Balanites aegyptiaca del. (Zygophyllaceae) is widely used in traditional medicine, both human and veterinary, throughout Africa for its many properties, including antiparasitic properties. This experimental study aims to optimise the extraction conditions of the seeds of Balanites aegyptiaca del. Aqueous maceration was carried out with mass to volume ratios of 40%, 30%, 20%, 10% and 5% and extraction times of 6, 12, 24, 36 and 48 hours. Extraction yields, phytochemical screening, saponins assay, antioxidant activities (ABTS and FRAP) and antiparasitic tests on Heligmosomoides bakeri were used to compare the different extracts. The pharmaco-chemical study generally showed that aqueous maceration gave the best results, with a mass/volume ratio of 10% after 12 hours of maceration. The yield obtained was 28.03% with a saponins content of 13.81 mg/g. The antioxidant activities were 4.25 ± 0.17µg/mL by the ABTS method and 0.739µg/mL by the FRAP method. The larvicidal activity also showed that the 10%12h extract produced 100% larval mortality from 25ug/mL. These data provide a basis for guiding the choice of extraction process parameters in producing this antiparasitic phytomedicine.

Objective: Breast cancer (BC) is the most common cause of death among females. There are many prognostic systems, the most recent of which are the molecular subtypes. Recently, it was included that thyroid disease is a favorable factor for the patients with BC and that the thyroid hormones have an effect on the disease. Thyroid stimulating hormone (TSH), however, is thought to be unrelated to the cancer aggressiveness. In the current study we aimed to examine the status of the postoperative TSH levels, as well as the impact of the thyroid disease on the cancer aggressiveness. Methods: A retrospective comparative analysis of invasive BC patients was performed between 2017 and 2019 year. 111 patients were selected. They were divided into group A (n=62) and group B (n=49), based on the presence or absence of thyroid disease, respectively. The data was processed with SPSS version 25. Results: There is a significant difference between group A and group B concerning the molecular subtypes, ki-67, and estrogen receptor. The current study supports the fact that TSH is responsible for the aggressiveness of the invasive BC and not the thyroid hormones themselves. Moreover, based on the correlation analyses calcium levels preoperatively are linked to cancer aggressiveness and could be used as future prognostic factors. Conclusion: Indeed, the thyroid disease appears to have more favorable prognosis based on the molecular subtype frequency but more emphasis in future studies should be given to the TSH and its relation to the overall survival of the patients.

Cranioplasty (CP) is the main surgical procedure aimed at reproducing a structural or morphological defect of the skull. It has been shown that cranioplasty can be useful for patients with traumatic brain injury (TBI) to achieve functional cognitive and motor improvements. Here, we describe a patient with long-term severe TBI who recovered consciousness following delayed CP. We found that a delayed CP may result in a meaningful functional recovery with emergence from a minimally conscious state and recovery of functional communication, even more than a year after decompressive craniectomy. Delayed intervention is equally successful in promoting functional recovery in long-term TBI patients, as early CP has already shown.

The drought response index (DRI) is an indicator of drought tolerance after adjustment for variation in flowering date and potential yield under well-watered conditions. Using a temperate japonica mapping population of 97 recombinant inbred lines from a cross between Otomemochi (OTM) and Yumenohatamochi (YHM), we evaluated DRI during the reproductive stage under very severe drought in one year and under severe drought in the next year. DRI under very severe drought (−6.4 to 15.9) and severe drought (−3.9 to 8.3) positively correlated with grain dry weight under drought. Three QTLs for DRI were identified: RM3703–RM6911–RM6379 and RM6733–RM3850 both on chromosome 2 in both years combined;. and RM8120–RM2615–RM7023 on chromosome 6 in the second year. The latter collocated with putative genes for signaling and defense mechanisms (e.g., PIN1B, BZIP46) revealed by database analysis. Top-DRI lines retained root dry weight and had bigger steles. QTL-by-environment interaction had a greater relative contribution than the main effects of QTLs. Comparison with three previous studies revealed that the QTLs for DRI were unique to each experiment and/or population; most of them closely colocalized with reported drought-yield QTLs.

Introduction; to the best of the authors knowledge no past research has established how illness narrative master plots are expressed initially, and then if, and how they change longitudinally following musculoskeletal trauma. The aim of the current research was able to consider how specific master plots were expressed, interact and change across time following musculoskeletal trauma. Methods; a narrative analysis was undertaken that included individuals who had experienced a musculoskeletal traumatic injury. Individuals were included if they were an inpatient within 4 weeks of the first interview had mental capacity to participate and were able to communicate in English. Three interviews were undertaken (within 4 weeks of injury, 6 and 12 months). A 5-stage categorical form type narrative analysis was performed. Results; Twelve individuals (49.9±17.5 years; 7 male, 5 female) completed interviews at three time points following the trauma event (<4 weeks months, 6 months and 12 months). Three main narratives that appeared to work together to facilitate a positive accommodation of the trauma event into the individual’s life were presented. These included the resumption narrative, the activity narrative and quest narrative. Finally, less often regressive narratives were identified although these narratives were, at times, actively avoided. Discussion; The current results provide important consideration for how narratives are used within clinical practice, in particular the value of how these three narratives could be access and promoted.

In solving the Collatz conjecture, it turns out that if we let all integers k be 6n, 6n+1, 6n+2, 6n+3, 6n+4, 6n+5, then we can solve the Collatz conjecture periodically. The Collatz conjecture states that for any positive integer P (initial value), if n is even, divide n by 2; if n is odd, repeat the rule of multiplying n by 3 and adding 1, which always converges to 1. One open problem has been proved by this paper. The authors hope to contribute to the mathematical community by presenting simple proofs of conjectures in the history of mathematics such as the Collatz conjecture.

This research explores the application of ARIMA (Autoregressive Integrated Moving Average) models and parallel computing techniques to analyze and forecast anemia diagnoses in children under 36 months in the Junín region of Peru. Using health data from 2023-2024, including insurance type, patient information, diagnosis dates, hemoglobin levels, and treatment details, we develop predictive models to understand trends and patterns in childhood anemia. The study aims to demonstrate the effectiveness of time series analysis and high-performance computing in addressing this critical public health issue. Results indicate improved forecasting accuracy and computational efficiency, potentially aiding in resource allocation and policy development for anemia prevention and treatment programs.

Wild-grown edible mushrooms are important in world diet, which are also efficient metal accumulators. Yunnan, southwest China is the main producing region with typically high geochemical metals. Environmental factors, bioaccumulation, distribution and human health risk of metals were examined in paired soil and Tricholoma matsutake (n=54). T. matsutake grows on acidified soils (pH=3.95–6.56) and metals showed strong heterogeneity with Fe, Mn, Zn and Cu ranged at 16–201, 0.046–8.58 g kg–1 and 22.6–215, 3.7–155 mg kg–1. High soil Fe content led to its great accumulation in T. matsutake (0.24–18.8 g kg–1). However, though soil Mn content was great higher than Zn and Cu, their concentrations in T. matsutake were comparable (21.1–487 vs. 38.7–329 and 24.9–217 mg kg–1). This suggested that T. matsutake prefers to accumulate Zn and Cu than Mn, and supported by bioaccumulation factor (BAF=0.32–17.1 vs. 0.006–1.69). Fe was mainly stored in stipe, while Mn, Zn and Cu were in cap, with translocation factor (TF) was 0.58 vs. 1.28–1.94. Therefore, stipe Fe showed the highest health risk index (HRI) at 1.28–26.9, followed by cap Cu (1.01–2.33), while 98–100% of Mn and Zn were risk-free. The higher concentration and greater risk of Fe was attributed to the significant effect of soil Fe content (R=0.34) and soil pH (R=–0.57). This study suggested that Fe as an essential mineral may exert toxic effects via T. matsutake consumption from geochemical high background areas.

Objective: To verify knowledge about HPV, promote educational action and encourage vaccination among students from 6th to 9th grade in the public school system of Campo Grande - MS. Methods: Conducting a structured interview. Results: It was pointed out that 70.1% had heard about HPV, however, 38.1% stated that it is a virus that causes cancer and 11.3% related it to the virus that causes warts. The free availability of the vaccine was known to 57.7% of participants and 62.3% were vaccinated with at least one dose. 79 students were vaccinated during the actions. Conclusion: There is a lack of knowledge, as the majority did not know how to relate HPV to the development of cervical cancer. The interaction between primary health care and schools resulted in the dissemination of knowledge about HPV, an increase in vaccine doses administered, favoring an increase in vaccination coverage among students.

This paper investigates the long-run relationship between the U.S. dollar and Canadian dollar by defragmenting the bilateral exchange rate induced by nominal and real shocks. The methodology centers on a structural vector autoregressive (SVAR) model, including the analysis of impulse response and variance decomposition to account for the impact of nominal and real shocks on exchange rate movements. The study also decomposes the real shocks into demand and supply factors from both Canada and U.S. and compare their impact on the nominal and real exchange rate. Results are compared to shocks driven by country specific nominal factors. The study is conducted using quarterly based data over December 1972 – December 2023. Findings suggest that the real shocks have a permanent impact on both the nominal and real exchange, compared with nominal shocks which have a temporary impact. Country-specific real supply-side factors have a more discerning impact than country-specific real demand-side factors. Country-specific nominal barely impacted the nominal and real exchange between U.S. and Canada.

Lymphadenopathy is a common manifestation of both reactive and malignant diseases, and fine needle aspiration (FNA) is an effective and inexpensive screening method. It can prevent unnecessary invasive surgery and excisional biopsy, especially in benign cases. Unfortunately, the lack of universally accepted terminology for reporting results has hindered its widespread support. The Sydney system proposal for lymph node cytopathology categorization and reporting introduced five diagnostic categories to address the lack of universally accepted terminology for reporting results in lymphadenopathy. Our study analyzed 188 lymph node FNC samples from King Abdulaziz University Hospital, Saudi Arabia, examining clinical follow-up data, pathology records, patient information, and final diagnosis from January 2019 to December 2022. Most specimens were from axillary LNs, with 99.5% tissue correlation. The Sydney System Category classification identified 56.9% of cases as malignant, while 26.1% were benign. The final surgical specimen diagnosis revealed a higher percentage of malignant diagnoses, with the highest ROM in malignant/Category V. In conclusion, our study demonstrates that LN-FNAC offers high diagnostic accuracy for LN aspirates, with the Sydney approach potentially aiding risk stratification and achieving consistency in cytologic diagnosis, but further multi-centric research is needed.

The purpose of this paper is to review the involvement of mitochondria in the actions of nitroglycerin (glycerol trinitrate -GTN) and the redox disturbances underlying diseases it treats. The paper begins by explaining complex I as the initial site of formation of superoxide and the process whereby it leads to the development of glutathione dependent tolerance. Next, the paper describes new formulations for preventing tolerance. The paper ends by illustrating diseases that may benefit from treatment with novel glutathione based GTN formulations and treatment approaches.

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

Tea (Camellia L.) falls into the family Theaceae, is a valuable commercial crop, and tea products made from its buds and young leaves are favored by consumers all over the world. The more common Thea plant is Camellia sinensis (C. sinensis), but its most important relative, Camellia taliensis (C. taliensis), is also utilized by locals in the area of cultivation to manufacture tea. In this investigation, C. taliensis (DL) and C. sinensis (QJZ) were characterized in terms of their agronomic traits, physicochemical indices, metabolomics, and transcriptomics. The leaf area of DL is larger than that of QJZ; the color of DL’s buds and leaves is yellowish-green, while that of QJZ’s is green. DL’s buds and leaves are more densely velvety than those of QJZ. The HPLC results indicated that the physicochemical contents varied considerably between the two samples, with DL having greater concentrations of EGCG and GABA than QJZ, while QJZ had remarkably higher concentrations of C, CA, and EGC than DL. A total of 2269 metabolites and 362,190,414 genes were positively identified, with the number of DAMs and DEGs being 1001 and 34,026, respectively. The flavonoids, phenolic acids, and alkaloid metabolites were dramatically different between the two tea group plants. Bioinformatics profiling revealed that the DAMs and DEGs of the two tea group plants interacted with each other and were involved in metabolic pathways including “biosynthesis of secondary metabolites”, “biosynthesis of amino acids”, “biosynthesis of cofactors”, “phenylpropanoid biosynthesis”, and “flavonoid biosynthesis”. Overall, these results provide statistical support for germplasm conservation and production for both C. taliensis and C. sinensis.

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality worldwide and a major global health burden. The treatment of HCC has experienced a paradigm shift in the last few years, following the discovery of immunotherapy. However, despite the profound success of immunotherapy in other cancer types, their response in HCC remains unsatisfactory. Some of the reasons that can explain this poor response include the immunosuppressive microenvironment of HCC, the absence of reliable biomarkers for response, and drug resistance. Previous preclinical and clinical studies have highlighted the role of combination therapy in overcoming some of these hurdles. In this article, we discuss the benefit of combining immune checkpoint inhibitors (ICIs) with stereotactic body radiation therapy (SBRT) in HCC and shed light on promising clinical trials.

Surfactant proteins A and D (SP-A and SP-D) belong to the collectin subfamily of C-type oligomeric lectins. They are pattern-recognition molecules (PRM), able to recognise pathogen- or dan-ger-associated molecular patterns (PAMP, DAMP) in the presence of Ca2+ cations. That property enables opsonisation or agglutination of non-self or altered/abnormal self-cells, and contributes to their clearance. Like other collectins, SP-A and SP-D are characterised by the presence of four distinct domains: a cysteine-rich domain (at N-terminus), a collagen-like region, an α-helical neck domain and a globular carbohydrate-recognition domain (CRD) (at C-terminus). Pulmonary sur-factant is a lipoprotein complex, preventing alveolar collapse by reducing surface tension at the air-liquid interface. SP-A and SP-D, produced by type II alveolar epithelial cells, and Clara cells, are not only pattern-recognition molecules but also contribute to the surfactant structure and homeo-stasis. Moreover, they are expressed in a variety of extrapulmonary sites where they are involved in local immunity. The term “cancer” includes a variety of diseases: tumours start from uncontrolled growth of abnormal cells in any tissue which may further spread to other sites of the body. Many cancers are incurable, difficult to diagnose and often fatal. This short review summarises anti- and pro-tumourigenic associations of SP-A and SP-D as well as perspectives of their usefulness in cancer diagnosis and therapy.

In contemporary society, digital technology permeates every aspect of our routines. This study assessed students' comprehension of the environmental impacts of prolonged screen time, specifically during binge-watching sessions. It investigated awareness of carbon emissions from electronic device usage, binge-watching habits, and influencing factors such as content preferences, duration, and frequency. The study also explored potential interventions to mitigate environmental impacts. Using a mixed-methods approach, data were collected from 525 higher education students (150 male, 375 female) through self-designed standardized questionnaires. The analysis involved Percentage, t-test, ANOVA, Multiple Correlation, and coding processes. Results indicated that 66.67% of students had a high level of understanding regarding the environmental impact of binge-watching, while only 4.76% were highly aware of the carbon emissions from extended screen time. Additionally, 23.81% exhibited high levels of binge-watching habits and behavior. Gender disparities were significant; females demonstrated a deeper understanding of the environmental impacts (t=4.08, p < α) and showed different binge-watching habits compared to males (t=3.16, p < α). However, no significant gender difference was found in awareness of carbon emissions (t=0.28, p > α). A notable difference (t=12.98, p < α) was observed between students' understanding of environmental impacts and their awareness of carbon emissions. The study also revealed a weak positive correlation (R=0.36) and significant differences [F(2, 1572) = 320.10, p < 0.05, 0.01] in understanding the environmental impacts, awareness of carbon emissions, and binge-watching behaviors. Factors influencing binge-watching and potential regulatory measures were also identified.

Photocatalytic processes offer promising solutions for environmental remediation and clean energy production, yet their efficiency under visible light remains a significant challenge. Here, we report a novel silver-graphene (Ag-G) modified TiO2 (Ag-G-TiO2) nanocomposite photocatalyst that demonstrates remarkably enhanced photocatalytic activity for both dye wastewater degradation and hydrogen production under visible and UV light irradiation. Through comprehensive characterization and performance analysis, we reveal that the Ag-G modification narrows the TiO2 bandgap from 3.12 eV to 1.79 eV, enabling efficient visible light absorption. The nanocomposite achieves a peak hydrogen production rate of 191 μmolesg-1h-1 in deionized water dye solution under visible light, significantly outperforming unmodified TiO2. Intriguingly, we observe an inverse relationship between dye degradation efficiency and hydrogen production rates in dye solutions with tap water versus deionized water, highlighting the critical role of water composition in photocatalytic processes. Our findings demonstrate sustained hydrogen production under visible light and rapid initial rates under UV irradiation, underscoring the versatility of Ag-G-TiO2 catalyst. This work not only advances our understanding of fundamental photocatalytic mechanisms but also presents a promising material for solar-driven environmental and energy applications, potentially contributing to the global transition towards sustainable technologies.

Pancreatic cancer is a refractory cancer with limited treatment options. Various cancer types are resistant to the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). Eugenol, the main component of clove oil, exhibits anticancer, anti-inflammatory, and antioxidant effects. However, no studies have reported that eugenol increases TRAIL sensitivity by upregulating death receptor (DR) expression. Here, we aimed to investigate eugenol as a potent TRAIL sensitizer. Increased apoptosis and inhibition of cell proliferation was observed in pancreatic cancer cells treated with eugenol and TRAIL compared with those treated with eugenol alone. Eugenol upregulated the expression of DR5, inhibited FLICE-inhibitory protein (FLIP), an anti-apoptotic protein, and increased p53, a tumor suppressor protein. In addition, eugenol induced the generation of reactive oxygen species (ROS) and caused endoplasmic reticulum (ER) stress. C/EBP-homologous protein (CHOP) knockdown using siRNA decreased the expression of DR5 and reduced the combined effects of eugenol and TRAIL. These results demonstrate that eugenol enhances TRAIL-induced apoptosis by upregulating DR5 through the ROS-mediated ER stress-CHOP pathway, enhancing ER stress by inducing p53 and downregulating FLIP expression. This suggests that eugenol has the potential to treat pancreatic cancer by increasing cell sensitivity to TRAIL.

In this research work, we examined the decomposition mechanisms of N-substituted diacetamides. We focused on the substituent effect on the nitrogen lone pair electron delocalization, withdrawing and electron donor groups. DFT functionals used included: B1LYP, B3PW91, CAMB3LYP, LC-BLYP, and X3LYP. Dispersion functions gd3bj were applied when necessary to improve non-covalent interactions in the transition state. Pople with higher angular moments and def2-TZVP basis sets were also applied and were crucial for obtaining consistent thermodynamic parameters. The proposed mechanism involves a six-membered transition state with the extraction of an α hydrogen. Several conformers of N-diacetamides were used to account for the decrease in entropy in the transition state in the rate-determining state. All calculations, including Natural Bond Orbital (NBO) analyses, were performed using the Gaussian16 computational package and its GaussView 6.0 visualizer, along with VMD and GNUPLOT software. The isosurfaces and IBSI indexes were calculated using MultiWFN and IGMPlot, respectively.

Background: The aim of this study is to explore the independent and joint associations between physical activity (PA) and sleep duration with depressive symptoms. Methods: We included and analyzed 18,052 participants (age ≥ 20 years) from the cross-sectional National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2014. Results: After adjustment, both males and females showed a significant correlation between PA, sleep duration, and depressive symptoms. In the joint association analysis, we found: 1. The interaction between PA and sleep duration was statistically significant in males but not significant in females (P=0.380). 2. Compared to individuals with the lowest PA level and not meeting the National Sleep Foundation's (NSF) guidelines, those with the highest PA level and recommended sleep duration had a 79% decrease in depression risk in males (odds ratio [OR] 0.21, 95% confidence interval [CI] 0.14-0.32) and a 74% decrease in females (OR 0.26, 95% CI 0.20-0.35). 3. In male participants adhering to NSF guidelines, each increase in PA quartile is associated with a 19% reduction in the risk of depression (OR 0.81, 95% CI 0.71-0.92). Conversely, among male participants not adhering to NSF guidelines, there is a 23% decrease in depression risk (OR 0.77, 95% CI 0.69-0.86). For female participants, the respective reductions in depression risk are 20% (OR 0.80, 95% CI 0.73-0.89) and 14% (OR 0.86, 95% CI 0.80-0.93). Conclusion: For males, adherence to recommended sleep duration weakens the relationship between physical activity and depression, while the opposite is observed for females.

Petrochemicals and oil refineries are industrial processes that use compounds and polymers derived directly or indirectly from natural gas or crude oil for chemical purposes. They have posed a number of short- and long-term risks to the environment and the people who live nearby. The study aims to determine how the presence of industrial areas, such as oil refineries, affects the local population's perception of their surroundings. The investigation centers on the Tehran Oil Refinery, a major refinery hub, and its perceived environmental impact. For this purpose, a Geographic Information System for Public Participation (PPGIS) covering three basic sections has been designed: socio-demographic information of the participants; self-perceived health; and landscape valuation before and after an intervention. The main observations show a complex interaction between industrial presence and the perception of landscape values. Participants' reactions to the manipulated Photographs reveal important details about the psychological impact of visual elements on emotional perception. There is also a direct relationship between the level of stress and emotional perception in the manipulated and original photos.This research adds to the larger debate about the effects of industrialization on the environment and society. It emphasizes the importance of considering public perception when planning and developing industrial projects. The goal is to strike a balance between industrial operational needs and environmental quality preservation, resulting in long-term urban growth.

Indole-3-acetic acid (IAA), as an important regulator of potato growth, seriously affects the growth and yield of potato. Although many studies have reported that IAA-producing Bacillus can promote plant growth, little research has been done on its synthesis pathway and the molecular mechanisms. In this study, IAA-producing strain WL35 was identified as Fitibacillus barbaricus, and its yield was 48.79 mg·L-1. The results of the pot experiments showed that WL35 significantly increased plant height, stem thickness, chlorophyll content and number of leaves of potato plants by 31.68%, 30.03%, 32.93% and 36.59%, respectively. In addition, in the field experiments, WL35-treated plants increased commercial potatoes yield by 16.45%, vitamin C content by 16.35%, protein content by 75%, starch content by 6.60%, nitrogen, phosphorus and potassium accumulation by 9.98%, 12.70% and 26.76%, respectively. Meanwhile, the synthetic pathway of WL35 was found to be dominated by the tryptophan-dependent pathway, the IAM, TAM and IPA pathways worked together, and the pathways that played a role at different times were different. Furthermore, RNA-seq analysis showed that there were a total of 2875 DEGs regulated in the samples treated with WL35 seed dressing compared with the CK, of which 1458 genes were up-regulated and 1417 genes were down-regulated. Potato roots express differential genes enriched in processes such as carbohydrate metabolism processes and cellular polysaccharide metabolism, which regulate potato plant growth and development. The above results provide a theoretical basis for the further exploration of the synthesis pathway of IAA and its growth-promoting mechanism on potato.

Background: Surgical parameters of phacoemulsification can have a significant impact on behavior of anterior hyaloid membrane (AHM). Methods: In a prospective study using anterior segment optical coherence tomograph the attachment or detachment of AHM of 82 eyes were examined after uneventful phacoemulsification preoperatively and postoperatively over a 1-year period. The impact of capsulorhexis size, number of hydrodissections, difficulty of nucleus rotation, nuclear sclerosis grade, cumulative dissipated energy (CDE), ultrasonic time, total surgical time, difficulty of irrigation/aspiration, intensity of capsular polish, weakness of zonular fibers, presence of lens materials in Berger's space (LM-BS), and fluid usage were investigated related to the behavior of AHM. Results: In presence of zonular weakness and high CDE, a significant linear trend was observed regarding anterior vitreous detachment (AVD) at all postoperative times. Similarly, AVD is observed at 1-month, 3-month, and 1-year follow-up in cases of high nuclear sclerosis grade and high fluid usage. A significant linear trend was observed in the case of zonular weakness, hard nucleus and extensive capsular polish with LM-BS, while CDE, total surgical time, and fluid usage were significantly higher in these cases. Conclusions: Zonular weakness, high CDE, hard nucleus and high fluid usage are risk factors of postoperative AVD.

AI advances integrate generative design tools in architecture, providing architects with sophisticated design options. It enables the creation of intricate, high-performing projects by exploring diverse design possibilities with AI and algorithms. Generative AI and generative design empower architects to create better-performing, sustainable, and efficient design solutions and explore diverse design possibilities. This paper leverages multimodal generative AI to enhance design creativity by combining textual and visual inputs. Blockchain technology converts design metadata into NFTs, ensuring secure, authentic, and traceable data storage. The framework addresses data ownership, legal adherence, and client-architect collaboration and is entirely scalable for digital design authentication. This research exemplifies the pragmatic fusion of Generative AI and blockchain technology applied in architectural design for more transparent, secure, and effective results. This study provides a strategy that uses generative AI technologies to achieve an efficient and creative workflow in the early stages of architectural design.

The growing demand for high-power DC Fast Charging (DCFC) stations for Electric Vehicles (EVs) is expected to lead to increased peak power demand and reduction of grid power quality. To maximize the economic benefits and station utilization under practical constraints set by regulatory authorities and DCFC station operators, this study explores and provides methods for connecting DCFC stations to the grid employing low power interconnection rules and Distributed Energy Resources (DERs). The system uses automotive Second Life Batteries (SLBs) and Photovoltaic (PV) systems as energy buffers and local energy resource to support EV charging and improve the station techno-economic feasibility through load shifting and charge sustaining. The optimal sizing of the DERs and the selection of the grid interconnection topology is achieved by means of a Design Space Exploration (DSE) by means of exhaustive search approach to maximize the economic benefits of the charging station and to mitigate high-power demand to the grid. Without loosing of generality, this study considers a range of DER sizes, grid interconnection specifications, and related electricity tariffs of American Electric Power (AEP) Ohio and the Public Utility Commission of Ohio (PUCO). Various scenarios and strategies have been defined to account for the interconnection requirements of the grid to the DCFC with DERs. The system’s techno-economic performance of different scenarios has been analyzed and compared using a multitude of metrics.

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

The aim of this study was to analyze the relationship between healthy vascular aging (HVA) and the Mediterranean diet alongside other lifestyles in a Spanish population aged 35 to 75 years without previous cardiovascular diseases. Methods: Cross-sectional descriptive study with 501 individuals aged 35 to 75 years recruited from five health centers by random sampling stratified by age and sex (55.90±14.24 years, 49.70% men). HVA was determined in two steps. Step 1: Subjects with vascular damage to the carotid arteries or peripheral arterial disease were classified as non-HVA. Step 2: The study population was classified by age and sex using the percentiles of the vascular aging index (VAI), with VAI ≤p25 considered HVA and >p25 considered non-HVA. The VAI was estimated using the following formula (VAI = (log (1.09) × 10 cIMT + log (1.14) cfPWV) × 39.1 + 4.76. Carotid-femoral pulse wave velocity (cfPWV) was measured with the SphygmoCor^® device and carotid intima-media thickness using Sonosite Micromax^® ultrasound. Mediterranean diet (MD) adherence, alcohol and tobacco use were recorded through validated questionnaires. Physical activity was assessed with the ActiGraph-GT3X^® accelerometer. Results: The mean VAI value was 61.23±12.86; (Men 63.47±13.75 and women 59.04±11.54; p<0.001). HVA was found in 18.9% (men 19.9% and women 17.8%). In the multiple regression analysis after adjusting for possible confounding factors, the mean VAI value showed a positive association with alcohol use (β=0.020) and sedentary hours per week (β=0.109), and a negative association with hours of activity per week (β=-0.102) and with the number of healthy lifestyles (β=-0.640). In the logistic regression analysis after adjusting for possible confounding factors, and compared to those classified as non-HVA, subjects classified as HVA were more likely to show adherence to MD (OR = 0.571), perform more than 26 hours per week of physical activity (OR = 1.735), spend less than 142 hours per week being sedentary (OR = 1.696), and have more than two healthy lifestyles (OR = 1.877). Conclusion: The results of this study suggest that the more time spent doing physical activity and the less time spent sitting, the lower the vascular aging index and the greater likelihood of being classified in the group of subjects showing HVA.

Wear phenomena on natural stone of the cultural heritage are induced from various sources. Consequently, the development of multifunctional protective materials which combine two or more useful properties is an effective strategy to address the synergistic effects of various wear mechanisms. A multifunctional coating, consisting of a silane-based precursor and zinc oxide (ZnO) nanoparticles (NPs), is produced and tested for the protection of limestone. The hybrid coating combines the following three properties: superhydrophobicity, including water-repellency, photocatalytic self-cleaning and biocidal activity. The relative concentration of the NPs (0.8% w/w), used for the suggested composite coating, is carefully selected according to wetting studies, colourimetric measurements and durability (tape peeling) tests. The non-wetting state is evidenced on the surface of the composite coating by the large contact angle of water drops (≈153°) and the small contact angle hysteresis (≈5°) which gives rise to the physical self-cleaning scenario (lotus effect). The photocatalytic chemical self-cleaning is shown with the removal of methylene blue, induced by the UV-A radiation. Moreover, it is shown that the suggested coating hinders the incubation of E. coli and S. aureus as the inhibition were 94.8 and 99.9 %, respectively. Finally, preliminary studies revealed the chemical stability of the suggested coating.

Global attention to climate change has surged since the advent of the Paris Agreement, intensifying the importance of measuring and managing carbon productivity indicators on a national level. Nevertheless, concerns persist regarding the reliability of such measurements because of inherent discrepancies in implementing and operating national-level carbon productivity indicators, coupled with their inherent uncertainty. This study proposes a multiple regression model to address these issues aimed at refining national-level carbon productivity indicators metrics, accounting for factors such as the gross domestic product and total greenhouse gas emissions by sectors. The objective was to offer insights into enhancing and effectively utilizing current indicators, enabling a more nuanced interpretation of the variation in the carbon productivity indicators across diverse industrial landscapes. This study showed that adjustments of the carbon productivity metrics reflect disparities in emissions across industrial structures, with countries characterized by high emissions from non-service industries showing improving trends. In addition, this paper proposes an auxiliary indicator estimating method for carbon productivity, emphasizing its utility in interpreting productivity indicators within the context of varying industrial compositions across OECD countries. This study underscores the inadequacies of the current national productivity estimating method, pinpointing areas requiring refinement. Specifically, the method for estimating the auxiliary indicator for carbon productivity guarantees enhanced rationality when integrated with current methodologies. Moreover, by elucidating the nuances of industrial structures, this study advocates for more sophisticated approaches to interpreting and managing the productivity indicators tailored to each unique economic landscape of each country. Nevertheless, the limitations stemming from data availability underscore the need for further research, particularly in refining the national-level carbon resource productivity indicators analyses and exploring the thematic productivity variations in greater depth. By addressing these gaps, future studies will contribute to a more comprehensive understanding of national-level carbon resource productivity indicators dynamics and reveal targeted strategies for sustainable development.

Staphylococcus aureus is an opportunistic human pathogen and a leading cause of bloodstream infections. It can acquire different antibiotic resistance genes, leading to treatment failure. Aim: We elaborate on the genomic characteristics; antibiotic resistance, virulence, pathogenicity, phylogenomics and clonal diversity of S. aureus implicated in bloodstream infections. Six multidrug-resistant (MDR) S. aureus, three methicillin-resistant S. aureus (MRSA) and three methicillin-sensitive S. aureus obtained from blood cultures underwent whole genome sequencing and bioinformatics analysis. All isolates carried different permutations and combinations of resistance genes including, blaZ, mecA, aac(6')-aph (2''), ant(9)-Ia, ant(6)-Ia, mepR, fosB, norA, norC, lmrS, arlS, arlR, mgrA, kdpD and sdrM. We found 6 spa types (t9475, t355, t045, t1265, t1257, and t7888) with varying profiles of virulence genes responsible for immune invasion, enterotoxins, adhesion/biofilm, haemolysins, and leukotoxins. Panton-Valentine leukocidin (Luk-PV) was found in one MSSA isolate. Two SCCmec types IVd(2B) and I(1B) were identified. Isolates belonged to four multilocus sequence types (MLSTs), the most common of which was ST5 (n=3). The STs were clustered into two clonal complexes CC5 and CC8. We found two MRSA clones typed as ST5-CC5-t045-SCCmec_I(1B), and the human-associated MRSA endemic clone ST612-CC8-t1257-SCCmec_IVd(2B). The insertion sequences IS30 and IS6 associated with virulence were found in two isolates. The presence of virulent MDR S. aureus in bloodstream infections poses a clinical concern because of limited treatment options and increased risk of mortality.

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol stands as a cornerstone in modern aviation surveillance and Aircraft Traffic Control systems, integral to the NextGen project initiated by the US Department of Federal Aviation Administration (FAA) in 2005. ADS-B utilizes data links to autonomously broadcast Aircraft navigational and identification information to augment air transportation system capacity and safety. However, concerns regarding the protocol's security persist, particularly as its adoption expands. The unencrypted nature of transmitted aircraft data and the absence of robust authentication mechanisms render the protocol susceptible to exploitation by malicious actors. In this study, we comprehensively reviewed existing research in the field, identifying a crucial gap necessitating a holistic survey. Prior surveys have predominantly focused on specific aspects, such as vulnerabilities, attacks, or critiques of existing solutions. Our survey addresses this gap by thoroughly exploring the aviation system, providing readers with a nuanced understanding of ADS-B security. Utilizing a detailed SWOT analysis diagram, our paper delves into the vulnerabilities inherent in the ADS-B protocol outlines potential threats and scrutinizes various attack scenarios. We systematically categorize and analyze existing security solutions, considering cost-effectiveness, scalability, implementation complexity, and coverage against diverse attack vectors. Furthermore, we critically evaluate these solutions, elucidate ADS-B security requirements, discuss current challenges, and propose future research directions. This survey serves as a comprehensive resource for researchers and practitioners alike, shedding light on the multifaceted landscape of ADS-B security and paving the way for enhanced aviation system resilience in the face of evolving cybersecurity threats.

Field implementations of inductive power transfer (IPT) face many practical challenges that dramatically reduce power transmission effectiveness. Coil misalignment is a persistent issue in IPT systems, especially in applications involving vehicles or nonvisible coils. Furthermore, magnetic field symmetry convolutes the decomposition of misalignment measurements in multiple dimensions and frequently impedes the efficacy of traditional position correction strategies. This paper presents an automated methodology to sense misalignments and align IPT coils using robotic actuators and sequential Monte Carlo methods. The misalignment of a Class EF inverter-driven IPT system was modeled by tracking changes as its coils move apart laterally and distally. These models were integrated with particle filters to estimate the location of a hidden coil in 3D, given a sequence of sensor measurements. During laboratory tests on a Cartesian robot, these algorithms aligned the IPT system within 1 cm (0.025 coil diameters) of peak lateral alignment. On average, the alignment algorithms required less than four sensor measurements for localization. After laboratory testing, this approach was implemented with an agricultural sensor platform at the Utah Agricultural Experiment Station in Kaysville, Utah. In this implementation, a buried sensor platform was successfully charged using an aboveground, vehicle-mounted transmitter.

Background: Land use and land cover change (LULCC) in the Ruhuhu River Sub-Basin (RRSB), a crucial watershed within the Lake Nyasa Basin in Tanzania, poses a significant threat to water resource sustainability and ecological integrity. However, a lack of comprehensive data on long-term LULCC trends has hindered effective conservation efforts. Methods: This study utilized Landsat 5 TM and Landsat 8 OLI data within Google Earth Engine to quantify LULCC dynamics from 1990 to 2023. Six land cover classes were analyzed: water, forest, barren land, grassland, shrubland, and farmland. Results: Results revealed a substantial decline in forest cover (56.92% to 28.60%), primarily converted to farmland (2.99% to 20.22%). Shrubland expanded initially but then declined, while barren land steadily increased. These changes have profound implications for water resources, biodiversity, and ecosystem services within the RRSB and the broader Lake Nyasa Basin. Conclusions: This research highlights the urgency of implementing sustainable land management practices to mitigate the adverse impacts of LULCC in the RRSB. The high classification accuracies achieved (90.9% to 98.7%) validate the robustness of the methodology. This study provides crucial insights for policymakers, land managers, and conservation practitioners, emphasizing the need for targeted interventions to promote sustainable land use and ensure the long-term resilience of the RRSB ecosystem.

Indole derivatives are key components of natural products and possesses a wide range of biological and pharmaceutical applications. Here we present the synthesis of a new indole derivative namely 2-(1-ethyl-5-nitro-1H-indole-7-carbonyl) butyl 4-methylbenzenesulfonate (5). The structural elucidation of 5 was accomplished through comprehensive spectroscopic analysis, including Fourier-transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), and high-resolution mass spectrometry (HRMS). Our molecular docking study revealed that compound 5 exhibits strong affinity towards Tyrosinase, making it a promising candidate as an antioxidant agent. Keywords: Indole derivative; Tosyl group; Molecular docking; Antioxidant agent.

To evaluate the efficacy of percutaneous dilatational tracheostomy (PDT) combined with adjuvant therapies in preserving vocal function in amyotrophic lateral sclerosis (ALS) patients. Methods: We performed a retrospective analysis of 47 ALS patients who underwent PDT at the Rodem Hospital from 2021 to 2023. Post-operatively, these patients were provided with a comprehensive treatment plan that included regenerative injection therapy, low-frequency electrical stimulation, respiratory rehabilitation, and swallowing rehabilitation therapy. Additionally, a balloon reduction program was implemented for effective Tracheostomy tube (T-tube) management. The preservation of vocal functions was evaluated 4 weeks following the procedure. Results: While some patients maintained or slightly improved their ALSFRS-R speech scores, the overall trend indicated a de-crease in speech scores post-PDT. This suggests that PDT combined with adjuvant therapies may not universally improve vocal function, but can help maintain it in certain cases. Conclusion: Our findings indicate that PDT combined with mesotherapy, low-frequency electrical stimulation, and swallowing rehabilitation therapy may play a role in maintaining vocal function in limb type ALS patients, though further research is needed to optimize patient management and validate these results.

Introduction: In Traditional Chinese Medicine (TCM), tongue diagnosis plays an important role. Besides shape, colour and textural attributes of tongue regions have significance due to their association with different organs (viz. heart, lung, kidney-bladder, liver-gallbladder and stomach-spleen) in health and disease. Although numerous quantitative methods have been proposed to reduce inter and intra observer variability in tongue diagnosis, almost all of them considered only global colour/ textural features i.e. from entire body of tongue. In this work, regional colour and texture information of tongue have been analysed for healthy subjects (NOM) and patients suffering from chronic acidity-indigestion (ACD). Methods: Tongue boundaries are marked manually in each image and then tongue bodies are automatically partitioned into five regions linked with said internal organs. Rough assessments of regions’ boundaries are obtained from literature and then they are fine-tuned according to experts’ advice. As boundaries are not well defined, regions near the common boundary of two or more organs, are not assigned to any organ. Several first and second order statistical features based on grey scale intensities and a* values of LAB colour space (indicative of redness) have been extracted from five different regions of tongue images. Intragroup analysis using Wilcoxon signed rank test compared different regions within individual study group. Additionally, intergroup analysis using Wilcoxon rank sum test compared tongues of NOM with ACD for each region separately. Results: Intragroup analysis reveals a* values are statistically different (p&lt;0.01) between stomach-spleen and liver-gallbladder regions for ACD while no significant change of a* are noted between these regions of normal tongue. It was found from intergroup analysis that correlation (one of the second order texture features extracted from grey scale images) of heart region has significantly decreased while correlation of kidney, liver-gallbladder and stomach-spleen regions significantly increased from NOM to ACD. Conclusion: This study sheds light on importance of inclusion of regional textural analysis of tongue in quantitative studies and can be applied to automated tongue diagnosis for other diseases.

Microalgae cultivation for biotechnological purposes is an expanding field. Their cultivation is usually performed on a liquid culture medium and require the presence of an energy source. Culture media are water-salt solutions containing nitrogen, sulfur, phosphate sources, with trace of transition metals. Light source supplies energy through photosynthesis process, resulting in metabolic reactions and cell growth. Thanks to the huge number of existing species and their diversity, it is possible to exploit alternative water sources with chemical and physical properties far from the commonly used freshwater media. Among these, oilfield or formation waters (AFW) are saline wastewater produced during oil drilling. They represent over 95 % of the total fluids collected from gas and oil wells during fuel extraction. This study exploits the adaptation capability of a Galdieria sulphuraria strain in different salinity conditions to build up a more feasible microalgae-based platform. Batch cultivation of G. sulphuraria was evaluated in a range from 0 to 20 g/L NaCl in terms of growth rate, metabolite content, photophysiology, and intracellular redox state. Moreover, the same strain has been tested for artificial formation water growth in semicontinuous cultivation mode. In these condition, NaCl preadaptation effect has been assessed too. Results clearly demonstrate that biomass composition is influenced from medium salinity. Strains preadapted in 0 to 20 g/L range of NaCl salinity show almost same cell growth profile and a slightly different ratio between lipids, carbohydrates, and proteins. Pigments content and photophysiology point out that variations of osmotic pressure and ionic strength in medium affect Photosystem II (PSII). Regulation of light harvesting is necessary to trigger metabolism shift toward synthesis of metabolites required in the adaptation process.

This case report describes the successful repair of a radial bone fracture and skin defect in a dog using an ulnar bone graft and an advancement flap. A one-year-old spayed female Poodle dog weighing 1.7 kg was brought in with non-weight-bearing lameness, an open wound, and a frac-ture in the right forelimb. The dog had fallen off the bicycle being ridden by its owner, causing its right forelimb to be caught in the wheel. The treatment included surgical debridement of the necrotic tissue, skin reconstruction with an advancement flap, and radial bone reconstruction with an ulnar bone graft, bone morphogenetic protein (BMP), humeral cancellous bone and a ti-tanium T-shaped plate. Postoperative management included antibiotics, pain medication, and activity restriction. The dog made a good recovery and was able to bear weight on the affected limb four months after surgery.

The application of deep learning in autonomous vehicles has surged over the years with the advances in technologies. This research explores the integration of deep learning algorithms into autonomous vehicles (AVs), focusing on their role in perception, decision-making, localization, mapping, and navigation. It shows that deep learning, which as a part of machine learning, mimics the human brain's neural networks, enabling advancements in perception, decision-making, localization, mapping, and overall navigation. Techniques like convolutional neural networks are used for image detection and steering control, while deep learning is crucial for path planning, automated parking, and traffic maneuvering. Localization and mapping are essential for AVs' navigation, with deep learning-based object detection mechanisms like Faster R-CNN and YOLO proving effective in real-time obstacle detection. Apart from the roles, the study also revealed that integration of deep learning in AVs faces challenges such as dataset uncertainty, sensor challenges, and model training intricacies. However, these issues can be addressed through increased standardization of sensors, real-life testing for model training, and advancements in model compression technologies can optimize the performance of deep learning in AVs. The study concludes that deep learning plays a crucial role in enhancing the safety and reliability of AV navigation. This study contributes to the ongoing discourse on the optimal integration of deep learning in AVs, aiming to foster their safety, reliability, and societal acceptance.

The concentrations and ratios of plant C, N, and P serve as important indicators of ecological processes. However, how plant and soil C:N:P relationships and ratios change with forest stand types remain unclear. Here, we analyzed the ecological stoichiometric characteristics by measuring leaf and soil organic C, total N and P contents in four stand types in Liaocheng, including Populus tomentosa pure forest, Populus tomentosa-Robinia pseudoacacia mixture forests, Platanus orientalis pure forest, and Salix matsudana pure forests. We find that: (1) The N and P leaf contents varied significantly across the four forest stands, with Populus tomentosa-Robinia pseudoacacia mixture forests having higher P levels. Platanus orientalis pure forests had lower C and N but higher P levels compared to others. (2) Uncoupled cycling of P in leaf-soil systems due to environmental influences, but C and N elements showed coupled cycles in some forest stands. (3) All forest stand types were limited by N and P elements. Overall, environmental factors, in addition to species variations, influence the C, N, P, and C:N:P ratios in leaves and soils of different forest stand types. Enhancing conservation and efficient use of N and P elements is crucial for sustainable plantation forest management to promote optimal growth in the region.

Micro (nano) plastics are emerging pollutants and their gradual accumulation in soil due to factors such as improper wastewater processing, plastic film abuse and atmospheric deposition could pose a significant threat to the environment. However, there is limited research on the uptake and transposition of micro (nano) plastics by terrestrial plants and the effects of microplastics on terrestrial plant growth. Therefore, the sources of plastics in soil as well as the uptake and transposition pathways of micro (nano) plastics in terrestrial plants are systematically summarized in this study. The effects of micro (nano) plastics on plants and their mechanisms are thoroughly discussed, which mainly affect the growth and development of plants by blocking roots, triggering oxidative damage and altering the nature of the soil and the microbial community as well as the combined toxic effects with other pollutants. Future research should strengthen the in-situ experiments to study the mechanisms by which soil micro (nano) plastics affect the uptake and transposition of individual plants and plant growth. It should also focus on the factors affecting the uptake of micro-(nano) plastics, the behaviour of micro-(nano) plastics in soil and plant uptake, transposition processes and their mechanisms and combined effects of micro-(nano) plastics and pathogens on plants. Moreover, new detection technologies should be developed to monitor their impacts on ecosystems to better manage their potential risks to the environment.

Experiential learning, defined as the result, source, or context of knowledge obtained from direct experience, is increasingly bolstered by technology and human-computer interaction (HCI) principles and protocols. This article will describe how technology-based human-computer interaction (HCI) has been used in experiments to enhance direct knowledge experience. In this paper, immersive technologies (such as Virtual Reality, Augmented Reality, and haptics) will be described based on cognitive learning theory, empirical research and practical experience gained from implementing cutting-edge technology and maximizing HCI principles in constructive learning. Additionally, this article will describe how AI can be used to create individualized learning environments according to a student's needs in the future. While cost, technical issues and specialised trainings are the obstacle to deliver personalized learning experiences especially to economically disadvantaged students, technological change opportunities are projected, and these technologies will take educational outcomes to the next level.

This paper presents the results of theoretical and applied research that employs methodological experimentation in a project for the protection and integrated transformation of the downtown area of the city of Sharjah in the United Arab Emirates. The particular nature of this case relates to two factors: a) strategies and policies to protect and enhance the cultural heritage as a driver for tourism and the cultural development of the entire Emirate, from archaeological goods to the urban fabrics in historical centres (Sharjah and Korfakkhan), in contrast to the surrounding emirates; and b) the client’s request to define guidelines to manage the urban cultural heritage during a time of transition while awaiting the results of UNESCO candidacy. This unique fact denotes a sensitivity and long-term policies regarding the cultural heritage which view the recovery of the urban historical heritage, assuming the cultural component as the fourth dimension of sustainability. The methodological approach, the results of the research, and design are organized on the dual urban and building scale to understand the structure and elements of the historical centre. The actions and interventions are differentiated with respect to urban fabric, building, archaeological good, and landscape and translate the strategies of the guidelines into short-/mid-/long-term design actions.

Most crops are fertilized with high amounts of nitrogen, and have an alarmingly low utiliza-tion efficiency. For this reason, the coordination between the fertilizer contribution and the ni-trogen requirements of the crop is very important. Therefore, the objective of this study was to determine the nitrogen use efficiency, and create new NUE indices that can determine and calculate the final destination of the assimilated nitrogen, for the formation and development of green bean plant organs, fertilized with molybdenum nanofertilizer applied foliarly and combined with soil fertilization of ammonium nitrate. The plants were grown in a greenhouse covered with anti-aphid mesh and irrigated with nutrient solution. Three sources of foliar Molybdenum (Nano fertilizer, Molybdenum Chelate and Sodium Molybdate) were applied in four doses of 0, 5, 10 and 20 ppm Mo, complemented with edaphic fertilization of NH4NO3 (0, 3, 6 and 12 mM of N). As results, the NUE indices showed that with the application of the nanofertilizer, the total biomass production increased 41.65% more than with the application of the chelate, and 36.84% more than with the application of molybdate. Finally, it is con-cluded that the use of NUE indices is an important approach that evaluates the fate of nitro-gen and accurately estimates plant yield.

We conducted a retrospective evaluation of the clinical outcomes and prognostic factors in patients with non-metastatic castration-resistant prostate cancer (nmCRPC) treated with first-line androgen receptor signaling inhibitors (ARSI) in real-world clinical practice in Japan. Between 2012 and 2023, a total of 127 consecutive patients with nmCRPC received ARSI treatment. Overall survival (OS), metastatic-free survival (MFS), and prostate-specific antigen progression–free survival (PSA-PFS) from ARSI initiation were assessed using Kaplan–Meier methodology. Clinical factors associated with OS in nmCRPC were analyzed using the Cox proportional hazards model. Among the patients, 72, 26, 12, and 17 received enzalutamide (ENZ), abiraterone (ABI), apalutamide (APA), and darolutamide (DARO) as first-line therapy. The median OS and MFS for all patients were 79.0 and 42.0 months, respectively. Median PSA-PFS was 27.0, 20.0, 10.0, and 14.0 months for patients treated with ENZ, ABI, APA, and DARO, respectively (p = 0.33). Multivariate analysis revealed that a baseline PSA level ≥3.67 ng/ml at ARSI initiation was significantly associated with poorer OS (p = 0.002). ARSI demonstrated favorable efficacy in nmCRPC patients. There were no significant differences in clinical outcomes among different types of ARSI therapy for nmCRP. Elevated baseline PSA at ARSI initiation was significantly associated with poorer OS.

The ever-increasing demand for seafood-containing diets, especially fish, primarily due to their superior nutritional value, has impacted the availability of wild stocks, necessitating the focus on other underutilised aquaculture species. In this study, the proximate and fatty acid (FA) composition of the indigenous black South African mussel (Choromytilus meridionalis) was investigated. The effects of the hot-smoking as preservation method on the proximate composition for mussels were assessed using the standard AOAC protocols; while gas chromatography-flame ionised detection (GC-FID) was used to determine the FA content. The moisture level in hot-smoked mussels significantly (P

Background: Acute kidney injury (AKI) and contrast-induced nephropathy (CIN) are common complications following percutaneous coronary intervention (PCI) or coronary angiography (CAG), presenting significant clinical challenges. Machine learning (ML) models offer promise for improving patient outcomes through early detection and intervention strategies. Methods: A comprehensive literature search following PRISMA guidelines was conducted in PubMed, Scopus, and Embase from inception to June 11, 2024. Study characteristics, ML Models, performance metrics (AUC, accuracy, sensitivity, specificity, precision), and risk of bias assessment using the PROBAST tool were extracted. Statistical analysis used a random-effects model to pool AUC values, with heterogeneity assessed via the I² statistic. Results: From 431 initial studies, 14 met the inclusion criteria. Gradient Boosting Machine (GBM) and Support Vector Machine (SVM) models showed the highest pooled AUCs of 0.87 (95% CI: 0.82-0.92) and 0.85 (95% CI: 0.80-0.90), respectively, with low heterogeneity (I² < 30%). Random Forest (RF) had a similar AUC of 0.85 (95% CI: 0.78-0.92) but significant heterogeneity (I² > 90%). Multilayer Perceptron (MLP) and XGBoost models had moderate pooled AUCs of 0.79 (95% CI: 0.74-0.84) with high heterogeneity. RF showed strong accuracy (0.83, 95% CI: 0.70-0.96), while SVM had balanced sensitivity (0.69, 95% CI: 0.63-0.75) and specificity (0.73, 95% CI: 0.60-0.86). Age, serum creatinine, left ventricular ejection fraction, and hemoglobin consistently influenced model efficacy. Conclusions: GBM and SVM models, with robust AUCs and low heterogeneity, are effective in predicting AKI and CIN post-PCI/CAG. RF, MLP, and XGBoost, despite competitive AUCs, showed considerable heterogeneity, emphasizing the need for further validation.

Arsenic trioxide (ATO) has been shown to inhibit pancreatic cell growth in vitro and to promote the inhibitory effects of gemcitabine on pancreatic cancer in vivo. However, the high toxicity of ATO associated with the required high doses and indiscriminate targeting has limited its clinical application. This study aimed to determine whether coupling arsenic to a tumor homing peptide would increase the inhibitory potency against pancreatic cancer cells. The effects of this peptide-linked arsenic compound and ATO on pancreatic cancer growth were tested in vitro and in a mouse model. The data demonstrated that the peptide-linked arsenic compound inhibited pancreatic cancer cell growth more potently with IC50 values 10 times lower than ATO. Like ATO, the peptide-linked compound induced cell death and cell cycle arrest. More importantly, the peptide-linked arsenic compound inhibited pancreatic cancer growth in mice and enhanced the inhibitory effect of gemcitabine on pancreatic cancer growth at 2 times lower molar concentration than ATO. These results indicate that the peptide-linked arsenic compound inhibited pancreatic cancer more potently than ATO and suggest a potential clinical use for the combination of gemcitabine with the peptide-linked arsenic compound for the treatment of pancreatic cancer.

South Africa (SA) is grappling with a severe food insecurity crisis exacerbated by socioeconomic challenges. This resulted in the Department of Basic Education (DBE) advocating for the establishment of vegetable gardens at schools. However, information on the suitability of the soils in SA for sustainably growing Beetroot is unavailable. This study aimed to assess the suitability of soils for sustainable Beetroot production at various schools in the Kgakotlou circuit. Four Secondary Schools were selected: Mothimako, Madipoane, Klaas Mothapo and Phomolong. A detailed soil survey was carried out to study soils in vegetable gardens. Soil samples were collected for laboratory analysis of physicochemical properties. The soil suitability was evaluated using the physicochemical properties of the soils and optimal soil requirements for Beetroot production. We found various soils in the schools, including Cambisols (Hutton and Nkonkoni), Leptosol (Glenrosa), Plinthosol (Westleigh), and Acrisols (Tshiombo and Tubatse). Portions of the gardens on Hutton and Westleigh soil were moderately suitable (S2), limited by electrical conductivity (EC). Meanwhile, portions of Tshiombo, Tubatse, and Nkonkoni were marginally suitable (S3), limited by pH and EC. Portions on Glenrosa soil at Klaas Mothapo and Phomolong were not suitable (NS) and were limited by shallow depth, soil pH and EC. The results reveal the importance of considering soil suitability before establishing vegetable gardens in school settings. Indexing soil suitability using the physicochemical properties of soil resources for sustainable beetroot production is proposed for schools in the Kgakatlou circuit and other parts of SA.

Considering that emotional events diversify as one ages, this study formulates the Salient Episodic Memory Aggregation Hypothesis, which claims that aging induces homogenization of episodic memory and consequently increases the salience of emotional episodes. To test this hypothesis, the study focused on sadness episodic memory and conducted a web-based survey and a combined analysis consisting of natural language processing, machine learning, and network graph analysis. A sample of 2,954 adults aged between their 20s and over 70s participated in this study. They were asked to describe a sad event they had experienced and assess the psychological properties of the recalled episodes. After isolating and lemmatizing episodic words using natural language processing, vocabulary frequency was counted for each generation, and network graph analysis based on machine learning was performed to compare the structures of sadness episodes between generations. As a result, there were mainly two types of episodic words for which frequencies either declined or increased with age. The network structures of episodic words for the older generations possessed higher proximity (shortest path length) to higher concentrations of episodic words. These findings support the current hypothesis, indicating that the nature of sadness episodes differ between generations, and that older people have more aggregated episodic memory structures.

Prostate cancer (PCa) ranks as the second most fatal and sixth most prevalent cancer among males globally. This study focuses on leveraging deep learning networks to detect the Gleason grading of prostate cancer from histopathology images stained with Hematoxylin and Eosin (H&amp;E). Six pathologists annotated the images, resulting in six distinct labels for each input image. A common ground truth label was established through majority voting approach. Subsequently, the dataset was trained using architectures: UNeT, UNeT++, DeepLabV3, DeepLabV3+, and GAN based segmentation network. Notably, GAN based network demonstrated superior performance, achieving an F1-score of 0.872 and a Jaccard Index of 0.777, outperforming the other architectures considered in this study.

This paper aims to study and analyze the effect of the flow rate and amplitude of walling waves on the peristaltic flow of Jeffrey’s fluid through an irregular channel. In addition, it analyses streamlined patterns and their local and global bifurcation flow. The theory of dynamical systems is used to explore the position of critical points and their bifurcation. Numerical and analytical methods are presented to display effective changes in amplitude and rate of the flow on the transport of fluid. Three types of streamline patterns occur backward, trapping and augmented flow in the channel through movement due to changes in the value rate parameters.

The Latin American Giant Observatory (LAGO) is a ground-based extended cosmic rays observatory designed to study transient astrophysical events, the role of the atmosphere on the formation of secondary particles, and space-weather-related phenomena. With the use of a network of Water Cherenkov Detectors, LAGO measures the secondary particle flux, a consequence of the interaction of astroparticles impinging on the Earth with the atmosphere. These interactions yield a flux of secondary particles that can be grouped into three distinct basic constituents: the electromagnetic, muonic, and hadronic components. In this work we extend our previous research by using detailed simulations of the expected atmospheric response to the primary flux and the corresponding response of our WCDs to atmospheric radiation. After implemented OPTICS, a density-based clustering algorithm, to identify patterns in data collected by a single WCD, we have further refined our approach by implementing a method that categorizes and differentiates particle groups using advanced unsupervised machine learning techniques. Our analysis demonstrates that applying our enhanced methodology can accurately identify the originating particle with a high degree of confidence on a single-pulse basis, highlighting its precision and reliability. These promising results suggest the feasibility of implementing machine-learning-based models throughout LAGO distributed detection network and other astroparticles observatories for semi-automated, onboard and real-time data analysis. When a particle enters a Water Cherenkov Detector (WCD), it generates a measurable signal characterized by unique features correlating to the particle’s type and the detector’s specific response. The resulting charge histograms from these signals provide valuable insights into the flux of primary astroparticles and their key characteristics. However, this data is insufficient to effectively distinguish between the contributions of different secondary particles. This research extends our previous investigations, wherein we implemented OPTICS, a density-based clustering algorithm, to identify patterns in data collected by a single WCD. We have further refined our approach by implementing a method that categorizes and differentiates particle groups using advanced unsupervised machine learning techniques. This methodology facilitates the differentiation among particle types and utilizes the detector’s nuanced response to each particle type, thus pinpointing the principal contributors within each group. In this work, we utilize OPTICS to analyze simulated data, further validating the proposed method. We created a simulated dataset by combining the outputs of the ARTI and MEIGA frameworks. This dataset simulates the expected WCD signals produced by the flux of secondary particles during one day at the LAGO site in Bariloche, Argentina, situated at 865 meters above sea level. To achieve this, real-time magnetospheric and local atmospheric conditions for February and March of 2012 were analyzed, and the resultant atmospheric secondary-particle flux was integrated into a specific MEIGA application featuring a comprehensive Geant4 model of the WCD at this LAGO location. The output from MEIGA was modified for effective integration into our machine learning pipeline. Our analysis demonstrates that applying our enhanced methodology can accurately identify the originating particle with a high degree of confidence on a single-pulse basis, highlighting its precision and reliability. These promising results suggest the feasibility of implementing machine-learning-based models throughout the LAGO distributed detection network for semi-automated, onboard and real-time data analysis. Our analysis demonstrates that OPTICS can accurately identify the originating particle with a high degree of confidence on a single-pulse basis, highlighting its precision and reliability. These promising results suggest the feasibility of implementing machine-learning-based models throughout the LAGO distributed detection network for semi-automated, onboard data analysis.

Background: Endoplasmic reticulum (ER) stress is a significant player in the pathophysiology of various neurodegenerative and neuropsychiatric disorders. Despite the established link between ER stress and inflammatory pathways, there remains a need for deeper exploration of the specific cellular mechanisms underlying ER stress-mediated neuroinflammation. Methods: This study aimed to investigate how severity of ER stress can impact the release of proinflammatory cyto-kines IL-6 and IL-8 from astrocytes and microglia, comparing the effects with those induced by well-known immunostimulants - tumor necrosis factor alpha (TNF-α) or lipopolysaccharide (LPS). Results: Mild ER stress has a distinct effect on the cytokine release compared to more intense stress levels, i.e. diminished IL-6 production was accompanied by an increase in IL-8 level, which was significantly more pronounced in astrocytes than in microglia. On the contrary, prolonged or more severe ER stress induced inflammation in glial cells, leading to a time- and concentration-dependent buildup of pro-inflammatory IL-6 but unlike inflammatory agents, ER stress inducer diminished IL-8 secretions by glial cells. Conclusion: The differences could hold importance in identifying ER stress markers as potential drug targets for treatment of neurodegenerative diseases or mood disorders, yet it requires confirmation in more complex animal studies.

In today's volatile and competitive business landscape, achieving synergy between supply chain agility and marketing flexibility is imperative for organizations striving to enhance resilience and maintain competitiveness. This qualitative study explores the integration of these strategic elements and their impact on organizational performance in turbulent markets. Semi-structured interviews were conducted with key stakeholders from diverse industries to capture insights into adaptation strategies, challenges, and outcomes associated with aligning supply chain agility and marketing flexibility. Findings reveal that supply chain agility, characterized by rapid response capabilities to disruptions and fluctuating demands, is essential for optimizing operational efficiency and maintaining continuity in uncertain environments. Meanwhile, marketing flexibility enables organizations to adjust strategies swiftly based on real-time market insights, enhancing customer engagement and market responsiveness. The study identifies organizational silos, resistance to change, and technological limitations as primary barriers to achieving seamless integration. Benefits of synergy include improved customer satisfaction, accelerated time-to-market for new products, and enhanced competitive advantage through personalized marketing strategies and optimized resource allocation. Moreover, organizations that effectively integrate supply chain agility with marketing flexibility reported greater innovation, employee satisfaction, and sustainable growth.

Drawing from literature and Geert Hofstede’s cultural dimensions, this study delves into the impact of cultural factors on family structures, roles, and relationships. Ghana and Latvia have different cultural and social orientations that influence family dynamics. Through a comparative lens, this paper will contribute to understanding how a country’s culture influences family dynamics, highlighting the influence of Power Dynamics of parenting style and Individualism vs. Collectivism on interaction levels within the family.

Online food delivery services are rapidly growing in popularity, making customer satisfaction critical for company success in a competitive market. Accurate delivery time predictions are key to ensuring high customer satisfaction. While various methods for travel time estimation exist, effective data analysis and processing are often overlooked. This paper addresses this gap by leveraging spatial data analysis and preprocessing techniques to enhance the data quality used in Bayesian models for predicting food delivery times. We utilized the OSRM API to generate routes that accurately reflect real-world conditions. Next, we visualized these routes using various techniques to identify and examine suspicious results. Our analysis of route distribution identified two groups of outliers, leading us to establish an appropriate boundary for maximum route distance to be used in future Bayesian modelling. The spatial analysis revealed that these outliers were primarily deliveries to the outskirts or beyond the city limits. By refining the data quality through these methods, we aim to improve the accuracy of delivery time predictions, ultimately enhancing customer satisfaction.

Objective: To explore the functions that physical activity (PA), life satisfaction, and self-efficacy have in the process of coping with anxiety among Chinese college students, and to explore the mediating role of life satisfaction and self-efficacy in this process. Methods: Participants were 358 college students (186 males, 172 females, mean age 20.88, SD=±1.80). Psychosocial tests including the Physical Activity Rating Scale (PARS-3), College Student Life Satisfaction Scale (CSLSS), General Self-Efficacy Scale (GSES), and Generalized Anxiety Disorder Scale (GAD-7) were completed. Correlations between variables were calculated using Pearson's test. The mediation model was tested using the SPSS 26.0 PROCESS macro and regression bootstrap. Results: Physical activity showed a negative correlation with anxiety (β= -0.1617, p < 0.001), life satisfaction and self-efficacy played a role in the relationship between physical activity and anxiety, and, more importantly, physical activity affected anxiety through the parallel mediating effects of life satisfaction and self-efficacy, with a total mediating effect of 55.34%. Conclusion: By increasing college students' participation in physical activity, it helps to promote the growth of their life satisfaction and self-efficacy, which is the key to reducing anxiety and promoting college students' mental health.

In the Lemongrass (Cymbopogon citratus), the investigations showed a wide range of active molecules their biological properties. However, most of these studies were conducted on the wid varieties, while cultivated plan addressed. This study aimed to characterize the biomolecules and biological activities of Lemongrass growing us African conditions sons in in Marocco. Marocco. Phenolic compound profiles of aqueous (AE) E) ethanol ethanol (EE), (EE), and methanol (ME) extract: fractions were obtained with steric exclusion chromatography on Sephadex 050 gel and identified by LC-MS/MS polyphenols (TPC), flavonoids (TFC), and antioxidant activities (FRAP: scavenging value and TAC: Total Antioxidant C the fraction were evaluated as well as the antimicrobial activity Obtained results showed that the ME contained e compounds (ie. Apigenine-7-0-rutinoside and myricitine-3-0-rutinoside). The AE showed the presence of five mole kaemiferol-3-0-glucuronide), while EE showed the presence of three molecules (Le. Quercetine-3-0-rutinoside). Reg chemical characterization, the rization, e highest value of Total phenolic content (TPC) was obtained in conten btained in AE ΑΕ (25) (4.60-0.29 mg highest value of Total flavonoids content (TFC) was obtained Ined in ME (29) (0.7±0.08 mg/g). Concerning the antioxide the highest FRAP was obtained in ME (29) (97.89%) and the highest total antioxidant capacity (TAC) was obtained (89.89%) Correlation between FRAP, TPC, and TFC was noted poly in fractions of AE and ME. All tested extracts of and their fractions showed a significant antimicrobial effect. The lowest minimum inhibitory concentration (MIC) wa for ME against E. col. Extracts biological activities and their fractions were governed by their active molecules. Ther new and clarify a novel aspect of bioactive molecules in the extracts of cultivated C. citratus Equaly, throughout this we clarified the relationship between identified molecules and their biological properties including antioxidant and comparative studies new activities, which is new for the study area. This study is suggested to be a reference. assays of other biological activities for the study plant

Multicropping can solve the energy and GHG balance problems, but the emergence, development and productivity of such mixed crops are at risk due to uneven distribution of precipitation. For this reason, investigations were performed at the Experimental Station of Vytautas Magnus University, Lithuania. Single maize crop was compared with Crimson/red clover, Persian clover, and alfalfa intercropped maize cultivations. Results showed that under arid conditions, the intercrops biomass was about 4 times less than under humid. Humid conditions were less suitable for maize and when growing with intercrops they produced about 3-5 t ha-1 less dried biomass, and when growing sole - about 6 t ha-1 less biomass than in arid conditions. Due to the higher yield of maize biomass in arid season, better energy indicators of the crop were obtained in arid conditions than in humid. The difference between net energy was about 122-123 MJ ha-1 in all treatments, except for the maize crop with intercropped alfalfa, where the difference was 62 MJ ha-1. All tested technologies were environmentally friendly, CO2 equivalent varied between treatments from 804 to 884 kg ha-1. Uneven distribution of precipitation during vegetative season makes us think about the improvement of intercropping technologies. Sowing intercrops at the same time with maize could improve its germination but increase the problem of weed spread.

In the contemporary era, youthful and healthy skin is a pivotal determinant of beauty. Choices pertaining to one's dietary and lifestyle practices wield substantial influence over skin health. Currently, the focal point of attention lies in strategies to delay skin aging and maintain skin quality. Remarkably, the skin, the body's largest organ, serves as the primary defense barrier against external elements. Skin aging encompasses intrinsic and extrinsic categories, both susceptible to genetic, lifestyle, and environmental factors. Given the strides in science and technology, the pursuit of effective and safe interventions for skin aging assumes paramount importance. Thus, this review delves into the intricate relationship between diet, lifestyle, and skin aging, culminating in an exploration of the crucial role played by excess iron in this intricate nexus. Understanding these dynamics holds promise for advancing our knowledge of skincare and the quest for timeless vitality.

Double-walled carbon nanotube-yttria-stabilized ZrO2 nanocomposites are prepared by a mixing route followed by Spark Plasma Sintering. Incorporation of carbon at contents higher than 2 wt.% results in significantly lower friction coefficients, both against alumina and steel balls. Double-walled carbon nanotubes improve wear resistance and reduce friction without severe damage, contrary to multi-walled carbon nanotubes.

The Theory of differences between elements explains the reasons for the differences in physical concepts between different elements, such as quantum physics and the Theory of general relativity, being explained through observations. Thus, it is possible to conclude from the observations that the differences are motivated by the reactions between the elements, by the composition of the elements, and by the influence of the spaces that promote losses and gains of characteristics; therefore, there is no general similarity between quantum physics and the general Theory of relativity. The study aims to understand the elements and their physical concepts that make up the Universe.

We introduce a novel algebraic structure, termed algebra B, which generalizes Lie algebras through the definition of a non-associative and unital algebra. We demonstrate that algebra B retains essential properties such as bilinearity and antisymmetry, and satisfies both the Jacobi and Malcev identities; this occurs when the product operations of Lie and Malcev algebras are derived from the product operation defined in our algebra. By examining the connections between algebra B, Malcev algebras, and Lie algebras, we establish that algebra B effectively generalizes these structures. Furthermore, we show that algebra B can generate complex entities with a novel structure distinct from those currently known. Our findings lay the groundwork for future investigations into the practical applications and further theoretical development of this new algebraic framework.

This study aimed to translate and validate the Genomic Nursing Concept Inventory (GNCI) in Greek, analyze the genomic knowledge of nurses in Crete, Greece, and explore potential factors that could affect it. This cross-sectional study included 324 nurses from public hospitals and primary care units between July and December 2022. The GNCI is a 31-item questionnaire that evaluates genomic nursing concepts, but it has not been translated and validated in Greek. The translation process included independent forward translations, reconciliation, and back-translation. To evaluate internal consistency, Cronbach’s alpha was used, and Confirmatory Factor Analysis (CFA) was conducted to determine the fit of the model. Multiple linear regression analysis was performed to examine the associations between the demographic variables and GNCI scores. The internal consistency of the GNCI was acceptable (Cronbach’s alpha= 0.622). The CFA indicated that the one-factor model had an adequate fit (SRMR = 0.076, CD = 0.677, CFI = 0.744). The mean GNCI score was moderate (0.35±0.14). Regression analysis suggested that only gender could affect GNCI scores, with female nurses scoring higher than male nurses (p&gt;0.001). In conclusion, the Greek version of the GNCI is a reliable tool for assessing genomic knowledge among Greek nurses.

Introduction: The escalating morbidity, mortality, and healthcare costs associated with invasive candidiasis pose significant challenges in pediatric intensive care units (PICUs). Conventional diagnostic methods fall short in effectiveness, while various risk factors exacerbate the prevalence of these infections. This study introduces a novel model that amalgamates the Candida Score with key predictors to enhance the specificity and applicability of mortality risk assessments for pediatric patients with fungemia. Methods: This retrospective cohort study aimed to develop an integrated model for estimating mortality risk in children with fungemia in PICUs. We constructed and evaluated multiple predictive models using the Candida Score and other relevant clinical and laboratory variables. The discriminative abilities of the models were assessed using the area under the receiver operating characteristic curve (AUC). Results: The study cohort comprised 85 pediatric patients admitted between 2016 and 2020, with a median age of 6 months and a male predominance of 62.4%. The mortality rate was 45.9%. Candida albicans was the most prevalent causative agent, accounting for 37.55% of fungemia cases. Multivariable Logistic regression revealed the duration of mechanical ventilation, and the Candida Score were significant predictors of mortality. Each additional day of ventilation increased mortality odds by 11.5% (OR = 1.115, 95% CI: 1.025-1.212, p = 0.011), while a higher Candida Score more than doubled the odds (OR = 2.205, 95% CI: 1.359-3.578, p = 0.001).The Random Forest predictive model demonstrated superior discriminative performance, with an AUC of 0.838 (95% CI: 0.738-0.917), outperforming Gradient Boosting and Logistic Regression models, which had AUCs of 0.7759 (95% CI: 0.667-0.877) and 0.7085 (95% CI: 0.589-0.813), respectively. Although the internal validation yielded satisfactory results, external validation is warranted. Conclusion: This study presents an innovative approach for accurately assessing the risk of mortality due to fungemia in PICU patients by integrating the Candida Score with critical predictors. The Random Forest model emerged as the most effective predictive tool due to its exceptional discriminative ability.

Existing methods for simulating missile dynamics and training often rely on three degrees of freedom (3DOF) motions, limiting their ability to represent the complex maneuvers and targeting strategies of modern missiles. This paper proposes integrating virtual reality (VR) technology with six degrees of freedom (6DOF) dynamics to enhance the accuracy and efficiency of missile simulation and training. By incorporating 6DOF dynamics, simulations can capture the full range of missile motion, providing a comprehensive understanding of their capabilities and limitations. Through VR, users can immerse themselves in realistic missile scenarios, interact with dynamic behaviors in real-time, and refine their targeting and interception skills. The integration of VR with 6DOF dynamics also facilitates real-time feedback and evaluation, enhancing training efficiency and proficiency in missile operations. This approach aims to revolutionize missile training by bridging the gap between traditional simulation methods and real-world dynamics.

To identify the effect of frailty on loneliness of older adults receiving home care, considering their socioeconomic and homebound status. This cross-sectional study enrolled 218 individuals aged ≥65 years receiving home-based health services “Help at Home” in the Region of Evrytania, Greece, after an open invitation by Municipality authorities from March to June 2022. Tilburg Frailty Indicator (TFI) was used for the evaluation of frailty, UCLA Loneliness Scale version 3 for loneliness and social isolation was accessed through five questions (living alone, frequency of interaction with children, relatives, friends, and participation in social organizations). The mean age of the participants was 81.48 ± 9.06, 61.9% were female, 54.1% experienced high levels of loneliness (UCLA-3 mean 45.76 ±11.10 [range 20-68]), and 46.3% of the participants identified as socially isolated. Also, 58.3% of the individuals were classified as frail (TFI mean 5.95 ± 3.07, [TFI range 0-13], with 57.3% experiencing physical frailty, 43.6% psychological frailty, and 27.1% social frailty. An analysis of covariance (ANCOVA) placing UCLA-3 as the dependent variable revealed that loneliness and across all domains of TFI were significantly higher in participants with frailty (total frailty [yes] 49.27 vs. [no] 40,87 p &lt;0.001) particularly, (physical frailty [Yes]=48.99 vs. [No]=41.42, p &lt;0.001, psychological: 48.60 vs. 43.57 p &lt;0.001 and social: 53.38 vs. 42.94 p &lt;0.001) compared to non-frail individuals, even after adjusting for potential confounding effects (covariates: gender, age, marital status, family status, living status, educational level, annual income, chronic diseases, homebound status, and social isolation). Our data analysis confirmed that frailty is a significant risk factor for higher levels of loneliness among older adults who received home-based healthcare.

This study explores the impact of regular physical exercise on the quality of life and body image among Para-athletes, emphasizing the necessity of such activities for physical, social, and psychological health. This qualitative study employs content analysis and ethnomethodology to evaluate seven Para-athletes from the Navy's Paralympic Project, using focus group interviews to assess their perceptions. The findings reveal that participation in structured sports programs positively influences body image and quality of life, leading to improved performance in training, social interactions, and competitive events. The analysis suggests that motivation and self-esteem are fundamental to the sporting success of Paralympic athletes. Both external and internal motivations are crucial for sustaining athletic careers and overcoming challenges. Self-esteem enables athletes to remain confident in their abilities, even after setbacks.

Objective: This study aims to investigate the relationship between sports psychological capital, coach leadership behavior, and satisfaction among middle school students in the 2023 sports college entrance examination in Chongqing. Methods: Using the structural questionnaire design, this paper carries out a questionnaire survey on the candidates who come to participate in the volleyball specialty college entrance examination in Chongqing, the corresponding database was established and the data were statistically processed by spss21.0 and amos18.0. Results: 1) there was a significant positive correlation between sports psychological capital, coach leadership behavior and examinees satisfaction; 2) sports psychological capital and coach leadership behavior had a certain influence on five dimensions of examinees' personal treatment, personal performance, team integration, team interaction and support from relatives and friends; 3) The sense of self-efficacy in sports psychological capital and coach's leading behavior are the most important to examinees' satisfaction; 4) Both coaches' leadership behavior and sports psychological capital can directly affect examinees' satisfaction, but sports psychological capital is the most important. It can not only directly affect examinees' satisfaction, but also act as an intermediary between coaches' leadership behavior and examinees' satisfaction. Conclusion: Sports College Entrance Examination Students can improve training satisfaction and sports performance by strengthening sports psychological capital training and perceiving coach's leadership behavior; In the leadership behavior of coaches, we should emphasize training and appropriately weaken authoritative teaching, while the training of sense of hope and toughness should be highlighted in sports psychological capital.

Mental health in Puerto Rico is a complex and multifaceted issue that has been shaped by the island’s unique history, culture, and political status. Recent challenges, including disasters, economic hardships, and political turmoil, have significantly affected the mental well-being of the population coupled with the limitations in the accessibility of mental health services. Puerto Rico has fewer mental health professionals per capita than any other state or territory in the United States. This comprehensive review examines the impact of disasters on mental health and mental health services in Puerto Rico. Given the exodus of Puerto Ricans from the island, the review also provides an overview of mental health resources available on the island as well as the continental United States. The review identifies efforts to address mental health issues, with the intent of gaining a proper understanding of the available mental health services, key trends, as well as observable challenges and achievements within the mental health landscape of the Puerto Rican population.

Dehydroepiandrosterone (DHEA) is considered an endogenous steroid hormone precursor, and 17-ß Estradiol (E2) is one of the estrogen steroid hormones. Of the thirteen known human cytosolic sulfotransferases (SULTs), SULT2B1a has been shown to be expressed in steroid hormone-responsive tissues such as the prostate, ovary, and placenta, as well as the fetal brain. Previous studies have demonstrated that SULT2B1a is capable of sulfating 3β-hydroxysteroids such as DHEA and pregnenolone. The present study aimed to investigate the effects of human SULT2B1 SNPs on the enzymatic characteristics of SULT2B1a allozymes in mediating the sulfation of DHEA and E2. To inspect the effects of single nucleotide polymorphisms of the SULT2B1 gene on the sulfation of DHEA and E2 by SULT2B1a allozymes, 13 recombinant SULT2B1a allozymes were produced, expressed, and purified using established procedures. 13 SULT 2B1a nonsynonymous missense coding SNPs (cSNPs) were selected among numerous identified human SULT 2B1a SNPs by a comprehensive database search. The corresponding cDNAs, packaged in pGEX-2TK expression vector, and encoding the selected 13 SULT2B1a allozymes, have been generated by performing site-directed mutagenesis. These were then bacterially expressed in BL21 E. coli cells and purified using glutathione-Sepharose affinity chromatography. The purified allozymes were tested for their ability to sulfonate DHEA and E2. In terms of the kinetic parameters, the wild-type SULT2B1a exhibited higher enzyme affinity towards DHEA than with E2. In comparison with the wild-type SULT2B1a, the purified allozymes displayed differential sulfating activities towards DHEA and E2. Accordingly, these findings indicate an apparent effect of SULT2B1 cSNPs on the sulfating activities of SULT2B1a allozymes toward DHEA and E2, and may provide for a better understanding of the pharmacokinetics of DHEA and E2 in individuals with differing SULT2B1a genotypes.

Gemcitabine (2',2'-difluoro-2'-deoxycytidine), a widely used anticancer drug, is considered as a gold standard in treating aggressive pancreatic cancers. Gamma-proteobacteria that colonize the pancreatic tumors contribute to chemoresistance against gemcitabine by metabolizing the drug to a less active, deaminated, form. The gemcitabine transporters of these bacteria are unknown to date. Furthermore, there is no complete knowledge on the gemcitabine transporters in Escherichia coli or any other related proteobacteria. In this study, we investigate the complement of gemcitabine transporters in E. coli K-12 and two common chemoresistance-related bacteria (Klebsiella pneumoniae, Citrobacter freundii). We find that E. coli K-12 has two high-affinity gemcitabine transporters with distinct specificity properties, namely NupC and NupG, whereas the gemcitabine transporters of C. freundii and K. pneumoniae include the NupC and NupG orthologs, indistinguishable functionally from their counterparts, and, in K. pneumoniae, one additional NupC variant, designated KpNupC2. All these bacterial transporters have higher affinity for gemcitabine than their human counterparts. The highest affinity (KM 2.5-3.0 μΜ) is exhibited by NupGs of the Bacteria-specific Nucleoside-H+ Symporter (NHS) family followed by NupCs (KM 10-13 μΜ) of the Concentrative Nucleoside Transporter (CNT) family, 15-100 times higher than the affinities reported for the human gemcitabine transporter hENT1/SLC29A1 which is primarily associated with gemcitabine uptake in the pancreatic adenocarcinoma cells. Our results offer a basis for further insight into the role of specific bacteria in drug availability within tumors and understanding the structure-function differences of bacterial and human drug transporters.

Diabetes is one of the metabolic syndromes that demands the great concern affecting millions of people all over the world. Viral infections were also considered as responsible for diabetes. Though, variety of medications for prevention and treatment of diabetes are available, numerous limitations are also prevailing that cannot be neglected. Precise drug-targetability, controlled drug-release, oral bioavailability, minimizing side effects are a few to consider. To address most of these shortcomings of traditional drug-delivery models, nanoformulation has been employed therein a wide range of nanoformulation models are developed. The pharmacology of a drug can be greatly enhanced through nanoformulation models in diabetes treatment in terms of enhanced bioavailability, prolonged and sustained drug-lease, maintain maximum drug concentration in serum, higher intestinal absorption, and protection from enzymatic degradation. In this review work, recently designed nanoformulation models for efficient insulin delivery and the other properties concerning diabetes such as reducing blood glucose level, total cholesterol, triglycerides, lipid profile, wound healing, elevating antioxidant enzymes etc. are discussed. Classification of the nanoformulation models is done based on the nature of the fabricating material employed in nanoformulation. This review may be helpful in designing a more efficient nanoformulation model for diabetes treatment.

Background and objectives: Main aim of the study is to analyze the outcomes of NSTEMI admissions and testing the relevance of TIMI as a risk score in a real-world setting. Also looking at any potential social or health care disparities involved with outcomes of NSTEMI admissions. The study also investigates factors associated with mortality in NSTEMI admissions and correlation between in-hospital mortality and heart catheterization. . Materials and Methods: NSTEMI admissions were analyzed using the National Inpatient Sample. TIMI scores were calculated in the admissions and association between all-cause mortality and calculated TIMI score >=2 was analyzed. Difference in outcomes based on heart catheterization was studied in the subgroup with TIMI score >=2. Correlation between time to heart catheterization and all-cause mortality in NSTEMI admissions were analyzed. Results: No significant social or healthcare disparities were noted amongst outcomes for NSTEMI admissions. NSTEMI admissions with a calculated TIMI score >=2 had a statistically significant association with all-cause mortality during the admission. Prevalence of mortality among NSTEMI admissions with calculated TIMI score >2, who did not undergo heart catheterization was higher with statistical significance when compared to admissions that underwent heart catheterization. NSTEMI admissions with a calculated TIMI score >2 who underwent catheterization on or beyond the 4th day of hospitalization had statistically significant association with all-cause mortality during the admission. Age at admission, presence of CKD and CHF were associated with mortality in NSTEMI admissions, with statistical significance. Keywords: NSTEMI; TMI score; heart catheterization

School bullying represents a widespread expression of violence in the peer context. Guided by the social-ecological model, this study investigated the longitudinal and transactional pathways linking domestic and neighborhood/community violence exposure (through direct victimization and witnessing), self-serving cognitive distortions (CDS), and school bullying perpetration. Furthermore, the cognitive desensitization hypothesis that the literature has supposed to develop in response to chronically violent contexts was examined. Two four‐wave cross-lagged panel mediation models were tested in a sample of 778 high school students (28.1% males; Mage [Time 1; T1] = 14.20, SD = 0.58). The results showed that both domestic and neighborhood/community violence exposure, as a victim and as a witness, respectively, were associated to self-serving CDs and bullying perpetration over time. Moreover, significant associations between CDs and bullying perpetration over time were found, with bidirectional effects for each of these longitudinal patterns. Finally, self-serving CDs were found to significantly mediate the relationships between both domestic violence victimization and community violence witnessing and school bullying perpetration. These findings highlight the need to consider school bullying as a social phenomenon stemming from a complex and bidirectional interplay between the individuals and the environments they inhabit confirming a basic postulate that “violence breeds violence”.

: This study aims at exploring Turkish consumers’ behaviors toward purchasing green fashion. A mixed-methods approach was used in this study. Six experts from the main brands in the fashion industry in Türkiye were interviewed. A total of 268 questionnaires were collected from Turkish consumers, and their responses were analyzed. The theory of planned behavior (TPB) informed the theoretical framework of this study. The main components of the TPB were extended to include perceived consumer effectiveness. A thematic analysis was conducted to analyze and code the interviews. To test the hypotheses, structural equation modeling (SEM) was conducted. The findings show that the key factors of the TPB, i.e., attitudes (ATTs), subjective norms (SNs), and perceived behavioral control (PBC), as well as perceived consumer effectiveness, significantly impact the intentions of Turkish consumers to purchase sustainable fashion. However, the results highlight some inconsistencies, gaps, and barriers that discourage the purchase intentions of consumers, including a lack of information, misinformation, greenwashing, green skepticism, a lack of trust, and the high cost of sustainable fashion.

Porcine pleuropneumonia (PPP) is one of the main causes leading to massive losses in the pig industry, with high economic impacts. Among different etiological agents, Actinobacillus pleuropneumoniae (APP) is responsible for severe fibrinous-necrotizing pleuropneumonia. A total of 19 different APP serotypes are currently recognized. This study aimed to identify APP serotypes isolated from pneumonic lesions in naturally infected and dead pigs in the Piedmont Region and to describe lesions. A total of 107 dead pigs with a suspected PPP diagnosis were included in this study. Lungs were evaluated using gross pathology scoring systems, APP isolation and serotypes identification by multiplex PCR were conducted. Gross lung lesions were mainly represented by fibrinous pneumonia and pleuropneumonia. APP was isolated in 21/107 (19.6%) samples. On the contrary, PCR indicated APP DNA presence in 53/107 (49.5%) of lung samples. The most observed serotypes were serotype 2 in 24/53 (45.3%) and serotype 6 in 13/53 (24.5%) samples. Moreover, multiplex PCR results suggested a coinfection of different serotypes in 5 samples. This study highlights the relevance of the different techniques application (i.e. bacteriological culture, PCR, gross and histopathology) for improving the identification of APP infections.

This study investigated the adaptability of Dunaliella salina to different salinity levels, with emphasis on growth, pigment concentration, and desalination potential. It was found that among the 21 salinity levels, salinity 75 produced consistently favorable results in cell count (13.08 x 10³ ± 1.41 x 10³ cells/mL), dry biomass (2.46 ± 0.06 g/L), pigment content (chlorophyll a = 97.5 ± 0.1 µg/L, chlorophyll b = 123.6 ± 0.3 µg/L), and desalination (9.32 ± 0.47 reduction). Therefore, salinity 75 was selected for the final trial (scale-up), which revealed unanticipatedly high cell counts (58.96 x 10³ ± 535.22 cells/mL), with dry biomass weight being statistically different (higher) than the expected (4.21 ± 0.02 g/L) (p<0.0001), most likely due to high cell count and energy reserve storage for high salinity adaption in the form of bio-compounds. Pigment growth continued (chlorophyll a = 95.4 ± 2.2 µg/L, chlorophyll b = 128.1 ± 5.1 µg/L), indicating pigment production under salt stress. Notably, desalination did not occur in this stage, possibly due to the necessity for a bigger initial inoculate, prolonged exposure or bioaccumulation becoming the prevailing mechanism over desalination. Nevertheless, the trial highlights D. salina's strong adaptation to various salinity levels. This suggests a promising future in halophyte research, particularly in understanding the mechanisms that prevent salt accumulation in cells and how to overcome this barrier. Additionally, these results suggest that microalgae could be a viable resource in saline-rich environments unsuitable for conventional agriculture, promoting industrial adaptation to adverse conditions.

This study presents an in-depth analysis of land use and land cover change on the Kerch Peninsula over a period spanning three decades. Utilizing convolutional neural networks alongside satellite imagery analysis, we have mapped and quantified the changes in land use and cover, revealing significant trends and transformations within the peninsula's landscape. The research aims to elucidate the interplay between anthropogenic activities, climatic variations, and policy interventions in shaping land cover dynamics, thereby providing insights into the environmental and socio-economic impacts of these changes. Our findings indicate a marked increase in urban expansion at the expense of natural ecosystems, including forests and wetlands, underscoring the urgent need for sustainable land management strategies. The study highlights the role of agricultural intensification and expansion in altering the peninsula's ecological balance and emphasizes the critical importance of integrating change analysis and prediction. By leveraging advanced remote sensing and GIS technologies, our analysis not only enhances the understanding of the complex dynamics driving land use and land cover change but also showcases the potential of predictive modeling in forecasting future land cover scenarios. The implications of this study extend beyond the Kerch Peninsula, offering valuable lessons for managing land use changes and conserving natural landscapes in similar regions globally.

In this research work the study of Buongiorno Model Darcy Forchheimer flow of Hybrid nanofluid flow on isothermal permeable stretch/shrink sheet with homogeneous and heterogeneous reaction is investigated. The effects of MHD, thermal radiation, viscous dissipation, Joule heating, and heat generation/absorption are taken into account. Hybrid nanofluids can act as a medium for heterogeneous-homogeneous reactions. The nanoparticles dispersed in the fluid can influence reaction kinetics and species transport, potentially, altering reaction rates and pathways. The applications of HNF in reactions, both homogeneous and heterogeneous, lie in leveraging their enhanced thermal properties, catalytic potential, and improved mixing capabilities to optimize reaction efficiency and control reaction conditions. Similarity transformation is used to convert a set of PDEs into a set of ODEs. HAM is used for the solution of the obtained ODEs system. In a heterogeneous reaction, the concentration gradient is amplified; in a homogeneous reaction, the impact is opposite. Moreover, at higher compositions of HNPs, the concentration and velocity rise while the temperature falls. Furthermore, as the values of homogeneous and heterogeneous reactions increase, the concentration falls. It is reliable with the idea that a greater reaction rate lowers the diffusion rate. Nevertheless, these parameters do not affect temperature or velocity.

The limited understanding of how digital platforms, especially the Metaverse, influence public perception and attitude towards sustainable fashion in large scaled markets such as China highlights a critical gap. This study aims to examine the perspectives and perception of the Chinese public regarding sustainable fashion in the Metaverse. Through content analysis, this study evaluated 3,889 Weibo posts from Shanghai Fashion Week 2024 to identify key sentiments and discussions on sustainable and digital fashion. Results indicate that 76.08% of the conversations centered on sustainable fashion, reflecting strong public commitment to environmental issues. The findings highlight characteristics of public perception towards the utilization of immersive technologies and underscore the Metaverse's potential as a platform for fostering environmental consciousness in the fashion industry. This research provides crucial insights for fashion brands looking to integrate sustainability into their digital strategies, addressing a significant gap in current literature and offering practical guidance for leveraging digital platforms to promote sustainable consumption.

In order to explore the effects of glutamate on the growth performance, antioxidant capacity and protein metabolism of juvenile Chinese mitten crab. 0%, 1% and 2% glutamate were supplemented to low protein (30%) and normal protein (35%) diets respectively. There were 5 parallel tanks in each treatment, and the feeding duration was 8 weeks. The results showed that dietary glutamate did not significantly affect the weight gain of Chinese mitten crab. Diets supplemented with 2% glutamate significantly decreased the crude protein of crabs. The T-AOC of crabs fed the 30% protein diets was significantly lower than crabs fed the 35% protein diets. At 30% protein level, the superoxide dismutase (SOD) activity significantly increased with the increase of glutamate content. Dietary glutamate significantly down-regulated the relative expressions of mTOR, PI3K, S6K1 and 4EBP at 35% protein level. In conclusion, dietary glutamate cannot significantly increase the growth of Chinese mitten crab, but it can improve the antioxidant capacity in Chinese mitten crab under low protein condition.

This study aimed to investigate the incidence of Esox lucius with bacterial septicemia in five fish ponds of Xinjiang, China. We analyzed the water quality of each fish pond as well as the clinical symptoms and pathological changes of fish with bacterial septicemia. Furthermore, we isolated and identified pathogenic bacteria from the liver, spleen, and kidney of the infected fish based on morphology and physiology, as well as using biochemical and molecular biology techniques. By detecting the water quality of the infected fish pond, the clinical symptoms and pathological changes of the infected fish were observed, pathogenic bacteria were isolated and purified from the liver, spleen, and kidney of the died illness fish. the pathogenicity of pathogenic bacteria was identified by morphology, physiology, biochemistry, and molecular biology, and the drug sensitivity of 16 antibiotics was studied by standard Kirby–Bauer disk diffusion method. The results showed that bacterial septicemia of Esox lucius occurred in water with high levels of ammonia nitrogen, nitrates, pH, total alkalinity, and total hardness, mainly caused by the mixed infection of Aeromonas hydrophila, Aeromonas veronii and Aeromonas sobria. A rapid multiplex PCR method for the detection of pathogenic Aeromonas hydrophila was established. The isolates were sensitive to enrofloxacin, flufenicol, and doxycycline and resistant to penicillin and neomycin. This study laid a foundation for the early prediction, warning, rapid diagnosis, and effective prevention and control of bacterial septicemia.

Nonischemic dilated cardiomyopathy (DCM) is a complex cardiovascular condition often characterized by genetic pathogenesis. Comprehensive genetic testing has become a crucial aspect of DCM diagnosis and management, offering insights into prognosis and the identification of at-risk individuals. This case series and mini literature review examines the diagnostic and therapeutic dimensions of DCM, emphasizing the role of genetic evaluation. We delve into distinct genetic pathways associated with DCM and their pathogenetic mechanisms, emphasizing the evolving significance of genetic markers, particularly in cases where arrhythmia risk is heightened. The historical reliance on cardiac morphology to subtype cardiomyopathies is being complemented by the identification of genetic variants, further refining DCM subtypes, and aiding in clinical management.The giant sarcomere protein, titin, is a pivotal determinant of cardiomyocyte stiffness and plays a crucial role in cardiac strain sensing. Titin's extensive size and complexity make it susceptible to dysregulation, which has far-reaching consequences in cardiac disorders. This case series with a literature review explores the molecular mechanisms governing titin-based forces in both health and disease. It highlights the influence of isoform diversity and post-translational modifications on myocardial stiffness and contractility. In the context of cardiac diseases, we discuss how titin properties are altered, focusing on changes in titin stiffness and protein quality control. Notably, we address the pathomechanisms associated with truncation in the titin gene (TTN) in human cardiomyopathy, shedding light on potential therapeutic approaches for conditions such as HFpEF and TTN-truncation cardiomyopathy.This comprehensive understanding of DCM and Titin’s role in cardiac physiology and pathology provides a solid foundation for addressing cases like that of our patients, who were presented with features of heart failure and arrhythmias. Despite immediate and extensive resuscitative measures, the patient's protracted response to the treatment raised questions about the potential underlying genetic factors contributing to their clinical presentation. These cases underscore the importance of genetic evaluation in unraveling the complexity of cardiomyopathies, ultimately enhancing our ability to manage and treat such challenging cases.

The excavations carried out by the Ephorate of Antiquities of Piraeus and Islands at the cemetery in the Phaleron Delta, Attica (late 8th - 4th century B.C.), have uncovered in total 1961 burials of various types, among which the Burial 923 is of particular importance as it is the only case of secondary cremation inside a copper alloy lebes. The use of such a valuable bronze vessel, symbolizing prestige, social status and wealth, as a cinerary urn indicates the importance of this find for the interpretation of issues related to the use of the cemetery and the ritual customs of the period and makes imperative the need to preserve the object despite its significant erosion. In this paper, we will present issues related to the lifting and conservation of the bronze vessel, that was found buried within a coastal and sandy depositional environment. Also, the condition of the vessel was scientifically investigated using optical microscopy (OM), portable X-ray fluorescence (p-XRF) and X-ray diffraction (XRD) techniques. The results showed a completely mineralized bronze artefact with tin corrosion products in the core, which indicate decuprification of the copper alloy.

The aim of this investigation is focused on the effects of hooked-end steel fibers on both fresh and hardened properties of modified self-compacting concretes (SCC). For this purpose, the steel fibers are associated with other residues contents (i.e. marble, granite and rubber). This concatenated materials contents constitutes a novelty since no investigations are reported. It is found that the increase of rubber content, a better ability to absorb energy is observed. This indicates that a good alternative of structural material is provided. Fresh properties are evaluated by using flow, T500 time, V-funnel, J-ring methods. The mechanical behavior is evaluated in terms of compressive strength, tensile strength, static and dynamic modulus of elasticity, and damping ratio. Experimental results of the water absorption, porosity and density are also attained. It is also found that a SCC mixture containing steel fiber, marble/granite residue and rubber content is a potential mixture to be considered when in SCC designing associated with improved damping ratio. Although the rubber content decreases the mechanical behavior and slump flow, the concatenated utilization of MGR and steel fiber contents provide a slight improve in the damping result. An environmental benefit can also be associated since the cement consumption is decreased with marble additions.

The vast network of interconnected devices of the Internet of Things poses significant security challenges, necessitating the upgrade of current wireless networks to the 6G standard and an improved intrusion detection system for host networks. Thus this article therefore underscores a game theory concept to analyze the security impediments in wireless communication systems, where a host network bandwidth is jeopardized by the intruder while acting as a legitimate user. While game theory can help with the impending security concerns, network slicing is saliently proposed for large and complicated networks, precipitating a layer wise fragmentation of the concerned network and effectively addressing the security issues in different layers of the IoT framework. However, with increasing network complexity, network security issues incorporating traditional measures become increasingly cumbersome. Therefore, this paper also briefly mentions some of the ML techniques that can be used to classify and segregate valid users from the compromised nodes in the host network. The paper discusses the potential of incorporating intelligence into wireless communication systems to enhance the host network security. The paper further aids in analyzing existing security issues in different layers of wireless communication systems, underscoring network slicing for further classification of intruders from user nodes and training the host network using ML/AI per the user application specification.

This study examines HIV/AIDS-associated knowledge and attitudes towards treating disadvantaged communities among predoctoral dental students in U.S. dental schools who had not yet commenced their Community-Based Dental Education (CBDE) training. It also compares the difference in knowledge and attitudes between students with reported community engagement with PLWHA, and those without. Our study comprised 89 predoctoral dental students within their D1-D3 years of dental school who had not yet initiated their Community-Based Dental Education (referred to as pre-CBDE dental students). Responses were collected via an online survey. Participants were 68% females, 94% heterosexual, of mean age (years): 25.9 ± 3.5 SD. The majority (62%) were in their first (D1) and second (D2) years of dental education. Of the thirty knowledge questions, only five received a minimum of 90% correct responses. Similarly, we found no statistical differences in most of the knowledge/attitude sections, between those with and without prior PLWHA exposure. Encouragingly, 90% of our participants reported prior experience working with disadvantaged communities. Early community engagement fosters a sense of professional responsibility towards administering dental care to disadvantaged communities and we propose that it must be encouraged among aspiring dental school students.

Quantum revival phenomena, wherein the wave function of a quantum system periodically returns to its initial state after evolving in time, are investigated in this study. Focusing on electrons confined within a quantum box with an impurity, both weak and strong coupling regimes are explored, revealing intricate relationships between impurity parameters and temporal dynamics. The investigation considers the influence of impurity position, impurity strength, and external factors such as aluminum concentration, temperature, and hydrostatic pressure on classical periods and revival times. Through analytical derivations and graphical analyses, the study elucidates the sensitivity of quantum revivals to these parameters, providing valuable insights into the fundamental aspects of quantum mechanics. While no specific physical applications are discussed, the findings offer implications for quantum heat engines and other quantum-based technologies, emphasizing the importance of understanding quantum revivals in confined quantum systems.

Heart sounds and murmurprovidecrucial diagnosis information for valvular heart diseases (VHD). Phonocardiogram (PCG) combined with modern digital processing techniques, provides a complementary tool for clinicians. This article proposes a benchmark different time-frequency representations, which are spectogram, mel-spectogram and cochleagram for obtaining images, in addition to the use of two interpolation techniques to improve the quality of the images, which are Bicubic and Lanczos. Deep features are extracted from a pre-trained model called VGG16 and for feature reduction the Boruta algorithm is applied. To evaluate the models and obtain more precise results, nested cross-validation is used. The best results achieved in this study were for coclegram with 99.2% accuracy and mel-spectogram representation with the bicubic interpolation technique which reached 99.4% accuracy, both having support vector machine (SVM) as classifier 10 algorithm. Overall, this study highlights the potential of time-frequency representations of PCG 11 signals combined with modern digital processing techniques and machine learning algorithms for 12 accurate diagnosis of VHD.

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

Cancer diagnosis and classification are pivotal for effective patient management and treatment planning. In this study, we present a comprehensive approach utilizing ensemble deep learning techniques to analyze breast cancer histopathology images. Our datasets are based on two widely employed datasets from different centers for two different tasks: BACH and BreakHis. Within the BACH Dataset, we deployed an ensemble strategy incorporating VGG16 and ResNet50 architec-tures to achieve precise classification of breast cancer histopathology images. Introducing a novel image patching technique, to preprocess a high-resolution image, which facilitates focused analysis of localized regions of interest. The annotated BACH dataset encompasses 400 WSIs across four distinct classes: Normal, Benign, In Situ Carcinoma, and Invasive Carcinoma. In addition, we employed the BreakHis dataset, utilizing VGG16, ResNet34, and ResNet50 models to classify mi-croscopic images into eight distinct categories (four benign and four malignant). For both models we leveraged a five-fold cross-validation approach for rigorous training and testing. Preliminary ex-perimental results indicate a Patch classification accuracy of 95.31% (on BACH dataset) and WSI image classification accuracy of 98.43% (BreakHis). This research significantly contributes to on-going endeavors in harnessing artificial intelligence to advance breast cancer diagnosis, potentially fostering improved patient outcomes and alleviating healthcare burdens.

Major cardiovascular events (MACE) are a cause of major mortality worldwide. The narrowing and blockage of coronary arteries with atherosclerotic plaques is diagnosed and treated with percutaneous coronary intervention (PCI). During this procedure, coronary angiography (CAG) remains the most widely used guidance modality for the evaluation the affected blood vessel diameter in order to decide if intervention with stent colocation is suitable, where small blood vessels (&lt; 2.75 mm) are majorly left untreated; however, small vessel coronary artery disease (SvCAD) is a significant risk factor for recurrence of MACE, and there are some limitations to the use of CAG that could be improved with the use of newer techniques such as intravascular ultrasound (IVUS), although at higher costs, which might explain their underuse. To address this discrepancy and identify specific cases for its use, we conducted a retrospective study in patients who underwent PCI for MACE with at least one small blood vessel affected. The affected small blood vessels’ diameter was obtained with both CAG and IVUS, additionally we underwent a multivariate analysis to identify risk factors associated with a change in diameter. We included information from 48 patients with mean + SD age of 69.1 + 11.9 years and 34% were masculine gender. We found a significant positive low correlation in diameter measurements of small blood vessels (r=0.1242 p=0.014). Mean diameter with CAG and IVUS was 2.1 mm (95% CI 1.9-2.2), and 2.8 (2.8-3.0) the estimated difference was of 0.8 mm (95 % CI 0.7-0.9). In total 37 (77%) of patients had a reclassification of their blood vessels from a small to medium (2.75-3.00 mm) in 21 cases, or even large (&lt;3.00 mm) in 15 cases, after IVUS; this was important for the decision of intervention and stent collocation. The only variable associated with reclassification of blood vessels after adjusted in a multivariate analysis was DT2 (p=0 0.035). Our findings corroborate that blood vessels might appear smaller with CAG, especially in the diabetes population, therefore at least in these cases the use of IVUS is recommended over CAG.

This study assessed the performance of low-dose CT lung scans across various acquisition parameters and examined the impact of iterative reconstruction (IR) algorithms on image quality for lung cancer screening. The performance of multi-slice CT scanners was assessed by using a Catphan 600 phantom, specifically within the CTP404 test module that contains materials like Teflon, Delrin, Acrylic, Polystyrene, LDPE, PMP, Air, and water. Three protocols were selected and categorized into standard, low dose, and ultra-low dose. The standard protocol featured a tube voltage of 100 kVp for single-detector CT, a pitch of 0.75, detector collimation of 0.60 mm, and a gantry rotation time of 0.33 seconds, with 5 mm slice thickness. Images were reconstructed using standard kernels like B80f and 170f, combined with either FBP or various IR algorithms. Findings indicated that the noise power spectrum (NPS) peak value (HU2mm2) increased with higher IR levels, with FBP showing the highest peak. Additionally, NPS spatial frequency diminished as IR levels rose. Optimizing contrast and spatial resolution for both background and regions of interest involved adjusting the target transfer function (TTF) and contrast-to-noise ratio (CNR), crucial for protocol optimization. Proper adjustment of IR levels is vital, as higher levels can alter image texture and affect NPS spatial frequency. The results of this study showed that the use of IR algorithms in low-dose CT lung scans significantly improved image quality, particularly in terms of noise reduction and spatial resolution. However, the choice of acquisition parameters also played a crucial

Membrane gas absorption technology has been considered as a promising approach to mitigate CO2 emissions from power plants. The aim of this study is to evaluate the environmental impacts of CO2 absorption and desorption processes by hollow fiber membrane contactors using life cycle assessment methodology. On the basis of ReCipe 2016 Midpoint and ReCipe 2016 Endpoint methods, the research results show that, membrane gas absorption system exhibits the lowest environmental impacts across the majority assessed categories in comparison with chemical absorption and membrane gas separation systems. The CO2 capture process via membrane gas absorption has the most significant impact on METP category, with heat consumption as the primary contributing factor accounting for 55%, followed by electricity consumption accounting for 43.1%. According to the sensitivity analysis, heating by natural gas shows a better performance than other heat supply sources in improving overall environmental impacts. In addition, the increasing utilization of renewable energy in electricity supply reduces the global warming potential, fossil resource consumption and ozone formation.

Acemetacin (ACM) is a new non-steroidal anti-inflammatory drug with anti-inflammatory, analgesic, and antipyretic effects. However, the poor water solubility and gastrointestinal side effects limit its use. Recently, the co-amorphous (CAM) strategy has attracted great interest to improve solubility for poorly water-soluble drugs, and basic amino acids have the potential to protect the gastrointestinal tract. In order to develop highly efficient and low toxic ACM formulation, we propose to prepare ACM CAM, with basic amino acids (lysine, arginine and histidine) as co-formers, using a cryo-milling method. The solid-state behaviors of the ACM CAMs were characterized by polarizing light microscopy, differential scanning calorimetry and powder X-ray diffraction. Fourier transform infrared spectroscopy and molecular docking were carried out to understand the formation mechanism. Moreover, the gastro-protective effects of ACM CAMs were evaluated in a rat gastric ulcer model. The results demonstrated CAMs improved the dissolution rates of ACM compared with the neat amorphous counterpart. Furthermore, ACM CAMs are significantly effective in mitigating the ACM-induced gastric ulcer in rats, and the ulcer inhibition rates were almost 90%. More importantly, this study provided a useful method for mitigating drug-induced gastrointestinal damage and broadened the applications of drug-amino acid CAMs.

Available options to combat bacterial infections are getting scarce. We require innovative and imaginative approaches to enhance the identification and discovery of effective antimicrobials capable of combating bacteria resistant to multiple or all available drugs. These methods should either directly eliminate the resistant bacteria or influence their viability indirectly by inhibiting their virulence or reducing their resistance to antibacterial agents. One interesting approach is to analyze ancient remedies presumably used to treat bacterial infections, try formulating them, and test them against modern microbes. The field was recently named ancientbiotics. This approach allows us to take advantage of centuries of accumulated empirical knowledge, from several traditional medicines of various ancient cultures across the world. The strategy has already resulted in promising formulations to combat the ESKAPE group of nosocomial pathogens. Moreover, molecular de-extinction consists of genome analysis of extinct species in the search for useful antimicrobials, such as peptides. The de-extinction of simple organisms such as bacteriophages may eventually become a resource for novel tools to combat multidrug-resistant bacteria. In this review, we summarize and discuss the reported antimicrobial effects of ancient remedies and de-extinct molecules known to modern science, and discuss possible new strategies to further harness the potential of past remedies and molecules to help us fight the rise of superbugs.

This study evaluates the viability of n-octanol as an alternative fuel in a direct-injection diesel engine, aiming to enhance sustainability and efficiency. Experiments employed varying blends of n-octanol (10%, 30%, and 50% by volume) with pure diesel, analyzing impacts on engine performance and emissions. The methodology involved testing each blend in a single-cylinder engine, measuring engine performance parameters such as brake torque and brake power under full load conditions across an engine speed range from 1400 to 2500 rpm. Comparative assessments of performance and emission characteristics at a constant engine speed of 1700 rpm were also conducted with varying loads. Results indicated that while n-octanol blends consistently improved brake thermal efficiency, they also increased brake specific fuel consumption due to the lower energy content of n-octanol. Consequently, while all n-octanol blends reduced nitrogen oxides (NOx) emissions compared to pure diesel, they also significantly decreased carbon monoxide, hydrocarbons, and smoke opacity, presenting a comprehensive reduction in harmful emissions. However, the benefits came with nuanced trade-offs: notably, higher concentrations of n-octanol (especially the 50% blend) led to a relative increase in NOx emissions as the octanol ratio increased. The study concludes that n-octanol significantly improves engine efficiency and reduces diesel dependence, but optimizing the blend ratio is crucial to balance performance improvements with comprehensive emission reductions.