A cyclic antipodal points of a circle is a pair of points that are the intersection of the circle with a diameter of the circle. A recent proof of Ptolemy’s Theorem, simultaneously in both (i) Euclidean geometry; and (ii) the relativistic model of hyperbolic geometry (which is identified with the Klein model of hyperbolic geometry), motivates in this article the study of four cyclic antipodal points of a circle, ordered arbitrarily counterclockwise. The translation of results from Euclidean geometry into hyperbolic geometry is obtained by means of hyperbolic trigonometry, called gyrotrigonometry, to which Einstein addition gives rise. Formulas that extend the Pythagorean formula in both Euclidean and hyperbolic geometry are obtained as byproducts

As a key mediator of chronic pain, neurotrophin nerve growth factor (NGF) binds to two neurotrophin receptors: p75 neurotrophin receptor (p75NTR) and tyrosine kinase receptor A (TrkA). The formation of the p75NTR-NGF-TrkA complex is implicated in the potentiation of chronic pain signals, making it an attractive target for therapeutic explorations. NGF analogues and monoclonal antibodies (mAbs) targeting NGF represent two distinct approaches in modulating the intricate signaling pathways involved in pain transduction mediated by the p75NTR-NGF-TrkA complex. While NGF analogues offer the advantage of tailored design to fine-tune neurotrophic responses, monoclonal antibodies provide a more systemic and comprehensive blockade of NGF, inhibiting its interactions with both p75NTR and TrkA receptors. However, the use of mAbs may pose challenges related to potential side effects and interference with the physiological functions of NGF. As a result, balancing the benefits and drawbacks of the two approaches is critical for advancing therapeutic strategies towards the alleviation of p75NTR-NGF-TrkA-mediated pain. In this study, therefore, a novel structural and biophysical approach was employed for the design of NGF analogues to suppress p75NTR-NGF-TrkA-related chronic pain signaling. Employing high-throughput structural modeling and biophysics-based intermolecular binding affinity calculations, this article for the first time puts forward a set of NGF analogues, including in particular NGF analogues with four site-specific mutations, for whose dimerizations the K d at 37 ^◦C were reduced by three orders of magnitude (from 10^-9 M to 10^-6 M) compared to the K d at 37 ^◦C for the dimerization of native NGFs. Overall, the integration of structural and biophysical perspectives enhances our understanding of the rational design of NGF analogues as promising candidates for the development of NGF-targeted analgesic therapies, which balances the benefits and drawbacks of anti-NGF antibodies and NGF analogues for advancing therapeutic strategies towards the alleviation of p75NTR-NGF-TrkA-mediated pain.

The Gulf of Mannar, a UNESCO World Biosphere Reserve, faces severe overfishing and habitat degradation threats. In this study, we investigate the pivotal role of ecosystem services in sustaining local livelihoods and overall well-being. By conducting a comprehensive survey of 480 respondents across two districts, we gathered extensive data on demographics, livelihoods, fishing practices, reliance on ecosystem services, and community management participation. The analysis reveals a critical dependence on the Gulf's resources (income, food security, traditions) with gender disparities (men fish, women in pre/post-harvest), but fishing is only allowed in the 10km buffer zone (not the core zone). The findings emphasize the promise of community-based strategies, such as Marine Protected Areas and reviving co-management committees, for achieving sustainable fisheries management. However, we also identify gaps, including the need for more nuanced well-being indicators and improved models for community management participation. To address these challenges, we advocate for sustainable fishing practices, tackling social inequities, especially gender disparities in resource access and decision-making, and investing in healthcare, education, and social safety nets for fishing communities. Promoting alternative livelihoods can alleviate pressure on fish stocks, and empowering local communities through capacity building and community-based management initiatives is crucial for ensuring the long-term sustainability of both the Gulf of Mannar ecosystem and the well-being of its dependent communities. This multifaceted approach holds significant promise for balancing ecological health with human prosperity.

Arsenic is a prevalent environmental pollutant with recognized carcinogenic properties. Liver fibrosis is a frequent consequence of arsenic poisoning, with the activation of hepatic stellate cells (HSCs) being a central event. Solute Carrier Family 7 Member 11 (SLC7A11), a pivotal regulator of ferroptosis, may be involved in the process of arsenic-induced liver fibrosis. This study utilized lentiviral vector-mediated SLC7A11 silencing in LX-2 cells (a type of human hepatic stellate cells) to establish an SLC7A11 knockout cell model, which was then exposed to sodium arsenite (NaAsO2). Protein interactions were assessed through Protein Immunoprecipitation (IP), and protein levels were evaluated via Western blot analysis. It was found that NaAsO2 decreased cellular Fe2+ levels and nuclear receptor co-activator 4 (NCOA4) expression, with SLC7A11 silencing reversing these effects. Additionally, IP analysis revealed an interaction between Beclin1 and SLC7A11 proteins in LX-2 cells exposed to NaAsO2. Silencing SLC7A11 attenuated the reduction in Tumor Protein p53(P53), and p-mammalian target of rapamycin (p-mTOR) protein levels, along with the rise in Beclin1, Phosphorylated adenosine monophosphate activated protein kinase (p-AMPK), α-smooth muscle actin (α-SMA) and Fibroblast activation protein-α (FAP) induced by NaAsO2. Consequently, SLC7A11 silencing promoted cellular ferroptosis, reduced autophagy levels through the P53/AMPK/mTOR pathway, and inhibited HSC activation by NaAsO2, potentially mitigating liver fibrosis.

As the aging of the world accelerates, clarifying the relationship between cultural differences and ageism is an urgent issue. Therefore, in this study, we conducted a correlation analysis between the six cultural scales of Hofstede et al. [1] and the 10 ageism scales calculated from data on 35,232 people from 31 countries included in the World Values Survey Wave 6 by Inglehart et al. [2]. The results of a partial correlation analysis controlling for economic and demographic factors showed that the cultural scales were correlated with ageism. This is the first study to show that diverse cultural scales are related to multiple dimensions of ageism.

This paper addresses the challenges faced by icebreakers in polar environments, particularly the difficulty in sensing underwater ice formations when navigating through thick ice layers, which often results in suboptimal icebreaking effectiveness. To overcome these challenges, this paper introduces a novel underwater robot equipped with both sensing and ice-breaking capabilities. We propose a path planning method for icebreaking that leverages the synergistic capabilities of the Safe Particle Swarm Optimization and Genetic Algorithm (GA-SPSO). The GA-SPSO algorithm integrates the global search prowess of the particle swarm optimization with the local optimization strength of the genetic algorithm, enabling efficient and adaptive path planning in complex ice environments. The underwater unmanned vehicle (UUV)-assisted icebreaking approach developed here utilizes the UUV's flexibility and high-precision environmental sensing to provide real-time optimization suggestions for icebreaker navigation paths. Simulation results demonstrate that the GA-SPSO algorithm not only effectively circumvents hazardous areas but also significantly reduces the energy consumption and operational time of icebreakers, thereby enhancing the safety and stability of navigation. When compared to the conventional Safe Particle Swarm Optimization (SPSO), our approach shows marked improvements in path length, convergence speed, and obstacle avoidance capabilities, significantly enhancing the success and efficiency of polar navigation missions.

The integration of generative AI (GAI) into the financial sector has brought about significant advancements, offering new solutions for various financial tasks. This review paper provides a comprehensive examination of recent trends and developments at the intersection of GAI and finance. By utilizing an advanced topic modeling method, BERTopic, we systematically categorize and analyze existing research to uncover predominant themes and emerging areas of interest. Our findings reveal the transformative impact of finance-specific large language models (LLMs), the innovative use of generative adversarial networks (GANs) in synthetic financial data generation, and the pressing necessity of a new regulatory framework to govern the use of GAI in the finance sector. This paper aims to provide researchers and practitioners with a structured overview of the current landscape of GAI in finance, offering insights into both the opportunities and challenges presented by these advanced technologies.

Based on the composite perspective of environment-building-resource(EBR), influencing factors of the greenness of rural buildings were sorted out by brainstorming and expert consultation, an innovative comprehensive evaluation system was constructed and the weight ofthe impact factors were calculated by fuzzy analytic network process(FANP). The EBR greenness comprehensive scoring standards of each influence factor were established by means of questionnaire, field measurement and numerical simulation. As a typical representative of human populated areas in southwest China, 13 villages in the second circle of Chengdu were selected as case study areas by means of the regional average distribution theory and minimum sampling criteria. Innovative combination of obstacle degree model and spatial interpolation analysis, the key factors affecting the greening of rural buildings were diagnosed. The results showed that, indoor thermal environment(E21), indoor light environment(E22), popularity of biogas facilities (R12), green building material usage(R13) have a significant impact on the EBR greenness score. The EBR score of study area shows a spatial distribution pattern of high in the west and low in the east, with extremely uneven scores in various dimensions. According to the key factors obtained from the systematic evaluation, the refined exploration of promotion strategies and measures was carried out, the greenness improvement suggestion was put forward.

Circular RNAs (circRNAs) are covalently closed RNAs that are present in all eukaryotes tested. CircRNAs are less abundantly expressed than mRNAs. Recent RNAseq analyses indicate that more than 800,000 circRNA isoforms exist in humans, which is more than twice the number of currently known mRNA isoforms. CircRNAs are generated through backsplicing that depends on pre-mRNA structures, which are influenced by intronic elements, for example primate-specific Alu elements, leading to species-specific circRNAs. CircRNAs are mostly cytosolic, stable and influence cells by sequestering miRNAs and RNA-binding proteins. We review the increasing evidence that circRNAs are translated into proteins using several cap-independent translational mechanisms, that include internal ribosomal entry sites, N6-methyladenosine RNA modification, adenosine to inosine RNA editing and interaction with the eIF4A3 component of the exon junction complex. CircRNA are translated under conditions that favor cap-independent translation, notably in cancer. CircRNA-encoded proteins are shorter than mRNA-encoded proteins and overall have a high propensity for phase separation. In summary, circRNA encoded proteins are translated under particular cellular conditions and contribute to proteome diversity and pathophysiology.

The use of thiosemicarbazones (TSCs) as ligands for the functionalization of nanoparticles (NP) for various purposes, such as the covalent immobilization is fueled by their modular character (thiosemicarbazides + carbonyl compound), allowing enormously broad variation of up to four substituents on the main R1R2C=N(1)–NH–C(S)–N(4)R3R4 core. For R1 and R2 we introduced di-2-pyridyl ketone for the coordination of metals and 9-anthraldehyde for luminescence. R3 and R4 substituents were varied for various purposes. Amino acids were functionalized at the N4 position to [R1R2TSC–spacer–amino acid] conjugates for future peptide conjugation or for direct anchoring to NP via their carboxylic function. Further direct NP anchoring functions such as phosphonic acid (OP(OH)2), glucose, o-hydroquinone, OH, and thiol (SH) were introduced with or without separation through hydrocarbon spacer units such as phenyl, cyclohexyl, benzyl, ethyl and methyl in [R1R2TSC–spacer–anchor group] conjugates. [R1R2TSC–spacer–end group] conjugates including OH, S-Bn (Bn = benzyl), NH-Boc (Boc = tert-butyloxycarbonyl), COOtBu, or N3 end groups were produced for the facile formation of amide, ester, or triazine conjugates through click chemistry. The synthesis of the thiosemicarbazides H2NH–C(S)–NR3R4 starting from amines, including amino acids, SCCl2 or CS2, and hydrazine and their condensation with dipyridyl ketone and anthraldehyde lead finally to 34 new TSC derivatives. They were synthesized in up to six steps with overall yields ranging from 10 to 85% and were characterized by a combination of elemental analyses, mass spectrometry, and magnetic nuclear resonance spectroscopy. UV-vis absorption and photoluminescence spectroscopy allowed to easily trace the dipyridyl imine and anthracene chromophores.

The layer-by-layer (LBL) fabrication method allows for controlled microstructure morphology and vertical component distribution, and also offers a reproducible and efficient technique for fabricating large-scale organic solar cells (OSCs). In this study, polymer D18 and PYIT-OD are employed to fabricate all-polymer solar cells (all-PSCs) using the LBL method. Morphological studies reveal that the use of additives optimizes the microstructure of the active layer, enhancing the crystallinity and charge transport capability. The optimized device with 2% CN additive significantly reduces bimolecular recombination and trap-assisted recombination. All-PSCs fabricated by the LBL method based on D18/PYIT-OD deliver a power conversion efficiency (PCE) of 15.07%. Our study demonstrates the great potential of additive engineering via LBL fabrication method in regulating microstructure of active layers, suppressing charge recombination, and enhancing the photovoltaic performance of devices.

Coal bottom ash (CBA) is a byproduct of coal-burning power plants. This material can be used as a fine aggregate replacement in concrete to reduce global natural material depletion. Concrete usage is increasing rapidly; subsequently, the industry’s carbon footprint is increasing. Using CBA in the construction industry will reduce the technical and economic problems associated with power plants by reducing solid waste. This project aimed to determine if adding new sustainable materials, such as CBA, to concrete will reduce natural raw material usage, energy consumption, and greenhouse gas emissions while improving performance. This study included two projects: comparing increased CBA content to the two-control project and determining the optimum content based on the compressive strength. The optimum CBA content is 50%, which reduces fine aggregate usage in a concrete mix by 50% while maintaining equivalent or better concrete strength than a pure Portland concrete mix without CBA. The air content of the concrete mix containing % CBA decreased with increased CBA content and compressive strength, possibly due to the spacing factor of the voids in the mix and CBA’s porous and fineness behavior. The CBA optimum content had a unit weight lower than the controls for both projects, which makes the CBA mix a lightweight concrete. Using this material can significantly reduce natural material usage and environmental harm by reducing CBA waste disposal and improving concrete performance.

Along with the familiar Rossby–Haurwitz waves, two-dimensional flows on the surface of a rotating sphere in the regime of zonostrophic turbulence harbour another class of waves known as zonons. Zonons are wave packets produced by energetic large-scale Rossby–Haurwitz wave modes `enslaving’ other wave modes. They propagate westward with the phase speed of the enslaving modes. Zonons can be visualized as enslaving modes’ `ringing’ in the enslaved ones with the frequencies of the former, the property that renders zonons non-dispersive. Zonons reside in high-shear regions confined between the opposing zonal jets yet they are mainly attached to westward jets and sustained by the ensuing barotropic instability. They exchange energy with the mean flow while preserving their identity in a fully turbulent environment, a feature characteristic of solitary waves. The goal of this study is to deepen our understanding of zonons’ physics using direct numerical simulations, a weakly non-linear theory, and asymptotic analysis, and ascertain that zonons are indeed isomorphic to solitary waves in the Korteweg - de Vries framework. Having this isomorphism established, the analysis is extended to eddies detected in the atmospheres of Jupiter and Saturn based upon the observed mean zonal velocity profiles and earlier findings that circulations on both planets obey the regime of zonostrophic macroturbulence. Not only the analysis confirms that many eddies and eddy trains on both giant planets indeed possess properties of zonons, but the theory also correctly predicts latitudinal bands that confine zonal trajectories of the eddies.

The Azores Archipelago is a collection of volcanic islands near northwestern Portugal in the Atlantic Ocean. Because of the importance of accurate environmental monitoring for the advancement of research, transportation and tourism, a LoRaWan Sensor Network was developed to monitor levels of air pollution across these islands. This study presents an approach to the implementation of a blockchain network that is both lightweight and scalable, with the goal of preventing man-in-the-middle attacks on the design of sensor networks.

Background: The aim of this audit is to evaluate the characteristics of dental infections requiring hospitalisations, which may help improve preventative and management policies. Methods: This study retrospectively evaluated the patients’ records admitted to a public hospital due to dental infections between 2018 and 2019. Results: A total of 102 patients, mostly in thirties with equal gender distribution were admitted with dental infections, presenting with pain (100%), swelling (99%), Trismus (40.2%), dysphagia (27.4%), fever (21%) >37°C, Tachycardia (24.75%) and Tachypnoea (9.3%). Most patients presented (68%) on weekends, outside regular working hours and public holidays. 54 (52.5%) patients had taken prior antibiotics. Dental Caries, smoking, mental health issues and illicit drug use were featured strongly. The majority of patients (56.4%) underwent treatment under local anaesthesia. The total length of hospital stay was 271 days (mean 2.66). Augmentin was the most prescribed antibiotics. Complications were reported in 8.8% patients, primarily related to airway compromise. Conclusion: Dental infections leading to hospitalizations continue to be a burden on the healthcare system. A notable finding was the presentations primarily on weekends, outside regular hours and public holidays and the majority requiring dental intervention under local anaesthesia. Provision of on call emergency dental services may reduce length of hospital stay and admissions.

Domestic crime, conflict, and instability pose a significant threat to many contemporary governments. These challenges have proven to be particularly acute within modern-day Mexico. While there have been significant developments in predicting intrastate armed and electoral conflict in various contemporary settings, such efforts have thus far been limited in their use of spatial as well as temporal correlations, as well as in the features they have consid- ered. Machine learning, especially deep learning, has been proven to be highly effective in predicting future conflicts using word embeddings in Convolutional Neural Networks (CNN) but lacks the spatial structure and, due to the black box nature, cannot explain the importance of predictors. We develop a novel methodology using machine learning that can accurately classify future anti-government violence in Mexico. We further demonstrate that our approach can identify important leading predictors of such violence. This can help policymakers make informed decisions and can also help governments and NGOs better allocate security and humanitarian resources, which could prove beneficial in tackling this problem. Using a variety of political event aggregations from the ICEWS database alongside other textual and demographic features, we trained various classical machine learning algorithms, including but not limited to Logistic Regression, Random Forest, XGBoost, and a Voting classifier. We considered a mix of CNN + Long Short Term Memory (LSTM) networks to decode the spatial and temporal relationship in the data. The performance of all the black box deep learning models was not at par with the classical machine learning models. We also evaluated the temporal relationships in the data to identify important predictors that fuel anti-government violence along with their directions using Shapley additive values. The voting classifier, utilizing a subset of features derived from LASSO across 100 simulations, consistently surpasses alternative models in performance and demonstrates efficacy in accu- rately classifying future anti-government conflicts. Notably, Random Forest feature importance indicates that some features, including but not limited to homicides, accidents, material conflicts, and positive worded citizen information sentiments emerge as pivotal predictors in the classification of anti-government conflicts. Finally, we conclude the research by analysing the spatial structure of the data using Moran’s I index extended version for spatiotemporal data to identify the global spatial dependency and local clusters followed by modelling the data spatially and evaluating the same using Gaussian Process Boost(GPBoost). The global spatial autocorrelation is minimal, characterized by local- ized conflicts cluster within the region. Furthermore, in Phase 3, the Voting Classifier method demonstrates superior performance over GPBoost, leading to the inference that no substantial spatial dependency exists among the various locations.

To secure computers and information systems from attackers taking advantage of vulnerabilities in the system to commit cybercrime, several methods have been proposed for real-time detection of vulnerabilities to improve security around information systems. Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system. As there are different types of cyberattacks, each of the existing state-of-the-art machine learning models depends on different algorithms for training which also impact their suitability for detection of a particular type of cyberattack. In this research, we analyzed each of the current state-of-theart machine learning models for different types of cyberattack detection from the past 10 years with a major emphasis on the most recent works for comparative study to identify the knowledge gap where work is still needed to be done with regard to detection of each category of cyberattack

The study evaluated potassium peroxymonosulfate (PPMS) efficacy against rifampicin-resistant Salmonella Infantis (rif-SI), Escherichia coli (E. coli), Salmonella Infantis (SI), Newcastle disease virus (NDV) and avian influenza virus (AIV). The assessment encompassed varied concentrations, organic material conditions, and exposure durations to comprehensively evaluate PPMS efficacy. Moreover, PPMS’s efficacy was tested on diverse carrier surfaces and clothing to evaluate its bactericidal and virucidal potential. At the recommended concentrations (1X), PPMS effectively inactivated all pathogens within 5 sec, except for NDV, which required 30 sec in the presence of organic materials. At 0.5X, PPMS successfully inactivated E. coli, AIV and NDV within 5 sec in the absence of organic material. However, rif-SI and SI necessitated 30 sec for inactivation. Most pathogens were inactivated within 30 sec, with the exception for AIV, which was inactivated within 5 sec. PPMS effectively eliminated rif-SI on all carriers within 30 sec. Moreover, at both concentrations, PPMS successfully inactivated AIV on all carriers within 30 sec, except on stainless steel at 0.5X. Furthermore, PPMS at both concentrations required 5 and 30 sec, respectively, to inactivate AIV on the rayon sheet. Therefore, due to its demonstrated efficacy against a wide range of pathogens across diverse surfaces, PPMS emerges as a crucial alternative disinfectant significantly enhancing biosecurity on and around chicken farms. found in and around animal farms, slaughterhouses, and hospitals.

Calcretes are indurated terrestrial carbonates that are widespread in arid and semi-arid settings and serve as important archives of present and past environments. Here we use geochemical tools to explore the nature and origin of calcretes documented from tropical Niue Island in the Southwest Pacific. The study recognizes two types of calcretes that differ in their mineral assemblage, microfabrics, elemental chemistry and carbon and oxygen isotopes. The calcretes common in the paleo-lagoon soils consist of 90% low-Mg calcite and ~10% highly weathered Mg-Al silicates. These pedogenic calcretes formed in the soil profiles within the vadose zone and bear the following distinctions: (i) Fe/Al ratio of 0.75, identical to the ratio in soils (Fe/Al=0.76 ±0.5), substantiates the link between the calcretes and soils; (ii) presence of rhizoliths, root voids, micritic nodules and clasts are consistent with a pedogenic calcrete fabric, and (iii) 13C and 18O depletions of -10.6‰ and -5.3‰, respectively, are compatible with carbon sources from microbial and roots respiration, and formation in oxygen isotope equilibrium with vadose waters. Unlike the pedogenic calcrete, a rare calcrete from the coastal terrace contains an exceptionally rare hydrotalcite mineral (65%) coated by microbial films. We contend that the hydrotalcite-rich calcrete was deposited through interaction of dolomite with seawater, similar to the method of producing hydrotalcite in the laboratory. 13C and 18O enrichments of 0.8 to 1.7‰ and -1.0 to -1.6‰, respectively, are in agreement with (i) mixed carbon sources consisting of microbial CO2 degassing, seawater HCO3 and dolomite dissolution, and (ii) oxygen isotope equilibration with a seawater-derived fluid.

Soil formation results from the weathering and alteration of bedrock, influenced by climatic conditions and biotic factors, including living organisms. The mineralogical composition of the parent material, along with plant species and soil microorganisms, forms the foundational elements of an ecosystem's energy cycle. Afforestation in arid-semi arid regions plays a crucial role in preventing erosion and enhancing soil quality, offering significant economic and ecological benefits. This study assessed the impact of parent material diversity on soil physicochemical properties, microbial basal respiration (MR), and microbiological characteristics, as well as their subsequent effects on plant growth, 15 years post-afforestation. For this purpose, various soil physicochemical parameters, MR, soil microbial biomass carbon (Cmic), stoichiometry (microbial quotient= Cmic/Corg = qMic and metabolic quotient = MR/Cmic = qCO2), and tree growth metrics such as height and diameter were measured. The results of the one-way ANOVA indicated that afforested soils on limestone bedrock exhibited significantly better physicochemical and microbiological properties, as well as tree growth parameters, compared to those on andesite. Notably, sensitive microbial properties such as Cmic, MR, and qMic were positively influenced by afforestation. The highest Cmic (323 g C kg−1) and MR (1.3 CO2–C g−1 h−1) values were recorded in limestone-derived soils. Currently, the measured properties of soils can be ranked as LS>AS>LC>AC. Conversely, the highest qCO2 values were observed in the control plots of andesite parent material (7.22). This study highlights the importance of selecting appropriate parent material and understanding soil characteristics to optimize afforestation efforts in bare areas. As a result, the higher plant growth capacity and carbon retention of limestone soil indicate that it has high microbial biomass and microbial activity (qMic).

This study comprehensively explores Serbia's Disaster (Risk) Management System, aiming to critically evaluate its inherent strengths and weaknesses. Using descriptive-analytical methods and qualitative interpretation, SWOT analysis was applied to collect data from scientific papers, books, and institutional reports. This study delves deeply into the nuances of Serbia's Disaster Management Framework, revealing a nuanced landscape of strengths, weaknesses, and strategic improvement opportunities. Identified strengths underscore a robust foundation characterized by proficient professionals, state-of-the-art technology, and cohesive teamwork, all pivotal for effective emergency preparedness and response. Conversely, weaknesses underscore pressing imperatives for enhancements in regulatory enforcement, resource allocation, and infrastructure upgrades, presently hampering the framework's efficacy and response readiness. This research contributes to the ongoing discourse on disaster risk management and serves as a catalyst for further scholarly inquiry and policy formulation. By mapping out the structure of Serbia’s Disaster (Risk) Management Framework and integrating diverse data sources, the study enriches theoretical models and lays the groundwork for practical policy interventions. Its findings, including precise recommendations for policy reform and strategic improvements, provide valuable insights for policymakers, emergency management experts, and stakeholders seeking to enhance disaster preparedness and response capabilities on both national and global scales.

Video self-supervised learning (VideoSSL) offers significant potential for reducing annotation costs and enhancing a wide range of downstream tasks in video understanding. The ultimate goal of VideoSSL is to achieve human-level video intelligence across a spectrum of tasks, from low-level tasks such as pixel temporal correspondence to high-level complex spatio-temporal tasks like action recognition. However, most existing VideoSSL methods focus on isolated aspects of this spectrum and fail to integrate different levels of task complexity. Our study presents the first comprehensive survey that connects all families of VideoSSL methods. We provide a detailed review of the full spectrum of VideoSSL, from low to high levels, by conceptually linking their self-supervised learning objectives and including a comprehensive categorization. Our extensive evaluation highlights the strengths and limitations of each SSL objective across various downstream task families. We also detail the challenges in current VideoSSL research such as data curation, interpretability, deployment, and privacy concerns, an area that previous surveys have not thoroughly explored. In addressing these challenges, we recognize the strengths of existing methods in addressing these challenges and outline future directions for research.

Orthodontic appliances may cause discomfort for patients. It could influence person‘s psychological well–being. The aim was to examine psychological health of patients wearing orthodontic appliances. It is important to analyze well-being of patients during orthodontic treatment because it is started in a young age and it may affect one’s psychological health. Therefore, for doctors and patients it is important to understand and take every aspect of the treatment into consideration when deciding when to start the treatment and what appliance to choose. 339 patients answered anonymous questionnaire. They were divided into four groups according to their age and type of appliance. Main reasons to seek treatment were crooked teeth and bad bite. Statistically signifi-cant difference was between women and men as women seeked treatment because of crooked teeth, meanwhile men indicated bad bite as main reason. 48.7% of subjects noted that they were feeling good during treatment, however, 4% of all patients noted that they were feeling bad. 45% of subjects stated that they felt unhappy at least sometimes. 43% of subjects felt stress. Even though patients indicated various negative aspects on their well-being during treatment, for the majority of the subjects end results significantly increased their psychological well-being.

Background/Objectives: We defined the value of a machine learning algorithm to distinguish between the EEG response to no light or any light stimulation, and between red or green light stimulation in awake volunteers with closed eyelids. This new method of EEG analysis is visionary in the understanding of visual signal processing and will facilitate anaesthetic depth research. Methods: X-gradient boosting models were used to classify the cortical response to VEP stimulation (no light vs. any light stimulation; red vs. green light stimulation). For each of the two classifications, three scenarios were tested: training and prediction in all participants (all), training and prediction in one participant (individual), training across all but one participant with prediction in the participant left out (one out). Results: Ninety-four Caucasian adults were included. The machine learning algorithm had a very high predictive value and accuracy in differentiating between no light and any light stimulation (AUCROCall: 0.96; accuracyall: 0.94; AUCROCindividual: 0.96±0.05, accuracyindividual: 0.94±0.05; AUCROConeout: 0.98±0.04; accuracyo-neout:0.96±0.04). The machine learning algorithm was highly predictive and accurate in distinguishing between green and red colour stimulation (AUCROCall: 0.97; accuracyall: 0.91; AUCROCin-dividual: 0.98±0.04, accuracyindividual: 0.96±0.04; AUCROConeout: 0.96±0.05; accuracyoneout: 0.93±0.06). The predictive value and accuracy of both classification tasks was comparable between males and females. Conclusions: Machine learning algorithms could almost continuously and reliably differentiate between the cortical EEG responses to no light or any light stimulation and between green or red colour stimulation using VEPs in awake female and male volunteers with eyes closed. Our findings may open new possibilities for using VEPs in the intraoperative setting.

After the end of colonial rule in 1997, the Hong Kong education system has been experiencing a policy reform on Senior Secondary Education (NSS) Curriculum commenced in September 2009 aiming to educate students as globalized Hong Kong citizens for the Western. Although previous scholars argued that it is hard to differentiate between domestic values and the Western values in account of curriculum development (Sewpaul, 2007), this study demonstrates an analysis using the dichotomy to investigate how local curriculum, especially in the post-colonial areas, embrace both the Western values and domestic values. Using content analysis on the NSS curriculum guides, this article evaluates the influence of the Western values and Chinese values in the NSS curriculum through investigating: (1) how the Western values and Chinese values was incorporated into the curriculum throughout its development (2) why some values are more significantly highlighted in the curriculum guide. Findings include that more Chinese values are involved in the curriculum documents. This may be because of the upholding of domestic values as a post-colonial city. The Western values which are academically related are greatly incorporated into the local curriculum.

This study aimed to evaluate the impact of the built environment (i.e., walk, transit, and bike scores) on the location and transportation or “alternative transportation” credit (LTc1) in Leadership in Energy and Environmental Design for Existing Buildings version 4 (LEED-EB-v4) Platinum (n1 = 24), Gold (n2 = 112), Silver (n3 = 46), and Certified (n4 = 34) office buildings in the USA. Spearman’s test was used to estimate the correlation between built environment scores and LTc1 scores for each certification level. The Wilcoxon–Mann–Whitney test was used to estimate pairwise comparison between unpaired Platinum, Gold, Silver, and Certified groups. The Platinum, Gold, and Silver certification levels showed positive and significant correlations between the built environment and LTc1 (0.44 ≤ r ≤ 0.74, p ≤ 0.0312). By contrast, Certified certification levels showed a non-significant correlation (0.18 ≤ r ≤ 0.33, p ≥ 0.0579). Pairwise comparison showed that Platinum and Gold groups outperformed Certified groups in terms of built environment and LTc1 scores (Cliff’s δ ≥ 0.37, p ≤ 0.0099). Thus, for LEED-EBv4-certified projects located in downtown areas, LTc1 can be seen as a significant lever to achieve high levels of LEED certification.

Large Language Models (LLMs) have demonstrated promising capabilities to solve complex tasks in critical sectors such as healthcare. However, LLMs are limited by their training data which is often outdated, the tendency to generate inaccurate ("hallucinated") content and a lack of transparency in the content they generate. To address these limitations, retrieval augmented generation (RAG) grounds the responses of LLMs by exposing them to external knowledge sources. However, in the healthcare domain there is currently a lack of systematic understanding of which datasets, RAG methodologies and evaluation frameworks are available. This review aims to bridge this gap by assessing RAG-based approaches employed by LLMs in healthcare, focusing on the different steps of retrieval, augmentation and generation. Additionally, we identify the limitations, strengths and gaps in the existing literature. Our synthesis shows that proprietary models such as GPT-3.5/4 are the most used for RAG applications in healthcare. Also, there is a lack of standardized evaluation frameworks for RAG-based applications. In addition, the majority of the studies do not assess or address ethical considerations related to RAG in healthcare. It is important to account for ethical challenges that are inherent when AI systems are implemented in the clinical setting. Lastly, we highlight the need for further research and development to ensure responsible and effective adoption of RAG in the medical domain.

Epilepsy is one of the most prevalent and serious brain disorders, affecting 70 million people worldwide. Antiseizure medications (ASMs) though relieve symptoms and prevent the occurrence of future seizures in epileptic patients have limited effect on epileptogenesis. Addressing the multifaceted nature of epileptogenesis and its association with Nod-like receptor family pyrin domain containing 3 (NLRP3) inflammasome-mediated neuroinflammation requires a comprehensive understanding of the underlying mechanisms for development of targeted therapeutic strategies beyond conventional antiseizure treatments. Several types of NLRP3 inhibitors have been developed and their effect has been validated both in vitro and in vivo models of epileptogenesis. In this review, we discuss the advances in understanding the regulatory mechanisms of NLRP3 activation as well as progress made and challenges facing in the development of NLRP3 inhibitors for the treatment of epilepsy.

This research aims to explore the integration method of deep learning and large language models in speech recognition to improve the system’s recognition accuracy and ability to handle complex contexts. Deep neural network (DNN), convolutional neural network (CNN), long short-term memory network (LSTM) and Transformer-based large language model are used to build an integrated acoustic and language model framework. Experiments on TIMIT, LibriSpeech and Common Voice datasets show that the ensemble model shows significant improvements in both word error rate (WER) and real-time factor (RTF) compared to traditional models. Especially in terms of adaptability to multiple languages and accent changes, the model shows superior performance. The conclusion shows that through technology integration, the performance of the speech recognition system in complex environments can be effectively improved, providing a new direction for the future development of speech recognition technology.

This paper investigates the potential of different fermentation feedstocks towards succinic acid production. Three alternative flowsheets were constructed and modelled in SuperPro Designer™, utilizing different fermentation substrates: crude glycerol (a by-product of the biodiesel industry), a commercial 95% glucose syrup and pure glycerol. Techno-economic analysis of the modelled plants showed that all three potential investments can be economically profitable, with the crude glycerol case as the most promising one. The succinic acid production cost for the crude glycerol scenario is estimated at 3.59 $/kg, while a thorough study of the capacity effect to the economics showed that it could drop as low as $2.6 $/kg. Parametric analysis and optimization performed on a flowsheet level, indicated opportunities for lowering the production cost down to 3 $/kg, a value that could pave the framework for a further potential decrease in the selling price of the product.

The genus Strophantus belongs to the Apocynaceae family of flowering plants which grows primarily in tropical Africa. The plants are widely used in traditional herbal medicine. S. sarmentosus, in particular, is used for the treatment of, e.g., joint pain and rheumatoid arthritis, wound infections, head lice, diarrhoea, snake bite, and eye conditions. Despite the widespread use, dedicated research characterizing bioactive plant components is scarce. Investigations focussed mainly on the cardenolides, because of their cardioactivity and historical use as cardiotonic. There are also studies concerning the antibacterial, antioxidant and anti-inflammatory activity of plant extracts. This review summarizes the present knowledge about the biochemical and analytical reserach on Strophantus, in general, and S. sarmentosus, in particular, and describes the current state-of-the-field based on the available sientific literature.

Introduction: The World Health Organization (WHO) recommends visual inspection with acetic acid (VIA) for cervical cancer screening (CCS) in lower-resource settings; however, quality varies widely, and it is difficult to maintain a well-trained cadre of providers. The Smartphone-Enhanced Visual Inspection with Acetic acid (SEVIA) program was designed to offer secure sharing of cervical images and real-time supportive supervision to health care workers providing screening in semirural Tanzania, in order to improve quality and accuracy of visual assessment of the cervix for treatment. The purpose of this evaluation was to document early learnings from patients, providers, and higher-level program stakeholders, on barriers and enablers to program implementation. Methods: From September 9th to December 8th, 2016, observational activities and open-ended interviews were conducted with image reviewers (n= 5), providers (n=17), community mobilizers (n=14), patients (n=21), supervisors (n=4) and implementation partners (n=5) involved with SEVIA. Sixty-six interviews were conducted at 14 facilities, in all 5 of the program regions. Results SEVIA was found to be a highly regarded tool for the enhancement of CCS services in Northern Tanzania. Acceptability, adoption, appropriateness, feasibility, and coverage of the intervention were highly recognized. It appeared to be an effective means of improving good clinical practice among providers and fit seamlessly into existing roles and processes. Barriers to implementation included network connectivity issues, and community misconceptions and adoption of CCS more generally. Conclusion: SEVIA is a practical and feasible mobile health intervention and tool that easily integrated into the National CCS program to enhance quality of care. With the introduction of HPV DNA testing as a primary screening strategy for cervical cancer prevention in settings such as Tanzania, the role of a mobile health platform for program surveillance, tracking follow-up care, and quality assurance of visual assessment of the cervix for treatment (in women who test positive for high-risk HPV) further supports the importance of programs, such as SEVIA, in low resource contexts. Further expansion of the program, especially to rural areas where screening providers can benefit from virtual support for screening services through the use of the mobile App, could strengthen the delivery of services within the national cervical cancer prevention program.

The Geopyörä breakage test uses two counter-rotating wheels to nip and crush rock specimens with a tightly controlled gap between rollers. The force applied and energy consumed during breakage are measured with instrumentation. In contrast to drop weigh test (DWT) methods, the breakage energy is a response to the rock compressive strength and degree of compression, not a controlled test input, such as the kinetic input energy of a falling weight. This paper presents the detailed measures conducted to evaluate the accuracy and precision of energy measurements across various ore types using the Geopyörä device. While force measurement was assessed just for its precision. The outputs are compared directly to the DWT measures of fragmentation at the same energy and fitted A and b parameters. The test reproducibility was evaluated using a Round-Robin methodology, testing several samples in multiple laboratories. The results confirmed that the new test has sufficient accuracy to match DWT results and excellent precision to assure reproducibility.

The Herpotrichiellaceae family is an important group of dematiaceous filamentous fungi, associated with a variety of pathogenic fungal species causing Chromoblastomycosis (CBM) and Phaeohyphomycosis (PHM), both with polymorphic clinical manifestations and worldwide incidence. Currently, the identification of this family and determination of the causative agent is challenging due to the subjectivity of morphological identification methods, necessitating the use of molecular techniques to complement diagnosis. In this context, genetic sequencing of the Internal Transcribed Spacer (ITS) has become the norm due to a lack of alternative molecular tools for identifying these agents. Therefore, this study aimed to develop PCR-Multiplex methodologies to address this gap. Sequences from the ITS and Large subunit (LSU) of ribosomal DNA were used, and after manual curation and in vitro analyses, primers were synthesized for the identification of the aforementioned targets. The primers were optimized and validated in vitro, resulting in two PCR-Multiplex methodologies: one for identifying the Herpotrichiellaceae family and the bantiana clade, and another for determining the species Fonsecaea pedrosoi and Fonsecaea monophora. Ultimately, the assays developed in this study aim to complement other identification approaches for these agents, reducing the need for sequencing, improving the management of these infections, and enhancing the accuracy of epidemiological information.

Background: Self-harm (SH) refers to self-injury or intentional self-poisoning with varying degrees of suicidal intent and is a major public health issue for children and adolescents (C&A) worldwide. Given significant gaps exist in our understanding of the associated psychopathology in C&A, this paper outlines the protocol for a prospective clinical study examining risk factors of SH and additional candidate parameters (not routinely assessed) during an acute SH episode. Methods: The EXPAAND (EXploring Psychiatric and Attentional risk-factors in Adolescents Needing intervention for Deliberate self-harm) is a randomised control trial to assess additional novel candidate risk factors for SH in C&A and to evaluate the effectiveness of SH-targeted brief psychological intervention (Therapeutic Assessment (TA)), within a real-world acute clinical setting, as we include neurodiversity and gender diversity in this study. EXPAAND is conducted in 4 phases: (i) recruitment & randomisation; (ii) extended assessment; (iii) randomised intervention; and (iv) follow-up observational period to ascertain clinical outcomes for comparison. Expected Results: We envisage that by diagnosing and treating attentional disorders when detected will mitigate potential confounding effects of these conditions. We also expect that SH-focused TA will be effective in reducing subsequent SH and in improving engagement in follow-up and subsequent treatments.

Skin inflammation associated with chronic diseases has the direct action of keratinocytes in its immunopathogenesis, leading to a series of immune responses. However, there are still no highly targeted treatments, and the development of more specific therapies is highly desirable. In the present work, nanocapsules containing quinizarin (QZ/NC) were developed, evaluating their act in a model of the keratinocytes inflammatory process in vitro with the action of Photodynamic Therapy, analyzing the permeation in a 3D skin model. Physicochemical, stability, cytotoxicity and permeation analyses of the nanomaterials were carried out. The nanocapsules showed desirable physicochemical characteristics and were stable during the analysis period, without spectroscopic modifications. The cell viability test carried out showed no cytotoxicity at the lowest QZ/NC concentrations. The permeation and cellular uptake studies showed the permeation of QZ/NC in 3D skin models and the intracellular incorporation and internalization of the drug, enhancing its action in the drug delivery technique. Promising results were presented using the model developed to induce the inflammatory process in vitro and applying the synthesized nanomaterial in conjunction with PDT, where a decrease in the levels of cytokines analyzed was observed, representing a possible new therapeutic approach for inflammatory skin diseases.

In the face of persistent soil degradation in Benin due to poor agricultural practices, including excessive use of chemical fertilizers, there is an urgent need to seek solutions that integrate microorganisms of interest. The aim of the study was to assess the effect of combining three strains of indigenous arbuscular mycorrhizal fungi on maize production in northern Benin. The study involved 34 growers in Ouénou, Bagou, and Kokey. The experimental set-up consisted of three elementary plots with three treatments. Growth parameters were measured every 15 days, from the 15th to the 60th day after sowing, on ten plants per plot. Plant nutritional status, grain yield and mycorrhization were measured. Results showed that biostimulant + 50% NPK_Urea had similar positive effects on growth parameters to those induced by the application of 100% NPK_Urea. Gains of 30.25 to 36.35% were recorded in plant height at Kokey. On the other hand, biostimulant+ 50% NPK_Urea induced a better phosphorus uptake of 21.08 to 27.77%. In addition, the grain yield of mycorrhizal plants was 8.37% higher than that of plants receiving 100% NPK_Urea at Ouénou. These results show that this technology could be integrated into the agricultural system to promote sustainable maize growing in Benin.

: (1) Background: Hepatitis B core antibodies (anti-HBc) are a marker of hepatitis B virus (HBV) exposure; hence a normal HBV serology profile is characterized by HBV surface antigen (HBsAg) and anti-HBc positivity. However atypical HBV serologies occur and we aimed to determine the prevalence of an atypical profile (HBsAg+/anti-HBc-) in a cohort of people with HIV-1 (PWH) in Botswana. (2) Methods: Plasma samples from an HIV-1 cohort in Botswana (2013-2018) were used. Samples were screened for HBsAg and anti-HBc. Next generation sequencing was done using the GridION platform. Wilcoxon rank-sum test and Chi-squared tests were used for comparison of continuous and categorical variables respectively. (3) Results: HBsAg+/anti-HBc- prevalence was 13.7% (95% CI 10.1 – 18.4) (36/263). HBsAg+/anti-HBc- participants were significantly younger (p<0.001), female (p=0.02), ART naïve (p=0.04) and had detectable HIV viral load (p=0.02). There were no mutational differences in sequences isolated from participants with HBsAg+/anti-HBc- versus those with HBsAg+/anti-HBc+ serology. (4) Conclusions: We report a high HBsAg+/anti-HBc– atypical serology profile prevalence among PWH in Botswana. We caution against HBV testing algorithms that consider only anti-HBc+ samples for HBsAg testing as they are likely to underestimate HBV prevalence. Studies to elucidate the mechanisms and implications of this profile are warranted.

The viral genus Henipavirus includes two highly virulent zoonotic viruses of serious public health concern. Hendra henipavirus and Nipah henipavirus outbreaks are restricted to Australia and Southeast Asia, respectively. Henipavirus genus comprises mostly bat-borne viruses, but exceptions have already been described with novel viruses having rodents and shrews as reservoir animals. In the Americas, scarce evidence supports the circulation of these viruses. In this communication, we report a novel henipa-like virus from opossums (Marmosa demerarae) from a forest fragment area at Peixe-Boi municipality, Brazil, after which the virus was named the Peixe-Boi virus (PBV). The application of next-generation sequencing and metagenomic approach led us to discover the original evidence of a henipa-like virus genome in Brazil and South America and the original description of henipaviruses in marsupial species. These findings emphasize the importance of further studies to characterize PBV and clarify its ecology, impact on public health and its relationship with didelphid marsupials and other henipaviruses.

The X-ray induced spin crossover transition of an Fe(II) molecular thin film in the presence and absence of a magnetic field has been investigated. The thermal activation energy barrier in the soft X-ray activation of the spin crossover transition for [Fe{H2B(pz)2}2(bipy)] molecular thin films is reduced in the presence of an applied magnetic field, as measured through X-ray absorption spectroscopy at various temperatures. The influence of a 1.8 T magnetic field is sufficient to cause deviations from the expected exponential spin state transition behavior that is measured in the field free case. We find that orbital moment diminishes with increasing temperature, relative to the spin moment in the vicinity of room temperature.

Saccharomyces cerevisiae cells are killed by zymocin, a tRNase ribotoxin complex from Kluyveromyces lactis, which cleaves anticodons and inhibits protein synthesis. Zymocin’s action requires specific chemical modification of uridine bases in the anticodon wobble position (U34) by the Elongator complex (Elp1-Elp6). Hence, loss of anticodon modification in mutants lacking Elongator or related KTI (K. lactis Toxin Insensitive) genes protects against tRNA cleavage and confers resistance to the toxin. Here, we show that zymocin can be used as a tool to genetically analyse KTI12, a gene previously shown to code for an Elongator partner protein. From a kti12 mutant pool of zymocin survivors, we identify motifs in Kti12 that are functionally directly coupled to Elongator activity. In addition, shared requirement of U34 modifications for nonsense and missense tRNA suppression (SUP4; SOE1) strongly suggests that Kti12 and Elongator cooperate to assure proper tRNA functioning. We show that the Kti12 motifs are conserved in plant ortholog DRL1/ELO4 from Arabidopsis thaliana and seem to be involved in binding of cofactors (e.g. nucleotides, calmodulin). Elongator interaction defects triggered by mutations in these motifs correlate with phenotypes typical for loss of U34 modification. Thus, tRNA modification by Elongator appears to require physical contact with Kti12, and our preliminary data suggest that metabolic signals may affect proper communication between them.

Nowadays, one of the greatest challenges in Data Meshes revolves around detecting and creating Data Domains and Data Products for providing the ability to adapt easily and quickly to changing business needs. This requires a disciplined approach to identify, differentiate and prioritize distinct data sources according to their content and diversity. The current paper tackles this highly com-plicated issue and suggests a standardized approach that integrates the concept of Data Blueprints with Data Meshes. In essence, a novel standardization framework is proposed that creates Data Products using a metadata semantic enrichment mechanism, the latter also offering Data Domain readiness and alignment. The approach is demonstrated using real-world data produced by mul-tiple sources in a poultry meat production factory. A set of functional attributes is used to compare qualitatively the proposed approach against existing data structures utilized in storage architectures with quite promising results. Finally, experimentation with different scenarios varying in data product complexity and granularity suggests successful performance.

Disasters, whether natural or human-induced, pose significant threats to human lives, property, and infrastructure. This study examines the effectiveness of search and rescue (SAR) dogs in locating survivors during disasters, with a focus on the experiences in Serbia, Croatia, and Slovenia. The primary goals are to evaluate training protocols, operational challenges, success rates, and the overall impact of SAR dogs in disaster scenarios. The findings indicate that SAR dogs greatly enhance the efficiency of disaster response operations. Their superior sense of smell, agility, and ability to manoeuvre through complex terrains make them crucial for quickly locating survivors. However, the performance of SAR dogs is affected by various factors, including the quality of their training, environmental conditions, and the coordination between handlers and dogs. The research highlights several challenges encountered by SAR dogs, such as extreme weather conditions, hazardous terrains, fatigue, and psychological stress. Additionally, limited resources and inconsistent training standards can hinder their effectiveness. The study underscores the importance of standardized training protocols, increased resource allocation, and better coordination among SAR teams. By addressing these challenges, the efficiency of SAR dogs can be further optimized, resulting in more effective disaster responses and higher survival rates. SAR dogs play an essential role in disaster management in Serbia, Croatia, and Slovenia. Ongoing investment in their training and welfare, along with improved operational protocols, will ensure their crucial contribution to saving lives during disasters. This study contributes to a broader understanding of the effectiveness of SAR dogs and provides practical recommendations for enhancing disaster response strategies.

The application of OpenAI's advanced artificial intelligence language model, ChatGPT, in education has garnered widespread attention from the academic community. The openness and intelligence features of ChatGPT demonstrate great potential and value in supporting students' learning, daily life, and communication. This study, grounded in the theoretical frameworks of Innovation Diffusion Theory (IDT) and the Technology Acceptance Model (TAM), conducted a systematic empirical analysis through a questionnaire survey of 677 university students who had used or were currently using ChatGPT. The results indicate that the six perceived attributes of innovation significantly influence university students' behavioral intention to use ChatGPT, while attitudes towards ChatGPT, perceived usefulness, and perceived ease of use indirectly influence students' behavioral intention to continue using ChatGPT. Based on the findings of this study, we propose an extended Technology Acceptance Model (TAM) that incorporates key elements of Innovation Diffusion Theory (IDT) to optimize the application of advanced technologies, such as ChatGPT, in education, thereby improving students' learning efficiency and behavioral performance. These findings not only provide important insights into the complex relationships between college students’ perceptions of ChatdGPT technology and predictors of behavioral intentions, but can also help relevant education departments, higher education institutions, and university teachers to effectively plan and evaluate the use of ChatGPT as a learning tool.

Epigenetic changes regulate gene expression through histone modifications, chromatin remod-eling and proteins interpreter of these modifications. The PRC1 and PRC2 complexes shape gene repression via histone modifications. Specifically, the CBX protein family aids PRC1 recruitment to chromatin, impacting the progressive multistep process driving chromatin silencing. Among family members, CBX3 is a complex protein involved in aberrant epigenetic mechanisms that drive lung cancer progression. CBX3 promotes lung tumorigenesis by interacting with key pathways such as PI3K/AKT, Ras/KRAS, Wnt/β-catenin, MAPK, Notch, and p53, leading to in-creased proliferation, inhibition of apoptosis, and enhanced resistance to therapy. Given our current lack of knowledge, additional research is required to uncover the intricate mechanisms underlying CBX3 activity, as well as its involvement in molecular pathways and its potential biomarker evaluation. Specifically, the dissimilar roles of CBX3 could be reexamined in order to gain a greater insight into lung cancer pathogenesis. This review aims to provide a clear overview of the context-related molecular profile of CBX3, which could be useful for addressing clinical challenges and developing novel targeted therapies based on personalized medicine.

This study investigated how the type and homogenisation parameters of the feed mixture affect the efficiency of the encapsulation process and the microcapsule properties of phenol-rich grape pomace extract (GPE) during the spray drying process with goat whey protein (GW) as wall material. GPE was obtained by solid-liquid extraction of grapes with 50% ethanol. Effects of ultrasonic homogenisation parameters (UB): temperature: 30-50 °C; time: 5-30 min; stabilisation time after homogenisation: 15-45 min, and homogenisation parameters on a magnetic stirrer (MS): temperature (25-50 °C), time (10-60 min) and homogenisation speed (600-1200 rpm) were tested using response surface methodology (RSM) and Box-Behnken design. After selecting the optimal homogenisation conditions, the spray drying process parameters were optimised in the same way, namely: inlet air temperature (160-190 °C), GW fraction (0.5-3.5) and feed flow (6-10 mL/ min). The results showed that GW has a high potential as a wall material in the spray drying process, especially for the purpose of protecting polyphenolic compounds from GPE.

Green hydrogen is a fuel that in the coming years will play a very important role in the energy transition process in developed countries, especially those seeking to reach a level of zero emis-sions, for which reason its demand is expected to increase significantly. This article analyzes the fundamentals to produce hydrogen, with a focus on the oxidation reaction of a thermochemical solar cycle for the dissociation of water vapor. Solar thermochemical cycles have been extensively investigated, but it is still in the development stage by groups of researchers who have focused on finding the right materials and conditions to improve the efficiency of the process, especially at high temperatures. The theoretical foundations are analyzed, compiled from exhaustive scientific investigations related to the oxidation of iron in water vapor, the relationship with the activation energy of the corrosive process, thermodynamic aspects and the kinetic model according to a heterogeneous reaction. In addition, some high temperature oxidation mechanisms, pH effects, reactors and materials (fluidized beds) used are presented. The scientific review indicates that the production of hydrogen through a thermochemical cycle is more efficient than electrochemical processes (electrolysis), if the limitations of the reduction stage of the cycle are overcome.

The development requirements for reusable liquid rocket engines have set higher standards for the reliability design of turbopump structures. To address the issue of bearing failure in turbopumps under harsh conditions such as low temperature, high speed, heavy load, and repeated start-stop cycles, this paper proposes replacing ball bearings with thrust foil bearings. We used liquid nitrogen instead of liquid hydrogen and liquid oxygen to simulate the ultralow temperature and low viscosity operating environment of turbopumps, evaluating the potential feasibility of using thrust foil bearings in this context. The numerical calculations primarily include the formulation of the foil deformation equations based on the link-spring model for the wavy foil and the thin plate finite element model for the top foil. These equations are solved by coupling the Reynolds lubrication equation, the fluid film thickness equation, and the foil deformation equations using the finite difference method, Newton-Raphson method, and finite element method. A detailed analysis is conducted on the effects of rotational speed, fluid film thickness, thrust disk inclination angle, and wavy foil interface friction coefficient on the static and dynamic characteristics of thrust foil bearings. The research findings provide guidance for the application of thrust foil bearings in liquid rocket turbopumps.

Generating electricity from coal combustion is highly associated with ongoing pollution problems that negatively impact the environment. Coal fly ash (CFA) is a predominant waste by-product of coal combustion which is disposed of in exposed ash dams constructed in the vicinity of power stations. Its disposal requires a large piece of land and therefore more land is converted to unproductive disposal sites, degrading the ecosystem. This waste material is classified as a hazardous substance in South Africa due to unacceptable levels of inorganic and persistent organic pollutants and its potential for dust creation. CFA is recycled and sold to the building and construction sectors, but the rate of its utilization is far less than the production rate resulting to high volumes that is stockpiled in disposal sites. More than 500 million tons CFA is produced yearly and over 200 million tons yearly remain unused globally and more CFA will continue to be produced due to high consumer energy demands, especially in countries with heavy reliance on coal for power generation. In this context, the paper discusses production of CFA, pollution problems due to its disposal, examines existing gaps within the scope of ash dam restoration processes and presents opportunities offered by phytoremediation (a low-cost and environmentally friendly technology that utilizes plants to restore the degraded environments). Ecological restoration through the use of socio-economically valuable plants (aromatic plants, legumes and grasses) has potential in addressing societal challenges and consequently impacting positively the livelihood of communities.

Periacetabular osteotomy (PAO) is an effective approach for surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip and limited field of view (FoV) during the surgery, it is challenging for surgeons to perform a PAO surgery. To solve this challenge, we propose a robot-assisted augmented reality (AR)-guided surgical navigation system for PAO. The system mainly consists of a robot arm, an optical tracker, and a Microsoft HoloLens 2 which is a state-of-the-art (SOTA) optical see-through head-mounted display (OST-HMD). For AR guidance, we propose an optical marker-based virtual-physical registration method to estimate a transformation from the optical tracker coordinate system (COS) to the virtual space COS, such that virtual models can be superimposed on the corresponding physical counterparts. Furthermore, to guide the osteotomy, the developed system automatically aligns the bone saw with osteotomy planes planned in preoperative images, and then provides surgeons with not only robot assistance but also AR guidance. Comprehensive experiments were conducted to evaluate both virtual-physical registration accuracy and osteotomy accuracy of the developed navigation system. The proposed virtual-physical registration method achieved an average mean absolute distance error (mADE) of 1.96 ± 0.43 mm. The developed system achieved an average distance deviation of 0.82 ± 0.17 mm and an average angular deviation of 3.77 ± 0.85 . Experimental results demonstrated high virtual-physical registration accuracy. The sub-millimeter distance deviation demonstrated the osteotomy accuracy of the proposed system.

Studies on Medical Geology have up till recently tended to emphasise the harmful effects of geological material and processes. This is perhaps justifiable, given the realisation that many environmental diseases could have causal links with some geo-environmental variables as co-factors, making such studies extremely valuable in the improvement of diagnoses and therapy. However, this review aims to show that in addition to the high value of such research, studies conducted on the beneficial properties of Earth materials also have considerable merit, given their enormous potential for assuaging a wide range of environmental health disorders. For instance, certain geological materials including clay minerals contain active substances that show considerable promise in various applications such as pharmaceutical formulations, aesthetic medicine, and indigenous medicine. This review synthesises current knowledge of how certain geological materials can be exploited in formulating remedies for some human health problems. Reports of the therapeutic uses of clay minerals, zinc oxide (zincite), zeolite, and kaolin are appraised. The review shows that ancient and contemporary use of geological materials such as clay minerals have played crucial roles in the treatment of several human diseases, with recent and ongoing research revealing further development in these applications. Well strategised clinical trials using available resources could give impetus to further research in elucidating the potential of various geomaterials as innovative clinical remedies for some human diseases and infections as well as aid the proper scientific documentation of their natural uses.

Satellite-based rainfall estimation products provide a vital alternative source of rainfall data in areas where conventional precipitation measurement is not readily available. In order to facilitate the use of these products there is the need to evaluate their accuracies. This study evaluated the accuracy of three satellite rainfall products; TMPA 3B42RT, TMPA 3B42 and CMORPH in the Pra basin (23,330 km²) of Ghana. The evaluation was through the point-to-pixel method by comparing 0.25°x 0.25° satellite grids to gauged rainfall based on gauge locations and analyzed statistically using correlation coefficient (r), bias and percent bias (pBias) as the performance verification methods. Seven (7) gauge stations with no missing data for the period of 2003-2008 was used in the evaluation. The analysis was based on daily, monthly, annual and seasonal timescales. Our results showed a good correlation between the TMPA products and the gauged data on all timescales considered. The CMORPH on the other hand showed huge overestimation at all gauge locations. The TMPA 3B42 was seen to be the best amongst the three products. The overall rainfall in the basin was well depicted by the TMPA 3B42 and 3B42RT. Although there wasn’t a perfect match between the 3B42RT and 3B42 products and the gauged rainfall, these products can be used to supplement gauged rainfall measurements in the basin and in estimation of rainfall in ungauged basins with similar characteristics.

(1) Food banks have played an important role in reducing food losses and waste and improving the food insecurity situation of vulnerable people. This study aims to conduct a systematic review of food bank evaluation studies and bring new perspectives for future research and decision-making. (2) 58 articles were selected and analyzed from a survey on the Web of Science and Science Direct Platforms. Bibliometric analyses and analyses of the evaluation methodologies used were presented. (3) The bibliometric results indicate an internationalization of the studies since 2013, with a focus on developed countries, and a direct relationship between the location of the research institutes and the location of the organizations studied. Analysis of evaluation methodologies showed that the main aspects evaluated are related to long-term impact, short-term impact and results, indicating less interest in the internal processes and activities of organizations. This result raises important questions for researchers and decision-makers: to what extent evaluation studies reflect the reality and context of a given country or region and to what extent evaluation studies reflect the management processes of food banks.

Since Charles Goodyear discovered the sulfur curing of Natural Rubber in 1839, many studies were carried out to understand the mechanism of sulfur curing. Nowadays, the broadly accepted mechanism includes an activated accelerator complex formed by Zinc oxide, stearic acid, accelerators and sulfur. Furthermore, it is also broadly accepted that the coupling of the sulfur to the polymer takes place in the allylic position to the double bond. Modern passenger car tire treads do not contain any longer Natural Rubber but a blend of SSBR and BR, filled with a silica /silane system. Is it possible to transfer all gained knowledge from the Natural Rubber crosslink reaction to such a modern passenger car tire tread formulation or is it required to “re-think” the sulfur curing?

Experiments to measure a single molecule/particle, i.e. an individual molecule/particle, at room temperature or under physiological conditions without immobilization, for example on a surface, or without significant hydrodynamic flow have so far failed. This failure has given impetus to the underlying theory of Brownian molecular motion towards its stochastics due to diffusion. Quantifying the thermodynamic jitter of molecules/particles inspires many and forms the theoretical basis of single-molecule/single-particle biophysics and biochemistry. For the first time, our simulation results for a live cell (cytoplasm) show that the tracks of individual single molecules are localized in Brownian motion, while there is fanning out in fractal diffusion (anomalous diffusion).

Experiments to measure a single molecule/particle, i.e. an individual molecule/particle, at room temperature or under physiological conditions without immobilization, for example on a surface, or without significant hydrodynamic flow have so far failed. This failure has given impetus to the underlying theory of Brownian molecular motion towards its stochastics due to diffusion. Quantifying the thermodynamic jitter of molecules/particles inspires many and forms the theoretical basis of single-molecule/single-particle biophysics and biochemistry. For the first time, our simulation results for a live cell (cytoplasm) show that the tracks of individual single molecules are localized in Brownian motion, while there is fanning out in fractal diffusion (anomalous diffusion).

Amazon Web Services (AWS) instances provide a convenient way to run training on complex ’omics data analysis workflows without requiring participants to install software packages or store large data volumes locally. However, efficiently managing dozens of instances is challenging for training providers. We present a set of Bash scripts that make it quick and easy to manage Linux AWS instances pre-configured with all the software analysis tools and data needed for a course, and accessible using encrypted login keys and optional domain names. Creating over 30 instances takes 10-15 minutes. A comprehensive online tutorial describes how to set up and use an AWS account and the scripts, and how to customise AWS instance templates with other software tools and data. We anticipate that others offering similar training may benefit from using the scripts regardless of the analyses being taught.

Background: Experiential learning (EL) experiences are an important component of a university education, positively impacting career-related attitudes, knowledge, and skills. Students also require EL opportunities to gain experiences required for admission to competitive graduate and professional programs. Students with disabilities face barriers accessing and benefiting from such opportunities. Purpose: This study examined the degree to which demographic factors, type and severity of disability, dispositional factors, and overall adjustment and wellbeing are predictive of the quality of EL experiences among university students with disabilities. Methodology/approach: A survey was distributed to undergraduate students with disabilities who have participated in EL courses. Results were analyzed using multiple linear regression. Findings/conclusions: Dispositional and adjustment and wellbeing variables, including the environmental mastery dimension of their psychological wellbeing rather than demographic factors, such as gender or type and severity of disability, are significant predictors of the quality of EL experiences among students with disabilities. Implications: For students with disabilities to have academically and professionally successful EL experiences, post-secondary institutions must continue to provide appropriate accommodations and educate instructors about the diverse and complex needs of this student group. This must include an understanding of the uniqueness of each individual student’s needs.

On return to campus after the pandemic, students were subjected to receiving lectures online, in class, or by the emerging hybrid approach. This study reports students' preference over the three approaches based on the experience gained during the 2022/23 academic session. One hundred and twenty-seven (127) on-campus Education students in one public university in Malaysia participated in the study. Data was collected through an online forum and interviews with the participants. The data collected was analyzed using content and thematic analysis. Preference for the hybrid approach emerged as a finding with three themes describing what makes the wholly online class unpopular (themes one and two); and, the popularity of the hybrid approach (theme three): 1. On-campus learner-environment challenges; 2. Perceived lack of Faculty engagement and support in the online learning environment; and, 3. Student engagement through faculty presence and technology innovation. What the students valued most in the hybrid approach is the face-to-face technology-enhanced classroom interaction that is retained, believing that learning is more effective and interesting in class than online. They considered the additional online learning activities as complementing the classroom learning. The approach provides an opportunity for fundamental learning in class and supplementary learning online. These findings imply that institutions should prioritize technology integration into face-to-face instruction, leveraging innovative approaches to enhance student engagement and learning outcomes. Lecturers should consider adopting hybrid teaching models that combine the benefits of in-person interaction with the flexibility of online learning, catering to diverse student preferences and optimizing the educational experience.

Background: Individuals living in rural areas often face challenges in accessing healthcare, increasing their risk of poor health outcomes. Farmers, a sub-population in rural areas, are particularly vulnerable to mental health issues and suicide, yet exhibit low rates of help-seeking behavior. The aim of our study was to develop an in-depth understanding of the issues influencing mental help-seeking among farmers living in rural areas from the perspectives of healthcare providers, as well as to explore the strategies providers use to navigate through these issues to effectively engage with this vulnerable population. Methods: We used a descriptive phenomenological approach to understand healthcare providers’ perspectives, experiences, and approaches to providing mental healthcare to farmer clients in rural areas. Semi-structured interviews were conducted with 21 participants between March and May 2023. Results: Our analysis yielded five thematic areas: (1) ensuring accessibility, (2) establishing relatability, (3) addressing stoicism and stigma, (4) navigating dual roles, and (5) understanding community trauma. Conclusions: Healthcare service delivery for farmers is multifaceted. This study fills a gap in knowledge by translating these the data to inform an evidence-based model and a list of recommendations for implementing agriculturally-informed practices in rural areas.

The fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing kThe fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing knowledge for the information- theoretic fractal dimensions. On another applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.

Software stands as one of the most rapidly evolving technologies in the present era, characterized by its swift expansion in both scale and complexity which leads to challenges in quality assurance. Software Defect Prediction (SDP) emerges as a methodology crafted to anticipate undiscovered defects, leveraging known defect data from existing codes. This methodology serves to facilitate software quality management, thereby ensuring overall product quality. Machine Learning (ML) and Deep Learning (DL) methodologies exhibit superior accuracy and adaptability compared to traditional statistical approaches catalyzing active researches in this domain. However, it makes us hard to generalize not only because of the disparity between open-source project and commercial project but also the difference on each industrial sectors. Consequently, further research utilizing datasets sourced from diverse real-world sectors becomes imperative to bolster the applicability of these findings. In this study, we utilized embedded software for telecommunication systems of SAMSUNG ELECTRONICS, supplemented by the introduction of nine novel features to train the model, and subsequent analysis of results ensued. Experimental outcomes revealed that the F-measurement metric has been enhanced from 0.58 to 0.63 upon integration of the new features, thereby signifying a performance augmentation of 8.62%. This case study is anticipated to contribute to bolster the application of SDP methodologies within analogous industrial sectors.

By using 0.35-um CMOS process, this work achieves a design of analogous band-gap reference voltage circuit with low temperature coefficient. The proposed circuit operates at 3V and generates a reference current of 44 uA. The HSPICE simulation results show the temperature coefficient of this circuit is 23 ppm/℃ at range of -10 ℃ to 100 ℃, and the line regulation (the ratio of output current variation to supply voltage variation) is estimated as 1.95 uA/V from supply voltage variation of 3 V to 5 V. The experimental chip is fabricated and measured. The circuit provides adjustable capability for output voltage among temperature variation of -10 - 100 ℃. The chip area is 534 × 695 um^2. In this new design, the operational amplifier is not necessary. The chip design effort can be great reduced.

In the present study, the new biological sources in the form of lichen Usnea orientalis Motyka was screened for its antidermatophytic potential. Six species of dermatophytes were chosen on the basis of their prevalence for antidermatophytic assays, and the Clinical Laboratory Standard Institute (CLSI)-recommended broth microdilution procedure was used to detect the efficacy of extract against dermatophytes. Thin layer chromatography of lichen extracts reveals the presence of two secondary metabolites viz. salazinic acid and usnic acid. U. orientalis extract exhibited promising antidermatophytic activity against all tested pathogens. Amongst all tested pathogens, E. floccosum exhibited most susceptibility towards extract, whereas T. mentagrophytes exhibited the least susceptibility. Topical application of U. orientalis extract might be helpful in the cure of dermal infections.

Financial fraud poses a severe threat to the integrity of corporate financial statements and market efficiency. While auditors play a crucial role in detecting and preventing such fraud, the unique characteristics of this domain, including class imbalance, high misclassification costs, and am-biguous attributes, pose significant challenges. Traditional classification algorithms may not be optimally suited for this task. This paper proposes a novel stacking ensemble learning approach to enhanced detecting of Financial Statement Scam. By combining the strengths of multiple base learners, including Random Forest, XGBoost, and Gradient Boosting Decision Trees, our model leverages their diverse predictions to improve overall performance. A Logistic Regression me-ta-learner is employed to integrate the outputs of the base learners, capturing their collective wisdom while mitigating individual weaknesses. Extensive experimentation using a real-world dataset shown the superiority of our approach, achieving remarkable recall, precision, accuracy, and area under the curve metrics. The proposed model outperforms individual base learners, under-scoring the efficacy of ensemble learning in tackling the intricate problem of financial fraud detection. This research contributes to the creation of substantial and robust fraud detection systems, fostering trust and transparency in financial markets.

Some time ago, Kobayashi et al. experimentally studied the so-called Lee-Naughton-Lebed's (LNL) angular effect in strong electric fields [K. Kobayashi, M. Saito, E. Omichi, and T. Osada, Phys. Rev. Lett. \textbf{96}, 126601 (2006)]. They found that strong electric fields split the LNL conductivity maxima in $\alpha$-(ET)$_2$-based organic conductor and hypothetically introduced the corresponding equation for conductivity. In this Letter, for the first time we suggest quantum mechanical theory of the LNL angular oscillations in moderately strong electric fields. In particular, we demonstrate that the obtained by us approximate theoretical formula coincides with the hypothetical one and well describes the above mentioned experiments.

Our previous study has found the anti-tumor activity of oleandrin in osteosarcoma cells in vitro, but the signal transduction process of cell apoptosis induced by oleandrin is uncertain, which is explored in this study. Fluorescence staining and flow cytometry (FCM) was performed to detect the cell apoptosis, intracellular reactive oxygen species (ROS) and mitochondrial membrane potential (MMP). Caspase-3 activity was detected using a commercial kit. The protein expression of cytoplasmic cytochrome c, mitochondrial cytochrome c, bcl-2, bax, caspase-9, Fas, FasL, caspase-8 and caspase-3 was detected using western blot. A pan-caspase inhibitor, z-VAD-fmk, was applied to block the apoptotic pathway and the apoptosis status were re-tested. We found that oleandrin significantly induced the increased apoptosis of U2OS cells. Meanwhile, the intracellular ROS was elevated, but the MMP decreased. The cytochrome c in mitochondria was notably decreased but increased in cytoplasm. The caspase-3 activity was also enhanced with the increase of drug concentration and treatment time. Oleandrin also down-regulated the level of bcl-2, but remarkably up-regulated the expression of bax, cleaved caspase-9, Fas, FasL, cleaved caspase-8 and cleaved caspase-3. Furthermore, the pre-treatment with z-VAD-fmk almost completely reverted the oleandrin-induced apoptosis. The results suggested that oleandrin induces the apoptosis of osteosarcoma cells via mitochondrial- and death receptor-dependent pathways.

Necroptosis is a regulated form of cell death implicated in several pathological conditions, in-cluding viral infections. In this study, we investigated the expression and correlation of necroptosis markers, MLKL, RIP1 and RIP3, in human liver tissue from fatal cases of yellow fever (YF) using immunohistochemistry (IHC). Liver samples were obtained from 21 YF-positive individuals and five flavivirus-negative controls with preserved liver parenchymal architecture. The cases un-derwent histopathological analysis, followed by tissue immunostaining with the immuno-histochemical method of streptavidin-biotin peroxidase. Using the in situ method, we evaluated the centrilobular (Z3), midzonal (Z2), periportal zone and portal tract (PT) zones of human liver parenchyma with markers for necroptosis, RIPK1, RIPK3 and MLKL. Quantitative analysis re-vealed significantly higher expression of MLKL, RIP1 and RIP3 in the liver parenchyma of YF cases compared to controls in different zones (Z3, Z2, Z1) and portal tracts (PT) of the liver, especially in zone 2. Immunostaining confirmed the localization of MLKL, RIP1 and RIP3 in hepatocytes and inflammatory infiltrates, highlighting their involvement in the pathogenesis of YF. Pearson's correlation analysis demonstrated significant correlations between necroptosis markers which indicate their coordinated regulation during YF-induced liver injury.

Diseases in articular cartilages have affected millions of people globally. Although the biochemical and cellular composition of articular cartilages is relatively simple, there is the limitation in self-repair ability of cartilage. Therefore, developing the strategies for cartilage repair is very important. Here, we reported a new manufacturing process of water-based polyurethane based photosensitive materials with hyaluronic acid and applied the materials for 3D printed customized cartilage scaffolds. The scaffold has high cytocompatibility and is one that closely mimics the mechanical properties of articular cartilages. It is suitable for culturing human Wharton's jelly mesenchymal stem cells (hWJMSCs) and the cells showed an excellent chondrogenic differentiation capacity. We consider that the 3D printing hybrid scaffolds may have potential in customized tissue engineering and facilitate the development of cartilage tissue engineering.

This study investigates the evolution of the vegetation and beach dune system at Enebrales Beach in Huelva, Spain, from 2003 to 2022. Utilizing orthophotographs and advanced GIS techniques, we analyzed changes in natural surface areas, vegetation cover, and dune stability. The results demonstrate significant ecological improvements: a recovery of 25,300 m² in dunes and 7,400 m² in beach areas, and a total vegetation cover increase of nearly 10,000 m². Interventions, including reforestation with native species and the stabilization of dune ridges, have been effective in enhancing the coastal ecosystem's resilience. Additionally, the beach's carrying capacity increased, allowing for approximately 2,000 more users without compromising ecological integrity. These findings underscore the importance of continued conservation efforts and adaptive management to maintain and further improve the ecological health and sustainability of Enebrales Beach Dune.

A whole-exome capture and next-generation sequencing applied to an 11 y/o patient with a clinical history of congenital hypotonia, generalized motor and cognitive neurodevelopmental delay, severe cognitive deficit, without any identifiable Syndromic pattern, and to her parents, disclosed a de novo heterozygous pathogenic mutation, c.697_699del p.Phe233del (rs786204835)(ACMG classification PS2, PM1, PM2, PP5), harbored in the PURA gene (MIM*600473) (5q31.3), associated to Autosomal Dominant Mental Retardation 31 (MIM # 616158). We used the significant improvement in the accuracy of protein structure prediction recently implemented in AlphaFold that incorporates novel neural network architectures and training procedures based on the evolutionary, physical, and geometric constraints of protein structures. The wild-type (WT) sequence and the mutated one, missing the Phe233, were reconstructed. The predicted local Distance Difference Test (lDDT) for the PURA WT and the PURA-Phe233del showed that the occurrence of the Phe233del affects between 220-320 amino acids. The distortion in the PURA structural confor-mation in the ~5Å surrounding area after the p.Phe233del produces a conspicuous disruption of the repeat III, where the DNA and RNA helix unwinding capability occurs. PURA Protein-DNA Docking corroborated these results in silico Analysis that showed a loss of the contact of the PURA-Phe233del III repeat domain model with the DNA. Together, i) the energetic and stereochemical, ii) the hydropathic indices and polarity surfaces, and iii) the hybrid Quantum Mechanics-Molecular Mechanics (QM-MM) analyses of the PURA molecular models demarcate at the atomic resolution the specific surrounding region affected by these mutations and paves the way for future cell-based functional analysis. To the best of our knowledge, this is the first report of a de novo mutation underpinning a PURA syndrome in a Latin American patient and highlights the importance of predicting the molecular effects in protein structure using artificial intelligence algorithms and molecular and atomic resolution stereochemical analyses.

Every individual at some point encounters the progressive biological process of aging which is considered one of the major risk factors for common diseases. The main drivers of aging are oxi-dative stress, senescence, and Reactive oxygen species (ROS). The renin-angiotensin-aldosterone system (RAAS) includes several systematic processes for the regulation of blood pressure which is caused by an imbalance of electrolytes. During activation of RAAS, binding of angiotensin II (ANG II) to angiotensin II type I receptor (AGTR1) activates intracellular NADPH oxidase to generate superoxide anions and promote uncoupling of endothelial NO synthase, which in turn decreases NO availability and increases ROS production. Promoting oxidative stress and DNA damage mediated by ANG II is tightly regulated. Individuals with sodium deficiency-associated diseases such as Gitelman syndrome (GS) and Bartter syndrome (BS) show down-regulation of inflammation-related processes and have reduced oxidative stress and ROS. Additionally, the histone deacetylase-Sirtuin-1(SIRT1) has a significant impact on the aging process with reduced activity with age. However, GS/BS patients generally sustain higher levels of SIRT1 activity than aged-matched healthy individuals. In this review, we highlight the importance of the hallmarks of aging, inflammation, and the RAAS system in GS/BS patients and how this might impact healthy aging. We further propose fu-ture research directions for studying the etiology of GS/BS at the molecular level using pa-tient-derived renal stem cells and induced pluripotent stem cells.

Background: Respiratory syncytial virus (RSV) is a significant cause of illness in adults, especially older adults and those with underlying conditions. This study aimed to assess the incidence of RSV hospitalizations in adults and identify risk factors for hospitalization and poor outcomes. Methods: A retrospective cohort study was conducted using data from two hospitals in southern Israel from 2016-2022. We calculated incidence rates of RSV and influenza hospitalizations. Risk factors for hospitalization were analyzed using Poisson regression. We evaluated poor outcomes (death, ICU admission, or mechanical ventilation) among RSV-hospitalized patients. Results: The median annual incidence of RSV hospitalization was 28.2/100,000 population, increasing with age to 199/100,000 in those ≥75 years. Significant risk factors for RSV hospitalization included pulmonary diseases (RR 4.2, 95% CI 3.4-5.2), cardiovascular diseases (RR 3.3, 95% CI 2.6-4.2), and chronic renal failure (RR 2.9, 95% CI 2.3-3.7). Among hospitalized RSV patients, 13.9% had poor outcomes. Renal failure (RR 1.81, 95% CI 1.23-2.66), neutropenia (RR 2.53, 95% CI 1.19-5.35), neutrophilia (RR 1.66, 95% CI 1.81-2.34), and lymphopenia (RR 2.03, 95% CI 1.37-3.0) were associated with poor outcomes. Conclusions: RSV causes a substantial burden of hospitalizations in adults, particularly among older adults and those with comorbidities. Identifying high-risk groups can help target prevention and treatment strategies, including vaccination.

The present study describes a comprehensive analysis of the Adverse Drug Reactions (ADRs) documented in the Database of the Spanish Pharmacovigilance System (FEDRA) concerning the use of biological medications used for severe refractory asthma, specifically omalizumab, mepolizumab, reslizumab, benralizumab, dupilumab, and tezepelumab. Emphasis was placed on ADRs not documented in the Technical Sheet (Summary of Product Characteristics, SmPC) of the respective specialties (Xolair®, Nucala®, Cinqaero®, Fasenra®, Dupixent®, and Tezspire®), which could potentially trigger a warning signal in Pharmacovigilance, indicating previously unidentified risks. The analysis encompassed data from the inception of each drug ́s marketing until January 22, 2024, including cases originating from various sources: direct submissions to the Spanish Pharmacovigilance System, communications from the Pharmaceutical Industry, and findings from literature review. Notifications were analyzed independently of their origin, so a complete review of all ADRs associated with these medications was ensured. In essence, this investigation highlights the critical role of post-marketing safety information, emphasizing the relevance of comprehensive reporting by healthcare professionals to facilitate a robust Pharmacovigilance system, ultimately advancing patient care and safety.

Patients with chronic kidney disease (CKD), particularly those with end-stage kidney disease (ESKD) undergoing dialysis or kidney transplantation, face ongoing challenges in relation to the risk of COVID-19. In addition to their underlying condition, factors such as immune-evasive variants, immunosuppressive therapies, and the need for dialysis contribute to poor COVID-19 outcomes in this population. Severe COVID-19 can lead to the deterioration of CKD/ESKD, resulting in acute kidney injury, septic shock, and respiratory failure. Moreover, patients with CKD/ESKD have shown impaired response to COVID-19 vaccination, with seroconversion failures associated with the burden of immunosuppressive treatments, further heightening their vulnerability to severe disease. Despite the current endemic, it is crucial to acknowledge the ongoing significance of COVID-19 as a serious threat to patients burdened with chronic diseases like CKD and ESRD. Understanding the impact of COVID-19 on these patients is essential, as they remain at risk of severe disease progression. This paper presents the results of a literature review to enhance our understanding of COVID-19-related risks in patients with CKD/ESKD. Expert insights and illustrative scenarios provide practical perspectives and highlight the importance of risk stratification based on clinical factors for guiding targeted measures and treatments to mitigate COVID-19 risks in these vulnerable patients.

Viral hepatitis is currently acknowledged as a significant public health issue that necessitates a prompt and immediate response. Hepatitis is a significant worldwide health problem that causes the death of approximately 1.5 million individuals annually. The objective of this study was to ascertain the occurrence rate of hepatitis A, E, B, and C infections in the Hajjah governorate of Yemen from 2020 to 2023.A retrospective study was conducted in the Hajjah Governorate of Yemen for four years, 2020– 2023. About 41162 cases were collected from the clinical records of epidemiological surveillance in the Public Health Office of the Hajjah Governorate. All cases were diagnosed in different laboratories based on direct observation of viral hepatitis in the blood sample. The required data were obtained by using the designed questionnaire. The findings of the present investigation were summarized as follows: The current findings indicate that the prevalence rate of Hepatitis A and E was 761 (1.85%), while the prevalence rate of Hepatitis B and C was 971 (2.36%) among the participants of the study. The current findings indicate that the incidence of Hepatitis A and E was greater in 2022 (2.3%), while Hepatitis B and C had a higher rate in 2020 (2.9%). The study revealed a higher prevalence of hepatitis A and E among individuals originating from Al Miftah district 116, with a rate of 7.5%. Furthermore, the prevalence of hepatitis B and C in Hajjah city was significantly higher, reaching 579 cases (22.9%). The month with the highest incidence of hepatitis A and E viruses was September, with a rate of 85 cases (2.6%), while the lowest incidence was observed in April, with a rate of 1.3%. The prevalence of hepatitis B and C viruses was highest in October 1997, with a rate of 2.8%, followed by November 1997 with the same rate. The lowest observed incidence of 1.6% was recorded in April. In Autumn, a significant prevalence of hepatitis A and B viruses, as well as hepatitis B and C viruses, was identified at rates of 2.2% and 2.6%, respectively.The study findings indicate that the occurrence of HAV, HEV, HBV, and HCV in the study area is consistent with global trends. Although the study found a low prevalence of hepatitis viruses, these types of viruses will continue to pose a significant risk to public health. Based on this study, it is imperative for authorities to actively enhance public awareness in order to enable prompt planning and essential arrangements for an effective response to outbreaks or epidemics. This will ultimately lead to a reduction in illness, death, and economic burden.

The purpose of this project is to develop and build an extensible fixture. This fixture is ideal to milling, drilling, and shaping operations. Jigs and fittings are often the most cost-effective methods of mass fabricating a component. As a result, jigs and fittings are used and play a vital part in the mass production system. These are specialist work holding and tool-guiding devices. The quality of jigs and fixtures used in a process has a substantial impact on its performance. A fixture is distinctive because it is meant to fit a given area or shape. The basic purpose of a fixture is to find and, in certain instances, hold a workpiece throughout an operation. A jig differs from a fixture in that it leads the tool to the right position or movement during an operation, in addition to locating and supporting the workpiece. When a key is reproduced, the original key serves as a base for the path reader, which regulates the tool's movement to construct the duplicate key. In this situation, a CWC machine's route reader works as a jig, with the original being referred to as the template. Sometimes the template and jig refer to the same part of a production system.

Research on retinoid-based cancer prevention, spurred by the effects of vitamin A deficiency on gastric cancer and subsequent clinical studies on digestive tract cancer, unveils novel avenues for chemoprevention. Acyclic retinoids like 4,5-didehydrogeranylgeranoic acid (4,5-didehydroGGA) emerged as potent agents against hepatocellular carcinoma (HCC), distinct from natural retinoids such as all-trans retinoic acid (ATRA). Mechanistic studies reveal GGA's unique induction of pyroptosis, a rapid cell death pathway, in HCC cells. GGA triggers mitochondrial superoxide hyperproduction and ER stress responses through Toll-like receptor 4 (TLR4) signaling and modulates autophagy, ultimately activating pyroptotic cell death in HCC cells. Unlike ATRA-induced apoptosis, GGA and palmitic acid (PA) induce pyroptosis, underscoring their distinct mechanisms. While all three fatty acids evoke mitochondrial dysfunction and ER stress responses, GGA and PA inhibit autophagy, leading to incomplete autophagic responses and pyroptosis, whereas ATRA promotes autophagic flux. In vivo experiments demonstrate GGA's potential as an anti-oncometabolite, inducing cell death selectively in tumor cells and thus suppressing liver cancer development. This review provides a comprehensive overview of the molecular mechanisms underlying GGA's anti-HCC effects and underscores its promising role in cancer prevention, highlighting its importance in HCC prevention.

Brazilian garimpeiros are a highly hard-to-reach and mobile population, with little access to basic hygiene and health services, and have been crossing the border to work irregularly in gold mines in French Guiana since the 90s. This study aimed to characterize this population and identify their main health problems. A cross-sectional study was carried out in the municipality of Oiapoque-AP, with two surveys: before (2018) and after (2019) the implementation of Malakit. Individuals were recruited from resting places and submitted to a questionnaire with demographic variables, history and knowledge of malaria, and health issues in the mines. Simultaneously, a clinical evaluation was performed. The garimpeiros were mainly men from Maranhão, Pará, and Amapá, with a low educational level and worked on average for 10 years in the mining sites. The study population mentioned numerous health problems: malaria, followed by leishmaniasis, flu, body aches, headaches, and digestive problems. Other diseases mentioned were skin diseases, bat bites, hepatitis, and HIV infection. This vulnerable population is constantly subjected to heavy routines and exposed to different diseases and infections that can spread across borders. Knowledge of this is essential for developing public health policies that can be integrated into specific epidemiological situations.

The use of artificial intelligence algorithms (AI) has gained importance for dental applications in recent years. Analyzing using IA information from different sensor data such as images or X-ray radiographs can help to improve medical decisions and to achieve early diagnosis of different dental pathologies. In particular, the use of deep learning (DL) techniques based on convolutional neural networks (CNNs) has obtained promising results in dental applications based on images, in which approaches based on classification, detection, and segmentation are being studied with growing interest. However, there are still several challenges to be tackled, such as the data quality and quantity, the variability among categories, and the analysis of the possible bias and variance associated with each dataset distribution. In this work, we compare three different DL object detection models, which are Faster R-CNN, YOLO V2, and SSD. Each object detection architecture was trained, calibrated, validated, and tested with three different feature extraction CNNs which are ResNet-18, ResNet-50, and ResNet-101, which were the networks that best fit our dataset distribution. Based on such detection networks, we detect four different categories of angles in third molars using X-ray panoramic radiographs by using Winter's classification criterion. This criterion characterizes the third molar's position regarding the second molar's longitudinal axis. The detected categories for the third molars are distoangular, vertical, mesioangular, and horizontal. For training, we used a total of 644 panoramic X-ray images. The results obtained in the testing dataset reached up to 99% mean average accuracy performance, demonstrating the YOLOV2 obtained higher effectiveness in solving the third molar angle detection problem. These results demonstrate that the use of CNNs for object detection in panoramic X-rays represents a promising solution in dental applications.

This study investigated a novel radioimmunotherapy strategy for targeting tumor angiogenesis. We developed a radiopharmaceutical complex by labeling an anti-adenosine triphosphate syn-thase (ATPS) monoclonal antibody (mAb) with the radioisotope 177Lu using DOTA as a chelating agent. 177Lu-DOTA-ATPS mAb demonstrated high labeling efficiency (99.0%) and stability in se-rum. MKN-45 cancer cells exhibited the highest cellular uptake, which could be specifically blocked by unlabeled ATPS mAb. In mice, 177Lu-DOTA-ATPS mAb accumulated significantly in tumors, with a tumor uptake of 16.0 ± 1.5%ID/g on day 7. 177Lu-DOTA-ATPS mAb treatment sig-nificantly reduced the viability of MKN-45 cells in a dose-dependent manner. In a xenograft tumor model, this radioimmunotherapy strategy led to substantial tumor growth inhibition (82.8%). Furthermore, combining 177Lu-DOTA-ATPS mAb with sunitinib, an anti-angiogenic drug, en-hanced the therapeutic efficacy of sunitinib in the mouse model. Our study successfully developed 177Lu-DOTA-ATPS mAb, a radioimmunotherapy agent targeting tumor blood vessels. This ap-proach demonstrates significant promise for inhibiting tumor growth, both as a single therapy and in combination with other anti-cancer drugs.

During the last two decades several cases of venous thrombosis (VTE) after a prolonged period at a computer has been described, denominated “eThrombosis”. Video gaming on a computer has become very popular and can be a social activity where several players are gathered to play against each other or in a virtual environment for several days (“LAN (i.e., Local Area Network) parties”) where the participants are sedentary and consuming calorie-rich food items. The aim of this study was to investigate a potential coagulation activation during a 42 hour LAN party. Nine male gamers volunteered for the LAN party. Citrated blood was sampled before and every 6 hours, and plasma was analyzed for thrombin generation, and Thrombin-antithrombin-complexes (TAT), prothrombin Fragment 1+2 (F1+2), and D-dimer. Thrombin generation increased slightly but not significantly during the LAN party, whereas the coagulation activation markers were unchanged. These results do not indicate that the coagulation system is activated significantly during 42 h gaming with minimal physical activity. Although an increased activity cannot be excluded, it does not directly indicate a risk of VTE in general. It may be specific and particularly susceptible in-dividuals who are prone to thrombosis and, therefore, are at risk of developing e-thrombosis.

Wind turbines are a solution for sustainable energy, significantly reducing carbon emissions and fostering a circular economy for more cost-effective and cleaner power generation, in line with worldwide environmental aspirations. In this context, this research aims to explore a novel Two-Stage Twisted Blade micro-Vertical Axis Wind Turbine ($\mu$-VAWT) alternative inspired by the Savonius Rotor (SR). This investigation utilizes the $\kappa-\omega$ SST turbulence model to explore the power coefficient ($C_P$) and torque coefficient ($C_T$), finding $C_P$ values ranging from 0.02 to 0.04 across the turbine by altering the free stream velocity ($V$). $C_T$ analysis further delves into four specific sections, highlighting areas of particular interest. These results are validated by examining velocity contours, pressure contours, and streamlines in four horizontal sections, demonstrating that the proposed turbine model exhibits minimal torque fluctuation. Moreover, the analysis of vertical wind streamlines illustrates very low interference with various wind turbine proposals, underscoring the turbine's efficiency and potential for integration into diverse wind energy projects.

The genome sequencing technologies reveal the molecular mechanisms of differentiated thyroid cancer (DTC). Unlike somatic mutation analysis from thyroidectomy samples, germline mutations showing genetic susceptibility to DTC are less understood. The study aimed to assess the prevalence of germline mutations predisposing to DTC in a cohort of Polish individuals based on their whole genome sequencing (WGS) data. We analyzed sequencing data from 1076 unrelated individuals, released openly for academic and clinical research as The Thousand Polish Genomes database (https://1000polishgenomes.com). The list of genes chosen for further analysis was based on the review of previous studies. The cohort contained 104 variants located within the coding and noncoding DNA sequences of 90 genes selected by ClinVar classification as pathogenic and potentially pathogenic. The frequency of variants in the Polish cohort (our study) was compared to the frequency estimated for the non-Finnish European population, obtained from the gnomAD database (gnomad.broadinstitute.org). Statistically significant variants included 23 genes. Even though the Polish population is genetically similar to other European populations, there are significant differences in variant frequencies contributing to the disease development and progression, such as RET, CHECK2, BRCA1, SLC26A4 or TERT. Further studies are needed to identify genomic variants associated directly with DTC.

Hydrogels, soft materials with 3D polymer networks in aqueous solution, have been developed for engineering and bio-related fields. However, these conventional hydrogels are weak and brittle due to lack of energy dissipation mechanisms. Recently, dual-network hydrogels have been proposed, combining rigid and flexible networks and exhibiting high strength, stretchability, and toughness. This paper explores the rheological properties of dual-network hydrogels based on acrylamide and sodium alginate under large deformations. This dual network is a combination of a covalently crosslinked polyacrylamide network and a supramolecular crosslinked sodium alginate network at the presence of divalent calcium cations. Small and large amplitude oscillatory shear methods with Fourier transform rheology, stress decomposition method, and Chebyshev polynomial analysis of large amplitude oscillatory shear (LAOS) data were employed to evaluate non-linearity limit, toughness, and network rigidity. The concentration of calcium ions affects (concentrations 0-80 mg/ml) the nonlinear transition and limit points, and all gel samples exhibit strain hardening, shear thickening, and shear densification.

The potentially active A subunit of coagulation factor XIII (FXIII-A) is an intracellular transglutaminase expressed in various cell types including platelets and monocytes/macrophages. It is involved in stabilizing protein structures by cross-linking through Nε-(?-L-glutamyl)-L-lysyl iso-peptide bonds. Macrophages are major cellular constituents of the atherosclerotic plaque and are important in determining its structural/functional features. Two of their important functions are the accumulation of oxidized LDL in the lipid core, and by cross-linking structural proteins they may stabilize the plaque and protect the thrombi of atherogenic origin against fibrinolytic degradation. It is important to know whether these functions operate in parallel utilizing the same cellular compartments. First, we showed that monocyte-derived human macrophages significantly increase their FXIII-A content when up-taking oxidized LDL. This phenomenon is very likely independent of the process of transformation into foam cells, as the transformation of vascular smooth muscle cells into foam cells fails to result in the expression of FXIII-A. FXIII containing macrophage-like cells are abundant in the plaque and FXIII-A is also present in the extracellular core. Several cells co-stained for FXIII-A and for Oil Red O suggest that expression of FXIII-A and lipid up-take are common features of macrophages present in the atherosclerotic plaque.

Photosynthesis is one the most important biological processes on earth, producing life-giving oxygen and is the basis for a large variety of plant products. Measurable properties of photosynthesis provide information about its biophysical state and, in turn, the physiological conditions of a photoautotrophic organism. For instance, chlorophyll fluorescence of an intact photosystem is not linear as in the case of a single fluorescent dye in solution, but shows temporal changes related to the quantum yield of the photosystem. Commercial photosystem analyzers already use the fluorescence kinetics characteristics of photosystems to infer the viability of organisms under investigation. Here, we provide a novel approach based on an optical Fabry-Pérot microcavity or that enables the readout of photosynthetic properties and activity for an individual cyanobacterium. This approach offers a completely new dimension of information, which would normally be lost due to averaging in ensemble measurements obtained from a large population of bacteria.

The success of total hip arthroplasty depends on the experience of the surgeon, and one of the ways the surgeon currently determines the final implant insertion depth is to listen to the change in audible pitch of the hammering sound. We investigated the use of acoustic vibration emissions as a novel method for insertion quality assessment. A non-invasive contact microphone-based measurement system for insertion depth estimation, fixation and fracture detection was developed using a simplified in vitro bone/implant (n=5). 2583 audio recordings were analysed in vitro to obtain energy spectral density functions. Out of the four main resonant peaks under in vitro conditions, broach insertion depth statistically correlates to increasing 3rd and 4th peak frequencies. Degree of fixation was also observed as higher goodness of fit (0.26-0.78 vs. 0.12-0.51 between two broach sizes, the latter undersized). Finally, however, the moment of fracture could not be predicted. A cadaver in situ pilot study suggests comparable resonant frequencies in the same order of magnitudes with the bone model. Further understanding of the signal patterns are needed for an early warning system diagnostic system for imminent fractures, bone damage, improving accuracy and quality of future procedures.

Influenza B virus (IBV) is a major respiratory pathogen of humans, particularly in the elderly and children and vaccines are the most effective way to control it. In previous work, incorporation of two mutations (E580G, S660A) along with the addition of a HA epitope tag in the PB1 segment of B/Brisbane/60/2008 (B/Bris) resulted in an attenuated strain that was safe and effective as a live attenuated vaccine. A third attempted mutation (K391E) in PB1 was not always stable. Interestingly, viruses that maintained the K391E mutation were associated with the mutation E48K. To explore the contribution of the E48K mutation for stability of the K391E mutation, a vaccine candidate was generated by inserting both mutations along with attenuating mutations E580G and S660A in PB1 of B/Bris (B/Bris PB1att 4M). Serial passage of the B/Bris PB1att 4M vaccine candidate in eggs and MDCK indicated high stability. In silico structural analysis revealed a potential interaction between amino acids at positions 48 and 391. In mice, B/Bris PB1att 4M was safe and provided complete protection against homologous challenge. These results confirm the compensatory effect of mutation E48K to stabilize the K391E mutation, resulting in a safer, yet still protective, IBV LAIV vaccine.

There is a growing need for novel in vitro corneal models to replace animal-based ex vivo test in drug permeability studies. In this study we demonstrate a corneal mimetic that models the stromal and epithelial compartments of human cornea. Human corneal epithelial cells (HCE-T) were grown on top of a self-supporting porcine collagen-based hydrogel. Cross sections of the multilayers were characterized by histological staining and immunocytochemistry of zonula occludens-1 protein (ZO-1) and occludin. Furthermore, water content and elastic properties of the synthetized collagen type I-based hydrogels were measured. The apparent permeability coefficient (Papp) values of a representative set of ophthalmic drugs were measured and correlated to rabbit cornea Papp values found in the literature. Multilayered structure of HCE-T cells and expression of ZO-1 and occludin in full thickness of multilayer were observed. The hydrogel-based corneal model exhibited excellent correlation to rabbit corneal permeability (r=0.96), whereas insert-grown HCE-T multilayer was more permeable and the correlation to the rabbit corneal permeability was lower (r=0.89). The hydrogel-based human corneal model predicts the rabbit corneal permeability more reliably in comparison to HCE-T cells grown in inserts. This in vitro human corneal model can be successfully employed for drug permeability tests whilst avoiding ethical issues and reducing costs.

This study was conducted to determine whether overcrowding in the emergency department (ED) affects the occurrence of a return visit (RV) within 72 hours. The crowding indicator of index visit was the average number of total patients, patients under observation, and boarding patients during the first 1 and 4 hours from ED arrival time and the last 1 hour before ED departure. Logistic regression analysis was conducted to determine whether each indicator affects the occurrence of RV and post-RV admission. Of the 87,360 discharged patients, 3,743 (4.3%) returned to the ED within 72 hours. Of the crowding indicators pertaining to total patients, the last 1 hour significantly affected decrease in RV (p=0.0046). Boarding patients were found to increase RV occurrence during the first 1 hour (p=0.0146) and 4 hours (p=0.0326). Crowding indicators that increased the likelihood of admission post-RV were total number of patients during the first 1 hour (p=0.0166) and 4 hours (p=0.0335) and evaluationg patients during the first 1 hour (p=0.0059). Overcrowding in the ED increased the incidence of RV and likelihood of post-RV admission. However, overcrowding at the time of ED departure was related to reduced RV.

The application of nanotechnology to the petroleum industry has sparked recent interest to increase oil recovery while reducing environmental impact. Nanocellulose is an emerging nanoparticle that is derived from trees and may provide an environmentally friendly alternative to current enhanced oil recovery (EOR) technologies. However, before nanocellulose can be applied as an EOR technique, further understanding of its transport behavior and retention in porous media is required. The research documented in this paper examines retention mechanisms that occur during nanocellulose transport. In a series of experiments, nanocellulose particles dispersed in brine were injected into sandpacks and Berea sandstone cores. The resulting retention and permeability reduction were measured. The experimental parameters that were varied include sand grain size, nanocellulose type, salinity, and flow rate. Under low salinity conditions, the dominant retention mechanism was adsorption and when salinity was increased, the dominant retention mechanism shifted towards log-jamming. Retention and permeability reduction increased as grain size decreased, which results from increased straining of nanocellulose aggregates. In addition, each type of nanocellulose was found to have significantly different transport properties. The experiments with Berea sandstone cores indicate that some pore volume was inaccessible to the nanocellulose. As a general trend, the larger the size of aggregates in bulk solution, the greater the observed retention and permeability reduction. Salinity was found to be the most important parameter affecting transport. Increased salinity caused additional aggregation, which led to increased straining and filter cake formation. Higher flow rates were found to reduce retention and permeability reduction. Increased velocity was accompanied by an increase in shear which is believed to promote breakdown of nanocellulose aggregates.

During speciation-with-gene-flow, a transition from single-locus to multi-locus processes can occur, as strong coupling of multiple loci creates a barrier to gene flow. Testing predictions about such transitions with empirical data requires building upon past theoretical work and the continued development of quantitative approaches. We simulated genomes under different evolutionary scenarios of gene flow and divergent selection, extending previous work with the additions of neutral sites and coupling statistics, allowing us to investigate if and how selected and neutral sites differ in the conditions they require for transitions during speciation. As the per-locus strength of selection grew and/or migration decreased, it became easier for selected sites to show divergence – and thus to rise in linkage disequilibrium (LD) with each other as a statistical consequence – farther in advance of the conditions under which neutral sites could diverge. Indeed, even very low rates of gene flow were sufficient to prevent differentiation at neutral sites. However, once strong enough, coupling among selected sites eventually reduced gene flow at neutral sites as well. To explore whether similar transitions might be detectable in empirical data, we used published genome resequencing data from three taxa of Heliconius butterflies. We found that allele-frequency outliers and F ST outliers exhibited stronger patterns of LD than the genomic background, as expected. The statistical characteristics of LD – likely indicative of the strength of coupling of barrier loci – varied between chromosomes and taxonomic comparisons. Broad qualitative agreement between the patterns we observed in the empirical data and our simulations suggests that selection drives rapid genome-wide transitions to multi-locus coupling, illustrating how divergence and gene flow interact along the speciation continuum.

Viral integration within the host genome plays a pivotal role in carcinogenesis. Various disruptive mechanisms are involved, leading to genomic instability, mutations, and DNA damage. With next-generation sequencing (NGS), we can now precisely identify viral and host genomic breakpoints and chimeric sequences, which are useful for integration site analysis. In this study, we evaluated a commercial hybrid-capture NGS panel specifically designed for detecting three key viruses: HPV, HBV, and HIV-1. We also tested workflows for Viral Hybrid Capture (VHC) and Viral Integration Site (VIS) analysis, leveraging customized viral databases in CLC Microbial Ge-nomics. By analyzing sequenced data from virally infected cancer cell lines (including SiHa, HeLa, CaSki, C-33A, DoTc2, 2A3, SCC154 for HPV; 3B2, SNU-182 for HBV; and ACH-2 for HIV-1), we precisely pinpointed viral integration sites. The workflow also highlighted disrupted and neigh-boring human genes that may play a crucial role in tumor development. Our results included in-formative virus-host read mappings, genomic breakpoints, and integration circular plots. These visual representations enhance our understanding of the integration process. In conclusion, our seamless end-to-end workflow bridges the gap in understanding viral contributions to cancer development, paving the way for improved diagnostics and treatment strategies.

Our study is part of the ongoing discussion concerning influencer marketing as there seems to have been a shift and social media marketing is bigger than ever. Social media outlets are excellent vehicles for fostering relationships with consumers who can be susceptible to influencer advertising. Therefore, companies now pay for posts on users’ profiles to generate popularity for products. How this approach affects consumers’ buying behavior is an interesting research question. We reference Herbert Simon’s economics of attention as an appropriate theoretical construct for describing the reality of the internet. Based on unique survey data from 513 Polish respondents, the study applies econometric methods and supervised and unsupervised machine learning techniques to identify the primary consumer groups with different characteristics of engagement and sensitivity to influencer activities, revealing the possible drivers of purchase intent. The findings provide valuable insights into consumers’ informational preferences, demonstrating how social media influencers may attract attention and drive sales.

Oxidative stress, characterized by an imbalance between the production of reactive oxygen species (ROS) and the body's antioxidant defenses, significantly affects cellular function and viability. It plays a pivotal role in modulating action potentials (APs), essential for properly functioning excitable cells such as neurons, smooth muscles, pancreatic beta cells, and myocytes. The interaction between oxidative stress and AP dynamics is crucial for understanding the pathophysiology of various conditions, including neurodegenerative diseases, cardiac arrhythmias, and ischemia-reperfusion injuries. This review explores how oxidative stress influences APs, focusing on alterations in ion channel functionality, signaling pathways, and membrane properties. By integrating current research, we aim to elucidate how oxidative stress contributes to disease progression and discuss potential therapeutic interventions targeting this interaction.

Flexible manipulators have been widely used in industrial production. However, due to the poor rigidity of the flexible manipulator, it is easy to generate vibration. It will reduce the working accuracy and service life of the flexible manipulator. It is necessary to suppress the vibration during the operation of the flexible manipulator. Based on the energy method and Hamilton principle, the partial differential equations of the flexible manipulator are established. Secondly, an improved radial basis function (RBF) neural network is combined with the fuzzy backstepping method to identify and suppress the random vibration during the operation of the flexible manipulator, and the Lyapunov function and control law are designed. Finally, Simulink was used to build a simulation platform, three different external disturbances were set up, and the effect of vibration suppression was observed through the change curves of the final velocity error and displacement error. Compared with RBF neural network boundary control method and RBF neural network inversion method, the simulation results show that the effect of RBF neural network fuzzy inversion method is better than the previous two control methods, the system convergence is faster, and the equilibrium position error is smaller.

The key to the practical application of organometal–halide–crystals perovskite solar cells (PSCs) is to achieve thermal stability through robust encapsulation. This paper presents a method to significantly extend the thermal stability lifetime of perovskite solar cells to over 5,000 h at 85 °C by demonstrating an optimal combination of encapsulation methods and perovskite composition for carbon–based multiporous–layered–electrode (MPLE)–PSCs. We fabricated the four types of MPLE-PSCs using two encapsulation structures (over– and side–sealing with thermoplastic resin films) and two perovskite compositions ((5–AVA)x(methylammonium (MA))1–xPbI3 and (formamidinium (FA))0.9Cs0.1PbI3), and analyzed the 85 ºC thermal stability followed by ISOS–D–2 protocol. Without encapsulation, FA0.9Cs0.1PbI3 exhibited higher thermal stability than (5–AVA)x(MA)1–xPbI3. However, encapsulation reversed the phenomenon (that of (5–AVA)x(MA)1–xPbI3 became stronger). The combination of (5–AVA)x(MA)1–xPbI3 perovskite absorber and over–sealing encapsulation effectively suppressed the thermal degradation, resulting in the PCE value at 91.2% of the initial value after 5,072 h. On the other hand, another combination (side–sealing on (5–AVA)x(MA)1–xPbI3, over– and side–sealing on FA0.9Cs0.1PbI3) resulted in decreased stability. The FA–based perovskite was decomposed for these degradation mechanisms by the condensation reaction between FA and carbon. For side–sealing, the space between the cell and the encapsulant was estimated to contain approximately 1,260,000 times more H2O than in over–sealing, which catalyzed the degradation of the perovskite crystal. Our results demonstrate that MA–based PSCs, which are generally considered to be thermally sensitive, can significantly extend their thermal stability after the proper encapsulation. Therefore, we emphasize that finding the appropriate combination of encapsulation technique and perovskite composition is quite important to achieve further device stability.

Core chlorophytes possess glycerol-3-phosphate dehydrogenases (GPDs) with an unusual bidomain structure, consisting of a glycerol-3-phosphate phosphatase (GPP) domain fused to canonical GPD domains. These plastid-localized enzymes have been implicated in stress responses, being required for the synthesis of glycerol under high salinity and triacylglycerols under nutrient deprivation. However, their regulation under varying environmental conditions is poorly understood. C. reinhardtii transgenic strains expressing constitutively bidomain GPD2 did not accumulate glycerol or triacylglycerols in the absence of any environmental stress. Although, the glycerol contents of both wild type and transgenic strains increased significantly upon exposure to high salinity. Cycloheximide, an inhibitor of cytoplasmic protein synthesis, abolished this response in the wild type. In contrast, GPD2 transgenic strains were still capable of glycerol accumulation when cultured in medium containing cycloheximide and NaCl. Thus, pre-existing GPD2 protein appears to become activated for glycerol synthesis upon salt stress. Interestingly, staurosporine, a non-specific inhibitor of protein kinases, prevented this post-translational GPD2 protein activation. Structural modeling analyses suggested that substantial conformational rearrangements, possibly triggered by high salinity, may characterize an active GPD2 GPP domain. Understanding this mechanism(s) may provide insights into the rapid acclimation responses of microalgae to osmotic/salinity stress.

The development of photocurable compositions is in high demand for the manufacture of func-tional materials for electronics, optics, medicine, energy, etc. The properties of the final pho-to-cured material are primarily determined by the initial mixture, which needs to be tuned for each application. In this study we propose to use simple systems based on di(meth)acrylate, polyimide and photoinitiator for the preparation of new photo-curable compositions. It was es-tablished that a fluorinated cardo copolymide (FCPI) based on 2,2-bis-(3,4-dicarboxydiphenyl)hexafluoropropane dianhydride, 9,9-bis-(4-aminophenyl)fluorene and 2,2-bis-(4-aminophenyl)hexafluoropropane (1.00:0.75:0.25 mol) has excellent solubility in di(met)acrylates. This made it possible to prepare solutions of FCPI in such monomers, to study the effect of FCPI on the kinetics of their photopolymerization in situ and the properties of the resulting polymers. According to the obtained data, the solutions of FCPI (23 wt.%) in 1,4-butanediol diacrylate (BDDA) and FCPI (15 wt.%) in tetraethylene glycol diacrylate were tested for the formation of the primary protective coatings of the silica optical fibers. It was found that the new coating of poly(BDDA–FCPI23%) can withstand prolonged annealing at 200°C (72 h), which is comparable or superior to the known most thermally stable photo-curable coatings. The proposed approach can be applied to obtain other functional materials.