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Lignin, one of Earth’s most abundant biopolymers, is rich in phenolic and aliphatic functional groups, offering significant potential for chemical modification. Technical lignin, a byproduct of the kraft process, is produced in large quantities annually and can be used to enhance the properties of polymer matrices such as polypropylene (PP). PP, a widely used nonpolar polymer, suffers from low surface free energy, leading to poor adhesion properties. Combining PP with polar, renewable-source polymers like lignin can improve these properties. This study investigates the direct acetylation of kraft lignin (KL) to improve its dispersion in the PP matrix and enhance wettability and adhesion. The acetylation of KL was confirmed through FTIR and DSC analyses. PP and acetylated KL (AKL) were combined and processed via continuous extrusion. The blends’ thermal and mechanical properties, lignin dispersion, and wettability were evaluated. Additionally, PP and PP–lignin films were bonded to aluminized biaxially oriented polypropylene (BOPP) for peel tests. Results showed increased surface free energy and improved adhesion, particularly in samples with AKL due to better dispersion. This direct acetylation route significantly enhances PP’s surface free energy and adhesion, presenting a sustainable alternative to fossil-based materials and promoting the use of lignin, a renewable and low-cost polymer.

The aim of this study was to evaluate the isolated and associated use of the nematophagous fungi Pochonia chlamydosporia (isolate VC4) as an ovicide and Duddingtonia flagrans (isolate AC001) as a predator in the control of Taenia saginata eggs. Viable T. saginata eggs were obtained by dissecting mature proglottids from a specimen. For the experimental assay, four groups were formed in microtubes, as follows: (G1—T. saginata eggs/control); (G2—100 T. saginata eggs + VC4); (G3—100 T. saginata eggs + AC001); (G4—100 T. saginata eggs + VC4 + AC001). All the groups were stored in a B.O.D. incubation chamber at a temperature of 27 °C for 15 days and then the contents of the microtubes were analyzed using an optical microscope with a 40x objective. At the end of the assay the treated groups (G2 to G4) showed ovicidal activity (destruction of eggs) compared to the control group (G1). The highest ovicidal percentage was observed in group G2 (eggs + VC4), with 43.3%. In groups G3 and G4 (combination of fungal isolates), the ovicidal percentages were 25.7% and 25.6%, respectively. The results of this study shed light on a new possibility for the combined use of different species of nematophagous fungi, which could be used in the future for environmental biological control of T. saginata eggs.

The growth of renewables in public energy networks requires suitable strategies to assess the stable operation of the respective power electronic devices, e.g., inverters. Different assessment methods can be performed with regard to the available knowledge and the assessment objective, e.g., a specific frequency range or the input signal characteristics that are typically classified into small-signal and large-signal disturbances. This paper addresses the limits of the measurement-based small-signal stability analysis in the harmonic frequency range of commercially available single-phase inverters for photovoltaic applications. The harmonic stability is analyzed, and the results for a sinusoidal background voltage and distorted background voltages are assessed based on measurements. The measurements prove that even in the harmonic frequency range, the harmonic stability analysis can only provide a sufficient but not a necessary condition in terms of the statement towards an instable operation.

The anti-tumoral activity of somatostatin has been demonstrated in both animal experiments and human tumors. Clinical trials have reported conflicting results. We therefore hypothesized that somatostatin might have different effects in various hepatocellular carcinoma cells. Their clarification would possibly allow for the better selection of patients suitable for the optimal treatment results. We studied the mRNA and protein expression of TNF receptors and the TNFa-induced apoptosis using the HepG2 and the Hep3B human hepatocellular carcinoma cells after incubation with the somatostatin analog octreotide. RT-PCR, Western blot, and parameters associated with apoptosis (NF-kB nuclear translocation, P65 Ser536 and P65 Ser468 phosphorylation, DNA fragmentation) were assessed. Only TNFR1 was constitutively present in the two cell lines. Octreotide incubation led to an earlier reduction in TNFR1 mRNA and protein in HepG2 compared to Hep3B cells (1 h and 6–12 h, respectively). NF-kB translocation to the nucleus was induced by TNFa and was more prominent in Hep3B. Translocation was unaffected by octreotide. Serine phosphorylation was significantly induced by TNFa and was more evident in the Hep3B cells. TNFa-induced Ser536 phosphorylation was inhibited by octreotide only in the HepG2 cells. DNA fragmentation was not influenced by either octreotide or TNFa in the HepG2 cells, but TNFa induced fragmentation in the Hep3B cells (1.8-fold increase) verified by the TUNEL index (43 compared to 19 for the HepG2 cells). Octreotide and TNFa co-incubation induced apoptosis in the HepG2 cells (1.7-fold increase compared to controls) but inhibited apoptosis in the Hep3B cells. We conclude that: (1) octreotide reduced TNFR1 receptor expression in both cell lines, (2) parameters of apoptosis were differentially affected by octreotide in the two cell lines, and (3) this might be a partial explanation for the conflicting results of somatostatin analog treatment in human hepatocellular carcinoma trials.

This study investigates the practices and rules of Genoese gilding, drawing insights from a 16th-century manuscript containing regulations for gold leaf production. Employing X-ray and ion beam techniques, we quantitatively assess the manuscript’s gold leaf thickness without destructive sampling. Artisanal goldbeater-produced leaves of different thicknesses, applied with a guazzo or mordant technique, served as standards. Further analysis of samples with unknown thickness from the furniture of Palazzo Spinola di Pellicceria in Genoa (Italy) has confirmed the method’s applicability to practical cases. External beam Rutherford backscattering spectrometry (RBS) and particle-induced X-ray emission (PIXE) analyses were carried out using 3 MeV protons at the LABEC accelerator laboratory in Florence. A linear relationship between Gold Lα peak yield and leaf thickness, as measured by RBS, has been established for optimal calibration of portable or hand-held X-Ray fluorescence (XRF) instrumentation for in situ measurements. Moreover, the caratage of the gold foil preserved in the manuscript has been assessed.

Population growth, coupled with industrial and agricultural development, has resulted in increased demand for freshwater supply. For countries with scarce water resources, desalination constitutes the only viable solution to this problem. Reverse osmosis (RO) technology has become widely used as the membrane materials have been upgraded and the costs have been reduced. Nowadays, RO is the foremost technology for desalting different types of water such as seawater, brackish, and tap water. However, its design is critical since many parameters are involved in obtaining a good design. The high use of RO encourages the establishment of a procedure that facilitates the design process and helps in obtaining an optimum-performance RO desalination system. This paper presents a procedure divided into three parts: (1) classifying RO parameters; (2) choosing the parameters in a certain order and doing the calculation process through 12 steps; and (3) then inserting the selected parameters and the obtained values on RO System Analysis (ROSA) software. These points are then summarized by creating an algorithmic chart to follow during the design phase of the RO system using ROSA. An example on the proposed list is then taken to validate the procedure, and a comparison is conducted on choosing different values for the parameters. The results of this comparative study show that choosing different parameters affects the RO system productivity. Additionally, every design has a specific optimum set of parameters, which depends upon the design constraints set by the user.

Quito (Ecuador) has a history of mudflow events from ravines that pose significant risks to its urban areas. Located close to the Pichincha Volcanic Complex, on 31 January 2022, the northwest and central parts of the city were hit by a mudflow triggered by unusual rainfall in the upper part of the drainage, with 28 fatalities and several properties affected. This research focuses on the affected area from collector overflow to the end, considering sedimentological characteristics and behavior through various urban elements. This study integrates the analysis of videos, images, and sediment deposits to understand the dynamics and impacts of the mudflow using a multidisciplinary approach. The methodology includes verifying multimedia materials using free software alongside the Large-Scale Particle Image Velocimetry (LSPIV) to estimate the kinematic parameters of the mudflow. The affected area, reaching a maximum distance of 3.2 km from the overflow point, was divided into four zones for a detailed analysis, each characterized by its impact level and sediment distribution. Results indicate significant variations in mudflow behavior across different urban areas, influenced by topographical and anthropogenic factors. Multimedia analysis provided insights into the mudflow’s velocity and evolution as it entered urban areas. The study also highlights the role of urban planning and infrastructure in modifying the mudflow’s distribution, particularly in the Northern and Southern Axes of its path, compared with a similar 1975 event, seven times larger than this. It also contributes to understanding urban mudflow events in Quito, offering valuable insights for disaster risk management in similar contexts.

In an era marked by rapid technological progress, the pivotal role of Artificial Intelligence (AI) is increasingly evident across various sectors, including local governments. These governmental bodies are progressively leveraging AI technologies to enhance service delivery to their communities, ranging from simple task automation to more complex engineering endeavours. As more local governments adopt AI, it is imperative to understand the functions, implications, and consequences of these advanced technologies. Despite the growing importance of this domain, a significant gap persists within the scholarly discourse. This study aims to bridge this void by exploring the applications of AI technologies within the context of local government service provision. Through this inquiry, it seeks to generate best practice lessons for local government and smart city initiatives. By conducting a comprehensive review of grey literature, we analysed 262 real-world AI implementations across 170 local governments worldwide. The findings underscore several key points: (a) there has been a consistent upward trajectory in the adoption of AI by local governments over the last decade; (b) local governments from China, the US, and the UK are at the forefront of AI adoption; (c) among local government AI technologies, natural language processing and robotic process automation emerge as the most prevalent ones; (d) local governments primarily deploy AI across 28 distinct services; and (e) information management, back-office work, and transportation and traffic management are leading domains in terms of AI adoption. This study enriches the existing body of knowledge by providing an overview of current AI applications within the sphere of local governance. It offers valuable insights for local government and smart city policymakers and decision-makers considering the adoption, expansion, or refinement of AI technologies in urban service provision. Additionally, it highlights the importance of using these insights to guide the successful integration and optimisation of AI in future local government and smart city projects, ensuring they meet the evolving needs of communities.

Several factors contribute to the increase in irrigation demand: population growth, demand for higher value-added products, and the impacts of climate change, among others. High-quality water is essential for irrigation, so knowledge of water quality is critical. Additionally, water use in agriculture has been increasing in the last decades. Lack of water quality can cause drip clog, a lack of application uniformity, cross-contamination, and direct and indirect impacts on plants and soil. Currently, there is a need for more automated methods for evaluating and monitoring water quality for irrigation purposes, considering different aspects, from impacts on soil to impacts on irrigation systems. This work proposes a data-driven method to address this gap and implemented it in a case study in the PCJ river basin in Brazil. The methodology contains nine components and considers the main steps of the data lifecycle and the traditional machine learning workflow, allowing for automated knowledge extraction and providing important information for improving decision making. The case study illustrates the use of the methodology, highlighting its main advantages and challenges. Clustering different scenarios in three hydrological years (high, average, and lower streamflows) and considering different inputs (soil-related metrics, irrigation system-related metrics, and all metrics) helped generate new insights into the area that would not be easily obtained using traditional methods.

This paper reviews some recent contributions by the authors and their associates and highlights a few innovative ideas, which led them to address some hard combinatorial network routing and ordered optimisation problems. The travelling salesman, which is in the NP hard category, has been reviewed and solved as an index-restricted shortest connected graph, and therefore, it opens a question about its ‘NP Hard’ category. The routing problem through ‘K’ specified nodes and ordered optimum solutions are computationally demanding but have been made computationally feasible. All these approaches are based on the strategic creation and use of an alternative solution in that situation. The efficiency of these methods requires further investigation.

Background: Perivascular adipose tissue (PVAT) attenuation has emerged as a novel biomarker for identifying high-risk arterial plaques due to its association with inflammation. Recognizing the systemic nature of atherosclerosis and its link with major cardiovascular events in coronary disease, this study evaluated PVAT attenuation in the peripheral arteries using CT imaging to expand the understanding of its diagnostic and prognostic potential. Methods: a retrospective analysis of 53 consecutive patients who underwent CT angiography, examining PVAT density across five primary peripheral arterial segments. A 5 mm region of interest adjacent to the vascular wall was analyzed by two blinded readers, with reproducibility coefficients calculated to determine the reliability of the measurements. For the statistical analyses, mean values were derived from these measurements. The patients were stratified into four groups based on the degree of arterial stenosis: 70%. PVAT density comparisons between these groups were performed using the Kruskal–Wallis test and the pairwise Mann–Whitney U test with Holm–Bonferroni correction for multiple comparisons. Results: the Kruskal–Wallis test revealed statistically significant disparities in PVAT density across the categorically differentiated stenosis groups (p < 0.001), indicating an association between PVAT density and arterial stenosis severity. This association was especially pronounced in the external iliac, common femoral, superficial femoral, and popliteal arteries, where the p-values were consistently below 0.05. Subsequent pairwise analyses utilizing the Mann–Whitney U test with Holm–Bonferroni correction affirmed these findings, in particular for the external iliac, common femoral, superficial femoral and popliteal arteries (p < 0.05). Conclusions: our findings reinforce the correlation between increased PVAT density and the degree of arterial stenosis, supporting the clinical value of PVAT as a non-invasive biomarker for cardiovascular risk stratification and potentially guiding therapeutic interventions.

(1) Introduction: Coenzyme Q10 (CoQ10) is a component present in the transport chain of mitochondrial electrons with antioxidant property. Currently, there are limited studies which indicate the effects of its supplementation on Metabolic Syndrome (MetS) and Non-Alcoholic Fatty Liver Disease (NAFLD). (2) Objective: This work was conducted to determine the effects of CoQ10 supplementation in women with MetS and NAFLD. (3) Methodology: This double-blind randomized clinical-controlled trial was performed among 22 women with MetS and NAFLD. Patients were randomized into two groups: group A (n = 11), which received 200 mg/day of CoQ10; and group B (n = 11), which received a placebo medication for 12 weeks. The hepatic steatosis present in NAFLD, the volume of abdominal fat, and visceral fat volume were evaluated by Magnetic Resonance Imaging (MRI). Anthropometric, blood pressure, and marker serums that compound the MetS were also analyzed. (4) Results: A decrease in visceral fat volume (p = 0.02), abdominal circumference (p = 0.03/CI = 0.19–3.80), and increase in HDL-cholesterol (p = 0.01/CI = −9.80: −1.44) was observed in the CoQ10-supplemented group. We did not find significant changes in any of the other variables evaluated. (5) Conclusions: Supplementation with CoQ10 for 12 weeks, even if discreetly, brought some benefits for the supplemented group whereas no changes were observed in the control group.

Intelligent transportation and advanced mobility techniques focus on helping operators to efficiently manage navigation tasks in smart cities, enhancing cost efficiency, increasing security, and reducing costs. Although this field has seen significant advances in developing large-scale monitoring of smart cities, several challenges persist concerning the practical assignment of delivery personnel to customer orders. To address this issue, we propose an architecture to optimize the task assignment problem for delivery personnel. We propose the use of different cost functions obtained with deterministic and machine learning techniques. In particular, we compared the performance of linear and polynomial regression methods to construct different cost functions represented by matrices with orders and delivery people information. Then, we applied the Hungarian optimization algorithm to solve the assignment problem, which optimally assigns delivery personnel and orders. The results demonstrate that when used to estimate distance information, linear regression can reduce estimation errors by up to 568.52 km (1.51%) for our dataset compared to other methods. In contrast, polynomial regression proves effective in constructing a superior cost function based on time information, reducing estimation errors by up to 17,143.41 min (11.59%) compared to alternative methods. The proposed approach aims to enhance delivery personnel allocation within the delivery sector, thereby optimizing the efficiency of this process.

Over the last decades, the analysis of complex microbial communities by high-throughput sequencing of marker gene amplicons has become routine work for many research groups. However, the main challenges faced by scientists who want to make use of the generated sequencing datasets are the lack of expertise to select a suitable pipeline and the need for bioinformatics or programming skills to apply it. Here, we present MetaXplore, an interactive, user-friendly platform that enables the discovery and visualization of amplicon sequencing data. Currently, it provides a set of well-documented choices for downstream analysis, including alpha and beta diversity analysis, taxonomic composition, differential abundance analysis, identification of the core microbiome within a population, and biomarker analysis. These features are presented in a user-friendly format that facilitates easy customization and the generation of publication-quality graphics. MetaXplore is implemented entirely in the R language using the Shiny framework. It can be easily used locally on any system with R installed, including Windows, Mac OS, and most Linux distributions, or remotely via a web server without bioinformatic expertise. It can also be used as a framework for advanced users who can modify and expand the tool.

Since biodiversity is a multifaceted aspect of natural systems, several indices have been suggested to measure it. In this paper, we examined a number of well-known diversity indexes to see whether some performed better than others when applied to forest data. In order to reach this goal, we used data on basic forest variables (such as the diameters, heights, and volumes of trees) from forest plots to see if common diversity indices lead to the same conclusions about changes in biodiversity in a pairwise comparison (i.e., comparing the same region at two different times or two different regions at the same time). Out of a collection of 17 diversity indices, 8 of them exhibited robustness, indicating their constant ability to demonstrate either an increase or decrease in biodiversity over pairwise comparisons. However, it is important to note that the remaining seven diversity indices may yield inconsistent or inconclusive results, but only with regard to forest data, highlighting the complexity and nuances of measuring biodiversity with different sorts of data. In this review article, all 17 indices are presented, allowing the reader to choose which ones are most applicable to their particular dataset (genetic, econometric, sociometric, etc.).

The pathogenesis of acute and chronic pancreatitis has recently evolved as new findings demonstrate a complex mechanism operating through various pathways. In this review, the current evidence indicating that several mechanisms act in concert to induce and perpetuate pancreatitis were presented. As autophagy is now considered a fundamental mechanism in the pathophysiology of both acute and chronic pancreatitis, the fundamentals of the autophagy pathway were discussed to allow for a better understanding of the pathophysiological mechanisms of pancreatitis. The various aspects of pathogenesis, including trypsinogen activation, ER stress and mitochondrial dysfunction, the implications of inflammation, and macrophage involvement in innate immunity, as well as the significance of pancreatic stellate cells in the development of fibrosis, were also analyzed. Recent findings on exosomes and the miRNA regulatory role were also presented. Finally, the role of autophagy in the protection and aggravation of pancreatitis and possible therapeutic implications were reviewed.

Background: Despite the expanding use of orthopedic devices and the application of strict pre- and postoperative protocols, the elimination of postoperative implant-related infections remains a challenge. Objectives: To identify and assess the in vitro and in vivo properties of antimicrobial-, silver- and iodine-based implants, as well as to present novel approaches to surface modifications of orthopedic implants. Methods: A systematic computer-based review on the development of these implants, on PubMed and Web of Science databases, was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: Overall, 31 in vitro and 40 in vivo entries were evaluated. Regarding the in vitro studies, antimicrobial-based coatings were assessed in 12 entries, silver-based coatings in 10, iodine-based in 1, and novel-applied coating technologies in 8 entries. Regarding the in vivo studies, antimicrobial coatings were evaluated in 23 entries, silver-coated implants in 12, and iodine-coated in 1 entry, respectively. The application of novel coatings was studied in the rest of the cases (4). Antimicrobial efficacy was examined using different bacterial strains, and osseointegration ability and biocompatibility were examined in eukaryotic cells and different animal models, including rats, rabbits, and sheep. Conclusions: Assessment of both in vivo and in vitro studies revealed a wide antimicrobial spectrum of the coated implants, related to reduced bacterial growth, inhibition of biofilm formation, and unaffected or enhanced osseointegration, emphasizing the importance of the application of surface modification techniques as an alternative for the treatment of orthopedic implant infections in the clinical settings.

This review article aims to provide an updated and comprehensive overview of the latest trends in adult upper limb prostheses, specifically targeting various amputation levels such as transradial, transmetacarpal, transcarpal, and transhumeral. A systematic search was conducted across multiple databases, including IEEE Xplore, MDPI, Scopus, Frontiers, and Espacenet, covering from 2018 to 2023. After applying exclusion criteria, 49 scientific articles (33 patents and 16 commercial prostheses) were meticulously selected for review. The article offers an in-depth analysis of several critical aspects of upper limb prostheses. It discusses the evolution and current state of input control mechanisms, the number of degrees of freedom, and the variety of grips available in prostheses, all tailored according to the level of amputation. Additionally, the review delves into the selection of materials used in developing these prostheses and examines the progression of technology readiness levels. A significant focus is also placed on the evolution of prosthesis weight over the years for different amputation levels. Moreover, the review identifies and explores critical technological challenges and prospects in upper limb prostheses. Finally, the article culminates with a conclusion that encapsulates the key findings and insights on the advancements and ongoing developments in this field.

Canada has one of the most complex and rigorous drug approval and public reimbursement processes and is, unfortunately, one of the countries with the longest delays in drug access. To assess the overall impact of systemic delays in access to cancer therapy, a targeted literature review (TLR) was performed to identify studies associated with the clinical, economic, and quality of life impacts of delayed access to oncology drugs. Using MEDLINE/PubMed databases and snowballing, four unique records met the eligibility criteria. Results revealed that clinical outcomes were the most impacted by systemic delays in access to oncology drugs (e.g., life years lost, overall survival, and progression-free survival). The four articles retrieved by the TLR specifically illustrated that a substantial number of life years could potentially be saved by increasing systemic efficiency regarding the development, approval, and reimbursement processes of new drugs for advanced malignancies. It is imperative that initiatives are put in place to improve the performance and speed of Canadian drug regulatory and health technology assessment (HTA) processes, especially for new cancer therapeutics. The proposed solutions in this paper include better coordination between HTA and Canadian payers to harmonize coverage decisions, international collaborations, information sharing, and national standards for timeliness in oncology drug access.

Consumers are looking for safer and more natural food options that are produced through natural methods without using synthetic preservatives. They also desire extended shelf life for their food products. Several medicinal and aromatic plants species combine food, spice, aromatic, and medicinal recognized attributes. The essential oils from these plants contain a unique mixture of compounds specific to each plant, showing notable antioxidant and antimicrobial properties. Essential oils are used widely as they are environmentally friendly, non-toxic, and biodegradable substitutes for harsh chemical preservatives. Thyme and clove are aromatic plants commonly used in traditional gastronomy, particularly in meat-based recipes. The preservation effects of these essential oils on fresh meat have not been widely studied. Therefore, the aim of this study is to review the use of thyme and clove essential oils in meat preservation, with particular emphasis on their antioxidant properties to mitigate lipid and protein oxidation. Different strategies have been used to boost the effects of essential oils in foods, which include mixtures of essential oils, encapsulation and nanoemulsification techniques, with or without edible coatings. The final objective is to promote the wide use of essential oils for meat preservation, eventually in combination with other innovative approaches.

We, the QUARTET Collaboration, propose an experiment to measure the nuclear charge radii of light elements with up to 20 times higher accuracy. These are essential both for understanding nuclear physics at low energies, and for experimental and theoretical applications in simple atomic systems. Such comparisons advance the understanding of bound-state quantum electrodynamics and are useful for searching for new physics beyond the Standard Model. The energy levels of muonic atoms are highly susceptible to nuclear structure, especially to the mean square charge radius. The radii of the lightest nuclei (with the atomic number, Z=1,2) have been determined with high accuracy using laser spectroscopy in muonic atoms, while those of medium mass and above were determined using X-ray spectroscopy with semiconductor detectors. In this communication, we present a new experiment, aiming to obtain precision measurements of the radii of light nuclei 3≤Z≤10 using single-photon energy measurements with cryogenic microcalorimeters; a quantum-sensing technology capable of high efficiency with outstanding resolution for low-energy X-rays.

This research explores the thermal and mechanical properties enhancement in hollow concrete blocks by incorporating recycled expanded polystyrene (EPS) and crumb rubber (CR). Key thermal properties—including average thermal resistance (R¯), average thermal conductivity (λ¯), and average specific heat (Cp¯)—were analyzed, while mechanical properties were evaluated via compressive strength tests. Findings indicate that the addition of EPS and CR significantly improved thermal resistance, with specific heat and compressive strength remaining within acceptable thresholds. The optimal mixture of 35% EPS and 5% rubber by volume led to a remarkable 49.67% increase in thermal resistance compared to standard hollow blocks while still achieving a compressive strength (σ¯) around 7 MPa. These results classify the blocks as non-load-bearing, highlighting their potential for energy-efficient construction using sustainable materials. This research advances sustainable building materials by providing practical solutions to improve building performance in Lebanon.

A series of homoleptic rare earth (RE) complexes bearing phosphino-aryloxide ligands (1-RE, 2-La) has been prepared. The complexes have been characterised using multinuclear NMR and IR spectroscopy, X-ray crystallography and elemental analysis. Structural characterisation highlighted the different RE–P interactions as a result of differing Lewis acidity and ionic size across the series, hinting at the possibility of FLP-type activity. The potential reactivity of these complexes has been tested by reacting them with small molecules (H2, CO, CO2). A series of side-products (3-RE) has also been observed, isolated and characterised, featuring the incorporation of a phosphonium-aryloxide ligand.

Artificial Intelligence (AI) has changed how processes are developed, and decisions are made in the agricultural area replacing manual and repetitive processes with automated and more efficient ones. This study presents the application of deep learning techniques to detect and segment weeds in agricultural crops by applying models with different architectures in the analysis of images captured by an Unmanned Aerial Vehicle (UAV). This study contributes to the computer vision field by comparing the performance of the You Only Look Once (YOLOv8n, YOLOv8s, YOLOv8m, and YOLOv8l), Mask R-CNN (with framework Detectron2), and U-Net models, making public the dataset with aerial images of soybeans and beans. The models were trained using a dataset consisting of 3021 images, randomly divided into test, validation, and training sets, which were annotated, resized, and increased using the Roboflow application interface. Evaluation metrics were used, which included training efficiency (mAP50 and mAP50-90), precision, accuracy, and recall in the model’s evaluation and comparison. The YOLOv8s variant achieved higher performance with an mAP50 of 97%, precision of 99.7%, and recall of 99% when compared to the other models. The data from this manuscript show that deep learning models can generate efficient results for automatic weed detection when trained with a well-labeled and large set. Furthermore, this study demonstrated the great potential of using advanced object segmentation algorithms in detecting weeds in soybean and bean crops.

This study focused on the phenology of Coffea arabica var. Esperanza L4A5, an F1 interspecific hybrid obtained by crossing commercial varieties with wild genotypes from Ethiopia and Sudan. Most phenological studies on C. arabica have been conducted in traditional high-altitude regions, leaving a gap in the understanding of its behavior in non-traditional areas such as the Caribbean region of Costa Rica. To establish a baseline on the phenological behavior of the Esperanza L4A5 hybrid in this region, we conducted a four-year study examining the effects of different agroforestry associations: (1) Albizia saman; (2) Hymenaea courbaril and Erythrina poeppigiana; (3) Anacardium excelsum and Erythrina poeppigiana; and coffee plots under full sun. Additionally, the phenology of the coffee plants was evaluated under differentiated fertilizations (physical, chemical, and without fertilization), considering meteorological factors such as temperature, humidity, and rainfall. The observed variables included the development of floral nodes, pre-anthesis, anthesis, and fruiting stages. To analyze the relationships between environmental factors, tree cover, fertilization, and the phenological stages, we employed multiple linear regression (MLR), which revealed that both tree cover and physical and chemical fertilizations had significant effects on the presence of developed floral nodes and, consequently, on fruit production. Furthermore, the random forest (RF) model was applied to capture complex interactions between variables and to rank the importance of meteorological factors, tree cover, and fertilization practices. These analyses demonstrated that the Esperanza L4A5 hybrid exhibited viable phenological development under the atypical conditions of the Caribbean region of Costa Rica, suggesting its potential to adapt and thrive in non-traditional coffee-growing areas.

Integrating advanced technologies such as artificial intelligence (AI) with traditional agricultural practices has changed how activities are developed in agriculture, with the aim of automating manual processes and improving the efficiency and quality of farming decisions. With the advent of deep learning models such as convolutional neural network (CNN) and You Only Look Once (YOLO), many studies have emerged given the need to develop solutions to problems and take advantage of all the potential that this technology has to offer. This systematic literature review aims to present an in-depth investigation of the application of AI in supporting the management of weeds, plant nutrition, water, pests, and diseases. This systematic review was conducted using the PRISMA methodology and guidelines. Data from different papers indicated that the main research interests comprise five groups: (a) type of agronomic problems; (b) type of sensor; (c) dataset treatment; (d) evaluation metrics and quantification; and (e) AI technique. The inclusion (I) and exclusion (E) criteria adopted in this study included: (I1) articles that obtained AI techniques for agricultural analysis; (I2) complete articles written in English; (I3) articles from specialized scientific journals; (E1) articles that did not describe the type of agrarian analysis used; (E2) articles that did not specify the AI technique used and that were incomplete or abstract; (E3) articles that did not present substantial experimental results. The articles were searched on the official pages of the main scientific bases: ACM, IEEE, ScienceDirect, MDPI, and Web of Science. The papers were categorized and grouped to show the main contributions of the literature to support agricultural decisions using AI. This study found that AI methods perform better in supporting weed detection, classification of plant diseases, and estimation of agricultural yield in crops when using images captured by Unmanned Aerial Vehicles (UAVs). Furthermore, CNN and YOLO, as well as their variations, present the best results for all groups presented. This review also points out the limitations and potential challenges when working with deep machine learning models, aiming to contribute to knowledge systematization and to benefit researchers and professionals regarding AI applications in mitigating agronomic problems.

The objectives of the present work were the investigation of gastrointestinal parasitic infections in dogs in small ruminant farms in Greece, the elucidation of potential predictors for these infections and the description of practices related to administration of anthelmintics to dogs. This study was carried out in 444 small ruminant farms in Greece. Faecal samples were collected directly from the rectum of the dogs in the farms. The samples were processed by means of conventional parasitological techniques, specifically, a combined sedimentation flotation technique. There were dogs in 92.8% of the farms, with a median number of four dogs per farm. The following variables were associated with the presence of dogs in the farms: the presence of wild mammal predators near the farms, the increased daily period of farmers’ presence at the farm, goats as the livestock species at the farm and the management system applied in the farm. Helminth eggs were detected in samples from 72.6% of the farms. The main helminth eggs detected were those of hookworms (Uncinaria/Ancylostoma) and Toxocara canis, in 68.6% and 51.3% of the farms, respectively. In our multivariable analyses, an association emerged between the presence of canid predators near a farm and the detection of these helminths in faecal samples: in 76% and 60% of the samples, respectively, versus in 58% and 39% of the samples from farms with no canid presence. Of farmers with dogs, 16.0% reported that they omitted the administration of anthelmintics to the animals. In multivariable analysis, the semi-extensive or extensive management system applied in the farm, the lower annual milk production per animal and the lack of collaboration with a veterinary practice were the significant predictors for the omission of anthelmintic administration to the farm dogs. There was also a clear association in the omission of anthelmintic administration to the dogs and to the livestock on the farm. The most frequently administered anthelmintic was praziquantel, which was used in 93.6% of the farms.

(1) Background: Osteoarthritis (OA) is a serious chronic disease mostly affecting the knee joint. Despite the many efforts for developing strategies to predict and control Knee Osteoarthritis (KOA), the disease is on the rise. This paper describes the process for the creation of a simulation model, the Dynamic Knee Osteoarthritis Simulation (DYNAMIKOS) model, that captures the complex interrelationships of the risk factors for the development of KOA; (2) Methods: The DYNAMIKOS model will be based on the System Dynamics approach. The first step will be to develop a Causal Loop Diagram (CLD) model for the risk factors involved incorporating a series of Group Modeling Building (GMB) workshops with experts and stakeholders. Using data from a representative sample of KOA patients, the statistical approaches Exploratory Factor Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling (SEM) will be carried out. (3) Results: This study will develop a simulation System Dynamics model for the risk factors of KOA based on the results of CLD and SEM; (4) Conclusions: The proposed DYNAMIKOS model could be used for effectively analyzing the complex interrelationships among the multiple factors that constitute the spread of KOA. In this way, plausible prevention strategies could be implemented for effectively managing and leading the potential eradication of KOA.

The psychometric properties of the Malay Suicidal Behaviors Questionnaire-Revised (SBQ-R) need to be tested as it is increasingly utilized, and there is a lack of a brief, validated scale to examine suicidal behaviors in Malaysia. A total of 713 and 715 undergraduates answered the English and Malay SBQ-R, respectively. Exploratory factor analysis derived a one-factor solution, with a total explained variance of 58.0% accounted for by the four items. Confirmatory factor analyses supported the one-factor model for the Malay SBQ-R, with acceptable fit indices (χ2/df = 0.451, comparative and Tucker–Lewis fit indices = ≥1.000, standardized root mean square residual = 0.014, root mean square error of approximation = 0.000, and 90% CI [0.000, 0.083]). Measurement invariance was achieved when comparing the SBQ-R between the English and Malay versions, indicating that both versions are similar in Malaysian undergraduates. Convergent validity was established through a strong correlation between the Malay SBQ-R and the Malay Yatt Suicide Attitude Scale (r = 0.74; p < 0.001). Good internal consistency was achieved for both the English (α = 0.83; ω = 0.85) and Malay (α = 0.81; ω = 0.84) versions. The Malay SBQ-R has adequate validity and reliability for use in Malaysian undergraduates.

Heart failure is a complex syndrome and our understanding and therapeutic approach relies mostly on its phenotypic presentation. Notably, the heart is characterized as the most energy-consuming organ, being both a producer and consumer, in order to satisfy multiple cardiac functions: ion exchange, electromechanical coordination, excitation–contraction coupling, etc. By obtaining further knowledge of the cardiac energy field, we can probably better characterize the basic pathophysiological events occurring in heart disease patients and understand the metabolic substance changes, the relationship between the alteration of energy production/consumption, and hence energetic deficiency not only in the heart as a whole but in every single cardiac territory, which will hopefully provide us with the opportunity to uncover the beginning of the heart failure process. In this respect, using (a) newer imaging techniques, (b) biomedicine, (c) nanotechnology, and (d) artificial intelligence, we can gain a deeper understanding of this complex syndrome. This, in turn, can lead to earlier and more effective therapeutic approaches, ultimately improving human health. To date, the scientific community has not given sufficient attention to the energetic starvation model. In our view, this review aims to encourage scientists and the medical community to conduct studies for a better understanding and treatment of this syndrome.

Demand is high for small, lightweight, and power-dense machines. However, as power increases and size decreases, rejecting losses becomes more difficult. Many novel cooling systems have been developed, which have allowed machines to be made smaller while increasing power. This paper proposes a cooling system making use of soft magnetic composite (SMC) cores to improve cooling specifically in a high-speed axial-flux machine via the use of an integrated cooling channel in the SMC core. A series of experiments on a prototype machine are performed and the experimental data are used to determine a set of parameters for the FEA thermal model. Using the thermal FEA model, a comparison is completed with a traditional closed cooling system using laminated steels and an attached cooling plate.The SMC machine is then simulated at speeds up to 160 krpm and currents up to 8 A. To achieve the same coil temperature between the two designs, the laminated steel model required 4 MPa contact pressure at 10 krpm and 5 MPa contact pressure at 20 krpm. At the same time, the novel design removed approximately 20% more heat per shear air gap surface area and approximately 15% more heat per total machine surface area than the version with the attached cooling plate. Extending the operating range of the model to 160 krpm demonstrated that the maximum temperature rise remained below 180 °C.

Conventional mineral fertilization (CMF) is a common practice in infertile sugarcane-cultivated tropical soils, increasing production costs and environmental concerns. Combining CMF with composted sewage sludge (CSS) could be a sustainable strategy. We aim to evaluate changes in soil chemical properties, macro- and micronutrient concentrations in the soil surface (Ap1; 0–25 cm) and subsurface (Ap2; 25–50 cm) horizons, after CSS application with or without CMF in sugarcane cultivation (first and second ratoon cane). Eleven treatments, featured by CSS increase rates and mixed with CMF at different concentrations, were tested in the first ratoon; during the second, the CSS residual effect was evaluated. Applying CSS in sugarcane-cultivated soils, improved the following: (i) soil organic matter, pH, the sum of bases, cation-exchange capacity, and base saturation; (ii) overall nutrient concentrations (P, K, Ca, Mg, B, Cu, and Zn). The treatments showing the best performances were those with 5.0 Mg ha−1 of CSS. Composted sewage sludge has the potential for use as an organic natural fertilizer reducing the need for CMF. When applied in infertile tropical soils, additional positive effects can be achieved, such as decreasing production costs and providing socio-economic benefits.

Analyzing water quality variations is essential for the allocation of water to different uses and for applying remedial measures. Thessaly Plain was extremely fertile, and up until the early 20th century, the area was a breadbasket for Greece. The highly important for the national agricultural production, albeit severely degraded Pinios River, has been assessed for its chemical–physicochemical (C-P) status. The research was based on the results of the national monitoring program for the years 2018–2020, considering 218 seasonal samples. A total of 39% of the total samples and 70% of the 30 monitoring stations revealed a lower-than-good C-P status based on Water Framework Directive (2000/60/EC) boundaries. The exceedances are attributed predominately to elevated phosphate, total phosphorous, and nitrate concentrations. Exceptionally, the Pinios River seems to be mainly affected by point sources of organic pollution and secondarily by agricultural return flows and drainage processes, whereas dominant mineralization and nitrification processes control the concentration and type of nitrogen and phosphorus compounds. The coronavirus lockdown seems not to have affected aquatic quality significantly, whereas the improvement of C-P status at the river outflow via dilution by local mountain springs is threatened by an ongoing dry spell affecting the country. Within the upcoming river basin management plans, prompt remediation measures in the Pinios basin should target point sources of pollution and control agrochemicals, particularly focusing on adaptation strategies for extreme weather events.

Current language models have achieved remarkable success in NLP tasks. Nonetheless, individual decoding methods face difficulties in realizing the immense potential of these models. The challenge is primarily due to the lack of a decoding framework that can integrate language models and decoding methods. We introduce DecoStrat, which bridges the gap between language modeling and the decoding process in D2T generation. By leveraging language models, DecoStrat facilitates the exploration of alternative decoding methods tailored to specific tasks. We fine-tuned the model on the MultiWOZ dataset to meet task-specific requirements and employed it to generate output(s) through multiple interactive modules of the framework. The Director module orchestrates the decoding processes, engaging the Generator to produce output(s) text based on the selected decoding method and input data. The Manager module enforces a selection strategy, integrating Ranker and Selector to identify the optimal result. Evaluations on the stated dataset show that DecoStrat effectively produces a diverse and accurate output, with MBR variants consistently outperforming other methods. DecoStrat with the T5-small model surpasses some baseline frameworks. Generally, the findings highlight DecoStrat’s potential for optimizing decoding methods in diverse real-world applications.

Probing the chemical profiles and biological activities of medicinal plants is important for the discovery of new potent therapeutic products. Our study deciphers the chemical composition of the essential oils (EOs) obtained from three different flowers of Lantana camara and evaluates their antioxidant and anticancer activities. This work represents the first study of EOs obtained from this plant and is based particularly on the difference in flower color. In addition, no other reports dealing specifically with the antitumor effects of such flower-derived EOs have been described in the literature. The collected flowers, white, pink, and orange, were extracted by hydrodistillation to yield EO1, EO2, and EO3 respectively. Gas chromatography–mass spectroscopy was primarily employed to identify the existing volatile compounds in the samples. Their antioxidant activities were screened through both DPPH (2,2-diphenyl-1-picrylhydrazyl) scavenging assays and FRAP (ferric-reducing antioxidant power) assays. The antiproliferative effects were evaluated on two distinct breast cancer cell lines, MCF-7 and MDA-MB-231, and compared to a normal human breast cell line, MCF-10A, using an MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium) assay. All EOs showed notable antioxidant potential attributed to the active phytochemical compounds, with results being supported by a positive correlation between such activity and the total phenolic and flavonoid content. The most eminent, EO1, revealed a selective dose-dependent antiproliferative effect in both breast cancer cell lines, thus reflecting its potent role as an anticancer agent. We suggest that this highly selective activity is associated with the presence of bicyclogermacrene and epi-bicyclosesquiphellandrene in its chemical composition.

Perovskite solar cells (PSCs) have been on the forefront of advanced research for over a decade, achieving constantly increasing power conversion efficiencies (PCEs), while their route towards commercialization is currently under intensive progress. Towards this target, there has been a turn to PSCs that employ a carbon electrode (C-PSCs) for the elimination of metal back contacts, which increase the cost of corresponding devices while at the same time have a severe impact on their stability. Chalcogenides are chemical compounds that contain at least one chalcogen element, typically sulfur (S), selenium (Se), or tellurium (Te), combined with one metallic element. They possess semiconducting properties and have been proven to have beneficial effects when incorporated in a variety of solar cell types, including dye sensitized solar cells (DSSCs), quantum dot sensitized solar cells (QDSSCs), and Organic Solar Cells (OSCs), either as interlayers or added in the active layers. Currently, an increasing number of studies have highlighted their potential for achieving high-performing and stable PSCs. In this review, the most promising results of the latest studies regarding the implementation of chalcogenides in PSCs with a carbon electrode are presented and discussed, merging two research trends that are currently on the spotlight of solar cell technology.

Background: It has been demonstrated that the concept of infinite absorption time, associated with the absorption rate constant, which drives a drug’s gastrointestinal absorption rate, is not physiologically sound. The recent analysis of oral drug absorption data based on the finite absorption time (F.A.T.) concept and the relevant physiologically based finite-time pharmacokinetic (PBFTPK) models developed provided a better physiologically sound description of oral drug absorption. Methods: In this study, we re-analyzed, using PBFTPK models, seven data sets of ketoprofen, amplodipine, theophylline (three formulations), and two formulations (reference, test) from a levonorgestrel bioequivalence study. Equations for one-compartment-model drugs, for the estimation of fraction of dose absorbed or the bioavailable fraction exclusively from oral data, were developed. Results: In all cases, meaningful estimates for (i) the number of absorption stages, namely, one for ketoprofen and the levonorgestrel formulations, two for amlodipine, the immediate-release theophylline formulation, and the extended-release Theotrim formulation, and three for the extended-release Theodur formulation, (ii) the duration of each absorption stage and the corresponding drug input rate, and (iii) the total duration of drug absorption, which ranged from 0.75 h (ketoprofen) to 11.6 h for Theodur were derived. Estimates for the bioavailable fraction of ketoprofen and two theophylline formulations exhibiting one-compartment-model kinetics were derived. Conclusions: This study provides insights into the detailed characteristics of oral drug absorption. The use of PBFTPK models in drug absorption analysis can be leveraged as a computational framework to discontinue the perpetuation of the mathematical fallacy of classical pharmacokinetic analysis based on the absorption rate constant as well as in the physiologically based pharmacokinetic (PBPK) studies and pharmacometrics. The present study is an additional piece of evidence for the scientific and regulatory changes required to be implemented by the regulatory agencies in the not-too-distant future.

The functions of bacterial plasmid-encoded toxin–antitoxin (TA) systems are unambiguous in the sense of controlling cells that fail to inherit a plasmid copy. However, its role in chromosomal copies is contradictory, including stress-response-promoting fitness and antibiotic treatment survival. A hybrid pathogenic Escherichia coli strain may have the ability to colonize distinct host niches, facing contrasting stress environments. Herein, we determined the influence of multiple environmental stress factors on the bacterial growth dynamic and expression profile of previously described TA systems present in the chromosome of a hybrid atypical enteropathogenic and extraintestinal E. coli strain. Genomic analysis revealed 26 TA loci and the presence of five type II TA systems in the chromosome. Among the tested stress conditions, osmotic and acid stress significantly altered the growth dynamics of the hybrid strain, enhancing the necessary time to reach the stationary phase. Using qPCR analyses, 80% of the studied TA systems were differentially expressed in at least one of the tested conditions, either in the log or in the stationary phase. These data indicate that type II TA systems may contribute to the physiology of pathogenic hybrid strains, enabling their adaptation to different milieus.

We evaluated the surgical stress response of dogs undergoing three ovariohysterectomy (OVH) techniques. Twenty-nine healthy females were allocated into groups: celiotomy and ligature (CelioSut), celiotomy and bipolar energy (CelioBip), and a video-assisted technique using two portals and bipolar energy (VidBip). Clinical evaluation was performed, and the following blood analyses were determined: acute phase proteins (C-reactive protein and haptoglobin), white blood cell counting (WBC), and biomarkers of oxidative status. The VidBip required more time despite a smaller incision, lower heart rate, and earlier feeding and urination. All groups had high white blood cells counts; the C-reactive protein (CRP) levels peaked at 6 and 12 h in all groups and was higher in the CelioBip and VidBip groups compared to CelioSut; haptoglobin concentrations peaked at 48 h in all groups and increased in dogs of the CelioSut group. Trolox equivalent antioxidant capacity, ferric reducing ability of plasma, cupric reducing antioxidant capacity, and advanced oxidation protein were not significantly different among the groups or time points. Total thiol concentrations were lower in CelioBip and CelioSut groups. All surgical techniques induced an inflammatory and oxidative stress response, but the video-assisted technique produced early clinical recovery. The bipolar device produces fewer disturbances than suspensory ligament rupture and ligature.

Extracellular vesicles (EVs) are bilayer vesicles released by cells in the microenvironment of the liver including parenchymal and non-parenchymal cells. They are the third important mechanism in the communications between cells, besides the secretion of cytokines and chemokines and the direct cell-to-cell contact. The aim of this review is to discuss the important role of EVs in viral liver disease, as there is increasing evidence that the transportation of viral proteins, all types of RNA, and viral particles including complete virions is implicated in the pathogenesis of both viral cirrhosis and viral-related hepatocellular carcinoma. The biogenesis of EVs is discussed and their role in the pathogenesis of viral liver diseases is presented. Their use as diagnostic and prognostic biomarkers is also analyzed. Most importantly, the significance of possible novel treatment strategies for liver fibrosis and hepatocellular carcinoma is presented, although available data are based on experimental evidence and clinical trials have not been reported.

The intestinal microbiota is closely related to liver diseases via the intestinal barrier and bile secretion to the gut. Impairment of the barrier can translocate microbes or their components to the liver where they can contribute to liver damage and fibrosis. The components of the barrier are discussed in this review along with the other elements of the so-called gut–liver axis. This bidirectional relation has been widely studied in alcoholic and non-alcoholic liver disease. However, the involvement of microbiota in the pathogenesis and treatment of viral liver diseases have not been extensively studied, and controversial data have been published. Therefore, we reviewed data regarding the integrity and function of the intestinal barrier and the changes of the intestinal microbioma that contribute to progression of Hepatitis B (HBV) and Hepatitis C (HCV) infection. Their consequences, such as cirrhosis and hepatic encephalopathy, were also discussed in connection with therapeutic interventions such as the effects of antiviral eradication and the use of probiotics that may influence the outcome of liver disease. Profound alterations of the microbioma with significant reduction in microbial diversity and changes in the abundance of both beneficial and pathogenic bacteria were found.

Identifying potential system attacks that define security requirements is crucial to building secure cyber systems. Moreover, the attack frequency makes their subsequent analysis challenging and arduous in cyber–physical systems (CPS). Since CPS include people, organisations, software, and infrastructure, a thorough security attack analysis must consider both strategic (social and organisational) aspects and technical (software and physical infrastructure) aspects. Studying cyberattacks and their potential impact on internal and external assets in cyberspace is essential for maintaining cyber security. The importance is reflected in the work of the Swedish Civil Contingencies Agency (MSB), which receives IT incident reports from essential service providers mandated by the NIS directive of the European Union and Swedish government agencies. To tackle this problem, a multi-realm security attack event monitoring framework was proposed to monitor, model, and analyse security events in social(business process), cyber, and physical infrastructure components of cyber–physical systems. This paper scrutinises security attack patterns and the corresponding security solutions for Swedish government agencies and organisations within the EU’s NIS directive. A pattern analysis was conducted on 254 security incident reports submitted by critical service providers. A total of five critical security attacks, seven vulnerabilities (commonly known as threats), ten attack patterns, and ten parallel attack patterns were identified. Moreover, we employed standard mitigation techniques obtained from recognised repositories of cyberattack knowledge, namely, CAPEC and Mitre, in order to conduct an analysis of the behavioural patterns

Currently, there is significant interest in developing algorithms for processing electrodermal activity (EDA) signals recorded during sleep. The interest is driven by the growing popularity and increased accuracy of wearable devices capable of recording EDA signals. If properly processed and analysed, they can be used for various purposes, such as identifying sleep stages and sleep-disordered breathing, while being minimally intrusive. Due to the tedious nature of manually scoring EDA sleep signals, the development of an algorithm to automate scoring is necessary. In this paper, we present a novel scoring algorithm for the detection of EDA events and EDA storms using signal processing techniques. We apply the algorithm to EDA recordings from two different and unrelated studies that have also been manually scored and evaluate its performances in terms of precision, recall, and F1 score. We obtain F1 scores of about 69% for EDA events and of about 56% for EDA storms. In comparison to the literature values for scoring agreement between experts, we observe a strong agreement between automatic and manual scoring of EDA events and a moderate agreement between automatic and manual scoring of EDA storms. EDA events and EDA storms detected with the algorithm can be further processed and used as training variables in machine learning algorithms to classify sleep health.

Prostate cancer is a common and life-altering condition among Canadian men, yet little is known about how follow-up care is provided to those who have completed treatment. Despite improving survival rates, survivors experience ongoing needs and are often not provided with support to manage them. This study sought to investigate the post-treatment experiences and needs of prostate cancer survivors and to determine if and how these needs are being met. Using a qualitative description design, prostate cancer survivors who had completed treatment took part in semi-structured interviews. The interviews were recorded and analyzed thematically. The participants experienced varying levels of satisfaction with their follow-up care. While primary care providers played significant roles, continuity of care and specialist involvement varied. Most participants felt unprepared to manage the long-term effects of their cancer due to a lack of information and resources from their healthcare providers. Instead, participants turned to their peers for support. Ongoing physical and psychosocial needs went unmet and had significant impacts on their daily lives. Participants felt that support for these issues should be automatically integrated into their follow-up care. In summary, this study revealed the importance of integrated, patient-centered follow-up care for prostate cancer in Atlantic Canada.

The pathogenesis of inflammatory bowel disease (IBD) implicates several interconnecting factors. Immunity and external factors interact, and most aspects are still under investigation. Autophagy and apoptosis are two critical pathways that decide the fate of the individual cells of the intestinal mucosa. Experimental and clinical data indicate that the two are closely interconnected and usually mutually exclusive. However, despite the abundant information on their role, very limited translation into therapeutic application has been seen during recent years. In this review, research on these two pathways is presented. After a general overview of autophagy and apoptosis, their association with IBD, including the important mitophagy and ferroptosis, is discussed. The influence of autophagy- and apoptosis-related genes is also discussed. Finally, the interplay of autophagy and apoptosis in IBD is presented and the implications for treatment applications are examined. It is shown that dysregulated autophagy leads to increased apoptosis of enterocytes and impairs the tight junction proteins of the protective intestinal barrier. Dysregulated autophagy also induces the downregulation of lysozyme and the other antimicrobial proteins’ production. Mucus production by the goblet cells is also reduced due to defective autophagy and increased apoptosis.

Despite recent advancements in prosthetic technology, lower-limb amputees often remain limited to passive prostheses, which leads to an asymmetric gait and increased energy expenditure. Developing active prostheses with effective control systems is important to improve mobility for these individuals. This study presents a machine-learning-based approach to classify five distinct locomotion tasks: ground-level walking (GWL), ramp ascent (RPA), ramp descent (RPD), stairs ascent (SSA), and stairs descent (SSD). The dataset comprises fused electromyographic (EMG) and inertial measurement unit (IMU) signals from twenty non-amputated and five transtibial amputated participants. EMG sensors were strategically positioned on the thigh muscles, while IMU sensors were placed on various leg segments. The performance of two classification algorithms, support vector machine (SVM) and long short-term memory (LSTM), were evaluated on segmented data. The results indicate that SVM models outperform LSTM models in accuracy, precision, and F1 score in the individual evaluation of amputee and non-amputee datasets for 80–20 and 50–50 data distributions. In the 80–20 distribution, an accuracy of 95.46% and 95.35% was obtained with SVM for non-amputees and amputees, respectively. An accuracy of 93.33% and 93.30% was obtained for non-amputees and amputees by using LSTM, respectively. LSTM models show more robustness and inter-population generalizability than SVM models when applying domain-adaptation techniques. Furthermore, the average classification latency for SVM and LSTM models was 19.84 ms and 37.07 ms, respectively, within acceptable limits for real-time applications. This study contributes to the field by comprehensively comparing SVM and LSTM classifiers for locomotion tasks, laying the foundation for the future development of real-time control systems for active transtibial prostheses.

Wild edible plants have attracted increasing interest from researchers because of their richness in biologically active phytochemicals. These are found to be a potential remedy for oxidative-stress-mediated diseases such as diabetes mellitus. In this study, total phenol, total terpene, and total flavonoid content as well as antioxidant and antidiabetic activities of Scorzonera phaeopappa Boiss from Lebanon were determined. Using dichloromethane, dichloromethane ammonia, methanol, acetone, and ethanol, extracts were prepared from the edible leaves. The antioxidant activity and the antidiabetic activity were determined by 2,2-diphenyl-1-picrylhydrazyl scavenging, Fe2+-chelating and α-amylase/α-glucosidase inhibitory assays, respectively. Dichloromethane ammonia was found to have the highest extraction capacity on phenols (2.73 mg GAE /100 mg extract) and terpenes (232.42 mg LE/100 mg extract). Methanol was found to have the highest extraction capacity on total flavonoids (63.05 mg QE/100 mg extract). The methanol extract exhibited the highest DPPH scavenging activity (IC50 0.07 mg/mL) and the highest chelating activity as compared to other extracts (0.08 mg/mL, chelating activity 50%). The acetone extract was two times more active than acarbose against α-amylase enzyme and was the most active against α-glucosidase (6.3 mg/mL). Significant positive correlations were observed between total phenol content and α-glucosidase inhibitory assay and total terpene content and α-glucosidase inhibitory assay.

The expression of estrogen receptors (ERs) in breast cancer (BC) represents a strong prognostic and predictive biomarker and directs therapeutic decisions in early and advanced stages. ER-low-positive BC, defined by the immunohistochemical (IHC) expression of ERs from 1% to 9%, constitutes a distinct subset of total BC cases. Guidelines recommend that a low expression of ERs be reported in pathology reports since the benefit of endocrine therapy in patients with ER-low-positive BC is uncertain. Recently, several cohorts, mostly of a retrospective nature, have been published, reporting the clinicopathological characteristics and outcomes of ER-low-positive BC. However, the majority of the data focus on early-stage BC and the use of (neo)adjuvant therapy, and there is a significant lack of data regarding metastatic ER-low-positive BC. Further factors, including tumor heterogeneity as well as the potential loss of ER expression due to endocrine resistance, should be considered. Including patients with ER-low-positive BC in clinical trials for triple-negative breast cancer (TNBC) might improve the understanding of this entity and allow novel therapeutic approaches. The design and conduction of randomized clinical trials regarding this subgroup of patients are greatly anticipated.

Background/Objectives: Fracture-related infections (FRIs) are a significant complication in conflict zones, where limited resources and damaged infrastructure complicate orthopedic care. Methods: This study retrospectively reviews the management of FRIs during medical missions to Gaza from April to July 2024. Results: Among 135 patients treated for war-related fractures, 30% were identified with suspected FRIs, which were primarily following explosive injuries. Contributing factors to the high incidence of infection included malnutrition, poor sanitation, and the scarcity of sterile surgical supplies. The absence of standard infection control measures further complicated treatment. Conclusions: These findings highlight the critical need for a comprehensive approach that incorporates infection prevention, sustainable healthcare planning, and quality assurance tailored to the realities of conflict zones. The study underscores the importance of international support to ensure the availability of essential medical supplies and to develop effective, context-specific strategies for infection management. By applying these insights, healthcare providers can improve patient outcomes and reduce the burden of FRIs in resource-limited settings affected by conflict.

The genetic wealth of range-restricted species is threatened by human activities such as habitat fragmentation or alteration. This research focused on the genotype effect in sexual propagation with freshly collected seeds of vulnerable local endemic plants in Crete, namely, Campanula pelviformis and Petromarula pinnata (Campanulaceae), which can be sustainably utilized for agro-alimentary, medicinal, and ornamental purposes. The morphological characteristics of seed length, width, and weight of freshly collected seeds from five wild-growing populations of C. pelviformis and seven wild-growing populations of P. pinnata from lowlands (500 m) altitudes were measured and subjected to germination experiments at four incubation temperature treatments (10, 15, 20, and 25 °C). The effects of temperature, genotype, and their interactions were statistically significant for seed germination, with the results similar to those of previous studies on stored seeds of the same populations. Freshly collected seeds of both species germinated best at incubation temperatures of 10 °C and 15 °C (>68.13% for all population of C. pelviformis and >80.63% for six out of seven populations of P. pinnata), while significant differences were detected among genotypes for both species at each incubation temperature and among genotypes, even from similar altitudes. A statistically significant effect of altitude on germination percentages was observed at an incubation temperature of 20 °C between lowland and semi-mountainous genotypes for both species. The data produced in this study may enhance conservation efforts and lead to species-specific information that can be exploited in the future for their introduction as novel multi-purpose crops.