Fire detection is crucial for ensuring human safety and minimizing property damage. By utilizing advanced technologies, we can identify fires early, before they escalate. Autonomous fire detection systems are particularly vital in high-risk areas with minimal human presence. To address this need, we propose an automated fire-detection model based on YOLOv8. We modified the architecture of YOLOv8 and achieved impressive performances. Through comprehensive analysis of different YOLO models and their predecessors, we identified and addressed substantial gaps in this field. Also, by augmenting the framework with additional capabilities, we surpassed previous models, enabling real-time fire detection. Our proposed model achieves impressive performances, with 98% accuracy in fire detection and 97.8% in smoke detection. Moreover, recall rates for fire and smoke are 97.1% and 97.4%, respectively, with a mean average precision (mAP) accuracy of 99.1% for both cases. Finally, we applied an explainable artificial intelligence technique to interpret our proposed model and its results. This study lays the foundation for future research aimed at enhancing fire detection efficiency. The reliability of our modified model presents promising opportunities for future advancements, ensuring increased effectiveness and precision in efficient fire detection.

Electrochromic measurements have been performed to optimize the composition of reactive magnetron-sputtered mixed layers of Zinc oxide and Tin oxide (ZnO-SnO2). A combinatorial material synthesis approach was applied throughout the deposition experiments, and the samples represented the full composition range of the binary SnO2-ZnO system. The Coloration Efficiency (CE) of the mixed oxide films were determined with simultaneous measurement of layer transmittance and applied electric current through the using organic propylene carbonate electrolyte cells in a conventional three-electrode configuration. Optical parameters and composition have been determined and mapped by using Spectroscopic Ellipsometry (SE). Scanning Electron Microscopy (SEM) with Energy-Dispersive X-ray Spectroscopy (EDS) has been used to check the SE results as it was used in our earlier paper [N. T. Ismaeel et al, Materials 2023, 16(12), 4204] for (TiO2-SnO2). Zn and Sn targets were put separately from each other, and the Indium-Tin-Oxide (ITO) covered glass and Si-probes on a glass substrate (30 cm × 30 cm) were moved under the two separated targets (Zn and Sn) in a reactive Argon-Oxygen (Ar-O2) gas mixture. By using this combinatorial process, all the compositions (from 0 to 100%) were achieved in the same sputtering chamber after one sputtering process. CE data evaluated from the primary data plotted against the composition displayed a characteristic maximum at around 29 % ZnO. Our combinatorial approach allows the localization of the maximum at 5% accuracy.

Link prediction is a significant field in network science, which focuses on predicting the probability of the existence or formation of a link between nodes in a social network based on currently observed connections. The effectiveness of traditional algorithms can vary depending on the type of network, making some methods more suitable than others for specific scenarios. Recently, several efficient link prediction algorithms have been developed, demonstrating robust results in both prediction accuracy and interpretability. However, existing research has not clearly established the relationship between network characteristics and link creation mechanisms for community influence analysis and anomaly detection. The ability to predict complex networks with diverse features still requires further investigation. In light of this, we introduce a novel framework designed to combine the best features of different link prediction algorithms when applied to the network, with the aim of achieving more reliable predictions about how networks will evolve. According to the proposed framework, we first focus on the feature extraction stage. During this phase, we systematically identify and extract a comprehensive set of features from the network before moving onto the classification phase. Here, we utilize state-of-the-art ensemble learning models to assess and classify potential links within the network. By training our machine learning models on the extracted features, we can effectively predict whether a particular link is likely to form (positive link) or unlikely to form (negative link). The ML models were trained and evaluated using two datasets: Twitch and Facebook. Results: Additionally, we assessed their performance on these datasets by conducting specific preprocessing and hyperparameter tuning steps. The final prediction model achieves AUC values between 94% and 99.3%. This research contributes significantly to efforts aimed at enhancing link prediction in dynamic socisal network contexts, providing valuable insights into the effectiveness of different ML algorithms in predicting future connections and enhancing our understanding of network dynamics.

This manuscript explores significant advancements and emerging challenges in CAR T cell therapies, focusing on the production methodologies and regulatory complexities. The discussion highlights ongoing challenges like the lack of in vivo persistence, lengthy production times, and elevated costs associated with current CAR T cell therapies. It analyzes innovative solutions such as genetic engineering techniques aimed at enhancing cellular efficacy and endurance, alongside cutting-edge manufacturing processes, including closed systems and development of allogeneic products. These advancements hold promise for reducing costs and improving production efficiency, potentially increasing patient access to these transformative therapies globally. Furthermore, the manuscript underscores the necessity for expanding ongoing research and enhancing regulatory frameworks to fully realize and implement these innovations in CAR T cell manufacturing and bring these innovations to fruition.

This pioneering study explores the geospatial and temporal patterns of natural and human-induced disasters from 1900 to 2024, providing essential insights into their global distribution and impacts. Utilizing the comprehensive international EM-DAT database, our analysis reveals significant trends and disparities in disaster occurrences and their widespread consequences. Results showed a dramatic escalation in both natural and man-made (technological) disasters over the decades, with notable surges in the 1991-2000 and 2001-2010 periods. A total of 25,836 disasters were recorded worldwide, of which 69.41% were natural disasters (16,567) and 30.59% were man-made (technological) disasters (9,269). The most significant increase in natural disasters occurred from 1961-1970, while man-made (technological) disasters surged substantially from 1981-1990. Seasonal trends reveal that floods peak in January and July, while storms are most frequent in June and October. Droughts and floods are the most devastating in terms of human lives, while storms and earthquakes cause the highest economic losses. The most substantial economic losses were reported during the 2001-2010 period, driven by catastrophic natural disasters in Asia and North America. Our research highlights Asia as the most disaster-prone continent, accounting for 41.75% of global events, with natural disasters making up 61.89% of these events. Oceania, despite experiencing fewer total disasters, shows a remarkable 91.51% of these as natural disasters. Africa is notable for its high incidence of man-made (technological) disasters, which constitute 43.79% of the continent's disaster events. Europe, representing 11.96% of total disasters, exhibits a balanced distribution but tends towards natural disasters at 64.54%. Examining specific countries, China, India, and the United States emerged as the most frequently affected by both natural and man-made (technological) disasters. The impact of these disasters has been immense, with economic losses reaching their highest during the decade of 2010-2020, largely due to natural disasters. The human toll has been equally significant, with Asia recording the most fatalities and Africa the most injuries. Particularly, the decade from 2001 to 2010 experienced the greatest economic losses, primarily driven by natural disasters in Asia and North America. These insights highlight the urgent need for tailored disaster risk management strategies that address the distinct challenges and impacts in various regions. By understanding historical disaster patterns, policymakers and stakeholders can better anticipate and manage future risks, ultimately safeguarding lives and economies.

This paper presents a co-designed solution aimed at improving community healthcare assistance management. To enhance patients’ self-awareness of their health status, encouraging active participation in care process, and to support nurses in delivering patient-centered care, we have developed an innovative platform with a highly customized app. This platform was designed using a multi-disciplinary bottom-up approach. Patient data collection and processing facilitate the automation of care timeline planning, based on real time patients’ needs and the available resources. To achieve this goal different components have been considered: real-time health data collection and processing, patient care planning, decision support for nurses, secure communication for data transmission, and user-friendly interfaces to ensure easy access to platform functionalities.

(1) Background: A wide literature based on loading and unloading bending tests has been carried out over the half past century for assessing the force released by superelastic wires. The aim of this investigation is not only to characterize a broadly described superelastic NiTi and a novel CuNiTi archwire, but also to provide novel insights into the load vs deflection profiles. A harmonic scenario for superelastic wires will be shown as temperature is kept constant at 37°C. However, a completely different picture will be highlighted as a temporary heating step up to 50°C is introduced within the force vs deflection profiles. (2) Methods: A variety of NiTi and a novel CuNiTi round and rectangular cross-section archwires have been investigated. Static 3-point bending tests up to a deflection level of 3.0 mm have been carried out for detecting the unloading force plateau levels occurring at 37°C. A hold deflection step of 5 min at deflection levels occurring along the unloading plateau extension is introduced. The effect of a temporary heating up to 50°C on the force plateau level released by the investigated wires is analyzed. (3) Results: Mechanical profiles suggest that the plateau force levels detected at 37°C are consistent with those broadly reported in the literature, but they only represent a single block puzzle of the force scenario that a superelastic wire releases during the orthodontic treatment. (4) Conclusions: Once a superelastic wire is bent and clinically applied, the effect of a temporary heating up to 50°C (e.g. hot food or drink ingestion) produces a significant plateau force increase whose magnitude depends on the deflection level. The highest force increase of about 50% and 40% have been detected at deflection levels located at the beginning of the unloading plateau extension for NiTi and CuNiTi wires, respectively.

Quill mites of the family Syringophilidae are widely distributed parasites of birds inhabiting the interior of feather quills. In this paper, we provide detailed information on the host spectrum and distribution for six previously described species of syringophilines associated with starlings with new host and locality records. Additionally, we describe three new species, Aulonastus indonesianus Marcisova, Skoracki and Patan sp. n. from the Common Hill Myna Gracula religiosa Linnaeus in Indonesia (Java) and the White-necked Myna Streptocitta albicollis (Vieillot) in Indonesia (Celebes), Aulonastus anais Skoracki and Patan sp. n. from the Golden Myna Mino anais (Lesson) in Papua New Guinea, and Syringophiloidus poeopterus Skoracki and Patan sp. n. from the Abbott's Starling Poeoptera femoralis (Richmond) in Tanzania. Finally, we explore the host-parasite interactions within the system comprising starlings and syringophiline mites.

Japanese plum tree (Prunus salicina Lindl.) is mainly cultivated in temperate areas of China and some European countries. Certain amounts of wood (from pruning works) are generated every year from this crop of worldwide commercial significance. The main objective of this work was to value this agricultural woody residue, for which the chemical composition of pruning wood extracts from six Japanese plum cultivars was investigated, and the antiproliferative activity of extracts and pure phenolics present in those extracts was measured. For the chemical characterization, total phenolic content and DPPH radical-scavenging assays and HPLC‒DAD/ESI‒MS analyses were performed, the procyanidin (‒)-ent-epicatechin-(2α→O→7,4α→8)-epicatechin (5) and the propelargonidin (+)-epiafzelechin-(2β→O→7,4β→8)-epicatechin (7) being the major components of the wood extracts. Some quantitative differences were found among plum cultivars, and the content of proanthocyanidins ranged from 1.50 (cv. ‘Fortune’) to 4.44 (cv. ‘Showtime’) mg/g of dry wood. Regarding the antitumoral activiy, eight wood extracts and four phenolic compounds were evaluated in MCF-7 cells after 48 h of induction, showing the wood extract from cv. ‘Songold’ and (‒)-annphenone (3) the best antiproliferative activity (IC50: 424 ppm and 405 ppm, respectively).

The study involved a comparison of the chemical, physical, microbiological, and functional attributes of must extracted from Solaris cultivar grapes cultivated under both conventional and organic farming systems. This study aimed to determine the influence of cultivation methods on various must properties, including the levels of health-promoting polyphenols and health-threatening mycotoxins and pesticide residues. It was observed that the organic grapes hosted a greater diversity and quantity (OTUs) of bacteria and fungi. The predominant bacteria were Sphingomonas (with similar numbers in both crops) and Massilia (more abundant in grapes from the conventional crop). These two bacterial groups collectively accounted, on average, for about 40% of all OTU sequences detected. Lower levels of bacteria of the genera Hymenobacter and Pseudomonas and others colonized the grapes. Among the fungi, Erysiphe and Aureobasidium were dominant, comprising about 50–70% of all detected taxa. Notably, Erysiphe was predominantly found in conventionally grown grapes, while Aureobasidium, Mycosphaerella, and Botryotinia were present in comparable quantities in fruit from both types of crops. No mycotoxins were detected in the must or marc, despite the presence of genes responsible for aflatoxin and ochratoxin biosynthesis in both types of grape juice. The organic must exhibited significantly higher levels of polyphenols and displayed improved antioxidant properties and technological characteristics. Moreover, sulfur and copper used in the protection of the organic plantation passed from the fruit surface into the must. Also, pesticide residues, namely cyprodinil and fludioxonil from conventional cultivation, were detected in the must.

Mpox, formerly known as Monkeypox, is a rare viral disease initially discovered in Africa in 1958. Since its first identification, several outbreaks have occurred in various African nations. Recently, the global community has witnessed a resurgence in the number of Mpox cases reported worldwide, prompting the World Health Organization (WHO) to declare the ongoing multi-country outbreak a public health emergency in July 2022. This study reports on the first cases of Mpox detected in Khartoum State, Sudan, outlining the epidemiology, preparedness, and public health response to this new challenge. A total of 55 suspected cases were identified, with two confirmed cases. The clinical manifestations observed in these cases align with the classic skin rash typical of Mpox, presenting alongside symptoms like fever, headache, and joint pain. The findings underscore the need for heightened surveillance, early detection, and timely intervention to prevent the domestic spread of Mpox and its potential impact on public health. Continued global efforts are needed to support effective screening, diagnostic, and control measures, ultimately enhancing preparedness and response in the face of this emerging disease.

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.

Low dietary intake of calcium, vitamin D, vitamin C and magnesium has been associated with increased risk of osteoporosis. The purpose of the study was to evaluate changes in several bone health indicators and metabolic biomarkers in postmenopausal women, with high osteopenia or osteoporosis, followed by a nutritional intervention program. 115 apparently healthy postmenopausal women (52±8 years old) were randomized into four groups: group I (n=40) received daily 1000 mg vitamin C, 100 mcg vitamin D3, 500 mg calcium(Ca) and 300 mg magnesium (Mg); group II (n=42) received daily 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg; group III (n=18) received daily 5 mg bisphosphonates, 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg; and group IV (n=15) received daily about 364 mg polyphenols via an innovative functional food (50 g olive paste enriched with mountain tea extract) along with 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg. Groups I -III received supplementation for a year whereas group IV for 5 months. Changes in bone health indicators and metabolic biomarkers were assessed at the beginning and at the end of the study. Anthropometric indices and whole-body bone mineral density (BMD) were also evaluated at the beginning and at the end of the intervention period. The results revealed improved elevated levels of 25(OH)D3, in groups II, III and IV (+3,71% and +1.45% and +5.62% respectively). Significant positive changes were recorded, for whole-body BMD, in all four study groups. Significant beneficial changes for total cholesterol were observed in group IV (-2.07%, P<0.05) and positive changes in group I for HDL biomarker (+61.62%, P<0.05). Additional larger-scale clinical trials and intervention studies are considered essential, to fully investigate and elucidate associations between dietary components and biochemical indices of bone health.

Two decades after the antiretroviral therapy (ART) introduction, several challenges still prevail in maintaining people living with HIV (PLHIV), even with "Test and Treat" and/or "Rapid Start of ART" initiatives, as well as the scale-up of ART worldwide to promote access and adherence to treatment. This review examined articles on ART adherence in Africa between 2016 and 2023, published in English and indexed in PubMed. A total of 16 articles out of 2415 were eligible and included for analyses. Overall, ART adherence rates in SSA regions ranged from 43% to 84%. Rates in the centre of the SSA region ranged from 58% to 80%, in the north from 50% to 83%, in the south from 77% to 84%, in the west from 43% to 60% and in the east from 69% to 73%. Most African countries use the self-report to assess treatment adherence, although unreliable. The main factors with negative influence on ART adherence were comorbidities, lack of motivation, socioeconomic difficulties or side effects. Conclusion: Adherence to ART is a good indicator for controlling the spread of HIV. It is important to overcome the barriers that make it difficult to comply with ART and reinforce the factors that facilitate the accession of medication.

Candidiasis is considered an emerging public health concern because of the occurrence of drug-resistant Candida strains and the lack of available structurally diverse antifungal drug armamentariums. The indole alkaloid globospiramine from the anticandidal Philippine medicinal plant Voacanga globosa exhibits a variety of biological activities; however, its antifungal properties remain to be explored. In this study, we report the in vitro antifungal activities of globospiramine against Candida albicans and Candida tropicalis and explore its possible target proteins using in silico methods. The colony-forming unit (CFU) viability assay revealed time- and concentration-dependent anticandidal effects of the alkaloid by decreasing almost 50% of the viable CFUs 60 min after treatment. Results of the MIC and MFC assays indicated inhibitory and fungicidal effects of globospiramine against C. albicans (MIC = 8 µg/mL; MFC = 4 µg/mL) and potential fungistatic effects against C. tropicalis at lower concentrations (MIC = 4 µg/mL; MFC > 64 µg/mL). The FAM-FLICA poly-caspase assay showed metacaspase activation in C. albicans cells at concentrations of 16 and 8 µg/mL, which agreed with the MIC and MFC values. Molecular docking and molecular dynamics simulation experiments indicated stable, strong binding of globospiramine with the target proteins 1,3-β-glucan synthase and Als3 adhesin enzymes, which are indirectly involved in apoptotic-driven candidal inhibition.

Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak and accumulated rainfall-based damage are likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index (SWRI24−hr−S), derived from normalising the existing 24-hourly water resources index (WRI24−hr−S) in literature, to monitor flash flood risks on an hourly scale. The proposed SWRI24−hr−S is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V) and peak (Q). The comprehensive result analysis establishes the practical utility of SWRI24−hr−S in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fiji’s study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data is available, offering crucial information for flood risk monitoring, assessment, and the development of effective mitigation strategies.

Attention to the work-related musculoskeletal disorders (WMSDs) involve also statistical surveys showing an increasing trend in the incidence of WMSDs. Technological development retrieves new tools and methods for the assessment of physical load at work. In addition to the conventional questionnaires and scaling assessment systems, these methods are mostly based on the direct sensing of appropriate parameters, which allows more precise quantification. The aim of this paper is to compare the assessment of ergonomic risk through current legislative regulations. A Captiv wireless sensor system was used at a car headlight quality control assembly workplace for sensing, data acquisition and data processing. During the evaluation of the postures and movements at work, we discovered differences in the applicable standards: Decree 542/2007 Coll. (Slovak legislation), STN EN 1005-4+A1, French standards default in the Captiv system. Standards define the thresholds for hazardous postures with significant differences in several evaluated body segments, which also affects the final evaluation of the measurements. Based on the results of our research, we found that respondents were in an acceptable position for approximately 63% of the total duration of the work activity in terms of the Legislative method, 44% with Captiv and 27% with Standards method.

This study aimed to investigate the relationship between sleep duration, dementia severity, age, and ANS regulation. This cross-sectional pilot study included 27 older patients with probable Alzheimer’s disease, hospitalized at a psychiatric center. We measured heart rate variability to assess ANS regulation at night, evaluated dementia severity using the Clinical Dementia Rating scale, and obtained sleep duration data from sleep diaries maintained by psychiatric nurses. The data were analyzed using repeated-measures generalized linear models with age, sex, dementia severity, and medication (antipsychotics) as covariates. A sleep duration of 7–8 h per night was associated with better ANS regulation than other sleep durations, as indicated by sympathovagal balance (p = 0.005). ANS dysregulation was characterized by a 20.7% increase in sympathetic nervous system activity and a 14.8% decrease in parasympathetic nervous system (PSNS) activity. We found a significant correlation between dementia severity and PSNS activity (p = 0.04) and observed an inverted U-shaped association between sleep duration and ANS regulation. This pilot study demonstrated that a sleep duration of 7–8 h per night may be critical in maintaining optimal ANS regulation. Bidirectional associations between sleep duration, inadequate sleep duration, aging, and ANS regulation warrant further investigation.

Regulation of the diet in terms of the content of soluble and insoluble fibre is of great importance from the point of view of dietetics, microbiology of the gastrointestinal tract and immunology of the organism. Dietary fibre plays an important role in maintaining the balance between the con-tinuity of gut mucus production (intestinal mucosa), the stability of the intestinal microbiome composition, the regeneration of the intestinal epithelium and the immune status within the gut-associated lymphoid tissue (GALT) are played by pectin and their metabolic products in the form of pectin oligosaccharides. The main purpose of this review was to focus on pectin, their functions, their impact on the human's health and on some of the most promising prebiotics due to their solubility in the gastrointestinal tract in the form of pectin oligosaccharides. They have the properties of pectin, but have also additional features and postbiotics obtained in fermentation process can affect the intestinal microbiome and GALT-related immunity. They can be obtained from plant agro-wastes.

Shoulder tendinopathies produce pain and reduce functionality. The aim of this randomized clinical trial was to analyze the effects of Percutaneous electrolysis (PE), Percutaneous peripheral Nerve Stimulation (PNS) and eccentric exercise (EE), on pain (NPRS), strength, electromyographic activity, ultrasound characteristics of the tendon (echogenicity, thickness and hypervascularization) and functionality (DASH and SPADI) on individuals with supraspinatus tendinopathy. Participants (n=50) were divided into two groups, they received 4 treatment sessions, one per week, of PE and PNS (n=25) or 10 treatment sessions of TENS and US (n=25). Both groups performed EE program consisted of 3 sets of 10 repetitions of each of the 3 exercises, twice a day, during the 4 weeks. Follow-up was carried out at 4, 12 and 24 weeks after the start of the intervention. There are statistically significant differences in the analysis between groups (p<0.001) in the post-treatment and follow-up measurements favorable to the PE+PNS+EE treatment on pain (NPRS), strength, supraspinatus electromyographic amplitude, ultrasound characteristics of the tendon (echogenicity, thickness and hypervascularization) and DASH and SPADI questionnaires. The combined treatment PE, PNS and EE is an effective option in the clinical management of tendinopathies, with positive results in the short and long term on the variables studied.

This study explores the Experience Economy dimensions within fishing tourism, adopting a data science perspective by employing web crawling for extensive data gathering on reviewer profiles from TripAdvisor. Utilizing Natural Language Processing (NLP) techniques, it scrutinizes the relationship between Experience Economy dimensions and user profiling aspects. Findings reveal "Entertainment" as the predominant dimension in tourist reviews, followed by "Aesthetic," "Educational," and "Escapist." Particularly notable are the frequent co-occurrences of "Entertainment"-"Aesthetic" and "Educational"-"Entertainment" pairs. The practical implications underscore the potential socioeconomic benefits of fishing tourism for local communities and fishermen, emphasizing the necessity for governmental support in terms of infrastructure, leadership, legislation, and financial backing to foster sustainable development in this sector. Notably, this research stands as a pioneering effort in its focus on Experience Economy dimensions and user profiling within the context of fishing tourism, drawing data from business pages and user profiles.

Emulsifiers like egg yolk (EY) are necessary for the formation of mayonnaise, which is an oil-in-water type colloid. This study aimed to assess the potential of defatted soybean powder treated with supercritical carbon dioxide (DSF-SC) in enhancing the quality of plant-based may-onnaise as plant-based alternatives gain popularity. This study involved producing DSF-SC and comparing its quality attributes to those of mayonnaise made with varying amounts of control soy flour (CSF), DSF-SC, and EY. It was found that mayonnaise made with DSF-SC, with increased emulsifier quantity, showed better emulsion stability, viscosity, and smaller, more uniform particle size compared with CSF mayonnaise. Additionally, DSF-SC mayonnaise was overall rated higher in sensory evaluation. The addition of approximately 2% DSF-SC positively influenced the emul-sion and sensory properties of the vegan mayonnaise, making DSF-SC a promising plant-based alternative emulsifier for replacing animal ingredients.

The per capita availability of freshwater resources on a global scale is gradually decreasing due to population growth, rapid urbanization, industrialization, and modern lifestyles. In this situation, wastewater management becomes a major concern. Conventional treatment processes used to treat wastewater discharges are not adequate for the advanced removal of pollutants, especially refractory organic pollutants, which are mainly organic compounds that are not easily biodegradable in the environment. The use of photocatalytic membrane reactors (PMRs) for tertiary wastewater treatment has attracted much interest in recent periods, and various configurations have been investigated. The performance of a PMR using an iron doped titanium photo catalyst and Polysulfone-based polymeric membrane for municipal wastewater treatment was evaluated under natural and simulated solar light. Obtained results proved that solar driven PMRs can remove organic loading (COD) with high efficiencies and may represent a suitable alternative for the tertiary treatment step of municipal wastewater.

There is a growing trend among consumers to seek out natural foods and products with natural ingredients. This shift in consumer preferences had a direct impact on both food and pharmaceutical industries, leading to a focus of scientific research and commercial efforts to meet these new demands. The aim of this work is to review recent available scientific data on foods of interest, such as artichoke, gooseberry, and polygonoideae plants, as well as olive oil and red raspberries. Interestingly, the urgency of solutions to the climate change emergency has brought new attention to by-products of grapevine bunch stem and cane, which have been found to contain bioactive compounds with potential health benefits. There is a pressing need for a faster process of translating scientific knowledge from the laboratory to real-world applications, especially in the face of the increasing societal burden associated to non-communicable diseases (NCDs), environmental crises, the post-pandemic world, and ongoing violent conflicts around the world.

The Tibetan Plateau(TP) is known as ‘the water tower of Asian’, its precipitation variation play an important role in the eco-hydrological processes and water resources regimes. based on the monthly mean precipitation data of 65 meteorological stations over the Tibetan Plateau and the surrounding areas from 1961-2015,variations, trends and temporal-spatial distribution were analyzed, furthermore, the possible reasons were also discussed preliminarily. The main results are summarized as follows: the annual mean precipitation in the TP is 465.54mm during 1961-2015, among four seasons, the precipitation in summer accounts for 60.1% of the annual precipitation, the precipitation in summer half year (May.- Oct.) accounts for 91.0% while that in winter half year (Nov.- Apr.) only accounts for 9.0%; During 1961-2015, the annual precipitation variability is 0.45mm/a and the seasonal precipitation variability is 0.31mm/a, 0.13mm/a, -0.04mm/a and 0.04mm/a in spring, summer, autumn and winter respectively on the TP; The spatial distribution of precipitation can be summarized as decreasing from southeast to northwest in the TP, the trend of precipitation is decreasing with the increase of altitude, but the correlation is not significant. The rising of air temperature and land cover changes may cause the precipitation by changing the hydrologic cycle and energy budget, furthermore, different pattern of atmospheric circulation can also influence on precipitation variability in different regions.

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Reducing the levels of toxic chemicals that cause adverse health and environmental impacts is a challenge for the international community. There is a need of a global strategy. Indeed, too often the problems associated to the exposure of chemical substances is recognized a posteriori, in the presence of consequences already observed. The prediction of the likely effects of chemical exposure on human health is based on classical tests with animals, which are time and money consuming, may deviate from an accurate prediction towards humans, and arises ethical concerns. Regulations are now considering the adoption of in silico (or computational) methods, which can be used for prioritizing substances according to the probability to be toxic for the biosphere. Several initiatives have prioritized chemicals, typically based according to some criteria, such as chemicals which may be endocrine disruptors, or persistent, bioaccumulative, or toxic (PBT). However, these initiatives focused on a certain range of adverse properties, and covered a certain number of substances only. We applied a set of largely validated and widely used predictive methods to large collections of chemicals: (i) to about 340,000 with a defined function, and (ii) to about 6 millions, which have been synthetized. The aim of this study is to quantify the putative impact of existing and future chemicals on towards human health, ecological and environment properties. The impact on the environment is the cause of major concern. This is the case of pesticides and hazardous, which is quite expected; however, also pharmacologically active candidate compounds of natural origin may have a high level of ecotoxicity. Pesticides and hazardous are also the categories of higher concern for humans, followed by pharmaceuticals. The pesticides and the hazardous are the categories of higher concern also on the environmental point of view. The results of our analysis could be the basis for the identification of new safety rules.

1) Landsat operational land imager (OLI) data and consequent laboratory measurements were used to predict Chlorophyll-a (Chl-a) concentration and the trophic states for an inland lake within the East Kolkata Wetland, India; 2) The most suitable band ratio was identified by performing Pearson correlation analysis between Chl-a concentrations and possible OLI band and band ratios from the study points; 3) The results showed highest correlation coefficient from the band ratio OLI5/OLI4 with an R value of 0.85. The prediction model was then developed by applying regression analysis between the band ratio OLI5/OLI4 and Chl-a concentration of the study points. The reflectance ratios of the validation points were given as input on the prediction model and the model output was considered as predicted Chl-a values of the validation points to check the efficiency of the prediction model. The regression model between laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points revealed a high correlation with an R² value of 0.78. Trophic State Index (TSI) of the lake was also calculated from laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points. The study presented a high correlation of TSI determined from predicted data with TSI from laboratory reference data (R = 0.88). The TSI values of the lake ranged from 65 to 75 which indicate that the lake is appeared to be eutrophic to hypereutrophic conditions. 4) This empirical study showed that Landsat 8 OLI imagery can be effectively applied to estimate Chl-a levels and trophic states for inland lakes.

This study examines the evolution and eventual decline of the spirit of primitive federalism within Confucianism, tracing its trajectory from the time of the Duke of Zhou and Confucius to the significant reinterpretations by Dong Zhongshu. The Duke of Zhou's establishment of a confederation-like system and the "Zhou ritual norms" laid the groundwork for a political structure that embraced diversity and distributed power among states, reflecting a proto-federalist concept. Confucius's teachings continued this legacy, advocating for a return to the systems of the Duke's era, where both the central government and local states shared responsibilities and rights. The crux of this study lies within its fourth section, which narrates a tale of transformation happened under Emperor Wu of Han, where Dong Zhongshu distorted the original Confucianism and reinterpreted it as a centralized ideology. In Confucian theory, the shift involved the suppression of alternative philosophies, the establishment of Confucianism as the state's dominant ideology, and a reinterpretation of Confucianism that supported an centralized framework and cultural assimilation. In political practice, he re-envisioned the role of feudal lords as administrative extensions of a centralized government, effectively eroding local autonomy and shifting towards a unified, centralized system. Under the auspices of political authority, Confucian theory was transformed from a federalist theory promoting diversity, inclusivity and advocating decentralization, to one that legitimized a centralized and unified system.

Identification of topical research issues using bibliometric data is complicated by the fact that the citation of publications from recent years has not yet been formed. In this paper, it is proposed to use the average citation of the journal over two years rather than the article citation to estimate to estimate the weight of the keyword occurring in the sample under consideration. In order to identify the terms that characterize relevant research topics, it is proposed to represent the term co-occurrence network in coordinates of the average occurrence of the term per year and the average normalized citation of the term to visualize the graph. Furthermore, this methodology proposes the use of preprocessing of keywords using a lemmatization dictionary. 3,696 bibliometric records for 2022–2024 from the ScienceDirect platform on the topic of industry digitalization were used for the analysis. The VOSviewer and Scimago Graphica programs were used sequentially. The former was used to display the overall landscape of the study, while the latter was used to analyze in more detail the individual slices of bibliometric data obtained with VOSviewer. A ‘convex hull’ was used to facilitate the perception of cluster boundaries. After analysing the data and highlighting the terms, it is proposed to provide context by quoting strings from publications and defining of lesser-known terms. The industry digitalization is not only a technical and technological issue but also an economic one, as evidenced by terms such as ‘digital economy’ and ‘Industry 5.0’.

Telemedicine has emerged as a transformative tool in modern healthcare, particularly during the COVID-19 pandemic, which catalyzed its rapid expansion. Despite its demonstrated potential in enhancing remote patient monitoring, AI-driven diagnostics, and telepsychiatry, widespread adoption of telemedicine remains constrained by persistent barriers. This review examines the current state of telemedicine, identifying major advancements alongside key challenges that impede its full integration into global healthcare systems. These barriers include the digital divide, regulatory inconsistencies across regions, and patient concerns about data security and the quality of virtual care. Addressing these issues requires a coordinated multi-sectoral approach, emphasizing infrastructure development, regulatory harmonization, patient education, and the incorporation of emerging technologies such as AI, blockchain, and virtual reality. By overcoming these challenges, telemedicine can be established as a cornerstone of equitable, accessible, and patient-centered healthcare worldwide.

Renewable energy is essential to environmental sustainability and ranks high among the United Nations strategic goals. In this context, as opposed to conventional biomass gasification, co-gasification emerges as a promising technological pathway to effectively combine the distinct benefits of various gasification feedstocks in order to generate hydrogen-rich syngas. The goal of achieving net-zero emissions has further raised the demand for biomass co-gasification. However, the complicated reactions involved in co-gasification process pose challenge in optimizing the process parameters for increased productivity and performance. To the author’s knowledge, there is no consensus regarding the most suitable machine learning (ML) based regression models for optimizing biomass-plastics co-gasification process, as no prior research has examined the effectiveness of different regression models for this process. Further, the practical application of ML models is adversely affected by their black box nature and lack of interpretability. To address these gaps, the objective of the currect research is two-fold: Firstly, to model the co-gasification process using seven different ML algorithms. Secondly, to develop an evaluation framework and assess model interpretability to select an ideal model for co-gasification interpretation and optimization. The support vector regression(SVR) model demonstrated the most reliable predictive performance. The study employed learning curve analysis and cross validation analysis to substantiate the model predictive performance and exhibit its potential to generalize. Beyond performance analysis, Shapely additive explanation, (SHAP) is first explored in the realm of cogasification to interpret the prediction of the studied models from global and local perspective. The research findings are expected to provide valuable insights to better understand and optimize biomass-plastics cogasification process for H2-rich syngas production.

A novel approach to optimizing turbomachinery performance is presented in this chapter, which integrates Computational Fluid Dynamics (CFD) simulations, an artificial neural network (ANN) with a modified Non-dominated Sorting Genetic Algorithm II (NSGA-II). Using this enhanced algorithm, substantial performance improvements can be achieved through geometric optimization. The effectiveness of this method is demonstrated in two case studies: an inducer for a centrifugal pump and a Savonius wind turbine. The inducer is designed to maximize head coefficient, hydraulic efficiency, and net positive suction head by optimizing factors such as inlet and outlet blade angles. The optimization process employs the Group Method of Data Handling (GMDH) for objective function modeling, followed by Pareto front plotting and TOPSIS for identifying trade-off optimal points. Results indicate significant improvements in head coefficient, hydraulic efficiency, and NPSHR by 14.3%, 0.3%, and 30.2%, respectively. Twist angle, aspect ratio, and overlap ratio are also optimized for wind turbine blades. The power coefficient is enhanced by 5.32%, the torque coefficient by 13.74%, and the rotational speed by 0.071% through multi-objective optimization. As a result of this approach, efficiency improves, and valuable insights into the optimal design principles for turbomachinery components are also gained.

In the contribution, through literary content analysis, we present the results of the analysis of the publication The Boy From Block 66: A WW2 Jewish Holocaust Survival True Story (2023). We are convinced that this book can be included in the teaching of Literary Education at various levels of education, especially at the level of application of the historical and integrative approach of introducing students to the literary themes of the Shoah. For two excerpts from this publication, we present several questions and tasks, the aim of which is to guide pupils to an adequate internalization of the tone of the events of the Shoah. We are convinced that (not only) this publication is an adequate narrative in which the events that connote the Shoah are presented authentically and in an attractive way for young readers, and whose presentation in this publication leads to a certain de-abstracting of them.

This paper addresses the lack of analytical tools for visual data analysis in IEEE Xplore, an abstract database of publications on technical problems in electronics and electrical engineering. The openness of the platform and the good fillability of a large number of bibliometric record fields make it attractive for visual data analysis. The topic of machine learning and artificial intelligence applied to power systems, which are critical issues in the energy transition process, is chosen as an example for visual data analysis. The programs and utilities used for data analysis were VOSviewer, Scimago Graphica, FP-Growth algorithm, Inkscape, and MultiDendrograms. The use of IEEE Terms field data to identify publication topics in the exported data is analyzed in the most comprehensive way. This paper can be considered a reference for professionals interested in bibliometric analysis and visualization of IEEE Xplore data.

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

The author previously investigated the thermodynamic properties of the one-dimensional Potts-SOS model on the lattice of positive natural numbers N in [Akin H, Phys. Scr. 99 (2024), 055231]. In this present paper, we extend that research by determining the Gibbs measures for the same mixed-type model using partition functions constructed on a second-order semi-infinite Cayley tree. By leveraging the self-similarity of the Cayley tree, we analyze the behavior of these partition functions and identify the regions where phase transitions occur. We pinpoint these phase transition regions through a stability analysis of the dynamical system associated with the model at specific fixed points.

ObjectivesIn increasingly stressful times, many people are increasingly turning to fast food, neglecting to drink enough fluids and often forgoing regular exercise. The fast tempo of everyday life leaves little room for healthy habits, such as cooking at home, which means that a conscious and balanced diet takes a back seat.MethodsA descriptive pilot study was conducted to investigate the effects of an eight-week intervention program. This program included the daily intake of breakfast, cooking at home, adequate fluid intake and daily physical activity. The aim of the study was to evaluate the effects of these measures on the participants' body weight and general health.Results During the 56-day intervention, there was a steady trend towards weight reduction, and at the end of the intervention phase, a significant weight reduction in the test person could be observed. At the end of the intervention, the participant was still 45 years old, measured a body weight of 73.4 kg, which represents a BMI of 25.1 and is classified as slightly overweight. ConclusionThe results of the pilot study demonstrate clearly that the health mix of regular cooking at home, a daily breakfast, a daily physical activity session and sufficient fluid intake can be an effective booster for weight loss in adults. This combination has not only led to a significant reduction in body weight, but has also shown that simple, everyday measures can have a profound effect on health.

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

Objectives. The aim of the study is to identify relevant research topics based on pooled bibliometric data of International Journal of Hydrogen Energy publications from 2022-2024, collected from The Lens and ScienceDirect platforms. Data source. Bibliometric records of International Journal of Hydrogen Energy articles published in 2022-2024 from The Lens and ScienceDirect platforms were used. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility. Results. The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The 'Fields of Study' data of The Lens can be rationally interpreted as system keywords similar to Scopus Index Keywords. The possibility of using 'Fields of Study' data in a method similar to bibliographic coupling is shown. The practicality of using an Alluvial diagram to show the co-occurrence of the four terms was demonstrated. The study also emphasizes the advisability of joint use of VOSviewer and Scimago Graphica programs for complex visualization of bibliometric analysis results. The study identified two dominant publication topics in International Journal of Hydrogen Energy for 2022-2024, which can be described in terms of: 'Catalysis, Hydrogen, Physical_chemistry, Chemical_engineering, Nanotechnology, Electrochemistry, Organic_chemistry, Materials_science' and 'Electrical_engineering, Hydrogen_production, Renewable_energy, Environmental_science, Hydrogen_economy, Hydrogen, Engineering'.

The utilization of Artificial Intelligence (AI) in biotechnology is widespread, addressing challenges such as elucidating disease pathophysiology and novel therapeutic approaches. AI plays a critical role in tasks such as drug manufacturing, chemical analysis, RNA and DNA sequencing, and enzyme studies by automating processes and expediting data collection and analysis. AI has particularly transformed the analysis of omics data for researchers, providing tools to handle complex and multifaceted datasets effectively. Through AI, integrative analysis of multi-omics data can be conducted in efficient ways. This article discusses the application of multi-omics and AI technologies in studying various diseases related to infection (COVID-19), mutation (cancer), and senescence (alopecia) to understand their pathophysiology. The applications of AI were performed as the aspect of the diagnosis, prognosis, and treatment for each disease. We introduce AI-driven analysis of pathophysiology can overcome traditional limitations in pathology, with diverse features showing potential in defining the causes of diseases, and potentially enhancing primary omics data in the distinguish the subtype of diseases. In this context, integrated approaches using multi-omics data and AI technology could provide fresh biological insights by comprehending the molecular mechanism of diseases and is instrumental in advancing precision medicine. We anticipate that the rapidly advancing AI-based multi-omics data analysis will significantly contribute to promoting healthy longevity.

Objectives. The aim of this study was to demonstrate the ability to visualize the results of the Scilit platform's bibliometric data analysis on the topic "AI & Machine Learning" to identify publications reflecting specific issues of the topic. Data source. Bibliometric records exported from the Scilit platform on the topic "AI & Machine Learning" for the years 2021–2023 were used. For each year, 6,000 records were downloaded in CSV and RIS format. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility, GSDMM algorithm. Used services: Elicit, QuillBot, Litmaps. Results. It has been shown that bibliometric data from the open access abstract database Scilit can serve as a quality alternative to subscription-only databases. Data exported from the Scilit platform require preprocessing to make them available in a format that can be processed by programs such as VOSviewer and Scimago Graphica. The use of GSDMM and FP-growth algorithms is effective for structuring bibliometric data for further visualization. The Scimago Graphica software provides wide possibilities for building compound diagrams, in particular, for representing the network of keywords in such important coordinates for bibliometric analysis as average year of publication and average normalized citation, as well as for building an alluvial diagram of co-occurrence of more than two keywords. The possibility of using such services as elicit.com, quillbot.com and app.litmaps.com to accelerate the selection of publications on the topic under study is shown.

The anatomy of mature vertebrate hearts is marked by a looped design, which is roughly characterized by two components: (1), s-shaped (sigmoid) routing of the cardiac flow path(s), and (2,) bilaterally asymmetric (chiral) routing of the cardiac flow path(s). The looped heart design is regarded as a phylogenetically conserved feature among vertebrates and is thought to represent a significant determinant of the cardiac pumping function. It evolves during the embryonic period of development by a morphogenetic process called “cardiac looping”. During the past decades, remarkable progress has been made in the uncovering of the genetic, molecular, and biophysical factors contributing to cardiac looping. Thereby, a special focus was directed on the evolution of a bilaterally asymmetric (chiral) heart configuration, which is said to play a central role in the determination of the alignments and separations of the pulmonary and systemic flow paths in the multi-chambered hearts of tetrapods. In contrast to the recent progress made in uncovering of the biological driver of cardiac looping, our present knowledge about the functional consequences of cardiac looping is at an immature state. This article provides an overview and discussion of the currently available information about the looped design of vertebrate hearts and its functional implications.

Environmental, social, and governance (ESG) investment has become a common trend in capital markets, and many institutional investors have publicly declared their long-term ESG investment target (ESGIT). This study focuses on investors who conduct strategic asset allocation (SAA) using composite indices but establish their ESGIT outside the SAA process. A mismatch could arise between investors’ planned and actual portfolios because they must pursue their ESGIT by asset selection, which inevitably makes the constituents of their portfolios different from those of composite indices. To scrutinize the potential existence of a misalignment between their SAA and ESGIT, this study analyzes actual stock and bond indices over the past decade using traditional mean-variance optimization. The results reveal significant differences between the expected and realized performances, and the misalignment is more significant when the analysis period is divided into two sub-periods: stable and volatile. Specifically, the results indicate that the efficient frontier constructed using ESG indices significantly differs from that constructed using composite indices, and that the difference between these two efficient frontiers becomes more significant during volatile periods. Furthermore, the results show that investors cannot meet their targets if their ESGIT is established outside the SAA process.

The discovery of the quantum tunnelling effect---the transmission of particles through a high potential barrier---was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a novel deep neural network (DNN) architecture that processes information using the effect of quantum tunnelling. I demonstrate the ability of the quantum tunnelling DNN (QT-DNN) to recognise optical illusions like a human. Hardware implementation of QT-DNN is expected to result in an inexpensive and energy-efficient neuromorphic chip suitable for applications in autonomous vehicles. The optical illusions recognition tests developed in this paper should lay foundations for cognitive benchmarking tasks for AI systems of the future, benefiting the fields of sociophysics and behavioural science.

Background. Keyword co-occurrence analysis is a crucial tool for comprehending research trends, identifying relevant studies, and gaining insight into the connections between various concepts and topics. Objective. This study focuses on analyzing the co-occurrence of keywords using FP-growth algorithm and direct search methods. Materials and methods. The methodology involved extracting bibliometric data of Energies journal for 2023-2024 from MDPI publisher platform, keyword lemmatization and keyword co-occurrence estimation. Clustering and visualization were performed using Multidendrograms and Scimago Graphica software. Results. The results showed that the FP-growth algorithm can achieve a close match with the direct search results, which facilitates data preparation for clustering. In addition, finding the co-occurrence of three or more keywords significantly reduced the number of possible combinations, which allowed the identification of specific research topics. Conclusions. This study highlights the usefulness of the FP-growth algorithm in keyword analysis and provides insights into ways to refine search queries to abstract databases for the purpose of designing and writing literature and systematic reviews.

The Metaverse of Things (MoT) is an advanced technology that has the potential to revolutionise urban living in the present era. This article explores the advantages, uses, and transformative outcomes of MoT in smart cities. The covered subjects encompass sustainability, urban planning, citizen participation, infrastructure management, and various more. MoT integrates the Internet of Things (IoT) with metaverse technologies. The ultimate objective is to develop virtual environments that are highly interactive, interconnected, and immersive while maintaining a high level of fidelity to reality. The IoT utilises virtual reality (VR), augmented reality (AR), and other digital technologies to gather data, facilitate communication, and automate certain processes, thereby enhancing several elements of urban living. It is all a component of the metaverse. The IoT will bring about a profound transformation in the way cities gather and utilise data to enhance services and optimise efficiency. Cities that can efficiently distribute this data can enhance public safety, optimise energy usage, regulate traffic, and manage waste properly. MoT apps that utilise immersive technologies and the IoT can be used to generate more intelligent and captivating cityscapes. The implementation of MoT can greatly enhance the quality of life for residents of smart cities through improvements in transportation, healthcare, education, and community engagement. The study's author examined how smart cities utilise the IoT to enhance the daily experiences of their inhabitants. This study examines the technical structure, possible advantages, and difficulties of implementing MoT in urban settings, aiming to enhance the resilience, responsiveness, and adaptability of cities. The findings emphasise the importance of robust legislative frameworks, stringent security requirements, and well-developed infrastructure to facilitate the extensive use of MoT technology. These factors are crucial for establishing a highly interconnected and efficient urban environment.

This article explores the profound implications of Dr. Anthony Fauci's testimony before the U.S. House Select Subcommittee on the Coronavirus Pandemic, where he admitted that key COVID-19 policies lacked scientific backing. By analyzing the foundation of these decisions, the piece delves into the broader issues of scientific evidence, hypothesis validation, and the societal consequences of implementing unverified measures. It raises critical questions about the role of scientific rigor and accountability in policy-making, urging a reflection on our approach to scientific inquiry and decision-making in public health.

High-power lasers play an important role in modern science, industry, and medicine. A signifi-cant milestone was reached on December 5, 2022, when Inertial Confinement Nuclear Fusion (ICF) achieved scientific breakeven, releasing more energy than the input laser energy. Additionally, Extreme Ultraviolet Lithography (EUVL) has enabled the development of microchips with 3 nm process nodes, marking a leap in semiconductor technology. These examples together with the recent achievement of a 10 PW (1015 W) laser output heralds remarkable advancements in technology and science soon. Laser systems are broadly classified based on their operating re-gimes into two main categories: Continuous Wave (CW) operation, where the laser is continuously pumped and emits a steady beam of light, and the pulsed regime, in which the laser pro-duces single or multiple pulses at various repetition rates. This review will primarily focus on pulsed laser systems, exploring their various types and recent technological advancements.

Many historic buildings and monuments on the Salento Peninsula (Apulia, southern Italy) were built from locally quarried Miocene calcarenites belonging to the Pietra Leccese Formation (Late Burdigalian-early Messinian). The main facies consists of a homogeneous and porous biomicrite, pale yellow in color and fine- to medium-grained, very rich in planktonic Foraminifera and massive or thick-bedded in outcrop. Additionally, there are other facies among which Piromafo stands out for its aesthetic appearance, which is enhanced by its greenish-brown or greenish-grey colors. Its physical characteristics, in terms of thermal properties mainly due to the mineral content and fabric, make it a good refractory and insulation material. Piromafo occurs in the upper part of the Pietra Leccese Fm. and is repre-sented by a fine- to medium-grained glauconitic and phosphatic biomicrite with macrofossils, es-pecially Bivalves and Gastropods. Despite its important historical use as building and ornamental material, especially in the Roman and Baroque architecture, a research gap exists in the scientific literature describing the properties of the stone and their correlation. Therefore, the aim of this paper is to present a wide range of properties useful to explain the in-situ behavior and damage susceptibility of the stone in monu-ments and buildings, but also for selecting preservation treatments and strategies. Thus, an overall assessment of the main petrophysical and mechanical properties especially for restoration/conservation purposes was performed using both standard and unconventional tech-niques. Starting from rock fabric inspection, particular attention was given to the relationship be-tween pore-size distribution and, hydraulic and thermal properties of the material. Unconfined compressive strength, flexural strength and indirect tensile strength were also estimated.

Little has been written in literature about the clinical comparison of the single use of chlorhexidine (CHX) rather than its combination with cetylpyridinium chloride (CPC). The purpose of this study was to compare the clinical effectiveness of two at-home antiseptic regimens. Healthy subjects scheduled for dental surgery were enrolled. After the surgery, patients were randomly allocated in a first group (Group A) which received a manual ultra soft toothbrush (Mentadent Professional®), an antiseptic toothpaste with 0,12% CHX and Vitamin B3 (Mentadent Professional Azione Intensiva Gengive®) and an antiseptic mouthwash with 0,12% CHX and 0,07% CPC. The second group (Group B) received solely an antiseptic mouthwash with 0,2% in conjunction with Anti Discoloration System (Curasept ADS/DNA®) and were encouraged to use their usual toothbrush and toothpaste. Patients were instructed to use the products twice a day and to rinse for 30 seconds. On day 7, patients were examined for the Early Healing Score, Visual Plaque Index of the sutures, Numerical Rating Scale and mouthwash taste. Group A showed a statistically significant levels of EHS and taste satisfaction. The regimen based on CHX associate with vitamin B3 in the toothpaste and CPC in the mouthwash resulted in superior clinical outcomes and satisfaction compared to solely CHX.

Mercury (Hg) analyses in species of fish are performed for two reasons 1) to safeguard human health, 2) to assess environmental quality, since different environmental changes may increase the Hg concentrations in fish. These analyses are important since both natural and human activities can increase these Hg concentrations, which can vary extensively, depending on the species, age and catching location. Unfortunately, humans consuming Hg contaminated fish or other marine foodstuffs cannot taste Hg contamination; this can be only detected by chemical analysis. If the aim of Hg analysis is to protect the health of marine-food consumers, researchers workers must consider the location where the fish were caught and interpret the results accordingly. Health and environmental officials must appreciate that in specific places many local people may have a daily diet almost entirely consisting of fish or other marine foods, and these individuals should not be exposed to high concentrations of Hg. Regional and national health and environmental officials should follow the guidance of international organizations when drawing their final conclusions about whether or not the products are safe to eat.

This study presents a comprehensive comparative analysis of retrofitting techniques aimed at enhancing the seismic resilience of seismically vulnerable historical buildings. Recognizing the dual objectives of structural safety and architectural preservation, this research evaluates and compares several advanced retrofitting methods, including base isolation, strengthening of masonry, steel bracing systems, Fiber-Reinforced Polymer (FRP) wrapping, and damping devices. Each technique is critically assessed based on its effectiveness in mitigating seismic risks, its compatibility with historical architectural features, and its applicability to various building types. Base isolation is highlighted for its ability to decouple buildings from ground motion, thereby significantly reducing seismic forces and protecting architectural integrity. Strengthening of masonry through the use of fiber-reinforced polymers and steel elements enhances the ductility and strength of masonry walls, making them more resilient to seismic forces. Steel bracing systems are shown to provide essential lateral support, particularly in timber-framed structures, improving overall stability and reducing deformation during earthquakes. FRP wrapping is identified as a versatile technique that strengthens structural elements without compromising aesthetic value, making it suitable for reinforcing concrete and masonry components. Damping devices, including viscous dampers and tuned mass dampers, are discussed for their ability to dissipate seismic energy and control structural vibrations, offering a minimally invasive solution that preserves historical aesthetics. The study also addresses several challenges and research gaps associated with these retrofitting techniques, such as ensuring architectural compatibility, assessing long-term material performance, optimizing cost-effectiveness, and navigating complex regulatory frameworks. By advancing knowledge in these areas, the research aims to foster interdisciplinary collaboration and innovation in the development of retrofitting solutions. Ultimately, this study contributes to the ongoing efforts to safeguard historical buildings against seismic hazards. By leveraging cutting-edge technologies and best practices in structural engineering and architectural conservation, stakeholders can develop sustainable, cost-effective, and culturally sensitive retrofitting strategies that protect valuable cultural heritage for future generations.

Salinity, resulting from climate change and excessive mineral fertilization, burdens farmers and negatively impacts soil and water ecosystems in the Northeastern Nile Delta. Organic and biological approaches are crucial for addressing these issues. This study examined the effects of individual and combined inoculations with cyanobacteria, yeast, and Arbuscular Mycorrhizal Fungi (AMF), with or without K-humate, on enhancing salinity tolerance, increasing yield, and improving crop quality of wheat and faba bean. The aim was to reduce NPK mineral fertilizer application rates to 25% of recommended doses. An economic evaluation was also conducted. In a preliminary laboratory experiment, the interactive effects of these microbiomes on the production of plant antioxidant enzymes and soil enzymes were investigated under salinity stress. Results showed that co-inoculation, especially with K-humate, yielded superior outcomes compared to individual inoculations. The laboratory experiment findings were confirmed by a field trial conducted in saline-alkaline soil in the Northeastern Nile Delta region. The study found that the integrated inoculation of cyanobacteria, yeast, and mycorrhizae with K-humate, along with 25% mineral NPK fertilization enhanced microbial activity, including AMF colonization, spore density, and total bacteria, cyanobacteria, and yeast counts in the plant rhizosphere. It also increased soil enzyme activity, improving soil fertility compared to individual or mineral control treatments. This integration resulted in wheat yields of 2.77 tons/ha and faba bean yields of 4.75 tons/ha. Crop quality improved, with higher levels of nitrogen, potassium, phosphorus, and protein in wheat grains and faba bean seeds. Microbiomes inoculation increased potassium uptake over sodium, enhancing the potassium/sodium ratio and salt stress tolerance. This approach reduces reliance on costly mineral fertilizers by up to 75%, enabling economically viable cultivation in marginal lands. These sustainable practices optimize resource utilization, maximize economic efficiency, and preserve natural resources.

Medical image segmentation is a critical step in various healthcare applications, aiding in diagnosis, treatment planning, and disease monitoring. In this study, we investigate the efficacy of a segmentation approach based on the 2D wavelet transform. Leveraging a dataset comprising 10 diverse medical images, we evaluate the performance of our segmentation method using three key metrics: accuracy, precision, and recall. Our findings demonstrate that the proposed approach enhances segmentation accuracy, offering promising results compared to existing methods. By harnessing the multi-resolution feature extraction capabilities of the 2D wavelet transform, our method achieves improved delineation of medical image structures, paving the way for more accurate and efficient healthcare interventions.

Relevance of the subject. Keyword selection is critical to finding relevant literature and requires justification for querying abstract databases and other sources to ensure accuracy and completeness. The topic of Energy Systems is of great importance due to the introduction of renewable energy sources, modern control methods, and complex energy systems during the energy transition. The aim of this study. The goal of this paper was to identify keywords that would be useful to subject matter experts when collecting literature on a particular topic, based on entries in the IEEE Terms field. Data. Bibliometric data were exported from the IEEE Xplore platform in the following order: for 2019-2023, 2000 records sorted by relevance, for 2024, 1680 records current as of April 11, 2024. Analytical methods applied and software used. VOSviewer, Scimago Graphica implementing the Clauset-Newman-Moore algorithm and agglomerative hierarchical clustering method implemented in Multidendrograms. Results. The main issues of the Energy Systems topic are presented in tabular and graphical formats. The fpgrowth utility offers flexible data preparation options, which makes it worthwhile to conduct a separate study to analyze the score of co-occurrence terms given by its algorithm.

Background: Breast cancer and other neoplasms like acute lymphocytic leukemia pose a serious threat to public health worldwide. Treatment for malignancies including acute lymphocytic leukemia and breast cancer requires enzymes that break down L-glutamine. An amidohydrolase called L-glutaminase can be an effective chemotherapeutic tool for treating various cancers. Methods: On mineral L-glutamine agar selective medium (MGA), a few bacterial isolates were examined in the current investigation to see if they produced L-glutaminase. However, the most effective positive bacterial isolates generating L-glutaminase were identified using morphological and biochemical testing. Molecular detection using the direct Southern blotting approach was also used to determine the main positive isolate that produces L-glutaminase. L-glutaminase synthesis by bacteria was evaluated for its characteristics. Using an MTT test, the anticancer activity was evaluated. Results: exclusive bacterial isolates that used L-glutamine as their sole source of metabolic nitrogen exhibited favorable growth on MGA. PH 7.4 and a temperature of 37 0C were the ideal environmental and physiological conditions for developing positive bacterial isolates. From the soil samples taken from various soil conditions in Egypt, the morphological and biochemical analyses showed that Bacillus cereus 14579 was the main positive bacterial generating L-glutaminase isolate. At a pH of 7.4 and a temperature of 37 °C, the following activators—KCL, ZnSO4, FeSO4, K2HPO4, and MgSO4—provided the high-grade circumstances for characterizing L-glutaminase synthesis. Bacillus cereus-produced L-glutaminase has shown excellent bioavailability and effectiveness as an anticancer therapy. The yield [productivity] was 5.2 U/ml during the original manufacture from MGA, but it increased to 42.96 U/ ml by bacterial recombinant DNA manufacturing. The molecular mass of L-glutaminase was roughly 37 KDa. L-glutaminase was purified, yielding final enzyme recovery of 55 1.23%, total activity 12,990± 19.76 ( U), specific activity 384.66± 8.92( U/ mg of protein), and purification fold 2± 2.99. Furthermore, the L-glutaminase activity was raised by 19%, 23%, 15%, and 9%, respectively, by the enzymatic activators Mn2+, K+, Na+, and Fe3+. It demonstrated strong DPPH scavenging activity (IC50 = 61 μg/ mL) and anticancer activity( IC50 = 40.72, 9.7, 7.39, 20.61, 51.28, and 11.55 μg/ mL, respectively) against human liver (HepG-2), colon ( HCT-116), breast ( MCF-7), lung( A-549), lymphocytic( CCL-120), and cervical( Hela) cancer cell lines. A stronger affinity for its substrate was shown by the kinetic parameters of Km and Vmax, which were 13.2 10-5 M and 119.86 μmol/ ml/ min, respectively. Conclusion: Acute lymphocytic leukemia and breast cancer are examples of auxotrophic malignancies for which L-glutamine serves as the only metabolic source, and L-glutaminase generated by Bacillus cereus was an appropriate enzyme in the therapy of these diseases.

On 17 October 1947, Niels Bohr was made a knight of the Order of the Elephant by the King of Denmark in view of his outstanding achievements and contributions to science. Bohr designed his own coat of arms that featured a pattern of Yin and Yang (Tai Chi symbol) to symbolize the wave-particle complementarity. However, Bohr’s Yin-Yang diagram (YYD) was neither drawn based on the principles of quantum mechanics, nor did it originate from the traditional Taoist YYD. Scientists still have doubts about the legitimacy of using YYD as the icon of the wave-particle complementarity, because the YYD belonging to quantum mechanics itself is unknown so far. This article reports the YYDs existing in quantum mechanics and justifies the role of YYD in the wave-particle duality by showing that any system, whether classical or quantum, has an ideal YYD as long as it satisfies Bohr’s principle of complementarity (BPC). The deviation of a deformed YYD from the ideal YYD indicates the extent to which a real system satisfies BPC. This article constructs the quantum YYD by the complex quantum trajectory of a particle tunneling via a step barrier, which displays the continuous transition between the wave behavior and the particle behavior. It appears that the YYD designed by Bohr in his coat of arms resembles the YYD generated by tunneling motion, not only in appearance but also in the governing equation.

Rubella infection is typically mild or asymptomatic except when infection occurs during pregnancy. Infection in early pregnancy can cause miscarriage, stillbirth, or congenital rubella syndrome. Only individuals that are still susceptible to rubella infection during child-bearing age are vulnerable to this burden. Rubella containing vaccine (RCV) is safe and effective, providing life-long immunity. However, average age-at-infection increases with increasing vaccination coverage, which could potentially lead to increased disease burden as well, if the absolute risk of infection during child-bearing age increases. Dynamics of rubella transmission were explored using EMOD, a software tool for building stochastic, agent-based infection models. Simulations of pre-vaccine, endemic transmission of rubella virus introduced RCV at varying levels of coverage to determine the expected future trajectories of disease burden. Introducing RCV reduces both rubella virus transmission and disease burden for a period of around 15 years. Increased disease burden is only possible more than a decade post-introduction, and only for contexts with low current burden and high transmission intensity. Low or declining rubella virus transmission intensity is concurrently associated with both greater disease burden and greater vaccine effectiveness. The risk of increasing burden through vaccination only exists for locations with persistently high infectivity, high connectivity, and high fertility. A trade-off between the risk of a small, future burden increase and a large, immediate burden decrease strongly favors RCV introduction.

Purpose of publication: - Preparation of bibliometric data exported from the Scilit platform on energy efficiency and conservation for further analysis to identify relevant research topics. - To identify potential issues in the processing of data exported from the Scilit platform. - Providing colleagues with the opportunity to use the prepared data and examples of their analysis for independent research on topical issues of energy efficiency and energy conservation using materials provided by the Scilit platform. Research Materials: Files in CSV and RIS formats exported from Scilit for the query "energy conservation OR efficiency" in Common Fields [Title, Abstract, Keyword], using filters: Content Type → Journal Article; Year→2021-2023; Subject → Industrial Engineering (29.8K), Energy and Fuel Technology (9.8K), Manufacturing Engineering (9.2K). A total of 30K records sorted by their relevance (10K for each year) were exported. Data are current as of 14-03-2024. Methods: Preprocessing of title, annotation, and keyword field texts using lemmatization dictionaries collected on GitHub, removal of keywords taken from GATE and spaCy, and "manual" editing. Using VOSviewer to analyze publication topics by clustering keywords based on their co-occurrence. Using Scimago Graphica to build bubble diagrams.Application of the GSDMM algorithm for clustering bibliometric records by title and annotation texts. Creation of a dictionary for this algorithm using the keyword field.Use of the Carrot2 demo version and the NMF algorithm for a more detailed analysis of the topics of the record clusters obtained from GSDMM. Results: are presented in the form of initial and interim tables and graphs obtained in the course of this study. The full tables are provided as references to the attached materials. Supplementary material for this preprint on figshare: Chigarev, Boris (2024). Supplementary material for preprint "Analyzing the Possibilities of Using the Scilit Platform to Identify Current Energy Efficiency and Conservation Issues". figshare. Dataset. https://doi.org/10.6084/m9.figshare.25574058.v1

Background: RSV, or respiratory syncytial virus, is a deadly condition that is present all over the world today. The infection is initially contained in the lower respiratory tract without systemic transmission. The objective of the study: Bioinformatics was used in Egypt to create an mRNA vaccine against the Respiratory syncytial virus (RSV). Methodology: In the present screening experimental study, a lipid nanoparticles vaccine of mRNA of the surface fusion protein of Respiratory syncytial virus was manufactured. The present vaccine delivery system was lipid nanoparticles with a particle size of approximately 90 nanometres, manufactured by the hot micro-emulsion method. In stages 1 and 2 of clinical trials, the immunogenicity of the current mRNA RSV vaccine was evaluated. Results: The current vaccine demonstrated 81% immunogenicity in animal testing, but only 69% in stages 1 and 2 of clinical trials. Its side effects were manageable. The results persisted for a while. In the current trial, the vaccination proved effective as a preventative measure against RSV infection. The current vaccination lacked antibody-dependent enhancement, which causes non-protective antibodies to develop. These non-neutralizing antibodies exacerbate infection by activating cytokines and complement cascade through the formation of immune complexes or enhancement of the virus entry and replication in the host cells. On the other hand, the current RSV mRNA vaccine of the surface fusion protein consequent on the production of powerful neutralizing antibodies with prolonged immunity especially to infants and elderly candidates who received the optimal dosage regimen.

The advancement of autonomous capabilities in maritime navigation has gained significant attention, with a trajectory moving from decision support systems to full autonomy. This push towards autonomy has led to extensive research focusing on collision avoidance, a critical aspect of safe navigation. Among the various possible approaches, Dynamic Programming is a promising tool for optimizing collision avoidance maneuvers. This paper presents a DP formulation for collision avoidance of autonomous vessels. We set up the problem framework, formulate it as a multi-stage decision process, define cost functions and constraints focusing on the actual requirements a marine maneuver must comply with, and propose a solution algorithm leveraging parallel computing. Additionally, we present a greedy approximation to reduce algorithm complexity. Through case studies, we demonstrate the effectiveness of the proposed approach in navigating complex scenarios, contributing to the future of autonomous maritime navigation. Through case studies, we show the efficacy of our approach in navigating complex scenarios.

Technological advances in the last decades have led to the realization of the concept of a smart environment. A significant part of this development is decentralized ledger technology and its variant, a blockchain. The blockchain database is immutable, open to all stakeholders, secure by architecture and robust. Applying a blockchain in water supply sanitary control creates opportunities for optimization, higher quality of service, cost reduction, better sanitary standards and public control. Physical, chemical, and biological water supply contamination is a great source of public health hazards. Implementation of a blockchain for water supply IoT, from the source point to the consumption point, enables effective response to changing environments, possible cross-contamination, stormwater management or disaster and emergency action. The chapter encompasses all fundamental elements and principles of water collection, distribution and consumption, with a focus on the health hazards and sanitary requirements for potable water. The chapter listed the main contaminants, methods of their registration and elimination, and requirements for drinking water in accordance with WHO, EU Drinking Water Directive and EPA standards. Blockchain technology solutions are described for smart water supply, including smart supply management, smart contracts, tokenization, smart compliance systems, and, most importantly, effective utilization of distributed ledger technologies for sanitary monitoring of water sources, water treatment, and water distribution systems.

This paper explores the relationships between marketing strategies, social media platforms, the adoption and diffusion of products and services, and organizational resilience to gain an understanding of the ability of organizations to cope with disruptive events (e.g., COVID-19). This can be achieved through effective marketing strategies and the efficient use of social media platforms. In fact, resilience thinking can help organizations maintain their operations by increasing the adoption and diffusion of their products and services through the use of effective marketing strategies. To achieve this article’s objectives, a literature review is conducted to help develop a conceptual framework that highlights a clear relationship between the previously discussed concepts. In addition, the novel nature of the relationship between marketing strategies and organizational resilience is dissected and its significance for organizations is demonstrated. In fact, the findings of this study suggest that effective marketing strategies that consider the "what," "who," and "how" dichotomies and the efficient use of social media to promote the adoption and diffusion of products and services can significantly enhance the resilience of organizations. These relationships can serve as a starting point for further studies examining and empirically analyzing marketing strategies and their positive effect on strengthening organizational resilience.

Pakistan relies mostly on fossil fuel for fulfilling its energy demand which is expensive as 11 well as not friendly for the environment. The need of the hour is to shift from fossil fuels to renew-12 able energy resources like geothermal, wind, solar etc. to cater for global warming issues. Pakistan 13 has a lot of potential geothermal sites because of several fault lines and hot springs. A sound 14 knowledge of ground temperature is essential to use geothermal energy, which is obtained by drill-15 ing boreholes and putting sensors making it an expensive procedure. Thus, to avoid huge cost for 16 drilling bore holes, particularly for ground temperature analysis, a numerical approach has been 17 considered for determining ground temperature. Furthermore, correlation charts between air and 18 ground temperatures have been developed as there were no proper studies on the ground temper-19 ature of Pakistan. Then, with the help of a boreholes drilled in National University of Sciences and 20 Technology Islamabad Pakistan, the actual ground and numerically calculated temperatures have 21 been compared which shows an error margin in the range between 0.27% for higher depths to 7.3% 22 near surface. Thus, it is shown that the proposed method is easy to implement and better than large 23 scale testing methods for the depths at which geothermal energy is extracted.

The paper presents a method to assess the effect of electrolyte additives on the energy capacity of Pb-acid batteries. The method applies to any chemically unreactive additive, including suspensions and gels. The approach is thermodynamically based and it leads to the definition of a region of admissible concentrations –the battery’s admissible range– where the battery can undergo an indefinite number of charge/discharge cycles without suffering permanent damage. An experimental procedure to determine this range is presented. The obtained results provide a way to assess the potential of electrolyte additives to improve the energy capacity of Pb-acid batteries. The same results also provide a means to determine the additive concentration that produces the maximum energy capacity increase of the battery. The paper closes with an example of application of the proposed approach to a practical case.

Determination of antibody titre of dogs vaccinated against canine distemper in Jos North and South local Government Areas of Plateau State was carried out by collection of sera of vaccinated dogs and administration of well-structured questionnaires to dog owners. The samples collected were analyzed using the immune-blot ELISA Kit to determining the antibody titre (immunoglobulin G). It indicated that dogs vaccinated against the disease mounted adequate protective immunity. The result revealed that 54 (90.0%) of the sampled dogs have protective immunity, with those given more than one dose having higher level of protective antibody. Statistically, the result showed that the antibody titre did not differ significantly in relation to immunity and sex, breed, age and location but significant difference was seen in relation to number of primary vaccination. The result also revealed that those dogs that received booster doses (secondary vaccination) had more protective antibody. The study was aimed at evaluating the antibody titre of dogs vaccinated against canine distemper in Jos, Plateau State.

This research project was funded by the Masterplan for Acceleration and Expansion of Indonesia's Economic Development (MP3EI). The objective of this study was to examine the role of indigenous people of Marind in the agricultural development of rice cultivation in Merauke. A survey was conducted in three villages in Merauke using stratified random sampling. The finding suggest that indigenous people of Marind have a crucial role in the agricultural development of rice cultivation in Papua.

This paper aims to present a particular study of the performances of electric vehicles based on real driving conditions on a cycle carried out using the general conditions of Regulation (EU) 1832/2018 regarding RDE tests. In this sense, a modern electric SUV was used and the experimental tests were made using a measuring equipment connected to the vehicle via the OBD2 plug. In the following, the experimental results will be analyzed and presented and the main influencing factors on the energy performance that may occur in real running conditions will be identified.

Low learning rates in Convolutional Neural Networks (CNNs) for image segmentation tasks can lead to convergence issues, unstable models, large oscillations, risk of divergence, sensitivity to the initial weights, and biases of the model. All these challenges make CNNs computationally expensive and require considerable training data. In contrast, achieving a high learning rate has been a significant challenge for CNNs. In response to the abovementioned challenge, this work aims to increase the learning rate of the image segmentation process. Images of any object in the universe taken from any camera can broadly be divided into spectral and geometric properties. Both these properties are prominently visible in satellite images. Therefore, if a method can classify satellite images, it can be applied to classify any image using the same technique. In this paper, Evolutionary Convergent Functions (ECF) are proposed. They convert features' spectral and geometric properties in a satellite image into mathematical equations using a decision tree and then converge with a neural network. Different high-resolution data have been chosen to extract additional features from it. This transformation process, anchored in decision tree methodology, converges with neural networks to yield unparalleled results, all while eliminating the need for computationally intensive convolutions. The proposed method extends beyond conventional boundaries by using varied high-resolution datasets. Each dataset is carefully selected with distinctive features. This research explores the untapped potential of ECF to advance the field of automated image classification, aiming to broaden the scope of current methodologies. The synergy between spectral and geometric properties emerges as a powerful combination, endowing our methods with the ability to extract nuanced and context-rich information for image analysis. The results show a high accuracy, i.e., above 90%, in almost all objects of different shapes and spectral signatures. Additionally, in terms of prediction time, ECF is faster than U-Net, a state-of-the-art method that is evidence of ECF efficiency and speed.

With increased life expectancy and improved modern lifestyles, there has been a growing concern for health, including the prevention of disease and the improvement of physical appearance. Consumers are increasingly aware of the benefits of using natural ingredients in healthcare products and at the same time are concerned about the challenges of sustainability. In this sense, the use of marine bioactive compounds as cosmetic ingredients and in food supplements has become increasingly popular due to the benefits derived from their various properties. However, some of these compounds have limited use, mainly due to their low stability and poor aqueous solubility, and solutions need to be developed to overcome these limitations. In this sense, the use of lipid nanoparticles, such as solid lipid nanoparticles (SLN) and nanostructured lipid carriers (NLC), has been explored as these carriers show ability to protect and enhance the absorption of molecules. Several studies have demonstrated the efficacy of encapsulating these compounds and incorporating them into cosmetics and food supplements. However, there is still no global legislation and safety concerns have been raised. Further clinical studies in animals and humans are needed to clarify safety issues.

Background/Objectives: Malnutrition significantly hinders the recovery of patients undergoing convalescent rehabilitation. Proper nutritional management can improve rehabilitation outcomes. This study aimed to establish a novel nutritional screening method (J-Method) specifically for convalescent rehabilitation patients and compare it to the widely used Mini Nutritional Assessment Short Form (MNA-SF). Methods: We developed the J-Method for convalescent rehabilitation settings and compared its results with that of the MNA-SF. The J-Method comprised six items derived from various nutritional screening methods and obtained solely from medical records, without patient interviews. Data were collected from 148 patients aged > 65 years with cerebrovascular diseases admitted to a convalescent rehabilitation ward (CRW). Nutritional status was evaluated using the J-Method and MNA-SF, and results were compared. Results: The J-Method more precisely identified patients as malnourished than the MNA-SF. The results of nutritional screening using the J-Method identified patients in need of nutritional management intervention and suggested that, to improve the rehabilitation effect, nutritional management should be initiated in an acute hospital before admission to a CRW. Conclusions: The J-Method may be more effective than the MNA-SF for nutritional screening in convalescent rehabilitation settings as it provides a more accurate assessment of malnutrition without requiring patient interviews.

Background/Objectives: This study aimed to compare the diagnostic accuracy of the Wells and Geneva scores, used with a 500 ng/mL D-dimer cutoff, along with the age-adjusted D-dimer (AADD), YEARS, and PEGeD algorithms in patients with and without COVID-19. The performance of various D-dimer thresholds was also evaluated. Methods: This retrospective study included patients who presented to the emergency department and underwent computed tomography pulmonary angiography (CTPA) for suspected pulmonary embolism (PE). The diagnostic performance of clinical prediction algorithms was compared between two groups. Results: We analyzed data from 1423 patients; PE diagnosis and COVID-19 positivity rates were 7.3% and 69.9%, respectively. In patients with COVID-19, the Wells score with a 500 ng/mL D-dimer threshold exhibited 97.22% sensitivity (95% CI: 80.53–100.00) and 4.99% specificity (95% CI: 3.58–6.39). Using AADD increased the specificity to 7.81% (95% CI: 6.08–9.54) while maintaining sensitivity at 97.22% (95% CI: 93.43–100.00); similar results were observed for the Geneva score. The YEARS algorithm exhibited 86.11% sensitivity (95% CI: 78.12–94.10) and 32.75% specificity (95% CI: 29.73–35.78), whereas the PEGeD algorithm exhibited 86.11% sensitivity (95% CI: 78.12–94.10) and 34.06% specificity (95% CI: 31.00–37.12). The YEARS and PEGeD algorithms demonstrated better performance in patients with COVID-19 in terms of specificity and accuracy. Conclusion: COVID-19 infection did not significantly affect the diagnostic performances of the clinical algorithms for PE. YEARS and PEGeD performed better in patients with COVID-19, making them preferable. Higher D-dimer thresholds improved specificity but increased the risk of missed PE diagnoses.

In the Anthropocene era, lake ecosystems are facing significant human-related pressures, resulting in a decline in both biodiversity and habitat quality. Restoration initiatives can effectively enhance the resilience of freshwater environments. This research delves into various established and novel method aimed at encouraging the growth of a macrophyte, Vallisneria spiralis, in the littoral zone of Lake Como, a southern alpine Italian lake. For this aim, Vallisneria spiralis was collected and placed in tanks filled with four different types of 3D-printed biodegradable substrates. Remarkably, the plant demonstrated a growth rate of 4 mm per day, increasing from an initial number of 12 plants to 400 after four months, with a total surpassing 700 specimens by the conclusion of the study. Following their introduction into the natural environment, the survival rate of plants positioned on substrates that remained stable and in contact with the lakebed reached 85.7%. This research is the first to indicate that Vallisneria spiralis could be a viable option for restoration projects in coastal lake habitats, particularly when utilizing biodegradable substrates. The hope is that this study can serve as a valuable model for future restoration initiatives and improve sustainability of freshwater ecosystems.

Cancer remains a primary cause of mortality, with over 18.1 million new cases and 9.6 million deaths globally in 2018. Chemotherapy, which utilizes a spectrum of cytotoxic drugs targeting rapidly dividing cancer cells, is a predominant treatment modality. However, the tendency of chemotherapeutics to induce drug resistance and exhibit non-specific cytotoxicity necessitates the development of new anticancer agents with heightened efficacy and minimized toxicity. In recent years, the discovery of safe and effective antibacterial/antiviral agents has also been a hot spot in medicinal chemistry. This paper comprehensively reviews the synthesis, anticancer/ antibacterial/antiviral activity, and structure-activity relationships of natural 1,4-naphthoquinones and their derivatives. It highlights their potential as efficient and low-toxicity anti-tumor and anti-infectious drug candidates.

The global burden of respiratory syncytial virus (RSV) and severe associated disease is prodigious. RSV specific vaccines have been launched recently but there is no antiviral medicine commercially available. RSV polymerase (L) protein is one of the promising antiviral targets along with fusion and nucleocapsid proteins. During medicinal chemis-try campaign, two potent L-protein inhibitors (PC786 and PC751) were identified. Both compounds inhibited RSV A/B-induced cytopathic effect in HEp-2 cells equally, but PC786 was more potent than PC751 in bronchial epithelial cells. Repeated treatment with escalating concentrations on RSV A2 infected HEp-2 cells revealed both inhibitors led to a Y1631H mutation in the L protein, but only PC786 induced a mutation in the M protein (V153A). By L-protein fragment and M protein binding analysis, we showed that the M protein interacts with the 1392-1735 amino acid region of the L protein, where potentially PC786 binds. In addition, PC786 treatment or PC786 induced mutant RSV was found to increase M protein nuclear localisation later in infection concomitant with delayed fusion protein localisation at the budding viral filaments. As M protein is known to play a key role in virus assembly and budding late in infection, our data suggests that disrupting the interaction between M and L could provide a novel target for antiviral development.

This study analyzes the elemental and oxide compositions of three selected agricultural residues—Dried Pawpaw Leaves (DPL), Kolanut Pod (KNP), and Sweet Orange Peel (SOP)—for their potential as heterogeneous catalysts. Energy Dispersive X-ray (EDX) analysis identified calcium (25%) and potassium (29%) as the primary elements in DPL and KNP, with calcium oxide (CaO) and potassium oxide (K2O) as the dominant oxides. SOP had a similar composition but lacked vanadium. Calcined residues were analyzed at temperatures ranging from 500°C to 900°C using X-ray Fluorescence (XRF), revealing stable silicon dioxide (SiO2) content and temperature-dependent variations in CaO and K2O, indicating their catalytic potential for transesterification processes. Scanning Electron Microscopy (SEM) showed non-uniform, spongy microstructures, enhancing the surface area and catalytic efficiency. Fourier Transform Infrared Spectroscopy (FTIR) identified functional groups essential for catalytic activity, such as hydroxyls, methyl, and carboxyl. X-ray Diffraction (XRD) confirmed the presence of crystalline phases like calcium carbonate and calcium oxide, crucial for catalytic performance. Experimental biodiesel production using a mixture of the calcined residues (33.33% each of KNPA, SOPA, and DPLA) resulted in the highest biodiesel yield at 65.3%. Model summary statistics, including R² (0.9824) values and standard deviations (0.0026), validated the experimental design, indicating high precision and prediction accuracy. These results suggest that the selected agricultural residues, when calcined and mixed properly, can serve as effective heterogeneous catalysts, with significant implications for biodiesel production, supporting previous research on the importance of calcium in catalytic processes.

Cancer remains one of the most critical global health issues. Conventional treatments, such as radiotherapy, surgery, or chemotherapy, have limitations, especially concerning side effects, resistance, and recurrence. Consequently, new innovative treatments to overcome these problems are needed. Photothermal therapy (PTT) is a promising alternative that uses photothermal agents that convert near-infrared light (NIR) into heat to kill cancer cells. Nanoparticles can be used as photothermal agents and also as drug delivery platforms, improving the drugs’ stability, allowing for targeted delivery, and reducing toxicity. Due to its broad absorption band, high surface area, and versatility for surface functionalization, tungsten disulfide (WS2) has high potential in this context. This paper presents the state-of-the-art on the use of WS2-based materials to achieve effective and biocompatible anti-anticancer new treatment strategies.

Insurance companies need to calculate solvency capital requirements in order to ensure that they can meet their future obligations to policyholders and beneficiaries. The solvency capital requirement is a risk management tool essential for, when extreme catastrophic events occur, resulting in a high number of possibly interdependent claims. This paper studies the problem of aggregating the risks coming from several insurance business lines and analyses the effect of reinsurance in the level of risk. Our starting point is to use a Hierarchical Risk Aggregation method, which was initially based on 2-dimensional elliptical copulas. We then propose the use of copulas from the Archimedean family and a mixture of different copulas. Our results show that a mixture of copulas can provide a better fit to the data than an individual copula and consequently avoid over or underestimating of the capital requirement of an insurance company. We also investigate the significance of reinsurance in reducing the insurance company’s business risk and its effect on diversification. The results show that reinsurance does not always reduce the level of risk, but can also reduce the effect of diversification for insurance companies with multiple business lines.

A major cause of genital discomfort in women around the world is bacterial vaginosis, which results from excessive growth of pathogenic bacteria in the vaginal ecosystem. Current treatment consists of antibiotics and/or probiotics, which show favourable therapeutic effects, but also cause problems such as drug resistance and recurrence. Considering faecal transplantation's success, transplantation of vaginal fluid from healthy donors could provide the most effective treatment for bacterial vaginosis. However, experimental treatments have shown that vaginal microbiome transplantation may not be a one-size-fits-all solution. The present article examines the limitations of current standardized therapy, the advantages of vaginal microbiome transplantation, and presents future novel strategies for treating bacterial vaginosis based on current research findings and clinical trials development worldwide.

Identifying effective and accessible interventions for family caregivers of persons with dementia (PWD) is crucial as the prevalence of dementia increases in Asia. This study investigated the efficacy of a telephone-intervention on reduction of caregiver burden, depressive and anxiety symptoms among family caregivers (FC) of PWD in Malaysia. A single-blinded randomized controlled trial was carried out with 121 FCs of PWD selected from memory or psychiatry clinics in three tertiary hospitals in Malaysia who were randomly allocated into intervention or control group. The intervention group received the psychoeducational intervention delivered by a healthcare staff via telephone for 10 sessions over 12 weeks. The outcome of the intervention was measured by the Malay version of the Zarit Burden Interview and the Hospital Anxiety and Depression Scale at baseline and post-intervention. Intention-to-treat analysis shows that caregiver burden, anxiety symptoms, and psychological distress among FCs in the intervention group decreased by 7.57 units (p<0.001), 2.46 units (p<0.001) and 2.98 units (p=0.011) respectively at post-intervention, compared to the differences from baseline to post-intervention in the control group. Policies aimed at integrating the telephone-intervention into memory/psychiatry clinics in Malaysia may help FCs of PWD to reduce their caregiver burden and stress while caring for a family member with dementia.

The potential of technical lignins slow pyrolysis is briefly summarized. The pyrolysis process, which can be self-sustained by burning the co-produced gas, can primarily produce high-quality biochar in significant amounts, to be used as a fuel and as a reductant in metallurgy. Together, significant amounts of bio-oil can be produced, rich in guaiacols, which are commercial and expensive chemicals produced today via petrochemical routes and used in pharmacology, food chemistry, polymer chemistry, etc. Such compounds or bio-oil itself can also be converted by hydrodeoxygenation into biofuels.

Aging is a complex and inevitable biological process characterized by a gradual decline in physiological function, including increased oxidative stress, chronic inflammation, and mitochondrial dysfunction. While aging is a natural part of life, it is often accompanied by various disorders collectively known as age-related diseases (ARDs) or aging disorders. These include neurodegenerative diseases like Parkinson’s (PD), cardiovascular diseases, diabetes, osteoporosis, and frailty, among others. As the global population ages, the prevalence of ARDs such as PD and frailty is rising, necessitating innovative approaches to enhance healthy aging. Nutraceuticals are natural bioactive compounds in foods that offer health benefits beyond essential nutrition, which is pivotal in preventing and managing aging-related disorders. Nutraceuticals, with their antioxidant, anti-inflammatory, and neuroprotective properties, offer promising strategies to counteract these processes and promote healthy aging. This review highlights the potential of nutraceuticals as valuable adjuncts in managing PD and frailty, two conditions intricately linked to ARD. By examining the differential impacts of these bioactive compounds on the underlying mechanisms of each condition, this study underscores the promise of nutraceuticals in promoting healthy aging. The review aims to inform future research and clinical strategies by advocating for developing novel bioactive compounds, using advanced delivery technologies, and integrating personalized approaches based on genetic and epigenetic profiles. These efforts will pave the way for more precise, effective, and individualized interventions, ultimately extending health span and preventing ARD.

The emergence of antimicrobial resistance (AMR) in pathogens transmitted through food poses a significant threat to global public health, complicating infection treatment and increasing mortality rates. This review explores the role of resistome mapping as a crucial tool for understanding the transmission dynamics of antimicrobial resistance genes (ARGs) in foodborne pathogens, such as Salmonella, Escherichia coli, Listeria monocytogenes, and Campylobacter spp., as well as various techniques for resistome mapping, such as metagenomic sequencing, PCR-based methods, and whole-genome sequencing (WGS), highlighting the significance of horizontal gene transfer (HGT) as a key mechanism for ARG dissemination in foodborne pathogens. Additionally, we investigated the influence of agricultural practices and environmental factors on AMR development, highlighting the critical need for improved surveillance, antibiotic stewardship, and global collaboration to mitigate the spread of resistant ARGs through the food chain. The perceptions gained from resistome mapping play an essential role in developing effective approaches to address AMR and to ensure food safety.

The energy supply for isolated systems remains a current challenge in Brazil and worldwide, particularly when known solutions are compared regarding cost, the ability to supply energy on demand, and sustainability. In this context, green hydrogen, which has been considered one of the main paths for the decarbonization of the energy chain, is also seen as a potential solution for energy supply in isolated systems. Based on a literature review of articles addressing the topics of green hydrogen and isolated systems, an analysis is conducted on the application of green hydrogen as an energy supply solution for isolated systems. The review identified and collected data on important parameters for comparing solutions, such as CAPEX, OPEX, energy cost, and the price per kilogram of hydrogen. Using these data, analyses were performed to provide an overview of the application of green hydrogen in isolated systems. One of the objectives of this work is to present a comprehensive analysis of the green hydrogen chain and its application in the context of electricity generation, particularly for isolated systems in Brazil.

This study presents the development of a diglycidyl monomer containing two imine groups that can act as dynamic and reversible bonds. During the curing of the monomer with two different amine hardeners, we confirmed the formation of new imine groups due to the transamination reaction, not reported before, between the imine groups of the diepoxy monomer with the amine groups of the hardener. The effect of this structural change is observed for the first time in the stress relaxation behavior, resulting in the overlapping of two different relaxation modes. The analytical modelling could extract two distinct characteristic relaxation times using a double-element Maxwell model. A second characterization of the stress relaxation process by frequency sweep experiments was performed to corroborate the results obtained, confirming speedy stress relaxation. Acid-catalyzed hydrolysis was performed on the studied materials, demonstrating the complete degradation of the network. We finally confirmed that the synthesized diepoxy compound is suitable for preparing carbon fiber-reinforced composite materials, demonstrating easy fiber impregnation, fast reshaping and especially a total degradation of the polymer matrix that allows the recovery of the carbon fibers in mild conditions. This epoxy-amine system is an excellent candidate for overcoming the traditional limits of thermosets in preparing fiber-reinforced composites.

Stunting is a major public health issue in Aceh, Indonesia, requiring advanced analytical techniques for effective interventions. This study presents a novel hybrid machine learning framework designed to enhance the analysis of stunting through improved classification, predic-tive modeling, and clustering optimization. The framework utilizes Support Vector Machines (SVM) with Radial Basis Function (RBF) and Sigmoid kernels for classification. The RBF kernel achieved an accuracy of 91.3%, significantly outperforming the Sigmoid kernel's 85.6%. Linear Regression was employed for predictive modeling, yielding a Mean Squared Error (MSE) of 0.137, which indicates strong predictive accuracy. In clustering, the optimized K-Medoids method, in-corporating a weight product approach, demonstrated superior efficiency by requiring only 3 iterations for convergence, compared to 7 iterations for the conventional K-Medoids method. Additionally, it achieved a higher Calinski Harabasz Index of 93.7, compared to 85.2 for the conventional method. This comprehensive approach enhances accuracy and efficiency across classification, prediction, and clustering tasks, providing valuable insights for targeted interventions and policy development to address stunting in Aceh.

We describe a forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) to operationally forecast conditions in Northern and Central California. It was established in 2014 and has been periodically improved. In the current configuration, WRF forecasts are routinely performed multiple times each day on a 2-km grid, and the results are used as input to wildfire fuel moisture, fire probability, and wildfire spread models. Components of the system include a stochastically perturbed ensemble; an annually updated reanalysis covering more than 30 years; and validation against PG&E’s extensive mesonet and other observing networks. We describe the development and validation of the next operational edition. Configurations tested include irrigation triggered by crop growing season and an ensemble-based approach with intelligently sub-selected Global Ensemble Forecast System (GEFS) members. The latter approach allows for enhanced uncertainty sampling in WRF forecasts and can greatly improve WRF forecasts when calibrated by observations.

This paper evaluates the open and closed loop DC-DC converter operation within a DC coupling multilevel inverter architecture to obtain an infinite level stepped sinusoidal voltage. Adding a cascade controller to the DC-DC converter should reduce the settling time and increase the number of levels in the output voltage waveform, it could decrease the speed error and phase shift concerning the sinusoidal reference signal. The proposed methodology consists of implementing an experimental multilevel inverter with DC coupling, through a single-phase bridge inverter energized from a BUCK converter, trigger signals for the two converters are obtained from a control circuit based in an ATMEGA644P microcontroller, and a digital controller is also implemented to evaluate the operation of the BUCK converter in open and closed loop and observe its influence in the stepped sinusoidal output voltage. The evaluation is performed to energize a resistive load with common output voltage in multilevel inverters, that is 3, 5, 7, 11, and infinity levels. Results show that during the design stage, fast dynamic elements, like the storage capacitor, can be used to obtain a minimum THD because the settling time is sufficiently fast and the speed error remains small and there isn’t a need for a controller. A digital controller requires processing time and although in theory, it can reduce the settling time to a minimum, the processor introduces latency in the control signals generation, producing the opposite effect. Controller complexity of the digital controller must be considered because it increases processing time and influences the efficiency of the closed-loop operation.

Heat exchangers play a vital role in numerous sectors like power generation and automotive manufacturing. Enhancing the energy efficiency of these exchangers stands as a significant hurdle. Utilizing nanofluids emerges as an optimal solution to augment heat transfer rates, leveraging their superior thermal conductivity while addressing economic constraints linked with traditional heat exchanger technologies. The motivation for this study is to consider the comprehensive synergistic features of MWCNTs, SiO₂, and hybrid MWCNTs–SiO₂ EG-based nanofluids in plate heat exchangers. This was achieved by simulating a plate heat exchanger using CFD (Fluent and Gambit softwares) considering the comparison of two SiO₂, MWCNTs, and their hybrid forms at different mass concentrations. The Reynolds-Averaged Navier-Stokes (RANS) method was employed to model turbulent flows, and the nanoparticles were compared in both single-phase and two-phase states, with their properties derived from experimental studies. Moreover, Nusselt number, convective heat transfer coefficient, and pressure drop variations were computed at different Reynolds numbers. The findings indicated an increase in the Nusselt number with the incorporation of the hybrid nanofluid, achieving a maximum enhancement of 11.19% in comparison to EG at a Reynolds number of 240 and a concentration of 0.86 wt.%. Noticeably, the pressure drop remained negligible at lower Reynolds numbers, exhibiting marginal variations up to 0.3% at higher Reynolds numbers. At a concentration of 0.86 wt.% and a Reynolds number of 480, the introduction of MWCNTs, hybrid, and SiO₂ nano-additives resulted in respective increases in the heat transfer coefficient by 21.02%, 10.76%, and 2.16% and corresponding alterations in pressure drop of 0.11%, 0.04%, and 0.02%.

Interpore hydrates are the main occurrence forms of marine gas hydrates. Pore characteristics are a vital factor affecting the thermodynamic properties of hydrates and their distribution in sediments. Currently, the characterization of the pore system for hydrate-bearing reservoirs are little reported. Therefore this paper focus on the Krishna-Godavari Basin, via varies methods to characterize the hydrate-bearing sediments in the region. The results showed that X-ray Diffraction(XRD) combined with Scanning Electron Microscope (SEM)and Cast Thin Section (CTS) can better characterize the mineral composition in the reservoir, High Pressure Mercury Injection (HPMI) focused on the contribution of pore size to permeability, Constant Rate Mercury Injection(CRMI) had the advantage of distinguishing between pore space and pore throat, and Nuclear Magnetic Resonance Cryoporometry (NMRC) technique can not only obtain the pore size distribution of nanopores with a characterization range greater than Nitrogen Gas Adsorption (N2GA), but also quantitatively describe the trend of fluids in the pore system with temperature. As for pore system, Samples 58 and 68 all developed nanopores, the mineral distribution was relatively scattered, and they were rich in paleontological shells such as foraminifera, among which Sample 68 had more pyrite content, and abundant pyrite framboid was observed, which made the intergranular pore develop and provide more nanopores. Sample 58 has a high concentration of pore and throat, high pore connectivity, low pore curvature, and pores with a diameter of 10μm contributing to the main permeability, with an average pore radius of 2.495μm, whereas Sample 68 has poor pore connectivity, high curvature, and pores with a diameter of 1μm contributing to the main permeability, with an average pore diameter of 60 nm, which explains the obvious difference in permeability between the two samples.

Harmful algal blooms are a serious problem for humanity, so the development of tools and methods for their timely detection is an urgent task. The use of optical methods often allows scientists to solve problems of remote and automated monitoring. Temperature spectra of fluorescence can be used as distinctive features of algae, and the fluorescence parameters obtained from them can be used for identification. The paper presents a description of the fluorescence parameters of Alexandrium catenella, and shows their stability during cumulative cultivation. In addition, the cytometric properties of the culture and its pigment composition were studied. In addition, the article compares all the studied properties of this microalga with the alga Prorocentrum cordatum. We demonstrated clear differences in their fluorescence parameters, which makes it possible to distinguish these microalgae by optical methods, for example, during their dominant blooms.

Land transportation is contributing to global greenhouse gas (GHG) emissions significantly. Switching from gasoline-powered vehicles to electric vehicles (EVs) is the most practical way to decarbonize land transportation. Some regions of the world have seen significant advancements in the adoption of electric vehicles, largely due to government policies through subsidies and other rules and laws that globally made the cost of acquisition and ownership more advantageous for EV owners compared to their internal combustion engine (ICE) counterparts. The success of EV adoption in Norway, China, the United States of America (USA), the European Union (EU), and India has been linked to the favorable government policies. At present, China is the largest EV market in the world, enjoying a better advantage than any other market. It also has the highest manufacturing capacity and the largest number of EVs in operation. Norway has the highest EV penetration rate, with over 90% of newly registered cars, and one of the lowest costs of ownership globally. In this review, we present the current state of EV technology and performance, together with consumer perspectives and barriers, EV regulations in the regions with the highest penetration rates, and the decarbonization of land transportation. China is competing with the USA for leadership in manufacturing and technology, especially in the areas of artificial intelligence (AI) and batteries. In order to achieve the goal of decarbonizing road transportation, we proposed that a number of factors, including government energy policies and regulatory standard development, necessary infrastructure investments and developments, AI incorporation in EVs, innovation in EV and battery technologies, and consumer perspectives, play a crucial role.

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

Background: Previous studies have found variable impact of the coronavirus disease 2019 (COVID-19) pandem-ic on the consumption of antimicrobial drugs in human medicine, with trends in several European countries differing between community and inpatient prescribing. Aim: This study analysed changes in the volumes and use density of antibacterial and antifungal drugs dis-pensed in acute care hospitals in Germany between 2019 and 2022. Methods: Surveillance data for the four years available from 279 hospitals, among them 272 for antifungals, were expressed as the total volumes of daily doses or as use density (daily doses per 100 patient/occupied bed days) per year and analysed descriptively, using recommended hospital-adapted daily dose definitions (RDD) and (as sensitivity analysis) WHO/ATC-defined daily dose definitions (DDD). Hospitals were stratified according to size (number of beds) and university affiliation, and location (East, West, South). Results: There were significant decreases both in the total number of patient days and antibacterial drug vol-umes in 2020 through 2022 compared with 2019. The relative changes between 2019 and 2020, 2021 and 2022 were -12.8%, -13.5%, and -13.3% for patient days, and -9.7%, -11.0%, and -10.1% for antibacterial RDD, respec-tively. Broad-spectrum betalactams, notably piperacillin-tazobactam and carbapenems, increased in volume unlike most other drug classes. The resulting antibacterial drug use density was slightly but significantly increas-ing with pooled means (and medians) of 43.3 (40.0) RDD/100 in 2019 compared to 44.8 (41.7), 44.5 (40.80), and 44.9 (41.7) RDD/100 in the years 2020 through 2022, respectively. Antifungal drug volumes and use density increased after 2019 and peaked 2021 (differences between 2019 and 2021 for total volumes +6.4%, and for pooled mean use density values +22.9%, respectively). These trends were similar in the different hospital strata and comparable when DDD instead of RDD were used. Conclusions: Similar to what has been observed in a majority of European countries the total volume of antibac-terial drug use in German acute care hospitals decreased with the pandemic without a rebound phenomenon in 2022. In association with restricted hospital capacities and presumably more immunocompromised general medi-cine patients, however, inpatient prescribing of (primarily broad-spectrum) antibacterials and of antifungal drugs increased.

Different materials prepared by appropriate synthesis methods and applying different post syn-thesis processes could be used as hole transport layer in perovskite solar cells. In the present work annealing was employed to enhance physical properties of copper oxide (CuO) thin films fabricated via spin coating technique and the effects of annealing on their optical, morphological, electrical and structural properties were investigated. The XRD findings revealed the polycrystalline structure with large crystallite size. Optical spectra showed larger transmission beyond the visible region, reduced absorption, and a decrease in bandgap energy from 1.93 eV to 1.81 eV. The Ag phonon modes at 299.22 and 304 cm-1 shown by the Raman shift confirmed the development of the CuO pure phase. FTIR spectra showed the Cu-O stretching band at 759, 764 and 446 cm−1. SEM revealed the agglomeration of nano crystallites with large grains on the surface. The carrier type conductivity of annealed CuO thin films was determined via two-point hot probe technique. Low resistivity values were determined via four-point probe method. These findings indicate that CuO thin films may be successfully used as a companion with an n-type layer in p-n junction solar cells, and a hole transport layer in perovskite solar cells.

Induction motors are the most numerous and significant dynamic loads in power systems. In transient voltage stability analysis, dynamic equivalent models are commonly used to simplify the representation of a group of induction motors. This paper presents an method for the grouping and aggregation of induction motors at a common bus. Firstly, grouping rules were provided for clustering induction motors into several subgroups based on the mechanical principles of rotor force and motion, and Aggregation Rules were provided for aggregating a motor subgroup into a single-unit model based on the relationship between voltage drop and power transmission in distribution networks. Secondly, guided by the grouping rules, high-speed remaining electromagnetic torque and low-speed remaining electromagnetic torque were defined as new clustering indicators, and an adaptive K-means clustering method using silhouette coefficient verification was provided to obtain the optimal motor subgroups. Thirdly, guided by the Aggregation Rules, a dynamic equivalent method was further provided to obtain the equivalent single-unit model from a motor subgroup. Lastly, a transient voltage stability simulation in a typical distribution network was presented to illustrate that the proposed clustering and equivalent methods are more reasonable, accurate, and effective than traditional methods, as the obtained model has better dynamic characteristics and can more accurately reproduce the process of voltage collapse.

Nutrient profiling (NP) models that assess nutrient density of foods can help remedy micronutrient deficiencies. We used NP methods to identify the most nutrient-rich foods in the 2019 FAO/INFOODS Western Africa Food Composition Table (WAFCT). The WAFCT had complete data for 909 foods. Three versions of the well-established Nutrient Rich Food (NRF) model were used: 1) the original NRF9.3; 2) a new NRF6.3 based on 6 priority micronutrients (iron, zinc, calcium, folate, vitamin A, vitamin B12); and 3) NRF 15.3, based on 15 nutrients to encourage (NRF6.3 nutrients + vitamin D, vitamin E, vitamin C, vitamin B1, vitamin B2, vitamin B3, vitamin B6, copper, and magnesium). Data analyses used one-way ANOVAs and independent t-tests, with significance at α=0.05. Animal-source foods were rated higher by NRF6.3 priority micronutrient and NRF15.3 NP models than by the NRF9.3 model. African indigenous vegetables had higher protein content and higher nutrient density compared to non-indigenous vegetables. African indigenous grains had higher nutrient density compared to non-indigenous grains. Though animal-source foods received some of the highest scores, NP models adapted to the West African context showed that African indigenous vegetables and grains were also nutrient rich. Indigenous foods could be important sources of priority micronutrients for the region.

Competent authorities of many countries, including Belgium, impose control measures (preventing wild bird access to feeders and water facilities, indoor confinement of captive birds, or fencing off outdoor ranges with nets) to professional and non-professional keepers of birds to prevent the spread of avian influenza (AI). Flemish laying hen farmers (FAR, n = 33) and private keepers of captive birds (PRI, n = 263) were surveyed about their opinion on, and compliance with, AI-measures legally imposed during the most recent high-risk period before this survey in 2021. Participants answered questions on a 5-point Likert scale (1 = the worst, 3 = neutral, and 5 = the best). FAR indicated better compliance with the AI-measures compared to PRI, except for confinement with nets. PRI and FAR perceived the level of compliance with AI-measures by other private bird keepers to be lower compared to themselves. FAR regarded the AI-measures as more effective than PRI. To prevent the spread of AI more effectively, national authorities could focus on information campaigns explaining to private bird keepers, in particular, the need for the various control measures that they impose, implement alternative control measures that have broader support or implement stricter enforcement of the control measures.