Combined hepatocellular cholangiocarcinoma (cHCC-ICC) is a rare malignancy that involves a combination of features of hepatocellular carcinoma and intrahepatic cholangiocarcinoma (ICC). cHCC-ICC is generally considered to exhibit a more aggressive clinical course compared to ICC; however, its risk factors and outcomes remain largely undefined. A single-center retrospective study of 82 patients diagnosed with ICC or cHCC-ICC from June 2011 and January 2023, all of whom underwent surgical resection. Our analysis included 70 patients with resected ICC and 12 with resected cHCC-ICC. The overall survival (OS) for the entire cohort was 21.6 months, with a recurrence-free survival (RFS) of 11.8 months. The cHCC-ICC group had significantly higher levels of AST and ALT (AST median 206 vs. 46; ALT median 165.5 vs. 48; p=0.012 and p=0.013, respectively), whereas the ICC group had higher alkaline phosphatase (median 66 vs. 104; p=0.03). CA 19-9 values (p=0.02) were higher in the ICC group, while AFP values were higher in the cHCC-ICC group (p=0.0004). The cHCC-ICC group had a significantly higher rate of recurrence (83% vs. 47%, p=0.028) with a significantly decreased RFS (4.7 months vs. 12.4 months; log-rank p=0.007). cHCC-ICC is a rare entity that needs to be further studied to improve patient outcomes. Our study showed that RFS is lower in the cHCC-ICC group as compared to ICC patients alone. Further studies are warranted and possibly suggest the need for more aggressive initial treatment strategies in patients diagnosed with cHCC-ICC.

Epigallocatechin gallate (EGCG), the principal catechin in green tea, exhibits diverse therapeutic properties. However, its clinical efficacy is hindered by poor stability and low bioavailability. This study investigated solid particle-in-oil-in-water (S/O/W) emulsions stabilized by whey protein isolate (WPI) and sodium caseinate (NaCas) as carriers to enhance the bioavailability and intestinal absorption of EGCG. Molecular docking revealed binding interactions between EGCG and these macromolecules. The emulsions exhibited high encapsulation efficiencies and augmented EGCG bioaccessibility by 64% compared to free EGCG in a simulated gastrointestinal digestion model. EGCG-loaded emulsions demonstrated minimal cytotoxicity towards Caco-2 cells and facilitated EGCG transport across the intestinal epithelial layer without compromising tight junction integrity. Notably, EGCG-loaded emulsions protected Caco-2 cells against oxidative stress by suppressing intracellular reactive oxygen species generation. The results demonstrate the potential of WPI- and NaCas-stabilized S/O/W emulsions to enhance the bioavailability, intestinal absorption, and bioactivity of EGCG, expanding its applications in functional foods and nutraceuticals.

The pivotal role of the basolateral amygdala (BLA) in the emotional modulation of hippocampal plasticity and memory consolidation is well established. Specifically, multiple studies have demonstrated that the activation of the noradrenergic (NA) system within BLA governs these modulatory effects. However, most of the current evidence has been obtained by direct infusion of synthetic NA or beta-adrenergic agonists. In the present study, we aimed to investigate the effect of endogenous NA release in the BLA, induced by a natural aversive stimulus (coyote urine), on memory consolidation for a neutral hippocampal-dependent task. We combined a weak version of the object location task (OLT) with mild predator odor exposure (POE) for our experiments. To investigate the role of the BLA in memory modulation, a subset of the animals (Wistar rats) were treated with the non-selective beta-blocker propranolol at the end of the behavioral procedures. Hippocampal tissue was collected either 90 minutes after drug infusion or 24 hours after the OLT test. The samples were used to determine the levels of phosphorylated CREB (pCREB) and activity-regulated cytoskeleton-associated protein (Arc) - two molecular markers of experience-dependent changes in neuronal activity. The result suggests that POE is a behavioral paradigm suitable for studying the interaction between BLA and the hippocampus in memory prioritization and selectivity.

Deep inhalation breath hold (DIBH) has become a valuable technique in left breast cancer radiotherapy, offering the possibility to reduce radiation exposure to organs at risk (OARs) and minimize the risk of cardiac complications. The treatment method involves patients stopping breathing during irradiation to temporarily distance the heart from the radiation field, reducing potential cardiac and other complications. Research shows that DIBH reduces the radiation dose to the heart and lungs. However, the effectiveness of DIBH is determined by a variety of factors, including the patient's training, cooperation, anatomical features, age and choice of radiotherapy technique. Additionally, cardiovascular risk factors: diabetes, smoking, hypertension can affect the effectiveness and potential complications of DIBH. Moreover, lack of consent, fear, anxiety, depression and comorbid psychiatric disorders disqualify some patients from the DIBH treatment method. Careful patient selection, comprehensive training and optimization of treatment parameters are essential to maximize the benefits of DIBH while minimizing potential side effects. DIBH enhancement techniques, such as IMRT or VMAT, also have an important role to play. The purpose of this review article is to summarize the factors affecting the efficacy and side effects of DIBH in radiation therapy for left breast cancer, with the aim of optimizing its clinical application while minimizing side effects.

Maternal diet plays a significant role in the fatty acid composition of breast milk. Natural trans fatty acids (TFAs) are generated through the biohydrogenation of unsaturated fatty acids (FAs) in the rumen of animals by bacterial isomerases and are consequently found in milk, dairy products, and meat from ruminant animals. Dietary products such as milk and meat are the primary sources of natural TFAs for humans, derived from rumen fermentations. These peculiar fatty acids hold nutritional significance as they not only lack the detrimental effects on endothelium characteristic of industrially produced trans fat, but also exhibit anti-inflammatory properties. The relationship between the presence in breast milk of eight fatty acids (including natural TFAs trans-vaccenic and conjugated linoleic acid) and maternal diet has been explored, and their abundance has been compared to that of infant formulas. Two cohorts of lactating women participated in this study, originating from a Spanish region adhered to the Southern European Atlantic Diet or Atlantic Diet. While the consumption of conventional meat or dairy products does not seem to increase the abundance of trans fatty acids in breast milk, trans-vaccenic and oleic acid are among the most distinctive features of breast milk fat in mothers consuming naturally improved dairy products, with an improved fatty acid profile. The most significant differences between natural breastfeeding and formula feeding lie in natural trans fatty acids, since formula are notably deficient, while overfortified in alpha-linolenic acid in comparison to breast milk.

Mustard, a widely used condiment, is derived from mustard seeds and partially defatted mustard flour. Varieties of mustard are primarily distinguished by the ratios of mustard seeds and spices used in their production. This study assessed the microbiological safety of mustard products from the Mustard and Ketchup Factory in Poland, produced between 2019-2021, in compliance with Polish and EU regulations. Three mustard types were analyzed: gourmet, creamy, and spicy, crafted from 'Borowska' white mustard and 'Małopolska' Sarepta mustard seeds. The preparation included powdered mustard seeds, water, sugar, and vinegar. Samples of mustards (20 g each) were tested in triplicate for Salmonella, spore-forming anaerobic bacteria, coliform bacteria, Staphylococcus aureus, mold, and yeast. Additionally, water and spices used in production were analyzed for total coliforms, Escherichia coli, Enterococcus, Salmonella, aerobic mesophilic microorganisms, anaerobic spore-forming bacteria, and mold. Results indicated that spices and water met all microbiological criteria. Mustard samples tested negative for Salmonella and anaerobic spore-forming bacteria, with coliforms, Staphylococcus aureus, mold, and yeast counts within acceptable limits, ensuring compliance with food safety and hygiene standards. This research underscores the importance of ongoing monitoring and strict microbiological standards to maintain food safety. Future studies should develop advanced microbial detection methods and implement robust quality control measures to reduce contamination risks in mustard and other food products.

Introduction: The image of the nurse is a source of concern because of its impact on recruitment to the profession, policy decisions about the profession, funding of nursing services, consumer use of nursing services and how the image of the nurse affects nursing practice. Aim: This study aims to assess the psychometric properties of the Italian version of the Nursing Attitudes Questionnaire (NAQ-IV). Methods: 564 persons between the years 2022 and 2023 with heterogeneous ages and occupations from Northern, Central and Southern Italy participated in the study. Cronbach's alpha, item versus total correlations, skewness and kurtosis were calculated; factor analysis was performed using principal axis factoring and the viramax rotation method. Results: The results showed a Cronbach's alpha of 0.89 on the scale and between 0.88 and 0.89 between the factors; all items tested for correlation between the item and the total and the criteria for variance in the responses. Factor analysis showed a 4-factor model explaining more than 59.91% of the variance, with the largest variance being explained by the 'Role & professionalism' factor (25.96%). Conclusion: These results allow for a discussion regarding the theoretical framework of the NAQ-IV and provide a reliable and valid instrument for the comparison of welfare, organisation of health services, role, professionalism, stereotypes, values, advocacy, motivation and perceived satisfaction with the figure of the nurse and nursing care.

Retroviruses perpetuate their survival by incorporating a copy of their genome into the host cell, a critical step catalyzed by the virally encoded integrase. The viral capsid plays an important role during the viral life-cycle, including nuclear importation in case of lentiviruses and integration targeting events, hence, targeting the integrase and the viral capsid is a favorable therapeutic strategy. While integrase strand transfer inhibitors (INSTIs) are recommended as first-line regimens given their high efficacy and tolerability, lenacapavir is the first capsid inhibitor and the newest addition to the HIV treatment arsenal. These inhibitors are however designed for treatment of HIV-1 infection, and their efficacy against HIV-2 remains widely understudied and inconclusive, supported only by few limited phenotypic susceptibility studies. We therefore carried out inhibition profiling of a panel of second-generation INSTIs and lenacapavir against HIV-2 in cell culture, utilizing pseudovirion inhibition profiling assays. Our results show that the tested INSTIs and lenacapavir exerted excellent efficacy against ROD-based HIV-2 integrase, and interestingly, raltegravir also showed modest antiviral activity against the SARS-CoV-2 Omicron variant in antiviral assays carried out in Vero E6 cells.

In recent years, there has been an increasing interest in adopting novel sensing technologies for the continuous monitoring of structural systems. In this respect, Micro-Electro-Mechanical System (MEMS) sensors are widely used in several applications, including Structural Health Monitoring (SHM). Thanks to their significantly lower cost, ease of installation on the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through the network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analysis show that MEMS can correctly detect modal frequencies, useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring.

With the development of higher voltage power grid, the high and low voltage parallel loops are emerging, which lead to energy losses, even threaten the security and stability of power system. The multi-infeed HVDC configurations widely appearing in AC/DC interconnected power system make this situation even worse. Aimed at energy saving and system security, a decision optimization method for power grid operating condition with high and low voltage parallel loops is proposed in this paper. Firstly, considering hub substation distribution and power grid structure, parallel loop opening schemes are generated with GN algorithm. Then, candidate opening schemes are preliminarily selected from all these generated schemes based on a filtering index. Finally, with the influence on power system security, stability and operation economy in consideration, an evaluation model for candidate opening schemes is founded based on analytic hierarchy process (AHP). And a fuzzy evaluation algorithm is used to find the optimal scheme. Simulation results of New England 39-bus system and an actual power system validate the effectiveness and superiority of this proposed method.

Background: Population studies have shown that prehypertension is associated with adverse cardiometabolic risk profile even among apparently healthy populations. Although associations between serum triglyceride (TG) concentrations and the risk of atherosclerotic cardiovascular disease have been reported, there are lack of data on the association of hypertriglyceridemia with cardiovascular risk (CVR) in a low risk prehypertensive population. Aim: Our aim was to analyze the cardiorenometabolic characteristics of prehypertensives (PHT) compared to normotensives (NT) and untreated hypertensives (HT) and its associations with CVR. Materials and methods: In our cross-sectional study we included 323 apparently healthy untreated subjects 18-45 years who underwent basic anthropometric and standardized blood pressure measurement, fasting blood sampling, spot urine collection and transthoracic echocardiogram. Results: Higher BMI, waist circumference, HOMA-IR, LDL-cholesterol, TG, uric acid and LVMI contribute to higher CVR in PHT compared to true NT (p

Thorough and precise gene structure annotations are essential for maximizing the benefits of genomic data and unveiling valuable genetic insights. The cucumber genome was first released in 2009 and updated in 2019. To increase the accuracy of predicted gene models, 64 published RNA-seq data and 9 new strand-specific RNA-seq data from multiple tissues were used for manual comparison with the gene models. The updated annotation file (version 2.0) contains increased 24,145 predicted genes from previous version (24317 genes) with a higher BUSCO value of 96.9%. 6231 and 1490 transcripts were adjusted and newly added, respectively, accounting for 31.99% of the overall gene tally. These newly added and adjust genes were renamed (CsaV3.1_XGXXXXX), while genes remaining unaltered preserve their original des ignations. A random selection of 21 modified/added genes were validated using RT-PCR analyses. Additionally, tissue-specific patterns of gene expression were examined using newly obtained transcriptome data with the revised gene prediction model. This improved annotation of cucumber genome will provide essential and accurate resources for studies in cucumber.

1) Background: Capturing patients’ medical histories significantly influences clinical decisions. Errors in this process lead to clinical errors, increase costs and dissatisfaction among physicians and patients. Physicians in developing countries are overloaded with patients and cannot always follow the proper history-taking procedure. The challenges are acknowledged; however, a comprehensive understanding of the status and the remedies remained unexplored. 2) Objective: This paper aims to investigate the workload, history-taking challenges, and the willingness of the physicians to accept digital solutions. 3) Methods: A cross-sectional online survey was conducted on 104 physicians across Bangladesh, featuring 22 questions regarding their professional environment, workload, digitization status of health records, challenges in history-taking, and attitudes toward adopting digital solutions for managing patient histories; 4) Results: 92.67% of the physicians face workloads, 88.46% struggle in medical history-taking, and only 4.81% use digital medical records. About 70% struggle to complete the necessary history-taking steps, emphasizing the urgent need for solutions. An AI-based Smart Health Gantt Chart (SHGC) system has been introduced for their instant feedback. 93.27% of physicians expressed their willingness to use such a system. 5) Conclusions: The proposed SHGC has the potential to enhance healthcare efficiency in developing nations, benefit physicians, and improve patient-centered care.

Thyroid surgery rates have tripled over the past 3 decades making it one of the most frequently performed procedures within general surgery. They are associated with the possibility of serious postoperative complications having a significant impact on the patient's quality of life. The recurrent laryngeal nerve (RLN) palsy and the external branch of the superior laryngeal nerve (EBSLN) palsy are, next to hypoparathyroidism and bleeding after operation, one of the most common complications. The introduction of neuromonitoring into thyroid surgery, enabling both confirmation of anatomical integrity and assessment of laryngeal nerve function, was a milestone that has begun a new era in thyroid surgery. The International Neural Monitoring Study Group made standardization of the technique of RLN and EBSLN monitoring during thyroid and parathyroid surgery which increased prevalence of neural monitoring during thyroidectomy. Current status of IONM and benefits of its use have been presented in this publication.

Depressive disorders represent the leading contributors to mental health-related global burden, and they are often diagnosed in the context of many comorbid disorders, such as cardiovascular disorders, Stroke, Parkinson’s Disease, Major Neurocognitive Disorders and Headache, thus worsening their outcomes. Depression is a challenge for “real-world” clinicians, due to the low rates of remission despite the increasing number of antidepressant strategies currently available. Indeed, current antidepressant strategies often fail to achieve acceptable rates of remission. One of the main challenges of “real-world” management of depression is represented by geriatric depression, which is common and under diagnosed. The challenge of diagnosis and treatment of geriatric depression in real world calls for the need of a deeper exploration of its management in clinical practice. This is the purpose of the present cross-sectional survey, aimed at evaluating the clinical approach to late-life depression in a sample of expert physicians working in geriatric settings in Italy, thus trying to provide useful insights on geriatric depression care.

Bergamot flavonoids have been shown to prevent metabolic syndrome, non-alcoholic fatty liver disease (NAFLD) and stimulate autophagy in animal models and patients. To investigate further the mechanism of polyphenol-dependent effects, we performed RT2-PCR array analysis on 168 metabolism, transport and autophagy-related genes expressed in rat livers exposed for 14 weeks to different diets: standard, cafeteria (CAF) and CAF diet supplemented with 50 mg/kg of Bergamot Polyphenol Fraction (BPF). CAF diet caused a strong upregulation of the gluconeogenesis pathway (Gck, Pck2) and a moderate (>1.7 fold) induction of genes regulating lipogenesis (Srebf1, Pparg, Xbp1), lipid and cholesterol transport or lipolysis (Fabp3, Apoa1, Lpl) and inflammation (Il6). However, only one -oxidation gene (Cpt1a) and a few autophagy genes were modulated in the CAF group compared to controls. While most of these transcripts were significantly modulated by BPF, we observed a particularly potent effect on lipogenesis genes, like Acly, Acaca, Fasn and Scd1, which were suppressed far below the mRNA levels of control livers as confirmed by alternative primers-based RT2-PCR analysis and western blotting. These effects were accompanied by downregulation of pro-inflammatory cytokines (Il6, Tnfa, and Il10) and diabetes-related genes. Few autophagy (Map1Lc3a, Dapk) and no -oxidation gene expression changes were observed, suggesting minor transcriptional effects on autophagy. In conclusion, chronic BPF supplementation efficiently prevents NAFLD by modulating hepatic energy metabolism and inflammation gene expression programs, with no effect on -oxidation, but profound suppression of de-novo lipogenesis.

Infections caused by KPC-producing K. pneumoniae continue to pose a significant clinical challenge due to emerging resistance to new antimicrobials. We investigated the association between two drugs whose roles have been repurposed against multidrug-resistant bacteria: fosfomycin and temocillin. Temocillin exhibits unusual stability against KPC enzymes, while fosfomycin acts as a potent “synergizer”. We conducted in vitro antimicrobial activity studies on 100 clinical isolates of KPC-producing K. pneumoniae using a combination of fosfomycin and temocillin. The results demonstrated synergistic activity in 91% of the isolates. Subsequently, we assessed the effect on Galleria mellonella larvae using 5 different KPC-Kp isolates. The addition of fosfomycin to temocillin increased larvae survival from 73 to 97% (+Δ 32%; isolate 1), from 93 to 100% (+Δ 7%; isolate 2), from 63 to 86% (+Δ 36%; isolate 3), from 63 to 90% (+Δ 42%; isolate 4), and from 93 to 97% (+Δ 4%; isolate 10), respectively. Among the temocillin-resistant KPC-producing K. pneumoniae isolates (24 isolates), the addition of fosfomycin reduced temocillin MIC values below the resistance breakpoint in all isolated except one. Temocillin combined with fosfomycin emerges as a promising combination against KPC-producing K. pneumoniae, warranting further clinical evaluation.

Background: Disparity in adult mortality (AM) with reference to social dynamics and health care has not been sufficiently examined. This study aimed to identify the gap in the understanding of AM in relation to religion, political stability, economic level, and universal health coverage (UHC). Methods: A cross-national study was performed with different sources of data, using the administrative record linkage theory. We created a new data set using data from the 2013 World Bank data catalogue by region, The Economist (Political instability index 2013), Stuckler David et al. (Universal health coverage, 2010), and religious categories of all UN country members. Descriptive statistics, a t-test, an ANOVA followed by a post hoc test, and a linear regression were used where applicable. Result: The average AM rate for males and females was 0.20 ± 0.10 and 0.14 ± 0.10, respectively. AM was significantly higher in economically weak countries, countries with political instability, countries with traditional religion, without achievement of UHC, and Sub-Saharan Africa (p<0.01). There was high disparity of AM between countries with and without UHC (F = male: 61.89, female: 51.85, p<0.001) and between groups with low and high income (F = male: 36.33, female: 42.39, p<0.001). UHC and political stability would significantly reduce AMR by > 0.41 in both sexes and high economic status would reduce male AMR by 0.44, and female AMR by 0.70, in relation to countries without UHC, with political instability, and low economic status. Conclusions: Disparities in AM can be reduced after the achievement of UHC and economically productive activities for those adults affected by conflict and political unrest.

Asphaltene-resin-paraffin deposition (ARPD) is a complicated and prevalent issue in oil and gas industry, impacting the efficiency, integrity of petroleum extraction, production, transportation and processing systems. Considering all witnessed ARPD problems in Azerbaijan oil fields, this paper proposed a chemical method and optimized the type and the concentration of chemical inhibitors. And then the effect of selected chemical reagent on inhibiting the ARPD amount and thus en-hancing oil recovery was detected by reservoir simulation during both waterflooding and CO2 flooding production. Three new chemical compounds (namely, Chemical-A, Chemical-B and Chemical-C) were examined in laboratory conditions and their impact on rheological properties of high-paraffin oilfield samples of Azerbaijan (X, Y and Z) were investigated. Experimental results show that Chemical-C with concentration of 600 g/t has the best efficiency for alleviating the problems. After adding Chemical-C to the crude oil, the freezing point of oil is decreased from 12 °C to (-4) °C, ARPD amount is declined from 0.185 to 0.016 g and oil effective viscosity is reduced from 16.2 mPa·s to 3.1 mPa·s. It is determined that for water and CO2 flooding, higher injection pressure resulted in reduced asphaltene precipitation. Adding selected ARPD inhibitor, the oil recovery for waterflooding can increase from 52% to 62%, while it can rise from 55% to 68% for CO2 flooding.

Dark pigmentation can be observed in various parts of the plant, ranging from foliage to petals to berries. The molecular basis of black pigmentation appears to vary among species, with anthocyanins playing a significant role, although specific anthocyanin types and their mechanisms differ. These findings suggest that the development of phenotypes is species-specific or varies between larger taxonomic groups; this is further supported by the polyphyletic nature of dark pigmentation. Additionally, several different regulatory mechanisms have been described for the occurrence of dark pigmentation. Firstly, the repression or knockout of the competing flavone biosynthesis has been shown to lead to darker pigmentation while another mechanism is based on the activation and upregulation of the anthocyanin biosynthesis genes in the presence of MYB transcription factors. Potential ecological functions of dark pigmentation were identified as the protection of the photosynthesis apparatus, camouflage against herbivores, and the attraction of pollinators. Promising industrial applications include microbial factories for the production of natural food colourants, induction of novel phenotypes for the ornamental plant industry and lastly the increase of anthocyanins within agriculturally relevant crops.

Exoskeleton technology has been shown to be useful for individuals with spinal cord injury (SCI), potentially facilitating their recovery of motor function and social reintegration. However, studies on the safety and usability of exoskeletons are limited. This study aimed to design a powered exoskeleton for SCI and evaluate its safety and usability. Ten healthy adults participated in this study. The prototype exoskeleton featured an adjustable frame, computer-controlled hip and knee joint actuators, and a gait-trigger sensor. The experimental actions included walking, standing, and sitting, with and without the prototype. Safety outcomes included adverse events, vital signs, numerical rating scale (NRS) scores for pain, discomfort, and fatigue, and prototype-human body clearance. Usability outcomes included donning and doffing times, subjective ratings, gait speed, stride length, and kinematic parameters of hip and knee joint angles. Safety outcomes showed no serious adverse events, stable vital signs, minimal NRS scores, and acceptable clearance. Usability outcomes showed high efficiency and received positive ratings. Kinematic parameters showed significant positive correlations between normal walking and walking with the prototype for both hip and knee joint angles, confirming its effectiveness in assisting walking. However, further device improvements and gait parameter tuning are necessary for future clinical application.

In recent years, the scientific and technological developments led to an explosion of available videos on the web, increasing the necessity of fast and effective video analysis and summarization. Video summarization methods aim to generate a synopsis by selecting the most informative parts of the video content. The user’s personal preferences, often involved in the expected results, should be taken into account in the video summaries. In this paper, we provide the first comprehensive survey on personalized video summarization relevant to the techniques and datasets used. In this context, we classify and review personalized video summary techniques based on the type of personalized summary, on criteria, on the video domain, on the source of information, on the time of summarization, and on the machine learning technique. Depending on the type of methodology used by the personalized video summarization techniques for the summary production process, we classify the techniques into five major categories, which are feature-based video summarization, key frame selection, shot selection-based approach, video summarization using trajectory analysis, and personalized video summarization using clustering. We also compare personalized video summarization methods and present 37 datasets used to evaluate personalized video summarization methods. Finally, we analyze opportunities and challenges in the field and suggest innovative research lines.

We propose a novel unsupervised semantic segmentation method for fast and accurate flood area detection utilizing color images acquired from Unmanned Aerial Vehicles (UAVs). To the best of our knowledge, this is the first fully unsupervised method for flood area segmentation in color images captured by UAVs, without the need of pre-disaster images. The proposed framework addresses the problem of flood segmentation based on parameter-free calculated masks and unsupervised image analysis techniques. First, a fully unsupervised algorithm gradually excludes areas classified as non-flood utilizing calculated masks over each component of the LAB colorspace, as well an RGB vegetation index and the detected edges of the original image. Unsupervised image analysis techniques, such as distance transform, are then applied, producing a probability map for the location of flooded areas. Finally, flood detection is obtained by applying the hysteresis thresholding segmentation. The proposed method is tested and compared with variations, and other supervised methods in two public datasets, consisting of 953 color images in total, yielding high-performance results, with 87.4% and 80.9% overall accuracy and F1-Score, respectively. The results and computational efficiency of the proposed method show that it is suitable for on board data execution and decision-making during UAVs flight.

A detailed review of the scientific literature was undertaken to examine the most recent developments in plasma processing in the field of medicine. The first part of the review includes a detailed breakdown of the different types of coatings that can be applied onto medical devices using plasma, with a specific focus on antimicrobial surfaces. The developments during 2023 in plasma deposited biocompatible, drug delivery and adhesive coatings are described and specific applications in additive manufacturing are highlighted. The use of plasma and plasma activated liquids as standalone therapeutics continues to evolve and pertinent advances in this field are described. In addition, the combination of plasma medicine with conventional pharmaceutical interventions was reviewed and key emerging trends were highlighted, including the use of plasma to enhance drug delivery directly into tissue. The potential synergies between plasma medicine and chemotherapeutics for oncology and infection treatment is a growing area and recent advancements are noted. Finally, the use of plasma to control excess antibiotics and to intentionally degrade such materials in waste streams is described.

Six bacterial strains with differing abilities to produce varying concentrations of Indole Acetic Acid were tested individually and in consortia for plant growth promoting and fitness related traits of Cicer arietinum. In all experiments the presence of the nitrogen fixer Mesorhizobium ciceri resulted in increased biomass production. In the absence of this strain, IAA Psedomonas putida and Bacillus megaterium hinder plant growth and fitness related traits. The application of mixes of the three strains always resulted in better plant performance when M. ciceri was present. Whereas P. putida has a noticeable plant growth-promoting effect B. megaterium resulted less effective. The low levels of IAA produced by the selected strains had a significantly greater positive effect on plant biomass accumulation, flower, pods and seed production as well as on total plant nitrogen and nitrogen concentration in seed than high IAA producer strains.

Aim: To analysis the relationship between healthy adults right ventricular diameter (RVD) and geographical factors. Location: China’s 22 provinces, municipalities and autonomous regions. Methods: Using correlation analysis the relationship between RVD and nine geographic factors, build predictive models by factor analysis. Results: There is significant correlation between RVD and geographical factors, and the annual average temperature is most relevant geographical factors, a predictive model was built by factor analysis: Ŷ = 19.46 + 0.0007072X1 + 0.001034X2 -0.05412X3 -0.001405X4 -0.0006351X5 + 0.02903X6 + 0.01243X7 -0.01033X8 + 0.03816X9 ± 0.63. Then using Kriging interpolation interpolate the geographical distribution of Chinese healthy adult right ventricular diameter reference value in ArcGIS software. Main Conclusion: If geographic factors can be derived in anywhere of China, RVD can be calculated by the model, you can also get RVD from geographical distribution.

The blood count is crucial for assessing bone marrow's cell production and differentiation during infections, gauging disease severity, and monitoring therapeutic responses. The profile of blood count in chronic form of paracoccidioidomycosis (PCM) has been insufficiently explored. To better understand the changes in hematological cells in different stages of the PCM chronic form, we evaluated the blood count, including immature blood cells in automated equipment, before and during the treatment follow-up of 62 chronic PCM patients. Predominantly male (96.8%) with an average age of 54.3 (SD 6.9) years, participants exhibited pre-treatment conditions such as anemia (45.2%), monocytosis (38.7%), and leukocytosis (17.7%) which became less frequent after clinical cure. Anemia was more prevalent in severe cases. Notably, hemoglobin and reticulocyte hemoglobin content increased, while leukocytes, monocytes, neutrophils, immature granulocytes, and platelets decreased. Chronic PCM induced manageable hematological abnormalities, mainly in the red blood series. Monocytosis, indicating monocytes' role in PCM's immune response, was frequent. Post-treatment, especially after achieving clinical cure, significant improvements were observed in various hematological indices, including immature granulocytes and reticulocyte hemoglobin content, underscoring the impact of infection on these parameters.

In this paper, a new approach is proposed for designing ultra-low-power FFT (Fast Fourier Transform) system suitable for use in energy harvesting powered sensors. Bit-serial architecture is adopted to reduce the power consumption of butterfly operation. Simulation results show that, compared with state-of-the-art bit-serial and conventional parallel processors, the proposed technique is superior in terms of silicon area, power consumption, dynamic energy use due to variable precision arithmetic. A sample design of a 64-point FFT shows that the implementation can save about 40% area and 36% leakage power compared with a conventional parallel counterpart, accordingly achieving significant power benefits at a low sample rate and low voltage domain. The dynamic variation of the arithmetic precision can be achieved through a simple modification of the controller with hardware area overhead of 10% gate count.

Lung cancer is the leading cause of cancer related mortality worldwide. In order to improve its overall survival, early diagnosis is required. Since current screening methods still face some pitfalls, such as high false positive rates for low-dose computed tomography, researchers are still looking for early biomarkers to complement existing screening techniques in order to provide a safe, faster and more accurate diagnosis. Biomarkers are biological molecules found in body fluids, such as plasma, that can be used to diagnose a condition or disease. Metabolomics has already shown to be a powerful tool in the search for cancer biomarkers since cancer cells are characterised by impaired metabolism, resulting in an adapted plasma metabolite profile. The metabolite profile can be determined using nuclear magnetic resonance, or NMR. Although metabolomics and NMR metabolite profiling of blood plasma are still under investigation, there is already evidence for its potential for early-stage lung cancer diagnosis, therapy response, and follow-up monitoring. This review highlights some key breakthroughs in this research field, where the most significant biomarkers will be discussed in relation with their metabolic pathways and in light of the altered cancer metabolism.

Background: The study aimed to investigate the association between environmental tobacco smoke exposure and the risk of wheezing among rural and urban preschool children in Mpumalanga province, South Africa, an area associated with poor air quality. Methods: In this study, parents/caregivers of preschool children (n=3145) completed a modified International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. Data were analysed using multiple logistic regression models. Results: The overall prevalence of Wheeze ever was 15.14%, with a higher prevalence in urban pre-schoolers than rural pre-schoolers (20.71% vs 13.30 %, P<0.000). Moreover, the total prevalence of asthma ever was 2.34%. The prevalence was greater in urban pre-schoolers than in rural pre-schoolers (3.92% vs 1.81%, P<0.001). In the final adjusted model, both urban and rural area children who lived with one or more people who smoked in the same household (WE: OR 1.44, 95% CI 1.11-1.86) (CW: OR 2.09, 95% CI 1.38-3.16) and (AE: OR 2.49, 95% CI 1.12-5.54) were found to have an increased likelihood of having Wheeze Ever, Current Wheeze and Asthma Ever as compared to those who lived with non-smokers. Conclusions: The implementation of smoking limits and prohibition is crucial in areas that are frequented or utilized by children. Hence, it is imperative for healthcare providers to actively champion the rights of those who do not smoke within the society, while also endorsing legislative measures aimed at curtailing the extent of tobacco smoke exposure.

Traumatic vascular injuries consist in direct or indirect damage to arteries and/or veins and accounts for 3% of all traumatic injuries. Typical consequences are hemorrhage and ischemia. Extremities vascular injuries can occur isolated or in association in major trauma with other organ injuries. They account for 1-2% of patients admitted to Emergency Department, for approximately 50% of all arterial injuries. Lower extremities are more frequently injured than the upper ones in adult population. The outcome of vascular injuries is strictly correlated to the environment and the time background. Treatment can be challenging notably in polytrauma because of the dilemma of which injury should be prioritized and treatment delay can cause disability or even death especially for limb vascular injury. Our purposes are to discuss the role of Computed Tomography Angiography (CTA) in the diagnosis of vascular trauma and its optimized protocol to achieve the definitive diagnosis, and to assess the radiological signs of vascular injuries and the possible pitfalls.

In contrast to conventional non-destructive testing (NDT) and non-destructive evaluation (NDE) methodologies, including radiography, ultrasound, and eddy current analysis, the coplanar capacitive sensing technique emerges as a novel and promising avenue within the field. This paper endeavors to elucidate the efficacy of coplanar capacitive sensing, also referred to as capacitive imaging (CI), within the realm of NDT. Leveraging extant scholarly discourse, this review offers a comprehensive and methodical examination of the coplanar capacitive technique, encompassing its fundamental principles, factors influencing sensor efficacy, and diverse applications for defect identification across various NDT domains. Furthermore, this review deliberates on extant challenges and anticipates future trajectories for the technique. The manifold advantages inherent to coplanar capacitive sensing vis-à-vis traditional NDT methodologies not only afford versatility in application but also underscore its potential for pioneering advancements in forthcoming applications.

The development of multidrug resistance by pathogenic bacteria and yeast is a significant medical problem that needs to be addressed. One possible answer could be the combined use of antibiotics and silver nanoparticles, which have different mechanisms of antimicrobial action. Nanoparticles can be combined with antifungal agents in the same way. Biogenic silver nanoparticles synthesized using environmentally friendly technology using extracts of biologically active plants are an effective nanomaterial that needs to be comprehensively investigated for implementation into medical practice. In this study, the synergistic effects arising from their combined use with antibiotics and fungicides against various bacteria and yeasts, included in the ESKAPE list, were studied. Effective concentrations of substances were established, recommendations for the studied pathogenic species were presented and the effect of destruction of the bacterial membrane was illustrated. The most significant synergistic effect was manifested in pathogenic candida and brewer's yeast.

To characterize the fecal microbiota of lactating Bactrian camels, this study employed a random selection of camels, assigning them to three groups: the first parity group, the third parity group, and the fifth parity group. The fecal microbial community of lactating camels was assessed using 16S rRNA amplicon sequencing, and the resulting library was sequenced on an Illumina NovaSeq platform. The first parity group was characterized by Verrucomicrobiaceae as a distinctive bi-omarker, whereas Clostridiaceae exhibited a similar role to the third parity group. In terms of functional analysis, the relative abundance of the Steroid biosynthesis pathway was highest in the first parity group, whereas the fifth parity group demonstrated a higher relative abundance of the Tuberculosis pathway compared to the other groups. The first parity group exhibited the greatest presence of seven types of enzymes, whereas the fifth parity group displayed the highest levels of two specific enzymes. Additionally, a positive association was observed between the relative abundance of the Steroid biosynthesis pathway and Verrucomicrobiaceae. Furthermore, the relative abundance of the Tuberculosis pathway displayed positive correlations with 14 enzymes. In conclusion, this study revealed that different parity was associated with distinct fecal microbial ecologies in lactating Bactrian camels.

In the context of restorative dentistry and the use of different techniques and dental adhesive systems, this study was to designed to assess the degree of adhesive absorption and wetting for each dental micro applicator; and also quantify the amount of lost fiber flocks after three applications of dental adhesive on the inside surface of a plastic veneer tooth in order to reveal a potential contaminating factor at the adhesive interface. Initially, one drop of dental adhesive was dispensed into a glass dental mixing well. The dental adhesive was then applied onto the inside surface of the veneer restoration for 30s using a dental micro applicator which was weighed afterwards. For each dental micro applicator, this sequence was repeated three times and measured again by the same operator. Each adhesive application was analyzed separately, to show the values independently and compare them to the initial weight. The samples of Fiber-Free Elastomer Bristle Micro Applicators (FEBM) demonstrated the best performance with a good degree of absorption and wetting of the dental adhesive without the loss fiber flocks and release-induced weight loss. The samples of Conventional Fiber Flocked Micro Applicators (CFFM) demonstrated good initial absorption and wetting of the dental adhesive, but visually shed several fiber flocks which resulted in significant weight loss and can also be considered a contaminating factor at the adhesive interface.

The use of Retrieval-augmented generation (RAG) using large language models (LLMs) has shown potential for addressing issues such as hallucinations and inadequately contextualized responses. A pivotal stage in the RAG process involves a retriever for retrieving chunks based on semantic similarity with the query. In this study, we advocate for and provide experimental evidence supporting integrating and maintaining questions and answers (QA) formatted databases to improve retrieved-context representations and response quality. Our experiments evaluate our approach on benchmark RAG datasets using standard evaluation metrics and provide comparative analyses against state-of-the-art retrieval methods, showing the potential of our approach.

Today, polymeric Drug Delivery Systems (DDS) appear as an interesting solution against bacterial resistance, having great advantages such as low toxicity, biocompatibility, and biodegradability. In this work, two polyketones (PK) have been post-functionalized with taurinate (PKT) or sulfanilate (PKSK) and employed as biocompatible carriers for Vancomycin against bacterial infections. Mod-ified PKs were easily prepared by Paal-Knorr reaction and loaded with Vancomycin at variable pH. All polymers were characterized by FT-IR, DSC, TGA, SEM and elemental analysis. Antimicrobial activity was tested against Gram positive Staphylococcus aureus ATCC 25923 and correlated to the different pH used for its loading (between 2.3 and 8.8). Distinctively, minimum inhibitory con-centrations achieved with PKT and PKSK loaded with Vancomycin are similar, 0.23μg/mL and 0.24μg/mL respectively, i.e. six times lower that Vancomycin alone. The use of post-functionalized aliphatic polyketones has thus been demonstrated to be a promising way to obtain very efficient polymeric DDS.

The main goal of our scientific study is to determine the particular characteristics of the endo-scopic image of the otorhinolaryngologic pathology of nasopharynx, which is called chronic rhinosinusitis in association with gastroesophageal acid reflux disease. Background/Objectives: to identify a specific features in the endoscopic picture of chronic rhinosinusitis associated with acid gastroesophageal reflux disease symptoms. Methods: there were selected 521 adult patients, from this sample as a main group we have selected only 95 patients with the highest scores on the Reflux Symptom Index (RSI) (>20) and Reflux Symptom Score-12 (RSS-12) (>130) questionnaires. As a control group we have selected 41 adult patients only with chronic rhinosinusitis and 10 healthy patients. Results: there were significant changes in the nasopharyngeal mucosa. In-creased vascularity of the nasopharyngeal mucosa was noted in 91 patients (95,7%). Hypertrophy of the nasopharyngeal mucosa was found in 83 patients (87,4%). In 77 (81,1%) patients, mucus was found in the nasopharynx with different characteristics of color and consistency, and no mucus or other secretions were found in the middle nasal passages in these patients. In 62 pa-tients (65,3%) asymmetric hypertrophy of the mucosa of the oropharynx was noted. Conclusions: the presence of specific features of the endoscopic picture of the nose and nasopharynx of pa-tients with chronic rhinosinusitis associated with gastroesophageal disease symptoms and pro-posed a method for assessing the degree of influence of gastroesophageal reflux disease on the mucosal layer of the nose and nasopharynx. The possible influence of symptoms of gas-tro-oesophageal reflux disease on the course and severity of clinical manifestations of exacerba-tions of chronic rhinosinusitis needs further investigation.

Although researchers have proposed various indentation size effect (ISE) models, these models often involve different form and number of parameters that can make our wonder which is the best in existed ISE models. Three types of ISE test data, namely, normal ISE, reverse ISE and transition of normal to reverse ISE, are used to evaluate the sixteen ISE models. The comparatively study indicates that H-J, N-G-Fs, N-G-H, N-G-A and N-G-Qs models can accurately predict the normal ISE. The reason for this is that the friction stress that is not related to dislocation activities or the indentation size effect of plastic zone has been introduced into these models. Therefore, these two factors should be considered in future ISE models. The sixteen ISE models are originally proposed to describe the normal ISE of different materials. However, to our surprise, some of these models are able to capture the reverse ISE and the transition of normal to reverse ISE of different materials. The determination coefficients (DC) of the sixteen ISE models are also determined for different materials. For reverse ISE, the highest DC value for NiCSi, TC4 and PED Ni are given by the EXP, N-G-Fs and N-G-A models, respectively. For the transition of normal to reverse ISE, the N-G-YC, N-G-Fs, and N-G-H models produce the maximum DC for ZrO2, Cu and Y2O3-ZrO2, respectively. Moreover, the mean DC of the N-G-Fs model is the maximum among the sixteen ISE models, followed by the N-G-H model, but they cannot accurately predict the reverse ISE. Therefore, the N-G-Fs and N-G-H models should be further modified to accurately predict the reverse ISE.

Analysis of immediate effects of the COVID-19 pandemic on SMEs in Rwanda aims to assess and quantify the economic and financial impacts of the pandemic during the lockdown and presents options adopted by SMEs to reopen their business opera-tions. It also seeks to recommend options for sustainable and resilient economic recovery from the scars of COVID-19. This analysis used data collected from nearly 220 SMEs located across the country and applied an Exploratory Data Analysis (EDA) and multivariate linear regression models to measure the pandemic effects. The study revealed that firms downsized employment by 36.4 per cent, but data depict significant deviation within SMEs by their size. The COVID-19 pandemic has had a greater magni-tude of negative effects on sales levels among small businesses. Tax amounts were reduced amidst the crisis however, data do not show any significant variations among SMEs. Additionally, SMEs owners applied various coping mechanisms during re-opening. The study used firm-level data, providing detailed and reliable effects of the shocks on business performance. This analysis recommends establishing the medium-term financing and technical support for SMEs to ensure steady and sustainable recovery from pandemic effects as well as strengthening their resilience to any other socio-economics shocks.

In this review we collect some recent achievements in the accurate and efficient solution of the Nonlinear Schrödinger Equation (NLSE), with the preservation of its Hamiltonian structure. This is achieved by using the energy-conserving Runge-Kutta methods named Hamiltonian Boundary Value Methods (HBVMs) after a proper space semi-discretization. The main facts about HBVMs, along with their application for solving the given problem, are here recalled and explained in detail. In particular, their use as spectral methods in time, which allows efficiently solving the problems with spectral space-time accuracy.

The escalating global population and subsequent demand for agricultural products have led to a surge in agricultural waste generation, posing significant disposal challenges. Conventional disposal methods such as burning and dumping not only harm the environment but also jeopardize human health and safety. Recognizing the urgent need for sustainable waste management, researchers have increasingly focused on repurposing agricultural plant waste as a valuable resource. This paper presents a comprehensive review of the potential of agricultural plant waste in wealth creation and sustainable development. It highlights the detrimental impacts of current disposal methods and emphasizes the necessity for alternative approaches. By analyzing the physical, mechanical, and chemical properties of plant fibers, particularly cellulose, hemicellulose, and lignin, this review underscores their suitability for diverse applications. Moreover, it explores the emerging trend of utilizing pineapple leaf fiber, a sustainable and lightweight material, in structural applications such as UAV construction. With its exceptional mechanical properties and biodegradability, pineapple leaf fiber holds promise as a viable alternative to traditional materials, contributing to a more sustainable future. In conclusion, this review advocates for a paradigm shift towards embracing agricultural plant waste as a valuable asset for economic prosperity and environmental sustainability. It underscores the importance of continued research and technological advancements to unlock the full potential of agricultural waste in fostering a circular economy and driving sustainable development globally.

Background: Obesity among pregnant women is common, and their offspring are predisposed to obesity, insulin resistance, and diabetes. Circulating metabolites that are related to insulin resistance and are associated with this decreased tissue-specific uptake are unknown. Here, we assessed metabolite profiles in elderly women and who were either female offspring from obese mothers (OOM) or offspring of lean mothers (OLM). Metabolic changes were tested for associations with metrics for insulin resistance. Methods: 37 elderly women were separated into an elderly offspring from obese mothers (OOM; n = 17) and elderly offspring from lean/normal weight mothers (OLM; n = 20) groups. We measured plasma metabolites using 1H-NMR and also insulin-dependent tissue specific glucose uptake in skeletal muscle were assessed. Associations were made between metabolites and glucose uptake. Results: Compared to the OLM group, we found that the 22:6 docosahexaenoic acid percentage of the total long chain n-3 fatty acids (DHA/FA) was significantly lower in OOM (P = 0.015). DHA/FA associated significantly to skeletal muscle GU (P = 0.031) and M-value in the OLM group only (P = 0.050). Conclusions: DHA/FA is associated with insulin-dependent skeletal muscle glucose uptake and that this association is significantly weakened in the offspring of obese mothers.

Pancreatic ductal adenocarcinoma (PDAC) represents an extremely aggressive type of cancer due in part to early invasion and metastasis, which in turn involves epithelial-mesenchymal transition (EMT) of the tumor cells. Prompted by the discovery that two PDAC-derived tumor cell lines of the quasi-mesenchymal subtype (PANC-1, MIA PaCa-2) exhibit neuroendocrine differentiation (NED), we asked whether NED is associated with EMT. Using quantitative real-time PCR and immunoblot analysis, we initially verified endogenous expression of various NED markers, i.e., chromogranin A (CHGA), synaptophysin (SYP), somatostatin receptor 2 (SSTR2) and SSTR5 in PANC-1 and MIA PaCa-2 cells. In HPDE6c7 normal pancreatic duct epithelial cells and in BxPC-3, another PDAC cell line with an epithelial phenotype, the expression of CHGA, SYP and neuron-specific enolase 2 (NSE) was either undetectable or much lower than in PANC-1 and MIA PaCa-2 cells. Parental cultures of PANC-1 cells exhibit EM plasticity (EMP) and harbor clonal subpopulations with different EMT phenotypes [Ungefroren et al 2022]. Monitoring the NED state of mesenchymal and epithelial PANC-1 subclones showed that the NE phenotype is more pronounced in M-type clones when compared to E-type ones. Inducing EMT in parental cultures of PANC-1 cells by treatment with transforming growth factor (TGF)-β1 repressed epithelial genes and co-induced mesenchymal and NED genes, except for SSTR5. Surprisingly, treatment with bone morphogenetic protein (BMP)-7 differentially affected gene expression in PANC-1 and MIA PaCa-2 cells. It synergised with TGF-β1 in the induction of vimentin, SNAIL, SSTR2 and NSE but antagonised it in the regulation of CHGA and SSTR5. From these data, we conclude that in EMT of PDAC cells mesenchymal and NED markers are co-regulated, and that mesenchymal-epithelial transition (MET) is associated with a loss of both the mesenchymal and NED phenotypes. Analysing NED in another tumor type, small cell carcinoma of the ovary hypercalcemic type (SCCOHT), revealed that two model cell lines of this disease (SCCOHT-1, BIN-67) do express CDH1, SNAI1, VIM, CHGA, SYP, ENO2 and SSTR2, but that in contrast to BMP-7 none of these genes was transcriptionally regulated by TGF-β1. We conclude that in PDAC-derived tumor cells, NED is closely linked to EMT and TGF-β signaling, which may have implications for the therapeutic use of TGF-β inhibitors in PDAC management.

Abstract: The study used whole-genome sequencing (WGS) and bioinformatics analysis for the genomic characterization of 60 isolates of Listeria monocytogenes isolated from cattle farms, cattle abattoirs, and retail outlets in Gauteng province, South Africa. The isolates' sequence types (STs), clonal complexes (CCs), and lineages were determined using in silico multilocus sequence typing (MLST). We used BLAST-based analyses to identify virulence and antimicrobial genes, plasmids, proviruses, and the CRISPR-Cas system. The study investigated any association of the detected genes to the origin in the beef production chain of the L. monocytogenes isolates. Overall, in 60 isolates of Listeria monocytogenes, there were 7 STs, 6 CCs, 44 putative virulence factors, 2 resistance genes, 1 plasmid with AMR genes and 3 with conjugative genes, 1 CRISPR gene, and all 60 isolates were positive for proviruses. Among the 7 STs detected, ST204 (46.7%) and ST2 (21.7%) were the most prominent, with ST frequency varying significantly (p&lt;0.001). The predominant CC detected were CC2 (21.7%) and CC204 (46.7%) in lineages I and II, respectively. Of the 44 virulence factors detected, 26 (across Listeria Pathogenicity Islands, LIPIs) were present in all the isolates. The difference in the detection frequency varied significantly (P&lt;0.001). The two AMR genes (fosX and vga(G)) detected were present in all 60 (100%) isolates of L. monocytogenes. The only plasmid, NF033156, was present in 3 (5%) isolates. A CRISPR-Cas system was detected in 6 (10%), and all the isolates carried proviruses. Significant differences were detected in the frequencies of STs and virulence factors regarding the source and sample type of the L. monocytogenes isolates. The presence of both fosX and vga(G) genes in all the isolates from the three industries (cattle farms, abattoirs, and retail outlets) can potentially cause therapeutic implications. Our study, which characterized L. monocytogenes recovered from the three levels in the beef production chain in the country, provides the first evidence of the distribution of the pathogen with potential food safety and therapeutic implications.

Pituitary adenylate cyclase-activating polypeptide receptor 1 (PAC1-R) has a higher affinity for pituitary adenylate cyclase- activating polypeptide (PACAP) than for vasoactive intestinal peptide (VIP). PACAP exerts its neuroprotective effects through PAC1-R. PAC1-R has become a target for drug development, and we targeted PAC1-R to screen small positive allosteric modulator 1 (SPAM1). SPAM1 has a neuroprotective effects, and in the D-galactose (D-gal) mouse model, SPAM1 improved the structure of the hippocampal dentate gyrus and restored the number of neurons. Compared with D-gal model mice, SPAM1 treatment upregulated the expression of Sirtuin 6 (SIRT6) and Lamin B1, and downregulated the expression of YinYang 1 (YY1) and p16. Consistent with this, the same results were obtained in senescent RGC-5 cells. Meanwhile, SPAM1 was also found to up-regulate SIRT6 and down-regulate YY1 expression in normal RGC-5 cells. Then, we further explored the mechanism of SPAM1 neuroprotection by whole transcriptome sequencing and proteomic analysis, and found that SPAM is involved in the longevity regulating pathway, and confirmed the up-regulation of neurofilament light polypeptide and neurofilament medium polypeptide by western blot, thus laying a pharmacological foundation for SPAM1 as a therapeutic agent for neurodegenerative diseases. polypeptide and neurofilament medium polypeptide. Thus, it lays a pharmacological foundation for SPAM1 as a therapeutic drug for neurodegenerative diseases.

Today, it is difficult to have a high-field nuclear magnetic resonance device (NMR) due to the high cost of its acquisition and maintenance. These high-end machines require significant space and specialist personnel for operation and offer exceptional quality in the acquisition, processing, and other advanced functions associated with detected signals. However, alternative devices are low-field nuclear magnetic resonance devices. They benefit from the elimination of high-tech components that generate static magnetic fields and advanced instruments. Instead, they used magnetic fields induced by ordinary conductors. Another category of spectrometers uses the Earth's magnetic field, which is simple and economical, but limited in use. These devices are called Earth Field Nuclear Magnetic Resonance (EFNMR). This device is ideal for educational purposes, especially for engineers and those who study nuclear magnetic resonance, such as chemistry or other experimental sciences. Students can observe their internal workings and conduct experiments that complement their education without worrying about damaging equipment. This article provides a detailed explanation of the design and construction of electrical technology devices for the excitation of atomic spin resonance using Earth's magnetic fields. Covers all necessary stages, from research to analysis, from simulation, assembly, construction of each component, and the development of comprehensive software for spectrometer control.

Outliers seriously affect the accuracy in geometric model fitting. Previous works in coping with outliers involve threshold selection and scale estimation. However most scale estimators suppose the inlier distribution as a Gaussian model, which usually poorly meets the cases in geometric model fitting. Outliers, considered as the points with big residuals to all the true models, share common items with big values in quantized residual preferences, thus making the outliers gather away from the inliers in quantized residual preference space. In this paper we make use of this outlier consensus in quantized residual preference space by extending the usage of energy minimization to combine the model error and the spatial smoothness in quantized residual preference space for outlier detection. The energy minimization based outlier detection process follows an alternate sampling and labeling framework. After the outlier detection, an ordinary energy minimization method is employed to optimize the inlier labels, which also follows the framework of alternate sampling and labeling. The experimental results in this study show that the energy minimization based outlier detection method can detect most of the outliers in the data. Furthermore, the proposed energy minimization based inlier segmentation process segments the inliers into different models quite accurately. Overall, the performance of the proposed method is better than most of the state-of-the-art methods.

The global increase in population has placed significant pressure on food security, leading to the emergence of aquaculture as a vital source of aquatic foods. However, rising costs and the limited availability of fishmeal in aquafeeds have spurred the search for alternative protein sources. While plant-based ingredients have been integrated into commercial aquafeeds, they come with challenges, including low protein content, palatability issues, and the presence of antinutritional factors. In this context, fish silage, derived from fish waste and discarded fish, stands out as a promising alternative technology due to its cost-effectiveness and sustainability attributes. The production of fish silage involves the addition of organic/inorganic acids or lactic acid bacteria to homogenized fish waste. This process yields a valuable mixture rich in peptides, free amino acids, and partially hydrolyzed proteins, offering significant nutritional benefits for animal diets. Beyond its nutritional advantages, fish silage contributes to environmental sustainability by reducing the impact of waste disposal and enhancing the value of fish waste. The objective of this review is to promote sustainable practices in the aquaculture industry in response to the increasing demand for high-quality feed nutrients. To achieve this, it includes an analysis of research results related to silage technology, an appraisal of the advantages and disadvantages of using fish silage as a feed additive, and a focus on emerging trends in this field.

The Vu Gia - Thu Bon River Basin (VG-TB) is confronting numerous challenges related to water security (WS), particularly in the face of the impacts of climate change. These challenges manifest in salinity intrusion, altered rainfall patterns, and reduced water supply in downstream areas. To assess the current state of water security in the basin, the study employed statistical analysis methods, Process Analysis Method (PAM), SMART, and Analytic Hierarchy Process (AHP) to develop a comprehensive Assessment Framework for Water Security (AFWS) in the VG-TB. The AFWS encompasses five key dimensions, 17 indicators, and 28 variables, aligning with the UN-Water definition of water security and addressing the Sustainable Development Goal 6 (SDG6) criteria for global water sustainability. It also adheres to the Asian Development Bank's (ADB) approach to water security assessment as outlined in the Asian Water Development Outlook (AWDO) reports. This allows for the computation of a comprehensive Water Security Index (WSI) for specific regions, serving as a foundation for decision-making and policy formulation aimed at enhancing water security in the context of climate change and facilitating sustainable basin development in the future.

Schizophrenia is a complex mental disorder influenced by genetic and environmental factors, including diet. Oxidative stress and inflammation play a crucial role in the pathophysiology of schizophrenia. Nutritional deficiencies, such as lack of omega-3 fatty acids, vitamin D, and B vitamins, during prenatal and postnatal periods can nega-tively impact neurodevelopment and increase the risk of schizophrenia. Patients with schizophrenia show imbalances in antioxidant enzymes such as: glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase (CAT) and reduced levels of antioxidants (vitamin E, vitamin C), leading to increased oxidative stress markers such as malondialdehyde (MDA). Cytokine-mediated inflammation, microglial activation, and gut dysbiosis are associated with schizophrenia onset and symptom severity. There is no clear and universally accepted diet for the treatment of schizophrenia, which is considered the most popular. However, various diets and nutritional methods are being researched and applied to alleviate the symptoms of schizophrenia and improve the general health of patients, including the mediterranean diet, ketogenic diet, gluten-free diet and DASH diet. A healthy diet rich in anti-inflammatory and antioxidant nutrients can help manage schizophrenia by reducing oxidative stress, preventing complications, and improving quality of life. Omega-3 fatty acids, vitamin D and B vitamins are par-ticularly important for brain development and function. In this review we will focus on the influence of diet on schizophrenia. Additional research is needed to develop per-sonalized dietary recommendations for patients with schizophrenia.

The research aims to discover the natural occurrence of patulin (PAT) in selected citrus fruits from the central cities of Punjab and Pakistan's Northern cities. Total 2970 samples of twelve citrus fruits; kinnow, orange, grapefruits, bitter orange, mausami, red blood, pineapple, sweet orange, rough lime, sweet lime, kagzi lime and lemon were examined using liquid chromatography fitted with UV detector. The limit of detection (LOD) and quantification limit was 0.04 and 0.12 µg/kg, respectively. The results have shown that 56% of samples of citrus fruits from Punjab's central cities, Pakistan, were discovered to be infected from PAT. The elevated amounts of PAT ranging from 0.04 to 1150 µg/kg were found in citrus fruit samples from Multan cities. Furthermore, 31.7% of samples of citrus fruits from Northern cities of Pakistan were discovered to be infected with PAT, and the elevated amounts were found ranging from 0.04-320 µg/kg from Swat city. About 22.1% of samples of citrus fruits have levels of PAT greater than the suggested limits established by the European Union (EU). PAT's dietary intake levels ranged from 0.10-1.11 µg/kg bw/day from the central cities of Punjab, Pakistan, and 0.13-1.93 µg/kg bw/day were documented from Northern cities of Pakistan.

The research aims to discover the natural occurrence of patulin (PAT) in selected citrus fruits from the central cities of Punjab and Pakistan's Northern cities. Total 2970 samples of twelve citrus fruits; kinnow, orange, grapefruits, bitter orange, mausami, red blood, pineapple, sweet orange, rough lime, sweet lime, kagzi lime and lemon were examined using liquid chromatography fitted with UV detector. The limit of detection (LOD) and quantification limit was 0.04 and 0.12 µg/kg, respectively. The results have shown that 56% of samples of citrus fruits from Punjab's central cities, Pakistan, were discovered to be infected from PAT. The elevated amounts of PAT ranging from 0.04 to 1150 µg/kg were found in citrus fruit samples from Multan cities. Furthermore, 31.7% of samples of citrus fruits from Northern cities of Pakistan were discovered to be infected with PAT, and the elevated amounts were found ranging from 0.04-320 µg/kg from Swat city. About 22.1% of samples of citrus fruits have levels of PAT greater than the suggested limits established by the European Union (EU). PAT's dietary intake levels ranged from 0.10-1.11 µg/kg bw/day from the central cities of Punjab, Pakistan, and 0.13-1.93 µg/kg bw/day were documented from Northern cities of Pakistan

Background and Objectives: To analyze survival in peritoneal and hemodialysis patients using chest radiography and biochemical parameters, determine dialysis etiologies and common mortality causes, reveal prognostic factors, and contribute to clinical practice. Materials and Methods: This retrospective cohort study was based on the analysis of data from 33 peritoneal dialysis and 37 hemodialysis patients who were followed and treated in our hospital between October 2018 and February 2020. Chest X-ray measurements (cardiothoracic index, pulmonary vascular pedicle width, right pulmonary artery diameter, diaphragmatic height) and biochemical parameters (urea, albumin, creatinine, parathormone, ferritin, hemoglobin, arterial blood gas, potassium) were analyzed to assess their impact on survival. Statistical analyses were performed using the Shapiro-Wilk, Wilcoxon signed rank test, Mann-Whitney U test, McNemar test, Kaplan-Meier survival analysis, Cox regression analysis, Spearman correlation test, Phi test, and ROC analysis. Results: The most common etiologies of dialysis were hypertension, type 2 diabetes mellitus, and urogenital disorders. The most common cause of death in peritoneal dialysis patients was peritonitis (38.5%), while in hemodialysis patients, it was cardiovascular diseases (47.4%). In chest X-ray measurements, pulmonary vascular pedicle width (p=0.003) and pulmonary artery diameter increased significantly (p=0.002) in hemodialysis patients, while pulmonary vascular pedicle width (p=0.028) and diaphragmatic height (p=0.004) increased significantly in peritoneal dialysis patients. No significant difference was found between the two groups in terms of biochemical parameters. Kaplan-Meier survival analysis showed that there was no significant difference in survival between peritoneal dialysis and hemodialysis methods (P>0.05). Significant correlations were found between both radiologic status and clinical status and between intact parathormone levels and pulmonary vascular pedicle width (p=0.016, p=0.024). In Cox regression analysis, age, intact parathormone levels, iPTH/PVPW ratio, and clinical status were found to be factors affecting survival (p

Abstract: Doppler renal resistive index (RRI) has been used for several decades as a potential indi-cator for renal disease and progression. In recent years, RRI has emerged as a useful prognostic indicator for a range of co-morbidities in patients who are acutely unwell and as a potential marker for sub-clinical acute kidney injury (AKI) and post procedural AKI risk. Despite this, the clinical and theoretical determinants of RRI are poorly understood and remain contentious. Method: A narrative review of studies exploring the theoretical, experimental, and clinical evidence for factors affecting RRI. No date restrictions were set. Findings: Both experimental and clinical data confirm that RRI is markedly affected by a range of systemic and renal determinants and is influenced closely by the underlying risk factors and sys-temic vascular changes that lead to progressive renal damage. Discussion: This paper provides an overview of the key haemodynamic determinants of renal re-sistive index and aims to clarify their relative importance. With reference to a simplified theoretical model, evidence from experimental and clinical studies is reviewed. Pathophysiological factors and patient characteristics that influence RRI are explored to provide a better understanding of why RRI values change in the presence of common or complex pathologies. Conclusion: By gaining a better understanding of the complex systemic and renal factors that influ-ence RRI, ultrasound users will be better prepared to understand and interpret changes in RRI across a range of patient presentations.

The mineralogical indices, e.g., Quartz Index (QI), Carbonate Index (CI), Mafic Index (MI) for ASTER multispectral thermal infrared (TIR) data have been applied to various geological materials. The indices are proved to be robust in extracting geological information at the local scale. Considering the relatively narrow spatial coverage of each ASTER scene compared to LANDSAT, many scenes are needed when mosaicking the images to be mapped at regional scales. We develop a system to search ASTER data for a target area given the vast and expanding ASTER data archive. The data is then conditioned, prioritized, and the indices are calculated before finally mosaicking the imagery. The maps of the indices covering the very wide region of the central Tibetan Plateau are produced with this system. The characteristic features of the indices relating to their geology in the study area are analyzed and discussed. Many interesting lithological and structural information that are not currently well understood in the central Tibetan Plateau, the highest and most extensive plateau in the world, with an average elevation of over 4,500 meters above sea level, for example, distributions of the mafic-ultramafic rocks along the suture zones, the quarzitic and marine sedimentology accreted to the Eurasian continent and sulfate layers related to the Tethys and neo-Tethys geological setting can be retrieved from the processed ASTER images.

Cognitive deterioration caused by illness or aging often occurs before symptoms arise, and their timely diagnosis is crucial to reducing its medical, personal, and societal impacts. Brain-Computer Interfaces (BCIs) stimulate and analyze key cerebral rhythms, enabling reliable cognitive assessment that can accelerate diagnosis. The BCI system presented analyzes Steady-State Visually Evoked Potentials (SSVEPs) elicited in subjects of varying age to detect cognitive aging, predict its magnitude, and identify its relationship with SSVEP features (band power and frequency detection accuracy), which were hypothesized to indicate cognitive decline due to aging. The BCI system was tested with subjects of varying age to assess its ability to detect aging-induced cognitive deterioration. Rectangular stimuli flickering at theta, alpha, and beta frequencies were presented to subjects, and frontal and occipital EEG responses were recorded. These were processed to calculate detection accuracy for each subject and calculate SSVEP band power. A neural network was trained using the features to predict cognitive age. The results showed potential cognitive deterioration through age-related variations in SSVEP features. Frequency detection accuracy declined after age group 20–40 and band power, throughout all age groups. SSVEPs generated at theta and alpha frequencies, especially 7.5 Hz, were the best indicators of cognitive deterioration. Here, frequency detection accuracy consistently declined after age group 20-40 from an average of 96.64% to 69.23%. The presented system can be used as an effective diagnosis tool for age related cognitive decline.

Quantum amplitude estimation is a numerical integration technique and a candidate for the first operationally used quantum algorithm providing a quantum advantage in the NISQ era. Its main metric is the generated Fisher information per second, as it describes the accuracy of the numerical integration. The development of this metric can be coupled to the quantum volume of the used quantum processor with a phenomenological noise model. Since the increase of the quantum volume seems to follow an exponential pattern, insight in the integration power of quantum amplitude estimation for the upcoming years can be obtained. This shows that quantum amplitude estimation as a numerical integration technique will not provide an advantage for functions without significant improvements to the connectivity, reliability and speed of quantum processors. Beyond that, this method may be used the estimate the development of many more NISQ era algorithms.

The aim of the study is to assess the loads that are transferred from the main rotor and the tail rotor to the helicopter fuselage. These loads change in the various phases of the transient flight as a result of the variable control of the maneuver and as a result of the variable flow around the blades. The knowledge of the loads allows for the proper selection of the level of excitations that should load the fuselage structure during fatigue and strength tests. The simulation model describing the helicopter flight is discussed. This model takes into account the motion of each blade relative to its hinges. Results are shown for two maneuvers - pullup/pushover and diving. The values of extreme loads transferred to the fuselage were obtained.

An effective empirical statistical method is developed to improve the process of mineral resource estimation of seabed polymetallic nodules and is applied to analyse the abundance of seabed polymetallic nodules in the Clarion Clipperton Zone (CCZ). The newly proposed method is based on three hypotheses as the foundation for a model of “Idealized Nodules”, which was validated by analysing nodule samples collected from the seabed within the Tonga Offshore Mining Limited (TOML) exploration contract. Once validated, the “Idealized Nodule” model was used to deduce a set of empirical formulae for predicting the nodule resources, in terms of Percentage Coverage and Abundance. The formulae were then applied to analysing a total of 188 sets of nodule samples collected across the TOML areas, comprising box-core samples and towed camera images collected by one of the authors and detailed in [4]. The analysis also relies upon detailed box-core sample measurements from other areas reported by [7]. Numerical results for resource prediction were compared with field measurements, and reasonable agreement has been achieved. The new method has the potential to achieve more accurate mineral resource estimation with reduced sample numbers and sizes. They may also have application in improving the efficiency of design and configuration of mining equipment.

This paper proposes a real-time local positioning system (RT-LPs) utilizing a mobile platform equipped with three anchor nodes placed in a right-angle triangle formation for a real-time locating system (RTLS). After deriving an analytic formula to calculate the target position utilizing the measured distances among anchor nodes and the target node, we find that four parameters have an effect on the position error of the target node. The spacing between anchors is a design parameter that must be large enough to the reduce position error. However, the distance from the anchor node to the target node is an operation parameter that must be small enough to reduce the position error. Additionally, the measured ranges among the anchors and the target node have probabilistic distributions with a mean and variance, which are dominant parameters that have effects on the position error. A comparison study was conducted to determine the effects of the parameters of the target position in both a simulation and an experiment, showing rates of approximately 4% ~ 10%. These findings indicate that our simulation can work properly with the proposed method after assuming that the distance error is a Gaussian model.

The current study aimed to: i) Monitor levels of PM₁₀, at Shebika, Haram, Masfala, Azizia, Awali and Mina in Makkah city, KSA during the period of 01 Shawwal 1436H – 27 Rabi Al-Awwal 1437H, by using LVS instruments; and; 2) assess health risk (non-cancer and cancer risks) on humans (children and adult) exposed to PM₁₀ in ambient air of Makkah city.The results showed that: the high PM₁₀ levels were found in Haram site, while the lower levels were found in Awali site. These levels were lower than that set for PM₁₀ by PME (Daily limit of 340 µg/m³). Vehicles emissions and constructions sources may be the main source of PM₁₀ levels in Makkah city. The human health risk assessments showed that: the daily exposure doses of PM₁₀ were ranked in the order: D_ing > D_dermal > D_inh for children and adult in Makkah city. Ingestion of PM₁₀ particles was the main exposure pathway for both children and adults. The HIs and cancer risk values were within the safe level, indicating that (non-carcinogenic and carcinogenic) risks for humans exposed to PM₁₀ in Makkah city were negligible.

Debates regarding human capital disclosure (HCD) emphasise the usefulness of people-related information in stimulating investor confidence and building stakeholder trust. Despite this, human capital (HC) information is interwoven in most international sustainability reporting standards such as the global reporting initiative (GRI), thereby concealing the impact of human resource (HR) practices in shareholder value creation. The aim of this study is to develop a taxonomy to assess HCD in the sustainability reports to capture the true value of HC distinctively. A content analysis-based study with a deductive approach was followed by utilising the GRI standards to isolate and classify people-related information into an HCD sustainability taxonomy. 40% HC metrics were extracted from the GRI standards and subsequently classified into 7 dimensions, namely, human capital allocation, human capital wellbeing, human capital investment, human capital network, human capital governance, human capital risk and human capital earnings. Furthermore, 40 GRI content indexes of the companies listed in the Johannesburg Stock Exchange (JSE) revealed that most disclosures are covered in the human capital governance and human capital earnings categories. HCD sustainability provides investors and HR professionals with a useful tool to assess people-related information from the sustainability reports for isolating the true value of HC.

The introduction of Maritime Autonomous Surface Ship (MASS) through the development of autonomous navigation technologies is expected to bring about new technologies, new vessel types, and new job roles such as remote operation center (ROC) and remote operator (RO). The MASS Code are currently being discussed through Maritime Safety Committee (MSC) of International Maritime Organization (IMO). This code is expected to be adopted in the form of non-mandatory guidelines until 2025, with the goal of establishing mandatory requirements by 2028. Additionally, revisions to the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW) related to crew training and qualifications are planned for adoption by 2027, which will include requirements for MASS operators. This paper aims to examine the fundamental competencies required for safe MASS operation by remote operators using the Analytic Hierarchy Process (AHP) method, considering the emergence of the new profession of RO. Building upon the 66 Knowledge, Understanding &amp; Proficiencies (KUPs) outlined for marine officer in the STCW Convention, the study seeks to identify the additional competencies necessary for RO and contribute to the development of a training model for the future.

The role of natural factors mainly solar eleven-year cycle variability, and volcanic eruptions on two major modes of climate variability the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) are studied for around last 150 years period. The NAO is the primary factor to regulate Central England Temperature (CET) during winter throughout the period, though NAO is impacted differently by other factors in various time periods. Solar variability indicates a strong positive influence on NAO during 1978-1997, though suggests opposite in earlier period. Solar NAO lag relationship is also shown sensitive to the chosen times of reference and thus points towards the previously proposed mechanism/ relationship related to the sun and NAO. The ENSO is influenced strongly by solar variability and volcanic eruptions in certain periods. This study observes a strong negative association between the sun and ENSO before the 1950s, which is even opposite during the second half of 20th century. The period 1978-1997, when two strong eruptions coincided with active years of strong solar cycles, the ENSO, and volcano suggested a stronger association, and we discussed the important role played by ENSO. That period showed warming in central tropical Pacific while cooling in the North Atlantic with reference to the later period (1999-2017) and also from chosen earlier period. Here we show that the mean atmospheric state is important for understanding the connection between solar variability, the NAO and ENSO and associated mechanism. It presents a critical analysis to improve knowledge about major modes of variability and their role in climate. We also discussed the importance of detecting the robust signal of natural variability, mainly the sun.

A flow chart is presented depicting coupling in ocean-atmosphere system, initiated by solar decadal variability that involves El Niño Southern Oscillation (ENSO). Possible mechanisms for Canonic ENSO, Modoki ENSO and Canonic-Modoki ENSO are proposed considering their relevance to the decadal variation of Hadley, Walker circulation and mid-latitude jets. It also discusses subsequent teleconnections by ENSO on Indian Summer Monsoon (ISM) with a special emphasis on later two decades of the last century. Possible mechanisms relating to a disruption of the usual ENSO-ISM teleconnection for those decades are emphasised; the role of volcanos and the change in the sun- NAO (North Atlantic Oscillation) connection were attended. The regional Hadley circulation, via the NAO in the northern hemisphere and Indian Ocean Dipole in the southern hemisphere, during that period, may have a role in the change in ISM behaviour- which though captured in observation but missed by models. The representation of flow chart helps to improve understanding of various types of ENSO in both temporal as well as spatial scale. The overall study subsequently can benefit the modelling community by not only improved the representation of ENSO in models but also better representation of ISM teleconnection via regional Hadley cell.

Spatiotemporal variations of sediments transported along rivers play a crucial role in a wide spectrum of uses, such as navigation, recreation, habitats or hydropower production. The advancement in technology has made it possible to use various indirect techniques to study and evaluate the transport of suspended sediment in fluvial environments. To investigate large-scale phenomena, remote sensing is becoming a largely utilized approach, as it allows to combine spatially-distributed and local information. Dam-induced sediment reduction occurs in large and small rivers worldwide, having profound implications on the fluvial systems. However, the systematic change of suspended sediment concentration (SSC) and its dynamic processes are not well known, and generally investigated only at the very local scale using field information. In this work, SSC maps were created by combining satellite images with local monitoring SSC data, using the Zhijiang -Chenglingji reach of the Changjiang River (China) as a case study, and analyzing how SSC dynamics changed over the period 2017-2022 in correspondence of extreme events. Multiple relationships between measured SSC and bands reflectance were tested, showing the potential of the best-performing one (R2=0.43) in mapping SSC spatiotemporal variations over an extent of dozens of kilometres, eventually providing new insights into the SSC dynamics at hotspots of the river systems, such as confluence zones, barriers, and reservoirs.

We propose Context-aware Feature Transformer Network (CaFTNet), a novel network for human pose estimation. To address the issue of limited modeling of global dependencies in convolutional neural networks, we design Transformerneck to strengthen the expressive power of features. Transformerneck directly substitutes the 3×3 convolution in bottleneck of HRNet with Contextual Transformer (CoT) block, while reducing the complexity of the network. Specifically, CoT first produces keys with static contextual information through 3×3 convolution. Then, relying on the query and contextualization keys, the dynamic contexts are generated through two concatenated 1×1 convolutions. Static and dynamic contexts are eventually fused as an output. Additionally, for the multi-scale networks, in order to further refine the features of the fusion output, we propose an Attention Feature Aggregation Module(AFAM). Technically, given an intermediate input, AFAM successively deduces attention maps along channel and spatial dimensions. Then, Adaptive refinement module(ARM) is exploited to activate the obtained attention maps. Finally, the input undergoes adaptive feature refinement through multiplication with the activated attention maps. Through the above studies, our lightweight network provides a powerful clue for detection of keypoints. Experiments are implemented on the COCO and MPII datasets. The model achieves 76.2 AP on the COCO val2017. Compared to other methods with the CNN as the backbone, CaFTNet reduces the number of parameters by 72.9 %. On the MPII, our method uses only 60.7% of the number of parameters, acquiring semblable results to other methods with the CNN as the backbone.

In econometrics and finance, volatility modelling has long been a specialised field for addressing a variety of issues pertaining to the risk and uncertainties of an asset. This study presents a robust framework, through a step-by-step design, that is relevant for effective Monte Carlo simulation (MCS) with empirical verifications to estimate volatility using the Generalized Autoregressive Score (GAS) model. The framework describes an organised approach to the MCS experiment that includes "background (optional), defining the aim, research questions, method of implementation, and summarised conclusion". The method of implementation is a workflow that consists of writing the code, setting the seed, setting the true parameter a priori, data generation process, and performance assessment through meta-statistics. Among the findings, it is experimentally demonstrated in the study that the GAS model with a lower unconditional shape parameter value can generate a dataset that adequately reflects the behaviour of financial time series data, relevant for volatility estimation. This dynamic framework is intended to help interested users on MCS experiments utilising the GAS model for reliable volatility calculations in finance and other areas.

This study rolls out a robust framework relevant for simulation studies through the Generalised Autoregressive Conditional Heteroscedasticity (GARCH) model using the rugarch package. The package is thoroughly investigated, and novel findings are identified for improved and effective simulations. The focus of the study is to provide necessary simulation steps for volatility estimation that involve "background (optional), defining the aim, research questions, method of implementation, and summarised conclusion". The method of implementation is a workflow that includes writing the code, setting the seed, setting the true parameters a priori, data generation process and performance assessment through meta-statistics. This novel, easy-to-understand steps are demonstrated on financial returns using illustrative Monte Carlo simulation with empirical verification. Among the findings, the study shows that regardless of the arrangement of the seed values, the efficiency and consistency of an estimator generally remain the same as the sample size increases. The study also derived a new and flexible true-parameter-recovery measure which can be used by researchers to determine the level of recovery of the true parameter by the MCS estimator. It is anticipated that the outcomes of this study will be broadly applicable in finance, with intuitive appeal in other areas, for volatility estimation.

Existing methods for 3D human pose estimation mainly divide the task into two stages. The first stage identifies the 2D coordinates of the human joints in the input image, namely the 2D human joint coordinates. The second stage uses the results from the first stage as input to recover the depth information of human joints from the 2D human joint coordinates to achieve 3D human pose estimation. However, the recognition accuracy of the two-stage method relies heavily on the results of the first stage and includes too many redundant processing steps, which reduces the inference efficiency of the network. To address these issues, we propose the EDD, a fully End-to-end 3D human pose estimation method based on transformer architecture with Dual Decoders. By learning multiple human poses, the model can directly infer all 3D human poses in the image using a pose decoder, and then further optimize the recognition result using a joint decoder based on the kinematic relations between joints. With the attention mechanism, this method can adaptively focus on the most relevant features to the target joint, effectively overcoming the feature misalignment problem in the human pose estimation task and greatly improving the model performance. Any complex post-processing step, such as non-maximum suppression, is eliminated, further improving the efficiency of the model. The results show that the method achieves an accuracy of 87.4% on the MuPoTS-3D dataset, significantly improving the accuracy of end-to-end 3D human pose estimation methods.

Age estimation in dental radiographs Orthopantomography (OPG) is a medical imaging technique that physicians and pathologists utilise for disease identification and legal matters. For example, for estimating post-mortem interval, detecting child abuse, drug trafficking, and identifying an unknown body. Recent development in automated image processing models improved the age estimation's limited precision to an approximate range of +/- one year. While this estimation is often accepted as accurate measurement, age estimation should be as precise as possible in most serious matters, such as homicide. Current age estimation techniques are highly dependent on manual and time-consuming image processing. Age estimation is often a time-sensitive matter in which the image processing time is vital. Recent development in Machine learning-based data processing methods has decreased the imaging time processing; however, the accuracy of these techniques remains to be further improved. We proposed an ensemble method of image classifiers and transfer learning techniques to enhance the accuracy of age estimation using OPGs from one year to a couple of months (1-3-6). This hybrid model is based on convolutional neural networks (CNN) and K nearest neighbours (KNN). The hybrid (HCNN-KNN) model was used to investigate 1,922 panoramic dental radiographs of patients aged 15 to 23. These OPGs were obtained from the various teaching institutes and private dental clinics in Malaysia. To minimise the chance of overfitting in our model, we used the principal component analysis (PCA) algorithm and eliminated the features with high correlation. To further enhance the performance of our hybrid model, we performed systematic image pre-processing. We applied a series of classifications to train our model. We have successfully demonstrated that combining these innovative approaches has improved the classification and segmentation and thus the age-estimation outcome of the model. Our findings suggest that our innovative model, for the first time, to the best of our knowledge, successfully estimated the age in classified studies of one year old, six months, three months and one-month-old cases with accuracies of 99.98, 99.96, 99.87, and 98.78 respectively.

Ukraine is an associate member of the European Union and in the coming years it is expected that all the data and services already used by European Union countries will become available for Ukraine. An important program, which is the basis for building European monitoring services for Smart Cities, is the Copernicus program. The two most important services of this program are Copernicus Land Monitoring Service (CLMS) and Copernicus Atmosphere Monitoring Service (CAMS). CLMS provides important information on Land Use in Europe. In the context of Smart Cities, the most valuable one is the Urban Atlas service, which is related to local CLMS services and provides a detailed digital city plan in vector form, which is segmented into small functional areas classified by the CORIN nomenclature. The Urban Atlas is a geospatial layer with high-resolution, which is built for all European cities with a population of more than 100,000 that combines high-resolution sat-ellite data, city segmentation by blocks and functional areas, important city infrastructure, etc. This product is used as a basis for city planning and obtaining analytics on the most important indicators of city development including air quality monitoring. For Ukraine, such geospatial products are not provided under the Copernicus program. It is important to start work on its development and implementation as early as possible, so that when the first city atlas appears, Ukraine will be ready to work with it together with the European community. This requires preparing the basis for na-tional research and training national stakeholders and users to use this product. To make this happen it’s necessary to have national geospatial product, which can be used as an analogue of the city atlas. In this article authors analyzed the existing methods of air quality assessment and assessment of the SDG indicator 11.6.2 achieving for European cities, based on which the indicator 11.6.2 for Ukraine for 5 years was evaluated for the first time. The obtained results are analyzed and the values of indicator 11.6.2 for Ukraine are compared with European countries.

In recent years, since the propagation channel characteristics have been effectively used for applications such as motion sensing, position detection, etc. A great deal of attention is attracted to channel sounding methods easy to utilize using low-cost devices. This paper presents a device-free indoor location estimation method using spatio-temporal features of radio propagation channels using the 2.4-GHz band 3-by-3 MIMO channel sounder developed using commodity wireless LANs. The measurement results demonstrated a reasonable performance of the proposed method with small number of antennas.

This paper proposes the use of compressive sensing to tackle the Massive MIMO channel estimation problem. As our results show compressive sensing-based estimators perform as well as the optimum MMSE estimator.

For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affect the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination resulting in a large baseline error, leads to the modulation error in azimuth and the slope error in range for timely Digital Elevation Model (DEM) generation. In order to address this problem, a baseline estimation method based on external DEM is proposed in this paper. Firstly, according to the characteristic of the real-time orbit of GF-3 images, orbit fitting is executed to remove the non-linear error factor. Secondly, the height errors are obtained in slant-range plane between Shuttle Radar Topography Mission (SRTM) DEM and the GF-3 generated DEM after orbit fitting. At the same time, the height errors are used to estimate the baseline error which has a linear variation. In this way, the orbit error can be calibrated by the estimated baseline error. Finally, DEM generation is performed by using the modified baseline and orbit. This procedure is implemented iteratively to achieve a higher accuracy DEM. Based on the results of GF-3 interferometric SAR data for Hebei, the effectiveness of the proposed algorithm is verified and the accuracy of GF-3 real-time DEM products can be improved extensively.

Cestrum parqui L'Herit. (Solanaceae family) is a species of forest shrub, self-incompatible and specialized in pollination, widespread in the subtropical area of the planet and now widely dis-tributed also in the Mediterranean area. The constituents of its leaves have antimicrobial, anti-cancer, insecticidal, antifeedant, and herbicidal properties. The spread of this species represents a valuable source of compounds with high biological value. Research on potential uses, under-standing of the nutritional and functional composition, and applications of C. parqui extracts is important and very promising for its commercial use. To date, there are some reports on the potential applications of C. parqui extracts as selective natural pesticides and for their potential phytotoxic role. Scientific knowledge and the use of extraction techniques for these components are essential for commercial applications. This article summarizes the research and recent studies available on the botany, phytochemistry, functional properties, and commercial applications of C. parqui as a biopesticide.

This study addresses the critical challenge of Speech Enhancement (SE) in noisy environments, where the deployment of Deep Neural Networksolutions on microcontrollers is hindered by their extensive computational demands. Focusing on this gap, our research introduces a novel SE method optimized for MCUs, employing a 2-layer GRU model that capitalizes on perceptual speech properties and innovative training methodologies. By incorporating self-reference signals and a dual strategy of compression and recovery based on the Mel scale, we develop an efficient model tailored for low-latency applications. Our GRU-2L-128 model demonstrates a significant reduction in size and computational requirements, achieving a 14.2× decrease in model size and a 409.1× reduction in operations compared to traditional DNN methods like DCCRN, without compromising performance. This advancement offers a promising solution for enhancing speech intelligibility in resource-constrained devices, marking a pivotal step in SE research and application.

Wetlands are one of the crucial natural resources. They provide invaluable biodiversity resources, aid in water quality improvement, support ground water recharge, help in moderating climate change and support flood control. Environment is in the other hand, where we live and something, we are very familiar with our day to day life. Geographic Information Systems (GIS), Remote Sensing and Global Positioning System (GPS) were a useful tool for wetland and environmental change analysis and to improve on the classification accuracy. This study investigates population and environmental change of Jarmet wetland and its surrounding area change analysis over the period of 1972 to 2015. The purpose of this study was to show land use/ land cover change of Jarmet wetland and its surrounding environment over years as a response to population growth. For this purpose, multi-temporal satellite imageries (Landsat MSS 1972, TM1986, ETM+ 2000, 2005 and 2015 and SRTM 2000) were obtained and used for LULC change analysis, elevation analysis and change detection analysis. ERDAS Imagine 2015, ARC GIS 10.5.1, Global Mapper11, ENVI 5.0 and DNR Garmin softwares were used to process the image data and accuracy assessment analysis. The result of LULC showed that there is spatial reduction in wetland, forest, Shrubland and grassland in the period of 43 years (1972-2015) by -1,722.8 ha, -296.2 ha, -1,718.7 ha and -661.9 ha respectively, due to increase in the farmland and plantation area as a response to overpopulation, lack of environmental policy implementation and irresponsible for natural resource degradation. The accuracy assessment of LULC change are done for recent satellite image showed the overall accuracy of 84.06% with Kappa index 75.19% this means this classification is accurately classified and handle greater than 75% of error. Finally, this study suggests that create strictly natural resource conservation law, stopping illegal expansion of farmland, educating society about the value of natural resource especially wetland and create a source of income for society rather than farming.

The new hybrid composite materials for PEM fuel cell were synthesized by UV-polymerization of acrylic monomers (acrylonitrile (AN), acrylic acid (AA), ethylene glycol dimethacrylate (EGDMA)) and sulfo aromatic monomer – sodium styrene sulfonate (SSS), and tetraethoxysilane/3-methacryloxypropyltrimethoxysilane (TEOS/MAPTMS)-based sol-gel system. By means of X-ray spectroscopy fractal structure of the obtained materials was characterized. Proton conductivity and viscoelastic properties of the materials were investigated depending on the content of inorganic component in nanocomposites. On the basis of impedance studies, an equivalent scheme is proposed that successfully describes the proton conductivity in the synthesized composite electrolyte membranes.

This study aimed to determine the correlation of colour M-mode velocity propagation in the assessment of left ventricular diastolic function among acute decompensated heart failure patients with preserved ejection fraction (HFpEF). This research is an observational analytical study using a cross–sectional study design conducted from April to June 2022. The subjects of this study were patients diagnosed with acute HFpEF and treated at Dr. Soetomo General Academic Hospital, Surabaya. Patients with heart rhythm disturbances, moderate to severe valvular heart disease, and congenital heart defects were excluded from this study. Patients were measured for diastolic function including mitral valve early mitral inflow velocity (MV E Velocity), mitral peak velocity of early filling (E’) (E' Septal and E' Lateral), left atrial volume index (LAVI), The maximal tricuspid regurgitation velocity (TR V Max), Vp, the ratio of early diastolic mitral inflow velocity to early diastolic mitral annulus velocity (E/E'), the ratio between early and late ventricular filling velocity (E/A) and E/Vp Ratio. N-terminal-pro hormone B-type natriuretic peptide (NT–ProBNP) examination was also performed on study subjects as an additional diagnosis of acute heart failure. There were 33 patients who met the inclusion and exclusion criteria and were included in our study. There were 26 patients (78.8%) with grade I diastolic dysfunction, 4 patients (12.1%) with grade II diastolic dysfunction, and 3 patients (9.1%) with grade III diastolic dysfunction. There is a strong positive correlation between Vp with parameters E' Septal (p = &lt; 0.001; r = 0.636) and E' Lateral (p = &lt; 0.001; r = 0.650). Vp is negatively correlated with the ratio E/E' (p = 0.029; r = –0.37). The PCWP estimate with E/Vp ratio had a strong correlation with the NT–Pro BNP value &gt; 300 pg/ml in acute HFpEF patients (p = &lt; 0.001; r = 0.726) compared to the PCWP estimate with E/E' (p = &lt; 0.001; r = 0.549). There is no correlation between Vp value and degree of diastolic dysfunction in patients with acute HFpEF.

Counter-current spontaneous imbibition of water is a critical oil-recovery mechanism. In the laboratory, the Amott test is a widely used technique to assess efficacy of brine imbibition into oil-saturated core plugs. The classic Amott-cell methodology was designed to estimate ultimate oil recovery, but not the recovery dynamics that provides essential information about the imbibition mechanisms. Retention of oil droplets at the external core surface and delayed onset of oil production are the two key artifacts of the classic Amott experiment. This retention, referred to here as the ``external-surface oil holdup effect'', often results in stepwise recovery curves that obscure true dynamics of spontaneous imbibition. To address these holdup drawbacks of the classic Amott method, we modified the Amott cell and experimental procedure. For the first time, using water-wet Indiana limestone cores saturated with brine and mineral oil, we showed that our improvements of the Amott method enabled accurate and reproducible measurements of oil-recovery dynamics. We used the Generalized Extreme Value (GEV) statistics to describe oil-production histories from water-wet heterogeneous limestone cores with finite initial water saturations, for the first time. We demonstrated that our four-parameter GEV model accurately described the recovery dynamics, and that optimal GEV parameter values systematically reflected the key characteristics of the oil-rock system, such as oil viscosity and rock permeability. These findings gave us a more fundamental understanding of spontaneous, counter-current imbibition mechanisms and insights into what constitutes a predictive model of counter-current water imbibition into oil-saturated rocks with finite initial water saturation.

Scaffold guided breast tissue regeneration (SGBTR) can both transform reconstructive and cosmetic breast surgery. Implant-based surgery is the most common method. However, there are inherent limitations as there is replacement of tissue rather than regeneration. Regenerating autologous soft tissue has the potential to provide a more like-for-like reconstruction with minimal morbidity. Our SGBTR approach regenerates soft tissue by implanting additively manufactured bioresorbable scaffolds filled with autologous fat graft. A pre-clinical large animal study was conducted implanting 100 ml breast scaffolds (n=55) made from medical-grade polycaprolactone in 11 minipigs for 12 months. Various treatment groups were investigated where immediate or delayed autologous fat graft, as well as platelet rich plasma were added to scaffolds. Computed Tomography and Magnetic Resonance Imaging was performed on explanted scaffolds to determine volume and distribution of regenerated tissue. Histological analysis was performed to confirm tissue type. At 12 months we were able to regenerate and sustain a mean soft tissue volume of 60.9 4.5 ml (95% CI) across all treatment groups. There was no evidence of capsule formation. There were no immediate or long-term post-operative complications. In conclusion, we were able to regenerate clinically relevant soft tissue volumes utilizing SGBTR in a pre-clinical large animal model.

The fish supply chain (FSC) industry faces a significant challenge in terms of maintaining fish quality and authenticity throughout the chain. The main goal of modern FSC systems is tracking and tracing the fish product at each stage, from harvester to end customer, as well as assessing its quality and authenticity. Integrating FSC with new technologies, such as Blockchain (BC), Big Data, Artificial intelligence (AI), and Internet of Things (IoT), enhances fish product traceability, authenticity, visibility, and security. We propose a BC-based FSC framework that follows a layered architecture consisting of a SC layer, an IoT layer, and a BC layer. We integrate a new AI-based hand-held device, a Quality, Adulteration & Traceability (QAT) device, that can identify fish species and assess fish quality. We leverage the key features of BC and smart contracts, deployed over the Ethereum platform for the proposed framework integrated with QAT technology. Extensive validation of smart contracts is conducted to prove its practical feasibility.

The process involved in preparing driving simulator tests is a labor intensive one, and the nature of this complexity depends on the sophistication of the tests to be carried out, as well as the number of participants. Which has an impact on the duration of the research itself. The very solution of using driving simulators is a research tool that has been in use for many years and with great success. They are used in a very wide range of areas of human functioning. They replicate in a very realistic way the conditions that can occur in the external environment, offer the possibility of repetition of particular conditions and insight into certain behaviors that could be very difficult to initiate in real life. This article also describes the dis- ease of using simulators to conduct research activities, along with the workflow from assumptions to finalizing the research. An algorithm is also presented for the study of individual participants, with examples for separate research scenarios concerning driver behavior in the vicinity of pedestrian crossings.

This study examines the effectiveness of a comprehensive psychomotor development program combined with adapted football training for adolescents diagnosed with intellectual disabilities in Romania. Twelve participants, with a mean age of 17.42 years underwent a carefully designed intervention program spanning 36 weeks. The program aimed to enhance fundamental movement skills, integrate these skills into specialized football training, and culminate in a Unified 7-a-side Football Match. Results indicate significant improvements in psychomotor skills, including static and dynamic balance, pulse processing speed, and identified stimuli. Moreover, the intervention positively impacted social interaction among participants. Statistical analysis, employing Pearson Correlation Analysis and Paired Samples t-Test (One-Sample), compared assessments. Results revealed significant differences between pre- and post-intervention measurements, providing robust evidence of the program's efficacy. The positive correlations between physical parameters and social interaction highlight the interconnectedness between physical fitness and social engagement. Our findings suggest that improvements in physical abilities may contribute to increased social interaction among children with intellectual disabilities, underscoring the holistic nature of our intervention, which addresses multiple dimensions of development simultaneously. The findings underscore the holistic benefits of integrating psychomotor development and adapted football programs for adolescents with intellectual disabilities, emphasizing the importance of promoting inclusive physical activities for their overall well-being.

Direct and indirect effects after mine operations cease must ideally be subject to perpetual monitoring routines in order to detect possible risks or avoid adverse effects on the surrounding ecosystems at an early stage. In this contribution, mining subsidence lakes created inside the nature reserve Kirchheller Heide and Hilsfeld Forest are subjected to analysis for a long-term monitoring scheme. For this purpose, we employ high-resolution unmanned aerial system (UAS)-based multispectral and thermal mapping tools to provide a fast, non-invasive and multitemporal environmental monitoring method. Specifically, we propose to monitor vegetation evolution through multispectral analysis, biotypes identification using machine learning algorithms, and water surface extent detection, together with their thermal behavior. The aim of this contribution is to present the proposed workflow and first results to establish a baseline for future analyses and subsequent surveys for longterm multi-temporal monitoring

Background: A new access technique was developed to reduce postoperative adverse events after the extraction of impacted maxillary wisdom teeth. Hence, this study aimed to assess the occurrence of adverse events after extraction of maxillary impacted wisdom teeth using traditional or modified access. Methods: Two different surgical incision designs were used for bilateral wisdom tooth extractions in 30 patients. The traditional incision was performed distal to the second molar in the center of the tuberosity, followed by a buccal releasing incision. After tooth extraction the wound was secured by sutures. The new technique consists of an oblique incision from the distal palatal aspect of the tuberosity towards the buccal aspect of the second molar. After tooth extraction, cyanoacrylate glue was used on the wound. Results: Lower pain was reported by patients at the site treated with the new technique (p&lt;0.01). Edema, postsurgical bleeding, and hematoma were similar in both groups. The surgical time was shorter for the new technique (p&lt;0.01). Conclusions: The new technique applied for the extraction of impacted maxillary wisdom teeth reduced postsurgical pain and the duration of surgery.

Byers Peninsula (62°34’-62°40’S-60°54’61°13’W), 60 km2 in size, is considered one of the largest ice-free areas in Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving effects of climate changes, limnology and microbiology, live cycles, but not albedo. Surface albedo is one of the key physical parameters in the surface energy budget of polar regions. Most of Antarctica is covered by ice sheets; only about 0.44% of the area is permanently ice-free. However, in maritime Antarctica, the ice-free areas, corresponding to small islands, peninsulas, and coastal beaches, account for about 3% of the territory. To incorporate the contribution of these areas into global albedo models, it is necessary to relate the soil properties of the ice-free areas to the surface albedo response. Also, mapping soil properties and albedo have and special interest in these ice-free areas. Image classification using machine learning methods trained with georeferenced soil data could be useful for mapping soil properties and albedo in multispectral optical satellite images. A shallow neural network implemented using the Keras Python module was used to define and train models of soil properties using 15 explanatory variables corresponding to bands and spectral indices of a Sentinel image and a population of 49 soil samples taken from the top 5 centimeters of the soil profile. The soil samples were analyzed in the laboratory and a spectral library in the Vis-Nir range (350-2500 nm) was created. The albedo of the samples was integrated from the ADS spectra. At the same time, a linear regression model of albedo using the soil properties as explanatory variables was performed. The R2 fit of this new model was about 0.82 and the error of estimation was 4.1. The model was extended to the entire Byers Peninsula using the ML soil property models as explanatory variables. The RMSE of the extended models increased up to 8.2. We think that the main cause of this increase (2.6 points) is related to the error propagation, phenomenon due to the use of models as explanatory variables. However, another important part of the error increase could be due, among other reasons, to the use of an image that, although corrected, is not completely free of clouds.

The bioindicator potential of seagrass ecosystems in coastal trace metal monitoring is low for tropical island ecosystems. This study evaluated the bioindicator potential of six seagrass species exposed to anthropogenic trace metal pollution in the Andaman and Nicobar Islands (ANI) of India. Sediment and seagrass biomass, samples were analyzed for trace metals (Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Zn) from four locations of ANI exposed to anthropogenic contamination. Geo accumulation Index values indicated moderate trace metal contamination in seagrass sediment. Seagrass trace metal accumulation from sediment was both species-specific and location- specific for ANI. Small seagrass species such as H. ovalis, H. beccarii and H. uninervis accumulated the maximum concentration of six trace metals (Cr, Cu, Fe, Ni, Pb, Zn) in their tissues compared to big seagrass species like T. hemprichii and E. acoroides of ANI. This study indicates leaves of small seagrass and roots of big seagrass species can serve as short- and long-term bioindicators respectively, of coastal trace metal contamination in tropical islands of ANI.

Smokeless tobacco (ST) products vary significantly in their oral carcinogenicity. Much is known about the differences in chemical, but not bacterial, constituents of these products. In this study, we explore the composition and function of the bacteriome in ST products from 4 countries using q-PCR and 16S rRNA-based next generation sequencing. The bacterial load (16S rRNA copies/gram) was lowest in Swedish snus (3.4E+6) and highest in Yemeni shammah (6.6E+11). A total of 491 species-level taxa, many of which are potentially novel, belonging to 178 genera and 11 phyla were identified. Species richness and diversity were highest for Swedish snus and lowest for Yemeni shammah. Bacillus, Paenibacillus, and Oceanobacillus spp. were the most abundant in American snuff; species of Pseudomonas, Massilia, Propionibacterium, Puniceispirillum and Gloeothece predominated in Swedish snus. In Sudanese toombak, Facklamia, Desemzia, Atopostipes and Lysinibacillus spp. accounted for the majority of the bacteriome. Yemeni shammah exclusively contained Bacillus spp. PICRUSt functional prediction showed that genes encoding cadmium/zinc and nickel transport systems were enriched in the presumptively “high carcinogenicity” products. The bacteriome of ST products thus differed qualitatively, quantitatively and functionally. The relevance of these differences, particularly with respect to nickel and cadmium, to oral carcinogenesis warrants further investigation.

Lake ice thickness (LIT) is a sensitive indicator of climate change identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow-ice and ice-water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LITand FFSAR_LITretracker, respectively. LIT retrievals from Sentinel-6 SAR data at different posting rates are evaluated against those obtained from thermodynamic lake ice model simulations and Low Resolution Mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, allowing precise assessment of the continuity between LRM and SAR LIT retrievals. Consistency checks of the Sentinel-6 SAR LIT estimates are also performed using optical/radar images that provide information on the snow/ice conditions on the same dates. The analysis is performed on Great Slave Lake and Baker Lake (Canada) that differ in terms of lake size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The accuracy of the LIT estimates with the SAR LIT retrackers is on the order of 5 cm once the ice is well established on the lakes, meeting the GCOS requirements of LIT measurement uncertainty, which is a factor of 2 to 3 times better than that of LIT obtained with LRM data, bringing a further improvement compared to previous analyses and methods. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions.

In the literature, estimation of weighted extropy are least considered. In this paper some non parametric estimators of weighted extropy are given. The validation and comparison of the estimators are implemented with the help of simulation study and data illustration. The usefulness of the estimators are demonstrated using real data sets.

Hybrid electric vehicles are certainly one of the key solutions for improving fuel efficiency and reducing emissions, especially in special vehicle application and with the use of CO2 neutral fuels. Determining the energy management strategy and finding the optimal solution with regard to the aforementioned goals re-mains the one of the main challenges in the design of HEV. This paper presents a new vehicle modeling method, with an emphasis on HEVs, which is based on the frequency analysis of emissions and consumption according to the current specific traction power of the vehicle. The evaluation of the newly introduced model in the RDE, NEDC and WLTP cycle was performed and the results were compared with the standard verified vehicle model that was created in AVL's CruiseM software package. Positive traction energies have positive deviations of between 0.35% and 2.85%. The largest deviation in CO2 emissions was recorded for the HEV model in the RDE cycle and in the non-hybrid model in the WLTP cycle of 3.79% and 4.4% respectively, all other combinations of cycle and vehicles had deviations of up to about 1%. As expected, the largest relative deviations were recorded for NOx emissions from 0.13% to 9.62% for HEV in the WLTP cycle.

3D human pose estimation has made significant advancements through the integration of deep learning techniques. This survey provides a comprehensive review of recent 3D human pose estimation methods, with a focus on monocular images, videos, and multi-view cameras. Our approach stands out through a systematic literature review methodology, ensuring an up-to-date and meticulous overview. Unlike many existing surveys that categorize approaches based on learning paradigms, our survey offers a fresh perspective, delving deeper into the subject. For image-based approaches, we not only follow existing categorizations but also introduce and compare significant 2D models. Additionally, we provide a comparative analysis of these methods, enhancing the understanding of image-based pose estimation techniques. In the realm of video-based approaches, we categorize them based on the types of models used to capture inter-frame information. Furthermore, in the context of multi-person pose estimation, our survey uniquely differentiates between approaches focusing on relative poses and those addressing absolute poses. Our survey aims to serve as a pivotal resource for researchers, highlighting state-of-the-art deep learning strategies and identifying promising directions for future exploration in 3D human pose estimation.

Age estimation is an important tool when dealing with human remains or undocumented minors. Although the skull, the skeleton or the hand-wrist are used on age estimation as maturity indicators, they often present lack of good conditions for a correct identification or estimation. Few systematic reviews (SRs) have been recently published; therefore, this umbrella review critically assesses their level of evidence and provides a general comprehensive view. An electronic database search was conducted in four databases (PubMed, Cochrane, WoS, LILACS) up to December 2022, focusing on SRs of age estimation through forensic dentistry procedures. The methodological quality was analyzed using the measurement tool to assess SRs criteria (AMSTAR2). Eighteen SRs were included, five of critically low quality, six of low quality, three of moderate quality and four of high quality. The SRs posited that Willems’ method is more accurate and less prone to overestimation; most methods seem to be geographically sensitive; and 3D-Imaging and artificial intelligence tools demonstrate high potential. The quality of evidence on age estimation using dental approaches was rated as low to moderate. Well-designed clinical trials and high standard systematic reviews are essential to corroborate the accuracy of the different procedures of age estimation in forensic dentistry.

In this study, we present different methods of estimating fuzzy reliability of a two-parameter Rayleigh distribution via the maximum likelihood estimator, median first-order statistics estimator, quartile estimator, L-moment estimator, and mixed Thompson-type estimator. The mean-square error MSE as a measurement for comparing the considered methods using simulation through different values for the parameters and unalike sample sizes is used. The results of simulation show that the fuzziness values are better than the real values for all sample sizes, as well as the fuzzy reliability at the estimation of the Maximum

The COVID-19 pandemic has expanded globally and caused serious consequence in both health system and the economy. MPV is one of two oral antivirals for COVID-19 with mild-to-moderate symptoms that have received FDA approval so far. This study aims to evaluate the cost-utility of using MPV in COVID-19 treatment. To compare the utility costs of MPV and non-MPV treatments for COVID-19 patients, we used a decision tree model. Data on clinical efficacy, cost, and quality of life were gathered from previous studies. The incremental effective cost ratio (ICER) calculated based on costs incurred and quality-adjusted life years (QALY), was considered as primary out-come. The total cost of MPV treatment and not using MPV was 15,362,516 VND (618 USD) and 15,771,262 VND (634 USD), respectively. The estimated QALY with using-MPV was 28.33, while without MPV was 19.72. The ICER was dominant, resulting in savings of 47,453 VND/QALY (1.9 USD). MPV is a cost-effective medication used to treat COVID-19. In mild-to-moderate COVID-19 patients, MPV considerably lowers costs and improves quality of life. However, several clinical factors of the drug still need to be taken into account.

As one of the critical state parameters of the battery management system, lithium battery state of charge (SOC) can provide an essential reference for battery safety management, charge/discharge control, and energy management of electric vehicles. To analyze the application of deep learning in electric vehicle power battery SOC estimation, this study reviewed the technical process, common public datasets, and the neural networks used, structural characteristics, advantages and disadvantages of lithium battery SOC estimation in deep learning method. First, the specific technical processes of the deep learning method for SOC estimation were analyzed, including data collection, data preprocessing, feature engineering, model training, and model evaluation. Secondly, the current commonly and publicly used lithium battery dataset was summarized. Then, the input variables, data sets, errors, and advantages and disadvantages of four types of deep learning methods, were concluded using the structure of neural network used for training as the classification criterion. Finally, the challenges and future development directions of lithium battery SOC estimation in deep learning method were explained.

Introduction: Anterior cervical discectomy and fusion (ACDF) for cervical disc herniation (CDH) is commonly performed. Specific postoperative complications include dysphagia, dysphonia, cervicalgia, adjacent segment disorder, cage subsidence, and infections. However, interscapular pain is commonly reported by these patients after surgery, although its mechanisms have been not clarified yet. Methods: This retrospective series of 31 patients undergoing ACDF for CDH at a single Academic Hospital. Baseline and postoperative clinical, radiological, and surgical data were analyzed. The linear regression analysis was conducted to identify any factor independently influencing the occurrence rate of postoperative interscapular pain. Results: The mean age was 57.6±10.8 years, and the M:F ratio was 2.1. The preoperative mean VAS-arm was 7.15±0.81 among the 20 patients reporting brachialgia, and the mean VAS-neck was 4.36±1.43 among those 9 patients reporting cervicalgia. At 1 month interscapular pain was still reported by 8 out of the 17 patients who experienced it postoperatively, and it was recovered in all patients after 2 months. The regression analysis showed how the interscapular pain was not directly associated to age(p=0,74), gender(p=0,46), smoking status(p=0,44), diabetes(0,42), preoperative brachialgia(p=0,21) or cervicalgia(p=0,48), symptoms duration(p=0,13), baseline VAS-arm(p=0,11), VAS-neck(p=0,93), or mJOA(p=0,63) scores, or disc height modification(p=0,90). However, the postoperative increase of the mean zygapophyseal joint rims distance was identified as an independent factor in determining interscapular pain (p=0,02). Conclusions: Our study revealed that the onset of interscapular pain following ACDF may be determined by over-distraction of the zygapophyseal joints rim. Then, proper sizing of prosthetic implants could reduce this painful complication.