Calcium phosphates and manganese phosphates play a significant role in biomedical and engineering applications, and these compounds are both synergistic. These compounds could have great potential for use in different applications, particularly as precursors of biomaterials. Therefore, the aim of this study was to explore the effect of the gradual replacement of Ca2+ with Mn2+ on the phase composition and crystal structure of brushite (CaHPO4·2H2O), which could be useful for the production of Mono- and Biphasic Ca1−xMnxHPO4·nH2O Compounds. In order to prepare the starting solutions required for this study, Ca(NO3)2·4H2O, (NH4)2·HPO4, and Mn(NO3)2·4H2O were used at various molar concentrations. Afterwards, the Ca1−xMnxHPO4·nH2O compounds were prepared using dissolution and precipitation methods. These compounds were characterized using XRD, SEM, FT-IR, XPS, and TGA techniques. The findings revealed that Mn substituted Ca partially at low Mn/Ca molar ratios, 0.25, and Mn doping increased the unit cell of CaHPO4·2H2O. The produced biphasic compound was composed of monoclinic CaHPO4·2H2O and nanostructured orthorhombic MnHPO4·(H2O)3 after a continuous increase in the Mn/Ca molar ratio to 1.5. When the Ca/Mn molar ratio was above 1.5, a monophasic compound of the MnHPO4·(H2O)3 phase was formed. The MnHPO4·(H2O)3 compound was successfully prepared for the first time using this dissolution-precipitation method. It was also established that the Mn/Ca ratio of the starting solution can be modified to produce CaHPO4·2H2O and MnHPO4·(H2O)3 phases with specific weight percent compositions.

Antifungal properties are found in essential oil extracts of oregano (Origanum vulgare), rosemary (Salvia rosmarinus), clove (Syzygium aromaticum), thyme (Thymus), cinnamon (Cinnamomum verum), basil (Ocimum basilicum), therefore, the ability to prevent or inhibit the growth of Cladosporium spp., Lasiodiplodia spp., Colletotrichum spp., Fusarium spp., and Aspergillus spp. was studied. Cladosporium spp., Lasiodiplodia spp. Colletotrichum spp. Fusarium spp. y Aspergillus spp. fungi that were isolated and purified from the rot found on the banana peels (Musa paradisiaca). To perform a visual (macro-scopic) analysis of the Petri dish containing the pure fungus and a more detailed (microscopic) analysis of the fungal spores to classify it by genus, then, dilutions are prepared to inoculate onto amended PDA medium with chloramphenicol. Weekly re-inoculations are performed until iso-lated and purified fungi are obtained, which are then evaluated for in vitro inhibition and in vivo growth, according to the results of the in vivo analysis, the fungi were classified from higher to lower severity in: Colletotrichum spp., Lasiodiplodia spp., Aspergillus spp., Fusarium spp. and Cladosporium spp and based on fungal growth observations, it was found that basil and rosemary do not inhibit growth at the maximum concentration. Cinnamon inhibits at 400 ppm, rosemary halts fungal growth at 600 ppm, clove at 1000 ppm, and oregano at 800 ppm.

This study explored the correlation between concentrations of phenolic compounds (phenols, tannins, and flavonoids) and the versatility of woody medicinal plants in the Caatinga, a seasonally dry forest region in Brazil. We examined whether these compounds influence the versatility of plants used by populations, given their known therapeutic properties. Plants were categorized as high or low versatility based on their relative importance (RI) values ​​at the regional level. Samples collected in Catimbau National Park, Pernambuco, were analyzed using colorimetric methods: Folin-Ciocalteu reagent for total phenols, casein precipitation for tannins, and aluminum chloride complexation for flavonoids. Contrary to expectations, no significant differences in phenolic compound concentrations were found between the high and low versatility groups. Higher levels of total phenols and tannins were observed in Myracrodruon urundeuva and Anadenanthera colubrina, both highly versatile species. However, less versatile species, such as Mimosa tenuiflora and Schinopsis brasiliensis, also showed high levels. Flavonoid content, notably lower than phenols and tannins, did not show significant variation between groups. Although phenolic compounds contribute to the therapeutic properties of medicinal plants, their concentration alone does not determine the versatility of plants in the Caatinga. Versatility is more likely influenced by ecological conditions, cultural practices, and species availability. This study highlights the need to integrate multiple perspectives in ethnopharmacological research.

Lupus, also known as systemic lupus erythematosus (SLE), is a chronic autoimmune disease that can lead to inflammation and damage to multiple organs and tissues in the body. The symptoms vary from patient to patient, which makes the disease manifest very differently, resulting in difficulty in diagnosing and treating patients. Some may experience fatigue, hair loss, joint pain, and more. In the past, a general approach of blanket immunosuppression was commonly used to treat lupus. These immunosuppressive drugs would broadly target the immune system and focus on reducing symptoms. However, recent research has shown that selective immunotherapies such as monoclonal antibodies (anifrolumab and belimumab) which target specific components of the immune system are more effective in managing lupus because of their ability to reach specific cells in the immune system rather than easing symptoms. Anifrolumab blocks the activity of type I interferons, while belimumab neutralizes BLyS to reduce the production of autoantibodies, the root cause of SLE.¹⁻² This paper will introduce the immunology of the disease, explore how the more traditional approach of blanket immunosuppressive drugs work compared to the newer selective immunotherapies, and review the results from the clinical trials of anifrolumab and belimumab.

Introduction: In Ethiopia, maternal undernutrition is a major public health concern. However, comprehensive evidence is lacking in the southern part of Ethiopia, specifically the household and community-level related determinants of undernutrition. Besides, the evidence about the prevalence and determinants of undernutrition is not yet documented in the current study setting. Thus, this study aimed to determine the prevalence of undernutrition and identify its determinants among pregnant women in Hawela Lida district of the Sidama region, Ethiopia.Methods: A community-based cross-sectional study was conducted on a sample of 515 pregnant women from June 1–25, 2024. A multi-stage sampling method was utilized to select eligible pregnant women. We collected data using the Open Data Kit smart phone device and exported it to Stata version 17 for further processing and analysis. A multi-level mixed-effects modified Poisson regression analysis with robust variance was used to account for between and with cluster effects.Result: The prevalence of undernutrition among pregnant women was 41.7% (95% CI: 37.3–45.6). The prevalence of undernutrition was associated with planned pregnancy (adjusted prevalence ratio [APR]: 0.80; 95% CI: 0.66-0.98), household food insecurity (APR: 1.64; 95% CI: 1.26-2.13), inadequate dietary diversity (APR: 1.79; 95% CI: 1.43-2.25), and women’s poor knowledge of nutrition (APR: 1.68; 95% CI: 1.32-2.12) at individual levels. The identified determinants of undernutrition at the community level were low community literacy rates (APR: 4.62; 95% CI: 1.13–18.79) and low community wealth status (APR: 1.91; 95% CI: 1.10–3.31).Conclusion: Two in five pregnant women had an undernutrition problem in the study setting. Individual and community-level determinants contributed to the high prevalence of undernutrition. Thus, any prevention and control approaches to undernutrition should consider inter-sectorial collaboration to account for determinants at various levels. Besides, any program must emphasize the delivery of nutrition education about dietary diversity, particularly targeting pregnant mothers who have poor knowledge of nutrition and unplanned pregnancy at the individual level. Moreover, creating a small business reform for the community with low wealth status using agricultural extension workers must be considered.

The current emphasis in the advancement of space-based synthetic aperture radar (SAR) is on lightweight payloads under 100kg with resolutions surpassing 1m. This focus is directed towards meeting the launch criteria for multiple satellites on a single rocket and cutting costs. This article discusses the creation and progress of a Ku-band SAR payload for the Taijing-4(03) Satellite, launched on January 23, 2024 accompanied by four other satellites. The SAR payload design was customized to meet the demands of a micro-nano satellite platform, resulting in a lightweight, flat design weighing less than 80kg, seamlessly integrated with the plate-shaped satellite platform. The article also introduces a beam optimization strategy for the phased array SAR antenna, significantly boosting the SAR system’s performance. The SAR payload provides various operating modes like slide-spot, strip, scan 1, scan 2, and others, with a maximum achievable resolution exceeding 1m. Extensive in-orbit testing of the payload produced numerous high-quality SAR images with potential uses in emergency disaster mitigation, safeguarding ecosystems, monitoring forests, managing crops, tracking sea ice, and more.

We introduce and analyze conceptual approximations of the Boussinesq equation for horizontal unconfined aquifers during the pure drainage phase, without any reharge and zero-inflow conditions. We employ a variety of methods, which include wave solution, variable separation and series expansion to constract a new model and explore its behavior and performance against the Boussinesq equation and its exact (non-closed form) solution, at early and later times. The modeled non-linear forms are finally linearized concluding with explicit analytical expressions that incorporate most of the basic characteristics regarding the evolution of the water table and the outflow from the exact Boussinesq equation under different initial conditions. The endeavors of this work might be useful for theoretical and modeling purposes related to this problem.

AbstractEthiopia is a country that is in the process of development. Unfortunately, the management and utilization of watershed resources in this region are inadequate. This has resulted in a decrease in the quality of essential resources like soil, water, plants, and animals. Our research delved into the intricate biophysical conditions, conservation practices, and key issues surrounding watersheds along with their root causes and current strategies. The study was particularly focused on understanding the reality and different approaches employed in watershed management practices at the Gullele Botanical Garden located in Addis Ababa. We gathered information through interviews with experts and technicians, direct on-site observations, and official records from the garden's administration office. The gathered data was meticulously analyzed both qualitatively and quantitatively using Arc Map 10.3 to gain a comprehensive understanding of the area. Our findings revealed that the main objective of watershed management in areas surrounding restricted forest sites, Dam A, and Dam B was centered on conserving soil and water resources. The study emphasized the importance of selecting appropriate technologies for effective water and soil conservation practices. Data collection was done using purposive and random sampling methods, drawing information from a variety of sources such as the Gullele Botanical Garden office, literature, research reports, student theses, and both published and unpublished organizational documents. Despite these efforts, our study highlighted inefficiencies in the institutions responsible for watershed management. In particular, the maintenance of stone bunds, gullies, and gabions was not conducted adequately, leading to project deficits. Moving forward, we recommend raising awareness, enhancing training programs, and strengthening law enforcement and watershed policies to transform the knowledge, skills, and attitudes of technicians and staff involved in watershed management techniques for the better.

Portland cement emits large amounts of CO2 in production. Given proposals for "carbon peaking and carbon neutralization" studying alternative low-carbon cementitious materials to reduce emissions is extremely important. Alkali-activated slag (AAS) cement, a new green cementitious material, has high application potential. The chemical corrosion resistance of AAS concrete is important for ensuring durability and prolonging service life. Studying the chemical corrosion mechanism of AAS concrete and understanding its influence on performance provides important theoretical foundations for application in different environments.

The significance of digital sustainability in donation-based crowdfunding platforms lies in its ability to encourage environmentally aware and socially responsible practices in the sphere of online philanthropy. Fundraising has been revolutionized by the emergence of donation-based crowdfunding platforms. This study explores the various factors influencing individuals' attitudes towards these platforms, particularly focusing on perceived usefulness, ease of use, credibility, and self-efficacy. The study examines how these factors affect donation intentions and electronic word-of-mouth intentions, utilizing data from 326 college students. The findings confirm that perceived usefulness, ease of use, credibility, and self-efficacy play crucial roles in shaping attitudes. Furthermore, these attitudes significantly impact both donation intentions and electronic word-of-mouth intentions. Adjustments to the structural model highlight the interconnectedness of these factors, improving the model's accuracy. The results provide practical guidance for platform administrators, campaign creators, and stakeholders involved in online philanthropy, emphasizing the need for user-friendly designs, trust-building, and fostering user confidence for successful crowdfunding efforts.

Whereas there is an increasing number of scientific publications investigating the optimal anti-biotic treatment for diabetic foot infections, we are lacking corresponding data in the adult non-diabetic (postsurgical) foot infection population. We therefore established one of the largest single-center databases on this topic and retrospectively investigate failures of a combined sur-gical and antibiotic therapy for surgical site foot infections. Overall, 17.4% of the episodes expe-rienced any therapeutic failures; especially among the infected ankle prostheses. In contrast, neither the age, the biological sex, pathogens, the duration of post-debridement antibiotic treatment, the number of surgical debridement, or the use of negative-pressure wound care could alter the failure risk. In multivariate logistic regression analyses, the duration of postsur-gical antibiotic use was completely indifferent (as a continuous variable with odds ratio 1.0, 95% confidence interval 0.96-1.03), or when stratified into inter-tertiary groups. Our results poten-tially enable shorter applications of systemic antibiotics in favor of a better stewardship in the non-diabetic adult population. Consecutive prospective-randomized trials are under way to identify eligible patient populations for a potentially shorter durations in surgical site infections after elective foot and ankle surgery.

Patients with heart failure (HF) with improved LVEF (HFimpEF) demonstrate better clinical outcomes when compared with individuals without restoration of cardiac function. Identification of predictors for HFimpEF may play a crucial role in individual management of HF with reduced EF (HFrEF). Cell-free nuclear (cf-nDNA) DNA are released from damaged cells and contribute to adverse cardiac remodeling, cardiac dysfunction and inflammation. The purpose of the study was to elucidate whether cf-nDNAs are associated with HFimpEF. It has been prescreened 1416 patients with HF using local database. Between October 2021 and August 2022 we included 452 patients chronic HFrEF after prescription of optimal guideline-based therapy and identified HFimpEF in 177 individuals from them according to the criteria of European Society of Cardiology. Measurements of circulating biomarkers were performed at baseline and in 6 months. Detection of cf-nDNA was executed with real time quantitative PCR (qPCR) using NADH dehydrogenase, ND2 and beta-2-microglobulin. We found that HFimpEF was associated with a significant decrease in the levels of cf-nDNA when compared with the patients from persistent HFrEF cohort. Presence of ischemia-induced cardiomyopathy (odds ration [OR] = 0.75; confidence interval [CI] = 0.62 – 0.88; p = 0.044), type 2 diabetes mellitus (OR = 0.77; CI = 0.71 – 0.82; p = 0.042) and digoxin administration (OR = 0.85; CI = 0.72-0.97; p = 0.042) were negative factors for HFimpEF, whereas NT-proBNP ≤1940 pmol/mL (OR = 1.42; 95% CI = 1.19-1.98, p = 0.001), relative decrease in NT-proBNP levels (>35% vs. ≤35%) from baseline (OR = 1.52; 95% CI = 1.38-0.69, p = 0.001) and cf-nDNA ≤7.5 μmol/L (OR = 1.56; 95% CI = 1.07-2.94, p = 0.001) were positive predictors for HFimpEF. Multivariate logistic regression adjusted to ischemia-induced cardiomyopathy, IV HF NYHA class, and digoxin use yielded that NT-proBNP ≤1940 pmol/mL (OR = 1.43; 95% CI = 1.21-1.88, p = 0.001) and cf-nDNA ≤7.5 μmol/L (OR = 1.64; 95% CI = 1.19-2.15, p = 0.001) independently predicted HFimpEF. In conclusions: we established that the levels of cf-nDNA≤7.5 μmol/L independently predicted HFimpEF and improved discriminative ability of as single measured NT-proBNP as well as relative decrease in NT-proBNP levels ≤35% from baseline.

Nasal tumors are some of the most common tumors in aged golden retrievers. Nasal tumors are mostly found to be adenocarcinomas or carcinomas. Radiation therapy is the first option to debulk the tumor, and oral or intravenous chemotherapy is administered depending on the prognosis. Therefore, it is important to select the most appropriate drug for chemotherapy considering the price and the presence of concurrent disease. Anticancer drugs include first-generation chemotherapies, second-generation targeted anticancer drugs, and third-generation immunotherapy drugs. Considering their price and effectiveness, first- or second-generation anticancer drugs are mainly used. We report a case in which a retriever with a nasal tumor was successfully treated and managed using a combination of chlorambucil (4mg/day, SID) and prednisolone (10mg/day) orally for 9 months at a general practice. A 35 kg spayed female golden retriever aged 8 years and 8 months visited the Bundang New York Animal Hospital in July 2023. A protocol of 4 weeks of chemotherapy followed by 1 week of rest was repeated, and the nasal exudate persisted. The exudate was significantly reduced. The size of the nasal tumor was monitored using CT imaging at a referral hospital, and the images were taken in the following order: 1. before radiation therapy at the referral hospital and before chemotherapy; 2. after radiation therapy and before chemotherapy; and 3. after radiation therapy and after chemotherapy. Since the first instance of nasal bleeding, 12 months have passed (as of July 24). The nasal exudate is barely visible, and the retriever’s vital signs and weight remain stable. The size of the nasal tumor significantly decreased after 9 months of chemotherapy without moderate side effects. This study demonstrates that a prednisolone/chlorambucil metronomic combination can be an alternative to second-generation anticancer drugs as it is the cheapest and most effective way to manage tumors along with conventional radiation therapy.

The study of the pathogenesis of febrile seizures and their consequences frequently necessitates gene expression analysis. The primary methodology employed for such analysis is reverse transcription with quantitative polymerase chain reaction (RT-qPCR). To guarantee the accuracy of data obtained by RT-qPCR, it is crucial to utilize stably expressed reference genes. The objective of this study was to identify the most suitable reference genes for use in the analysis of mRNA production in various brain regions of rats following prolonged neonatal febrile seizures. The expression stability of eight housekeeping genes was evaluated using the online tool RefFinder in the dorsal and ventral hippocampal regions and in the temporal and medial prefrontal cortex of the brain. The Ppia gene exhibited the greatest stability of expression. Conversely, the genes with the least stable expression level are Actb and Ywhaz; thus, it is not recommended to use them for normalization in a febrile seizure model. Additionally, the majority of housekeeping genes demonstrate age-related, region-specific fluctuations. Therefore, it is crucial to employ the appropriate housekeeping genes for each brain structure under investigation when examining the expression dynamics of genes of interest in a febrile seizure model.

Reconstructing 3D indoor scenes from 2D images has always been an important task in computer vision and graphics applications. For indoor scenes, traditional 3D reconstruction methods suffer from the lack of surface details, poor reconstruction of large flat surface textures and areas with uneven lighting, and many falsely reconstructed floating debris noises in the reconstructed models. We add adaptive normal priors to the neural implicit reconstruction process to optimize the network, and improve the accuracy of volume density prediction by adding regularization terms to the neural radiation field to constrain the volume density obtained by weight distribution, and learn a smooth SDF surface from the network to obtain an explicit mesh model. Experiments show that the method proposed in this paper outperforms the state-of-the-art methods on ScanNet, Hypersim, and Replica datasets.

Purpose: The aim of this study was to compare the topical anesthetic effect of a 10% atomized lidocaine spray and an EMLA cream at different time intervals using parameters of visual analogue scale (VAS) score and heart rate (HR). Methods: The randomized split-month study included 30 patients (17 boys, 13 girls) aged 8.22 ± 1.8 years. Application of atomized lidocaine spray or cream was randomly used in the upper second premolar region. The parameters was measured before and at each needle insertion after 10,30,60 and 120 sec. Paired t -test and independent t-test were used for statistic analyses. Results: Compared to the first applications (10 sec), atomized lidocaine and EMLA cream applications significantly decreased scores of VAS at the applications at 30 and 120 seconds, respectively. Despite atomized lidocaine showed early effect compared to EMLA, there were no significant differences in VAS scores between the atomized lidocaine and EMLA cream at the 60 and 120 seconds measurements. Although HR significantly increased at first anesthetic administration with the atomized lidocaine spray, HR significantly decreased at 30 and 120 seconds administrations. Conclusion: Atomized 10% lidocaine-based topical anesthetics significantly reduced pain more rapidly and better than EMLA from needle pricks in the buccal mucosa. Therefore, atomized lidocaine topical anesthesia could be used as a substitute for EMLA cream before buccal anesthetic administration. On the other hand, further comprehensive studies are required to explore the effects of several doses of atomized lidocaine in various areas of the oral cavity.

The relationship between Herpes Simplex Virus (HSV) and oral risk habits is still uncertain. This study aimed to investigate the connection between oral risk habits and HSV status in a group of male patients from Sri Lanka who have oral fibroepithelial polyps. We collected 25 fibroepithelial polyps from nine oro-maxillofacial units in six provinces of Sri Lanka. Tissue samples were taken from frozen excisional biopsies to avoid contamination and tested for HSV- DNA using a real-time PCR assay. The results showed that HSV-DNA was present in 44% of the samples, with 66.67% being HSV-1 and 33.33% being HSV-2. However, there was no significant correlation between HSV status and oral risk habits such as betel quid chewing, smoking, and alcohol abuse. The study suggests the need for larger case-control studies to determine any significant associations between different types of Herpes Simplex Virus and oral risk habits.

Limiting training data in low-resource languages is a barrier to Natural Language Processing (NLP). Regardless, languages with thousands of users worldwide require improved NLP capabilities. The Table-to-Text task—typically develops natural language descriptions using data tables, tests model reasoning abilities—although it is especially tough in multi-language settings. System output frequently lack credit to their underlying data. Intermediate planning strategies—which include Question-Answer (QA) blueprints—improving summarization tasks by presenting related QA pair prior to verbalization. Therefore, this study analyses whether QA blueprints improve multilingual Table-to-Text output attribution. An enlarged multilingual dataset, encompassing African languages, contains QA blueprints that were produced and filtered heuristically. This dataset is used to fine-tune sequence-to-sequence model (transformers)—both with and without blueprints. Two configurations are evaluated—English reference blueprints with language target verbalization and modified blueprints. These results show that English-only models benefit from blueprints, whereas multi language models cannot. Errors in machine-translating blueprints provide challenges, as do models that rely on their generated blueprints.

The effectiveness of a hybrid technique for identifying seismic damage in planar, multistory, steel X or V-braced frames is demonstrated here through an example of a six-story frame. This proposed technique, referred to as “M and P”, combines the instrumental Monitoring (M) with Pushover analysis (P). According to the methodology, the diagram of stepping eigenfrequencies of the frame in the inelastic region is initially plotted against seismic roof displacement. The fundamental natural frequency detected via the monitoring process is then utilized in this key diagram to reveal the inelastic roof displacement that corresponds to the damage state of the steel braced frame. This displacement is subsequently used as the target in the pushover analysis, facilitating the identification of seismic damage in the existing steel braced frame. Finally, the damage image is correlated with the damage stiffness matrix of the frame at the same inelastic roof displacement. The investigation results indicate that combining instrumental monitoring with pushover analysis enables accurate identification of seismic damage potential in existing steel braced frames.

Background: Despite tremendous advances in medicine, infective endocarditis (IE) continues to be a challenge for physicians due to increasing morbidity and unchanged high mortality. Objectives: Our aim was to evaluate clinical outcomes in patients with IE and to identify predictors of in-hospital mortality. Material and methods: The study was retrospective, single-centered, and included 270 patients diagnosed with IE, for the period 2005-2021 (median age 65 (51–74), man 177 (65.6%). Results: Native IE (NVIE) was found in 180 (66.7%), prosthetic IE (PVIE) in 88 (33.6%) and cardiac device-related IE (CDRIE) in 2 (0.7%), significantly more in the non-survivors group. Healthcare associated IE (HAIE) was 72 (26.7%), the most common pathogen were Staphylococci and the proportion of Gram-negative bacteria (GNB) non-HACEK were significantly higher in non-survivor’s vs survivors (11 (15%) vs 9 (4.5%), p=0.004). Overall, early surgery was performed in 54 (20%) patients, with a significant difference between deceased/alive (3 (4.5%) vs 51 (25.1%, p=0.000). The all-cause in-hospital mortality rate was 24.8% (67). The risk factors identified that increased the risk of death were septic shock (OR – 83 1; 95% CI (17.0-405.2), p=0.000) and acute heart failure (OR –24.6; 95% CI (9.2-65.0), p=0.000). Early surgery (OR – 0.03, 95% CI (0.01-0.16), p=0.000) and low Charlson comorbidity index (OR – 0.85, 95% CI (0.74-0.98, p=0.026) in turn reduce this risk. Conclusion: We found that acute heart failure and septic shock are independent predictors of in-hospital mortality. Low Charlson comorbidity index and early surgery increased survival. Knowing the predictors of death would change the therapeutic approach to a more aggressive one and improve the near and long-term prognosis of patients with IE.

Glucagon-like peptide-1 (GLP-1) agonists are gaining attention as a potential treatment for obesity. While studies have shown that these medications greatly impact dietary habits, their relationship to consumer food waste is unexplored. We analyzed data from 505 U.S. consumers who self-report GLP-1 medication use and found that 25% agree that they waste more food since beginning the medication with 61% disagreeing with this statement. Respondents are less likely to agree with this statement if they have been on the medication a longer time and more likely to agree if they report experiencing nausea since beginning the medication. Several dietary changes are also significantly associated with self-reported changes in food waste since starting the medication. With previous literature finding GLP-1’s significant impact on individual food consumption and dietary choices, our findings suggest that the effects of this novel class of anti-obesity medications may cast a significant impact on food waste patterns. With the potential for widespread adoption of these medications, and given that approximately one-third of food in the United States is wasted by consumers, understanding the interaction of these two consumer trends is critical for projecting their joint impact on the food system.

Knowledge is not merely the characteristic of certain pieces of information being deemed true, believed and justifiable, but rather a process. The sentences that reaches the status of knowledge forms a universe that provides an interpretation of the reality one aims to describe. Language exchanges information through communication and the justification, if concludes successfully with respect to a sentence, it elevates the information to the status of knowledge. We provide a model where we define the fundamental elements of communication and grammar. As a result, knowledge must be \open\ (everyone must be able to acquire it), \free\ (everyone must be able to justifiy) and \tidy\ (everyone must be able to retrace the justification process in all its parts recursively). Ultimately, the development of knowledge processing, referred to as \emph{knowmatic}, represents the evolution of the information technologies (\it).

: The global impact of the COVID-19 pandemic has resulted in substantial morbidity and mortality rates. Consequently, there is a pressing need for clinical research focused on the prevention, diagnosis, and treatment of this disease. To comprehensively study the course of COVID-19 in the Philippine population, it is essential to have a comprehensive dataset that includes relevant treatment and diagnostic information. While individual patient reports related to the disease are available at various institutions in the Philippines, there is a need for a more extensive and representative database to facilitate robust analysis. The purpose of this review is to elucidate various challenges and opportunities as well as propose solutions for the development and implementation of a prospective COVID-19 patient registry within a regional context in the Philippines. The primary clinical objective of establishing this registry was to enhance the accuracy of disease diagnosis. In this review, we present a comprehensive explanation of the systematic rationale, design, and execution of a COVID-19 patient registry in the Western Visayas region of the Philippines. Based on this review, several factors exist that hinder the implementation of a COVID-19 patient registry in the regional setting in the Philippines including lack of funding, facilities, infrastructure, manpower, expertise, and unwillingness of some hospitals to pursue research. We also discussed herewith the proposed program implementation for the establishment of such registry in a regional setting in the Philippines.

A medium scale household in South Africa consumes about 1000 kWh on average, and ae household spend about 3000 ZAR per month on energy supply using grid electricity. Grid electricity. South Africa’s energy is supplied by a huge governmental organization. Statistical analyses indicate that projected increase of the cost of grid electricity in South Africa is about 30% per annum for the next five years. Our research show that Photo-Voltaic (PV) technology can offer a viable alternative, provided a large initial capital outlay can be made. The technology is user-friendly and easy to operate. It is calculated that the cost of electricity, capitalized over 20 years, considering an 80 % supply of needs and assuming 20 sunny days per month, is about 2.80 ZAR. The study also shows that utilizing a hybrid combination of renewable energies, such as combining PV supply with solar thermal energy absorbers, and converting thermal energy to electricity, as energy supply systems, could reduce the current cost of electricity per household in South Africa to about half of national grid supply prize, R1,50 per kWhr. The study also shows that water provides as a most viable medium to store energy, instead of using expensive battery technology to perform such functions.

Significant advancements have been made in controlled drug delivery systems in recent years, especially for oral administration. Conventional methods, although groundbreaking, encounter significant constraints when handling drugs with weak acidity or alkalinity because of their solubility being influenced by pH. The release rates of these ionizable drugs are subject to variability, which is influenced by factors such as the pH of the gastrointestinal tract (GIT), patient-specific conditions, and whether the patient is in a fed or fasted state. As a result, there is often a lack of correlation between in vitro and in vivo data. Therefore, it is imperative to develop drug delivery systems that are not affected by changes in pH in order to address these limitations. This review delves into different strategies that have been developed to achieve drug release that is not affected by changes in pH. These strategies include the utilisation of Diffucaps technology, the incorporation of pH modifiers and surfactants, the combination of non-ionic and ionic polymers, the implementation of supersaturating techniques with nucleation inhibitors, and the utilisation of osmotic drug delivery systems. We assess the efficacy of these methods in reducing the influence of pH fluctuations on the solubility and release rates of drugs. In addition, we explore the potential of these innovative techniques to enhance the reliability and predictability of drug delivery, ultimately leading to better therapeutic results. This review provides an in-depth information of various pH independent controlled drug delivery based formulation and By summarizing the existing technologies and looking into the future, the importance of innovation in pH independent delivery systems is emphasised, laying a good foundation for the future design of simple drug delivery systems, which will be conducive to achieving a wider range of applications in oral drug delivery system.

This study aims to conduct a content analysis of the postgraduate theses on the education of the concept of atom in Turkey from 2000 to 2023. The study utilized the document analysis method, a qualitative research design approach. The theses were obtained by conducting a search in the "Thesis Center" of the Council of Higher Education (YÖK). "Thesis Classification Form" and "Thesis Screening Form" were used as data collection tools. Content analysis was performed on 51 theses that were conducted between 2000 and 2023 and whose full versions were accessed. It was observed that the theses were conducted in 25 different universities, using more than one data collection tool and analysis method. It was determined that most of the theses were supervised by academicians having the title of Prof.Dr. It was determined that almost all of the theses were conducted in the form of research-studies, qualitative research approach was mostly used as the research method, quasi-experimental model was mostly used as the research model, and students were generally used as the sample group. The most widely used data collection tools in the theses were interviews and achievement tests, while t-tests and content analysis were used as analysis techniques. In the selection of thesis topics, the studies in which teaching methods were tried the most were conducted. It was determined that students had difficulty in understanding the concept of atom and had misconceptions.

Background The increasing number of elderly individuals in South Korea, now entering a super-aging era, underscores the growing importance of understanding their specific oral health needs. This study investigated changes in oral health conditions, salivary parameters, halitosis, systemic diseases, and medication usage with aging. Methods This study was retrospectively conducted using the medical records of patients who presented with complaints of xerostomia or halitosis between August 2020 and May 2023. A total of 274 patients (66 males, 208 females, mean age 59.39 ± 16.10 years) were included in this study. Results Aging was found to be significantly associated with the presence of sticky saliva, poor oral hygiene, tongue coating, and halitosis (all p < 0.05). Correlation analyses further revealed significant associations between aging and several conditions, including hypertension (r = 0.495, p < 0.001), diabetes mellitus (r = 0.255, p < 0.001), amlodipine usage (r = 0.249, p = 0.001), osteoporosis (r = 0.195, p = 0.001), cardiovascular disease (r = 0.150, p = 0.013), and the presence of tongue coating (r = 0.205, p = 0.001). Conversely, none of the salivary parameters demonstrated a significant relationship with aging. Furthermore, halitosis did not exhibit significant differences across age groups (all p > 0.05), with the exception of methyl mercaptan levels, which were notably higher among patients in their 20s (p = 0.049). Conclusions The findings of this study can help clinicians develop targeted strategies to address specific oral health challenges associated with aging in elderly patients.

As urban areas expand and populations grow, environmental challenges such as the urban heat island effect, air pollution, and light pollution intensify. The urban heat island effect exacerbates extreme heat conditions, leading to prolonged periods of unhealthy and hazardous environments for both humans and other species. This study investigates the thermal environment associated with the urban heat island effect, focusing on the role of trees in mitigating this issue. Using ENVI-met simulations, the study examines various factors influencing tree cooling effectiveness, including seasonal variations, building shading, transpiration rates, tree placement, and spacing. A new tree-planting strategy is developed based on these findings, aiming to enhance thermal comfort. The study compares the thermal environment of sidewalks under the new tree-planting scheme with the existing arrangement across different months. Results indicate that the new scheme reduces UTCI temperatures by 2.2°C on the hottest day, 0.97°C on the coldest day, and 1.52°C annually in the study area of Los Angeles, demonstrating that the cooling benefits of trees in hot weather outweigh the potential drawbacks in cold weather, highlighting its potential to mitigate the urban heat island effect.

Art's unique style and creativity are essential in defining a work's identity, conveying emotions, and shaping audience perception. Recent advancements in diffusion models have revolutionized art design, animation, and gaming, particularly in generating original artwork and visual identities. However, traditional creative processes face challenges such as slow innovation, high costs, and limited scalability. Consequently, deep learning has emerged as a promising solution for enhancing painting-style creative design. In this paper, we present the Painting-Style Design Assistant Network (PDANet), a groundbreaking network architecture designed for advanced style transformation. Our work is supported by the Painting-42 dataset, a meticulously curated collection of 4,055 artworks from 42 illustrious Chinese painters, capturing the aesthetic nuances of Chinese painting and offering invaluable design references. Additionally, we introduce a lightweight Identity-Net, designed to enhance large-scale text-to-image (T2I) models by aligning internal knowledge with external control signals. This innovative Identity-Net seamlessly integrates image prompts into the U-Net encoder, enabling the generation of diverse and consistent images. Through extensive quantitative and qualitative evaluations, our approach has demonstrated superior performance compared to existing methods, producing high-quality, versatile content with broad applicability across various creative domains. Our work not only advances the field of AI-driven art but also offers a new paradigm for the future of creative design.

Dispatching goods is becoming more difficult to manage in the field of logistics due to the high demand for order shipments. This is relative to the increasing popularity of the use of e-commerce platforms among consumers, where delivery of products is required as compared to buying in physical stores. Dispatch management is one of the critical components in a supply chain since it covers the coordination tasks among stakeholders from warehouse up to the consumer’s doorstep. In this study, the authors intend to propose a framework leveraging geographic information to sustain the logistics operations, specifically in terms of managing last-mile delivery and return trip orders. This includes scheduling, communications, and inventory of goods shipment. A mobile application built on this framework was integrated with a waypoint order optimization algorithm considering the entire route traversing all the required pick-up and delivery points. It was pilot tested with an actual dispatch operation of a logistics company yielding a decrease of 87% in total shipment time, 79% in operations cost, and 3% in carbon footprint per vehicle. With the adoption of this framework, the study aims to contribute to the overall efficiency and sustainability of logistics operations in a wider geographic range.

Background: Ubiquitination is an important post-transcriptional modification crucial for maintaining cell homeostasis. As a deubiquitination enzyme, ubiquitin-specific protease 1 (USP1) is associated with tumor progression; however, its role in bladder cancer is unknown. This study was aimed to analyze USP1 expression and study its roles in bladder cancer. Methods: The web server GEPIA was used to analyze the USP1 expression. To explore USP1 function in bladder cancer, we constructed USP1-knockout cell lines in UMUC3 cells. A FLAG-USP1 (WT USP1) plasmid and a plasmid FLAG-USP1 C90S (catalytic-inactive mutant) used to overexpress USP1 in T24 cells. CCK8, colony formation, and transwell assays were used to assess cell viability, proliferation and migration. RNA sequencing (RNA-seq) and dual-luciferase reporter assays were performed to screen the pathway. Coimmunoprecipitation and immunofluorescence were used to explore the interaction between USP1 and c-MYC. Xenograft mouse model was used to study the role of USP1 in bladder cancer. Results: USP1 expression is upregulated in human bladder cancer cells and correlated with poor patient prognosis. USP1 overexpression promoted cell proliferation, clone formation, and migration; this was attenuated by genetic ablation of USP1. Furthermore, we observed that USP1- deficiency inhibited tumor formation in vivo. Mechanistically, the c-MYC pathway was remarkably activated compared with the other pathways. Furthermore, USP1 could directly interact with c-MYC. and increase c-MYC stability depending on the catalytic activity of USP1. Conclusions: Our results suggest that high expression of USP1 promotes bladder cancer progression by stabilizing c-MYC; hence, USP1 it may serve as a novel therapeutic target for treating bladder cancer.

Introduction: Pulmonary hypertension (PH) in systemic sclerosis (SSc) can be caused by different pathophysiological mechanisms, including precapillary PH (pulmonary arterial hypertension), post-capillary PH (secondary to left heart diastolic dysfunction), or combined pre- and post-capillary PH. To unmask occult post-capillary PH, fluid loading with saline during right heart catheterization (RHC) is recommended. In the present study, we investigated the response to fluid challenge test (FCT) in patients with SSc who were referred for RHC due to their high likelihood of PH on screening echocardiography. Methods: Demographic data, clinical characteristics, echocardiographic and RHC data, and cardiac magnetic resonance imaging (CMR) results were obtained from the patients' hospital records or by contacting their rheumatologist. A positive FCT was defined as an increase in pulmonary capillary wedge pressure (PCWP) to more than18 mmHg with rapid saline infusion. Patients were followed for a median (IQR) of 15 (7-20) months. Results: Of the total 98 scleroderma patients 34 patients (29 female) were included. The mean age (SD) was 50.6(8.2) years. Baseline RHC data showed that 20 patients had no PH and 14 patients had mild precapillary PH (mPAH). Ten patients (50%) of the patients with no PH and 10 patients (71.4%) with mPAH had a significant increase in PCWP after a fluid loading. There was no statistically significant difference between the patients with positive and negative FCT in terms of the presence of LGE/inflammation on CMR examination. During follow-up, 3 patients died. Mortality was due to SSc-related complications in two patients. Conclusion: This study provides preliminary evidence that FCT may be a useful adjunct to baseline RHC testing to identify SSc patients with latent postcapillary PH. Further studies are needed to confirm these results and determine the optimal role of the fluid challenge test in the clinical management of SSc patients with suspected PH.

AI integration is becoming more important in today’s world and could potentially be very useful in the life sciences and biotechnology. This study evaluates the effectiveness of AI systems in teaching molecular cloning techniques to newcomers in molecular biology, focusing on a comparison between Gemini Advanced (powered by Gemini Ultra 1.0) and ChatGPT (GPT-4o). Molecular or DNA cloning is a lab technique for creating multiple copies of a specific DNA segment. It involves isolating the DNA fragment, inserting it into a vector, and introducing it into a host cell, typically bacteria, which then generates numerous copies of the DNA. This essential technique underpins genetic engineering, allowing for gene study, protein expression, and the creation of genetically modified organisms. The primary objective of this study was to assess whether individuals with limited laboratory experience could effectively acquire a specific molecular biology skill set solely through an AI system, rather than relying on the more traditional ‘learning by shadowing’ approach. Participants with limited lab experience completed these tasks using both Gemini and GPT-4o, and evaluated on quality of instructions, conciseness, scientific accuracy, and user satisfaction. Results indicated that both AI systems demonstrated strengths in delivering clear and comprehensive instructions, but in different ways. Gemini, although more interactive with images and diagrams lacked directness and had a harder time keeping past steps in its “memory”. On the other hand, GPT-4o was much more direct and concise in the steps listed and had more accurate results akin to what is performed in the lab. This study underscores the potential of AI-driven tools to simplify complex biotechnological procedures, making them accessible for learners at all levels.

Background. National surveys reported on variable prevalence of chronic kidney disease (CKD) due to differences in characteristics of population, design, equations used to estimate glomerular filtration rate (eGFR) and definitions. The EH-UH 2 survey is the first study evaluating CKD prevalence, characteristics and awareness in Croatia. Methods. This was a cross-sectional nationwide observational study designed to assess the prevalence and cardio-kidney-metabolic risk factors in Croatia which included 1765 randomly selected subjects. We estimated the prevalence of CKD by means of albumin-to-creatinine ratio (ACR) and eGFR (CKD EPI equation). Comorbidities, anthropometric and social factors related to the prevalence of CKD were analyzed, and CV risk profile was evaluated. Results. The weighted prevalence of CKD (any stage), CKD stage ≥ G3A A2, and CKD defined only as eGFR < 60 ml/min/1.73 m2 were estimated at 17.1%, 9.8% and 7.9%, respectively. The prevalence was higher in men than in women (11.8% vs. 7.9%; p 30 mg/g was 15.1%. Older age, male gender, diabetes, ePWV, and uric acid were independently associated with CKD prevalence. The awareness of CKD of 9.5%. Unaware were older with lower income, less educated, having more frequently diabetes, hypertension (less frequently controlled) and milder renal impairment. Conclusion. In Croatia, the estimated prevalence of CKD is high, being more frequently presented in men than in women. CKD patients have unfavorable CV risk profile. The awareness of CKD is very low reflecting poor health literacy in general population but also in health care workers.

The artificial solar saltwork fields of Hon Khoi are important industrial and biodiversity resources in southern Vietnam. Most hypersaline environments in this area are characterized by saturated salinity, nearly neutral pH, intense ultraviolet radiation, elevated temperatures and fast desiccation processes. However, the extreme halophilic prokaryotic communities associated with these stressful environments remain uninvestigated. To fill this gap, a metabarcoding approach was conducted to characterize these communities by comparing them with solar salterns in northern Vietnam as well as with Italian salterns. Sequencing analyses revealed that the multiple reuses of crystallization ponds apparently create significant perturbations and structural instability in prokaryotic consortia. However, some interesting features were noticed when we examined the diversity of ultra-small prokaryotes belonging to Patescibacteria and DPANN Archaea. Surprisingly, we found at least five deeply branched clades, two from Patescibacteria and three from DPANN Archaea, which seem to be quite specific to Hon Khoi saltwork fields ecosystem and can be considered as a part of biogeographical connotation. Further studies are needed to characterize these uncultivated taxa, to isolate and cultivate them, which will allow us to elucidate their ecological role in these hypersaline habitats and to explore their biotechnological and biomedical potential.

The Gaussian signaling strategy with power control for the Gaussian Z-interference channel with weak interference is reviewed in this paper. In particular, we study the various communication strategies that may arise at various points of the capacity region and identify the locations of the phase transitions between the various strategies. The Gaussian Z-interference channel with weak interference is known to have two critical points in its capacity region, where the slope of the region shows a sudden change. They occur at the points of the unconditional maximum rate for one of the users and the maximum rate that can be accommodated by the other user. In this paper, we discuss two additional critical points (locations of phase transitions) in the achievable region of this channel. At these points, we do not observe a discontinuous slope in the achievable rate region, but there is a discontinuity in the second derivative of the rate contour of the achievable region. This review paper is mainly based on some of our ITA (Information Theory and Applications Workshop, UCSD, San Diego, CA, USA) papers since 2011.

This work aims to assess the impact of the COVID-19 pandemic on mortality and incidence of complications in patients with bacteremia due to Staphylococcus aureus (BSA). All episodes of BSA at the Costa del Sol University Hospital (Marbella, Spain) were recorded during the acute phase of the COVID-19 pandemic (March 2020 - March 2022), compared with a previous period (February 2018 - February 2020). Demographic, clinical and prognostic variables were recorded. The outcome was measured as 14 and 30-day mortality and the incidence of complications-death. Mortality during the pandemic was 28.7% at 14 days and 35% at 30 days, while in the pre-pandemic group it was 18.9% and 23.3%, respectively. In overall complication-death, the incidence rate is higher in the pandemic group with 42.7%. No significant differences were obtained between groups. 17 patients with COVID-19 were identified, with a mortality rate of 64.7% and 70.6% at 14 and 30 days. Multivariate analysis established the presence of sepsis at diagnosis as a predictor of mortality, but not BSA during the pandemic phase. In conclusion, BSA is a disease with high mortality, slightly higher during the pandemic phase. No differences were found in adherence to the bundle in our centre.

In this study, we investigate different control scenarios through theoretical analysis and numerical simulations. To account for two important types of control for an early ascending stage of an outbreak, social distancing and treatment with antiviral medications, a compartmental model is considered with one control, $u_1(t)$, aimed to lower the disease transmission rate and the other control, $u_2(t)$, aimed to lower the period of infectiousness. In all experiments, the implementation of control strategies reduces the daily cumulative number of cases and successfully "flattens the curve". The reduction in the cumulative cases is achieved by eliminating or delaying new cases. This delay is incredibly valuable as it provides public health organizations with more time to advance antiviral treatments and devise alternative preventive measures. The main theoretical result of the paper, Theorem 3.1, concludes that the optimal control functions, $u_i(t)$, $i=1,2,$ may be increasing until some moment $\tau \in [0, T)$. However, for all $t \in [\tau, T]$, both controls, $u_i(t)$, decline as $t$ approaches $T$ (possibly causing the number of newly infected people to grow). Numerical simulations presented in Section 4 confirm theoretical findings, which indicates that, ideally, around the time $t=\tau$, the control strategy has to be upgraded and a vaccination campaign needs to start to ensure the epidemic wave does not rebound.

Background: Diagnostic accuracy of Parkinson’s disease (PD), a synucleinopathy, based on diagnostic criteria is suboptimal. A biomarker for synucleinopathies is pivotal both from a clinical and from a research aspect. CSF a-synuclein has been extensively studied over the past two decades as a candidate biomarker of synucleinopathies. Herein we present data on studies focusing on total, phosphorylated and oligomeric CSF a-synuclein in PD. Methods: Pubmed, Scopus and Web of Science were searched for studies with &gt;10 PD patients and control subjects, with data (mean, SD) on total, phosphorylated or oligomeric a-synuclein. Cohen’s d, as a measure of effect size, was calculated for all a-synuclein forms. Subgroup analysis and meta-regression were performed in an effort to explain between-study heterogeneity. Results: Thirty studies on total, six studies on oligomeric and one study on phosphorylated a-synuclein were included. Total a-synuclein was decreased and oligomeric a-synuclein increased in PD patients vs. controls. Effect size was medium for total and high for oligomeric a-synuclein. A-syn forms provided suboptimal combined sensitivity/specificity for the differentiation of PD from controls. There was significant between-study heterogeneity. PD cohort characteristics (sex, age, disease duration, UPDRS, H&amp;Y) and study characteristics (study design, healthy vs. neurological controls, control for CSF blood contamination, method of a-syn measurement) could not account for between-study heterogeneity. Publication bias was limited. Conclusions: CSF a-synuclein levels lack sufficient accuracy to be used as biomarkers for PD. Standardization of (pre)analytical variables may improve the discriminatory power of a-synuclein forms in the future.

Fractional flow reserve (FFR) is regarded as the gold standard for assessing the functional significance of coronary artery lesions, yet it remains underutilized in clinical practice. Our objective was to investigate whether FFR results have the potential to alter treatment decisions for coronary lesions compared to visual assessments of angiographic images made by three operators at a high-volume interventional center. In this retrospective study, we aimed to reassess the angiographic images of 63 patients presenting with chronic coronary syndrome (n=39, 61.9%) and acute coronary syndrome (n=24, 38.1%) who underwent FFR. Three experienced interventional cardiologists (with >300 PCI procedures per year) reevaluated, blinded to FFR results, 105 ambiguous lesions in 63 patients to determine angiographic significance and treatment strategy. The observers reached a concordant agreement (≥2 operators made the same decision) to perform PCI in 60 (57.1%) of the lesions based on angiographic evaluation. Interestingly, 9 (15%) of these lesions were functionally non-significant (FFR &gt;0.80). The observers agreed to defer PCI in 45 (42.9%) of the lesions; however, 4 (8.9%) of these were functionally significant (FFR ≤0.80) and required PCI. Thus, inter-observer concordance in visual-guided therapeutic decision-making is variable and not always confirmed by the functional significance of coronary lesions.

Air pollution has become one of the biggest problems throughout the world. Smog has a severe effect on the pulmonary and circulatory systems, which causes a significant number of deaths globally. Therefore, the remediation of air pollutants to maintain ecosystem processes and functions and to improve human health is a crucial problem confronting mankind today. This review aims to discuss the health effects of smog on humans. This review will also focus on the bioremediation of air pollution (smog) using bacteria, fungi, phytoremediation, nanotechnology, and phylloremediation (using plants and microbes). Phyllo-remediation is the most effective technology for removing air pollution naturally. The future perspective presents a great need to produce an ecosystem where microbes, plants, and nanoparticles synergistically control smog. In addition, further advancements would be needed to modify the genetic makeup of microbes and plants. Biotechnological approaches like CRISPR-Cas9 can be applied to the editing and cutting specific genes responsible for the bioremediation of VOCs, NOx, SOx, and harmful hydrocarbons. The extracted genes can then be expressed in biologically modified microorganisms and plants for enhanced bioremediation of smog.

This paper delves into the intricate nature of the different essence interactions that shape our perceived reality, leveraging a blend of existing empirical data and original experiments. Through a multidisciplinary approach encompassing quantum mechanics, general physics, metaphysics, philosophy, and spiritualism, it seeks to elucidate the fundamental interplays governing phenomena such as gravity, mass, electromagnetism, force, motion, and quantum mechanics. This exploration promises a reexamination and unification of these principles, offering novel perspectives on the extraordinary phenomena that underpin our reality. By comprehending and manipulating these interactions, the potential arises to orchestrate reality towards desired ends. This study not only unveils compelling avenues for scientific advancement but also proposes transformative technologies and concepts, including light-speed transportation, remote viewing, communication with the deceased, alchemy, and the realization of what is commonly perceived as magic. These visionary notions not only push the boundaries of current understanding but also provide a captivating glimpse into the future possibilities that may await humanity.

Digital twin technology, a cutting-edge approach that creates dynamic digital replicas of physical systems, is increasingly integral to various industrial applications. However, the effective deployment of digital twins often faces challenges associated with data availability, quality, and interoperability, which can impede the development and operational efficacy of these virtual counterparts. This paper presents a systematic review of the application of artificial intelligence (AI) in enhancing and managing digital twin technologies across multiple domains such as industry, healthcare, urban planning, business, education, technology, and others. It specifically examines how machine learning models, particularly neural networks and deep generative models, are being employed to optimize the creation, maintenance, and functionality of digital twins. The review explores the role of artificial intelligence in overcoming data-related limitations by providing robust, scalable data solutions for digital twins. Additionally, it addresses critical considerations of real-time data processing and system interoperability within these applications. This survey not only identifies the prevailing challenges and opportunities within this emerging field but also highlights potential future research directions that could further the integration of AI with digital twin technology. Through a detailed exploration of the intersection between AI and digital twins, this paper aims to contribute significantly to the knowledge base and encourage further innovations in this interdisciplinary area.

The implementation of cybersecurity standards and directives in the maritime sector plays a crucial role in protecting critical maritime infrastructures from cyber threats. The level of protection depends heavily on humans. However, the effectiveness of cybersecurity training and compliance programs, an essential component of these standards, is often hindered by challenges related to the sector’s environment, including the established technologies, practices, and norms. This paper aims to identify these challenges through a literature review and set the basis for more effective human risk minimisation, responses, and training. We identify 18 challenges and validate them with an online survey (N=205) capturing real-world perspectives from maritime-related stakeholders. Our findings contribute to enhancing the effectiveness of maritime cybersecurity training and compliance programs, ultimately strengthening the maritime cybersecurity posture.

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

Imaginary dimensions in physics require an imaginary set of base Planck units and some negative parameter $c_n$ corresponding to the speed of light in vacuum $c$. The second, negative fine-structure constant $\alpha_2^{-1} \approx -140.178$ present in Fresnel coefficients for the normal incidence of electromagnetic radiation on monolayer graphene leads to the imaginary Planck units. Furthermore, it sets $c_n \approx -3.06 \times 10^8~\text{[m/s]}$. It follows that electric charges are the same in real and imaginary dimensions. Neutron stars and white dwarfs, objects emitting perfect black-body radiation, need energy exceeding their mass-energy equivalence ratios. Complex energies are defined in terms of real and imaginary Planck units. Their imaginary parts, inaccessible for direct observation, store the excess of these energies. It follows that black holes are fundamentally uncharged, charged micro neutron stars and white dwarfs with masses lower than $5.7275 \times 10^{-10}~[\text{kg}]$ are unphysical, and the radii of white dwarfs' cores are limited to $R_{\text{WD}} < 6.7933~G M_{\text{WD}}/c^2$. It is conjectured that the maximum atomic number $Z=238$. A black-body object is in the equilibrium of complex energies of masses, charges, and wavelengths if its radius $R_\text{eq} \approx 2.7665~G M_{\text{BBO}}/c^2$, which corrects the value of the photon sphere radius $R_{\text{ps}}=3G M/c^2$, taking into account the value(s) of the fine-structure constant(s), which is otherwise neglected in general relativity.

With growing global emphasis on sustainable development and social responsibility, Environmental, Social, and Governance (ESG) ratings have emerged as critical metrics to evaluate commercial banks’ operating performance. The paper utilizes panel data spanning 2009 to 2022 from large state-owned and joint-stock commercial banks in China. It employs a two-way fixed effect model and robustness tests, alongside tests for heterogeneity analysis and moderating effect to conduct empirical analysis. The findings of the fixed effect model indicate that improvements in ESG performance have advantageous impacts on commercial banks’ operating performance, particularly with higher growth rate for operating income Robustness tests including mixed regressions, Tobit tests, variable substitutions, and tests of endogenous bias have validated that initial regression findings still hold. Tests of heterogeneity analysis reveal that among large state-owned commercial banks, banks with higher leverage, larger major shareholder ownership, and larger banks scales, ESG performance can significantly affect the banks’ operating performance, and the relationship exhibits positive. Furthermore, the paper finds that GDP growth rate, CPI and analysts’ coverage can strengthen the relationship between ESG performance and commercial banks’ operating performance through moderating effects. The research provides policy proposals and strategic recommendations tailored for policymakers, banks, and investors, building on these insights.

Nowadays, there is an increasing concern about environmental challenges ranging from emissions to overconsumption. Most of the environmental problems today are direct consequences of human consumption. Understanding the factors that affect consumer purchasing decisions is critical to developing demand for and commitment to sustainable consumption. In this regard, this study aims to explore the environmentally sustainable consumption behavior of Ethiopian consumers by using an extended model of the theory of planned behavior. Data were collected using a self-administered questionnaire having open and closed-ended questions. A total of 523 Ethiopian consumers were selected using convenience sampling technique. Structural equation modeling with AMOS V.26.0. was applied for data analysis. The findings show that Ethiopian consumers have very low awareness about the impact of their clothing consumption and disposal. Their consideration of sustainability attributes during purchasing decisions is also low. The structural equation model analysis showed that all variables had a positive and significant effect on the dependent variables at p<0.05, except the effect of personal norms on an environmentally responsible purchasing intention. These results provide additional evidence on the role of environmental labels in purchasing sustainable apparel products. The results of the study allow a better understanding of the factors determining sustainable consumption behavior and suggest practical solutions to their producers. As theory-building activities, with implications for the conceptualization of sustainable consumption behavior are sparse in the literature, this work has also been able to detect sustainable consumption behavior trends and practices by using the availability of a sustainable apparel product and consumers price perceptions of environmentally responsible apparel as a mediating effect of intention and behavior in developing countries, particularly Ethiopia.

This work presents the results of optimizing the physicochemical properties of composite briquettes based on microsilica for metallurgical-grade silicon production. Microsilica, a waste product of silicon production, contains a sufficiently high amount of silicon dioxide (96-97%). This fact makes microsilica a promising composite material for metallurgical processing. However, its granulometric composition limits its direct use. The method of briquetting on an industrial briquetting press was used. The influence of the granulometric composition of the composite mixture on the heat tolerance and strength of the finished briquettes was studied. The methods of obtaining and testing the briquettes, their composition, and the briquetting and drying process are described. The obtained briquettes were tested for the smelting of metallurgical silicon. The silicon recovery rate in the metal with the standard charge was 71%, while the recovery rate with the briquetted monocharge was 85%. The results of silicon smelting from the briquettes demonstrated the high quality of the obtained metal, corresponding to the standards of metallurgical-grade silicon. The implementation of these technologies not only improves the quality of the final product but also addresses environmental issues related to the disposal of microsilica, reducing its accumulation and minimizing its impact on the environment.

Abstract: This review article provides a comprehensive overview of the anatomical structure of the human brain, highlighting its key components and their functional significance. The brain is the central organ of the nervous system, responsible for controlling and coordinating various bodily functions. The article begins with an introduction to the brain's gross anatomy, including the cerebrum, cerebellum, brainstem, and diencephalon. It then delves into the detailed microstructure of the brain, discussing neurons, glial cells, and the complex network of neural connections. The review also explores the functional organization of the brain, emphasizing the roles of different regions such as the frontal, parietal, temporal, and occipital lobes. It discusses the importance of the limbic system in emotional processing and the basal ganglia in motor control. Additionally, the article covers the brain's vascular system and the blood-brain barrier, which are crucial for maintaining the brain's homeostasis. Recent advancements in neuroimaging techniques, such as magnetic resonance imaging (MRI) and functional MRI (fMRI), have significantly enhanced our understanding of brain anatomy and function. These techniques have enabled researchers to map brain activity in real-time, providing insights into cognitive processes and neurological disorders. The article concludes by discussing the implications of understanding brain anatomy for clinical practice, including the diagnosis and treatment of neurological conditions. It also highlights areas for future research, emphasizing the need for further exploration of the brain's structural and functional complexity.

Well-annotated gene and genomic sequences serve as a foundation for making inferences in molecular biology and evolution, and can directly impact public health. The first SARS-CoV-2 genome was submitted to GenBank and used to develop the two successful vaccines. Conserved protein domains are often chosen as targets for developing antiviral medicines or vaccines. Mutation and substitution patterns provide crucial information not only on functional motifs and genome/protein interactions but also for characterizing phylogenetic relationships among viral strains. These patterns, together with the collection time of viral samples, serve as the basis for addressing the question of when and where the host-switching event occurred. Unfortunately, viral genomic sequences submitted to GenBank undergo little quality control, and critical information in the annotation is frequently changed without being recorded. Researchers often have no choice but to hold blind faith in the accuracy of the sequences. There have been reports of incorrect genome annotation but no report that casts doubt on the genomic sequences themselves because it seems theoretically impossible to identify genomic sequences that may not be authentic. This paper takes an innovative approach to show that some SARS-CoV-2 genomes submitted to GenBank cannot be possibly authentic. Specifically, some SARS-CoV-2 genomic sequences deposited in GenBank with collection time in 2023 and 2024, isolated from saliva, nasopharyngeal, sewage, and stool are identical to the reference genome of SARS-CoV-2 (NC_045512). The probability for such occurrence is effectively 0. I also compile SARS-CoV-2 genomes with changed sample collection time. One may led astray in bioinformatic analysis without being aware of errors in sequences and sequence annotation.

This paper explores the application of machine learning (ML) in predicting functional recovery in patients with ischemic stroke. As technology advances, ML shows significant potential in the field of stroke medicine, especially in the areas of big data analytics and personalized medicine. Studies have shown that ML algorithms can improve the accuracy of stroke image analysis, subtype classification, risk assessment, treatment guidance, and prognosis prediction. However, the widespread use of ML still faces challenges such as data standardization, model validation, privacy, and bias. This paper reviews the current application status of ML in the field of stroke, discusses the challenges faced, and looks forward to the future development direction, aiming to promote the practical application of ML technology in the diagnosis and treatment of stroke to improve the prognosis and quality of life of patients.

The study on the sustainable utilization capacity of water resources is of great significance for the realization of sustainable water resources management and development in the water-scarce regions of Northwest China. It provides insights into the potential for sustainable utilization of these resources. To evaluate the sustainable utilization capacity of the Huangshui Basin, a comprehensive evaluation index system was constructed based on three aspects: climate factors, water resources systems, and socio-economic factors. The evaluation was conducted using two methods: the fuzzy comprehensive evaluation model and the ELECTRE III evaluation method. The results indicate that the Huangshui Basin's water resources, as a whole, exhibit a medium sustainable utilization capacity. Climatic factors and socio-economic characteristics are the main factors affecting the sustainable utilization of water resources in the Huangshui Basin. Based on the results, measures such as strengthening the introduction of external water resources, enhancing water resources management, and implementing comprehensive remediation efforts in the basin can improve the level of sustainable use of water resources. The research results can provide a reference for decision-making regarding the evaluation of sustainable utilization capacity of water resources in water-scarce areas and the optimization of water resources management in the Huangshui Basin.

This research reviews a novel artificial intelligence (AI) based application called ‘TLDetect’, which filters and classifies anomalous glow curves (GCs) of thermoluminescent dosimeters (TLDs). Until recently, GCs review and correction in the lab were performed using an old in-house software, which uses Microsoft Access database and allows the laboratory technician to manually review and correct almost all GCs without any filtering. The newly developed application ‘TLDetect’ uses a modern SQL database and filters out only the necessary GCs for technician review. TLDetect first uses an Artificial Neural Network (ANN) model to filter out all regular GCs. Afterwards, it automatically classifies the rest of the GCs into five different anomaly classes. These five classes are defined by GCs typical patterns, i.e. high noise at either low or high temperature channels, untypical GC width (either wide or narrow), shifted GCs whether to the low or to the high temperatures, spikes, and the last class contains all other unclassified anomalies. By this automatic filtering and classification, the algorithm substantially reduces the amount of technician’s time of reviewing the GCs and makes the external dosimetry laboratory dose assessment process more repeatable, accurate and fast. Moreover, a database of GCs class anomalies distribution over time is saved along with all their relevant statistics, which can later assist with preliminary diagnosis of TLD reader hardware issues.

China has enacted a range of policies to improve its water ecosystem since the middle of the 20th Century. Some of these measures include the creation of Seven River Conservancy Commissions, the development (combination and recombination) of series of ministries and departments to address environmental pollution and degradation, and recently the implementation of the river chief system. To understand if the river chief system can transfer to other political jurisdictions the authors gathered data using key word searches of the Web of Science and Google Scholar, official government sites, media sites and key international organizations. Based on this the authors review the development of the river chief system in the context of broader ecological reforms, place the rise of the river chief in the context of potential lessons for future improvement, and speculate on the possibility that China could transfer the river chief to countries facing similar challenges in their water governance regimes.

With the increasing demand for security surveillance, assisted driving, and remote sensing, target detection networks with rich environmental perception capabilities and high detection accuracy have become a research hotspot. However, detection techniques based on single-modality images face limitations in environmental adaptability, as they are easily affected by lighting conditions, as well as obstacles such as smoke, rain, and vegetation, leading to information loss and failing to meet the required accuracy. To address these issues, we propose a target detection network—IV-YOLO, which integrates features from both visible and infrared images. We built a dual-branch fusion network based on YOLOv8 (You Only Look Once v8) that combines infrared and visible images for target detection. On this foundation, we designed a Bidirectional Pyramid Feature Fusion structure (Bi-Fusion) to fully integrate complementary features from different modalities, reducing detection errors caused by feature redundancy and extracting fine-grained features of small targets through dual-modal fusion. Additionally, we developed the Shuffle-SPP structure, which combines channel and spatial attention mechanisms to enhance focus on deep features and further aggregate upsampling, extracting richer features. To improve the model’s expressive power, we designed a loss function tailored for multi-scale target detection boxes, accelerating the network’s convergence during training. Experimental results show that the proposed IV-YOLO network achieves an average precision (mAP) of 74.6% on the UAV remote sensing dataset, 75.4% on the KAIST pedestrian dataset, and 84.8% on the FLIR dataset. While ensuring detection accuracy, our model significantly reduces computational load, making it well-suited to meet real-time requirements. This architecture is expected to find broad application in fields such as autonomous driving, public safety, and others.

Fungal trunk disease (FTD) poses a significant threat to hazelnut (Corylus avellana L.) production worldwide. In Chile, the fungus Diplodia mutila, from the Botryosphaeriaceae family, has been frequently identified causing this disease in the Maule and Ñuble Regions. However, control measures for D. mutila remain limited. This research aimed to evaluate the effectiveness of chemical and biological fungicides against D. mutila under in vitro, controlled pot experiment, and field conditions. An in vitro screening of 30 fungicides was conducted. The effectiveness was assessed by measuring the length of vascular lesions in hazelnut branches inoculated with D. mutila mycelium disks under controlled and field conditions. Field trials were conducted in a hazelnut orchard in Ñiquén, Ñuble Region, Chile. Results showed that three biological and five chemical fungicides were selected in vitro with &gt; 31% inhibition after 14 days. In pot experiments, all fungicides reduced necrotic lesions on branches by 32 to 61%. In field experiments, the most effective systemic fungicides were fluopyram/tebuconazole, fluxapyroxad/pyraclostrobin, and tebuconazole, while the effectiveness of antagonists Pseudomonas protegens ChC7 and Bacillus subtilis QST713 varied with seasonal temperatures. Effective conventional and biological fungicides against D. mutila could be integrated into disease management programs to protect hazelnut wounds from infections.

The integration of Augmented Reality (AR) into Human-Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI, emphasizing their role in enhancing collaboration, trust, and safety. By aggregating findings from numerous studies, this research highlights key challenges, including the need for improved situational awareness, enhanced safety, and more effective communication between humans and robots. A framework developed from the literature is presented, detailing the critical elements of AR necessary for advancing HRI. The framework outlines effective methods for continuously evaluating AR systems for HRI. This structured approach focuses on enhancing collaboration and safety, with a strong emphasis on integrating best practices from Human-Computer Interaction (HCI) centered around user experience and design.

Objective: To investigate the causal relationships between intestinal microbiome biomarkers and colorectal cancer (CRC) and its subtypes. Method: The meta-analysis method was used to integrate the largest genome-wide association study data from the MiBioGen consortium (n=18,340). Single nucleotide polymorphisms (SNPs) significantly associated with intestinal microbial relative abundance were extracted as instrumental variables (IVs). Based on the Finnish database (R9 version) with 326,322 participants, the two-sample Mendelian randomization (MR) analysis was adopted to explore the causal relationships between intestinal microbes and CRC and its specific subtypes, such as colon cancer and rectal cancer. Result: A total of 3,310 SNPs were screened as IVs. The MR analysis revealed significant associations between various microbial traits and CRC, including its subtypes. Specific microbes, such as Erysipelotrichaceae, exhibited protective effects, while others, like Orato, were demonstrated as risk factors. Notably, specific biomarkers (e.g., Streptococcus thermophilus) for CRC were determined. This study provides new insights and potential targets for the pathogenesis, diagnosis, and treatment of CRC. Conclusion: Significant causal relationships exist between intestinal microbes and CRC and its pathological types. Specific microbes, such as Erysipelotrichaceae, play a protective role, whereas others, like Orato, serve as risk factors. These findings offer new insights into the pathogenesis of CRC and provide a foundation for future prevention and treatment strategies.

There are some limitations in using the Body Condition Score (BCS) for client education to prevent obesity, hyperlipidemia-related diseases, and orthopedic diseases in dogs because it is hard to quantify in detail. In small dogs, patellar luxation is a common orthopedic disease that is related to obesity and hind leg muscle. In this study, we evaluated the thorax/thigh circumference ratio as a prognostic evaluation index, along with the BCS, for assessing patellar dislocation and other hyperlipidemia-related diseases. I analyzed eleven client-owned dogs that visited Bundang New York Animal Hospital, South Korea. According to the results, triglycerides (TGs) showed a negative correlation with thorax/thigh value (R = -0.585, p-value = 0.059) and a strong positive correlation with thigh circumference (R = 0.749, p-value = 0.008). Total cholesterol (TC) showed a strong positive correlation with thigh circumference (R = 0.776, p-value = 0.005), whereas the thorax/thigh value showed a negative correlation with the medial patella luxation (MPL) grade with low significance (R = -0.343, p-value = 0.302). These data indicate that thigh circumference can be an excellent negative indicator for hyperlipidemia and thorax/thigh value shows a low correlation with medial patella luxation, which encompasses other factors including varus and trochlear groove, despite the limitations of this study due to the small sample size.

The arrest of Pavel Durov, the CEO of Telegram, represents a critical moment in the ongoing discourse surrounding free speech and content moderation. This event exemplifies the tension between upholding individual liberties and addressing the potential societal harms caused by unregulated digital communication. This paper explores the implications of Durov’s arrest and Telegram’s stance on free speech through the lens of John Stuart Mill’s Harm Principle. The Harm Principle, as articulated in Mill’s seminal work On Liberty (1859), provides a valuable theoretical framework for examining the balance between individual freedom and societal protection. This paper argues that the application of the Harm Principle can offer a nuanced perspective on the ethical responsibilities of digital platforms like Telegram in the age of global communication.

White oak mortality is a significant concern in forest ecosystems due to its impact on biodiversity and ecosystem functions. Understanding the factors influencing white oak mortality is crucial for effective forest management and conservation efforts. In this study, we aimed to investigate the spatial pattern of white oak mortality rates at different locations of the eastern US and explore the underlying processes involved with the spatial distribution patterns. Multicycle Forest Inventory and Analysis data were compiled to capture white oak plots across the eastern US. White oak mortality data were collected across plot systems that utilized Diameter at Breast Height between two periods. Ripley’s K function was used to study the spatial pattern of white oak mortality rate. Results found clustered patterns at both local and broad scales and random patterns at broad scales only across the southern and northern regions. However, the central region indicated both clustered and random patterns at local scale only. We found uniform patterns at a broad scale across all regions. Our findings demonstrated the importance of the spatial pattern of the white oak mortality rate and the underlying factors associated with it. This research can inform forest management practices for the conservation of white oak populations at varying scales. Future research is needed for a comprehensive assessment of biotic and abiotic factors for forest management strategies at various spatial scales aimed at mitigating white oak mortality.

Alkaline and alkaline-thermal activation were used in an attempt to synthesize zeolites using the sedimented illite fraction of raw Devonian clays from the Kuprava clay pit in Latvia. The Si/Al molar ratio of these clays is 2.79. Thermal and hydrothermal treatments were conducted using 6M and 10M NaOH solutions, along with different curing environments. The treated samples were analyzed using XRD, FTIR, and SEM, and were compared to the raw and calcined illite fraction samples. The main phase that forms after alkaline treatment is hydrosodalite (Na8[AlSiO₄]₆(OH)₂∙2H₂O). Using a higher concentration of NaOH leads to a significant increase in hydrosodalite formation. Increasing the curing temperature from 120°C to 600°C slightly reduces hydrosodalite formation due to the crystallization of the nepheline (Na₃K(Al₄Si₄O₁₆)) phase. This phase forms relatively intensively when the chemically treated samples are cured in a nitrogen environment at 600°C, thereby reducing the formation of hydrosodalite. The characteristic layered-fused structure of clay minerals remains in all chemically treated samples when cured at 600°C in air, but it does not remain when cured at the same temperature in nitrogen. The intensive formation of hydrosodalite is mainly achieved through hydrothermal treatment, along with a primary treatment using 10M NaOH. Considering the calculated size of the crystallites, treatment with 6M NaOH and curing at 120°C can also be seen as beneficial for hydrosodalite formation.

Glutamate transporter-1 (GLT-1) dynamics are implicated in excitotoxicity and Alzheimer's disease (AD) progression. Early stages of AD are often marked by hyperactivity and increased epileptiform activity preceding cognitive decline. Previously, we identified a direct interaction between GLT-1 and Presenilin 1 (PS1) in the brain, highlighting GLT-1 as a promising target in AD research. This study reports the significance of this interaction and uncovers a novel role of GLT-1 in modulating amyloid-beta (Aβ) production. Overexpression of GLT-1 in cells reduces the levels of Aβ40 and Aβ42 by decreasing γ-secretase activity pertinent to APP processing and induces a more "open" PS1 conformation, resulting in decreased Aβ42/40 ratio. Inhibition of the GLT-1/PS1 interaction using cell-permeable peptides produced an opposing effect on Aβ, highlighting the pivotal role of this interaction in regulating Aβ levels. These findings emphasize the potential of targeting GLT-1/PS1 interaction as a novel therapeutic strategy for AD.

In order to solve the problem of structure damage location and degree identification, the weighted mean of vectors algorithm (INFO), a high-performance optimization one, was first introduced to identify structure damage. The genetic algorithm (GA) are improved to obtain a refined genetic algorithm (RGA). An objective function is constructed by combining the dynamic response transfer-ratio without modal analysis. INFO and RGA algorithms are used to optimize the objective function for damage identification. Though simulations, the INFO, RGA, GA algorithms were used to identify the damage on a simply supported beam and cantilevered plate with different levels of noise and different frequency spacing of pickup points. The simulations verify the effectiveness of the three damage identification methods, and the INFO algorithm has the highest damage identification accuracy, the RGA is second and the GA is the worst.

Background: The Second Victim Phenomenon (SVP) significantly impacts the well-being of healthcare professionals and patient safety. While SVP has been explored in various healthcare settings, there is limited data on its prevalence and associated factors among nurses in Austria. This study investigates the prevalence, symptomatology, and preferred support measures for SVP among Austrian nurses. Methods: A nationwide, cross-sectional, anonymous online survey was conducted using the SeViD questionnaire (Second Victims in German-speaking Countries), which includes the Big Five Inventory-10 (BFI-10). Statistical analyses included binary logistic regression and multiple linear regression using the bootstrapping, bias-corrected and accelerated (BCa) method based on 5000 bootstrap samples. Results: 928 participants responded to the questionnaire. Among the respondents, 81.58% (744/912) identified as Second Victims (SVs). The primary cause of becoming a SV was aggressive behavior from patients or relatives. Females reported a higher symptom load than males, and higher agreeableness was linked to increased symptom severity. Notably, 92.47% of SVs who sought help preferred support from colleagues, and the most pronounced desire among participants was to process the event for better understanding. Conclusions: The prevalence of SVP among Austrian nurses is alarmingly high, with aggressive behavior identified as a significant trigger. The findings emphasize the necessity for tailored support strategies, including peer support and systematic organizational interventions to mitigate the impact of SVP on nurses and to improve overall patient care. Further research should focus on developing and implementing effective prevention and intervention programs for healthcare professionals in similar settings.

The Keeling Curve shows that in addition to the progressive increase in the amount of CO₂ in the atmosphere, the rate of increase in the rate of uptake of CO₂ into the atmosphere, both in ppm and gigatons C/year, has been progressively increasing from 1960 to the present, despite some leveling off of man-made emissions. There is a similar processive increase in the earth’s heat imbalance. I propose that this is due to the additive effect of multiple partially activated tipping points putting the earth into a positive feedback mode such that these increases in rate will continue even after net zero emissions from fossil fuels is attained. As a result, controlling global warming will require a marked acceleration of Carbon Dioxide Removal using multiple Negative Emission Technologies.

An efficient cooling system is necessary for the reliability and safety of the modern microchips for longer life. As microchips become smaller and more powerful, the heat flux generated by these chips per unit area also rises sharply. Traditional cooling techniques are inadequate to meet the recent cooling requirements of microchips. To meet the current cooling demand of Microelectromechanical devices (MEMS) devices and microchips, microchannel heat sinks (MCHS) technology is the latest invention that can dissipate a significant amount of heat because of its high surface area to volume ratio. This study provides a concise summary of design, material selection, and performance parameters of MCHS that are developed over the last few decades. The limitations and challenges associated with different techniques employed by researchers over time to enhance the thermal efficiency of microchannel heat sinks are discussed. The effects on the thermal enhancement factor, Nusselt number, and pressure drop at different Reynold numbers, in passive techniques (flow obstruction) i.e. ribs, grooves, dimples, and cavities change in curvature of MCHS are discussed. This study also discusses the increase in heat transfer using nanofluids and how change in coolant type also significantly affects the thermal performance of MCHS by obstructing flow. This study provides trends and useful guidelines for researchers to design more effective MCHS to keep up with the cooling demands of power electronics.

Mycotoxin contamination of food and feed is a worldwide problem that needed to be addressed with highly efficient and biologically safe techniques. RNA interference (RNAi) is a natural mechanism playing an important role in different processes in eukaryotes, including regulation of gene expression, maintenance of genome stability, protection against viruses and others. Recently, RNAi-based techniques have been widely applied for the purposes of food safety and management of plant diseases, including those caused by mycotoxin-producing fungi. In this review, we summarize the current state-of-art of RNAi-based approaches for reducing aggressiveness of key toxigenic fungal pathogens and mycotoxin contamination of grain and its products. The ways of improving RNAi efficiency for plant protection and future perspectives of this technique, including progress in methods of double-stranded RNA production and its delivery to the target cells are also discussed.

The European Parliament had adopted legislative resolution of 10 April 2024 on the proposal for a directive of the European Parliament and of the Council concerning urban wastewater treatment. The reduction of pollution in discharged treated wastewater in the parameters of BOD5, total ni-trogen and total phosphorus was emphasized. Based on these results, it stated that the impacts on the quality of lakes, rivers and seas in the EU are visible and tangible. At the same time, it was emphasized that the sector of urban wastewater removal and treatment is responsible for 0.8% of the total electricity consumption and about 0.86% of all greenhouse gas emissions in the entire EU. Almost a third of these emissions could be prevented by improving the treatment process, better use of sewage sludge and increasing energy efficiency, as well as a higher rate of use of renewable resource technologies. It is also necessary to better integrate treatment processes into the circular economy. Sludge management and water reuse is sub-optimal as too many valuable resources are still being wasted. This review article is focused on sustainable municipal wastewater treatment, innovative and new wastewater treatment processes and technologies (combined and hybrid processes, Anammox, etc. and their use in practice with the aim of increasing environmental and energy efficiency and reducing the carbon footprint. The research is focused on the possibilities of increasing the efficiency of energy processing of sludge, reuse of nitrogen and phosphorus, sludge and reuse of treated wastewater.

Background: Ventilatory strategies in acute respiratory distress syndrome patients aim to mitigate the risk of acute lung injury (ALI). However, prolonged utilization of these strategies may precipitate alveolar carbon dioxide elevation and pH reduction. This scoping review endeavors to present extant knowledge concerning hypercapnia effects in experimental models, with or without ALI, specifically focusing on delineating the immunologically mediated pulmonary tissue damage; Methods: A systematic exploration encompassing PubMed, Web of Science, ScienceDirect, Cochrane Reviews, and Scielo databases was undertaken. Articles published between January 1, 2008, and December 31, 2022, were screened for their elucidation of hypercapnia's immunological impact on lung tissue, utilizing experimental or biological models, irrespective of ALI presence; Results: Following duplicate removal and predefined criteria filtering, 30 pertinent articles scrutinizing hypercapnia's influence on pulmonary epithelium were identified. It was observed that hypercapnia induces perturbations in innate immune response gene transcription, mediated via Nuclear Factor-kappa B attenuation. Furthermore, a compromised innate immune response against injurious agents was noted. Concurrently, disruption and subsequent resealing of alveolar epithelial cells were evidenced, primarily through Na/K-ATPase endocytosis, impeding fluid reabsorption at the alveolar epithelium level; Conclusions: In experimental settings, with or without ALI, hypercapnia's immunomediated mechanisms exacerbate innate immune system impairment and disrupt the respiratory epithelium's repair and healing processes.

Chronic Obstructive Pulmonary Disease (COPD) is a disease characterized by local and systemic inflammation independently of the risk factor; during the exacerbations, such inflammation is accentuated and amplified. A practical inflammatory marker and one with an applicable predictive value in the follow-up has been sought. FeNO has shown an excellent performance in that respect within the context of asthma and has also been studied in tobacco-smoke COPD (COPD-TS). In Biomass-smoke COPD (COPD-BS), this, to our knowledge, has not been evaluated. Objective: To measure FeNO levels in patients with COPD-BS and to compare these with those of patients with stable COPD-TS and in healthy controls. Methods: Transversal, observational, descriptive, comparative, and analytical study. A total of 57 patients, including 23 with COPD-BS, 17 with COPD-TS, and 17 healthy control subjects. The measurement of FeNO was carried out on all of these by means of the on-line chemiluminescence technique; the values were expressed in parts per billion (ppb) for their analysis. Results: It was observed that the FeNO values were similar between COPD-BS and COPD-TS and were significantly different between the healthy and stable COPD (both groups). No correlation was found between pulmonary function and symptoms with FeNO in any of the groups. Conclusions: The level of FeNO in stable COPD is found to be increased in a similar manner in COPD-BS and COPD-TS, with a significant difference on comparing it with that of the healthy subjects.

Farmers today are using biochemical treatments to improve their crop yields. Commercialized organic biostimulants exist in the form of pyroligneous acid generated by burning agricultural waste products. During the 2023 growing season we demonstrated that soil treatment with a commercial pyroligneous acid product, Coriphol™, manufactured by Corigin Solutions, Inc., stimulated plant growth and significantly improved yield with an optimal treatment dose of 2 gal./acre. In the present work we examined the effect of this treatment on soybean nutritional content using seed harvested from the 2023 season. Total mean seed protein content for untreated control plants was 32.26 ± 0.49% of dry mass and increased 10.8% to 35.64 ± 0.64% with treatment. This increase resulted in a net reduction in total free amino acid content although levels of the es-sential dietary amino acid, lysine, were boosted 6-fold. Total lipid content was unaffected by treatment with mean levels of 21.61 ± 0.70% of dry mass noted. Treatment, however, reduced saturated fatty acid content by roughly 40% while reducing the polyunsaturated content of linoleic acid in favor of the monounsaturated fatty acid, oleic acid. Finally, Coriphol™ treatment did not impact seed content of eight essential micronutrients including Na, Mg, K, Ca, Fe, Ni, Cu and Mo, but did significantly boost Zn and Mn levels. Altogether, these results demonstrate that soil treat-ment with the growth stimulant Coriphol™ has the potential to improve the dietary nutritional value of soybean.

This paper presents proof of Riemann's hypothesis by utilizing the golden ratio and the ellipse's eccentricity in six dimensions. This proof extends across all scientific fields. this research introduces logical and mathematical principles for distributing, recognizing, and categorizing prime numbers. It also explores the relationship between prime numbers and the complex conjugate of five prime numbers in various dimensions. Accordingly, it delves into the classification of even numbers based on prime numbers. This study examines the proof of Riemann's hypothesis from a geometric dimension perspective. Based on this, the mathematical structure of an integrated theory is defined. properties and principles associated with prime numbers reveal connections between quantum mechanics and general relativity.

The construction of tall buildings generates a high spatial and temporal concentration of greenhouse gas (GHG) emissions. Research studies have shown that as building height increases, more resources per floor area are required to withstand the increasing effects of lateral loads (wind and earthquake). This has major implications for the environmental performance of tall buildings since the Embodied GHG Emissions (EGHGE) of structural systems tend to represent the greatest portion of the life cycle GHG emissions of tall buildings. This study presents a data driven-based approach for decarbonization of tall buildings and evaluates the significant impact of material types (concrete, steel, and timber), concrete strength, and structural systems relative to a building's height on the EGHGE associated with tall buildings. In mitigating the effects of climate change, this research implements machine learning (ML) algorithms as an early-stage design tool to facilitate the choice of materials, and structural systems for tall buildings. This work considers a wide range of high-rise buildings with four different types of lateral structural systems (Braced-Frame system, Outrigger-Belt system, Shear Wall system, and Tubular system), four different types of construction materials (concrete, steel, hybrid, and timber), varying heights (ranging from 10 to 100 stories), and various concrete materials with different compressive strength ranging from 32 to 90 MPa. Data gathered from more than 100 existing tall building projects along with the data obtained from finite element analysis of 120 high-rise buildings models were utilized to train various ML regression algorithms: Decision Tree, Support Vector Machine, Polynomial Regression, and Elastic-Net Regularized Regression. The performance of ML models was carefully assessed, and the best prediction model was selected to estimate the total amount of CO2 emissions for high-rise buildings. Results indicate that hybrid structures with the Out-Rigger-Belt system exhibit the lowest carbon emission (110 kg/m2) compared to other structural types and systems.

Canada is known to have a complex pathway for new drug approval and reimbursement resulting in delayed access to patients with serious and life-threatening diseases such as cancer. Several recent publications from key stakeholders including patients, physicians and policymakers highlight patient helplessness, physician frustrations and policymakers entangled in a massive network of bureaucracy unable to make headway. Several quantitative assessments using time from regulatory approvals to successful reimbursements confirm long review times and high rejection rates for oncology drugs especially those receiving conditional approvals. A consensus forum of 18 Canadian oncology clinicians recently voiced frustration with the process and inability to deliver guideline-supported efficacious therapies to their patients. This manuscript compares data extracted from publicly available data sources from 2019 to June 2024 to previous publications. Methods: Public databases from Health Canada, the Canadian Agency for Drugs and Technologies in Health (CADTH), which is in the process of changing to Canada’s Drug Agency, and the pan-Canadian Pharmaceutical Alliance (pCPA) were reviewed and data collected were analyzed with descriptive statistics. Results: From the data, three trends emerge, i) an increasing number of oncology drugs are receiving conditional approvals from Health Canada, ii) the percentage of conditionally approved oncology drugs receiving positive reimbursement recommendations from CADTH is still low but appears to be improving, but delays in access are now contingent upon pCPA deciding whether to negotiate price and then the duration of any negotiation, and iii) real-world evidence is no longer part of decision-making for conditional approvals. A slight increase in positive endorsement of RWE used to support CADTH recommendations was observed. Conclusion: Lack of timely access to oncology drugs hurts Canadian patients. While a small trend of improvement appears to be emerging, longer-term data collection is required to ensure sustained patient benefits.

The lack of dense random-access memory is one of the main obstacles to the development of digital superconducting computers. It has been suggested that AVRAM cells, based on the storage of a single Abrikosov vortex — the smallest quantized object in superconductors — can enable drastic miniaturization to the nanometer scale. In this work, we present numerical modeling of such cells using time-dependent Ginzburg-Landau equations. The cell represents a fluxonic quantum dot containing a small superconducting island, an asymmetric notch for vortex entrance, a guiding track, and a vortex trap. We determine the optimal geometrical parameters for operation at zero magnetic field and the conditions for controllable vortex manipulation by short current pulses. We report ultra-fast vortex motion with velocities more than an order of magnitude faster than those expected for macroscopic superconductors. This phenomenon is attributed to strong interactions with the edges of a mesoscopic island, combined with the nonlinear reduction of flux-flow viscosity due to nonequilibrium effects in the track. Our results show that such cells can be scaled down to sizes comparable to the London penetration depth, ∼100 nm, and can enable ultrafast switching on the picosecond scale with ultra-low energy per operation, ∼10−19 J.

Introduction: The balance of bioelements is crucial as it ensures the organism's homeostasis and proper execution of reactions within the body, nerve conductivity, and correct polarity of cell membranes, but it is also very important for fertility. It is known that disturbances in the balance of bioelements lead to reproductive dysfunction. In women, changes in the composition of follicular fluid can occur, which can lead to limited follicular growth and lack of oocyte activation. Objective: The main objective was to examine whether the concentration of bioelements Na, K, Ca, Mg, and Fe in follicular fluid influences the outcome of the in vitro fertilization process. Methods: The study involved 120 female patients undergoing in vitro fertilization. Follicular fluid obtained after follicle aspiration in the ovaries was used as biological material for analysis. The values of Na (selective electrode method), K (selective electrode method), Ca (arenajo method), Mg (spectrophotometric method), and Fe (colorimetric method) in follicular fluid were determined using the AU 680 apparatus, Beckman Coulter. Istanbul Consensus criteria for clinical embryologists were used to assess embryo quality. Statistical analysis was performed using the SPSS 20 software package. Results: Analysis of follicular fluid samples showed no correlation between the concentration of bioelements in follicular fluid and the quality of oocytes or the outcome of in vitro fertilization. Conclusion: Based on our results, it can be concluded that the concentration of bioelements in follicular fluid does not affect the outcome of in vitro fertilization.

Tianjin is currently in the phase of urban stock renewal, yet its industrial heritage encounters significant challenges, including constrained spatial development, a misalignment between industrial progress and the reuse of industrial heritage, and an understated cultural representation. This study applies geospatial analysis to delineate the distribution characteristics of Tianjin's industrial heritage across time, space, and typology. Moreover, the geographic detector is employed to assess the impact of various factors on the development of Tianjin's industrial heritage, ultimately elucidating the correlations between existing challenges and objective patterns. The conclusion of this paper presents three strategic approaches for the renewal of industrial heritage, emphasizing historical culture, environmental space, and sustainable development. These strategies are designed to provide a solid research foundation for protecting and revitalizing Tianjin's industrial heritage resources.

Type 2 Diabetes mellitus (T2DM) and cancer share common risk factors including obesity, in-flammation, hyperglycemia, and hyperinsulinemia. High insulin levels activate PI3K/Akt/mTOR signaling pathway promoting cancer cell growth, survival, proliferation, metastasis, and an-ti-apoptosis. The inhibition of PI3K/Akt/mTOR signaling pathway for cancer remains a promising therapy, however, the combination of therapeutic inhibitors may solve the resistance to such agents. Understanding the metabolic link between diabetes and cancer can assist in improving the therapeutic strategies used for the management of cancer patients with diabetes and vice versa. This review provides an overview of shared molecular mechanisms between diabetes and cancer as well as discusses established and emerging therapeutic anti-cancer agents targeting the PI3K/Akt/mTOR pathway in cancer management.

Nutritional interventions facilitating the consumption of available, affordable, and environment-compatible health-promoting functional foods (FF) are a promising strategy for controlling non-communicable diseases (NCDs) responsible for decreasing health expectancy. Given that the complex of tomato micronutrients produces healthier outcomes than lycopene, its major antioxidant component, we have devised a new controlled berry processing to improve its health-supporting properties. The newly generated whole tomato food supplement (WTFS), enriched by 2% olive wastewater polyphenols, contains a complex of healthy nutrients with converging biologic activities superior to those provided by tomato commodities. WTFS equals the antioxidant activity of N-acetyl-cysteine and interferes with multiple inflammation-eliciting and sustaining metabolic pathways. WTFS inhibits prostate experimental tumors, and improves benign prostate hypertrophy-associated symptoms. No side effects have been so far reported for dietary supplementation with WTFS compared to the culinary use of tomatoes. Although WTFS may be susceptible to further improvements and clinical scrutiny, its composition embodies the features of an advanced FF to ease adherence to dietary regimens, i.e. the Mediterranean diet, aimed at contrasting the low-grade inflammation. Ongoing investigations suggest new areas of potential translational use of WTFS, as a basis for developing more targeted FF interceptive or preventive of NCDs.

Agrivoltaic agrotunnels are currently designed for high density grow walls that are not amenable to bush berries or root crops. Commercial grow bins provide deeper substrates for produce with more root systems but have high costs per unit growing area. To overcome the economic limitations of grow bins, this study applies the distributed manufacturing open-source design paradigm to develop four designs for low-cost open source structures. The designs target root vegetables and bush fruit specifically to be adopted by remote communities with limited or no outdoor growing environment to offset the market price for imported fresh produce. The indoor growing designs provide the necessary structure for supporting grow light and grow bins and enabled the transplanted berry plants to flower and produced fruits. They provide a comparable amount (110L) or more of grow volume from 106 to 192 L. The water reservoir volume for the commercial system (62 L) and grow area (0.5 m³) is surpassed by all new designs that range from 64 to 192 L and 0.51 to 0.76 m³, respectively. These superior properties are possible with material costs for all four designs that save more than 90% of the economic cost of the commercial systems.

Alzheimer’s is a degenerative brain condition brought on by intricate brain changes after cell injury. The prevalence of Alzheimer’s disease is highest in those over 65. Presently, AD is detected by manual examination of a patient’s Magnetic Resonance Imaging (MRI) scan and neuropsychological assessments. Due to its subpar accuracy and performance, solutions based on artificial intelligence (AI) have not been made more widely available. This paper proposes a deep Convolutional Neural Network (CNN) with the pre-trained MobileNet-V2 architecture as the model’s base for feature extraction and reducing the parameter size and training time. The proposed model accurately classifies various early stages of AD. The proposed approach visualizes the class activation maps in the form of a heat map on brain MRI scans via the Grad-CAM algorithm that lifts the black-box nature of the deep model. To handle the imbalance problem of the AD data set acquired from Kaggle, the oversampling algorithm SMOTE interpolates new images to even the class samples. The proposed multi-class classification deep model is named Bio-AD and evaluated using different quality metrics. The Bio-AD model has the following values for evaluation metrics: 97.92%, 99.87%, 97.87%, 98%, 98%, and 0.0646 for accuracy, Area Under the Curve (AUC), F1-score, Precision, Recall, and loss respectively. The proposed Bio-AD model is compared with DenseNet-169, VGG-19, and InceptionResNet-V2 using different quality metrics and outperformed in comparison with all other models using the AD data set.

The contemporary treatment for metastatic castration-sensitive prostate cancer (mCSPC) has evolved significantly, building on successes in managing metastatic castration-resistant prostate cancer (mCRPC). Although androgen deprivation therapy (ADT) alone has long been the cornerstone of mCSPC treatment, combination therapies have emerged as the new standard of care based on recent advances, offering improved survival outcomes. Landmark phase 3 trials demonstrated that adding chemotherapy (docetaxel) and androgen receptor pathway inhibitors to ADT significantly enhances overall survival, particularly for patients with high-volume, high-risk, or de novo metastatic disease. Despite these advancements, a concerning gap between evidence-based guidelines and real-world practice remains, with many patients not receiving recommended combination therapies. The challenge in optimizing therapy sequences, considering both disease control and treatment burdens, and identifying clinical and biological subgroups that could benefit from personalized treatment strategies remains. The advent of triplet therapy has shown promise in extending survival, but the uro-oncology community must narrow the gap between evidence and practice to deliver the most effective care. Current research is focused on refining treatment approaches and utilizing biomarkers to guide therapy selection, aiming to offer more personalized and adaptive strategies for mCSPC management. Thus, aligning clinical practices with the evolving evidence is urgently needed to improve outcomes for patients facing this incurable disease.

About 14% of adolescents experience mental illnesses globally. The rate increased after the COVID-19 pandemic. This study aimed to estimate the prevalence of COVID-related major mental illnesses (depression and anxiety) and their predictors among adolescents. This community-based cross-sectional study was conducted among 350 adolescents aged 10-19 years, recruited from rural communities in West Bengal, India. The study areas included 27 subcenters in the Budge Budge II Block, which comprised 1,91,709 population and 45,333 households. Data were collected from randomly selected households by trained research assistants through house-to-house interviews. Pretested standardized questionnaires, Patient Health Questionnaire (PHQ) for depression, Generalized Anxiety Disorder (GAD) for anxiety, and a demographic questionnaire were used for data collection. The prevalence of anxiety was 35.7% (125 out of 350), and the prevalence of depression was 30.0% (105 out of 350). Females had significantly higher scores of anxiety (6.67 ± 4.76 vs. 3.42 ± 3.17, respectively, p &lt;0.001) and depression (5.51 ± 4.99 vs. 3.26 ± 3.86, respectively, p &lt;0.001) compared to males. Adolescents who had COVID-19 cases or deaths in the family had significaly higher scores of anxiety and depression compared to those who didn’t have these events. In multivariate analysis, the statistically significant predictors of anxiety were COVID-19 death in the family, COVID-19 cases in the family, female gender, and a lower income group (p &lt;0.001 for all). For depression, the significant predictors included COVID-19 death in the family, COVID-19 cases in the family, female gender, a lower income group, and a higher age group in adolescents (p &lt;0.001 for all). Based on the study results, we recommend that immediate attention is needed for adolescents’ mental health support and coping with stresses following COVID-19.

Hydrogen mobility embodies a promising solution to address the challenges posed by traditional fossil-fuel-based vehicles. The use of hydrogen in small heavy duty road vehicles based on internal combustion engines (ICEs) may be appealing for two fundamental reasons: direct electrification seems less promising in heavy duty transport systems and fuel cell-based hydrogen vehicles implementation may not proceed at the expected pace due to higher investment costs compared to ICEs. On the other hand, hydrogen combustion is gaining attractiveness and relies on robust and cheap technologies, but it is not the only renewable solution. In this framework, this work presents a methodology to assess Weel-to-Whell primary energy consumption and CO2 emissions of small heavy-duty vehicles. The methodology is applied in a real case-study, namely a passenger coach travelling on a 100 km-mission in non-optimized conditions. Therefore, the suitability of hydrogen is compared with standard diesel and other alternative diesel-type fuels (biodiesel and synthetic diesel types). Hydrogen shows competitivity with standard diesel from the point of view of CO2 emission reduction (-29%) while it hides a higher primary energy consumption (+40%). Nonetheless, HVO brings the highest benefits both from the point of view of primary energy consumption and emission reduction, namely -35% and 464-634 kgCO2/100km avoided compared to hydrogen.

The Kraaipan and Amalia greenstone belts in South Africa occurs in the western part of the Kaapvaal Craton. The two belts stretch discontinuously in an approximately north-south orientation over a distance of about 250 km from southern Botswana in the north to the Vaal River near Christiana in the south and are separated by a distance of about 90 km. Gold mineralization is hosted in banded iron-formation at both the Kalahari Goldridge deposit (Kalgold) in the Kraaipan greenstone belt in the north, and the Amalia deposit in the Amalia greenstone belt in the south, with the mineralization associated with quartz-carbonate veins. The footwall of these deposits is generally composed of mafic volcanic schist and hanging wall consisting of graywackes, schist and shale units. The Kalgold and Amalia gold deposits show some variation in the redox condition of the mineralizing system, mineralization temperatures and fluid chemistry. The ore mineral assemblage is characterized by magnetite-pyrrhotite-pyrite at Kalgold, which is indicative of reducing conditions, and magnetite-hematite-pyrite assemblage at Amalia that suggest a relatively oxidizing environment. Average mineralizing temperatures determined from chlorite geothermometry were relatively higher at the Kalahari Goldridge deposit ranging from 350 to 400oC compared to 335 to 370oC (mean, 352± 18, n = 113) at Amalia. The composition of the fluids derived from fluid inclusions are indicative of low salinity H2O-CH4-CO2-rich fluids at Kalgold against relatively H2O-CO2-rich fluids at Amalia. Evidence from strontium-carbon-oxygen isotopic ratios from carbonates suggests differences in redox conditions in the deposits could be attributed to different flow pathways by the evolving fluid from a common source (with minimum 87Sr/86Sr=0.70354) to the sites of gold deposition; with significant ore fluid interaction with thick sequence of carbonaceous meta-pelitic rock units at the Kalahari Goldridge deposit, that is absent in the Amalia deposit.

The aim of the study was to investigate the effects of Botox injection therapy, with or without wearing thermoformed occlusal splints, in patients with sleep apnea and nocturnal bruxism and to determine their degree of satisfaction after completing the therapy. The selected patients (n = 36, 24 female and 12 male) with sleep apnea and nocturnal bruxism were divided into two groups. The first group of 18 patients (G1) was treated by injecting Botox (Allergan) into the masseter muscle. The 18 patients in the second group (G2) benefited from associated therapy represented by Botox injections in masseter muscle and the wear of thermoformed occlusal splints. Four monitoring sessions were realized: at baseline, at three weeks, at three months, and at six months after the effectuation of treatments. The associated therapy (Botox and thermoformed occlusal splints) presented much better results over time in decreasing the sleep apnea and nocturnal bruxism symptoms than the one represented only by injections with Botox, but Botox injections presented a rapid relief of both disease signs. Patient satisfaction after the applied treatments was very good, but in patients with associated therapy, it was better after six months than in first-group patients.

We study Hadamard's variational formula for simple eigenvalues under dynamical and conformal deformations. Particularly, harmonic convexity of the first eigenvalue of the Laplacian under the mixed boundary condition is established for two-dimensional domain, which implies several new inequalities.

The mechanism of the mechanically assisted mineral carbonation of commercial olivine under flow of CO2/N2 mixture has been elucidated by ex situ powder X-ray diffraction and Fourier-transform infrared spectroscopy. The overall CO2 conversion depends to the rotation frequency of the mill’s engine, and reached 85% within 90 minutes of mechanical treatment, at a flow rate of 2.5 l min-1. By tuning the frequency rotation, the kinetics of CO2 conversion changed from a sigmoid behaviour into a more complex reaction pathway, involving subsequent steps. The structural analyses suggest the clinochlore, a Mg- and Fe- containing aluminosilicate gathered among the components of olivine, is formed and consumed in different stages, thus promoting the CO2 sequestration that eventually results into the formation of hydrated and anhydrous Mg-based carbonates.

Objective: SARS-CoV-2 remains the third most common cause of death in North America. We studied methotrexate and tumor necrosis factor inhibitor (TNFi) effects on neutralization responses post-COVID vaccination, in immune-mediated inflammatory disease(IMID). Methods: Prospective data and sera on adults with inflammatory bowel disease (IBD), rheumatoid arthritis (RA), spondyloarthritis (SpA), psoriatic arthritis (PsA) and systemic lupus (SLE) were collected at 6 academic centres in Alberta, Manitoba, Ontario, and Quebec between 2022-2023. Sera from two time points were evaluated for each subject. Neutralization studies were divided between 5 laboratories, and each lab’s results analyzed separately using multivariate generalized logit models (ordinal outcomes: absent, low, medium, and high neutralization). Odds ratios (ORs) for methotrexate and TNFi effects were adjusted for demographics, IMID, other biologics and immunosuppressives, prednisone, COVID vaccinations (number/type), and infections in the 6 months prior to sample. Adjusted ORs for methotrexate and TNFi were then pooled in random-effects meta-analyses (separately for ancestral, and Omicron BA1 and BA5 strains). Results: Of 479 individuals (958 samples), 292 (61%) were IBD, 141 (29.4%) RA, and the remainder PsA, SpA and SLE. Mean age was 57 (62.2 % female). For both individual labs and the meta-analyses, adjusted ORs suggested independent negative effects of TNFi and methotrexate on neutralization. The meta-analysis adjusted ORs for TNFi were 0.56 (95% confidence interval, CI 0.39, 0.81) for the ancestral strain and 0.56 (95% CI 0.39, 0.81) for BA5. The meta-analysis adjusted OR for methotrexate was 0.39 (95% CI 0.19, 0.76) for BA1. Conclusions: SARS-CoV-2 neutralization in vaccinated IMID was diminished independently by TNFi and methotrexate. As SARS-CoV-2 circulation continues, ongoing vigilance regarding optimized vaccination is required.

Essential oils oregano (Origanum vulgare), rosemary (Salvia rosmarinus), clove (Syzygium aromaticum), thyme (Thymus), cinnamon (Cinnamomum verum), basil (Ocimum basilicum), have antifungal properties. This study evaluated its ability to inhibit growth of isolated fungi and purified obtained from the rot of the banana peel, for the purpose of combating or inhibiting fungal growth in bananas (Musa paradisiaca). The methodology consists in preparing the dilutions to inoculate on PDA medium (Potato Dextrose Agar) amended with chloramphenicol to re-inoculate until obtaining the isolated and purified fungi of Trichoderma spp., Aspergillus spp., Penicillium spp. and Fusarium spp., which are characterized macroscopically and microscopically, subsequently, the growth is analyzed in vivo and the inhibition percentage in vitro. The results of the analysis in vivo report that the fungi in order of severity from greatest to least, was Penicillium spp., Trichoderma spp, Fusarium spp. y Aspergillus spp., while that the analysis in vivo reports that the rosemary and the basil does not inhibit fungal growth, while that the clove inhibit a 800 ppm, the cinnamon to 400 ppm and the oregano to 200 ppm to the four fungi. -2077601433541Citation: To be added by editorial staff during production. Academic Editor: Firstname Lastname Received: date Revised: date Accepted: date Published: date Copyright: © 2024 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).00Citation: To be added by editorial staff during production. Academic Editor: Firstname Lastname Received: date Revised: date Accepted: date Published: date Copyright: © 2024 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Recent research has drawn attention to the ambiguity surrounding the definition and learnability of Out Of Distribution (OOD) recognition. The term "Out of Model Scope" (OMS) detection provides a clearer perspective, although the original problem remains unsolved. The ability to detect OMS inputs is particularly beneficial in safety-critical applications such as autonomous driving or medicine. By detecting OMS situations, we not only enhance the system's robustness but also prevent it from operating in unknown and unsafe scenarios. In this paper, we introduce a novel approach for OMS detection that combines three sources of information: 1) the original input, 2) the latent feature space extracted by an encoder, and 3) the synthetic data generated from the encoder's latent feature space. We demonstrate the effectiveness of combining original images and synthetically generated images against adversary attacks in the computer vision domain. We achieve results comparable to other state-of-the-art methods and demonstrate that any Encoder can be integrated into our pipeline in a plug-and-train fashion. Our experiments further evaluate which combination of the Encoder's features works best in order to discover OMS samples and highlight the importance of a compact feature space for the training of the Generator.

This paper explores the properties of projective vector fields on semi-Riemannian manifolds. The main result establishes that if a projective vector field η on such a manifold is also a conformal vector field with potential function ψ, then η must either be homothetic, or the vector field ζ, which is dual to dψ, is a light-like vector field. Additionally, it is shown that a complete Riemannian manifold admits a projective vector field that is also conformal and non-Killing if and only if it is locally Euclidean. The paper also presents other results related to the characterization of Killing and parallel vector fields using the Ricci curvature and the Hessian of the function given by the inner product of the vector field.

Cyclic voltammetry can be applied as the reliable method for the determination of chloride ions in a range from several to couple hundred ppm. Since the standard potential of chloride ion/gaseous chlorine is 1.36 V vs NHE the efficient oxidation of Cl- ion occurs at very positive electrode potentials, usually higher than + 1.7 V vs NHE electrode. It is possible to observe this phenomenon only at noble-metal or inert carbon electrodes. Many other solutes, usually organic compounds, are often oxidized at this potential. This is the reason why determination of Cl- content directly from increase of the oxidation current is not reliable and can lead to overestimated values. However, gaseous chlorine, generated at positive potential dissolves in the analyzed solution and can be reduced in the reverse scan of cyclic voltammetric curve. Optimization of the experimental procedure using the statistical tools allowed for the development of the improved method for the direct quantification of chloride ions in acid copper electroplating baths. Under the proposed experimental conditions, the calibration curve (Cl2 voltammetric reduction current vs. chloride ions concentration) is represented by the linear model for the concentration of chlorides ranging from 10 to 200 mg/dm3.

Microplastics, pervasive in both terrestrial and aquatic ecosystems, have emerged as significant contributors to greenhouse gas (GHG) emissions, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). This review synthesizes recent studies from 2019 to 2024, revealing the complex mechanisms through which microplastics influence GHG production. These mechanisms include the adsorption of nutrients and pollutants onto microplastic surfaces and their role as substrates for microbial colonization. The impacts of microplastics vary significantly across different environments, such as agricultural soils and marine sediments. The review underscores the urgent need for standardized methodologies and long-term field studies to accurately assess the ecological consequences of microplastics. Notably, the role of nitrous oxide (N2O), a potent GHG with a global warming potential nearly 300 times that of CO2, remains underexplored in the context of microplastic interactions, highlighting a critical research gap. Additionally, the synergistic effects of microplastics with other pollutants require further investigation to fully understand their cumulative impact on GHG emissions. This review calls for a coordinated effort among researchers and policymakers to advance our understanding of microplastics' role in global GHG budgets and to develop effective strategies for mitigating their environmental and climatic impacts.

Side-chain liquid crystal polymers have been mixed with ferromagnetic particles, and the for-mation of a monodomain in magnetic fields studied. At relatively low concentrations, the presence of ferroparticles substantially speeds up the rate of formation of a monodomain with the magnetic field and at a given concentration of ferrofluid that rate is independent of the magnetic field strength. In this way, rapid formation of a monodomain is possible at magnetic field strengths far lower than required for the liquid crystal polymer alone. This is anticipated to very helpful in the fabrication of devices based on monodomain liquid crystal elastomers. Wide angle x-ray scattering has been used to monitor the formation of the monodomain and small angle x-ray scattering can give some indication of the ferroparticle behaviour. A model is developed to explain the behaviour. The alignment properties of the ferroparticles is related to their ability to form chains under the influence of very low magnetic fields; these chains are of relatively low stability and may become disrupted after long times, high magnetic fields, or high concentrations. In general, the best results for alignment were at volume fractions below 1%, and under these con-ditions there is the potential for producing monodomain samples with improved properties; in particular shape changes with temperature are significantly larger as a result of improved backbone orientation. Experiments involving monodomain formation and director realignment suggest that the presence of ferroparticles results in a modification in the mechanism for alignment development driven by the organisation of the polymer backbone as a consequence of the con-straints offered by the morphology of the chains of ferroparticles.

This paper explores the application of machine learning (ML) in predicting functional recovery in patients with ischemic stroke. As technology advances, ML shows significant potential in the field of stroke medicine, especially in the areas of big data analytics and personalized medicine. Studies have shown that ML algorithms can improve the accuracy of stroke image analysis, subtype classification, risk assessment, treatment guidance, and prognosis prediction. However, the widespread use of ML still faces challenges such as data standardization, model validation, privacy, and bias. This paper reviews the current application status of ML in the field of stroke, discusses the challenges faced, and looks forward to the future development direction, aiming to promote the practical application of ML technology in the diagnosis and treatment of stroke to improve the prognosis and quality of life of patients.

Celiac disease is a chronic small intestinal immune-mediated enteropathy precipitated by exposure to dietary gluten, affecting approximately 1% of the global population and two million Americans. An increasing number of studies have identified a link between celiac disease and adverse maternal and fetal outcomes during pregnancy and after birth. Additionally, both celiac disease and pregnancy are associated with an increased risk for nutrient deficiencies, specifically vitamin B12 and folate. Deficiencies in these key nutrients are linked with several negative maternal and fetal health outcomes including preeclampsia, gestational diabetes, spontaneous abortion/miscarriage, preterm birth, NTDs, Intrauterine Growth Restriction, and low gestational age and birthweight. This review examines the current literature related to the folate trap and vitamin B12 deficiency in patients with celiac disease and pregnant women independently, and to provide rationale for future research to explore the correlation between the folate to B12 ratio in pregnant woman with celiac disease.

Real time condition monitoring and precision health assessment system is a mandatory need for effective maintenance program in industrial sector. Rapid advancement in the information technology and other engineering technologies have invited more proactive attention from research and development in industrial sectors and particularly in condition monitoring of machines and related Industrial processes. In this work, drill bit condition monitoring techniques have been developed based on wavelet analysis and artificial neural networks (ANN) for automatic drill bit fault detection and classification. An experimental work has been conducted to capture the vibration signals for analysis. In this experiment, the CNC drill machine is used with high carbon steel drill bit and mild steel material as work piece. The cutting condition parameters are kept constant and the wear level is varied from 0.2 to 0.6 mm. The Data Acquisition system (DAQ) with Lab VIEW software is used to capture the vibration signals for drill bit with different wear conditions using accelerometer. The captured vibrations data are analyzed using continuous wavelet transform (CWT) with Morlet wavelet and Daubechies wavelet as a prime function. In general, the CWT coefficient is used to generate the inputs features to ANN for automatic tool condition classification, with two outputs (0, 1) for healthy and (1, 0) for faulty. The outcome of ANN showed 98% of accuracy in the wear prediction and this results show the effectiveness of the combed WT and ANN for automatic classification of tool wear conditions with high success rate.