Leydig cells, pivotal for male fertility, undergo significant oxidative stress due to their proximity to macrophages and reactive oxygen species (ROS) generated by extracellular structures. This stress disrupts Leydig cell function, impairing steroidogenesis and spermatogenesis, ultimately leading to male infertility. Oxidative stress triggers apoptosis and inhibits testosterone production, crucial for spermatogenesis regulation. Understanding the mechanisms of oxidative stress and antioxidation on Leydig cells is vital. Some studies highlight the role of antioxidants in mitigating oxidative damage, emphasizing critical pathway of Sirt1 in oxidative stress and Nrf2 in antioxidation. Future research should focus on screening antioxidant substances and optimizing antioxidant dosages for Leydig cell protection and testosterone restoration, thereby enhancing reproductive performance. This review provides insights into combating male infertility by addressing Leydig cell oxidative stress and antioxidation.

This study aimed to develop fermented cashew nut cheese alternative supplemented with Chondrus crispus and Porphyra sp. for enhancing their nutritional and sensory characteristics, as well as familiarizing consumers with seaweeds consumption. The impact of seaweeds supplementation was evaluated through analysis of some physicochemical, microbiological and organoleptic properties of the developed food products. The total lipids content decreased with the supplementation with seaweeds. Crude protein content also slightly decreased, while elemental analysis showed that mineral and trace elements (Ca, K, Mg, Na, Fe, I, Se, and Zn) content increased when C. crispus was added to the paste. The analyses of color and textural (TPA) attributes showed that theese were significantly influenced by adding seaweeds to the cashew paste. Generally, the microbiological results comply with the different European guidelines for assessing the microbiological safety of ready-to-eat foods placed on the market, except for aerobic mesophilic bacteria and marine agar counts. Flash Profile analysis al-lowed to distinguish samples attributes, showing an increased flavor complexity of plant-based cheese alterna-tives supplemented with seaweeds. Overall, the study indicates that seaweed enrichment mainly influenced the physicochemical and sensory characteristics of plant-based cheese alternatives.

The correlation of periodic seasonal vertical ground movement (SVGM) with climatic data from earth observation was investigated in this work. The European Ground Motion Service (EGMS) vertical ground movement measurements, provided from 2018 to 2022, were compared with temperature and precipitation data from MODIS and CHIRP datasets respectively. Measurement Points (MP) from EGMS over Italy provided a value of ground vertical movement approximately every 6 days. Precipitation and temperature datasets were processed to provide Drought Code (DC) maps calculated ad hoc for this study at 1 km spatial resolution and daily temporal resolution. Seasonal patterns were analysed to assess correlation with Spearman’s rank correlation coefficient (ρ) between this measure and DC from Copernicus CEMS (DCCEMS) and from MODIS+CHIRP (DC1km) and from temperature. Results over the considered area (Italy) showed that 0.46% of all MPs (32 826 MPs out of 7 193 676 MPs) have a ρ greater than 0.7: 12 142 of those have positive correlation, and 20 684 have negative correlation. DC1km was the climatic factor that provided the higher number of correlated MPs, roughly giving +59% more correlated MPs than DCCEMS and +300% than temperature data. If ρ greater than 0.8 was considered, the number of MPs drops by a factor of 10; from 12 142 to 1 275 for positive correlation and from 20 684 to 2 594 for negative correlation between DC1km values and SVGM measurements. Correlations lagged in time resulted in most of the correlated MPs being inside a window of +/- 6 days (a single satellite overpass time). Because DC and temperature are strongly co-linear, further analysis to assess which is better at explaining the seasonality of MPs was carried out, resulting in DC1km significantly explaining more variance of the SVGM than temperature for the inversely correlated points more than the directly correlated points. Spatial distribution of correlated MPs shows that they are unevenly distributed in clusters the Italian territory. This work will lead to further investigation both at local scale and at a pan-European scale. An interactive WebGIS application open to the public is available for data consultation. Data are shared in a public repository for replication of the method.

Plant-microbe interactions are pivotal in a plant's growth and development. Mycor-rhizal fungi, in particular, play a crucial role in maintaining sustainable agroecosys-tems through symbiotic relationships with plant roots, improving soil health, facili-tating nutrient uptake, and enhancing plant stress resilience. Arbuscular mycorrhizal (AM) fungi enhance plant growth by increasing the absorption of essential nutrients, particularly phosphorus, nitrogen, potassium, zinc, and copper. The mutualistic rela-tionship between AM fungi and plants promotes a balanced microbial community and improves soil structure by forming stable soil aggregates. Additionally, mycorrhizal fungi increase plant tolerance to abiotic stresses, including drought, salinity, and heavy metal toxicity, by regulating osmotic balance, producing antioxidants, and altering exudatemorphology. It also negate harmful effects of high soil phosphorus levels and bolster plant resilience to environmental stresses. Beneficial microorganisms, such as potassium-solubilizing microbes and nitrogen-transforming bacteria, further enhance the functionality of mycorrhizal associations. Furthermore, mycorrhizal fungi con-tribute to plant health by reducing the incidence of root pathogens and soilborne dis-eases. However, the sustainability of mycorrhizal fungi is threatened by intensive agricultural practices, including heavy tillage, continuous monoculture, and excessive use of chemical fertilizers and pesticides. These practices disrupt hyphal networks and reduce microbial diversity, compromising mycorrhizal functionality. Alternatively, sustainable farming practices such as reduced tillage, crop rotation, and organic amendments are recommended to support healthy mycorrhizal populations. By adopting these practices, we can achieve long-term agricultural productivity while maintaining a healthy soil environment.

Tantalum powder is included into the composition of Non-Adhesive Gel-like Embolic Materials (NAGLEMs) for X-ray opacity. The duration of X–ray opacity during embolization is primarily associated with the particle size, which differs in the most used NAGLEMs - ONYX (Medtronic) and SQUID (Balt). NAGLEMs are widely used for embolization of branches of the middle meningeal artery (MMA) in patients with chronic subdural hematomas (CSDH). Considering the size (5-15 microns) of the target dural vessels, we assumed that not only the viscosity of NAGLEMs, but also the size and shape of tantalum granules may be important for the penetration of these gel-like embolic agents and determine their behavior. We obtained a significant difference – the sample SQUID 18 contains medium-sized granules, which are ten times smaller than the tantalum granules in the sample ONYX 18- 0.443± 0.086 (M ± SD) vs 5.2± 0.33 (M ± SD). Tantalum granules in SQUID 18 have a regular spherical shape, in ONYX 18 they have an irregular angular shape. When comparing the behavior of gel-like embolic agents of the same viscosity during MMA embolization in patients with CSDH (an average age of 62.2 ± 14.3 years), in the group, where SQUID 18 (n=8) was used, the gel-like embolic agent in dural vessels demonstrated significantly greater penetration ability compared with the group where ONYX 18 (n=8) was used. Accordingly, not only the viscosity of NAGLEMs, but also the size and shape of tantalum granules can have a significant effect on the penetration ability of gel compositions.

A new model of gravity is presented here that is similar to MOND and Chameleon theory but uses an Entropic Gravity approach that is not based fundamentally on the First Law of Thermodynamics. Instead, the Second Law of Thermodynamics will be mainly used here as it was applied in Black Hole Physics via the Area Theorem and the Holographic Principle. The Area Theorem was considered here to imply, not only that the total area of the event horizon will never shrink when entropy increases, but also that the mass or energy content within the black hole will always be greater than the original mass-energy input, though not necessarily violating the energy conservation law. This black hole property will be extended to include even a non-black hole setting. Moreover, the approach does not use the Equipartition Theorem to relate energy to temperature ($E=Nk_{b}T$) instead we used Vopson's Energy-Mass-Information Equivalence Principle ($E=k_{b}T\ln(\Omega)$). The theory uses $E=NE_{p}$, for the total energy of a massive object where $E_{p}$ is the Planck Energy and $N$ is the number of Planck Energy to represent the amount of information within the limit set at the Planck scale. It is shown here that gravity emerges whenever information is updated within a given volume of space with a magnitude that is defined not only by the gravitating matter but also by the energy generated in space within the vicinity of the gravitating matter. The model is the first to consider the role of both spacetime and matter as a medium to store information and apply it to describe gravity in a fundamental way.

The problem of land degradation has become a global issue. It is primarily caused by direct destruction of the natural ecosystems, irrational use and depletion of the land resources, and the growing agro-technogenic load on soils. The current state of sloped agricultural landscapes is characterized by a significant increase in the area of soils with varying degrees of erosion that require the development of scientifically based measures to protect against the erosion processes for the purpose of their further environmentally safe use, taking into account the requirements of sustainable development of the land use and farming systems, and the agricultural sphere, as a whole. There has been obtained and summarized modern scientific information on the development of adaptive-ecological and organizational-economic measures for the conservation (establishment) of erosion-degraded and low-productivity soils of arable sloped lands through the environmentally sound use of agricultural lands, the development and implementation of a soil-protective adaptive-landscape farming system. Contemporary scientific research has been carried out by means of field route studies and land inventory to determine the geomorphological and soil characteristics of the studied polygons, taking into account the basic principles of application in the geospatial analysis and practical use in the landscape studies by means of the Auto CAD computer program, the boundaries of the polygons - watersheds on raster topographic maps being determined, digitized in the local coordinate system (SK-63). The research methodology included the collection and analysis of cartographic and field experimental materials to determine the geoecological situation of the formation and manifestation of spatio-temporal erosion-hydrological processes in the area studied, conducting scientific research to study the erosion and washout of soils in the key areas, agricultural landscape polygons, determining the influence of natural and anthropogenic factors upon the estimated intensity of the erosion processes, and office processing of the results, obtained in the field. The reliability and validity of the results are confirmed by the large volume of data obtained and their statistical processing, based on the software: Office 2016, "Statistika 13", "Statgraphics 19" and "MapInfo Pro v12.5.5". It has been established that the introduction of a set of measures for the conservation of the degraded lands of the sloped agro-landscape systems by stopping intensive economic activity with subsequent use of the land plots as hayfields and pastures, ensured a significant reduction in soil loss due to erosion, while the soil loss on heavily and moderately eroded soils of the studied sites amounted to 2.38-4.19 t ha-1, which differs slightly from the maximum permissible standard indicators of soil loss for the heavily and moderately eroded soils. The main characteristics of the agrochemical, agrophysical and other properties of the washed-out chernozems have stabilized during the conservation period. At the same time, the humus content in the cultivated soil layer has increased to 3.85%, the optimal values are characterized by the soil acidity pH 7.1 - 7.3 (close to neutral). Attention has been focused on the specifics of the land conservation by excluding it from economic circulation with its subsequent use as pasture and hay lands.

The anti-oxidative stress and anti-inflammatory effects of natural products can prevent diabetic complications such as retinopathy, nephropathy, neuropathy, and blood vessel damage. Fucoxanthin has potent antioxidant and anti-inflammatory properties. This research aimed to examine the preventative effects of fucoxanthin nanoparticles against aortic damage in diabetic rats. Dynamic Light Scattering (DLS) was utilized to identify the size of fucoxanthin nanoparticles. The experiment consisted of five groups (n=8) namely: Rats only received Streptozotocin (STZ) solvent and fucoxanthin nanoparticles solvent as a control group; Rats only received STZ and solvent of fucoxanthin nanoparticles solvent as the diabetic group; and Rats received STZ and fucoxanthine nanoparticles at a dose of 75, 150 and 300 mg/Kg BW as fucoxanthin nanoparticle group. The fucoxanthin nanoparticle sizes were 217.2 ± 42.8 nm in DLS. The dose-dependent administration of fucoxanthin nanoparticles elevated significant superoxide dismutase (SOD), glutathione peroxidase (GPx), nitric oxide (NO), endothelial nitric oxide synthase (eNOS), and insulin. However, blood glucose, malondialdehyde (MDA), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and endothelial cell necrosis decreased compared to those in the streptozotocin group. Our findings suggest that fucoxanthin nanoparticles decrease malondialdehyde levels and increase superoxide dismutase and glutathione peroxidase levels to inhibit oxidative stress, consequently preventing diabetes-induced aortic damage. Furthermore, fucoxanthin nanoparticles also may inhibit inflammation by reducing IL-6 and TNF-α levels. These mechanisms reduce endothelial cell necrosis, which can increase the expression of eNOS and NO levels in the aorta of diabetic rats.

Vulvar carcinoma is a rare disease, meeting the criteria of a “rare cancer”. The incidence has been increasing, especially in women <60 years of age. Squamous cell carcinoma (VSCC) accounts for an overwhelming majority of vulvar carcinomas and is the focus of this review. As with many cancers, the increased understanding of molecular events during tumorigenesis has led to emergence of molecular subclassification of VSCC, which is subclassified into those tumors arising secondary to high risk human papillomavirus infection (HPV associated, or HPVa) and those which arise independent of HPV (HPVi), most commonly in the setting of a chronic inflammatory condition of the vulvar skin. This latter group of HPVi VSCC arises in most cases secondary to mutations in TP53, but recently attention has focused on the uncommon TP53 wildtype HPVi VSCC. These three molecular subtypes of VSCC (HPVa, HPVi p53 abnormal, HPVi p53 wild type), and their precursor lesions, cannot be diagnosed based on routine histopathological examination and immunostaining for p53 and p16, as surrogate markers for TP53 mutation and high-risk HPV infection, respectively, is essential. Molecular subtyping of VSCC shows high reproducibility and provides important prognostic information. The HPVa VSCC have the most favorable prognosis while the HPVi VSCC with TP53 mutations (p53abn) have the worst prognosis, and the HPVi VSCC with wild type TP53 (p53wt) have an intermediate prognosis. In this review, we discuss the evidence supporting this molecular subclassification and its implications for diagnosis and treatment of VSCC and its precursors.

Background: Several studies have questioned the reliability of the interview process in predicting resident success. Objective: Statistical analysis of the resident interview structure might guide process improvements and increase the validity of the selection methodologyMethod: We performed a prospective comparative analysis of our general surgery residency interview process over two consecutive academic years (AY 2022 and 2023). We used descriptive statistics as well as a mixed effects ordered logit model to measure bias and guide process improvement. Results: Eighty total students were interviewed. We found numerous statistical biases including leniency bias exacerbated by the unequal distribution of evaluators; significant differences in the variance from evaluator’s scoring (p<0.0001) and non-normal distribution (p<0.001). Rater reliability was “good” in both years: 0.69 (C.I. 0.51-0.82). Using uncorrected means, on average, each student was statistical different from 11.5±1.1 other students. Using our model, we improved the number of statistically distinct groupings as each student now differed by 30±1.0 others (p<0.0001). In AY23, we restructured the interviews so that all the evaluators scored every student which greatly improved the interview accuracy using the same mixed model; R-squared of 0.95 versus 0.70; and a smaller percent of students had a change in their rank using with the improved structure (57% versus 90%, p<0.05), compared to AY22.Conclusions: Due to numerous statistical biases, there is little differentiation between students and thus little validity in the process for scoring students using raw mean scores. This can be overcome by developing a structured interview and correcting for statistical biases.

The circular economy with compost fertilization is included in the sustainable orchard paradigm, creating a holistic production ecosystem. Modern orchards are mostly intensive and super-intensive, requiring different rootstocks. This research presents the response to compost fertilization of two specific pear rootstocks (quince ‘CTS 212’ and ‘Farold® 40’) and own-rooted trees, analyzing six resistant cultivars in a circular production system. The dynamic of nitrogen and carbon content in leaves, soil respiration coefficient, the evolution of the fruit maturity stage in the field, and some biometric parameters such as trunk cross-section area, the annual vegetative growth, and fruiting shoots annual number were analyzed. The results highlighted the effect of compost fertilization on plants: almost all variants presented higher nitrogen amounts in leaves in the first and second years. Carbon content in leaves had a lower dynamic over time. Rootstock and compost fertilization influenced the fruit maturity dynamic, but a single pattern was not identified. Quince as pear rootstock expressed a higher sensitivity to compost application, the biometric parameters as trunk cross-section area, and almost all cultivars' annual vegetative growth were higher than the control's. Positive output can lead to future model upscaling in the farms and households.

We propose a SUSY-inspired loss framework to address the generalizationrobustness trade-off in AI. Combining bosonic and fermionic components, the loss ensures smooth learning and robustness against adversarial attacks. Parallel transport stabilizes weight updates across non-Euclidean loss landscapes. Validation on CIFAR-10 demonstrates stable convergence and enhanced performance under FGSM and PGD attacks, confirming the effectiveness of the proposed approach. Keywords: Supersymmetry, Generalization, Robustness, Adversarial Attacks, Parallel Transport, Loss Optimization, CIFAR-10.

Non-orthogonal multiple access (NOMA) enables the parallel offloading of multiuser tasks, effectively enhancing throughput and reducing latency. Backscatter communication, which passively reflects radio frequency (RF) signals, improves energy efficiency and extends the operational lifespan of terminal devices. Both technologies are pivotal for the next generation of wireless networks. However, there is little research focusing on optimizing the transmit power in backscatter-assisted NOMA-MEC systems from a green IoT perspective. In this paper, we aim to minimize the transmit energy consumption of a Hybrid Access Point (HAP) while ensuring task deadlines are met. We consider the integration of Backscatter Communication (BackCom) and Active Transmission (AT), and leverage NOMA technology and user cooperation to mitigate the double near-far effect. Specifically, we formulate a transmit energy consumption minimization problem, accounting for task deadline constraints, task offloading decisions, transmit power allocation, and energy constraints. To tackle the non-convex optimization problem, we employ variable substitution and convex optimization theory to transform the original non-convex problem into a convex one, which is then efficiently solved. We deduce the semi-closed form expression of the optimal solution and propose an energy-efficient algorithm to minimize the transmit power of the entire wireless powered MEC. Simulation results demonstrate that our proposed scheme significantly reduces the transmit power of the HAP compared to existing schemes, validating the effectiveness of our approach.This study provides valuable insights for the design of green IoT systems by optimizing the transmit power in NOMA-MEC networks.

Sodium valproate is a established antiepileptic drug of first choice, primarily used to treat epilepsy, but also bipolar disorder and prevent migraine headaches. Valproate increases concentrations of gamma-aminobutyric acid in the brain, due to inhibition of enzymes responsible for the catabolism of gamma-aminobutyric acid. Main goal of this research consisted in the optimization and development for a new sensitive spectrophotometric quantitative analysis method of sodium valproate from tablets in the Visible field. Following the quantitative color reaction of sodium valproate with diazonium salt of alpha naphthylamine in alkaline medium, a light yellow azo dye was formed and spectrophotometrically analyzed at the wavelength of 386 nanometers. The amount of pure sodium valproate found on pharmaceutical extended-release tablet was 492.578 milligrams compared to the official declared pure amount of 500 milligrams on prolonged-release tablet. Amount found was assigned to a percentage content of 98.5156 percent pure sodium valproate in a pharmaceutical tablet. Mean average percentage error (deviation) from the officially stated value was about 1.4844 percent, which was included within normal limits, below five percent maximum limit allowed by European and Romanian Pharmacopoeias rules (5 percent). Spectrophotometric method was subjected to the statistical validation procedure and was successfully validated. Linear regression was analyzed. Method presented a very good linearity over the entire concentrations range 0.16 – 2.08 microgram on milliliter. Linear regression coefficient R square was 0.999330 and the correlation coefficient R was represented by 0.999665, were within the normal ranges of values.

Since the domestication of plants, pathogenic fungi have consistently threatened crop production, evolving genetically to develop increased virulence under various selection pressures. Understanding their evolutionary trends is crucial for predicting and designing control measures against future disease outbreaks. This paper reviews the evolution of fungal pathogens from natural habitats to agricultural settings, focusing on eight significant phytopathogens: Pyricularia oryzae, Botrytis cinerea, Puccinia spp., Fusarium graminearum, F. oxysporum, Blumeria graminis, Zymoseptoria tritici, and Colletotrichum spp. Also, we explore the mechanism used to understand evolutionary trends in these fungi. The studied pathogens have evolved in agroecosystems through either (1) introduction from elsewhere or (2) local origins involving co-evolution with host plants, host shifts, or genetic variations within existing strains. Genetic variation, generated via sexual recombination and various asexual mechanisms, often drives pathogen evolution. While sexual recombination is rare and mainly occurs at the center of origin of the pathogen, asexual mechanisms such as mutations, parasexual recombination, horizontal gene or chromosome transfer, and chromosomal structural variations are predominant. Farming practices like mono-cropping resistant cultivars and prolonged use of fungicides with the same mode of action can drive the emergence of new pathotypes. Furthermore, host range does not necessarily impact pathogen adaptation and evolution. Although halting pathogen evolution is impractical, its pace can be slowed by managing selective pressures, optimizing farming practices, and enforcing quarantine regulations. The study of pathogen evolution has been transformed by advancements in molecular biology, genomics, and bioinformatics, utilizing methods like next-generation sequencing, comparative genomics, transcriptomics and population genomics. However, continuous research remains essential to monitor how pathogens evolve over time and to develop proactive strategies that mitigate their impact on agriculture.

As a branch of regional innovation theories, social filter theory fundamentally reveals the reasons for the geography of innovation in different countries and regions. However, compared with some other regional innovation theories, social filter theory has been as silent as a sleeping beauty and hasn’t been fully developed. For enriching and developing social filter theory, this article systematically traces the source and comments on four aspects: the concept of social filter, the construction and measurement of indicators of social filter, the mechanism and empirical re-search of social filter affecting regional innovation and innovation transformation. Until recently regional innovation theories primarily focused on the superficial description of the phenomenon of innovation, but lack of attention to the local social filter condition of innovation generation and innovation transformation, which are the pre-condition of constructing mature innovation system. Therefore, additional efforts are still required to fill the current knowledge gap from the recom-mended directions in the article.

The metabolomics of Newhall navel oranges with geographical indication (GI) was measured by LC-MS/MS from three areas Ganzhou, Fengjie, and Zigui in China. Orthogonal partial least squares-discriminant analysis was performed for samples classification and important metabolites identification. This approach identified the best markers (i.e. tricarboxylic acid, amino acids, and phenolics) of the geographical origin able to discriminated Fengjie, Ganzhou, and Zigui organge samples. The results showed that peeled-samples from Zigui were richest and those from Fengjie lowest in all of the top ten most important markers. In whole samples, the highest levels of seven important markers occurred in those from Zigui, and the other three important markers appeared the highest levels in those from Ganzhou. According to the variation of the best markers, and the highest value of titratable acidity in those from Zigui, the samples planted in Ganzhou have the best balance between taste and nutrition. This work confirms the approach of metabolomics combined with OPLS-DA is an effective way for origin tracing and overall quality evaluation.

Custom copper smelters, dependent on purchased concentrates, face increasing economic pressures amid falling treatment and refining fees. With declining availability of high-grade, low-impurity concentrates, copper demand is expected to surge to support the transition to renewable energy. This study, based on recent observations of Chinese custom smelters, examines their strategies to address the challenge of purchasing concentrates at record-low treatment and refining charges. By investing in slag flotation technology, smelters can enhance copper, gold and silver recoveries. Through blending of high-grade and low-grade concentrates they can capitalize on the gap between the recoverable and payable metals, which is often referred to as “free metals”, while also benefiting from by-products, mainly sulfuric acid. While this approach offers economic opportunities, it introduces operational complexities. To mitigate these, laboratory testing combined with advanced digital predictive tools based on thermodynamics is crucial. This study demonstrates the use of thermodynamic models supported by experimental work for analyzing furnace operations. FactSage® software and a custom database are employed to define the operating window of two common flowsheets: 1) Flash Smelting + Flash Converting and 2) Bottom-Blown Smelting + Bottom Blowing Converting.

Various methods have been studied to speed up the wound healing process. Promoting the rapid development of blood vessels, also known as angiogenesis, is essential as this significantly accelerates skin regeneration. This study identified a polysaccharide from the red alga Osmundea pinnatifida (PSOP) that promotes angiogenesis and accelerates wound healing. Firstly, we analyzed the structural characteristics of PSOP using various techniques such as UV-visible spectrum, Fourier-transform infrared (FT-IR) spectroscopy, X-ray diffraction (X-RD), scanning electron microscopy (SEM), and high-performance liquid chromatography coupled to refractive index detector (HPLC-RID). We also evaluated the antioxidant properties of PSOP in vitro using tests for DPPH free radical scavenging capacity, iron reduction capacity (RPA), and total antioxidant capacity (TAC). Additionally, we observed a significant increase in new blood vessel formation in the chorioallantoic membrane model (CAM assay) using a fertilized hen egg, indicating the pro-angiogenic effect of PSOP. Furthermore, we tested the wound-healing potential of PSOP hydrogel in vivo using excision wounds in the Wistar rat model. The results showed a notable acceleration of wound closure and an improvement in tissue regeneration and collagen deposition quality within 11 days, indicating the strong wound-healing activity of PSOP. Our computational study suggested that the PSOP units bind to cyclooxygenase 2 (COX-2) and vascular endothelial growth factor (VEGF) with acceptable affinities and interactions, which might explain the observed beneficial wound healing properties and the pro-angiogenic effect seen in the experimental assays. Our findings support using the polysaccharide PSOP for wound treatment due to its antioxidant and pro-angiogenic potential.

We developed a sensor optimized for joint motion monitoring by exploring the effects of stitch pattern, yarn thickness, and NP number on the performance of knitted strain sensors. We conducted stretching experiments with basic weft-knit patterns to select the optimal stitch pattern and analyze its sensitivity and reproducibility. The plain stitch with a conductive yarn located on the reverse side exhibited the highest gauge factor value (143.68) and achieved excellent performance, with a stable change in resistance even after repeated sensing. For in-depth analysis, we developed six sensors using the aforementioned pattern with different combinations of yarn thickness (1-ply, 2-ply) and NP number (12, 13, 14). Based on bending experiments, the GF across all sensors was 60.2–1092, indicating noticeable differences in sensitivity. However, no significant differences were observed in reproducibility, reliability, and responsiveness, confirming that all the sensors are capable of joint motion monitoring. Therefore, the plain-patterned plating stitch structure with conductive yarn on the reverse side is optimal for joint motion monitoring, and the yarn thickness and NP numbers can be adjusted to suit different purposes. This study provides basic data for developing knitted strain sensors and offers insights into how knitting methods impact sensor performance.

Precise monitoring of NOx concentrations in nitric oxide delivery systems is crucial to ensure the safety and well-being of patients undergoing inhaled nitric oxide (iNO) therapy for pulmonary arterial hypertension. Currently, NOx sensing in commercialized iNO instruments predominantly relies on chemiluminescence sensors, which not only drives up costs but also limits their portability. Herein, we developed solid state gas sensors utilizing Ni-based sensing materials for effectively tracking the level of NO and NO2 in NO delivery system. These sensors comprised of NiO-SE or (NiFe2O4+30 wt.% Fe2O3)-SE vs. Mn-based RE demonstrated high selectivity towards 100 ppm NO under the interference of 10 ppm NO2 or 3 ppm NO2 under the interference of 100 ppm NO, respectively. Meanwhile, excellent stability, repeatability, and humidity resistance were also verified for proposed sensors. Sensing mechanisms were thoroughly investigated through assessments of adsorption capabilities and electrochemical reactivity. It turns out that the superior electrochemical reactivity of NiO towards NO, alongside with the NO2 favorable adsorption characteristics of (NiFe2O4 + 30 wt.% Fe2O3), is the primary reason for the high selectivity to NOx. These findings indicate a bright future for the application of these NOx sensors in innovative iNO treatment technologies.

Background/Objectives: To describe the effects of muscle-targeted oral nutritional supplementation (MT-ONS) on nutrition, functional capacity, and other health outcomes in patients after femur fracture surgery; Methods: A prospective, open-label, single-center study was conducted. Patients aged 80+ post-femur fracture were recruited. They were assessed at baseline and after 90 days with MT-ONS, 100% whey protein enriched with leucine and vitamin D. Demographics, clinical and nutritional status (MNA®-SF), functional capacity [Barthel Index (BI), Lawton &amp; Brody (LB) scale], muscle strength (dynamometry), cognition [Global Deterioration Scale (GDS)], tolerability, and satisfaction data were collected. Descriptive statistics were performed. Ethical approval was obtained; Results: Thirty-one patients (74% women, mean age 87 ± 3.99 years) were enrolled. At baseline, 32% were malnourished and 65% at risk. After ≥90 days of MT-ONS, malnutrition decreased to 13% and well-nourishment increased to 32%. Ninety percent gained weight, with significant muscle strength improvements (+2 kg, p&lt;0.001). Eighty-one percent achieved a BI score ≥60 points [mean 84.8 (± 17.82)]. BI score improvements correlated with higher baseline muscle strength (rho=0.413, p=0.021) and better nutritional status (rho=0.464, p=0.009). LB mean score was 4.84 (± 2.26). Improvements correlated with pre-fracture BI score (rho=0.475, p=0.007). Positive correlations were noted between nutritional status, muscle strength, and functional outcomes. Cognition remained stable (GDS=1 in 67.7% patients). Tolerability and satisfaction with MT-ONS were high at 90%; Conclusions: MT-ONS, 100% whey protein enriched with leucine and vitamin D for ≥90 days, enhances nutritional status and functional recovery in patients after femur fracture surgery.

In Antarctica, SAR interferometry was largely used in coastal glacial areas, while in rare cases this method was used on the Antarctic plateau. In this paper, the authors present a digital elevation and ice flow map based on SAR interferometry for an area encompassing Talos Dome (TD) and the Frontier Mountain (FM) meteorite site in North Victoria Land/Antarctica. A digital elevation model (DEM) was calculated using a double SAR interferometry method. The DEM of the region was calculated by extracting approximately 100 control points from the Reference Elevation Model of Antarctica (REMA). The two DEMs differ slightly in some areas, probably due to the penetration of the SAR-C band signal into the cold firn. The largest differences are found in the western area of TD, where the radar penetration is more pronounced and fits well with the layer structures calculated by the georadar and the snow accumulation observations. By differentiating a 70-day interferogram with the calculated DEM, a displacement interferogram was calculated that represents the ice dynamics. The resulting ice flow pattern clearly shows the catchment areas of the Priestley and Rennick Glaciers as well as the ice flow from the west towards Wilkes Basin. The ice velocity field was analyzed in the area of FM. This area has become well known due to the search for meteorites. The velocity field in combination with the calculated DEM confirms the generally accepted theories about the accumulation of meteorites over the Antarctic Plateau.

This research presents a novel methodology for classifying MRI images into two categories: tumor and non-tumor. The study utilizes a combination of two advanced Convolutional Neural Network (CNN) architectures, VGG16 and ResNet50, to address the challenges in analyzing the complexity and variability of brain MRI scans. The approach begins with a comprehensive preprocessing phase, where the MRI images are enhanced through techniques such as resizing, grayscale conversion, Gaussian blurring, and brain area isolation. Central to the approach is the application of the Multi-verse Optimizer (MVO), a metaheuristic algorithm inspired by theories of the multi-verse in physics. The MVO is utilized to optimize the parameters for data augmentation and to fine-tune the combination of trainable layers within the VGG16 and ResNet50 models. The results of this study indicate a high level of effectiveness of the combined CNN models, significantly enhanced by the MVO, in classifying MRI images. These models show marked improvements in accuracy, precision, and recall, underscoring their potential utility in enhancing brain tumor diagnosis. The paper concludes with an analysis of these findings, emphasizing the importance of this approach in medical imaging and suggesting potential avenues for future research in the area of automated MRI classification.

This study proposes a new concept that explains the modern technological change: technology invasiveness that breaks into a scientific and technological ecosystem, with accelerated diffusion of large quantities of products leading to main change in the innovation ecotone that transfers knowledge and know-how in businesses and markets. Invasive technologies conquer scientific, technological and business space of alternative technologies and expand the knowledge space of adjacent possible by introducing radical innovations that support dynamic interactions between new technologies and emerging development and applications. This theoretical approach is empirically verified in emerging path-breaking technology of transformer, a deep learning architecture having unsupervised and semi-supervised algorithms that create new contents and mimics human ability (Generative Artificial Intelligence). Statistical evidence here, based on patent analyses, reveals that the growth rate of transformer technology is 55.82% (over 2016-2023) more than double compared to 23.02% of all other technologies, such as Convolutional Neural Network: it is force that is revolutionizing the way societies interact with machines. Hence invasive technologies are considered as one of the major causes of global technological change and this study offers a profound exploration of how invasive technologies drive technological change, significantly contributing to our understanding of technological evolution’s dynamics and its societal and industry impacts.

The anti-oxidative stress and anti-inflammatory effects of natural products can prevent diabetic complications such as retinopathy, nephropathy, neuropathy, and blood vessel damage. Fucoxanthin has potent antioxidant and anti-inflammatory properties. This research aimed to examine the preventative effects of fucoxanthin nanoparticles against aortic damage in diabetic rats. Dynamic Light Scattering (DLS) was utilized to identify the size of fucoxanthin nanoparticles. The experiment consisted of five groups (n=8) namely: rats only received streptozotocin (STZ) solvent and fucoxanthin nanoparticles solvent as a control group; rats only received STZ and solvent of fucoxanthin nanoparticles solvent as the diabetic group; and rats received STZ and fucoxanthin nanoparticles at a dose of 75, 150 and 300 mg/kg BW as the fucoxanthin nanoparticle group. The fucoxanthin nanoparticle sizes were 217.2 ± 42.8 nm in DLS. The dose-dependent administration of fucoxanthin nanoparticles elevated significant superoxide dismutase (SOD), glutathione peroxidase (GPx), nitric oxide (NO), endothelial nitric oxide synthase (eNOS), and insulin. However, blood glucose, malondialdehyde (MDA), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and endothelial cell necrosis decreased compared to those in the streptozotocin group. Our findings suggest that fucoxanthin nanoparticles decrease malondialdehyde levels and increase superoxide dismutase and glutathione peroxidase levels to inhibit oxidative stress, consequently preventing diabetes-induced aortic damage. Furthermore, fucoxanthin nanoparticles also may inhibit inflammation by reducing IL-6 and TNF-α levels. These mechanisms reduce endothelial cell necrosis, which can increase the expression of eNOS and NO levels in the aorta of diabetic rats.

Background: The practice of heading in soccer is widely recognized as an important aspect of the game both offensively and defensively, frequently implemented by players. However, concerns persist about the negative impact of this technique on players' cognitive function and symptoms, both in the short and long-term. This meta-review aims to systematically map the existing literature on soccer heading and its implications on the long-term effects; Methods: We conducted a meta-review of systematic reviews following PRISMA-ScR guidelines in PubMed, Embase and Web of Science databases. Searches were conducted between 21 February and 20 March 2024, in English, with a limitation to articles published between January 2000 and March 2024.; Results: Three systematic reviews were eligible for having addressed the subject of head-ball impacts in soccer and their physiological, neurological and cognitive impact. While most studies did not report any significant long-term changes, short-term impairments in memory and reaction time were observed in some instances, normalizing within 24 hours. Neurochemical markers showed mixed results, with increased NF-L levels persisting up to a month in certain cases. Visual reflexes and corticomotor inhibition also exhibited temporary dysfunctions post-heading; Conclusions: This meta-review highlighted the limited number of systematic reviews on the effects of heading in soccer in young and adult players. The current evidence suggests that while heading may lead to short-term cognitive and physiological changes, the long-term effects remain uncertain and probably under-studied. Further research, particularly with professional players and standardized methodologies on long-term follow-up, is needed to clarify these potential risks and inform safety measures in soccer.

Background and Objective: Obtaining reliable and up-to-date information on mortality causes is essential for planning and implementation of effective preventive interventions. We present here an analysis of the leading causes of death in the US in 2022. Material and Methods: We conducted an electronic search of the US Centers for Control and Prevention (CDC) Web-based Injury Statistics Query and Reporting System (WISQARS) to obtain information on the leading causes of death in the US for the most recent searchable year (2022), stratified by age and sex. Results: Overall, heart disease was the leading cause of death (26.2% of all deaths), followed by malignant neoplasms (22.7%), unintentional injuries (8.5%) and coronavirus disease 2019 (COVID-19; 6.9%). Although heart disease and malignant neoplasms remained the leading causes of death in both sexes, unintentional injuries were the third cause for men (10.5%), while strokes were the third cause in women (7.5%). COVID-19 remained the fourth most common cause of death in both sexes (7.1% in men and 6.8% in women). The ten most common causes of death showed an increasing mortality tendency in parallel with the aging of population, with similar trends for both sexes. The only exception was unintentional injury, which was the most common cause of death in both sexes between the ages of 15 and 44 years, then reached a plateau, for increasing again in people aged 65 years or older. Conclusions: Greater efforts should be put into prevention and education, as heart disease, cancer and even unintentional injuries are preventable diseases.

This study presents a comparative analysis of two advanced attention-based deep learning models—Attention-LSTM and Attention-GRU—for predicting cryptocurrency price movements. The models utilize historical OHLCV data, combined with four technical indicators: SMA, EMA, TEMA, and MACD, to enhance the accuracy of classification into three categories: uptrend, downtrend, and neutral. Both models aim to capture market dynamics through sequential data while incorporating attention mechanisms to focus on relevant time steps. Experimental results demonstrate that the inclusion of technical indicators significantly improves model performance, with MACD yielding the highest accuracy. The Attention-GRU model shows computational advantages, while the Attention-LSTM model excels in capturing long-term dependencies.

Data governance has emerged as a critical factor in determining the effectiveness and long-term stability of IT systems in today’s data-driven environment. It encompasses frameworks that guide organizations in managing data collection, storage, processing, usage, and sharing, while ensuring alignment with business objectives, compliance with regulations, and adherence to ethical standards. However, the complexities associated with data governance, particularly in the context of new technological models, pose significant challenges. This systematic review aims to explore the role of data governance in enhancing data quality, system stability, and regulatory compliance. It seeks to identify common issues, effective practices, and strategic implications for implementing data governance frameworks across diverse industries, focusing particularly on small and medium enterprises (SMEs). We conducted a systematic review of 68 eligible studies published between 2014 and 2024, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The included studies were assessed for risk of bias using the Cochrane Risk of Bias Assessment Tool. The review covered a range of study types, including qualitative (60%), quantitative (19%), and mixed-methods (21%) research, to provide a comprehensive understanding of data governance's impact on IT performance. The findings highlight that data governance significantly influences system success by improving data quality, operational efficiency, and regulatory compliance. Although qualitative studies predominantly emphasized in-depth analysis, a moderate representation of empirical validation through quantitative studies was observed. Common challenges identified include data migration issues, resistance to change, and budget constraints, particularly during system upgrades. Effective practices involve aligning data governance with business strategies, employing hybrid models, and regularly updating governance policies to adapt to technological advancements such as AI and big data. This review provides practical recommendations for IT managers and policymakers to enhance data governance frameworks. These include phased implementation approaches, the establishment of data governance committees, and the use of performance metrics to monitor data quality and system resilience. While significant progress has been made, further research is needed to address gaps related to emerging technologies and the unique challenges faced by SMEs in developing regions.

Background: The use of salivary biomarkers offers a non-invasive approach to understanding the metabolic and inflammatory status of hypertensive patients. This study aimed to quantify the salivary nitric oxide (NO), total cholesterol, triglycerides, high-density lipoproteins (HDL), and low-density lipoproteins (LDL) levels in hypertensive individuals and healthy controls in a sub-population in Saudi Arabia. Methods: This cross-sectional study comprised diagnosed hypertensive patients (test group, 40–50 years old) and age-matched healthy controls who visited the dental hospital in the College of Dentistry, King Khalid University, for dental treatment. Nitric oxide, total cholesterol, triglycerides, HDL, and LDL levels in saliva were assessed. An independent sample t-test was used to compare the results between the hypertensive and control groups. Results: The study included 40 hypertensive patients (20 males and 20 females, aged 40-50) and 40 age-matched healthy individuals (20 males and 20 females). Significant differences in the triglyceride (p = 0.007), cholesterol (p = 0.033), and NO (p = 0.014) levels were observed between the two groups. The triglyceride level was significantly correlated with age in the test group (p = 0.04). Conclusion: This study demonstrated significant differences in the nitrate levels and lipid profiles between hypertensive patients and healthy individuals in a sub-population in Saudi Arabia. The findings indicate that saliva can be used as a non-invasive diagnostic tool for assessing nitrate levels and the lipid profile. However, additional studies with larger sample sizes and more precise testing parameters are required to validate the findings.

Background/Objectives: Nowadays there is a progressive increase in surgical interventions in the fields of cardiology and oncology. This situation increasingly involves the need to identify strategies for managing complications that may affect patients in the post-surgical period, during the rehabilitation phase. Among the symptoms most frequently encountered in this context are pain and postural dysfunction, for which a decisive support could derive from the application of Focused Mechano-Acoustic Vibrations (FMAVs) therapy. Methods: In this pilot observational study, 20 patients (12 women and 8 men; average age of 48 years) who underwent cardiac or oncological surgery were observed during the execution of a FMAVs treatment protocol applied in the post-operative period. Patients were evaluated at the beginning and at the end of the protocol through the Numeric Pain Rating Scale (NPRS) and the computerized postural analysis for the calculation of the Postural Biometric Index (PBI), that quantifies postural dysfunctions. All patients were treated with 8 biweekly sessions of FMAVs applied on specific Myofascial Trigger Points (MTrPs). Results: At the end of the protocol, significant reductions of 26.4% for pain detected by NPRS and 17.9% for postural dysfunction detected by PBI were observed. Conclusions: Treatment with FMAVs can determine improvements in pain and postural dysfunction in cardiac and oncological patients subjected to surgery. This preliminary study lays the foundation for further in-depth research on the topic.

Using assembly theory of strings of any natural radix $b$ we find some of their salient regularities. In particular, we show that the upper bound of the assembly index depends quantitatively on the radix $b$ and the longest length $N$ of a string that has the assembly index of $N-k$ is given by $N_{(N-k)}=b^2+b+3k-2$ for $k=\{1,2\}$ and by $N_{(N-3)}=b^2+b+6$. We also provide particular forms of such strings. Knowing the latter bound we conjecture that the maximum assembly index of a string of length $N>N_{(N-2)}$ is given by $a_{\text{max}}^{(N,b)} = \lfloor N/2 \rfloor + b(b+1)/2$. For $k=1$ such odd length strings are nearly balanced and there are four such different strings if $b=2$ and seventy-two if $b=3$. We also show that a string containing $k$ copies of an $n$-plet has the assembly index of at most $N-1 - (n-1)k - a$, where $a$ is the assembly index of this $n$-plet. Finally, we show that the assembly depth of a minimum assembly index string is equal to the assembly index of this string, while the assembly depth of a maximum assembly index string has a value between $\left\lceil \log_2(N) \right\rceil$ and the assembly index of this string. Since these results are also valid for $b=1$, assembly theory subsumes information theory.

Helium is a strategic rare gas resource related to national security and the development of high-tech industries, the high-quality development of helium industry chains has a great significance to improve the security of helium resource. This paper through literature and market research, summarizes the progress of helium resource endowmen, exploration and development, supply and demand pattern, trade market and industrial technology, equipment through literature and market research in the world, analyses the development situation of global helium resources industry chains. This study proposes the development status and challenges of China's helium industry and the corresponding development path of helium industry based on the upstream, midstream, downstream and downstream indicators. Most of the countries in the world have not started helium exploration or remain in low exploration level, but the exploration practice shows that global helium resource potential is considerable; helium exploration and development subjects become diversified in recent years, which may change the global helium supply and demand pattern; The helium reservoir forming theory and exploration and development technology are underdeveloped, and the helium extraction equipment is continuously improved; The global helium production capacity, supply and demand，trade pattern market would be profoundly changing. For a long time, the United States has had an absolute say in the global helium trade system, the contradiction between supply and demand would persist for a long time and significant price fluctuations. China's helium development challenges and opportunities coexist considering the global helium industry chain existing pattern and the new trend of development. There is an urgent need to build an independent and controllable , stable and resilient helium industrial chain, and provide helium resources guarantee for the development of high-tech industries.

Building decarbonization is a major challenge for cities. Deciding what, when, and how to retrofit a building is difficult, given the complex interaction between energy costs and investment requirements. Several tools have been developed in the last years to help public and private stakeholders with these decisions, but none cover aspects the authors think are fundamental. For this reason, an urban building retrofit tool was developed and is presented in this article. This new tool is based on a bottom-up approach, with all buildings simulated individually, considering aspects such as shading or adjacencies. As a second step, three scenarios with different levels of ambition have been implemented in the tool, and the energy demand and emissions resulting from these scenarios have been calculated. As a third step, the retrofitting scenarios' initial investment and operational costs have been implemented via a detailed Life Cycle Costs (LCC) approach. The authors describe the robust and scalable structure that has been developed and the application of this structure to calculate the LCCs of different retrofitting scenarios in Montréal.

As network systems become larger and more complex, there is an increasing focus on how to verify the security of systems that are at risk of being attacked. Automated penetration testing is one of the effective ways to do this. Uncertainty caused by adversarial relationships and the "fog of war" is an unavoidable problem in penetration testing research. However, related methods have largely focused on the uncertainty of state transitions in the penetration testing process, and have generally ignored the uncertainty caused by partially observable conditions. To address this new uncertainty introduced by partially observable conditions, we model the penetration testing process as a partially observable Markov decision process (POMDP), and propose an intelligent penetration testing decision method compatible with it. We experimentally validate the impact of partially observable conditions on penetration testing. The experimental results show that our method can effectively mitigate the negative impact of partially observable conditions on penetration testing decision. It also exhibits good scalability as the size of the target network increases.

Pichia pastoris is extensively employed as a host for expressing foreign proteins, and its secretion system is especially advantageous for efficient protein purification. Ulp1 is essential for the cell cycle. In Saccharomyces cerevisiae, the absence of Ulp1 leads to G2/M cell cycle arrest. Similarly, in Pichia pastoris, we also observed G2 phase stalling in Ulp1 knockout cells. RNA-seq data revealed significant changes in seven genes, including INO1. Interestingly, overexpressing INO1 in Ulp1 knockout cells restored cell proliferation, suggesting that Ulp1 regulates cell proliferation through INO1. However, adding extra inositol to Ulp1 knockout cells was not able to restore cell prolifera-tion, indicating that the enzyme activity of INO1 is not essential for cell proliferation. Our data provide new insights into Ulp1 functions in the cell cycle and raise new questions about yeast cell cycle regulation.

Objective: The aim of this review was to identify newly discovered bacteria from individuals with periodontal/peri-implant diseases and organize them in new clusters (GF-MoR complexes) to update Socransky’s complexes (1998). Methods: The focus question was developed based on the PCC (Population, Concept, Context) strategy: “In patients with periodontal and/or peri-implant disease, what bacteria (microorganisms) were detected through laboratory assays?” The search strategy was applied to PubMed/MEDLINE, PubMed Central, and Embase. The search keyterms, combined with Boolean markers, were: (1) bacteria, (2) microbiome, (3) microorganisms, (4) biofilm, (5) niche, (6) native bacteria, (7) gingivitis), (8) periodontitis, (9) peri-implant mucositis, and (10) peri-implantitis. The search was restricted to 1998–2024 and English language. The bacteria groups in the oral cavity obtained/found were retrieved and were included in the GF-MoR complexes which were based on the disease/condition, presenting six groups: (1) Health, (2) Gingivitis, (3) Peri-implant mucositis, (4) Periodontitis, (5) Peri-implantitis, and (6) Necrotizing and Molar-Incisor (M-O) pattern Periodontitis. The percentual found per group refers to the number of times a specific bacterium was found associated with a particular disease. Results: A total of 381 articles were found; 162 articles were eligible for full-text reading (k=0.92); 9 articles were excluded with justification, and 153 were included in this review (k=0.98). Most of the studies reported results for Health condition, Periodontitis, and Peri-implantitis (3 out of 6 GF-MoR clusters), limiting the number of bacteria found in the other groups. Therefore, it is essential to understand that bacterial colonization is a dynamic process, and the bacteria present in one group can also be present in other one or others, such as observed with the bacteria found in all groups (Porphyromonas gingivalis, Tannarela forsythia, Treponema denticola, and Aggregatibacter actinomycetemcomitans) (GF-MoR’s red Triangle); the second most observed bacteria were grouped at GF-MoR’s blue Triangle: Porphyromonas spp., Prevotela spp., and Treponema spp., present in 5 of the six groups; and the third most detected bacteria were clustered in the grey Polygon (GF-MoR’s grey Polygon): Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, and Eikenella corrodens. These three geometric shapes had the most relevant bacteria for periodontal and peri-implant diseases. Specifically, per group, GF-MoR’s Health had 58 species; GF-MoR’s Gingivitis presented 16 bacteria; the GF-MoR’s Peri-implant mucositis included 17 bacteria; GF-MoR’s Periodontitis group had 101 different bacteria; GF-MoR’s Peri-implantitis presented 61 bacteria; and the last group was a combination of Necrotizing diseases and Molar-Incisor (M-I) pattern Periodontitis, with seven bacteria. Observing the top seven bacteria of all groups, all were gram-negative; Groups 4 and 5 (Periodontitis and Peri-implantitis) presented the same top seven bacteria. Conclusion: For the first time in the literature, GF-MoR’s complexes are presented, gathering the bacteria according to the condition found and including more bacteria than Socransky’s complexes. On this understanding, this study can drive future research into treatment options for periodontal and peri-implant diseases, guiding future studies and collaborating to prevent and worsen systemic conditions. Moreover, it permits the debate about the evolution of the bacterial clusters correlated to periodontal and peri-implant diseases and conditions.

Post-exercise recovery is fundamental to optimizing athletic performance, focusing on muscle repair, glycogen replenishment, rehydration, and reducing exercise-induced inflammation. This review examines the evolving landscape of recovery nutrition, highlighting the transition from conventional supplements—such as protein, carbohydrates, creatine, and branched-chain amino acids (BCAAs)—to functional foods rich in bioactive compounds. Emerging evidence supports the efficacy of functional foods like tart cherry juice, turmeric, and omega-3 fatty acids in mitigating oxidative stress and inflammation, thus accelerating recovery. Additionally, probiotics and prebiotic-rich foods are gaining recognition for enhancing gut health, promoting nutrient absorption, and strengthening immune function, which are crucial in recovery processes. The concept of personalized nutrition, guided by genetic and metabolic profiling, is explored as a promising approach to tailor recovery strategies to individual physiological needs. Continued research into the long-term effects of supplements, the role of functional foods, and nutrient interactions is essential for developing more comprehensive and individualized recovery protocols. Integrating functional foods with personalized nutrition offers a holistic strategy to enhance recovery, optimize performance, and promote long-term health in athletes.

One of the most pressing environmental problems contemporary civilizations confront is the ever-increasing amount of plastic waste. Because of their impact on every living thing, these wastes are seen as a major issue on a global scale. To counteract the harmful environmental effects caused by conventional disposal methods, it is critical to show that eco-friendly alternatives are viable. Biodegradation is one of the best eco-friendly methods for removing plastic waste. In this study, we aimed to identify bacteria from sewage wastewater treatment plants (SWW) that could degrade polyethylene. The bacterial strains isolated from sewerage wastewater were incubated for 120 days in 50 ml of minimal salt media (MSM) containing 60mg polyethylene. After four months, our research revealed that Bacillus tropicus (SH4) demonstrated significant potential, degrading poly-ethylene up to 21.6%. We observed the changes after biodegradation using FTIR, GC-MS, and SEM analysis. In conclusion, microorganisms extracted from sewage wastewater possess the ability to mitigate plastic contamination in aquatic ecosystems. Future proteomics and genome investiga-tions are necessary to elucidate the enzymes and metabolic processes implicated in plastic breakdown.

Floor traps were placed in a feed mill in Greece, for a period of approx. 13 months to illustrate the relative abundance and the distribution of the stored product insects found. More than 20 taxa were found, with most of them belonging in Coleoptera. The most abundant species found were the rice weevil, Sitophilus oryzae (L.) and the granary weevil, Sitophilus granarius (L.) which are common primary colonizers of grains, and the confused flour beetle, Tribolium confusum Jacquelin du Val and the red flour beetle, Tribolium castaneum (Herbst), which are secondary colonizers that usually occur in processed amylaceous commodities. Interestingly, the highest population densities of all four species were recorded during the same period, with the secondary colonizers slightly preceding those of the primary ones. Although competition among these species has been recorded in previous studies, we found that these four species could coexist during the entire trapping period in the same sampling units, that indicates possible spatial segregation and different colonization patters in space and time. Our results demonstrate that trapping in storage and processing facilities is an essential component in making decisions for stored product pest management strategies in localized applications, and can drastically reduce the need for treating the entire facility.

Thistle (Onopordum acanthium) has been traditionally employed for liver protection, however, we recently identified silibinin, the main bioactive compound of thistle extract, as an in vitro pancreatic lipase inhibitor, which suggested a potential role as anti-obesity agent. This study aimed to assess, in vivo, the efficacy, safety, and effects of silibinin on human lipase. As a secondary objective, we evaluated potential changes on gut microbiota after silibinina treatment. A randomized trial comparing 150mg/silibinin, 300mg/silibinin, and a thistle extract (equivalent to 150 mg/silibinin) with placebo and orlistat/120mg was conducted. Fecal fat excretion, clinical parameters, and microbiota changes were analyzed. Orlistat showed the highest fecal fat excretion, although thistle extract had similar results (p = 0.582). The 150 mg/silibinin group reported the fewest adverse effects. Both silibinin and orlistat reduced plasma triglycerides (p=0.016) and waist circumference (p=0.001). Specific microbiota changes, such as increases in Mycobacteriaceae and Veillonellaceae, were associated with higher fat excretion. Silibinin proved to be safe and effective for obesity, with minimal adverse effects and no significant changes in microbiota diversity. Further studies are needed to explore its microbiota-related benefits.

The influence of sericin supplementation and chilling temperatures (4°C and 15°C) on the short-term storage quality and fertility of rabbit semen was assessed over 72 hours of storage. In experiment 1, pooled semen (from five ejaculates) was diluted to a concentration of 50M ml−1, and assigned to control, 0.1% and 0.5% sericin groups, stored at 4 or 15°C. Sperm motility, sperm kinematics, viability, membrane and acrosome integrity were assessed at 0, 24, 48, and 72 hours of storage. The experiment 2 and 3 were conducted to observe effect of sericin on bacterial growth and in vivo fertility. The results of experiment 1 showed that sericin treatment, storage temperature, and storage duration influenced progressive and total motility, as well as sperm kinematics. Similar effects were observed for acrosome integrity, membrane integrity, and sperm viability. The results of experiment 2 indicated the antimicrobial effects of sericin when sperm were stored at 15C for 72 hours. While promising pregnancy outcomes were observed with sericin treated sperm for 72 hours, these results not significantly different. The study conclusively demonstrates that sericin treatment enhances the quality of rabbit semen when stored at lower temperatures for longer durations. Antimicrobial effects of sericin could be a contributing factor to the improved in-vitro and in-vivo fertility of rabbit sperm.

This study presents the design and analysis of a proportional electromagnet used in electro-pneumatic brake systems for heavy vehicles. The solenoid was designed using a traditional method and its static and dynamic characteristics were investigated both theoretically and experimentally. ANSYS Maxwell was employed for theoretical static analysis, focusing on the effects of geometric dimension parameters in the fixed and moving pole contact region on the Force-Displacement characteristics. Optimal dimensions for proportionality were determined under suitable operating conditions. The static analysis results provided magnetization curve data, which were used to create look-up tables for a dynamic model in MATLAB-Simulink. Following static analysis, a prototype electromagnet was manufactured and tested. The solenoid achieved a constant magnetic force of 45 ± 3N with a current of 1.3A over a working range of 1-3 mm. The dynamic model, incorporating data from ANSYS, yielded results that closely matched experimental findings.

This study explores integrating Building Information Modeling (BIM) technology into risk management practices for construction projects, aiming to enhance project performance through improved risk identification, assessment, and mitigation. The research employs the Analytical Hierarchy Process (AHP) to prioritize BIM-based strategies across multiple risk management dimensions, including technical, financial, sustainability, and time management. The findings demonstrate that BIM-financial strategies rank most among BIM-driven risk management, followed by sustainability and time. In contrast, Technical, Operation, and maintenance capabilities have the lowest rank. Given the high priority of BIM financial strategies, it has been applied to conduct sensitivity analysis; the sensitivity analysis results demonstrate the dynamic nature of BIM sub-criteria strategy in response to changes in the weight of financial considerations. As financial concerns diminish, the shift towards sustainability, health, safety, and time efficiency underscores the importance of a more balanced approach in BIM strategy prioritization. BIM- risk management improves project outcomes by enabling real-time data-driven decision-making, enhancing stakeholder collaboration, and optimizing resource use, cost control, and sustainability. This research contributes to theoretical and practical advancements in construction risk management, suggesting that BIM can be a transformative tool for optimizing project performance while addressing the complexities and uncertainties inherent in the construction industry.

The promotion of pesticide use reduction is an inevitable requirement for advancing green and low-carbon transformation of agriculture. Analyzing the impact and mechanism of agricultural digital technology applications, represented by plant protection unmanned aerial vehicles (UAVs), in reduction of pesticide application intensity by farming households is of great significance for exploring feasible pathways for low-carbon transformation in rice production. Based on the survey data of 455 sample farming households in Jiangxi Province, China, this paper employs the Ordinary Least Squares (OLS) and Propensity Score Matching (PSM) methods to examine the relationship between plant protection UAVs and the intensity of pesticide application. The research results indicate that the use of plant protection UAVs substantially reduces the intensity of pesticide application in rice by 24.9%. Heterogeneous analysis reveals that the inhibitory effect of plant protection UAVs on pesticide application intensity is more pronounced among non-aged farming households, large-scale farming households, and part-time farming households. Therefore, in order to achieve the goal of rlow-carbon transformation in rice production, it is essential to improve agricultural support policies and establish market promotion and application mechanisms to jointly promote the adoption of plant protection UAVs aerial spraying technology and other agricultural digital technologies.

Transformations in agriculture not only change the ways in which natural resources and social capital are used, but are also a prerequisite for different opportunities to create added value and improve the viability of rural areas. The purpose of the article is to assess the differences and effects of transformations in agriculture in the Bulgarian regions. Based on statistical data from the Censuses of agricultural holdings in 2010 and 2020, the DEA analysis method was applied. Six models (3 input oriented and 3 output oriented) were constructed and tested, and the efficiency coefficients were assessed on regional level. The degree of structural changes and efficiency of the used production and other resources were evaluated and conclusions were drawn. In the majority of the models, differences are observed between the northern regions of the country and the South Western and South Central regions. The most significant are the efficiency coefficient of the labor force used and the output produced, the gross value added and the net mixed income. In the other models, multidirectional changes are observed. North Western is the region in which all calculated efficiency coefficients increase, and in North Eastern and South Eastern, the most calculated coefficients decrease.

Background/Objectives: Before a cochlear implant is considered, patients undergo various audiological tests to assess their suitability. One key test measures the auditory brainstem response (ABR) to acoustic stimuli. However, in some cases, even with maximum sound stimulation, no response is detected. Methods: The promontory test involves electrical stimulation near the auditory nerve, allowing patients to associate the sensation. Ideally, the electrode is placed in the middle ear after opening the eardrum. This method, along with LA-TT-EABR and LA-TT-EALR, helps assess the auditory nerve's existence and excitability. The TympEALR test, utilizing a tympanic PromCERA, provides an alternative measurement. Previous research has shown the possibility of deriving brainstem and cortical potentials through trans-tympanic electrical stimulation, allowing for objective assessment of the auditory nerve's integrity and potentially objectifying patient sensations. Results: Sixteen patients have been tested using TympEALR. In seven of these, we found a positive response. The morphology was similar to other EALRs, e.g., using cochlear implants or trans-tympanic stimulation electrodes. We observed a higher influence of electrical artifacts than in other EALRs. Conclusions: TympEALR showed positive results in nearly half of the study participants, potentially avoiding invasive procedures. TympEALR can be a valuable alternative to trans-tympanic methods. More research is needed to determine if a negative result suggests against cochlear implantation.

Sunflower (Helianthus annuus L.) is an important oilseed crop cultivated extensively across the globe. High salinity adversely impacts plant growth and physiological processes. In this study, the data of the phenotypes and various indices were collected to clarify the physiological mechanisms underlying sunflower's salt tolerance with the seedlings of two salt-tolerant (182265 and 182283) and two salt-sensitive (182093 and 186096) genotypes, which were exposed to 350 mM NaCl for 4 days. The findings revealed that, during the seedling stage, salt-tolerant sunflowers accumulated less Na+ and more K+, resulting in a higher K+/Na+ ratio that mitigated ionic toxicity throughout the plants, compared to the salt-sensitive resources. Furthermore, the salt-tolerant germplasms also exerted salt tolerance through the following several pathways: they maintained robust osmotic regulation by accumulating higher levels of proline, soluble sugars, and other osmolytes; they neutralized reactive oxygen species (ROS) by elevating the activity of antioxidant enzymes; and they sustained optimal growth by boosting photosynthesis. Taken together, this study provided a more comprehensive assessment of the sunflower's physiological salt tolerance, offering valuable insights for further exploration of the molecular mechanisms of salt tolerance and accelerating the breeding process for sunflower varieties with improved salt resilience.

Bronchial asthma remains a serious medical problem, as approximately 10% of patients fail to achieve adequate symptom control with available treatment options. Macrophages play a pivotal role in pathophysiology of asthma, as well as in some other respiratory disorders. Typically, they are classified into two major classes, M1 and M2, however, recent findings indicate that in fact there is a whole range of macrophage polarization and functional diversity beyond this bimodal division. Isolation of individual cell sub-populations and identification of their role and diagnostic/therapeutic significance is still a challenge. Here we have attempted to assess the differences between patient-derived macrophage populations from bronchoalveolar lavage fluid (BALF) samples in different pulmonary disease conditions, based on their capability to interact with a range of specific as well as relatively non-specific carbohydrate-based ligands (containing galactose, mannose, trimannose, etc). Obviously, the main target of these ligands was CD206, however, other minor receptors, able to bind carbohydrates, have also been reported for macrophages. In addition, variations in receptor clustering and distribution may substantially affect affinity to the same ligand. Interestingly, with a panel of 5-6 different carbohydrate-based ligands with FTIR or fluorescent marker we were able not only to distinguish between healthy and disease states, but also between closely related diseases, such as purulent endobronchitis, obstructive bronchitis, pneumonia, and bronchial asthma. In some cases, the activated macrophage affinity to galactose base ligands was higher than that to mannose, indicating that complexes of CD-206 or other receptors may contribute substantially to macrophage functional features. For further investigation specific sub-populations of macrophages, seen as hallmarks to specific diseases, can be isolated and studied separately, probably giving new insights with diagnostic and therapeutic significance for hard-to-treat patients. Some of the markers varied from 0 to 100% in different types of bronchitis and pneumonia, which, we believe, deserves further investigation. Hard-to-treat group of patients with resistant disease can also be identified with this approach as fingerprint method, with a purpose to find a more targeted therapeutic strategy, improving their clinical outcomes.

The purpose of this paper is to determine the polycyclic aromatic hydrocarbons (PAHs) from medicinal plants and infusions prepared on them, as well as the assessment of the transfer of these contaminants from plants to infusions. The separation of compounds was achieved using microwave extraction for dryed plants and liquid-liquid extraction in the case of infusions. The extracts were cleaned by solid phase extraction, and compounds analysed by gas chromatography coupled with mass spectrometry (GC-MS). The risks related to the consumption of the infusions from the analysed plants were also evaluated by calculating the exposure contribution to the infusion consumption (EDI, ng/Kg.bw/day) and Margins of Exposure (MOEs). The average total content of PAHs varied from 277.22±12.78 to 2466.46±203.45µg/kg in dry plants, and benzo[b]fluoranthene and benzo[a]pyrene are the compounds present in all samples. In the herbal tea infusions, the average total PAHs content varied between 612.55±46.12ng/L and 2292.2±140.24ng/L. Statistical analysis showed that only BabF shows a significant strong correlation between the content of individual PAHs in plants and their infusions, while BaP, 4PAHs and HMW-compounds showed weak correlations. Average transfer rates of ∑16PAHs from plants to infusions varied from 7.25 to 32.86%. The MOEs of BaP and 4PAHs in herbal tea infusions with the highest PAH content confirmed that the consumption of medicinal teas presents a low risk to contamination with PAHs.

This study presents a novel investigation into the use of Light Emitting Diodes (LEDs) for the in vitro rooting of 'Marubakaido' and 'M9' apple tree rootstocks, marking the first time this approach has been reported in the literature. The research compares four different light sources: blue LED (450 nm), red LED (660 nm), a combination of red and blue LEDs, and traditional fluorescent lamps as a control. Mini-cuttings were inoculated in Murashige &amp; Skoog (MS) medium with reduced nutrient concentrations and supplemented with indoleacetic acid (IAA) and sucrose. The explants were incubated under controlled conditions for 30 days, allowing for a thorough evaluation of the effects of different light sources on various growth metric. The study found that blue LEDs significantly increased dry mass accumulation in 'Marubakaido' seedlings compared to both red LEDs and fluorescent lamps, demonstrating the effectiveness of LEDs in promoting plant growth. Utilizing LEDs not only enhances seedling development but also offers economic benefits over fluorescent lamps. LEDs are known for their high luminous efficiency, low energy consumption, and long lifespan, which can lead to reduced operational costs in plant production systems. This research not only contributes to the understanding of light effects on plant tissue culture but also suggests that the combination of blue and red LEDs can serve as a viable alternative to fluorescent lamps, potentially transforming practices in the field of horticulture and plant propagation.

It is crucial to conduct quality control tests to assess the quality and consistency of medicinal plant products before they are used. Products can often be placed on the market without registration, but some countries may require manufacturers to present product labels to authorities before selling them. These labels should confirm the composition of the product, particularly the concentrations of cannabidiol (CBD). The information on the label should provide unambiguous details about the qualitative composition and concentration of primary cannabinoids, such as CBD and THC. However, since there is a lack of regulatory control, it is possible to find inaccurate information on the label. This study aimed to create and validate a high-performance liquid chromatography method for identifying active compounds (cannabinoids) in CBD oil. The main compounds identified included Cannabidivarin (CBDV), Cannabidiolic Acid (CBD-A), Cannabigerolic Acid (CBG-A), Cannabigerol (CBG), Cannabidiol (CBD), Tetrahydrocannabivarin (THCV), Cannabinol (CBN), ∆9- Tetrahydrocannabinol (d9 -THC) ∆8- Tetrahydrocannabinol (d8-THC), Cannabicyclol (CBL), Cannabichromene (CBC), and Tetrahydrocannabinolic Acid (THCA-A), determined in line with the International Conference on Harmonization's (ICH) guidelines. The method was validated for linearity, accuracy, precision, limit of detection (LOD), and limit of quantitation (LOQ). It was determined to be linear, with a correlation coefficient (R2) ranging from 0.99937 to 0.99973. The LOD and LOQ values calculated from the calibration curve ranged from 0.05 to 0.13 and 0.50 to 0.61 µg/mL, respectively. The method also exhibited acceptable precision, with relative standard deviation values lower than or equal to 2%. The method's accuracy was assessed through recovery percentages and fell within an acceptable range (98.12–102.39%). This study's rigorous methodology and comprehensive findings significantly contribute to cannabinoid analysis. This validated protocol was used to analyze the cannabinoid concentration levels in 14 CBD oil products in the Republic of North Macedonia. The performance parameters indicate that the developed and validated method is suitable for quantitatively determining cannabinoids in CBD oil. The analysis of 14 CBD oil products revealed no significant derogation regarding the labeling, i.e., they were by the producers' declared variability.

The easiest way to utilise leather waste shavings is normally to produce new fuels from the most contaminated fractions for combustion or gasification. But since these waste contain up to 10% of nitrogen (N), burning it only for the energy recovery would not be rational. On the other hand, the chromium (Cr) content exceeding 5% in half of the waste stream (w/w) is too significant to be applied in agriculture. In this work, 4 acid hydrolysates from leather waste shavings both wet-white free of Cr and wet-blue with Cr were used: 2 with a mixture of acids and supplemented with Cu, Mn, Zn and other 2 as semi-product from collagen extraction using hydrochloric acid. The acid hydrolysates were prepared using a specific combination of acids under controlled conditions, ensuring the maximum release of nitrogen while maintaining the safety and integrity of the process. Additionally wet-green leather waste shavings eg. impregnated with olive extract were used followed by their 2 treatments: amendment with a biochar from “wet white” leather waste shavings and amendment with this biochar incubated with a commercial phosphorus stimulating microbial consortia BactoFos. They were applied as organic nitrogen-based fertilisers in a glasshouse experiment, consisting of 4-5 subsequent harvests every 30 days, under spring-autumn conditions in northern Poland. Ryegrass dry matter and nitrogen plant content were measured across 7 increasing fertiliser doses. Nitrogen utilisation, relative agronomic effectiveness, nitrogen use efficiency, total ryegrass dry matter and nitrogen utilisation breakdown across harvests were calculated. Biochar amended wet-greens provided the highest nitrogen use efficiencies exceeding 100% after 4 months growth (for 20 kg N/ha) and varying from 17% to 37% in particular months. This is backed up by another parameter (relative agronomic effectiveness) that for these materials exceeded 150% for single month and in total around 33%. Biochar amendments significantly increased agronomic parameters for wet-greens and their microbial treatment enhanced them even further. In sustainability aspects, assuming only the industrial partner waste potential, that gives 919,8 t of recycled nitrogen per year, which comes back to the environment in plant biomass. Recycling this type of waste can replace inorganic fertilizers reducing greenhouse gas emissions and carbon footprint.

By the strong relation between ξ function and the Riemann ζ function, we will prove the Riemann hypothesis which states that ”All non-trivial zeros z = x+y i of ζ must lie on the critical line x = 1/2". ”.

This paper presents a comprehensive review of the You Only Look Once (YOLO) framework, a transformative one-stage object detection algorithm renowned for its remarkable balance between speed and accuracy. Since its inception, YOLO has evolved significantly, with versions spanning from YOLOv1 to the most recent YOLOv11, each introducing pivotal innovations in feature extraction, bounding box prediction, and optimization techniques. These advancements, particularly in the backbone, neck, and head components, have positioned YOLO as a leading solution for real-time object detection across a variety of domains. In this review, we explore YOLO's diverse applications, including its critical role in medical imaging for COVID-19 detection, breast cancer identification, and tumor localization, where it has significantly enhanced diagnostic efficiency. YOLO's robust performance in autonomous vehicles is also highlighted, as it excels in challenging conditions like fog, rain, and low-light environments, thereby contributing to improved road safety and autonomous driving systems. In the agricultural sector, YOLO has transformed precision farming by enabling early detection of pests, diseases, and crop health issues, promoting more sustainable farming practices. Additionally, we provide an in-depth performance analysis of YOLO models—such as YOLOv9, YOLO-NAS, YOLOv10, and YOLOv11—across multiple benchmark datasets. This analysis compares their suitability for a range of applications, from lightweight embedded systems to high-resolution, complex object detection tasks. The paper also addresses YOLO's challenges, such as occlusion, small object detection, and dataset biases, while discussing recent advancements that aim to mitigate these limitations. Moreover, we examine the ethical implications of YOLO's deployment, particularly in surveillance and monitoring applications, raising concerns about privacy, algorithmic biases, and the potential to perpetuate societal inequities. These ethical considerations are critical in domains like law enforcement, where biased object detection models can have serious repercussions. Through this detailed review of YOLO's technical advancements, applications, performance, and ethical challenges, this paper serves as a valuable resource for researchers, developers, and policymakers looking to understand YOLO’s current capabilities and future directions in the evolving field of object detection.

The emergence of quantum computers poses a significant threat to the security of conventional public-key cryptosystems, driving the demand for quantum-resistant cryptographic solutions. In response, NIST conducted a multi-year competition, ultimately selecting four ciphers. Among these, Falcon employs CDT sampling, which produces arrays of random values derived from a discrete Gaussian distribution during the signature generation phase. This array is then used with secret key information, forming the core of Falcon. Enhanced variants of Falcon, such as Mitaka, SOLMAE, and Antrag, implemented CDT sampling using comparison operations. Previous research by Choi et al. proposed a single trace analysis and countermeasure for CDT sampling, which exploited a non-constant-time vulnerability in 8-bit AVR microcontrollers. However, this vulnerability is specific to certain environments, and a potentioal vulnerability in comparison operation based constant-time CDT sampling remain not studied. This paper is an extension of that study. This paper investigates the constant-time operation of comparison operation-based CDT sampling on Arm Cortex-M4-based chips and proposes a deep learning-based side-channel analysis to recover the sampling values using novel vulnerability. The proposed model achieves an F1 score of 1.0 and a recovery success rate of 99.97%.

To mitigate the emissions of greenhouse gases from fossil fuels, biodiesel production has be-come more attention over the past decade, especially for the use of waste cooking oils and non-edible oils as starting feedstock. For the biodiesel production process, the suitability of a catalyst is a core function implemented in the transesterification reaction. heterogeneous cata-lysts were superior to homogeneous catalysts due to some advantages such as no saponification products formed, recyclability, and less equipment corrosion. Recent studies also revealed that heterogeneous solid base catalysts are widely used for the production of biodiesel. Further-more, the biomass-based ash derived from herbaceous & agricultural biomass is increasing rap-idly because of its environmental sustainability, high biodiesel yield and low catalyst cost. To search for the depth of green catalysts, this mini-review paper thus focused on the summary of various heterogeneous biomass-based potassium-rich catalysts for the sustainable production of biodiesel. Due to cocoa pod husk that’s rich in potassium-containing minerals, it was found that its derived ash may be the most commonly used solid base catalyst in the biodiesel production.

Background/Objectives: Indocyanine green videoangiography, integrated in the operative microscope, is frequently used in cerebrovascular surgery; it is believed to be a simple and reliable method for capturing high-resolution images in a real-time setting. This technology is often preferred, for cost or availability, to Doppler or intraoperative angiography DSA (Digital substraction angiography): with the same assumption it was possible, in our preliminary experience, to partially vicariate the aforementioned devices using the SPY mode of the Stryker endoscope; it allowed the visualization of fluorescence in high definition.; Methods: A retrospective analysis was conducted on a series of 5 patients suffering from cerebral aneurysm or AVM who underwent, during the last year at our institution, surgical treatment with the aid of the microscope supported by the Stryker endoscope in SPY mode for the visualization of fluorescence emitted by indocyanine green; Results: The intraoperative use of indocyanine green was a safe, rapid and effective technique within a preliminary case study of "regular - not giant" aneurysms and AVM located superficially in the cerebral parenchyma. The endoscopic technique in SPY mode has allowed to partially vicariate, in selected cases, the use of Doppler, intraoperative angiography and integrated microscope video angiography; Conclusions: the main purpose of aneurysm surgery is to completely exclude them from the cerebral vascular circulation in the absence of residues in the collar and occlusion of adjacent vessels; similarly, in AVM surgery the goal is the early identification of the nidus and to avoid residues within it given the high risk of new rupture. For these purposes, we propose, in selected cases and keeping in mind the limitations of the technique already described in the literature, the support of the endoscope in SPY mode during the microsurgical procedure in order to visualize the green fluorescence of indocyanine.

Currently, in Europe, producers of building materials are implementing innovative solutions that provide a chance for the widespread construction of zero-emission and zero-energy build-ings. However, they encounter legal barriers related to the lack of standardization procedures enabling the rapid placing of innovative construction products on the market. The European project Horizon 2020: Measuring Envelope products and systems contributing to the next gener-ation of healthy nearly Zero Energy Buildings (MEZeroE), is to support producers of innovative envelope products used in zero-energy buildings, including in the field of certification, CE marking and placing them relatively quickly on the market. The article presents one of the research procedures developed and tested by Pilot Measurement & Verification Lines (PM&VL7) as part of the MEZeroE project for FLEX&ROBUST polyurethane flexible connectors. This procedure takes into account applicable legal requirements regarding CE marking and also indicates a certification path for this type of products.

Microplastics (MP), defined as plastic particles less than 5 mm, pose a significant global environmental threat, particularly in aquatic ecosystems, due to their persistence and potential harmful effects on wildlife and human health. They can absorb persistent organic pollutants (POP) like polycyclic aromatic hydrocarbons (PAH) and polychlorinated biphenyls (PCB), raising concerns about their impact on biota. To elucidate this, the present study employed attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to analyse the characteristics of MP sourced from commercial cosmetics. It also utilised nematodes, which are widely accepted indicators of environmental change. Indeed, despite the known risks of MP in aquatic habitats, knowledge of their effects on free-living and beneficial nematodes is limited. This study investigated the toxicity of MP on Caenorhabditis elegans and two entomopathogenic nematode species, Steinernema feltiae (the enviroCORE strain SB12[1]) and Steinernema carpocapsae (a commercial strain from e-NEMA) in laboratory bioassays. Nematodes were exposed to various concentrations of MP and other pollutants in controlled settings over 72 to 96 hours. Additionally, high-throughput 18S rDNA sequencing was used to analyse nematode biodiversity in sediments from the River Barrow (RB) in SE Ireland. Results revealed that MP adversely affected nematode survival and community structure, highlighting the ecological risks posed by MP pollution in river sediments and emphasizing the need for further research into the health of benthic ecosystems in Ireland.

The application of three-dimensional (3D) printing/bioprinting technologies and cell therapies has garnered significant attention due to their potential in the field of regen-erative medicine. This paper aims to provide a comprehensive overview of 3D print-ing/bioprinting technology and cell therapies, highlighting their results in diverse medical applications, while also discussing the capabilities and limitations of their com-bined use. The synergistic combination of 3D printing and cellular therapies has been recognised as a promising and innovative approach, and it is expected that these tech-nologies will progressively assume a crucial role in the treatment of various diseases and conditions in the foreseeable future. This review concludes with a forward-looking perspective on the future impact of these technologies, highlighting their potential to revolutionize regenerative medicine through enhanced tissue repair and organ re-placement strategies.

Localization accuracy in non-line-of-sight (NLOS) scenarios is often hindered by the complex nature of multipath propagation. Traditional approaches typically focus on NLOS node identification and error mitigation techniques. However, the intricacies of NLOS localization are intrinsically tied to propagation challenges. In this paper, we propose a novel single-site localization method tailored for complex multipath NLOS environments, leveraging only angle of arrival (AOA) estimates in conjunction with a ray-tracing (RT) algorithm. The method transforms NLOS paths into equivalent line-of-sight (LOS) paths through the generation of generalized sources (GSs) via ray tracing. A novel weighting mechanism for GSs is introduced, which, when combined with an iteratively reweighted least squares (IRLS) estimator, significantly improves the localization accuracy of non-cooperative target sources. Furthermore, a multipath similarity displacement matrix (MSDM) is incorporated to enhance accuracy in regions with pronounced multipath fluctuations. Simulation results validate the efficacy of the proposed algorithm, achieving localization performance that approaches the Cramér-Rao lower bound (CRLB), even in challenging NLOS scenarios.

Economic interests, penchant, and goals or pursuits drive and stir the motivation and impetus or motives for and the reason behind most business activities and ventures, which is in line with classical economic theory and capitalism; however, this revolves around one of the 3-4 pillars outlined and identified as “economic, legal, ethical, and discretionary or philanthropic” by ‘Carroll in this article and from previous works or articles. It is essential and crucial to note the line and clear distinction or border drawn between competing and complementary frameworks as exemplified in the present article by Carroll and different motives for different organizations in pursuing ‘CSR. The central objective of this presentation and research activity is to examine the decision-making and choice architecture from the influences of nudge on the economic decisions and aspects of ‘CSR pursued by managers stressing on the ‘RBV: resource-based view and point to the potentials and use of ‘CSR as a strategic tool by corporations from a stakeholder’s perspective, paying attention to crucial decision-makings and the need for striking a balance from the competing interests perspective, even though an economic aspect of ‘CSR is pursued and prioritized while gaining a competitive advantage or leveraging from the ‘RBV point of view.

The role of onion as a second most consumed and cultivated vegetable around the world and its renown qualities that made it to be called as “queen of the kitchen” have positioned it to be very vital to the nutritional and economical contributions around the world. Polyploidy serves the purpose of groundbreaking innovation towards plant breeding by improving plants’ yield and vigor. This study was conducted to determine the effect of different concentrations of colchicine on the seedlings of onion on the morphology, antioxidant activity and dissolved sugars. Three concentrations of colchicine were used; including 0.05, 0.1 and 0.2% (w/v) which were applied to the seeds of Allium cepa for the exposure period of 24 hours. Chromosomal analysis confirmed the induction of polyploidy which led to the successful duplication of the chromosomes number from diploid (2n = 16) to tetraploid (4n = 32). Successful induction of polyploidy was achieved by the application of 0.05% (w/v) concentration of colchicine as it yielded the formation of seedlings which were morphologically and biochemically superior over the remaining concentrations and control at p ≤ 0.05 probability. The 0.05% (w/v) concentration showed the highest survival rate between the treatments by recording 83.33% compared to 33.33% and 0.00% of 0.1 and 0.2% (w/v) concentrations respectively, but topped by the control which recorded 91.57% survival rate. Furthermore, the 0.05% concentration of colchicine showed significant difference in the morphology as it recorded the biggest size of seedlings by height reaching up to 73.6cm tall with the diameter of the bulbs reaching 5.64 cm after 14 weeks. It also showed significant difference in the antioxidant activity by recording the highest DPPH scavenging percentage of up to 72.58%, followed by 0.1% and control. The tetraploids also showed significant difference in the dissolved sugars as they recorded the highest refractive index between the treatments and control. The application of 0.05% (w/v) concentration of colchicine resulted in the formation of the seedlings that have superiority in the morphology, antioxidant activity and amount of dissolved sugars compared to other treatments and control.

Background/Objectives: While studies suggest that young children can learn and think about sustainability, most research has focused on children aged three to five, leaving a significant gap in understanding how to engage toddlers (under three) in early childhood education for sustainability (ECEfS). This study aims to address this gap, a crucial and often overlooked area, by investigating early childhood teachers' perceptions of ECEfS and their pedagogical practices for nurturing sustainability in a toddler group in a Swedish preschool. Methods: The study employed a case study approach, incorporating observations, interviews, and document analysis for data collection. Qualitative techniques were used for data analysis. The research was conducted with a strong commitment to ethical considerations, including obtaining participants' consent, ensuring confidentiality and privacy, informing them of their right to withdraw, and maintaining anonymity. Results: The findings of this study bring hope. They indicate that teachers understand education for sustainability and can implement sustainability-related pedagogical practices in a toddler group. They can create suitable learning environments and establish connections between sustainability issues and daily life activities in the classroom, enhancing the children's overall learning experience. Conclusions: The study's findings underscore the pivotal role of educators in shaping the mindsets and behaviors of future generations, thereby supporting the long-term goals of sustainable development. By nurturing toddlers' innate curiosity and harnessing their brain's plasticity, educators can effectively engage toddlers in ECEfS and promote sustainable development from an early age. The study's implications highlight the need to prioritize ECEfS during toddlerhood to realize the full potential of this critical investment in the future of our planet.

The present paper reports exact results for the muon self-energy and anomalous g-factor. A unique to the muon cut-off terms that remove the radial singularity in the system and regularize the corresponding electrodynamics are presented. Equations of motion and a transcendental equation satisfied by the muon anomalous g-factor are derived, with solution a_m=0.0011659201231(18). The obtained value matches the latest experimental one found in the literature to about 0.46 ppb ruling out a possible tension between theory and experiment.

Background/Objectives: Calculating the radiation dose from CT in 18F-PET/CT examinations poses a significant challenge. The objective of this study is to develop a deep learning-based automated program that standardizes the measurement of radiation doses. Methods: The Torso CT was segmented into six distinct regions using TotalSegmentator. An automated program was employed to extract the necessary information and calculate the effective dose (ED) of PET/CT. The accuracy of our automated program was verified by comparing the EDs calculated by the program with those determined by nuclear medicine physician (n=30). Additionally, we compared the EDs obtained from an older PET/CT scanner with those from a newer PET/CT scanner (n=42). Results: The CT ED calculated by the automated program was not significantly different from that calculated by the nuclear medicine physician (3.67 ± 0.61 mSv and 3.62 ± 0.60 mSv, respectively, p = 0.7623). Similarly, the total ED showed no significant difference between the two calculation methods (8.10 ± 1.40 mSv and 8.05 ± 1.39 mSv, respectively, p = 0.8957). A very strong correlation was observed in both CT ED and total ED between the two measurements (r2 = 0.9981 and 0.9996, respectively). When comparing the older and newer PET/CT scanners, the CT ED was not significantly different. However, the PET ED was significantly lower in the newer scanner than in the older scanner (4.39 ± 0.91 mSv and 6.00 ± 1.17 mSv, respectively, p &lt; 0.0001). Consequently, the total ED was significantly lower in the newer scanner than in the older scanner (8.22 ± 1.53 mSv and 9.65 ± 1.34 mSv, respectively, p &lt; 0.0001). Conclusions: We successfully developed a deep learning-based automated program that calculates the ED of torso 18F-PET/CT, thereby eliminating inter-operator variability.

Background/Objectives: Although the protective effects of zinc against COVID-19 are documented, its impact on the COVID-19 vaccine immunogenicity remains unknown. Methods: We conducted a prospective study involving a cohort of 79 Japanese individuals (aged 21–56 years; comprising three subcohorts) and measured their serum zinc levels pre-vaccination and anti-SARS-CoV-2 IgM/IgG levels pre- and post-vaccination over 4 months. Results: Serum zinc concentrations ranged 74–140 and 64–113 ug/dL in male and female individuals, respectively, with one male and 11 female participants exhibiting subclinical zinc deficiency (60–80 ug/dL). Mixed models for antibody titers, accounting for subcohorts, repeat measurements, and covariates (e.g., vaccine type, sex, age, height, steroid use, medical history, smoking and drinking habits, perceived stress, and sleep disturbances) showed positive effects of zinc on IgM (p = 0.012) and IgG (p = 0.013) in 45 female individuals with 255 observations. However, a similar association was not found in the 34 male participants with 162 observations. This discrepancy may be attributed to one participant being included in the subcohort with frequent repeat measurements (10 repeats in 4 months). COVID-19 mRNA vaccine immunogenicity was enhanced in the participants with high baseline blood zinc levels within the reference range. Conclusions: Our findings underscore the relevance of maintaining adequate zinc levels before vaccination, which can be achieved through a balanced diet and healthy lifestyle choices.

Premature skin aging, also known as photoaging, refers to the changes of the structure and function of the skin caused by chronic sun exposure. The ultraviolet radiation in the sunlight is one of the key factors that causes photoaging. Thus, MMPs, TGFB1, and NF-κB signaling can be an effective therapeutic strategy for UVB exposure. In this study, we used human dermal fibroblast and mouse macrophage cells to identify the mediators of skin photoaging. Quercitrin isolated from ‘Green Ball’ apple peel was treated to UVB-irradiated fibroblast cell and lipopolysaccharide (LPS)-induced macrophages to identify photoaging prevention effect of quercitrin. Genes that are associated with photoaging was determined by using ELISA, western blot, and qPCR. Quercitrin increased collagen biosynthesis in UVB-irradiated fibroblast cell via regulating MMPs, TIMP-1, TGFB1, HAS2, and COL1A2. In addition, quercitrin regulated p-65, iNOS, COX-2, and mediators (PGE2 and NO), in the NF-κB signaling process, and inhibited the production of cytokines in LPS-induced macrophages. These results indicates that quercitrin can improve photoaging damaged skin by regulating MMPs, TGFβ, and NF-κB signaling pathway modulators.

Purpose – This paper aims to investigate the role of forensic accounting skills in enhancing auditor self-efficacy towards fraud detection in Indonesia. In addition, explores the moderating effect of the implementation of Generalized Audit Software (GAS) and whistleblowing system on the relationship between accounting and auditing skills and auditor self-efficacy, as well as its role in enhancing fraud detection. Methodology– A cross-sectional survey was developed and distributed to 537 external auditors working in Indonesia. This study uses a multiple linear regression analysis method with multiple linear moderation models using WarpPLS 8.0 software. Findings – The study results indicate a significant direct relationship between practical communication skills, psychosocial skills, accounting and auditing skills, and auditor self-efficacy. However, technical and analytical factors do not affect auditor self-efficacy. The study's results indicate a significant direct relationship between auditor self-efficacy and fraud detection. It is revealed that implementing GAS moderates the relationship between auditor self-efficacy and fraud detection. In contrast, the study's results do not show a significant relationship between technical and analytical skills and auditor self-efficacy. Novelty– This research paper's originality lies in exploring the role of forensic accounting skills by using GAS and Whistleblowing systems to enhance auditor self-efficacy toward fraud detection in Indonesia.

This study investigates the relationship between economic growth and energy con-sumption—both renewable and non-renewable—in European Union countries during the green transition. Using a panel dataset of 28 EU countries from 1995 to 2021, we employ econometric techniques, including the Westerlund cointegration test, to assess long-term equilibrium relation-ships, accounting for cross-sectional dependence and slope heterogeneity. The results indicate that, while both renewable and non-renewable energy consumption are associated with economic growth, their roles differ. Renewable energy consumption shows a positive but less robust rela-tionship with GDP, with limited evidence of a predictive impact on economic growth. In contrast, non-renewable energy consumption demonstrates a more robust bidirectional causality with GDP, indicating a more intertwined relationship with economic growth during the study period. Our results have significant policy recommendations, indicating that promoting renewable ener-gy sources does not hinder economic growth. Moreover, such promotion has the potential to con-tribute substantially to economic growth in the future. Therefore, in addition to other crucial ben-efits, such as increased energy security, the development of renewable energy sources does not pose a threat to the economy. This is particularly relevant as many EU countries, including Po-land, Romania, Hungary, Bulgaria, Slovakia, and Lithuania, still have underdeveloped renewa-ble energy sectors.

This paper examines the role of public enterprises in providing safe drinking water in developing countries and analyses the factors influencing households' water source choices using a revealed preference model. The study, conducted in rural Nepal, reveals a substantial willingness to pay for convenient access to safe water, challenging the notion that rural households, especially women, do not value time savings from improved water access. The findings suggest that the predominant supply-driven, heavily subsidised approach of public water utilities warrants reconsideration. The paper argues that the willingness to pay exists but the willingness to charge is stymied. This policy creates a vicious cycle of poor service and poor cost recovery. The paper suggests a paradigm shift towards a more demand-responsive approach, allowing households to choose and pay for their desired service levels while ensuring a minimum level of safe water for all. This could enhance sustainability, welfare, and financial viability of public water utilities. The study concludes that public enterprises have a critical role in ensuring universal access to safe water but should adopt a more dynamic, accountable, and service-oriented approach, incorporating user preferences and contributions while retaining their core public mandate.

Sustainable crop production includes methods of growing food in a responsible manner avoiding application and dependence on chemically produced fertilizers and pesticides. The latter means development of approaches that lead to environmentally mild inputs based on the production-consumption-recycling principle. Biofertilizers are an important tool to achieve sustainable crop production. In this work, we report the results of experiments on growth and spore/mycelium production of plant growth promoting A. niger applying standard nutritional medium (potato-dextrose broth, PDB) enriched with 3% insoluble phosphate (20 to 200 mesh hydroxyapatite of animal-bone origin, HABO) and 0 to 80 g/L glycerol (a by-product of biodiesel production. Results showed the ability of A. niger to acidify the medium with the highest titratable acidity of 28.9 mmol/1 (at 5% of glycerol) and solubilize animal bone char under these conditions. As a second stage of the experimental work, the resulting final products were used to formulate gel-based inoculant. Both, the spores and mycelium produced during the fermentation process were further used as a base for formulation to make the biofertilizer production the key in the Sustainable Agriculture. Storage of the resulting products reported here was facilitated by the presence of glycerol in the formulation system.

US life expectancy now lags significantly behind the majority of high-income countries, having grown more slowly since 1980 for reasons that are not evident and have been debated. An exploratory system dynamics model is presented that reproduces the full pattern of US life expectancy from 1960 to the present. Multiple socioeconomic and behavioral factors help to explain the historical pattern, two of them apparently most responsible for the stagnation since 1980: the growth of obesity and the leveling off of growth in social spending. Some of the factors in the model are traced back to earlier causes, and obesity’s growth in particular is traced back to excess growth in private health care spending and its adverse effect on workers’ wages. The model’s base run does a good job of reproducing a variety of historical time series data going back to the 1960s, and counterfactual testing produces plausible results. The model may thus be considered a reasonable starting point for more conclusive future modeling of US life expectancy.

Odor Source Localization (OSL) technology allows autonomous agents like mobile robots to find an unknown odor source in a given environment. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. Compared to traditional olfaction-only OSL method, our proposed method integrates vision and olfaction sensor modalities to localize odor sources even if olfaction sensing is disrupted by turbulent airflow or vision sensing is impaired by environmental complexities. The model leverages the zero-shot multi-modal reasoning capabilities of large language models (LLMs), negating the requirement of manual knowledge encoding or custom-trained supervised learning models. A key feature of the proposed algorithm is the `High-level Reasoning’ module, which encodes the olfaction and vision sensor data into a multi-modal prompt and instructs the LLM to employ a hierarchical reasoning process to select an appropriate high-level navigation behavior. Subsequently, the `Low-level Action’ module translates the selected high-level navigation behavior into low-level action commands that can be executed by the mobile robot. To validate our method, we implemented the proposed algorithm on a mobile robot in a complex, real-world search environment that presents challenges to both olfaction and vision-sensing modalities. We compared the performance of our proposed algorithm to single sensory modality-based olfaction-only and vision-only navigation algorithms, and a supervised learning-based vision and olfaction fusion navigation algorithm. Experimental results demonstrate that multi-sensory navigation algorithms are statistically superior to single sensory navigation algorithms. The proposed algorithm outperformed the other algorithms in both laminar and turbulent airflow environments. The code for this work can be found at: https://github.com/SunzidHassan/24_Vision-Olfaction-LLM.

Adolescent eating disorders pose a significant public health challenge, deeply affecting both physical and emotional well-being. Early diagnosis is important for improving treatment outcomes, though it remains complex due to multiple influencing factors. The family perspective is essential in this process, as it provides valuable insights into changes in adolescents’ habits and emotional health. Methods: A descriptive qualitative study was conducted in Madrid, Spain, between January and February 2023, using a phenomenological approach to explore the experiences and perspectives of family members of adolescents with eating disorders. Results: Four thematic blocks with their categories were identified: (T1) Diagnosis, (T2) Family (T3) Resources, and (T4) Treatment. Participants emphasized the need for early intervention and a multidisciplinary approach to the treatment of eating disorders. Family therapy was recognized as vital in treatment, and common dissatisfaction in the public health structure underscored the need for greater investment in research and access to specialists. Mental health nurse practitioners have an important role in providing comprehensive care and support as well as mental health literacy. Conclusions: A holistic patient-centered approach, including family involvement and appropriate support systems, is key to improving outcomes and quality of life of adolescents undergoing treatment for eating disorders. Improving healthcare resources and addressing the challenges faced by families is essential. In addition, mental health literacy is critical, as it enables families to understand the disease better, make informed decisions, and actively participate in the recovery process, contributing to improved therapeutic outcomes and quality of life for patients.

Food insecurity (FI) is a persistent issue in Brazil, with significant disparities across the country's macroregions. This study investigated food acquisition locations and types of foods purchased at different levels of FI, utilizing data from 57,920 households in the 2017–2018 Brazilian Household Budget Survey. Food acquisition locations were grouped into supermarkets, small markets, fairs/farmers’ markets/public markets, and others. Foods were categorized into 12 groups: rice, beans, vegetables, fruits, red meats, fish, poultry, eggs, milk and dairy products, bread, cookies, and sugary drinks. Supermarkets are the primary source of food in Brazil. However, in the North and Northeast regions, small markets are more frequently used across all levels of FI. Nationally, most food groups are predominantly purchased at supermarkets. Nevertheless, households experiencing moderate or severe FI rely more on small markets for essential items such as rice, beans, and proteins, as well as ultra-processed foods. These findings highlight the need for public policies that improve food access for vulnerable populations and address regional inequalities. Enhancing access and ensuring food security across different regions is essential to promote equitable and healthy diets throughout the country.

The article presents extremely current issues concerning imaging and measurements carried out using coordinate optical systems in which the result of scanning spatial objects is a point cloud. What is important, the entire accuracy assessment of the conducted fast, effective coordinate measurement nowadays takes place in the computational area, beyond direct sensory percep-tion, and depends increasingly on its power and the computational algorithms used. Further-more, we are getting closer and closer to recognising virtual standards in coordinate metrology as a direction that allows for an increase in measurement accuracy. Especially in recent years, the importance of the problem has been confirmed by the activities of the most significant scientific and research centres. They focus on improving the accuracy of the data obtained in the form of point clouds, using more precise scanning methods for this purpose, and developing filtering algorithms to remove noise, including methods using artificial intelligence. Based on many years of research, the authors identified a problem regarding the difficulty in developing data obtained from optical systems, such as laser triangulation head systems, systems operating on the principle of structural light, photogrammetric systems, as well as computer tomographs, and the impact of these systems on the assessment of measurement accuracy. Therefore, the optical measurement process was analysed in terms of the quality of the acquired point clouds. The authors presented the division of factors, which, in coordinate optical meas-urements, generate errors in data acquisition and development. The authors also indicated which of these factors generate the most significant errors and, above all, emphasised the impact of the software used, the measurement operator, and the methods of cloud filtration applied by the operator. Therefore, the accuracy assessment of the optical measurement has been noted as a critical problem, and so far, it has not been solved effectively. In the article, as a solution to this problem, the authors proposed the OPTI-U method of estimating uncertainty for optical meas-urements. The method, what is very important, was developed and verified under the conditions of an accredited calibration laboratory. The summary also gives directions for further work on developing and disseminating the developed method, particularly introducing virtual standards.

Background: Malnutrition is a widespread issue among old people, significantly impacting health outcomes. Nutritional interventions can improve health, but their success often depends on the attitudes and knowledge of healthcare workers. This study examines the influence of continuing education on healthcare workers' attitudes and practices toward old people's nutrition. Aim: The study assesses healthcare workers' attitudes toward old people's nutrition using the validated Italian version of the SANN-G questionnaire, focusing on staff in nursing homes in Northern Italy. Methods: A cross-sectional study was conducted with 1,789 healthcare workers from 41 facilities. The SANN-G questionnaire measured attitudes across five dimensions: nutritional norms, habits, assessment, intervention, and individualization. Data were collected online and on paper, with descriptive and inferential statistical analyses (chi-square and ANOVA) performed using R software. Results: Most respondents were female (68.59%) and aged 41–50 (33.31%), with nursing assistants comprising 35.83%. Only 23.48% scored positively on the SANN-G scale, with most displaying neutral or negative attitudes. Education on malnutrition significantly improved attitudes, particularly in assessment, intervention, and individualization. Younger respondents and nurses were more likely to have positive attitudes after educational interventions, while older respondents and physicians tended to show neutral or negative attitudes. Conclusion: Continuing education on malnutrition is crucial for fostering positive attitudes among healthcare workers. Specialized education leads to more proactive approaches, highlighting the need for targeted educational programs to improve old people's nutritional care.

This study aimed to determine the prevalence of coinfection with malaria and intestinal parasites and assess its association with anemia in school-aged children from rural and urban settlements in Gabon. This cross-sectional study involved afebrile school children recruited at schools between May and June 2021. Blood and stool samples were collected from participants who provided informed consent to participate in the study. Hemoglobin concentration (Hb) was measured using a HemoCue photometer (HemoCue 201, HemoCue, Angelholm, Sweden). Giemsa-stained blood films were examined to detect malaria parasites and any filarial infections, while the Merthiolate-iodine concentration (MIc) method was used to identify intestinal parasitic infections (IPIs). A total of four hundred and seventy (470) school-aged children were successfully enrolled in this study. The observed prevalence rates were as follows: malaria infection at 69.6%, IPIs at 19.1%, filaria at 5.1%, Schistosoma infection at 15.0%, and anemia at 29.0%. Coinfections of malaria with IPIs, filaria, and Schistosoma were present in 12.3%, 4.7%, and 6.6% of the children, respectively. Malaria and filaria infections were associated with residing in Lastourville (LTV) city and were also correlated with age, whereas IPIs were associated with male gender and living in the city of LTV. Anemia was linked to malaria infection and was more prevalent among children living in rural areas. The findings of this study indicate that malaria, IPIs, and Schistosoma infections continue to pose a significant public health problem in the study area, even though only malaria infection appeared to be associated with anemia. Nevertheless, these results highlight the need for implementing control measures to reduce the rates of malaria, IPIs, filaria, and Schistosoma, particularly in Lastourville.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with cognitive dysfunction, memory decline, and behavioral disturbance, and pathologically characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. Although various hypotheses have been proposed to explain the pathogenesis of AD, including the amyloid beta hypothesis, oxidative stress hypothesis, and abnormal phosphorylation of tau proteins, the exact pathogenic mechanisms underlying AD remain largely undefined. Furthermore, effective curative treatments are very limited. Epidemiologic studies provide convincing evidence for a significant association between type 2 diabetes and AD. Here, we showed energy metabolism using glucose, lactate and ketone bodies and lipids as energy substrates in normal brain, and changes in such energy metabolism due to type 2 diabetes. We also showed the influences of such altered energy metabolism due to type 2 diabetes on the pathology of AD. Furthermore, we comprehensively searched the risk factors related with type 2 diabetes for AD, and showed possible therapeutic interventions based on considering risk factors and altered brain energy metabolism due to type 2 diabetes for the development of AD.

The black soldier fly larvae meal has attracted attention as a sustainable alternative protein ingredient in poultry feed. In the present study, we sought to determine the effect of black soldier fly larvae on the growth performance of broilers as replacement to fishmeal. Forty (40) one day old broiler chicks were randomly selected and distributed in 4 replicates. The Black soldier fly larvae were formulated and added to broiler’s marsh as replacement to fishmeal. Birds were fed on four experimental diets formulated as follows 15% black soldier fly (BSF15), 20% (BSF20) and 25% (BSF25) corresponding to dietary BSF inclusion levels of 150 g/kg, 200 g/kg and 250 g/ kg, respectively and the control diet (BSF0) contained 20% of fishmeal (FM) as protein sources (250 g/kg). Feed and water were provided ad libitum. Proximate analysis showed that BSFLM contained comparable nutrient values to fishmeal. The highest average weight gain was achieved when birds were provided diet with 25% BSFLM. Based on this study, it can be concluded that black soldier fly larvae meal represents an alternative source of animal protein to replace fishmeal in broiler chicken diet in their diet without adverse effect on growth performance and consumer preferance.

The real birth of Brazil can be traced to the remote Jesuit village of São Paulo de Piratininga, founded in 1554, after arduous efforts to ascend the Serra do Mar. This isolated settlement, inhabited by a mixture of Indigenous peoples and Portuguese colonizers, became the pivotal point for the expansion of Portuguese territory in South America. The people of São Paulo, or paulistas, shaped by their harsh environment and violent history, forged a unique identity. Through their relentless expeditions, the bandeirantes ventured deep into the interior, hunting Indigenous peoples for slavery and expanding the Portuguese domain beyond the boundaries defined by European treaties. This essay explores how the humble origins of São Paulo de Piratininga grew into a force that shaped the modern Brazilian state and its borders.

The finite volume method (FVM) is a kind of numerical analysis method that is simple and can take into account the topography as the finite element method (FEM). The adjoint state method (ASM) can easily and efficiently calculate the gradient vector of the objective function for the inversion. We developed a program to apply these methods to 3-D Magnetotelluric (MT) inversion and verified it using test models. In the forward modelling, it was confirmed that the program could perform analysis properly and efficiently considering topography and subsurface resistivity heterogeneity. Furthermore, we conducted the inversion using a synthetic open dataset and could reconstruct the true model of the dataset. The comparison with the previous work revealed that the computation time was comparable in spite of the fact that we calculated without MPI implementation, which the previous work used.

The understanding of properties of multipartite systems is a long-lasting challenge in quantum theory that signals the need for new ideas and alternative frameworks that shed light on the intricacies of the quantum behavior. In this work, we argue that symmetric spaces provide a common language to describe two qubit and two mode Gaussian systems. Our approach relies on the use of equivalence classes that are defined by a subgroup of the maximal symmetry group of the system and involves an involution which enables the Cartan decomposition of the group elements. We work out the symmetric spaces of two qubits and two modes to identify classes which include an equal degree of mixing states, product states, X states, among others. For three-qubits and three-modes, we point out how the framework can be generalized and report partial results about physical interpretations of the symmetric spaces.

Generating coherent and comprehensive responses remains a significant challenge Question-Answering (QA) systems when working with short answers especially for low-resourced languages like Farsi. We present a novel approach to expand these answers into complete, fluent responses, addressing the critical issue of limited Farsi resources and models. Our methodology employs a two-stage process: first, we develop a dataset using rule-based techniques on Farsi text, followed by a BERT-based ranking system to ensure fluency and comprehensibility. The resulting model demonstrates strong compatibility with existing QA systems, particularly those based on knowledge graphs. Notably, our system exhibits enhanced performance when integrated with large language models using Chain-of-Thought (CoT) prompting, leveraging detailed explanations rather than single-word answers. Our approach significantly improves response quality and coherence compared to baseline systems. We release our dataset to support further research in Farsi QA\footnote[1]{\href{https://huggingface.co/datasets/SLPL/syntran-fa}{https://huggingface.co/datasets/SLPL/syntran-fa}}.

Is the existence of populist sentiments linked to greater affective polarization? Is there a relationship between these two factors (populist sentiments and affective polarization) and the endorsement of far-right ideologies? Are there differences in the types of media prioritized by individuals with varying levels of affective polarization? This exploratory study, conducted in the context of the early legislative elections in Portugal in April 2024, analyzes data from a sample of 130 first-time young voters. It suggests an association between the defense of far-right arguments, the possession of populist sentiments, and levels of affective polarization. The study also found variations in affective polarization among young people who prioritized different types of social media to inform themselves on political issues.

Software Engineering education has grown during the past couple of decades as a specialized branch of computer science education to address employment demands. Software Engineering education is constantly evolving because of its dynamic nature. However, there are still some gaps between the skills being taught in the universities and skills required for employment. In this paper, we present our experience of designing and delivering a new module to enhance skills for employment. We have taken a structured approach to analyze the gap through literature review and our personal experiences of engaging with employers of our students. Based on the analysis, we arrived at a set of gaps between what we teach and what the employers of our students need. We prioritized the gaps and envisaged a new module ‘Contemporary Software Engineering’ to address the gaps and subsequently help our students for an easy transition to job. As part of our experience, we present the background, design and delivery of the module and reflect on our journey of delivering the module for a few years.

Big data-driven machine learning and artificial intelligence (ML/AI) is not all computational social sciences (CSS) have. Agent-based modeling (ABM) or multi-agent system (MAS) is another fundamentally different but equally useful approach in CSS. In fact, the two approaches start from very different orientations and their differences have deeper root in ontology. ML/AI aims to imitate and then surpass human capacities, from sensing to perceiving, reasoning, calculating, and acting. In contrast, ABM seeks to simulate how social outcomes emerge from the complex interactions of agents’ actions within a specific environment. Yet, precisely because these two technologies are different, they can be complementary to each other. There is a bright future for integrating ABM with ML/AI for tackling real world challenges.

Abstract Introduction: Despite the determination to succeed in eliminating neglected tropical diseases, these have been increasing within certain endemicities, particularly in depriving region. Objective: This study aimed to assess the relative burden of neglected tropical diseases in rural and urban slum settings in Eastern Ethiopia. Methods: A comparative cross-sectional study was conducted from February 25 to April 30, 2024 with a multistage random sampling technique used. A survey tool with the integration of the spectrum was employed. Data were entered using Epi-Data version 3.1 and analyzed using STATA 16. Descriptive statistics and multivariable logistic regression analysis was used to identify the risk factors and the level for statistical significance was declared at p-value < 0.05 with 95 % CI. Result: The response rate was 93 % and the mean age of house heads was 31.6 (Range; 18. 63) with 5.7 average family size. The overall prevalence of NTDs among study participants was 22.6 % (95% CI; 20.2, 25.2); urban slum it was 15 % (95% CI; 12.2, 18.4) while it was 29.8 % (95% CI; 26, 33.9) in rural. Though there is no statistically significant difference, the relative prevalence of NTDs in rural to urban was two. The multivariable analysis provided that the risk factors associated with NTDs were government employment (AOR: 12.5 (1.17, 132.4)), good income (AOR: 0.13 (.03, 0.57)), Child playing with soil (AOR: 5.8 (1.52, 22.0)); child hand washing at critical times ( AOR: 11.2 (1.7, 74.9)), presence of flies in the child faces (AOR: 20.3 (4.7, 88.6)) and type of drinking water sources (AOR: 0.11 (0.02, 0.73)). Conclusion: the burden of NTDs was moderate in the study area dominated by STH, Trachoma, and scabies. Socio economic and WASH factors were found to be associated with NTDs. Collaborated efforts among stakeholders are crucial to prevent and control NTDs.

In this work, we propose an alternative theoretical model to explain the accelerated expansion of the universe, based on the gravitational collapse of a black hole in a higher-dimensional space. We suggest that this collapse causes a rupture in the fabric of spacetime, generating a new universe whose accelerated expansion is a direct consequence of this process. Through detailed calculations, we demonstrate that the current acceleration of the universe is consistent with observational data, such as those from type Ia supernovae and the cosmic microwave background. Additionally, we address the problem of the universe's low initial entropy, proposing that this model provides a natural explanation for the order observed in its early stages. The results suggest that this alternative approach offers a viable explanation for cosmic expansion and raises new questions about the role of gravitational phenomena and the evolution of the universe.

The integration of omics technologies, including genomics, metabolomics, proteomics, and microbiomics, has transformed sports science, particularly in soccer, where these advancements have the potential to enhance player performance, injury prevention, and recovery. This review examines the role of single nucleotide polymorphisms (SNPs) across key genes influencing various physiological traits crucial for elite soccer players. Genes related to the cardiovascular system (ACE, AGT, NOS3, VEGF), muscle structure and function (ACTN3, CKM, MLCK), neurotransmission (ADRA2A, ADRB2, BDNF, DRD1, DBH), connective tissue integrity (COL1A1, COL2A1, COL5A1, ELN, EMILIN1, TNC), energy metabolism (AMPD1, MCT1, UCP1/2/3), oxidative stress response (GSTM1, GSTP, GSTT), hormonal regulation (CYP2D6, HSD17B14), and growth factors (GDF-8, IGF2, HGF) are all highlighted for their roles in influencing soccer-specific traits like endurance, speed, and injury risk. Furthermore, the incorporation of omics data allows for personalized strategies in training, nutrition, and recovery, tailoring interventions to each player's genetic and biochemical profile. For example, genomic markers such as ACE I/D and ACTN3 R577X are linked to key athletic traits like endurance and muscle injury susceptibility, while proteomics sheds light on muscle repair mechanisms, and metabolomics provides real-time insights into energy metabolism and fatigue markers. Microbiomics explores the role of gut health in recovery and overall performance, revealing correlations between microbial diversity and enhanced athletic outcomes. This comprehensive approach, referred to as Socceromics, offers a more holistic understanding of an athlete’s health and performance capabilities. Integrating these findings into real-world applications is essential for optimizing training regimens and reducing injury risk, ultimately pushing the boundaries of what athletes can achieve on the field. Future research should focus on expanding the scope of omics integration and improving the generalizability of findings across diverse populations and genders, thus advancing the field of precision sports medicine.

This paper aims to propose a stochastic linear parameter varying (LPV) model approach to design a state feedback controller for three-phase two-level inverters. To deal with the parameter changes, stochastic noise and delays faced by the inverter, it is modeled as a stochastic LPV system with time delay. The stability analysis and control synthesis are conducted for the LPV system. With parameter-dependent Lyapunov functionals, the sufficient stability condition for asymptotical mean-square stability is obtained. In addition, the slack matrix technique is employed to improve the feasibility and reduce the conservatism of the conditions. The obtained theoretical results are applied to the three-phase two-level inverter, whose currents are treated as state variables and controlled to reach the equilibrium point. The simulation results validate the effectiveness of the proposed theories and demonstrate the advantages of using the slack matrix.

Background and aims: The COVID-19 pandemic significantly impacted the mental health of healthcare professionals, especially those working in Psychosocial Care Centers (CAPS), which are crucial services in the Brazilian mental health system. This study aimed to analyze satisfaction and workload as predictive factors for psychological distress among CAPS professionals during the pandemic. Methods: A cross-sectional study was conducted with 53 professionals from seven CAPS. The Workload Impact Scale (IMPACTO-BR) and Job Satisfaction Scale (SATIS-BR), the General Health Questionnaire (GHQ-12), and a sociodemographic questionnaire were used. Descriptive and analytical statistical analyses were performed. Results: Professionals reported moderate satisfaction (3.67 ± 0.45) and mild workload (1.82 ± 0.63). One-third of the sample showed scores indicative of psychological distress. Logistic regression analysis revealed that workload (OR = 1.39, 95% CI = 0.0025) and low job satisfaction (OR = 1.23, 95% CI = 0.0495) were significant predictors of psychological distress. Conclusions: Low job satisfaction and high professional workload were predictive variables of psychological distress. These findings highlight the need for investments in promoting the quality of life at work for mental health professionals, especially during crises. The implications for human resource management and public policy development emphasize the importance of an integrated approach that considers the well-being of professionals for the effectiveness and sustainability of the psychosocial care model.

Generative adversarial networks consisting of two parts, generator and discriminator, have obtained acceptable results in classification, prediction and generation of new samples in the discussion of 4G, 5G and 6G. In this article, the aim is to review a comprehensive study in relation to these networks. At the beginning of this research, different topics such as network training, network error checking and types of GAN's are investigated. In the following, the applications of GAN will be discussed separately.

Explainability is essential for AI models, especially in clinical settings where understanding the model's decisions is crucial. Despite their impressive performance, black-box AI models are unsuitable for clinical use if their operations cannot be explained to clinicians. While deep neural networks (DNNs) represent the forefront of model performance, their explanations are often not easily interpretable by humans. On the other hand, using hand-crafted features extracted to represent different aspects of the input data and traditional machine learning models are generally more understandable. However, they often lack the effectiveness of advanced models due to human limitations in feature design. To address this, we propose ExShall-CNN, a novel explainable shallow convolutional neural network for medical image processing. This model enhances hand-crafted features to maintain human interpretability while achieving performance levels comparable to advanced deep convolutional networks, such as U-Net, for medical image segmentation. ExShall-CNN and its source code are publicly available at: https://github.com/MLBC-lab/ExShall-CNN

Developing cost-efficient systems for transporting CO2 is key to accelerate the deployment of carbon capture and storage. The present work explores the impact of reducing the pressure of tank-based inland and at-sea transport on their techno-economic performance. The study uses established techno-economic models for CO2 transport, adjusted with the most up-to-date knowledge on costs of low-pressure containment and transport. Particularly, the impact of cargo tank material and design on the transport costs shows that low-pressure cargo tank systems can be 50% less expensive than medium-pressure systems if materials with similar price and strength can be used. This results in reductions in transport costs as high as 30% for long distances. This is partly driven by the currently suggested size limitation on medium-pressure shipping which limits its economies of scale. If this limitation is alleviated, the cost advantage of low-pressure shipping compared to medium-pressure is more limited (10-20%) although it remains advantageous. The same scaling effects on capacity were not found for truck and barge inland transport, thus yielding 1-10% cost reductions of low- relative to medium-pressure transport. These results imply that future systems may combine medium-pressure inland and low-pressure at-sea transport, and that efficient solutions connecting the two must be investigated.

There are different audit methods for analysing operational facts and identifying deficiencies in business process management. However, financial data and transactions indirectly relate to physical objects and their attributes, resulting in distinct characteristics for their analysis and auditing methods. It is important to find new methods for finding a process extraction solution based on the financial audit data space to increase the efficiency of the auditors' work by reducing their time costs and increasing the possibility of detecting financial anomalies in large amounts of financial data. The research presents discussed different financial data space (FDS) methods, and process mining (PM) that include related classifications of financial data and external and internal factors that can influence data behavior (value changes) and the peculiarity of FDS is that it includes not only the characteristics of financial data but also other operational characteristics (events, environmental and internal changes, business location) that may be related to the change in financial objects (FO) values. The authors of the paper discuss the prototypes of specific elements in financial data analysis that were developed using the Process Mining software tool Disco and present the conclusions of the effectiveness of the financial processes cube defined to increase the analytical possibilities of the auditor's work with large amounts of data, introducing more flexible functionality for the analysis of financial activities.