C-C motif chemokine receptor-8 (CCR8) belongs to class A of G protein-coupled receptors (GPCRs). CCR8 interacts with the specific chemokine ligand CCL1/I-309 in humans, which is produced by various cells, including tumor-associated macrophages and regulatory T cells (Treg). CCR8 is highly expressed on Treg and T-helper 2 (T_H2) cells recruited to the inflammation site and is implicated in allergy, asthma, and cancer progression. The CCR8⁺Treg has been suggested to be an important regulator in the immunosuppressive tumor microenvironment (TME); therefore, it has been desired to develop sensitive monoclonal antibodies (mAbs) for CCR8. This study developed a specific mAb for human CCR8 (hCCR8), which is useful for flow cytometry by employing the Cell-Based Immunization and Screening (CBIS) method. The established anti-hCCR8 mAb, C₈Mab-21, (mouse IgM, kappa) reacted with hCCR8-overexpressed Chinese hamster ovary-K1 (CHO/hCCR8) cells, TALL-1 (acute T lymphoblastic leukemia), CCRF-HSB2 (human T-lymphoblastic leukemia), and natural killer cells, which express endogenous hCCR8 by flow cytometry. Furthermore, C₈Mab-21 demonstrated a moderate binding affinity for CHO/hCCR8 and TALL-1 with a dissociation constant of 6.5×10^-8 M and 2.0×10^-8 M, respectively. C₈Mab-21, which was established by the CBIS method, could be a useful tool for analyzing the hCCR8-related biological response using flow cytometry.

Antibody light chains form amyloid fibrils that lead to progressive tissue damage in amyloid light chain (AL) amyloidosis. The properties of each patient’s unique light chain appear to determine its propensity to form amyloid. One factor is N-glycosylation, which is more frequent in amyloid-associated light chains than in light chains from the normal immune repertoire. However, the mechanisms underlying this association are unknown. Here, we investigate the frequency and position within the light chain sequence of the N-glycosylation sequence motif, or sequon. Monoclonal light chains from AL amyloidosis and multiple myeloma were identified from the AL-Base repository. Polyclonal light chains were obtained from the Observed Antibody Space resource. Sequons are enriched among AL-associated light chains derived from a subset of precursor germline genes. Sequons are observed at multiple positions, which differ between the two types of light chains, κ and λ, but are similar between light chains from AL amyloidosis and multiple myeloma. Positions of sequons map to residues with surface-exposed sidechains that are compatible with the folded structures of light chains. Sequons within κ light chains are predominantly observed in framework region 3. Sequons within λ light chains are mainly located in complementarity determining region 3, at residues near the interfaces with light or heavy chain partners in homodimeric free light chains or antibodies, respectively. We suggest that N-glycosylation of λ light chains may lead to decreased stability of protein complexes, thus promoting unfolding that can lead to aggregation. Within the known structures of λ AL amyloid fibrils, many residues where sequons are observed are buried, inconsistent with N-glycosylation. Overall, there is no clear structural rationale for why N-glycosylation of κ light chains is associated with amyloidosis. Better understanding of the roles of N-glycosylation in AL amyloidosis is required before it can be used as a marker for disease risk.

The Paralympic movement leaders, sporting mega-event organizers, and para-athletes in Brazil and elsewhere made frequent claims about the potential of the Paralympics to raise disability rights awareness and generate change in society’s perceptions of disabled people. However, how disabled people themselves view the Paralympics and their outcomes is insufficiently explored in the media and academic literature. This article has a two-fold purpose: first, to explore the views and perceptions of disabled Brazilians regarding the societal change claims made about the Rio 2016 Paralympics; and second, to problematize these claims of lasting societal change through the lens of critical disability theory. The online qualitative survey conducted a year after the Rio mega-event explored the following issues: a) attitudes of broader society towards disabled people; b) disability sport as a tool for social inclusion and equality; c) para-athletes’ visibility and the broader challenges; d) images of disabled people in the Paralympic coverage; and e) outcome of media’s attention for disabled people in general. The main argument is that realizing the Paralympic legacy promises is more complex than the Paralympic movement leaders and the event organizers acknowledge and that the social change legacies are the responsibility of the larger community long after the Games are over.

Psychedelics have recently (re)emerged as therapeutics of high potential for multiple mental health conditions, including substance use disorders (SUDs). Despite early mid-20th century anecdotal reports and pilot studies demonstrating the possibility of these substances in efficaciously treating conditions such as alcohol and opioid use disorders, legal restrictions and social stigma have historically hindered further research into this area. Nevertheless, concurrent with the rise in SUDs and other mental health conditions, researchers have again turned their attention to these compounds, searching for differing pharmacological targets as well as more holistic treatments that might increase patient adherence and efficacy. The aim of this review is to examine the emerging evidence with regards to the therapeutic treatment of SUDs with the psychedelic compounds psilocybin, ketamine, lysergic acid diethylamide (LSD), 3,4-methylenedioxymethamphetamine (MDMA), ayahuasca, ibogaine and peyote.

Understanding complex Portable Document Format (PDF) files, such as research papers, clinical reports, and scientific manuals, is often a time-consuming endeavor. While significant progress has been made in developing question-answering (QA) systems that yield contextually relevant responses, the creation of a comprehensive end-to-end machine learning model capable of addressing intricate questions remains a formidable challenge. These systems typically rely on substantial labeled training data to effectively train their foundational models for specific tasks. However, assembling such datasets is particularly challenging for complex documents, including annual reports from major technology companies. In this paper, we address this issue by developing a QA system specifically designed for PDF documents, focusing on the domains of finance, biomedicine, and scientific literature. We manually curated datasets from these areas for evaluation purposes and utilized pre-trained Bidirectional Encoder Representations from Transformers (BERT) models from the Hugging Face library. The models were evaluated using the F1 score, achieving a notable score of 44% with the BERT Large model.

Vitex agnus-castus L.(VAC) belonging to the Verbenaceae family is a Mediterranean plant which is widely used in traditional Tunisian medicine. The aim of this study was to investigate the phytochemical composition, antioxidant, antiviral and cytotoxic potential of methanolic VAC fruits extracts. Quantitative analyses of the different constituents of extracts were evaluated by high-performance liquid chromatography with photodiode-array detection (HPLC-DAD). Spectrophotometric methods and chemical tests were used for phytochemical characterization and antioxidant activity. The cytotoxic study was evaluated using epidermoid carcinoma Hep-2 cells, while the antiviral assessment against clinical isolates of coxsackievirus B3 (CBV-3) was determined by using a HEp cell survival assay. VAC extracts presented several components and minerals The results of HPLC-DAD indicated the presence 7 of phenolic compounds with a remarkable abondance of chlorogenic and coumaric acids as polyphenols compounds. The data also showed that VAC extracts had an important antioxidant effect (IC50=0.061 mg/mL) with a reduced cytotoxicity (CC50= 213 µg/ml), and these effects are displayed in a dose-dependent manner. However, all the tested extracts are inactive against CBV-3. The results achieved confirm the important role of this plant as a source of therapeutic activities.

(1) Background: Human papillomaviruses (HPV) are primarily related to cervical cancer around the world. This study presented an in silico design of a chimeric L1/L2 mRNA-based vaccine candidate against a diverse spectrum of human papillomaviruses; (2) Methods: We employed a computational strategy to predict and screen for antigenicity, allergenicity, toxicity, and conservation of immunodominant cytotoxic T cells, helper T cells, and linear B-cell epitopes from the most conserved HPV L1 and L2 proteins. The selected epitope peptides were coupled together with appropriate linkers to create a multi-epitope chimeric peptides. The mRNA-based vaccine was developed by combining an optimized open reading frame with co-translation regulation and co-transcription components; (3) Results: Twenty five (25) non-toxic, non-allergenic, highly antigenic, and conserved epitopes were identified. The final vaccine had a molecular weight of 60161.29 kDa, a theoretical pI of 9.44, and a solubility of 0.451. The mRNA-based vaccine had a stable mRNA structure with a minimum free energy of -731.10 kcal/mol and an estimated molecular weight of 644.98 kDa. The suggested vaccine had no cross-affinity for the human genome and achieved a global population coverage rate of 86.24%. The vaccine demonstrated a stable docking complex and robust interactions with Toll-like receptor 4 (TLR4) with binding affinities of -1377.5 kcal/mol and was capable of stimulating immunoglobulin IgG, IgM, T and B cells lymphocytes, and cytokines by in silico simulation; (4) Conclusion: The vaccine is considered a preventive and therapeutic candidate; however, further in vitro and in vivo tests are needed to prove its safety and efficacy.

Background: Orthognathic surgery is a surgical procedure that consists of osteotomies and maxillary movements aimed at facial harmony and occlusal repositioning. Methods: The present study aimed to perform a retrospective study using cone beam computed tomography (CBCT) to evaluate the air volume of the maxillary sinus and its attached structures, detection and diagnosis of anatomical defects, induced or not by maxillary advancement surgery - mandibular and/or maxillary impaction in two stages: preoperative (T0) and postoperative of at least 6 months (T1). Results: Of the 31 patients selected, it was found that the volume of the maxillary sinus had no statistically significant change, descriptively there were 6.45% for retention cyst and 32.25% for mucosal thickening, reduction in 6 cases of septal deviation in T1 that were present in T0 in patients undergoing maxillary advancement and impaction. Furthermore, it was possible to observe a decrease in postoperative cases of obstructed ostium and an increase in cases of patent ostium. Conclusion: That orthognathic surgery for maxillary advancement and/or impaction does not pose a risk to the health of the maxillary sinuses during the period analyzed.

Efficient classification of body position is crucial for monitoring infants’ motor development. It may fast-track the early detection of developmental issues related not only to the acquisition of motor milestones but also to postural stability and movement patterns. In turn, this may facilitate and enhance opportunities for early intervention that are crucial for promoting healthy growth and development. Manual classification of human body position based on video recordings is labour-intensive, leading to the adoption of Inertial Motion Unit (IMU) sensors. IMUs measure acceleration, angular velocity, and magnetic field intensity, enabling automated classification of body position. Many research teams are currently employing supervised machine learning classifiers that utilise hand-crafted features for data segment classification. In this study, we used a longitudinal dataset of IMU recordings made in the lab in three different play activities of infants aged 4-12 months. The classification was conducted based on manually annotated video recordings. We found superior performance of the CatBoost Classifier over the Random Forest Classifier in the task of classifying five positions based on IMU sensor data from infants, yielding excellent classification accuracy of Supine (97.7%), Sitting (93.5%) and Prone (89.9%) position. Moreover, using data ablation experiments and analysing the SHAP values, the study assessed the importance of various groups of features from both time and frequency domains. The results highlight that both accelerometer and magnetometer data, especially their statistical characteristics, are critical contributors to improving the accuracy of body position classification.

An MFI zeolite (Si/Al = 40) was desilicated by alkaline treatment in order to generate mesopores. Temperature, alkali concentration and treatment duration were adjusted to maximize mesoporosity while preserving the zeolite structure. Special attention was paid to the characterization of the strength and accessibility of the acid sites. The catalysts were tested in the isobutane/butene alkylation, a reaction typically catalyzed by zeolites but limited by coke deposition. Additionally, glycerol esterification with acetic acid was used as test reaction, due to the requirement of large pores to take part. The results confirmed that mesopores were successfully generated in the MFI zeolite, and the diffusion through the solid was enhanced, but the active sites remained mainly confined in the micropores.

In the outskirts of the Pinios dam reservoir (Ilia Regional Unit, Greece) a freshwater refinery serves the water supply needs of the surrounding Municipalities, in which high concentrations of Fe and Mn, before treatment, have been observed. The main purpose of this research is to investigate the mechanism of increased iron (Fe) and manganese (Mn) levels in the reservoir of the Pinios dam, which impacts its freshwater refinery's operation. A comprehensive hydrochemical and sedimentological analysis was conducted over a hydrological year, focusing on the spatial and temporal distribution of Fe and Mn in both water and sediment samples across the established research monitoring stations. Sediment samples from the reservoir's bottom revealed predominantly fine-grained material, rich in total organic carbon, with elevated Mn and Fe oxide levels. Significant seasonal variations in Fe and Mn levels were also discovered, with higher Mn levels observed in the anoxic bottom waters of the reservoir during the dry season, attributed to the reduced conditions favoring Mn oxide dissolution over Fe. Conversely, during the wet season, a homogenization of metal concentrations throughout the water column was observed due to increased oxygenation and freshwater inflow. These outcomes were confirmed by the hydrochemical analysis, indicating that the redox conditions, pH, temperature, as well as the presence of organic matter significantly influence the mobility and bioavailability of these metals in the reservoir. The findings of this study clarify that the high concentration of Fe and Mn can be linked to the mineral composition of the upstream Neogene and flysch formations in the study area. As these formations are affected by geological weathering, they tend to enrich the streams, through soil erosion and runoff processes, in metals like Fe and Mn, which are eventually transported into the dam reservoir. This study highlights the critical role of geological, sedimentological and hydrological factors in shaping the hydrochemistry of dam reservoirs, providing essential insights for water resource management and environmental conservation strategies.

This article presents an in-depth overview of clustering techniques, which play a vital role in unsupervised learning by uncovering natural groupings in data. We examine five prominent methods: k-Means, k-Medoids, Kohonen Networks and Self-Organizing Maps (SOMs), Fuzzy C-Means, Hierarchical Clustering, and Spectral Clustering. Each technique is described in detail, including its mathematical foundation, operational mechanism, applications, strengths, and limitations. The goal is to provide a thorough understanding of each approach, helping readers select the most appropriate method for their data analysis needs. Practical examples are also provided, demonstrating the application of these clustering techniques in various real-world contexts such as customer segmentation, image processing, and bioinformatics.

A vast amount of non-biodegradable waste is generated during mining and processing operations of dimensional stones such as marble. This, over the years has become a global nuisance by damaging the environment through means of more than one. Therefore it has become necessary to find a technique to safely dispose or reuse marble waste. This paper reviews the impact of replacement of the conventional materials by marble waste was studied in terms of fresh, mechanical and durability properties of concrete. The air pollution caused by the dust generated in the process of crushing and extracting marble can cause serious problems to the general physiological functions of plants and it affects human life as well. Therefore, the objectives of this study were to assess the air quality of areas with marble factories and areas without marble factories, where the concentration of particulate matter in terms of total suspended particles (TSP) was determined. This paper also reviews some eco-innovation options considering the pollution caused, consumption of water and electricity and the disposal of marble waste and their waste.

In the field of recommender systems, difficult negative samples that are easily misclassified by classifiers have higher learning value. In order to solve the problem that the existing graph convolutional network lacks the exploration of negative sampling strategy, a multivariate sampling based on graph convolution collaborative filtering recommendation model was proposed. Firstly, part of the information in the positive sample was injected into the negative sample, and the high quality difficult negative sample was selected by the inner product method. Then, contrastive learning is used to maximize the similarity between the difficult negative samples and the positive samples, so that the difficult negative samples are as close to the positive samples as possible in the feature space. Ultimately, a multi-task approach was employed to concurrently enhance both the recommendation supervision task and the contrastive learning task. To validate the effectiveness of our approach, we conducted comparative evaluations utilizing three publicly accessible datasets. The experimental outcomes indicate that our proposed model surpasses the baseline model in terms of performance.

Cultivation is advocated as a solution for sustainable exploitation of medicinal plants. Understanding environmental factors influencing plant species distribution will eliminate the introduction of medicinal plants indiscriminately to inappropriate cultivation regions. The study investigated environmental conditions for the distribution of Artemisia afra and mapped out potential areas for its cultivation in South Africa. Soil samples were collected in the Free State Province in South Africa for analysis. To identify suitable environmental conditions for the natural distribution of A. afra, the South African National Botanical Institute database and physically collected Global Positioning System points were used in maximum entropy model. Monthly long-term average interpolated weather surfaces were used to estimate the effect of climate change on future climate suitability for A. afra distribution. Sixty-one percent of soil samples from different A. afra populations were clay loam soils with slightly acidic to neutral pH. The carbon source utilization, Shannon Weaver Index, and species richness were positively correlated to one group of fourteen soil samples, and species evenness was positively correlated to the second group, consisting of four samples. Climate change will only affect the distribution of A. afra in the very long term. The current study provides critical information for identifying suitable cultivation areas for A. afra, while supporting conservation efforts from an ecological point.

The results of the study of the interaction between the CeF3+EuF3 system and the salt melt NaCl–KCl by spectroscopic methods are presented. It was established that no significant changes occur with CeF3 ions upon dissolution in the NaCl–KCl melt. Instead, the transition of EuF3 into solution-melt, both individually and in the CeF3+EuF3 system, is accompanied by oxidation-reduction reactions with the formation of Eu2+. Diffuse reflection spectra of the samples – both bottom (insoluble sediment) and upper parts of the solidified salt melt in the UV range indirectly indicate the excitation of photoluminescence of Ce3+ and Eu2+ ions. On the other hand, the presence of absorption bands in the near-IR range of the spectrum (1900-2300 cm−1) confirms the preservation of a certain proportion of Eu3+ ions in the salt melt. The influence of various factors (composition of the solidified salt melt sample, excitation wavelength, previous and subsequent heat treatment, and composition of the medium) on the nature of the excitation and emission spectra of the samples was studied. A very intense 5d-4f luminescence of Ce3+ and Eu2+ ions (at 330 and 430 nm, respectively), mainly in the upper part of salt melts, and much weaker 4f-4f luminescence of Eu3+ ions were observed. Certain parameters were optimized to reduce the proportion of luminescence of Ce3+ and, especially, Eu3+ ions and to increase the luminescence of Eu2+ ions. Solidified salt solutions-melts of the NaCl–KCl–CeF3–EuF3 system are promising materials for the creation of solar ultraviolet radiation detectors.

Phubbing - the act of snubbing someone by concentrating on a smartphone - is claimed to be an increasing, even normative, behaviour receiving more research attention. However, evidence about the adequacy of instruments that allow screening for phubbing is limited. Thus, the main purpose of the present study was to analyze the psychometric properties of the Phubbing scale in a sample of adolescents and young adults, and present a reliable and valid short form. The final sample included a total of 1351 adolescent students (54.25% males), aged between 12 and 21. A two-dimensional model of a short version of the PS with 6 items (PS-6) displayed appropriate goodness of-fit indices. Strong measurement invariance for the two-dimensional model across gender and educational level was confirmed. McDonald’s Omega coefficients for the Communication, the Obsession, and the Total score of the PS-6 were 0.617, 0.669, and 0.701, respectively. The PS-6 was positively associated with several indicators of psychological difficulties and negatively associated with psychological well-being and self-esteem. The present study contributes valuable information about the psy-chometric adequacy of the PS-6, a short instrument that allows screening for Phubbing in adoles-cents and young adults.

This study describes the properties of high-T_c cuprates by introducing rotating holes that are created by angular momentum conservations on a 2D CuO₂ surface, and which have a different mass from that of a normal hole because of the magnetic field energy induced by the rotation. This new particle called a macroscopic Boson describes the doping dependences of pseudo-gap temperature and the transition temperature at which an anomaly metal phase appears and describes the origin of the pseudo-gap. Furthermore, this study introduces a new model to handle many-body interactions, which results in a new statistic equation. This statistic equation describing many-body interactions accurately explains why high-T_c cuprates have significantly high critical temperatures. Moreover, a partition function of macroscopic Bosons describes the properties of anomaly metal phase, which sufficiently agree with experiments. Note that, the calculations were conducted, using the result from our previous study that analytically describes the doping dependence of T_c. By introducing a macroscopic Boson and the new statistical model for many-body interactions, this study uncovered the mystery of high- T_c cuprates, which have been a challenge for many researchers. An important point is that, in this study, pure analytical calculations are consistently conducted, which agree with experimental data well (i.e., they do not use numerical calculations or fitting methods but use many actual physical constants).

This study retrospectively evaluated the prevalence and drug susceptibility of Candida species in patients diagnosed with oral mucosal candidiasis at the Department of Periodontal and Oral Mucosal Diseases, Silesian Medical University, from 2018 to 2022. A total of 1286 patients were examined (788 females, 498 males) through mycological testing to identify Candida strains and assess their drug resistance to amphotericin B, nystatin, flucytosine, econazole, ketoconazole, miconazole, and fluconazole. Among the 958 patients with positive results, Candida albicans accounted for 66.79% of infections, followed by non-albicans Candida (NAC) strains (33.21%), with rare strains identified in 0.82%. Drug resistance in C. albicans was less than 10% for most antifungals but reached 30% for azoles, while NAC strains exhibited more than 40% resistance, with C. krusei being the most resistant. Key risk factors for candidiasis included removable denture use and uncontrolled diabetes mellitus. The study highlights an increase in NAC infections, multi-strain infections, and decreasing efficacy of antifungal treatments, especially for NAC strains, with more severe cases observed in patients with multiple risk factors.

The purpose of the study was to train participants on the nutritional values (carbohydrates) of various food items and evaluate the effect over three weeks. Twenty-seven participants were assigned to three different conditions. Initially, participants pre-sorted cards labeled with food items and categories, and any incorrectly sorted items were identified and customized for each participant. Tailored stimuli were then used for many-to-one conditional discrimination training. Conditions 1 and 2 aimed to establish three-member classes, while condition 3 aimed for five-member classes. Participants in all conditions sorted food items into categories of “more than 40,” “20–40,” and “less than 20” grams of carbohydrates. Additionally, participants in conditions 2 and 3 could sort items into a “don’t know” category. Maintenance of the learned categories was tested after one week. Participants who did not meet the mastery criterion received additional training and testing. A follow-up test was conducted two weeks after the maintenance test. During both the maintenance and follow-up phases, tests for emergent relations and sorting were conducted. The results showed that most participants responded correctly in both the emergent relations and sorting tests. The majority of participants did not require additional training or testing, and the equivalence classes were maintained across all conditions over the three-week period.

Diabetes is a significant global health issue impacting millions. Approximately 26 million diabetics experience foot ulcers, with 20% leading to amputations, resulting in high morbidity, mortality, and costs. Plantar pressure screening shows potential for the early detection of Diabetic Foot Ulcers (DFUs). Although foot ulcers often occur due to excessive pressure on the soles during dynamic activities, most studies focus on static pressure measurements. This study’s primary objective is to apply wireless plantar pressure sensor-embedded insoles to classify and detect diabetic feet from healthy ones based on dynamic plantar pressure. The secondary objective is to compare statistical-based and Machine Learning (ML) classification methods. Data from 150 subjects were collected using the insoles during walking, revealing that diabetic feet have higher plantar pressure than healthy feet, consistent with prior research. The Adaptive Boosting (AdaBoost) ML model achieved the highest accuracy of 0.85, outperforming the statistical method, which had an accuracy of 0.67. These findings suggest that ML models, combined with pressure sensor-embedded insoles, can effectively classify healthy and diabetic feet using plantar pressure features. Future research will focus on using these insoles with ML to classify various stages of diabetic neuropathy, aiming for early prediction of foot ulcers in home settings.

Gaia-X, a European initiative, aims to create a digital sovereignty framework for service ecosystems in the future internet. Its applicability to the health domain has been explored in the Gaia-X-Med project, which aimed to establish a common dataspace for various medical use cases based on Gaia-X principles. This paper presents the approach to secure authentication and digital contract negotiation central to this endeavour and discusses the challenges that arose during adoption of the Gaia-X framework, in particular relating to the strict requirements of the European healthcare domain with regards to privacy and consent regulations. By exploring the practical implications of Gaia-X in the healthcare context, this paper aims to contribute to the ongoing discussions surrounding digital sovereignty of both citizens and corporations, as well as its realization via future internet technologies.

Four fundamental forces of nature are too important to say because they dominate the formation and evolution of the universe. However, until now, their origins and physical essences have not been answered with wide acceptations. This paper gives new explanations for the origins and essences of these four forces based on different understandings, which can easily explain that all of the four fundamental forces of nature are originated from the electric force only and so can be unified to be one force. First of all, the gravitational force is a synthesized electric force produced by a huge amount of electric charges via particular movements and distributions. Depending on inference of nuclear structure, which has strong supports by observed phenomena, the strong and weak forces are deduced to be electric forces too. The introduced new understandings can explain observed confusing phenomena simply and effectively, such as “galaxy shape”, “dark matter”, “dark energy”, “gamma-ray bursts” in nuclear fission or fusion and from black holes, and so on. The author wrote this paper is for helping to find the natural truth earlier.

The argument of this article is threefold. First, the article argues that, from its rise in the sixteenth century to our own time, the advancement of modern physics, as mathematical-experimental science, has been defined by the invention of new mathematical structures. Secondly, the article argues that quantum theory, specifically with quantum mechanics, gave this thesis a radically new meaning by virtue of the following two features: one the one hand, quantum phenomena themselves are defined by purely physical features, as essentially different from all previous physics; and on the other, quantum mechanics and quantum field theory are defined by purely mathematical postulates, which connect them to quantum phenomena strictly in terms of probabilities, without representing or otherwise relating to how these phenomena physically come about. While these two features may appear discordant, if not inconsistent, I argue that they are in accord with each other, at least in certain interpretations (including the one adopted here), designated as “reality without realism,” RWR, interpretations. This argument allows this article to offer a new perspective on a thorny problem of the relationships between continuity and discontinuity in quantum physics. In particular, rather than being concern only with the discreteness and continuity of quantum objects or phenomena, quantum mechanics and quantum field theory relate their continuous mathematics to the irreducibly discrete quantum phenomena, in terms of probabilistic predictions, while, at least in RWR interpretations, precluding a representation or even conception of how these phenomena come about. This subject is rarely, if ever discussed, apart from previous work by the present author. It will, however, be given a new dimension in this article which introduces, as one of its main contributions, a new principle: the mathematical complexity principle.

Accurate estimation of the state of health (SOH) of batteries for automotive applications, particularly in electric vehicle battery management systems (EV-BMS), is still under study and is highly relevant to ensure battery system availability. This paper proposes a comprehensive SOH estimation method that goes beyond the methods that are based on the estimation of the battery available capacity by the integral of the current, or the estimation of the increase of the internal resistance of the battery. The SOH estimator is based on a partial capacity discharge method and a linear state of charge (SOC) observer based on an equivalent electrical circuit model. This method uses readily available manufacturer data and is designed for real-time applications. The proposed method was tested and validated with three different automotive battery technologies in a Model-In-Loop (MIL) environment with OPAL-RT platform, utilizing voltage and current measurements of pulsed discharge current profiles at temperature-controlled conditions and an electric vehicle’s driving profile.

The rise of non-albicans Candida species, exhibiting unpredictable antifungal resistance, complicates treatment and contributes to the growing threat of invasive, life-threatening infections. This study evaluated the antifungal activity of four benzo[a]phenoxazine derivatives (C34, C35, A42, and A44) against 14 Candida strains following EUCAST standards. Fluconazole interactions were analysed through fractional inhibitory concentration index (FICI) calculation and response surface analysis, based on the Bliss model. Macrophage-like J774A.1 cells were used to assess Candida killing in the presence of synergistic compounds. The MIC values against the different strains varied, with C34 showing the strongest activity, followed by C35, while A42 had the highest MIC values, indicating lower efficacy. However, A42 demonstrated the best synergy with fluconazole against fluconazole-resistant Candida strains. Cytotoxicity assays revealed that the chloropropyl group present in C35 and A42 enhanced cytocompatibility. Co-culture with macrophages showed significant yeast killing for C. albicans and C. auris when fluconazole and A42 were combined, requiring concentration 4- and 16 times lower than their MIC values, enhancing antifungal activity. Given fluconazole's fungistatic nature and the emergence of drug-resistant strains, benzo[a]phenoxazine derivatives' ability to enhance fluconazole's efficacy presents a promising strategy to address antifungal resistance in critical pathogens. These findings align with global research priorities, offering new potential avenues for developing more effective antifungal therapies.

Cardiac ischemia-reperfusion injury (IRI) occurs when blood flow is restored to the myocardium after a period of ischemia, leading to oxidative stress and subsequent myocardial cell damage, primarily due to the accumulation of reactive oxygen species (ROS). In our previous research, we identified that miR-25 is significantly overexpressed in pressure overload-induced heart failure, and its inhibition improves cardiac function by restoring the expression of SERCA2a, a key protein involved in calcium regulation. In this study, we aimed to investigate the role of miR-25 in the context of ischemia-reperfusion injury. We found that miR-25 was markedly upregulated under hypoxic conditions in both in vitro and in vivo models. Through in silico analysis, we identified Sestrin3 (SESN3), an antioxidant protein known for its protective effects against oxidative stress, as a novel target of miR-25. Based on these findings, we hypothesized that inhibiting miR-25 would restore Sestrin3 expression, thereby reducing ROS-induced myocardial cell damage and improving cardiac function. To test this hypothesis, we employed two model systems: a hypoxia/reoxygenation (H/R) stress model using H9c2 myoblasts and a surgically induced ischemia-reperfusion injury mouse model. Our results demonstrated that the use of miR-25 inhibitors significantly improved cardiac function and reduced myocardial damage in both models through the restoration of SESN3 expression. In conclusion, our findings suggest that targeting miR-25 may serve as a novel therapeutic modality to alleviate oxidative damage in the heart.

Telerobotics involves the operation of robots from a distance, often using advanced communication technologies combining wireless and wired technologies and a variety of protocols. This application domain is crucial because it allows humans to interact with and control robotic systems safely and from a distance, often performing activities in hazardous or inaccessible environments. Thus, by enabling remote operations, telerobotics not only enhances safety but also expands the possibilities for medical and industrial applications. In some use cases, telerobotics bridges the gap between human skill and robotic precision, making the completion of complex tasks requiring high accuracy possible without being physically present. With the growing availability of high-speed networks around the world, especially with the advent of 5G cellular technologies, applications of telerobotics can now span the gamut of scenarios ranging from remote control in the same room to robotic control across the globe. However, there are a variety of factors that can impact the control precision of the robotic platform and user experience by the teleoperator. One such critical factor is latency, especially across large geographical areas or complex network topologies. Consequently, military telerobotics and remote operations, for example, rely on dedicated communications infrastructure for such tasks. However, this creates a barrier to entry for many other applications and domains, as the cost of dedicated infrastructure would be prohibitive. In this paper, we examine the network latency of robotic control over shared network resources in a variety of network settings, such as a local network, access-controlled networks through Wi-Fi and cellular, and also a remote transatlantic connection between Finland and the United States. The aim of this study is to quantify and evaluate the constituent latency components that comprise the control feedback loop of this telerobotics experience - between a camera feed to observe the telerobotic platform's environment by the operator in one direction and the control communications from the operator to the robot in the reverse direction and to subsequently use these insights to optimize the end-to-end latency for optimizing the user experience. The results show stable average round trip latency of 6.6 ms for local network connection, 58.4 ms connecting over Wi-Fi, 115.4 ms connecting through cellular, and 240.7 ms connecting from Finland to the United States over a VPN access-controlled network. These findings pave the way toward a better understanding of the capabilities and performance limitations of telerobotics activities over commodity networks.

This study presents the experimental and analytical evaluations on an innovative connection class under cyclic loading. The connection was an H- or I-shaped section as a short stub column (SSC) between the end-plate and the column. The stub section was bolted to the column flange on the one side and bolted to the beam along with the welded end-plate on the other side. Stiffeners were installed on the webs and flanges of the beam and stub to ensure the necessary stiffness of the connection. The variables included thickness of stub flange/web and height of stub web. The cyclic loading was applied on a sample of the proposed connection according to AISC ANSI/AISC 341-16 loading protocol. Experimental observations displayed that the proposed connection, one can either employ hot rolling sections or create the connection as a plate girder, in which case the flange thickness and stub web, as well as the distance between two flanges and their height, was obtained according to the demand and performance of the structure. The optimum cross-section of the stub was then obtained. Also, the analytical model was calibrated using the finite element method (FEM), and its performance was confirmed. The effective parameters of the proposed connection were determined by modeling in the FEM software, and the design method was presented.

The widespread clinical application of collagen sponge-delivered recombinant human bone morphogenetic protein-2 (rhBMP-2) for spinal fusion currently remains limited. This limitation is due to potential adverse events associated with the rapid release of excessively high doses. This study aimed to investigate the impact of varying PGmatrix 3D Shape peptide hydrogel (PepGel) formulations on the release kinetics of rhBMP-2 in vitro. Three PepGel formulations were assessed: 1) 50% v/v PepGel, where solution A (crosslinking reagent) was mixed with solution B (synthetic peptides) and rhBMP-2 solution, making a 50% v/v (solution B volume/total volume) PepGel; 2) 67% v/v PepGel; 3) 80% v/v PepGel. Each sample was loaded with 12 µg of rhBMP-2 and incubated in PBS. The incubation solution containing released rhBMP-2 was collected at 1 hour, 6 hours, and 1, 2, 4, 7, 10, 14, and 21 days, and released rhBMP-2 was quantified using a BMP-2 ELISA kit. To explore how PepGel formulations influence rhBMP-2 release, the gel porosities, swelling ratios, and mechanical properties of the three PepGel formulations were quantitatively analyzed. The results showed that rhBMP-2 encapsulated with 50% v/v PepGel exhibited a sustained release over the 21-day experiment. Between days 7 and 21, the 50% v/v PepGel demonstrated significantly higher rhBMP-2 release rates compared to the 67% and 80% v/v formulations. Higher histological porosity of PepGel was significantly correlated with increased rhBMP-2 release rates. Conversely, the swelling ratio and elastic modulus at 1.0 Hz of the 50% v/v PepGel was significantly lower than that of the 67% and 80% v/v formulations. In conclusion, this study indicates that varying the formulation of crosslinked PepGel can control rhBMP-2 release rates in vitro by modulating gel porosity, swelling ratio, and mechanical properties. Encapsulation with 50% v/v PepGel offers a sustained rhBMP-2 release pattern, which could mitigate the adverse effects associated with burst release of rhBMP-2 if replicated in vivo.

The following two consequences of the axiom of constructibility V = L are established for every n ≥ 3: 1. Every linear $\bf\Sigma^1_n$ set is the projection of a uniform planar $\bf\Pi^1_{n-1}$ set. 2. There is a planar $\bf\Pi^1_{n-1}$ set with countable cross-sections, not covered by a union of countably many uniform $\bf\Sigma^1_n$ sets. If n = 2 then claims 1,2 hold in ZFC alone, without the assumption of V = L.

This article reports on the development of a big data processing platform that uses hot words（politics, economy, military, culture and society） reflecting the national image as the search object and the key time points as the time domain of data resources. The platform crawls (in real time), continuously expands and dynamically monitors a corpus of mainstream media covering China in developed countries (including the United States, Britain, Germany, France and Japan) and in developing countries (such as Brazil, India and South Africa). In this study, the principles of platform development and operation and the software and hardware operating environment were determined.

We mathematically derived a comprehensive theoretic framework “Asymmetry Theory”, based solely on the well-established principle of “the constancy of the velocity of light” without any other assumptions, like the ether. This paper proves that Asymmetry Theory encompasses all results of Special Relativity (STR) as a special case when the observer moves perpendicularly to the “source-observer” line. It explains everything STR does but extends beyond it, offering novel and groundbreaking insights. The longstanding controversies surrounding STR arise from its application outside its intended special case, hence, they are all resolved in Asymmetry Theory. Asymmetry Theory is supported by all experiments supporting STR, like Kaufmann, Ives-Stilwell, muon lifetime, nuclear reaction…., and those contradicting STR, like the Lunar range and GPS tests of light speed and the lack of transverse Doppler shift. Despite its mathematical rigorousness and all experimental evidence, we propose two new experiments to decisively test predictions from both theories.The mathematically derived Asymmetry Theory is a more comprehensive theoretical framework covering STR as a special case. It is self-consistent and theoretically proved by Maxwell’s equations. It does not contradict any established physical observations but instead resolves century-old controversies by providing a unified, mathematical and paradox-free explanation of key phenomena. Furthermore, its groundbreaking results offer a unified perspective across various distinct laws of physics, including: A formula for light velocity mathematically explains the Sagnac effect, one-way light speed, stellar aberration, Michelson-Morley, Hafele-Keating and Optic clocks. Electrodynamics formulas encompass particle acceleration, Mass-Energy and matter wave. A unified formula for all cases of classical and transverse Doppler effects covers time-varying Doppler effect, cosmological redshift, and Cherenkov radiation. A generalized form of Maxwell's equations for moving observers directly derives the formulas for light speed, Doppler effect and Sagnac effect.

This study investigated commensal and pathogenic E. coli from pigs at farms and slaughterhouses in Sardinia, focusing on genetic relatedness and antimicrobial resistance (AMR). Samples were collected from six fattening pig farms (A-F) and five slaughterhouses (S1-S5). In the farms, environmental fecal sampling from the fattening pigs’ pens was carried out and information regarding farm management and biosecurity measures were collected. Pigs that had been in the sampled pens were selected for sampling at the slaughterhouse. Mesenteric lymph nodes, colon content and carcass surface samples were collected at the five slaughterhouse (S1-S5), in a total of 38 samples form 152 animals. At the slaughterhouses, also environmental samples were collected from food-contact surfaces and non-food-contact surfaces (36 samples overall). E. coli was detected in all farms, 97% of pigs, and 100% of slaughterhouses. Whole genome sequencing and antimicrobial susceptibility testing were per-formed on 96 isolates, revealing 13.5% pathogenic isolates, including ExPEC, ETEC, STEC-ETEC hy-brids, and UPEC. A total of 40 sequence types (STs) were identified, with ST10 being the most com-mon. High-risk clones (ST88, ST101, ST410, and ST648) were also detected. Over half of the isolates (52.1%) carried at least one AMR gene, with 42.7% harboring multiple AMR genes, particularly tet (37.5%) and blaTEM (32.3%). High phenotypic resistance was observed for tetracycline, ampicillin, and sulfamethoxazole-trimethoprim. The study highlights the widespread presence of pathogenic E. coli in pigs, even in isolated environments, and emphasizes the need for continuous surveillance due to the significant AMR found in both pathogenic and non-pathogenic isolates.

This study examines the impact of prompt engineering on large language models (LLMs), focusing on a comparison between multitasking and single-task prompts. Specifically, we explore whether a single prompt handling multiple tasks — such as Named Entity Recognition (NER), sentiment analysis, and JSON output formatting — can achieve similar efficiency and accuracy to dedicated single-task prompts. The evaluation uses a combination of performance metrics to provide a comprehensive analysis of output quality. Experiments were conducted using a selection of open-source LLMs, including LLama3.1 8B, Qwen2 7B, Mistral 7B, Phi3 Medium, and Gemma2 9B. Results show that single-task prompts do not consistently outperform multitasking prompts, highlighting the significant influence of the model’s data and architecture on performance.

Background: Chronic heart failure (CHF) often necessitates the use of high doses of diuretics, which can lead to side effects such as worsening renal function and electrolyte imbalances. Methods: A total of 102 patients (median age 75 years) were included in the study and divided into two groups based on the level of diuretic therapy. The diuretic group received the following average doses: furosemide — 39.1 ± 22.1 mg, torasemide — 7.4 ± 3 mg, and spironolactone — 42 ± 12.4 mg. Biochemical analyses were performed on days 1 and 7 of hospitalization, with measure-ments of sodium, potassium, glucose, urea, and plasma osmolality (eOSM). Results: By day 7, the plasma osmolality in the diuretic group increased from 300 [297; 304] to 302.2 [298.3; 305.8] mOsm/L (p = 0.039). Urea levels in the diuretic group rose to 7.95 [5.65; 9.90] mmol/L by day 7, while remaining stable in the non-diuretic group at 5.90 [5.05; 7.50] mmol/L (p = 0.012). The proportion of urea to plasma osmolality (PropUrea/eOSM) in the diuretic group in-creased to 2.63% [1.89; 3.28] compared to 2.00% [1.70; 2.50] in the non-diuretic group (p = 0.011). The proportion of sodium to plasma osmolality (PropNa/eOSM) in the diuretic group decreased to 46.46% [46.02; 46.74], compared to 46.68% [46.33; 46.89] in the non-diuretic group (p = 0.050). Analysis of PropNa/eOSM and PropUrea/eOSM on day 7 without considering salt intake yielded statistically significant results, though they were less robust compared to models including salt intake. For example, in the PropUrea/eOSM model, the odds ratio (OR) was 3.01 (95% CI 1.74, 5.89; p < 0.001), and in the PropNa/eOSM model, the OR was 0.19 (95% CI 0.07, 0.43; p < 0.001). Conclusion: The study confirmed that high salt intake and active diuretic therapy significantly influence the biochemical parameters of patients with chronic heart failure (CHF), contributing to the develop-ment of the aestivation phenomenon. This is characterized by an increase in nonionic osmolytes such as urea, which may represent a physiological adaptation to stress. Patients receiving diuret-ics and following a high-salt diet exhibited significant changes in plasma osmolality and urea levels, indicating a physiological adaptation that may worsen prognosis by increasing the risk of sarcopenia and cachexia. Further research is needed to better understand these mechanisms and develop strategies to mitigate the negative effects.

The effects of Lactiplantibacillus plantarum 1008 (LP1008) on age-related cognitive impairment and skeletal muscle atrophy have been reported previously. However, its role in obesity- and age-related hypogonadism has yet to be explored. This study investigated the therapeutic efficacy of low- and high-dose LP1008 in a high-fat diet-fed male mouse model. Mice were fed a standard diet or 45% high-fat diet for 28 weeks, and the high-fat diet-fed mice were divided into vehicle, low-dose or high-dose LP1008 groups on the basis of the treatment administered for an additional 8 weeks. We found that LP1008 suppressed the increase in total cholesterol levels and liver function parameters and alleviated histological changes in the brain, cecum, gastrocnemius, and testes. In terms of reproductive function, LP1008 attenuated the decreases in sperm quality, sperm maturity, testosterone levels, and levels of enzymes involved in testosterone biosynthesis. Furthermore, LP1008 altered impairments in spatial learning and memory and induced slight alterations in the gut microbiota. Moreover, LP1008 exerted antioxidant, anti-inflammatory, and anti-apoptotic effects in aged, obese male mice. LP1008 reversed diet-induced obesity, age-related reproductive dysfunction, and pathological damage by increasing testosterone levels and altering the gut microbiome through the regulation of mediators involved in oxidative stress, apoptosis, and inflammation.

Solving maximum matching problems in bipartite graphs is critical in fields such as computational biology and social network analysis. This study introduces HybridGNN, a novel graph neural network model designed to efficiently address complex matching problems at scale. HybridGNN combines the capabilities of Graph Attention Networks (GAT), GATv2, and Graph SAGE (SAGEConv) layers, integrating techniques like mixed precision training, gradient accumulation, and Jumping Knowledge networks to enhance computational efficiency and performance. Additionally, the incorporation of Graph Isomorphism Networks (GIN) enhances the model's ability to discriminate between structurally different graphs. A time complexity analysis shows that HybridGNN achieves efficient computation across different layers. When evaluated on an email communication dataset, HybridGNN outperformed traditional algorithms such as Hopcroft-Karp, particularly on large and complex graphs. These results demonstrate that HybridGNN offers a powerful and efficient approach for solving maximum matching problems in bipartite graphs, with potential applications in various fields requiring analysis of large-scale and complex graph data.

The monitoring and control of an assembly/disassembly/replacement (A/D/R) multifunctional robotic cell (MRC) with the ABB 120 Industrial Robotic Manipulator (IRM) based on IoT (Internet of Things)-Cloud, VPN (Virtual Private Network), and Digital Twin (DT) technology, are presented in this paper. The approach integrates modern principles of smart manufacturing as outlined in Industry/Education 4.0 (automation, data exchange, smart systems, machine learning, predictive maintenance) and Industry/Education 5.0 (human-robot collaboration, customization, robustness and sustainability). Artificial intelligence (AI) based on Machine Learning (ML) enhances system flexibility, productivity, and user-centered collaboration. Several IoT edge devices are engaged, connected in a local network (LAN), for remote and local processing and data acquisition. The system is connected to the Internet, via Wireless Area Network (WAN) and allows remote control via Cloud and VPN. IoT dashboards, as human machine interfaces (HMIs), SCADA (Supervisory Control and Data Acquisition) and OPC-UA (Open Platform Communication-Unified Architecture) facilitate remote monitoring and control of MRC, planning and management of A/D/R task. The assignment, planning and execution of A/D/R tasks were carried out using an augmented reality (AR) tool. Synchronized timed Petri nets (STPN) were used as digital twin like a virtual reality (VR) representation of A/D FRC operations. This integration of an advanced technology into a laboratory mechatronic system, where the devices are organized in a decentralized, multilevel architecture, creates a smart, flexible, and scalable environment that caters to both industrial applications and educational frameworks.

The kiwifruit cultivars include fruit having a diversity of flesh colors in the range red to yellow to green, associated with specific pigment accumulations. In the yellow-fleshed cultivars, chlorophyll degradation is necessary to unmask the underlying carotenoid pigments, which are responsible for the yellow color. This study aimed to conform the enzymatic activity involved in chlorophyll degradation using different degreening temperatures in the yellow-fleshed kiwifruit (cv. ‘Kiss,’ Actinidia chinensis var. chinensis) and in the contrasting green-flesh kiwifruit (cv. ‘Hayward’, Actinidia chinensis var. deliciosa). ‘Kiss’ was harvested at hue angle 106.9 ° and degreening was carried out at 0, 5, 10 or 15 °C for 41 d. Additionally, one week later, a second batch of kiwifruit was subsequently treated at 30 °C for one week to explore the inhibitory effect on degreening and to elucidate the roles of chlorophyllase and magnesium dechelatase enzymes in the process. Fruit degreened at 30 °C was maintained at 15°C for 23 d afterward and was compared with fruit stored at 0 °C or at 15 °C for 30 d. Similar degreening treatments were applied to cv. ‘Hayward’ at commercial maturity. Every seven days, flesh color, pigment concentrations and the activities of chlorophyllase and magnesium dechelatase in the flesh were evaluated. Degreening of ‘Kiss’ kiwifruit was enhanced by the 15 °C treatment or by 30 °C treatment for seven days and was associated with increasing of carotenoids and decreasing of chlorophyll a. The magnesium dechelatase activity was greater in fruit degreening at 15°C, which was consistently maintained throughout the degreening period; however, the activity remained low at very high temperature (30 °C). Regardless of the above, degreening at 30 °C was not inhibited, showing faster color change and high chlorophyllase activity during the exposure time. In contrast, ‘Hayward’ maintained its green color with high concentrations of the chlorophylls and carotenoids. However, the high chlorophyllase and the low magnesium dechelatase activities found in ‘Hayward’, suggest the chlorophyllase enzymes are not the only ones involved in flesh degreening.

Background Lipoprotein(a) [Lp(a)] is a well-established risk factor for incident atherosclerotic cardiovascular (CV) disease. However, evidence regarding its association with recurrent events is limited. To address this gap, we conducted a retrospective analysis of routine clinical data, focusing on patients hospitalized for acute myocardial infarction (AMI) between 2000 and 2022 with available admission Lp(a) results. Methods Patients were stratified into three groups based on their Lp(a) level (≤50 mg/dL, 51–90 mg/dL, and >90 mg/dL). A multivariable-adjusted Cox regression analysis was performed to assess the associations of Lp(a) with recurrent AMI, CV mortality, and all-cause mortality. Results A total of 2248 patients (31.5% women), with a mean age of 64.7 ± 12.2 years, were retrospectively followed until December 31, 2022, or death. The multivariable-adjusted hazard ratios (HRs) for recurrent AMI were 1.01 (p=0.921) for levels 51–90 mg/dL and 1.51 (p=0.013) for levels >90 mg/dL, compared with levels ≤50 mg/dL. The corresponding HRs for CV mortality were 1.13 (p=0.300) and 1.14 (p=0.348), and those for all-cause mortality were 1.09 (p=0.310) and 1.20 (p=0.090), respectively. Stratification by sex and age revealed a significant association of Lp(a) with recurrent AMI only in women aged >65 years, with adjusted HRs of 2.34 (p=0.013) for levels 51–90 mg/dL and 3.94 (p90 mg/dL, compared with levels ≤50 mg/dL. Conclusions We observed a significant association of Lp(a) with recurrent AMI only in patients with Lp(a) levels >90 mg/dL. No associations were found between Lp(a) and CV or all-cause mortality. Notably, the association with recurrent AMI was most pronounced in women aged >65 years.

Congenital insensitivity to pain with anhidrosis (CIPA), also known as hereditary sensory and autonomic neuropathy type IV (HSAN IV), is an exceedingly rare genetic disorder characterized by the inability to perceive pain, inability to sweat, and various neurological and orthopedic complications. This is a case report of a 3-year-old female patient diagnosed with CIPA syndrome who presented repeatedly to Children’s Clinical University Hospital (CCUH) in Riga, Latvia with severe orthopedic manifestations. The patient had repeated fractures, several surgeries, and extensive spread of the disease throughout the left leg, which caused significant functional impairment and decreased quality of life. Despite aggressive orthopedic interventions including surgical interventions and physical therapy, the patient's condition remained challenging to manage due to the inherent limitations posed by the insensitivity to pain. The council of doctors discussed the patient's condition and changes, deciding that reconstructive surgery is not feasible, and amputation is recommended. Through this case report, we aim to highlight the unique orthopedic challenges encountered in the management of CIPA patients, emphasizing the importance of a multidisciplinary approach involving orthopedic surgeons, pediatricians, geneticists, and physiotherapists. Additionally, we discuss the need for further research to elucidate optimal management strategies and improve outcomes in this rare and complex patient population.

This paper presents a robust control strategy for trajectory tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimizes trajectory tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy aims to counteract disturbance effects caused by the slip phenomena through the wheel-terrain contact and bidirectional interactions propagated by the mechanical coupling between the SSMM base and arm. To capture such interactions, the mobile base dynamics and arm joints consider a coupled nonlinear model with bounded uncertainties based on principles of full-body energy balance and link torques. In addition, the SSMM dynamics stands by dynamical models, which are capable of capturing nonlinear speed relationships. Thus, a centralized control architecture integrates a nominal and ancillary controller based on the Active Disturbance Rejection Control (ADRC) to strengthen robustness of the Nonlinear Model Predictive Control (NMPC), operating the SSMM dynamics as a single robotic body. The NMPC is responsible for trajectory tracking control of a five Degrees of Freedom (DoF)’s SSMM. Meanwhile, the ADRC uses an Extended State Observer (ESO) to quantify the impact of external disturbances and uncertainties, generating compensation for unmeasurable disturbances. In addition, the proposed robust control strategy compensates for the model mismatch errors, which are generated by the difference between an SSMM nominal model (disturbance-free) and its real-time response. Results indicate that the approach is able to compensate for effects by 70% using pre-set trajectories and regulation tests against unmeasurable disturbances applied to simulated SSMR model.

Objectives: To evaluate the possible long-term cerebral deposition of amyloid-β in PD patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) and its possible influence on axial and cognitive variables. Methods: Consecutive PD patients treated with bilateral STN-DBS with a long-term follow-up were included. Amyloid-β deposition was evaluated postoperatively through a 18F-flutemetamol positron emission tomography (PET) study. Axial symptoms have been assessed using a standardized clinical-instrumental approach. Speech was assessed by perceptual and acoustic analysis while gait by means of the instrumented timed up and go test (iTUG). Motor severity was evaluated applying the UPDRS part III score and subscores while cognitive functions through a complete neuropsychological assessment. Different stimulation and drug conditions were assessed: on-stimulation/off-medication, off-stimulation/off-medication, on-stimulation/on-medication conditions (single and dual task). Results: 19 PD patients (male: 11; age: 63.52 years; on-stimulation/on-medication UPDRS-III: 17.05) with a five-year postoperative follow-up were included. Amyloid-β deposition was found in 21% of patients (4/19) with a prevalent involvement of prefrontal, limbic and parietal areas. Compared with patients without amyloid-β deposition, PD patients with positive 18F-flutemetamol PET study showed higher preoperative UPDRS-I (p=.037) score and lower postoperative Raven's matrices scores (p=.05). Conclusions: Our results suggest that in the long-term after STN-DBS a significant percentage of PD patients may present brain amyloid-β deposition. However, larger samples are needed to evaluate the possible role of amyloid-β deposition in the development of axial and cognitive alterations after surgery.

Flavonoids are a class of polyphenolic secondary metabolites found in plants. Due to their ubiquity in our daily dietary intake and their major anti-oxidative, anti-inflammatory and anti-mutagenic activities, they have been a major focus of wide-ranging research for the past two decades. Mass spectrometry combined with liquid chromatography is one of the most popular techniques for the analysis of flavonoids. In this study, high-resolution accurate mass electrospray tandem mass spectrometry was used to study 30 flavonoids in both positive and negative ionisation modes. From the data obtained, common losses are summarised and compiled. Dominating neutral losses are tabulated. The radical loss of CH3. was observed in flavonoids containing methoxy groups and three diagnostic product ions were identified which could be useful in structural elucidation of unknown flavonoids and flavonoid metabolites. Energy breakdown graphs were utilised to dis-tinguish between three pairs of structural isomers, and to help rationalise proposed fragmentation pathways. Lastly, a competition of loss of CH3. and methane were reported for rhamnetin and isorhamnetin in the negative ion mode for the first time. Proposed fragmentation pathways were given to rationalise the differences in peak intensities for this competitive process.

Cadmium (Cd) is a toxic metal primarily found as a by-product of zinc production. Cd was a proven carcinogen, and exposure to this metal has been linked to various adverse health effects, which were first reported in the mid-19th century and thoroughly investigated by the 20th century. The toxicokinetics and dynamics of Cd reveal its propensity for long biological retention and predominant storage in soft tissues. Cd pollution, primarily from industrial activities, strongly contaminates soil and water and affects human health and ecosystems. Cd enters the human body mainly through ingestion and inhalation, with food and tobacco smoke being the primary sources. It accumulates in various organs, particularly the kidney and liver, and is known to cause severe health problems, including renal dysfunction, bone diseases, cardiovascular problems, and many others. On a cellular level, Cd disrupts numerous biological processes, inducing oxidative stress generation and DNA damage. This comprehensive review explores Cd pollution, accumulation, distribution, and biological impacts on bacteria, fungi, edible mushrooms, plants, animals, and humans on a molecular level. Molecular aspects of carcinogenesis, apoptosis, autophagy, specific gene expression, stress protein synthesis, and ROS formation caused by Cd were discussed as well. This paper also summarizes how Cd is removed from contaminated environments and the human body.

The requirements for accurate models of renewable energy power plant are urgent for power system operation analysis. Most existing model research in this area is for wind turbine and photovoltaic (PV) power generation unit, a rare renewable power plant model validation mainly adopts the single-machine infinite-bus system. The single equivalent machine method is always used, and the interactions between the power plant and the grid are ignored. The voltage at the interface bus is treated as constant, although this is not consistent with its actual characteristics. The phase shifter method of hybrid dynamic simulation has been applied in the model validation of wind farm. However, this method is heavily dependent on phasor measurement units (PMU) data, resulting in limited application scope, and it is difficult to realize the model error location step by step. In this paper, the fast-responding generator method is used for renewable power plant model validation. The complete scheme comprising model validation, error localization, parameter sensitivity analysis, and parameter correction is proposed. Model validation is conducted based on measured records from a large-scale PV power plant in northwest China. The comparison of simulated and measured data verifies the feasibility and accuracy of the proposed scheme.

Recent avian influenza outbreaks have heightened global concern over viral threats with the potential to significantly impact human health. Influenza is particularly alarming due to its history of causing pandemics and zoonotic reservoirs. In response, significant progress has been made toward the development of universal influenza vaccines, largely driven by the discovery of broadly neutralizing antibodies (bnAbs). bnAbs have the potential to neutralize a broad range of influenza viruses, extending beyond the traditional strain-specific response. This could lead to longer-lasting immunity, reducing the need for seasonal vaccinations, and improve preparedness for future pandemics. This review offers a comprehensive analysis of these antibodies, their application in clinical studies, and both their potential and possible shortcomings in managing future influenza outbreaks.

The rise of abusive language on social media is a significant threat to mental health and 1 social cohesion. For Bengali speakers, the need for effective detection is critical. However, current 2 methods fall short in addressing the massive volume of content. Improved techniques are urgently 3 needed to combat online hate speech in Bengali. Traditional machine learning techniques, while 4 useful, often require large, linguistically diverse datasets to train models effectively. This paper 5 addresses the urgent need for improved hate speech detection methods in Bengali, aiming to fill the 6 existing research gap. Contextual understanding is crucial in differentiating between harmful speech 7 and benign expressions. Large language models (LLMs) have shown state-of-the-art performance in 8 various natural language tasks due to their extensive training on vast amounts of data. We explore the 9 application of LLMs, specifically GPT-3.5 Turbo and Gemini 1.5 Pro, for Bengali hate speech detection 10 using Zero-Shot and Few-Shot Learning approaches. Unlike conventional methods, Zero-Shot 11 Learning identifies hate speech without task-specific training data, making it highly adaptable to new 12 datasets and languages. Few-Shot Learning, on the other hand, requires minimal labeled examples, 13 allowing for efficient model training with limited resources. Our experimental results show that 14 LLMs outperform traditional approaches. In this study, we evaluated GPT-3.5 Turbo and Gemini 1.5 15 Pro on multiple datasets. To further enhance our study, we considered the distribution of comments 16 in different datasets and the challenge of class imbalance, which can affect model performance. The 17 BD-SHS dataset consists of 35,197 comments in the training set, 7,542 in the validation set, and 7,542 18 in the test set. The Bengali Hate Speech Dataset v1.0 & v2.0 includes comments distributed across 19 various hate categories: personal hate (629), political hate (1,771), religious hate (502), geopolitical hate 20 (1,179), and gender abusive hate (316). The Bengali Hate Dataset comprises 7,500 non-hate and 7,500 21 hate comments. GPT-3.5 Turbo achieved impressive results with 97.33%, 98.42%, and 98.53% accuracy. 22 In contrast, Gemini 1.5 Pro showed lower performance across all datasets. Specifically, GPT-3.5 Turbo 23 excelled with significantly higher accuracy compared to Gemini 1.5 Pro. These outcomes highlight a 24 6.28% increase in accuracy compared to traditional methods, which achieved 92.25%. Our research 25 contributes to the growing body of literature on LLM applications in natural language processing, 26 particularly in the context of low-resource languages.

This study explored the adsorption of carboxylic acids, especially free fatty acids (FFA), present in biofuel (distilled fractions of bio-oil such as gasoline-like hydrocarbons, kerosene-like hydro-carbons and diesel-like hydrocarbons) using red mud-based adsorbents. The red mud was ther-mally activated (at 40 °C and 600 °C) and chemically activated with HCl (0.25M, 1M, and 2M). Analytical techniques were used to characterize the adsorbents' properties. At the same time, the study examined factors like feed type, adsorbents, FFA content, adsorbent percentage, activation temperature, acid solution concentration and contact time to assess adsorption efficiency. The characterization results indicated that chemical activation with 0.25M HCl significantly in-creased the surface area to 84.3290 m²/g, surpassing thermally activated samples (35.2450 m²/g at 400 °C). Adsorption experiments demonstrated that all chemically activated samples, with 5% adsorbent, adsorbed over 2000 mg FFA per gram of adsorbent, with CARM – 1M HCl achieving 100% removal of acids from gasoline-like hydrocarbons. Kinetic modeling showed that the pseudo-second-order model best represented the adsorption data, as evidenced by high R² values and close agreement between experimental and calculated qe values. Therefore, adsorption with chemically activated red mud efficiently deacidifies biofuels, providing a cost-effective and promising approach for their upgrading.

Material Flow Analysis (MFA) is a key tool in the circular bioeconomy, providing insight into the flow of materials within a system. Its use in the wood-based value chain is increasingly recognized and provides valuable information for policy making. Based on a comprehensive literature review, this article presents recent applications, challenges and research gaps related to MFA methodologies that are crucial for describing the expanding circular wood-based bioeconomy. Different MFA models and their methodologies are described and classified according to their scale and scope. The discourse on future research directions highlights the need to critically examine new material flows associated with bioeconomy development, including hidden by-product streams and end-use wood product recycling, as well as the role of regulators. The results of this study provide advice on data collection methods and the implementation of MFA models, offering valuable information for future research in the sector.

The management of skin cancer presents challenges in reconstructive surgery to achieve the best patient outcome and rapid wound healing. The most used antiseptic in pre and post operative care is Povidone Iodine solution. However, valid antiseptic alternatives should be considered. The primary endpoint of our study was to achieve the best healing in patients receiving fluorescein solution versus two comparator arms (Eosin and Povidone-Iodine).182 patients were enrolled and divided into three randomized groups according to the type of antiseptic solution received: Fluorescein (n = 63), Eosin (n= 60), and Povidone-Iodine (n = 59). To assess the endpoint of our study the ASEPSIS score was used to objectively evaluate graft healing. Results of the ASEPSIS score for each group were analyzed. The comparison demonstrated that there was no statistically significant difference among the three groups regarding the endpoint of our study, thus between fluorescein and povidone-iodine (p = 0.89), eosin and fluorescein (p = 0.54), and eosin and povidone-iodine (p = 0.81). Patients responded positively to the use of the Fluorescein antiseptic solution, although no more than the others. This study suggests that this type of antiseptic can be successfully used in skin graft management.

Wireless network technologies, including 3G, 4G, and 5G, are transforming telecommunications infrastructure globally. However, the adoption and effectiveness of these technologies vary significantly across regions and industries, posing unique challenges and opportunities for Small and Medium Enterprises (SMEs). Understanding the critical factors influencing network deployment and optimization in different contexts is essential for telecom companies and business leaders. This systematic review aims to evaluate the infrastructure, performance, and strategic implications of wireless network technologies (3G, 4G, and 5G) across multiple industries and geographic regions, providing insights for SMEs and telecom companies on adopting these technologies to enhance operational efficiency and competitiveness. A comprehensive search of academic databases, including Google Scholar, Web of Science, and SCOPUS, was conducted using keywords such as “wireless network,” “3G,” “4G,” “5G,” “evaluation,” and “infrastructure.” Studies were selected based on pre-established eligibility criteria, and a risk of bias assessment was performed using the Newcastle-Ottawa Scale. Statistical synthesis and sensitivity analyses were conducted to identify key trends and challenges. A total of 121 studies were included, with the majority focusing on 5G technology (42%) and its infrastructure. Key findings highlight the importance of network densification, high-speed connectivity, and low-latency applications, particularly in urban regions. The analysis also revealed significant regional disparities in infrastructure deployment, with developing countries facing challenges in expanding coverage and integrating advanced technologies. Industry-specific customization of wireless networks is essential for sectors such as manufacturing, healthcare, and retail. Wireless network technologies present vast opportunities for SMEs, but their successful implementation requires addressing regional infrastructure gaps and tailoring solutions to industry-specific needs. Telecom companies must prioritize strategic investments in network densification, scalability, and security to fully leverage the benefits of 5G. The findings of this review provide actionable insights for business leaders and policymakers aiming to optimize wireless technology deployments for enhanced performance and competitiveness.

This report describes the asymmetric synthesis of a focused library of enantiopure structured tri-acylglycerols (TAGs) comprised of a single saturated fatty acid (C6, C8, C10, C12, C14 or C16), a pure bioactive n-3 polyunsaturated fatty acid (EPA or DHA) and a potent drug (ibuprofen or naproxen) intended as a novel type of prodrugs. One of the terminal sn-1 or sn-3 positions of the glycerol backbone is occupyed with a saturated fatty, the remaining one with a PUFA, and the drug entity is present in the sn-2 position. This was accomplished by a six-step chemoenzymatic approach starting from enantiopure (R)- and (S)-solketals. The highly regioselective immobilized Candida antarctica lipase (CAL-B) played a crucial role in the regiocontrol of the synthesis. All combinations, the total of 48 such prodrug TAGs were prepared, isolated and fully characterized, along with 60 acylglycerol intermediates, obtained in very high to excellent yields.

Objective: In recent years, the field of Essential Thrombocythemia (ET) research has seen a significant accumulation of scientific findings, but comprehensive bibliometric analyses remain lacking. This study aims to fill that gap by performing a thorough bibliometric analysis of ET research, identifying key contributors and collaboration networks, and mapping the development trends to provide insights for future research directions. Methods: A bibliometric analysis of ET-related publications from 2001 to 2024 was conducted using CiteSpace, VOSviewer, and R packages. Data were retrieved from the Web of Science Core Collection, with a focus on publication volume, citation analysis, co-authorship networks, co-citation relationships, and citation bursts. Results: A total of 4,297 studies published in 778 journals were included in the analysis. ET research has seen rapid growth, with researcher clusters in the United States and Europe driving progress through extensive regional and international collaborations. Leading researchers, such as Ayalew Tefferi from the Mayo Clinic and Alessandro M. Vannucchi from the University of Florence, have made significant advances in ET classification, molecular mechanisms, targeted therapies, and disease management. The discovery of driver mutations, such as JAK2, has revolutionized the diagnostic and therapeutic approaches to ET. Research focus has shifted from clinical morphological diagnosis to molecular diagnostics, with the field now entering the era of targeted therapies. However, the inherent heterogeneity of ET continues to present challenges for the widespread implementation of personalized precision treatment. Conclusion: Bibliometric analysis demonstrates significant advances in ET research, particularly in molecular pathology and targeted therapies. However, the heterogeneity of ET remains a major obstacle to personalized treatment. Future research should focus on further elucidating the pathogenesis of ET and improving stratified management approaches to achieve individualized precision therapy.

The number of bibliometric studies published in the scientific literature has been increasing in recent years. Some authors publish more bibliometric studies than others do. To identify authors who focus on bibliometric studies and their publication strategy is based on these studies. To determine whether the focus on bibliometric studies can be considered a successful publication strategy. A bibliometric analysis, including a citation analysis, was used to determine the results. The Scopus database was chosen as the source of bibliometric data. In total, 100 authors who frequently publish bibliometric studies were identified. For almost half of them, bibliometric studies can be considered the main or important part of their publication portfolio. A relatively small group of authors widely publishes bibliometric studies. The bibliometric indicators of these authors indicate that this specialization in bibliometric studies is quite successful.

This study introduces an ensemble model designed for real-time monitoring of bedridden patients.The model was developed using a unique dataset, specifically acquired for this study, that captures six typical movements. The dataset was balanced using the Synthetic Minority Over-sampling Technique, resulting in a diverse distribution of movement types. Three models were evaluated: a Decision Tree Regressor, a Gradient Boosting Regressor, and a Bagging Regressor. The Decision Tree Regressor achieved an accuracy of 0.892 and an R2 score of 1.0 on the training dataset, and 0.939 on the test dataset. The Boosting Regressor achieved an accuracy of 0.908 and an R2 score of 0.99 on the training dataset, and 0.943 on the test dataset. The Bagging Regressor was selected due to its superior performance and trade-offs such as computational cost and scalability. It achieved an accuracy of 0.950, an R2 score of 0.996 for the training data, and an R2 score of 0.959 for the test data. The study also employs K-Fold cross-validation and learning curves to validate the robustness of the Bagging Regressor model. The proposed system addresses practical implementation challenges in real-time monitoring, such as data latency and false positives/negatives, and is designed for seamless integration with hospital IT infrastructure. This research demonstrates the potential of machine learning to enhance patient safety in healthcare settings.

Autonomous systems are permanently in an ongoing interaction with the environment that surrounds them. Agency, in this sense, is often conceived as a system-environment asymmetry, where the system is able to influence the environment more than viceversa. Autonomous systems, however, are closed under information, meaning that they can only specify their own states by means of intelligent processes (unless we consider cognitive processes of higher order), even if they can influence and be influenced by physical processes outside of their mechanistic distinctions. Agency then, computationally speaking, should be understood as the causal effect that the system by means of its intelligent process can exert over itself, as in opposition to the environment. Being thus, we argue that a first measure of causality should capture the possibility of the system to withstand the effect of the environment over its future states, that is, to measure and compare the influence of the environment and the system, over the the system. We suggest that specific kind of mappings (represented as probability distributions) can increase the degree of underdetermination that can be quantified through information metrics (in particular, using entropy measure and the Earth Mover's Distance for comparisons) in the discrete case. After revising relevant related concepts, we introduce some mathematical formulations in the attempt to capture more formally the notion of underdetermination in autonomous systems. Finally, we exemplify these ideas and formulations through a toy-experiment in the the Game of Life cellular automaton.

This research work is an extension of a previous work in which the authors created an innovative family of fuzzy implication using as t-conorm probor, as fuzzy negation the 1-x and the type of Newton's binomial. The purpose of this paper is to compare the type of fuzzy implication probor with three other constructed fuzzy implications produced by max, Einstein and Lukasiewicz t-conorms maintaining in each case the same negation. T-conorms perform the fuzzy logical operation "or" of the corresponding fuzzy sets. The main methods used for the comparisons are the basic axioms of fuzzy logic. The authors performed six combinations of t-conorm comparisons, in order to find the rank order of the five fuzzy implications. Although the general type of fuzzy implication probor came out smaller than Hamacher, Einstein and Lukasiewicz and the type of Einstein smaller than Lukasiewicz authors make extensive tests using four different membership functions and different values to the parameter m so as to examine which out of the four fuzzy implications receive the best results. The application of isosceles trapezium to the fuzzy implications probor and Einstein give the best values (most values greater than or equal to 0.9 and equal to 1).

The productive sustainability of Pennisetum clandestinum in the Peruvian highlands was evaluated through productivity, growth and chemical composition. The effect of the nitrogen (N2) dose applied to the soil, the use of organic matter and the frequency of cutting or phenological age on the productive yields, chemical composition, plant height and growth rate of Kikuyu were determined. Experimentation was carried out under a randomised block design in divided plots. A multivariate analysis of variance (MANOVA) was used to determine the associated differences in each study factor. It was determined that applying 120 kg of N2 increases the annual protein production to 3 454.53 kg ha-1. yr-1, and a crude protein (CP) level of 23.54%, the distance of the live fences influences the biomass production to 19 176.23 kg DM ha-1 at an interval of 8.5 to 11.5 meters from the base of the cypress tree (Cupressus lusitanica). Organic matter favours the biomass yield of Kikuyu. Although there is no difference in dry matter production between 30 and 60 days of cutting, CP production is higher at 30 (p&lt;0.05). The highest DM production per day is obtained at 45 days, generating a higher biomass accumulation of 21 186.9 kg DM ha-1. yr-1. The consideration of Pennisetum clandestinum for dairy cattle is viable, taking into account that the possibility of implementing a plant improvement programme on this species is open, aimed at increasing the composition of the diet in high-production cows due to its high yield and good chemical composition in highland conditions.

As UAVs are increasingly employed across various industries, the demand for robust and accurate detection has become crucial. LiDAR has developed as a vital sensor technology because to its ability to offer rich 3D spatial information, particularly in applications such as security and airspace monitoring. This review systematically explores recent innovations in LiDAR-based drone detection, deeply focusing on the principle and components of LiDAR sensor, its classifications based on different parameters and scanning mechanisms, as well as the approaches for processing LiDAR data. The review briefly compares several deep learning approaches, including point-based, voxel-based, and hybrid models, that have improved drone detection, tracking, and classification. We also explore the integration of multi-modal sensor fusion, which combines LiDAR data with other complimentary modalities to improve UAV detection and tracking in complex environments such as GNSS-denied zones.

The increasing energy consumption and industrial activities that release carbon dioxide (CO2) emissions into the atmosphere have become one of the most serious environmental issues of today. This article discusses the current status in Azerbaijan regarding the development of effective approaches to reduce carbon emissions and ensure sustainable development, and it proposes relevant strategies for managing the carbon footprint. By exploring the interrelationship between the economy and the environment, it aims to contribute to the formation of more effective policies for managing CO2 emissions in Azerbaijan. According to the results of the econometric model established within the research for the period of 1990-2023, as the Azerbaijan economy grows, per capita CO2 emissions tend to increase, which can be linked to rising industrial activity, energy consumption, and other factors driving economic growth. The presence of a positive long-term relationship between population growth and per capita CO2 emissions can be attributed to higher overall energy consumption, increased demand for goods and services, and rising transportation needs. The strong correlation between economic growth and CO2 emissions suggests that it may be too early to assert the validity of the Kuznets curve for Azerbaijan economy as a developing country.

This study assessed the financial management practices and challenges of food cart businesses in Cabanatuan City, Nueva Ecija. The study used a descriptive research design and structured surveys and questionnaires to gather quantitative data from 20 food cart businesses. The data were analyzed using statistical tools such as weighted means, frequencies, and percentages to provide a comprehensive overview of these small enterprises' financial practices and challenges. Key findings highlight that while many businesses demonstrate basic financial literacy, significant gaps exist in financial record-keeping, budgeting, and revenue management. The study emphasizes the importance of improving these practices to ensure the sustainability and growth of food cart businesses. The research contributes to the broader discourse on small business management and economic development by identifying common challenges and offering targeted recommendations. The findings underscore the need for targeted interventions, such as financial training and policy support, to enhance the financial acumen of food cart owners. This study adds to the existing body of knowledge as it provides practical insights that can benefit business owners, policymakers, and community stakeholders in fostering a more resilient and economically vibrant local economy.

Super-resolution (SR) techniques have shown great promise in enhancing the resolution of MRI images, which are often limited by hardware constraints and acquisition time. Regularization-based methods, which incorporate prior knowledge into the SR process, have been especially effective in improving image quality and mitigating the effects of noise and blur. In this paper, we propose an advanced regularization method for MRI super-resolution that balances high-frequency detail preservation with noise suppression. By leveraging spatially adaptive regularization techniques and a robust denoising process, the proposed method outperforms traditional SR algorithms, as demonstrated on real-world MRI datasets.

Light quality within greenhouses is a critical factor for crop development and is essential for optimal photosynthetic activity. Modifying the optical properties of cover materials can significantly enhance crop performance. This study aimed to assess the effects of an experimental plastic cover, characterized by high transmittance of photosynthetically active radiation (PAR) and high light diffusivity, on the growth, yield, fruit quality, photosynthetic activity, and fungal disease incidence in two cucumber (Cucumis sativus L.) crops. The trials were conducted over two consecutive autumn-winter crop seasons in a multispan greenhouse divided into two sectors, separated by a vertical polyethylene sheet. The experimental plastic cover was installed in the West sector (40 m × 25 m), while a standard commercial cover was used in the East sector (40 m × 20 m). Results demonstrated that plants grown under the experimental cover exhibited an 8.5% and 15.3% increase in photosynthetic activity during the first and second crop seasons, respectively. PAR radiation at the canopy level was also higher in the experimental sector by 8% and 10.5% across both seasons. Additionally, marketable yield increased by 4.2% in the first season and 14.3% in the second season under the experimental cover. No significant differences were observed in fruit quality and plant growth parameters between the two sectors. The experimental plastic cover, with its high PAR transmittance and light diffusivity, enhanced the internal light environment of the greenhouse without incurring additional costs. This improved light environment positively influenced photosynthetic activity and yield in cucumber crops. Furthermore, a lower incidence of fungal diseases was observed in plants grown under the experimental cover during both crop cycles.

What is an observer? What is an observation? How do observations inform beliefs? What is the relationship between observers and physical objects in spacetime? These are central, and as yet unresolved, questions in the foundations of physics and consciousness science. We propose an answer taking consciousness as fundamental, resulting in a theory of conscious agents whose mutual interaction is governed by Markov chains. We describe observation via a new trace order on Markov chains. In this context, no observer is aloof: it must be an integral part of any system it observes. We find that the trace order forms a non-Boolean logic, mapping homomorphically to the “Lebesgue” logic” of probabilistic beliefs. We explore implications of conscious agent theory for the “hard problem” of consciousness, and propose a route to empirical tests using data from scattering experiments with subatomic particles.

Salt stress is an environmental factor that limits plant seed germination, growth, and survival. We performed a comparative RNA sequencing transcriptome analysis of the seeds during germination from two cultivars with contrasting salt tolerance responses. A transcriptomic comparison between salt-tolerant cotton cv Jin-mian 25 and salt-sensitive cotton cv Su-mian 3 revealed both similar and differential expression patterns between the two genotypes during salt stress. The expression of genes related to aquaporins, kinases, reactive oxygen species (ROS) scavenging, trehalose biosynthesis, and phytohormone biosynthesis and signaling that include ethylene (ET), gibberellin (GA), abscisic acid (ABA), jasmonic acid (JA), and brassinosteroid (BR) were systematically investigated between the cultivars. Despite the involvement of these genes in cotton's response to salt stress in positive or negative ways, their expression levels were mostly similar in both genotypes. Interestingly, a PXC2 gene (Ghir_D08G025150) was identified, which encodes a leucine-rich repeat receptor-like protein kinase (LRR-RLK). This gene showed an induced expression pattern after salt stress treatment only in salt-tolerant cv Jin-mian 25, but not salt-sensitive cv Su-mian 3. Our multifaceted transcriptome approach illustrated a differential response to salt stress between salt-tolerant and salt-sensitive cotton.

This study investigates the relationship between decentralized party organization and inclusive local participation in decision-making processes within Nigeria's two leading political parties: the People's Democratic Party (PDP) and the All Progressives Congress (APC), from 2015–2023. The study employed a multi-stage sampling technique to select 400 respondents, including national and local party leaders, assembly members, and grassroots members from the six geopolitical zones in Nigeria. A total of 384 valid responses were retrieved, yielding a 96% response rate. Data was collected through questionnaires administered via Google Forms, and distributed through email and social media platforms, particularly WhatsApp. Regression and correlation analyses reveal a significant positive relationship between decentralized party structures and inclusive local participation (r = 0.820, p < 0.05), with decentralized frameworks explaining 67.2% of the variance in inclusive local participation (R² = 0.672). However, regional disparities in the implementation of decentralization present challenges to its uniform effectiveness. This study emphasizes the importance of standardizing decentralization policies to enhance local decision-making, promote inclusiveness, and strengthen party institutionalization. The findings offer valuable insights for party leaders, policymakers, and researchers on how decentralization can promote internal democracy and foster stability within political parties.

Algeria ranks second after Afghanistan for the incidence of cutaneous leishmaniasis worldwide. As a result, it is critical to expand the traditional knowledge. Interviews were conducted with 21 herbalists in Annaba and El-Tarf provinces including 26 variables. The multiple correspondence analysis and the hierarchical clustering analysis were applied using the FactoMineR package. Nineteen species were reported and derived from thirteen plant families. Among them, the most important families were the Lamiaceae with five species. According to the Relative Frequency Citation value, the most famous species are the aerial parts of Teucrium polium L. (57.14%). Secondly, a data matrix for the species generated showed higher contribution values in the first dimension for the lack of the topical administration form, the presence of preparation’s mode by decoction and cataplasm, and the association of medicinal plants specifically with olive oil and honey, respectively. The analysis of the first dimension demonstrates a high association for three variables: Ta_F, Oa_F, and Dec_MP, with correlation ratios η2 of 6.261E-01, 5.501E-01, and 4.772E-01 (p&lt;0.05), respectively. Finally, the cluster analysis of species identified three clusters discriminated by the administration form per os with a p-value of 7.49E-05 (p&lt;0.05).

Cancer remains a primary cause of mortality, with over 18.1 million new cases and 9.6 million deaths globally in 2018. Chemotherapy, which utilizes a spectrum of cytotoxic drugs targeting rapidly dividing cancer cells, is a predominant treatment modality. However, the tendency of chemotherapeutics to induce drug resistance and exhibit non-specific cytotoxicity necessitates the development of new anticancer agents with heightened efficacy and minimized toxicity. In recent years, the discovery of safe and effective antibacterial/antiviral agents has also been a hot spot in medicinal chemistry. This paper comprehensively reviews the synthesis, anticancer/ antibacterial/antiviral activity, and structure-activity relationships of natural 1,4-naphthoquinones and their derivatives. It highlights their potential as efficient and low-toxicity anti-tumor and anti-infectious drug candidates.

Background: The early identification of patients at risk of peri-procedural complications and poor prognosis is very important. We conducted our study to determine if there are associations between serum orexigenic neuropeptide Y (NPY) concentration and nutritional status, and prognosis among patients undergoing surgery for colorectal cancer (CRC). Materials and Methods: A cohort study with a 3-month follow-up was conducted with 84 consecutive inpatients who underwent elective surgery in one center between 2016 and 2019 for primary CRC. In all patients, clinical characteristics and nutritional status were assessed. In a long-term follow-up (median; IQR: 1322; 930-1788 days; average 3.6 years), the patients’ survival status was checked during a telephone visit. Results: Before CRC surgery, patients with serum NPY concentration equal to or higher than the median value (661.70 pg/ml) had, in comparison to individuals with lower blood NPY concentration, higher scores in Mini Nutritional Assessment, Barthel, and Instrumental Activities of Daily Living (IADL) questionnaires, greater handgrip strength, a lower score in the Patient-Generated Subjective Global Assessment, almost a three times lower risk of perioperative complications, as well as, at the 3-month follow-up visit, higher Barthel and IADL scores and larger calf circumference. Higher blood NPY concentration was predictive of a low Nutritional Risk Screening 2002 score at the 3-month visit, and significantly influenced patients’ survival during the 1200 days after CRC surgery. Conclusions: Higher blood NPY concentration was associated with lower nutritional risk, more favorable patient nutritional and functional status, and better survival during the 1200 days after CRC surgery.

In Åhlberg (2021, 2022b), I presented evidence for 57 health-promoting substances that all green vascular WEPs contain. I continued searching for health-promoting substances in the plant cells' basic structures and processes. While reading research reports of five invasive species, I found eight more health-promoting substances all green vascular wild edible plants have. This article adds eight new substances to the earlier 57, bringing the total to 65. This is a novel finding for which I provide research evidence. I present the latest research on five invasive wild edible plants (WEPs) species. Each contains at least the same 65 health-promoting substances and a varying number of species-specific health-promoting substances. Each WEP has 1) shared health-promoting substances that all green vascular plants have and 2) species-specific health-promoting substances. I also present how many of these substances prevent Alzheimer’s disease, according to experimental research.

Fiber-optic Mach-Zehnder interferometers are widely used in research areas such as telecommunications, spectroscopy, and quantum information. These optical structures are known to be affected by phase fluctuations that are usually modeled as multiparametric noise.This multidimensional noise must be stabilized or compensated for to enable fiber-optic Mach-Zehnder architectures for practical applications. In this work, we study the effectiveness of a modified Perturb-and-Observe (P&amp;O) algorithm to control multidimensional phase noise in fiber-based multi-arm Mach-Zehnder interferometers. We demonstrate the feasibility of stabilizing multidimensional phase noise by numerical simulations using a simple feedback control scheme and analyze the algorithm’s performance for systems up to dimension 8x8. We achieved minimal steady-state errors that guarantee high optical visibility in complex optical systems with N×N matrices (with N=[2,3,4,5,6,7,8]).

This review highlights the therapeutic potential of epigallocatechin gallate (EGCG) and forskolin in managing retinal diseases, with a focus on glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy. EGCG, a potent polyphenol from green tea, exhibits significant antioxidant, anti-inflammatory, and neuroprotective effects, making it a promising candidate for reducing oxidative stress and inflammation in ocular tissues. Forskolin, a diterpene from Coleus forskohlii, increases cyclic AMP (cAMP) levels, which helps lower intraocular pressure (IOP) and provides neuroprotection. Both compounds target critical pathways involved in retinal disease progression, including oxidative stress, mitochondrial dysfunction, and inflammation, offering complementary therapeutic benefits. The review consolidates preclinical and clinical studies, highlighting the potential of EGCG and forskolin as adjunctive or alternative treatments for retinal diseases. Future research should explore the synergistic effects of these compounds, particularly in combination therapies aimed at addressing multiple pathogenic mechanisms in retinal health.

Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater Based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time and resource-efficient manner, as wastewater samples are representative of all cases within the catchment area, whether they are clinically reported or not. However, analysis and interpretation of WBS datasets for decision-making during public health emergencies, such as the COVID-19 pandemic, remains an area of opportunity. In this article, a database obtained from wastewater sampling at wastewater treatment plants (WWTPs) and university campuses in Monterrey and Mexico City between 2021 and 2022 was used to train simple clustering and regression-based risk assessment models to allow for informed prevention and control measures in high-affluence facilities, even if working with low-dimensionality datasets and a limited number of observations. When dividing weekly data points based on whether the seven-day average daily new COVID-19 cases were above a certain threshold, the resulting clustering model could differentiate between weeks with surges in clinical reports and periods between them with an 83.3% accuracy rate. Moreover, the clustering model provided satisfactory forecasts one week (79.2% accuracy) and two weeks (72.9%) into the future. However, the prediction of the weekly average of new daily cases was limited (R2 = 0.452, MAPE = 180.2%), likely because of insufficient dimensionality in the database. Overall, while simple, WBS-supported models can provide relevant insights for decision-makers during epidemiological outbreaks, regression algorithms for prediction using low-dimensionality datasets can still be improved.

The expanding Arabic user base presents a unique opportunity for researchers to tap into vast online Arabic resources. However, the lack of reliable Arabic word embedding models and limited availability of Arabic corpora pose significant challenges. This paper aims to address these gaps by conducting an experiment to train word embedding models with Arabic corpora and examine the influence of varying hyperparameter values on different NLP tasks. To gather data for training the models, we collected information from three distinct sources: Wikipedia, newspapers, and 31 Arabic books. Each corpus’s specific impact on the outcomes was analyzed. The experiment involved assessing the models across diverse NLP tasks, including sentiment analysis, similarity tests, and analogy tests. The findings revealed that both the corpus size and hyperparameter values had distinct effects on each test. In the Analogy test, employing a larger vocabulary size positively influenced the outcomes, with Fasttext models using skip-gram approaches performing well in solving Analogy Test questions. For sentiment analysis, we discovered that vocabulary size played a crucial role. In the similarity score test, Fasttext models achieved the highest scores, with lower window sizes and smaller vector sizes leading to better results. Overall, our models performed well, achieving a score of 99%, 90% accuracies for sentiment analysis and Analogy Test, respectively. Moreover, they achieved a similarity score of 8 out of 10. Our findings indicate that our models can serve as a valuable resource for Arabic NLP researchers, equipping them with a robust tool for handling Arabic text.

Bone fractures are common injuries that require quick and accurate diagnosis to provide the right medical care. The “convolutional neural network” technique relies mostly on manual inspection, by radiologists and can be laborious and prone to error. The objective of this work was to increase the efficiency and accuracy of fracture identification by automating the examination of X-ray images using convolutional neural networks. A “convolutional neural network” model created to detect bone fractures in X-ray images was used in the present study. The model was trained and validated using an extensive dataset of X-ray images, which included both fractured and nonfractured bones. Multiple convolutional layers were used in the “convolutional neural network” architecture for feature extraction, and pooling and fully connected layers were added for classification. The main measures used to assess the model's performance were sensitivity, specificity, and accuracy. In regard to identifying bone fractures, the “convolutional neural network”-based model outperformed the conventional technique. With significant gains in sensitivity and specificity, this approach achieved a high accuracy rate and decreased the frequency of false positives and false negatives. We used “convolutional neural network” tool in PyTorch for bone fracture detection and we outlined the important considerations that must be considered when attempting to achieve this goal Additionally, we contrasted every study with our baseline. Here our maximum accuracies were 99.05%, 98.60%, 99.45% and 99.74% for epochs 8, 9, 10 and 11, respectively. These findings highlight the model's ability to improve the diagnostic efficiency and accuracy in clinical settings. Using “convolutional neural network” to identify bone fractures from X-ray images is a promising development in medical imaging. In the end, our method improves patient outcomes by ensuring faster and more reliable fracture diagnosis while also lessening the diagnostic burden on radiologists. Subsequent investigations will focus on incorporating this system into clinical procedures and investigating its utilization in real-time emergency situations. Since there was no medical intervention on human subjects in this investigation, trial registration regulations were not applied.

Spontaneous preterm birth (sPTB), defined as live birth before 37 weeks of gestational age, is associated with immune dysregulation and pro-inflammatory conditions that profoundly impact newborn health. The question of immune integrity at the maternal-fetal interface is a focus of recent studies centring not only sPTB but the conditions often affiliated with this outcome. Regulatory T cells (Tregs) play a critical anti-inflammatory role in pregnancy, promoting fetal tolerance and placentation. Due to this gestational role, it is hypothesised that decreased or dysfunctional Tregs may be implicated in cases of sPTB. This review examines studies comparing Treg presence in healthy term pregnancies and those with sPTB-associated conditions, revealing conflicting findings across different conditions and within sPTB itself. Treg deficiencies may contribute to health issues in preterm newborns. Current sPTB treatments are limited, underscoring the potential of in utero therapies targeting inflammation, including T cell interventions. Future research aims to establish consensus on the role of Tregs in sPTB and associated conditions and advancing understanding of mechanisms leading to Treg deficiencies in adverse pregnancy outcomes.

Natural wood is generally perceived as expensive, while wood-based boards are cheap, but re-search has yet to explain definitively why these two materials receive such disparate evaluations. This study aimed to uncover the reasons behind this phenomenon by proposing an emo-tion-driven approach to material research. We collected 10 types of natural wood and artificial boards as experimental samples and tested 20 subjects' subjective evaluation of the samples and physiological indicators (electroencephalography and electrodermal activity). Through data analysis, we identified the relationships between the subjective and physiological data and the impact of material composition on these data. Specifically, we observed significant correlations between subjective and physiological data; however, no correlation was found between subjective and physiological valence. We also discovered that the components of materials significantly influence participants' subjective and physiological emotions. For example, materials with a rough texture elicited higher positive affectivity than those with a smooth texture, materials with coarse and mixed textures elicited higher positive affectivity than those with fine textures, and the brighter materials evoke more positive emotions in participants. This study revealed how material components influence participants' emotions and, more importantly, analyzed the processing techniques behind these components, providing a theoretical basis for the future development of high-value-added products made from wood-based boards.

Large genomic rearrangements of PALB2 gene, particularly deletions and duplications, have been linked to hereditary breast-ovarian cancer. Our research specifically focuses on delineating the intronic breakpoints associated with rearrangements of PALB2 exon 11, which is crucial for understanding the mechanisms underlying these genomic changes in patients with hereditary breast and ovarian syndrome. By next-generation sequencing, we identified one duplication and three deletions of PALB2 exon 11, confirmed by Multiplex Ligation-Dependent Probe Amplification analysis. To assess the impact on transcription and potential splicing issues, Reverse-Transcription PCR was performed on patients' RNA. For detailed characterization of intronic breakpoints, primer walking approach and long-range PCR were implemented, followed by Sanger sequencing. Our analysis revealed a tandem duplication of 5134 base pairs (bp) mediated by AluY repeats located in introns 10 and 11, respectively. Moreover, identical deletions were identified in three unrelated patients, encompassing an approximate 8050 bp region mediated by AluSx elements. Both genomic alterations resulted in a truncated PALB2 protein due to introduction of a premature stop codon. This study underscores the remarkable instability of intronic regions flanking exon 11 of PALB2 and identifies a previously unreported hotspot involving Alu repeats with very high sequence homology in introns 10 and 11 of the gene. Our findings suggest avenues for further research, such as investigating the prevalence of similar genomic rearrangements in larger cohorts and exploring functional studies to understand how these alterations contribute to hereditary breast cancer pathogenesis.

Background and Objective: Diabetes Mellitus is a long-term, multifaceted metabolic condition that necessitates ongoing medical management. Hypogonadism is a syndrome that is a clinical and/or biochemical indicator of testosterone deficiency. Cross-sectional studies have reported that 20-80.4 % of all men with Type 2 diabetes have hypogonadism, and Type 2 diabetes is related with low testosterone. This study presents an analysis of the use of ML and EL classifiers in predicting testosterone deficiency. In our study, we compared optimized traditional ML classifiers and three EL classifiers using grid search and stratified k-fold cross-validation. We used the SMOTE method for the class imbalance problem. Methods: This database contains 3397 patients for the assessment of testosterone deficiency. Among these patients, 1886 patients with type 2 diabetes were included in the study. In the data pre-processing stage, firstly outlier/excessive observation analyses were performed LOF and missing value analyses were performed with random forest. The SMOTE is a method for generating synthetic samples of the minority class. Four basic classifiers, namely MLP, RF, ELM and LR, were used as first level classifiers. Tree ensemble classifiers, namely ADA, AGBoost, and SGB, were used as second level classifiers. Results: After SMOTE, while the diagnostic accuracy decreased in all base classifiers except ELM, sensitivity values increased in all classifiers. Similarly, while the specificity values decreased in all classifiers, F1 score increased. The RF classifier gave more successful results on the base-training dataset. The most successful ensemble classifier in the training dataset was the ADA classifier in the original data and in the after SMOTE data. The testing data, XGBoost is the most suitable model for your intended use in evaluating model performance. XGBoost, which exhibits a balanced performance especially when SMOTE is used, can be preferred to correct class imbalance. Conclusions: SMOTE is used to correct the class imbalance in the original data. However, as seen in this study, when SMOTE was applied, the diagnostic accuracy decreased in some models, but the sensitivity increased significantly. This shows the positive effects of SMOTE to better predict the minority class.

Objective: Colorectal cancer (CRC) is the third most prevalent malignant tumor type and the second leading cause of cancer-related death. Sequence similarity family 50 member A (FAM50A) plays a vital role in numerous disease processes, including tumor progression. This study aimed to evaluate the prognostic significance of FAM50A in CRC and to explore its role in CRC cell proliferation. Methods: The Cancer Genome Atlas (TCGA) database was used to assess the mRNA expression levels of FAM50A in CRC. Immunohistochemical staining was used to study the expression of FAM50A in CRC tissues. Patient survival data were used to assess the prognostic significance of FAM50A in CRC using Kaplan–Meier analysis and Cox regression analysis. The Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine, and colony-formation assays were employed to assess the impact of FAM50A knockdown on tumor cell proliferation. Co-expression and correlation heatmaps were used to identify genes whose expression levels were highly correlated with FAM50A, and to further investigate the possible mechanism of action of FAM50A in CRC cell proliferation. Results: Analysis of data from TCGA database revealed a notable upregulation of FAM50A expression levels in CRC tissue compared with adjacent normal tissue. Moreover, FAM50A expression was positively correlated with N, M, and TNM stages in 145 patients with CRC. Cox regression analysis and construction of a nomogram revealed that high FAM50A expression was a prognostic indicator for poor overall survival in patients with CRC. Knockdown of FAM50A decreased cell proliferation ability, the proportion of EdU positive cells, and the number of CRC cell colonies, whereas overexpressing FAM50A promoted proliferative phenotypes. The expression levels of three genes in CRC were significantly negatively correlated, while the expression levels of 18 genes were significantly positively correlated, with the expression level of FAM50A. Conclusion: FAM50A may be a novel prognostic marker for CRC, and may participate in regulating tumor progression by interacting with some highly correlated molecules that drive CRC cell proliferation.

This paper presents in detail the foundation of security theory for ``Quantum stream cipher based on Holevo-Yuen theory". This type of cipher is a technology that provides information-theoretic security (ITS) to optical data transmission by randomizing ultrafast optical communication signals with quantum noise. In general, a quantitative security of ITS is discussed in terms of unicity distance in Shannon theory. However, the quantum version requires modeling beyond the Shannon model of random cipher to utilize the characteristics of the physical layer. Therefore, as first step, one has to develop a generalized unicity distance theory and apply it to evaluation of security. Although a complete theoretical formulation has not yet been established, this paper attempts to give a primitive structure of a generalization of Shannon random cipher and shows that the realization of this is generalized quantum stream cipher. In addition, we introduce several implementation methods of the generalized quantum stream ciphers and their security performances.

The integration of artificial intelligence, particularly Large Language Models (LLMs), has the potential to significantly enhance therapeutic decision-making in clinical oncology. Initial studies across various disciplines have demonstrated that LLM based treatment recommendations can rival those of multidisciplinary tumor boards (MTBs); however, such data are currently lacking for urological cancers. This study provides the methodological foundation for the prospective CONCORDIA trial, which will generate this data for the first time. In this preliminary work, we evaluated the proposed measurement tool for the CONCORDIA study -the System-Causability-Scale (SCS) and its modified version (mSCS) - based on recommendations from ChatGPT-4 and an MTB for 40 urological cancer-scenarios. Both scales demonstrated strong validity, reliability (all aggregated Cohen’s K &gt; 0.74), and internal consistency (all Cronbach’s Alpha &gt; 0.9), with the mSCS showing superior reliability, internal consistency, and clinical applicability (p&lt;0.01). Two Delphi processes were used to define the LLMs to be tested in the CONCORDIA study (ChatGPT-4 and Claude 3.5 Sonnet) and to establish the acceptable non-inferiority margin for LLM recommendations compared to MTB recommendations. The forthcoming ethics-approved and registered CONCORDIA non-inferiority trial will require 110 urological cancer scenarios, with an mSCS difference threshold of 0.15, a Bonferroni corrected alpha of 0.025, and a beta of 0.1. Blinded mSCS assessments of MTB recommendations will then be compared to those of the LLMs. In summary, this work establishes the necessary prerequisites prior to initiating the CONCORDIA study and validates a modified score with high applicability and reliability for this and future trials.

Objectives: The Implicit Prosody Hypothesis (IPH) posits that individuals generate internal prosodic representations during silent reading, mirroring those produced in spoken language. While converging behavioral evidence supports the IPH, the underlying neurocognitive mechanisms remain largely unknown. Therefore, this study investigated the neurophysiological markers of sensitivity to speech rhythm cues during silent word reading. Methods: EEG was recorded while participants silently read four-word sequences, each composed of either trochaic words (stressed on the first syllable) or iambic words (stressed on the second syllable). Each sequence was followed by a target word that was either metrically congruent or incongruent with the preceding rhythmic pattern. Results: Single-trial event-related potentials (ERPs) and time-frequency representations (TFRs) triggered by the target words were examined using a hierarchical mass univariate general linear modeling approach to investigate the effects of metrical expectancy and stress type. ERP findings revealed significant differences based on expectancy, with words carrying unexpected stress eliciting larger negativities between 240-628 ms after word onset. TFRs further revealed that different frequency bands were sensitive to distinct aspects of rhythmic structure in language. Alpha activity, linked to attention, reflected expectations about the rhythmic pattern. Theta and beta activity, associated with processing rhythm and timing, were sensitive to both the expected rhythm and the specific location of stressed syllables within words. Conclusions: These findings highlight comparable neurophysiological responses to both implicit and explicit speech rhythm, further supporting the IPH and emphasizing the role of prosody in silent reading.

Pursuing sustainable energy solutions has prompted researchers to focus on optimizing energy extraction from renewable sources. Control laws that optimize energy extraction require accurate modeling, often resulting in time-varying, nonlinear differential equations. An energy-maximizing optimal control law is derived for time-varying, nonlinear, second-order, energy harvesting systems. We demonstrate that sustaining periodic motion under this control law when subjected to periodic disturbances necessitates identifying appropriate initial conditions, inducing the system to follow a limit cycle. The general optimal solution is applied to two point absorber wave energy converter models: a linear model where the analytical derivation of initial conditions suffices and a nonlinear model demanding a numerical approach. A stable limit cycle is obtained for the latter when the initial conditions lie within an ellipse centered at the origin of the phase plane. This work advances energy-maximizing optimal control solutions for nonautonomous nonlinear systems with application to point absorbers. The results also shed light on the significance of initial conditions in achieving physically realizable periodic motion for periodic energy harvesting systems.

This paper explores the application of AI-guided instruction combined with Alternate Reality Games (ARG) to enhance learning performance, specifically focusing on students' learning emotions, engagement, and control beliefs. Based on the Retrieval-Augmented Generation (RAG) Large Language Model (LLM) framework, this study aims to address challenges caused by traditional AI-led instruction, such as emotional detachment and learning disengagement. By integrating immersive ARG experiences, the study evaluates the learning outcomes of students with different cognitive styles in an introductory digital learning course. A qualitative grounded theory approach is used, analyzing data from interviews with 65 students to understand their learning experiences. The findings indicate significant improvement in students' engagement, emotional connections, and sense of control over their learning process when ARG elements were incorporated. Implications for the future of digital learning, as well as recommendations for addressing challenges in AI-enhanced education, are discussed.

Hyperbaric oxygen therapy (HBOT) involves inhaling nearly 100% oxygen in a pressurized environment and is commonly used to treat various diseases and injuries. Despite its well-known safety, HBOT is associated with complications, with frequent middle ear barotrauma (MEB) and oxygen toxicity. Understanding the characteristics and risk factors associated with these complications is critical for improving patient’s compliance and treatment outcomes. This retrospective multicenter study aimed to analyze the characteristics and factors associated with complications during HBOT using a computer-controlled pressurized monoplace hyperbaric chamber. We conducted a retrospective observational study across two tertiary hospitals in Korea, involving patients who received HBOT from October 2017 to June 2020. Data were extracted from electronic medical records and hyperbaric chamber logs, including patient demographics, medical history, HBOT indications, and details of complications. Statistical analyses, including chi-square and t-tests, were used to compare variables. A total of 247 patients (mean age: 59.35 ± 15.05 years, 63.56% male) were included. The most common indications for HBOT were sudden sensorineural hearing loss (27.94%) and post-graft/flap (24.29%). Hypertension (46.15%) and diabetes mellitus (39.27%) were the most frequent comorbidities. Otalgia was the most prevalent side effect (33.20%), followed by chest discomfort (2.02%) and headache (1.62%). A significant proportion of patients (11.74%) terminated HBOT due to complications, with most pauses occurring at pressures between 1.2 to 1.4 ATA (26.67%). Complications, particularly otalgia, significantly impact patient compliance with HBOT. The incidence of complications varies by pressure level during treatment, suggesting the need for tailored strategies to minimize complications. This study highlights the importance of patient monitoring and education to improve the safety and efficacy of HBOT in monoplace chambers.

The increasing environmental concerns related to no-biodegradable plastics have driven the development of biodegradable alternatives derived from renewable resources. Polylactic acid (PLA), a biodegradable polymer known for its favorable mechanical strength and biocompatibility, suffers from brittleness and poor ductility. This study aims to improve the flexibility of PLA by blending it with polycaprolactone (PCL) and polyethylene oxide (PEO). Specifically, thin films were fabricated from neat PLA, PCL, PLA/PCL, and PLA/PEO blends using both electrospinning and solvent casting to investigate the effects of processing methods on their mechanical behavior. The films were characterized using SEM, FTIR, XRD, DSC, uniaxial tensile testing, and water contact angle measurements. The surface morphology of single electrospun fibers was further examined using AFM. We found that electrospun PLA films exhibited higher elongation at break and ultimate strength with a slightly lower Young’s modulus in comparison to its solvent-cast films. FTIR, XRD, and DSC analyses consistently showed that the electrospun PLA films had significantly lower crystallinity compared to their solvent-cast counterparts. Notably, AFM phase imaging revealed that the electrospun PLA fibers exhibited an aligned crystalline structure. Blending PLA with PCL significantly improved elongation at break in electrospun films, which, unlike solvent-cast blends, retained a Young's modulus comparable to electrospun PLA. This improvement is likely due to reduced phase separation and enhanced crystalline alignment. Furthermore, electrospun films of neat PLA, PCL and PLA/PCL blends were more hydrophobic than their solvent-cast counterparts. Although PLA/PEO blends demonstrated enhanced surface hydrophilicity, they exhibited a marked reduction in mechanical properties. Overall, this study demonstrates that electrospinning effectively enhances the flexibility and mechanical performance of PLA-based films by mitigating the effects of poor miscibility in polymer blends and promoting molecular alignment. These findings suggest that electrospinning is a promising processing method for producing PLA-based films with enhanced flexibility and mechanical integrity, without the need for plasticizers or compatibilizers.

Interspecific competition between mosquito larvae may affects adult vectorial capacity, potentially reducing disease transmission. It also influences population dynamics, cannibalistic and predatory behaviors. However, knowledge of interspecific competition between Ae. aegypti and Anopheles species is limited. The study examined interspecific competition between Ae. aegypti larvae and either An. arabiensis, An. gambiae, or An. funestus on individual fitness in semi-field settings. The experiments involved density combinations of 100:100, 200:0, and 0:200 (Ae. aegypti: Anopheles), reared with and without food, in small habitat (8.5 cm height × 15 cm diameter) with 0.5 litre and medium habitats (15 cm height × 35 cm diameter) with 1 litre of water. The first group received Tetramin® fish food (0.02 g), while the second group was unfed to assess cannibalism and predation. While, interspecific competition affected both genera, Anopheles species experienced greater effect, with reduced survival and delayed development, compared to Ae. aegypti. The mean wing lengths of all species were significantly small in small habitats in mixed population (p &lt; 0.001). The presence of food reduced cannibalism and predation compared to its absence. These interactions have implications for diseases transmission dynamics and can serve as biological indicators to signal the impacts of vector control interventions.

Polyamines (PA), such as putrescine, spermine, and spermidine, are bioactive molecules that play a vital role in plant responses to stresses. Although they are frequently applied to achieve higher levels of stress tolerance in plants, their function in seed biology is still not fully under-stood. Only in a few papers PA were described as seed priming agents, but most of the data re-port only the physiological and biochemical PA effects, and only a few of them concern the molecular mechanisms. In this review, we summarized PA seed priming effects on germination, seedling establishment, and young plant response to abiotic stresses, and tried to draw a general scheme of PA action during early developmental plant stages.

Ice cream is popular but contains high amounts of saturated fats and few health-promoting ingredients. In the presence of xanthan gum (0.25%), the blueberry peel particles prepared through ball-milling treatment (BMP) were used to prepare ice cream containing camellia oil as a fat replacer. BMP possessed smaller particle sizes, larger contact angles, and higher contents of anthocyanin aglycone, as compared with commonly-milled blueberry peel particles. BMP with the smallest D_[4,3] value (about 10 μm) and the largest contact angle (66.30°) were obtained by ball-milling the blueberry peel at 15 Hz for 6 h (BMP_{15 Hz 6 h}). The ice cream mixes were depicted as linear viscoelastic gel-like solids, and their apparent viscosity, G′ and G′ increased with the increase in BMP_{15 Hz 6 h} concentrations. Ice cream with strong antioxidant activity and good freeze-thaw stability was acceptable and desirable in the presence of less than 0.5% BMP_{15 Hz 6 h}.

A contribution of Epstein-Barr Virus (EBV), Human Cytomegalovirus (HCMV), and certain types of Human Papilloma Virus (HPV) to the overall pathogenesis of upper airways cancers seems a priori reasonably conceivable. The existing evidence mostly relates them to nasopharyngeal squamous and undifferentiated carcinomas; indications emerge about their involvement in other upper airways cancers too. Markers of EBV, HCMV, HPV16, HPV18, (and Mycoplasma pneumoniae as a negative control) were searched in a series of 68 samples of neoplastic tissues from 57 patients diagnosed with different upper airways cancers. The results provide clues in favor of an actual role of EBV, HCMV, and HPV18, in the web of causation of upper airways squamous and undifferentiated carcinomas, possibly of upper airways adenocarcinomas too.

We study the crossed Andreev reflection and the nonlocal transport in the staggered graphene/superconductor/periodic line defect superlattice (LDGSL) junctions. The staggered pseudospin potential in the left graphene electrode suppress the local Andreev reflection, while the elastic cotunneling of K′ valley electrons is inhibited due to the exclusive rightward motion of K valley electrons in the right LDGSL electrode, thereby enabling the realization of perfect intravalley crossed Andreev reflection for incident electrons from the K′ valley. Meanwhile, the intravalley elastic cotunneling occurs while both local Andreev reflection and crossed Andreev reflection are completely eliminated for incident electrons in the K valley. Furthermore, the probability of intervalley crossed Andreev reflection scattering is significantly lower than that of intravalley CAR scattering across a broad range of incident angles and electron energies. Our results are helpful for designing the flexible and high-efficiency Cooper pair splitter based on the valley degree of freedom.

Physical properties such as shape, volume, and size influence the dynamics of biological systems. In this context, we focus on the geometric properties of limb movements and their physiological and biomechanical effects. Using hand grasping as a paradigmatic example, we describe how dynamic changes in geometric configuration can affect the pathophysiology of grasping. We focus on precision pinch, the simplest and most basic form of grasping, where one finger remains stable while another moves against it (Brand and Hollister, 1999). The thumb and index finger come together to grasp small objects with great precision, such as a pen. During the precision pinch, the geometric configuration of the hand changes, modifying the distribution of forces and the functional connectivity between the fingers. These changes may offer a new approach to the biomechanics of artificial arms. While current approaches consider grasps as homogeneous structures, we argue that local variations in hand geometry can lead to new biomedical effects with intriguing operational implications.

Harmful cyanobacterial blooms produce cyanotoxins which can adversely affect humans and animals. Without proper monitoring and detection programs, tragedies such as the loss of pets or worse are possible. Multiple factors including rising temperatures and human influence contribute to the increased likelihood of harmful cyanobacteria blooms. Current approaches to cyanobacteria and their toxins monitoring included microscopic methods, immunoassays, liquid chromatography coupled with mass spectrometry (LCMS), and molecular methods such as qPCR. This review highlights current research into early detection methods for harmful cyanobacterial blooms and the pros and cons of these methods.

Purpose: The study aims to investigate racial disparities in fall-related injuries among Black and White breast cancer survivors who received chemotherapy, focusing on the risks associated with different chemotherapy regimens. Methods: This retrospective cohort study involved 11,400 breast cancer survivors (Stage 1-3) treated with chemotherapy between January 1, 2019, and December 31, 2023. Chemotherapy types studied include Doxorubicin, Cyclophosphamide, Paclitaxel, Docetaxel, and Carboplatin. Logistic regression and descriptive analyses were used to assess fall risk associated with each chemotherapy type, stratified by race. Results: The overall fall-related injury rate was higher among Black survivors (14.7%) compared to White survivors (10.0%), with a significant difference in fall risk between the two groups (p < 0.001). Fall risk was notably elevated for Black patients treated with Cyclophosphamide, Docetaxel, and Carboplatin. Conclusions: The findings highlight significant racial disparities in fall-related injuries among breast cancer survivors receiving chemotherapy. These disparities may be influenced by socioeconomic factors and healthcare access. Implications for Cancer Survivors: Interventions targeting fall prevention and equitable healthcare access are critical to reducing these disparities among Black breast cancer survivors.

Thoracic ultrasonography (TUS) has emerged as a critical tool in the diagnosis and management of respiratory diseases in cattle, particularly bovine respiratory disease (BRD), which is one of the most economically significant health issues in feedyard operations. The objective of this review is to explore TUS in veterinary medicine including the historical development, methodologies, and clinical applications for diagnosing and prognosing respiratory diseases. The review also emphasizes the importance of operator training, noting that even novice operators can achieve diagnostic consistency with proper instruction. Ultrasound was introduced in the mid-20th century for back-fat thickness measurements, TUS has evolved to offer a non-invasive, real-time imaging modality that allows for the detection of lung and pleural abnormalities such as consolidations, pleural effusions, and B-lines. These features are vital indicators of respiratory disease, and their early identification through TUS can significantly improve clinical outcomes. Compared to traditional diagnostic methods like auscultation or radiography, TUS provides superior accuracy in detecting both subclinical and advanced respiratory conditions, particularly in high-risk populations. Furthermore, TUS has demonstrated strong prognostic value, with studies showing that the extent of lung consolidation correlates with higher relapse risk, reduced growth performance, and increased mortality.

Oxidosqualene cyclases (OSCs), enzymes are responsible for converting linear triterpenes into teracyclic ones, which known as precursors of other important and bioactive metabolites. Two OSCs genes encoding parkeol synthase and lanostadienol synthase have been found in representatives of the genera Apostichopus and Stichopus (family Stichopodidae, order Synallactida). Since the limited number of sea cucumber OSCs were so far studied, OSCs encoding gene(s) of the sea cucumber Eupentacta fraudatrix (family Sclerodactylidae, order Dendrochirotida) were investigated to fill this gap. Here we employed RACEs, molecular cloning and Oxford Nanopore Technologies to identify candidate OSC mRNAs and genes. The assembled cDNAs were 2409 bp (OSC1) and 3263 bp (OSC2) which were shared the same CDS size of 2163 bp encoding a 721-amino-acid protein. The E. fraudatrix OSC1 and OSC2 had higher sequence identity to each other (77.5%) than to other holothurian OSCs (64.7–71.0%). According to the sequence and molecular docking analyses, OSC1 with L436 is predicted as parkeol synthase, while OSC2 with Q439 is predicted as lanostadienol synthase. Based on the phylogenetic analysis, E. fraudatrix OSCs cDNAs clustered with other holothurian OSCs forming the isolated branch. As a result of gene analysis, high polymorphism and larger size of the OSC1 gene suggest that this gene may be an ancestor of the OSC2 gene. These results implied that E. fraudatrix genome contains two OSC genes with different from Stichopodidae OSCs genes evolutionary pathway.

Detection of volatile organic compounds (VOCs) is a rapidly growing research area due to importance of VOCs in environmental pollution, human health assessment, food quality control, and homeland security. Optical sensing materials based on porphyrins are particularly appealing for VOCs detection, owing to availability of porphyrins, their exceptional optical and binding properties, as well as their photo- and chemical stability. As research and technology continue to advance, optical sensors involving these materials are expected to play an increasing role in various applications. This article presents a comprehensive overview of porphyrin-based sensing materials developed for use as optical sensors for VOCs. First, sensing films composed exclusively of porphyrin molecules are discussed followed by materials obtained by grafting or incorporation of porphyrins into organic and inorganic polymer matrices. Considering growing interest to multianalyte analysis with porphyrin-based sensor arrays, special section is devoted to this area.