Stability studies remain a crucial aspect of power systems dynamic analysis, and are typically explored in three main categories: numerical methods, linearization techniques, or direct methods, which utilize Lyapunov energy functions. This paper belongs to the third category, and highlights the usefulness of the Popov stability criterion in the analysis of nonlinear power system models. The main advantage of this criterion is that it provides conditions for global asymptotic stability of an equilibrium point, for a nonlinear dynamic system. We show a general method to apply this stability criterion, and examine its uses in several specific applications and case-studies. The results are demonstrated by analyzing the stability of a system that includes a grid-connected storage device and a renewable energy source.

A straightforward way to avoid the problem of the infinite zero-point energy principally is to negate the axiom of infinity of Zermelo-Fraenkel set theory. However, in so doing the real numbers and, as a corollary, the concept of infinitesimals would be given up making mathematical analysis, as it is known today, impossible. That said, consider a set whose members uniquely index points comprising a region of space. Providing four binary operations and their properties are defined on an index set, it is a field. The present paper demonstrates that to find the characteristic of an index field of the space of the observable universe is computationally intractable. Accordingly, such field cannot be distinguished from that of characteristic zero in any way possible. Meaning that one can negate the axiom of infinity and still use the real numbers inside the space of the observable universe for all intents and purposes.

This study aimed to determine the impact of garden-based learning on youth with intellectual disabilities (YwID). As it is not easy for YwID to collect information, experience situations, and make decisions independently, this study needed to devise an approach that could help the participants properly utilize the garden’s resources. Accordingly, it developed and operated a customized learning program for YwID and analyzed its impact. The findings show that gar-den-based learning generates specific changes in the knowledge, skills, and attitudes of YwID, such as emotional healing to recover psychological stability, social healing through social rela-tionships, physical healing through new activities, and independent healing through individu-alized plans. Participants experienced sympathizing with others and maintaining positive rela-tionships and obtaining knowledge, skills, and attitudes for behaving responsibly through gar-dening. Garden-based learning utilizing flowers and plants enhanced physical and mental health, improved functioning, helped YwID adapt to the environment, and integrated YwID into society. This is a form of vocational training by which people with disabilities could become employable by learning gardening skills, promoting their participation in society, and upgrading their quality of life. Hence, garden-based learning may transform people’s perception of disability and help people with disabilities respond to challenges.

Water mapping for satellite imagery has been an active research field for many applications, 1 in particular natural disaster such as flood. Synthetic Aperture Radar (SAR) provides high-resolution 2 imagery without constraint on weather conditions. Single-date SAR approach is less accurate than 3 multi-temporal but can produce results more promptly. This paper proposes novel segmentation 4 schemes that are designed to process both a target superpixel and its surrounding ones for the 5 input for machine learning. We devise MISP-SDT/XGB schemes to generate, annotate, and classify 6 superpixels, and perform land/water segmentation of SAR imagery. These schemes are applied to 7 Sentinel-1 SAR data to examine segmentation performances. Introducing single/mask/neighborhood 8 models in the MISP-SDT scheme and single/neighborhood models in the MISP-XGB, we assess the 9 effects of the contextual information about target and its neighbor superpixels on its segmentation 10 performances. As to polarization, it is shown that the VH mode produces more encouraging results 11 than the VV, which is consistent with previous studies. Also, under our MISP-SDT/XGP schemes 12 the neighborhood models show better performances than FCNN models. Overall, the neighborhood 13 model gives better performances than the single model. Results from attention maps and feature 14 importance scores show that neighbor regions are looked at or used by the algorithms in the neighbor- 15 hood models. Our findings suggest that under our schemes the contextual information has positive 16 effects on land/water segmentation.

Background/Objectives: The ongoing COVID-19 pandemic has underscored the need for alternative prophylactic measures, particularly for populations where vaccines may not be effective or accessible. This study aims to evaluate the efficacy of intranasally administered IgY antibodies derived from hen egg yolks as a protective agent against SARS-CoV-2 infection in Syrian golden hamsters, a well-established animal model for COVID-19. Methods: Hens were immunized with the spike protein of SARS-CoV-2 to generate IgY antibodies. These antibodies were extracted from the egg yolks, purified, and their neutralizing activity was tested in vitro. Syrian golden hamsters were then treated with the IgY antibodies before being challenged with SARS-CoV-2. Viral loads were quantified using droplet digital PCR (ddPCR), and lung pathology was assessed through histopathological analysis. Results: The in vitro assays showed that IgY effectively neutralized SARS-CoV-2. In the in vivo hamster model, IgY treatment led to a significant reduction in viral loads and a marked decrease in lung consolidation and inflammation compared to the positive control group. Histopathological findings further supported the protective role of IgY in reducing lung damage caused by SARS-CoV-2. Conclusions: The results demonstrate that IgY antibodies exhibit strong antiviral activity and can significantly reduce SARS-CoV-2 viral loads and associated lung pathology in hamsters. These findings suggest that IgY could be a viable prophylactic option for preventing SARS-CoV-2 infection, particularly for individuals who cannot receive or respond to vaccines. Further studies are warranted to optimize dosage and explore the long-term efficacy of IgY antibodies.

In this paper, I present a possible explanation for accelerated expansion of the universe, and introduce the cosmic scale, size of the universe and cosmic time, age of the universe. The observed expansion of the universe, which relates the stretching of Shrunk space to the new theory, is derived. This model is based on the two principal long-range forces: the gravitational force and the repulsive force generated by shrunk space. They are the two most basic fundamental quantities in the universe that govern cosmic evolution. They may provide the clockwork mechanism that operates our eternal cyclic universe. This model of Space-time and its unique properties of shrinking and stretching enables us to describe a sequence of events from the Big Bang to the Big Crunch.

This paper proposes a novel blockchain-based system designed to revolutionize transparency, traceability, and reliability within the organic food supply chain. Addressing persistent challenges such as certification fraud, opaque supply chains, and the high costs associated with organic food production, stakeholders including farmers, processors, distributors, retailers, and consumers stand to benefit from the system’s innovative approach. By leveraging blockchain technology and a robust system architecture, the proposed system offers enhanced transparency, improved traceability, and streamlined certification processes. Through detailed exploration of key components such as user interfaces, smart contracts, consensus mechanisms, IoT integration, and governance frameworks, the paper illustrates the practical application of blockchain technology in improving transparency and traceability throughout the food supply chain. A case study focusing on the organic Tofu supply chain further demonstrates the system’s potential to enhance sustainability, efficiency, and integrity in organic food production and distribution networks. The paper concludes by discussing potential implementation challenges and suggesting areas for future research and development to advance the impact of blockchain technology on the food supply chain.

Several environmental and economic issues have been brought about by mass accumulations of Sargassum along the coastlines in Trinidad and Tobago, and the wider Caribbean region. Though there are massive environmental issues associated with this seaweed biomass, there is also a chance to make innovations, thereby making this problem into a solution. The holopelagic species such as S. natans and S. fulitans have considerably high amounts of beneficial compounds which can be leveraged for agriculture. The value chain transformation of Sargassum from a nuisance to a resource for agricultural production is narrated in the following report. Details of the application of products from Sargassum including composts, soil amendments, and liquid biostimulants are given. A case study is presented for OJA1 biostimulant, which was developed from Sargassum biomass at the University of the West Indies, St. Augustine, Trinidad. This biostimulant has shown increased productivity and resistance to diseases of several cash crops. The valorization of Sargassum contributes to sustainable agriculture and propels economic development in coastal communities. The Caribbean could lead with the adoption of the circular economy, turning environmental adversity into a lever for sustainable development.

The drug discovery process is a complex and time-consuming endeavor that can greatly benefit from advancements in computational biology. This study explores the implementation of GPU-accelerated computational methods to enhance molecular docking simulations and virtual screening techniques, two crucial components of drug discovery. By leveraging the parallel processing capabilities of Graphics Processing Units (GPUs), we significantly accelerate the analysis of protein-ligand interactions and the identification of potential lead compounds. Our approach utilizes optimized algorithms and software frameworks to achieve substantial speedups over traditional CPU-based methods. Results demonstrate that GPU-accelerated molecular docking simulations and virtual screening can reduce computation times by up to 10-fold, enabling rapid and accurate identification of promising drug candidates. This accelerated workflow has the potential to revolutionize the drug discovery pipeline, facilitating the development of novel therapeutics and reducing the time and cost associated with bringing new treatments to market.

The SPEcies-At-Risk index for metals (SPEARmetal) was refined using updated physiological sensitivity data and validated to assess the ecological impact of metal contamination on benthic macroinvertebrate communities in the upper Nakdong River, near a Zn smelter in Korea. Biosurvey and chemical monitoring were collected at 18 sites surrounding the smelter and nearby mines. Acute ecotoxicity tests on 20 indigenous species from the Korean peninsula were conducted and used to update taxon-specific metal sensitivity data. The refined SPEARmetal index, based on this updated sensitivity, was significantly lower than previous versions, with most values below the severe impact threshold (0.5) in the mainstream. The correlation between hazard quotients in water and the SPEAR index improved, with the correlation coefficient increasing from 0.63 to 0.70. Despite consistently high benthic macroinvertebrate indices (BMI) across the study area, generic ecological indices such as total richness, EPT (Ephemeroptera, Plecoptera, Trichoptera), and Shannon diversity showed correlations with metal contamination levels. Principal component analysis identified SPEARmetal as the primary indicator associated with metal contamination in both water and sediment. These findings highlight the improved performance of the refined SPEARmetal index as a more sensitive and specific tool for assessing the ecological status of metal-impacted aquatic ecosystems compared to traditional indices.

This paper presents a novel method for evaluating the accuracy of orientation sensors commonly used in practical applications, utilizing measurements obtained from a commercial robotic manipulator as the reference instrumentation. The core concept of the method involves determining the rotational transformations between the robot's base frame and the sensor frame, as well as between the TCP (Tool Center Point) frame and the sensor frame, without requiring precise alignment. These transformations are assumed to be arbitrarily chosen, allowing the computation to rely solely on the logged TCP orientations and synchronized sensor measurements. The proposed approach enables systematic testing and evaluation of orientation sensing devices without necessitating exact measurement of the rotations between the sensor frame and the reference instrumentation. The method's effectiveness is demonstrated through the evaluation of an Inertial Navigation System module and the SLAM-IMU fusion capabilities of the HTC VIVE headset.

Addressing the issue of compromised performance and stability in distributed drive electric vehicles during high-speed operation in the event of motor failure. A fault-tolerant control strategy for distributed drive electric vehicles is proposed, based on Model Reference Adaptive Control (MRAC). First, a seven-degree-of-freedom vehicle dynamics reference model is established, from which the output torque of each wheel during stable operation is determined. Secondly, based on the compensation principle that maintains constant longitudinal speed and total torque before and after the fault, the output torque of the remaining wheels is determined to ensure normal vehicle operation in the event of a single motor failure. To improve torque distribution accuracy, an MRAC controller that takes into account the output hysteresis of the motor is designed. The transfer functions of both the reference model and the actual model are derived. Using Lyapunov's second method, the adaptation rate of the MRAC system is formulated, ensuring that the state of the actual model converges to that of the reference model, thereby achieving adaptive regulation of system parameters and global stability. Finally, simulation experiments are conducted under high-speed dual-lane conditions. The results indicate that, in the case of a single motor failure with constant vehicle speed, the yaw rate and lateral displacement of the vehicle's center of mass decrease, thereby validating the effectiveness of the proposed fault-tolerant control strategy.

If we assume that: a. The four fundamental forces of nature are independent waves without rest mass, and their speeds are constant in a vacuum, just like light. b. Light or electromagnetic waves and gravity are comparable in structure. The weak and strong interials are similar in structure. c. Light and the weak interaction have the same speed c_L with spin number +1 or -1. d. Gravity and the strong interaction have the same speed c_G without spin. e. The primary particles, namely electrons (or positrons), electron neutrinos, and dark neutrinos in this paper, are made of the above four waves. We can find and describe some fundamental characteristics of the primary particles (e.g., their sizes, energies, and interactions) and introduce new attractive results from them (e.g., the source of the Pauli exclusion principle, the solution of the Einstein-Podolsky-Rosen paradox, and c_G slightly faster than c_L).

Accurate exchange rate prediction is fundamental to financial stability and international trade, positioning it as a critical focus in economic and financial research. Traditional forecasting models often falter when addressing the inherent complexities and non-linearities of exchange rate data. This study explores the application of advanced deep learning models, including LSTM, CNN, and transformer-based architectures, to enhance the predictive accuracy of the RMB/USD exchange rate. Utilizing 40 features across 6 categories, the analysis identifies TSMixer as the most effective model for this task. A rigorous feature selection process emphasizes the inclusion of key economic indicators, such as China-U.S. trade volumes and exchange rates of other major currencies like the euro-RMB and yen-dollar pairs. The integration of grad-CAM visualization techniques further enhances model interpretability, allowing for clearer identification of the most influential features and bolstering the credibility of the predictions. These findings underscore the pivotal role of fundamental economic data in exchange rate forecasting and highlight the substantial potential of machine learning models to deliver more accurate and reliable predictions, thereby serving as a valuable tool for financial analysis and decision-making.

Enterprise Architecture (EA) development with an Agile approach is believed to be an alternative solution to various current EA development challenges. Agile Enterprise Architecture (EA) is an EA development that applies Agile principles and focuses on collaborative and incremental de-velopment, adaptation, and sharing information about business and IT modes to guide the ef-fective implementation of Agile projects. There have been many discussions of literature related to EA management, but literature review studies that specifically describe Adaptive or Agile EA management are still rare. The research method of this study follows two consecutive phases: bibliometric analysis and content based analysis. First, bibliometric analysis utilizing the VOSviewer software to identify the state of the field and global research patterns in Agile EA from 2012 to 2023, including author and institutional distributions, frequent categories and keywords, contributions from journals and authors, and highly cited works. Next, thematic analysis and meta-analysis to reveal various frameworks or models used in agile EA implementation and its dimensions. The extracted bibliometric and content data from 59 selected articles were processed using the VOSviewer tool for identifying and understanding the relationships between main concepts through network mapping. There are several Agile-based EA frameworks based on empirical research found in EA development, such as Adaptive Enterpise Architecture, Adaptive Integrated Digital Architecture Framework (AIDAF), Lean Enterprise Architecture Frameowrk (LEAF), Scrum for EA, and several other Agile EA frameworks developed that have been ob-served. Various agile methods have been adopted in developing the agile EA framework, in-cluding its application in various industrial sectors in several countries, the risks faced and future research opportunities to increase the effectiveness of agile EA implementation in Digital Transformation.

Two gravel pit lakes in central Texas were examined over the course of two years with upgradient and downgradient piezometer installations. Groundwater and lake water were sampled bimonthly for nutrients, water levels, and groundwater chemistry, in addition, rain and lake gauges and mini-piezometers were installed, depth surveys were conducted, and a simple 2-D flow model was constructed. The project goal was evaluating and examining flow dynamics and chemical effects as groundwater flows to surface water and back to groundwater with the intent to understand the effects that gravel pit lake systems have on connected shallow groundwater. Both lake systems were shown to be flow-through systems that influence the water quality by decreasing the dissolved nutrients in the groundwater in their vicinity while oxygenating the water and altering the pH. However, the lakes are also prone to high levels of evaporation, rendering minor improvements to water quality at the cost of decreasing the quantity of water in storage within the aquifer. Similar groundwater and mine lake systems may show comparable tendencies, providing new information for water managers, regulators, and stake holders about the potential roles that non-remediated gravel pit lakes may play in local ecosystems and aquifer dynamics.

In the present paper, a numerical analysis of the performance of microchannels featuring rectangular, trapezoidal, and double-trapezoidal cross-sections is presented. The fully developed laminar forced convection of a Newtonian fluid with constant properties is considered. The non-dimensional forms of governing equations are solved by setting slip velocity and uniform heat flux as boundary conditions. Model accuracy was established using the available scientific literature. The numerical results indicate that viscous dissipation effects led to a decrease in the average Nusselt number across all microchannels examined in this study. The degree of reduction is influenced by the cross-section, aspect ratio and Knudsen number. The lowest average Nusselt number values were observed under continuum flow conditions for all the microchannels investigated.

The rise in popularity of online social networks has led a large number of users to share a substantial amount of personal information on these platforms. This trend has caused privacy issues and security concerns among the users since the increased availability of personal data online increases the risk of unauthorized access, identity theft, and misuse of information. In response to these concerns, the ephemeral and anonymous online social networks have emerged in recent years. Platforms like Snapchat, Signal and WhatsApp have enabled a disappearing message setting allowing users to view and share content online for a limited period of time, before its self-destruction. The shift towards ephemeral social networks marks a new development in social media usage. Despite introducing this new dynamic to social media, various issues such as data breaches, cyber-bullying, and misinformation persist and continue to affect both conventional and upcoming social networks adversely. In an attempt to study online social networks from an ephemerality perspective, this study, spanning a period of ten years, employs a survey based approach to compare and analyze the usage patterns of users on conventional and ephemeral social networks over the period of ten years, and seeks to determine the factors affecting the usage and eventual likelihood of users migrating from conventional online social networks to ephemeral social networking platforms.

This study describes the first successful rearing of capelin from hatch to adulthood in a laboratory setting using intensive culture methods. Over the span of about two years the capelin were reared in aquaculture tanks under a constant temperature of 7°C. The capelin demonstrated a robust linear growth during their first year of life, with a mean length increment of 0.36 mm per day. Due to their accelerated growth, some of the capelin became sexually mature as early as one-year post hatch. The first year was characterized by a rapid increase in condition factor (CF) while the second year showed a plateau. The von Bertalanffy growth equation effectively described the two-year growth of the cultivated capelin, predicting an asymptotic length (L∞) of 18.4 cm, similar to the 18.6 cm median L∞ of wild Icelandic capelin (1981–2018 cohorts). The cultivated capelin were projected to reach this length in 2.6 years, compared to about 6 years for wild capelin. This study provides new insights into the growth dynamics of capelin, and although the species is sensitive to handling, it demonstrates that intensive culture methods can be used to investigate biological aspects of this important forage species.

Increased inflammation and heightened physiological stress reactivity have been associated with pathophysiology of depressive symptoms. The underlying biological mechanisms by which inflammation and stress can affect neurogenesis is through alterations of the kynurenine (KYN) pathway, which is activated under stress. Meanwhile, n-3 polyunsaturated fatty acids (n-3 PUFA) supplementation has anti-inflammatory properties and may enhance stress resilience. Whether n-3 PUFA alters stress responsivity KYN is unknown. This placebo-controlled trial examined the effect of n-3 PUFA on KYN metabolism, inflammation, depressive symptoms and mood; and stress-induced changes following a laboratory stressor. Using a placebo-controlled design, 47 healthy male adults were received 4g/d of Omega-3, or a placebo for 12 weeks. A significant group-by-time interaction was found for inflammation markers - gp130 (F= 7.07, p = 0.011), IL-6R alpha (F= 10.33, p = 0.003), and TNF_RI (F= 10.92, p = 0.002). No significant group-by-time interactions were found for mood or depressive symptoms, except for Hedonic Tone (F= 6.50, p = 0.014), neither for KYN metabolites and stress-induced changes to the KYN metabolites and mood following a laboratory stressor. Overall, elevating n-3 PUFAs levels in healthy males ameliorates inflammatory markers but does not ameliorate KYN metabolism, depressive symptoms, mood, or stress responsivity KYN metabolism and mood. The study was registered at ClinicalTrials.gov with identifier NCT05520437 (30/08/2022 first trial registration).

Globally, the transport sector is a major contributor to air pollution. Currently in the UK, vehicle emissions contribute significant amounts of nitrogen oxide (NOx) and particulate matter (PM) pollution in urban areas. Low-emission zones policies have been used as an intervention to tackle air pollution, and in this context, the UK launched the Low- Traffic Neighbourhood scheme. This study investigates the impacts of the Low- Traffic Neighbourhood in Kings Heath, Birmingham, UK, to evaluate its impact in reducing air pollution and local community perspectives about the scheme and perceived impacts on health and well-being. The study employs a mixed-method ap-proach comprising air quality monitoring assessment and a survey questionnaire involving 210 residents. The findings reveal an increase in active travel and a reduction in air pollution levels in the years after the implementation of the scheme, although the area is still non-compliant with the 2021 WHO air quality guidelines. Nonetheless, the scheme has a polarizing effect and created a division within the local community about the overall scheme acceptance and spatial distribution of the scheme’s benefits. The study underscores the importance of comprehensive baseline data, long-term community engagement, and integration with broader urban planning initiatives to enhance the success of future Low-Neighbourhood Traffic schemes.

Metastasis in oncological diseases remains one of the main reasons for negative prognosis regarding treatment. Any new data on the biophysical and biochemical characteristics of circulating metastatic cells will help to develop the concept of antimetastatic therapy. In this study we found a number of differences in spectroscopic and morphological features of circulating metastatic cells. FTIR and Raman spectra of cultivated by adhesive and de-adhesive methods (last as a model for metastatic cells) have showed spectroscopic features, namely in FTIR in the region of CH - stretching vibrations associated with structural rearrangements in the cell membrane, as well as changes in the intensity and position of the PO2- group vibrations bands correlated with a proliferative activity. The spectral features in the regions of OH stretching and Amid I vibrations and other spectral markers of the metastatic cells under different cultivation conditions were derived. Raman spectra showed redistribution of amino acid Tyr/Trp ratio and in Tyr duplet intensity in the region of 500-900 cm-1 , as well different glycogen level in different cells. The spectroscopic markers are in the accordance with biochemical data. CARS and confocal optical microscopy were applied for determination a state of the cells and F-actin expression level that turned out to be higher for adhesive cells in comparison with de-adhesive cells. Shape and morphological property of the cells drastically differs. The correlation of vibrational markers with biochemical data and cytofluorometric method were discussed.

Silicone mammary implants (SMIs) frequently result in capsular fibrosis, which is marked by the overproduction of fibrous tissue surrounding the implant. This review provides a detailed examination of the molecular and immunological mechanisms driving capsular fibrosis, focusing on the role of foreign body responses (FBR) and microbial biofilm formation. We investigate how microbial adhesion to implant surfaces and biofilm development contribute to persistent inflammation and fibrotic responses. The review critically evaluates antimicrobial strategies, including preoperative antiseptic protocols and antimicrobial-impregnated materials, designed to mitigate infection and biofilm-related complications. Additionally, advancements in material science, such as surface modifications and antibiotic-impregnated meshes, are discussed for their potential to reduce capsular fibrosis and prevent contracture of the capsule. By integrating molecular insights with clinical applications, this review aims to elucidate the current understanding of SMI-related fibrotic responses and highlight knowledge gaps. The synthesis of these findings aims to guide future research directions of improved antimicrobial interventions and implant materials, ultimately advancing the management of capsular fibrosis and enhancing patient outcomes.

We present a new quadratic transformation identity for the confluent Heun function. This transformation is independent of the previously discovered quadratic transformation (Heliyon 10, e36535, 2024) and offers additional insights into the properties of this special function. Like the first transformation, this new identity involves two arbitrary parameters and has potential applications in both mathematical and physical contexts, particularly in quantum mechanics.

Background: Choline is an essential nutrient required for proper cell functioning. Due to its status as a precursor to acetylcholine, an important neurotransmitter connected to cognition and neuromuscular function, maintaining or enhancing choline levels is of interest. Supplementation with alpha-glycerylphosphorycholine (A-GPC) can maintain choline levels, but its ability to offer support towards cognition remains an area of ongoing research. Methods: Using a randomized, double-blind, placebo-controlled, crossover approach, 20 resistance-trained males (31.3 ± 11.0 years, 178.6 ± 7.3 cm, 84.6 ± 11.4 kg, 15.4 ± 5.6 % fat) consumed either a placebo (PL), 630 mg A-GPC (HD), or 315 mg (LD) A-GPC (GeniusPure™, NNB Nutrition). After resting hemodynamic assessments, participants took their assigned dose and had cognitive assessments (Stroop, N-Back, and Flanker), visual analog scales, and hemodynamics evaluated 60 minutes after ingestion. All participants then warmed-up and completed vertical jumps and bench press throws before completing a bout of lower-body resistance exercise (6 x 10 repetitions using the Smith squat at a load of 70% 1RM). Venous blood was collected 5, 15, 30, and 60 minutes after completion of the squat protocol to evaluate changes in growth hormone and follow-up visual analog scales and cognitive measurements were evaluated 30 minutes after completing the exercise bout. Results: When compared to PL, changes in Stroop total score were statistically greater after HD (13.0 ± 8.2 vs. 5.2 ± 9.0, p = 0.013, d = 0.61) and LD (10.8 ± 7.7 vs. 5.2 ± 9.0, p = 0.046, d = 0.48) administration in addition to significantly faster times in completing the Stroop test in the HD group when compared to PL (-0.12 ± 0.09s vs. -0.05 ± 0.09s, p = 0.021, d = 0.56). No significant differences between groups were found for the Flanker and N-Back assessments while a tendency was observed for HD to have faster reaction times when compared to PL during the Flanker test. No groups differences were realized for visual analog scales, physical performance, or growth hormone. Statistically significant changes in heart rate and blood pressure were observed in all groups, with all recorded values aligning within clinically accepted normative values. Conclusions: HD and LD A-GPC supplementation significantly increased cognitive performance in a group of young, healthy males as measured by changes in the Stroop Total Score and completion time of the Stroop test. These results extend the previously published research which indicated that A-GPC can augment cognition in clinical populations to healthy individuals undergoing acute exercise stress.

New asphalt mixtures have been improved by using fibers (polypropylene, polyester, asbestos, carbon, glass, nylon, lignin, coconut, sisal, recycled rubber, PET, wood, bamboo and cellulose), reducing the temperature and compaction energy for their collocation, minimizing the impact on the environment, increasing the tenacity and resistance to cracking of hot mix asphalt (HMA), preventing asphalt drainage in a Stone Mastic Asphalt (SMA). Hence, this paper aims to evaluate the influence of the chemical (lignin content, ash, viscosity, degree of polymerization and elemental analysis), morphological (SEM), spectroscopic (FTIR-ATR and XRD) and calorimetric (ATG and DSC) properties of celluloses from bagasse Agave tequilana Weber var. Azul (ABP), corrugated paperboard (CPB) and commercial cellulose fiber (CC) as Schellenberg drainage (D) inhibitors of the SMA. The ABP was obtained through a chemical process by alkaline cooking, while CPB by a mechanical refining process. The chemical, morphological, spectroscopic and calorimetric properties were similar among the analyzed celluloses, but CPB and ABP cellulose are excellent alternatives to CC cellulose for inhibiting drainage. However, CPB is the most effective at low concentrations. This is attributed to its morphology, which includes roughness, waviness, filament length, orientation and diameter, as well as its lignin content and crystallinity.

In the present work, vertically aligned ultrathin 2D In2S3 nanosheets are grown with a chemical vapor deposition technique to enhance the photoresponse by increasing surface area, and optical absorption. The 2D vertically aligned In2S3 nanosheets have shown excellent PEC water-splitting in terms of excellent photocurrent density value of 4.5 mAcm-2, incident photon to current conversion efficiency is 53 % and hydrogen production of 90% has been achieved in the visible region with higher stability. Ultrathin vertically aligned In2S3 nanosheets also show high responsivity, high charge carrier density, lesser recombination rate, and a capacious space charge layer for excellent water-splitting performance. This straightforward method of creating ultrathin 2D nanosheets of In2S3 also has significant potential for other fields where effective absorption and charge separations are required, like photodetection, optical electronics, and gas sensing.

Chronic wounds have a significant impact on patients' quality of life, necessitating the management of pain, infection, bleeding, and emotional challenges. Debridement, which involves the removal of nonviable tissue, is crucial for promoting wound healing. In addition to surgical methods, cost-effective alternatives such as local solutions and ointments with biological properties have been explored. The use of natural compounds with anti-inflammatory, antibacterial, and collagen-synthesizing abilities holds promise for wound healing. This study aimed to assess the safety and effectiveness of a wound-healing ointment containing bioactive ingredients derived from medicinal plants (extracts, essential oils, and vegetable oils). Pre-clinical tests were conducted following standardized protocols. The chemical composition of the ointment was characterized using Fourier transform infrared (FTIR) spectroscopy to gain insights into its synergistic action. FTIR analysis revealed similarities between the product's spectrum and that of bioactive compounds. The in vitro tests demonstrated that all formulations of the ointment induced no cell death, DNA damage, or acute toxicity in cell cultures. No lethal dose was observed, indicating the safety of the ointment at all concentrations. In vivo preclinical analyses demonstrated no adverse responses being effective in the healing process, similar to the gold standard (Silver Sulfadiazine). The regenerative ointment displayed excellent biocompatibility and bioactivity in vitro and in vivo studies, contributing to the development of innovative and sustainable wound management therapies.

This study presents an eco-epidemiological model exploring a prey population infected by two distinct pathogen strains in the presence of an unaffected predator population. The model investigates how prey herding behavior provides protection against predation under multi-strain infections. A well-posedness and boundedness analysis of the populations ensures the robustness of the model. Linear stability analysis reveals that, under specific herd shapes and predator mortality rates, prey infected with either strain can vanish. Bifurcation analysis uncovers critical dynamics: a supercritical Hopf bifurcation occurs at a threshold prey herd shape (k), indicating the onset of stable oscillatory population cycles. As predator mortality (δ) varies, both subcritical and supercritical Hopf bifurcations emerge, marking shifts between stable and unstable dynamics, potentially leading to prey extinction or sharp population collapses. The analysis further identifies a Generalized Hopf bifurcation, distinguishing between predictable cycles and more complex. Numerical simulations confirm these findings, offering insights into predator-prey dynamics in ecosystems subject to multi-strain infections. The results have potential implications for understanding disease control, population stability, and ecological resilience.

The study presents the conceptual development and simulation of a robotic exoskeleton for ankle rehabilitation. The device is designed for ankle rehabilitation in patients with musculoskeletal disorders, injuries, or neurological diseases. The exoskeleton is equipped with three linear electric actuators that provide precise control of joint movements in multiple planes, allowing dorsiflexion and plantar flexion, inversion, and eversion. By utilizing a screw drive, the exoskeleton provides smooth and controlled movements, significantly reducing the risk of re-injury and improving rehabilitation. Simulation of the device and simulation results showed its high compatibility with the biomechanical features of the ankle joint. Virtual testing confirmed that the exoskeleton provides the smooth, controlled movements necessary for effective rehabilitation. Due to its ability to adapt to the individual physical capabilities of the patient, the device can be used in both active and passive forms of movement support. The results of the study demonstrate the potential of the exoskeleton in clinical applications, including its use in rehabilitation centers and at home. Its cost-effectiveness, ease of use, and high accuracy of movement control make this device a promising solution for restoring the functions of the lower extremities in patients with various musculoskeletal disorders.

Molecular cages have promising host-guest properties for drug delivery applications. Specifically, guest⊂cage complexes can be used for on-command release of encapsulated guest molecules in response to specific stimuli. This research explores both dynamic and constrictive binding guest⊂cage systems for drug encapsulation and release in biological environments. In dynamic systems, the guest rapidly passes in and out through the portals of the cage, enabling drug delivery in vitro but facing limitations in vivo due to dilution effects that result in guest release. These challenges are addressed by constrictive binding systems, where the guest is trapped in a "gate-closed" state within the cage. In these systems, the on-command release is triggered by a "gate opening" event, which lowers the guest-out energy barrier. The full guest release is achieved when gate opening reduces the cage-guest affinity, making constrictive binding systems more effective for controlled drug delivery. As a result, this study shows that guest⊂cage complexes have suitable properties for drug delivery in biological contexts.

Future manned and deep space missions require an Electrical Power System (EPS) that can deliver high power while overcoming challenges like weight and volume constraints and the harsh environment of space. To supply, store, and transmit power to various satellite subsystems, a variety of DC-DC converters are employed. The design specifications of DC-DC converters for various satellite applications are identified in this article, which also offers a state-of-the-art review of non-isolated, isolated, and integrated topologies. Foreseeing the future of electric propulsion, various electric sources for electric propulsion are contrasted, and converters for electric propulsion are studied. The chosen topologies are compared in terms of practical parameters like reliability, modularity, redundancy, efficiency, and power density. Application-wise comparisons of the topologies are also presented, along with details on how well they work with different kinds of satellites. The article also identifies the areas that are still unexplored for each application. In view of the identified research gaps, a generalized Modular Isolated Interleaved topology of a DC-DC converter is proposed for satellite applications, which is one of the articles’ unique contributions. The MATLAB simulation results of the proposed method, taking Cuk converter as an example for a total power of 5kW are presented. Findings indicate that adding more modules improves the system’s overall reliability, efficiency, and power density by lowering losses, semiconductor current stress, and component size. Such designs are easily adaptable to satellite applications, particularly at high power levels.

Hypertrophic cardiomyopathy (HCM) is a common form of cardiomyopathy in cats, and heart failure occurs as diastolic dysfunction progresses. HCM in cats is broadly classified as non-obstructive and obstructive hypertrophic cardiomyopathy, depending on the presence or absence of outflow tract obstruction. Measurement of the intraventricular pressure differences (IVPD) using Color M-mode (CMM) has attracted attention as a reliable diastolic index as it correlates with catheterization, the gold standard for assessment of diastolic performance. Since, IVPD is affected by the size of the heart, the intraventricular pressure gradient (IVPG) index, which is unaffected by heart size, is used by dividing IVPD be LV length. In the present study, CMM IVPG was used to non-invasively assess diastolic impairment in cats with obstructive hypertrophic cardiomyopathy. This study was conducted on ten control cats and 18 cats in the HCM group. Although no severe left atrial enlargement was observed in the HCM group, the Basal IVPG was significantly increased in the HOCM group compared to the control group. While IVPD typically suggests impaired diastolic function and reduced ventricular compliance, the significant increase observed in the HOCM group compared to controls may suggest an indirect elevation in left atrial pressure, likely secondary to left ventricular outflow tract obstruction. The increase in IVPG in HOCM, as shown in this study, is a pathological effect of left ventricular outflow tract obstruction that cannot be detected by conventional echocardiographic indices, and evaluating IVPG is useful for evaluating cardiac function from a different perspective than conventional methods.

The effective removal of impurities from natural quartz is a very challenging subject, but there is no relevant study on the mesoscopic structure of quartz sand particles, and there is still a lack of direct evidence on the structure-activity relationship between mesoscopic structure and purification effect. In this paper, the effects of calcination temperature, calcination time, quenching frequency and grinding frequency on the formation of mesoscopic fractures in natural quartz sand were studied, and a linear regression model was established by fractal and differential methods. The results show that the cracked structure of quartz sand and its variation law have remarkable fractal characteristics, and thermal expansion and phase transformation are the main factors affecting the cracked structure and specific surface area of quartz sand. The non-phase change thermal expansion results in the formation of semi-closed wedge-shaped fractures in the open fractures of quartz sand, resulting in a significant decrease in the specific surface area of the cracked sand. On the contrary, the phase change expansion is conducive to the generation of more Me10 mesoporous fractures and the increase of the specific surface area of cracked sand. In addition, thermal stress and mechanical force are more likely to form Me50 and Me10 mesoporous cracks, where the average proportion of Me50 is higher than 75%. Based on this, the linear regression model between the fractal dimension and the pore volume distribution, SBET is further established, and the correlation coefficient R2 is mostly above 96%. In addition to offering insightful findings for the investigation of the structure-activity relationship between the purification effect and the mesoscopic structure of quartz sand, this also establishes the groundwork for the advancement of high purification technology for natural quartz sand.

The main purpose of this paper is to review systematically both theoretical and empirical literature about the relationship between corporate governance variables and the performance of microfinance institutions. The theoretical reviews were: agency theory stakeholders’ theory, resource dependency theory, stewardship theory, and social contract theory which deal with corporate governance mechanism and their effect on the performance of the firm. Empirical studies carried out in different countries at different times together with different findings were reviewed to compare the effect of corporate governance mechanisms on the performance of microfinance institutions and to establish areas of gaps for further studies. Board characteristics which include size, education, meeting frequency, board composition, and board independence, and their effect on the financial performance of microfinance institutions were discussed. The findings of different scholars show a lack of consistency on the effect of corporate governance variables on the financial performance of Microfinance Institutions so further investigation is required from potential scholars. Finally, theoretical, measurement and methodological drawbacks of previous studies were identified, and significant recommendations were forwarded for future studies in this area.

This study proposes a new maximum power point tracking (MPPT) method based on machine learning with improved power production efficiency for application to photovoltaic (PV) systems. Power loss occurs in the incremental conductance (InC) method, depending on the size of the voltage step used to track the maximum power point. Additionally, the size of the voltage step must be specified by the initial user; however, an appropriate size cannot be determined in a rapidly changing environment. To solve this problem, this study presents a gradient descent InC (GD InC) method that optimizes the size of the voltage step by applying an optimization method based on machine learning. The effectiveness of the GD InC method was verified and the optimized size of the voltage step was confirmed to produce the largest amount of power. When the size of the voltage step was optimized, a maximum difference of 4.53% was observed compared to case when the smallest amount of power was produced. The effectiveness of the GD InC method, which improved the efficiency of power production by optimizing the size of the voltage step, was verified. Power can be produced efficiently by applying the GD InC method to PV systems.

For the past 20 years, reintroduction efforts have been underway to reestablish a migratory population of Northern Bald Ibises (Geronticus eremita) in Central Europe, which now consists of more than 250 birds. They breed both north and south of the Alps and migrate to a common wintering ground in Tuscany. Recently, the start of autumn migration is increasingly delayed, which correlates with extended warm periods in autumn. Later in the year, however, the birds no longer find sufficient thermals to cross the Alps and remain in the northern Alpine foothills. In order to save their lives, we had to capture the affected birds before onset of winter, which is not a sustainable solution. A new approach to solving the problem is the establishment of a second migration route to a wintering area in Andalusia, Spain, connecting our population with a sedentary population there. The new migration route bypasses mountain barriers and allows the birds to reach the wintering grounds also later in the year. The modelling of a pan-European population will provide the birds with high ecological and spatial flexibility. Our project exemplifies the consequences of advancing global warming for animal populations and the associated challenges for conservation projects.

In response to the growing environmental concerns and sustainability imperatives in the (GCC) and the world in general, companies are increasingly being urged to integrate environmental accountability into their core strategies and operations by accounting for environmental performance in their financial statements and the impact on supply chains and sustainable development. The problem of the study is to identify the impact of environmental accounting disclosure challenges on supply chains and sustainable development in companies. By taking the experiments of 20 companies and representatives of the study community interested in the topic, and using the heuristic research approach through the questionnaire tool and a set of key variables, including the adoption of disclosure on environmental accounting performance (DEAP), supply chain sustainability performance(SP), Sustainable Development Index(SD), and using the (PLS) program, in the statistical analysis, the study reached the most important results: The study revealed a positive relationship between the disclosure of environmental accounting performance, improved supply chains and sustainable development in the companies represented by the study sample in the (GCC), where both financial performance and environmental performance contribute to achieving the Sustainable Development Goals and supply chains. Accordingly, the study recommends many recommendations, the most important of which are: the need for companies to be encouraged to disclose the performance of environmental accounting as a strategic necessity, promote more sustainable supply chain management, improve financial performance, and effectively contribute to achieving the Sustainable Development Goals, thereby enhancing sustainability within companies and across supply chains, the study also recommends the need to continue studies in this aspect, especially in the (GCC) and East Asian countries, to urge companies to disclose the performance of environmental accounting in their financial statements.

This paper provides an overview of the social reasons that lead women to consider egg cryopreservation, as well as the attitudes and knowledge of women towards this procedure. Methods: For the creation of this article, a literature review was carried out both in the existing medical literature and in search engines. The key points are 1. The main reasons women choose to delay childbearing are the lack of a suitable male partner, education and career advancement, and financial instability. Women feel societal and family pressure to have children, even though they may not feel ready. 2. Women's attitudes towards egg cryopreservation vary. While some are open to the idea, many are opposed to it, especially when it is used for non-medical reasons. There are concerns about the success rates, health risks, and ethical implications of the procedure. 3. The legal and regulatory framework around egg cryopreservation differs across countries. Some countries allow it only for medical reasons, while others have more permissive policies. The issue of who should bear the financial cost of the procedure is also debated. 4. There is a need to better educate women, as well as healthcare providers, about fertility decline and the options available for preserving fertility, including egg cryopreservation.

The aim of the study was to analyze the association between single nucleotide polymorphism (SNP) rs80860411A>C located in the intergenic region of chromosome 13 (near the GALNT15 gene encoding Polypeptide N-Acetylgalactosaminyltransferase15, GALNTL2) and fat-tening and slaughter traits of pigs. The study was conducted on 426 individuals belonging to three breeds: Polish Landrace (n = 192), Polish Large White (n = 187) and Pulawska (n = 48). The rs80860411 genotypes were determined using the PCR-RFLP method. Association analysis was performed for each breed separately, as well as for the entire study group. The study showed that rs80860411A>C had a significant effect on fattening performance traits, as well as on several slaughter performance traits, including: width of the loin eye, loin and ham weights without skin and backfat and carcass meat content (P ≤ 0.01, P ≤ 0.05). The obtained results indicate that the studied SNP has the potential to be included in pig selection programs, thus potentially influencing the improvement of fat-tening and slaughter traits of different pig breeds.

This study examines the evolution and eventual decline of the spirit of primitive federalism within Confucianism, tracing its trajectory from the time of the Duke of Zhou and Confucius to the significant reinterpretations by Dong Zhongshu. The Duke of Zhou's establishment of a confederation-like system (fengjian) and the "Zhou ritual norms" laid the groundwork for a political structure that embraced diversity and distributed power among vassal states, reflecting a proto-federalist concept. Confucius's teachings continued this legacy, advocating for a return to the balanced systems of the Duke's era, where both the central government and local states shared responsibilities and rights. Transformation happened under Emperor Wu of Han, where Dong Zhongshu re-envisioned the role of feudal lords as administrative extensions of a centralized government, effectively eroding local autonomy and shifting towards a unified, centralized system. This ideological shift involved the suppression of alternative philosophies and the establishment of Confucianism as the state's dominant ideology, leading to a reinterpretation of Confucianism that supported an authoritarian framework and cultural assimilation, thus diminishing the rights of the people. In intrinsic tensions between centralized authority and the pursuit of a more decentralized and inclusive form of governance, Confucian theory was transformed from a federalist theory promoting diversity, and advocating decentralization, to one that legitimized a centralized, unified, and authoritarian system. This cannot help but be lamented as a pity of Confucianism.

The government of Laos has made significant efforts to halt deforestation and promote forest conservation in the Northern Uplands of Laos. However, there is no comprehensive assessment of the initiatives and factors that influence youth involvement in forest resource conservation. Our goal was to find sustainable forest management practices and understand the factors affecting young people's behaviors related to forest conservation. We conducted our study in 3 districts, covering 15 villages. We used multiple regressions to identify the factors influencing sustainable forest management behaviors, involving 330 youths who were systematically and randomly selected to participate in structured interviews. Our results showed that conservation knowledge and recognition are associated with demographic and socioeconomic factors, especially education. Factors related to forest conservation recognition included the amount of information available, gender, monthly income, land ownership, and distance from the forest to home. Most households rely on forest products for their livelihoods. We found that higher levels of education provide people with more job opportunities, which improves their job status and quality of life. Community members who received relevant information were more forward-thinking in their forest management behaviors and willing to contribute to related activities. Providing essential information to young people can help improve sustainable forest management behaviors.

Thanks to the Chinese government's strong monetary stimulus initiative, the Chinese stock market has seen a recent surge. A similar scenario in history reminds us that such a surge carries significant potential risks and undermines economic sustainability. This study examines the economic stimulus by the Chinese government during 2008 and 2015 utilizing monetary and real estate policy to stimulate stock market expansion, and identifies a pattern of path dependency in the government's approach to economic challenges. In the context of the fiscal pressures of 2024, the government has again employed an extraordinary level of intervention to catalyze a significant uptick in the stock market. While this has led to a temporary increase in stock market indices, it poses substantial risks. The potential for a stock market bubble, detached from fundamental values, could precipitate a subsequent market collapse. Additionally, the government's market stimulus may be aimed at providing financial support to underperforming state-owned enterprises, which in the long-run will damage China's economic sustainability. There is also a concern that the measures to stimulate the stock market could interlink the bond market and banking sector with the equity, potentially inciting broader systemic risks. Furthermore, the housing market crisis and investors' skepticism towards the extent of China's marketization reforms will also intensify. Overall, we believe that the current round of stock market stimulus is not sustainable and leaves the door open for future risks.

Extremely premature infants are at significant risk for developing bronchopulmonary dysplasia (BPD) and neurodevelopmental impairment (NDI). Although BPD is a predictor of poor neurodevelopmental outcomes, it is currently unknown how BPD contributes to brain injury and long-term NDI in preterm infants. Extracellular vesicles (EVs) are small, membrane-bound structures released from cells into the surrounding environment. EVs are involved in inter-organ communication in diverse pathological processes. Inflammasomes are large, multiprotein complexes that are part of the innate immune system and are responsible for triggering inflammatory responses and cell death. Apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) is pivotal in inflammasome assembly and activating inflammatory caspase-1. Activated caspase-1 cleaves gasdermin D (GSDMD) to release a 30 kD N-terminal domain that can form membrane pores, leading to lytic cell death, also known as proptosis. Activated caspase-1 can also cleave pro-IL-1and pro-IL-18 to their active forms, which can be rapidly released through the GSDMD pores to induce inflammation. Recent evidence has emerged that activation of inflammasomes is associated with neonatal lung and brain injury, and inhibition of inflammasomes reduces hyperoxia-induced neonatal lung and brain injury. Additionally, multiple studies have demonstrated that hyperoxia stimulates the release of lung-derived EVs that contain inflammasome cargos. Adoptive transfer of these EVs into the circulation of normal neonatal mice and rats induces brain inflammatory injury. This review focuses on EV-inflammasomes’ roles in mediating lung-to-brain crosstalk via EV-dependent and EV-independent mechanisms critical in BPD, brain injury, and NDI pathogenesis. EV-inflammasomes will be discussed as potential therapeutic targets for neonatal lung and brain injury.

This brief report detailed the investigation of secondary school students' future intention to use Computer-Based Testing (CBT) in Lagos, Nigeria. A sample of 531 students, which is made-up of new and returning users of CBT, responded to a questionnaire based on a four-point Likert scale. The study aimed to explore whether ease of use, gender, computer self-efficacy, and prior experience influence the future intention to use CBT. Findings show that students who find CBT easier to use have a significantly higher intention to use it again. This association remains significant even when controlling for gender, computer self-efficacy, and experience. New users demonstrated a slightly higher mean intention to use CBT than returning users, possibly due to the novelty effect. This report recommends improving CBT's ease of use to accommodate varying levels of computer literacy and self-efficacy. Limitations of the investigation include the nominal nature of the data and the self-reported responses, which could impact the accuracy of the analysis. Future studies should adopt more robust methodologies, such as Structural Equation Modeling, to better explore these relationships.

Background: Bone metastases (BM) have a detrimental effect on survival for patients with solid cancers. Materials and methods: This systematic review respected the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Results: When investigating OP as a risk factor for BM development, for breast cancer patients, some articles do not differentiate between intrinsic breast cancer subtypes. BMD does not seem to contribute in a significant manner when investigating Luminal A breast cancer. While researching breast cancer regardless of intrinsic subtype, untreated OP increases the risk of bone metastasis when compared to no OP group or treated OP group. In urological cancer cases, OP seems to predispose the patients to BM, especially early after diagnosis. Investigating risk factors for OP development in cancer patients resulted in the identification of 32 articles. Most articles identified risk factors for osteoporosis development in the context of breast cancer patients. Other commonly investigated solid cancers were prostate, other urological cancers, gynecological malignancies, and other less common subtypes of solid tumors. Discussion: While investigating OP as a risk factor for BM, it becomes clear that there is a high grade of heterogeneity in the behavior of each type of cancer in its dynamic concerning bone metastasis, and thus, OP might have different behaviors as a risk factor depending on the situation. Conclusion: There is a need for data regarding cancer subtypes that have not been explored concerning their interaction with the skeletal system in a low bone mineral density scenario.

The circular economy and sustainable development are crucial in addressing environmental pollution from solid waste, especially plastics. Plastic waste has sparked significant social concerns, driving a redesign of products in the flexible packaging industry. This study focuses on redesigning flexible plastic packaging to improve recyclability and accelerate degradability while maintaining essential mechanical and barrier properties for food applications. The goal is to create sustainable packaging that reduces material usage, ensures recyclability, and promotes faster degradation at the product's end of life. The study compared the redesigned packaging's mechanical, physical, and barrier properties with existing products. Results showed that switching from a trilaminate to a bilaminate structure, as in laminated coils and Doypack packaging, reduced material thickness without compromising performance. Oxygen permeability was maintained at 35.38 cc/m²·day, and moisture permeability at 0.56 mg/m²·day for laminated coils. These changes reduced raw material consumption by 26.48% for laminated coils and 12.68% for Doypack packaging. Additionally, a degradable solution combining cellulose paper with a high-barrier polymer reduces plastic adhesives and solvents by 50%, reducing water usage. This research provides a practical approach to more sustainable flexible packaging in the food industry, achieving material reductions without sacrificing performance. The findings can be directly applied to promote sustainable packaging solutions within circular economy initiatives.

This study examined the effectiveness of virtual delivery of the Strength at Home (SAH) intervention program for intimate partner violence in a sample of 605 military Veterans across 69 Veterans Affairs (VA) Medical Centers through a national implementation of the program. Outcome measures included physical IPV, psychological IPV, coercive control behaviors, posttraumatic stress disorder (PTSD) symptoms, and alcohol misuse. Significant pre-intervention to post-intervention reductions were found for all outcomes, with similar effect size estimates relative to a prior investigation of in-person delivered SAH through the same national VA implementation. Study findings suggest that virtual delivery of SAH may be as effective as in-person delivery which has important implications for program access and impact.

The new PV technologies, such as bifacial modules, brings the challenge of analyzing the response of numerical models and their fit to actual measurements. Thus, this study explores various models available in the literature for simulating the IV curve behavior of bifacial photovoltaic modules. The analysis contains traditional models, such as single and double-diode models, and empirical or analytical methodologies. Therefore, this paper proposes and implements a model performance assessment framework. This framework aims to establish a common basis for comparison and verify the applicability of each model by contrasting it with experimental data under controlled conditions of irradiance and temperature. The study utilizes bifacial modules of PERC+, HJT, and n-PERT technologies, tracing IV curves using a high-precision A+A+A+ solar simulator and conducting two sets of laboratory illumination easurements: single-sided and double-sided. In the first case, each face of the module is illuminated separately, while in the latter, the incident frontal illuminating light is reflected on a reflective surface. Experimental data obtained from these measurements are used to evaluate three different approximations for bifacial IV curve models in the case of double-sided illumination. The employed model for single-sided illumination is a single-diode model. The evaluation of various models revealed that shadowing from frames and junction boxes contributes to an increase in the error of modeled IV curves. However, among the three evaluated bifacial electrical models, one exhibited superior performance, with current errors approaching approximately 20%. To mitigate this discrepancy, a proposed methodology highlighted the significance of accurately estimating Io, suggesting its potential to reduce errors.

In the era of industrial evolution satellites are being viewed as swarm intelligence that do not relies on single system but multiple constellations collaborate autonomously. This has enhanced the potential of the GNSS system to contribute in the improved position, navigation and timing (PNT) services. However, Multipath (MP) and Non-line-of-sight (NLOS) receptions remain the prominent vulnerability for GNSS in harsh environments. The aim of this research is to investigate its impact of MP and NLOS on GNSS performance and then proposed a Received Signal Quality Monitoring (RSQM) algorithm. RSQM works twofold: Initially it performs a signal quality test based on fuzzy inference system. The input parameters are Carrier-to-Noise ratio (CNR), Range Residuals (RR) and Code-Carrier Divergence (CCD) and it computes the membership functions based on mamdani method and classify the signal quality as LOS, NLOS, weak NLOS, and strong NLOS. Secondly, it performs an adaptive navigation strategy to exclude/mask the affected range measurements, while considering the satellite geometry constraints (i.e., DOP≤2).. For this purpose, comprehensive research to quantify the multi-constellation GNSS receiver with four constellation configuration (GPS,BeiDou, GLONASS and Galileo) has been carried out in various operating environments. This RSQM based GNSS receiver has capability to identify signal quality and perform adaptive navigation accordingly to improve the navigation performance. The results suggest that GNSS performance in terms of position error is improved from 5.4m to 2.3m averagely in the complex urban environment. Accumulating RSQM with GNSS has great potential for future industrial revolution (Industry 5.0) making things automatic and sustainable like autonomous vehicle operation.

Different researchers analyzed effective computational methods that maintain the precision of Allen-Chan (AC) equations and their constant security. This article presents a method known as reduced order model technique by utilizing kernel principle component analysis (KPCA), a nonlinear variation of traditional principal component analysis (PCA). KPCA is utilized on the data matrix created using discrete solution vectors of the AC equation. In order to achieve discrete solutions, small variations are applied for dividing up extraterrestrial elements, while Kahan’s method is used for temporal calculations. Handling the process of backmapping from small-scale space involves utilizing a non-iterative formula rooted in the concept of the multi-dimensional scaling (MDS) method. Using KPCA, we show that simplified sorting methods preserve dissipation of energy structure. The effectiveness of simplified solutions from linear PCA and KPCA, the retention of invariants, and computational speeds are shown through one-, two-, and three-dimensional AC equations.

Background/Objectives: The study outlines the systematic approach taken to develop and apply a robust NLP algorithm to determine the necessity of performing routine imaging after central venous catheter (CVC) placement and removal, based on the incidence of pneumothorax observed. Methods: Electronic health records from four university hospitals in Salzburg, Austria, on X-rays performed between 2012 and 2021 following CVC procedures, were analyzed using an NLP al-gorithm. The algorithm detected a pneumothorax in radiologists' reports and clinician requests, while excluding cases with contraindications such as chest injuries, prior pneumothorax, missing data, or unrelated follow-up X-rays. Chi-square tests were used to compare pneumothorax rates between CVC insertion and removal, and multivariate logistic regression identified risk factors, with a focus on age and gender. Results: The study analyzed 17,175 cases of patients aged 18 and older, with 95.4% involving CVC insertion and 4.6% involving CVC removal. Pneumothorax was identified in 106 cases after insertion (1.3%) and in 3 cases after removal (0.02%). The Chi-square test showed no statistically significant difference in pneumothorax incidence between insertion and removal (p = 0.4797), in-dicating no substantial difference in pneumothorax risk between these procedures. Conclusions: Given the lack of significant difference in pneumothorax incidence between CVC insertion and removal, and the established consensus that routine imaging is unnecessary after CVC removal, these findings indicate that routine imaging following CVC insertion may also be unnecessary in asymptomatic patients.

In this paper we consider the standard Schur problem for a square matrix A, namely the similarity unitary transformation of A into upper Schur form containing the eigenvalues of A on its diagonal. Since the profound work of Issai Schur (1909), this is a fundamental issue in the theory and applications of matrices. Nevertheless, certain details concerning the Schur problem need further clarification especially in connection with the perturbation analysis of the Schur decomposition relative to perturbations in A. In particular, the concept of regular solution to the perturbed Schur form is introduced and illustrated by several examples. We also introduce the concepts of diagonally spectral matrices and of quasi-Schur condensed forms of a matrix A, and show that they may be much less sensitive to perturbations in A.

Alzheimer’s disease (AD) is the most widespread neurodegenerative disorder. Recently, it was found that mucus extract from Cornu aspersum have beneficial effects on memory and cognitive processes in a rat scopolamine model of AD. The present study elucidated mechanisms of action of standardized mucus snail extract (SE) enriched with fraction above 20 kDa on Alzheimer-type dementia in rats. Using proteomic analysis on two-dimensional polyacrylamide gel electrophoresis (2D–PAGE) on rat cortex extracts we compared protein expression in both groups: the first group treated intraperitoneally with scopolamine (Sco, 2 mg/kg, 11 days) and the second (Sco + SE) group treated intraperitoneally with Sco (Sco, 2 mg/kg) and protected by SE (0.5 ml/100 g bw) applied daily orally for 11 days. Brain cortex was separated and the expression of various proteins related to memory and cognitive functions were identified. We found that the expression of Ubiquitin carboxyl-terminal hydrolase isozyme L1, Calbindin, Vacuolar ATP synthase catalytic subunit A, Tropomyosin beta chain, 14-3-3 zeta/delta, Kinesin-1 heavy chain and Stathmin-4 significantly differs in SE-protected rats as compared to non-treated dement animals, and these brain proteins might be potential therapeutic targets for Alzheimer’s type dementia treatment.

Background: Pet ownership is a common wellbeing enhancing practice globally, offering com-panionship and emotional support. However, it also entails financial responsibilities that can pose challenges and have negative wellbeing impacts for both human and animal. Aims/Purpose: This study aimed to explore pet owners' the financial aspects of pet ownership in New Zealand, including the importance of pet insurance, the impact of veterinary costs, and the ethical considerations of owning a pet. Understanding these aspects of pet ownership is crucial for promoting responsible pet ownership and ensuring animal welfare. Study Designs: Data was collected through a nationwide online survey conducted in 2019 as part of the Furry Whānau Wellbeing research project. The survey included questions about the financial aspects of pet ownership, and respondents were asked to indicate their level of agreement with various statements. Findings: The study found that the cost of veterinary care is a significant concern for many pet owners, with 83.9% of respondents agreeing that expense is a factor in the level of healthcare their pets receive. While pet insurance can mitigate financial burdens, only a third of respondents considered it essential due to high costs and exclusions. The study also revealed disparities for rural and low-income households. Conclusions: The financial aspects of pet ownership present a complex challenge, impacting both pet and owner wellbeing. This research highlights the need for comprehensive strategies to promote sustainable and equitable pet ownership, including improving access to affordable vet-erinary care, enhancing financial literacy among pet owners, and providing support systems for those facing economic hardship.

The integration of augmented reality (AR) into education for sustainability curricula not only makes learn-ing more engaging, motivating, and effective, but also equips students with the knowledge and skills to address pressing environmental challenges. This paper presents a case study of a pedagogical approach based on the exploration of an AR game in the EduCITY app and aims to analyse the potential of the ‘EduCITY at the UA Campus’ mobile AR game in what concerns the promotion of education for sustaina-bility among secondary students. The game was explored in the largest annual event of the University of Aveiro – XPERiMENTA – which invited students and the wider community to participate in activities on the campuses. At the end of the activity, an individual and anonymous questionnaire to evaluate the game was applied. Students indicated that the game raises awareness of sustainability and contributes to the de-velopment of knowledge and skills in this area. They were motivated throughout the match and managed to get a good performance out of playing. This study adds to the literature on the use of AR games in edu-cation for sustainability, by revealing that it can be an effective tool for engaging and motivating students with sustainability-related learning.

The thickness estimation is crucial for evaluating landslide evaluating. The traditional non-contact mass conservation method adopts three-dimensional deformation to estimate landslide thickness, which may be unsuitable due to the limitations of observations. In this study, a more feasible approach for estimating landslide thickness based on 2D deformation derived from two-track Interferometric Synthetic Aperture Radar (InSAR) observations is proposed, specifically applied to the Xiongba landslide. The comparison between the estimated thickness from the InSAR-derived 2D deformation and the measured thickness by geological and drilling methods validates the reliability of the proposed method. The mapped InSAR LOS deformation rate fields reveal two distinct deformation regions, including a frontal zone exhibiting significant deformation and a relatively stable zone. The analysis of the 2D deformation indicates that surface uplift at the front edge of the Xiongba-H2 landslide may result from the pushing of the rock-soil mass in areas of high deformation. The inversion result suggests that the thickness of the Xiongba-H2 landslide is ranging from 10 to 100 m, corresponding to the active volume of 6.17×107 m3. A thicker region is identified, at the front edge along the Jinsha River, posing the potential of further failure. It is believed that the proposed low-cost, easily implementable approach could enhances the applicability of InSAR technology for landslide motion analysis and hazard assessment.

Most of the existing trajectory privacy protection methods provide a unified degree of privacy protection for data, and most of the methods mainly focus on the spatial and temporal dimensions of trajectory data, with little consideration of the semantic information of the location. To address these issues, we propose a hierarchical temporal semantic tree-based personalized trajectory privacy protection (HTST-PTPP) scheme, which mainly constructs a hierarchical temporal semantic tree by considering semantic categories and residence time. Then, quantifies the privacy protection requirements of each location, divides the privacy level, and uses differential privacy technology to realize personalized trajectory privacy protection. Finally, experiments are carried out on two real data sets. The experimental results show that our HTST-PTPP scheme has good performance in data availability and privacy protection.

In this study, hybrid materials were synthesized incorporating curcumin, Cu²⁺ or Fe³⁺, and Kappa-carrageenan as a reducing agent to improve its stability, considering that curcumin has low thermal and solution stability, which limits its applications. Colorimetric analysis showed color changes in the hybrids, ultraviolet-visible spectroscopy revealed band shifts in the hybrids, and infrared analysis indicated shifts in wavenumbers, suggesting changes in the vibrational state of curcumin after bonding with metal ions. These techniques confirmed the formation of the hybrid materials. Thermogravimetric and chromatographic analyses demonstrated greater thermal and solution stability for the hybrids compared to curcumin. Additionally, the hybrid composites effectively developed natural and sebaceous latent fingerprints with good clarity and contrast on glass surfaces. Both composites performed similarly to commercial gold powder. When applied to surfaces representative of forensic scenarios, the composites were versatile, revealing sufficient fingerprint details for human identification on both porous and non-porous surfaces. Scanning electron microscopy images showed greater clarity in sebaceous and natural fingerprints developed with the Fe composite compared to the Cu composite, due to minimal interaction of Fe with the glass surface.

Insurance companies need to calculate solvency capital requirements in order to ensure that they can meet their future obligations to policyholders and beneficiaries. The solvency capital requirement is a risk management tool essential for, when extreme catastrophic events occur, resulting in a high number of possibly interdependent claims. This paper studies the problem of aggregating the risks coming from several insurance business lines and analyses the effect of reinsurance in the level of risk. Our starting point is to use a Hierarchical Risk Aggregation method, which was initially based on 2-dimensional elliptical copulas. We then propose the use of copulas from the Archimedean family and a mixture of different copulas. Our results show that a mixture of copulas can provide a better fit to the data than an individual copula and consequently avoid over or underestimating of the capital requirement of an insurance company. We also investigate the significance of reinsurance in reducing the insurance company’s business risk and its effect on diversification. The results show that reinsurance does not always reduce the level of risk, but can also reduce the effect of diversification for insurance companies with multiple business lines

Abstract: Objective: Evaluation of individuals with intravenous drug addiction who developed infective endocarditis (IE) is required for a better understanding of the management that can be applied in these cases. This study aimed to shed light on the complex interplay between intravenous drug use and IE with the ultimate goal of improving patient care and outcomes Method: The study examined the clinical outcomes of 43 patients admitted with infective endocarditis (IE) associated with injection drug use. Data was collected over an average follow-up period of 12 months, providing a substantial timeframe to assess the long-term effects of different treatment approaches. The research focused on comparing the outcomes between two distinct groups: patients who received medical treatment alone and those who underwent surgical intervention in addition to medical management. Results This study included 43 intravenous drug users who were diagnosed with infective endocarditis (IE). The mean age of the patient cohort was 31 ± 9 years with a predominance of males (74.4%). All cases involved native valve IE, with the aortic valve being the most commonly affected (62.9%), followed by the tricuspid (30.2%) and mitral valves (6.9 %). Multiple valve involvement was observed in 13.9% of the cases. The study population had a high prevalence of comorbidities, particularly HIV infection (65.1%) and hepatitis C infection (25.5%). The study also revealed that 19.3% of the patients had previously experienced IE. Mortality rates were slightly higher in patients with recurrent IE (23.2%) than in those who experienced their first episode. Transthoracic echocardiography proved to be a highly effective diagnostic tool for detecting vegetation in 95% of the cases. Microbiological analysis identified Staphylococcus aureus as the predominant causative organism, isolated from blood cultures in 55.8% of the cases. These findings highlight the complex nature of IE in intravenous drug users, emphasizing the importance of comprehensive management strategies that address both cardiac manifestations and underlying comorbidities in this high-risk population. Conclusions: Injection drug use–associated infective endocarditis presents a significant challenge in modern healthcare, with patients facing a high risk of complications and poor clinical outcomes despite current therapeutic approaches. This persistent issue underscores the complexity of treating individuals with both infectious diseases and substance use disorders. The multifaceted nature of these cases often involves immediate cardiac infection, as well as concurrent medical, psychological, and social challenges that can complicate treatment and recovery.

This study presented a centrifuge-based method for determining hydraulic properties in growing media, offering insights into water dynamics in growth substrates. The objectives of this study were to test the practical applicability of the centrifuge method as a quick test for a wide range of growing media, ii) to compare a simple substitution method to describe the bulk density of growing media with results of the standard method, and iii) to give a recommendation under which conditions the centrifuge quick test could serve as a replacement for the standard method. Methods involved centrifugation and correlation analyses. Results showed good agreement between the centrifuge and DIN methods, with notable compression effects at lower pF stages. The method's rapidity (2 days vs. up to 8.5 days) and correlation with standard methods highlight its potential for practical applications. Limitations, such as compression effects, were noted, emphasizing the need for careful interpretation. Overall, the centrifuge method provided a valuable tool for research and substrate development. This study contributes to refining measurement techniques in growth substrates, encouraging ongoing research in water dynamics in growing media.

Cone-beam computed tomography (CBCT) has become a vital tool in implantology, playing a key role in both pre- and post-surgical phases. Preoperatively, CBCT provides detailed three-dimensional evaluation of anatomical structures, offering precise information on bone quality and quantity, as well as the location of critical structure. This accuracy enhances surgical planning, reducing intra- and postoperative risks and ensuring more precise implant placement. Post-surgically, CBCT is equally important for monitoring osseointegration and detecting potential complications, such as failed integration, infections, or implant misalignment. Its high-resolution imaging capabilities enable clinicians to make accurate therapeutic adjustments, improving treatment outcomes. Overall, CBCT improves decision-making in implantology, offering greater predictability and safety compared to traditional two-dimensional radiography, significantly enhancing the success rates of implant-based oral rehabilitation procedures.

Photovoltaic (PV) energy has been a preferable choice with the rise in global energy demand, as it is a sustainable, efficient, and cost-effective source of energy. Optimizing the power generation is necessary to fully utilize the PV system. Harvesting more power uses cascading of impedance source converters taking input from low-voltage PV arrays which requires multiple maximum power point tracking (MPPT) controllers. To solve this problem, a three-level inverter topology with a new PV arrangement, offering a smaller size with lower cost is designed in this article. The design criteria for parameters are discussed with the help of the small signal analysis. In this paper, three PV arrays are used to harvest maximum energy, which requires only one MPPT controller and employs a modified perturb and observe (P&O) algorithm, being faster, highly efficient, and reducing the computational burden of the controller. Moreover, a three maximum power points tracker algorithm, which perturbs one parameter and observes six variables, is designed for the selected converter topology. This MPPT algorithm offers better dynamics and is highly efficient with a conversion efficiency of 99.2% during uniform irradiance and 97% efficiency during variable irradiance conditions.

Environmental pollution indicated by the presence of PM2.5 particulate matter varies based on prevailing atmospheric conditions described by certain meteorological variables. Consequently, it is important to understand atmospheric behavior in areas such as the Aburrá Valley, which experiences recurrent pollution events twice a year. This study examines the behavior of specific meteorological variables and PM2.5 particulate matter in the Aburrá Valley. By using statistical analysis tools such as correlation coefficients, principal component analysis (PCA), and multiple linear regression models, the research identifies relationships between PM2.5 and daily cycles of temperature, rainfall, radiation, and wind speed and direction. Data sets were analyzed considering periods before and after the COVID-19 lockdown (pre-pandemic and pandemic, respectively), and specific pollution events were also analyzed. Furthermore, this work considers the relationships between PM2.5 and meteorological variables, contrasting the pre-pandemic and pandemic periods. This study characterizes diurnal cycles of meteorological variables and their relationship with PM2.5. There are consistent patterns among temperature, atmospheric boundary layer (ABL) height, and solar radiation, whereas precipitation and relative humidity show opposite behavior. PM2.5 exhibits similar relative frequency functions during both daytime and nighttime, regardless of rainfall. An inverse relationship is noted between PM2.5 levels and ABL height at different times of the day. Moreover, the PCA results show that the first principal component explains around 60% of the total variance of the hydrometeorological data. The second PC explains 10%, and the rest of the variance is distributed among the other three to eight PCs. In this sense, there is no significant difference between the two PCA analyses with hydrometeorological data from a pre-pandemic period and a COVID-19 pandemic. Multiple regression analysis indicates a significant and consistent dependence of PM2.5 on temperature and solar radiation across both analyzed periods. This work presents new insights that enhance the diagnosis, understanding, and modeling of environmental pollution, thereby supporting informed decision-making and strengthening management efforts.

Wheat is one of the most important crops to ensure food production globally. Understanding the mechanism of leaf senescence in wheat plays a crucial role in improving its productivity and resilience under varying stress scenario. In this study, we investigated biochemical, functional, and ultrastructural changes during leaf senescence in wheat genotypes with contrasting drought tolerance. For this, key parameters such as chlorophyll and total protein content, membrane stability, malondialdehyde level, and the activity of antioxidant enzymes (superoxide dismutase, ascorbate peroxidase, guaiacol peroxidase, benzidine peroxidase, catalase) were comparatively analyzed during both natural and drought-induced senescence. Additionally, the expression of superoxide dismutase isoform genes functioning in different cellular compartments was studied, alongside ultrastructural changes in flag leaves. The experiments involved genotypes of bread wheat (Triticum aestivum L.) and durum (Triticum durum Desf.) wheat. After the booting stage, irrigation was discontinued for drought-treated plants. Flag leaves were sampled at 7, 14, 21, 28, and 35 days after anthesis. The drought-tolerant genotypes exhibited slower chlorophyll degradation, lower lipid peroxidation levels, higher membrane stability, and more robust antioxidant responses, maintaining cellular function longer than the sensitive genotypes, which showed accelerated leaf senescence. Transcript levels of FeSOD increased significantly post-flowering but declined as senescence progressed, while MnSOD expression rose towards the end of ontogenesis. Ultrastructural analysis revealed progressive damage to chloroplast membranes, thylakoid structures, and mesophyll cell walls under stress conditions. These findings contribute to a deeper understanding of the physiological and molecular responses of wheat to drought stress, offering potential targets for improving crop performance in water-limited environments.

Pre-transport management activities can cause stress, injuries, and mortality in poultry. This study aimed to gather information about the current pre-transport practices (selection of unfit chickens, catching preparations, catching, and crating) for spent hens and broilers by questioning Flemish poultry farmers. The results showed that catching preparations such as an extra selection of chickens unfit for transport was performed by a minority of the poultry farmers, and that layer farmers were less in line with the EU-legislation for water and feed withdrawal than broiler farmers. All birds were caught inverted except for one broiler farmer who used mechanical catching (not yet common in Flanders). Additionally, mechanical catching may involve extra costs, increased biosecurity risks, and specific recommendations for the stable (height and width). The broiler farmers preferred mechanical catching for broiler catchers' well-being, while upright catching was considered better for animal welfare than catching more than three chickens by one/two legs, mechanically, or by wings. Awareness of the need to perform an extra selection by the poultry farmers before catching is required. Preparations like closing areas under the aviary system and removing litter (layers) can further streamline the process and reduce animal suffering.

Nanotechnology is being used in agriculture to improve plant nutrition while maintaining soil texture and safeguarding it against microbial illnesses. Examples of such applications include the utilization of nano-fertilizers, nano-pesticides, and nano-herbicides. Nanotechnology plays a crucial role in maintaining soil health, hence promoting the overall well-being of plants. Nanoparticles have been shown to enhance agricultural productivity and output, mitigate the opposing effects of chemical runoff and nutrient loss. Several factors, including concentrations, physiochemical properties, and plant species, influence the impact of nanoparticles on plants. Several nanoparticles have been shown to impact plant physiology, leading to enhanced biomass output and germination rate. Nanoparticles have the ability to alter molecular pathways in plants via their impact on gene expression. The presence of quantum dots, carbon nanotubes, ZnO, Ag, Fe2O3, Se, Au, TiO2, Al2O3, SiO2, and non-metal oxides of nanoparticles is of significant importance in the promotion of plant development and growth. Extensive research has been conducted on the role of NPs in the reduction of growth, inhibition of chlorophyll, and enhancement of photosynthetic efficiency. The main purpose of this study was to offer a comprehensive overview of studies that have examined the impacts, translocation, and interactions of nanoparticles with plants.

Teclistamab (TEC) is the first B-cell maturation antigen-directed bispecific antibody approved by the European Medicines Agency and Food and Drug Administration for triple-class exposed relapsed/refractory multiple myeloma (RRMM). As TEC is increasingly being used in real-world (RW) settings, this study sought to gather existing RW evidence on effectiveness, safety, healthcare resource utilization, and clinical practices associated with TEC. A systematic literature review was performed to identify RW observational studies of adults with RRMM treated with TEC. Sixty-one records representing 41 unique studies were included; sample sizes ranged from 8 to 572 patients. Where reported, median follow-up ranged from 2.3 to 33.6 months and more than 65% of patients would have been ineligible for the pivotal trial of TEC (MajesTEC-1) in all but one study. Across populations with ≥50 patients, overall response rates ranged from 50 to 66% and cytokine release syndrome (CRS) rates ranged from 18 to 64%. Tocilizumab use for CRS management was reported in 14 studies, with two indicating lower CRS rates (13% and 26%) when used prophylactically. Survival and infection outcomes showed wide variability due to short follow-up in most studies. Overall, early RW effectiveness and safety outcomes of TEC were comparable to findings from MajesTEC-1.

New vaccination programs need a method to measure success based on pre-defined outcomes evaluated over pre-specified time frames. Reimbursement of newly approved vaccines is often reliant on simulated projections that approximate real-world scenarios, due to limited long-term data availability. Adjustments to reimbursement prices are infrequent, barring instances of market competition-induced price erosion through tender processes. Consequently, comprehensive monitoring of the vaccine effect (VE) for an adequate duration to evaluate the success of vaccination programs remains rare. Such data are essential to inform expectations of vaccine effect and the timeline for measurable success of the investment. An example is provided here by the 15-year assessment of the rotavirus vaccination program in Belgium (RotaBIS study spanning 2005 to 2019 across 11 hospitals). The vaccination program started in late 2006 and yielded sub-optimal outcomes. Long-term VE surveillance data provided insights into infection dynamics, disease progression, and vaccine performance. The presented analysis introduces novel conceptual frameworks and methodologies. Cost-effectiveness analysis (CEA) evaluates the initial target vaccination population, considering the effectiveness of direct and indirect effects of the vaccine, compared with a historical group that is unvaccinated. Cost-impact analysis (CIA) covers a longer period and considers the whole vaccinated and unvaccinated population in which the vaccine has direct and indirect effects. The success index ratio of CIA over CEA outcomes evaluates the vaccination performance. Good performance has ≤ 1 index value combined with a low CEA. This measure is therefore a valuable aid for new vaccine introductions. It supports the establishment of robust monitoring protocols.

Antibiotic resistance is a global public health issue, largely driven by the misuse of these medications. This study aimed to compare the knowledge, attitudes and practices related to antibiotic use among students in Ecuador and Nigeria through a cross-sectional survey. The results indicated a strong understanding in both countries of the risks associated with inappropriate antibiotic use and the importance of completing prescribed treatments. However, significant differences were noted in the practice of self-medication, which was more prevalent in Ecuador. Additionally, behaviors such as insistence on obtaining antibiotics and the storing of leftover medications were common, underscoring the need for targeted educational interventions. The implications of these findings for promoting responsible antibiotic use are further discussed.

Large Language Models (LLMs) have emerged as powerful tools in the domain of artificial intelligence, specifically enhancing natural language processing capabilities. These models leverage extensive datasets and sophisticated algorithms to automate and enhance tasks traditionally performed by humans, thereby revolutionizing innovation and entrepreneurship. LLMs accelerate product development, streamline business operations, and enable precise and rapid decision-making, all of which are crucial for maintaining competitiveness in dynamic markets. This paper categorizes the applications of LLMs in innovation and entrepreneurship into three main areas: technological innovation, strategic decision-making, and process automation. By exploring various integrations of LLMs in entrepreneurial ventures, this work offers both theoretical insights and practical examples, underscoring the transformative impact of LLMs in shaping modern business landscapes.

Background: Hepatitis A virus (HAV) is a leading cause of acute viral hepatitis and is primarily transmitted via the fecal-oral route. The clinical presentation and progression of the disease vary based on the patient's age. Turkey is classified as an intermediate endemic country, and HAV infection remains a significant public health issue worldwide. Methods: This study conducted a systematic meta-analysis to evaluate age-specific HAV seroprevalence rates in Turkey from 2000 to 2023. A comprehensive literature search identified 177 articles, of which 57 met the inclusion criteria. Studies were assessed for quality and categorized by age groups: 0-

This research paper presents a detailed analysis of a Lightweight Block Cipher’s power consumption and security features (LWBC), specifically designed for IoT applications. To accurately measure energy consumption during the execution of the LWBC algorithm, we utilised the Qoitech Otii Arc, a specialised tool for optimising energy usage. Our experimental setup involved using the Otii Arc as a power source for an Arduino NodeMCU V3, running the LWBC security algorithm. Our methodology focused on energy consumption analysis using the shunt resistor technique. Our findings reveal that the LWBC is highly efficient and provides an effective solution for energy-limited IoT devices. We also conducted a comparative analysis of the proposed cipher against established LWBCs, which demonstrated its superior performance in terms of energy consumption per bit. The proposed LWBC was evaluated based on various key dimensions such as power efficiency, key and block size, rounds, cipher architecture, gate area, ROM, latency, and throughput. The results of our analysis indicate that the proposed LWBC is a promising cryptographic solution for energy-conscious and resource-limited IoT applications.

The aim of the present study was to evaluate the contamination state of the surface soil from 10 parks and playgrounds from Galati, Romania, and the health hazard. The soil samples, collected in each site from the playing ground and from the edge of the park, were analyzed by using com-bined Wavelength- (WDXRF) and Energy-Dispersive (EDXRF) X-ray fluorescence techniques. A total number of 27 chemical elements (Ag, Al, As, Ba, Ca, Cd, Cr, Co, Cu, Fe, Hg, K, Mg, Mn, Na, Ni, P, Pb, Rb, Sb, Sc, Sn, Sr, Ti, V, Zn and Zr) were quantified in the urban soils, and the results were compared to the normal and alert values from Romanian legislation for toxic trace elements, as well as with European and world average values of element concentrations. The mineralogical analyses were performed by Scanning Electron Microscopy with Energy Dispersive X-ray Analysis (SEM-EDX) and Attenuated Total Reflectance-Fourier Transform Infrared technique (ATR-FTIR). To assess the soil contamination and the impact on human health of the presence of potential toxic elements and heavy metals in the soil, a series of pollution and health risk indices were used. All the results indicated an unpolluted to moderate polluted soil. The soil samples collected from the edge of the parks presented higher values for the specific pollutants that originated from heavy traffic, such as Cu, Cr, Zn and Pb. The non-carcinogenic risk to children was assessed using the estimate daily intakes (EDI), afferent to the pathways that pollutants can enter the human body, such as ingestion, dermal contact and inhalation. Using the obtained values for EDI, the hazard quotient and hazard index were determined, which strengthen the formerly issued presumption that soil pollution is moderate and, by itself, does not present any threat to the children’s health.

The Cu cocatalyst supported on the surface of TiO2 photocatalysts has demonstrated unique activity and selectivity in photocatalytic CO2 reduction. The valence state of copper significantly influences the catalytic process; however, due to the inherent instability of copper's valence states, the precise role of different valence states in CO2 reduction remains inadequately understood. In this study, CuOx/TiO2 catalysts were synthesized using an in-situ growth reduction method, and we investigated the impact of various valence copper species on CO2 photocatalytic reduction. Our results indicate that Cu+ and Cu0 serve as primary active sites, with the selectivity for CH4 and CO products during CO2 photoreduction being closely related to their respective ratios on the catalyst surface. The adsorption and activation mechanisms of CO on both Cu+ and Cu0 surfaces are identified as critical factors determining product selectivity in photocatalytic processes. Furthermore, it is confirmed that Cu+ primarily facilitates CH4 production while Cu0 is responsible for generating CO. This study provides valuable insights into developing highly selective photocatalysts.

Abstract: Industrial hemp (Cannabis sativa L.) is primarily a dioecious plant, and monoecious varieties developed for high yield. Production practices vary by varieties prompting the need for the present study aimed to describe the floral characteristics and evaluate pollen quantity and viability of a monoecious (Henola) and three dioecious (CFX-2, Canda, and Joey) varieties. All varieties have five lanceolate anthers, basifixed to a threadlike filament. Anther length was significantly different but not anther width among varieties. The longest length (0.38 ± 0.046 cm) was recorded in Henola, and shortest (0.34 ± 0.043 cm) in CFX-2. Anther width ranged from 0.088 ± 0.0024 to 0.095 ± 0.0021cm. Pollen grains were triporate and spheroidal in shape and size differed significantly with the largest in Joey (27.83 ± 0.78 μm) and Henola (27.489 ± 0.99 μm), and smallest in Canda (22.04 ± 0.56 μm). The number of pollen grains differed significantly among varieties ranging from 29,183 in Henola to 104,548 in Joey. Even though Henola recorded the lowest pollen number it had the highest percentage (69.3%) of viable pollen and Canda recorded the lowest. There was a moderate, positive and significant relationship (r = 0.496) between anther length and the number of pollen grains in Joey. The relationship in Henola was moderate and non-significant (r = 0.356), weak and non-significant in Canda (r = 0.188), and in CFX-2 (r = 0.037). The findings from our study provide information for growers and researchers on hemp breeding and cultivation practices that may contribute to prevent cross pollination.

The COVID-19-induced strain on global supply chains led to significant market imbalances and unprecedented inflation, particularly affecting urban economies. Containment policies and stimulus packages resulted in unpredictable demand shifts, challenging urban supply chain planning and resource distribution. These disruptions underscored the need for robust risk management models, especially in cities where economic activity and population density exacerbate supply chain vulnerabilities. This study develops a comprehensive risk model tailored for G-7 urban economies, analyzing the causal and cointegration relationships between key economic indicators. Using Granger causality tests and a factor-augmented vector autoregression (FAVAR) approach, the study examines complex time series and high-dimensional variables, focusing on urban-specific indicators such as the Composite Leading Indicator (CLI) and Business Confidence Indicator (BCI). Our results indicate strong causal relationships among these indicators, validating CLI as a reliable early predictor of urban economic trends. The findings confirm the viability of this urban supply chain risk management model, offering potential pathways for strengthening urban resilience and economic sustainability in the face of future disruptions. This approach positions the study within the context of urban science, emphasizing the impacts on cities and how urban economies can benefit from the developed risk model.

Background: Intracranial suppurative infections in pediatric patients, while rare, pose a significant risk to patient mortality. Early recognition and fast initiation of diagnosis and treatment are crucial to prevent fatal outcomes. Between December 2022 and May 2023, a significant cluster of nine cases emerged, each necessitating neurosurgical intervention. This series highlights an important trend in clinical outcomes and raises questions about underlying factors contributing to this pattern. The need for surgical procedures in all instances suggests a commonality in severity, warranting further investigation into potential causes and preventative measures. This retrospective monocentric study aims to explore the clinical features associated with these cases to identify specific disease patterns that can expedite management in clinical practice. Methods: Cramer’s V effect size was employed to evaluate combinations of clinical features, followed by Fisher’s exact test applied to a constructed contingency table. A p-value was assessed for significance analysis, with combinations achieving a Cramer’s V value of 0.7 or higher classified as exhibiting very strong correlations. Results: The analysis revealed distinct patterns of clinical features among children diagnosed with intracranial abscesses. Significant associations were identified, including correlations between sinusitis and Streptococcus pyogenes, fever accompanied by affected temporal, frontal and frontobasal lobe regions. Conclusions: Despite the generally limited statistical analysis of pediatric intracranial abscesses in the existing literature, this study provides meaningful significant associations between clinical features, delineating specific disease patterns. By addressing this gap, the findings contribute valuable insights and offer a framework that could enhance clinical decision-making and support timely disease management in pediatric cases.

The article titled "Immunoglobulins and Its Applications" provides a comprehensive overview of the structure, function, and therapeutic significance of immunoglobulins, also known as antibodies. These vital proteins, produced by plasma cells in response to immunogens, are essential components of the immune system, playing a critical role in recognizing and neutralizing pathogens such as bacteria and viruses. The article elaborates on the five primary classes of immunoglobulins (IgA, IgD, IgE, IgG, and IgM), each distinguished by its unique structural and functional properties. It discusses the molecular composition of immunoglobulins, highlighting the significance of their variable and constant regions in antigen binding. The paper also explores the diverse immune functions mediated by these proteins, including precipitation, agglutination, and neutralization of antigens. Additionally, the article emphasizes the therapeutic applications of immunoglobulins, particularly in treating immune deficiencies and other diseases. Advances in monoclonal antibody technology have significantly expanded the utility of immunoglobulins in both research and medicine, leading to the development of innovative therapeutic approaches such as humanized monoclonal antibodies and bifunctional antibodies. This comprehensive analysis underscores the critical role of immunoglobulins in both natural immunity and therapeutic interventions.

Objectives: This study focused on the presence or absence of vascular invasion and extrahepatic metastasis in hepatocellular carcinoma (HCC) and examined their impact on systemic treatment outcomes. Methods: We retrospectively analyzed 362 patients with unresectable HCC who received first-line systemic therapy. The prognostic evaluation was based on the presence of vascular invasion and extrahepatic metastasis at the time of treatment initiation. Results: Patients with vascular invasion or extrahepatic metastasis (advanced group) had significantly worse outcomes than those without these features (intermediate group), with median survival times of 434 and 658 days, respectively. Further subdivision of the advanced group into three categories—patients with only extrahepatic metastasis (m group, n = 77), patients with only vascular invasion (v group, n = 78), and patients with both vascular invasion and extrahepatic metastasis (vm group, n = 52)—revealed that the m group had significantly better outcomes than those in the other two groups, with median survival times of 649, 323, and 187 days, respectively. A comparison of the clinical backgrounds among the three groups demonstrated that the m group had significantly better liver function at the time of treatment initiation than that in the other two groups. Multivariate analysis, including performance status, Child–Pugh score, and the use of immune checkpoint inhibitors as first-line therapy, identified the m group as an independent and significant prognostic factor (hazard ratio, 0.50). Conclusions: Unresectable HCC with extrahepatic metastasis and no vascular invasion represents a novel staging category for systemic treatment.

In Kenya, Rift Valley Fever (RVF) outbreaks pose significant challenges, being one of the most severe climate-sensitive zoonoses. While Machine Learning (ML) techniques have shown superior performance in time series forecasting, their application in predicting disease outbreaks in Africa remains under explored. Leveraging data from the International Livestock Research Institute (ILRI) in Kenya, this study pioneers the use of ML techniques to forecast RVF outbreaks by analysing climate data spanning from 1981 to 2010, including machine learning models. Through a comprehensive analysis of ML model performance and the influence of environmental factors on RVF outbreaks, this study provides valuable insights into the intricate dynamics of disease transmission. The XGB Classifier emerged as the top-performing model, exhibiting remarkable accuracy in identifying RVF outbreak cases, with an accuracy score of 0.997310. Additionally, positive correlations were observed between various environmental variables, including rainfall, humidity, and claypatterns, and RVFcases, underscoring the critical role of climatic conditions in disease spread. These findings have significant implications for public health strategies, particularly in RVF-endemic regions, where targeted surveillance and control measures are imperative. However, the study also acknowledges the limitations in model accuracy, especially in scenarios involving concurrent infections with multiple diseases, highlighting the need for ongoing research and development to address these challenges. Overall, this study contributes valuable insights to the field of disease prediction and management, paving the way for innovative solutions and improved public health outcomes in RVF-endemic areas and beyond.

Arbuscular mycorrhizal fungi (AMF) and rhizobia are crucial for plant productivity, microbial community structure, and soil quality, making them key components for sustainable ecosystem development. The symbiotic relationship between AMF and rhizobia is essential for effective biological nitrogen fixation and nutrient absorption, reducing reliance on chemical fertilizers and promoting sustainable agricultural practices. However, studies have shown that soil environment can hinder the symbiotic relationship between AMF and rhizobia. We conducted a meta-analysis of 158 articles from 1980 to 2022 to explore the synergistic interactions in legume-AMF-rhizobium systems and the potential mechanisms underlying synergism. Our findings revealed that the inoculation with AMF and/or rhizobia significantly (P < 0.001) increased legume plant nitrogen content, phosphorus content, shoot biomass, yield, AMF colonization rate, nodule number, and nodule weight compared to uninoculated controls (effect size d >0). There was a substantial synergistic effect between AMF and rhizobia (P < 0.001). However, soil salt, drought and pH stress inhibited the positive effects of inoculation treatments, possibly due to the plant trade off strategies under adverse stress conditions. Under well-watered condition, the d values of plant yield in the rhizobia, AMF and co-inoculation treatments were 2.047, 1.661, and 3.412 (QM = 246, P < 0.001), respectively, which were higher than that of 1.196, 0.765, and 1.828 (QM = 195, P < 0.001) in the drought stress treatment. This research may potentially lead to new solutions for sustainable agricultural systems in the face of global climate change.

We propose the DIKWP-TRIZ framework, an innovative extension of the traditional Theory of Inventive Problem Solving (TRIZ) designed to address the complexities of cognitive processes and artificial consciousness. By integrating the elements of Data, Information, Knowledge, Wisdom, and Purpose (DIKWP) into the TRIZ methodology, the proposed framework emphasizes a value-oriented approach to innovation, enhancing the ability to tackle problems characterized by incompleteness, inconsistency, and imprecision. Through a systematic mapping of TRIZ principles to DIKWP transformations, we identify potential overlaps and redundancies, providing a refined set of guidelines that optimize the application of TRIZ principles in complex scenarios. The study further demonstrates the framework’s capacity to support advanced decision-making and cognitive processes, paving the way for the development of AI systems capable of sophisticated, human-like reasoning. Future research will focus on comparing the implementation paths of DIKWP-TRIZ and traditional TRIZ, analyzing the complexities inherent in DIKWP-TRIZ-based innovation, and exploring its potential in constructing artificial consciousness systems.

Keywords: Structural Equation Modeling (SEM); economic and social preferences; consumer choices; econometric model; Partial Least Square (PLS).

The degradation of mangrove ecosystems in East Java poses significant challenges to both environmental sustainability and local businesses dependent on mangrove tourism. This study explores the implementation of the Mangrove Ecosystem Transformation Approach (META), a holistic framework designed to integrate environmental conservation with business resilience in the mangrove tourism sector. By combining quantitative, qualitative, and model development methods, this research investigates how innovative technologies can support sustainable tourism management. The study identifies critical factors influencing business resilience, evaluates the environmental impact of mangrove tourism, and demonstrates how META can improve operational efficiency and environmental outcomes. The findings highlight the potential for META to serve as a model for sustainable tourism in coastal areas, ensuring long-term business viability and environmental preservation.

Motivated from Deutsch entropic uncertainty principle and several product uncertainty principles, we derive an uncertainty principle for the product of entropies using functions.

We will outline the relationship between luminosity distance and cosmological redshifts, demonstrating that it is consistent with a new cosmological model recently proposed by Haug and Tatum [1], which appears to resolve the Hubble tension within the Rh = ct cosmology.

Introduction: To describe a case of unilateral exudative retinal detachment and severe uveitis with a large subretinal deposit in a 6-year-old girl presenting with left thigh lymphadenitis. Case Presentation: A metagenome next-generation sequencing (mNGS) of the vitreous body was performed, revealing Bartonella henselae. The patient showed the resolution of retinal detachment and uveitis, as well as improvement of left thigh lymphadenitis, in response to systemic and ocular antibiotics and corticosteroids. Conclusion: Bartonella henselae neuroretinitis may manifest as exudative retinal detachment with extensive subretinal lesions and uveitis. The treatment involving systemic and ocular antibiotics and corticosteroids proved to be effective.

ediatric bronchoscopy is a widely used diagnostic and therapeutic procedure; however, it is frequently associated with postoperative complications, including laryngeal edema, hypoxemia, and respiratory distress【1】【2】. Nursing interventions have the potential to mitigate these complications; however, their overall effectiveness in pediatric populations remains under-investigated. This meta-analysis aimed to evaluate the impact of nursing interventions on the incidence of postoperative complications following pediatric bronchoscopy. A random-effects model was applied to calculate pooled odds ratios (OR) with 95% confidence intervals (CI), estimating the effect of nursing interventions on postoperative complications. Heterogeneity was assessed using the I² statistic, and publication bias was evaluated using funnel plots and Egger’s test. Nursing interventions were associated with a significant reduction in postoperative complications, with a pooled OR of 0.22 (95% CI: 0.13, 0.37; p < 0.0001). The heterogeneity across studies was low (I² = 0%), indicating consistent results across the included studies【1】【3】【6】. Funnel plot analysis revealed slight asymmetry; however, Egger’s test did not indicate significant publication bias (p = 0.1213)【7】. Given the consistency of these findings, integrating structured nursing protocols into postoperative care has the potential to substantially improve patient outcomes. Further research is warranted to explore the long-term impacts and cost-effectiveness of these interventions【9】【10】

Magnesium-doped hydroxyapatite (Mg-HAp) nanofibers show promise for medical applications due to their structural similarity to bone mineral and enhanced biological properties, such as improved biocompatibility and antimicrobial activity. This study synthesized Mg-HAp nanofibers using a microwave-assisted hydrothermal method (MAHM) to evaluate their cytotoxicity, biocompatibility, and antimicrobial efficacy compared to commercial hydroxyapatite (HAp). Characterization through X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Energy Dispersive X-ray Spectroscopy (EDS), and Fourier Transform Infrared Spectroscopy (FTIR) confirmed the successful incorporation of magnesium, producing high-purity, crystalline nanofibers with hexagonal morphology. Rietveld refinement showed slight lattice parameter shortening, indicating Mg2+ ion integration. Cell viability assays (MTT and AlamarBlue) revealed a significant increase in fibroblast proliferation with 2% and 5% Mg-HAp concentrations compared to controls (p&lt;0.05), demonstrating non-cytotoxicity and enhanced biocompatibility. Antimicrobial tests (disk diffusion method, 100 µg/ml) showed that Mg-HAp had strong antibacterial effects against Gram-positive and Gram-negative bacteria, and moderate antifungal activity against Candida albicans. In contrast, commercial HAp showed no antimicrobial effects. These results suggest Mg-HAp nanofibers have significant advantages as biomaterials for medical applications, particularly in preventing implant-related infections, supporting further clinical development.

In this study, we propose a conservative and compact finite difference scheme designed to preserve both the mass change rate and energy for solving the sixth-order Boussinesq equation with the surface tension. Theoretical analysis confirms that the proposed scheme achieves second-order accuracy in temporal discretization and fourth-order accuracy in spatial discretization. The solvability, convergence, and stability of the difference scheme are rigorously established through the application of the discrete energy method. Additionally, a series of numerical experiments are conducted to illustrate the effectiveness and reliability of the conservative scheme for long-time simulations.

In this study, we examined the effects of the organizational power resources used by school principals on teachers' work alienation and trait anxiety levels. Then, we examined the mediating role of trait anxiety in the relationship between organizational power resources and work alienation. We used the correlational scanning model and mediation model in the research. The research sample consists of 400 teachers working in Turkish public schools. In our research, "Organizational Power Scale in Schools", "Work Alienation Scale" and "Trait Anxiety Scale" were used. As a result of the research, we found significant relationships between the variables. Accordingly, there is a positive relationship between trait anxiety and work alienation, a positive relationship between trait anxiety and coercive power and legal power, a negative relationship between trait anxiety and expert, charismatic and reward power, a positive relationship between work alienation and coercive power, and a positive relationship between work alienation and reward power. Negative relationships were observed between expertise and charismatic power. Finally, it was determined that trait anxiety had a mediating role in the relationship between the power resources used by school principals and the level of work alienation of teachers.

The monitoring of fog density is of great importance in meteorology and its applications in environment, aviation and transportation. Nowadays, vision-based fog estimation from images taken with surveillance cameras has made a great supplementary contribution to the scarcely traditional meteorological fog observation. In this paper, we propose a new Random Forest (RF) approach for image-based fog estimation. In order to reduce the impact of data imbalance on recognition, the StyleGAN2-ADA (generative adversarial network with adaptive discriminator augmentation) algorithm is used to generate virtual images to expand the data of low proportions. Key image features related to fog are extracted, and an RF method, integrated with the hierarchical and k-medoids clustering, is deployed to estimate the fog density. The experiment conducted in Sichuan in February 2024 shows that the improved RF model has achieved an average accuracy of fog density observation to 93%, 6.4% higher than the RF model without data expansion, 3%-6% higher than the VGG16, the VGG19, the ResNet50, and the DenseNet169 with or without data expansion. What is more, the improved RF method exhibits a very good convergence as a cost-effective solution.

The temperature sensors play important roles in wide spreading human activities. Non-contact method has great advantages, but the detection precision encounters big challenge. In this work, a double-layer asymmetric terahertz (THz) metamaterial combined with phase transition oxide was proposed to realize non-contact temperature sensor with high sensitivity. The metamaterial exhibits band-stop filtering effects in the simulated transmission spectra. Temperature changes induce a reversible phase transition in VO2, resulting in altered conductivity. Numerical results indicate that the S21 parameter increases from -44.33 dB to -4.78 dB at a frequency of 1.22 THz as the conductivity of the VO₂ film increases from 10 to 5000 S/m, achieving a modulation depth of 89%. This work provide a great insights for the development of metamaterials based high-precision temperature measurement.

Background/Objectives: Post traumatic growth (PTG) has the potential to draw positive consequences from trauma. Hence, the interest of finding ways to promote PTG. Research has identified an attentional bias towards positive resilience-related words (e.g., “persistence”, “purpose”) in university students who report high PTG after experiencing adversities. Although people can respond to these experiences by showing low PTG, this bias seems to help with their struggle by making purposeful contents more accessible. Therefore, boosting attentional bias towards positive resilience-related words could help people with low PTG. Methods: In this study, the participants were thirty-six university students who had experienced bullying before entering university. Using a Stroop emotional task, they identified the color of resilience and neutral words, either positive or negative, before and after being submitted to transcranial direct current stimulation. Stimulation was targeted at the right temporal area involved in intentionality processing. Results: In the anodal condition, the results support a stimulation effect on the resilience attentional bias that could benefit participants with low PTG. A significant moderation of approach motivation for this effect was also found. Specifically, only when participants had medium or high approach motivation, did stimulation boost the attentional bias in students with low PTG. Conclusions: These results support that tDCS stimulation in this brain area is effective in enhancing resilience attentional bias in low PTG students. However, for this effect to occur it is necessary to have approach motivation, which is motivation related to goals.

Digitized heritage is regarded as an emerging field, with existing studies primarily focusing on one case study or technological aspect. Thus, there remains a notable gap in the literature regarding the understanding of how these technologies can be utilized in smart heritage management. Approaches that harness technological advancements to enhance smart management and aid the decision-making process regarding the use of appropriate technology at various heritage sites remain insufficiently explored. To address this gap, this study conducted a cross-case analysis to survey the use of heritage technologies across selected cases to find underlying trends and correlations related to the scale and technology used. The findings of this study provide insights into the nexus of technology integration into heritage management, highlighting the role of tangible heritage documentation technologies. The present study concludes that smart management framework necessitates an ongoing process involving the integration of cultural heritage data, documentation, and the Internet of Things (IoT). IoT facilitates the connectivity of physical items to the internet, thereby supporting the safeguarding and interpretation of cultural heritage knowledge. Such framework operates through a collaboration platform that engages experts, local communities, and tourists to ensure a meaningful and interactive interconnection.

The present study is reviewing leachate models useful for proactive and rehab actions to safeguard surface and subsurface soft water which become even more scarce. Integrated management plans of water basins are of crucial importance since intensively cultivated areas are adding huge quantities of fertilizers affecting surface water basins and groundwater. Aquifers progressively are being nitrified on account of the nitrogen-based fertilizers’ surplus, rendering water for human consumption not potable. Well-tested solute leaching models standalone or part of a model package provide rapid site-specific estimates of the leaching potential of chemical agents, mostly nitrates, below root zone of crops and the impact of leaching towards groundwater. Most of the models examined were process-based or conceptual approach. Nonetheless, empirical prediction models, though rather simplistic and therefore not preferrable, demonstrate certain advantages such as extensive calibration database information requirements, which in many cases is unavailable not to mention stochastic approach and the involving of Artificial Intelligence (AI). Models were categorized according to the porous medium and agents to be monitored. Integrated packages of nutrients’ models are irreplaceable element for extensive catchment to monitor the terrestrial nitrogen balanced cycle and to contribute to the policy making as regards the soft water management.

Prepregs, which are resin-impregnated and expensive composites, are mainly limited to high-end applications within the aeronautical, defence, automotive, and energy sectors. Prepreg technology is mainly protected by under trade secrets resulting in limited studies on recent advancements. A Scopus search revealed 861 articles and 16 reviews for the keywords ‘epoxy’ and ‘prepreg’. However, this was narrowed down to 123 articles and 4 reviews using keywords ‘formula development’ and ‘B-stage’. In this review, the control strategies of B-staging, resin tack, and viscosity and their measuring techniques are discussed. Based on resin impregnation techniques and B-stage control, two approaches are proposed to develop prepreg resin formulations: conventional resin impregnation and viscosity-controlled resin impregnation. The approaches would be extremely useful especially for advancing beyond the existing prepreg applications and developing smart materials and functional composites through advanced resin modification strategies.

Plasmonic-based biosensors have gained prominence as potent optical biosensing platforms in both scientific and medical research, attributable to their enhanced sensitivity and precision in detecting biomolecular and chemical interactions. However, the detection of low molecular weight analytes with high sensitivity and specificity remains a complex and unresolved issue, posing significant limitations for the advancement of clinical diagnostic tools and medical device technologies. Notably, abnormal cholesterol levels are a well-established indicator of various pathological conditions; yet, the quantitative detection of its free form is complicated by its small molecular size, pronounced hydrophobicity, and the necessity for mediator molecules to achieve efficient sensing. In the present study, a novel strategy for cholesterol quantification was developed, leveraging a plasmonic optical readout in conjunction with a highly specific cholesterol-binding peptide (C-pept) as a biorecognition element, anchored on a functionalized silica substrate. The resulting biosensor exhibited an exceptionally low detection limit of 21.95 µM and demonstrated a linear response in the 10-200 µM range. This peptide-integrated plasmonic sensor introduces a novel one-step competitive method for cholesterol quantification, positioning itself as a highly sensitive biosensing modality for implementation within the AVAC platform, which operates using reflective dark-field microscopy.