The emergence of the COVID-19 outbreak has caused a pandemic situation in over 210 countries. Controlling the spread of this disease has proven difficult despite several resources employed. Millions of hospitalization and deaths have been observed, and thousands of cases daily with many measures in place. Due to the complex nature of COVID-19, we proposed a system of time-fractional equations to understand the transmission of the disease better. Nonlocality involved in the model has made fractional differential equations appropriate for modeling the behavior. However, solving these types of models is computationally demanding. Our proposed generalized compartmental COVID-19 model incorporates effective contact rate, transition rate (from exposed quarantine and recovered to susceptible and infected quarantined individuals), quarantine rate, disease-induced death rate, natural death rate, natural recovery rate, recovery rate of quarantine infected for a holistic study of the coronavirus disease. A detailed analysis of the proposed model is carried out, including the existence and uniqueness of solutions, local and global stability analysis of the disease-free equilibrium analysis, and sensitivity analysis. Furthermore, numerical solutions of the proposed model are obtained with the generalized Adam-Bashforth-Moulton method developed for the fractional order model. Our analysis and solutions profile show that each of these incorporated parameters is very important in controlling the spread of COVID-19, especially quarantining exposed and infected individuals and the effective contact rate. Based on the results with different fractional order, we observe that there seems to be a third or even fourth wave of the spike in cases of COVID-19, which is what is happening right now in many countries.

Cold chain logistics of Agricultural Products demand forecasting can provide the scientific basis for the country to formulate logistics strategy, which further promotes the development of social economy and the improvement of living standards in China. In this paper, a new mathematical combined model is proposed to Agricultural Products Demand. Shandong, one of a China’s province, serves as the main producer and distributor of agricultural products. Based on the index system created from multiple related factors influencing cold chain logistics demand of agricultural products in Shandong, this paper employs principal component analysis to reduce the dimension of various indexes and predicts principal components with time series. Thereafter, multiple linear regression model and neural network model were constructed to forecast the cold chain logistics demand of agricultural products in Shandong, and their combined forecast models were compared. What's more, the paper provides insight for reference and decision-making concerning the development of cold chain logistics industry of agricultural products in Shandong province.

Thermal interface material (TIM) that can exist as liquid at the service temperature enables efficient heat transfer across two adjacent surfaces in electronic applications. In this work, the thermal conductivities of different phase regions in the Ga-In system at various compositions and temperatures are measured for the first time. A modified comparative cut bar technique is used for the measurement of the thermal conductivities of In_xGa_1-x (x=0, 0.1, 0.214, 0.3, and 0.9) alloys at 40, 60, 80, and 100^oC that are the temperatures commonly encountered in consumer electronics. The thermal conductivity values for the liquid and semi-liquid (liquid+β) Ga-In alloys are higher than the TIM currently used in consumer electronics. These measured quantities, along with the available experimental data from the literature, served as input for the thermal conductivity parameter optimization using the CALPHAD (CALculation of PHase Diagram) method for the pure elements, solution phase, and two-phase region. A set of self-consistent parameters for the description of the thermal conductivity of the Ga-In system is obtained. There is good agreement between the measured and calculated thermal conductivity values for all the phases. Hence, it can be envisaged that liquid/semi-liquid Ga-In alloys can be considered as a potential TIM in consumer electronics due to its high thermal conductivity.

Machine learning plays a key role in present day crime detection, analysis and prediction. The goal of this work is to propose methods for predicting crimes classified into different categories of severity. We implemented visualization and analysis of crime data statistics in recent years in the city of Boston. We then carried out a comparative study between two supervised learning algorithms, which are decision tree and random forest based on the accuracy and processing time of the models to make predictions using geographical and temporal information provided by splitting the data into training and test sets. The result shows that random forest as expected gives a better result by 1.54% more accuracy in comparison to decision tree, although this comes at a cost of at least 4.37 times the time consumed in processing. The study opens doors to application of similar supervised methods in crime data analytics and other fields of data science

Multiphase systems are important in minerals processing, and usually include solid-solid and solid-fluid systems. Examples of operations in multiphase systems include flotation, dewatering, and magnetic separation, among several other unit operations. In this paper, the current trends in the process system engineering tasks of modeling, design, and optimization, in multiphase systems, are analyzed. Different scales of size and time are included, and therefore the analysis includes modeling at the molecular level and unit operation level, and the application of optimization for the design of a plant. New strategies for the modeling and optimization of multiphase systems are also included, with a strong focus on the application of artificial intelligence (AI) and the combination of experimentation and modeling with response surface methodology (RSM). The paper finishes with tools to study the uncertainty, both epistemic and stochastic, which is present in all mineral processing operations. It is shown that all these areas are very active and can help to understand, operate, design, and optimize mineral processing that involves multiphase systems.

Transient analysis of gas flow in pipeline was studied. Finite Element Method based on ANSYS FLOTRAN was used to account for changes in pressure, temperature and flow rate. Compressibility factor function of temperature and pressure was considered. For non-isothermal transient results, the pressure and the flowrate gave wave propagation as a result of slow transients created by demand condition at the outlet end of custody transfer. Results obtained were in agreement with the demand restrictions at the outlet end of custody transfer indicating that the predictions are accurate and reliable. The results demonstrated that the Finite Element Method gave accurate prediction of pressure, temperature and flowrate in transient gas studies. For steady state non-isothermal model, results showed that the magnitude of the average pressure drop was higher when pressure was predicted with constant compressibility factor, but the same average pressure drop was reduced when the pressure was predicted with variable compressibility factor, z. Since compressibility factor is a function of temperature and pressure, the above findings signifies that in the case when gas temperature does not stabilize, the prediction of pressure with isothermal model and constant compressibility factor will lead to significant errors.

The detection of early biomarkers and molecular mechanisms in Parkinson’s disease (PD) remains a challenge. Recent research has pointed to potential roles for peptidylarginine deiminases (PADs), a family of calcium activated enzymes, and associated post-translational protein citrul-lination/deimination in early stages of the disease, with a focus on hippocampal and cortex re-gions of the brain. Further analysis of brain region specific changes in PAD isozymes and identi-fication of brain-region specific citrullinomes, therefore remain to be studied. This study assessed brain-region specific PAD isozyme expression (PADs 1-4; PAD6) and associated citrullinated protein targets in the 6-hydroxydopamine (6-OHDA) induced rat model of pre-motor PD. Cortex, hippocampus, striatum, midbrain, cerebellum and olfactory bulb were compared between con-trols/shams and the PD model. In cortex, a significant increase of PAD2 and PAD3 was observed in the PD model. In hippocampus, PAD3, PAD4 and PAD6 showed strongest levels, but with no significant changes observed between PD and controls. In striatum, a significant reduction in all PAD isozymes was observed in the PD model. In the olfactory bulb, PAD3 was significantly el-evated in PD. In midbrain, PAD2, PAD4 and PAD6 showed strongest signal but with no signifi-cant changes between PD and controls. In cerebellum, a significant increase was seen in PAD3, PAD4 and PAD6 in the PD model. Citrullinated protein hits were most abundant in cortex and hippocampus, while for the PD model an increase in citrullinated hits was particularly observed in cortex and cerebellum, compared to controls. For all brain regions there was a considerable difference in citrullinated protein IDs between the PD model and the controls. Citrullinome as-sociated KEGG pathways differed in the six brain regions; some were overlapping for controls and PD, some were identified for the PD model only, and some were identified in control brains only. KEGG pathways identified in PD brains onlywere: “Axon guidance”; “Spinocerebellar ataxia”; “Hippo signalling pathway”; “NOD-like receptor signalling pathway”; “Phosphatidyl-inositol signalling system”; “Rap1 signalling pathway”; “Platelet activation”; “Yersinia infection”; “Fc gamma R-mediated phagocytosis”; “Human cytomegalovirus infection”; “Inositol phosphate metabolism”; “Thyroid hormone signalling pathway”; “Progesterone-mediated oocyte matura-tion”; “Oocyte meiosis”; and “Choline metabolism in cancer”. Our findings highlight differences in PAD isozymes, citrullinated proteins and associated KEGG pathways between brain regions, in pre-motor PD.

Marijuana is the most used illicit drug among youths in the United States. The objectives of the study were to identify the association between marijuana use and other risk behaviors including suicidality among high school students. The 2021 Mississippi Youth Risk Behavior Survey data sets were combined for this study. Crude odds ratio (OR) and adjusted odds ratio (AOR) with a 95% confidence interval were generated using the survey packages in R to account for weights and the complex sampling design of YRBS data. Tobacco products and alcohol use were significantly associated with marijuana use. Students who responded “Yes” to questions “currently used an electronic vapor product?”, “currently smoked cigarettes or cigars?” or “currently drank alcohol?” were more likely to use marijuana compared to students who responded “No”, after adjusting for other risk factors. Marijuana use is also significantly associated with students who had sex, compared to those who never had sex. The adjusted odds ratio is nearly doubled in those who had sex with the same sex or both sexes, compared to those who had heterosexual sex only. After adjusting for other health risk factors, the association between current marijuana use and attempted suicide was not statistically significant. The impact of students’ not sleeping in their parent's or guardian's home on current marijuana use was not significant after adjusting for other risk factors. Marijuana use is evenly burdened between males and females and between all race categories among Mississippi high school students. The identified associations seem to indicate that electronic vapor, tobacco products, and alcohol use could be the forerunners for drug use and should be treated accordingly in drug use prevention programs.

The goal of this work was to develop the acrylonitrile-butadiene (NBR) elastomer composites filled with hydroxyapatite (HAP), which were characterized with improved cure characteristics and burning resistance. Silane, i.e., (3-aminopropyl)-triethoxysilane, ionic liquid, i.e., 1-decyl-3-methylimidazolium bromide and surfactant, i.e., cetyltrimethylammonium bromide, were used to improve the filler’s dispersibility in the elastomer matrix and to reduce the time and temperature of vulcanization. The effect of HAP and dispersants on the cure characteristics, crosslink density and physico-chemical properties of NBR composites was explored. The additives used, especially the ionic liquid and surfactant, effectively improved the dispersion of HAP in NBR matrix. The amount of HAP and the dispersant used strongly affected the cure characteristics and crosslink density of NBR. The optimal vulcanization time significantly increased with HAP content and was pronouncedly reduced when ionic liquid and surfactant were applied. In addition, ionic liquid and surfactant significantly lowered the onset vulcanization temperature, improved the crosslink density and hardness of the vulcanizates, while impairing their elasticity. HAP and dispersants did not significantly affect the damping properties and chemical resistance of NBR vulcanizates. Above all, application of HAP considerably enhanced the resistance of vulcanizates to thermo-oxidative aging and reduced their flammability compared to the unfilled NBR.

This article aims to assess Pakistan's National Spatial Data Infrastructure implementation efforts through well-established approaches including the SDI readiness model, organizational aspects, and state of play. The findings underscored challenges related to human resources, SDI education/culture, long-term vision, GI awareness, sustainable funding, metadata availability, online geospatial services, and geospatial standards hindering the NSDI development in Pakistan. However, certain factors, such as the legal framework for NSDI establishment, web connectivity, geospatial software availability, core spatial dataset availability, and institutional leadership, exhibit favorable standings. Thus, to enhance the development of NSDI for Pakistan, recommendations include bolstering financial and human resources, improving online geospatial presence, and fostering a long-term vision for NSDI.

This study introduces an innovative seeding method for cells on large scaffolds (1-100 sqcm) with an accuracy of 0.1mm, comparing the conventional drop-wise seeding technique with an automated seeding approach using an open sourced robotic liquid handling system (OpenLH). This automated system employs an algorithm in which the user inputs the desired droplet volume and seeding pattern dimensions such in number of rows, columns and distance between droplets, thus optimizing the distribution of cells on the scaffold. By adjusting these parameters, the method achieves greater accuracy and consistency over manual seeding and requires less operation space volume than dynamic seeding. Additionally, the system’s tip replacement feature can support the precise seeding of multiple cell types on a single scaffold and the dispensing of growth factors to foster patterns of cell differentiation and proliferation on the large 3D scaffold. This seeding method not only enhances the precision and efficiency of cell distribution on scaffolds but also shows significant potential for scalability in the cultured meat industry, where large scaffolds are essential. The adoption of such automated systems could promote efficient scaffold-based tissue engineering by promoting uniform cell distribution and enabling the creation of complex tissue constructs, thereby advancing both biomedical research and cultured meat production.

Sea level rise due to global warming is a continuing and, disappointingly, accelerating process, which has already affected and will further impact coastal lowlands and the social and economic activities in these areas. Delos Island, situated in the middle of the Cyclades in the Aegean Sea, was considered the most sacred of all islands in ancient Greek culture and a trading hub for the entire eastern Mediterranean. Uninhabited since the 7th century AD, and consistently the focus of research and touristic attention, the island is designated as an archaeological site and inscribed on the Unesco World Heritage List. Previous studies on the relative sea level (rsl) changes suggest a steadily rsl rise during the last 6,300 years, starting from a sea level at -4.80±0.20m in the Late Neolithic. The seafront of the ancient city of Delos is subject to the effects of the rsl rise, which have caused significant coastline retreat and exposure to the northerly winds and waves, whereas parts of the coastal lowland where the remains of the ancient city lie are inundated, forming extended wetlands. The future impacts of rsl rise on the seafront of ancient Delos are illustrated on very high-resolution digital surface models, evaluating both the flooding risk under different climatic projections, as provided by the IPCC AR6 report, and the ongoing land subsidence, as recorded by GNSS data. An rsl rise ranging from 87cm (SSP1-2.6 scenario) to 148cm (SSP5-8.5 scenario) is anticipated by 2150, requiring both resilience strategies and adaptation solutions as well as mitigation policies to cope with the effects of climate change.

The discrete element method (DEM) coupled with computational dynamics (CFD) has been considered one of the most sensitive ways of studying fluidized beds. This paper presents gas-solid fluidized bed simulations by use of CFD-DEM. The two-phase interaction is calculated in a way of decoupling. Within the effective neighborhood of the particles, the kernel approximation method is used to calculate the local porosity, thereby calculating the drag force on the particles. At the grid scale, the momentum exchange coefficient is calculated using a two fluid model based method, thereby calculating the source term of the phase interaction in the fluid control equation. The simulated form, size and motion process of the big bubble are all consistent with experimental observations. The simulated solid volume fraction and relative pressure averaged in a horizontal plane at 45 mm above the bottom are in reasonable agreement with the experimental data. The fluctuation of the simulated bed height over time is similar to the experimental measurement results. The reproduction of these qualitative and quantitative results indicates that the proposed method effectively improves simulation performance and accuracy.

Chronic granulomatous disease (CGD) is a group of rare primary inborn errors of immunity characterised by a defect in the phagocyte respiratory burst, which leads to severe and life-threatening infective and inflammatory complications. Despite recent advances in our understanding of the genetic and molecular pathophysiology of X-linked and autosomal recessive CGD, and growth in the availability of functional and genetic testing, there remain significant barriers to early and accurate diagnosis. In the current review, we provide an up-to-date summary of CGD pathophysiology, which underpins methods of diagnostic testing for CGD and closely related disorders. We present an overview of the benefits of early diagnosis and when to suspect and test for CGD. We discuss current and historical methods for functional testing of NADPH oxidase activity, as well as assays for measuring protein expression of NADPH oxidase subunits. Lastly, we focus on genetic and genomic methods employed to diagnose CGD, including gene-targeted panels, comprehensive genomic testing and ancillary methods. Throughout, we highlight general limitations of testing, and caveats specific to interpretation of results in the context of CGD and related disorders, and provide an outlook for newborn screening and the future.

The increase in the frequency of droughts in Africa has increased the interest in crops with drought escape mechanisms like grain Amaranth (Amaranthus hypochondriacus). However, the white-seeded grain Amaranth is easily cross-pollinated by its black seeded wild relatives such as smooth pigweed (Amaranthus hybridus). A study to investigate a minimum isolation distance enough to prevent seed contamination study was carried out at three sites namely Gweru and Bindura (2020/2021 rainy season) and Shamva (2021/2022 rainy season). Smooth pigweed was planted at distances of 3 to 150 m from pure grain Amaranth. Close monitoring of phenology and measurement of meteorological conditions such as temperature, wind speed and direction were done during the anthesis period. Cross-pollination in grain Amaranth was influenced by distance from the pollen source. A maximum of 12.9 % contamination rate was measured within the 10 m radius from the pollen donor plot and a minimum outcrossing rate of 0.45 % was recorded at the widest distance of 150 m. It can be concluded that complete removal of wild relatives of grain Amaranth is important within the field at as far as 150 m from the crop.

Recent advancements in semiconductor photonic and electronic devices such as Uni-travelling-carrier photodiodes (UTC-PDs), have played a significant role in the development of Terahertz communication technology. However, a major challenge that still persists is the limited output power from a single UTC-PD required for practical transmission distances. To enhance the output power, we propose and demonstrate a novel Terahertz wave power combining technique using a photomixer device that comprises of two arrayed UTC-PDs monolithically integrated with a microstrip line-based 2 × 1 Wilkinson power combiner and a rectangular patch antenna on a Silicon Carbide (SiC) substrate at 300 GHz. At photocurrents of 8 mA and 10 mA from the two UTC-PDs, the device experimentally exhibited a 7.3 dB increase in power relative to the power obtained with 8 mA UTC-PD and a 4.4 dB increase in power relative to the power obtained with 10 mA UTC-PD, when both UTC-PDs were irradiated. This implies that power can be enhanced by a factor of N2 if the photocurrent is multiplied by a factor of N. This technology presents a holistic and cutting edge platform for further power multiplication by further increasing the number of arrayed UTC-PDs.

Exosomes, natural nanovesicles that contain a cargo of biologically active molecules such as lipids, proteins, and nucleic acids, are released from cells to the extracellular environment. They then act as autocrine, paracrine, or endocrine mediators of communication between cells by delivering their cargo into recipient cells and causing downstream effects. Exosomes are greatly enriched in miRNAs, which are small non-coding RNAs that act as cytoplasmic posttranscriptional repression agents, modulating the translation of mRNAs into proteins, as well as nuclear transcriptional gene activators. Neuronal exosomal miRNAs have important physiologic functions in the Central Nervous System (CNS), including cell-to-cell communication, synaptic plasticity, and neurogenesis, as well as modulating stress and inflammatory responses. Stress-induced changes of exosomal functions include effects on neurogenesis and neuroinflammation, which can lead to the appearance of various neuropsychiatric disorders, such as schizophrenia, major depression, bipolar disorder, and Alzheimer's and Huntington’s's diseases. The current knowledge regarding the roles of exosomes in the pathophysiology of common mental disorders is discussed in this review.

In patients with primary central nervous system lymphoma (PCNSL), the choice of surgical strategy for histopathologic assessment is still controversial, particularly in terms of preoperative corticosteroid (CS) therapy. To provide further evidence for clinical decision-making, we retrospectively analyzed data from 148 consecutive patients who underwent surgery at our institution. Although patients treated with corticosteroids preoperatively were significantly more likely to require a second or third biopsy (p=0.049), it was only necessary in less than 10% of the cases with preoperative corticosteroid treatment. The choice of surgical procedure did not affect diagnostic accuracy (p>0.05). Preoperative CSF sampling did not provide additional information but was associated with delayed surgery (p=0.02). Surprisingly, diagnostic accuracy was significantly lower when patients were treated with anticoagulation or dual antiplatelet therapy (p=0.015). In conclusion, preoperative CS therapy can challenge the histological diagnosis of PCNSL. At the same time, our data suggest that preoperative CS treatment only presents a relative contraindication for an early surgical intervention. The standard surgical approach is stereotactic biopsy, but other approaches can be individually considered. If a definitive diagnosis cannot be made after the first surgical intervention, the timing of a repeat biopsy after discontinuation of CS remains a case-by-case decision.

Increasing evidence of sexual dimorphism in pathophysiology of metabolic complications caused by sex steroids is under investigation. The gut microbiota represents a complex microbial ecosystem involved in energy metabolism, immune response, nutrition acquisition, and health of host organisms. Gender-specific differences in composition are present between females and males. The purpose of this study was to use cross-sex fecal microbiota transplantation (FMT) for the detection of sex-dependent metabolic, hormonal, and gut microbiota changes in female and male recipients. Healthy non-obese female and male Wistar rats were divided into donor, same-sex, and cross-sex recipient groups. After a 30-day period of FMT administration, biochemical markers (glucose and lipid metabolism) and sex hormones were measured and gut microbiota was analyzed. Cross-sex male recipients displayed significantly lower testosterone concentration compared to males that received same-sex FMT. Sex-dependent changes caused by cross-sex FMT were detected, while several bacterial taxa correlated with plasma testosterone levels. This study represents the first to study the effect of cross-sex changes in the gut microbiome concerning metabolic and hormonal changes/status in adult non-obese Wistar rats. Herein, we present the cross-sex FMT as a potential tool to modify sex-specific pathologies.

This article explores the cross-cultural significance of three iconic fairy tales: Cinderella, Snow White, and Sleeping Beauty. Using a comparative analysis approach, the study investigates recurring themes, motifs, and symbolism found in these tales across different cultures and time periods. The research draws on primary and secondary sources such as literary works and scholarly articles to uncover the underlying messages that resonate with audiences worldwide. The historical and cultural contexts of the tales are also examined to provide a deeper understanding of their significance in shaping cultural identity and values. The findings of the research demonstrate the enduring legacy of these tales and their continued relevance in contemporary society. The study highlights how the tales have evolved and adapted over time to reflect changing cultural values and beliefs. The interpretation of the findings offers insights into the role of storytelling in shaping cultural identity and values, and the ways in which these stories continue to inspire and captivate audiences worldwide. Overall, this research provides a comprehensive and nuanced understanding of the significance of these three fairy tales across cultures and time. By illuminating the similarities and differences in these tales, the study offers a fresh perspective on the power of storytelling and its ability to transcend cultural boundaries. The research contributes to the fields of folklore, cultural studies, and cross-cultural communication, inspiring further exploration into the captivating world of fairy tales.

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.

Recently, methods to detect DoS and spoofing attacks that occur on in-vehicle networks using CAN Protocol are being studied through deep learning models such as CNN, RNN, and LSTM. These studies have produced significant results in the field of In-Vehicle Network attack detection using deep learning models. In addition, significant results are being achieved through research on applying time series-based deep learning models such as LSTM to detect DoS attacks and replay attacks occurring in in-drone networks by expanding them to drones using the UAVCAN protocol. In this paper, we conducted an experiment to detect in-drone network attacks through non-time series analysis using machine learning models and deep learning models, and through appropriate learning for each attack type, it can also be analyzed through non-time series analysis. The results showed that it was possible to detect attacks.

Currently, there is a tenacious need to find new ways to purify water by eliminating bacterial biofilms, textile dyes, and toxic water pollutants. These contaminants pose significant risks to both human health and the environment. To address this issue, in this study, we have developed an eco-friendly approach that involves synthesizing Cobalt-doped Cerium Iron Oxide (CCIO) nanocomposite (NC) using an aqueous extract of Gossypium arboreum L. stalks. The resulting nanoparticles can be used to effectively purify water and tackle the challenges associated with these harmful pollutants. Nanoparticles excel in water pollutant removal by providing high surface area for efficient adsorption, versatile design for simultaneous removal of multiple contaminants, catalytic properties for organic pollutant degradation, and magnetic features for easy separation, offering cost-effective and sustainable water treatment solutions. CCIO nanocomposite has been synthesized by green co-precipitation method due to biomolecules and co-enzymes present in the aqueous extract of Gossypium arboreum L. stalk; a single-step procedure completed in 5 h reaction time. Further, the synthesis of nanocomposites was confirmed by various characterization techniques such as Fourier-transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), Field emission scanning electron microscopy (FE-SEM), Transmission electron microscopy (TEM), Thermogravimetric analysis (TGA), Dynamic light scattering (DLS), and Energy Dispersive X-Ray (EDX). CCIO NCs were discovered to have a spherical shape and an average size of 40 nm. Based on DLS zeta potential analysis, CCIO NCs were found to be anionic. Also, CCIO NCs showed significant antimicrobial and antioxidant activity. Overall, considering the physical and chemical properties, the application of CCIO NCs in the adsorption of various dyes (~91 %) and water pollutants (chromium = ~ 60 %) has been considered since they exhibit great adsorption capacity owing to their microporous structure which can be a step forward in water purification.

With the increasingly online exposure of urban public spaces, the new concept of "Internet-celebrity cities" has emerged in China. The online internet-famous sites are the main characteristics of "Internet-celebrity cities". To fully understand online users' preferences in such kind of public spaces, this article took 27 typical riverfront internet-famous sites (RIFS) in Changsha city (China), as an example. Through the online images and review comments on social media platform "Xiaohongshu", the study analyzed users’ perception of RIFS specially on visual and emotional preferences. It revealed the following findings:(1) The popularity of RIFS had a significant head effect and there were far more positive emotions than neutral and negative emotions in review comments. (2) According to 5 different categories of RIFS: modern buildings with river views, restaurants with strong visual impact became the main attractions on commercial RIFS. The art exhibition RIFS attracted visitors to experience traditional culture and highlight their aesthetic pursuits. In the historical and cultural RIFS, people preferred to see the historical buildings with surrounding natural environment, as well as river and mountains views. Ecological Recreational RIFS showed the similar results with the uncultivated RIFS, for the main focus was on the ecological environment, a broader vision and the specific atmosphere. Moreover, the uncultivated RIFS showed more diversified attraction points. This study can provide a new perspective on the waterfront vitality and can offer a targeted and attractive manner for waterfront regeneration that are different from traditional methods.

Background: Chronic lateral epicondylitis challenges the therapeutical approach; underlying mechanisms are incompletely understood; neuropathic pain and central and peripheral sensitization may explain the fact that botulinum toxin was found to play a role in pain and function management. Methods: We searched the literature for MeSH terms: lateral epicondylitis or synonyms and botulinum toxin. Results: We found 14 papers containing trials on botulinum toxin injection into the tendon or into the extensor muscles (particularly extensor carpi radialis brevis and extensor communis digitorum). We followed the administration pathways, doses, timing and side effects. Conclusion: With chronic course, the focus of the therapy shifts from the afflicted tendon to the inserting muscles, as muscle contracture may create a vicious loop to perpetuate and aggravate the disease. Doses, timing and side effects are discussed.

In this comprehensive review, we delve into the realm of intention recognition within the context of digital forensics and cybercrime. The rise of cybercrime has become a major concern for individuals, organizations, and governments worldwide. Digital forensics is a field that deals with the investigation and analysis of digital evidence in order to identify, preserve, and analyze information that can be used as evidence in a court of law. Whereas, Intention recognition is a subfield of artificial intelligence that deals with the identification of agents’ intentions based on their actions and change of states. In the context of cybercrime, intention recognition can be used to identify the intentions of cybercriminals and even to predict their future actions. Employing a meticulous six-step systematic review approach, we curated research articles from reputable journals and categorized them into three distinct modeling approaches: logic-based, classical machine learning-based, and deep learning-based. Notably, intention recognition has transcended its historical confinement to network security, now addressing critical challenges across various subdomains, including social engineering attacks, AI black box vulnerabilities, and physical security. While deep learning emerges as the dominant paradigm, its inherent lack of transparency poses unique challenges in the digital forensics landscape. We advocate for hybrid solutions that blend deep learning’s power with interpretability. Furthermore, we propose the creation of a comprehensive taxonomy to precisely define intention recognition, paving the way for future advancements in this pivotal field.

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates Quantum Spiking Neural Networks (QSNN) and Quantum Long Short-Term Memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conduct a comparative analysis of our model against existing quantum models such as Quantum Neural Networks and their classical counterparts, elucidating its unique contributions. Through empirical results, we aim to underscore the effectiveness of our approach in optimizing energy consumption in practical scenarios.

Osteosarcoma (OS) are the most prevalent malignant bone tumors in adolescents and young adults.. OS cells grow in a permissive local microenvironment which modulates their behavior and facilitates all steps in tumor development (e.g., proliferation/quiescence, invasion/migration, drug resistance) and contributes to their intrinsic heterogeneity. The lung parenchyma is the most common metastatic site in OS, and metastatic foci are frequently associated with a poor clinical outcome. Although multiple factors may be responsible for the disease, including genetic mutations (e.g., Rb, p53), the molecular mechanism of development of OS remains unclear and the conventional treatment for OS is still based on a sequential approach that combines chemotherapy and surgery. Also, despite the increase in clinical trials, the survival rates for OS have not improved. Non-specific targeting therapies thus show poor therapeutic effects with side effects at high doses. For these reasons, many efforts have been done to characterize the complex genome of osteosarcoma thanks to the whole exome analysis with the aim to identify predictive biomarkers to give to these patients a better therapeutic option. This review aims to summarize and discuss the main recent advances in OS molecular research for precision medicine.

Motivated by diffraction experiments on the $\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$ reconstructed Si(111) due to deposition of rare earth elements (Dy, Tb) and silicide formation we analyse the splitting and non-splitting of superstructure spots. For this purpose, we model diffraction patterns for one dimensional structures generated by the binary surface technique and use supercell models to keep the analysis simple. Diffraction pattern are calculated in the framework of the kinematical diffraction theory and they are analyzed as a function of the domains and domain boundaries. Basic properties of the diffraction pattern are analyzed for model systems of a two-fold and a three-fold periodicity. The rules derived from these calculations are applied to the "real-world" system of Si(111)-($\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$)-RESi$2_{}$ (RE = Dy or Tb). Depending on the combination of domains and domain boundaries of different types a plethora of different features are observed in the diffraction patterns. These are analyzed to determine the sizes of both domain boundaries and domains from experimentally observed splitting of specific superstructure spots.

Consumption of refined foods and beverages high in sugar make the teeth susceptible to the formation of biofilm, and lead to dental caries and diseases of the oral cavity such as periodontitis and periodontal disease. The aim of the present study was to determine the ability of selected probiotics to inhibit growth and biofilm formation by the cariogenic bacterium Streptococcus mutans in vitro. We screened strains of latic acid bacteria (LAB) (n=120) from the Bioresources Collection and Research Center (BCRC), saliva of healthy adults and infant stool. The antimicrobial activity of LAB in vitro was evaluated by agar spot culture and co-culture of the S. mutans strains. We determined the effect of heating and dilution factors (2- and 4-fold) on the antagonistic activity of LAB. Antagonistic substances in the spent culture suspensions (SCS) of LAB were precipitated by extraction with ammonium sulphate and chloroform to characterise the protein and lipophilic fractions. Results of co-culturing show that the SCS of the three LAB strains (Lactobacillus pentosus 13-1, 13-4 and Lactobacillus crispatus BCRC 14618) subjected to heat treatment showed significantly high antimicrobial activity. We found that substances produced by L. pentosus 13-4 which have the potential to exhibit antimicrobial properties might be lipophilic proteins. Additionally, we infer that the mechanism of reducing biofilm formation by Lactobacillus strains is associated with sucrose-dependent cell–cell adhesion and the gtfC level of glucosyltransferases (Gtfs) in the biofilm. Native LAB strains screened in our study may be used in chewing gums and other processed foods for preventing tooth decay.

As argued by ‘Declaration of Concrete Environment (2010)’ of Korea and ‘Declaration of Asian Concrete Environment (2011)’ of six Asian countries, concrete as a single material has lately shown extremely large impact on environmental issues such as climate change. Assessment of environmental impact from concrete material and production has considerable importance. Concrete is a major material used in the construction industry that emits a large amount of substances with environmental impacts during its life cycle. Accordingly, technologies for the reduction in and assessment of the environmental impact of concrete from the perspective of Life Cycle Assessment must be developed. At present, the studies in relation to greenhouse gas emission from concrete are being carried out globally as a countermeasure against climate change. In this study, a sustainable concrete mix design algorithm was designed using correlation analyses, and its carbon emission and cost reduction performances were assessed. Using correlation analyses, the concrete strength, w/b and s/a ratios, and CO₂ emissions were identified as major variables of concrete mix design that influenced other variables. Also, this study aims to evaluate the CO₂ emission reduction performance of the algorithm-deduced sustainable concrete mix design, and therefore, the CO₂ emissions of the sustainable concrete mix design are compared with those of the actual concrete mix design applied to the construction of the office building A in South Korea.

Human milk (HM) feedings are associated with reduced risks of neurodevelopmental and neurocognitive delays and systemic inflammatory diseases in infants born prematurely and/or at a low birth weight. Utilizing a neonatal piglet model, HM feedings were compared to bovine milk-derived infant formula (IF)-feedings with the aim of understanding the underlying mechanisms involved in reducing these risks. Six male piglets at postnatal-day (PD)2 were randomized into two feeding groups: HM-fed (n = 3) or IF-fed (n = 3) for 28 days. At 3- and 4-weeks-old, piglet memory and learning performance were assessed using novel object recognition (NOR). At PD30 piglets were euthanized, and whole brains were excised, weighed, and preserved for further analyses, and brain microglial morphology, and systemic inflammatory cytokines were quantified. During NOR, HM-fed piglets had significantly more non-novel revisits at both 3- and 4-weeks-old compared to IF-fed piglets. Microglia of HM-fed piglets had longer processes, more branch points, more endpoints, and a larger territorial volume compared to IF-fed piglets at PD30. In a neonatal piglet model, HM-feedings may improve cognition and reduce brain inflammatory response compared to IF-feedings.

Although various atmospheric corrosion simulation models have been developed that give good results, industrial environments are still challenging. This paper aims to investigate the effect industrial atmospheres in Bor on the mechanical properties of structural steel S235JR and to create a constitutive model and also laboratory experimental conditions that will give the best results as an accelerated corrosion test. Atmospheric corrosion tests lasted six months, using sites close to the Electrolytic Refining Plant and Sulphuric Acid Plant, as well as air quality monitoring stations at a remote location in the city of Bor. The laboratory experiments included a salt chamber test lasting 120 h and 240 h and immersing the specimen in the electrolyte from the Electrolytic Refining Plant for 30 days. The results were compared with the standard specimens stored in the laboratory. The X-ray diffraction (XRD) method was used to identify the composition of corrosion products. The scanning electron microscopy (SEM) analysis was applied to analyze the fracture surfaces of the specimens. The use of the Complete Gurson Model (CGM) described the tensile characteristics of the corroded specimens. The study has shown that an enhanced acceleration model and conditions could be developed using numerical analysis of the test results.

Mangrove ecosystems are one of the most productive on our planet but have declined globally by 30-50%. Many species rely on mangrove habitat and thus their conversion to aquaculture farms has led to a noticeable loss in commodities such as wild fish stocks. This study aimed to assess 1) the influence of the presence of aquaculture and 2) restoration projects on the ecosystems ability to provide resources. We collected data on mangrove vegetation (i.e., biomass, richness and abundance), soil nutrients (i.e. organic carbon, aluminium and nitrogen), crab abundance and fishing pressure in six sites. We set up 15 plots in each site and collected data between May and July 2023. Via generalised linear mixed models we found that the abundance and richness of crabs was significantly higher in aquaculture plots than in no aquaculture plots. Aquaculture plots had higher topsoil aluminium, topsoil and subsoil Nitrogen, and had lower topsoil Carbon than non-aquaculture sites. Restored sites had less Nitrogen in the topsoil than unmanaged sites. Biomass did not change between aquaculture, restored and unmanaged plots. We found a negative correlation between crab abundance and richness and mangrove DBH, suggesting that the species of crabs present preferred areas with propagules for feeding (e.g., Grapsidae crabs). The content of nitrogen in the subsoil was positively correlated with mangrove richness, diversity and height, suggesting the importance of nitrogen availability for mangrove growth. The content of aluminium in the subsoil was negatively correlated with the content of organic carbon both in topsoil and subsoil, suggesting the detrimental effect of aluminium on the carbon cycle. Fishing practices were observed in all sites during the data collection period. Even if most of the vegetation parameters were not significantly affected by presence of aquaculture or management for restoration, it is clear that important variables such as aluminium carbon, and nitrogen content in the soil and crab assemblages were highly variable.

Microplastic pollution (MP) in marine environments around the globe is severe and enough precautions have not been taken so far for its prevention. The focus of this study is to quantify MPs from beach sediment and seawater samples and to identify their distribution and types along the western coast of Sri Lanka from the Kelani River estuary to the Mahaoya estuary. Nine sites along this 42 km stretch were selected and random sampling was employed to collect a minimum of 8 sediment samples from each site between October and December 2021. Water samples were also collected, parallel to the sediments, from the ocean surface. FTIR analysis revealed that most of the MPs found were polyethylene(PE), polypropylene(PP), polystyrene(PS), polyethylene terephthalate(PET), and phenol formaldehyde resin. The mean abundance of MPs varied from 2.0 ± 0.6 items/L to 161.0 ± 15.7 items/L in water samples and, from 3.0 ± 0.3 items/m2 to 656.0 ± 34.5 items/m2 in sediment samples. The MPs found were identified in different shapes as fragments (80.2%), pellets (14.9%), fibers (2.7%) and foams (2.5%). Analysis revealed that the beach sediments were contaminated with PS, phenol formaldehyde resin, PET, PP and PE, while surface seawater is dominated by phenol formaldehyde resin, PS, PP and PE.

Penile cancer (PeCa) is a rare urological malignancy characterized by significant geographic variations in both incidence and mortality rates. Due to its rarity and the consequent lack of randomized trials, current management is based on retrospective studies and small prospective trials. In addition, the diagnostic pathways and treatment strategies exhibit substantial heterogeneity, differing significantly between less developed and well-developed countries. The prognosis of PeCa is determined by the presence and extent of regional lymph node (LN) involvement. Therefore, early detection and treatment of LN metastasis is paramount to ensure better outcomes. In recent decades, the overall survival for PeCa has increased, mainly due to advancements in imaging techniques and risk stratification. We aim to provide an overview of the current role of PET CT imaging in the management of patients with PeCa.

Neurosteroids are pleiotropic molecules involved in various neurodegenerative diseases with neuroinflammation. We assessed neurosteroids serum levels in a cohort of Parkinson’s Disease (PD) patients with heterozygous glucocerebrosidase (GBA) mutations (GBA-PD) compared with matched cohorts of consecutive non-mutated PD (NM-PD) patients, and healthy subjects with (GBA-C) and without (NM-HC) GBA mutations. A consecutive cohort of GBA-PD was paired for age, sex, disease duration, Hoehn & Yahr stage, and comorbidities with a cohort of consecutive NM-PD. Two cohorts of GBA-C and HC were also considered. Clinical assessment included the MDS-UPDRS and the Montreal Cognitive Assessment (MoCA). Serum samples were processed and analyzed by liquid chromatography coupled with triple quadrupole mass spectrometry. Twenty-two GBA-PD (males: 11, age: 63.68), 22 NM-PD (males: 11, age: 63.05), 14 GBA-C (males: 8; age: 49.36), and 15 HC (males: 4; age: 60.60) were studied. Compared to NM-PD, GBA-PD showed more hallucinations and psychosis (p<0.05, Fisher’s exact test) and higher MDS-UPDRS part-II (p<0.05). Most of the serum neurosteroids were reduced in both GBA-PD and NM-PD compared to the respective control cohorts, except for 5α-DHP. Allopregnanolone was the only neurosteroid significantly lower (p<0.01, Dunn’s test) in NM-PD compared to GBA-PD patients. Only in GBA-PD, allopregnanolone, and pregnanolone levels correlated (Spearman) with a more severe MDS-UPDRS part-III. Allopregnanolone levels also negatively correlated with MoCA scores, and pregnanolone levels correlated with more pronounced bradykinesia. This pilot study provides the first observation of changes in neurosteroid peripheral levels in GBA-PD. The involvement of the observed changes in the development of neuropsychological and motor symptoms of GBA-PD deserves further attention.

In this study, we investigated the relationship between age and microbial diversity in cattle, revealing significant changes in both protist diversity and fungal microbiota composition with age. Using fecal samples from 21 Simmental cattle, we analyzed microbial communities through 18S rRNA gene sequencing. Results indicated significant differences in alpha protist diversity among the three age groups, while fungal composition varied notably with age and was linked to hematological parameters. Despite the stability of fungal alpha diversity, compositional changes suggest the gut as a stable niche for microbial colonization influenced by diet, clinical parameters, and microbial interactions. All cattle were maintained on a consistent diet, tailored to meet specific nutritional needs of each age group. These findings emphasize the importance of understanding age-related microbial dynamics to enhance livestock management and animal health, contributing to broader ecological and biomedical research. However, the study was limited by the lack of comprehensive metabolic analyses correlating microbiota changes with specific age-related variations, indicating a need for further research in this area.

We compared the functional and morphologic effects in the loading dose between patients with treatment-naïve neovascular age-related macular degeneration treated with either intravitreal aflibercept (IVA) or intravitreal faricimab (IVF) injection in clinical settings. This retrospective study included 30 eyes from 28 patients who started IVA treatment between June and September 2022 and 30 eyes from 29 patients who started IVF treatment between October 2022 and March 2023. The mean best corrected visual acuity (BCVA) significantly improved from pre-treatment after loading dose in the IVA group (from 0.46 ± 0.46 to 0.36 ± 0.37, p=0.0047) and not in the IVF group (from 0.46 ± 0.41 to 0.44 ± 0.45, p=0.60). The mean central retinal thickness (CRT) significantly improved in both groups. The proportion of eyes with residual exudative change was greater in the IVF group than in the IVA group at 2 months after the first treatment. (p=0.026) We further analyzed the patients who obtained complete resolution of exudative changes after the loading dose. The IVA group had a significant improvement in BCVA, whereas the IVF group did not p=0.0047 and 0.20, respectively) Although IVA and IVF significantly improved the CRT, the BCVA improved significantly in IVA group and not in IVF group.

Epidemiological studies have shown that consuming olive oil rich in phenolic bioactive compounds is associated with a lower risk of neurodegenerative diseases and better cognitive performance in aged populations. Since oxidative stress is a common hallmark of age-related cognitive decline, incorporating exogenous antioxidants could have beneficial effects on brain aging. In this review, we firstly summarize and critically discuss the current preclinical evidence and the potential neuroprotective mechanisms. Existing studies indicates that olive oil phenolic compounds can modulate and counteract oxidative stress and neuroinflammation, two relevant pathways linked to the onset and progression of neurodegenerative processes. Secondly, we summarize the current clinical evidence. In contrast to preclinical studies, there is no direct evidence in humans of the bioactivity of olive oil phenolic compounds. Instead, we have summarized current findings regarding nutritional interventions supplemented with olive oil on cognition. A growing body of research indicates that high consumption of olive oil phenolic compounds is associated with better preservation of cognitive performance, conferring an additional benefit, independent of the dietary pattern. In conclusion, the consumption olive oil rich in phenolic bioactive compounds has potential neuroprotective effects. Further research is needed to understand the underlying mechanisms and potential clinical applications.

The blackening of cut carrots decreases their shelf life and causes severe economic losses but the molecular and metabolic mechanisms that underpin this phenomenon remain poorly characterized. Studies were therefore undertaken to determine the molecular and metabolic causes of the blackening. The susceptibility of blackening was dependent on the period of time that the crop was stored underground prior to harvest. The structure of the cell walls in the black regions was substantially changed compared to the orange regions. The black regions of carrot batons had decreased immunodetection of xyloglucan, HG-pectin, RG-I pectin, galactan and arabinan but had higher levels of lignin and phenolic compounds compared to the orange regions. Transcript profiling analysis revealed that phytohormone signalling processes were activated in the black regions. Transcripts associated with auxin signalling and ethylene-responsive transcription factors were increased in the black regions. In contrast, the levels of transcripts encoding proteins associated with secondary metabolism were decreased in the black regions. These findings implicate ethylene and auxin-related processes in the control of the primary to secondary metabolism shift that results in lignification and cell wall disruption that underpin the blackening process.

(1) Background: Breast cancer is the second leading cause of cancer death among women. The accurate prediction of survival intervals will help physicians make informed decisions on treatment strategies or the use of palliative care for patients; (2) Methods: The gene expression is predictive and correlates to patient prognosis. To establish a reliable prediction tool, we collected the RNA-seq data of breast cancer patients, a total of 1187 RNA-seq data (median age 58 years), in FPKM format from the TCGA database. Among them, 144 RNA-seq data with date of death information was selected to establish the SaBrcada-AD dataset. We first normalized the SaBrcada-AD dataset to transcripts per million (TPM) to build survival prediction model SaBrcada. After normalization and dimension raising, the differential gene expression data were used for testing eight different deep learning architectures. Among them, GoogLeNet performed the best. Considering the effect of age on prognosis, we examined all ages between the lower and upper quartiles of patient age for a stratified random sampling test; (3) Results: Stratifying by age based on a cut-off of 61 years of age improved the accuracy of SaBrcada compared to previous findings, resulting in an accuracy of 0.798. We also built a free website tool to provide 5 kinds of predicted survival period information for clinician reference; (4) Conclusions: We established a breast cancer survival analysis prediction model, SaBrcada, and a website tool with the same name. Through this highly reliable survival analysis model and website tool, information on survival intervals will be provided for clinicians as part of precision medicine.

Aging is a complex biological process, with gradual and progressive decline in structure and function in many organ systems. Our objective is to determine if structural changes produced by aging, vary with sex, in a stressful situation such as dehydration. The expression of Slc12a3 mRNA in renal cortex, α-smooth muscle actin (α-SMA) and fibronectin, was evaluated in male and female rats aged 3 and 18 months submitted or not to water deprivation (WD) for 48 hours. When comparing ages, 18-month-old males showed lower expression of Slc12a3 mRNA than 3-month-old males, and control and WD 18-moth-old male and female rats exhibited higher expression of α-SMA than respective 3-month-old rats. Fibronectin was higher in both control and WD 18-month-old males than respective 3-month-old males. In females, only control 18-month-old rats showed higher fibronectin than control 3-month-old rats. When we compared sex, control and WD 3-month-old female rats had lower expression of Slc12a3 mRNA than re-spective males. WD 18-month-old male rats presented higher expression of fibronectin and α-SMA than WD 18-month-old female rats. When we compared hydric condition, WD 18-month-old males displayed lower relative expression of Slc12a3 mRNA and higher α-SMA expression than control 18-month-old males. Aging, sex, and dehydration lead to alteration in kidney structure.

Background: The identification of novel therapeutic strategies for Ovarian cancer (OC), the most lethal gynecological neoplasm, is of utmost urgency. Here, we have tested the effectiveness of the compound 2c (4-Hydroxy-2,6-bis(4-nitrobenzylidene)cyclohexanone 2). 2c interferes with cyste-ine-dependent deubiquitinating enzymes (DUBs), thus affecting the ubiquitin-proteasome de-pendent degradation of proteins. Methods: 2c phenotypic/molecular effects were studied in two OC cell lines, primary tumor cells cultured in 2D/3D and in a mouse xenograft model. We also propose an in-silico model of 2c interaction with DUBs. Finally, we tested the effect of 2c conju-gated to several linkers to generate 2c-derivatives usable for improved drug delivery. Results: 2c effectively impairs OC cell line and primary tumor cell viability in both 2D and 3D conditions. The effectiveness is confirmed in a xenograft mouse model of OC. We show that 2c impairs pro-teasome activity and triggers apoptosis most likely by interacting with DUBs; we propose a mechanism for the interaction with a model DUB via an in-silico evaluation of the en-zyme-inhibitor complex. 2c also reduces cell growth by down-regulating the level of the transcrip-tion factor E2F1. Finally, 2c activity is often retained after the conjugation with linkers. Conclu-sion: Our data strongly support the potential therapeutic value of 2c/derivatives in OC.

We report on the successful preparation of wet dressings hydrogels based on Chitosan-Poly(N-Vinyl-Pyrrolidone)-Poly(ethylene glycol)-Poly(acrylic acid) and Poly(ethylene oxide) by e-beam cross-linking in weakly acidic media, to be used for rapid healing and pain release of infected skin wounds. The structure and compositions of hydrogels investigated according to sol-gel and swelling studies, network parameters, as well as FTIR and XPS analyses showed the efficient interaction of the hydrogel components upon irradiation, maintaining the bonding environment while the cross-linking degree increasing with the irradiation dose and the formation of a structure with the mesh size in the range 11-67 nm. Hydrogels with gel fraction above 85% and the best-swelling properties in different pH solutions were obtained for hydrogels produced with 15 kGy. The hydrogels are stable in the simulated physiological condition of an infected wound and show appropriate moisture retention capability and the water vapor transmission rate up to 272.67 g m-2 day-1, to ensure fast healing. The hydrogels proved to have a significant loading capacity of ibuprofen (IBU), being able to incorporate a therapeutic dose for the treatment of severe pains. Simultaneously, IBU was released up to 25% in the first 2h, having a release maximum after 8h.

Weight and age interact to modify cognitive effects of head acceleration events after two seasons of youth football Abstract This is a follow-up study of youth American football players in a second season of play. Season-one findings identified a relationship between a head acceleration measure (HITsp) and cognitive score changes with weight modifying the effect in 9 to 10 year-olds. Sixty-eight youth completed a second season of play wearing helmet-mounted sensors and were assessed with neuropsychological tests pre- and post-season. Regression analysis of the full sample demonstrated a small but significant negative effect of HAE on cognition as indexed by test score changes: R2 = .06, F = 4.06, p = .024. Outcome differences between those who started playing at ages nine to 10, compared to those who started between 11 and 13 were identified: t(66) = -3.39, p<.01, d = -.84, 95th CI -2.77 to -.72. Regression models including players’ weights found that the relationship of weight to outcome was different by group: greater negative cognitive effects were found in younger-heavier players (R2 = 0.21, F =3.21, p = 0.03) and older-lighter players (R2 = 0.18, F =4.26, p <.001). These findings confirmed a negative relationship of HAE and cognitive change and point to player weight as an important developmental factor to consider in understanding concussion biomechanics.

Pertussis is a vaccine-preventable disease caused by the bacterium Bordetella pertussis. Over the past years, the incidence and mortality of pertussis increased significantly. A possible cause is the switch from whole cell to acellular pertussis vaccines, although other factors may also contribute. To develop future vaccines and improve current vaccination strategies, it is critical to understand factors influencing the generation of immunological memory. We applied high-dimensional flow cytometry to investigate changes in B cells in individuals of different ages and distinct priming backgrounds upon administration of an acellular pertussis booster vaccine. These findings were correlated to vaccine-specific plasma cells and serum Ig levels. Expansion and maturation of plasma cells 7 days post-vaccination was the most prominent cellular change in all age groups, and was most pronounced for more mature IgG1+ plasma cells. Cellular responses were stronger in individuals primed with whole cell vaccine than in individuals primed with acellular vaccine. Moreover, IgG1+ plasma cell expansion weakly correlated with Prn- and PT- specific serum IgG levels. Our study points at plasma cells as a potential early cellular marker of an immune response and contributes to understanding differences in immune responses between age groups and priming backgrounds.

Recently, flares have been considered as a major source of air pollution from the petroleum refining industry. The United Nations have instigated an international effort related to the management of flare emissions to reduce the global warming impact related to flaring. Eliminating or removing the need for gas flares is difficult because these devices are generally used as safety devices to allow combustion of flammable gases in a controlled fashion which supports safe operation. However, reducing flaring is generally possible using well designed efficiently operated flare equipment. In general, flare performance can be enhanced following the API-521 methodology and using assist- media including air and steam to achieve smokeless operation. This present work will discuss flare emissions in petroleum refining industry, and a method to manage flare emissions. Moreover, this work will discuss flare Combustion Efficiency (CE) and Distraction and Removal Efficiency (DRE) in terms of efficient flare operation. This work uses actual operating flare data, published previously, will be used in this work together with the CFD Code C3d. This code, developed at the USDOE Sandia National Laboratory is based on a standard LES methodology to conduct transient flare analysis is used to simulate flare operation to estimate flame shape and emissions produced. In this work, a new air-assisted flare tip design which uses the Coanda effect to improve flare operation was analysed. This new flare design reduces the emission rate that demonstrates the design effectiveness. The analysis considers a flare 1m high and (6") diameter in the centre of a 4m*4m*4m domain. Boundary conditions considering no cross wind and an ambient temperature of 300K. The initial condition is a hydrostatic pressure profile across the computational domain. In the air assist simulation, stoichiometric ratio will be a variable and therefore more than one case was considered.

This study presents an innovative approach to interdisciplinary education by integrating principles of biology, engineering and art to foster holistic learning experiences for children. The focus lies on assembling mycelium bricks as engineered living materials with promising applications in sustainable construction. Through a collaborative group task, children engage in the hands-on creation of these bricks, gaining insights into mycology, biomaterials engineering and artistic expression. The curriculum introduces fundamental concepts of mycelial growth and its potential in sustainable material development. Children actively participate in fabricating 3D forms (negative and positive) using mycelium bricks, thereby gaining practical knowledge in shaping and moulding living materials. This hands-on experience enhances their understanding of biological processes and cultivates an appreciation for sustainable design principles. The group task encourages teamwork, problem-solving, and creativity as children collaboratively compose structures using mycelium bricks. Integrating art into the activity adds a creative dimension, allowing participants to explore aesthetic aspects while reinforcing the project’s interdisciplinary nature. Conversations about the material’s end of life and decomposition are framed within the broader context of Nature’s cycles, facilitating an understanding of sustainability. This interdisciplinary pedagogical approach provides a model for educators seeking to integrate diverse fields of knowledge into a cohesive and engaging learning experience. The study contributes to the emerging field of biomimetics education, illustrating the potential of integrating living materials and 3D understanding activities to nurture a holistic understanding of science, engineering and artistic expression in young learners.

In strawberry cultivation, precise disease management is crucial for maximizing yields and reducing unnecessary fungicide use. Traditional methods for measuring Leaf Wetness Duration (LWD), a critical factor in assessing the risk of fungal diseases such as botrytis fruit rot and anthracnose, have been reliant on sensors with known limitations in accuracy and reliability and difficulties with calibrating. To overcome these limitations, this study introduced an innovative algorithm for leaf wetness detection systems employing high-resolution imaging and deep learning technologies, including convolutional neural networks (CNNs). Implemented at the University of Florida's Plant Science Research and Education Unit (PSREU) in Citra, Florida, USA and expanded to three additional locations across Florida, USA, the system captured and analyzed images of a reference plate to accurately determine the wetness and, consequently, the LWD. The comparison of system outputs with manual observations across diverse environmental conditions demonstrated the enhanced accuracy and reliability of the artificial intelligence-driven approach. By integrating this system into the Strawberry Advisory System (SAS), this study provided an efficient solution to improve disease risk assessment and fungicide application strategies, promising significant economic benefits and sustainability advances in strawberry production.

Road traffic accidents are associated with different factors, such as non-signalized road networks, inexperienced drivers, lack of communication skills, distraction, and visual or cognitive impairment of road users, which have led to this increase in traffic accidents. Understanding these factors in alignment with road user communication skills can provide solutions that can reduce traffic fatalities. Road users’ communication is predominantly formal in nature, but informal means of communication also exist but are not given proper attention during the driving training and licence testing processes. Therefore, this study investigated communication skills between drivers as a factor contributing to traffic accidents in South African cities. Consequently, 16 traffic scenarios of communication between drivers were simulated using PTV Vissim and Blender software, and a semistructured interview questionnaire was used to collect data from South African road users. The questionnaire was further used to evaluate the confidence level of road users concerning informal communication. The data were analysed via regression analysis to establish the relationship between traffic accidents and miscommunication between drivers. The information gathered and analysed from this study helps to understand the informal communication types between drivers and establish where communication loss exists, which ultimately leads to a traffic accident. The results also show that misinterpretation of communication signals can present the possibility of traffic safety risk.

Despite the availability of COVID-19 vaccines, the global pandemic remains a significant health challenge. Timely detection of the virus is crucial for effective containment efforts, prompting the exploration of machine learning (ML) models for COVID-19 detection. highlights the ongoing significance of COVID-19 as a global health crisis despite the availability of vaccines. To address the need for timely virus detection, the study explores the efficacy of machine learning (ML) models, including DNN, Voting, Bagging, SVC_rbf, SVC_linear, SVC_polynomial, and SVC_sigmoid, in predicting COVID-19 infection probability. With a dataset comprising 4000 samples split into 3200 for training and 800 for testing, the analysis reveals that DNN and Voting models demonstrate the highest performance, achieving an impressive accuracy of 89%. These results underscore the potential of ML techniques, particularly DNN and ensemble methods like Voting, in facilitating early COVID-19 detection and contributing to effective pandemic management. The study emphasizes the importance of continued research to further refine and optimize ML-based COVID-19 detection systems.

Banks have enormous potential in supporting the achievement of sustainable development goals (SDGs) in accordance with their function as financial intermediaries through sustainable lending. However, the average national financing growth for the sustainable business activity category over the past four years is still 12%. The aim of this research is to identify the conditions of sustainable lending at state-owned conventional banks and analyze the influence of the value chain, economic performance and ESG performance on sustainable lending. The research was conducted at state-owned commercial banks in Indonesia. The research utilized a Structural Equation Modeling (SEM). The SEM results of this study describe value chain, ESG performance (environmental, social and governance) and economic performance have direct and positive influences on sustainable lending, of which ESG performance has the biggest influence. As per individual aspect, social orientation gives the biggest contribution toward sustainable lending.

Stallion mules have been used as working equids in several countries. Aggressiveness, under the influence of testosterone, resulted in the necessity for surgical castration before work training. The gonadotropin-releasing hormone (GnRH) vaccine may be an alternative method for immunocastration in mules. The objectives were to evaluate the effect of GnRH vaccine on anti-GnRH antibody production, serum testosterone level, clinical adverse effects, and behavior toward human manipulation. Twenty-five mules were separated into 3 groups: Control-intact, Control-castrated, and Treatment. Treatment was further divided into subgroups according to condition (intact or unilateral cryptorchid) and age. Treatment received 195 µg GnRH vaccine intramuscularly at week 0, 4, and 8. Anti-GnRH antibody increased at week 6 and 10, then gradually decreased to baseline at week 22. Treatment-intact-young had the highest anti-GnRH antibody, resulting in lower serum testosterone levels during week 2-6 and 12-16 compared to Control-intact. Subcutaneous edema adjacent to the injection site was detected only in Treatment-intact after booster vaccination. During week 6-22, the behavioral scores of Treatment significantly changed toward at ease with human contact compared to a score before vaccination. In conclusion, mules responded to GnRH vaccine, which could temporarily suppress testosterone for up to 16 weeks.

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment–based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

Powdery mildew is a severe disease causing substantial yield losses in wheat production worldwide. The Chinese wheat landrace Changanhongmai (CAHM) exhibits high resistance to the physiological race E09 of powdery mildew. This study aims to characterize the powdery mildew resistance gene in CAHM, and develop molecular markers for marker-assisted selection of wheat. To investigate the genetic characteristics of this resistant gene, we developed F1 plants, F2 generation population, and F2:3 families from a cross between CAHM and SY225. Genetic analysis demonstrated that all F1 plants were resistant to the disease, while the ratio of resistant to susceptible plants was 3: 1 in both the F2 population and F2:3 families, indicating that CAHM is inherited in a manner of single dominant powdery mildew resistance gene, which was tentatively designated as PmCAHM. By using bulk segregation analysis, we constructed a genetic map encompassing Xgwm273, Xwmc626, Xgwm11, Xgwm18, Xgdm28, Xgpw7812, Xgpw5195, Xwmc694 and PmCAHM. Among these markers, Xgpw7812 and Xgpw5195 were flanking markers tightly linked to PmCAHM at a genetic distance of 2.5 cM and 8.4 cM, respectively. Furthermore, nullisomic-tetrasomic analysis revealed that PmCAHM is located on chromosome 1B. These results indicate that PmCAHM differs from the internationally recognized powdery mildew resistance genes in both location and source. In addition, a new germplasm/line NW1748 with large seeds and powdery mildew resistance was developed from the cross and back cross populations of Fengyou 1718 (FY1718)/CAHM//FY 1718. Therefore, PmCAHM can serve as a novel powdery mildew resistance source for breeding of wheat by using NW1748 as the donor in the future.

Cholesterol homeostasis is pivotal for cellular function. Acyl-coenzyme A:cholesterol acyltransferase 1 (ACAT1), also abbreviated as SOAT1, is an enzyme catalyzing the storage of excess cholesterol to cholesteryl esters. ACAT1 is an emerging target to treat diverse diseases including atherosclerosis, cancer, and neurodegenerative diseases. F12511 is a high affinity ACAT1 inhibitor. Previously, we developed a stealth liposome-based nanoparticle to encapsulate F12511 to enhance its delivery to the brain and showed its efficacy in treating a mouse model for Alzheimer’s disease (AD). In this study, we introduce F26, a close derivative of F12511 metabolite in rats. F26 was encapsulated in the same DSPE-PEG2000/phosphatidylcholine (PC) liposome-based nanoparticle system. We employed various in vitro and in vivo methodologies to assess F26's efficacy and toxicity compared to F12511. Results demonstrate that F26 is more effective and durable than F12511 in inhibiting ACAT1, in both mouse embryonic fibroblasts (MEFs) and in multiple mouse tissues including the brain tissues, without exhibiting any overt systemic or neurotoxic effects. This study demonstrates the superior pharmacokinetic and safety profile of F26 in wild-type mice, and suggests its therapeutic potential against various neurodegenerative diseases including AD.

Objectives: To compare the effects of high-velocity resistance training to slow-velocity re-sistance training on neuromuscular and functional parameters and to analyze the relationship between changes in walking speed and improvements in neuromuscular parameters following intervetions. Methods: 40 participants were randomly assigned to either a high-speed resistance training group (GHS, n = 18; age = 80.41 ± 10.12 years; BMI = 23.81 ± 3.45 kg/m²) or a low-speed resistance training group (GLS, n = 22; age = 82.89 ± 5.32 years; BMI = 23.81 ± 3.45 kg/m²). Before and after the interventions, gait speed (m/s) was assessed using a 10-minute walking test, and relative maximal force (Relative F max, N/kg) was evaluated during maximal voluntary isometric con-traction of the plantar flexors. From the force-time curve, early (0 – 50 ms) and late (100 – 200 ms) rates of force development (RFD) were extracted from the linear slopes (Δ force / Δ time). Results: Gait speed significantly improved in both groups (p < 0.05). However, the improvement was more pronounced in the GHS compared to the GLS (p < 0.05). Relative Fmax showed a more significant increase in the GLS than in the GHS (p < 0.05). Moreover, a significant 10% increase in early RFD in the GLS and a 20.1% increase in the GHS were observed (p < 0.05). The improvement in early RFD was greater in the GHS (p < 0.05). Additionally, late RFD improved significantly only in the GHS (+20.4%, p < 0.05). Conclusion: High-velocity resistance training appears particularly effective in improving the ability to rapidly generate force, which is essential for many daily activities re-quiring explosive movements and quick responses.

Paratuberculosis, or Johne's disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic granulomatous enteritis affecting both domestic and wild ruminants. The agent was also found in wild mammals such as wild boar (Sus scrofa), however, the role of wild mammals in the epidemiology of MAP is unclear. During the research period, 941 free-ranging wild boar (S. scrofa) legally hunted in two locations in the Centre-eastern region of Portugal were examined. Ninety-seven wild boar exhibited one or more gross lesions and were tested for the presence of Mycobacterium avium subsp. paratuberculosis using acid-fast staining, mycobacterial culture, poly-merase chain reaction (PCR), and histopathological examination. Forty-five animals (46.4%, 95% CI: 36.5-56.3%) were identified as infected, as indicated by positive results in culture and/or PCR. The findings revealed that the most significant risk factor was being a juvenile compared to year-lings and adults (OR = 10.2, 95% CI: 2.2-48.0). Based on our results, 37.9% (n = 11) of the infected animals were considered suitable for human consumption. Our findings offer novel insights into mycobacterial infections in wild boar populations in Portugal and suggest that wild boar could be a source of human infection if zoonotic potential is considered.

Oncomelania Hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of its habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB), and the ecological stability. Therefore, it is crucial to analyse the influence of climate change on the distribution of O. Hupensis in order to achieve accurate control over its population. This study utilised the MaxENT model to forecast possible snail habitats by utilising snail distribution data obtained from historical literature. The subsequent outcomes were achieved: The primary ecological factors influencing the distribution of O. Hupensis are elevation, minimum temperature of coldest month, and precipitation of wettest month; Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution centre for O. hupensis; Specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest; These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, resulting in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.

To mitigate pyrethroid resistance in mosquito vectors of emerging and re-emerging human pathogens, there is an urgent need to discover insecticides with novel modes of action. Natural alternatives, such as extracts derived from plants, may serve as substitutes for traditional synthetic insecticides if they prove to be sustainable, cost-effective, and safe for non-target organisms. Hemp (Cannabis sativa) is a sustainable plant known to produce various secondary metabolites with insecticidal properties, including terpenoids and flavonoids. The goal of this study was to assess the larvicidal activity of hemp leaf extract on 1st instar mosquito larvae from both pyrethroid-susceptible (PS) and pyrethroid-resistant (PR) strains of Aedes aegypti Another goal was to identify which components of the extracts were responsible for any observed larvicidal activity. We found that methanol extract of hemp leaves induced similar concentration-dependent larvicidal activity against PS (LC50: 4.4 ppm) and PR (LC50: 4.3 ppm) strains within 48 hours. Partitioning of the dried leaf extract between methanol and revealed that full larvicidal activity was restricted to the methanol fraction. Analysis of this fraction by gas chromatography-mass spectrometry and nuclear magnetic resonance showed it to be dominated by cannabidiol (CBD). Larvicidal assays using authentic CBD confirmed this compound was primarily responsible for the toxicity of hemp leaf extract against both strains. We conclude that hemp leaf extracts and CBD have the potential to serve as viable sources for the development of novel mosquito larvicides.

Plain lakes play a crucial role in the hydrological cycle of a watershed, but their interactions with adjacent rivers and downstream water bodies can create complex river-lake relationships, often leading to frequent flooding disasters. Taking Poyang Lake as an example, this paper delves into its interaction with the Yangtze River, revealing the spatiotemporal patterns of flood propagation within the lake and its impact on surrounding flood control measures. The aim is to provide insights for flood management in similar environments worldwide. This study employs a comprehensive approach combining hydrological statistical analysis and two-dimensional hydrodynamic modeling, based on extensive hydrological, topographic, and socio-economic data. The results indicate that the annual maximum outflow from Poyang Lake is primarily controlled by floods within the watershed, while the highest annual lake water level is predominantly influenced by floods from the Yangtze River. The peak discharge typically reaches the lake outlet within 48 hours, with the peak water level taking slightly longer at 54 hours. However, water storage in the lake can shorten the time for the peak discharge to arrive. When converging with floods from the Yangtze River, the peak water level may be delayed by up to 10 days due to the top-supporting interaction. Furthermore, floods from the "Five Rivers" propagate differently within the lake, affecting various lake regions to differing degrees. Notably, floods from the Fu River cause the most significant rise in lake water level under the same flow rate. The top-supporting effect from the Yangtze River also significantly impacts the water surface slope of Poyang Lake. When the Yangtze River flood discharge far exceeds that of the "Five Rivers" (i.e., when the top-supporting intensity f value exceeds 4), the lake surface becomes as flat as a reservoir. During major floods in the watershed, the water level difference in the lake can increase dramatically, potentially creating a "dynamic storage capacity" of up to 840 million cubic meters.

Postprandial glucose levels between 4 and 7.9 hours (PPG4–7.9h) correlate with mortality from various diseases including hypertension, diabetes, cardiovascular disease, and cancer. This study aimed to assess if predicted PPG4–7.9h could diagnose diabetes. Two groups of participants were involved: Group 1 (4420 participants) had actual PPG4–7.9h, while Group 2 (8422 participants) lacked this measure but had all the diabetes diagnostic measures. Group 1 underwent multiple linear regression to predict PPG4–7.9h using 30 predictors, achieving accuracy within 11.1 mg/dL in 80% of the participants. Group 2 had PPG4–7.9h predicted using this model. Receiver operating characteristic curve analysis showed that predicted PPG4–7.9h could diagnose diabetes with an accuracy of 87.3% in Group 2, with a sensitivity of 75.1% and specificity of 84.1% at the optimal cutoff of 102.5 mg/dL. Simulation on 10,000 random samples from Group 2 revealed that 175 participants may be needed to investigate PPG4–7.9h as a diabetes diagnostic marker with a power of at least 80%. In conclusion, predicted PPG4–7.9h appears to be a promising diagnostic indicator for diabetes. Future studies seeking to ascertain its definitive diagnostic value might require a minimum sample size of 175 participants.

This paper proposed three-dimensional numerical simulation method by coupling of electrostatic and fluid fields to evaluating the performance of electrical sensor in the concentration measurement of gas/solid two-phase flow. Compared with the static numerical simulation, this real-time dynamic 3-D simulation method can research on a designed capacitance sensor combining the dynamic characteristics of the two-phase flows for concentration measurement. Several fluid-electrostatic models of transmission pipes with different sensor structures are built. Under different test positions and different particle concentrations, the flow characteristics and the corresponding electric signals can be obtained, and the correlation coefficient between the concentration values and the capacitance values are used for performance evaluation of the sensors. The effects of flow regimes on concentration measurement are also been investigated in this paper. To validate the results of simulation, an experimental platform with horizontal straight pipe for phase volume concentration measurement of solid/air two-phase flow is built, and the experimental results agree well with simulation conclusions. The simulation and test results show that the coupling models can give constructive reference opinions for the sensor design and collection of installation position in different transmission pipelines, which are very important for the practical process of pneumatic conveying system.

Background and Objectives: Renal cell carcinomas and upper tract urothelial carcinomas are types of malignancies that originate in the kidneys. Each of these examples shows an increasing trend in the frequency and the mortality rate. This study aims to comprehensively define carcinomas by analysing clinical, paraclinical, and histological aspects to predict aggressiveness and mortality. Materials and Methods: We conducted a retrospective investigation on a group of patients suspected with kidney cancers. Results: We identified 188 cases. We observed a higher mortality rate and older age in individuals with urothelial carcinomas. Anemia, acute kidney injury, hematuria and perineural invasion were the main risk factors that predicted their mortality. Tumour size in renal cell carcinomas correlates with the presence of necrosis and sarcomatoid areas. Factors that indicate a higher rate of death are older age, exceeding of the renal capsule, the lesion that includes the entire kidney, lymphovascular invasion, acute kidney injury, and anemia. Conclusions: Even if they originate at the renal level, and the clinical-paraclinical picture is similar, the histopathological characteristics make the difference. In addition, to these are added the previously mentioned common parameters that can represent important prognostic factors. In conclusion, the characteristics commonly identified in one type of cancer may act as risk factors for the other tumor. The detected data include threshold values and risk factors, making a significant contribution to the existing literature.

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with themselves, their environment, and hosts via metabolites and signaling molecules. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metagenomics methods, and modeling formalisms. Furthermore, the review explains model building, examples of microbiome model applications for prediction, optimization, and control. It concludes with guidelines, software, and repositories for modeling. Each section provides entry-level information, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

It has been known for nearly over 150 years that fatigue life data exhibits a considerable amount of variability. Furthermore, statistically modeling fatigue life adequately is challenging. Different empirical approaches have been used, each of which has merit; however, none is appropriate universally. Even when a sufficiently robust database exists, the scatter in the fatigue lives may be extremely large and difficult to characterize. The complications in empirical modeling are exacerbated for long life estimation when experimental observations are rare. The purpose of this work is to review traditional and more modern empirically based methodologies for estimating the cumulative distribution functions for fatigue life, given an applied load. To assess the applicability of the methods confidence bounds will be estimated. The analyses will be performed on an historic set of data for annealed aluminum wire tested in reverse torsion fatigue. These data are available in publications. It is recommended that a time dependent distribution function that is an based on principles of reliability that can be generalized for a variety of modeling applications should be considered for fatigue life estimation.

The study is devoted to the issues of mathematical modeling and simulating the sport differential mechanism (DM) with controllable torque redistribution. The issue is caused by the elaboration of ADAS systems with the automated torque vectoring for transmissions of all-wheel-drive (AWD) vehicles and the inclusion of such devices in the combined autonomous vehicle trajectory control scheme. At the article's beginning, the use of devices for redistributing traction forces is reasoned by analyzing the curvilinear vehicle motion, where they could ensure the accuracy of vehicle steerability. The literature review highlights modern developments in the field of modeling and researching such DMs. Considering the vehicle turn with a minimum radius, the conditions corresponding to passing greater torque over the outrunning rear axle are determined. All the mechanism's components and loads acting between them are described in detail. To form an original method of mathematical description of the mechanism functioning, the system of differential equations, systems of kinematic and force connections are considered separately. The article details the mathematical approach to generalize the way for automating the equation compilation for rotational mechanical systems such as vehicle transmissions. In the simulation section, a Simulink model reflecting the functional components and calculation procedures is presented. A series of testing and simulations on the DM operation with forcible torque distribution is carried out. Modeling data are presented, and the analysis of simulation results is performed. In the completion, conclusions are made regarding the scope and use of this model and the prospects for further developing the method proposed to automate the formation of equation systems.

Traditional photodynamic therapy (PDT) is often limited in its efficacy by insufficient light penetration, inefficient photosensitizer energy transfer, and inadequate target tissue oxygenation. X-ray activated PDT (XPDT), using nanoparticle (NPs) photosensitizers comprised of europium-doped yttrium oxide cores encased within silica shells (Y₂O₃:Eu@SiO₂), offers the potential of overcoming most of these limitations. Aimed at maximizing the generation of reactive oxygen species (ROS), this study reports methodologies for investigation of the effects of synthesis conditions on the characteristics of Y₂O₃:Eu@SiO₂ NP. Transmission electronic microscope (TEM) revealed that the NP core diameter was linearly, positively correlated with condensation time (R2 = 0.7357, p < 0.05) and linearly, negatively correlated with urea concentration (R2 = 0.958, p < 0.05). The addition of cetyltrimethylammonium bromide (CTAB) during core synthesis demonstrated enhanced particle dispersion. Silica coating via APTES-1 and TEOS-3 conditions resulted in Y₂O₃:Eu@SiO₂ NPs that generated the highest ROS, with 8.7-fold and 8.9-fold increase respectively in relative fluorescence intensity at 8 Gy irradiation compared to a 5.2-fold increase in PBS under the same condition. In vivo evaluation using 18F-fluorothymidine positron emission tomography (18F-FLT PET) of mouse xenografts of a human prototypical cancer (ovarian) revealed a 55% reduction in tumor proliferation of radiation-sensitive CAOV3 tumors treated with Y₂O₃:Eu@SiO₂ NPs compared to a 19% reduction in tumor proliferation of radiation-resistant SKOV3 tumors on the fourth day post-treatment. Taken together, these findings suggest Y₂O₃:Eu@SiO₂ NPs can serve as effective photosensitizers for XPDT and their performance characteristics can be optimized by selecting synthesis conditions and parameters to deliver the desirable therapeutic effects, offering novel approaches to circumventing many of the limitations of conventional PDT in the treatment of cancer.

Oxidative stress and chronic inflammation both at the systemic and central level, are important early events in atherosclerosis and Alzheimer’s disease (AD). Purpose. To investigate the oxidative stress, inflammatory, and Tau-phosphorylation lowering effects of pomegranate polyphenols (PP) (punicalagin, ellagic acid, peels, and arils extracts). Methods. We used flow cytometry to quantify protein expression of proinflammatory cytokines (IL-1β) and anti-inflammatory mediators (IL-10) in THP-1 macrophages, as well as M1/M2 cell-specific markers (CD86 and CD163) expression in human microglia HMC3 cells. IL-10 protein expression was also quantified in U373-MG human astrocytes. The effect of PP on human amyloid beta 1-42 (Aβ1-42)-induced oxidative stress, was assessed in microglia by measuring ROS generation and lipid peroxidation, using respectively 2′,7′-dichlorofluorescein diacetate (DCFH-DA) and thiobarbituric acid reactive substances (TBARS) tests. Neuronal viability and cell apoptotic response to Aβ1-42 toxicity were assayed using the MTT (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay and the annexin-V-FITC apoptosis detection kit; respectively. Finally, flow cytometry analysis was also performed to evaluate the ability of PP to modulate Aβ1-42-induced Tau-181 phosphorylation (pTau-181). Results. Our data indicate that PP were significantly (p

A new two-step method for developing a nanocomposite of polypropylene (PP) decorated with photocatalytically active TiO2 nanoparticles (nTiO2) is proposed. This method involves low-temperature plasma functionalization of polypropylene followed by ultrasound-assisted anchoring of nTiO2. The nanoparticles, polymeric substrate, and resultant nanocomposite were thoroughly characterized using nanoparticle tracking analysis (NTA), microscopic observations (SEM, TEM, EDX), spectroscopic investigations (XPS, FTIR), thermogravimetric analysis (TG/DTA), and water contact angle (WCA) measurements. The photocatalytic activity of the nanocomposites was evaluated through the degradation of methyl orange. The individual TiO2 nanoparticles ranged from 2-6 nm in size. Oxygen plasma treatment of PP generated surface functional groups (mainly -OH and -C=O), transforming the surface from hydrophobic to hydrophilic, which facilitated efficient deposition of nTiO2. Optimized plasma treatment and sonochemical deposition parameters resulted in an active photocatalytic nTiO2/PP system, degrading 80% of methyl orange under UVA irradiation in 200 minutes. The proposed approach is considered versatile for the functionalization of polymeric materials with photoactive nanoparticles and, in a broader perspective, can be utilized for the fabrication of self-cleaning surfaces.

The leaves of Nicotiana glauca (Solanaceae) plant, are known for its major cause of health concern. This study investigated the antioxidant activity and polyphenols composition of aerial parts of N.glauca collected from its wild habitat in Jordan, using Methanol-Conventional (MC) and deep eutectic solvents (DESs) extraction methods in addition to nicotine content determination using UHPLC. The results have shown that the MC extract contains fewer total phenols and flavonoid content than the DES extract at ratio of 90% (0.1194 ±0.009 and 0.311± 0.020 mg/mL equivalent to gallic acid) and (0.01084±0.005 and 0.928 ± 0.09 mg/mL equivalent to rutin), respectively. Moreover, the study showed that the MC extract contains 635.07 ppm nicotine compared to the DES extraction method, which contains 1194.91 ppm. Both the MC and the DES extracts exhibited weak antioxidant activities with the highest was 33%inhibition equivalent to ascorbic acid was found for DES at (90%) ratio. The UHPLC-MS/MS analysis revealed the presence of variations in the detected compounds between the two extraction methods used. This study found that en-vironmentally friendly DES extraction of N. glauca produced higher phenol and flavonoid content than MC method, highlighting green chemistry methods' superior efficiency and environmental benefits for extracting valuable phytoconstituents.

Faced with increasing climate challenges, this pioneering study introduces groundbreaking approaches to ensure the resilience of potato crops in east-central Poland. Our research aimed to develop an innovative, cost-effective system tailored to the diverse local conditions of this region. Conducted between 2018 and 2020, the study analyzed integrated and organic production systems across different soil types and potato varieties. The experiment was conducted using a randomized block design with three replications in two locations. Integrated practices, enhanced by mineral fertilization and chemical protection, notably delayed the onset of late blight by 16 days and extended the critical infection period by 17% compared to their organic counterparts. Remarkably, the integrated systems resulted in a 49% increase in total production and a 52% increase in commercial yields, demonstrating their effectiveness in enhancing crop resilience. Different potato varieties exhibit varied responses to cultivation systems, influencing both yield and disease resistance. Further investigation into these varietal responses can help optimize cultivation practices, leading to improved efficiency and sustainability in potato farming. Location and soil conditions have a significant impact on potato yield and the spread of potato blight. Further research into specific soil properties and the adaptation of varieties to local conditions can contribute to increased productivity and stability in potato production. This study not only paves the way towards sustainable agriculture but also highlights the crucial role of soil diversity in shaping resilient farming practices.

Although migraine belongs to the main causes of disability worldwide the mechanisms of its pathogenesis are poorly known, which is among the reasons that this disease is underdiagnosed and undertreated. As migraine diagnosis is based on the subjective assessment of symptoms, there is a need to establish objective markers of its occurrence and severity. Tryptophan (TRP) metabolism has been associated with the pathogenesis of neurological and psychiatric disorders. In the present work, we investigated an association between migraine and the urine concentration of TRP and its metabolites 5-hydroxyindoleacetic acid (5-HIAA), kynurenine (KYN), kynurenic acid (KYNA) and quinolinic acid (QA) in 21 low-frequency episodic migraine patients and 32 controls. Migraine patients displayed lower urinary levels of 5-HIAA and KYNA, but KYN and QA were enhanced as compared with the controls. Consequently, the patients were characterized by different values of the 5-HIAA/TRP, KYN/TRP, KYNA/KYN, and KYNA/QA ratios. Furthermore, urinary concentration of 5-HIAA was negatively correlated with Migraine Disability Assessment score, monthly migraine, and monthly headache days. A negative correlation between Patient Health Questionnaire 9 scores assessing depression. In conclusion, the urinary 5-HIAA level may be an easy-to-determine marker of migraine occurrence and severity and may contribute to the identification of migraine patients with depression.

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

Fast-scan cyclic voltammetry (FSCV) is an electrochemical sensing technique that can be used for neurochemical sensing with high spatiotemporal resolution. Carbon fiber microelectrodes (CFMEs) are traditionally used as FSCV sensors. However, CFMEs are prone to electrochemical fouling caused by oxidative byproducts of repeated serotonin (5-HT) exposure, which makes them less suitable as a chronic 5-HT sensor. Our team is developing a boron-doped diamond microelectrode (BDDME) that has previously been shown to be relatively resistant to fouling caused by protein adsorption (biofouling). We sought to determine if the BDDME exhibits resistance to electrochemical fouling, which we explored on electrodes fabricated with either femtosecond laser cutting or physical cleaving. We recorded the oxidation current response after 25 repeated injections of 5-HT in a flow-injection-cell and compared the current drop from the first to the last injection. The 5-HT responses were compared to dopamine (DA), a neurochemical that is known to produce minimal fouling oxidative byproducts and have a stable repeated response. Physical cleaving of the BDDME yielded a reduction in fouling due to 5-HT compared to the CFME and the femtosecond laser cut BDDME. However, the femtosecond laser cut BDDME exhibited a large increase in sensitivity over the cleaved BDDME. An extended stability analysis was conducted for all device types following 5-HT fouling tests. This analysis demonstrated an improvement in the long-term stability of boron doped diamond over CFMEs, as well as a diminishing sensitivity of the laser cut BDDME over time. This work reports the electrochemical fouling performance of the BDDME when it is repeatedly exposed to DA or 5-HT, which informs the development of a chronic, diamond-based electrochemical sensor for long-term neurotransmitter measurements in vivo.

Histone changes that are adjustable and transmitted without altering the DNA sequence are part of epigenetic control. In many disorders, most famously malignancy, abnormal genetic information is seen as a result of mismanagement of typical epigenetic mechanisms. A paradigm change in the diagnosis and treatment of cancer has been brought about by recent discoveries about the processes of epigenetic modifications, chromatin remodeling, and noncoding RNAs implicated in the changed expression patterns of tumor cells. There is a significant increase in the search for drugs that could alter the epigenetic environment altered by tumor cells and benefit from their therapeutic potential. Phytochemicals with a high concentration of naturally produced phenol molecules known as flavonoids can regulate genomic processes. Understanding the precise epigenetic alterations brought on by flavonoid-mediated mechanisms is necessary to develop combination therapy techniques and genomic therapies for cancer. This article aims to thoroughly examine the epigenetic modifications of flavonoids, including their anticancer properties.

Patients who survived critical COVID-19 frequently reported post-acute sequelae of COVID-19 (PASC) such as psychosomatic and neurocognitive health problems. The goal of this study was to identify clinical risk factors and other predictors for such long-term consequences in severely ill COVID-19 patients. Adult COVID-19 intensive care unit (ICU) survivors from August 2020 to May 2021 were enrolled. A broad range of clinical, laboratory and chest computed tomography (CT) data was collected during ICU stay. The association between ICU predictors and psychosomatic, respiratory and neurocognitive assessments 12 months after ICU discharge was analyzed using univariate regression analysis. In 17 patients (mean age 58.9 ± 11.4 years), laboratory markers (CRP, lymphocytes, hemoglobin), ICU severity (SOFA, SAPS II, need for mechanical ventilation), complications (ARDS), and lung CT data (ground-glass opacity) were promising predictors of depressive and anxiety symptoms, fatigue, and sleep problems. Recovery of psychosomatic health such as fatigue, depression and anxiety correlated with lower levels of inflammation and high hemoglobin levels. ARDS, mechanical ventilation and worse SOFA and SAPS II scores were further risk factors for depressive and anxiety symptoms. Our study identified novel associations such as pulmonary ground-glass opacity being positively associated with depression, anxiety, fatigue, and insomnia levels.

The formability and failure behavior of TRIP steel blanks were investigated through various stress states. The forming limit diagram (FLD) at fracture is constructed both experimentally and numerically. Numerical studies are performed to evaluate the applicability of different damage criteria in predicting the FLD as well as complex cross-die deep drawing process. The fracture surface and numerical results revealed that the material failed in a different mode for different strain path. Therefore, Tresca model which is based on shear stress accurately predicted the conditions where shear had the profound effect on the damage initiation, whereas Situ localized necking criterion was able to calculate the conditions which localization was dominant.

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)’s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco (Piaractus brachypomus) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing distance away from the Madre de Dios headwaters (as the crow flies), did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities.

Corrugated board, widely used in the packing industry, is a recyclable and durable material. Its strength and cushioning, influenced by geometry, environmental conditions like humidity and temperature, and paper quality, make it versatile. Double-walled (or five-ply) corrugated board, comprising two flutes and three liners, enhances these properties. This study introduces a novel approach to analyze 5-layered corrugated board, extending a previously published algorithm for single-walled boards. Our method focuses on measuring layer and overall board thickness, flute height, and center lines of each layer. Integrating image processing and genetic algorithms, the research successfully developed an algorithm for precise geometric feature identification of double-walled boards. Images were recorded using a special device with a sophisticated camera and image sensor for detailed corrugated board cross-sections. Demonstrating high accuracy, the method faced limitations only with very deformed or damaged samples. This research contributes significantly to quality control in the packaging industry and paves the way for further automated material analysis using advanced machine learning and image sensors. It emphasizes the importance of sample quality and suggests areas for algorithm refinement to enhance robustness and accuracy.

This six-year multicentre study investigated acute intentional poisoning with substances of abuse in adolescents to identify changes and patterns in substance use. Data from 568 adolescents were collected from three paediatric poison centres in Romania between January 2017 and December 2022. The study analysed the epidemiological and sociodemographic characteristics of the adolescents, including age, gender, place of residence, history of substance abuse, psychiatric history, and history of institutionalized care. The findings revealed that cannabis and new psychoactive sub-stances (NPSs) are the most commonly implicated substances, each with distinct profiles among adolescents. Cannabis was involved in 45.6% of cases, with a significant association with urban residency. NPSs were identified as the second most prevalent substance, accounting for 38.9% of cases. These were more prevalent in rural areas and among patients with psychiatric disorders. Cannabis and NPSs were also the most commonly implicated substances in acute intentional poisoning cases with substances of abuse. These substances have distinct profiles among adolescents, including age, gender, residency area, history of substance abuse, psychiatric history, and institutional care. These findings underscore the necessity of targeted public health interventions and integrated care approaches to address substance use and related mental health issues in adolescents.

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

This study investigated subclinical atherosclerosis progression in low-risk, middle-aged adults (N=141; mean age 49.6±4.7 years) using a 5-year ultrasound follow-up. We compared in-volvement of the carotid and femoral arteries. Methods: Clinical data, risk factors, and carotid/femoral intima-media thickness (IMT) and plaque presence were analyzed. Results: Cardiovascular risk factors and scores increased significantly at follow-up. Both carotid and femoral IMT increased (p&lt;0.001) but remained within the normal range. While plaque prev-alence rose and was similar in both arteries (carotid: 4.8% to 17.9%, femoral: 3.6% to 17.7%, p&lt;0.001 for both), the progression of plaque burden was greater in femorals. Notably, carotid IMT demonstrated a faster yearly progression rate compared to femoral IMT. The age- and sex-adjusted increase in IMT was also more frequent in the carotids (52.9% to 78.8%, p&lt;0.001) compared to femorals (23.2% to 44.7%, p&lt;0.001). Conclusions: This study demonstrates significant subclinical atherosclerosis progression in low-risk middle-aged adults during 5 years. Carotid arteries showed a faster progression rate and higher prevalence of increased age- and sex-adjusted IMT compared to the femoral arteries. However, plaque burden was similar in both territories, with greater progression in femorals. Identifying carotid and femoral atherosclerosis burden may be a valuable tool for risk stratification in this population.

Porcine parvovirus 8 (PPV8), a novel virus in the Parvoviridae family, was first identified in 2022 in lung samples of domestic pigs from China. Retrospective analyses showed that it had been circulating in China since 1998, but no other countries had reported its presence so far. A recent study conducted in South America did not detect any PPV8-positive samples in that region. Here we report the detection of PPV8 in Hungarian and Slovakian pig farms and the estimated prevalence of the virus in Hungary. Altogether 2230 serum, 233 oral fluid, and 115 processing fluid samples were systematically collected from 23 Hungarian and 2 Slovakian pig farms between 2020 and 2023. A real-time quantitative PCR method was developed to detect the viral genome. Our results revealed the presence of PPV8 on 65% of the Hungarian farms and on both Slovakian farms included in our study, marking its first detection in Europe. Oral fluid samples showed the highest positivity rates, reaching up to 100% in some herds. The viral genome was successfully detected in serum and processing fluid samples too, but with significantly lower prevalence rates of 4% and 5%, respectively. Genetic analysis of 11 partial VP2 sequences demonstrated high similarity to the original Chinese strain but with unique amino acid mutations, suggesting possible local evolution of the virus. Our study presents the first scientific evidence of PPV8 infection outside of China and offers a comprehensive assessment of its prevalence in the Hungarian pig population. Further research is required to understand its potential impact on swine health.

The paper presents new data on mineralogical-geochemical peculiarities of the granites and pegmatites of the Baikal area (Olkhon Region) with implications for the age, generation conditions and geodynamic settings of magmatism. The early Paleozoic granitoids of the Olkhon region are syncollisional formations produced from the gneiss-schistose substratum of the Olkhon metamorphic sequences. Pegmatoid granites and pegmatites of the Region were generated within a wide age range (458-390 Ma) and include different mineralogical and geochemical types. Amongst the Early Paleozoic granitoids, pegmatoid rocks are products of the collisional magmatism evolution and are similar to granites in terms of the mineral composition and distribution patterns of rare and rare earth elements. On the Olkhon island (Baikal lake) the pegmatite of the Tashkiney vein belong to the Be-Nb-Ta mineralogical-geochemical type demonstrating high contents of W, Sn U, Th and very low concentrations of Li and volatile components (F, B). In the Pryolkhonye area, vein pegmatite Iliksin is with Li, Be, Nb, Ta mineralization (lepidolite, vorobyevite, samarskite et al). The studied pegmatite veins are similar both by the profound negative Ba, Sr, Eu, and Zr anomalies. The zircons from the Tashkiney vein (390±5.0 Ma) and of the Iliksin vein (430.1±2.2 Ma, U-Pb isotope LA ICP MS metod) indicate the formation of pegmatite at the late post-collisional stage of magmatism in the Olkhon Region. As regard to mineralogical and geochemical characteristics, vein pegmatites with amazonite (Ainsky and Ulan-Nur) belong to the Li-F type. The tantalum mineralization, represented by microlites and minerals of the columbite-tantalite group is associated with the Ainsky amazonite pegmatite. As opposed to the Early Paleozoic syncollisional granitoids and pegmatoid formations, the middle Paleozoic vein bodies of pegmatites (Tashkiney, Iliksin, Ainsky, Ulan-Nur) are regarded as rare-metal pegmatites. In terms of geochemical characteristics, they are similar to the rare-metal pegmatoid granites and pegmatites of the intra-plate setting widespread in Mongolia and Transbaikalia. The rare-metal mineralization in the Olkhon region may be genetically related to the evolution of Be-Nb-Ta and Li-F types of the post-collisional granites and pegmatites.

In this paper, carbon nanotubes modified screen-printed electrode (CNTs/SPE) was prepared and the CNTs/SPE was employed for the electrochemical determination of antioxidant substance Chlorogenic acids (CGAs). A pair of well-defined redox peak of CGA was observed at the CNTs/SPE in 0.10 mol∙L^-1 acetic acid-sodium acetate buffer (pH 6.2) and electrode process is adsorption-controlled. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) method for the determination of CGA were proposed based on the CNTs/SPE. Under the optimal conditions, the proposed method exhibited linear ranges from 4.73×10^-7 to 4.45×10^-5 mol∙L^-1, the linear regression equation was Ipa(µA) = 4.1993 C (mol∙L^-1)+1.1039 (r = 0.9976) and the detection limit for CGA could reach 3.25×10^-6 mol∙L^-1. The recovery of matrine was 94.74~106.65% (RSD = 2.92%) in coffe beans. The proposed method is quick, sensitive, reliable, and can be used for the determination of CGA.

For the purpose of improve the sustainability of products sold in the EU, Digital Product Passports is a mandatory solution. These passports would systematically gather information about products, such as detailing the materials involved to aid recycling and remanufacturing efforts, or recording the emissions produced throughout the manufacturing process. The overall goal is the establishment of a circular economy in the EU. Current research on Digital Product Passports is focused on collating content for sector-specific applications. However, achieving sustainability goals through Digital Product Passports will require new methods and technical solutions for digital collaboration between supply chain participants, especially in the manufacturing sector. Collaborative work on Digital Product Passports requires trust and traceability in data and access management to ensure privacy over the data contained. One way to enable this securely and confidentially is through the use of blockchain technology, in which stored data cannot be concealed, which is key to the traceability of digital product data documentation. This paper therefore presents a concept for the implementation of generically applicable cross-industry blockchain-based digital product passports. To this end, generic supply chain processes have been abstracted and condensed into the architecture of smart contracts. Great attention is paid to the establishment of traceability as well as privacy through the selection of the blockchain technology Secret Network in combination with Gaia-X functionalities. An illustrative use case for digital product passports in manufacturing is used to demonstrate the applicability of the presented concept. In this use case information about the digital nameplate and carbon footprint is exchanged securely and confidentially in a multi-tenant supply chain network based on the Industry 4.0 infomation model of the Asset Administration Shell.

Tumor to stroma ratio is a highly debated prognostic factor in the management of several solid tumors and there is no universal agreement on its practicality. In our study we proposed to confirm or dismiss the hypothesis that a simple measurement of stroma quantity is an easy-to-use and strong prognostic tool. We have included 74 consecutive patients with colorectal cancer who underwent primary curative abdominal surgery. The tumors have been grouped into stroma-poor (stroma &lt;10%), medium-stroma (between 10 and 50%) and stroma-rich (over 50%). The proportion of tumor stroma ranged from 5% to 70% with a median of 25%. Very few, only 6.8% of patients had stroma-rich tumors, 4% stroma-poor tumors and 89.2%tumors with a medium quantity of stroma. The proportion of stroma, at any cut-off, had no statistically significant influence on the disease specific survival. This can be explained by the low proportion of stroma-rich tumors in our patient group and the inverse correlation of stroma proportion with tumor grade. The real-life proportion of stroma-rich tumors and the complex nature of the stroma-tumor interaction has to be further elucidated.

Negative temperature coefficient (NTC) materials are usually based on ceramic semiconductors and electrons are involved in their transport mechanism. A new type of NTC material, adequate for alternating current (AC) applications, is represented by zeolites. Indeed, zeolites are single-charge carrier ionic conductors with a temperature-dependent electrical conductivity. In particular, electrical transport in zeolites is due to the monovalent charge-balancing cations, like K⁺, capable of hopping between negatively charged sites in the aluminosilicate framework. Owing to the highly non-linear electrical behavior of the traditional electronic NTC materials, the possibility to have alternative types of materials, showing linearity in the electrical behavior, is very desirable. Among different zeolites, the natural clinoptilolite has been selected for investigating the NTC behavior since it is characterized by high zeolite content, convenient Si/Al atomic ratio, good mechanical strength, due to its compact microstructure, and low toxicity. Clinoptilolite has shown a rapid and quite reversible impedance change under heating, characterized by a linear dependence on temperature. X-ray diffraction (XRD) has been used to identify the natural zeolite, to establish all types of crystalline phases present in the mineral, and to investigate the thermal stability of these phases up to 150°C. X-ray photoelectron spectroscopy (XPS) analysis has been used for the chemical characterization of the natural clinoptilolite sample, providing important information on the cationic content and framework composition. In addition, since electrical transport takes place in the zeolite free-volume, a Brunauer–Emmett–Teller (BET) analysis of the mineral has been also performed.

(1) Background: Cardiorespiratory fitness (CRF) is a prognostic factor regarding long time morbidity and mortality. To assess CRF the well-known gold standard is cardiopulmonary exercise testing (CPET), which is a time consuming and expensive test. Therefore, alternative methods for routine evaluation of CRF are needed for the general population as well as for specific patient groups such as children and young adults with congenital heart disease. The Stair Climbing Test (SCT) is a simple and resource saving test reported in the current literature. This test is used in various settings to assess different health associated risk factors including cardiorespiratory fitness, muscular resilience, therapy effectiveness or pre- and postoperative morbidity and mortality.

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy lidar (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence at multiple spatial scales ≤ 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more evenly distributed by height and depth, respectively, as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5-4 meters, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Our study highlights the potential, and limitations, for fusing lidar and radar technologies to quantitatively couple above- and belowground ecosystem structure.

Several Lung diseases can result in lung damage structural changes, with lung transplantation as a only therapeutic option when the disease reaches an advanced progression, unfortunately, the success of lung transplantation is limited. In this context, lung bioengineering is considered a potential therapeutic alternative and the current approach is based on the use of the natural extracellular matrix (ECM) of the decellularized lung. The use of undifferentiated cells to seed an ECM can be a more practical strategy for lung bioengineering but the sterilization of the organ for this recellularization process is still a challenge. In this sense, Low-Level Laser Therapy (LLLT) can emerge as a potential treatment alternative. Therefore, the objective of this study was to verify if LLLT, can optimize lung recelularization with mesenchymal stem cells by cytokine modulation. For this, we decellularized lungs from C57BL/6 mice perfusing SDS 1% via pulmonary artery, sterilized with LLL (660nm, 100mW, 30s). Whole lung scaffolds were recellularized: (1) Recellularized Lung (2) Recellularized Lung + LLLT. Mesenchymal stem cells derived from human tooth pulp (DPSc) were seeded into lungs and incubated for 24 hours at 37ºC, 5% CO₂, in a bioreactor-like conditions, maintaining CPAP at 20cmH2O, 90% O2, and LLL at wavelength of 808nm, 100mW, 30s. Culture medium were analyzed at 24 hours. H&amp;E, immunostaining, SEM and ELISA assay were performed. We produced viable biological scaffolds absent of DNA content, preserving glycosaminoglycans and collagen I, III and IV, fibronectin, laminin and elastin and lung structure (SEM). The levels of IL-6 and IL-8 were stable during the 24 hours of culture. IFN-γ levels showed significant difference in the DPSc and DPSc+LLLT group in the 24-hour evaluation. The levels of IL-10 decreased after LLLT. These findings highlight LLLT's role in cytokine regulation and contamination prevention during lung recellularization with mesenchymal stem cells. Overall, these results demonstrated that LLLT's modulated cytokine levels and could prevent contamination during the lung recellularization process with mesenchymal stem cells, offering promise for enhanced therapeutic strategies in lung bioengineering.

The purpose of this paper is to assess the differential impacts of transformational and transactional leadership styles on employee performance during change initiatives within commercial banks in Sierra Leone. The research study utilised a cross-sectional survey design, and data was collected from 903 participants employed in the banking industry. The study used the structural equation model as the investigative instrument to examine the hypotheses. The findings reveal that transformational and transactional leadership styles demonstrate a strong bearing on employee performance, with the latter having a bigger influence. Organisational citizenship behaviour has a mediating effect between leadership styles and employee performance, while employee commitment does not act as a mediator between transformational leadership and employee performance, but it acts as a mediator between transactional leadership and employee performance. Commercial banks need to devise training programmes that will advance both leadership styles to arouse, energise, or inspire followers to display favourable behaviour and commitment to attain organisational. The paper makes an insightful contribution to the existing leadership literature by ascertaining the significance of leadership styles on performance and the role of commitment and organisational citizenship behaviour as mediators of the nexus between leadership styles and performance in the Sierra Leone banking industry.

We propose a neural-network-based watermarking method that introduces the quantized activation function that approximates the quantization of JPEG compression. Many neural-network-based watermarking methods have been proposed. Conventional methods have acquired robustness against various attacks by introducing an attack simulation layer between the embedding network and the extraction network. The quantization process of JPEG compression was replaced by the noise addition process in the attack layer of the conventional methods. In this paper, we propose a quantized activation function that can simulate the JPEG quantization standard as it is in order to improve the robustness against the JPEG compression. Our quantized activation function consists of several hyperbolic tangent functions and is applied as an activation function for neural networks. Our network was introduced in the attack layer of ReDMark proposed by Ahmadi et al. to compare it with their method. That is, the embedding and extraction networks had the same structure. We compared the usual JPEG compressed images and the images applying the quantized activation function. The results showed that a network with quantized activation functions can approximate JPEG compression with high accuracy. We also compared the bit error rate (BER) of estimated watermarks generated by our network with those generated by ReDMark. We found that our network was able to produce estimated watermarks with lower BERs than those of ReDMark. Therefore, our network outperformed the conventional method with respect to image quality and BER.

Current sampling methods for detecting the presence of the invasive freshwater hydrozoan Craspedacusta sowerbii rely mainly on visual confirmation of the medusa stage. Confirming the presence of the polyp stage is equally important to observing medusae since typical late summer/early fall occurrences or observations of medusae are sporadic though becoming more frequent. The polyp stage is important as it is the organism’s primary stage and is present throughout the year depending on water temperatures. Therefore, sampling methods for the polyp stage are commonly the collection of substrates such as rocks, plants or pieces of wood in a given body of water and can be cumbersome to examine. Based on preliminary culturing of the polyp stage on glass and plastic microscope slides in the lab, we designed a novel sampling methodology based on submerging 4 substrate types (small glass petri dishes, Hester-Dendy plates, plastic and glass microscope slides) to confirm the presence of C. sowerbii polyps in the field. We tested this method in various lakes in the Illinois-Indiana region (USA). The sampling method we designed was effective in that C. sowerbii polyps (and sometimes colonies) were found on both plastic and glass slides. While this method can be sufficient for detection of the polyp stage, it also shows significant potential for improvement; we highlight water flow and competition and predation from other organisms as significant factors influencing the collection of C. sowerbii polyps for future methodologies.

Sentiment analysis has become an important tool for understanding public opinion across languages and domains. Recently, there has been an increase in the number of studies on sentiment analysis in low-resource languages such as Kazakh. This is important to ensure that modern text analysis technologies are accessible to all users, regardless of their language background. The aim of the study is to create a sentiment analysis model for analyzing texts in Kazakh. As part of this work, we aim to use fine-tuning techniques on our own dataset for already existing models, thus improving their accuracy and efficiency for analyzing Kazakh language texts. This paper presents a manually collected dataset "KazIntTelCom" from the city information service 2GIS, consisting of user reviews, manually annotated by the authors taking into account the polarity of sentiment (i.e. negative positive or neutral). This dataset was used to fine-tune two pre-trained multi-lingual Transformer-based sentiment analysis models taken from the HuggingFace platform. The distillBERT and XLM-RoBERTa models were used for tuning. Also, the models were tested on the dataset "KazSAnDRA". The results show that accurate tuning even on a relatively small dataset gives a significant increase in performance, which is confirmed by an increase in the accuracy index by 20%-30%. In addition, false misses and false detections are analyzed, which allows us to identify directions for further improvement of the models. The contribution of this work, in addition to the dataset, is the analysis of model errors, which will help future developers to make more accurate settings of hyperparameters of training for sentiment analysis in Kazakh. These results are important for natural language processing and their adaptation to low-resource languages, promoting more inclusive and equitable access to modern analytical tools. Thus, this study demonstrates the effectiveness of the Transformers architecture for sentiment analysis in Kazakh and opens new opportunities for further model improvement.

Low carbon supply chain management (LCSCM) strategies are required in the Indian manufacturing industries due to rapidly growing energy usage for financial and environmental concerns. LCSCM technologies face a number of challenges that limit their adoption. Eleven hurdles were selected from the literature as well as the recommendations of business and academic experts. These barriers are defined by a number of factors, including a lack of information, financial worries, environmental concerns, and governmental limits, among others. In addition, efforts are being made to quantify the most optimal relevant barriers using Multi criteria decision making (MCDM) techniques such as interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL). MICMAC analysis is used to estimate the sensitivity and priority of barriers based on dependency power and driving power. One of these barriers is a needed factor; three are driving elements; four barriers are linked factors; and three are self-sufficient factors. The findings of this study can help academic specialists, industry representatives, and practitioners in their ongoing attempts to adopt 'LCSCM techniques' in Indian manufacturing industries. The model is appropriately explained and applies the link between the barriers.The objective of this paper is the Evaluation and selection of most influential of Barriers to Adopt Low Carbon Supply Chain Management (LCSCM) in the Indian Manufacturing Sector is interrelated.

Keywords: Vascular Malformation, Diode Laser, Angioma, Blue light, Conservative

Preventive Maintenance (PM) is a periodic maintenance strategy, which has great results for devices in extending their life, increasing productivity, and most importantly, help avoid unexpected breakdowns and their costly consequence. A preventive maintenance scheduling (PMS) is determining the time for carrying out PM, and it represents a sensitive issue in terms of impact on production if the time for the PM process is not optimally distributed. In this study, hybrid heuristic methods were used to solve the PMS problem, as genetic algorithm and Tabu research were adopted. The optimal solution was reached in a short time compared to previous studies in which optimal methods were used, integer programming and nonlinear integer programming. Also, sensitivity analysis was applied to measure the robustness and strength of the method used, where an optimal solution was obtained for all experiments and in record time. This method can be used for power plants in privet or public sectors, to generate an optimal PMS, to save money, and to avoid water or electricity cuts.