Plant flavonoids have increasingly paid a close attention to for new antimicrobial agents or adjuvants. In our previous work, it was confirmed that the cell membrane is the major site of plant flavonoids acting on the gram-positive bacteria, and which likely involves the inhibition of the respiratory chain. Inspired by the similar structural and antioxidant characters of plant flavonoids to MKH₂, we deduced that the quinone pool is probably a key target of plant flavonoids inhibiting gram-positive bacteria. To verify this, twelve plant flavonoids with six structural subtypes were preliminary selected, and their MICs against gram-positive bacteria were predicted from the antimicrobial quantitative relationship of plant flavonoids to gram-positive bacteria. The results showed they have different antimicrobial activities. After their MICs against S. aureus were determined using broth microdilution method, nine compounds with the MICs ranged from 2 to 4,096 μg/mL or more than 1,024 μg/mL were eventually selected, and then their MICs against S. aureus were determined interfered with different concentrations of MK-4 and the MKs extracted from S. aureus. The results showed that the greater the antibacterial activities of plant flavonoids were, the more greatly their antibacterial activities decreased along with the increase of the interfering concentrations of MK-4 (from 2 to 256 μg/mL) and MK extract (from 4 to 512 μg/mL), and while those, with the MICs equal to or more than 512 μg/mL, decreased a little or remained unchanged. Especially, under the interference of MK-4 (256 μg/mL) and MK extract (512 μg/mL), the MICs of α-mangostin, a compound with greatest inhibitory activity to S. aureus in these twelve plant flavonoids, increased by 16 times and 8 to16 times, respectively. Based on these above, it was proposed that the quinone pool is a key target of plant flavonoids inhibiting gram-positive bacteria, and which likely involves multiple mechanisms including some enzyme and non-enzyme inhibitions.

Reactions of quinones with compounds containing an amino group can produce a wide variety of addition or substitution products that depend on reactivity of both quinone and amino derivative. 6,7-Dichloropyrido[1,2-a]benzimidazole-8,9-diones undergo selective nucleophilic substitution reaction with different benzohydrazides and α-hydroxy-p-quinone imine derivatives stabilized by strong intramolecular hydrogen bond were isolated. Synthesized compounds represent a combination of several structural motifs: benzimidazole core fused with α-hydroxy-p-quinone imine which contains a benzamido fragment. The protonation/deprotonation processes were investigated in a solution using UV-Vis spectroscopy and 1H NMR titration experiment. X-ray crystallography analysis revealed a set of weak non-covalent interactions such as intra- and intermolecular hydrogen bonds and π-π stacking. Additionally, the redox behavior of 6,7-dichloropyrido[1,2-a]benzimidazole-8,9-dione and its p-imino derivative was investigated in acidic and neutral environment using cyclic voltammetry measurements. Cathode material based on 6,7-dichloropyrido[1,2-a]benzimidazole-8,9-dione could act as potential effective active electrode in aqueous electrolyte batteries, however further optimization is required.

Research interest in the occurrence, distribution, fate, and toxicity of N-(1,3-Dimethylbutyl)-N’-phenyl-p-phenylenediamine (6PPD) quinone, a derivative of the tire amino antioxidant 6PPD in urban environments, has surged. While several studies have found that 6PPD quinone exhibits acute, reproductive, and behavioral toxicity as well as mutagenicity and hepatotoxicity in aquatic and terrestrial animals, its environmental exposure data are fragmented and lack coherence across the source-to-exposure continuum, making it difficult to use for risk assessment and regulatory purposes. The present work developed an aggregate exposure pathway (AEP) framework to integrate the exposure data. An AEP network was developed for the atmospheric deposition of 6PPD quinone from tire wear in the Pearl River Delta, which led to human exposure. The 6PPD quinone research was organized, visualized, and evaluated with pertinent knowledge gaps identified using the weight of evidence assessment. Eight key exposure states were identified, with only two having high confidence levels and three having low confidence levels. Empirical support for the key transitional relationships decreased from High to Low from the source to the target site, indicating an urgent need for downstream mechanistic data. The proposed AEP framework integrated diverse 6PPD quinone research, facilitating a mechanistic understanding of the source-to-outcome continuum, as well as the development of quantitative predictive models for future research and environmental regulation.

: The phenomenon of dark scleral spots postmortem is well-known in forensic pathology, first de-scribed by Sommers in 1833. Despite this, their presence is currently considered a nonspecific sign, and their pathogenesis has received little attention in forensic literature. In recent years, however, preliminary studies have suggested new mechanisms in their pathogenesis and links to specific types of death. This study aims to create a model for studying scleral spots using an animal model. Thirty-three sheep, already slaughtered for food, were used. After decapitation, the heads were transported to an environment with known temperature and humidity. The right eye underwent eyelid excision, while the left eye's eyelids were sutured. Continuous observation for approximately 24 hours was conducted, with brief interruptions to observe the closed eyes. Macroscopic obser-vation revealed dark scleral spots in 100% (20 out of 20) of the open eyes after an average of 240.96± 58,36 minutes. The spots did not appear in any of the closed eyes. Experimental data indicate that, despite the different location compared to human cadavers, this model serves as an excellent ex-perimental framework for studying postmortem scleral spots.

Objective: In this study, we investigated vitamin D, inflammatory hematologic ratios such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), MHR and plasma atherogenic index (PAI) and possible relationships with insulin resistance in children. Methods: A total of 210 individuals, including 96 children with insulin resistance and 114 children without insulin resistance, aged 6-18 years, who were admitted to the Pediatric Endocrinology Outpatient Clinic at Medicine Hospital, Istanbul Atlas University were included in our study. Result: NLR, PLR, SII and MHR were significantly higher in patients with insulin resistance compared to those without. Fasting insulin, PAI, HOMA-IR, HOMA- were significantly higher and QUICKI was significantly lower in patients with insulin resistance compared to those without insulin resistance. NLR, SII and MHR were lower in normal vitamin D groups than the others were (p

The main goal of this study was to pinpoint functional candidate genes associated with multiple economically important traits in Nellore cattle. After quality control, 1 830 genomic regions sourced from 52 scientific peer-reviewed publications were used in this study. From these, a total of 8 569 positional candidate genes were annotated for reproduction, 11 195 for carcass, 5 239 for growth, and 3 483 for morphological traits, and used in the overrepresentation analysis. The significant genes (adjusted p-values<0.05) identified in the overrepresentation analysis underwent prioritization analyses, and an enrichment analysis of the prioritized overrepresented candidate genes was performed. The prioritized candidate genes were: GFRA4, RFWD3, SERTAD2, KIZ, REM2, and ANKRD34B for reproduction, RFWD3, TMEM120A, MIEF2, FOXRED2, DUSP29, CARHSP1, OBI1, JOSD1, NOP58, and LOXL1-AS1 for carcass, ANKRD34B, and JOSD1 for growth traits, and no gene prioritized for morphological traits. The functional analysis pinpointed the following genes: KIZ (plays crucial role in spindle organization, essential in forming a robust mitotic centrosome), DUSP29 (involved in muscle cell differentiation), and JOSD1 (involved in protein deubiquitination, thereby improving growth). The enrichment of the functional candidate genes identified in this study highlights that these genes play an important role in the expression of reproduction, carcass, and growth traits in Nellore cattle.

This experiment aimed to determine the temperature limits beyond which seahorse growth and reproduction become suboptimal due to climate change. Four temperatures (16, 20, 24, and 28°C) were tested to evaluate their effect on juvenile (1-56 days post-parturition (DPP)) and adult (one year old) seahorses. Additionally, the reproductive performance of adults was observed. Another experiment measured oxygen consumption (MO2) in the same age groups and temperatures. Adults showed significantly higher growth rates at 20 and 24°C compared to 16 and 28°C. Adult mortality rates were 0%, 0%, 6.2%, and 62.5% at the respective temperatures. Juvenile growth performance was higher at 20°C and 24°C but significantly lower at 16°C, with survival rates of 8%, 62%, 10%, and 0%, respectively. Oxygen consumption increased with age and temperature, ranging from 106.3±3.1 to 203.3±3.1 μmol O2/g BW/h at 16°C, and from 128.8±3.8 to 273.3±3.1 μmol O2/g BW/h at 28°C. The study highlights that juvenile and adult H. guttulatus have narrow thermal boundaries, beyond which reproduction, growth, and survival are seriously affected. Under climate change, the species appears unable to cope, potentially leading to their rapid disappearance.

Background: Heart failure (HF) with preserved ejection fraction (pEF) has lacked effective treatments for reducing mortality. However, previous studies have found an association between statin use and decreased mortality in patients with HFpEF. The aim of this study was to analyze whether statin therapy is associated with a reduction in mortality in these patients and whether the effect differs according to presence or absence of ischemic heart disease (IHD). Methods: We analyzed data from the National Registry of Heart Failure, a prospective study including patients admitted for HF in Internal Medicine units nationwide. Patients with HFpEF were classified according to the use of statins and differences between two groups were analyzed. A multivariate analysis was performed using Cox regression to assess factors independently related to mortality. Results: 2788 patients with HFpEF were included, 63% of them were women with a mean age of 80.1(±7.8) years. The statin-treated group (40.2%) was younger, with better functional status, and had a more common diagnosis of vascular disease and lower frequency of atrial fibrillation. The most frequent etiology of HF in both groups was the hypertensive one. Nevertheless, ischemic HF was more common in those who received statins (24.8% vs. 9.6%; p

Transient conjugate heat transfer measurements under varying temperature and velocity inlet boundary conditions at incompressible flow conditions were performed for flat plate and ribbed channel geometries. Therefrom local adiabatic wall temperatures and heat transfer coefficients are determined. Those data are analyzed using typical heat transfer correlations, e.g. Nu=CRe^mPr^n determining the local distribution of C and m. It is shown that they are closely linked. A relationship lnC=A−mB is observed with A and B as modeling parameters. They could be related to parameters in log law or power law representations for turbulent boundary layer flows. The parameter m is shown to have a close link to local pressure gradients and therewith near wall streamlines as well as friction factor distributions. A normalization of the C parameter allows to derive a Reynolds analogy factor and therefrom local wall shear stresses.

This paper reviews the ethical issues involved and argues that each of the usual policies for handling conscientious refusals faces serious challenges. Healthcare providers who refuse to provide medical services should be expected to explain their reasons, make prompt referrals, and bear some of the resulting costs or burdens.

Keywords: Financial Performance, Managerial Traits, Nifty 50 Companies, tenure of managers, Age of managers, Gender of Managers

A number of regolith-hosted REE occurrences have recently been discovered in the Esperance region in southern Western Australia. This paper summarizes major characteristics of the REE mineralization and discusses contributing factors and potential controls. The main aim is to explain why there is a lack of highly sought-after ion-adsorption clay type REE deposits across the region despite the presence of the regolith-hosted REE mineralization on a regional scale. Local mineralization mostly occurs as continuous flat-lying enrichment “blankets” within the residual regolith developed over Archaean–Proterozoic granite gneisses and granitoids with elevated REE content. The enriched horizon is commonly located in the lower saprolite and saprock and is accompanied by an overlying REE-depleted zone. This distribution pattern, together with the data on HREE fractionation and the presence of the supergene REE minerals, indicate chemogenic type enrichment formed by supergene REE mobilization into groundwater, downward transport and accumulation in the lower part of the weathering profile. Residual REE accumulation processes due to bulk rock volume and mass reduction during weathering also contribute to mineralization. It is proposed that climate and groundwater chemistry are the critical controls on the distribution of REEs in the weathering profile and on their speciation in the enrichment zone. Cenozoic aridification of climate in southwest Australia heavily overprinted pre-existing REE distributions in the weathering profile. Acidic (pH <4), highly saline groundwaters intensely leached away any relatively weakly bound, adsorbed or colloidal REE forms, moving them downward. Dissolved RREs precipitated as secondary phosphates in neutral to alkaline environment at lower Eh near the base of the weathering profile forming the supergene enrichment zone. Low denudation rates, characteristic of areas of low relief under the arid climate, are favorable for the preservation of the existing weathering profiles with REE mineralization.

In order to apply RAP fine aggregate to High Modulus Asphalt Concrete(HMAC), this study first extracts aged asphalt from RAP fine aggregate through extraction and distillation, and adds it to high modulus modified asphalt in proportions of 20%, 40%, 60%, and 80%. The performance changes of the recycled asphalt were investigated using conventional performance tests and dynamic shear rheological tests (DSR). Microscopic techniques such as four‐component analysis and infrared spectroscopy were employed to explain macroscopic performance changes in terms of component and functional group changes in the asphalt. Using HMAC‐20 gradation as an example, uniaxial compression dynamic modulus tests, rutting tests, freeze‐thaw splitting tests, and low‐temperature bending tests were conducted to evaluate the performance changes of recycled asphalt mixture with different RAP fine aggregate contents through four indices: dynamic modulus, dynamic stability, tensile strength ratio (TSR), and maximum bending strain. The results indicate that for every 20% increase in aged asphalt, the penetration at 25°C, ductility at 25°C, and dynamic viscosity at 60°C decrease by approximately 6.2%, 15.4%, and 3.9%, respectively, while the softening point increases by approximately 13.3%. It is concluded that the addition of aged asphalt significantly affects the ductility at 25°C and the softening point. As the aged content increases, the complex shear modulus (G*) and phase angle (δ) of the recycled asphalt decrease, while the rutting factor increases. The four‐component analysis and infrared spectroscopy of the asphalt demonstrate that the incorporation of aged asphalt is merely a physical blending phenomenon, involving changes in the content of the four components without the formation of new functional groups (new peaks). When RAP fine aggregate is applied to high modulus recycled asphalt mixture, compared to high modulus modified asphalt mixture, the recycled mixtures exhibit higher dynamic modulus and dynamic stability, but significantly reduced water stability and low‐temperature performance.

It’s very well known that the world's attention is currently focused on the energy transition. The energy security, in addition to the drive to reduce greenhouse gas emissions in order to limit global warming, and the generalization of the access to energy, have contributed to adoption of the Moroccan Energy Strategy with a strong focus on Renewable Energies (RE). Morocco is notoriously poor in conventional fossil primary energy resources with an energy dependence on the order of 90%. The energy crisis and that resulted from Covid-19 pandemic and the geopolitical conflicts, combined compounded with steady increase in demand have heavily affected the security and the stability of the country's energy situation. The transition to RE, by strongly engaging in the implementation of several solar, wind and hydro energy projects benefiting from the country's excellent solar and wind energy potential, has made the country the leader in RE in Africa. By 2030, the share of RE in the installed capacity is expected to reach 52%. In this work, an overview of the current situation of RE (particularly solar energy) in Morocco is provided, including, the potentials, obstacles and challenges, and future perspectives. Thanks to its high solar potential location, it’s predictable that Morocco effort will be focused on this field: the Erasmus Plus Innomed Project is a virtuous example of international cooperation, aiming at create a Solar Energy Network, in synergy with EU Partners.

Background: Dosimetric predictors of brain necrosis (BN) have not yet been established for fractionated stereotactic radiotherapy (SRT). Methods: Multivariate logistic models were developed for comprehensive analyses of dosimetric predictors in patients who received first-line fractionated SRT for brain metastases (BMs). The normal brain volume receiving a xx Gy biological dose in 2 Gy fractions (VxxGyE) was calculated from the retrieved dose-volume parameters. Results: Three-fraction SRT was delivered to 34 patients with 74 BMs (mean target volume, 4.3 cc), 5-fraction SRT to 58 with 106 BMs (15.4 cc), and 10-fraction SRT to 20 with 35 BMs (25.9 cc) according to protocols depending on the target volume (p <0.001). In the 5- and 10-fraction groups, the incidence of symptomatic BN was significantly higher in patients with a larger V50GyE (odds ratio: 1.07, p <0.02), V55GyE (1.08, p <0.01), or V60GyE (1.09, p <0.01). The incidence of BN was also significantly higher in cases with V55GyE >30 cc or V60GyE >20 cc (p <0.05). Conclusion: In 5- or 10-fraction SRT, at least V55GyE ≤30 cc or V60GyE ≤20 cc should be maintained to lower the risk of BN.

As the number of Uncrewed Aircraft Systems (UAS) operating in our National Airspace System (NAS) increases, so do UAS operations near or at an airport. The accelerating technology in Advanced Air Mobility (AAM) along with the related business opportunities will only further increase UAS operations at airports. This continued growth in new UAS technologies and applications introduces new hazards and risks to the airport environment. This proliferation of UAS highlights the importance of airports developing a robust Safety Management System (SMS) that includes specific UAS risk mitigations. To date, there is currently little empirical data regarding UAS traffic around airports. Nor is there a system to collect this data at a national level. This study attempted to gain insight into the commercial UAS operations across a broader airport population by surveying the airport manager population here in the United States. Research results found that 62% of airports are experiencing an increase in UAS operations in their surrounding airspace. This increase applies to all airspace classifications, with 67% of airports located in controlled airspace experiencing an increase in UAS operations. However, only 27% of airports have some type of UAS safety plan. Similarly, the increase in adverse UAS events near airports suggests that UAS operators may also lack robust safety plans or an understanding of the risks and regulations associated with operating near airports.

Chip pad alignment inspection is of great importance in the industrial field. However, due to the fact that chip pads are usually small, problems such as misdetection and missed detection often occur. When applying deep learning methods for chip pad detection, it is necessary to ensure accurate detection of small target chips while meeting the requirements of lightweight detection models for industrial needs. To solve the above problems, this paper proposes a lightweight model based on improved YOLOv5s. Firstly, the feature extraction part is improved to increase the network's focus on the target. Secondly, the feature fusion layer is improved to double the resolution of the prediction head, and the context-aware network is designed to enhance the context-capture ability of key features of small targets. Finally, SIoU is adopted as the loss function to improve the speed and accuracy of the regression frame. The experimental results show that the improved YOLOv5s algorithm improves the detection accuracy by 2.3% and reduces the network parameters by 81.8% compared to the original algorithm. The improved algorithm is combined with image processing techniques to design correction methods for alignment anomalies and realize real-time alignment anomaly correction in industry.

This study evaluated the presence of Human Papillomavirus (HPV) and Bovine Leukemia Virus (BLV) DNA in breast cancer (BC) samples from women in Northeastern Brazil. We analyzed 186 formalin-fixed, paraffin-embedded tissue block samples using PCR and qPCR to detect HPV and BLV DNA. BLV DNA was not detected in any BC patients. However, HPV DNA was found in 46.2\% of the BC samples: 44.6\% were positive for HPV16, 3.5\% for HPV31, and 2\% were coinfected with HPV16 and HPV31. Additionally, we found an association between HPV-positive BC and Ki-67 expression (P=0.03, OR=1.85; CI=1.02-3.34), as well as between HPV31-positive BC and mitotic index (P=0.047). Although BLV was not detected in BC patients from Northeastern Brazil, the association between HPV and cell proliferation markers warrants further investigation, as HPV may contribute to the aggressiveness of BC in these patients.

Inflammatory bowel diseases (IBD) involve chronic inflammation of the gastrointestinal tract, where effector CD4+ T-cells play a central role. Thereby, the recruitment of T-cells into the colonic mucosa represents a key process in IBD. We recently found that CCR9 and DRD5 might form a heteromeric complex on the T-cell surface. The increase of CCL25 production and the reduction in dopamine levels associated with colonic inflammation represent a dual signal stimulating the CCR9:DRD5 heteromer, which promotes the recruitment of CD4+ T-cells into the colonic lamina propria. Here, we aimed to analysing the molecular requirements involved in the heteromer assembly as well as to determining the underlying cellular mechanisms involved in the colonic tropism given by the stimulation of the CCR9:DRD5 complex. The results show that dual stimulation of the CCR9:DRD5 heteromer potentiates the phosphorylation of the myosin light chain 2 (MLC2) and the migration speed in confined microchannels. Accordingly, disrupting the CCR9:DRD5 assembly induced a sharp reduction in the pMLC2 in vitro, decreased the migratory speed in confined microchannels and dampened the recruitment of CD4+ T-cells into the inflamed colonic mucosa. Furthermore, in silico analysis confirmed that the interface of interaction of CCR9:DRD5 is formed by the transmembrane segments 5 and 6 from each protomer. Our findings demonstrated that the CCR9:DRD5 heteromeric complex plays a fundamental role in the migration of CD4+ T-cells into the colonic mucosa upon inflammation. Thereby, disassembling the formation of the CCR9:DRD5 represents an important therapeutic opportunity to treat IBD.

To evaluate dryland wheat genotypes' performance to different pre-crop and residue management under dryland conditions, a split-split plot experiment based on RCB design with three replications was conducted for two years (2017-2018 and 2018-2019). The site of study's long-term average precipitation, temperature, and relative humidity are 376 mm, 9 ◦C, and 50%, respectively. Wheat-wheat and vetch-wheat cropping systems were considered in the main plots, different wheat and vetch residue levels including 0, 2, and 4 t ha-1 were located in subplots, and five dryland wheat genotypes including Sadra, Hashtroud, Baran, Varan, and Ohadi were allocated in sub-sub plots. Results indicated that leaf chlorophyll content index (CCI) and stomatal conductance (gs) were greater in the vetch-wheat cropping system compared to the wheat monoculture system for all genotypes. Normalized differences vegetative index (NDVI) of genotypes improved by applying the crop residue. Over two years, the application of crop residues resulted in higher variable fluorescence at J and I steps as well as an increase in the photosynthesis performance index (PI). Varan and Baran genotypes stood out as the superior genotype, exhibiting the highest values physiological characteristics and grain yield under the application of 4 t ha-1 of vetch residue. Grain filling rate (GFR) was reduced, while grain filling duration (GFD) was increased with increasing the crop residue levels. The enhanced grain yield of wheat genotypes grown under vetch residue attributed to the factors such as improvement in leave pigments and photosynthetic efficiency which facilitate longer grain filling duration with high grain weight. As a result, it is advisable to adopt a vetch-wheat cropping system with a high proportion of crop residue in dryland regions to achieve increased and sustainable wheat production.

Traditional painting artefacts study and documentation face the limitations of well-known recording tools and methods, such as handwritten or digital descriptions, scaled 2D drawings in situ, measurements with calipers, rulers or tape measures, sketches, tracings, as well as conventional or technical photographs. This paper advocates Close-Range Photogrammetry (SfM-MVS) and Reflectance Transformation Imaging (RTI) for recording vital morphological and 2.5D geometric features of painted surfaces with high accuracy. These digital tools, widely accessible due to increased computing power, enhance art observation, material study and conservation assessment. Despite specialized alternatives like 3D laser scanners, the focus here is on the cost-effective SfM-MVS and RTI, which offer advanced pixel colour accuracy. The ability to reproduce photorealistic textures proves essential for accurate documentation of painted artefacts. The paper showcases promising results from applying these methods to a mural from the Palace of Tiryns, justifying their fundamental role in an integrated scientific art study methodology.

Image captioning aims at generating meaningful verbal descriptions of a digital image. Our paper focuses on the classic encoder-decoder deep learning model that consists of several components – sub-networks, each performing a separate task that, combined, form an effective caption generator. We investigate image feature extractors, recurrent neural networks, word embedding models, and word generation layers and discuss how each component influences the captioning model’s overall performance. Our experiments are performed on the MS COCO 2014 dataset. The results help design efficient models with optimal combinations of their components.

Cardiovascular disease is a leading cause of morbidity and mortality. New research elucidates in-creasingly complex relationships between cardiac and metabolic health, giving rise to new possible therapeutic targets. Sphingolipids are a heterogenous class of bioactive lipids with critical roles in normal human physiology. They have also been shown to play both protective and deleterious roles in the pathogenesis of cardiovascular disease. This review will explore the roles of Sphingolipids in vascular, cardiac, and metabolic pathologies and will evaluate the therapeutic potential in targeting Sphingolipids with the aim of prevention and reversal of cardiovascular disease, in order to improve long-term cardiovascular outcomes.

The application of AI technology in urban planning covers multiple levels, such as data analysis, decision support, and automated planning. Urban research relies on AI technology to understand and summarize the law of urban growth and improve the analysis of the evolution trend of urban space. Planning and design use AI technology to explore the relevant factors affecting urban development and their weights and discuss the critical role of green building technology in the sustainable development of the construction industry. With the increase in global energy consumption and carbon emissions, traditional building methods can no longer meet environmental protection requirements and efficient use of resources. As a sustainable development solution, green building technology has been paid more and more attention to and adopted by people. These technologies focus not only on the energy efficiency and environmental impact of buildings but also on the resource utilization and environmental load of green buildings over their entire life cycle driven by machine learning. This paper details the basic principles and applications of green building technologies, including AI-driven reduction of negative environmental impacts, improvement of occupant health, efficient use of resources, and optimization of indoor environmental quality. This paper focuses on the critical role of the LEED assessment system developed by the U.S. Green Building Council in advancing green building practices. In addition, the paper analyzes vital points such as water use in green building design, machine learning-driven wind environment optimization, solar technology application, and practical application cases of these technologies on a global scale.

Costa Rica, despite its global recognition for environmental sustainability, is grappling with a critical waste management crisis that threatens its ecological and public health achievements. This study provides a comprehensive analysis of Costa Rica's waste management system, focusing on the acute challenges in urban areas like San José, where nearly 47% of the nation’s waste is generated. The research highlights significant issues, including inadequate landfill capacities, low recycling rates, and regional disparities in waste management practices. Employing a hybrid modeling approach that integrates Linear Regression and ARIMA models, the study forecasts trends in waste minimization practices from 2024 to 2050, underscoring the importance of public engagement in recycling programs. Key findings reveal that Costa Rica's recycling rate remains alarmingly low at 9.6%, far below the global average and significantly less than countries like Germany and South Korea. The analysis critiques current government initiatives, such as the Environmental Health Route policy and the National Circular Economy Strategy, noting their limited success in improving recycling rates, particularly in rural areas. The study underscores the necessity for enhanced infrastructure, targeted public education, and the adoption of innovative technologies like AI and blockchain to achieve sustainable waste management. The findings contribute valuable insights for policymakers and stakeholders, offering strategic recommendations to bolster Costa Rica's efforts in aligning with global best practices and advancing its environmental sustainability goals.

In this paper, we introduce generalized entropy, the acceleration of its entropy and its the partial entropy. We assume that generalized entropy can be expressed as a second-order polynomial by applying the idea of logistics function to its entropy. In other words, we assume that the acceleration of generalized entropy is a constant. Besides, we show that the inverse of the partial entropy can express Newton's classical gravity, which is an inverse square law. By applying these concepts, we attempt to explain that 1) Gravity is constant within small distances with some conditions, It is possible that there exists 6-states within the distance R is small. Furthermore, within small distance, we show the possibility that the gravitational potential and the Coulomb potential can be treated in the same way. that 2) The rotation speed of a galaxy does not depend on its radius if the radius is within the size level of the universe. (the galactic rotation curve problem), and that 3) The gravitational acceleration toward the center changes at long distances compared to the classical theory of gravity. Furthermore, we show that the possibility of the existence of some constants which controls gravity and the speed of galaxies, and that gravity may relate on entropy.

The purpose of this manuscript is to examine the extent to which Polish SMEs use digital marketing tools in the context of their impact on economic performance. The choice of the objective is due to the research gap related to the lack of studies on the impact of the use of digital marketing tools on economic performance by SME companies in Poland. In order to achieve the objective, a two-stage approach was used. The first stage identified the degree of use of digital marketing tools by Polish SMEs compared to EU countries based on secondary data. The second stage analyzed the impact of the use of selected digital marketing and sales communication tools on the economic performance of Polish SMEs. The analysis was based on primary data, which were the results of surveys conducted on a sample of 574 Polish SMEs in the industrial sector. The analysis used statistical methods such as difference significance tests (Mann-Whitney U test, ANOVA Kruskal-Wallis test and Dunn's post-hoc tests), Kendall's rank correlation coefficient and Multivariate Adaptive Regression Splines (MARSplines). The results obtained have theoretical and practical values. The theoretical implications are the enrichment of the marketing concept of customer value creation taking into account the digital customer, which is also the originality of the research. Practical implications refer to indicating to SME managers the need for, as well as ways of implementing and financing digital technologies within the framework of various EU programs for digital transformation of member states.

The high spatial complexities of soil temperature modelling over semiarid land have challenged the calibration—predication framework, whose composited objective lacks comprehensive evaluation. Therefore, this study, based on the Noah land surface model and its full parameter table, utilizes two global searching algorithms and eight kinds of objective with dimensional—varied metrics, combined with dense site soil moisture and temperature observations of central Tibet, to explore different metrics’ performances on the spatial heterogeneity and uncertainty of regional land surface parameters, calibration efficiency and effectiveness, as well as spatiotemporal complexities in surface forecasting. Results have shown that metrics’ diversity has shown greater influence on the calibration—predication framework than the global searching algorithms themselves. Besides being significantly better than other metrics, the enhanced multi objective metric (EMO) and the enhanced Kling-Gupta efficiency (EKGE) have their own advantages and disadvantages in simulations and parameters respectively. Especially, EMO that composited with four metrics as correlated coefficient, root mean square error, mean absolute error, and Nash–Sutcliffe efficiency, has shown relatively balanced performance in surface forecasting when compared to EKGE. In general, the calibration—predication framework that benefited from EMO could greatly reduce the spatial complexities in soil temperature modelling of the semiarid land.

Determining the estrous cycle stages in mice is essential for optimizing breeding strategies, synchronizing experimental time lines, and facilitating studies in behavior, drug testing, and genetics. It is critical for reducing the production of genetically unmodified offspring in the generation and investigation of genetically modified animal models. An accurate detection of the estrus cycle is particularly relevant in the context of the 3Rs—Replacement, Reduction and Refinement. The estrous cycle, encompassing the reproductive phases of mice, is key to refining experimental designs and addressing ethical issues related to the use of animals in research. This study presents results from two independent laboratories on the efficacy of the Mouse Estrus Detector (MED) from Elmi Ltd. (Latvia) for the accurate determination of the estrus phase. The female mice of five strains/stocks (CD1, FVB/N, C57Bl6/J, B6D2F1, and Swiss) were used. The results showed that the MEDProTM is a low -traumatic, simple, rapid and painless method of estrus detection that supports the principles of the 3Rs. The use of the MEDProTM for estrus detection in mice caused minimal stress, enhanced mating efficiency, facilitated an increase in the number of embryos for the in vitro fertilization and allowed the production of the desired number of foster animals.

Building on swampy land is a major challenge due to the soft and waterlogged soil properties. Traditional approaches using wooden pile foundations have long been used but new technology with a more environmentally friendly and efficient approach needs to be applied to swampy land. The objectives of this research are: to obtain a conceptual model of modified wooden pile foundation construction combined with concrete, to identify the impact of soil condition changes due to foundation implementation and the swampy groundwater environment, and to determine the application of the 'constructed wetland' and rain garden adaptation methods to the foundation model concept.In this research, a qualitative method was used with a descriptive approach based on literature studies and data collection through surveys/field observations. There is interdisciplinary collaboration from architectural, material, and environmental fields. The method conducted includes experimental testing of the foundation model concept. The research stages are: identifying variations in foundation design on wetland, survey/field study observation of foundations in Banjarmasin, architectural-material-environmental analysis of the foundation model concept with rain garden adaptation, and finally, conclusions and suggestions.The rain garden concept is an innovation that can help address waterlogging issues by enhancing the improvement of foundation construction and drainage in swampy soils. In this paper, the use of galam wood, wooden pile foundations, and construction technology innovations to improve swampy soil conditions are discussed in detail.

Dextro-transposition of the great arteries (D-TGA) is a critical congenital heart defect that can impact neurodevelopment due to cerebral perfusion and oxygenation disorders. Materials and Methods: In a retrospective study conducted at a tertiary center between 2016 and 2023, we investigated the early effects of Prostaglandin E1 (PGE1) administration and balloon atrial septostomy (BAS) on cerebral blood flow and oxygenation in inborn neonates with D-TGA. Cerebral Doppler Ultrasound in the anterior cerebral artery (ACA) was performed to assess resistive index (RI), Peak Systolic Velocity (PSV), and End-Diastolic Velocity (EVD) before PGE1, before the BAS procedure and 24 hours after birth. Cerebral regional saturations of oxygen (crSO2) and cerebral fractional tissue oxygen extraction (cFTOE) were evaluated. D-TGA patients were divided into the PGE1 group and the PGE1+BAS group. Age-matched healthy controls were used for comparison. Results: All 83 D-TGA newborns received PGE1 within two hours after delivery, of whom 46 (55.42%) underwent BAS. 77 newborns composed the control group. PGE1 administration increased crSO2 from 47% to 50% in the PGE1 group but lower than in controls at 24 hours of life, while cFTOE remained elevated. The RI increased 24 hours after delivery (0.718 vs. 0.769; p=0.000002) due to decreased EDV (10.71 vs. 8.74; p<0.0001) following PGE1 treatment. The BAS procedure resulted in a significant increase in crSO2 from 42% to 51% at 24 hours of life in the PGE1+BAS group. Doppler parameters exhibited a similar trend as observed in the PGE1 group. Conclusion: PGE1 treatment and BAS are lifesaving interventions that may improve cerebral perfusion and oxygenation in newborns with D-TGA during the transition period.

With the rapid consumer adoption of mobile devices such as tablets and smart phones, the tele-traffic has experienced a tremendous growth, low power technologies are highly desirable for future communication networks. In this paper, we consider an ambient backscatter (AB) based user cooperation (UC) scheme for mmWave wireless powered communication networks (WPCN) with lens antenna arrays. Firstly, we formulate an optimization problem to maximize the minimum rate of two users by jointly designing power and time allocation. Then we introduce auxiliary variables and transform the original problem into a convex form. Finally, we propose an efficient algorithm to solve the transformed problem. Simulation results demonstrate that the proposed AB based UC scheme outperforms the competing schemes, thus improve the fairness performance of throughput in WPCN.

Understanding the structural intricacies of RNA molecules is essential for deciphering numerous biological processes. Traditionally, scientists have relied on experimental methods to gain insights and draw conclusions. However, the recent advent of advanced computational techniques has significantly accelerated and refined the accuracy of research results in several areas. A particularly challenging aspect of RNA analysis is the prediction of its secondary structure, which is crucial for elucidating its functional role in biological systems. This paper deals with the prediction of pseudoknots in RNA, focusing on two types of pseudoknots: K-type and M-type pseudoknots. Pseudoknots are complex RNA formations in which nucleotides in a loop form base pairs with nucleotides outside the loop and thus contribute to essential biological functions. Accurate prediction of these structures is crucial for understanding RNA dynamics and interactions. Building on our previous work in which we developed a framework for the recognition of H- and L-type pseudoknots, an extended grammar-based framework tailored to the prediction of K- and M-type pseudoknots is proposed. This approach uses syntactic pattern recognition techniques and provides a systematic method to identify and characterize these complex RNA structures. Our framework uses context-free grammars (CFGs) to model RNA sequences and predict the occurrence of pseudoknots. By formulating specific grammatical rules for type K and type M pseudoknots, we enable efficient parsing of RNA sequences to recognize potential pseudoknot configurations. This method ensures an exhaustive exploration of possible pseudoknot structures within a reasonable time frame. In addition, the proposed method incorporates essential concepts of biology, such as base pairing optimization and free energy reduction, to improve the accuracy of pseudoknot prediction. These principles are crucial to ensure that the predicted structures are biologically plausible. By embedding these principles into our grammar-based framework, we aim to predict RNA conformations that are both theoretically sound and biologically relevant.

The abstract should be a total of about 250 words and structured to contain the following headings: Background/Objectives, Methods, Results, Conclusions. Background/Objectives: Place the question addressed in a broad context and highlight the purpose of the study; Methods: Describe briefly the main methods or treatments applied. Include any relevant preregistration numbers, and species and strains of any animals used; Results: Summarize the article’s main findings; Conclusions: Indicate the main conclusions or interpretations. The abstract should be an objective representation of the article: it must not contain results which are not presented and substantiated in the main text and should not exaggerate the main conclusions. Clinical trial abstracts should include items that the CONSORT group has identified as essential.

Triple-negative breast cancer (TNBC) lacks the expression of estrogen receptors, human epidermal growth factor receptor 2, and progesterone receptors (PR). TNBC has the poorest prognosis among breast cancer subtypes and is more likely to respond to immunotherapy due to its higher expression of PD-L1 and a greater percentage of tumor-infiltrating lymphocytes. Immunotherapy has revolutionized TNBC treatment, especially with the FDA's approval of pembrolizumab (Keytruda) combined with chemotherapy for advanced cases, opening new avenues for treating this deadly disease. Although, immunotherapy can significantly improve patient outcomes in a subset of patients, achieving the desired response rate for all remains an unmet clinical goal. Strategies that improve responses to immune checkpoint blockade, including combining immunotherapy with chemotherapy, molecularly targeted therapy, or radiotherapy may improve response rates and clinical outcomes.  In this review, we provide a short background on TNBC and immunotherapy and explore the different types of immunotherapy strategies that are currently being evaluated in TNBC. Additionally, we review why combination strategies may be beneficial, provide an overview of the combination strategies, and discuss the novel immunotherapeutic opportunities that may be approved in the near future for TNBC.

Economic, social, and environmental sustainability are the results of efforts aiming to improve all aspects of milk production, respecting animal welfare and improving herd health. An epidemi-ological study was designed to assess the role of contagious pathogens (S. aureus and S.agalactiae) in a cohort of 120 dairy herds located in the southern regions of Italy. Milk quality was assessed using certified methods, and the prevalence of mastitis pathogens in bulk tank milk was determined using quantitative polymerase chain reaction. Welfare scores were assessed using a scoring card that have more than 100 items, including animal-based measurements. Statistical analyses were performed using general lineal model and logistic regression procedures. The results showed that S. aureus had a significant negative effect on the amount of milk components delivered to the dairy plant, and on the level of welfare. Whereas, the presence of S.agalactiae did not show any significant association. The major risk factors associated with the presence of S.aureus were also identified to help prioritise control programs. These results support the “One Sustainability” approach im-plying that an increase of animal productivity is related to the improvement of animal health and welfare and potentially leading to the mitigation of greenhouse gas emissions.Economic, social, and environmental sustainability are the results of efforts aiming to improve all aspects of milk production, respecting animal welfare and improving herd health. An epidemi-ological study was designed to assess the role of contagious pathogens (S. aureus and S.agalactiae) in a cohort of 120 dairy herds located in the southern regions of Italy. Milk quality was assessed using certified methods, and the prevalence of mastitis pathogens in bulk tank milk was determined using quantitative polymerase chain reaction. Welfare scores were assessed using a scoring card that have more than 100 items, including animal-based measurements. Statistical analyses were performed using general lineal model and logistic regression procedures. The results showed that S. aureus had a significant negative effect on the amount of milk components delivered to the dairy plant, and on the level of welfare. Whereas, the presence of S.agalactiae did not show any significant association. The major risk factors associated with the presence of S.aureus were also identified to help prioritise control programs. These results support the “One Sustainability” approach im-plying that an increase of animal productivity is related to the improvement of animal health and welfare and potentially leading to the mitigation of greenhouse gas emissions.

The construction industry is an important part of the national economic market of various countries; since 2013, the construction industry's added value in the gross domestic product has been more than 6%, reaching 6.89% in 2022, and is a pillar industry of the national economy. Intelligent construction is the realistic demand to promote the high-quality development of China's construction industry. It is the key focus of transforming and upgrading the traditional construction industry to information, digital, and intelligent. As a new production factor, construction robots have become the key to promoting intelligent construction. Under the guidance of various national and industry policies, thanks to China's huge construction market volume and rich application scenarios, many innovative and entrepreneurial entities have entered the field of construction robots. Architectural visualization is a crucial aspect of architectural design and communication. With the development of science and technology, artificial intelligence (AI) technology is increasingly becoming an essential tool for architectural visualization and communication. The emergence of AI technology has provided architects with more flexible and creative ways to present design ideas. All along, designers who love architecture have been passionate about exploring better solutions for architecture, but there is never an optimal solution for architectural design; AI is the fire of the future era; it brings us more opportunities but also forces us to face new challenges from the future.

This work focuses on the theoretical study of the effect of entanglement in the Yttrium Barium Copper Oxide (YBCO) superconductor on the critical current density, critical magnetic field, and penetration depth. Using the Ginzburg Landau (GL) theory, the expression for the GL coherence length, the critical current density, the lower critical magnetic field (Hc1), and the upper critical magnetic field (Hc2) for the entangled superconducting YBCO was obtained. At zero external magnetic fields, YBCO was found to undergo a transition from the normal state to the superconducting state at 93K and returned to normal. We found a direct relationship between the GL coherence length penetration depth and the temperature of the entangled superconducting YBCO. The graphs of the lower critical magnetic field (Hc1) and critical current density against temperature show a non-linear dependence.In contrast, the graph of the upper critical magnetic field (Hc2) against temperature (T) shows the linear dependence, which is in agreement with existing theoretical observations. On the other hand, the graph of critical current density against the distance of separation between the entangled electrons that form a cooper pair showed that the critical current density increases between 1.8 and 6 nanometers attaining a constant value after reaching 7 nanometers for infinite distances. Finally, for lower critical fields, the magnetic field decreases between 1.5 to 6 nanometers attaining a constant value of the magnetic field, for infinite values of distance of separation between the entangled pair of electrons

We report the case of a 45-year-old Caucasian man who was treated upfront with brentuximab vedotin (A) and doxorubicin, vinblastine, and dacarbazine (AVD; A+AVD) for advanced-stage classical Hodgkin's lymphoma (cHL). Right after completing the 6th cycle of induction therapy, he developed serotine fever, progressive clinical deterioration, symptomatic splenomegaly and se-vere anemia. Extensive infectious disease evaluations and serial PET scans were conducted to rule out lymphoma progression. Finally, a diagnosis of visceral leishmaniasis (VL) was performed. The patient was treated with parenteral amphotericin B, with rapid and complete resolution of clinical and laboratory abnormalities. We described this rare case of infectious complication after A+AVD delivered for cHL, and we performed a comprehensive review of the literature on the occurrence of VL in the context of non-HL and cHL, since this infection is becoming increasingly prevalent in non-tropical countries.

(1) Background: Food waste (FW) in Romania is 70 Kg/capita/year, while 70% of food waste comes from public catering, retail services, and households (over 50% – 47 million tons). (2) Methods: A cross-sectional observational study was conducted using an online questionnaire via the Google Forms platform from 15 April 2023 to 15 May 2023. The questionnaire was designed to assess various aspects, such as some socio-demographic information (age, sex, occupation, area of residence, study level, household members number, children < 18 years of age); the personal involvement and frequency of food purchases and homemade food cooking; the main sources that generate food waste; the motivation and frequency with which food waste occurs; the level of awareness regarding the impact of food waste; the respondents' intentions regarding sustainable behaviors and practices food management; the level of information and familiarity of the respondents with the notions of validity and how these may influence their food consumption decisions. (3) The results show that FW incidence is occasionally (42%), very rarely (43.33%), frequently (15%), and no food waste was reported by 2.66% of respondents. The [35-44] age category records the highest FW frequency, followed by [18-24]. The most wasted are homemade food (29.67%), bread and bakery products (27.00%), and fruits and vegetables (14.33%). High involvement in purchasing and buying food following a previously established list reduces FW frequency. The same is valid for high daily involvement in food and homemade cooking. High interest in the FW problem and its perception as a waste of money leads to diminishing it, while guilty feelings increase the FW level (37.50% to 73.33%). (4) Conclusions: The present study shows that household food waste management is a multifactorial process that involves numerous socio-demographic, behavioral, and emotional aspects. Extensive data analysis supports our results, revealing deep self-reported information details and confirming its complex approach.

Mega sporting events play a pivotal role in enabling host cities to stimulate urban regeneration and improvement. Numerous studies have examined the impact of mega sporting events from various perspectives; however, studies regarding residents’ perceptions of such events, particularly in the context of a global pandemic, are lacking. Therefore, this study examined the perceived benefits of the Beijing 2022 Winter Olympic Games on city image, satisfaction, and loyalty. Data were collected from 868 local residents of Beijing and Zhangjiakou, the venues for the 2022 Beijing Olympics. For data analysis, structural equation modelling was conducted using IBM SPSS 29.0 and AMOS 29.0. The findings revealed a significant impact of economic, environmental, and tourism benefits on city image, in contrast to no impact from perceived sociocultural benefits. Additionally, city image significantly influenced city satisfaction and loyalty. Therefore, in exceptional situations such as the COVID-19 pandemic, host cities should focus on developing economic, environmental, and tourism resources from a long-term perspective.

Preventing COVID-19 in Gaza is crucial due to the devastation of advanced health services infrastructure by war. Despite the high protection offered by COVID-19 vaccines against severe disease, a 2021 survey in Gaza found only half of the population vaccinated and one-third vaccine hesitant. This follow-up study conducted in March 2023 aimed to re-evaluate vaccination levels, hesitancy, exposure to vaccine promotion efforts, and other risk factors in Gaza. A community-based cross-sectional survey with multistage stratified sampling was used. Associations of primary exposures and other determinants with vaccine status and hesitancy were quantified using bivariate and multivariate logistic regression. In 2023, 63.5% of adults received at least one vaccine dose compared to 49.1% in 2021. Vaccine hesitancy prevalence was 31.7% in 2023 versus 34.1% in 2021 (p=0.395). Adjusted odds of vaccination were 4.2 times higher among those referred by health workers compared to those not referred. Adjusted odds of vaccine hesitancy among those who received information on the vaccine from health workers were 0.3 times that of people who did not receive information. Results suggest health workers could play a crucial role in future vaccination strategies, as their vaccine promotion efforts were linked to better vaccine outcomes. Investing in the skills development of community health workers to contribute to these efforts is recommended.

Growth monitoring of crops is a crucial aspect of precision agriculture, essential for optimal yield prediction and resource allocation. Traditional crop growth monitoring methods are labor-intensive and prone to errors. This study introduces an automated segmentation pipeline utilizing multi-date aerial images and ortho-mosaics to monitor the growth of cauliflower crops (Brassica Oleracea var. Botrytis) using an object-based image analysis approach. The methodology employs YOLOv8, Grounding Detection Transformer with Improved Denoising Anchor Boxes (DINO), and the Segment Anything Model (SAM) for automatic annotation and segmentation. The YOLOv8 model was trained using aerial image datasets, which then facilitated the training of the Grounded Segment Anything Model framework. This approach generated automatic annotations and segmentation masks, classifying crop rows for temporal monitoring and growth estimation. The study’s findings utilized a multi-modal monitoring approach to highlight the efficiency of this automated system in providing accurate crop growth analysis, promoting informed decision-making in crop management and sustainable agricultural practices. Results indicate consistent and comparable growth patterns between aerial images and ortho-mosaics, with significant periods of rapid expansion and minor fluctuations over time. The results also indicated a correlation between the both the time and method of observation which paves a future possibility of integration of such techniques aimed at increasing the accuracy in crop growth monitoring based on automatically derived temporal crop row segmentation masks.

Vaginitis is a widespread issue for women worldwide, yet current diagnostic tools are lacking. Bacterial vaginosis (BV) is the most prevalent type of vaginitis, found in 10-50% of reproductive aged women. Current diagnostic methods for BV rely on clinical criteria, microscopy, or detection of a few microbes by qPCR. However, many vaginal infections lack a single etiological agent and are characterized by changes in the vaginal microbiome community structure (e.g. BV is defined as a loss of protective lactobacilli resulting in an overgrowth of anaerobic bacteria). Shotgun metagenomic sequencing provides a comprehensive view of all the organisms present in the vaginal microbiome (VMB) allowing for a better understanding of all potential etiologies. Here, we describe a robust VMB metagenomics sequencing test with a sensitivity of 93.1%, specificity of 90%, a negative predictive value of 93.4%, and a positive predictive value of 89.6% certified by Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologist (CAP) and the Clinical Laboratory Evaluation Program (CLEP). We sequenced over 7,000 human vaginal samples with this pipeline and described general findings and comparison to US census data.

Global climatic pressures and increased human demands create a modern necessity for efficient and affordable plant phenotyping unencumbered by arduous technical requirements. The analysis and archival of imagery have become easier as modern camera technology and computers are leveraged. This facilitates the detection of vegetation status and changes over time. Using a custom lightbox, an inexpensive camera, and common software, turfgrass pots were photographed in a greenhouse environment over an 8-week experiment period. Subsequent imagery was analyzed for area of cover, color metrics, and sensitivity to image corrections. Findings were compared to active spectral reflectance data and previously reported measurements of visual quality, productivity, and water use. Results indicate that Red Green Blue-based (RGB) imagery with simple controls is sufficient to measure the effects of plant treatments. Notable correlations were observed for corrected imagery, including between a percent yellow color area classification segment (%Y) with human visual quality ratings (VQ) (R = -0.89), the dark green color index (DGCI) with clipping productivity in mg d-1 (mg) (R = 0.61), and an index combination term (COMB2) with water use in mm d-1 (mm) (R = -0.60). The calculation of green cover area (%G) correlated with Normalized Difference Vegetation Index (NDVI) (R = 0.91) and its RED reflectance spectra (R = -0.87). A CIELAB b*/a* chromatic ratio (BA) correlated with Normalized Difference Red-Edge index (NDRE) (R = 0.90), and its Red-Edge (RE) (R = -0.74) reflectance spectra, while a new calculation termed HSVi correlated strongest to the Near-Infrared (NIR) (R = 0.90) reflectance spectra. Additionally, COMB2 significantly differentiated between the treatment effects of date, mowing height, deficit irrigation, and their interactions (p < 0.001). Sensitivity and statistical analysis of typical image file formats and corrections that included JPEG (JPG), TIFF (TIF), geometric lens correction (LC), and color correction (CC) were conducted. Results underscore the need for further research to support image corrections standardization and better connect image data to biological processes. This study demonstrates the potential of consumer-grade photography to capture plant phenotypic traits.

Context: The global escalation of conflict, violence, and human rights violations sets a pressing backdrop for examining the resilience of forcibly displaced youth (FDY) in Canada. This study aims to unpack the multifaceted challenges and resilience mechanisms of FDY, focusing on their health, well-being, and integration into host communities. It seeks to identify current models of resilience, understand the factors within each model, and highlight gaps and limitations. Methodology: Using a university librarian-supported structured search strategy, this exploratory rapid review searched literature from Ovid Medline and Open Source databases, published in English between January 2019 and January 2024, that fit specific inclusion criteria. The eligible articles (N=12 out of 4,096) were charted and analyzed by two student researchers with the PI. Charted data were analyzed thematically. Results: The selected studies captured diverse geographical perspectives, resilience models (such as Ungar's ecological perspective and Masten's resilience developmental models), as well as protective and promotive frameworks. Key findings indicate the complexity of resilience influenced by individual, familial, societal, and cultural factors. Each model offers insights into the dynamic interplay of these influences on FDY's resilience. However, these models often fall short of addressing the nuances of cultural specificity, the impact of trauma, and the intersectionality of FDY's identities. Conclusion: Recognizing the diverse and evolving nature of FDY's coping mechanisms, this study advocates for a culturally appropriate approach to resilience that integrates an intersectionality framework of individual attributes and culturally sensitive models.

In recent years, there has been an increase in the number of illegal radio stations that exceed power limits or use illegal frequencies. There has been a radio monitoring system called the DEURAS system to control these illegal radio stations. This system monitors illegal radio stations by receiving illegal radio waves using sensor stations installed in various locations. However, these systems sometimes do not work well when there is no line of sight from the sensor stations to the illegal radio stations or when there are many reflected waves generated due to the surrounding environment. In this study, we proposed a radio wave source estimation using HAPS, an unmanned aerial vehicle flying at high altitude. The simulation results show that estimation from high altitude provides higher estimation probability and estimation accuracy than the conventional method.

Sodium phenyl dithiocarbamate (pl-dtc) as a ligand was prepared from the reaction of aniline (C6H5-NH2) and carbon(IV) sulfide (CS2) in the presence of sodium hydroxide via method of one-pot synthesis. Two coordination compounds ([VO(sfz)(pl-dtc)] and [Zn(sfz)(pl-dtc)]) from respective oxovanadium (IV) sulfate hydrate and zinc (II) chloride were prepared with mixed ligands involving sodium sulfadiazine (sfz) and the synthesized pl-dtc crystals, also via the method of one-pot synthesis. Structural analyses of the ligand and coordination compounds were assessed using characterization techniques involving physicochemical parameters and spectral analysis ( FT-IR, UV-Vis and NMR (1H NMR and 13C NMR) to confirm their synthenses and structures. Additionally, pl-dtc crystals which grew from the pl-dtc solution when refrigerated after five days, has its structure confirmed and revealed when subjected to single crystal x-ray crystallography technique. Differences in results of spectral analysis between ligands and their respective coordination compounds confirmed the coordination between ligands and coordination compounds. The in vitro antibacterial studies showed that the ligands had modest activity against Gram positive bacteria: Staphylococcus aureus, while, the coordination compounds had modest activities against the Gram negative bacteria: Escherichia coli when compared with ligand of pl-dtc.

Three filamentous freshwater cyanobacterial strains were grown at high light intensity to produce lipidic dyes composed of xanthophylls, carotenes and chlorophyll a. The properties of the pigments were evaluated as suitable natural compounds to be applied in dye-sensitized solar cells (DSSC). The assembled DSSC were characterized using the density current vs. potential profiles and electrochemical impedance spectroscopy. With an efficiency of 0.127 %, our results are higher than those previously reported using similar structured compounds from natural sources as algae and cyanobacteria, among others. The best efficiencies were probably related to the strains with high content in pigments probably related to myxoxanthophyll-like derivates and aphanizophyll, carotenoids with many hydroxyl groups able to interact with the semiconductor surface. The stability of the bonding between the dyes and the titanium oxide of the photoelectrode is crucial to ensuring acceptable performance of the DSSC, which was successfully achieved in our experiments with carotenoids with many hydroxyl groups. Our results point to cyanobacterial pigments as a promising source of natural dyes for use in solar cells.

Invasive Candida infections represent a significant cause of morbidity and mortality in the neonatal intensive care unit (NICU), particularly among preterm and low birth weight neonates. The nonspecific clinical presentation of invasive candidiasis, resembling that of bacterial sepsis with multiorgan involvement, makes the diagnosis challenging. Given the atypical clinical presentation and the potential detrimental effects of delayed treatment, empirical treatment is often initiated in cases with high clinical suspicion. This underscores the need to develop alternative laboratory methods other than cultures, which are known to have low sensitivity and a prolonged detection time, to optimize therapeutic strategies. Serum biomarkers, including mannan antigen/anti-mannan antibody and 1,3-β-D-glucan (BDG), both components of the yeast cell wall, a nano-diagnostic method utilizing T2 magnetic resonance and Candida DNA detection by PCR-based techniques have been investigated as adjuncts to body fluid cultures and have shown promising results in improving diagnostic efficacy and shortening detection time in neonatal populations. This review aims to provide an overview of the diagnostic tools and the current management strategies for invasive candidiasis in neonates. Timely and accurate diagnosis followed by targeted antifungal treatment can significantly improve the survival and outcome of neonates affected by Candida species.

In the modern days the data is coming from various devices like mobiles, tabs, laptops, computers, IOT devices e.tc and is stored in the electronics form in the systems using the concept of files or data bases. Clustering Technique is used to extract data from these sources. Improving the accuracy of the model is improved using the feature selection or feature engineering or both. The feature engineering is used to add a new feature based on the global mean. Along with that new feature in addition to the feature selection increase the overall accuracy of the model.

Background: There has been a lack of tools to identify listening difficulties in school settings for both hearing and hearing-impaired Italian students. Thus, the present study aimed to realize cross-cultural adaptation and validation of the Listening Inventory for Education-Revised for Italian students (LIFE-R-ITA). Methods: Following the validation of two forward-backward translations by a multidisciplinary committee, the content validation for the LIFE-R-ITA was performed by pre-testing six implanted children (8-18 years old). After minor cross-cultural adaptations, normative data were collected from a sample of 223 hearing students enrolled in different school settings and educational degrees. Results: For the LIFE-R-ITA, hearing students showed an average score of 72.26% (SD=11.93), reflecting some listening difficulties. The subscales (LIFE total, LIFE class, and LIFE social) indicated good internal consistency. All items were shown to be relevant. Most challenging situations happened when listening in large rooms, especially when other students made noise. LIFE social scores were significantly worse than those of LIFE class (p < 0.001). Conclusions: The LIFE-R-ITA may support teachers and clinicians in assessing students’ self-perception of listening at school. Such understanding may help students overcome their listening difficulties, by planning and selecting the most effective strategies among classroom interventions.

This study analyzed methodologies for identifying β-casein genotypes in dairy cows and the purity of A2 fermented milk. The research was justified by the need for quick and accurate techniques for herd screening and A2 milk quality control. The methodology included the development of an ELISA test to detect β-casein A1 in fermented milk and the evaluation of a commercial Lateral Flow Immuno Assay (LFIA) to identify A2A2 genotypes and the purity of A2 milk. The results showed that the ELISA test had high sensitivity and specificity (100%) in detecting β-casein A1. The LFIA test was 100% effective in identifying A2A2 genotypes and verifying the purity of A2 milk with a minimum detectable contamination of 5% for raw milk and 10% for fermented milk. Compared to traditional genotyping, these methods proved to be highly reliable and more practical for large-scale screening. It was concluded that the ELISA and LFIA were valuable tools for ensuring the quality and authenticity of A2 milk, meeting the demands of producers and consumers for safe and healthy dairy products.

Despite the growing adoption of Mobility as a Service (MaaS) in urban transportation systems, standard monitoring methods for evaluating its impact and effectiveness still need to be developed. This study proposes a quantitative state of MaaS analysis based on mobility market indicators and macroeconomic metrics to generate a MaaS Status Index (MSI). The intention is to introduce a standardised quantitative methodology for systematically assessing and comparing the state of MaaS in urban mobility systems. The MSI aims to quantitatively capture the economic, social, technological, and infrastructural conditions relevant to MaaS implementation. The methodology includes four steps: identifying relevant mobility markets, defining mobility market metrics, integrating macroeconomic metrics, and deriving the MSI formula. We apply the MSI methodology to the Austrian mobility market as a case study, demonstrating its practicality in assessing MaaS readiness and highlighting specific challenges and opportunities within the Austrian mobility system. The analysis covers the present (2017-2022) and the projected future (2023-2028). The findings indicate that the proposed MSI is an effective tool for evaluating MaaS implementation readiness.

Background and Objectives: Zonulin is a molecule that has been identified as an intestinal permeability marker in recent years. Zonulin previously linked to Diabetes Mellitus, Obesity and Cardiovascular Disease but but its role in chronic kidney disease (CKD) was unclear. This study aims to investigate the relationship between Zonulin and systemic inflammation (SI), endothelial dysfunction (ED), especially renal functions, in patients with CKD. Materials and Methods: One hundred sixty-three participants were enrolled in this study. All participants were divided into two groups, patient and control groups, according to the presence of CKD (eGFR

Interaction between multiple phases especially liquid-gas is one of the most common phenomena in industrial systems. Computer Vision enables modern systems to derive an automated and robust image-processing technique to address this issue. However, diverse experimental conditions still make it a challenging task to overcome. In Deep Learning, instance segmentation has created a niche in various computer vision applications as it aims to provide different instance IDs to objects belonging to the same class. In this paper, we propose a novel approach employing the YOLO (You Look Only Once) an end-to-end deep learning architecture for the detection and segmentation of bubbles in fluid flows. YOLOv5 offers significant improvements in both speed and accuracy compared to its predecessors like YOLOv3. Therefore, we train the YOLOv5 network on a dataset consisting of annotated images representing instances of bubbles across varied fluid flow environments. This paper provides both qualitative and quantitative evaluation of three YOLOv5 networks (small, medium, and extra-large) in detecting and segmenting bubbles with high accuracy and efficiency. Based on the metrics all three YOLOv5 models achieved high precision above 0.98 for bounding box detection and 0.97 for segmentation mask, and high recall value greater than 0.97 for box and 0.96 for mask quality was achieved. The achieved results indicate that the models accurately localize bubbles within the image frame, and distinguish bubble pixels from the background. Also, mean average precision (mAP50-95) consistently exceeds 0.84 across all models for the bounding box and 0.73 for the segmentation mask. The ascertained results emphasize the potential of YOLOv5 architecture as a powerful tool for automated bubble analysis in real-world applications. Our research contributes to advancing the field of deep neural networks in fluid systems and provides a fresh approach for future developments in automated bubble analysis.

Toxoplasma gondii is a protozoan and the etiologic agent of toxoplasmosis causes high mortality in immunocompromised individuals and newborns. Despite the medical importance of toxoplasmosis, few drugs are available for its treatment, which are associated with side events and parasite resistance. Here, we show a screening of molecules present in Covid-Box as a way of discovering new hits with anti-T. gondii activity. Covid-Box contains 160 molecules with known or predicted activity against SARS-CoV-2. Our analysis selected 23 Covid-Box molecules that can inhibit the tachyzoite forms of the RH strain of T. gondii in vitro by more than 70% at 1 µM after seven days of treatment. The inhibitory curves showed that most of these molecules inhibited the proliferation of tachyzoites with IC50 values below 0.80 µM; Cycloheximide and (-)-Anisomycin were the most active drugs, with IC50 values of 0.02 μM. Cell viability assays showed that the compounds are not toxic at active concentrations, and most are highly selective for parasites. Overall, all 23 compounds were selective, and for three of them (Apilimod, Midostaurin, and Salinomycin), this is the first report of activity against T. gondii. To better understand the effect of the drugs, we analyzed the effect of six of them on the ultrastructure of T. gondii using transmission electron microscopy. The main changes observed in parasite morphology after treatment with the selected drugs were changes in cell division and parasite organelles

Many natural and artificial liquid environments such as rivers, oceans, lakes, water storage tanks, aquariums, and urban water distribution systems, are difficult to access. As a result, technology is needed to enable autonomous liquid sampling to monitor water quality and ecosystems. The existing in-situ sample acquisition and handling systems for liquid environments are currently limited to a single use and are semi-autonomous, relying on an operator. Liquid sampling systems should be robust and light and withstand long-term operation in remote locations. The system components involved in liquid sampling should be sterilisable to ensure reusability. Here, we introduce a prototype of a liquid sampler that can be used in various liquid environments and may be valuable for the scientific characterisation of different natural, remote, and planetary settings. The Autonomous Planetary Liquid Sampler (APLS) is equipped with pre-programmed fully autonomous extraction, cleaning, and sterilisation functionalities. It can operate in temperatures between -10 ℃ and 60 ℃ and pressure of up to 0.24 MPa (~24 m depth below mean sea level on Earth). As part of the control experiment, we demonstrate its safe and robust autonomous opera-tion in a laboratory environment using a liquid media with Bacillus subtilis. A typical sampling procedure required 28 s to extract 250 mL of liquid, 5 s to fill the MilliQ water, 25 s for circulation within the system for cleaning and disposal, and 200 s to raise the system temperature from ~30 °C ambient laboratory temperature to 150 °C. The temperature is then maintained for another 3.2 hours to sterilise the critical parts, allowing a setup reset for a new experiment. In the future, the liquid sampler will be combined with various existing analytical instruments to characterise the liquid solution and enable the autonomous, systematic monitoring of liquid environments on Earth.

This paper adopts a systems firm-centered perspective on the environmental assessment of recyclable glass and PET soft drink containers. We employ LCA and discrete-event simulation modelling for the environmental assessment of the two soft drinks packaging alternatives in operational terms, over the entire supply chain, over a period of three years. The assessment is based on real data collected from a large soft-drinks producer and its suppliers. The research and practice contribution of the paper is twofold: first, it introduces a methodological framework for environmental assessment of companies’ packaging environmental impact under different product and operations strategies, and secondly, it provides a holistic environmental assessment of the two packaging materials (PET and glass) taking into account specific operational issues, such as product mix and recycling and reuse options, and activity interdependences and stochasticity. The results of the simulation experiments confirm at system level, for glass, the importance for sustainability, to increase the number of reuse cycles and the percentage of used bottles collected for refilling, whereas for PET, to increase the percentage of recycled PET in new bottles.

The objective of the research is to provide theoretical assessments on the relevance of sustainable agrotourism in protected natural areas as an alternative for sustainable development in areas of great ecological value, where the protection and conservation of the environment is a priority and the integration of agricultural activities with the preservation of biodiversity is achieved for the promotion of practices that not only minimize the environmental impact, but also contribute to the conservation of the natural environment. The research was carried out in the context of the Machalilla National Park in Ecuador using the deductive method, which allowed the analysis of the problem and the general theories linked to sustainable agro-tourism in protected natural spaces, the establishment of premises and the development of objectives to reach conclusions on the subject studied. Mixed research is presented, which allowed the integration of contributions from the analyses carried out for the treatment and processing of the information. Among the results, the systematization of sustainable agro-tourism in the context of protected areas is expected. The results show the need to broaden the debate on the relevance of sustainable agrotourism in protected natural areas as a sustainable development alternative for rural communities.

We investigate some information properties of consecutive k-out-of-n:G systems in light of fractional generalized cumulative residual entropy. We firstly derive a formula to compute fractional generalized cumulative residual entropy related to the system's lifetime and explore its preservation properties in terms of established stochastic orders. Additionally, we obtain useful bounds. To aid practical applications, we propose two non parametric estimators for the fractional generalized cumulative residual entropy in these systems. The efficiency and performance of these estimators are illustrated using simulated and real datasets.

This study sheds light on personal characteristics of and the coping strategies that older Canadians self-identifying as severely anxious post-COVID-19 were more and less prone to gravitate to. Our studied sample consisted of 606 older people residing in 10 Canadian provinces. Participants completed the Geriatric Anxiety Scale – 10 and a personal checklist of everyday coping strategies for mitigating anxiety. Severely anxious older Canadians tended to be in their 60s, and in poor to fair health. They were not significantly more likely to be women or to be chronically ill, nor to self-identify as non-binary or as having a life partner. Older Canadians experiencing severe anxiety were, however, far more likely to normalize their fear and anxiety, challenge their worries, and to relax or meditate. They were less inclined to decrease other sources of stress in their lives, to stay active, and to get enough sleep. We offer anticipatory guidance for mental health program planners and practitioners, and researchers, fruitful avenues of inquiry.

Goyor sarong is a cultural heritage of Tegal, Central Java made using Non-Machine Looms (ATBM) with characteristic motifs that describe the character of the Tegal people. This study aims to analyze the symbolic meaning of the goyor sarong and its existence in the gloved culture of contemporary Tegal society. The approach used in this study is qualitative with the type of research is descriptive qualitative. The informants interviewed were gloved cultural actors from diverse professions and socio-cultural backgrounds. Data were also obtained from literature studies including online media. The results of this study show that the typical motifs on the goyor sarong include lung, bottled, ceplok, prilik, and balian motifs. Goyor sarong are viewed from a symbolic point of view, have a symbiotic understanding between humans and symbolic objects, and understand the cultural meaning of goyor sarong to shape social life. The motifs in the goyor sarong are increasingly developing according to the times and consumer needs in the modern era. This is closely related to the gloved culture of contemporary Tegal society. The use of goyor sarongs in contemporary society usually indicates the strata and events attended. In the era of orientation development, the goyor sarong has more meaning than just symbolic elaboration. Sarong goyor as a culture has an important role for the community that depicts local fashion life in line with the issue of zero waste in the latest international fashion industry.

The relationship between the returns and volatility of stocks, gold, bonds, and Bitcoin (BTC) to changes in inflation, interest rates (SBI), and exchange rates is a compelling topic, encompassing factors such as inter-asset interactions, and the roles of assets as hedge or safe-haven. We aims the inter-assetscorrelation using Granger Causality Test and the role of hedge or safe-haven assets against uncertainty using GARCH for normal condition and quantile regression in crisis. Last, we built an optimal portfolio using the Arbitrage Pricing Model (APT) consists of 28% stocks, 16% gold, 27% bonds, and 29% BTC, with returns 1.7796% over the Rf. Monthly trading records from 2018 until 2023 are used. The results demonstrate a correlation between the returns of gold and bonds with BTC, while stock volatility is found to correlate with BTC volatility. Furthermore we found a negative correlation between gold returns and exchange rates, though gold shows no correlation with other variables, indicating its effectiveness as a hedge in normal conditions. The bond serve primarily as a diversifier against exchange rate and inflation in normal, bearish, and bullish market conditions. These findings suggest that gold and bonds are more stable instruments and serve as risk mitigation strategy for BTC.

Although extracorporeal membrane ventilation offers the possibility for low frequency ventilation, protocols commonly used in patients with acute respiratory distress syndrome (ARDS) and treated with extracorporeal membrane oxygenation (ECMO) vary largely. Whether strict adherence to low frequency ventilation offers benefit on important outcome measures is poorly understood. Background/Objectives: This pilot clinical study investigated the efficacy of low frequency ventilation on ventilator free days (VFDs) in patients suffering from ARDS treated with ECMO therapy. Methods: In this single-center randomized controlled trial, 44 (70% male) successive ARDS patients treated with ECMO (aged 56 ± 12 years, SAPS III 64 (SD ± 14)) were randomly assigned 1:1 to control group (conventional ventilation) or treatment group (low fre-quency ventilation during first 72 hours on ECMO: respiratory rate 4-5/min; PEEP 14-16cm H2O; plateau pressure 23-25 cm H2O, tidal volume: < 4mL/kg). The primary endpoint was VFDs at day 28 of ECMO start. The major secondary endpoint was ICU mortality, 28-day and 90-day mortality. Results Twenty-three (52%) patients could be successfully weaned from ECMO and were discharged from intensive care unit (ICU). Twelve patients in the treatment group and five patients in the control group showed more than one VFD at day 28 after ECMO. VFDs were 3.0 (SD ± 5.5) days in the control group and 5.4 (SD ± 6) days in the treatment group (P = 0.117). Until day 28 after ECMO initiation, patients in the treatment group could be more often successfully weaned from ventilator (OR of 0.164 of 0 VFDs at day 28 after ECMO start; 95% CI 0.036-0.758; P = 0.021). ICU mortality did not differ significantly (36% in treatment group and 59% in control group; P = 0.227). Conclusions: Low frequency ventilation is comparable to conventional protec-tive ventilation in patients with ARDS treated with ECMO. However, low frequency ventilation may support weaning from invasive mechanical ventilation in patients suffering from ARDS treated with ECMO therapy.

Research in renewable energy sources and micro-grid systems is critical for the evolving power industry. Micro-grids can supply diverse loads while reducing dependency on the utility grid. This paper models both pico-grids and nano-grids in the Singapore Institute of Technology Punggol campus, incorporating solar PV, energy storage systems (ESS), power electronics converters, and both DC and AC loads, along with utility grid connections. The pico-grid includes a battery storage system, a single-phase inverter linked to a single-phase grid, and DC and AC loads. The nano-grid comprises solar PV panels, a boost converter, a battery storage system, a three-phase inverter connected to a three-phase grid, and AC loads. Both the pico-grid and nano-grid are configurable in standalone or grid-connected modes. This configuration flexibility allows for detailed operational analysis under various conditions. The study conducts subsystem-level modeling before integrating all components into the simulation environment. MATLAB/Simulink is utilized to model, simulate, and analyze the power flow in both the pico-grid and nano-grid under different operating conditions.

Malaria and Typhoid fever are prevalent diseases in tropical regions, exacerbated by unclear protocols, drug resistance, and environmental factors. Prompt and accurate diagnosis is crucial to improve accessibility and reduce mortality rates. Traditional diagnosis methods cannot effectively capture the complexities of these diseases due to the presence of confusable symptoms. Although machine learning (ML) models offer accurate predictions, they operate as "black boxes" with non-interpretable decision-making processes, making it challenging for healthcare providers to comprehend how the conclusions are reached. This study employs explainable AI (XAI) models such as Local Interpretable Model-agnostic Explanations (LIME), and Large Language Models (LLMs) like ChatGPT, Gemini, and Perplexity, to clarify diagnostic results for healthcare workers, building trust and transparency in medical diagnostics. The models were implemented on Google Colab and Visual Studio Code because of their rich libraries and extensions. Results showed that the Random Forest model outperformed Extreme Gradient Boost and Support Vector Machines and important features for predicting Malaria and Typhoid were identified with the LIME plots. Among LLMs, ChatGPT 3.5 demonstrates a comparative advantage over Gemini and Perplexity, hence highlighting how crucial it is to use a hybrid strategy that combines ML, XAI, and LLMs to improve diagnostic performance and reliability in healthcare applications. The study recommends implementing the integrated ML, LIME, and LLM processes because it streamlines the development and maintenance process's workflow overall, makes use of resources more effectively, and improves explainability by allowing the LLM to consider the complete context that LIME provides.

Background: The predictive value of changes in C-reactive protein (CRP), procalcitonin and leukocyte levels, which are commonly used in the diagnosis of infection in sepsis and septic shock, remains a topic of debate. This study aims to evaluate the effectiveness of changes in CRP, procalcitonin, and leukocyte counts on the prognosis of patients admitted to the intensive care unit (ICU) with a diagnosis of pneumosepsis and pneumonia-related septic shock, and to investigate whether any of these markers have a superior predictive value over the others in forecasting prognosis. Methods: The study analyzed the demographic data, Charlson Comorbidity Index score (CCIS), CURB-65 score (confusion, uremia, respiratory rate, BP, age ≥ 65 years), and Acute Physiology and Chronic Health Evaluation II (APACHE-II) scores of 230 patients admitted to the ICU with a diagnosis of pneumosepsis and pneumonia-related septic shock between April 1, 2022, and December 31, 2023. The levels of CRP, procalcitonin, and leukocytes were also recorded and analyzed to assess their impact on 1-month and 3-month mortality outcomes. Results: According to multivariate logistic regression analysis, low BMI, male gender, high CCIS, CURB-65, and APACHE-II scores were found to be significantly associated with both 1-month and 3-month mortality (p<0.05). An elevated SOFA score was associated with 1-month mortality, while advanced age was related to 3-month mortality (p<0.05). Although there was no significant relationship between the first-day levels of leukocytes, CRP, and PCT and mortality, their levels on the third day were observed to be at their highest in both 1-month and 3-month mortality cases (p<0.05). Additionally, a concurrent increase in any two or all three of CRP, PCT, and leukocyte values was found to be higher in patients with 3-month mortality compared to those who survived (p=0.004). Discussion: Although PCT, CRP, and leukocyte values measured at the time of admission were not significantly associated with 1-month mortality in patients with pneumosepsis or pneumonia-related septic shock, the persistent elevation and concurrent increase of these values, along with male gender, advanced age, low BMI, and high CCIS, CURB-65, and APACHE-II scores, were found to be significantly associated with 3-month mortality.

Unmanned aerial vehicle UAV has become an important tool for emergency communication. When disaster happens, the roads in the disaster area always are seriously damaged, and theground infrastructure communication facilities are damaged. Under emergency conditions, UAV can go into key areas as communication nodes to provide communication services for users in the area.But it's difficult for UAV to cover the entire disaster area and the efficient rescue time will be delayed. Therefore, how to make the UAV accurately perceive the regional situation and deployed in the right position is worth studying. In this paper, a virtual simulation environment is established reasonably and deep reinforcement learning algorithm is used to train UAV agents. At the same time, a series of problems such as sparse reward and long training time are still not solved in the development of reinforcement learning algorithms,and the reward function is designed to improve training efficiency. First of all, we set a specific mountain emergency communication scenario, and combined with the specific application of the UAV to carry out virtual simulation, and build a virtual environment. Furthermore, an additional shaped reward function is designed to address the sparse reward problem. Through the improvement of deep Q-learning network DQN algorithm and the reward design based on potential function, the final evaluation index is improved, and the effectiveness of the algorithm is verified. The experimental results demonstrate our work can effectively shorten the training time and increase convergencerate.

Background/Objectives: Vitamin D’s effect on risk health outcomes is often evaluated using prospective cohort studies. Risk ratios (RRs; e.g., hazard ratios or odds ratios) are determined for incidence for participants with baseline serum 25-hydroxyvitamin D [25(OH)D] concentrations below or above specified values. Serum 25(OH)D concentrations vary over time, thereby diluting the effect of 25(OH)D for long follow-up periods. Inverse relationships between RR and follow-up period have been reported for all-cause mortality rate and cancer incidence rates. Here I evaluate the effect for neurological outcomes. Methods: I analyzed how follow-up period affected results from 10 cohort studies of all-cause dementia, 6 studies of Alzheimer’s disease, and 9 for cognitive impairment with respect to vitamin D deficiency. Results: For all-cause dementia, Alzheimer’s disease, and cognitive impairment, respectively, the linear regression fits are RR = 2.9 – 0.14 × years, r = 0.73, p = 0.02; RR = 2.9 – 0.14 × years, r = 0.69, p = 0.13; and RR = 1.8 – 0.066 × years, r = 0.72, p = 0.03. The regression fit to RR for the shortest follow-up period for each outcome is considered the best estimate of vitamin D deficiency’s effect on risk. Those values are approximately twice that found by averaging all RRs without considering the effect of follow-up period. Conclusions: Vitamin D’s effect on risk of neurological conditions should be determined with relatively short follow-up periods after repeated 25(OH)D measurements as warranted during follow-up.

The physical properties of a structure such stiffness although can be determined by some statical tests, the identification of damping parameter requires a dynamic test. In general, both theoretical prediction and experimental identification of damping are quite difficult. There are many different techniques available for damping identification, and each method gives a different damping parameter. The dynamic indentation method, rheometry, atomic force microscopy, and resonant vibration tests are commonly used to identify the damping of materials, including soft materials. While the viscous damping ratio, loss factor, complex modulus and viscosity are quite common to describe damping of materials, there are also other parameters such as the specific damping capacity, loss angle, half-power bandwidth, and logarithmic decrement to describe damping of various materials. Often one of these parameters is measured in practical applications and the measured damping parameter needs to be converted into another damping parameter for comparison purposes. In this review, the theoretical derivations of different parameters for the description and quantification of damping and their relationships, and the methods for damping identification are presented. The expressions for both high damping and low damping are included and evaluated. This paper could be a primary resource for damping research and teaching.

We define the function $Col: \mathbb{N} \to \mathbb{N}$ as the Collatz function, given by $3n + 1$ if $n$ is odd and $\displaystyle\frac{n}{2}$ if $n$ is even \cite{Lagarias1990}. The conjecture postulates that for any positive integer, at some point, its iteration will reach 1, or equivalently, every orbit will fall into the periodic cycle $\{4, 2, 1\}$. Two conditions would invalidate the conjecture: the existence of a divergent orbit or the presence of another cycle. In 2019 Terence Tao \cite{tao} proved that almost all orbits converge to the trivial cycle of $\{1,4,2\}$, in this work we will prove the non-existence of divergent orbits. The central idea is to decompose the dynamic system $Col$ into a binary dynamic system, generated by different compositions of two functions. This differs from a typical dynamic system, which is generated by the iteration of a single function. We consider the system generated by the functions $\theta, \psi: \mathbb{R} \to \mathbb{R}$, defined as $\displaystyle\theta(x) = \frac{x}{2}$ and $\displaystyle\psi(x) = \frac{3x + 1}{2}$, denoted as $\langle \theta, \psi \rangle$. We examine sequences of functions in $\langle \theta, \psi \rangle$ of the form $S_k(x) = s_k \circ S_{k-1}(x)$ with $s_k \in \{\theta, \psi\}$. We define a function that assigns to each element of these sequences an integer, called the minimum value positive integer or simply the minimum value. This corresponds to the smallest positive integer $n$ such that $S_k(n)$ is an integer. As we will prove later, the minimum value is monotonically increasing, meaning that increasing the terms of the sequence will never result in a value lower than the previous one. Based on this behavior, we distinguish two types of sequences: stable ones, where the minimum value is constant from a certain point, and unstable ones, where the minimum value is divergent. The main result for unstable sequences is that when the slope of the sequence is divergent, the sequence is unstable. From this result, we can prove that there are no divergent orbits for the function $Col$.

Let's define $\delta(x) = (\sum_{{q\leq x}}{\frac{1}{q}}-\log \log x-B)$, where $B \approx 0.2614972128$ is the Meissel-Mertens constant. The Robin theorem states that $\delta(x)$ changes sign infinitely often. Let's also define $S(x) = \theta(x) - x$, where $\theta(x)$ is the Chebyshev function. It is known that $S(x)$ changes sign infinitely often. We define the another function $\varpi(x) = \left(\sum_{{q\leq x}}{\frac{1}{q}}-\log \log \theta(x)-B \right)$. We prove that when the inequality $\varpi(x) \leq 0$ is satisfied for some number $x \geq 3$, then the Riemann hypothesis should be false. The Riemann hypothesis is also false when the inequalities $\delta(x) \leq 0$ and $S(x)\geq 0$ are satisfied for some number $x \geq 3$ or when $\frac{3 \times \log x + 5}{8 \times \pi \times \sqrt{x} + 1.2 \times \log x + 2} + \frac{\log x}{\log \theta(x)} \leq 1$ is satisfied for some number $x \geq 13.1$.

Agriculture stands as the cornerstone of Africa’s economy, supporting over 60% of the continent’s labor force. Despite its significance, the quality assessment of agricultural products remains a challenging task, particularly at large scale, consuming valuable time and resources. The African plum is an agricultural fruit that is widely consumed across West and Central Africa but remains underrepresented in AI research. In this paper, we collected a dataset of 2,892 African plum samples from fields in Cameroon representing the first dataset of its kind for training AI models. The dataset contains images of plums annotated with quality grades. We then trained and evaluated various state-of-the-art object detection and image classification models, including YOLOv5, YOLOv8, YOLOv9, Fast R-CNN, Mask R-CNN, VGG16, Detectron-121, MobileNet and ResNet, on this African plum dataset. Our experimentation resulted in mean average precision scores ranging from 88.2% to 89.9% and accuracies between 86% and 91% for the object detection models and the classification models respectively. We then performed model pruning to reduce model sizes while preserving performance, achieving up to 93.6% mean average precision and 99.09% accuracy after pruning YOLOv5, YOLOv8 and ResNet by 10-30%. We deployed the high-performing YOLOv8 system in a web application, offering an accessible AI-based quality assessment tool tailored for African plums. To the best of our knowledge, this represents the first such solution for assessing this underrepresented fruit, empowering farmers with efficient tools. Our approach integrates agriculture and AI to fill a key gap.

This study investigates resource adequacy and renewable energy integration in the United States, European Union, and Pakistan amid global energy market liberalization and greenhouse gas re-duction efforts. It explores how these regions are adapting to the surge in renewable sources like wind and solar, which, despite their financial and environmental benefits, challenge resource adequacy and the economic viability of traditional energy sources. In the US and EU, significant improvements have been introduced in wholesale electricity markets and capacity accreditation mechanisms, which enhanced the large-scale deployment of renewables. This shift has prompted a reevaluation of resource adequacy, leading to increased deployment of battery storage and demand response. Presently, gas-based generation is largely upholding resource adequacy, however, future trends indicate a move towards greater consumer participation, energy efficiency, and utility-scale storage, with a decline in fossil fuel use. Pakistan aims to adopt a liberalized market structure by balancing competitive markets with legacy contracts. Public pressure is driving a shift from costly fossil-based generation to renewables. Similarly, a trend in the rise of behind-the-meter solar generation can be witnessed. In future, Pakistan may also experience resource adequacy challenges. It will likely need to implement battery storage, demand response, and modern capacity accreditation tools, by drawing lessons from developed markets.

Given the conceptual confusion between resilience and sustainability in organizations in the literature, the present study reviews the 27-year global literature on resilience and sustainability in organizations to clarify the relationship between the two, and derive a framework as cutting-edge knowledge on how to ensure resilience and sustainability in organizations. Findings uncover five schools of thought: Sustainable Business Strategy, Predictive Analytics, Sustainable Supply Chain, Ecological Resilience and Sustainable Leadership. A cutting-edge framework, comprising sustainability practices, sustainability outputs, sustainability and resilience outcomes, is derived to guide future research and inform practitioners on how to ensure resilience and sustainability in their organizations.

Steroidogenic factor 1 (SF-1) is a nuclear receptor that regulates steroidogenesis and reproductive development. NR5A1/SF-1 variants are associated with a broad spectrum of phenotypes across individuals with disorders of sex development (DSD). Oligogenic inheritance has been suggested as an explanation. However, testing the impact of specific gene variants involved in a network remains difficult. To confirm the hypothesis that NR5A1/SF-1-related DSD follow an oligogenic mode of inheritance, we investigated a constellation of gene variants identified in a 46,XY severely undervirilized individual. Candidate genes were revealed by whole exome sequencing, and pathogenicity was predicted by different in silico tools. We found variants in NR1H2 and INHA associated with steroidogenesis, sex development, and reproduction. Functional testing was conducted in cell models. Novel SF-1 and NR1H2 binding sites in the AR and INHA gene promoters were found. Transactivation studies showed that wild-type NR5A1/SF-1 regulates INHA and AR gene expression, while the NR5A1/SF-1 variant had decreased transcriptional ac-tivity. NR1H2 was found to regulate AR gene transcription; however, the NR1H2 variant showed normal activity. This study expands the NR5A1/SF-1 network of interacting partners while strengthening the hypothesis that the broad phenotype observed in 46,XY DSD individuals may be caused by oligogenic pathogenicity.

This paper proposes an optimization method for the scheduling of a multi-energy virtual power plant supply-demand balance in the power market environment of Jiangxi Province. The objective of this method is to enhance the operational efficiency of the power grid, reduce energy costs, and facilitate economical and efficient energy distribution in the power market. The method comprehensively considers the characteristics and uncertainties of renewable energy sources such as solar and wind energy, and incorporates advanced multi-objective optimization algorithms. Additionally, real-time market price feedback is integrated to achieve accurate allocation of power supply and demand. Through a case study of a multi-energy virtual power plant in Jiangxi Province, this paper examines the optimal combination model for various energy sources within VPP, and analyzes the impact of different market environments on supply-demand balance. The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. Compared with traditional power supply models, it reduces average electricity costs by 15% and increases renewable energy utilization efficiency by 20%.

The impact of financial risks extends beyond the normal operation and survival of industrial and commercial enterprises and financial institutions. They also have the potential to impede the stable development of a country's and even the world's financial economy. This is clearly demonstrated by the severe consequences of the frequent financial crises that have occurred in recent years. It thus follows that the prevention of financial risks has become one of the core tasks of the operation and management of industrial and commercial enterprises and financial institutions. Portfolio optimization techniques are employed in the construction of a variety of asset allocation models, with reinforcement learning algorithms used to dynamically adjust investment strategies with the objective of maximizing returns and minimizing risks. The preliminary construction of an asset allocation model is achieved through the utilization of a genetic algorithm. Genetic algorithms emulate the processes of natural selection and genetic variation to identify the optimal portfolio of assets that will yield the greatest returns at a pre-established level of risk. Subsequently, the Deep Q-Learning algorithm is introduced to facilitate dynamic adjustments and optimization of the asset allocation, based on the initial construction. Deep Q-learning employs deep neural networks to forecast the prospective returns of disparate investment strategies, thereby optimizing the decision-making process through continuous learning and updating. The combination of genetic algorithms and deep Q-learning enables the system to identify the optimal investment strategy under a diverse range of initial conditions and to adapt it in real-time to respond to market fluctuations and uncertainties. The experimental analysis demonstrates that the proposed method exhibits an exemplary capacity for risk control and a robust ability to generate stable income growth across diverse market environments. In simulation experiments, portfolios constructed using this method demonstrate lower volatility and higher average returns than those generated through traditional methods.

The blood that remains in the placenta and umbilical cord after the birth of the infant is referred to as umbilical cord blood (UCB), which has the advantages of convenient source and less ethical controversy. MicroRNA (miRNA) is a class of non-coding RNAs that can regulate gene expression after translation and transcription. Alterations in miRNA expression involve changes in a range of gene expression pathways. An increasing body of research indicates that miRNAs are implicated in many human disorders and are involved in almost all biological medium processes. Due to their high stability in UCB, circulating miRNAs are considered promising biomarkers for diagnosis and disease prognosis. Herein, we conduct a comprehensive review to summarize the roles of diverse UCB miRNAs from different perspectives, including UCB miRNA as biomarker for developmental projections and disease diagnosis, the relationship between maternal gestational status and neonatal UCB miRNA expression, the therapeutic function of exosomal UCB miRNA, miRNA expression profiles in UCB cell lineages. Taken together, miRNAs in UCB are very promising biomarkers for indicating physiological states, disease states, drug responses, development states, or health conditions, which can help in diagnosing, classifying, and predicting diseases, prognosis, or providing personalized treatment plans for patients.

Anterior Cruciate Ligament (ACL) injuries rank among the most prevalent and severe types of injuries, significantly impacting both athletes and non-athletes alike. These injuries not only result in immediate physical impairment, such as intense pain, substantial swelling, and a marked loss of mobility, but also carry long-term health consequences that can alter a person's quality of life. Chronic pain, persistent instability, and an increased risk of developing osteoarthritis are among the lasting effects that can follow an ACL injury. An in-depth understanding of the biophysics behind ACL injuries is paramount for devising effective prevention and treatment protocols. Biophysics, which combines principles from physics with biological systems, provides crucial insights into the mechanical and structural integrity of the ACL and its susceptibility to injury under various conditions. This systematic review aims to collate and synthesize the current knowledge surrounding the biophysical mechanisms that underlie ACL injuries. The review encompasses a range of factors, including the biomechanical forces that place stress on the ligament, anatomical structures that may predispose individuals to injury, and physiological conditions that affect ligament health and resilience. Each of these factors plays a crucial role in the incidence and severity of ACL injuries. Biomechanical forces, for example, can involve sudden changes in direction or impact during physical activity, leading to excessive stress on the ACL. Anatomical factors might include variations in bone structure or ligament alignment that inherently increase the risk of injury. Additionally, physiological conditions such as muscle strength, flexibility, and overall ligament health can influence the likelihood and extent of an ACL injury. The findings of this review underscore the necessity of adopting integrated approaches in both injury prevention and rehabilitation. Such approaches must consider the multifaceted nature of ACL injuries, involving not only mechanical and anatomical aspects but also physiological and possibly even genetic factors. By emphasizing a multi-faceted understanding, interventions can be more effectively tailored to address the complex interplay of elements that contribute to ACL injuries. This holistic approach can lead to better outcomes for those at risk of or recovering from ACL injuries, enhancing the efficacy of prevention strategies and rehabilitation protocols.

Most research on sustainable small-scale, local producer lifestyles emphasises healthy food production, lacking integration of mental and spiritual well-being into a holistic concept of a healthy lifestyle. This study explores the motives behind the production activity of producers engaged in sustainable food production in several Western Hungarian sub-regions, aiming to identify their attitudes and motivations. The small-scale entrepreneurial mindset encompasses needs beyond physical and ethical aspects, such as involvement, socio-cultural attachment to the past, tradition, nature, place, and local culture. An online questionnaire was conducted with 73 local producers in the second quarter of 2024. The results of the factor and cluster analyses were used to classify the producers into two clusters: the "Value-Creator" and the "Proud" clusters. The main features of these two clusters were illustrated in persona profiles. The "Value-Creator" cluster, mainly women, feel a strong connection to the local community and view sustainable production as a lifestyle choice. The "Proud" cluster, consisting of young men, focus on the quality and uniqueness of their products. This research contributes to a deeper understanding of sustainable production by exploring producers' intrinsic motivations and lifestyle choices. The findings could also inform other entrepreneurial projects, such as urban initiatives.

This study investigates the use of artificial intelligence (AI) and ethnobotanical knowledge to identify natural compounds with potent antiviral activity against HPV-16. Through molecular docking simulations, we evaluated the binding affinities of various essential oil components, in-cluding Apigenin, against the key antigenic determinants of HPV-16 (E6, E7 oncoproteins, and L1 major capsid protein). Apigenin exhibited strong binding affinities, particularly to E6 Oncopro-tein. To further enhance these findings, we employed an AI-driven reverse engineering approach to predict a natural compound with superior efficacy. The AI identified Luteolin, a flavonoid with additional hydroxyl groups, as a promising candidate. Comparative docking studies demon-strated that Luteolin possesses significantly stronger binding affinities to all three HPV-16 targets, surpassing the efficacy of Apigenin. This work highlights the potential of AI in accelerating the discovery and optimization of natural antiviral agents, providing a powerful tool for pharmaco-logical and ethnopharmacological screenings. Our findings suggest that AI-guided identification of natural compounds can lead to the development of more effective antiviral therapies, warranting further experimental validation and potential synthesis in laboratory settings.

Lymphatic filariasis (LF) is a neglected tropical disease associated with poverty and poor environmental conditions. With the inclusion of vector control activities in LF surveillance actions, there is a need to develop simple methods to identify areas with higher mosquito density and consequent risk of W. bancrofti transmission. An ecological study was conducted in Igarassu, Metropolitan Region of Recife, Pernambuco, Brazil. The mosquitoes were captured in 2,060 houses distributed across 117 census tracts. The vector density index (VDI) was constructed, that measures the average number of lymphatic filariasis transmitting mosquitoes per number of houses collected in the risk stratum. Moreover, the social deprivation indicator (SDI) was constructed and was carried out through principal component factor analysis. The average number of female C. quinquefasciatus found in the high-risk stratum was 242, while the low-risk stratum had an average of 108. The overall VDI was 6.8 mosquitoes per household. The VDI for the high-risk stratum was 13.2 mosquitoes per household, while for the low/medium-risk stratum, it was 5.2. This study offers an SDI for the density of C. quinquefasciatus mosquitoes, which reduces the cost associated with data collection and allows for indicating priority areas for vector control actions.

This study primarily investigates the effect of fly ash (FA) content on the mechanical properties and hydration performance of alkali-activated ground granulated blast furnace slag cements (AAGC), and compares the related properties with ordinary Portland cement (OPC). Additionally, the study examined the hydration products, thermal analysis, MIP, SEM, chemically bound water, and pH values of AAGC. The compressive strength of AAGC showed a retrogression phenomenon from 3 to 28 days, with the 14-day and 28-day compressive strengths of AAGC being higher than those of OPC. The AAGC with 20% FA content exhibits the highest 28-day compressive strength (75 MPa). The hydration heat release rate curved of OPC and AAGC can be divided into the initial induction period, induction period, acceleration period, deceleration period and steady period. As FA content increases, the 28-day pore volume of AAGC increased while pH values and chemically bound water decrease. SEM images of AAGC with low FA content showed more microcracks.

Reproductive disorders are a common event in modern reproductive medicine, occurring both in spontaneous and assisted pregnancies. Studies of the molecular mechanisms of implantation disorders in thin endometrium, including the study of gene transcriptional activity, have shed light on the identification of potential biological markers of endometrial receptivity. Background/Objectives: to reveal significantly dysregulated selected genes expression between RIF and RPL patients with thin endometrium. Methods: Endometrial samples were collected in the implantation window days (LH+7 – LH+10) of the natural menstrual cycle from RIF patients (n=20) and RPL patients (n=19). Ten genes were chosen as target genes regarding their possible relations with the implantation process. Total RNA was purified, reverse-transcribed; gene expression was quantified by RT-PCR. Results: The expression of the IL-15, INFG and HPRT1 genes were significantly decreased in RIF with thin endometrium patients compared to the RPL patients (log2 fold change=0.92, p=0.023 for IL-15, log2 fold change=1.24, p=0.046 for INFG, and log2 fold change=0.579, p=0.046 for HPRT1). There were not significant differences in expression of CXCL8, CXCL1, MMP10, C4BPA, TNC, VEGFB and HAND2 genes between groups. Conclusions: decreased expression of IL-15, INFG and HPRT1 genes was found in patients with RIF with thin endometrium compared to the endometrium of women with RPL. This has practical significance for clinicians for differentiated prescription of immunomodulatory therapy in patients undergoing ART programs.

Companion cropping involves growing two or more species together, benefiting the conservation of natural resources and improving fertilization and nutrient cycling by balancing chemical and organic sources. Studies, as in the case of tree tomato and Hass avocado, have shown a significant increase in yield compared to monocultures, highlighting the viability of this practice. In addition to their environmental benefit, companion crops offer economic advantages to producers by obtaining multiple products in a single harvest, strengthening food security and the economy of rural families. This study evaluated three levels of fertilization and interactions between fruit trees at different altitudes, observing differential behavior in the variables evaluated. The combination of cape gooseberry and blackberry showed significantly positive results, with more leaves and fewer pests, demonstrating the benefits of companion plants. A trend towards the combined use of chemical and organic fertilizers was observed, a potential strategy to reduce costs and improve crop growth. The results were shared with producers interested in implementing companion cropping, encouraging the adoption of this more sustainable and profitable agricultural practice. Companion crop agriculture represents a viable and promising strategy for a more efficient and sustainable agriculture, with both environmental and economic benefits.

The increasing frequency and severity of phytoplankton blooms worldwide highlight the need for advancements in monitoring technologies. Optical remote sensors, such as Landsat, have proven to be a cost-effective method for large-scale, near-real-time assessments of phytoplankton biomass in lakes. However, its effectiveness is often compromised by atmospheric interferences like clouds, dust, and wildfire smoke, which can obscure the clear-sky conditions essential for accurate remote sensing. While partial atmospheric correction (removing only the Rayleigh effect) is commonly applied to address these interferences, it remains inadequate for mitigating the impact of wildfire smoke. This study investigates the potential of Landsat's coastal/aerosol band (B1) for assessing wildfire smoke interference effects on Chlorophyll-a (Chl-a) retrieval models, which serve as proxies for phytoplankton biomass. We employed cluster analysis of B1 values to create a screening system based on aerosol reflectance, categorizing smoke interference into low, moderate, and high levels. Subsequently, we applied both partial (Rayleigh-corrected reflectance) and full (Landsat 8 Level 2 surface reflectance) atmospheric corrections before developing the Chl-a retrieval models. Excluding high wildfire smoke interference (B1 &gt; 0.07) from the Chl-a calibration dataset significantly enhanced model performance, increasing the r-squared value from approximately 0.55 to 0.80. Moderate smoke interference (0.05 &lt; B1 &lt; 0.07) yielded results comparable to low-interference conditions. Notably, Rayleigh-corrected reflectance, even without additional aerosol band filtering, achieved higher r-squared values for the Chl-a retrieval model than full atmospheric correction. B1 thus proves to be a valuable tool for identifying low smoke-impacted observations, offering an effective method to monitor phytoplankton biomass amid increasing wildfire activity and improving the capacity to monitor aquatic environments in a changing global landscape.

Sustainability is a concept which engages the weighted balance between economic, environmental and social domains for all life forms and man. Within the frame of sustainability, it is important to realize that coexistence is part of a single life equation. Damage to the environment, social spectrum, and economic sectors (through deviant practices) reap havoc upon all life forms. Sustainability insures the existence of all within the single equation of life. Unsustainable, colonial practices prevail upon the present and the future of life.Sustainability should advocate for healthy environs for all life forms (including, but not exclusive to humans) to sustain themselves. The neglect and/or omission of concern for this mandate will lead to the deuteriation and eventual expiration of any such life forms. Life cannot be sustained in an imposed, artificial domain which is suited solely for mercantile purposes. History has taught us that the cost of dismissing the errors of the past and forging on results in error. This article proposes to explore the impact of the exploitation of agricultural practices, food availability, deforestation, dislocation, and "voluntary tourism" upon "Others" stemming from colonial occupation.

Despite inclusive design focusing on improving environmental accessibility for mobility aid (MA) users, it often fails to ensure true inclusivity due to mismatches between interventions and user perceptions. Therefore, understanding mobility aids users' perceptions of inclusivity is essential for advancing disability studies and design, as it highlights key interventions for more effective practices. This study aims to explore perceived inclusivity in MAs usage and identifies gaps in users' needs, classifying their needs and offering recommendations to meet them. First, the DARE-Inclusive Design Framework was used to develop interview guidelines and interpret results. Next, semi-structured, in-depth interviews were conducted with 12 experienced physiotherapists in Iran, and finally, an inductive thematic analysis was used to identify and present themes. Four themes were identified: 1. Perceived Financial Value: Assessing Worth, 2. Objective Enhancements: Optimizing Environments and MAs, 3. Subjective Enhancements: Trustworthiness, Support, and Hope, and 4. Contextual Factors: Interpretations and Representations. The four interconnected themes provide guidelines for inclusivity-oriented interventions, emphasizing financial assessment, high-tech integration, and aesthetic and symbolic considerations in mobility aid design. Physiotherapists can also mediate emotional responses and enhance inclusion during rehabilitation. Additionally, social context and disability etiology impact users' acceptance and use of MAs.

This study introduces a sophisticated neural network structure for segmenting breast tumors. It achieves this by combining a pretrained Vision Transformer (ViT) model with a U-Net framework. The U-Net architecture, commonly employed for biomedical image segmentation, is further enhanced with Depthwise Separable Convolutional Blocks to decrease computational complexity and parameter count, resulting in better efficiency and less overfitting. The Vision Transformer, renowned for its robust feature extraction capabilities utilizing self-attention processes, efficiently captures the overall context within images, surpassing the performance of conventional convolutional networks. By using a pretrained ViT as the encoder in our U-Net model, we take advantage of its extensive feature representations acquired from extensive datasets, resulting in a major enhancement in the model’s ability to generalize and train efficiently. The suggested model has exceptional performance in segmenting breast cancers from medical images, highlighting the advantages of integrating transformer-based encoders with efficient U-Net topologies. This hybrid methodology emphasizes the capabilities of transformers in the field of medical image processing and establishes a new standard for accuracy and efficiency in activities related to tumor segmentation.

Oral lichen planus (OLP) is a chronic inflammatory mucosal disease, and an apparent cause has not been identified. OLP is refractory to treatment, and malignant transformation has been reported. Therefore, discovering effective drugs with few adverse effects over long-term administration is crucial. In this study, we established an in vitro OLP model to investigate the effects of Cepharanthin®, an alkaloid mixture derived from Stephania cephalantha Hayata. Four alkaloids from Cepharanthin® suppressed the expression of cytokine genes at various degrees in activated T cells. However, the effect of Cepharanthin® was limited. On the other hand, Cepharanthin® and four alkaloids suppressed the expression of various cytokine genes in human oral epithelial cells when stimulated with IL-β. In the OLP model, activated T cells increased the inflammatory gene expression in the epithelial cells, while Cepharanthin® suppressed their gene expression. Anti-inflammatory effect of Cepharanthin® was observed by protein dot blot. The effects of Cepharanthin®️ might be expressed through two aspects: its effect of mildly suppressing the activation of T lymphocytes and strongly suppressing the response of epithelial cells to inflammatory stimuli. The in vitro model established in this study could be a tool for elucidating the mechanisms of OLP pathogenesis and disease persistence.

This review explores the nuanced decision-making surrounding postoperative radiotherapy for diffuse low-grade glioma (DLGG) patients, emphasizing the need for personalized treatment to balance the benefits of tumor control with the risks of long-term side effects. Radiotherapy is a cornerstone of DLGG treatment, offering significant improvements in progression-free survival, but its potential for cognitive decline and vascular lesions necessitates careful consideration of individual patient factors. The review delves into the complexities of radiotherapy timing, revealing that while early radiotherapy enhances progression-free survival, it does not significantly impact overall survival and may lead to earlier onset of cognitive decline. Conversely, delayed radiotherapy may mitigate cognitive decline but may result in shorter progression-free survival and the onset of neurological symptoms. The review advocates for a patient-centered approach, emphasizing the importance of weighing individual risks and benefits, and highlights the potential of artificial intelligence in predicting cognitive decline and the need to revisit previous research findings in light of the 2021 WHO (World Health Organization) classification update, underscoring the evolving nature of DLGG treatment and the ongoing quest for optimal therapeutic strategies.

Childsmile is Scotland’s national child oral health improvement programme designed to reduce inequalities in oral health and ensuring universal access to NHS dental services by working closely with children and their families. Research has shown that parents with more dental concerns are less likely to bring their children for regular preventive dental check-ups. Therefore, a communication toolkit named ‘Chatterbox’ was created to help families access dental care services. This study aimed to evaluate the acceptability of Chatterbox from the perspective of parents with young children and from staff who work with them. Thirty parents of young children, volunteers, and staff affiliated with three third-sector family support organisations in Dundee participated in in-depth interviews, focus groups, and observations to assess the objectives of Chatterbox. Framework analysis was conducted to capture the themes, patterns, and findings triangulated using observations and field notes. Chatterbox was found to promote effective communication, identify barriers to dental attendance, provide a platform for reflection, convey the complexities of daily life, and boost parents' confidence to seek assistance. Chatterbox has the potential to help parents in accessing preventive dental care for their young children, when used with trained support workers.

Pro-inflammatory cytokines play a role in the failure of β-cells in type 1 and type 2 diabetes. While existing data from ‘omics’ experiments allow for some understanding of the molecular mechanisms behind cytokine-induced dysfunction in β-cells, no report thus far has provided information on the direct imaging of the β-cell landscape with nanoscale resolution following cytokine exposure. In this study, we use Airyscan-based optical super-resolution microscopy of Insulinoma 1E (INS-1E) cells to investigate the structural properties of two subcellular membranous compartments involved in the production, maturation and secretion of insulin-containing granules, the Endoplasmic Reticulum (ER) and the Golgi Apparatus (GA). Our findings reveal that exposure of INS-1E cells to IL-1β and IFN-γ for 24 hours leads to significant structural alterations of both compartments. In more detail, both ER and GA fragment and give rise to vesicle-like structures with markedly reduced characteristic area and perimeter and increased circularity with respect to the original structures. These findings complement the molecular data collected thus far on these compartments and their role in β-cell dysfunction using and lay the ground for future optical-microscopy-based ex-vivo and in-vivo investigations.

This research paper examines the transformative impact of Artificial Intelligence (AI) on the global journalism industry. The integration of AI technologies, such as machine learning and natural language processing, has drastically changed journalistic practices and media operations. The study aims to understand how AI affects news production, distribution, and ethical considerations within journalism. By providing historical context and reviewing existing literature, this paper situates its analysis within the broader academic discourse. A mixed-methods approach is used for data collection and analysis, ensuring comprehensive and reliable findings. Results indicate that AI tools enhance journalistic efficiency and capabilities but also introduce challenges related to accuracy, authenticity, and editorial judgment. The implications for employment in journalism are significant, necessitating new skills and roles. The discussion interprets these findings in the context of media evolution and ethical standards. This study concludes by advocating for a balanced approach to AI adoption in journalism, emphasizing the importance of ethical guidelines, continuous journalist training, and ongoing research to navigate this evolving landscape.

Gastrointestinal (GI) cancers, such as colorectal and gastric cancers, pose significant global health challenges due to their high rates of incidence and mortality. Even with advancements in treatment and early detection, many patients still face poor outcomes, highlighting the critical need for new biomarkers and therapeutic targets. Telomere length (TL) and telomerase activity (TA) have gained attention in this context. Telomeres, protective nucleotide sequences at chromo-some ends, shorten with each cell division, leading to cellular aging. Telomerase, a ribonucleoprotein enzyme, counteracts this shortening by adding telomeric repeats, a process tightly regulated in normal cells but often dysregulated in cancer. This review critically evaluates the role of TL and TA in the pathogenesis of GI cancers, examining their potential as diagnostic, prognostic, and predictive biomarkers. It explores how alterations in telomere biology contribute to the initiation and progression of GI tumors and assesses the therapeutic implications of targeting telomerase. By integrating findings from diverse studies, this review aims to elucidate the intricate relationship between telomere dynamics and gastrointestinal carcinogenesis, offering in-sights into how TL and TA could be leveraged to enhance the early detection, treatment, and prognosis of GI cancers.

The study objective is to evaluate the reliability of the Göttingen Mini-pig (G-MP) as a large animal model for preclinical studies addressing articular cartilage treatment procedures. Second this work compared the G-MP to the domestic pig (DP) in terms of surgical anatomy, postoperative management, and follow-up period possibilities and challenges. Six G-MP and four DP underwent a two-stage surgical procedure including cartilage harvesting using a superolateral approach followed by cartilage implantation using a medial parapatellar tendon approach. The superolateral approach exposed 11% (SD ± 5) of the entire trochlea in G-MP and 20% in the DP model. The medial parapatellar tendon approach in G-MP exposed 63% (SD ± 4) of the trochlear surface and exposed 34% (SD ± 13) of the medial femoral condyle, allowing 4 trochlear lesions of 6mm of diameter and one to the medial condyle in 4 out of 6 G-MP and in all DPs. Cartilage thickness was under 1mm in G-MP compared to more than 2mm in DP. Weight-progression was + 4 kg/week in DP and + 0.2 kg/week for G-MP. The G-MP is a feasible model for cartilage research, with adequate access to the joint via the dual approach. Thus enabling 4-5 lesions of 6mm, however a thinner cartilage in the G-MP needs to be considered.

Chlorophyll-a (Chl-a), a proxy for phytoplankton biomass, is one of the few biological water quality indices detectable using satellite observations. However, models for estimating Chl-a from satellite signals are currently unavailable for many lakes. The application of Chl-a prediction algorithms may be affected by the variance in optical complexity within lakes. Using Lake Winnipeg in Canada as a case study, we demonstrated that separating models by the lake’s basins [north basin (NB) and south basin (SB)] can improve Chl-a predictions. By calibrating more than 40 commonly used Chl-a estimation models using Landsat data for Lake Winnipeg, we achieved higher correlations between in situ and predicted Chl-a when building models with separate Landsat-to-in-situ matchups from NB and SB (R² = 0.85 and 0.76, respectively; p &lt; 0.05), compared to using matchups from the entire lake (R² = 0.38, p &lt; 0.05). In the deeper, clearer waters of the NB, a green-to-blue band ratio provided better Chl-a predictions, while in the shallower, highly turbid SB, a red-to-green band ratio was more effective. Our approach can be used for rapid Chl-a modeling in large lakes using cloud-based platforms like Google Earth Engine with any available satellite or time series length.

Abstract: This study aimed to assess the agronomic performance and yield stability of elite white yam (Dioscorea rotundata) genotypes across diverse Nigerian environments. Twenty-five genotypes were evaluated at three locations in two consecutive growing seasons, 2022 and 2023. The genotypes were assessed for their agronomic performance, tuber yield and related traits using various analytical tools such as AMMI (Additive main effects and multiplicative interaction) and MTSI (Multi-trait stability index). The AMMI analysis revealed significant differences among the genotypes and across the environ-ments for all traits (p