Accent is on determination of appropriate friction factor of the pipes and on selection of the representative equation for water or natural gas flow which is valuable for existing conditions in the looped network of pipelines. Note that in a municipal gas pipeline, natural gas can be treated as incompressible fluid (liquid) i.e. as water or oil. Even under this circumstance, calculation of water pipelines cannot be literary copied and applied for calculation of gas pipelines. Inappropriate friction factor, equally as e.g. inappropriate usage of water flow equations for calculation of gas networks can lead to inaccurate final results. Few iterative methods for determining the optimal hydraulic solution of water- and gas- looped pipeline networks, such as, Hardy Cross, modified Hardy Cross, node-loop method, node and M.M. Andrijashev method, will be shown. Speed of convergence will be compared and discussed using a simple network with three loops.

Amyloids result from the aggregation of several unrelated proteins, due to either specific mutations or promoting intra- or extra-cellular conditions. Structurally, they are rich in intermolecular β-sheets and are the causative agents of several diseases, both neurodegenerative and systemic. It is believed that the most toxic species are small aggregates, referred to as oligomers, rather than the final fibrillar assemblies. Their mechanisms of toxicity are mostly mediated by aberrant interactions with the cell membranes, with resulting derangement of membrane-related functions. Much effort is being put in the search for natural antiamyloid agents, and/or in the development of synthetic molecules. Actually, it is well documented that the prevention of amyloid aggregation results in several cytoprotective effects. Here, we portray the state of the art in the field. Several natural compounds are effective antiamyloid agents, notably tetracyclines and polyphenols. They are generally non-specific, as documented by their partially overlapping mechanisms, and the capability to interfere with the aggregation of several unrelated proteins. Among rationally designed molecules, we mention the prominent examples of β-breakers peptides, whole antibodies and fragments thereof, and the special case of drugs contrasting transthyretin aggregation. In this framework, we stress the pivotal role of the computational approaches. When combined with biophysical methods, in several cases they have helped clarify in detail the protein/drug modes of interaction, which make it plausible that more effective drugs will be developed in the future.

This paper proposes a new approach to investigation into the aesthetics. Specifically, it argues that it is possible to explain the aesthetic and its underlying dynamic relations with axiomatic structure (the octahedral axiom derived category) based on contemporary mathematics – namely, category theory – and through this argument suggests the possibility for discussion about the mathematical structure of the aesthetic. If there was a way to describe the structure of aesthetics with the language of mathematical structures and mathematical axioms – a language completely devoid of arbitrariness – then we would make possible a synthetical argument about the essential human activity of “the aesthetics”, and we would also gain a new method and viewpoint on the philosophy and meaning of the act of creating a work of art and artistic activities. This paper presents one hypothesis as a first step in constructing the science of dynamic generative aesthetics based on axiomatic functionalism, which is in turn based on a new interdisciplinary investigation into the functional structure of aesthetics.

Dengue virus (DENV) and chikungunya virus (CHIKV) are reemergent arboviruses that are transmitted by mosquitoes of the Aedes genus. During the last several decades, these viruses have been responsible for millions of cases of infection and thousands of deaths worldwide. Therefore, several investigations were conducted over the past few years to find antiviral compounds for the treatment of DENV and CHIKV infections. One attractive strategy is the screening of compounds that target enzymes involved in the replication of both DENV and CHIKV. In this review, we describe advances in the evaluation of natural products targeting the enzymes involved in the replication of these viruses.

This paper aims to build up a preference function to evaluate the public benefits of the type of agricultural farming, biodiversity, water provisions, land use type, ecotourism modes, and a monetary attribute (environmental trust fund and willingness to contribute) associated with an ecosystem service and land use program in a forest park. This study used the choice experiments to build a random utility model, analyze the average preference for the above land use attributes based on the conditional logit and used a latent class model to test the resident’s heterogeneous preferences for land use planning in the forest park. We also estimated the welfare derived from various land use programs. The empirical result had shown that: (1) increasing organic farming area, maintaining the status quo of species biodiversity, increasing the surface water provision, increasing the area of custom flora, increasing the wetland area, and setting up an integrated framework for ecotourism increase the public’s preference for the land use program; (2) we found that farmer and non-farmer haven’t the same land use preferences; (3) the ecotourism development program incorporating biodiversity, organic farming, ethnobotany, and wetland area with integrated ecotourism are more preferred than other land use program scenarios.

Current language models have achieved remarkable success in NLP tasks. Nonetheless, individual decoding methods face difficulties in realizing the immense potential of these models. The challenge is primarily due to the lack of a decoding framework that can integrate language models and decoding methods. We introduce the DecoStrat which bridges the gap between language modeling and the decoding process in D2T generation. By leveraging language models, DecoStrat facilitates the exploration of alternative decoding methods tailored to specific tasks. We fine-tune the model on the MultiWOZ dataset to meet task-specific requirements and employ it to generate output(s) through multiple interactive modules of the framework. The Director module orchestrates the decoding processes, engaging the Generator to produce output(s) text based on the selected decoding method and input data. The Manager module enforces a selection strategy, integrating Ranker and Selector to identify the optimal result. Evaluations on the stated dataset show that DecoStrat effectively produces diverse and accurate output, with MBR variants consistently outperforming other methods. DecoStrat with the T5-small model surpasses some baseline. Generally, the findings highlight DecoStrat's potential for optimizing decoding methods in diverse real-world applications.

There is an increasing interest in revisiting plants for drug discovery proving scientifically their role as remedies. Pistacia lentiscus (PL) is a wild-growing shrub rich in terpenoids, which are pharmacological appealing. The more recurrent components in the oil are represented by α-pinene, terpinene, caryophyllene, limonene, and myrcene. High concentration of polyphenols enriches the extracts. PL-extracts showed in vitro and in animal model strong anti-inflammatory and anti-oxidative activities. The anti-inflammatory activity mainly occurs due to inhibition of NF-kB pathway or directly toward the proinflammatory cytokines, or arachidonic acid cascade against COX-2 and LOX. The antimicrobial activity of PL essential oil and extracts includes among others Staphylococcus aureus, Escherichia coli, periodontal bacteria and Candida sp.. In conclusion, the biological properties, and particularly the anti-inflammatory and anti-microbial capacity, propose PL as a new safe pharmaceutical agent.

The difficulties faced by the society in its goal of reducing mortality and improving the health status during the period of the COVID-19 pandemic showed that it is necessary to develop new approaches in the therapy of infectious diseases, leading to higher treatment efficiency and few side effects. The subject of the present study is the formation and characterization of the proper-ties of stable liposomes loaded with extracts from Bulgarian medicinal plants and monitoring their antiviral action against the human strain of coronavirus OC43 (HCoV-OC43) in vitro. The hydrodynamic diameter and -potential of the liposomes containing each type of payload were determined with DLS and electrokinetics. The encapsulated amount of extracts was evaluated against quercetin and gallic acid by using colourimetric methods. The BALB 3T3 Neutral Red Uptake (NRU) phototoxicity/cytotoxicity assay was used to estimate the safety of the compounds. For assessment of the antiviral activity against HCoV-OC43 of liposomes (Lip) containing medicinal plant extracts, the cytopathic effect inhibition test was used. Measurements of the virucidal activity and the effect on the virus adsorption stage was carried out using the endpoint dilution method, and ∆lgs were calculated by comparison with untreated controls. The estimated photo irritation factors (PIF) for the Lip containing extracts were < 2 which assigns them to the category of non-phototoxic substances. When the extracts were introduced into the liposomes as their carriers, the antiviral activity of the vesicles against the replication of HCoV-OC43 in vitro in-creased by several times compared to their individual activity described in our previous study. The determination of the effect of structures loaded with extracts on the extracellular virions and the stage of their adsorption to sensitive HCT-8 cells proved that the liposomes do not affect directly the viral surface or cell membrane, but only perform a function of carriers of the active substances and the observed result is due solely to the intracellular action of the extracts.

India, the world’s most populous country, is the world's third-largest emitter of greenhouse gases (GHGs). Despite employing several energy sources, it still relies heavily on coal, its primary energy source. Given India’s swiftly rising energy demand, this challenges meeting emission reduction targets. India has significantly increased investments in renewables like solar and hydrogen in recent years. While commendable, these initiatives alone cannot meet the country's expanding energy demands. In the short term, India must rely on both domestic and imported fossil fuels, with natural gas being the most environmentally friendly option. In this context, this paper attempts to forecast energy consumption, natural gas production, and consumption in India till 2050 using both univariate and multivariate forecasting methods. For multivariate forecasting, we have assumed two alternative possibilities for GDP growth: the business-as-usual and the high-growth scenarios. Each of our forecasts indicates a notable shortfall in the projected production of natural gas compared to the expected demand, implying our results are robust. Our model predicts that nearly 30-50 percent of India’s natural gas consumption will be met by imports, mainly in the form of LNG. Based on these findings, this paper recommends that Indian government policies emphasize increasing domestic natural gas production, importing LNG, and expanding renewable energy resources.

In this study, the asymmetric effect of oil and natural gas price shocks on the trade balance of 11 CESEE countries was estimated. These countries are net importers of oil and natural gas, and price shocks are often the cause of imbalances in trade. Quarterly data for the period 1994Q1 to 2023Q4 and nonlinear ARDL model were used. In the long run, a significant asymmetric effect due to the oil price shock on the trade balance of Bulgaria, Czechia, Latvia and Slovenia was found, as well as a significant asymmetric effect due to the natural gas price shock on the trade balance of Croatia. Also in the long run, a significant asymmetric effect due to wholesale prices on the trade balance of Romania, Bulgaria and Croatia was found as well as a significant asymmetric effect due to industrial production on the trade balance of Croatia, Czechia and Latvia was found, in addition to a significant asymmetric effect due to the exchange rate on the trade balance of Czechia, Poland and Romania.

This study presents an innovative method for producing thermosensitive bio-ink from chitosan hydrogels saturated with carbon dioxide and agarose. It focuses on a detailed characterization of their physicochemical properties and potential applications in biomedicine and tissue engineering. The ORO test approved rapid regeneration of the three-dimensional structure of chitosan-agarose composites in the unidirectional bench press simulation test. The diffusion of dyes through chitosan-agarose hydrogel membranes strongly depended on the share of both polymers in the composite and the molecular weight of the dyes. Glucose, as a nutrient marker, also diffused through all membranes regardless of composition. Biocompatibility assessment using MTT tests on 46BR.1N fibroblasts and HaCaT keratinocytes confirmed the safety of the bioink. The regenerative potential of the bioink was confirmed by efficient cell migration, especially HaCaT. Long-term viability studies showed that chitosan-agarose scaffolds, unlike the agarose ones, support cell proliferation and survival, especially 14 days after bioink extrusion. Experiments in a skin wound model in mice confirmed the biocompatibility of tested dressing and the beneficial action of chitosan on healing. Studies on vessel formation in chicken embryos highlight the potential of the chitosan-agarose composition for enhancing proangiogenic effects. This composition meets all entry criteria and possesses excellent biological properties.

Based upon the latest molecular phylogenies of Gonyosoma sensu lato, which recovered five clades with robust support, we utilize morphological characters to demonstrate the distinctiveness of each clade, resulting in the resurrection of three genera (Gonyophis Boulenger, 1891 [1], Rhynchophis Mocquard, 1897 [2], and Rhadinophis Vogt, 1922 [3]) and proposal of a new genus and a new tribe. A synopsis of the group, with descriptions and diagnoses, is provided for the five genera and eight species in addition to distribution maps and illustrations of the head of each taxon. An artificial key to the species and genera in the new tribe is presented in addition to estimated origin times for each clade.

Renal cancer is a common and serious malignant tumor of the urinary system. While surgery effectively treats early-stage renal cancer, advanced cases pose a significant challenge due to poor treatment outcomes and chemotherapy resistance. Therefore, there is an urgent need to develop alternative therapeutic strategies. Ferroptosis is a newly defined form of programmed cell death characterized by the accumulation of iron-dependent lipid peroxides, which plays a critical role in tumor progression and drug resistance. Recent studies have shown that ferroptosis is involved in the occurrence and development of renal cancer, ferroptosis related genes can induce cell apoptosis, and can be used as potential biomarkers for early diagnosis of renal cancer and participate in drug resistance of renal cancer chemotherapy. With the continuous improvement of the mechanism of ferroptosis, drugs targeting ferroptosis for the treatment of renal cancer are emerging in an endless stream, Based on the theoretical basis of the occurrence of ferroptosis, this paper reviewed drug-induced ferroptosis in renal cancer cells from the aspects of herbal medicine, natural compounds, drug resistance mechanisms, and nanomaterials, hoping to provide a new strategy for the treatment of renal cancer with ferroptosis related drugs.

This work reports a characterization of crystallographic phases and chemical composition of hercynite-spinel (FeAl2O4) natural long crystals and their powders using X-ray Diffraction, Scanning Electron Microscopy, Inductively Coupled Plasma mass spectrometry, and mineralographic/petrographic analysis. The samples studied show a high content of hercynite with Neumann bands/Widmanstätten patterns, coexisting with other crystallographic phases such as corundum, spinel (MgAl2O4), esseneite, kamacite, hedenbergite, pseudobrookite, and ulvospinel. The diffractograms of two of the samples examined exhibit an extraordinary sharpness of the diffraction peaks that determines a high degree of crystallinity, which is hard to obtain in hercynite synthesized by artificial methods. In addition, the hercynite natural samples are less porous than the artificially synthesized hercynite. The x-ray diffraction pattern of one of the pulverized crystalline samples allowed us to estimate the percentage of the main phases present. The crystallographic existent phases with the highest participation in one of the spinel samples were hercynite (43.4%), corundum (18.7%), spinel (18.4%), esseneite (17.2%), and kamacite with a 2.3 %. These results contribute to the structural characterization of this unique material widely used in many technological applications.

Source water quality is a key determinant of drinking water quality. The recast European Union 2020/2184 drinking water directive (DWD) introduced the obligation for comprehensive risk assessment in drinking water supplies, including the water source and incorporated new elements of natural origin in the list of parameters to be monitored. The current study is the first comprehensive assessment of 15 natural elements (B, Ba, Be, Ca, Co, K, Li, Mg, Mo, Na, Se, Sr, Ti, U and V) in 1155 (82%) Hungarian drinking water sources, including surface water, bank filtered and groundwater sources. Parameters posing a risk to health (Se, V and U) were typically below the lower limit of quantification (LOQ), but higher concentrations (max. 7.0, 17 and 41 µg/L, respectively) may occur in confined locations, the latter exceeding the DWD parametric value in one water supply. Li in a small geographical area, Mg and Ca in the majority of the water supplies reached the concentration range assumed to be protective to health. Water sources were grouped in 6 clusters based on their element distribution, some of them also showing clear geographical patterns. Water types were not differentiated, with the exception of karstic waters (dominated by Ca and Mg). None of the investigated parameters are expected to be a source of public health concern.

Natural language processing model (NLP) are used in chatbots to understand user input, interpret its meaning, and generate conversational responses to provide immediate and consistent assistance. This reduces problem-solving time and staff workload and increases user satisfaction. There are both rule-based chatbots, which use decision trees and are programmed to answer specific questions, and self-learning chatbots, which can handle more complex conversations through continuous learning about data and user interactions. However, only a few chatbots have been developed specifically for the Italian language. This work proposes an NLP model to develop a powerful and efficient Italian QA (Question Answering) chatbot that is easy to use for Italian Public Administration (PA). The proposed model is based on BERT (Bidirectional Encoder Representations from Transformer) architecture, where an Encoder/Decoder module and a Highway Network module have been added to perform more efficient filtering of input text. The Italian version of the Stanford Question Answering Dataset (SQuAD-IT) is used to test the proposed model. The proposed model is one of the first models developed for Italian language-specific chatbots.

Phased injection of natural gas into internal combustion marine engines is a promising solution for optimizing performance and reducing harmful emissions, particularly unburned methane, a potent greenhouse gas. This innovative practice distinguishes itself from continuous injection because it allows for more precise control of the combustion process with only a slight increase in system complexity. By synchronizing the injection of natural gas with the intake and exhaust valve opening and closing times while also considering the gas path in the manifolds, methane release into the atmosphere is significantly reduced, making a substantial contribution to efforts to address climate change. Moreover, phased injection improves the efficiency of marine engines, resulting in reduced overall fuel consumption, lower fuel costs, and increased ship autonomy. This technology has been tested on a single-cylinder, large-bore, four-stroke research engine designed for marine applications, operating in dual-fuel mode with diesel and natural gas. Performance was compared with that of the conventional continuous feeding method. Evaluation of the effect on equivalent CO2 emissions indicates a potential reduction of up to approximately 20%. This reduction effectively brings greenhouse gas emissions below those of the diesel baseline case, especially when injection control is combined with supercharging control to optimize the air-fuel ratio.

Objective: Daratumumab (Dara) is the first-in-class human-specific anti-CD38 mAb approved for treating multiple myeloma (MM). However, DARA-induced depletion of CD38high natural killer (NK) cells results in crippled antibody-dependent cellular cytotoxicity (ADCC), which limits its clinical detection and prediction for Dara efficacy. Therefore, we aimed to explore new NK subsets that could predict Dara efficacy and the underlying mechanism in Dara development. Methods: Multicolour spectral flow cytometry monitored changes in the immune cells of 13 paired RRMM patients. We used machine learning-driven clustering, FlowSOM (Flow Self-Organizing Maps), and dimensional reduction with tSNE (t-distributed Stochastic Neighbour Embedding) to identify unique cell populations pre- and posttreatment. Then, in vitro, fratricide and proliferation assays were performed to explore the function of new NK subsets against MM under Dara treatment. Results: The NK cells were divided into 25 subsets, among which we found that the percentages of KIR-NKP46+ NK cells decreased in paired RRMM patients compared to healthy controls but increased significantly post-Dara treatment. The fold change in KIR-NKP46+ after one dose of Dara treatment can predict whether the best response could be achieved within one month (ROC=0.86, p=0.011). Further in vitro experiments showed that KIR-NKP46+ NK cells are superior to KIR+ NK cells, cooperatively acting with daratumumab to sustainably eradicate MM cells. Meanwhile, apoptosis was significantly decreased, and the proliferation ability was relatively increased post-Dara treatment. Conclusion: In conclusion, the fold change in KIR-NKP46+ NK cell subsets after one dose of Dara treatment can predict the outcome of the curative effect, indicating a putative role of KIR-NKP46+ subsets against MM cells. The mechanism attributed to a relative expansion of the subset due to decreased apoptosis and increased proliferation ability.

The article offers a comprehensive overview of recent breakthroughs in eco-friendly polymers and polymer composites, underscoring their pivotal role in addressing sustainability challenges across diverse industrial sectors. Despite encountering obstacles related to performance and processability, biopolymers sourced from renewable materials emerge as promising alternatives for the plastics that are currently used by human beings. Natural fillers are highlighted as a strategic avenue for crafting sustainable composites, with residual natural fillers being particularly explored. Heightened environmental concerns propel discussions on the criticality of integrating biodegradable materials with natural fillers, underlining the urgency for clear frameworks and financial incentives to support adoption of these materials. Additionally, the article examines the potential of biodegradable polymers and polymer composites, with a specific emphasis on the utilization of polyhydroxyalkanoate (PHA) in composite materials and its market prospects. Moreover, it emphasizes the indispensable need for ongoing research and development endeavors to address environmental challenges within the polymer sector, reflecting a mounting interest in sustainable materials across industries.

The COLOSS research association has been assessing honey bee colony losses, associated risk factors and management, focusing on Western countries but with a progressive international expansion. Here, we report the first survey on the loss rates of colonies in 2022/23 in Ethiopia using COLOSS monitoring survey tools. A face-to-face interview questionnaire survey was conducted on 64 beekeepers selected from Oromia and Tigray regions. This covered 1,713 honey bee colonies distributed in 68 apiaries. The percentages of colonies lost were significantly different between Oromia (24.1%) and Tigray (66.4%) regions. Colony losses were attributed as unsolvable queen problems (8% in Oromia; 10% in Tigray), natural disaster (32%; 82%), and empty hives or dead colonies (60%; 8%). The loss rate was significantly affected by queen replacement (p

The rapid expansion of China's A-share market, coupled with the burgeoning volume of financial research reports, presents a unique challenge to traditional stock price prediction methodologies. This study introduces FAST-SCAN, a novel framework designed to leverage natural language processing (NLP) and time series analysis for the efficient and accurate prediction of stock market trends. By integrating advanced sentiment analysis, primarily through the utilization of the RoBERTa model, with dynamic time series forecasting, FAST-SCAN aims to distill actionable insights from the vast corpus of financial research reports. This approach not only enhances the speed and efficiency of financial analysis but also addresses the time-sensitive nature of market-influencing factors, thereby providing a competitive edge in stock price prediction. The framework demonstrates a notable improvement in predictive performance, achieving a 20% annualized return and a 7.19% RankIC, marking a significant advancement over conventional statistical analysis methods. Through its innovative combination of NLP and predictive analytics, FAST-SCAN paves the way for a more informed and strategic approach to investment in the A-share market, emphasizing the importance of timely, data-driven decision-making in the financial industry.

The Ebola virus disease (EVD) is an extremely contagious and fatal illness caused by the Ebola virus. Recently, Uganda witnessed an outbreak of EVD, which generated a lot of attention on various social media platforms. To ensure effective communication and implementation of targeted health interventions, it is crucial for stakeholders to comprehend the sentiments expressed in the posts and discussions on these online platforms. In this study, we used deep learning techniques to analyze the sentiments expressed in Ebola-related tweets during the outbreak. We explored the application of three deep learning techniques to classify the sentiments in 8,395 tweets as positive, neutral, or negative. The techniques examined included a 6-layer convolutional neural network (CNN), a 6-layer long-short-term memory model (LSTM), and an 8-layer Bidirectional Encoder Representations from Transformers (BERT) model. The study found that the BERT model outperformed both the CNN and LSTM-based models across all the evaluation metrics, achieving a remarkable classification accuracy of 95\%. These findings confirm the reported effectiveness of transformer-based architectures in tasks related to natural language processing, such as sentiment analysis.

Soil moisture can be an important indicator of climate change in humid and semi-arid areas. This indicator can more efficiently propose different public policies related to climate change than just using precipitation and temperature data. Given the above, the objective of this study is to evaluate changes in soil moisture in the state of Pernambuco during the period 1961-2021, using the System of Hydrological Response Units for Pernambuco. In this study, two river basins in the state of Pernambuco that represent the different climatic conditions of the state will be chosen. The results show that in the coastal region, there is a tendency towards more saturated soils, and in the semi-arid region, there is a tendency towards drier soils. With these results, it is possible to conclude that public policy decisions for the economy, environment, and society must consider this vital water balance variable.

This review delves into using natural antimicrobials in the dairy industry and examines various sources of these compounds, including microbial, plant, and animal sources. It highlights dairy products' most commonly used natural antimicrobials, such as nisin, lysozyme, lactoferrin, chitosan, and essential oils. It discusses the mechanisms by which they inhibit microbial growth and improve the shelf life of dairy products. Moreover, the review explores encapsulation technology as a promising approach for increasing the viability of natural antimicrobials. It discusses how encapsulation technology can protect these compounds from environmental factors that can reduce their effectiveness, such as pH, temperature, and oxygen exposure. The review also highlights the different materials that can be used for encapsulation, such as alginate, chitosan, and starch, and discusses their properties and suitability for encapsulating different natural antimicrobials. Finally, the review examines the benefits and challenges of using natural antimicrobials in dairy products. While natural antimicrobials offer several advantages, including improved safety, quality, and sensory properties of dairy products, it's crucial to be aware of the challenges associated with their use, such as potential allergenicity, regulatory requirements, and consumer perception. The review concludes by emphasizing the need for further research to identify and develop effective and safe natural antimicrobials for the dairy industry to ensure the quality and safety of dairy products for consumers.

The authors present a framework for assessing seasonal events which may influence maritime operations. Most maritime-related research tends to focus on single events, such as a storm, but maritime systems operate within complex systems that have some predictable patterns. These predictable patterns due to natural events, such as weather and water levels, can influence operations, while other factors, such as cargo peaks or cultural activities, could also shape maritime systems. By integrating data from emergency management databases and weather information sources with other inputs, the authors created a matrix of regionally specific predictable events that may occur within a region by time of year. The matrix was vetted with various stakeholder groups to verify the information in the matrix. The main findings were that a seasonal event matrix is helpful as a reference for examining operational patterns in a river for various uses, such as training, operational planning, and emergency response coordination.

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

Additive manufacturing (AM) has revolutionized the field of biopolymers by providing a range of opportunities to create complex and intricate structures. Here we provide an overview of developments in biopolymer AM, first in the context of how natural systems have impacted the synthetic processes of AM, and secondly in the context of how synthetically derived structures can be used for biomedical applications. In particular, we explore the range of biopolymers developed for AM, AM techniques for biopolymers, and potential biocompatible medical applications with a focus on four categories of tissue in the human body: skin, bone, heart, and nerve. Despite the current challenges of the technology, exciting results in tissue regeneration, synthetic replacements for natural grafts, and complex dynamic organoids have already come to pass - with many more possible in the future.

Saliva, as a diagnostic medium, offers a promising alternative to blood by virtue of its non-invasive collection, which enhances patient compliance, especially in paediatric and geriatric populations. In this study, we assessed the utility of saliva as a non-invasive medium for measuring V. cholerae-specific serum antibodies in naturally infected individuals. We tested paired serum and saliva samples obtained from a total of 63 cholera patients enrolled in a cohort study. Vibriocidal antibodies assay (IgM/IgG) as markers for accurate determination was used to determine cholera specific antibody levels. Using receiver operating characteristics (ROC) curve, we found that the best cut-off that maximizes (sensitivity + specificity) is 10 titers. At this saliva titer, the sensitivity is 76.9% (95%CI: 60.9%, 87.7%) and specificity is 80.0% (95%CI: 56.6%, 92.5%). Using Spearman’s correlation coefficient, we also found evidence of a positive correlation between Vibrio Cholerae saliva and serum antibodies (rho=0.66, p&lt;0.001). In conclusion, saliva-based diagnostic cholera tests has high diagnostic accuracy, and would be advantageous, cheaper, and quicker for early diagnosis of severe cholera outcomes.

Aims. In a male Italian cohort (initially aged 40-59, n=1712) followed-up during 61 years and reaching practical extinction, the natural history of major CVD mortality categories including coronary heart disease (CHD), stroke and other Heart Diseases of Uncertain Etiology (HDUE, including congestive heart failure) were studied along with their risk factor relationships. Methods and Results. Cox models were run with 12 covariates measured at entry as possible predictors. About 93% of all CVD deaths were covered by the 3 major groups selected here (N=751): 37.4% of them were diagnosed as CHD, 30.6% as stroke and 28.5 % as HDUE. CHD declined in the last 20 years of follow-up, while a sharp increase of HDUE mortality was seen. Baseline mean levels of serum cholesterol were 209.6, 204.2 and 198.0 mg/dl respectively for CHD, stroke and HDUE deaths: the multivariable coefficients of serum cholesterol were positive and significant for CHD (p<0.0001) and stroke (p=0.0203) and not significant for HDUE (p=0.3467). In Fine-Gray models, the algebraic signs of cholesterol coefficients were opposite for CHD versus the other mortality categories (t=3.13). The predictive performances of remaining risk factors were varied whereas that of Cox models was not very good, probably due to the attrition phenomenon and possible competing risks. Conclusion. Large differences in natural history and risk factors were found comparing the 3 CVD conditions, potentially indicating different etiologies and pointing to the need of not mixing them up in a grouped CVD category.

Natural polysaccharides, which are described in this study, are some of the most extensively used biopolymers in food, pharmaceutical and medical applications, because they are renewable and have a high level of biocompatibility and biodegradability. The fundamental understanding required to properly exploit polysaccharides potential in the biocomposite, nanoconjugate, and pharmaceutical industries is depended on detailed research of these molecules. Polysaccharides are preferred over other polymers because of their biocompatibility, bioactivity, homogeneity, and bioadhesive. Natural polysaccharides have also been discovered to have excellent rheological and biomucoadhesive properties, which may be used to design and create a variety of useful and cost-effective drug delivery systems. Polysaccharide-based composites derived from natural sources have been widely exploited due to their multifunctional properties, particularly in drug delivery systems and biomedical applications. These materials have achieved global attention and are in great demand because to their biochemical properties, which mimic both human and animal cells. Although synthetic polymers account for a substantial amount of organic chemistry, natural polymers play a vital role in a range of industries, including biomedical, pharmaceutical, and construction. As a consequence, the current study will provide information on natural polymers, their biological uses, food and pharmaceutical applications.Keywords: Polymers Biopolymers, Excipient, Natural source, Food and Pharmaceutical applications.

Natural radioactivity of 238U, 232Th and 40K for liquid and solid samples collected from Sidi Salem dam (Tunisia) and Aïn Dalia dam (Algeria) were measured using TERRA detector of rays (gam-ma, beta, and alpha), Atomic adsorption and Gamma-ray spectrometry were used to analyze the levels of radionuclides and toxic heavy metals, respectively. Toxic heavy metals (Fe, Bb, Zn, Ni, Cu, Cr and Cd) and associated health risks in surface water and sediment of dams have been in-vestigated in this present study. The radioactivity mean rates in the water samples were 1.72±0.01, 0.068±0.01 and 94.6±1.04 Bql-1 for 238U, 232Th and 40K respectively (Tunisia dam) and were 1.9± 0.24, 0.09±0.01 and 131.43±1.03 Bql-1 for 238U, 232Th and 40K respectively (Algeria dam). The 238U, 232Th and 40K radioactivity mean concentration measured in the sediment samples were 2.67±0.01, 0.18±0.012 and 197.87±2.01 Bqkg-1 respectively (Tunisian dam) and were 4.34±0.05, 0.27±0.05 and 287.61±3.34 Bqkg-1 respectively (Algeria dam). The activity concentration of 40K was higher than that of 238U and 232Th for the water and sediment samples. The mean activity concen-trations follow the order 40K > 238U > 232Th. The cumulative impact can be a serious immediate radiological health burden on the ecosystem, environment and people's health in this study area and can be transposable to any other similar region. The good knowledge of monitoring quality and quantity for the transboundary water resources and the international collaborations are es-sential to safeguard human health (women’s breasts cancer, thyroid cancer, neurological im-pact…), and avoid the conflicts, especially during these climatic upheavals of drought.

The results of the investigation showed that second-order kinetics govern the adsorption process, and the corresponding rate constants were found. To evaluate the parameters related to the adsorption process, the adsorption equilibrium was examined using a variety of mathematical models, such as the Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich isotherm models. The Langmuir isotherm was found to be the best appropriate among all models for describing the adsorption of Cu2+ and Ni2+ ions using bio-nanocomposite beads. The positive values of ΔH° indicate that the adsorption is physical and endothermic, in agreement with experimental results. The negative value of ∆G° shows that the adsorption process is spontaneous. Positive ΔS° values indicate increased randomness at the solid/liquid interface, during adsorption of Cu2+ and Ni2+ cations onto the engineered bio-nanocomposite. The maximum adsorbed amounts of metal ions by the bio-nanocomposite used were 370.37 mg/g for Ni2+ and 454.54 mg/g for Cu2+ from single system. For the binary system, according to the Langmuir isotherm, the maximum adsorbed amounts of Ni2+ and Cu2+ were 357.14 mg/g and 370,37 mg/g, respectively. There is proof that Alginate-Moroccan clay bio-nanocomposites can serve as a different, less expensive source of sorbents for the removal of metal ions from single and binary systems.

Numerous innovative advancements in dressing technology for wound healing have emerged. Among the various types of wound dressings available, hydrogel dressings, structured with a three-dimensional network and composed of predominantly hydrophilic components, are widely used for wound care due to their remarkable capacity to absorb abundant wound exudate, maintain a moisture environment, provide soothing and cooling effects, and mimic the extracellular matrix. Composite hydrogel dressings, one of the evolved dressings, address the limitations of traditional hydrogel dressings by incorporating additional components, including particles, fibers, fabrics, or foams, within the hydrogels, effectively promoting wound treatment and healing. The added elements enhance the features or add specific functionalities of the dressings, such as sensitivity to external factors, adhesiveness, mechanical strength, control over the release of therapeutic agents, antioxidant and antimicrobial properties, and tissue regeneration behavior. They can be categorized as natural or synthetic based on the origin of the main components of the hydrogel network. This review focuses on recent research on developing natural polysaccharide-based composite hydrogel wound dressings. Their preparation and composition, the reinforcement materials integrated into hydrogels, and therapeutic agents are also explored. Furthermore, their features and the specific types of wounds where applied are discussed as well.

This study applies several natural language processing techniques for characterizing social groups by analyzing published text in social media. The resulting computed values are proposed as features for modeling social groups and measure distances or similarities among them, along further data that could help understanding group behavior according to language usage. In this study, we have analyzed the messages published on Twitter regarding patriotism by the main political parties in Spain. The results show that lexical resources and topic modelling algorithms are useful to model different groups and serve as comparison tools to better understand the topics these groups are talking about.

Three new cembranoids (1–3) and a new casbanoid (4), along with three known analogues (5–7), have been isolated from the soft coral Sinularia nanolobata collected off Ximao Island. The structures including the absolute configurations of new compounds were established by extensive spectro-scopic data analysis, time-dependent density functional theory/electronic circular dichroism (TDDFT-ECD) calculations and the comparison with spectroscopic data of known compounds. In in vitro bioassay, compounds 1 and 5 exhibited moderate cytotoxic activities against human erythroleukemia (HEL) cells line with IC50 values of 37.1 and 42.4 uM, respectively.

In this research, the antioxidant and antibacterial activities of active films based on potato starch containing Viola odorata extract (VOE) were investigated both in vitro and in chicken fillets. The VOE was added to the starch film formulation at 0, 1, 2, and 3% (w/v). The results showed that by increasing the extract level, the total phenol content and antioxidant and antibacterial activity of the films against Escherichia coli, Staphylococcus aureus, and Salmonella typhimurium improved remarkability. The results of meat tests indicated significant antioxidant and antimicrobial activity of active films containing different levels of VOE in chicken fillets, and a direct relationship was observed between the concentration of the extract and the functional activity of the films, so with the increase in the concentration of the extract in the films, the rate of lipid oxidation and growth of microorganisms in chicken fillets decreased significantly during the storage period, and less volatile nitrogen bases, metmyoglobin, and oxidation products were produced in the fillets. In general, the results of this research demonstrated that active film based on potato starch containing VOE (especially 2 and 3% levels) has the ability to extend the oxidative and microbiological shelf life of chicken fillets during cold storage for at least eight days.

Natural fibers have been widely used as a reinforcing material for the construction of drones. The main goal of this review is to identify a biodegradable natural fiber material that can be built for Unmanned Aerial Vehicles (UAVs). The review shows that natural fibers such as kenaf and PALF can be used as an alternative composite material, particularly for multifunctional applications where their smaller weight and less expensive characteristics make them incredibly realistic. This review also discusses the mechanical properties, advantages and disadvantages, and fabrication of the composites.

During the production of furniture, large amounts of waste of these materials are generated, which are most often stored in warehouses without a specific purpose for their subsequent use. In highly developed countries, as many as 25 million tons of textile waste are produced annually, of which approximately 40% is non-clothing waste, such as carpets, furniture and car upholstery. The aim of the research was to produce and evaluate the dry-formed high-density fiberboards (HDF) with various shares of recycled particles of natural leather used in upholstery furniture production at different contents (1, 5 and 10% by weight). Mechanical properties (modulus of rupture, modulus of elasticity and screw withdrawal resistance) and physical properties (density profile, thickness swelling after water immersion, water absorption, surface absorption) were tested. The density profile and contact angle of natural leather have been also characterized. The results show that increasing the content of leather particles in HDF mostly has a positive effect on mechanical properties, especially screw withdrawal resistance and water absorption. It can be concluded, that, depending on the further use of HDF, it is possible to use recovered upholstery leather particles as a reasonable addition to wood fibers in HDF technology.

The close proximity of different buildings heights can cause disturbances in the working of the smoke and ventilation ducts of lower buildings, threatening the health and even the lives of residents. To define the influence of high-rise building on the work of the ducts of the neighbouring double-storied building, experimental investigations in the wind tunnel were conducted. On this basis, empirical equations and graphs were developed leading to determining the aerodynamic coefficients considering different wind directions and the height of ducts. The direction of the wind reveals a greater influence than the height of the ducts. Properly using deflectors or increasing the height of the duct ensures maintaining static rarefaction in the area of smoke and ventilation ducts. The creation of rarefaction ensures the reliability of the natural ventilation system and the safety of the health of residents.

Some of Iran's gas resources are known as sour gas because one of the major by-products of this gas is water. In fact, natural gas is combined with water vapor in underground reservoirs. In some areas, the amount of water vapor in natural gas is so high that it can be used as a source of drinking water. However, it should be noted that water vapor in natural gas may exacerbate corrosion in pipes and industrial equipment, and the combustion of more natural gas produces high temperatures that can lead to the production of nitrogen oxides (NOx), which They are the cause of air pollution. This is while the processed gas has a standard percentage composition in which the amount of water has the lowest position. The removal of moisture from natural gas is due to the need to prevent the reduction of the calorific value of the gas and also to purify the gas in order to achieve the necessary standards for delivering gas to petrochemicals, industries and domestic uses. The main goal of this research is to investigate the influencing parameters on zeolite TiO2 nanocomposite membranes in order to absorb moisture from gas. For this reason, with the construction of a TiZ-V membrane as a standard membrane, the result of the initial evaluation of a suitable membrane for gas dehumidification was made, and this membrane was placed as a standard for measuring the effect of the manufacturing parameters in a way that in each stage of membrane construction It was found that it was different from standard TiZ-V membrane only in terms of one parameter. This type of investigation made it possible to determine the effect of various effective parameters in membrane construction on efficiency. The findings showed that increasing the concentration of SiO2 has the greatest effect on increasing the water flux of the membrane. According to the other findings of this study, the effect of increasing the reaction time of the vapor phase carrier has been to reduce the process of paternity selectivity loss at higher pressures. Although due to the safety limitation of the equipment to measure the efficiency of the membrane at pressures higher than 7 bar, this measurement was not carried out, but charts were presented regarding the state of the water in the water, which were a measure of the superiority of the water in the water in comparison to the gas in the water, which is the higher water in the water It is an indicator of the appropriateness of the membrane's efficiency at its corresponding pressure, so that the examination of the difference between these two graphs shows the possibility of using the membrane at higher pressures

Natural fibres are the preferred options for garment, technical and medical textiles, nonwovens and composites. Their sustainability is a considerable advantage. Though, the nature of silk production and processing involves a large amount of waste. The present review explores the current issues of recycling silk waste into nonwovens for medical and air filtration purposes. The article proposes to obtain nonwovens from short fibres using electrospinning of fibroin solutions in volatile solvents. Longer fibres are proposed to be processed into needle punched nonwoven materials with a selection of an effective antistatic treatment.

In recent years, the FDA has approved numerous antitumor drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborated the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarized chemical drugs such as lorlatinib, osimertinib, and other natural products that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

Sediment thickness increases can cause floodplains and the water level increases. This has the potential to generate a flood. Using electromagnetic waves, Time Domain Electromagnetic (TDEM) detected resistivity or conductivity contrast of lithology in the subsurface. It is measured in the time domain. TDEM method has been developing for decades. Here we tried to develop a 1-D forward modelling program for central loop configuration in the water environment using the Adaptive Born Forward Mapping (ABFM) method. We simulated this program in several water environment conditions (such as freshwater, brackish water and saline water) to know its response. Preventing natural hazards, especially flood hazards which are caused by the floodplain increases is our motivation in this research. Our simulation shows that Central-Loop Configuration Time-Domain Electromagnetic Method is able for imaging the sediment thickness clearly. The response of this method is extremely sensitive in saline water to depth changing than in other water environments.

Natural disasters are showing an increase in the magnitude, frequency, and geographic distribution. Studies have shown that individuals’ self-sufficiency, which largely depends on household preparedness, is very important for hazard mitigation in at least the first 72 hours following a disaster. However, for factors that influence a household’s disaster preparedness, though there are many studies trying to identify from different aspects, we still lack an integrative analysis on how these factors contribute to a household’s preparation. This paper aims to build a classification model to predict whether a household has prepared for a potential disaster based on their personal characteristics and the environment they located. We collect data from the Federal Emergency Management Agency’s National Household Survey in 2018 and train four classification models - logistic regression, decision trees, support vector machines, and multi-layer perceptron classifier models- to predict the impact of personal characteristics and the environment they located on household prepare for the potential natural disaster. Results show that the multi-layer perceptron classifier model outperforms others with the highest scoring on both recall (0.8531) and f1 measure (0.7386). In addition, feature selection results also show that among other factors, a household’s accessibility to disaster-related information is the most critical factor that impacts household disaster preparation. Though there is still room for further parameter optimization, the model gives a clue that we could support disaster management by gathering publicly accessible data.

Increasing environmental concern and consumer demand for natural, sustainable and eco-friendly products have prompted the replacement of synthetic surfactants with their natural plant-based alternatives. Saponins are the plant based natural surfactants characterized by their foam forming properties in aqueous solution. Their natural origin makes them eco-friendly, bio-degradable and non-toxic. Further, they possess better physicochemical properties than the syn-thetic ones. They are also reported to exhibit a lot of useful biological activities such as anti-cancer, antifungal, anti-inflammatory, antimicrobial, antioxidant and cholesterol-lowering properties. Because of their excellent surface activity, biological activities and wide distribution in nature, saponin rich plants deserve deeper insight as a sustainable source of natural surfactants as they possess the potential to replace toxic synthetic surfactants abundant today. This review article is intended to provide a brief overview on the saponins with a special notion on their surface-active properties. It encourages further studies on development of commercial formulations based on saponins for the complete replacement of the synthetic counter parts, making better use of plants sources thereby contributing to global agenda of green environment.

The aim of this study was to determine the effect of Pandanus (Pandanus amaryllifolius 20 Roxb.) and Neem (Azadirachta indica) leaves powder on the repellency, mortality, and weight loss 21 of grains due to Sitophilus oryzae. The methodes of this study used a completely randomized design 22 (CRD) with 7 treatments and 4 replications. The results of this study indicate that the best treat- 23 ment in terms of causing repellency was the treatment of 10 grams of pandanus with a percentage 24 of 87.5%, while the best treatment in terms of causing pest mortality and was also able to reduce 25 the risk of rice weight loss due to Sitophilus oryzae was treatment 10 gram of neem with a mortality 26 percentage of 76.25% and weight loss of rice 3.14%. This research showed that neem leaf com- 27 pounds are better in terms of causing mortality, while Pandanus compounds are better in terms of 28 causing mortality of Sitophilus oryzae.

Fusarium graminearum is a dangerous pathogen of the cereals producing mycotoxins (trichothecene and zearalenone) harmful for human and animal health. There were evaluated sixteen winter wheat varieties for their response in conditions of natural infection with F. graminearum in the epidemic year 2019, being well known that accumulation of mycotoxins (DON, ZON and T-2) is induced by different biotic and abiotic factors. Field plot was organized in Latin rectangle randomized with three replicates. For all evaluated wheat varieties were collected field data (incidence, severity and infection degree of the fungus F. graminearum) and laboratory data (mycotoxins concentration in grains) that have been processed using the software JASP (Version 0.14) for descriptive statistics, and exploratory factor analysis (EFA). Microsoft Excel 2019 was used to calculate Pearson’s correlation coefficients. The results showed negative corelation between plants’ density and F. graminearum attack frequency. Positive correlations were found between DON and T-2 and between DON and fungus attack intensity. This work highlights that during a F. graminearum epidemic year some of the most influential factors in the contamination with harmful mycotoxins (DON, ZON and T-2) are: plants density, frequency of the attack on ear, diseased ears and attack intensity on ears.

Plant species with anti-inflammatory properties might play an essential role in combatting COVID-19 via reducing cytokine storms. We aimed to review the extant evidence of the potential therapeutic efficacy of natural products against cytokine storms by inhibiting interleukin-6 (IL-6) as a major pathological mediator. Data were collected following an electronic search in major databases (Pubmed, Scopus, Web of Science, Google Scholar) and also preprint articles on preprint and medRxiv servers by using a combination of relevant keywords. Seventeen active compounds and medicinal plants were found and reviewed in the present review. Results of both in-vivo and in-vitro experiments conducted on these compounds showed that Phillyrin, SMFM, Qiangzhi decoction, curcumin, Shen-Fu, Forsythia, and Alpha-Mangostin inhibit the production of IL-6. Andrographolide and Liu Shen Wan have an inhibitory effect on releasing this agent, while Ilex Asprella and Deoxy-11,12-didehydroandrographolide and naringin reduce the expression of IL-6. Theaflavin and Cholorogenic acid inhibit the secretion of IL-6, Xuebijing, and Chai-Hu-Gui-Zi-Gan-Jiang-Tang and Lipanpaidu prescription can reduce the serum level of IL-6. These agents also effectively improve infected lungs, increase survival rates, and minimize tissue damage. Medicinal plants and their phytochemical ingredients with down-regulatory effects on the expression of IL-6 have a potential influence on the inhibition of cytokine storms during viral infection caused by COVID-19. Therefore, phytochemicals could be regarded as promising candidates for managing cytokine storm inflammatory responses due to COVID-19 infection.

Biodiesel has caught the attention of many researchers because it has great potential to be sustainable fossil fuel substitute. Biodiesel has non-toxic and renewable nature and has been proven to emit less amount of environmentally harmful emissions such as hydrocarbons (HC), and carbon monoxide (CO), as well as smoke particles during combustion. Problems related to global warming caused by greenhouse gas (GHG) emissions could also be solved by utilizing biodiesel as a daily energy source. However, the expensive cost of biodiesel production, mainly because of the cost of natural feedstock, holds the potential of biodiesel commercialization. The selection of natural sources of biodiesel should be made with observations from economic, agricultural, and technical perspectives to obtain one feasible biodiesel with superior characteristics. This review paper presents a detailed overview of various natural sources, their physicochemical properties, as well as the performance, emission, and combustion characteristics of biodiesel when used in a diesel engine. The recent progress in studies about natural feedstocks and manufacturing methods used in biodiesel production were evaluated in detail. Finally, the findings of the present work reveal that transesterification is currently the most superior and commonly used biodiesel production method compared to other methods available.

In this study, we introduce a new type curve in 3-dimensional space which called B-lift curve and we obtain the Frenet operators of the B-lift curve. Moreover, we consider the correpondence of Frenet operators between the Blift curve and the natural lift curve. Finally, we investigate the B-lift curve according to the main curve is slant helix or darboux helix.

Kenya’s natural resource base has dwindled over years. The existence of many natural resource policies, some that are incompatible, has resulted in complex rangeland management regimes, giving rise to fragmented interventions and inadequate natural resource policies in relation to pastoralism. The majority of pastoral land resources held under a controlled access system by the national government that regulates management and utilization of resources. Pastoralists in Kenya have become among the most marginalized and disadvantaged minority groups. This is due to limited or under investment by government and other actors, and access to, or ownership of land, water and other resources, which are fundamental for pastoralism. This study examines significant obstacles for the establishment of a more inclusive ‘governance’ approach to natural resource management in northern Kenya, that characterize the customary Boran knowledge such as Deedha’s (traditional grazing unit) and formal institutions and seeks to address the tension between them through a legal framework that accommodates both. The results of the study established existence of the traditional structures and institutions in governance of natural resources within the pastoralist communities in Isiolo County. These institutions have evolved to cope with changing dynamics brought about by formalization of the natural resources governance. The resulted showed that various formal institutions from national government agencies to county government department were involved in management of the natural resources. However, the study established various operational divergence and links between informal and formal institutions involved in natural resources management. The study concluded that both informal institution such as Deedha and formal institutions constituted by national and county government did governance of natural resources among pastoralist communities in Isiolo County. The communities however have more trust in the informal structures and institutions because of their flexibility and inclusiveness.

Forest ecosystems are important providers of ecosystem functions and services belonging to four categories: supporting, provisioning, regulating, and cultural ecosystem services. Forest management, generally focused on timber production, has consequences on the ability of the system to keep providing services. Silviculture, in fact, may affect ecological structures and processes from which services arise. In particular, the removal of biomass causes a radical change in the stocks and flows of energy characterizing the system. Aiming at the assessment of differences in stored natural capital and ecosystem functions and services provision, three differently managed temperate forests of common beech (Fagus sylvatica) were considered: (1) a forest in semi-natural condition, (2) a forest carefully managed to get timber in a sustainable way and (3) a forest exploited without management. Natural capital and ecosystem functions and services are here accounted in biophysical terms. Specifically, all the resources used up to create the biomass (stock) and maintain the production (flow) of the different components of the forest system were calculated. Both stored emergy and empower decrease at increasing human pressure on the forest, resulting in a loss of natural capital and a diminished ability of the natural system to contribute to human well-being in terms of ecosystem services provision.

The climate of Bangladesh has changed drastically which may put considerable adverse impacts on mangrove fishers but very few studies focused on this professional group. An attempt was made to perceive the impact and adaptation measures of the Sundarbans mangrove resource users, employing interviews and focus group discussions. A total of 150 respondents were randomly selected from the Sundarbans west under Shyamnagar Upazila of Satkhira District. It was revealed that the abundance of fishes, fuel woods, honey, golpata (Nypa fruticans), and shrimp post-larvae (PL) was reduced considerably. The resource users have adapted themselves by changing their occupation and becoming jobless and depending on the other family members. PL collection, honey collection, shrimp culture, and wood collection were found professional adapting strategies to adopt cyclone, flood, salinity intrusion, river erosion, and drought. Several recommendations are elicited, the implementation of which is important to ensure livelihood sustainability of the mangrove communities.

Background: The Balaruc-les-Bains’ thermal mud was found to be colonized predominantly by microorganisms, with cyanobacteria constituting the primary organism in the microbial biofilm observed on the mud surface. The success of cyanobacteria in colonizing this specific ecological niche can be explained in part by their taxa-specific adaptation capacities, and also the diversity of bioactive natural products that they synthesize. This array of components has physiological and ecological properties that may be exploited for various applications.

Our understanding and theoretical interpretation of observations in astrophysics and cosmology depends on our knowledge of the fundamental constants and their possible dependence on time and space. Atomic spectroscopy and radio astronomy give important information on the validity and stability of the fundamental constants. The possible dependence of the fine structure constant alpha on time and spatial direction is an active topic of research.Period doubling is a universal property of nonlinear dynamical systems, and the doubling is exact in principle. The value of the elementary charge squared can be calculated by the period doubling process from the Planck charge and thereby the value of alpha.If ‘old’ and ‘new’ electrons are identical, then the Planck charge, i.e. a set of natural constants, has remained constant over time. In this article we show that the value of alpha calculated from the Planck charge is 0.007 % smaller than the current accepted value of alpha.

The market of natural and organic cosmetics has been growing in last decades. The increase in interest in this type of product is a consequence of the concern that consumers have been presenting in relation to the environment and health. In addition to the appreciation the use of sustainable ingredients in cosmetic formulations, the consumers are also concerned about pollution caused by the use of plastics, which leads industries to reinvent themselves and rethink about the composition of packaging. The factor that most drives the purchase of natural and organic cosmetics is the fact that the consumer, in addition to contributing to the preservation of the environment, is also using a sustainable product. The growing demand for natural and organic cosmetics results in a concern of the brands with the organic issue, with the decreased use of animal derived ingredients and with the updating the parameters required for certification of a cosmetic as natural or organic. Due to the few studies available in this area, the importance of clarifying the definitions and concepts of natural and organic cosmetics is evident, in order to contribute with accurate information for the cosmetic sector.

Coronavirus, also known as COVID-19, has been declared a pandemic by the World Health Organization (WHO). At the time of conducting this study, it had recorded over 1.6 million cases while more than 105,000 have died due to it, with these figures rising on a daily basis across the globe. The burden of this highly contagious respiratory disease is that it presents itself in both symptomatic and asymptomatic patterns in those already infected, thereby leading to an exponential rise in the number of contractions of the disease and fatalities. It is therefore crucial to expedite the process of early detection and diagnosis of the disease across the world. The case-based reasoning (CBR) model is an effective paradigm that allows for the utilization of cases’ specific knowledge previously experienced, concrete problem situations or specific patient cases for solving new cases. This study therefore aims to leverage the very rich database of cases of COVID-19 to solve new cases. The approach adopted in this study employs the use of an improved CBR model for state-of-the-art reasoning task in classification of suspected cases of Covid19. The CBR model leverages on a novel feature selection and semantic-based mathematical model proposed in this study for case similarity computation. An initial population of the archive was achieved with 68 cases obtained from the Italian Society of Medical and Interventional Radiology (SIRM) repository. Results obtained revealed that the proposed approach in this study successfully classified suspected cases into their categories at an accuracy of 97.10%. The study found that the proposed model can support physicians to easily diagnose suspected cases of Covid19 base on their medical records without subjecting the specimen to laboratory test. As a result, there will be a global minimization of contagion rate occasioned by slow testing and as well reduce false positive rates of diagnosed cases as observed in some parts of the globe.

The study explored the community perception of maternal deaths influenced by natural disaster, practice of maternal complications during natural disaster among the rural population in Bangladesh. It also explored the challenges faced by the community for providing health care and referring the complicated pregnant mothers during disaster. Three focus group discussions (FGDs) and eight in-depth interviews (IDIs) were conducted in the marginalized rural communities in the flood-prone Khaliajhuri sub-district, Netrakona district, Bangladesh. Flood is one of the major risk factors for influencing maternal death. Pregnant mothers seriously suffer from maternal complication, lack of antenatal checkup and even any doctor during flood. During the time of delivery, it is difficult to find even a skilled attendant and referring the patient with delivery complications to the healthcare facility. Boat is the only mode of transport. Majority maternal deaths occur on the boats during transfer from the community to the hospital. The rural people feel that the maternal deaths influenced by natural disaster are the natural phenomena. It needs some pre-preparation to support pregnant women during the disaster. There is unawareness of maternal health, related care and complications during disaster among the local health service providers and volunteers.

Different alcoholic beverages can have different effects on blood alcohol concentrations (BAC) and neurotoxicity even if equalized for alcohol content by volume. Anecdotal evidence suggested that natural wine is metabolized differently from conventional wines. This triple-blind study compared the BAC of 55 healthy male subjects after consuming the equivalent of 2 units of alcohol of a natural or conventional wine over 3 mins in two separate sessions one week apart. BAC was measured using a professional breathalyzer every 20 mins after consumption for 2 hrs. The BAC curves in response to the two wines diverged significantly at twenty minutes, at forty minutes and also at their maximum concentrations (peaks), with the natural wine inducing a lower BAC than the conventional wine (T20 0.40 vs. 0.46 [p<0.0002], T40 0.49 vs. 0.53 [p<0.0015], peak 0.52 vs. 0.56 [p<0.0002]). These differences are likely related to the development of different amino acids and antioxidants in the two wines during their production. This in turn may affect the kinetics of alcohol absorption and metabolism. Other contributing factors may also include pesticide residues, differences in dry extract content and the use of indigenous or selected yeasts. Further studies are needed to fully understand why natural wines are metabolized differently from conventional wines.

We discuss further details on the concepts of “drug-likeness”, “lead-likeness”, and “natural product-likeness”. The discussion will first focus on natural products as drugs, then a discussion of previous studies in which the complexities of the scaffolds and chemical space of naturally occurring compounds have been compared with synthetic, semi-synthetic compounds and FDA-approved drugs. This is followed by guiding principles for designing “drug-like” natural product libraries for lead compound discovery purposes. We end up by presenting a tool for measuring “natural product-likeness” of compounds and a brief presentation of machine learning approaches and a binary quantitative structure-activity relationship (QSAR) for classifying drugs from non-drugs and natural compounds from non-natural ones, respectively.

Here is shown method for the hydraulic solution of a looped gas-pipeline networks. Calculation of presented network is done according to principles of Hardy Cross method. The optimization was carried out by iteration of the pipes diameters, node consumptions are known and flow velocities through pipes have to stand below certain values. Accent is on determination of appropriate friction factor, and on selection of representative equation for natural gas flow under presented conditions in the network. Inappropriate usage of friction factor, equally as inappropriate usage of gas flow equation can lead to inaccurate final results. Here is shown new facts in comparison to previous calculation of gas distribution network in Kragujevac, Serbia which is done in 1994. After the implementation, measurements in situ have performed, and real measured values deviate from calculated. Causes for these errors are investigated, and improved and more accurate procedure is shown.

For decades, sepsis research has been motivated by the idea of a dangerous overreaction of the immune system in sepsis. But is it true that the response to sepsis is dysregulated? This review surveys the history of sepsis trials and found that evidence for dysregulation does not exist in many of the physiologic mechanisms of sepsis. It is time to consider the alternative hypothesis, that sepsis traits are often functional, and do more harm than good. This review discusses the implications of this perspective for the future of sepsis research

Bread wheat (Triticum aestivum L.) is staple of Pakistani people. However, its yield at farmer field is low as compared with its genetic potential. Integration of various crop and soil management strategies might be an option to enhance wheat productivity at farmer field. This 2-year experiment was conducted to check the influence of combine application of natural plant water extracts and biochar on the productvity of wheat during the winter season of 2015-16. The experiment consisted of seven treatment viz. (1) control (2) application of biochar (0.18 kg pot-1) alone, (3) application of sorghum water extract (SWE) alone, (4) application of moringa water extract (MWE) alone, (5) application of biochar + SWE, (6) application of biochar + MWE, (7) application of biochar + SWE+MWE. The results revealed that application of both crop water extracts in combination with biochar improved the growth and grain yield of wheat. Use of MWE in combination with biochar enhanced the grain weight, grain number and grain yield of wheat by 44, 14, and 24%, respectively than the control treatment. In crux, use of MWE in combination with biochar might be a viable option to improve the productivity of bread wheat.

Sourced so far mostly from beet root juice, betanin is a red-violet natural colorant increasingly used by the food, beverage and nutraceutical industries. We provide an updated bioeconomy perspective into a valued betacyanin whose supply and applications, we argue in this study, will rapidly expand.

The integral extraction via microwave-assisted hydrodiffusion and hydrodistillation of water-soluble bioproducts contained in the peel of Opuntia ficus-indica white and red cultivars harvested in Sicily, affords red and stable aqueous extracts mostly containing valued betanin, pectin and biophenols. Potentially useful as nutraceutical products, these aqueous extracts are a source of valued ingredients in high demand for a number of important food, cosmetic, beverage and nutraceutical applications.

The choice associated with words is a fundamental property of natural languages. It lies at the heart of quantitative linguistics, computational linguistics, and language sciences more generally. Information-theory gives us tools at hand to measure precisely the average amount of choice associated with words—the word entropy. Here we use three parallel corpora—encompassing ca. 450 million words in 1916 texts and 1259 languages—to tackle some of the major conceptual and practical problems of word entropy estimation: dependence on text size, register, style and estimation method, as well as non-independence of words in co-text. We present three main results: 1) a text size of 50K tokens is sufficient for word entropies to stabilize throughout the text, 2) across languages of the world, word entropies display a unimodal distribution that is skewed to the right. This suggests that there is a trade-off between the learnability and expressivity of words across languages of the world. 3) There is a strong linear relationship between unigram entropies and entropy rates, suggesting that they are inherently linked. We discuss the implications of these results for studying the diversity and evolution of languages from an information-theoretic point of view.

Natural gas hydrate, also known as combustible ice and mainly composed of methane, it is identified as the potential clean energy in the 21th century. Due to its large reserves, gas hydrate can ease problems caused by energy resource shortage and has gained attention around the world. In this paper, we focus on the exploration and development of gas hydrate as well as discussing its status and future development trend in China and abroad, then we analyze its opportunities and challenges in China from four aspects: resource, technology, economy and police with five forces model and PEST method. The results show, China has abundance gas hydrate resource; however the backward technologies and inadequate investment has seriously hindered the future development of gas hydrate, so China should establish relevant cooperation framework and intuitional arrangement to attract more investment as well as breaking through technical difficulties to make gas hydrate commercialization as soon as possible.

The increasing demands on global resources due to technological development driven by consumer expectations and demands have resulted in significant problems with ecological sustainability and material availability. The creation of biocomposites has resulted in notable advancements in the green industry within the materials science area this century, owing to concerns regarding sustainability and the environment. Globally, there is a surge in the creation of highly efficient materials derived from natural resources. In aviation applications, plant-fiber-supported polymer composite materials are becoming increasingly popular. Aerospace materials are typically used in aircraft construction as structural materials to support loads throughout different flight phases. There are many diverse mechanical qualities of natural fibres; therefore, selecting one for the interior parts of an aircraft cabin based only on its attributes leads to a multiple-attribute decision-support issue. In this paper, the effective natural fibre and polymer choice for use as reinforcing materials in composite materials is represented for the composite materials’ improvement to aircraft cabin luggage for aerospace implementations. This study can guide material designers in investigating different hybrid materials with the most effective natural fiber and polymer obtained by hierarchical strategy by elucidating the effective material choice to meet the criteria determined for the aircraft cabin luggage. For this purpose, the definitive rankings of the twelve polymers and sixteen natural fibers in terms of performance score were assessed using hierarchical strategy methodology.

The transition to renewable and sustainable energy sources is critical to solving the environmental and socioeconomic problems associated with the use of fossil fuel. This study uses an interdisciplinary approach to analyze the evolution, challenges and prospects of a sustainable energy transition in the context of recent discovery and exploitation of fossil resources. We study the case of Senegal from 2000 to 2027 and the role of natural gas in its energy transition. In 2000, Senegal's energy mix consisted of about 97% for fossil energy and only 3% for renewable energy. Nowadays, although fossil fuels are still dominant, but they account for about 70% of total electricity production. The country has indeed undertaken tremendous efforts to develop renewable energy sources including, solar, hydro and wind power, which currently account for about 30% of the total energy mix. Socio-economic indicators show that over the past two decades, Senegal's population and electricity production have grown significantly, leading to an increased energy demand/need. This growth has resulted in a five-fold increase in per capita energy consumption over the same period. Combining the strategic use of natural gas as a transition energy source with the continued development of renewable energy sources could make Senegal as a model for West Africa’s energy transition. The projections for 2027 suggest a structural shift in the energy mix, with natural gas, oil, and renewables at 47%, 32%, and 21%, respectively.

Antimicrobial resistance (AMR) is a worsening global health crisis that has arisen due to antibiotic overuse and misuse. Antibiotic resistance renders standard treatments less effective, making it difficult to control some infections, thereby increasing morbidity and mortality. Medicinal plants are sustainable treatment options that are becoming increasingly important as antibiotics lose their efficacies. The present study evaluates the antibacterial activity of aqueous, methanolic and ethyl acetate extracts prepared using Terminalia bellirica and Terminalia chebula fruit against six bacterial pathogens using disc diffusion and broth microdilution assays. The aqueous and methanol extracts of T. bellirica and T. chebula showed substantial zones of inhibition (ZOIs) against S. aureus and MRSA. The activity against those bacteria was determined to be strong, with minimum inhibitory concentrations (MIC) ranging from 94 µg/mL to 392 µg/mL. Additionally, the T. bellirica methanolic extract showed noteworthy antibacterial activity against E. coli and an ESBL E. coli strain (MIC values of 755 µg/mL for both). The aqueous T. bellirica and T. chebula extracts also inhibited K. pneumoniae growth (MIC values of 784 µg/mL and 556 µg/mL respectively), whilst the methanolic extracts of these plants also inhibited ESBL K. pneumoniae growth (MIC values of 755 µg/mL and 1509 µg/mL respectively). Eighteen additive interactions were observed when extracts were combined with reference antibiotics. Notably, strong antagonistic interactions occurred when any of the extracts were mixed with polymyxin B. All extracts were subjected to LC-MS analysis, revealing several interesting flavonoids and tannins, including 6-galloylglucose, 1,2,6-trigalloyl-β-D-glucopyranose, 6-O-[(2E)-3-phenyl-2-propenoyl]-1-O-(3,4,5-trihydroxybenzoyl)-β-D-glucopyranose, propyl gallate, methyl gallate, sanguiin H4, hamamelitannin, pyrogallol, gallic acid, ellagic acid, chebulic acid, and chebuloside II. All extracts were nontoxic when tested in brine shrimp assays. This lack of toxicity, combined with their antibacterial activities suggests that these plant species may be promising sources of antibacterial compound(s) that warrant further study.

This study innovates upon the field of dialog-driven query resolution (DDQR) utilizing knowledge graphs (KGs). Traditional methods in DDQR predominantly depend on fully supervised signals that presuppose the existence of perfect logical forms for queries. This reliance on gold logical forms for answer extraction is impractical in diverse real-world applications. When such forms are absent, contemporary methods, which lean on weak supervisory signals or employ heuristic and reinforcement strategies, recast DDQR as a knowledge graph path optimization problem. Despite the non-availability of gold logical forms, the rich conversational context provided by comprehensive dialog histories and domain-specific knowledge can be leveraged to optimize path selection in KGs effectively. We introduce an advanced method, termed CONVEX (CONVersational EXploration), which utilizes contrastive learning for path ranking. CONVEX addresses critical challenges by enabling learning under weak supervision and integrating the conversational context to enhance the representation quality for more effective path discrimination. Extensive evaluations of CONVEX on established benchmarks demonstrate its superiority across various metrics over current methods, notably improving Mean Reciprocal Rank (MRR) and Hit@5 by up to 20 and 36 percentage points respectively.

In two laboratory trials natural products, including freshly-picked leaves from spearmint, rosemary, and tansy plants; a water extract from soybean plants; peels from a common cucumber; and 1% peppermint oil in hexane were placed in a moist harborage preferred by Argentine ants, Linepithema humile, and the number of ants entering the harborage after two and four hours was counted. None of the recommended home remedies (tansy, cucumber, or soybean extract) deterred ants from an attractive, moist harborage in either trial even when the quantity of these treatments was increased 4- to 10-fold. Freshly picked leaves from rosemary and spearmint plants deterred ants from harboring, and the 1% peppermint oil was the most deterrent of all treatments.

Long COVID is a phenomenon in which individuals experience persistent symptoms after recovering from COVID-19. The symptoms are discovered to be unique for every individual and can affect multiple organs systems in the body. This study aims to identify effective natural remedies for long COVID by analyzing hub genes associated with the symptoms of the condition and evaluating the repurposed drugs catered and used for treating the symptoms of long COVID. The most common and prevalent symptoms of long COVID were identified; Fatigue, Shortness of Breath, Loss of Smell, Headache, Brain Fog, Chest Pain, Insomnia, Heart Palpitations, Dizziness, Joint Pain, Depression, Anxiety, Tinnitus, Loss of Appetite. Hub genes for each of the symptoms provided an insight on the key biological pathways of the symptom. Repurposed drugs identified, provided the template to identify the natural compounds with similar structure as a potential therapeutic drug. The natural compounds were retrieved using fingerprint search of the repurposed drugs from the NPASS Database. The findings of this study suggest several natural remedies for each symptom based on the molecular docking of the hub gene and natural compound using iGEMDOCK. The identified natural remedies may hold promise in treating long COVID, but further research is required to explore the efficacy and effectiveness of the proposed natural compounds. The results of the study pose important implications for the development of effective treatments for long COVID.

Agroforestry practices evolve with the development of basic and advanced facilities, changes in natural and artificial factors of land use change. The study aims to examine the socioeconomic characteristics and compare satisfaction levels across forest products and vegetable farming of the agroforestry community in Khost Province. Data were collected from 662 farmers and was analyzed using univariate Analysis of Variances (ANOVA) and Multivariate Analysis of Variances (MANOVA). The results found that forest and vegetable products, including fruits, berries, herbs, mushrooms, wild animals, oils, wood, honey, okra, eggplant, carrot, cucumber, pine nuts, pepper, and timber has different impact in terms of satisfaction with basic and advanced facilities, knowledge about land use and impacts, natural and artificial factors of land use change, and positive and negative impact of land use change. The limitation of the study included an absence of exogenous factors in the model such as climate change, financial conditions, market fluctuations, regulatory system, an area in which the study is selected, research design, and current condition of endogenous factors. Overall, agroforestry practices can improve the socioeconomic development of agroforestry-dependent communities in Khost Province, Afghanistan. This study provided useful insights for policymakers and development practitioners to promote agroforestry practice adoption and improve the socioeconomic development of agroforestry-dependent communities. Future works could explore the implications of agroforestry practices on the socioeconomic development of other dependent communities in Afghanistan.

Using desi-cow waste products like Jeevamrit, natural farming is widespread among farmers for improving soil biology and productivity. Jeevamrit enhances soil chemical and microbiological properties without needing large quantities of farmyard manure (FYM), as a sustainable farming practice with a reduced carbon footprint. Despite its traditional use, Jeevamrit faces criticism due to a lack of scientific evidence. This study investigated the comparative effect of Jeevamrit and chemical fertilizers on the growth and yield of marigold cv. Siracole. In this study mother block of marigold was raised for both summer and winter seasons. The cuttings were harvested from the mother block and then kept for rooting. The rooted cuttings were planted at monthly intervals and evaluated for flowering parameters and compared to those treated with RDF (30:20:20 N, P, and K g/m2). Soil supplied with Jeevamrit enhanced bacteria (26.33%), fungi (18.92%), and actinomycetes (31.21%) populations compared over the recommended dose of fertilizers (RDF) (i.e. N:P: K @ 30:20:20 g m-2). Jeevamrit-treated plants have marketable flower yield per square meter (3.98 %) and shelf life (9.93 %) compared to RDF. The study concludes that Jeevamrit @ 2 liter m-2 is a sustainable and effective alternative to traditional fertilizers for enhancing marigold production in the mid-hills of the Himalayan region, where natural farming is already accepted.

Securing funding is a critical yet complex task for organizations and individuals. This study presents an innovative chatbot designed to streamline the process using advanced Natural Language Processing (NLP) techniques and, specifically, a Retrieval-Augmented Generation (RAG) pipeline optimized for real-world applications. Our chatbot assists users in identifying suitable public tenders for financial support through natural language queries and a comprehensive public data database. The chatbot operates in a two-stage interaction model, initially providing summarized tender information for exploratory brainstorming, followed by detailed data upon user selection. A custom filtering mechanism ensures that the user interface elements responsible for swapping the interaction stages are consistent with the responses generated by the conversational agent. Human-evaluation tests demonstrated an average accuracy of 90.4% in document retrieval, with an average of 2.11 interactions required to find a specific tender. User satisfaction, rated on a scale of 1 to 5, averaged 3.14 (±1.73), indicating generally positive user experience with room for improvement. This approach addresses challenges of relevance, accuracy, and conversational flow, resulting in a reliable chatbot that simplifies the process of finding funding opportunities.

It is desirable to upgrade previous evolutionary theories, which have remained incomplete and controversial for decades. Here we employ the concept of carbon-based entities (CBEs), which include methane, amino acids, proteins, organisms, and other entities containing relatively many carbon atoms. We deduce the driving force, mechanisms, steps, modes, tempos of CBE evolution, through integration of biology, physics, and chemistry using logics for complex issues. We hence establish the Carbon-Based Evolutionary Theory (CBET). The CBET suggests that evolution is the increase in hierarchy, diversity, fitness of CBEs under natural selection and driven by thermodynamics due to the chemical effect of the thermodynamic features of the Earth on CBEs. It provides better explanations for life origin, macroevolution events, natural selection, sympatric speciation, and evolution tempos than previous evolutionary theories. It reveals the evolutionary basis of multiple important social notions, including diversity, collaboration, altruism, obeying rules, and proper increase in freedom. It refutes some wrong notions in thermodynamics, including negative entropy (negentropy) and that biological order is equal to thermodynamic order, which have misled many people. The CBET is supported by its deduction and application. It could be a rare bridge linking laws of thermodynamics, evolution of life, and development of human society, and could have great significance in various sciences.

Sentiment analysis has become an important tool for understanding public opinion across languages and domains. Recently, there has been an increase in the number of studies on sentiment analysis in low-resource languages such as Kazakh. This is important to ensure that modern text analysis technologies are accessible to all users, regardless of their language background. The aim of the study is to create a sentiment analysis model for analyzing texts in Kazakh. As part of this work, we aim to use fine-tuning techniques on our own dataset for already existing models, thus improving their accuracy and efficiency for analyzing Kazakh language texts. This paper presents a manually collected dataset "KazIntTelCom" from the city information service 2GIS, consisting of user reviews, manually annotated by the authors taking into account the polarity of sentiment (i.e. negative positive or neutral). This dataset was used to fine-tune two pre-trained multi-lingual Transformer-based sentiment analysis models taken from the HuggingFace platform. The distillBERT and XLM-RoBERTa models were used for tuning. Also, the models were tested on the dataset "KazSAnDRA". The results show that accurate tuning even on a relatively small dataset gives a significant increase in performance, which is confirmed by an increase in the accuracy index by 20%-30%. In addition, false misses and false detections are analyzed, which allows us to identify directions for further improvement of the models. The contribution of this work, in addition to the dataset, is the analysis of model errors, which will help future developers to make more accurate settings of hyperparameters of training for sentiment analysis in Kazakh. These results are important for natural language processing and their adaptation to low-resource languages, promoting more inclusive and equitable access to modern analytical tools. Thus, this study demonstrates the effectiveness of the Transformers architecture for sentiment analysis in Kazakh and opens new opportunities for further model improvement.

Senna rugosa is a species found in the Cerrado and used in folk medicine as a vermifuge and in the treatment of poisonous snakebites accidents. In this work, we identified the main secondary metabolites present in ethanolic extracts of the leaves (ELSR) and roots (ERSR) of S. rugosa and evaluated the potential cytoprotective effect against cellular macromolecular damage, as well as the cytotoxic properties of the extracts on the K562 and Jurkat leukemic cell lines. The identification of metabolites was done by liquid chromatography coupled with mass spectrometry. The antioxidant activities were investigated by direct ABTS•+ and DPPH• radical scavenging methods, protection against oxidative damage in proteins and DNA. The cytotoxic properties were investigated against healthy cells, isolated from human peripheral blood (PBMC) and leukemic cell lines. The leaf extract contains catechin, rutin, epigallocatechin derivatives, kaempferol glycosides, luteolin, and dimeric and trimeric procyanidins, while the root extract profile shows obtusichromoneside derivatives, 2-methoxystypandrone, stilbene derivatives, naphthopyranones, and flavanone derivatives. The extracts showed antioxidant activity, with IC50 of 4.86 ± 0.51 µg/mL and 8.33 ± 0.90 µg/mL in the ABTS assay for ELSR and ERSR, respectively. And in the DPPH• assay, the IC50 was 19.98 ± 1.96 µg/mL for ELSR and 13.37 ± 1.05 µg/mL for ERSR. The extracts protected macromolecules against oxidative damage at concentrations of 5 µg/mL. The cytotoxicity test against leukemic strains was observed after 24 and 48 hours of treatment. After 48 h, results against the K562 cell line demonstrate IC50 of 242.54 ± 2.38 µg/mL and 223.00 ± 2.34 µg/mL for ELSR and ERSR , respectively. While against the Jurkat cell line, these extracts showed IC50 of 171.45 ± 2.25 µg/mL and 189.30 ± 2.27 µg/mL, respectively Results on PBMC viability, demonstrate that the extracts showed selectivity for the leukemic cell lines. Together, our results reveal that the leaves and roots of S. rugosa have completely distinct and complex chemical compositions. This study expands the repertoire of identified chemical compounds and underscores their significant pharmacological potential in conditions related to oxidative stress and leukemia.

This study investigates the impact of climate change on the efficiency of organic honey production in Türkiye using a machine learning approach. The eXtreme Gradient Boosting (XGBoost) algorithm is employed for the Machine Learning (ML) modelling. The analysis includes data on organic honey production performance from 2004 to 2023, spanning a period of 20 years, and 8 different climate variables (16 variables depending on daytime and nighttime values). The dataset created to investigate the impact of climate change on organic honey yield comprises 28 columns and 120,960 rows. The study aimed to determine the significance of different climatic variables on the efficiency of organic honey production. The study found that, in addition to daytime solar radiation and temperature, wind speed and direction were also important factors. The sensitivity analysis has shown that minor alterations in the variables have a significant impact on the model's predictions. Additionally, non-linear relationships between the variables and honey production were identified. These findings suggest that it may be beneficial to consider implementing climate change adaptation and mitigation strategies in agricultural policies and beekeeping practices. The study suggests that machine learning has the potential to provide valuable insights into the complex relationship between climate change and agricultural production. This could aid in the sustainability and economic optimization of the sector.

The aim of this study was utilization of ground tea waste (GT) left after brewing the black tea as a biofiller of natural rubber (NR) composites. Ionic liquids (ILs), i.e., 1-ethyl-3-methylimidazolium lactate and 1-benzyl-3-methylimidazolium chloride, often used to extract phytochemicals from tea, were applied to improve the dispersibility of GT particles in elastomeric matrix. The influence of GT loading and ILs on curing characteristics, crosslink density, mechanical properties, thermal stability and resistance of NR composites to thermo-oxidative aging was investigated. The amount of GT did not significantly affect curing characteristics and crosslink density of NR composites, but had serious impact on tensile properties. Applying 10 phr of GT improved the tensile strength by 40% compared to unfilled NR. Further increasing in GT content worsened the tensile strength due to the agglomeration of biofiller in elastomer matrix. ILs significantly improved the dispersion of GT particles in elastomer and increased the crosslink density by 20% compared to the benchmark. Owing to the poor thermal stability of pure GT, it reduced the thermal stability of vulcanizates compared to unfilled NR. Most importantly, GT-filled vulcanizates showed improved resistance to thermo-oxidative aging, since the aging factor increased by 25% compared to the unfilled vulcanizate.

Background: The COVID-19 pandemic has affected Madagascar, Cameroon, and the Central African Republic (CAR), with each experiencing multiple waves by mid-2022. This study aimed to evaluate immunity against SARS-CoV-2 strains Wuhan (W) and BA.2 (BA.2) among healthcare workers (HCWs) in these countries, focusing on vaccination and natural infection effects. Methods: HCWs' serum samples were analyzed for neutralizing antibodies (nAbs) against W and BA.2 variants, with statistical analyses comparing responses between countries and vaccination statuses. Results: Madagascar showed significantly higher nAb titers against both strains compared to CAR and Cameroon. Vaccination notably increased nAb levels against W by 2.6-fold in CAR and 1.8-fold in Madagascar, and against BA.2 by 1.6-fold in Madagascar and 1.5-fold in CAR. However, in Cameroon, there was no significant difference in nAb levels between vaccinated and unvaccinated groups. Conclusion: The study highlights the complex relationship between natural and vaccine-induced immunity, emphasizing the importance of assessing immunity in regions with varied epidemic experiences and low vaccination rates.

Taraxacum kok-saghyz, a rubber-producing plant with excellent potential, emerges as a viable substitute for rubber tree (Hevea brasiliensis). While natural rubber is a desirable material, conventional techniques for assessing rubber content have faced challenges in meeting practical production requirements. To address this issue, we have developed a pyrolysis-mass spectrometry (PY-MS) instrument for the quantitative evaluation of natural rubber (NR) content in rubber-producing plants. The derived standard curve equation, established through external standard calibration, demonstrates a correlation coefficient (R2) surpassing 0.99. The method exhibits commendable recovery rates (93.27%-107.83%), relative standard deviations (RSD≤ 3.39%), and a swift analysis time of merely 10 minutes per sample, thereby enabling accurate and efficient quantification of NR. This approach possesses significant potential for extensive utilization in the assessment of rubber content in rubber-producing plants other than TKS. The integration of pyrolysis-mass spectrometry for the identification of polymers with high molecular weight offers a valuable pathway for the examination of diverse polymers.

Synthesis of natural products with complicated architecture often requires segments having the functional groups that can be structurally transformed with the desired stereogenic centers. Bicyclic ?-lactones have a great potential for a suitable segment for natural product synthesis. However, the stereoselective construction of such functionalized bicyclic ?-lactones is not as straightforward as one might expect. On the other hand, the Lewis acid template-mediated Diels-Alder reaction is one of the most powerful and versatile methods for providing bicyclic ?-lactones with high regioselectivity and stereoselectivity. In this reaction, the Lewis acid template activates the dienophile as well as linking the diene and dienophile by a temporary tether. Therefore, Diels-Alder reaction smoothly proceeds in a stereocontrolled manner, allowing a simple access to bicyclic ?-lactone as a valuable building block for the synthesis of complicated natural products. In this review, some highlights of the Lewis acid-mediated Diels-Alder reaction, along with its application to the synthesis of biologically active compounds are discussed.

Artificial intelligence (AI) tools, such as OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), have great potential in various fields, such as healthcare, education, and industry. This review highlights the applications and challenges of the ChatGPT versions 3.5 and 4.0 in radiology. ChatGPT can process medical texts, analyze medical images, and generate reports and summaries for different audiences. ChatGPT can also answer patients' questions and translate complex medical information into a plain language. ChatGPT has shown impressive results in medical tests and quizzes, indicating its potential to enhance diagnostic accuracy and medical education. These models show promise for reducing diagnosis times and healthcare costs. However, ChatGPT also faces challenges and limitations, such as a lack of visual content, ethical and legal issues, data quality, and error detection. This review highlights the benefits and future directions of ChatGPT and artificial intelligence (AI) in radiology.

Hepatitis E virus is a major etiological agent of chronic hepatitis in immunosuppressed individuals. Studies on HEV in the context of liver transplantation have produced mixed results, most of the data coming from studies conducted in high-income countries. This was a prospective cohort study of liver transplant recipients in southeastern Brazil. Recipients were systematically followed for one year, with the objective of determining the prevalence, incidence, genotype, and natural history of HEV infection in this population. We included 107 liver transplant recipients and 83 deceased donors. Positivity for anti-HEV IgG was detected in 11 (10.2%) of the recipients and in eight (9.7%) of the donors. None of the patients tested positive for HEV RNA at baseline or during follow-up. There were no episodes of reactivation or seroconversion, even in cases of serological donor-recipient mismatch or in recipients with acute hepatitis. Acute and chronic HEV infections seem to be rare events in the region studied. That could be attributable to social, economic, and environmental factors. Our data indicate that, among liver transplant recipients, hepatitis E should be investigated only when there are elevated levels of transaminases with no defined cause, as part of the differential diagnosis of seronegative hepatitis after transplantation.

It is essential to deal with data scattered among heterogeneous information sources, which can be structured, semi-structured, or unstructured, to give consumers a cohesive perspective of the data. Information gathering is challenging as a result, and one of the major causes of this is that data sources are developed to support specific applications. A method to simplify this procedure is to use ontology representation as an intermediate step. An ontology represents a knowledge structure that reasonably reflects the real world's complexity and is ideally used in many industries today. This research aims to enhance the functionality of a global ontology system by implementing and integrating a natural language query system. Leveraging NLP-based approaches, we constructed SPARQL queries for our ontologies to facilitate natural language translation into a well-structured query format. A dedicated query component was developed to transform natural language questions into SPARQL queries, with the selection of the optimal query graph to generate the final queries. In the subsequent phase, we explored the integration of distinct sentence encoders to improve latent sentence representations during query construction. The generated SPARQL queries were executed on the global ontology output and then translated into source-specific questions. This innovative approach enables unified access to heterogeneous data sources through a user-friendly natural language querying interface.

Wounds are breaks in the continuity of the skin and the underlying tissues, due to external causes, such as cuts, blows and impacts, or even, during surgical interventions. Millions of people suffer minor or serious injuries, sometimes ending in death. Today, there are many commercially available products that promote healing from wounds. The high demand from the healthcare industry has created a huge market that continues to grow, fueling research and development of new wound healing products. In the present article, we review recent advances in wound healing products based on natural biopolymers, stem cells, and microRNAs. We analyze the advances of both, the commercial products and the products that are still in research phase, and we also include an overview of the opportunities, barriers, and regulatory issues for the commercialization of these products in the European, American, and Asian markets.

Enzymes used in the synthesis of natural products are potent catalysts, capable of efficient and stereoselective chemical transformations. Lsd18 catalyzes two sequential epoxidations during the biosynthesis of lasalocid A, a polyether polyketide natural product. We performed protein engineering on Lsd18 to improve its thermostability and catalytic activity. Utilizing structure-guided methods of FoldX and Rosetta-ddG, we designed 15 mutants of Lsd18. Screening of these mutants using thermal shift assay identified stabilized variants Lsd18-T189M, Lsd18-S195M, and the double mutant Lsd18-T189M-S195M. Trypsin digestion, molecular dynamic simulation, circular dichroism (CD) spectroscopy, and X-ray crystallography provided insights into the molecular basis for the improved enzyme properties. Notably, enhanced hydrophobic interaction within the enzyme core and interaction of the protein with the FAD cofactor appear to be responsible for better thermostability.

This article explains how resistance alleles have become rare or have disappeared from honey bee populations in Europe (and probably also in North America). Honeybees have the highest recombination frequency of all animals, indicating that pathogenic bacteria, viruses, fungi and microsporidia are an important source of selection. To respond to new virulent strains of pathogens, honeybees need to have access to rare alleles that could foster immunity against a new pathogen. By mating in a large panmictic population, new rare alleles can be recruited, which can then be combined into new genotypes through recombination with useful alleles of other genes. Bee breeders, by selecting small samples from a large population tend to select common alleles and lose the rare ones. Rare alleles can become important when a new virulent pathogen arrives. The loss of rare alleles makes bees vulnerable to disease and parasites and explains, together with the problems caused by modern agriculture, why managed bees have high mortality rates.

In this paper, the main characteristics of the natural bitumen of the Munaily-Mola oil sands were studied with comparison crude oil of Karazhanbas oil field. During the experiment, the density, heating value, ash content and elemental composition of natural bitumen were determined, and these parameters were compared with the properties of Karazhanbas crude oil. As well as oil, resin and asphaltene fractions of both hydrocarbons were separated and each of them were analyzed at a Fourier transform IR-spectroscopy Spectrum-65 with 450-4000 cm−1 range. According to these indicators, it is concluded that natural bitumen is a heavy hydrocarbon raw material with highly resin-asphaltene compounds. Like Karazhanbas oil, natural bitumen can be used as a raw material for various petrochemical products. By finding ways of effective processing of natural bitumen, it can be used in useful areas of the national economy.

Human beings naturally move from one location to another in search of basic necessities. Road transportation is a low-cost, versatile, and widely accessible mode of transportation worldwide. However, using fossil-based (FB) fuels in transportation vehicles is inefficient, generates hazardous gases, and worsens environmental degradation. The current work assesses the application of clean fuels such as biofuels, natural gas, electricity, propane, and other emerging fuels to replace FB fuels in transport vehicles. Unlike FB fuels, the use of biohydrogen, biomethane, biodiesel, and bioethanol in transport vehicles resulted in emission reduction by 70 %, 63 %, 41 %, and 54 %, respectively, while electric vehicles lower maintenance costs, ensuring better engine performance, and better engine efficiency. The adoption of natural gas and propane as alternative fuels for transport vehicles is cost-effective, and promotes environmental sustainability. There is a need for targeted financial, infrastructural, and technical investments to further promote the application of these clean fuels for road transport application. The outcome of the study provides updated information and sensitizes automobile engineers, environmentalists, transport fleet operators, governments, and other stakeholders on the benefits derivable in the adoption of clean fuels as alternatives to FB fuels as transport vehicles fuel.

Hydrogels prepared from natural polymer have attracted extensive attentions in biomedical fields such as drug delivery, wound healing, and regenerative medicine due to their good biocompatibility, degradability and flexibility. This review outlines the commonly used natural polymer in hydrogel preparation, including cellulose, chitosan, collagen/gelatin, alginate, hyaluronic acid and starch. The polymeric structure and process/synthesis of natural polymers are illustrated, and natural polymer-based hydrogels including the hydrogel formation and properties are elaborated. Subsequently, the biomedical application of hydrogels based on natural polymer in drug delivery, tissue regeneration, wound healing and other biomedical field is summarized. Finally, the future perspectives of natural polymers and hydrogels based on them are discussed. For natural polymer, novel technologies such as enzymatic and biological methods are developed to improve the structural properties and the development of new natural based polymers or natural polymer derivatives with high performance is still very important and challenging. For natural polymer-based hydrogels, novel hydrogel materials, like double-network hydrogel, multifunctional composite hydrogels and hydrogel microrobots are designed to meet the advanced requirements in biomedical application, and new strategies such as dual-crosslinking, microfluidic chip, micropatterning and 3D/4D bioprinting, have been explored to fabricate advanced hydrogel materials with designed properties for biomedical application. Overall, natural polymeric hydrogels have attracted increasing interests in biomedical application, and the development of novel natural polymer-based materials and new strategies/methods for hydrogel fabrication is badly desirable and still challenging.

While fibrinolytic enzymes and thrombolytic agents offer assistance in treating cardiovascular diseases, the existing options are associated with a range of adverse effects. In our previous research, we successfully identified ficin, a naturally occurring cysteine protease that possesses unique fibrin and fibrinogenolytic enzymes, making it suitable for both preventing and treating cardiovascular disorders linked to thrombosis. Papain is a prominent natural cysteine protease derived from the latex of Carica papaya. The potential role of papain in preventing fibrin(ogen)lytic, anticoagulant, and antithrombotic activities has not yet been investigated. Therefore, we examine how papain influences fibrinogen and the process of blood coagulation. Papain is highly stable at pH 4-11 and 37-60°C by azocasein assay. In addition, SDS gel separation electrophoresis, zymography, and fibrin plate assays were used to determine fibrinogen and fibrinolysis activity. Papain appears to have a molecular weight of around 37 kDa, and is highly effective in degrading fibrin, with a molecular weight of over 75 kDa. Furthermore, papain-based hemostatic performance was confirmed in blood coagulation tests, a blood clot lysis assay, and a κ-carrageenan rat tail thrombosis model, highlighting its strong efficacy in blood coagulation. Papain shows dose-dependent blood clot lysis activity, cleaves fibrinogen chains of Aα, Bβ, and γ-bands and significantly extends prothrombin time (PT) and activated partial thromboplastin time (aPTT). Moreover, the mean length of the infarcted regions in the tails of Sprague-Dawley rats with κ-carrageenan was shorter in rats administered 10 U/kg of papain than in streptokinase-treated rats. Thus, papain, a natural cysteine protease, has distinct fibrin and fibrinogenolytic properties, suggesting its potential for preventing or treating cardiovascular issues and thrombosis-related diseases.

Tomato brown rugose fruit virus (ToBRFV) is a causal agent of severe emergent diseases in Solanaceae hosts with agronomic relevance, such as tomato and pepper. Herein, we analyzed the seed transmission rate and efficacy of different seed disinfection treatments and performed a comparison of molecular biology techniques seeking rapid and sensitive detection in seed lots. We evaluated several total RNA extraction and RT-PCR protocols using a distinct combination of PCR primers to test for the presence of the ToBRFV Mexican strain in tobacco host. Our results showed that the percentage of seed and seedlings transmission was less than 1% and that a 3% sodium hypochlorite solution was effective as a seed disinfection treatment. Finally, the most sensitive molecular method identified for virus detection consisted of a CTAB-Trizol RNA extraction followed by nested PCR using primers reported by Dovas et al. (2004). Additionally, we tested potential natural hosts in selected Cucurbitaceae and Solanaceae species. Our results showed that the ToBRFV Mexican strain is capable of experimentally infecting eggplant (Solanum melongena), tomatillo (Physalis ixocarpa), and tobacco (Nicotiana rustica).

In the food industry, Listeria is a standard control microorganism in ready-to-eat food since it may be pathogenic and cause a disease called listeriosis. The objective of the present study was to carry out a challenge test to verify the efficiency of different combinations of natural antimicrobial ingredients, against Listeria monocytogenes, to be used in ready-to-eat foods. Six different formulations of cooked ham were elaborated: a control, and five different formulations. An initial inoculation of 2 log cycles was used in the different products and the growth of Listeria was monitored at different temperatures and times (4° C for 17 w; 7ºC for 12 w). Control samples showed a progressive growth, reaching 5-6 log after 3 or 4 weeks. The rest of samples showed constant counts of Listeria during the all study. Only samples containing: 100 ppm nitrite + 250 PPM ascorbic acid+0,7% PRS DV-5 did not control the growth of Listeria at 7 ° C after 7 w of storage. The results obtained allowed to classified the cooked ham elaborated using any natural ingredients combinations as a “Ready-to-eat food unable to support the growth of L. monocytogenes other than those intended for infants and for special medical purposes”.

In this study, various percentage combinations of waste aggregates such as PET and crumb rubber were used to replace coarse and fine aggregates in natural rubber latex (NRL) modified concretes. Engineering properties such as compressive and flexural strengths, modulus of elasticity, and toughness obtained from compressive- and flexural stress-strain curves were investigated. Scanning electron microscopy (SEM) analysis was performed to examine the microstructural properties and to study the strength development of the studied concretes. The results indicated that both the compressive and flexural strengths of NRL-modified concretes with PET and crumb rubber aggregate replacements decreased with increasing replacement ratios. SEM analysis indicated that PET and crumb rubber (hydrophobic and non-polar materials) can affect the microstructure of the studied concrete by creating a weak interface between the aggregate and cement pastes, leading to reducing strength development. With the addition of the NRL additive, the film formation was found to act as a bridge and improved the bond strength of aggregates and hydration products of NRL-modified concrete. Furthermore, the integration of PET and crumb rubber aggregate can enhance the ability of the concrete to absorb energy and improve ductility. It was found that 10% of PET and crumb rubber aggregate replacement can be used for NRL-modified concrete as a rigid pavement, as its compressive and flexural strengths met the minimum requirement specified by the Department of Highways, Thailand. This research helps repurpose waste materials and reduce the environmental footprint of concrete production.

Diabetes and its complications are a global health burden, necessitating novel therapeutic approaches. Natural products and derivatives are gaining attention as potential agents for managing diabetes due to their diverse constituents and pharmacological activities. Algae, in particular, offer promising bioactive compounds with antidiabetic properties. This review provides an overview of natural products derived from algae in diabetes management, including advancements and future prospects. It highlights the significance of natural products in diabetes, explores algae's diversity, bioactive compounds, and mechanisms of action. The challenges, limitations, and strategies for optimizing algae-based interventions are discussed, alongside future research directions. Algae's multifaceted pharmacological activities and chemical constituents make them attractive for developing novel antidiabetic therapeutics. Further research and optimization of algae-based interventions have the potential to address the global burden of diabetes and improve patient outcomes.

Breast cancer is one of the most common types of malignant tumors worldwide and the leading cause of cancer-related deaths in women. According to the latest report from the World Health Organization, breast cancer has surpassed lung cancer, becoming the most diagnosed cancer globally. Herein, a systematic, quantitative, and visual analysis of the scientific achievements in natural products research and development for breast cancer over the past 30 years is presented. The study utilizes bibliometric and knowledge graph visualization techniques to analyze the trends, co-occurrence of keywords, cooperative networks, cited literature, and research hotspots in the field. The analysis shows that breast cancer natural drug development involves mutual cooperation between multiple countries, with China, the United States, and India being the most active players. Pharmacology is the discipline with the largest number of articles published in nearly 30 years. The study also reveals that the extraction of drugs from organisms and their metabolites is an important direction in the current development of anticancer drugs. The development of natural medicines for breast cancer together with the mining of genetic knowledge play an important role in treating human breast cancer. The research presented here provides insights into the current state of natural product research and development for breast cancer, and highlights the need for strengthening mutual communication and cooperation between countries and scientific research institutions to enhance the development of breast cancer treatment technologies and natural medicines.

In the past decade, considerable efforts have been devoted to the development of semitransparent organic solar cells. Numerous materials and architectures have been proposed for the future commercialization of these devices. Among these, the use of ternary active layers demonstrated a great promise for the development of efficient semi-transparent organic solar cells with the potential for future applications including self-powered greenhouses and powered windows. Researchers seek alternative solutions to the trade-off between device power conversion efficiency (PCE) and average visible transmittance (AVT), with photoactive materials being the key parameters that govern both (PCE) and (AVT) as well as device stability. Several new organic materials, including polymers and small molecules, were synthesized, and used in conjunction with a variety of techniques to achieve semitransparent conditions. In this review paper, we will look at the working principle and key parameters of semi-transparent organic solar cells, as well as the methods that have been used to improve the performance of ternary-based semi-transparent organic solar cells. The main approaches were concluded to be spectral enhancement and transparency increment of the active layer through bandgap tuning, utilizing novel organic semiconductors, and design architecture of the active layers.