metal creep has been a subject of extensive study for more than 110 years, because it affects the useful life of engineering components operating at high temperatures. It is even more so with ever-increasing operating temperatures of propulsion/power-generation systems by the environmental regulations to reduce greenhouse emissions. This review summaries the recent development in creep modeling with regards to creep strain evolution, creep rate, creep ductility, creep life and fracture mode, attempting to provide a comprehensive mechanism-based framework to address all the important creep phenomena and the long-standing issue of long-term creep life prediction with microstructural evolution and environmental effects.

The segmentation of abnormal regions is vital in smart manufacturing. However, the existing segmentation system for detecting sauce-packet leakage on intelligent sensors encounters an issue of imaging blurring caused by uneven illumination. This issue adversely affects segmentation performance, thereby impeding the rapid production of industrial assembly lines. To alleviate this issue, we propose the two-stage Illumination-aware Sauce-packet Leakage Segmentation (ISLS) method for intelligent sensors. The ISLS comprises two main stages: Illumination-aware region enhancement and leakage region segmentation. In the first stage, YOLO-Fastestv2 is employed to capture the Region of Interest (ROI), which reduces redundancy computations. Additionally, we propose an image enhancement to relieve the impact of uneven illumination, enhancing the texture details of ROI. In the second stage, we propose a novel feature extraction network. Specifically, we propose the Multi-scale Feature Fusion Module (MFFM) and the Sequential Self-Attention Mechanism (SSAM) to capture discriminative representations of leakage. The multi-level features are fused by MFFM with a small number of parameters, which capture leakage semantics at different scales. The SSAM realizes the enhancement of valid features and the suppression of invalid features by adaptive weighting of spatial and channel dimensions. Furthermore, we generated a self-built dataset of sauce-packets, including 606 images with various leakage areas. Comprehensive experiments demonstrate that our ISLS method shows better results than several state-of-the-art methods, with additional performance analyses deployed on intelligent sensors to affirm the effectiveness of our proposed method. Our code is available at https://github.com/LSJ5106/SauceDetect.

The development and utilization of wind energy is of great significance to the sustainable development of China's economy and the realization of the goal of "dual carbon". Under the typhoon system, the randomness and volatility of wind speed become an important basis for affecting the energy efficiency utilization and design of wind turbines. Therefore, based on wind speed and wind direction data at 10m, 30m, 50m and 70m heights of a wind power tower in Yancheng, Jiangsu Province, this paper analyzes the change characteristics of wind speed and wind direction by using BFAST method and Hurst index. Based on typhoon body data, topographic data and mesoscale system wind direction data, the causes of the occurrence and development of wind speed and wind direction of wind tower are further analyzed, and a conclusion is drawn: (1) In BEAST method, there are 5, 5, 6 and 6 change points at the height of 10m, 30m, 50m and 70m respectively. Among them, the change points at the height of 10m, 30m and 50m all change before and after node 325, and the change time point at the height of 70m is inconsistent with other heights. Hurst index results show that the inconsistency at 70m altitude is stronger than that at other altitudes. (2) The wind direction sequence at 10m, 30m, 50m and 70m altitude is fitted by stages, and the direction of wind direction is SE-E-SE-SW-W-NW, where, At the height of 70m, the deviation of the fitting trend line from other altitudes is larger in the wind speed strengthening stage and weakening stage. (3) The wind speed at the height of 10m and 70m has different response degrees to the typhoon body. The correlation between the wind speed and the distance between the wind measurement tower and the typhoon near the center is stronger at the height of 10m than at the height of 70m. The surface type and the wind direction of the mesoscale system also have certain effects on the wind speed and direction. In this paper, the change characteristics and influencing factors of wind speed and direction of wind tower are studied, which provides methods and theoretical support for the study of short-term wind speed when typhoon passes through, and provides reliable support for the selection of wind power forecast indicators and the selection and design of wind turbines under extreme gale weather systems.

Drought stress on soybean is a research-demanding matter for negative influence that agricultural drought brings about. This study was designated to evaluate the effect of drought stress on some gene expression in flowering and pod elongation stages in soybean. This experiment was carried out in split-plot format with RCBD design with four replicates. Drought stress as the main factor included three levels (irrigation after 50, 100, and 150 millimeters evaporation from the A-class evaporation pot) of which 50 millimeters evaporation is considered as control. The sub-factor included a factorial combination of 3 varieties (DPX, Sari and WE6) and two sampling stages (flowering and pod elongation). The gene expression analysis was carried out by using the QRT-PCR technique. According to our results, all genes have shown overexpression in drought stress despite this result was not the same for all genotypes and stress levels. Some genes have up-regulated in mediate stress (treatment 100) level (like as Gmdreb 2, Gmdreb 5, GmRD20A, GmaxACD2) and other genes up-regulated in serve stress (treatment 150) level. Between genotypes, DPX cultivar and WE6 line were better than of the sari cultivar for all genes up-regulated.

Epigenetic mechanisms, including histone post-translational modifications (PTMs), play a critical role in regulating pain perception and the pathophysiology of burn injury. However, the epigenetic regulation and molecular mechanisms underlying burn injury-induced pain remain insufficiently explored. Spinal dynorphinergic (Pdyn) neurons contribute to heat hyperalgesia induced by severe scalding-type burn injury through p-S10H3-dependent signaling. Beyond p-S10H3, burn injury may impact various other histone H3 PTMs. Double immunofluorescent staining and histone H3 protein analyses demonstrated significant hypermethylation at H3K4me1 and H3K4me3 sites and hyperphosphorylation at S10H3 within the spinal cord. By analyzing Pdyn neurons in the spinal dorsal horn, we found evidence of chromatin activation with a significant elevation in p-S10H3 immunoreactivity. We used RNA-seq analysis to compare the effects of burn injury and forma-lin-induced inflammatory pain on spinal cord transcriptomic profiles. We identified 98 DEGs for burn injury and 86 DEGs for formalin-induced inflammatory pain. A limited number of shared differentially expressed genes (DEGs) suggest distinct central pain processing mechanisms between burn injury and formalin models. KEGG pathway analysis supported this divergence, with burn injury activating Wnt signaling. This study enhances our understanding of burn injury mechanisms and uncovers converging and diverging pathways in pain models with different origins.

Drones have experienced rapid technological advancements, leading to the proliferation of small, low-cost, remotely controlled, and autonomous aerial vehicles with diverse applications, from package delivery to personal transportation. However, integrating these drones into the existing air traffic management (ATM) system poses significant challenges. The current ATM infrastructure, designed primarily for traditional manned aircraft, requires enhanced capacity, workforce, and cost-effectiveness to coordinate the large numbers of drones expected to operate at low altitudes in complex urban environments. To address this critical issue, this study aims to develop an intelligent, highly automated drone management system for integration into smart city transportation networks. The key objectives include: i) Developing a conceptual framework for an intelligent total transportation management system tailored for future smart cities, focusing on incorporating drone operations; ii) Designing an advanced air traffic management and flight control system capable of managing individual drones and drone swarms in complex urban environments; iii) Improving drone management methods by leveraging drone-following models and emerging technologies such as the Internet of Things (IoT) and the Internet of Drones (IoD); and iv) Investigating the landing processes and protocols for unmanned aerial vehicles (UAVs) to enable safe and efficient operations.

This review explores the crucial role of glycosphingolipids (GSLs) in the context of cardiovascular diseases (CVD), focusing on their biosynthesis, metabolic pathways, and implications for clinical outcomes. GSLs are pivotal in regulating a myriad of cellular functions that are essential for heart health and disease progression. Highlighting findings from both human cohorts and animal models, this review emphasizes the potential of GSLs as biomarkers and therapeutic targets. We advocate for more detailed mechanistic studies to deepen our understanding of GSL functions in cardiovascular health, which could lead to innovative strategies for diagnosis, treatment, and personalized medicine in cardiovascular care.

The spatial expansion of urban agglomerations is a direct manifestation of regional urbanization, reflecting the changes in scale and morphological characteristics of urban in temporal and spatial dimensions, which affects the efficiency of regional urbanization. This study employed a range of analytical techniques, including the urban spatial intensity index, center-of-gravity model, synergy index, inverse distance weighting interpolation method, and Geodetector, to examine the spatiotemporal evolution pattern and driving factors of the Beibu Gulf Urban Agglomeration in Guangxi, China between 2012 and 2022. The findings indicate that: (1) The Beibu Gulf Urban Agglomeration in Guangxi has been in a stable expansion trend over the past decade. However, the polarization effect of the central city space has gradually weakened, and the spatial expansion differences between cities have gradually narrowed, indicating an extensional development mode. (2) The economic and social gravity centers show a tendency of "eastward and southward" migration, which is opposite to the direction of the urban gravity center's displacement. The displacement directions of population and ecological gravity centers are roughly consistent with that of urban center. The distribution of economic and social resources are not aligned with the configuration of urban development, and the trajectory of the center of gravity of various development dimensions has shifted. (3) Economic and social expansion is significantly faster than population and ecology, but slower than urban expansion. The intensity of urban expansion is inconsistent with the distribution of synergies. The spatial differences in synergies between cities are gradually narrowing. The central city's radiation-driven role is insufficient. The development of nodal cities is less than expected. However, the benefits of urbanization in coastal cities are constantly being strengthened. (4) The disposable income of urban residents and per capita arable land area are the primary driving forces of urban expansion, while population density and urban green space area are significant contributors to urban expansion. Based on the above findings, it is recommended that the Beibu Gulf Urban Agglomeration of Guangxi should continue to enhance the scale efficiency of population agglomeration, optimize economic development and industrial resource allocation, promote urban-rural integration, strengthen inter-city connections, optimize spatial layout, and improve the overall production and living efficiency of regional cities and towns.

Salt stress is one of the most severe environmental stresses limiting the productivity of crops, including rice. However, there is a lack of information on how salt-stress sensitivity varies across different developmental stages in rice. In view of this, a comparative evaluation of contrasting rice varieties CSR36 (salt tolerant) and Jaya (salt sensitive) was conducted, wherein NaCl stress (50 mM) was independently given either at seedling (S-stage), tillering (T-stage), flowering (F-stage), seed-setting (SS-stage) or throughout the plant growth, from seedling till maturity. Except for S-stage, CSR36 exhibited improved NaCl stress tolerance than Jaya, at all other tested stages. Principal component analysis (PCA) revealed that the improved NaCl stress tolerance in CSR36 coincided with enhanced activities/levels of enzymatic/non-enzymatic antioxidants (root ascorbate peroxidase for T- and S+T stages and root catalase for F-, S+T and S+T+F-stages) and higher accumulation of osmolytes (shoot proline for F-stage and S+T+F-stage), indicating better antioxidant capacitance and osmotic adjustment, respectively. In contrast, higher shoot accumulation of Na+ and consequent increase in Na+/K+, Na+/Ca+2 and Na+/Mg+2 ratio in root and shoot, were identified as major variables associated with NaCl stress induced growth reduction in Jaya. In addition, CSR36 exhibited higher levels of Fe3+, Mn2+ and Co3+ and lower Cl- and SO42-, suggesting its potential to discriminate essential and non-essential nutrients, which might contribute to NaCl stress tolerance. Taken together, the findings provided the frame-work for stage-specific salinity responses in rice, which will facilitate crop-improvement programs for specific ecological niches including the coastal regions. Rice, salt stress, stage-specific salinity, antioxidant defense, ionic homeostasis, salt tolerance

The Korean water deer (WD), the dominant wildlife species in South Korea, is classified as vul-nerable on the IUCN Red List. Beside their several unique characteristics, they have a lower in-cidence of tick bites compared to other Cervidae species, particularly roe deer (RD). In natural environments, ticks exhibit questing behavior by waiting on grasses to climb onto host's hair coat. They use sensory organs to detect signals such as body temperature and chemicals from the host's skin, then move to preferred feeding location. Therefore, we conducted a comparative analysis of the skin tissue and hair features of both species to compare the factors leading to lower incidence of tick bites in WD. Notably, WD had significantly larger blood vessels, sebaceous glands, and sweat glands which maintain the barrier functions of the skin (p≤0.004), irregular scale surfaces in hair cuticles, and stiff and 2.83-times thicker primary hair diameter (p<0.001). Each parameters made the ticks difficult to move onto the epidermis of WD. To our knowledge, this is the first report which is focused on the comparative analysis for skin and hair feature in WD and RD. We suggest that these differences may attribute to evade tick bites in WD.

Cotton is one of the most important economic crops in the world, whereas insect attacks is a prime cause of its losses on yield and quality. Despite it is important, little is known about the mechanism of cotton response to insect. In this study, we simulated insect feeding by applying insect oral secretions (OS) to wounds, and combined transcriptome and metabolome analysis to comprehensively investigate how OS from two major pest species (Helicoverpa armigera and Spodoptera litura) affect cotton defense responses. Obvious differences were observed that 12,668 and 13,379 genes differently expressed respectively in cotton after being treated with different OS when compared with wounding along. Upon the addition of OS, JA-signaling pathway were rapidly and strongly induced, however SA-biosynthesis related gens were significantly down-regulated. By constructing the co-expression gene network, we identified a hub gene which encoding a leucine-rich repeat receptor kinase may play important role in recognition and signal transduction at early stage. We also found that OS from different insect species altered abundance of flavonoid related compound with different patterns. Interestingly, Gossypol which is a well-known anti-insect compound was kept a relative low content after OS application relative to wounding which implied the existence of the suppression effects of OS to cotton defense response. This study illustrated the transcriptional and metabolic changes of cotton in responding to OS from two chewing insect species, identified potential key gene during the interaction process and finds the evidence for OS’s inhibition effects on cotton defense response.

Psoriasis is considered an immune-mediated disease involving the innate and adaptative immune system triggered by environmental risk factors in genetically susceptible individuals. However, its physiopathology is not fully understood yet. Recent technological advances, specially genome and epigenome-wide studies, have allowed a more sensitive study of the genetic and epigenetic mechanisms, allowing an enhanced understanding of its physiopathology and facilitating the development of new drugs. In this review, we aim to summarize the current evidence on genetic and epigenetic mechanisms of psoriasis.

Context: The global escalation of conflict, violence, and human rights violations sets a pressing backdrop for examining the resilience of forcibly displaced youth (FDY) in Canada. This study aims to unpack the multifaceted challenges and resilience mechanisms of FDY, focusing on their health, well-being, and integration into host communities. It seeks to identify current models of resilience, understand the factors within each model, and highlight gaps and limitations. Methodology: Using a university librarian-supported structured search strategy, this exploratory rapid review searched literature from Ovid Medline and Open Source databases, published in English between January 2019 and January 2024, that fit specific inclusion criteria. The eligible articles (N=12 out of 4,096) were charted and analyzed by two student researchers with the PI. Charted data were analyzed thematically. Results: The selected studies captured diverse geographical perspectives, resilience models (such as Ungar's ecological perspective and Masten's resilience developmental models), as well as protective and promotive frameworks. Key findings indicate the complexity of resilience influenced by individual, familial, societal, and cultural factors. Each model offers insights into the dynamic interplay of these influences on FDY's resilience. However, these models often fall short of addressing the nuances of cultural specificity, the impact of trauma, and the intersectionality of FDY's identities. Conclusion: Recognizing the diverse and evolving nature of FDY's coping mechanisms, this study advocates for a culturally appropriate approach to resilience that integrates an intersectionality framework of individual attributes and culturally sensitive models.

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole. Letrozole inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. Letrozole resistance is increasingly being observed, which poses a unique problem for patients. We reanalyzed transcriptomic data comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two genes that significantly differed between these patients; with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 as the top transcriptional biomarkers for ER+ treatment resistance. Many of the other significant gene products play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified do not have a characterized role in ER+ breast cancer. Our analysis identified a set of genes that warrant further research to elucidate the molecular mechanism of Letrozole resistance in this patient population, as well as novel high-performing biomarkers. We anticipate that these findings could contribute to improved therapeutic outcomes in human patients.

Despite polycarbonate (PC) being a widely used engineering plastic, its notch and crack sensitivity pose challenges in critical applications. To address this, PC was blended with elastomeric polymers to explore the improvement in toughness. This study systematically investigates the toughening mechanisms of PC blended with acrylonitrile-butadiene-styrene (ABS), copolyether ester elas-tomer (COPE), and ABS and styrene-ethylene-butylene-styrene (SEBS) copolymer grafted with maleic anhydride (MA). The morphology and mechanical behavior were evaluated under qua-si-static and high-speed tensile tests and Charpy impact tests using optical, electronic, and atomic force microscopy and Raman spectroscopy. The morphological analysis reveals cavitation and crazing phenomena for COPE and SEBS-g-MA systems, and mostly debonding for ABS, indicating an improvement in toughening. While the addition of ABS improves the PC plastic deformation, modifying ABS with maleic anhydride enhances the elastic modulus. Blending PC with SEBS-g-MA increases the strain at break, and the addition of COPE significantly improves the deformation behavior of PC (by around 115%). This comparative study provides valuable insights into the performance of different PC-elastomer blends under similar conditions, supporting the selection of appropriate materials for given applications.

Cartilage degeneration is a characteristic of osteoarthritis (OA) which is often observed in aging populations. This degeneration is due to the breakdown of articular cartilage (AC) mechanical and tribological properties, primarily attributed to lubrication failure. Understanding the reasons behind these failures and identifying potential solutions could have significant economic and societal implications, ultimately enhancing the quality of life. This review provides an overview of developments in the field of AC, focusing on its mechanical and tribological properties. The emphasis is on the role of lubrication in degraded AC, offering insights into its structure and function relationship. Further it explores the fundamental connection between AC mechano-tribological properties and the advancement of its degradation and puts forth recommendations for strategies to boost its lubrication efficiency.

In recent years, the emergence of cancer drug resistance is one of the crucial tumor hallmarks which is supported by the level of genetic heterogeneity and complexities at cellular levels. Oxidative stress, immune evasion, metabolic reprogramming, overexpression of ABC transporters and stemness are among the several key contributing molecular and cellular response mechanisms. Topo-active drugs, e.g., doxorubicin and topotecan, are clinically active and are utilized extensively against a wide variety of human tumors and often results in the development of resistance and failure to therapy. Thus, there is an urgent need for an incremental and comprehensive understanding of mechanisms of cancer drug resistance specifically in the context of topo-active drugs. This review delves into the intricate mechanistic aspects of these intracellular and extracellular topo-active drug resistance mechanisms and explores use of potential combinatorial approaches by utilizing various topo-active drugs and inhibitors of pathways involved in drug resistance. We believe that this review will help guide basic scientists, pre-clinicians, clinicians, and policymakers toward holistic and interdisciplinary strategies that transcend resistance, renewing optimism in the ongoing battle against cancer.