To realize the energy recovery of wheat straw, the pyrolysis behavior of wheat straw was studied at three heating rates (10, 20, and 30 K/min) based on thermogravimetric analysis (TG–DTG). Kinetics and thermodynamics were analyzed using Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) model-free methods, and reaction mechanism was determined using Coats–Redfern (CR) model-fitting method. The results show that there are three weightlessness stages in the pyrolysis process, of which the second stage was the main weightlessness stage and two distinct peaks of weightlessness were observed in this stage. With increasing heating rate, the main pyrolytic weightlessness peaks of DTG curve shifts to higher temperature. The pyrolysis activation energy calculated by FWO and KAS methods are 165.17–440.02 kJ/mol and 163.72–452.07 kJ/mol, and the pre-exponential factor vary in the range of 2.58×1012–7.45×1036 s-1 and 1.91×1012–8.66×1037 s-1, respectively. The thermodynamic parameters indicates that wheat straw has the favorable conditions for product formation and containes potential energy to be utilized for bioenergy production, its pyrolysis reaction was non-spontaneous and the energy output is stable. CR method analysis shows that the A1/3 random nucleation model is the most suitable mechanism to characterize the pyrolysis process, and random nucleation may be in charge of the main pyrolysis stage. This study can provide a theoretical basis for the thermochemical conversion and utilization of wheat straw.

The risks for complications of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection are higher in obese individuals. Obesity is a state of chronic low-grade inflammation, with high leptin levels due to leptin resistance, high basal levels of other pro-inflammatory cytokines such as TNF-alpha, MCP-I and IL-6, and low adiponectin levels, thus contributing to a state of defective innate immunity as well as impaired B and T cell responses. Obesity is a risk factor for metabolic syndrome, diabetes, cardiovascular disease and hypertension. It has been observed that pre-existence of these diseases confers a higher risk of severe SARS CoV2 infection as well as the need for intensive care; even below the age of 60 years if their body mass index (BMI) is greater than 30 kg/m2, and even more so if it is > 35 kg/m2. The metabolic factors contributing to the changes in altering the immune mechanisms in obese individuals and how this enhances the susceptibility to infection and development of serious SARS-CoV2 infection have been the subject of many debates. Future development of targeted therapy and guidelines will be benefited by greater understanding into these metabolic pathways.

This article provides a comprehensive analysis of the global gas and liquefied natural gas (LNG) markets. The article begins by discussing the increasing demand for gas and LNG, particularly in Asia, as countries aim to transition to cleaner sources of energy. It explores how market volatility has led to energy security interventions and lasting economic and emissions impacts. It then explores the global supply and demand dynamics, highlighting the structural change expected in the market and the competition between Europe and Asia for limited new LNG supply. The article also focuses on Europe's increased flexibility and dependence on LNG imports, which have risen by 60% to 121 million tonnes, offsetting lower Russian pipeline imports. Furthermore, the article delves into global supply and demand dynamics, how the market is expected to remain tight, and how record gas and LNG prices have led to demand reductions. Additionally, it analyzes the future outlook and investment needs, highlighting the continued uptake of gas in heavy-duty transport and the need for further investment to avoid a supply-demand gap. The article concludes with an analysis of the implications for the future of the global gas and LNG markets.

The formation and localization of sporadic E(Es) layers predicted by the ions vertical drift velocity and its vertical change in the lower thermosphere during nighttime are shown analytically and by numerical simulations. The consideration of existence of a minimum negative value of the vertical change of the ions vertical drift velocity as a necessary condition of formation of Es layer and determining ions convergence rate into this layer, is extended in case of the presence of vertical wind. Upward vertical wind can shift the convergence regions upward, while downward vertical wind shift them downward, unlike the cases of presence of only meridional and zonal winds. It also changes the ion convergence rate compared to the one with just a horizontal wind. It is shown for the first time that the upward constant wind also causes the convergence of ions with maximum rate in the region where the ion-neutral collision frequency is equal to their cyclotron frequency. While demonstrating the presented theory by numerical simulations, HWM14 data is used for the meridional and zonal wind velocity profiles and the presence of its vertical component is assumed. In this case, in addition to the estimated ion drift velocity and its vertical changes, their initial distribution and ambipolar diffusion also determine the development of ion convergence/divergence processes. For small magnitude of vertical wind velocity, its significant influence on the ions/electrons behavior is demonstrated, which shows the importance of both tidal wind and wind changes caused by the propagation of atmospheric gravity waves on the formation of the Es layer. In this theoretical research it is shown that the realistic profile of the wind velocity, which takes into account the vertical component along with its zonal and meridional ones, is important for prediction of the Es layers formation, as well as regions of ion depletion.

The education system has become even more complex following the global pandemic, which saw face-to-face teaching transition to virtual teaching. To cope with this abrupt transition, it is essential that teachers had a sufficient level of digital teaching competence. This article aims to increase awareness of teachers' self-perception of their digital teaching competences in the educational field. Specifically, this study explores Spanish secondary school teachers’ knowledge and use of different ICT tools by evaluating their competence based on different areas proposed by The National Institute of Technology and Professional Development (Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado, INTEF), Madrid, Spain. From the results of the questionnaires, we have determined that teachers consider themselves to have an upper intermediate level of digital teaching competence, although there are still shortcomings that need to be addressed in order to improve this level of competence, and its true integration in the teaching–learning process.

This study aims to get growth and feed efficiency of Nile tilapia (Oreochromis niloticus) with plant oils supplement from paring coconut (P.C.) and candlenut (C.N.) enrichment of Se in rations formula. The oil of P.C. was dominated by saturated fatty acid (SFA) lauric (42.67%), while the extract of C.N. was unsaturated fatty acids (UFA), linoleic (34.4%), and oleic (48.99%). The extract of P.C. and C.N. or mix oils added 4% in basal ration formula (28% crude protein (C.P.) with energy-protein ratio 8 kcal/kg). Completely Randomized Design (6 × 3) consists R1: basal ration; R2: basal formula with blend of paring coconut and candlenut oils (2% PC + 2% CN); R3: blend oils (R2) with trace additive Se; R4: 4% PC + Se; R5: 4% CN + Se; R6: control ration (32% CP). The result of production parameters showed that blend oils supplement enrichment Se 0.15 ppm in feed formula with ratio SFA: UFA = 1: 1 was the best growth rate equal with high protein feed. Feed efficiency ranged from 50.14-57.93% and protein efficiency ratio 1.72-2.06 both for CN oil (SFA: UFA = 1 : 2), paring coconut (SFA : UFA = 2 : 1) or blend oils (SFA : UFA = 1 : 1). Incorporation of blend oils with Se can be used for Nile tilapia fingerlings (≥ 10 g). Paring coconut oil was trend increasing on feed efficiency for tilapia bigger stadium (≥ 30 g).

A characteristic feature of lightweight constructions is their low thermal mass which causes high internal temperature fluctuations that require high heating and cooling demand throughout the year. Phase Change Materials (PCMs) is effective in providing thermal inertia to low thermal mass buildings. The aim of this paper is to analyse the thermal behaviour of two proposed lightweight buildings designed for homeless people and to investigate the potential benefit achievable through the use of different types of PCM in the temperate climatic conditions of Christchurch, New Zealand. For this purpose, over 300 numerical simulations have been conducted using the simulation software DesignBuilder®. The bulk of the simulations were carried out under the assumption that the whole opaque building envelope is equipped with PCM. The results showed significant energy saving and comfort enhancement through the application of PCMs. Thereby, annual energy saving of over 50 % was reached for some of the PCMs considered. Additionally, the effectiveness of single, PCM-equipped structure components was investigated and substantial benefits between 19 and 27 % annual energy saving were achieved. However, occupant behaviour in terms of ventilation habits, occupancy of zones etc. remains one of the biggest challenges in any simulation work due to insufficient data.

Coronavirus disease is the current cause of global concern. The massive outbreak of COVID-19 has led the World Health Organization (WHO) to declare this as a pandemic situation. The Severe Acute Respiratory Syndrome Coronavirus-2 (SARSCoV-2) is responsible for COVID-19 leading to acute respiratory distress and substantial mortality in humans. However, the first laboratory confirmation of SARS-CoV-2 in a pet dog in Hong Kong has shown the possibility of human-to-animal transmission (zooanthroponotic) of the virus. Thereafter, many animals including cat, tiger, lion and mink have also been reported to acquire the virus in several countries. In this situation the role of veterinarian assumes important in treating the animals, helping in food security, disease diagnosis, surveillance and boosting the economy of livestock stakeholders at the grassroot level. In the absence of any selective vaccine or drug against SARS-CoV-2, the world is anticipated to triumph over this pandemic with collaborative, multisectoral, and transdisciplinary approach linking human, animal and environmental health. This article gives an insight into the confirmed SARS-CoV-2 outbreaks in animals, including the factors behind the shuffling of the virus among variety of species and also emphasizes on the role of veterinarian in managing and safeguarding public health so as to pave the way for adopting one health approach in order to conserve biodiversity.

The outbreak of Coronavirus disease 2019 (COVID-19) has posed a significant concern in many countries due to the rapid rate of transmission between humans. Taking advantage of the experience of the last epidemics in 2002 Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and 2012 Middle East Respiratory Syndrome Coronavirus (MERS-CoV), some regions of the world were well- prepared for the new outbreak. However, other countries needed to be adapted to the situation promptly. Many management strategies were established, and some restrictions were introduced in some regions. In this review, we aimed to determine countries’ public responses to the epidemic of COVID-19 and how they developed administrative approaches towards the outbreak.

Buildings use 30-40 % of all energy resources and are thus their main consumers in modern society. Moreover, buildings require a vast amount of different raw materials. During the last two decades, several green building certifications have been created in order to consider social, economic and environmental aspects of sustainability of buildings. One of the most famous and widely used of these certifications is Leadership in Energy and Environmental Design (LEED). So far, the use of LEED has concentrated in the US and other developed countries. One reason that restricts the use of this point-based system certification in developing countries is the limited data about its costs. In this study, the extra cost of the certification process will be evaluated besides the changes needed in the design of the building to reach the points required by LEED. At the first stage, the number of points the case study earns in its current format (Scenario 1) were found out, then the cost difference of getting either the Certified (Scenario 2) or Silver (Scenario 3) level LEED certification for the building was studied. It was found that besides some technical considerations, filling the criteria of the Certified and Silver level increases the total costs of construction by 3.4% and 5.9%. Further improvement of the building’s energy efficiency would enable the attainment of a higher-level certification. The results of the study could help to promote the use of green building certifications in Western Asia.

Farming systems prevalent in sub-Saharan Africa are exposed and vulnerable to climate change due to their high dependence on rainfall. However, most studies have only estimated the impacts of climate change on agricultural productivity at a regional or national level. We add to this literature by focussing on the sub-national impacts. This study uses 30 years (1981–2011) of yield and weather data in Zambia and applies the Just and Pope model to determine how rainfall and temperature affect yield and yield variability of maize and beans at the national and subnational levels. Results show a negative impact of temperature rise on yield and a positive impact of rainfall rise on yield, above the current mean levels. These results differ by agro-ecological region. Worst-case-scenario predicted impacts using HadGEM-ES2 global circulation model show that major yield decreases (25% for maize and 34% for beans) by 2050 will be in region II and will be driven mainly by temperature increase offsetting the positive gains from rainfall increase. The model mainly under-predicts yield for maize and overpredicts yield for beans. These findings call for agro-ecological region-specific adaptation strategies and well-planned policy interventions to make agriculture more resilient to climate change.

The application of 3D LiDAR technology has become increasingly extensive in tunnel monitoring due to the large density and high accuracy of the acquired spatial data. The proposed processing method aims at circle tunnels and provides a clear workflow to automatically process raw point data and easily interpretable results to analyze tunnel health state. The proposed automatic processing method employs a series of algorithms to extract point cloud of a single tunnel segment without obvious noise from entire raw tunnel point cloud mainly by three steps: axis acquisition, segments extraction and denoising. Tunnel axis is extracted by fitting boundaries of the tunnel point cloud rejection in plane with RANSAC algorithm. With guidance of axis, the entire preprocessed tunnel point cloud is segmented by equal division to get a section of tunnel point cloud which corresponds to a single tunnel segment. Then the noise in every single point cloud segment is removed by clustering algorithm twice, based on distance and intensity. Finally, clean point clouds of tunnel segments are processed by effective deformation extraction processor to get ovality and three-dimensional deformation nephogram.

Pharmaceutical poisoning is a significant global public health concern, causing approximately 190,000 deaths yearly. This scoping review aims to comprehensively map the available literature on pharmaceutical poisoning and compare patterns between high-income countries (HICs) and low-middle-income countries (LMICs). A systematic search was performed across the following databases: Embase, PubMed, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and CINAHL. Studies included were from 1st January 2011 to 31st December 2020, in English, with full text available. Seventy-nine articles were included in the study; 21 were from LMICs and 58 were from HICs. The toxic exposure was largely intentional (77%) in LMICs and accidental (68%) in HICs. Drugs acting on the nervous system were responsible for 95% of toxicities worldwide with analgesics accounting for the largest subtherapeutic group in both LMICs (40%) and HICs (58%). Notable statistics were that HICs accounted for 99% of opioid overdoses, and LMICs accounted for 19% of anti-epileptic-induced toxicities. Overall, the medical outcomes of poisonings were generally worse in LMICs. The review provides possible interventions to target specific geographic locations, based on the trends identified, to reduce the burden worldwide. Many gaps within the literature were recognised, calling for more robust analytical research.

Wireless energy harvesting (EH) communication has long been considered a sustainable networking solution. However, it has been limited in efficiency, which has been a major obstacle. Recently, strategies such as energy relaying and borrowing have been explored to overcome these difficulties and provide long-range wireless sensor connectivity. In this article, we examine the reliability of the wireless-powered communication network by maximizing the net bit rate. To accomplish our goal, we focus on enhancing the performance of hybrid access points and information sources by optimizing their transmit power. Additionally, we aim to maximize the use of harvested energy by energy-harvesting relays for both information transmission and energy relaying. However, this optimization problem is complex as it involves non-convex variables and requires combinatorial relay selection indicators optimization for decode and forward (DF) relaying. To simplify this problem, we utilize the Markov decision process and deep reinforcement learning framework based on the deep deterministic policy gradient algorithm. This approach enables us to tackle this non-tractable problem, which conventional convex optimisation techniques would be difficult to solve in complex problem environments. The proposed algorithm significantly improves the end-to-end net bit rate of the smart energy borrowing and relaying EH system by 13.22%,27.57%, and 14.12% compared to the benchmark algorithm based on borrowing energy with an adaptive reward for Quadrature Phase Shift Keying, 8-PSK, and 16-Quadrature amplitude modulation schemes, respectively.

This study describes the AMD impacted environments and critically discusses the effects of AMD, current prediction and prevention methods and treatment technologies. The study further, crit-ically analyses the case studies, gaps in AMD research and the challenges and opportunities of-fered by AMD. The study outlined future technological intervention aiming at a paradigm shift towards reducing the volume of sludge generated as well as the operating cost and improving AMD treatment efficiency. The integrated AMD treatment technologies that result in a holistic approach toward sustainable AMD treatment are a current need. As a result, a sustainable AMD treatment strategy has been made possible due to water reuse and rich resource recoveries such sulphuric acid, rare earth elements, and metals. The cost of AMD treatment can be decreased with the use of recovered water and resources, which is essential for developing a sustainable AMD treatment process.

The production of plants and crops is influenced by environmental stress, which is a serious scientific issue. Cotton is an essential crop for producing natural fibers that are used to make biofuel and edible oils. Salinity is the main element that influences cotton growth during the beginning of germination. The type of salt and the growth stage affects how sensitive a plant is to salt stress. Developing ways to enhance cotton performance in salty circumstances can be aided by an understanding of the response of cotton to salt, its mechanism of resistance, and its management methods. Osmotic and ionic imbalances originate due to the deposition of soluble salts under salinity stress in the plant's root zone. Soil salinity significantly reduces plant growth due to several factors, such as nutritional ion imbalance, which reduces K+, PO4-, and NO- absorption, excessive salt chloride concentrations, and osmotic stress, which hinders water availability. Research has revealed that compared to subsequent stages, the germination, emergence, and seedling phases are more vulnerable to salinity stress, which ultimately affects the seed cotton yield by delaying blooming, reducing fruiting positions, shedding fewer fruits, and reducing boll weight. The morphology, growth of cotton roots, shoots, yield, and fiber quality are all strongly impacted by salinity stress. It slows down plant feeding, cellular metabolism, and photosynthesis. The soil, water, and climate all affect how the plant responds to salinity stress. During salt stress, excessive exclusion of sodium or its compartmentalization is the key adaptation process in cotton. A major adaptive potential to create cotton types that can withstand salt is provided by the up-regulation of both physicochemical and non-enzymatic antioxidant genes. A successful strategy to increase cotton germination in saline soils is seed priming. Moreover, the transgenic strategy might be a viable choice for improving cotton yield in saline environments. Our review focuses on the impacts of salinity on cotton productivity as well as how plants react to salt stress. It also clarifies recent genetic advancements and molecular breeding for cotton's resistance to soil salt. To create salt-tolerant cultivars, a combination of traditional breeding and novel molecular approaches will be useful.

As the demand for aromatic and medicinal herbs increases, so does the pressure to intensify production, increasing the risk of overexploitation of these natural resources. Sustainability corresponds to the preservation of something that exists in the present and must be maintained in the future, implying accountability and obligation. However, in order to maintain the conditions and essential goods for the survival of future generations, consumers and businesses must commit to sustainable practices. The circular economy is considered one of the solutions to promote a sustainable system and can be defined as a transition from a linear model, where resources are transformed, used and discarded, to a circular (regenerative) model, where materials are reused whenever possible. An ecologically correct approach to waste reuse avoids the negative impacts associated with improper disposal of agro-industrial wastes, such as mass proliferation of microorganisms, production of greenhouse gases, loss of energy potential, and other negative impacts on the environment or human health. The objective of this study is to provide a compilation of good agricultural practices that promote sustainability in the production of medicinal and aromatic herbs, particularly in the areas of cultivation, harvesting, drying, extraction, and packaging, and to highlight the potential for evaluating processing residues in medicinal and aromatic herbs.

The screening and treatment of acid mine drainage (AMD) using Na₂FeO₄ has been explored. Elemental composition was performed using an ICP-OES for the raw and treated AMD. The AMD samples were collected from three different sampling sites (RTW1, RTW2 and RTW3) in Pretoria, South Africa with acidic pH ranging between 2.50 and 3.13. Total dissolved solids and Electrical Conductivity of AMD samples ranged between 960 and > 1000 mg. L^-1, 226 and 263 µS. cm^-1, respectively. The final pH of treated water samples increased up to ≥ 9.5 after treatment with Na₂FeO₄. Sodium ferrate showed dual functions by removing metals and raising the pH of the treated water. Concentrations of most trace elements were not complying with WHO and DWAF guideline standards in raw AMD while after treatment with Na₂FeO₄ the concentrations were below guidelines for domestic and irrigation purposes.

Health and wellness tourism should be particularly valued in the post-pandemic phase, as a stra-tegic product to enhance the population's well-being and quality of life indicators, at social, phys-ical, and environmental dimensions, with different proposals for specialized experiences that complement the destination's offer, positioning regions as health and wellness destinations. Thermal tourism should be encouraged, as a specific product, due to the innovation and diversi-fication observed in the services made available and the benefits recognized at different age levels of tourists and destinations communities. Considering the relevance of thermal springs and thermal tourists for tourism destinations image, positioning, and development, this research aims to identify the specific motivations of tourists to the practice of thermal tourism, to understand how the benefits that thermal tourists search for, and their sociodemographic profile influence the motivations, and how the motivations determine the travel characteristics. This research was de-veloped on the North and Centre of Portugal, for their relevance in the context of thermal springs and related tourism activities. To achieve the research objectives, a questionnaire survey was ap-plied to thermal tourists, through a non-probability by convenience sampling, using bivariate tests, such as Pearson’s chi-squared test, one-way ANOVA, and t-student. The results highlight that most respondents practiced thermal tourism due to leisure and relaxation benefits, such as the escape from daily stress, spend time with family, and being "pampered"; relaxation is the most valued motivation, followed by the search for psychological and physical wellbeing. The research found relations between the benefits expected by thermal tourists, and their travel characteristics such as the composition of the group, the general travel motivation, the thermal destination cho-sen, and the number of nights spent. In thermal tourism, new challenges emerge, demanding the development of strategies, products, and services responding to the needs of specific market segments.

The current study aims to develop a methodology for obtaining topology-optimal structures made of short fiber-reinforced polymers, which include the fluid-structure interaction. Accounting for the molding process during the internal iterations of topology optimization makes it possible to enhance the weight efficiency of structures—a crucial aspect, especially in aerospace. Anisotropy is considered through the fiber orientation tensor, which is modeled by solving the plastic molding equations for non-Newtonian fluids, and then introduced as a variable of the stiffness matrix during the structural analysis. The materials used were non-linearly modeled using an exponential-and-linear hardening law. The evaluation of weight efficiency in structures composed of short-reinforced composite materials using a dimensionless criterion is addressed. Experimental verification was performed to confirm the validity of the developed methodology. The evidence illustrates that considering anisotropy leads to stiffer structures and structural elements should be oriented in the direction of maximal stiffness. The load-carrying factor can be expressed in terms of failure criteria. The presented multidisciplinary methodology can be used to improve the quality of the design of structures made of short fiber-reinforced composites (SFRC) where high stiffness, high strength, and minimum mass are the primary required structural characteristics.

Organophilic nano clay is the composition of mostly clay and organic molecules designed to improve various materials' physical and chemical properties. Permanent deformation in asphalt pavements is primarily the result of inadequate compaction, excessive loading, and high temperatures. Rutting can result in aquaplaning, leading to accidents and costly maintenance and rehabilitation works that drain the economy. Such behavior of asphalt pavements may be attributable to poor selection of aggregate, asphalt binder, or substandard asphalt binders. This study used different percentages of organophilic nano clay ranging from 3.0% - 5.0% with two penetration grade bitumen, i.e., N.R.L 60-70 & N.R.L 80-100. Adding organophilic nano clay to asphalt binder significantly reduced the rutting potential under cyclic loading at high temperatures (55 °C). Ten modified formulations and two virgin bitumen specimens were prepared. The modified binders' viscosity and rutting were tested using the Rotational Viscometer and Wheel Tracker Test (W.T.T.), respectively. The results were analyzed using software for Statistical Analysis. It was recorded that organophilic nano clay-modified bitumen significantly affected rutting to interpret the results. The results indicated that rutting decreased and viscosity increased in all nano clay-modified bitumen samples, with a 4.5% O.N.C modified binder showing the most significant improvement.

Social networking applications such as Twitter have increasingly gained significance in terms of socio-economic, political, and religious as well as entertainment sectors. This in turn, has witnessed a wide gamut of information explosion in the social networking realm that can tend to be both useful as well as misleading at the same point of time. Spam detection is one such solution that caters to this problem through identification of irrelevant users and their data. However, existing research has so far laid primary focus on user profile information through activity detection and relevant techniques that may underperform when these profiles exhibit characteristics of temporal dependency, poor reflection of generated content from the user profile, etc. This is the primary motivation for this paper that addresses the aforementioned problem of user profiles by focusing on both profile information and content-based spam detection. To this end, this work delivers three significant contributions. Firstly, exhaustive use of Natural language processing (NLP) techniques has been rendered towards creation of a new comprehensive dataset with a wide range of content-based features. Secondly, this dataset has been fed into a customized state-of-art hybrid machine learning model that has been exclusively built using a combination of both machine learning and deep learning techniques. Extensive simulation based analysis not only records over 98% accuracy but also establishes the practical applicability of this proposal by proving that modeling based on the mixed profile and content-generated data is more capable of spam detection in contrast to each of these standalone approaches. Finally, a novel methodology based on logistic regression is proposed and supported by analytical formulations. This paves the way for the custom-built dataset to be analyzed and corresponding probabilities to be obtained that differentiate legitimate users from spammers. The obtained mathematical outcome can henceforth be used for future prediction of user categories through appropriate parameter tuning for any given dataset. This makes our method a truly generic one capable of identifying and classifying different user categories.

A popular account of the mixing patterns for the three generations of quarks and leptons is through the characters $\kappa$ of a finite group $G$. Here we introduce a $d$-dimensional Hilbert space with $d=cc(G)$, the number of conjugacy classes of $G$. Groups under consideration should follow two rules, (a) the character table contains both two- and three-dimensional representations with at least one of them faithful and (b) there are minimal informationally complete measurements under the action of a $d$-dimensional Pauli group over the characters of these representations. Groups with small $d$ that satisfy these rules coincide in a large part with viable ones derived so far for reproducing simultaneously the CKM (quark) and PNMS (lepton) mixing matrices. Groups leading to physical $CP$ violation are singled out.

Advances in next-generation sequencing have facilitated the discovery of a multitude of long non-coding RNAs (lncRNAs) with pleiotropic functions in cellular processes, disease and viral pathogenesis. It came as no surprise when viruses were also revealed to transcribe their own lncRNAs. Among them, gammaherpesviruses, one of the three subfamilies of the Herpesviridae, code their largest number. These structurally and functionally intricate non-coding (nc) transcripts modulate cellular and viral gene expression to maintain viral latency or prompt lytic reactivation. The lncRNAs allow the virus to escape cytosolic surveillance, sequester and re-localize essential cellular factors and modulate the cell cycle and proliferation. Some viral lncRNAs act as “messenger molecules”, transferring information about viral infection to neighboring cells. This broad range of lncRNA functions is achieved through lncRNA structure-mediated interactions with effector molecules of viral and host origin, including other RNAs, proteins and DNAs. In this review, we discuss examples of gammaherpesvirus-encoded lncRNAs, emphasize their unique structural attributes, and link them to viral life cycle, pathogenesis and disease progression. We will address their potential as novel targets for drug discovery and propose future directions to explore lncRNA structure and function relationship.

Consumer protection in the financial market has several dimensions. From a formal point of view, consumer rights are guaranteed by law. Market asymmetries are eliminated through the obligation to provide consumers with complete and objective information about financial products and services, honest marketing communication and professional sales practices. Programs are implemented in schools and the media to promote knowledge and responsible use of financial products and services. Despite the efforts made, the number of incorrect and suboptimal financial decisions is so high that the risk of households falling into excessive debt remains significant. The limited effectiveness of the law led to the claim that only effective education can reduce the risk of suboptimal financial decisions. Unfortunately, the efforts made in this area are not fully satisfactory. The aim of the article is to review scientific research on the financial knowledge of consumers in Central Europe and compare it to the results of a study conducted in Poland in January 2024. The results of the analysis could indicate the direction of further research on the possibilities of eliminating suboptimal financial decisions of consumers without limiting - for their better protection - access to financial products.

Rice canopy height and density are directly usable crop phenotypic traits for the direct estimation of crop biomass. Therefore, it is crucial to rapidly and accurately estimate rice canopy phenotypic parameters. To achieve non-destructive detection and estimation of essential phenotypic parameters in rice, a platform based on LiDAR point cloud data for rice phenotypic parameter detection was established. Data collection of rice canopy layers was performed across multiple plots. The LiDAR-detected canopy top point clouds were selected using a method based on the highest percentile, and the rice canopy surface model was calculated. Canopy height estimation was the difference between ground elevation and percentile value. To determine the optimal percentile defining the rice canopy top, testing was conducted incrementally from 0.8 to 1 with an increment of 0.005. The optimal percentile value was found to be 0.975. The root mean square error (RMSE) between LiDAR-detected canopy height and manually measured canopy height was calculated. The prediction model based on canopy height (R2=0.941, RMSE=0.019) exhibited a strong correlation with actual canopy height. Linear regression analysis was conducted between gap fraction of different plots and manually detected average Leaf Area Index (LAI) of rice canopy. Prediction models for canopy LAI based on ground return counts (R2=0.24, RMSE=0.1) and ground return intensity (R2=0.28, RMSE=0.09) showed strong correlations but had lower correlation with rice canopy LAI. Regression analysis was performed between LiDAR-detected canopy height and manually measured rice canopy LAI. The results indicated that the prediction model based on canopy height (R2=0.77, RMSE=0.03) was more accurate.

Infrared and visible image fusion technologies are used to characterize the same scene by diverse modalities. However, most existing deep learning-based fusion methods are designed as symmetric networks, which ignore the differences between modal images and lead to the source image information loss during feature extraction. In this paper, we propose a new fusion framework for the different characteristics of infrared and visible images. Specifically, we design a dual-stream asymmetric network with two different feature extraction networks to extract infrared and visible feature maps respectively. The transformer architecture is introduced in the infrared feature extraction branch, which can force the network to focus on the local features of infrared images while still obtaining their contextual information. And the visible feature extraction branch uses residual dense blocks to fully extract the rich background and texture detail information of visible images. In this way, it can provide better infrared targets and visible details for the fused image. Experimental results on multiple datasets indicate that DSA-Net outperforms state-of-the-art methods in both qualitative and quantitative evaluations. In addition, we also apply the fusion results to the target detection task, which indirectly demonstrates the fusion performances of our method.

When the minimal length approach emerging from noncommutative Heisenberg algebra, generalized uncertainty principle (GUP), and thereby integrating gravitational fields to this fundamental theory of quantum mechanics (QM) is thoughtfully extended to Einstein field equations, the possible deformation of the metric tensor could be suggested. This is a complementary term combining the effects of QM and general relativity (GR) and comprising noncommutative algebra together with maximal spacelike four–acceleration. This deformation compiles with GR as curvature in relativistic eight–dimensional spacetime tangent bundle, generalization of Riemannian spacetime, is the recipe applied to derive the deformed metric tensor. This dictates how the affine connection on Riemannian manifold is straightforwardly deformed. We have discussed the symmetric property of deformed metric tensor and affine connection. Also, we have evaluated the dependence of a parallel transported tangent vector on the spacelike four–acceleration given in units of L, where L = rℏcG3 is a universal constant, c is speed of light, and ℏ is Planck constant, and G is Newton’s gravitational constant.

Pakistan is under developing country and it has an unpredictable market nature of shareholder-investors observe the company’s performance. This research could help to companies in understanding financial behavior, attitude and investors’ satisfaction in stock trade. Financial behavior is comparatively new subject in Pakistan therefore; this study has examined the financial behavior and attitude of investors. The behavioral finance that has been attempted to understand the positive experiences influences investors’ financial behavior. This study has find out that investor satisfaction is strongest in influence of positive financial behavior of investor and trader in stock trading; positive experience and brokers suggestions are strengthens the investment decision of investors and increases behavior loyalty to prefer over competitor. The main purpose of research to determine the effect of financial behavior on investors’ attitude and behavioral loyalty and investors’ satisfaction to preference over competitor. The research framework links with experiences in stock trade for positive (negative) experiences, attitude and financial behavior is developed. The research framework is measured data from sample of Karachi and Karachi Stock Exchange; the data is analyzed in smart PLS based on PLS-SEM. This study focused on trading experience with company’s active investors and traders in banking industry in Pakistan. The future research could be research in other sectors with inter-related issue of investors and traders (brokers) in stock trade. This is the first study in this research area; this study will be determine the experiences with positive (negative) financial behavior, attitude, satisfaction and behavioral loyalty of investors and traders in stock trade. Therefore, adding in this area of study which will help understanding the investors and traders attitude, preference and financial behavior in financial market.

Aerated concrete, which is manufactured from binding material, sand, foaming agent and water, is currently being utilized in the construction industry because of its lightweight and durability. The binding material, cement, along with other materials used in the concrete produces huge carbon footprints during its fabrication. The utilization of natural aggregates name as coarse aggregates depletes the natural resources of the country. Therefore, huge amounts of agricultural wastes have led scholars to investigate the effectiveness of replacing conventional materials used in concrete with agricultural wastes. In the current study, rice husk ash (RHA) was used as supplementary cementing material, thereby reducing the amount of cement used in aerated concrete (AC) mixture will reduce carbon footprints. The experimental and numerical analysis were conducted to investigate structural behavior of reinforced RAC- B beams subjected to flexural load. Parametric study on structural performance of RAC- B beam under flexure were conducted using finite element analysis (FEA). From the experiment and FEA. Results from the parametric study showed that RAC-10%RHA-B with higher depth structurally performed better compared to RAC-B under flexure with greater load carrying capacity, lesser maximum deflection, and less cracks developing in the tension area.

Previous studies on the water-energy nexus mainly focused on the calculation and comparison of resource consumption at the national or regional level, lacking interprovincial sector-sector transfer analysis. In this study, the intensity of water and energy consumption of various sectors in China were calculated, the key nodes and paths of resource networks were identified, and countermeasures for resource conservation were proposed from the new perspective of the “dual saving” and “bidirectional saving” of water and energy. The results showed that the metallurgical industry (Me) in Jiangsu and the chemical industry (Ch) in Hebei and Jiangsu had high node strength in the water and energy network and were key sectors in China with “dual saving” effects of water and energy. The construction industry, Ch, Me in Jiangsu, electricity and hot water production and supply industry in Beijing, and Me in Hebei had high node strength in the water-related energy network and energy-related water network, significantly supporting the “bidirectional saving” effect of water and energy in China. The electrical equipment industry (El) in Jiangsu→El in Zhejiang, El in Zhejiang→El in Shanghai frequently appeared in key paths, which could effectively reduce the resource consumption of the entire network.

The Linear Fresnel Reflectors are a solar concentration technology that is versatile and can serve many industrial processes or thermal conditioning. Such collectors entail a certain footprint, generating shading on the surface where they are installed. This effect is rarely quantified but may play an indirect role on the surface below. When installed on a roof, the solar radiation heats the building less. In places where the annual heating demand is higher than the cooling demand, this constitutes an asset. However, this becomes a disadvantage when the cooling demand is higher annually than the heating demand. Essentially, the reduced solar radiation allows the growth of plants that would not grow without the shade provided by the collector. The present paper is a quantitative analysis of such shading based on the Linear Fresnel Reflector of the Cyprus Institute. The work was conducted using the Tonatiuh++ ray-tracing software to determine the annual radiation blocking. A total of four years of actual meteorological measurements were applied directly to the ray-tracing model.

This study proposes an image recognition method to assist swine farm managers in collecting health data related to pig feeding and excretion. Analyzing the correlation between sow health data and indoor air quality in the pigsties revealed significant influences of air quality indicators on sow health. Increased levels of TVOC, CO2, and temperature were found to negatively affect feeding health, while increased temperature, humidity, and PM10 were found to negatively impact excretion health. These findings provide a basis for evaluating variables when constructing future sow disease prediction models. Analyzing the correlation between pig health status and air quality can help swine farm managers improve sow production environments, reduce disease risks, enhance production efficiency, and provide valuable insights for future research on disease prediction models.

Many buildings built before the energy performance regulations are in a situation of thermal discomfort and energy inefficiency. The creation of intelligent environments advances towards new opportunities, based on real-time monitoring and on the development of sensors and technologies. Furthermore, the standards for building automation and electronic systems enable interoperability and interconnection between control devices and systems. The application of soft computing has significantly improved the energy efficiency, however, requires prior assessment to design the automation functions. Temperature, humidity, air quality, occupancy and energy consumption are the most common measured parameters, but the relationship with other operational variables such as occupancy or some building states remains as a research challenge. This article presents a methodology to develop the automatization of an existing large public building. The methodology consists of three stages: 1. Assessment and diagnosis to set appropriate actions using EN ISO 52120-1. 2. EN 50090 for open communication networks, and EN ISO 52120-1 to assign the technical building management. 3. System control deploying of low-cost and low-consumption input and output devices. It has been proved that it is possible to effectively automate an obsolete building with a low cost, open source system that can be easily applied in other buildings.

The present study examined and compared the effects of high- and low-molecular weight (MW) chitosan, a nutraceutical, on intestinal and liver lipid metabolism in rats fed with high-fat diet. Both high- and low-MW chitosan decreased liver weight, elongated small intestine, improved the dysregulation of blood lipids and liver fat accumulation, and increased fecal lipid excretion in high-fat diet-fed rats. Supplementation of both high- and low-MW chitosan significantly inhibited the decreased phosphorylated AMP-activated protein kinase (AMPK)α and peroxisome proliferator-activated receptor (PPAR)α protein expressions and the increased lipogenesis/cholesterogenesis-associated protein expressions (sterol regulatory element binding protein (SREBP)1c, SREBP2, and PPARγ) and the decreased apolipoprotein (Apo)E and microsomal triglyceride transfer protein (MTTP) protein expressions in the livers of high-fat diet-fed rats. Both high and low-MW chitosan supplementation could also suppress the increased MTTP protein expression and the decreased angiopoietin-like protein (Angptl)4 protein expression in the intestines of high-fat diet-fed rats. Comparison between high and low-MW chitosan, high-MW chitosan has a higher efficiency than low-MW chitosan on the inhibition of intestinal lipid absorption and the increase of hepatic fatty acid oxidation, which can improve liver lipid biosynthesis and accumulation.

Despite the Australian Government’s attempts to reduce domestic violence (DV) incidences, impediments that exist within the social and health systems and interventions designed to identify DV victims may contribute to female victims’ reluctance to disclose DV experiences to their primary healthcare providers. This scoping review aimed to provide the state of evidence about reasons for such reluctance to reveal DV, symptoms and comorbidities patients present to healthcare providers, detection and interventions in the clinical setting, and recommendations to generate more effective responses to DV. Female victims are reluctant to reveal DV because they do not trust or believe that general practitioners can help them to solve the issue, they do not acknowledge they are in an abusive relationship or are unaware that they are, or had been, victims of DV. The most common symptoms and comorbidities victims present with are sleep difficulties and fear. DV screening programs are the most prominent intervention type within Australian primary health services. This scoping review provides formative evidence that further research and interventions are required to increase professional skills, knowledge, sensitivity and referral processes among primary healthcare professionals treating patients experiencing DV in Australia.

Stage of cancer is a discrete ordinal response that indicates aggressiveness of disease and is often used by physicians to determine the type and intensity of treatment to be administered. For example, the FIGO stage in cervical cancer is based on the size and depth of the tumor as well as the level of spread. It may be of clinical relevance to identify molecular features from high-throughput genomic assays that are associated with stage of cervical cancer, to elucidate pathways related to tumor aggressiveness, identify improved molecular features that may be useful for staging, and identify therapeutic targets. High-throughput RNA-Seq data and corresponding clinical data (including stage) for cervical cancer patients has been made available through The Cancer Genome Atlas Project (TCGA). We recently described penalized Bayesian ordinal response models that can be used for variable selection for over-parameterized datasets such as the TCGA-CESC dataset. Herein, we describe our ordinalbayes R package, available from the Comprehensive R Archive Network (CRAN), which is capable of fitting cumulative logit models when the outcome is ordinal and the number of predictors exceeds the sample size, P>N, such as for TCGA data. We demonstrate use of this package through application to TCGA cervical cancer dataset. Our ordinalbayes package can be used to fit models to high-dimensional dataset and effectively performs variable selection.

Chlorophyll a concentration (Chl) is a key variable to estimate primary production (PP) through ocean color remote sensing (OCRS). Accurate Chl estimate is crucial for better understanding of spatio-temporal trends of PP over recent decades as a consequence of climate change. However, a number of studies have reported that currently operational chlorophyll a algorithms perform poorly in the Arctic Ocean (AO), which is mainly caused by the interference of colored and detrital material (CDM) with the phytoplankton signal in the visible part of the spectrum. To determine how and to what extent that CDM would bias the estimation of Chl, we evaluated the performances of 8 currently available ocean color algorithms: OC4v6, OC3Mv6, OC3V, OC4L, OC4P, AO.emp, GSM01 and AO.GSM. Our results suggest that the empirical AO.emp algorithm performs the best overall, but for waters with high CDM (acdm(443) > 0.067 m-1), which is of much interest in the Arctic, it is the two semi-analytical GSM models that show better performance. Besides, sensitivity analyses using an Arctic spectrally- and vertically-resolved primary production model further show that errors in Chl mostly propagate proportionally to PP estimates with 7% amplification at maximum. We aslo demonstrate that the higher level of CDM relative to Chl in the water column, the larger the bias would occur in both Chl and PP estimates. Although the AO.GSM overall best performs among algorithms tested in the present study, it tends to fail for a significant number of pixels (16.2% observed in the present study) particularly for waters with high CDM. Our results suggest that an algorithm that provides reasonable Chl estimates for a wide range of optically-complex Arctic waters is still required.

This project involves the development of Fire Suppression System (FSS) leveraging of Home automation system using Graphical System design (LabVIEW) software and Arduino microcontroller for real-time monitoring and control. The system integrates an Infrared (IR) flame sensor, an MQ2 gas sensor to detect and suppress fire hazards efficiently. The LabVIEW interface facilitates real-time monitoring of sensor data, allowing users to visualize and analyze the environmental conditions. Through this system, fires are automatically subdued, enhancing safety without requiring human intervention. This advances fire safety by swiftly containing threats and minimizing potential damage.

Deforestation brings vast and detrimental impact on the environment, economy, and social aspects of community. Thus, it is important to assess and analyze deforestation to inform the decision maker that oversees issued policy and development strategies. The present study aims to characterize deforestation in Central Kalimantan between 2006 - 2020. Utilized land cover map issued by Indonesian Ministry of Environment and Forestry, we analyzed the change in natural forest cover using Remote Sensing and Geographical Information System (GIS) to find the rate the trend, location, and land cover replacement of deforestation in Central Kalimantan Province, Indonesia. The research found that during the period Central Kalimantan lost 1.5 million ha of natural forest with the rate of deforestation 117,000 ha/year. In general, the deforestation shown decrease trend and fluctuated during the period. Deforestation majority takes place at secondary swamp and dry forest that are located at south part of the island. Most of deforestation resulted shrubs, plantations, and agriculture land. The finding of this research could be used as a base to determine the target location for rehabilitation strategy and approach to prevent further deforestation.

Ethiopia has decades of experience in implementing land and water management interventions. Nonetheless, there remains persisting challenges to follow an adaptive management (AM) approach in efforts of restoring and transforming agricultural landscapes. This review was carried out to synthesize evidences on the impact on agricultural landscapes following the implementation of land and water management practices and to evaluate the use of AM approaches. We explored how elements of the structures and functions of landscapes have been transformed, and how the components of AM, such as structured decision-making and learning processes, have been applied. Despite numerous environmental and economic benefits of land and water management interventions in Ethiopia, this review revealed gaps in AM approaches. These include: (i) insufficient efforts in relation to evidence based contextualization of interventions, (ii) insufficient efforts in monitoring of bio-physical and socio-economic processes and changes post implementation, (iii) lack of trade-off analyses, and (iv) inadequacy of local community engagement and provision of feedback. Given the many uncertainties we must deal with, efforts to restore and transform agricultural landscapes cannot follow a business-as-usual approach. Future investment, in AM approach, tailored to the needs and context would help to achieve the goals of sustainable agricultural landscape transformation. The success depends on three interdependent pillars of action: the ability to make a robust, co-developed plan of interventions, the ability to continuously monitor changes based on key variables, and to learn from the knowledge generated and apply the learning as implementation evolves.

Recent advances and demands in clinical applications drive a large amount of research to hydroxyapatite (HA) composite coatings fabricated by plasma spray. However, lower degree of HA crystallinity related to high temperature exposure in plasma spray usually leads to rapid weakening and disintegration of HA coatings and often promotes inflammatory responses in the surrounding tissue. In this research, graphene nanosheet (GNS) reinforced HA coatings were fabricated using plasma spray and followed by heat and hydrothermal treatment (hereafter referred to as thermal treatment). The addition of GNSs resulted in competing phenomenon to influence HA crystallinity viz. increased portion of the partially melted/unmelted zones and higher cooling rate during splat formation, leading to slight increase in HA crystallinity (~46.0-51.3%) in the as-sprayed coating. XRD and FTIR results showed that thermal treatment was capable of inducing significant transformation of amorphous HA to the crystalline form and removing other foreign non-HA compounds through regaining OH- ion, and therefore HA coatings displayed ~45.5-47.1% improvements in HA crystallinity regardless of addition or not of the GNS nanofillers. Microstructure observations revealed that thermal treatment enabled microcrack propagation due to stresses caused by crystallisation and phase transformations, and the residual partially melted/unmelted zone of the thermally treated GNS/HA coating was significantly decreased in size. More importantly, the added GNSs contributed greatly to the significant increase in surface nanoroughness of the thermally treated HA coatings owing to the fact that much more structural defects along with the GNSs mainly induced by thermal treatment might act as nucleation sites to accelerate HA nanoparticle precipitation, which would be beneficial for the improved adhesion strength of the osteoblast cells on the coating surface.

Slow and controlled release systems for drugs, have attracted increasing interest recently. A highly efficient metal-organic gels (MOGs) drug delivery carrier, i.e., MIL-100(Al) gels, has been fabricated by a facile, low cost and environment friendly one-pot process. The unique structure of MIL-100(Al) gels leads to a high loading efficiency (620 mg/g) towards doxorubicin hydrochloride (DOX) as a kind of anticancer drugs. DOX-loaded MOGs exhibited high stability under physiological conditions and sustained release capacity of DOX for up to 3 days (under acidic environments). They further showed sustained drug release behavior and excellent antitumor effects in in vitro experiments on HeLa cells, in contrast with the extremely low biotoxicity of MOGs. Our work provides a promising way for the anticancer therapy, by utilizing this MOGs-based drug delivery system, as an efficient and safe vehicle.

The most commonly used real-time augmentation services in China are International GNSS Service (IGS) real-time service, PPP-B2b service, and BeiDou Satellite-Based Augmentation System (BDSBAS) dual-frequency augmentation service. However, the research on the performance evaluation, comparison and application scope of these three products is still unknown and unrevealed. This article introduces methods for obtaining real-time augmentation information and real-time orbit and clock offset recovery. Based on real-time orbit and clock offset accuracy, positioning accuracy, and positioning availability, it systematically evaluates the performance of CNES, PPP-B2b, and BDSBAS augmentation information. The results indicate that the radial accuracy of CNES and PPP-B2b real-time orbit products is consistent, and the Root Mean Square (RMS) is better than 5 cm. CNES can achieve centimeter-level accuracy in both along-track and cross-track components, surpassing the decimeter-level accuracy of PPP-B2b. Both services demonstrate consistent accuracy in real-time clock offset, with PPP-B2b showing similar standard deviations (STD) of 0.16 ns for different satellites. However, for CNES, the STD of real-time clock offset varies for GPS, BDS-3 MEO, and BDS-3 IGSO satellites, with values of 0.10 ns, 0.19 ns, and 0.60 ns, respectively. The accuracy and availability of the two PPP services exhibit the same levels, with centimeter-level accuracy achieved after convergence and positioning availability exceeding 99%. Therefore, the difference between the two services in application areas depends on the acquisition of augmentation information. However, BDSBAS, which concentrates on code observations, demonstrates lower accuracy in real-time orbit and clock offset, positioning accuracy, and positioning availability compared to the other two services. Its primary application is in the aviation and maritime domains, where there is a greater need for service integrity, continuity, and reliability.

With rising rates of human obesity, the study aimed to determine the relationship between maternal diet-induced obesity and offspring morphometrics and behaviour in mice. Pregnant and lactating female mice fed a diet high in fat and sugar (HFHS) commonly consumed by human populations showed decreased food, calorie, and protein intake but increased adiposity at the expense of lean mass. The pre-weaning body weight of HFHS offspring was reduced for the first postnatal week but not thereafter with HFHS female offspring having higher body weights by weaning, due to continuing higher fractional growth rates. Post-weaning, there were minor differences in offspring food and protein intake. Maternal diet, however, affected fractional growth rate and total body fat content of male but not female HFHS offspring. Maternal diet did not affect offspring locomotor activity or social behaviour in either sex. Both male and female HFHS offspring displayed reduced anxiety-related behaviours with sex differences in particular aspects of the elevated plus maze task. In the novel object recognition task, performance was impaired in male but not female HFHS offspring. Collectively, the findings demonstrate that maternal obesity alters the growth, adiposity, and behaviour of male and female offspring, with sex-specific differences.

Waste management is an unavoidable technological operation in the process of raw material extraction. The main characteristic of this technological operation is the handling of large quantities of waste material, which can amount to several hundred million cubic metres. Working with this amount of material usually requires high-capacity systems for excavation and loading, a large fleet of trucks for haulage, construction, and maintenance of a complex roads network, use of a significant area of land in order to achieve the required capacities, etc. At the same time, this operation must comply with all administrative and environmental standards. Therefore, optimising waste rock management (particularly haulage and dumping) has the potential to significantly improve the overall value of the project. This paper presents a hybrid model for the optimisation of waste dump design and site selection. The model is based on different mathematical methods (genetic algorithm, analytic hierarchy process and heuristic methods) adapted to different aspects of the problem. The main objective of the model is to provide a solution (in analytical and graphical form) for the draft waste dump design, on the basis of which the final waste dump design can be defined.

This paper addresses the alliance route network design problem considering uncertainty of unit transportation cost. An alliance route network is constructed based on the hub-and-spoke (HS) network , in which airlines can achieve inter-area passenger transport through their international gateways. The design problem is formulated with a robust model containing a set of uncertain cost parameters. The model is established based on the three-subscript model of the HS network. A case study collected from real-world data is used to test the proposed model. The results show that the robust solution can reduce the impact of cost uncertainty.

The COVID-19 pandemic has created extraordinary challenges and prompted remarkable social changes around the world. The implications of the novel coronavirus and the public health control measures that have been implemented to mitigate its impact are likely to be accompanied by a unique set of consequences for specific populations living in low income-countries that have fragile health systems and pervasive social-structural vulnerabilities. This paper discusses the implications of COVID-19 and related public health interventions for children and young people living in Eastern and Southern Africa. Actionable prevention, care, and health promotion initiatives are proposed to attenuate the negative effects of the pandemic and government-enforced movement restrictions on children and young people.

Humanity’s social and economic development has been challenged by a range of adversities over the millennia that have caused widespread and unimaginable suffering. At the same time, these challenges have forced humans to evolve more wisely, overcoming adversity through creativity and leading to advancements in science and technology, medicine, ethics and legal systems, and socio-political systems. The dynamics of risks and opportunities caused by COVID-19, in the built, cyber, social and economic environments, present opportunities for deepening our understanding of resilient and sustainable development and infrastructure. This article reflects on five lessons that COVID-19 is teaching us about what it means to develop sustainably through the lens of transportation: (1) sustainable development planning and analytical frameworks must be comprehensive, for long-term sustainability; (2) multi-modal transportation is a superior vision for sustainable development than any one particular mode; (3) tele-activities are part of an effective infrastructure sustainability strategy; (4) economic capital is critically important to sustainable development even when it is not a critical existential threat, and, (5) effective social capital is essential in global disaster resistance and recovery, and can and must be leveraged between fast-moving and slow-moving disasters. Resilient and sustainable infrastructure will continue to be critical to addressing evolving natural and man-made hazards in the 21^st Century.

In this study, we evaluated the potential of fungal endophytes to control yellow rust in wheat (Triticum aestivum L.) as endophytes are beneficial microbes and alternate to pesticides for confronting pathogens. The in-vitro efficacy of the fungal endophytes isolated from different desert plants was evaluated and the best four namely Colletotrichum lindemuthianum, Piriformospora indica, Acremonium lolii and Trichoderma viride were selected. Seeds of two susceptible wheat genotypes namely Fareed-06 and Shafaq-06 obtained from screening experiment were inoculated by dipping in four endophytic spore suspensions and were sown using randomized complete block design under factorial arrangement. Data concerning about area under disease progress curve, final disease severity percentage, coefficient of infection,1000- grains weight and grain yield were recorded. Results showed that endophyte P. indica showed significant decrease in final disease severity (FDS) and area under disease progress curve (AUDPC), resultantly 12.2% grain yield gain in rust susceptible wheat genotypes of Fareed-06 and Shafaq-06 followed by the endophytes T. viride, C. lindemuthianum and A. lolii with the grain yield gain of 10.6%, 06.2% and 04.2% respectively. In crux, fungal endophytes are valuable microbes which can be employed to induce tolerance against P. striiformis in yellow rust vulnerable areas for better and sustainable wheat production.

This paper intends to delve deeply into the current understanding of the ways in which the transition from a central-based economy to an economy relying on free competition, has led to changes in the big urban centres, bringing about a change in the relationships with the suburban areas. The authors take into account the high population density, the lack of space and the elevated price of terrains inside the big cities, hence urban functions migrate beyond the administrative boundaries, thus favouring the process of suburbanization. Within this context, commercial forces are shifted, migrating from the centre to the urban peripheries, or even outside them. This research is based on a comprehensive process of participative investigation (2012-2022) in Bucharest, Ro-mania’s capital city. The research relies on field investigation, statistical and quantitative analyses and bibliographical sources. The conclusions rely primarily on the idea that political changes cannot be separated from economic, cultural and environmental ones, highlighting globalizing flows and the development of big cities. Industrial activities, strongly developed within a central-based economy, have significantly declined, partly compensated for by the development of the tertiary sector and of commercial services, in particular, leading to a functional reconversion of the urban peripheries and of suburban areas. The conclusions suggest that it is very important to be highly careful towards the dilemmas and provocations ensuing from uncontrolled urban growth, therefore several measures of urban planning should be taken with a view to achieving a better co-operation between urban stakeholders and those from the metropolitan areas so as to attain some common objectives in infrastructure in order to reach an integrated regional development.

Violence against paramedics has been described as a ‘serious public health problem’ but one that remains ‘vastly underreported’, owing to an organizational culture that stigmatizes reporting – hindering efforts at risk mitigation in addition to creating a gap in research. Leveraging a novel reporting process developed after extensive stakeholder consultation and embedded within the electronic patient care record, our objective was to provide a descriptive profile of violence against paramedics in a single paramedic service in Ontario, Canada. Between February 1, 2021, through January 31, 2023, a total of 374 paramedics in Peel Region (48% of the workforce) generated 941 violence reports, of which 40% documented physical (n=364) or sexual (n=19) assault. The violence was typically perpetrated by patients (78%) and primarily took place at the scene of the 9-1-1 call (47%); however, violent behavior frequently persisted or recurred while in transit to hospital and after arrival. Collectively, mental health, alcohol, or drug use were listed as contributing circumstances in 83% of violence reports. In all, 81 paramedics were physically harmed because of an assault. On average, our data correspond to a paramedic filing a violence report every 18 hours, being physically assaulted every 46 hours, and injured every 9 days.

Melt mixing is a convenient method to prepare polymer nanocomposites, but the extent of the dispersion of the solid filler reached is often limited, and may compromise the anticipated performance of these materials during service. Since the efficiency of extensional flows on dispersion is now well recognized, several mixers were designed with the aim of inducing both shear and extensional flow components. This work combines experimental and numerical data to better understand the kinetics of the dispersion of graphite nanoplates in a polypropylene melt, using a mixing device that consists of a series of stacked rings with equal outer diameter and alternating larger and smaller inner diameters, thus creating a series of converging/diverging flows. Numerical simulation of the flow using the opensource OpenFOAM software assuming both inelastic and viscoelastic responses predicted the velocity, streamlines, flow type and shear and normal stress fields for the mixer. Experimental and computed data were combined to determine the trade-off between the local degree of dispersion of the PP/GnP nanocomposite, measured as Area ratio, and the absolute average value of the hydrodynamic stresses multiplied by the local cumulative residence time. From considerations based on a theoretical approach to dispersion, the cohesive strength of the GnP agglomerates studied was estimated to be in the range 3 - 10kPa.

The effect of Al or Cu content on the microstructure and mechanical properties of continuous casting and extrusion Zn alloys has been studied by room temperature tensile test, X-ray diffraction, and scanning electron microscope. With the increase of Al content, the microstructure of continuous casting and extrusion Zn alloys slightly coarsens and the lamellar eutectic structure increases. The changes in the above structural factors result in a slight decrease in strength and a significant increase in elongation of Zn-Al alloys. The strength of Zn alloys increases as the Cu content increases, due to the increased content and size of the second phase in the Zn alloys. This means that the mechanical properties of Zn alloys can be adjusted by continuous casting and extrusion process, and the improvement of equipment capacity can improve the structure and morphology of the alloys.

Habitat loss and fragmentation are of concern to conservation biologists worldwide. However, not all organisms are affected equally by these processes, thus it is important to study the effects of living in fragmented habitats on species that differ in lifestyle and habitat requirements. In this study we examined dispersal and connectivity patterns of rodents, one endemic (Eliurus myoxinus) and one invasive (Rattus rattus), in two landscapes containing forest fragments and adjacent continuous forest patches in northwestern Madagascar. We generated genomic (RADseq) data for 66 E. myoxinus and 81 R. rattus individuals to evaluate differences in genetic diversity as well as inbreeding and connectivity in two landscapes. We found higher levels of inbreeding and lower levels of genetic diversity in E. myoxinus compared with R. rattus. We observed related dyads both within and between habitat patches and positive spatial autocorrelation at lower distance classes for both species, with a stronger pattern of spatial autocorrelation in R. rattus. Across each site we identified contrasting migration rates for each species, but these did not correspond to habitat-matrix dichotomies. The relatively low genetic diversity in the endemic E. myoxinus suggests ecological constraints that require further investigation.

Helicases are proteins that use the energy of ATP to unwind nucleic acids and to remodel protein-nucleic acid complexes. They are involved in almost every aspect of the DNA and RNA metabolisms and participate in numerous repair mechanisms that maintain cellular integrity. Helicases are classified into 6 superfamilies (SF1-6). The archaeal Lhr-type proteins are SF2 helicases that are mostly uncharacterized. They have been proposed to be a DNA helicase that acts in DNA recombination and repair processes in Sulfolobales and Methanothermobacter. In parallel, a protein annotated as an Lhr2 protein was also found in the network of proteins involved in RNA metabolism in Thermococcales. To this respect, we performed in-depth phylogenomic analyses to report the classification and taxonomic distribution of Lhr-type proteins in Archaea, and to better understand their relationship with bacterial Lhr. Furthermore, with the goal of envisioning the role(s) of aLhr2 in archaeal cells, we deciphered the enzymatic activities of aLhr2 from Thermococcus barophilus (Tbar). We showed that Tbar-aLhr2 is a DNA/RNA helicase acting on DNA:RNA and RNA:RNA duplexes and proposed that aLhr2 helicases are involved in processes dependent of DNA and RNA transactions.

Flow sensing in hostile environment is of increasing interest for applications in automotive, aerospace, and chemical and resource industries. Compared to their counterparts, thermal flow sensors are attractive candidates due to the ease of fabrication, lack of moving parts and higher sensitivity. Recently, a number of thermal flow sensor prototypes have been reported in the literature demonstrating the measurement of fluid flows under hostile conditions. This paper summarizes the concept of thermal flow sensing, operational modes and transduction mechanisms. Then, the choice of materials and their corresponding properties are presented in details. The paper also reports recent progress in the development of thermal flow sensors for harsh environment. In addition, the issues and considerations in packaging are reviewed. Finally, we conclude the review with the future prospects.

Radio astronomical observations at millimeter and submillimeter wavelengths are a very important tool of astrophysical research. However, there is a huge area in the northern Eurasia, including the whole Russian territory, which lacks sufficiently large radio telescopes effectively operating at these wavelengths. In this review we describe our long-term efforts to find suitable sites for such radio telescopes in this area, that is, sites with good atmospheric transparency at millimeter and submillimeter waves. We describe methods and instruments used for measurements and evaluations of the atmospheric opacity. They include special radiometric systems, which are used for estimations of the atmospheric opacity from the sky brightness measurements. Evaluation of the precipitable water vapor from such measurements by the artificial neural network is discussed. Alternative approaches use global atmospheric models and signals of the Global Navigation Satellite Systems. To date, a long-term radiometric monitoring has been performed at several candidate sites and atmospheric conditions for many sites have been evaluated using global atmospheric models. Several sites with the best atmospheric transparency at millimeter and submillimeter wavelengths have been selected. They can be effectively used for astronomical observations at least in the major atmospheric transparency windows at 1.3 mm and 0.85 mm. These results can be also used for space communications and radar systems.

Survivors of sexual and gender-based violence (SGBV) are often hindered in their quest to access quality healthcare. This could complicate the achievement of the laudable SDG Target 3.7. The study used an ethnographic approach to solicit information from health providers, adolescents, and young women (AYW) in 10 communities from Lagos and Ibadan; two major cities in Nigeria. Findings indicated that the structural system of services provided in the health services at the primary healthcare level was limited, which posed a great challenge in AYW’s utilization of services for sexual and gender-based violence (SGBV). Some of the challenges identified by health providers included non-existing counseling services, rehabilitation centers, referral problems, and a lack of training for health providers in handling victims of SGBV. The study provided the context of the health providers’ inadequacy and structural problem of health services in providing comprehensive support services to victims of SGBV like adolescents and young women in the slum setting. This poses a barrier to the utilization of services by the survivors. Necessary inclusive services that will meet the need of the victims of SGBV should be in place at primary healthcare centers close to the people in the community for accessibility.

Introduction: The identification of some prognostic markers in head and neck cancers (HNC) is necessary for the stratification of the therapeutic approach with benefits in increasing treatment response rates and limiting the toxic side effects of treatments. Neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and pallets-to-lymphocyte ratio (PLR) are currently validated as cheap and accessible biomarkers in different types of solid tumors. The purpose of the study was to evaluate the possible biomarker value of NLR, PLR and MLR recorded pre-treatment (radiotherapy/chemotherapy) for prognostic purposes in HNC. Materials and methods: The study included 190 patients with HNC included in the oncology record in the oncology outpatient clinic of the Craiova County Emergency Hospital starting from January 2002 and deceased until December 2022. Among them, 40 patients treated multimodally in the Clinic were included in the study of Oncology of the Craiova County Emergency Hospital for which the pre-treatment value (chemotherapy/radiotherapy) of NLR, PLR and MLR could be calculated. Overall survival (OS) values were correlated with NLR, PLR and MLR. Results: Median values for NLR, PLR and MLR were 6.15 (1.24-69), 200.79 (61.3- 1775.0) and 0.53 (0.12-5.5) respectively. In the study, the mean values for NLR, PLR and MLR of 2.88, 142.97 and 0.36 respectively were obtained. Median OS in the study group was 11 months (1-120). Although a negative Pearson`s correlation, the relationship between your variables was only weak, values R =.07, p=.67; R=.02, p=.31 and R=07, p=.62 being related with NLR, PLR and MLR respectively correlation with overall survival (OS). The median values of NLR, PLR and MLR were calculated (1.53, 90.32 and 0.18 respectively) for HNC cases with pre-treatment values of NLR <2 and for HNC cases with NLR values ≥6 (23.5, 232.78 and 0.79 respectively). Median OS for cases with NLR<2 and NLR≥6 were 17.4 and 13 months, respectively. Conclusions: The negative correlations of NLR, PLR and MLR with OS reported in the study are in accordance with the data reported in the literature for locally advanced recurrent and metastatic HNSCC cases. The comparative analysis of the data in the group with NLR<2 and NLR≥6 highlights an advantage of 4.4 months in median OS in favor of the group with low values of NLR. Being cheap and accessible, these markers could change the therapeutic approach even in centers with limited resources. The role of borderline NLR values as a prognostic factor in HNSCC must also be defined. PLR and MLR are less evaluated as biomarkers but the study demonstrates their potential to be used as prognostic biomarkers, it remains to be clarified if their inclusion in multivariable models along with NLR would bring a benefit

Raman Spectroscopy has long been anticipated to augment clinical decision making, such as classifying oncological samples. Unfortunately, the complexity of Raman data has thus far inhibited its routine use in clinical settings. Traditional machine learning models have been used to help exploit this information, but recent advances in deep learning have the potential to improve the field. However, there are a number of potential pitfalls with both traditional and deep learning models. We conduct a literature review to ascertain the recent machine learning methods used to classify cancers using Raman spectral data. We find that while deep learning models are popular, and ostensibly outperform traditional learning models, there are many methodological considerations which may be leading to an over-estimation of performance: primarily, small sample sizes which compound upon sub-optimal choices regarding sampling and validation strategies. Amongst several recommendations is a call to collate large benchmark Raman datasets, similar to those that have helped transform digital pathology, which researchers can use to develop and refine deep learning models.

Teledermatology, the dermatological consultation and diagnosis via digital communication technologies, has become increasingly important in modern healthcare. The integration of teledermatology into clinical practice has gained significant interest, especially during the COVID-19 pandemic. Numerous studies have shown the effectiveness and reliability of teledermatology, with high levels of patient satisfaction and diagnostic accuracy. Pathpoint® eDerma is a cloud-based dermatology platform that aims to streamline the documentation and management of dermatological conditions. It offers several clinical benefits, including faster diagnosis, reduced unnecessary procedures, improved access to care, and cost savings. The platform follows a comprehensive risk management plan and complies with safety regulations. It undergoes regular recertification and reviews to ensure its safety and effectiveness. The clinical evaluation of eDerma confirms its ability to deliver significant clinical benefits while effectively mitigating risks. The benefit-risk ratio of eDerma is highly acceptable, supporting its use in clinical settings to enhance dermatological care.

Exploring the determinants of biological community structure is important not only for understanding the formation of the community, but also for promoting its biodiversity conservation. We monitored butterfly communities in a grassland and woodland area of Mount Fuji, Japan, and explored the environmental factors that influenced them. Multivariate regression tree (MRT) analysis generated a 3-leaved MRT (G1, G2, and G3) and showed the total explained variation of 64.4% in the species composition. The explanatory variables discriminating between the two branches in the first node and in the second node of the MRT were neighbouring plant community and management status, respectively. The neighbouring plant community was related to the distribution of butterfly dietary resources and contributed much in determining the species composition of the community. While the management status was largely related to the amount of their dietary resources, affecting the species richness and diversity. The PCA results revealed that the three key groups (G1, G2, and G3) were formed along the gradients of these two factors. Consequently, to maintain mowing management and the diversity of neighbouring vegetation is very important for the continuance of butterfly community diversity and composition and the conservation of Red Listed species in the area.

The growing population with changing consumption patterns in developing countries is causing significant challenges with regards to solid waste management. Plastic wastes are particularly problematic, with single-use plastics leaking into the environment, including the marine environment, at an unprecedented rate. Approximately 80 percent of ocean plastics come from land-based sources or about 8 million tons are dumped into the ocean every year. Thailand was identified as one of the top 10 countries ranked by mass of mismanaged plastic wastes, with more than 60,000 tons per year entering the ocean through multiple outlets, including rivers. In the environment, plastic wastes can be degraded into small sizes (less than 5 mm), called microplastics (MPs), which could contaminate the ecosystems and the food chain, including foodstuffs and water supply. Tap water samples collected from a water supply treatment plant and Academic Institutions 1 and 2 in central Thailand were found to contain MPs about 304 ±90, 270 ±109 and 386 ±102 particles/L, respectively. In addition, MPs concentrations of 211 ±70 and 122 ±60 particles/L were also found in drinking water samples collected from commercial bottled water and membrane filtration water, respectively. The MPs sizes of 0-50 µm were most abundant in both the tap and drinking water samples whose shapes were mainly fragments and fiber. These data indicated potential health risks to the people who consume these water sources, and recommendations for health impacts minimization were proposed.

Road intersections are made of asphalt pavement, a popular road surface material used worldwide. The pavement may suffer deformities and deterioration, resulting in higher maintenance expenses and an elevated likelihood of road accidents, due to factors such as heavy vehicles and environmental variables like temperature and rainfall. To tackle these obstacles, researchers have devised several machine-learning algorithms and optimization techniques. These tools aim to forecast and scrutinize pavement deformation, with the goal of refining pavement design and maintenance approaches, as well as obtaining a more comprehensive comprehension of the factors that impact pavement effectiveness. This paper shows that heavy vehicles contribute significantly more to road erosion, and the retention and braking of vehicles greatly impact roadways. We also emphasize the statistical errors computed on the actual data range and demonstrate the results of the multilayer perceptron (MLP) model. The MLP model used the lath erosion standard to simulate future impact. Even though the model given is based on a small sample of data from one intersection, its estimates for road erosion in a year were found to be accurate when contrasted to real data. Controlling traffic flow can significantly improve road conditions, reducing erosion decay by reducing the time spent at intersections and other parameters. We conclude that machine learning can help control traffic flow, which can significantly improve road conditions, reducing vehicle time stretches at intersections.

The major stress-inducible Hsp70 (HSPA1A) is overexpressed in the cytosol of many highly aggressive tumor cells including glioblastoma multiforme and presented on their plasma membrane. Depending on its intracellular or membrane localization, Hsp70 either promotes tumor growth or serves as a target for NK cells. The kinetics of the membrane Hsp70 (mHsp70) density on human glioma cells (U87) was studied after different irradiation doses to define the optimal therapeutic window for Hsp70-targeting NK cells. To maintain the cells in the exponential growth phase during a cultivation period of 7 days different initial cell counts were seeded. Although cytosolic Hsp70 levels remained unchanged on days 4 and 7 after a sublethal irradiation with 2 Gy, 4 Gy and 6 Gy, a dose of 2 Gy resulted in an upregulated mHsp70 density in U87 cells which peaks on day 4 and starts to decline on day 7. Higher radiation doses (4 Gy, 6 Gy) resulted in an earlier and more rapid onset of the mHsp70 expression on days 2 and 1, respectively, followed by a decline on day 5. Membrane Hsp70 levels are higher in G2/M than in G1, however, an irradiation-induced cell cycle arrest on days 4 and 7, was not associated with an increase in the mHsp70 density. Extracellular Hsp70 concentrations increased significantly compared to sham (0 Gy) irradiated cells on days 4 and 7 but not on day 1. Functionally, elevated mHsp70 densities were associated with a significantly better lysis by Hsp70-targeting NK cells. In summary, the kinetics of changes in the mHsp70 density upon irradiation on tumor cells is time- and dose-dependent.

The current design of irrigation and fertilization systems often depends on a single index, leading to irrational systems due to the lack of a comprehensive multi-index evaluation. The aim of this study is to optimize the irrigation and nitrogen fertilizer application levels of spring maize using the TOPSIS method, in order to achieve a balance between growth characteristics, yield, water use efficiency, and soil nitrogen content. In the typical semi-arid region of Northeast China, through precise control experiments from 2022 to 2023, we adopted a two factor quadratic saturation D-optimal design method to study the effects of different irrigation amounts (145.40, 271.70, 348.20, 436.20 mm) and nitrogen fertilizer application amounts (34.80, 185.90, 277.40, 382.80 kg·hm-2) on spring maize. Results indicate that increasing both irrigation and nitrogen application rates can enhance dry matter accumulation by 15.17% to 32.70%. The impact of irrigation and fertilization on the net photosynthetic rate (Pn) of spring maize was found to be greater for irrigation amount than nitrogen application, particularly at 9:00 am and 13:00 pm, and slightly less so at 11:00 am and 15:00 pm. Concurrently, there was a significant increase in total nitrogen (TN1 by 20.85% for 0-20 cm soil layer, TN2 by 33.33% for 20-40 cm soil layer) and alkali-hydrolyzed nitrogen (AHN1 by 14.65% for 0-20 cm, AHN2 by 28.86% for 20-40 cm). Yields improved by 12.02% to 44.09%, and water use efficiency (WUE) saw an increase ranging from 20.08% to 140.07%. The optimal water and fertilizer management mode for spring maize SBDI (shallow buried drip irrigation) in semi-arid areas was determined through comprehensive analysis using TOPSIS entropy weight method. When the irrigation amount is 436.20 mm and the nitrogen fertilizer application amount is 277.40 kg·hm-2, it can significantly promote the accumulation of dry matter, yield, water use efficiency, photosynthetic characteristics, and soil nitrogen content of spring maize. This study provides a theoretical basis for the practical application of SBDI water fertilizer coupling technology for spring maize.

Abstract: An efficient and environmentally Pumice as a new catalyst for designing of 3,4- dihydropyrimidin-2(1H) ones / thiones via one-pot multi component condensation of aromatic aldehydes, urea/ thiourea and ethyl acetoacetate or acetyl acetone in excellent yields (96-99 %). The advantages using of this new catalyst is very cheap, available, non-toxic, stable under thermal conditions, easy work-up, improved yields, the product of reaction is very pure without using chromatographic methods and solvent free conditions.

The neonatal Hub and Spoke (HandS) ECMO approach provides emergent ECMO implantation to support neonates in severe cardio-respiratory life-threatening conditions at secondary (Spoke) centers, and a safe transfer to the ECMO center (Hub). We report a retrospective review of 11 neonates fom January 2014 to January 2020, presenting with life-threatening conditions and treated by HandS ECMO team in Spoke hospitals. Protocols and checklists were arranged by a local group of ECMO experts and shared with all the hospitals located in North-Eastern Italy. At the emergent call, all patients were cared for at the Spoke hospitals, receiving maximal respiratory and cardiovascular support (including high frequency oscillatory ventilation, inhaled nitric oxide, and major inotropic intravenous infusion). All but 3 patients were affected by life-threatening meconium aspiration syndrome. Median duration of ECMO support and hospitalization were 4 days (range 2-32) and 30 days ( range 8-50), respectively. All but 2 patients with congenital diaphragmatic hernia, were weaned off ECMO and discharged home without complications. At a median follow up of 14.4 months (1.3-74.8), all survivors were alive and in good clinical conditions, without medications, and normal somatic growth. All but one had normal neuropsychological development. We conclude that HandS ECMO model for treating neonates in life-threatening conditions is effective and successful. A specialized multidisciplinary team and common organizational protocols shared between Hub and Spoke centers are the key-points for success. While excellent results occur with MAS (100% survival), treatment was not successful in CDH, in which other that HandS ECMO issues are implied. Lessons learned from our experience are presented and discussed in this article.

Perfect cardiovascular health (CVH) has been defined by the American Heart Association as the lack of cardiovascular disease and the presence of seven key factors and health behaviors. In this study, we aimed to estimate the prevalence of ideal and poor CVH among the Polish adult population, taking the chosen socio-demographic factors into consideration. This is a cross-sectional study conducted among 3,901 adults without cardiovascular diseases, aged between 35 and 64 years. Participants completed a questionnaire, and they had anthropometric and physiological measurements taken. Blood samples were analyzed for fasting glucose and cholesterol levels. Ideal CVH was found in 5.4% of the participants, with the advantage of being toward city dwellers over those living in the rural areas (6.3% vs. 5.0%) p = 0.02. In case of the residents of rural areas, their likelihood of having an ideal body mass index (BMI) was found to be 22% lower (odds ratio (OR) = 0.78; 95% CI: 0.66–0.92), their likelihood of having an ideal diet was found to be 27% lower (OR = 0.71; 95% CI: 0.54–0.94), their likelihood of having perfect blood pressure was found to be 29% lower (OR = 0.71; 95% CI: 0.56–0.89), and their likelihood of having the perfect glucose levels were found to be 28% lower (OR = 0.72; 95% CI: 0.63–0.84), than the residents of urban areas. The prevalence of ideal cardiovascular behaviors and factors is lower in the rural community compared with people living in the city. Results indicate that more effort should be dedicated toward the country’s health policy, specifically concerning primary prevention. Preventive actions in the field of cardiovascular disease should be addressed to the residents of rural areas to a larger extent.

In the realm of agribusiness, transformative shifts are underway, propelled by the growing demands and expanding scales of grain production. This evolution calls for a critical reevaluation of the existing paradigms in coffee production and marketing paradigms, with a specific focus on integrating Artificial Intelligence (AI). This work aims to review, synthesize, and summarize the available data regarding how Machine Learning (ML) has been used to detect and classify characteristics in coffee beans and leaves. For this purpose, a comprehensive literature review of the most significant research contributions describing the application of AI for advanced classification techniques in coffee agriculture has been carried out. Our analysis suggests that implementing AI technologies allows the classification of coffee, encompassing various attributes such as maturity, roast intensity, disease identification, flavor profiles, and overall quality. More largely, this technological advancement holds the potential to revolutionize coffee farming by providing producers and agricultural specialists with sophisticated tools to enhance production efficiency, minimize costs, and improve the accuracy and confidence of their decision-making processes.

Green finance in the context of sustainable development sits within the broader discourse of environmental economics and sustainable finance. Their integration has become imperative in addressing global challenges, aiming to understand how financial mechanisms can be aligned with sustainability goals, investigating the role of green finance in promoting environmentally friendly investments and fostering sustainable development. This bibliometric analysis explores the evolution, trends, and challenges in green finance research. It examines 436 articles published between 2016 and 2024, revealing insights into influential publications, authors, journals, institutions, and countries engaged in green finance for sustainability. The study identifies China, the UK, and Pakistan as leaders in research output and citation impact. Furthermore, it highlights the interdisciplinary nature of green finance, reflected in diverse publication outlets spanning environmental, social, and economic domains. The analysis underscores the increasing global interest in green finance, as evidenced by the growing citation rates over time. Key findings include the pivotal role of green finance in energy efficiency, renewable energy development, and the promotion of sustainable economic growth. Overall, this research provides valuable insights for policymakers, researchers, and practitioners, emphasizing the importance of interdisciplinary collaboration and continued research efforts in advancing sustainable finance agendas.

Tight gas, a category of Deep Green Energy Resources, rely on advanced intelligent monitoring methods for their extraction. Conventional logging for reservoir evaluation relies on logging data and the manual setting of evaluation criteria to classify reservoirs. However, the complexity and heterogeneity of tight reservoirs pose challenges in accurately identifying target layers by using traditional well-logging techniques. Machine learning may hold the key to solving this problem, as it enables computers to learn without being explicitly programmed and manually added rules. Therefore, it is possible to make reservoir evaluation via using machine learning methods. In this paper, the reservoir quality index (RQI) and porous geometric parameters obtained from the optimized inversion of the spherical-tubular model are adopted to evaluate the reservoir. Then, three different machine learning approaches, the random forest (RF) algorithm, support vector machine (SVM) algorithm, and extreme gradient boosting (XGB) algorithm, are utilized for reservoir classification. The selected dataset covers more than 7,000 samples from five wells. The data from four wells are arranged as the training dataset, and the data of the remaining one well is designed as the testing dataset to calculate the prediction accuracies of different machine learning algorithms. Among them, accuracies of RF, SVM, and XGB are all higher than 90%, and XGB owns the highest result by reaching 97%. Machine learning based approaches can greatly assist reservoir prediction by implementing the well-logging data. The research highlights the application of reservoir classification with a higher prediction accuracy by combining machine learning algorithms with NMR logging based pore structure characterization, which can provide a guideline for sweet spot identification within the tight formation. This not only optimizes resource extraction but also aligns with the global shift towards clean and renewable energy sources, promoting sustainability and reducing the carbon footprint associated with conventional energy production. In summary, the fusion of machine learning and NMR logging based reservoir evaluation plays a crucial role in advancing both energy efficiency and the transition to cleaner energy sources.

Renal angiogram is a promising tool for diagnosing renal vasculature and structural alterations in renal diseases. In renal diseases, the vascular changes were observed earlier than the structural and other changes. However, the literature on angiograms in kidney diseases was limited. Six client-owned dogs with chronic kidney diseases with International Renal Interest Society (IRIS) stage II and III were selected for this study. Under general anesthesia, the femoral arterial catheterization was performed. With a Cobra (C2) catheter, Iohexol saline (50:50) was administered to evaluate the vascular changes of Renal failure, using selective and non-selective angiograms. The procedures were completed successfully with minimal complications. Serum biochemistry and urine protein creatinine ratio were estimated sequentially and quality of life was monitored. Due to contrast agent complications, a dog died within 14 days and necropsy was conducted. Though the renal angiogram has complications, it is a reliable tool for the diagnosis of vasculature changes associated with kidney diseases, in veterinary medicine.

The main objective of this work is to study the effects of carbon nanotubes (CNT) on the strength and electrical properties of cement mortar. Molecular dynamic simulations (MDS) were carried out for the mechanical and electrical properties of the cementitious composite and the associated mechanisms. To model the atomic structure of the Calcium-Silicate-Hydrates (C-S-H) gel, tobermorite 11Å was chosen. Single-walled carbon nanotubes (SWCNTs) embedded in tobermorite structure were tested numerically. In particular, the effect of the concentration of CNT in cement paste was studied. An innovative experiment of electrical characterization of a cementitious composite of carbon nanotubes has been developed.

3D point cloud classification tasks have been a hot topic in recent years. Most existing point cloud processing frameworks lack context-aware features due to the deficiency of sufficient local feature extraction information. Therefore, we design an augmented sampling and grouping (ASG) module to efficiently obtain fine-grained features from the original point cloud. In particular, this method strengthens the domain near each centroid and makes reasonable use of the local mean and global standard deviation to mine point cloud’s local and global features. In addition to this, inspired by the transformer structure UFO-ViT in 2D vision tasks, we first try to use a linearly-normalized attention mechanism in point cloud processing tasks, investigating a novel transformer-based point cloud classification architecture UFO-Net. An effective local feature learning module is adopted as a bridging technique to connect different feature extraction modules. Importantly, UFO-Net employs multiple stacked blocks to better capture feature representation of the point cloud. Extensive ablation experiments on public datasets show that our method outperforms other state-of-the-art methods. For instance, our network performed with 93.7% overall accuracy on the ModelNet40 dataset, which was 0.5% higher than PCT. Our network also archived 83.8% overall accuracy on the ScanObjectNN dataset, which is 3.8% better than PCT.

This study investigated the influence of land-use and precipitation change and variability on Lake Victoria’s water-level fluctuations. Extreme precipitation events, corresponding to extreme water-levels, over the lake and its catchment area were identified and their return periods estimated by fitting them into a generalized extreme value (GEV) distribution. Using general circulation models from the 6^th phase of the Coupled Model Intercomparison Project (CMIP6)’s Detection & Attribution Model Intercomparison Project (DAMIP), an assessment of the potential contribution of human-induced climate change on the observed precipitation patterns over the study area was done. The greatest precipitation anomalies for the period 1900-2020 were recorded in 1961’s October-December (OND) season and 2019’s June-August (JJA) and OND seasons, corresponding to the period when the highest water-levels were recorded in Lake Victoria. While land-use change in the study domain was observed, extended and unusually heavy June to December 2019 precipitation bore the greatest responsibility for the 2019/2020 high water-levels in Lake Victoria. The OND precipitation event of 2019 was a 1-in-52-year event compared to the 1961’s 1-in-693 years. Differences in return periods at various parts of the lake imply a high spatial climate variability within the lake itself. An analysis of the fraction of attributable risk (FAR) showed natural variability to have a greater influence on the JJA and OND precipitation patterns over Lake Victoria than human-induced climate change. However, variability over the land area of the study domain was mainly driven by human-induced climate change rather than natural variability, implying a unique climate system over Lake Victoria. Findings from the current study enhance the understanding of Lake Victoria’s water budget and motivate for further research to inform effective strategies on the planning and use of Lake Victoria’s water resources in a changing climate.

Coronavirus (COVID19) appears to be an inflection point that is forcing a disruption in medical education. However, it is not clear what the responses of the institutions are to this pandemic and how the adaptation of new methods may impact medical education in the post COVID-19 era. Objective: The study aims to explore how medical schools in Egypt responded to COVID-19 pandemic regarding the teaching and learning/assessment for undergraduate students. Design: A mixed method exploratory two-phase study was conducted. A survey was prepared and disseminated to a convenient non-probability sample of the medical school faculty through various social platforms. Then, a focus group guide was conducted to explore in more depth the findings. Results: The staff level of preparedness for that unexpected shift was evaluated by 55.1% of the survey participants as optimum to high and a good leadership support was reported by 70 % of them. They reported conflicting views about the proper role of medical education units but reinforced the idea of Egyptian Knowledge Bank’s crucial role in this transition. Additionally, there is a communication problem with the students that leads to their detachment. Subsequently, 84.6 % of the participants reported that their schools used alternative teaching methods for small groups, large groups, pre-clinical and clinical clerkships. However, 64.1 % of the participants identified a clinical skills teaching challenge. Although, 68.4% reported that alternative methods were used for formative assessment but absence of alternative methods for summative assessment was declared by 76.3%. Conclusions: Individuals moved faster than bodies and relied on support existing outside the universities when catastrophe happened. However, institutes which have experience in adapting modern engaging learning methods should organize a better response for crisis. Online learning should be integrated in the curriculum with a fair percentage especially in the early years of medical study.

Bisphenols are widely used in the synthesis of polycarbonate plastics, epoxy resins and thermal paper, which are used in manufacturing items of daily use. Packaged foods and drinks are the main sources of exposure to bisphenols. These chemicals affect humans and animals by disrupting the estrogen, androgen, progesterone, thyroid, and aryl hydrocarbon receptor functions. Bisphenols exert numerous harmful effects because of their interaction with receptors, ROS formation, lipid peroxidation, mitochondrial dysfunction, and cell signal alterations. Both cohort and case-control studies have determined an association between bisphenol exposure and increased risk of cardiovascular diseases, neurological disorders, reproductive abnormalities, obesity, and diabetes. Prenatal exposure to bisphenol results in developmental disorders in animals. These chemicals also affect the immune cells and play a significant role in initiating the inflammatory response. Exposure to bisphenols exhibit age, gender, and dose-dependent effects. Even at low concentrations, bisphenols exert toxicity, and hence deserve a critical assessment for their uses. Since bisphenols have a global influence on human health, the need to discover the underlying pathways involved in all disease conditions is essential. Furthermore, it is important to promote the use of alternatives for bisphenols, thereby restricting their uses.

To study the oil and gas distribution law in the slope area of the hydrocarbon-bearing basin, the distribution of the effective dominant path of sand bodies transporting oil and gas is a fundamental subject. In this paper, we introduced an effective way to predict such transport paths and applied the method to study the sand bodies of the lower first member of the Shahejie Formation (E3s1L) in the southern area of the Qikou Depression in the Bohai Bay Basin (Qinan). We first define the dominant hydrocarbon transport paths of the sand body as the superimposed area of the contiguously distributed area of the sand body and the paleotectonic ridges at the top of the formation where the sand body is located. Then we define the oil and gas supply area of the oil source fault as the overlapped area of the favorable transport path of oil source faults and the width of the associated fracture zone. Stacking the two areas, we can delineate the distribution of the effective dominant transport paths of the sand bodies. The results from our case study of the Qinan area show that the effective dominant paths of sand bodies transporting oil and gas in the E3s1L Formation in the Qinan area are distributed throughout the region with better development in the west than in the east. The paths in the eastern part extend from north to south, while the paths in the western part extend from northeast to southwest, which is favorable for the convergence of oil and gas generated from the source rocks of the third member of Shahejie Formation (Es3) in the Northeastern main depression of Qikou and the formation of oil and gas accumulations in the l E3s1L Formation. The results are consistent with the fact that oil and gas discovered in the E3s1L Formation in the Qinan region are mainly distributed in the central and western regions, with a small amount in the southeast. Therefore, the suggested method is feasible to predict the effective dominant path of sand bodies transporting oil and gas.

Bionic robotic hand can perform many movements similar to human hand. But there is still a significant gap in manipulation between robot and human hand. It is necessary to understand the finger kinematics and motion patterns of human hand to improve the performance of robotic hand. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hand of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a largest dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Besides, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by PIP joint. Regarding the finger sequence, the thumb started to move before four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided kinematic reference for the design of robotic hand and thus contribute to its development.

Obstetric Violence refers to dehumanized or derogative treatment of women in their pregnancy, childbirth or postpartum periods and may be manifested through the attitudes of health professionals or the performance of unjustified or outdated practices without maternal consent. Currently, there is no tool validated in Spain to measure women’s perception of obstetric violence. The objective of this study was to carry out the cultural adaption and validation of an existing 14-item Obstetric Violence Scale to the Spanish context, and to evaluate its psychometric properties. The research was conducted in two phases: first, a methodological study designed to evaluate content validity, through assessments by 8 experts (calculating the Aiken V coefficient) and face validity in a sample of 20 women; second, a cross-sectional study to evaluate construct validity (through confirmatory factor analysis and Rasch analysis), divergent validity against a scale of birth satisfaction, known groups validity and reliability. In Phase 1, Aiken V values higher than 0.71 were obtained for all items. Phase 2 was conducted on a sample of 256 women and the fit values for the unidimensional model were RMSEA: 0.070 [95%CI: 0.059-0.105] and GFI: 0.982 [95%CI: 0.823-0.990]. The Rasch analysis indicated poor performance of item 2, which was removed. The Omega and Cronbach's Alpha coefficients were 0.863 and 0.860, respectively. A final 13-item version of the Obstetric Violence scale was produced, with total score ranging from 0 (no obstetric violence perception) to 52 (maximum obstetric violence perception). The Obstetric Violence Scale is a reliable and useful tool to measure women's perception of obstetric violence.

Fe- and Al-rich metapelite from the Transangarian segment of the Yenisey Ridge (East Siberia, Russia) is a potential new source of high-alumina refractories. The rocks have relatively high average contents of Al2O3 (20 wt.%) and Fe2O3 (7.91 wt%), moderate K2O (3.44 wt%), and low CaO (0.74 wt%). Their dominant mineral assemblages are andalusite + muscovite + margarite + chlorite + biotite + quartz or staurolite + kyanite or/and andalusite + chlorite + muscovite + biotite + quartz with ±garnet and ±plagioclase. Al2SiO5 polymorphs occur as up to 1.5 cm andalusite porphyroblasts and partial or complete pseudomorphs after andalusite (kyanite and staurolite). Accessories include abundant Fe-Ti oxides and sporadic REE-, Y-, Ca-phosphates; sulfides are negligible. The composition of Al2SiO5 concentrates obtained in laboratory by heavy-media and magnetic separation from ≥0.06 mm fractions meet all requirements for raw material of this type: &gt;56 wt% Al2O3, &lt;42 wt% SiO2, &lt;1 wt% Fe2O3, &lt;1.2 wt% TiO2, and &lt;0.2 wt% (CaO+MgO). The andalusite, kyanite, and mixed ores yield 0.7-4.1 wt%, 0.7-2.2 wt%, and 1.9-6.0 wt% of concentrate, respectively. The best-quality ores rich in Al2SiO5 polymorphs reside in zones of contact and/or dynamic metamorphism superimposed over regional metamorphism of Al-rich rocks.

In order to formulate a reasonable water input model for cotton fields in southern Xinjiang, scientific and rational fertilization, reduce soil carbon leaching, and improve soil carbon sequestration capacity, the undisturbed soil column leaching test was used to simulate the current field management method in the study area. Two methods of drip irrigation and flood irrigation were set up, and three irrigation and three nitrogen fertilizer levels were used to carry out the undisturbed soil column leaching test. The results showed that the amount and mode of water and nitrogen input affected the distribution and leaching loss of organic carbon and inorganic carbon in soil. When the nitrogen application rate increased from 270 kg·hm-2 to 450 kg·hm-2, the leaching loss of soluble organic carbon and soluble inorganic carbon increased significantly. When the water input increased from 6000 m3·hm-2 to 9000 m3·hm-2, the leaching loss of DOC and DIC increased significantly. The carbon leaching loss under drip irrigation was higher than that under flood irrigation. The leaching rates of DOC and DIC were the fastest under the conditions of high water ( 9000 m3·hm-2 ) and high fertilizer ( 450 kg·hm-2 ). It shows that water and nitrogen input and irrigation methods are important factors affecting soil carbon leaching. In the case of excessive water input, long-term high-frequency irrigation is the main factor affecting carbon leaching.

To examine the association of sleep quality and work from home with physical inactivity (PI) in leisure time during Covid-19 pandemic. A population-based household survey was conducted in two Bra-zilian municipalities from October to December 2020. Leisure-time physical activity (PA) was self-reported, and individuals who practiced less than 150 minutes of moderate PA or 75 minutes of vigorous PA weekly were classified as PI. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). WFH was assessed by: "Currently, how is your work routine regarding location? Associations were investigated using logistic regression and directed acyclic graphs (DAG) for the multivariate models. A total of 1,750 adults were interviewed, 69.1% were PI and 51.9% had poor sleep quality. Furthermore, 79.8% were not in WFH. In multivariate analysis, leisure PI was associated with poor sleep quality (OR:1.59: 95% CI: 1.02-2.48), and not being in WFH (OR:1.62: 95% CI: 1.05-2.50). When performing the combined analysis between these two factors, and who were not in WFH were four times more likely to be PI at leisure (OR=4.22;95%CI:2.05-8.65). The results indicate a high prevalence of PI, with poor quality sleep and non-WFH associated with leisure PI. These combined factors exacer-bated the occurrence of PI.

Hyperaccumulator plant species growing on metal-rich soils can accumulate high quantity of metals and metalloids in aerial tissues and several proteomic studies on the molecular mechanisms at the basis of metals resistance and hyperaccumulation have been published. Hyperaccumulator are also at the basis of phytoremediation strategy to remove more efficiently metals from polluted soils or water. Arabidopsis halleri and Noccea caerulescens are both hyperaccumulators of metals and nano-metals. In this study it was assessed the change in some proteins in A. halleri and N. caer-ulescens after the growth in soil with cadmium and zinc, provided as sulphate salts (CdSO4 and ZnSO4) or sulfide quantum dots (CdS QDs and ZnS QDs). The protein extracts obtained from plants after 30 days of growth were analyzed by 2D-gel electrophoresis (2D SDS-PAGE) and identified by MALDI-TOF/TOF mass spectrometry. A bioinformatics analysis was carried out on quantitative protein differences between control and treated plants. In total, 43 proteins resulted significatively modulated in A. halleri, while 61 resulted modulated in N. caerulescens. Though these two plants are hyperaccumulator of both metals and nano-metals, at protein levels the mechanisms involved do not proceed in the same way but at the end bring to a similar physiological result.

Despite the productivity, achieving long-term sustainability and maintaining plant biodiversity become the pivotal goals in orchard floor management, especially along tree rows. Thus, the paradigm of eradicating weeds in the tree row using chemical herbicide or repeated soil tillage needs to be substituted with more sustainable alternatives. This study was conducted in two commercial apple and peach orchards in Marche region (Italy). Two integrated mechanical approaches, integrated mowing (mower + brush or disc) and integrated tillage (blade weeder + integrated mowing), were compared with standard herbicide system in a 2-years trial. Weed species abundance, soil coverage rate, and weed biomass productions, including gas exchange parameters, tree growth, fruit yield and quality were measured. Both integrated practices had significant effects on the number of weed species, total vegetation coverage, and dry weed biomass production. No significant differences were found in terms of tree gas exchange parameters, growth and fruit yield. However, a few fruit quality parameters such as fruit firmness, solid soluble content and dry matter content responded positively to the integrated practices. These results suggest that the integrated mechanical approaches of weed management increased orchard biodiversity, and they had no adverse effects on tree growth, fruit yield, and quality.

Currently, data regarding optimal treatment modality, response, and outcome specifically for N3 head and neck cancer are lacking. This study aimed to compare the treatment outcomes between definitive concurrent chemoradiotherapy (CCRT) to the neck and upfront neck dissection followed by adjuvant CCRT. 93 N3 squamous cell carcinoma head and neck cancer patients were included. Primary tumor treatment was divided to definitive CCRT (CCRT group) or curative surgery followed by adjuvant CCRT (surgery group). Neck treatment was also classified into two treatment modalities: definitive CCRT to the neck (CCRT group) or curative neck dissection followed by adjuvant CCRT (neck dissection group). Overall, the 2-year overall survival (OS), local recurrence-free survival (LRFS), regional recurrence-free survival (RRFS), and distant metastasis-free survival (DMFS) were 51.8%, 47.3%, 45.6%, and 43.6%, respectively. In both oropharyngeal cancer and nonoropharyngeal cancer patients, in terms of OS, LRFS, RRFS or DMFS no difference was noted regarding primary tumor treatment (CCRT vs. surgery) or neck treatment (CCRT vs. neck dissection). In summary, N3 neck patients treated with definitive CCRT can achieve similar outcomes to those treated with upfront neck dissection followed by adjuvant CCRT. Cautions should be made to avoid overtreatment for this group of patients.

Fire is a serious security threat that can lead to casualties, property damage, and environmental damage. However, despite the availability of object detection algorithms, challenges persist in detecting fires and smoke. These challenges include slow convergence speed, poor performance in detecting small targets, and high computational cost limiting deployments. In this paper, Fire smoke and human detection based on ConvNeXt and Mixed encoder (FCM-DETR), an end-to-end object detection algorithm based on Deformable DETR, is proposed. Firstly, we introduce ConvNeXt to take the place of Resnet, which greatly reduces the amount of computation and improves the ability to extract irregular flame features. Secondly, to effectively process multi-scale features, the original encoder is decoupled into two modules. Then Mixed encoder, an innovative encoder structure, is proposed, resulting in excellent performance of multi-scale fire and smoke features fusion. What can’t be overlooked is that the encoder block is compatible with any DETR-based models. Finally, the convergence speed is accelerated and the mean of average precision is improved by applying a novel loss function called Powerful IoU v2. The experimental results indicate that our model achieves the best detection accuracy compared to other models, with mAP reaching 66.7%, mAPs and Accuracyfire achieving impressive 50.2% and 98.05%, respectively.

The main inhibitory neurotransmitter in the mammalian brain is 4-aminobutyric acid (GABA). Phthalimide acts as a sodium channel antagonist, one of the finest targets for treating epilepsy is the sodium channel and JNK kinase activity is inhibited to treat epilepsy. a novel compound with multiple targets of action for the treatment of epilepsy also anti-oxidant activity has been designed. The compounds are designed in two series aldehydes and aniline. Docking of all the designed compounds has been done with the suitable protein GABA-AT, sodium channel, JNK protein, and anti-oxidant from protein bank. QSAR was done for constructing many linear regression models. In combination with the developed Docking and QSAR outcomes, ADMET has been performed for the active compounds. The result shows that 11 of the compounds have excellent binding energy in docking with all the receptors and also have good QSAR results and follow the ADMET. The structural understanding of human GABA-AT inhibition was obtained from molecular dynamics simulation studies for compound no. 11 at 5 nanoseconds. Synthesis and pharmacological activity also suggest that the designed compound no.11 be considered the best Novel Compound.

Geoenvironmental engineering involves defining solutions for complex problems, such as containment systems management, contaminant transport control, wastewater management, remediation of contaminated sites and valorization of geomaterials and wastes. In the last years, energy harvesting (EH) - or energy scavenging - methods and technologies have been developed to reduce the dependence on traditional energy sources, namely fossil fuels, and nuclear power, also responding to the increase of energy demands for human activities and to fulfill sustainable development goals. EH in geoenvironmental works and surrounding soil and water environment include a set of processes for capturing and accumulating energy from several sources considered deemed wasted or unusable associated to soil dynamics, stress and strain of geomaterials, hydraulic, vibrations, biochemical, light, heating and wind sources can be potential EH systems. Therefore, this work presents a review of the literature and critical analysis on the main opportunities for EH capturing, accumulating and use in geoenvironmental works, among basic electric concepts and mechanisms, analyzing those works in complex conditions involving biological, chemical, mechanical, hydraulic, and thermal coupled actions, concluding with the main investigation and challenges within geoenvironmental aspects for EH purpose.

Globally, gastric cancer is a major cause of cancer mortality, with a 5-year survival rate of 32% for locally advanced and metastatic gastric cancer. This systematic literature review summarized the clinical, safety, and humanistic outcomes associated with systemic regimens given as first line therapy for locally advanced and metastatic gastric cancer. The search included articles published in English in PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, and the American Society of Clinical Oncology meeting library, from inception to April 2022. Phase II and III randomized controlled trials conducted among western populations diagnosed with stage III and IV locally advanced and metastatic gastric cancer were included. Two investigators independently reviewed the studies, conducted data extraction, and assessed risk of bias in accordance with PRISMA guidelines. Twenty-four randomized controlled trials totaling 8,705 patients were included. Median overall survival ranged from 5.0-13.1 months, median progression-free survival ranged from 2.0-7.7 months, and objective response ranged from 13.0-64.1%. Two studies reported higher quality of life outcomes. Grade 3 and 4 adverse events were reported in most studies. Improvement in clinical outcomes can be seen in recently published randomized controlled trials for locally advanced and metastatic gastric cancer.

The automobile industry is often believed to be moving towards electric vehicles. Hybrid electric vehicles (HEVs) and electric vehicles (EVs) are anticipated to dominate the automotive industry. Regenerative braking is one of the modern approaches that recharge the battery by extracting the kinetic energy from the braking thus improving the vehicle range. However, the rate of current supplied by regenerative braking to the battery is a major concern as lithium-ion (Li-ion) is susceptible to failure due to the intensity of the charging-discharging rate, and operating temperature. So, this review article focuses on the effect of regenerative braking on the life of the battery and measures being taken to protect the battery from higher charging during regenerative braking. Various research articles are considered for observing the effect of regenerative braking on battery life. It is found that longer duration charging current obtained from regenerative braking that is irrespective of current intensity is the prominent factor of battery deterioration. If the SOC and the temperature are not in the optimal range, the Lithium plating rate increases. However, a higher level of regenerative braking increases the battery life even at high SOC and temperature by reducing the Depth of Discharge (DOD) and by using shorter recharging periods.

Cooking is a very decentralized and private way of energy consumption in human activities. The existing investigation and statistical analysis can’t effectively calculate the proportion of population relying on clean cooking fuel and utilization technology in the region. Therefore, based on the big data of the earth, this paper adopts the combination of spatial analysis and statistical analysis to determine the survey sample area, and according to the economic conditions, topographic characteristics, national policies for new energy construction and living habits of the provinces and cities under investigation, the questionnaire survey is conducted for the research area to calculate the proportion of the regional population relying on clean cooking fuels and utilization technologies. Taking the south of the Yangtze River in China as an example, the paper effectively calculates that 88.25% of the population depends on clean cooking fuel and technology in this region, of which 89.81% are in urban areas and 79.87% are in rural areas. Analysis of the survey data shows that the proportion of the population using clean cooking fuels and technologies is related to factors such as economic development, income and resource endowment. There is a large urban–rural gap in terms of energy consumption tendency and structure in the south of the Yangtze River in China and cooking energy consumption in rural households also varies from region to region. The technical ideas and conclusions of the paper have high reference application value, which can help promote the upgrading of clean energy utilization and provide data basis for relevant decision and policy making.

The study evaluated the association between nutrient patterns and body fat and regional adiposity in middle-aged black South African (SA) men and women and determined if this differed by sex. Body fat and regional adiposity (dual-energy x-ray absorptiometry), and dietary intake (7-day quantified food frequency questionnaire) were measured in black SA men (n=414) and women (n=346). Using principal component analysis, nutrient patterns were computed from 25 nutrients in the combined sample. Four nutrient patterns were extracted, explaining 67% of the variance in nutrient intake. Animal and fat, as well as the vitamin C, sugar and potassium driven patterns, were positively associated with total adiposity. In contrast, the retinol and vitamin B12 pattern was associated with the centralisation of fat. Notably, the strength of the association between the animal-driven nutrient pattern and BMI was greater in men (1.14 kg/m2, 95%CI (0.63-1.66)) than women (0.81 kg/m2, 95%CI (0.25-1.36)) (Pint=0.017). In contrast, the plant driven pattern was associated with higher abdominal subcutaneous adipose tissue (SAT) in women (44 cm2, 95%CI (22-67)) but not men (Pint =1.54 x 10-4). These interactions suggest that although men and women have similar nutrient patterns, the associations with the whole body and regional body fat are different.

Electromyographic (EMG) signals provide information about a person's muscle activity. For hand movements, in particular, the execution of each gesture involves the activation of different combinations of the forearm muscles, which generate distinct electrical patterns. Conversely, the analysis of these muscle activation patterns, represented by EMG signals, allows recognizing which gesture is being performed. In this study, we aimed to implement an automatic identification system of hand or wrist gestures based on supervised Machine Learning (ML) techniques. We trained different computational models and determined which of these showed the best capacity to identify six hand or wrist gestures and generalize between different subjects. We used an open access database containing recordings of EMG signals from 36 subjects. Among the results obtained, we highlight the performance of the Random Forest model, with an accuracy of 95.39%, and the performance of a convolutional neural network with an accuracy of 94.77%.

Parental labour migration, either one or both parents, has been associated with various challenges among left-behind children (LBC). However, there is a limited understanding of the LBC’s own views and experiences of social and mental wellbeing and how the new daily life circumstances they encounter following their parents’ migration impact them. This study aimed to understand the influence of parental migration and its aftermath on the social and mental wellbeing of children and adolescents (referred to as LBC) in two rural districts in Indonesia. Employing a qualitative design, data were collected through individual in-depth interviews with LBC (n=24) aged 14 to 18 years, recruited using the snowball sampling technique. Data were thematically analysed, guided by a qualitative data analysis framework. The findings showed that parental migration negatively impacted the social wellbeing of LBC. This impact was reflected in negative labelling from friends and changes in familial roles which influenced their social interactions and activities with peers. Parental migration also caused challenges to the mental wellbeing of LBC. These manifested in the LBC experiencing fractured emotional bonds, leading to negative emotions, including stress, anxiety, sadness, depression, frustration, loss of motivation, and self-imposed isolation, which were associated with their parents’ migration and abrupt disruptions in parent-child communication. The transition to new life situations with caregivers after parental migration and the dynamics within the caregivers’ households were additional factors that detrimentally affected their mental well-being. Unmet basic needs and educational needs due to financial hardships faced by mothers and caregivers, further exacerbated mental health challenges for the children. The findings indicate the importance and improvement of policies and interventions in Indonesia (e.g., counselling services, non-cash food assistance, family hope program, direct cash assistance) that cover and address the diverse needs of mothers or caregivers and the LBC.

Robotic systems have been widely used in various industries, so the security of communication between robots and their components has become an issue that needs to be focused on. As a framework for developing robotic systems, the security of ROS2 can directly affect the security of the upper-level robotic systems. Therefore, it is a worthwhile research topic to detect and analyze the security of ROS2. In this paper, we adopt a formal approach to analyze the security of the communication mechanism of ROS2. First, we use a state transition system to model the potential vulnerabilities of ROS2 based on the ROS2 communication mechanism and the basic process of penetration testing. Secondly, we introduce the CIA model on the basis of the established vulnerability model and use LTL to define its security properties. Then, we design and implement a vulnerability detection tool for ROS2 applications based on the vulnerability model and security properties. Finally, we experimentally test some ROS2-based applications, and the results show that ROS2 has vulnerabilities without additional protection safeguards.

Head and neck squamous cell carcinoma (HNSCC) takes the sixth place among the most common cancers in the world. Abnormal methylation can be one of the reasons for this cancer. The aim of this study was to investigate the DNA promotor methylation status of cancer-associated genes (ATM, APC, CDO1, RB1, TP53, WIF1) in patients with HNSCC. Bisulfite Conversion and Methylation-Sensitive High-Resolution Melting was used for analysis of the DNA methylation level of normal and tumor tissues in 44 patients. There were significant differences in DNA methylation level between patient’s tumor and normal tissues for CDO1 and WIF1 genes in all subjects and subgroups (p<0.05). In T3 subgroup there was significant correlation between CDO1 gene methylation and age in the normal tissue. The same correlation was detected also for the WIF1 gene methylation in tumor tissue samples in the subgroup with T3 and in normal tissue samples in the subgroup with T4 (p<0,05). In all genes no significant differences were found between the subgroups (T2, T3, T4 stage, primary/recurrent lesion, non-keratinizing/keratinizing SCC, age before/ after 50, smokers/non-smokers) of the patients. Thus, changes in the expression of the CDO1 and WIF1 genes can affect mechanisms of the occurrence and development of HNSCC.

The study investigated determinants of open defecation among rural women in Ghana. The study extracted data from the female’s file of the 2003, 2008 and 2014 Ghana Demographic and Health Survey (GDHS). A total of 4,284 pooled sample size of rural women aged 15-49 with complete information about the variables analyzed in the study. The outcome variable was “open defecation” (i.e., defecating in an open space rather than a toilet facility) whilst fourteen (14) key explanatory variables were used. Two regression models were built, and output reported in odds ratio. Descriptively, 42 in every 100 women aged 15-49 practised open defecation (n=1811, 95’CI=49-52). Open defecation significantly correlated with educational attainment, wealth status, religion, access to mass media, partner's education, and zone of residence. The likelihood to practice open defecation reduced among those with formal education [aOR=0.69, CI=0.56-0.85], those whose partners had formal education [aOR=0.64, CI=0.52-0.80], women in the rich wealth quintile [aOR=0.12, CI=0.07-0.20], the traditionalist [aOR=0.33, CI=0.19-0.57], and those who had access to mass media [aOR=0.70, CI=0.57-0.85]. Residents in the Savannah zone were over 21-fold higher to defecate openly [aOR=21.06, CI=15.97-27.77]. The prevalence of open defecation is disproportionately pro-poor indicating that impoverished rural women are more likely to perform it.