Emerging evidence suggests that sustained diabetes-associated factors such as inflammation, hyperinsulinemia, and hyperglycemia are major contributors to aberrant cell proliferation and subsequent neoplastic transformation. Epidemiological studies have also highlighted that diabetes promoting a sedentary lifestyle, with or without the direct involvement of insulin, is frequently linked to cancer. However, our knowledge regarding the molecular mechanisms that correlate hyperglycemia to oncogenic transformations remains limited. In this regard, a recent study has proved that hyperglycemia inactivates AMPK, which results in the destabilization of the TET2 and its tumour-suppressive role ultimately predisposing diabetes mellitus patients to cancer. To the management of hyperglycemia associated with oncogenesis, we need to explore a reverse pharmacology-based ethnopharmacological approach. Botanical-derived natural products are structurally and functionally more diverse with fewer or no side effects on humans. The present review discusses the molecular link between hyperglycemia and cancer progression with the effect of natural products as therapeutic agents on the hyperglycemia-cancer associated signalling pathway.

Documenting cultural heritage by using artificial intelligence (AI) is crucial for preserving the memory of the past and a key point for future knowledge. However, modern AI technologies make use of statistical learners that lead to self-empiricist logic, which, unlike human minds, use learned non-symbolic representations. Nevertheless, it seems that it is not the right way to progress in AI. If we want to rely on AI for these tasks, it is essential to understand what lies behind these models. Among the ways to discover AI there are the senses and the intellect. We could consider AI as an intelligence. Intelligence has an essence, but we do not know whether it can be considered “something” or “someone”. Important issues in the analysis of AI concern the structure of symbols -operations with which the intellectual solution is carried out- and the search for strategic reference points, aspiring to create models with human-like intelligence. For many years, humans, seeing language as innate, have carried out symbolic theories. Everything seems to have skipped with the advent of Machine Learning. In this paper, after a long analysis of history, the rule-based and the learning-based vision, we propose KERMIT as a unit of investigation for a possible meeting point between the different learning theories. Finally, we propose a new vision of knowledge in AI models based on a combination of rules, learning and human knowledge.

Natural products endowed of biological activity represent a primary source of commodities ranging from nutrition to therapeutic agents, as well as cosmetic tools, and recreational principles. These natural means have been used by mankind since centuries if not millennia. They are commonly used all over the world and socio-economical contexts but are particularly attractive in disadvantaged area or economically emerging situations all over the world. This is very likely due to the relatively easy recovery of these bioactive principles from the environment, to the low if any cost as well as ease of administration and to the general popular compliance concerning their consumption/ingestion. In this concise review, we focus on some popular bioactive principles of botanical origin which find a wide use in the Madagascan populations. But, due to space limitations only some most common and largely diffused principles in this country are considered. Finally, a possible nanotechnological administration is discussed in the case where a potential therapeutic usage is envisaged.

Deep neural networks are hegemonic approaches to many machine learning areas, including natural language processing (NLP). Thanks to the availability of large corpora collections and the capability of deep architectures to shape internal language mechanisms in self-supervised learning processes (also known as "pre-training"), versatile and performing models are released continuously for every new network design. But these networks, somehow, learn a probability distribution of words and relations across the training collection used, inheriting the potential flaws, inconsistencies and biases contained in such a collection. As pre-trained models have found to be very useful approaches to transfer learning, dealing with bias has become a relevant issue in this new scenario. We introduce bias in a formal way and explore how it has been treated in several networks, in terms of detection and correction. Also, available resources are identified and a strategy to deal with bias in deep NLP is proposed.

Anthelmintic drugs are the major line of defense against parasitic nematode infections, but the arsenal is limited and resistance threatens sustained efficacy of the available drugs. Discoveries of the modes of action of these drugs and mechanisms of resistance have predominantly come from studies of a related non-parasitic nematode species, Caenorhabditis elegans, and the parasitic nematode Haemonchus contortus. Here, we discuss how our understanding of anthelmintic resistance and modes of action came from the interplay of results from each of these species. We argue that this “cycle of discovery”, where results from one species inform the design of experiments in the other, can use the complementary strengths of both to understand anthelmintic modes of action and mechanisms of resistance.

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.

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.

The genus Beauveria include important entomopathogenic and endophytic fungi, among them, B. bassiana is the most studied species. However, there are few knowledge regarding their antimicrobial activity. The current research has been conducted to evaluate in vitro antibacterial efficacy of five isolates of B. bassiana against Bacillus cereus, B. megaterium, B. mojavensis, Clavibacter michiganensis (gram positive bacteria, G+ve), Xanthomonas campestris, X. vesicatoria, Escherichia coli, Pseudomonas aeruginosa and P. fluorescence (gram negative bacteria, G-ve). In addition, chemical composition of the principal diffusible metabolites and volatile organic compounds (VOCs) of the most efficient studied isolate of B. bassiana has been carried out using GC-MS analysis. The obtained results showed that, the isolate UniB2439-3 has promising antibacterial effect against most of studied target bacteria. GC-MS analysis of diffusible metabolites detected the presence of hexanedioic acid, bis(2-ethylhexyl) ester as the main compound in the cell-free culture filtrate. Furthermore, GC-MS analysis of VOCs revealed the presence of ethanol; butanal,2-methyl; 2,4-dimethyl-1-heptene; octane, 4-methyl and β-elemene as the main dominant bioactive compounds. The outgoing results explicated that, the isolates of B. bassiana have promising antibacterial activity which could be correlated to their diffusible and VOCs metabolites. Therefore, the selected isolate can be potentially used as a biocontrol agent against several bacteria especially G+ve ones. Taking in consideration that the antibiotics are forbidden in agriculture in many countries worldwide, search for possible natural alternatives as efficient antimicrobial agents are highly interesting.

The study utilizes the energy-flux-vector method to analyze the heat transfer characteristics of natural convection in a wavy-wall porous square cavity with a partially-heated bottom surface. The effects of the modified Darcy number and modified Rayleigh number on the energy-flux-vector distribution and mean Nusselt number are examined. The results show that when a low modified Darcy number with any value of modified Rayleigh number is given, the recirculation regions are not formed in the energy-flux-vector distribution within the porous cavity. Therefore, a low mean Nusselt number is obtained. The recirculation regions do still not form and thus the mean Nusselt number has a low value when a low modified Darcy number with a high modified Rayleigh number is given. However, when the values of the modified Darcy number and modified Rayleigh number are high, the energy flux vectors generate recirculation regions and thus a high mean Nusselt number is obtained.

This study focused on evaluating the potential of natural fermentation of pea flour (F) to improve the release of antioxidant compounds. Two fermentation conditions of F were performed: 1: 36.4% w/w, 24 h, 30°C (FF1); 2: 14.3% w/w, 24 h, 37°C (FF2); pH values decreased to 4.4-4.7, with a predominance of lactic acid bacteria. An increment of the proteolysis degree (TNBS method) (greater for FF2), polypeptides aggregation and decrease of solubility, increase of < 2 kDa peptides, and increase in the ORAC potency of PBS-soluble fractions after fermentation was demonstrated. After simulated gastrointestinal digestion (SGID, COST-INFOGEST), FF1D and FF2D showed greater proteolysis degrees (63 and 53%) than F1D and F2D (45%), with differences in the molecular composition of the different digests. ORAC and HORAC potencies increased in all cases. FF2D presented the greater ORAC value, with higher activities for > 4 kDa, some in the range 2 to 0.3 kDa. and < 0.10 kDa fractions. Fermentation also increased the 60 % ethanol extracted phenolic compounds, mainly flavonoids, and the ORAC activity. After SGID, the flavan-3-ols disappeared but some phenolic acids increased respect to F. Fermentation in condition 2 was considered the most appropriate to obtain a functional antioxidant ingredient.

Titica vine fibers (TVFs) extracted from aerial roots of Heteropsis flexuosa, from the Amazon region, were 10, 20, 30 and 40 vol% incorporated into an epoxy matrix for applications in ballistic multilayered armor systems (MASs) and stand-alone tests for personal protection against high-velocity 7.62 mm ammunition. The back-face signature (BFS) depth measured for composites with 20 and 40 vol% TVFs used as an intermediate layer in MASs was 25.6 and 32.5 mm, respectively, below the maximum limit set by the international standard. Fracture mechanisms found by scanning electron microscopy (SEM) attested the relevance of increasing the fiber fraction for applications in MASs. The results of stand-alone tests showed that the control (0 vol%) and samples with 20 vol% TVFs absorbed the highest impact energy (Eabs) (212 – 176 J), and consequently limit velocity (VL) values (213 – 194 m/s), when compared with 40 vol% fiber fractions. However, the macroscopic evaluation found that the plain epoxy, referring to control samples, shattered completely. In addition, for 10 and 20 vol% TVFs, the composites were fragmented or exhibited delamination fracture, which contributed to their physical integrity. On the other hand, the composite with 30 and 40 vol% TVFs, whose Eabs and VL varied between 166 – 130 J and 189 – 167 m/s, respectively, showed the best dimensional stability. The SEM images indicated that for composites with 10 and 20 vol% TVFs the fracture mode was predominantly brittle, due to the greater performance of the epoxy resin and the discrete action of the fibers. While for composites with 30 and 40 vol% TVFs, there was the activation of more complex mechanisms such as pullout, shearing and fiber rupture.

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.

A frequent problem in Geotechnics is the soils with inadequate physical-mechanical properties before the efforts to which they will be subjected by the constructions, incurring cost overruns caused by their engineering improvement. The need to improve the engineering properties of soils is not recent, currently observing that the most common alternatives are binders such as cement and lime. The climate change observed in recent decades and the uncontrolled emission of greenhouse gases have motivated Geotechnical and Geoenvironmental researchers to seek mechanisms for soil reinforcement from a more sustainable and environmentally friendly approach by proposing the use of recycled and waste materials. An alternative is natural fibers, which can be obtained as waste from many agro-industrial processes, implying their high availability and low cost. Sawdust as a by-product of wood processing has a rough texture that can generate high friction between the fiber and the matrix of the soils, leading to a significant increase in its shearing strength and bearing capacity. This concept of improving the properties of soils using natural fibers distributed randomly is inspired by the natural phenomenon of grass and/or plants that when growing on a slope can effectively stabilize a said slope.

There is a strong need and demand from the United Nations, public institutions, and private sector for classifying government publications, policy briefs, academic literature, and corporate social responsibility reports according to their relevance to the Sustainable Development Goals (SDGs). It is well understood that the SDGs play a major role in the strategic objectives of various entities. However, linking projects and activities to the SDGs has not always been straightforward or possible with existing methodologies. Natural language processing (NLP) techniques offer a new avenue to identify linkages for SDGs from text data. This research examines various machine learning approaches optimized for NLP-based text classification tasks for their success in classifying reports according to their relevance to the SDGs. Extensive experiments have been performed with the recently released Open Source SDG (OSDG) Community Dataset, which contains texts with their related SDG label as validated by the community volunteers. Results demonstrate that especially RoBERTa achieves very high performance in the attempted task, which is promising for automated processing of large collections of sustainability reports for detection of relevance to SDGs.

Most Acinetobacter baumannii strains are naturally competent. Although some information is available about factors that enhance or reduce the frequency of transformation of this bacterium, the regulatory elements and mechanisms are barely understood. In this article, we describe studies on the role of H-NS in the regulation of expression of genes related to natural competency and the ability to uptake foreign DNA. The expression levels of the natural transformation-related genes pilA, pilT, pilQ, comEA, comEC, comF, and drpA were significantly increased in a Δhns derivative of Acinetobacter baumannii A118. Complementation of the mutant with a recombinant plasmid harboring hns restored expression levels of six of these genes (pilT remained expressed at high levels) to those of the wild-type strain. The transformation frequency of the A. baumannii A118 Δhns strain was significantly higher than that of the wild-type. Similar, albeit not identical, effects occurred when hns was deleted from the hypervirulent A. baumannii AB5075 strain. Reduction of gene expression in a few cases was not as pronounced as to reach wild-type levels, and expression of comEA was enhanced further. In conclusion, the expression of all seven transformation-related genes was enhanced after deleting hns in A. baumannii A118 and AB5075, and these modifications are accompanied by an increase in the cells’ transformability. The results demonstrate a role of H-NS in A. baumannii’s natural competence.

Marine environments represent a great opportunity for the discovery of compounds with a wide spectrum of bioactive properties. Due to the privileged conditions of natural selection, marine natural products are subject to overcome the pressure put on identify novel drugs; not only in the case of newly discovered bioactive metabolites, but also in those previously known. Since drug resistance has caused an increase in infections caused by tuberculous and nontuberculous Mycobacteria, the re-evaluation of known bioactive metabolites has been suggested as a means to address this problem. In this sense, this study presents an evaluation of in vitro effect of laurinterol (1) and aplysin (2), two brominated sesquiterpenes isolated from Laurencia johnstonii against nine Mycobacterium tuberculosis strains and six nontuberculous mycobacteria. Laurinterol (1) exhibited good anti-tuberculous activity, especially against nontuberculous mycobacteria, being remarkable the effect against M. abscessus with MIC values lower than the reference drug imipenem. This study provides further evidence for the antimycobacterial activity of some sesquiterpenes from L. johnstonii, that can be considered an interesting lead compound for the discovery of novel antimycobacterial molecules to treat NTM infections.

Introduction: The need for therapeutic regimens for non-critically ill patients during the COVID-19 pandemic remains unmet. Previous work has shown that a combination of three aromatic plants’ essential oil (CAPeo) (Thymbra capitata (L.) Cav., Origanum dictamnus L., Salvia fruticosa Mill.) has remarkable in vitro antiviral activity. Given its properties, it was urgent to explore its potential in treating mild COVID-19 patients in primary care. Methods: 69 adult patients were included in a clinical, Proof-of-Concept (PoC) intervention study. Family physicians implemented the observational study in two arms (intervention and control group) during three study periods (IG2020, n=13, IG2021/22, n=25 and CG2021/22, n=31). The SARS-CoV-2 infection was confirmed by real-time PCR. The CAPeo mixture, was administered daily for 14 days, per os in the intervention group, while the control group received usual care. Results: The PoC study, found that the number and frequency of general symptoms, including general fatigue, weakness, fever and myalgia, decreased following CAPeo administration. The average presence (number) of symptoms decreased in IG (4.7 to 1.4) as well as in CG (4.0 to 3.1) by Day 7 compared to Day 1, representing a significant decrease in cumulative presence in IC (-3.3 vs. -0.9, p<0.001; η2=0.20) on Day 7 and on Day 14 (-4.2 vs. -2.9, p=0.027; η2=0.08). Discussion/Conclusion: Our findings suggest that CAPeo, possesses potent antiviral activity, in addition tο the Influenza A and B and the human rhinovirus HRV14 strains against SARS-CoV-2. The early and effective impact in alleviating key symptoms of COVID-19 may suggest this mixture can act as a complementary natural agent for mild COVID-19 patients

Ebola virus (EBOV) is a negative-sense RNA virus that can infect humans and nonhuman primates with severe health consequences. Development of countermeasures requires a thorough understanding of the interaction between host and pathogen, and the course of disease. The goal of this study was to further characterize EBOV disease in a uniformly lethal rhesus macaque model, in order to support development of a well-characterized model following rigorous quality standards. Rhesus macaques were intramuscularly exposed to EBOV and one group was euthanized at predetermined time points to characterize progression of disease. A second group was not scheduled for euthanasia in order to analyze survival, changes in physiology, clinical pathology, terminal pathology, and telemetry kinetics. On day 3, sporadic viremia was observed and pathological evidence was noted in lymph nodes. By day 5, viremia was detected in all EBOV exposed animals and pathological evidence was noted in the liver, spleen, and gastrointestinal tissues. These data support the notion that EBOV infection in rhesus macaques is a rapid systemic disease similar to infection in humans, under a compressed time scale. Biomarkers that correlated with disease progression at the earliest stages of infection were observed thereby identifying potential “trigger--to-treat” for use in therapeutic studies.

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.

Integrating voice assistant technology can potentially enhance accessibility and user interaction in web-based platforms for geospatial data visualisation and processing. This paper presents an open-source development incorporating a voice virtual assistant into the BStreams web application platform, designed specifically for visualising geospatial data. The study aimed to mitigate the observed limitations of virtual assistants in understanding the semantics and context of user commands in the geospatial domain. A discourse framework specialised for geospatial data was developed using a structured prototype methodology. In addition, a survey assisted in identifying commonly used English terminologies for geospatial data interaction. The questionnaire results were subsequently assessed using the ChatGPT natural language processing model. The application used open-source frameworks, including Web Speech API, Leaflet, Mapbox geocoding, and JavaScript. This investigation indicates that voice virtual assistants can potentially enhance human-computer interaction for geospatial data visualisation and processing. However, challenges related to natural language understanding, accents, and domain knowledge were raised. The paper advocates for further research to refine the integration of voice technology in this domain.

The demographic history of anatomically modern humans (AMH) involves multiple migration events, population extinctions and genetic adaptations. As genome-wide data from complete genome sequencing becomes increasingly abundant and available even from extinct hominins, new insights of the evolutionary history of our species are discovered. It is currently known that AMH introgressed with archaic hominins once they left the African continent. Current out of African human genomes carry fragments of archaic origin. This review focuses on the fitness consequences of archaic interbreeding in current human populations. We discuss new insights and challenges that researchers face when interpreting the potential impact of introgression on fitness and testing hypotheses about the role of selection within the context of health and disease.

In this review paper, we discuss the use of BERT, one of the most well-liked deep learning-based language models. The model's operation mechanism, key areas of applicability to text analytics tasks, comparisons with related models for each activity, and a description of certain proprietary models are all covered in this work. The data from several dozen original scientific studies that have been published in the last few years and have garnered the greatest interest from the scientific community were systematized in order to prepare this review. All researchers and students who wish to learn about the most recent developments in the field of natural language text analysis may find this survey helpful. Bidirectional Encoder Representations from Transformers, or BERT for short, is the subject of a thorough investigation that we present. The area of natural language processing holds significant importance in the creation of intelligent systems. To do a variety of activities, one must comprehend the sentence's correct meaning in order to produce the desired result. Computers have a hard time understanding languages because of how context constantly changes. The main challenge in natural language processing tasks is getting computers to understand text context, and BERT is seen as a revolution in this regard. It picks up the language and its meaning in a manner that is quite similar to how the human brain processes meaning from sentences. Its capacity to identify a word from both the left and right contexts of a sentence makes it special. A new era in the perception and comprehension of natural languages has been ushered in with the development of BERT, which could help computers understand natural languages more fully. This study aims to provide readers with a deeper knowledge of the BERT language model and how it is applied to different NLP tasks.

Antiviral drugs cannot treat dengue fever, a serious medical disease spread by the Aedes aegypti and Aedes albopictus mosquitoes. One important arbovirus disease is dengue fever. Safe, affordable and effective drugs that inhibit dengue virus (DENV) are needed to control dengue worldwide. Medicinal plants have long been considered an important alternative in the treatment of various diseases, including dengue fever. The aim of this study was to use databases PubMed, Google Scholar and Research Gate to identify plants of different tribes from different places that can be used for the treatment of DENV infection and open supportive care for dengue. Previous studies have shown antiviral activity of medicinal plants against DENV. The aim of the present study is to discover plants from different tribes from different places that can be used to treat DENV infection and provide open supportive care against dengue. The recommended reporting guidelines for systematic reviews and meta-analyses (PRISMA statement) were followed in the search and selection of articles using the PubMed database, Google Scholar and Research Gate. The final selection was made after careful consideration and up to 85 publications that met the inclusion criteria. It is said that different plants from different tribes and geographical locations can be used to treat DENV infection.

We have particularly investigated the correlation law of the effect of different carbon black fillings on the hyper-elastic mechanical behavior of natural rubber by conducting uniaxial tensile tests over a wide range of deformations with different volume fractions of carbon black fillings (0%, 4.7%, 8.9%, 12.8%, 16.4%, 19.7%, 22.7%, 25.2%). The results show that the stress-strain curve for carbon black filled rubber increases with the amount of filling, meaning that the rubber gradually becomes "harder". We explore the correlation between the carbon black filling volume and the parameters of the Yeoh constitutive model by examining the Yeoh constitutive model to characterize the hyper-elastic mechanical behavior of rubber with different carbon black fillings. A quantitative relationship between the material parameters and the carbon black filling volume in the Yeoh constitutive model is presented. A method for calculating the material parameters of the Yeoh constitutive model is developed and it predicts the correlation between the hyper-elastic properties of rubber and the volume fraction of carbon black filling.

Men are more likely to develop cancer than women. In fact, male predominance is one of the most consistent cancer epidemiology findings. Additionally, men have a poorer prognosis and an increased risk of secondary malignancies compared to women. These differences have been investigated in order to better understand cancer and to better treat both men and women. In this review, we discuss factors that may cause this gender difference, focusing on urothelial bladder cancer (UBC) pathogenesis. We consider physiological factors that may cause higher male cancer rates, including differences in X chromosome gene expression. We discuss how androgens may promote bladder cancer development directly by stimulating bladder urothelium and indirectly by suppressing immunity. We are particularly interested in natural killer (NK) cells because they are important, but often overlooked anti-cancer lymphocytes.

The aim of the research was a comprehensive evaluation of concrete using the EIPI method. In the evaluation the compressive strength of concrete and its durability properties represented by sorptivity and air permeability were taken into account. Since copper slag waste with increased natural radioactivity was used in the assessed concrete, additional evaluation was carried out taking into account the influence of natural radioactivity within the performance index. Also the reference concrete, which was made without the use of copper slag waste, was evaluated for comparative purposes. In order to make the evaluation as comprehensive as possible, the concrete made with the use of three types of cement was subjected to the assessment: CEM I, CEM II and CEM III. The results show that in both approaches the best result was achieved by concrete with CEM III cement. If natural radioactivity is not taken into account in the evaluation, the best result is obtained by concrete made with copper slag waste, and if radioactivity is considered, the best result is obtained with concrete without addition of the waste. It follows from the above that although natural radioactivity has a significant impact on the EIPI evaluation result, the decisive factor is still the type of cement.

Over the past decade, the One Strain Many Compounds (OSMAC) approach has been established for silent gene cluster activation and elicitation of secondary metabolite production, but so far the full secondary metabolome of a biosynthetically promising bacterium has not been elucidated yet. Here, we investigate the ability of seven categories of OSMAC conditions to enhance the diversity of new mass features from bacterial strains with little literature coverage but high biosynthetic potential. The strains Bacillus. amyloliquefaciens DSM7, Corallococcus. coralloides DSM2259, Pyxidicoccus. fallax HKI727, Rhodococcus. jostii DSM44719, and Streptomyces. griseochromogenes DSM40499 were selected after genome mining with antiSMASH. After cultivation under OSMAC conditions, the generated extracts were subjected to LC-MS and MZmine analysis to determine new mass features and evaluate the tested culture conditions. 4 predicted compounds, bacillibactin, desferrioxamine B, myxochelin A, and surfactin, were identified and up to 147 new mass features were detected in the generated extracts, which greatly surpasses the number of predicted gene clusters. Among the new mass features are bioactive compounds that were so far unreported for the strains such as cyclo-(Tyr-Pro) from DSM7 and nocardamin from DSM2259. Furthermore, the tested culture conditions were evaluated regarding their suitability for the generation of new mass features from the selected strains and promising new starting points for further screenings are postulated. Especially culture conditions with little prior literature coverage are responsible for the activation of predicted gene clusters

Protective coatings, in recent years also from nanocomposite formulations, are commonly applied onto architectural stone and stone artefacts, mainly to prevent absorption into the porous stone structure of condensed water and dissolved atmospheric pollutants. While standard protocols are available to assess a coating’s performance, understanding the response of the coating-stone system is a complex task, due to the interplay of various factors determining the overall behaviour. Characterization techniques allowing to correlate the extent and nature of surface modification upon treatment with the most relevant physical properties (i.e water absorption and surface wettability) are thus of great interest. Electrokinetic analysis based on streaming current measurements, thanks to its sensitivity towards even minor changes in the surface chemical composition, may fulfil such requirement. Indeed, by involving the interaction with a testing aqueous electrolyte solution, this technique allows to probe not only the outer surface but also the outermost layer of the pore network, which plays a crucial role in the interaction of the stone with condensed atmospheric water. In this work a correlation was found between the extent of surface modification, as determined by streaming current measurements, surface wettability and capillary water absorption of 6 coating-lithotype combinations (3 lithotypes and 2 nanocomposites).

Margarines are W/O emulsions with minimal fat and are heat treated when used for baking. Lipid oxi-dation has been identified as the major deterioration process of margarines and addition of antioxidants is necessary. Consumers are increasingly demanding that chemical antioxidants in foods be replaced by natural preservatives. A multivariate statistical study gave us oxidative stability depending on the com-position of 20 different commercial margarines and an analysis of the principal components allowed us to classify and select eight of them. This study analyzes the antioxidant capacity of six different natural ground herbs (Curcuma longa, Illicium verum, Rosmarinus officinalis, Taraxacum officinale, Thymus piperella and Thymus vulgaris) on the oxidative stability of eight selected margarines. In order to evalu-ate the oxidative stability, we determine the induction period (IP) with Rancimat assays at 120 ºC with 1.5 hours of suppression. As results, Rosmarinus officinalis increases the IP value by 73.17% with respect to its basal values, Curcuma longa, Thymus vulgaris and Thymus piperella increases it between 17% and 26% and Taraxacum officinale together with Illicium verum reduces it between 19% and 34% respec-tively. A multiple linear regression model approach shows that IP has a positive correlation with SFA, PUFA,  acids, MUFA/PUFA ratio and antioxidant activity.

Crowdsourced Data (CSD) generated by citizens is becoming more popular as its potential utilisation in many applications is increasing due to its currency and availability. However, the quality of CSD, including its relevance, is often questioned as the data is not generated by professionals nor follows standard data collection procedures. The quality of CSD can be assessed according to a range of attributes including its relevance. Information relevance has been explored through using in Geographic Information Retrieval (GIR) techniques to identify relevant information. This research tested a relevance assessment approach for CSD by adapting relevance assessment techniques available in the GIR domain. The thematic and geographic relevance were assessed using the Term Frequency-Inverse Document Frequency (TF-IDF), Vector Space Model (VSM) and Natural Language Processing (NLP) techniques. The thematic and geographic specificities of the queries were calculated as 0.44 and 0.67 respectively, which indicates the queries used were more geographically specific than thematically specific. The Spearman's rho value of 0.62 indicated that the final ranked relevance lists showed reasonable agreement with a manually classified list and confirmed the potential of the approach for CSD relevance assessment for other possible crowdsourced data analysis.

Gastric cancer, also known as stomach cancer, is a cancer which develops from the lining of the stomach. Accumulated evidences and epidemiological studies have been indicated that natural products play an important role in gastric cancer prevention and treatment, although its mechanism of action did not elucidate yet. Particularly, experimental studies have been showed that natural products displayed a protective effect against gastric cancer via numerous molecular mechanisms such as suppression of cell metastasis, anti-angiogenesis, inhibition of cell proliferation, induction of apoptosis, and modulation of autophagy. Although chemotherapy remains the standard treatment for advanced gastric cancer along with surgery, radiation therapy, hormone therapy and immunotherapy, but its adverse side effects including neutropenia, stomatitis, mucositis, diarrhea, nausea, and emesis are well documented. Additionally, intake of naturally occurring phytochemicals could increase the efficacy of gastric chemotherapy and chemotherapeutics resistance. However, natural product structural stability and powerful bioactivity are important to develop novel treatments for gastric cancer that may minimize such adverse effects. Therefore, the purpose of this review is to summarize the potential therapeutic effects of natural products on prevention and treatment of gastric cancer with intensive molecular mechanisms of action, bioavailability, and safety efficacy.

As the problem of light pollution becomes more serious, more and more scholars pay attention to this issue and carry out related research. In the perspective of cities, the measurements of light pollution mainly focus on the brightness of the sky or artificial lighting on the ground. However, there is lack of research on the whole urban space. With the two-dimensional brightness analyses, this paper processes the changes of the light environment of the whole urban space into image quantization. It gets the 3D and 2D light environment changes of luminance distribution, color temperature distribution and chromaticity in the three space layers, the ground layer, the urban canopy layer and the sky layer, from dusk with natural light to night with artificial lighting completely. It is found that the brightness difference between the light environments among the three city levels gradually reduces with the measuring time, and the final values maintain at 0.11~0.25 cd/m². In the ground layer, the light environment is mainly affected by the lighting facilities, and vegetation can prevent the light from scattering up. The light environment of the urban canopy layer is the brightest in the whole city space and has the largest influence on the sky layer. The color concentrates in the range of yellow and red. The color temperature near the ground distributes in 3000K~15000K, and near the sky distributes in 2300K~2700K which is warmer than the natural night sky. The sky brightness of Dalian city is about 951 times than the natural night sky.

The main restriction of the Semantic Web is the difficult of the SPARQL language, that is necessary to extract information from the Knowledge Representation also known as ontology. Making the Semantic Web accessible for people who do not know SPARQL, is essential the use of friendlier interfaces and a good alternative is Natural Language. This paper shows the implementation of a friendly prototype interface to query and retrieve, by voice, information from website building with the Semantic Web tools. In that way, the end users avoid the complicated SPARQL language. To achieve this, the interface recognizes a speech query and converts it into text, it processes the text through a java program and identifies keywords, generates a SPARQL query, extracts the information from the website and read it in voice, for the user. In our work Google Cloud Speech API makes Speech-to-Text conversions and Text-to Speech conversions are made with SVOX Pico. As results, we have measured three variables: The success rate in queries, the response time of query and a usability survey. The values of the variables allows the evaluation of our prototype. Finally the interface proposed provides us a new approach in the problem, using the Cloud like a Service, reducing barriers of access to the Semantic Web for people without technical knowledge of Semantic Web technologies.

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.

Herpes simplex virus (HSV) infections can be treated with direct acting antivirals like acyclovir and foscarnet, but long-term use can lead to drug resistance, which motivates research into broadly-acting antivirals that can provide a greater genetic barrier to resistance. Photodynamic inactivation (PDI) employs a photosensitizer, light, and oxygen to create a local burst of reactive oxygen species that inactivate microorganisms. The botanical plant extract Orthoquin^TM is a powerful photosensitizer with antimicrobial properties. Here we report that Orthoquin also has antiviral properties. Photoactivated Orthoquin inhibited herpes simplex virus type 1 (HSV-1) and herpes simplex virus type 2 (HSV-2) infection of target cells in a dose-dependent manner, across a broad range of sub-cytotoxic concentrations. HSV inactivation required direct contact between Orthoquin and the inoculum, whereas pre-treatment of target cells had no effect. Orthoquin did not cause appreciable damage to viral capsids or pre-mature release of viral genomes as measured by qPCR for the HSV-1 genome. By contrast, immunoblotting for HSV-1 antigens in purified virion preparations suggested that higher doses of Orthoquin had a physical impact on certain HSV-1 proteins that altered protein mobility or antigen detection. Orthoquin PDI also inhibited the non-enveloped adenovirus (AdV) in a dose-dependent manner, whereas Orthoquin-mediated inhibition of the enveloped vesicular stomatitis virus (VSV) was light-independent. Together, these findings suggest that broad antiviral effects of Orthoquin-mediated PDI may stem from damage to viral attachment proteins.

Tigrai region is one of the potential beekeeping areas in Ethiopia, which is endowed with diversified honeybee plant species. However, its honeybee plants are deforested and degraded due to natural and anthropogenic pressures. Area exclosures (AEs) has been practicing for the last three decades restore degraded habitats of the plant species in Ethiopia. Empirical data on the effectiveness of AE is still limited for restoration of honey bee plant species; this study was conducted to assess the roles of AE for species composition, density, and diversity and regeneration status of honeybee floras. Sixty quadrats were installed, 36 in AE and 24 in CGL (communal grazing lands) using a systematic sampling method. The study showed that a total of 42 honey bee plant species belonging to 23 families in AE and 33 species belonging to 17 families in CGL were recorded. The study also indicated a significant increase in the abundance, diversity, regeneration and the structure of the honey bee plant species was found in the AEs. The list presented herein provides a guide to stakeholders in establishing of AE for the foraging resource of honeybee in order to enhance the abundance, diversity and regeneration and structure. Thus, AE has made a significant contribution to solving the shortage of honeybee forages in the beekeeping industry. Therefore, the development of beekeeping is integrated with conservation of natural resources.

Climate information can help vulnerable populations anticipate disasters before they happen and enable communities prepare for and cope with them. A complementary log-log regression model based on quantitative study in coastal communities in Tanzania was used to assess the likelihood of the rural poor, rural non poor, urban poor, and urban non poor to receive early warning information about flood, drought and other disasters. Individuals in the urban poor category were 35% less likely to receive early warning information about flood, drought and other disasters whereas urban non-poor residents were 49% more likely to receive same. This disadvantage to the urban poor persists even when adaptive capacity, geographical location and socio-environmental factors are accounted. Nuclear households consisting of a male head and female partner who have children or not had higher likelihood of receiving early warning information on flood, drought and other disasters (OR = 1.47, p < 0.001) compared with their counterparts in female-centred households (no husband or male partner). Residents with tertiary education were more likely (OR = 1.91, p < 0.001) to report that they had received early warning information about flood, drought and other disasters compared with their counterparts without any formal education. This zero-order relationship was completed mediated by geographical location and socio-environmental factors in the multivariate model. The results underline the key role access to climate- and disaster-related information play in enhancing adaptive capacity to reduce vulnerability to natural hazards, as well as the importance of targeting the most vulnerable households in policy interventions to improve resilience in the face of a changing climate.

The disaster response operational strategies requires tool that a may provide time bound clear picture of potential spots. Natural disaster sometimes comes slowly like increment of water level resulting flood or early warning of tsunami whereas in manmade disasters like 1CBRNE attack or chemical accident or industrial structure collapse or leakage through a pipeline of some toxic hazardous gas requires very accurate and quick response strategies. 2Unmanned Aerial System is commercially used tools present in the market and also used by military organization for various operations throughout the world. The accuracy and time bound pictorial representation of the spots by these tow tools makes them very useful for providing clear picture of potential disaster sites and enabling decision makers to take decision on these representation. Apart of these the potential to deliver important material faster than any other mode also makes these equipment and technology a very important asset for making disaster risk reduction strategies. This paper elaborates the efficacy and utility of Unmanned Aerial System or Drones in developing robust and time bound strategies for disaster risk reduction. This paper also evaluates some experiences and describes some initiatives using Unmanned Aerial System to support disaster risk reduction strategies and post disaster decision making efforts.

Radon (²²²Rn) is the second most common type of lung cancer after smoking. As radon poses a significant risk to human health, radon-affected areas should be to ensure people’s awareness of risk and remediation. The primary goal of this research was to investigate the local natural radioactivity (in soils, water and indoors) because of the presence of tuff outcrops (from middle lower Pleistocene volcanic activity) that naturally produce radioactive gas radon at Cerveteri (Rome, Central Italy). The study area is characterized by the presence of several funerary sites pertaining to the Etruscan Necropolis of Cerveteri, which extends over a volcanic rock plateau. The results of the radon survey highlighted moderate (>16000 Bq/m³) but localized anomalies in soils and medium low (< 200 Bq/m³) values of indoor radon excepting some cases exceeding the threshold (> 300 Bq/m³) recommended by 2013/59 Euratom Directive. Although for thoron (²²⁰Rn) effects on human health, there exist no clinical data, the study of ²²⁰Rn average activity concentration in the soil gas survey has revealed new insights for the interpretation of radon sources that can affect dwellings, even taking into account the considerable difference in the half-lives of the ²²²Rn and ²²⁰Rn.

Italian Directives recommends the good quality of natural mineral waters but literature data assert a potential risk from several microorganisms colonizing wellsprings and mineral water bottling plants. Aim of study is the identification of microorganisms from spring waters (SW) and bottled mineral waters (BMW) samples. Methods: Routine microbiological indicators, Legionella spp., Nontuberculous mycobacteria (NTM), protozoa (FLA) and physical-chemical parameters were assessed in 24 SW and 10 BMW samples performing culture methods and molecular tests as PCR and qPCR. Results: In 33 out of 34 samples no cultivable bacteria were isolated with the exception of 83 CFU/L of Mycobacterium gilvum, detected in one warm rich-mineralized SW. qPCR showed the presence of Legionella genomic units in 24% of samples (mean 2,9x10²±1,7x10² GU/L) and NTM genomic units in 18% of samples (mean 5,7x10^3±4,1x10³ GU/L). Vermamoeba vermiformis and Acanthamoeba polyphaga were recovered respectively in 70% of BMW samples (counts from 1,3x10³ to 1,2x10⁵) and 42% of SW samples (counts from 1,1x10³ to 1,3x10⁴). Vahlkampfia spp. was detected in 42% of SW and 70% of BMW samples (mean 1,3x10⁴ ±2,9x10³ GU/L). Conclusion: The study highlights a low rate of microbial risk and the importance of risk assessment in natural mineral waters.

The gravitational constant is equivalent to natural units in its six unit dimensions. Evaluating the classical formulas in each unit dimension shows how inputs of mass and radius are transformed into the correct unit dimensions and magnitude of gravitational potential. Mass and radial distance are equivalent proportions of the Planck scale as the potentials they produce. Gravitational potentials of velocity, acceleration, energy, and force are proportional to a radial density limit of one Planck mass per Planck length of radial distance.

Streptomyces, being one of the most promising genera due to its ability to synthesize a variety of bioactive secondary metabolites of pharmaceutical interest, here studied in relation to its genomic and metabolomic potential. Coinciding with the increase in sequenced data, mining of bacterial genomes for biosynthetic gene clusters (BGCs) has become a routine component of natural product discovery. Herein, we describe the isolation and characterization of a Streptomyces tendae VITAKN with quorum sensing inhibitory activity (QSI) that was isolated from southern coastal parts of India. The nearly complete genome consists of 8,621,231bp with a GC content of 72.2%. Utilizing the BiG-SCAPE-CORASON platform, a sequence similarity network predicted from this strain was evaluated through sequence similarity analysis with the MIBiG database and existing 3,365 BGCs predicted by antiSMASH analysis of publicly available complete Streptomyces genomes. Crude extract analyzed on LC-HRMS/MS and Global Natural Product Social Molecular Networking (GNPS) online workflow using dereplication resulted in the identification of cyclic dipeptides (2,5-diketopiperazines, DKPs) in the extract, which are known to possess QSI activity. Our results highlight the potential use of genomic mining coupled with LC-HRMS/MS and bionformatic tools (GNPS) as a potent approach for metabolome studies in discovering novel QSI lead compounds. This study also provides the biosynthetic diversity of these BGCs and an assessment of the predicted chemical space yet to be discovered.

The present paper reviews evidence for ecological evolution of Montiaceae. Montiaceae (Portulacineae) comprise a family of ca. 275 species and ca. 25 subspecific taxa of flowering plants distributed mainly in extreme western America, with additional endemism elsewhere, including other continents and islands. They have diversified repeatedly across steep ecological gradients. Based on narrative analysis, I argue that phylogenetic transitions from annual to perennial life history have been more frequent than suggested by computational phylogenetic reconstructions. I suggest that a reported phylogenetic correlation between the evolution of life history and temperature niche is coincidental and not causal. I demonstrate how statistical phylogenetic comparative analysis (PhCA) missed evidence for marked moisture niche diversification among Montiaceae. I discount PhCA evidence for the relation between Montiaceae genome duplication and ecological diversification. Based on the present analysis of Montiaceae evolution, I criticize the premise of the prevalent statistical approach to PhCA, which tests Darwinian deterministic hypotheses against stochastic evolutionary null models. I discuss theoretical/empirical evidence that evolution is neither stochastic, nor Darwinistically-determined, but idiosyncratic. Idiosyncraticity describes the outcome of a stochastically perturbed nonlinear chaos-like process. The Principle of Evolutionary Idiosyncraticity (PEI) is based on the evolutionary theory of Natural Drift, which maintains that determinism in evolution is a property of the organism and not, as maintained by the theory of Natural Selection, its traits or its milieu. This determinism is characteristic of chaotic functions, which are absolutely determinate, generate self-similarity, but remain absolutely unpredictable. PEI explains precisely observations that evolution proceeds not linearly, but chaotically, producing both quasi-linear fractal-like patterns and non-linear jumps. PEI has ramifications for all areas of macroevolutionary research. In particular, it demonstrates both the fallacy and futility of the statistical PhCA approach that interprets evolutionary causes in terms of evolutionary correlations. However, statistical methods of PhCA can be applied heuristically and fruitfully to reveal idiosyncraticity and discover evolutionary novelty. This, in turn, is demonstrated by the emergence of statistical anomalies in evolutionary analyses of Montiaceae.

In the present paper, the comparison is conducted between three classical shell theories as applied to the linear vibrations of single-walled carbon nanotubes (SWCNTs); specifically, the evaluation of the natural frequencies is conducted via Donnell, Sanders and Flügge shell theories. The actual discrete SWCNT is modelled by means of a continuous homogeneous cylindrical shell considering equivalent thickness and surface density. In order to take into account the intrinsic chirality of carbon nanotubes (CNTs), a molecular based anisotropic elastic shell model is considered. Simply supported boundary conditions are imposed and complex method is applied to solve the equations of motion and to obtain the natural frequencies. Comparisons with the results of molecular dynamics simulations available in literature are performed to check the accuracy of the three different shell theories, where Flügge shell theory is found to be the most accurate. Then, a parametric analysis evaluating the effect of diameter, aspect ratio and number of waves along the longitudinal and circumferential directions on the natural frequencies of SWCNTs is performed in the framework of the three different shell theories. Assuming the results of Flügge shell theory as references, it is obtained that Donnell shell theory is not accurate for relatively low longitudinal and circumferential wavenumbers, for relatively low diameters and for relatively high aspect ratios. On the other hand, it is obtained that Sanders shell theory is very accurate for all the considered geometries and wavenumbers, and therefore it can be correctly adopted instead of the more complex Flügge shell theory for the vibration modelling of SWCNTs.

The objective is to study the local perceptions on the conservation of wild chimpanzees (Pan troglodytes verus) in the Réserve Naturelle Communautaire de Dindéfélo (RNCD), southeast of Senegal, to design specific actions to improve conservation management. We conducted 338 semi-structured interviews in three main villages of RNCD. Three-fourths of the population were farmers. Of those interviewed, 29% received elementary education. Two of the three villages participated in a project to plant trees as fences. On average, 66% of the respondents were animists. Of the respondents who were afraid to see a chimpanzee, 68% answered because they attack. Seventy-seven percent washed their clothes in the forest river because there was more water than in the village wells. Of the interviewees who threw the old clothes into the forest, 50% did it due to tradition. Ninety-six percent of respondents stated that chimpanzees do not feed from their crops. The main problems of the locals with the Reserve were lack of water and basic resources and not been allow to cut trees in protected areas. There were significant relationships between education (1 relationship), environmental project (4 relationships) and animism (11 relationships) with local perceptions. The 93% of the respondents who had the traditional belief that “if the old clothes were burnt, children would become sick” feel fear of chimpanzees, while those who did not have this animistic belief the 6% are afraid (χ² = 1.57, P < 0.02). These local perceptions allow us to design specific course of action to improve chimpanzee conservation and sustainable coexistence in this complex period of the Anthropocene.

Requirements are predominantly written in Natural Language (NL), which makes them accessible to stakeholders with varying degrees of experience, as compared to a model-based language which requires special training. However, despite its benefits, NL can introduce ambiguities and inconsistencies in requirements, which may eventually result in system quality degradation and system failure altogether. The system complexity that characterizes current systems warrants an integrated and comprehensive approach to system design and development. This need has brought about a paradigm shift towards Model-Based Systems Engineering (MBSE) approaches to system design and a departure from traditional document-centric methods. While, MBSE shows great promise, the ambiguities and inconsistencies present in NL requirements hinder their conversion to models directly. The field of Natural Language Processing (NLP) has demonstrated great potential in facilitating the conversion of NL requirements into a semi-machine-readable format that enables their standardization and use in a model-based environment. A first step towards standardizing requirements consists of classifying them according to the ``type'' (design, functional, performance, etc.) they represent. To that end, a language model capable of classifying requirements needs to be fine-tuned on labeled aerospace requirements. This paper presents the development of an annotated aerospace requirements corpus and its use to fine-tune BERT$_\text{BASE-UNCASED}$ to obtain aeroBERT-Classifier: a new language model for classifying aerospace requirements into design, functional, or performance requirements. A comparison between aeroBERT-Classifier and bart-large-mnli (zero-shot text classification) showcased the superior performance of aeroBERT-Classifier on classifying aerospace requirements despite being fine-tuned on a small labeled dataset.

The rhizosphere is a rich source of actinomycetes which can produce several potential biologically-active secondary metabolites. The principal goals for this research are to extract, purify and characterize the bioactive secondary metabolites produced by three different strains of actinomycetes isolated from the rhizosphere of rosemary, black locust and olive. The plant growth-promoting effect (PGPE) of the studied strains of actinomycetes on Ocimum basilicum L. (basil) and disease-control effect on necrotic stem lesions of “black leg” caused by Fusarium tabacinum on basil, were in silico evaluated. The cell-free culture filtrates from the studied actinomycetes isolates were evaluated in vitro for their antimicrobial activity against some common phytopathogens. The secondary metabolites obtained from the cell-free culture filtrates have been chemically characterized using high‐resolution electrospray ionization of liquid-chromatography/mass-spectrometric detection (ESI-(HR)Orbitrap-MS). Results of in silico trial showed that all studied isolates demonstrated PGPE on basil seedlings improving some Eco-physiological characteristics and reduced the disease incidence of F. tabacinum. The extracted metabolites from the studied actinomycetes demonstrated antimicrobial activity in Petri-plates assay. The chemical analysis revealed the presence of totally 20 different components. This research emphasizes how valuable the examined isolates are for producing bioactive compounds, indicating their putative antimicrobial activity and their potential employment as fungal-biocontrol agents. In particular, the obtained results revealed the possibility of green-synthesis of some important secondary metabolites such as N-Acetyl-L-histidinol, Rhizocticin A and Eponemycin from actinomycetes. The bioactive metabolites may be successively used to develop novel bio-formulations for both crop protection and/or PGPE.

The current emergency due to the worldwide spread of the COVID-19 caused by the new SARS-CoV-2 is a great concern for global public health. Already in the past, the outbreak of severe acute respiratory syndrome (SARS) in 2003 and Middle Eastern respiratory syndrome (MERS) in 2012 demonstrates the potential of coronaviruses to cross-species borders and further underlines the importance of identifying new-targeted drugs. An ideal antiviral agent should target essential proteins involved in the lifecycle of SARS-CoV. Currently, some HIV protease inhibitors (i.e., Lopinavir) are proposed for the treatment of COVID-19, although their effectiveness was not yet assessed. The main protease (Mpro) provides a highly validated pharmacological target for the discovery and design of inhibitors. We identified potent Mpro inhibitors employing computational techniques that entail the screening of a Marine Natural Product (MNP) library. MNP library was screened by hyphenated pharmacophore model, and molecular docking approaches. Molecular dynamics and re-docking further confirmed the results obtained by structure-based techniques and allowed to highlight some crucial aspects. Seventeen potential SARS-CoV-2 Mpro inhibitors have been identified among the natural substances of marine origin. As these compounds were extensively validated by a consensus approach and by molecular dynamics, the likelihood that at least one of these compounds could be bioactive is excellent.

The present state of the natural environment is significantly influenced by the construction sector. Due to the large amounts of consumed natural resources and materials as well as the high volume of emitted pollutants, the building industry is considered to have a key influence in achieving a global sustainable development. A considerable part of the ecological impact of the built environment is influenced by the energy consumed for creating appropriate indoor conditions as well as by the greenhouse gases that are emitted during the operation stage of a building’s life cycle. Therefore, the energy performances of existing buildings must be significantly improved in the near future. This paper analyzes the influence of the thermal insulation thickness of walls on the linear thermal transmittances and the heating demand of an existing building. The resulted values show that while increasing the insulation of the walls leads to a serious heat demand reduction, a deep renovation of the building cannot be achieved solely by using this solution.

The natural frequency of buildings decreases during a strong-motion earthquake, and the structure loses its stiffness. As a result, understanding the damaging process in the structure owing to changes in structural properties is critical during a seismic excitation. The time-frequency technique can detect the damaged building’s time-varying frequency contents. Wigner distributions (WD), Wigner-Ville distributions (WVD), pseudo-Wigner-Ville distributions (PWVD), smoothed pseudo-Wigner-Ville distributions (SPWVD), and synchrosqueezing transforms (SST) have all become popular in recent years for a variety of earthquake engineering applications, including building damage detection. This study proposes the local maximum synchrosqueezing transform (LMSST) for detecting frequency shifts in buildings during strong earthquakes. The data presented in the research show that the suggested method outperforms as compared to the conventional time-frequency methods for detecting frequency shifting in earthquake-damaged structures.

Depressive disorder is a disease that causes a decrease in daily function, and the prevalence of depressive disorder in Korea is the highest among OECD countries. However, due to lack of manpower and negative social awareness, timely treatment is not being performed properly. As a solution to this, AI counseling chatbots are emerging, and it is essential to use labeled datasets to create chatbots. Currently, many countries around the world, including Korea, use the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition, DSM-5, but there are no nine labeled datasets according to the DSM-5 depression disorder diagnosis criteria. This study collects sympathetic datasets, analyzes morphemes using Kind Korean Morpheme Analyzer and augments and builds a word dictionary using Word2Vec. As a result, we have labeled the dataset with nine criteria for diagnosing DSM-5 depressive disorder, which will enhance the performance of the counseling chatbot.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women, characterized by fluid-filled sacs in the ovaries and various symptoms including high androgen levels, endometrial irregularities, and cysts. While the cause of PCOS is unknown, it has been linked to genetic, endocrine, and metabolic factors, and there are several treatment options, including lifestyle modifications, medications, and surgery. Natural products, such as medicinal plants and fruits, are being explored as potential treatments for PCOS due to their bioactive compounds with pharmacological effects related to antioxidant, antimicrobial, anticancer, and antidiabetic properties. Some of these compounds improve insulin sensitivity, reduce inflammation, and enhance glucose metabolism, which is beneficial for women with PCOS. This review examined the effects of natural products on PCOS, including their effects on ovarian histological changes, blood glucose, sex hormones, and lipid profile, based on animal and human studies. This study suggests that the use of natural products as complementary medicine can be a promising resource for the development of effective therapeutics for PCOS, but that further research is needed to fully understand their benefits

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.

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.

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.

This review uses the National Cancer Institute (NCI) COMPARE program to establish an extensive list of heterocyclic iminoquinones and quinones with similarities in differential growth inhibition across the 60-cell line panel of the NCI Developmental Therapeutic Program (DTP). Many natural products and synthetic analogues are revealed, as potential NAD(P)H:quinone oxidoreductase 1 (NQO1) substrates through correlations to dipyridoimidazo[5,4-f]benzimidazoleiminoquinone (DPIQ), and as potential thioredoxin reductase (TrxR) inhibitors, through correlations to benzo[1,2,4]triazin-7-ones and pleurotin. The strong correlation to NQO1 infers the enzyme has a major influence on the amount of active compound with benzo[e]perimidines, phenoxazinones, benz[f]pyrido[1,2-a]indole-6,11-quinones, seriniquinones, kalasinamide, indolequinones, and furano[2,3-b]naphthoquinones, hypothesized as prodrugs. Compounds with very strong correlations to known TrxR inhibitors had inverse correlations to the expression of both reductase enzymes, NQO1 and TrxR, including naphtho[2,3-b][1,4]oxazepane-6,11-diones, benzo[a]carbazole-1,4-diones, pyranonaphthoquinones (including kalafungin, nanomycin A, and analogues of griseusin A), and discorhabdin C. Quinoline-5,8-dione scaffolds based on streptonigrin and lavendamycin can correlate to either reductase. Inhibitors of TrxR are not necessarily (imino)quinones, e.g., parthenolides, while oxidizing moieties are essential for correlations to NQO1, as with the mitosenes. Herein, an overview of synthetic methods and biological activity of each family of heterocyclic imino(quinone) is provided.

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.

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.

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.

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

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 use of intelligent sensor-based packaging in food products provide quick evaluation of the quaility of the food. This study was done to develop bio-based color sensor from surimi-based color sensor incorporated with sappan wood extract (SWE) for smart food packaging. The SWE with different concentration (0.15%, 0.25%, and 0.35%) was incorporated to the myofibrillar protein-based edible film. The sappan wood-surimi edible film (SSEF) was subjected to physical properties analysis and the color changes at different pH values and soaking time at different condition were evaluated. Based on the results, different concentration of the SWE significantly (p&lt;0.05) affected the physical properties of the film. With the increasing of pH values, the darkness, redness, and blueness of the film was increased. Based on the evaluation of the SSEF with different soaking condition, the color changes of the film in acidic condition were more stable than in neutral and alkaline condition. The results from this study showed that SSEF have the possibilities to be used as a smart food packaging possessing the capabilities to act as color sensor due to its sensitivity to the changes in pH condition of the product.

During the last two years the COVID-19 pandemic has affected the world population in several ways. An important increase in mental health problems is a consequence of this pandemic that is ubiquitous worldwide. In this work we study the effect of the pandemic on the mental health of a population of teenagers and youth based on the analysis of natural language processing, machine learning algorithms and expert knowledge. The data analysed was obtained from a chat helpline called Safe time from theIt Get’s Better Foundation in Chile. The data consists of 10,986 conversations gathered from 2018 until 2020 between volunteers from the foundation and users of the platform. We compared the conversationsbefore and during the pandemic in terms of their thematic content. Our analysis found: a significantdecrease in self-image appreciation during the pandemic; a significant decrease in the quality of personalrelationships during the pandemic, and a significant increase of performance appreciation.

Streptomyces sp. HNS054, which was previously isolated from a marine sponge, demonstrates vigorous growth and facile genetic modification. This study explores its potential as a marine ac-tinomycete chassis through complete genome sequencing and genetic engineering. With a 7.5 Mb genome containing 6678 predicted genes, 21 secondary metabolic biosynthetic gene clusters (BGCs), and 8 common site-specific recombination (SSR) system attB loci, HNS054 shows a close phylogenetic relation to S. griseoincarnatus strain RB7AG. Utilizing multiplexed site-specific ge-nome engineering (MSGE) and the CRISPR/Cas9 method, engineered strains derived from HNS054 (with three copies of the target BGCs) produce higher amounts of aborycin and ac-tinorhodin than S. coelicolor M1346 (containing three copies of the same BGCs). HNS054 stands out for its remarkable characteristics, including salt tolerance, rapid growth, and compatibility with synthetic biology tools, and positions it as a promising candidate for developing marine ac-tinomycete hosts to enhance secondary metabolite production.

Abstract: One of the most significant medical advancements of the 20th century was the discovery of antibiotics, which continue to play a vital tool in the treatment and prevention of diseases in humans and animals. However, the imprudent use of antibiotics in all fields of One-Health and concerns about antibiotic resistance among bacterial pathogens have raised interest in antibiotic use restrictions on a global scale. Despite the failure of conventional antimicrobial agents, only about 15 new antibiotics have been introduced clinically since year 2000 to date. Moreover, there have been reports of resistance to some of these new antibiotics. This has necessitated a need to search for an alternative strategy to combat antimicrobial resistant pathogens. Thus, this review compiles and evaluates the approaches—natural compounds, phage treatment, and nanomaterials—that are being used and/or suggested as the potential substitutes for conventional antibiotics. These strategies include those that focus on the enzymes or proteins, as well as the physiology and metabolism of resistant bacteria

Genetic and environmental factors including lifestyle are thought to play an important role in the pathophysiology of rheumatoid arthritis (RA). There is evidence that diet can enhance the inflammatory response in genetically predisposed individuals. On the other hand, certain types of diets are thought to alleviate RA symptoms due to their anti-inflammatory and antioxidant activities. Also, natural compounds with potential effectiveness in RA management belong to different chemical classes such as flavonoids, polyphenols, carotenoids, and alkaloids with their antioxidant characteristics. In this paper, the nutritional approaches to prevent or extenuate the disease progress were examined in the light of current literature. Mediterranean and vegan diets equally have been shown to exhibit positive effects on RA as the consumption of dietary fiber, antioxidants and anti-inflammatory compounds from fruits, vegetables, grains, nuts, and seeds are high. Whereas Mediterranean diet additionally includes beneficial nutrients of animal origin such as omega-3 polyunsaturated fatty acids from fish and seafood, patients on vegan diet need to be monitored closely for intake of all critical nutrients. Certain calorie restrictions and intermittent fasting diets have been shown to benefit RA patients although there is an obvious need for further studies to establish solid evidence-based recommendations and guidelines. The research data available strongly suggest that dietary approaches may help delay the onset of RA and/or improve symptoms and thus nutrition should be routinely addressed to facilitate management of the disease.

Kinetic modeling is an essential tool in systems biology research, enabling the quantitative analysis of biological systems and predicting their behavior. However, the development of kinetic models is a complex and time-consuming process. In this article, we propose a novel approach called KinModGPT, which generates kinetic models directly from natural language text. KinModGPT employs GPT-3 as a natural language interpreter and Tellurium as an SBML generator. We demonstrate the effectiveness of KinModGPT in creating SBML models from complex natural language descriptions of biochemical reactions. KinModGPT successfully generates valid SBML models from a range of natural language model descriptions of metabolic pathways, protein-protein interaction networks, and heat shock response. This article demonstrates the potential of KinModGPT in kinetic modeling automation.

Transient analysis of gas flow in pipeline was studied. Finite Element Method based on ANSYS FLOTRAN was used to account for changes in pressure, temperature and flow rate. Compressibility factor function of temperature and pressure was considered. For non-isothermal transient results, the pressure and the flowrate gave wave propagation as a result of slow transients created by demand condition at the outlet end of custody transfer. Results obtained were in agreement with the demand restrictions at the outlet end of custody transfer indicating that the predictions are accurate and reliable. The results demonstrated that the Finite Element Method gave accurate prediction of pressure, temperature and flowrate in transient gas studies. For steady state non-isothermal model, results showed that the magnitude of the average pressure drop was higher when pressure was predicted with constant compressibility factor, but the same average pressure drop was reduced when the pressure was predicted with variable compressibility factor, z. Since compressibility factor is a function of temperature and pressure, the above findings signifies that in the case when gas temperature does not stabilize, the prediction of pressure with isothermal model and constant compressibility factor will lead to significant errors.

Fire behavior of natural rubber latex foam under different thickness conditions(d=1,2and 5cm)were explored though a little of experiments by using the self-built small scale experimental platform. It can be shown that the flame spread law of thermally thin and thermally thickness are different. Natural rubber latex foam with thickness of 2cm show higher fire risk, which value of flame spread rate, maximum flame height, maximum mass loss rate and maximum temperature is 0.00293m/s, 851.875mm, 1.83g/s, 948K,repectively.That may because the thickness of residue formed of thermally thick materials is larger than the thin one, obstructing the contact of the natural rubber latex foam with fresh air .In addition, a special phenomenon is noticed that during the second stage, the bottom unburned zone located in the four edges(thermally thin material) and middle player(thermally thick material).

In the last decade and a half, the world has experienced the outbreak of a range of viruses such as COVID-19, H1N1, flu, Ebola, Zika Virus, Middle East Respiratory Syndrome (MERS), Measles, and West Nile Virus, just to name a few. During these virus outbreaks, the usage and effectiveness of social media platforms increased significantly as such platforms served as virtual communities, enabling their users to share and exchange information, news, perspectives, opinions, ideas, and comments related to the outbreaks. Analysis of this Big Data of conversations related to virus outbreaks using concepts of Natural Language Processing such as Topic Modeling has attracted the attention of researchers from different disciplines such as Healthcare, Epidemiology, Data Science, Medicine, and Computer Science. The recent outbreak of the MPox virus has resulted in a tremendous increase in the usage of Twitter. Prior works in this field have primarily focused on the sentiment analysis and content analysis of these Tweets, and the few works that have focused on topic modeling have multiple limitations. This paper aims to address this research gap and makes two scientific contributions to this field. First, it presents the results of performing Topic Modeling on 601,432 Tweets about the 2022 Mpox outbreak, which were posted on Twitter between May 7, 2022, and March 3, 2023. The results indicate that the conversations on Twitter related to Mpox during this time range may be broadly categorized into four distinct themes - Views and Perspectives about MPox, Updates on Cases and Investigations about Mpox, MPox and the LGBTQIA+ Community, and MPox and COVID-19. Second, the paper presents the findings from the analysis of these Tweets. The results show that the theme that was most popular on Twitter (in terms of the number of Tweets posted) during this time range was - Views and Perspectives about MPox. It is followed by the theme of MPox and the LGBTQIA+ Community, which is followed by the themes of MPox and COVID-19 and Updates on Cases and Investigations about Mpox, respectively. Finally, a comparison with prior works in this field is also presented to highlight the novelty and significance of this research work.

Since the exploitation of mineral resources results in the release of radionuclides, and consuming radionuclides affects public health in the short and long term. A case study of the environmental radiation impact from coal mining and germanium processing was carried out in southwest China. The coal mines contain germanium and uranium and have been exploited for more than 40 years. The farmlands around the site of coal mining and germanium processing have been contaminated by the solid waste and mine water in some extend since then. Samples of crops have been collected from contaminated farmlands in research area. The research area covers a radius of 5 km, in which there are 2 coal mines located. 210Pb and 210Po have been analyzed as the key radionuclides during monitoring program. The average activity concentrations of 210Pb and 210Po in the crops were 1.38 and 1.32 Bq/kg in cereals, 4.07 and 2.19 Bq/kg in leafy vegetables and 1.63 and 1.32 Bq/kg in root vegetables. The annual effective doses due to the ingestion of 210Pb and 210Po in consumed crops have been estimated for adult residents living in research area. The average annual effective dose was 0.336mSv/a, while the minimum was 0.171 mSv/a and the maximum was 0.948 mSv/a. The results show that crops grown on contaminated farmland contained an enhanced level of radioactivity concentration. Ingestion doses of local residents in research area were significantly higher than the China average level of 0.112 mSv/a, and the world average level of 0.042 mSv/a through 210Pb and 210Po in crops intake respectively.

Wound healing is rarely seen as a problem in healthy individuals; however, under certain pathophysiological conditions, this process can be impaired, leading to the emergence of chronic wounds, which are themselves a serious public health problem. This work aimed to review the most important and recent literature on the use of metallic nanoparticles, in this case those produced from plant extracts, and their application as healing agents. For this, we firstly provided an insight into the pathophysiology of the wound healing process and then the main routes for obtaining metallic nanoparticles. The methodology of synthesis, which is part of the so-called green synthesis, has been the subject of several studies reporting the use of medicinal plants as subtracts for the production of different nanoparticles (of silver, gold, and zinc). Additionally, their use as wound healing agents is close related with biological properties such as antimicrobial, anti-inflammatory, and healing. Finally, we addressed in vitro and in vivo studies reporting the efficiency of metallic nanoparticles synthesized with plant extracts and applied in different pharmaceutical forms on the wound healing process. Based on these satisfactory results, we verified that metallic nanoparticles are potential therapeutic alternatives when compared to the traditional synthetic healing agents, thus foreseeing the production of new drugs in the pharmaceutical market.

CONTEXT– Energy is widely involved in human activity and corresponding emissions of SOX, NOX and CO2 from energy generation processes affect global climate change. Clean fuels are desired by society because of their reduced greenhouse gas emissions. Hydrogen is once such candidate fuel. Much hydrogen is produced from fossil fuel, with biomass being an alternative process. OBJECTIVE– The project compared the environmental impact of hydrogen production by natural gas steam reforming vs. biomass gasification. METHOD–Environmental impact was calculated from the input and output data from life cycle inventory analysis. The impact assessment was focused on greenhouse gas emission, acidification, and eutrophication. Models of the two processes were developed and analysed in OpenLCA. The agribalyse database was used to connect inventory flow data to environmental impacts. FINDINGS– For all three metrics, biomass gasification had lower impacts than natural gas steam reforming, sometimes by large margins. For biomass gasification the silica sand production contributes most to all three impact categories, whereas for natural gas steam reforming it is the LPG extraction.

Abstract. Background: This paper investigates the propagation of behaviorally transmitted traits with negative effect on host fitness. Methods: We analyze equilibrium between genetically transmitted and behaviorally transmitted competing propagators and consider whether a behavioral propagator is linked to reproduction (e.g. vertical culture transmission), or not. We employ combined genetic and behavior-induced fitness components for hosts, while behavioral propagators have replication factors to distinguish from what’s good for the host (fitness). Results: A trait which spreads faster than its marginal host fitness contribution reduces population will establish itself. The often transient nature of laterally transmitted traits may be a defense against accumulation of deleterious traits. Laterally transmitted traits with high spreading rate often do not equalize with genetic traits, spreading outside natural selection of the hosts. Vertical transmission reduces replication rate and allows group selection against deleterious behaviorally transmitted traits. Competing mutually exclusive propagators contribute to inequality and altruism, but compete through adverse fitness since exclusivity assumes low conversion. Conclusion: Behaviorally transmitted traits, in some cases a tremendous advantage, may also be a significant problem in the development of societies.

Background: This year has seen the emergence of two major crises, a significant increase in frequency and severity of hurricanes and the COVID-19 pandemic. However, little is known as to how each of these two events have impacted the other. A rapid qualitative assessment was conducted to determine the impact of the pandemic on preparedness and response to natural disasters and the impact of past experiences with natural disasters in responding to the pandemic. Methods: Semi-structured interviews were conducted with 26 representatives of 24 different community-based programs in southern Louisiana. Data were analyzed using procedures embedded in the Rapid Assessment Procedure – Informed Community Ethnography methodology, using techniques of immersion and crystallization and focused thematic analysis. Results: The pandemic has impacted the form and function of disaster preparedness, making it harder to plan for evacuations in event of a hurricane. Specific concerns included being able to see people in-person, providing food and other resources to residents who shelter in place, finding volunteers to assist in food distribution and other forms of disaster response, competing for funds to support disaster-related activities, developing new support infrastructures, and focusing on equity in disaster preparedness. However, several strengths based on disaster preparedness experience and capabilities were identified, including providing a framework for how to respond and adapt to COVID and integration of COVID response with their normal disaster preparedness activities. Conclusions: Although prior experience has enabled community-based organizations to respond to the pandemic, the pandemic is also creating new challenges to preparing for and responding to natural disasters.

The assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing based procedure for quick updating the assessment of the population exposed to natural hazards. A relationship between satellite nightlights intensity and urbanization density from global available cartography is first assessed when all data are available. This can be used to extrapolate urbanization data at different time steps, updating exposure each time new nightlights intensity maps are available. As reliability test for the proposed methodology, the number of people exposed to riverine flood in Italy is assessed, deriving a probabilistic relationship between DMSP nightlights intensity and urbanization density from GUF database for the year 2011. People exposed to riverine flood are assessed crossing the population distributed on the derived urbanization density with flood hazard zones provided by ISPRA. The validation on reliable exposures derived from ISTAT data shows good agreement. The possibility to update exposure maps with higher refresh rate makes this approach particularly suitable for applications in developing countries, where exposure may change at sub-yearly scale.

Aim: Utilizing the subjective experience of nurse executives who have supervised nurses during a major disaster in a hospital setting, this study aims to describe the subjective experience of nurse executives (NE) who have supervised nurses’ response to major disaster. This paper will focus on strategies to support nursing response to disaster, specifically to strengthen resiliency and the ability to maintain function despite the shock of disaster, including those caused by climate changes. Methods: Semi-structured interviews were conducted with 11 hospital-based nurse executives who supervised nurses during some of the worst natural and human-made disasters in different regions of the United States. A phenomenological approach was used to analyze and describe emerging themes from qualitative data. Results: Three Nurse Executives demonstrated theme saturation for mitigation steps to augment traditional disaster readiness activities: 1.) Assessment of Human Infrastructure: Daily Skills Needed During Disaster Response, 2.) Identification and Study of Failure Points & Metrics, 3.) Strengthening Human Infrastructure: Rectifying Deficiencies), and 4.) Monitoring Metrics & Making Corrections During Conventional Periods. Conclusion: Mitigation steps may improve outcomes in hospital function during conventional times; therefore, may improve resiliency and the ability to maintain functions during major disasters, including climate change.

Natural circulation loop (NCL) systems are buoyancy-driven heat exchangers that are used in various industrial applications. The concept of passive heat exchange in NCL systems is attractive, because there is no need for an externally driven equipment (e.g., a pump) to maintain the fluid circulation. However, relying on buoyancy as the sole driving force may lead to several potential difficulties, one of which is generation of (possibly) time-varying nonlinearities in the dynamical system, where a difference in the time scales of heat transfer and fluid flow causes the flow to change from a steady-state regime to either an oscillatory regime or a flow-reversal regime, both of which are undesirable. In this paper, tools of symbolic time series analysis (e.g., probabilistic finite state automata (PFSA)) are proposed to identify selected regimes of operation in NCL systems, where the underlying principle is built upon the concept of pattern classification from measurements of fluid-flow dynamics. The proposed method is shown to be capable of identifying the current regime of operation from the initial time response under a given set of operational parameters. The efficacy of regime classification is demonstrated by testing on two data sets, generated from numerical simulation of a MATLAB SimuLink model that has previously been validated with experimental data. The results of the proposed PFSA-based classification are compared with those of a hidden Markov model (HMM) that serves as the baseline.

Aiming to improve the flame retardancy performance of natural rubber (NR), we developed a novel flame retardant synergistic agent through grafting of MCM-41 to graphene oxide (GO)，named as GO-NH-MCM-41，as an assistant of intumescent flame retardants (IFR). The structure of GO-NH-MCM-41 was characterized by FTIR, TEM and SEM tests, which confirmed that a fine grafting had been applied between GO and MCM-41. The flame retardancy of NR/IFR/GO-NH-MCM-41 composites was evaluated by limited oxygen index (LOI), UL-94 and cone calorimeter test. The LOI value of NR/IFR/GO-NH-MCM-41 reached to 26.3%; the UL-94 ratings improved to V-0 rating. Moreover, the addition of GO-NH-MCM-41 obviously decreased the peak heat release rate (PHRR) and the total heat release (THR) of the natural rubber composites. And the addition of GO-NH-MCM-41 increased the thickness of char residue. The images of SEM indicated the char residue were more compact and continuous. The degradation of GO-NH-MCM-41 based NR composites completed with a mass loss of 35.57% at 600 ℃. The tensile strength and the elongation at break of NR/IFR/GO-NH-MCM-41 composites were 13.9 MPa and 496.7%, respectively. The results of rubber process analyzer (RPA) reached the maximum value, probably due to a better network of the fillers in the matrix.

The pre-chamber technologies can improve the ignition performance of IC engines by more than two orders in magnitude and thereby substantial economic benefits. Compared with the common pre-chamber, a plug-and-play passive scheme is suitable for quick retrofit, which is getting more attention from the automobile industry. Good scavenging is the precondition for improving turbulent jet ignition performance for a passive pre-chamber. Therefore, detailed evaluations of the scavenging process and turbulent jet ignition deserve investigations for new pre-chamber schemes. In this paper, the effects of design parameters on ignition processes of plug-and-play passive pre-chamber were numerically studied, allowing for the lateral angle, orifice diameter, and vertical angle design. Seven pre-chamber schemes were evaluated, and four optimal ones were selected for bench tests. The characteristics of the scavenging process, turbulent jet ignition, and main-chamber combustion were investigated and analyzed. The results show that allowing for the trade-off between ignition energy and scavenging efficiency, the volume ratio of the pre-chamber to clearance is recommended to be 0.2~0.7%, and the corresponding area-volume ratio is 0.003~0.006 mm-1. Compared with the original natural gas engine, the pre-chamber retrofit can save up to 13.2% fuel consumption, which presents a significant improvement in fuel economy.

Introduction: Around a million people are reported to die by suicide every year, and due to the stigma associated with the nature of the death, this figure is usually assumed to be an underestimate. Suicide may be prevented if prompt intervention is taken to mitigate risk. Machine learning and artificial intelligence-based modelling, such as natural language processing (NLP) and other text analytics approaches, has the potential to become a major technique for the detection, diagnosis, and treatment of people who are suffering from mental health issues. The primary aims of this research are to determine whether NLP techniques have been utilised in the field of suicide prevention, and if so, were they effective? What were their limitations? Methods: PubMed, EMBASE, MEDLINE, PsycInfo, and Global Health databases were searched for studies that reported use of NLP for suicide ideation or self-harm. Thematic analysis was used to synthesise and analyse the included studies. Findings were reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, and the Mixed Methods Appraisal Tool (MMAT) was used in assessing paper quality. Result: The preliminary search of five databases generated 387 results. Removal of duplicates resulted in 158 potentially suitable studies. Twenty papers were finally included in this review. Discussion: Studies show that combining structured and unstructured data in NLP data modelling yielded more accurate results than utilizing either alone. Also, to reduce suicides, people with mental problems must be continuously and passively monitored. Further, NLP and other machine learning/artificial intelligence technologies can be used to address health inequities and electronic health records provide valuable data for creating suicide risk tools. Finally, Online, social media, and smartphone applications can be leverage in detecting people with suicide ideation. Conclusion: The use of artificial intelligence and machine learning opens new avenues for considerably guiding risk prediction and advancing suicide prevention frameworks. The review's analysis of the included research revealed that the use of NLP may result in low-cost and effective alternatives to existing resource-intensive methods of suicide prevention. To summarise, there is substantial evidence that NLP is useful in identifying people who have suicide ideation.

Nowadays, an analysis of virtual media to predict society’s reaction to any events or processes is a task of great relevance. Especially it concerns meaningful information on healthcare problems. Internet sources contain a large amount of pharmacologically meaningful information useful for pharmacovigilance purposes and repurposing drug use. An analysis of such a scale of information demands developing the methods that require the creation of a corpus with labeled relations among entities. Before, there have been no such Russian language datasets. This paper considers the first Russian language dataset where labeled entity pairs are divided into multiple contexts within a single text (by used drugs, by different users, by the cases of use, etc.), and a method based on the XLM-RoBERTa language model, previously trained on medical texts to evaluate the state-of-the-art accuracy for the task of indication of the four types of relationships among entities: ADR–Drugname, Drugname–Diseasename, Drugname–SourceInfoDrug, Diseasename–Indication. As shown based on the presented dataset from the Russian Drug Review Corpus, the developed method achieves the F1-score of 81.2% (obtained using cross-validation and averaged for the four types of relationships), which is 7.8% higher than the basic classifiers.

Arthrospira platensis is the widely available source of spirulina and contains distinctive natural pigments including carotenoids and C-phycocyanin (C-PC). In this study, the major carotenoid and C-PC contents were determined in seven commercially available spirulina powder products and laboratory-prepared A. platensis trichomes (AP-1) by an LC-DAD method and a UV-Visible spectrometry, respectively. The correlation of these two pigment content levels with Hunter color coordinates and antioxidant activity was also evaluated. The L* value failed to show a significant correlation with pigment content, but a positive correlation was observed between a* values and the contents of total carotenoid and C-PC. As b* values decreased, the total carotenoid and C-PC contents increased. AP-1 exhibited the highest content of total carotenoids, chlorophyll a and C-PC, and antioxidant activities among the samples. This observation could be related to degradation of these pigments during the mass production process. The carotenoid profiles suggested that the commercial spirulina powders originated from two different sources, A. platensis and A. maxima. Total carotenoid and C-PC content exhibited positive significant correlations with antioxidant activities measured by DPPH and ABTS assays. These results provide a strong scientific foundation for the establishment of standards for the commercial distribution of quality spirulina products.

Natural deep eutectic solvents (NADES) have been shown as selective and environmentally friendly solvents for the extraction of bioactive compounds. However, studies on the solubility of low molecular weight carbohydrates (LMWC) in NADES are scarce. In this work, new solubility data of LMWC in NADES are provided and a new approach based on the use of these solvents for the efficient fractionation of bioactive carbohydrates was explored for the first time. Several mono- and disaccharides and three NADES based on choline chloride (ChCl) and different donors [2-ethylene glycol (EtG), glycerol (Gly) and ethanedioic acid dihydrate (Eth)] were considered. While degradation of carbohydrates, mainly ketoses, was detected with ChCl:Eth due to its acidic nature, ChCl:EtG and ChCl:Gly were found to be useful alternatives for selectively separating bioactive ketoses and their corresponding aldoses (e.g. lactulose/lactose and tagatose/galactose) present in equimolar binary mixtures. In addition, the usefulness of ChCl:EtG for the selective enrichment of lactulose to be used as food ingredient or nutraceutical was proven (from a 25% in the reaction mixture to a 56% in the purified sample). NADES could be used for the selective fractionation of value-added carbohydrates from interfering sugars for several applications including food science, engineering or pharmaceuticals.

This research work focuses on the potential application of an organic compound, santalol obtained from santalum album in the inhibition of the enzyme tyrosinase which is actively involved in the biosynthesis of the melanin pigment. Over-production of melanin causes undesirable pigmentation in humans as well as other organisms that significantly downgrade their aesthetic value. The study is designed to explain the purification of tyrosinase from the mushroom Agaricus bisporus, followed by activity assay and enzyme kinetic to give insight into the santalol modulated tyrosinase inhibition in a dose dependent manner. The multi-spectroscopic techniques like UV-vis, fluorescence, and isothermal calorimetry are employed to deduce the efficiency of santalol as potential candidate against the tyrosinase enzyme activity. Experimental results are further verified by molecular docking. Santalol derived from the essential oils of santalum album, is widely used as remedy for skin disorders and potion for fair complexion since ancient times. Based on enzyme kinetics and biophysical characterization, this is the first scientific evidence where santalol inhibits tyrosinase, which may be employed in agriculture, food, and cosmetic industries by prevent excess melanin formation or browning.

The Abnormal increase in the mass of adipose tissue during adipogenesis results in obesity. Obesity is a predominant disorder and its widespread has become a critical concern worldwide. This is due to the burden of its associated co-morbidities like cancer, cardiovascular diseases and diabetes. Over-nutrition and the sedentary lifestyle are considered as the most significant causes of abnormal adipose tissue development. Appropriate lifestyle and behavioural interventions are the corner stones of successful weight loss, but to maintain such a lifestyle is highly challenging. Accordingly, natural products from plants either as crude extracts or purified phytochemicals have shown to have anti-obesogenic properties and are generally non-toxic and cost-effective. In this review, we discuss the comparative analysis of molecular mechanisms involved in adipogenesis and the recently reported anti-obesogenic effects of various plant products. We will provide a common platform for understanding obesity and adipogenesis, and a possible mechanism of action for anti-obesogenic plant products through AMP-activated protein kinase (AMPK), which will support the scientific development of traditional herbal medicine.

This paper evaluates an architectural design using an Energy Consumption consideration of Natural Ventilation in a hot dry climate (Khartoum State), at dwellings design applied. Method was used analysis of Autodesk IEVS software natural ventilation and energy consumption simulation. It resulted that to cooling, by natural ventilation in dwelling design used to get indoor temperature at the comfortable level during the summer. The Best-Case Situation of natural ventilation with consider of energy saving Based on the CFD simulation analysis, the performance of internal air velocity is approximately 0.7m/s. The wind velocity starts to slow down towards the rear of the apartment spaces. Approximately 95% of the internal areas have average air velocity between 0.43 m/s to 0.9 m/s. Internal Air flow pattern single floor house plan at Khartoum (Alazhari City); showing the internal air velocity of 0.7m/s near the window opening positions with the wind directions in the details and pressure of the air as worst-case situation, with velocity and temperature of the air with average 22o as a best-case situation. during a year. Architectural design process in the urban area of Alazhari City for dwelling towards to saving energy was applied and determined into an urban planning neighbourhood at Khartoum.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have triggered a recent pandemic of respiratory disease and affected almost every country all over the world. A large amount of natural bioactive compounds is under clinical investigation for various diseas-es. Especially, marine natural compounds are gaining more attention in the new drug develop-ment process. The present study has aimed to identify potential marine-derived inhibitors against the target proteins of COVID-19 using a computational approach. Currently, 16 marine clinical-level compounds were selected for computational screening against the four SARS-CoV-2 main proteases. Computational screening resulted from the best drug candidates for each target based on the binding affinity scores and amino acid interactions. Among these, five marine-derived compounds namely Chrysophaentin A (-6.6 kcal/mol), Geodisterol sulfates (-6.6 kcal/mol), Hymenidin (-6.4 kcal/mol), Plinabulin (-6.4 kcal/mol) and Tetrodotoxin (-6.3 kcal/mol) expressed the minimized binding energy and molecular interactions such as covalent and hydrophobic interactions to the SARS CoV-2 Main Protease. Using Molecular dynamic stud-ies, the Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (ROG), and Hydrogen bonds (H-Bonds) values were calculated for SARS-CoV-2 Main Protease with Hymenidin docked complex. Additionally, in silico Druglikeness and pharmaco-kinetic property assessments of the compounds demonstrated favorable druggability. These re-sults suggested that marine natural compounds are capable of fighting SARS-CoV-2. Further, in vitro and in vivo studies need to be carried out to confirm their inhibitory potential.

Petrosamine (1) – a colored pyridoacridine alkaloid from the Belizean sponge, Petrosia sp. that is also a potent inhibitor of acetylcholine esterase (AChE) – was investigated by spectroscopic and computational methods. Analysis of the petrosamine free energy landscapes, pKa and tautomerism revealed an accurate electronic depiction of the molecular structure of 1 as the di-keto form, with net charge of q = +1, rather than a dication (q = +2) under ambient conditions of isolation-purification. The pronounced solvatochromism (UV-vis) reported for 1, and related analogs, was investigated in detail and is best explained by charge delocalization and stabilization of the ground state (HOMO) of 1 rather than an equilibrium of competing tautomers. Refinement of the molecular structure of 1 by QM methods complements published computational docking studies to define the contact points in the enzyme active site that may improve design of new AChE inhibitors based on the pyridoacridine alkaloid molecular skeleton.

The classification of goods involved in international trade in Brazil is based on the Mercosur Common Nomenclature (NCM). The classification of these goods represents a real challenge due to the complexity involved in assigning the correct category codes especially considering the legal and fiscal implications of misclassification. This work focuses on the training of a classifier based on Bidirectional En-coder Representations from Transformers (BERT) for the tax classification of goods with NCM codes. In particular, this article presents results from using a specific Portuguese Language tuned BERT model as well results from using a Multilingual BERT. Experimental results justify the use of these models in the classification process and also that the language specific model has a slightly better performance.

Spatial approach based on the deformation measurement of volcanic dome and crater rim is key to evaluate the activity of a volcano, such as Merapi volcano where associated disaster risk is regularly taking lives. Within this framework, this study aime to detect localized deformation and change in the summit area that has occurred concomitantly with the dome growth and explosion reported. The methodology was focused on two sets of data, one LiDAR-based dataset of 2012 and one UAV-dataset of 2014. The results show that during the period 2012-2014, the crater walls are 100 m to 120 m high above the crater floor at its maximum (North to East-South-East sector), while the West and North sector presents a topographic range of 40 to 80 m. During the period 2012 – 2014, the evolution of the crater rim around the dome is generally stable (no large collapse). The opening of a new vent on the surface of the dome has displaced an equivalent volume of 2.04 E+04 m3 corresponding to a maximum -9 m (+/- 0.9 m) vertically. This concludes that during the period 2012 – 2014 when the dome of Merapi experienced phreatic or phreatomagmatic explosions, the topography around the dome rose. This rise does not seem to be related to large wall collapses, and it is likely that modification in the subsurface have triggered those changes.

In this investigation dyeing of alginate fiber was carried out after cationic treatment of EPTAC (2, 3-Epoxypropyl Trimethyl Ammonium Chloride). Optimum dyeing process and parameter show good dyeing performance when alginate fiber dyed with rhubarb dye. In addition to cationic treatment is taken into account for alginate fiber to improve fastness, color strength, breaking strength. Later in dyeing for fixation ferrous sulfate, copper sulphate was considered as mordents. Moreover using pre-mordanting methods conveyed the dyeing of alginate fiber with the stave of metallic mordant and without metallic salt mordents. The evaluation of each color dyed material was done through following two terms for instance CIELAB (L*, a*, and b*) and K/S values. According to AATCC test methods color fastness to washing of the dyed fiber was determined whereas according to the ASTM D3822M standard the breaking strength of alginate fiber was estimated and tested. When dyeing was carried out on alginate fiber through considering optimum parameter like 80◦C for 90 min, M: L 1:40 and at pH 7 which showed optimum results. In addition to mostly very good wash fastness was obtained while there was no fading of the color, whereas the moderate level of color fastness to crocking was achieved. Later after dyeing the evaluations of SEM of the cationized alginate fiber and FTIR of powder from the rhubarb dye were observed. The results suggested that the surface of cationized alginate fiber was smoother than the raw alginate fiber.

The Serra da Estrela Natural Park (NPSEs) in Portugal stands out as a well-preserved region abundant in medicinal plants, particularly known for their pharmaceutical applications in diabetes prevention and treatment. This comprehensive review explores these plants' botanical diversity, traditional uses, pharmacological applications, and chemical composition. The NPSEs boast a rich diversity with 138 medicinal plants across 55 families identified as traditionally and pharmacologically used against diabetes globally. Notably, the Asteraceae and Lamiaceae families are prevalent in anti-diabetic applications. In vitro studies reveal their significant inhibition of carbohydrate-metabolizing enzymes, and certain plant co-products regulate genes involved in carbohydrate metabolism and insulin secretion. In vivo trials demonstrate anti-diabetic effects, including glycaemia regulation, insulin secretion, antioxidant activity, and lipid profile modulation. Medicinal plants in NPSE exhibit various activities beyond anti-diabetic, such as antioxidant, anti-inflammatory, antibacterial, anticancer, and more. Chemical analysis identifies over fifty compounds like phenolic acids, flavonoids, terpenoids, and polysaccharides responsible for their efficacy against diabetes. The findings underscore the potential of NPSE medicinal plants as anti-diabetic candidates, urging further research to develop effective plant-based anti-diabetic drugs, beverages, and supplements.

Powder metallurgy is a preferred manufacturing method in various industries because it offers design flexibility, material efficiency and a cost-effective production. In this work, we study the effects of different compaction directions on the strength of parts produced by powder metallurgy. Al–4wt.%Cu alloys are used due to their recyclability, and three distinctive compaction pressures are applied, resulting in two sample groups. One group is air-cooled after sintering, while the other is water-quenched and naturally aged (T4 temper). Both the compressive and tensile strengths are measured and analyzed. The study reveals that both heat treatments and compaction directions significantly influence anisotropic strengths. The novelty of this research lies in the use of powders that can be reused from machining, turning, or foundry rejection. By omitting or reducing the melting stage and employing simple powder metallurgy, the cost-effective and environmentally friendly processes are achieved. The planning of compaction load, compaction direction, and heat treatments is found to play a crucial role in determining the final mechanical performance. Notably, this approach aligns with the environmental, social and governance (ESG) practices that have been increasingly adopted by industry.

The construction field uses up over one-third of the global energy consumption and contribute to 40% of CO2 emissions according to the International Energy Agency (IEA) and the 2020 annual reporter of United Nation, Goal 11 (Make cities inclusive, safe, resilient and sustainable) which discusses sustainable, safe and efficient buildings. Therefore, Morocco has a commitment to this program by publishing the law 47-09 of energy efficiency. This work aims to study the energy efficiency of two types of building, a conventional and a natural building. Conventional building is constructed using concrete, while the natural one uses sand clay and straws. As for the technique of making the natural building, it perpetually follows the same approach accustomed in rural zones of Atlas Mountains in Morocco. In this research we also simulate, temperature and humidity variation inside these buildings using TRNSYS software. Sketch Up software was employed to design these houses. The weather database is used for a typical meteorological year (TMY). In the case of natural building, many building configurations were simulated: roof insulation, floor insulation, different types of glazing and sun protection. What's more, the thermal comfort is revealed to be more conspicuous in the case of natural building.

Natural gas is an important energy source among various fossil fuels. However, natural gas typically contains a significant amount of water vapor, which can pose challenges in its usage. Therefore, the process of removing water vapor from natural gas, known as gas dehydration, is crucial in the gas industry. The presence of water vapor in the gas supply can lead to the formation of hydrates, which can cause issues such as blockages in pipelines. To tackle this problem effectively, gas dehydration makes use of Tri ethylene glycol (TEG) as a drying agent. TEG works by selectively absorbing water vapor from the natural gas flow, thereby significantly reducing its moisture content.In the gas dehydration process, wet gas is treated by using lean glycol in an absorber, where the water vapor is removed. The resulting rich glycol is then recovered and recycled for further use. In this study, we explore the possibility of replacing nitrogen with dry natural gas in the re-generator of the glycol dehydration system. The aim is to evaluate the feasibility and effectiveness of this alternative approach. To assess the performance of both techniques, we employed HYSYS modeling and simulation. Through this analysis, we compared the capital and utility expenses associated with each method while ensuring that the glycol purity requirements remained unchanged. By examining the results obtained from the simulations, we can gain insights into the economic viability and efficiency of utilizing dry natural gas in the re-generator stage of the glycol dehydration process.In addition to the primary purpose of removing water vapor, the wet gas obtained from the stripping mechanisms in the glycol dehydration process can serve additional functions. It can be utilized to power steam pumps and compressors, thereby maximizing energy efficiency within the system. Alternatively, the wet gas can be recycled back into the process for further treatment. To develop a comprehensive understanding of the entire mechanism, we constructed a model based on the actual flow diagram. This model takes into account the various components and processes involved in the glycol dehydration system, including the stripping mechanisms and their connection to other equipment. By analyzing the data and outcomes generated by this model, we can derive valuable insights. These findings can be utilized to optimize the heat and material balance within the plant, ensuring efficient operation and potentially leading to the design of an improved system in terms of energy consumption and overall performance

Agriculture has been experiencing a difficult situation because of limiting factors in its production, Natural biostimulants (NBs) have emerged as a novel alternative. This study reviews NBs produced through Solid-State Fermentation (SSF) from organic waste, focusing on the processes and production methods. The aim is to highlight their potential for improving agricultural productivity and promoting sustainable agriculture. Through a literature review, the effects of NBS on crops were examined, as well as the challenges associated with their production and application. The importance of standardizing production processes, optimizing fermentation conditions, and assessing their effects on different crops is emphasized. Furthermore, future research areas are identified, such as enhancing production efficiency and evaluating the effectiveness of SSF-produced NBS in different agricultural systems. In conclusion, SSF-produced NBS offers a promising alternative for sustainable agriculture, but further research and development are needed to maximize its efficacy and enable large-scale implementation.