The paper's objectives are to identify the main benefits, limitations, and challenges facing using Blockchain technology in the Supply Chain Management (SCM). To explore the factors that affect the adoption and application of Blockchain technology in SCM. The study uses a systematic literature review methodology to analyze and compare selected related articles published between 2016 and 2022 on the usage of Blockchain technology in the SCM. Several studies showed that there are many benefits to using Blockchain technology in SCM such as enhanced security, confidentiality, traceability, transparency, data accuracy, privacy, efficiency, accountability, and trust. At the same time, there are many limitations and challenges like scalability, interoperability, legal (regulatory) issues, high implementation and maintenance costs, standardization and information, lack of trust in technology, high energy consumption, limited awareness, integration with current systems, and privacy. Blockchain technology has the potential to revolutionize various industries, but there are still several issues that need to be addressed to fully realize its potential. Understanding the benefits and difficulties of applying Blockchain technology in different industries, including the SCM, is essential in determining its effectiveness and the different strategies needed to assess its application and implementation.

The purpose of this paper is to explore the effect of corporate social responsibility (CSR) on brand image in the apparel industry in Jordan, using the moderating variable of customer consciousness. The current research uses a quantitative, descriptive, cause-effect, and cross-sectional approach, and also it uses a convenience sampling method. Data was collected from 440 respondents. Results indicate that Jordanian Apparel organizations have medium to highly implementing of all items and constructs of CSR, brand image items, and consciousness items. Moreover, there is a strong relationship between CSR dimensions, a medium relationship be-tween each CSR dimension and brand image, a medium relationship between each CSR dimension and consciousness, a medium relationship between total CSR and brand image, a medium relationship between total CSR and consciousness, and the medium relationship between brand image and consciousness. Results of the first model show that total CSR affects the brand image. Where social responsibility has the highest positive effect, followed by ethical responsibility, then economic responsibility, however, environmental responsibility negatively affects the brand image. The second model shows consciousness moderates the effect of CSR on the brand image. The study recommends longitudinal research on the Jordanian Apparel industry, especially to test the effect of environmental responsibility on the brand image. Moreover, the re-search uses customers’ consciousness as a moderating variable, which improves the effect of CSR on brand image. The Apparel industry organizations in Jordan should revise their daily practices particularly environmental responsibility and/or increase their customers’ awareness of their practices. Finally, the current research contributes to existing studies by using consciousness as a moderating variable.

This study aims to explore the E-marketing orientations and relationship management constructs in Jordanian startup enterprises to examine their influence on brand visibility and loyalty in the context of the digital market . The sample consists of 161 managers in startup companies, and structural equation modeling is used to study the relationships between the constructs of e-marketing orientation, capabilities, E-relationship management, brand visibility, and loyalty. The results illustrate that the realization of e-marketing orientation is directly achieved by capabilities and visibility, thereby stressing the importance of a formulated digital market approach and that the realization of effective e-relationship management directly expression by e-marketing capabilities, demonstrating the significance of the digital market concept’s approach. The results further demonstrate that e-marketing capabilities and visibility serve as mediators between the realization of e-marketing orientations and loyalty, Two explanations may be drawn, one from the R resource-Based View theory, and another derived from R elationship M arketing T heory Thus, the study has theoretical implications in terms of R esource-Based V iew and R elationship M arketing T heory. The study offers essential managerial insights for practitioners into the entrepreneurship domain concerned with the necessity of e-marketing capabilities and E-RM attitudes at a customer-centered approach and the strategic application of digital channels to enhance visibility in the intense competition context. Therefore, the empirical results have contributions as essential insights for both stakeholders and account for practical, theoretical, and managerial perspectives in the entrepreneurship domain.

This research aims to explore the complex interplay between supply chain resilience (SCR), digital supply chain (DSC), and sustainability, focusing on the moderating influence of supply chain dynamism. The goal is to understand how these elements interact within the framework of contemporary supply chain management and how they collectively contribute to enhancing sustainability outcomes. The sample size is 300 CEOs and managers. The study approach integrates quantitative research methods. Structural equation modeling (SEM) is utilized to quantitatively analyze the direct and indirect effects of SCR and DSC on sustainability. The numerous surveys we conduct among supply chain ecosystem stakeholders provide a rich picture of practical implications and contextual nuances. In sum, our early findings generally support a positive relationship between SCR and sustainability in and of itself decrying the need for more resilient supply networks for sustainability. We further find the beneficial impact of digital technologies in promoting sustainability via enhancing environmental control and controlling for efficiency in supply chains. We also offer evidence to show that supply chain dynamism compounds the positive logic between SCR and DSC and sustainability. As a final word, it must be noted that our work speaks to the burgeoning Supply Chain Dynamism as moderator literature by examining the direct and contingent effects of SCR and DSC on not only performance but sustainability. By shedding light on the moderating role of dynamism, the study provides fresh insights into the multifaceted nature of supply chain management and sustainability practices. The study's findings enhance theoretical understanding by elucidating the synergistic effects of SCR, DSC, and sustainability in dynamic supply chain settings. It augments existing theoretical frameworks by integrating concepts of resilience, digitalization, and sustainability into a comprehensive model. Practical and economical, the research offers actionable guidance for organizations aiming to improve sustainability performance through resilient and digitally advanced supply chains. By acknowledging the role of supply chain dynamism, managers can tailor strategies to manage disruptions effectively and leverage digital innovations. Economically, adopting sustainable practices can result in cost savings and competitive advantages. The research emphasizes the importance of aligning supply chain strategies with sustainability goals to drive long-term value and societal impact.

This research explores and analyzes the challenges and opportunities due to globalization's impact on sustainable strategic management. The research uses a mixed-method design, combining primary and secondary data collection methods. Secondary data is sourced from various credible publications and analyzed through an extensive literature review. A case study approach is adopted, involving semi-structured interviews with six experienced managers from Tazweed Venture Capital in Jordan. The study employs a qualitative, descriptive, and analytical approach to develop a conceptual framework by exploring managers' experiences and perspectives on Globalization and its impact on Sustainable Strategic Management. The findings identify challenges of environmental degradation, economic inequality, transportation and logistics pressures, and compliance challenges for sustainability. While implementing sustainable practices incurs upfront costs, accessing renewable energy markets and financial support presents opportunities. Tazweed successfully implements sustainable strategic management, emphasizing stakeholder engagement and collaboration across departments. This research offers valuable insights and guidance for companies navigating globalization's impact on sustainability strategic management.

External audit reliance issues on the internal audit function (IAF) are increasingly important in financial auditing, yet its application in audit engagements lags behind other applications. Despite the belief that audit reliance will shape auditing in the future, limited and intervalley publications explore this transformative potential. This paper investigates the increasing importance of external audit reliance issues in financial auditing. It investigates the use of the IAF in external audit reliance decisions and its potential to enhance audit quality, process transparency, and stakeholders' credibility. Through a systematic literature review of 68 scientific articles from 1984 to 2022, factors influencing external auditors' dependence on the IAF are analyzed, including IAF work quality, assistance type, organizational factors, customer pressure, and business risk. The review highlights the IAF's crucial role in improving financial reporting integrity and external audit effectiveness. However, the challenges that allowed external auditors to decide whether to rely on the works of IAF like limited disclosures and accessible data hinder assessing IAF reliance effects, leading to information asymmetry that may impact stakeholder confidence. The paper discusses implications, limitations, and future research directions to explore technology adoption and optimize audit practices, promoting transparency in the audit process.

This paper addresses the conceptual exploration of various issues that form an integral part of the ethical dimensions surrounding the use of artificial intelligence (AI) in the field of marketing. We critically review some of the main ethical challenges AI poses to humanity: privacy, data security, bias, transparency, and accountability. Therefore, we will discuss the delicate balance between exploiting the transformation potential of AI for personally designed marketing strategies and ethical imperatives to safeguard the rights of consumers to retain trust. Then, the present regulatory landscape responding to these ethical challenges will be assessed by building on effective regulation, like the GDPR, existing proposed legislative frameworks, and industry guidelines. To underscore the role of an ongoing dialogue between marketers, technologists, ethicists, and regulators for developing a responsible AI ecosystem in marketing. Further, strategic recommendations for implementing company-based ethical AI marketing practices. The further strong guidelines provide enhancement transparency to consumers and investment in research to remove biases from algorithms. It also underscores principal scopes of further research and development, focusing on the need for new-age solutions to guide the ethical quagmires that AI-led marketing throws up. We suggest that integration should be done proactively and collaboratively. Thus, if attention is paid more to ethics and multidisciplinary dialogue, only such hyperbolic promises can be realized by AI-driven marketing. There are such promises through which AI-driven marketing will meet business goals and be huge at societies' values.

This work probes the combined effects of magnetic field and viscous dissipation on heat field and examine the second law analysis (entropy generation) in an electrically conducting fluid under the effect of wall mass transfer over continuous stretched non-isothermal surface with variable viscosity. The viscosity of the fluid is assumed to be an inverse linear function of temperature. The governing equation for the problem are changed to dimensionless ordinary differential equations by using similarity transformation and solved numerically by using Rung Kutta and Shooting technique. Velocity, concentration and temperature distribution are obtained and used to compute the entropy generation and the Bejan number in the flow field. The effect of variable viscosity, Schmidt number, Hartman and Reynolds number on the velocity, concentration, temperature, entropy generation and Bejan number are studied and discussed.

Load variations in any power system result in losses escalation and voltage drops. With the sensible and optimal allocation of distributed generators (DGs), these problems could be considerably mitigated. It has been seen in the priorly existing methods that ideally allocation of DGs has been carried out during fixed loads and constant power requirements. However, in real scenarios the loads are always variable and allocation of DGs must be done in accordance to the variations of the connected load. Therefore, the current paper addressed the aforementioned problem by distinctive optimal allocation of DGs for each variability of 24hour load horizon. However, the single exclusive solution is considered among all allocations of 24 hours. The min-max regret concept has been utilized in order to deal with such methodology. Altogether, 24 scenarios are analyzed wherein each scenario corresponds to a specific hour of the respective day. The optimal allocation of DGs in terms of their optimal sizing and placement has been carried out by using three algorithms including battle royal optimization (BRO), accelerated particle swarm optimization (APSO) and genetic algorithm (GA). The multi-objective optimization problem is evaluated on the basis of minimum value criterion of the multi-objective index (MO). MO comprises of active and reactive power losses and voltage deviation. Hence, in order to find robustness of proposed technique, Conseil international des grands réseaux electriques (CIGRE’s) MV benchmark model incorporating 14 buses has been considerably used as a test network. In the end the results of three proposed algorithms have been compared.

Today, satellite imagery has made a major contribution to the reconstruction and spatial prediction of sensitive or complex areas such as Pendjari and W Transboundary Reserves which constitute biodiversity reservoirs and habitats for wildlife conservation. Despite the protection to which they are subject, they remain dependent on climatic hazards that can influence their stability. This study has applied remote sensing techniques, combined with climate records from the last thirty years, to analyze the past dynamics of land use and climate changes, to predict the future states of the vegetation cover of the two national parks in Benin, as well as their periphery. The methodology used remote sensing and GIS techniques that allowed the supervised classification of Landsat images of 1985, 2000 and 2015. Climatic data were combined in R software to identify the break periods for climatic parameters. Finally, the predictive vegetation cover for the year 2030 was made by combining vegetation and climate in the "Land Change Modeler" extension. Ten land use and land cover classes were obtained. These are the agglomerations, mosaics of fields and fallows, water bodies, dense forests, gallery forests, clear forests and wooded savannahs, swamp forests and shrubby wooded savannahs, saxicolous savannahs and bare ground. The natural vegetation decreased from 90.85% in 1985 to 83.54% in 2000 then to 79.56% in 2015, a decline of 11.39% over a 30-year period. The analysis of the climatic curves revealed the presence of break, meaning drought frequency. The predictive modeling revealed that land use units projected to 2030 are consistent with past trends, but with the continued expansion of fields and fallows (2%) at the expense of vegetation cover. This study will motivate many others in the field.

The prolonged exposure to nicotine and the development of nicotine dependence have significant implications for cancer risk. Tobacco use, driven by nicotine addiction, is a major contributing factor to the development of various types of cancer. Smoking tobacco, in particular, has been strongly associated with an increased risk of lung cancer, as well as other malignancies. The harmful chemicals present in tobacco products, including carcinogens, can cause DNA damage and promote the initiation and progression of cancerous cells. This article presents a comprehensive literature review on the neurobiology of nicotine dependence and its implications for tobacco use treatment. Nicotine dependence is a complex phenomenon involving various neurobiological mechanisms. When nicotine enters the body, it binds to nicotinic acetylcholine receptors in the brain's reward circuitry, triggering the release of neurotransmitters like dopamine, serotonin, and norepinephrine. Over time, repeated nicotine exposure leads to neuroadaptive changes in the brain, resulting in increased motivation to seek and use the drug. Understanding the neurobiology of nicotine dependence is crucial for developing effective treatment strategies. Pharmacological interventions, such as nicotine replacement therapy and medications like bupropion and varenicline, can help individuals manage cravings and withdrawal symptoms. Additionally, behavioral therapies and counseling play a vital role in enhancing self-efficacy and providing support for smoking cessation efforts. By reviewing the existing literature, this article sheds light on the intricate neural pathways and processes involved in nicotine addiction. It emphasizes the importance of a multidimensional approach that combines pharmacological treatments and behavioral interventions to address the physiological and psychological aspects of nicotine dependence. This knowledge can inform the development of more targeted and personalized treatment approaches to help individuals overcome tobacco addiction and improve their chances of successful smoking cessation.

In this work, meshless methods are applied for the solution of two-dimensional steady-state heat conduction problems with nonlocal multi-point boundary conditions (NMBC). These meshless procedures are based on multiquadric radial basis function (MQ RBF) and its modified version (i.e. integrated MQ RBF). The proposed meshless methods which were recently published in \cite{Reutskiy2016} is compared with standard collocation method (i.e. Kansa's method). Three different sorts of solution domain are considered in which Dirichlet boundary condition is specified on some part of the boundary and is related to the unknown function values at a discrete set of interior points. The influence of NMBC on the accuracy and condition number of the system matrix associated to the proposed methods is investigated. The sensitivity of the shape parameter is also analyzed in the proposed methods. Performance of the proposed approaches in terms of accuracy and efficiency is confirmed on the benchmark problems.

Background. Green spaces contribute to a significant life quality and maintain the sustainability of cities. In Benin, despite the political greening willingness, municipalities are experiencing technical issues in finding suitable spaces to achieve this goal. This study should serve many other towns. It aims at identifying suitable areas for green spaces to integrate landscaping into urban planning in Abomey-Calavi district. Methods. The multi-criteria analysis combining GIS and the hierarchical classification approach were performed. Six factors (land use, altitude, slope, distance from main roads, proximity to urban centres and distance from flood zones, water bodies) were combined using the ArcGIS "Spatial Analysis" extension to generate a map of green space suitability. Results. large areas of land, of which 23.27% are very suitable and 26.06% are suitable for landscaping in this municipality. The ranking of the factors revealed altitude, proximity to road networks, large conurbations and distance from wetlands accounting for 18%, compared with 14% for the other factors regarding the study environment. However, the use of these results must take into account the existing inhabited areas for a good site selection. Conclusion. These outputs guidance to decision-makers in choosing suitable sites for green spaces there and integrating them into sustainable development.

Sensors became integrated through the control condition arrangement, either for visual, mechanical, biological, or chemical applications. New stuff is designed for detection, as Diluted Magnetic Semiconductors (DMS), and are considered attractive candidates that consist of a traditional 111- V, II-VI, or group IV semiconductor. Manganese Mn-doped GaN (Mn.Gac.N) epitaxial velum has a unique magnetic, visual and chemical properties in order to control system intelligent for detector design. The subject area of the magnetic properties of MnxGal-xN is on a large scale available, there are only a few studies on the visual properties and electrochemical properties of MnxGal-xN epitaxial velums. Where MnGaN velums were used in spintronic and opto-electronic applications according to their magnetic characterization and constructed MnGaN electrode are drop fabric potential for potentiometric sensor applications since they have good performance as ion-selective electrodes. The electrical and magnetic properties that allow the control of electron spin as well as complaint period, makes the materials ideal for spintronic applications. Designing such spintronic and optoelectronic devices based on MnxGal-xN requires a broader agreement of physical, visual, electrical and chemical properties epitaxial velums that are still seldom in the literature. This bailiwick displays the potential use of MnGaN semiconductor as an all solid-state potentiometric sensor for measuring anions in solutions in the control engineering field.

Climate change is affecting the planet, compromising survival and altering forest ecosystems. Investigating climatic variations in all regions is important. The aim of this research was to assess such variations in the W and Pendjari Biosphere Reserves in Benin from 1985 to 2015 and predict climate up to 2045. Drought frequency was assessed by using the Standardized Precipitation and Evapotranspiration Index (SPEI) and correlation was performed between climatic variables. Then a predictive analysis was computed. From 1985 to 2015, there was change in the climate with few severe dry and wet years while no extreme climatic condition was noticed. Most of the years showed nearly normal climatic conditions. The predicted climate indicates an absence of extreme conditions up to 2045 but an increase in the annual humidity is expected. A low decrease in annual mean temperature with high confidence is expected. Decision-makers can better organize adaptation programs and sensitize people in the reserves on their role in environmental conservation and mitigation of climate change using these outputs.

Keywords: Knowledge; Attitudes; Practices; Salt intake.

Background: Multi-drug resistance organisms (MDRO) often cause increased morbidity, mortality, and length of stays (LOS). However, there is uncertainty whether the infection of MDRO increase the morbidity, mortality, and ICU-LOS. Objective: This study performed to determine the prevalence of MDRO in ICU, site of infection and the association of MDRO or site of infection with mortality. Secondary outcome was determined by ascertaining the association of MDRO or site of infection with (ICU-LOS). Methods: A retrospective cohort study was performed with adult sepsis patients in ICU. Univariate and multivariate (MVA) logistic regression with cox regression modeling were performed to compute the association of MDRO on ICU-mortality. MVA modelling was performed for ICU-LOS predictors. Results: Out of 228 patients, the isolated MDRO was 97 (42.5%) of which 78% were gram-negative bacteria. The mortality rate among those with MDRO was 85 (37.3%). The hospital acquired infection (HAI) was significantly predictor for ICU-LOS in univariate linear regression (R² = 0.034, P=0.005). In MVA linear regression, both Enterococcus faecalis infection and acinetobacter baumannii (AC) -MDRO were predictors for ICU-LOS with (R² = 0.478, P<0.05). In the univariate cox regression, only the infection with AC- MDRO was a risk factor for ICU-mortality with [ HR =1.802 (95% CI: 1.2 – 2.706; P = 0.005)]. Conclusions: Identifying risk factors for MDRO highlight the appropriate administration of empirical antibiotics and effectively control of source of infection which would reduce mortality and ICU-LOS. The usage of broad- spectrum antibiotics should be limited for those having substantial risk factors to acquire MDRO.

Water microbial contamination is a serious issue that poses a risk to both animal and human health. 120 water samples collected from main water source and drinkers from a poultry farm. Different bacterial pathogens were isolated from water sources. Escherichia (E.) coli, Pseudomonas (P.) aureoginosa, (Salmonella) S. Typhimurim, Aeromonas (A.) hydrophila at different percentages. Variable degree of bacterial resistance to some commercial disinfectants commonly used to disinfect water system (iodine, terminator and H2O2). Nanoparticles were used to control bacteria in water. About the safety investigation for the prepared nanomaterials, the work results demonstrated that zinc oxide (ZnO) nanoparticles (NPs) exhibit the highest safety profile among the manufactured materials. The median fatal dose (LD50) for ZnO NPs was determined to be 3709 mg/kg body weight. In comparison, the LD50 values for zeolites and nanocomposites were 3251 mg/kg and 2658 mg/kg, respectively. Therapeutic dosages were estimated based on the LD50. Zeolite NPs, ZnO NPs and ZnO/zeolite NPs showing promising results in control of those bacteria. It was concluded that the escalating resistance of bacteria to disinfectants have led to a need to find alternative such as nanoparticles that proved promising results in control of pathogens, particularly it showed a safe effect on laboratory animals.

Molecular classifications of colorectal cancer (CRC) are benefitting cancer research by providing insights into subtype-specific disease prognosis and better therapeutic intervention. So far different conventional DNA markers such as microsatellite instability (MSI), CpG island methylator phenotype (CIMP), chromosomal instability (CIN), and BRAF and KRAS mutations have been used to classify CRC patients but have not shown promising prognostic values. Here, for the first time, we show classification of CRC tumors from Saudi Arabian patients based on gene expression profile (GEP). An existing method of CRC subtyping has been applied to the GEP of tumors from Saudi CRC patients. Survival analysis was carried out on predicted CRC subtypes. In-silico functional analyses were conducted on the gene signature used for subtype prediction. The predicted subtypes showed distinct but statistically insignificant overall survival distribution (log-rank test, p = 0.069). Comparison of predicted subtypes in Saudi CRC patients with that of the French one showed significant dissimilarity in the two populations (Chi-square test, p = 0.0091). Functional analyses of the gene signature used for subtyping suggest their association with “cancer” and “gastrointestinal diseases”. Most of the signature genes were found differentially expressed in CRC tumors compared to adjacent normal tissues. Such a classification framework might help improve the treatment of colorectal cancer patients.

In this paper we designed system for smart university building based on artificial intelligence (AI) and internet of things (IOT). Our idea can be summarized in smart security system that has different sensors to detect the surrounding environment of the class room in campus which keep everyone and everything on campus safer. By using (IOT), (AI) technologies and applications and by using microcontroller programming we can make the university building safer, secure and more energy saves.

Pruning is an important part in controlling the branching, good fruit size, and prodctivity of fruit trees. and consequently, ‘Valencia’ orange trees were grown many years ago, the trees were suffering from a decline in productivity in the newly reclaimed lands after certain years of plantation. This study elucidated the effect of pruning severity on growth, yield and fruit quality of ‘Valencia’ orange trees. Four levels of pruning were applied on 35 years old ‘Valencia’ orange trees as follows: T1: Control (un-pruned), T2: Light pruning ( 25% of main branches were removed); T3: Moderate pruning (50% of main branches were removed) and T4: Heavy pruning: 75% of main branches were removed. The treatments were done in February 15th (for each season). The results indicated that pruning severity increased vegetative growth paraments such as shoot length and leaf area and decreased canopy volume of Valencia orange trees in comparison to control. Maximum yield was gained from 75% followed by 50% and 25% pruning severity treatment. The pruning treatments improve in fruit weight, size, firmness, juice content, TSS%, TSS/acid ratio and vitamin C content. In addition, pruning produced an increasing in fruit yield per tree as well as yield increasing %. Hence, it might be concluded that pruning at different severity applied in February can be used effectively on ‘Valencia’ orange trees to improve vegetative growth, fruit physical and chemical properties. Besides, increasing fruit yield by nearly 20% in comparison to control.

New class of biologically active and non-active compounds can be synthesized via transition metal mediated Suzuki cross coupling reaction that has a great impact on the advancement of organic chemistry. These resulted products can lend a helping hand in pharmaceutical and polymer chemistry for the betterment of mankind. Suzuki-Miyaura cross coupling reaction is one of the best tools through which many natural and non-natural compounds can be synthesized.

The use of chimeric antigen receptor (CAR) in natural killer (NK) cells for cancer therapy is gaining momentum, marking a significant shift in cancer treatment. This review aims to explore the potential of CAR-NK cell therapy in cancer immunotherapy, providing a fresh perspective. It discusses the innovative approaches in CAR-NK cell design and engineering, particularly targeting refractory or recurrent cancers. By comparing CAR-NK cells with traditional therapies, the review highlights their unique ability to tackle tumor heterogeneity and immune system suppression. Additionally, it explains how novel cytokines and receptors can enhance CAR-NK cell efficacy, specificity, and functionality. The review underscores the advantages of CAR-NK cells, including reduced toxicity, lower cost, and broader accessibility compared to CAR-T cells, along with their potential in treating both blood cancers and solid tumors.

Phytoalexins are naturally-occurring molecules with antimicrobial activity deriving from the secondary metabolism of plants, which are synthesized in response to physical agents or stresses, phytopathogenic agents (fungi, bacteria and viruses) as well as numerous chemical compounds and biological control agents. Among these, grapevine phytoalexins, which belong to the chem-ical group of stilbenes, exhibit biocidal activity against a large number and a variety of plant pathogens. An important issue in research on these compounds is to be able to stimulate their synthesis in planta and to determine whether the induction of their production can serve as a basis for protecting that plant against its pathogens. Quite a few chemical compounds, derivatives of phytohormones bio-elicitors as well as biocontrol agents have been used to induce the synthesis of stilbene phytoalexins with the aim of conferring protection to grapevine against its main dis-eases (gray mold, downy mildew, powdery mildew and esca). This article reviews the experi-ments that have been carried out in this direction during the last thirty years and shows that the observed protective effects towards pathogens are generally linked to induction and priming of the grapevine phytoalexin response, confirming the interest of using, in a more general way, stimulation of the production of phytoalexins in plants as a basis for crop protection.

Kinesio tape is considered one of the most common techniques which using recently, where it is used as a therapeutic technique for pain relief, correction of joint position, prevention of oedema and injuries, improve range of motion and muscular activity for the individual. This study is a descriptive research design and aims to identify the effect of using Kinesio tape on the neuromuscular activity of quadriceps muscle after the rehabilitation program of the knee joint. The study sample consists of (10) players from different sports (football, basketball …etc.) and suffering from knee joint injuries. This sample was taken from Kafr-El sheikh and Kaleen club. Results showed that Kinesio tape doesn’t have any explicit effect on the neuromuscular activity of muscle but acts as a catalyst for muscle and promote a person’s feeling of psychological wellbeing and reassurance.When comparing results of using Kinesio tape during performing leg squatting and balance test with not using tape, founded that when performing leg squatting and balance test with using Kinesio tape, there were significant effects on muscle activity compared to not using it.

Synovial sarcomas are rare soft tissue tumors that infrequently occur in the ethmoid sinus, posing diagnostic challenges. Herein, we report a case of a 38-year-old male with a 7-month history of recurrent throbbing headaches, left eye pain, and facial nerve palsy, evolving into multiple stroke episodes. Radiological studies showed extension to the cavernous sinus, raising an initial suspicion of vasculitis. Histological findings of an endoscopic biopsy, however, confirmed a monophasic synovial sarcoma. Consequently, the patient was referred to a specialized center for comprehensive management. This case underscores the rarity of ethmoid sinus synovial sarcomas, their diverse clinical presentations, and the necessity of a multidisciplinary approach for accurate diagnosis and tailored therapeutic strategies.

The goal of the current study is to analyse several nonlinear two-dimensional time-fractional Rosenau Hymanequations. The two-dimensional fractional Rosenau-Hyman equation has extensive use in engineering and applied sciences. The fractional view analysis of two-dimensional time-fractional Rosenau-Hyman equations is discussed using the homotopy perturbation approach, adomian decomposition method, and Yang transformation. Some examples involving two-dimensional time-fractional Rosenau-Hyman equations are provided in order to better understand the suggested approaches. The solutions appear as infinite series. We offer a comparison between the accurate solutions and those that are generated employing the proposed approaches in order to demonstrate the effectiveness and applicability of the proposed techniques. The results are graphically illustrated using 2D and 3D graphs. It has been noted that the obtained results and the targeted problems real solutions are quite similar. Calculated solutions at various fractional levels describe some of the problems useful dynamics. Other fractional problems that arise in other fields of science and engineering can be solved using a modified version of the current techniques.

Salinity is the most significant abiotic stress affecting crop yield worldwide, breeders are Salinity is the most important abiotic stress limiting crop production throughout the world, and breeders are encouraged to test novel genotypes for their resistance to this selection agent. However, getting a sufficient number of plants for the evaluation can be a lengthy and time-consuming procedure that might be shortened by applying in vitro techniques. An experiment was conducted under controlled saline circumstances using a tissue culture technique to investigate the influence of salt on several physic-biochemical parameters. Micro-shoots of Volkamariana lemon, sour orange, trifoliate orange, and Cleopatra mandarin rootstocks were re-cultured on MS media supplemented with NaCl from 25, up to 150 mM. Following the experiments, all of the tested rootstocks' morphological and biochemical characteristics, stomata behavior, and element accumulation were measured. As a result, adding NaCl from 25 to 150 mM to MS media caused a reduction in all morphogenetic parameters such as shoot number, shoot length, leaves number, and survival percentage was measured compared with control. Photosynthesis pigment, RWC, K, and Ca ions were decreased by increasing NaCl from 100 to 150 mM. On the contrary, proline, Cl, and Na were increased. Cleopatra mandarin and Trifoliate orange are more tolerant to salt stress than Volkamariana lemon and sour orange citrus.

In the present paper, the effect of the non-linear thermal radiation on the neutral gas mixture in the unsteady state is investigated for the first time. The unsteady BGK technique of the Boltzmann kinetic equations for a neutral non-homogenous gas is solved. The solution of the unsteady case makes the problem more general significance than the stationary one. For this purpose, the moments' method, together with the traveling wave method, is applied. The temperature and concentration are calculated for each gas component and mixture for the first time.Furthermore, the study is held for aboard range of temperatures ratio parameter and a wide range of the molar fraction. The distribution functions are calculated for each gas component and the gas mixture. The significant non-equilibrium irreversible thermodynamic characteristics the entire system is acquired analytically. That technic allows us to investigate the consistency of Boltzmann's H-theorem, Le Chatelier principle, and thermodynamics laws. Moreover, the ratios among the different participation of the internal energy alteration are evaluated via the Gibbs formula of total energy. The final results are utilized to the argon-helium non-homogenous gas at different magnitudes of radiation force strength and molar fraction parameters. 3D-graphics are presented to predict the behavior of the calculated variables, and the obtained results are theoretically discussed.

Introduction: The attitudes of doctors and nurses toward patient safety is a significant factor in hospital safety climates and medical error rates. Yet, there are very few studies of patient safety attitudes in Saudi hospitals and none conducted in hospital emergency departments. Aims: The current study aims to investigate the discrepancy between the patient safety attitudes of doctors and nurses in a Saudi hospital emergency department. Materials and Method: The study employed a qualitative research designvia semi-structured interviews with Saudi and non-Saudi doctors and nurses working in a Saudi hospital emergency department to determine their attitudes and experiences about the patient safety climate. Results: The findings showed doctors and nurse held some similar safety attitudes, however, nurses reported issues with doctors with respect to their teamwork, communication, and patient safety attitudes. Moreover, several barriers to the patient safety climate were identified such as limits to resources, teamwork, communication, and incident reporting. Conclusion: The findings provide one of the few research contributions to knowledge on the differential patient safety attitudes of Saudi and non-Saudi doctors and nurses and suggest the application of such knowledge would enhance positive patient outcomes in emergency departments.

This research paper describes the social engineering concepts, techniques, and security countermeasures. This research aims to study various social engineering techniques to find the best countermeasures that would help to reduce social engineering attacks.

This paper presents multidisciplinary and innovative research concerning fighting against coronavirus through wastewater collection and treatment. Studies suggest that coronavirus exists in the wastewaters. Untreated wastewater is proved to spread the virus. Coronavirus is attacking people globally and shrinking the economy. This paper highlights the idea that the coronavirus shall be defeated with the help of wastewater collection and treatment as well. The question addressed by this paper is will communities defeat the coronavirus without well-collected and treated wastewaters? This research aims to display the role of wastewaters in the spread of coronavirus in cities and to require their collection. The methods to achieve the goals are theoretical surveys, case study strategy, mathematical modeling, statistical procedures, forecasting of future, and dialectical discussions. The findings of this research demonstrate the need for carefully collected and treated wastewaters to overcome the coronavirus. This paper gives suitable techniques to collect and treat wastewater such as wastewater stabilization ponds, bacterial reactors, and anaerobic ponds. The innovative idea of this paper, its suggested indicators to select a certain wastewater treatment technique in every city, and its outcome will assist the global community to fight the coronavirus more effectively.

The purpose of the current study was directed to investigate the effectiveness of docosahexaenoic acid (DHA) as a chemopreventive agent on experimentally induced hamster buccal pouch (HBP) carcinogenesis; Material and methods: 40 Syrian male hamsters, five weeks old, were divided into 4 groups of 10 animals in each as follows, GI: Topical application of liquid paraffin alone (thrice a week for 14 weeks), GII: Topical application of 7, 12 dimethyl benz[a]anthracene (DMBA) alone (0.5 % in liquid paraffin, thrice a week for 14 weeks), GIII: Topical application of DMBA (0.5 % in liquid paraffin, thrice a week for 14 weeks) + Oral administration of DHA (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks on alternative days of DMBA application), GIV : Oral administration of DHA alone (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks); Results: Gross observations and histopathological findings revealed a-GI: normal stratified squamous epithelium b- GII: well and moderately differentiated squamous cell carcinoma (SCC) c-: GIII: showed variable results ranges from hyperkeratosis, hyperkeratosis and focal hyperplasia, mild dysplasia, and well differentiated SCC with superficial invasion of tumor cells not extended to deeper areas d: GIV: normal similar to GI. Immunohistochemical results revealed that oral DHA treatment to DMBA treated hamsters restored the normal expression of bcl-2; Conclusion: DHA has the potential to be a dietary chemopreventive agent due to its capacity to improve carcinogen detoxification and to block/suppress the initiation and promotion stages of experimentally produced HBP carcinogenesis.

This research paper is to analyze the planning and design techniques of the tourism complexes in the process of municipalities’ master planning. First, it explains the importance of the tourism industry with the help of theories of scholars and experts. Then, it emphasizes the link between the economic developments of cities/regions with the development of the tourism industry. The innovation of this work is to integrate tourism industry planning and comprehensive regional/ urban planning. The main way of doing this is to plan and design the tourism complexes in the early stages of the master planning of the municipality. Urban land-use policies and locating techniques are suggested through this research. Land-use policies and new urban design models for the regional/urban sustainable development are some of the other handouts in this paper. The outcome of this research is good assistance for engineers, planners, and students of urban and regional development.

Speech emotion recognition (SER) is a technology that can be applied in distance education to analyze speech patterns and evaluate speakers’ emotional states in real-time. It provides valuable insights and can be used to enhance the learning experience by enabling the assessment of instructors’ emotional stability, a factor that significantly impacts information delivery effectiveness. Students demonstrate different engagement levels during learning activities, and assessing this engagement is an important aspect of controlling the learning process and improving e-learning systems. An important aspect that may influence student engagement is the emotional states of their instructors. Accordingly, this research uses deep learning techniques to create an automated system for recognizing instructors’ emotions in their speech when delivering distance learning. This methodology entails integrating Transformer, convolutional neural network, and long short-term memory architectures into an ensemble to enhance SER. Feature extraction from audio data used Mel-frequency cepstral coefficients, chroma, Mel spectrogram, zero crossing rate, spectral contrast, centroid, bandwidth, roll-off, and root-mean square, with subsequent optimization processes adding noise to, conducting time stretching, and shifting the audio data. Notably, several Transformer blocks were incorporated, and a multi-head self-attention mechanism was employed to identify the relationships between the input sequence segments. The pre-processing and data augmentation methodologies significantly enhanced the precision of the results in that the model achieved accuracy rates of 96.3%, 99.86%, 96.5%, and 85.3% on the Ryerson Audio-Visual Database of Emotional Speech and Song, Berlin Database of Emotional Speech, Surrey Audio-Visual Expressed Emotion, and Interactive Emotional Dyadic Motion Capture datasets. Furthermore, it achieved 83% accuracy on another dataset created for this research—the Saudi Higher Education Instructor Emotions dataset. The results demonstrate this model’s considerable accuracy in detecting emotions in speech data across different languages and datasets.

Globally, the fuel demand is increasing rapidly and the conventional method to produce fuel is toxic which causes environmental degradation and climate crisis. Therefore, biodiesel emerges as the substitute to overcome the conventional fuel problems because biodiesel is renewable and non-toxic. Biodiesel synthesis is the process of using fats and oils to produce biodiesel ester and glycerol. Biodiesel can be produced using edible and non-edible feedstock but using the edible feedstocks problems like fuel vs food, nutritional value and economic considerations were raised. Therefore, non-edible feedstocks are being used to overcome problems arising from edible feedstock. As non-edible feedstocks can easily be grown anywhere on land, doesn’t cause imbalance to food economy and has low cost. Many non-consumable seeds like Mahua, Jatropha, Castor, Neem etc. are used to produce biodiesel. Now a days, researchers are using nanoparticles to enhance the stability, quality, and properties of biodiesel. In future, researchers can use algae and microbial oils for production of biodiesel. Research can also use biojet fuel in such a way that it reduces the carbon emission. In future, production of biodiesel can be integrated into circular economy models to reduce environmental waste and impact. In this review we will discuss the production methods for biodiesel, catalysts for biodiesel production, and non-edible feedstock properties of biodiesel.

Global warming and climate change have been the major concern for multiple disciplines. Population growth, urbanization, and industrialization are major contributing factors to such a problem by escalating the use of fossil fuels to meet their energy demands. The building sector has the largest share in using the total globally produced energy and emitting tons of greenhouse gas emissions. Emerging eco-friendly technologies such as solar and wind energy harvesting are being extensively explored but still, they are insufficient. Nature-inspired technologies can be the solution to our problem. For instance, algae are microorganisms that use water, light, and CO2 to produce energy and sustain life. Exploiting such characteristics in the built environment is termed algae building technology, a very efficient and green application for a sustainable future. Algae-integrated façades show great versatility through biomass and energy production, wastewater treatment, shading, and thermal and acoustic insulation. In this paper, algae will be introduced as a robust tool toward a greener and more sustainable future, The algae-building technology and its implementation will be demonstrated. Steps for applying this sustainable approach in Egypt will be discussed.

(1) Background: Breast cancer (BC) is the second largest cause of mortality in female worldwide. Besides from basic risk factors, there are several hereditary variables that contribute to BC. Breast cancer has been linked to a variety of nuclear DNA changes as well as mitochondrial DNA alterations. The aim of this study was to analysis the association of mitochondrial tRNA leucine2 gene with BC. (2) Material and methods: In the current study, 24 samples have been collected from various families in Peshawar. DNA was extracted from Blood. PCR was used to amplify the mitochondrial tRNA MT-TL2 gene, and 22 samples were sequenced. The sequence was compared with accession #NC-012920.1 of the revised Cambridge Reference Sequence (rCRS). (3) Results: The results (Chromatograph, nucleotide sequence and rCRS alignment) shows mutations in mitochondrial tRNA MT-TL2 gene in our participants is not the cause of Breast cancer. (4) Conclusion: Yet, a significant number of BC patients must be studied, and their full mitochondrial DNA must be analyzed. This will provide an indication of the potential DNA marker that might be used to prevent BC deaths at the earliest stages.

Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, we propose novel hybrid machine learning approaches that exploit auxiliary numerical data. The proposed hybrid methods invoke different machine learning paradigms, including feature selection, classification, and regression. Additionally, numerical weather prediction (NWP) models are used in the proposed hybrid models. Feature selection is used for feature space dimension reduction to reduce the large number of recorded parameters that affect estimation and prediction processes. The rough set theory is applied for attribute reduction and the dependency degree is used as a fitness function. We investigate the effect of the attribute reduction process with thirty different classification and prediction models in addition to the proposed hybrid model. Then, different machine learning models are constructed based on classification and regression techniques to predict solar radiation. Moreover, other hybrid prediction models are formulated to use the output of the numerical model of Weather Research and Forecasting (WRF) as learning elements in order to improve the prediction accuracy. The proposed methodologies are evaluated using a data set that is collected from different regions in Saudi Arabia.

A ducted photovoltaic façade (DPV) unit Studied using experimental Prototype and simulated in a full scale Computational Fluid Dynamics CFD Model. The Study comes in two parts; This is Part I with the title detailed above and Part II titled ‘A Ducted Photovoltaic Façade Unit with Buoyancy Cooling: Part II CFD Simulation’.. The process adopted in the experimental study is replicated in the simulation Part. The aim was to optimize the duct width behind the solar cells to allow for maximum buoyancy-driven cooling for the cells during operation. Duct widths from 5 to 50 cm were tested in a Proto-type. A duct width of 45 cm had the maximum calculated heat removed from the duct; however, the lowest cell-operating temperature was reported for duct width of 50 cm. It was found that the DT between ducts' inlets and outlets range from 5.47 °C to 12.32 °C for duct widths of 5–50 cm, respectively. The ducted system enhanced module efficiency by 12.69% by reducing PV temperature by 27 °C from 100°C to 73 °C. The maximum calculated heat recovered from the ducted PV system is 422 W. This is 47.98% from the incident radiation in the test. Total summation of heat recovered and power enhanced by the ducted system is 61.67%.

This paper reviews the low-resilience problem in many cities, poor designs of cities to cope with disasters, and the need for tolerance of urban constructions. It explores answers concerning the question of how shall we build cities resiliently? The method of this applied research is a multiphase process that considers all physical and socioeconomic elements of a city. It introduces six indicator groups of urban management (M), economy (E), built environments (U), Infrastructures (I), natural environments (N), and health protection (H). The groups include 55 indicators as variables in the mathematical calculations in this paper. This paper builds a mathematical model to maximize the profitability of resilient buildings by optimizing investments in the required projects. The projects will upgrade the firmness and tolerance of cities against nature-based and human-made dangers and risks. There is a linear programming in 55 variables to select optimal solutions from fifty-five factorial alternatives. Then, the programming will develop into non-linear programming. The unique innovation of this paper is its linear programming interpretation by non-linear to give optimal solutions for the problem. Applying the Lagrange function in the Kuhn-Tucker conditions proves the accuracy of the hypothesis that post-COVID urbanization requires maximum resilience. Only in this way, the urban economies will be free of risks. Outcomes in this paper will assist in the pre-planning, design, and building of built environments everywhere resilient and sustainable.

This paper discusses devastating urban floods in the year 2019 that caused human and socioeconomic losses in many countries, including Iran. The main question addressed by this paper is the choice between two flood management models, namely, the optimal and nature-based flood management or the existing hazardous situation that damage the ecosystem and natural resources. The analysis of this paper will find the main responsible factors in the mentioned floods in Iran. For this reason, it examines the impacts of the existing flood management that neglects the ecosystems, environmental components, and nature. The method of this research includes theoretical studies, case studies with the help of structured interviews, and observations. A benchmarking technique compares the two alternatives. The comparisons use seven indicators abstracted from successful global experiences and local knowledge. Finally, this research presents a model for optimal flood management that is applicable everywhere in the world.

Abstract: Ovulation failure was associated with a reduction in pre-mating concentrations of oestradiol-17β and prolactin (PRL). The present study aimed to evaluate whether pre-mating PRL levels have a role on the reproductive efficiency of doe rabbits. A total of 78 multiparous California does (2nd parity) were divided, according to plasma pre-mating PRL, into five categories, >20-25, >25-30, >30-35, >35-40, and >40-45 ng/ml. Does in all categories were naturally mated and kindled, then their reproductive measurements and progesterone (P4) levels were determined. Results show that pre-mating PRL averaged 23.60±0.78, 28.00±0.83, 33.46±0.43, 38.17±0.49 and 41.98±0.68 ng/ml in five categories (p < 0.05), respectively, representing the highest distribution (38.5%) in the 3rd-category. Live body weight of doe rabbits, at mating, pregnancy, and parturition increased (p < 0.05) with increasing pre-mating PRL level. The number of services, litter size, and pregnancy rate increased (p < 0.05) by increasing PRL levels. Reproductive traits and P4 level at mid-pregnancy of does, and average weight of kits at birth increased (p < 0.05) by increasing PRL levels. The pre-mating PRL profile is important for the identification of reproductive performance in doe rabbits.

In present paper, spatial Minkowski Pythagorean Hodograph (MPH) curves are characterized with Rational Rotation Minimizing Frames (RRMFs). We define Euler-Rodrigues Frame (ERF) for MPH curves and by means of this concept, we reach the definition of MPH curves of type (n, m). Expressing the conditions provided by these curves in the form of Minkowski-Hopf map that we define, it is aimed to establish a connection with the Lorentz force which occurs during the process of Computer Numerical Control (CNC) type sinker Electronic Discharge Machines (EDMs). This approach is reinforced by split quaternion polynomials. Finally, we give conditons satisfied by MPH curves of low degree to be type (n, m) and construct illustrative examples.

Molecular analysis is an easier means to identify and isolate a specific gene which has imperative function for growth, body composition , fat deposition, metabolic and skeletal traits as well as the molecular genetics selection on individual genes is a very efficient method to genetically improve economically important traits in chickens. Insulin- like growth factor 1 ( IGF-1)is a member of a heterogeneous group of peptides with important growth.Transforming growth factorβ ( TGF-β) belongs to a large family of growth and differentiation factors that play a pivotal role in a great variety of biological activities including morphogenesis, development and differentiation. DNA was extracted from 48 chickens sampled from three strains Lohman (17) , Sinai (24) and Gimmizah (7) IGF-1 gene and TGFβ2 gene were amplified using PCR protocol. Electrophoresis was carried out on the products of PCR , bands viewed on transilluminator. The size of IGF-1 gene was 675 bp while the size of TGFβ2 gene was 188bp. Sharp bands were purified and sequenced and used the dendrogram to show the relationships between other vertebrate species

(1) Background: The present study was carried out to provide new information about the relation between angiogenesis, tumor stage Oral squamous cell carcinoma (OSCC); (2) Materials and methods: Thirty formalin-fixed paraffin embedded blocks were used, 10 of them were previously diagnosed as well differentiated OSCC, 10 moderate differentiated OSCC and 10 poorly differentiated OSCC. To determine the expression of CD31 and D2-40 proteins, streptavidin-biotin immunoperoxidase staining technique was used. The areas with the most vascular density (hot spots) were determined. The stained vessels were counted independently in intratumoral and peritumoral stroma in five areas of hot spot at ×400 magnification; (3) Results: Immunohistochemical staining using CD 31 protein showed that CD31-positive vessels in the peritumoral and intratumoral stroma subjacent to the malignant invading nests which was recorded highest values in poor differentiated OSSC followed by moderate differentiated OSSC then well differentiated OSSC. D2-40 expression was positive in lymphatic vessel in the peritumoral and intratumoral stroma subjacent to the malignant invading nests. Poorly differentiated OSSC tissue sections recorded the highest vessels count followed by moderate differentiated OSSC then well differentiated OSSC. There was statistically significant difference found between the three studied groups regarding CD31 and D2-40 levels. Also there was statistically significant positive correlation found between CD31 level and D2-40 level and vice versa; (4) Conclusion: CD31 and D2-40 are related to stage of OSCC and are consistent with angiogenesis in tumor progression.

The design of highly efficient sensitizers is one of the most significant areas in dye-sensitized solar cell (DSSC) research. We have studied a series of benzothiadiazole-based D-π-π-A organic dyes, putting emphasis on the influence of the donor moiety on the DSSC’s efficiency. Using linear response time-dependent density functional theory (TDDFT) with the CAM-B3LYP functional different donor groups were characterized in terms of electronic absorption spectra and key photovoltaic parameters. As a reference a dye has been considered which has a benzothiadiazole fragment linked via thiophene rings to a diphenylamine donor and a cyanoacrylic acid acceptor. The different systems are first studied in terms of individual performance parameters, which are eventually aggregated into the power conversion efficiency. Here only the amino-substituted species shows a modest increase, whereas the dimethylamino case even shows a decrease.

(1) Background: Colon polyps are common protrusions in the colon’s lumen with potential risks of developing colorectal cancer. Early detection and intervention of these polyps are vital for reducing colorectal cancer incidence and mortality rates. This research aims to evaluate and compare the performance of three machine-learning image classification models’ performance in detecting and classifying colon polyps. (2) Methods: The performance of three machine learning image classification models, Google Teachable Machine (GTM), Roboflow3 (RF3), and You Only Look Once version 8 (YOLOV8), in the detection and classification of colon polyps were evaluated. The study used a dataset of colonoscopy images of normal colon, polyps, and resected polyps. The study assessed the models’ ability to correctly classify the images into their respective classes using precision, recall, and F1 score generated from confusion matrix analysis and performance graphs. (3) Results: All three models successfully distinguished between normal colon, polyps, and resected polyps in colonoscopy images. GTM achieved the highest accuracies: 0.99, with consistent precision, recall, and F1 scores of 1.00 for the `normal’ class, 0.97 - 1.00 for `polyps,’ and 0.97 - 1.00 for `resected polyps.’ While GTM exclusively classified images into these three categories, both YOLOV8 and RF3 extended their capabilities to detect normal colonic tissue, polyps, and resected polyps, with YOLOV8 and RF3 achieving overall accuracies of 0.84 and 0.87, respectively. (4) Conclusions: Machine learning, particularly models like GTM, shows promising results in ensuring comprehensive detection of polyps during colonoscopies.

Abstract: This article explores the intricate relationship between environmental degradation, specifically air pollution, and economic growth in the Sultanate of Oman spanning the period from 1990 to 2022. We employ cointegration and vector error correction models to uncover both short- and long-term dynamics in the association between air pollution and economic growth. Fur-thermore, Granger causality analysis is utilized to investigate the causal links between these crucial variables. This data encompasses factors related to environmental quality and various control variables. The empirical results unveil a sustained long-term cointegration connection between the variables. Additionally, our findings highlight a statistically significant positive impact of economic growth and energy consumption on CO2 emissions. Furthermore, the short-term analysis reveals an annual adjustment of approximately 14.1% in N2O emissions dis-equilibrium. The Granger causality study indicates unidirectional causal relationships involving N2O emissions, economic growth, and CO2 emissions. The implications of these findings for Oman's policy landscape are substantial. To effectively reduce greenhouse gas emissions, it is imperative for Oman to establish robust climate change policies. Additionally, the government can play a pivotal role in encouraging and endorsing the use of renewable energy sources, such as green hydrogen, as a promising alternative to traditional oil and gas resources.

The physicochemical treatment/recovery techniques, including precipitation, membrane technology, solvent extraction, foam fractionation, adsorption, and aqueous two-phase systems, will be reviewed. The bio-treatment processes, based on microorganisms and/or enzymes consuming nutrients available in food-processing wastewater as low-cost substrates to produce valuable products, will be discussed in detail, including the production of microalga biomass in wastewater treatment systems. Finally, future research direction will be proposed to integrate the circular economy and develop integrated food processing wastewater management systems.

Promoting organic foods production and consumption contributes to accomplishing United Nations sustainable development goals. Social commerce provides a promising opportunity to develop the organic food industry. However, there is limited knowledge regarding customer behaviors in relation to purchasing organic foods via social commerce platforms. Therefore, this study expanded upon the unified theory of acceptance and use of technology (UTAUT-2) to develop a comprehensive model that explains how customers' social commerce trust and behavioral intentions to purchase organic foods using Instagram social commerce affect their purchasing behaviors. The research model was analyzed by employing partial least squares structural equation modeling (PLS-SEM) for the data collected from a quantitative survey of 410 customers who used Instagram to purchase organic foods in Iran. The results revealed that facilitated purchasing conditions, hedonic motivations, social influence, rating and reviews, and influencers’ endorsements increase customers' purchase intentions. Moreover, Instagram’s recommendations and referrals, influencers’ endorsements, as well as social influence boost customers' trust in the social commerce platform. Eventually, it was determined that influencers’ endorsements, social commerce trust, and purchase intention determine a customer’s organic foods purchasing behaviors. This research provides valuable insights for organic food marketers to optimize their social commerce strategies.

In this paper, we implement a new method binary Particle Swarm Optimization (PSO) for solving the kidney exchange problem, which will improve the future decisions of kidney exchange programs. Because using a kidney exchange, we can help incompatible patient-donor couples to swap donors to receive a compatible kidney. Kidney paired donation programs provide an innovative approach for increasing the number of available kidneys. Further, we implementing binary particle swarm optimization in parallel with MATLAB with one, two, three and four threads and from the computations point of view, the authors compare the performance to reduce the running time for kidney exchange to match patients as fast as possible to help clinicians. Moreover, implementing binary particle swarm optimization in solving the kidney exchange problem is an effective method. The obtained results indicate that binary PSO outperforms other stochastic-based methods such as genetic algorithm, ant lion optimization, and efficient the number of resulting exchanges.

This article describes a simple Susceptible Infected Recovered (SIR) model fitting with COVID-19 data for the month of march 2020 in New York (NY) state. The model is a classical SIR, but is non-autonomous; the rate of susceptible people becoming infected is adjusted over time in order to fit the available data. The death rate is also secondarily adjusted. Our fitting is made under the assumption that due to limiting number of tests, a large part of the infected population has not been tested positive. In the last part, we extend the model to take into account the daily fluxes between New Jersey (NJ) and NY states and fit the data for both states. Our simple model fits the available data, and illustrates typical dynamics of the disease: exponential increase, apex and decrease. The model highlights a decrease in the transmission rate over the period which gives a quantitative illustration about how lockdown policies reduce the spread of the pandemic. The coupled model with NY and NJ states shows a wave in NJ following the NY wave, illustrating the mechanism of spread from one attractive hot spot to its neighbor.

Competition between cotton, winter, and summer crops is the greatest obstacle for plant breeders in Egypt. Breeders are thus seeking early maturing, high-yielding cultivars that are suited for planting following winter crops. This study was conducted during the 2016 and 2018 growing seasons at the Sakha agriculture research station, Egypt's agricultural research facility. This research used breeding material from the F2, F3, and F4 generations that resulted from crossing Giza 94 and Uzbekistan. During the 2016 growing season, the F2 population was cultivated, and the top 5% of the F2 population (75 plants) were chosen based on the selection criteria. In the summer of 2017, the F3 families were cultivated, and 5% of the superior F3 families were chosen to become the F4 fam-ilies, which were planted in the summer of 2018 at the single plant and bulk studies in a randomised full block design with three replications. The average performance of the characteristics boll weight, seed cotton yield, lint percentage, and lint index increased as generations passed from F2 to F4. In the meanwhile, the characteristic value of the first flower to open decreased, showing the accu-mulation of advantageous alleles. For all examined characteristics, the phenotypic coefficient of variance was greater than the genotypic coefficient of variation. In addition, the data demonstrated that heritability in a broad sense was greater in F4 populations than in F3 and F2 populations. With a few exceptions, the phenotypic and genotypic associations for all investigated characteristics were positive and very significant. According to the data, initial opening flowering and boll weight had a substantial impact on seed cotton output per feddan. In general, five superior families No. 9, 13, 18, 19, and 20 were chosen from the F4 population, which were more significant for yield and yield component than the commercial variety, and these genotypes may be promising for the breeding programme to develop new genotypes with superior yield.

Almost one fifth of breast cancer cases express Human Epidermal Growth Factor-2 (HER2), and such expression is associated with highly proliferative tumor and poor prognosis. The introduction of anti-HER2 therapies has dramatically changed the natural course of this aggressive subtype of breast cancer. However, anti-HER2 therapy can be associated with substantial toxicities, mostly cardiac, and high cost. Over the past few years, there has been growing interest in de-escalation of anti-HER2 therapies to minimize adverse events and healthcare costs, while maintaining the efficacy of treatment. Data from clinical observations and single-arm studies have eluted to the minimal impact of anti-HER2 therapy in low-risk patients, like those with node-negative and small tumors. Though single-arm, the APT trial, in which patients with node-negative, small tumors received single-agent paclitaxel for 12 cycles plus trastuzumab for 1 year, was a practice-changing study. Several other recently published studies, like the PERSEPHONE trial, have shown more convincing data that 6 months of trastuzumab is not inferior to 12 months, in terms of disease-free survival (DFS), suggesting that de-escalating strategies with shorter treatment may be appropriate for some low-risk patients. Other de-escalating strategies involved adaptive, response-directed approach, and personalized therapy that depends on tumor genomic profiling.

Intelligent Transportation Systems (ITS) encompasses technologies, services, and applications facilitating communication between vehicles (V2V) and between vehicles and fixed infrastructure (V2I and I2V). This mutual interaction constitutes a Vehicular Ad-Hoc Network (VANET) which supports a plethora of applications targeting critical transportation aspects, such as safety, mo-bility, and environmental considerations. Dedicated Short Range Communications (DSRC), op-erating on the 5.9 GHz band, is pivotal for such exchanges. We introduced an innovative algorithm designed to identify jamming attacks and transition the Safety Application to a secure fail-safe mode. This algorithm leverages a dual-metric strategy, incorporating both distance and PDR measurements. Field tests confirm that our algorithm adeptly recognizes the activities of deceptive jammers, ensuring a prompt shift of the safety application into its fail-safe state. This paper delves into these countermeasures, evaluating their efficiency via mathematical modelling, simulations, and on-ground testing. Findings acknowledge that these strategies bolster the reliability of safety applications in jamming scenarios. Furthermore, the approaches propounded align with ongoing standardization endeavours by relevant authorities, ensuring communication mediums remain unhindered.

L-gulonolactone oxidase enzyme (GULO) catalyzes the last step of L-ascorbic acid (vitamin C) biosynthesis. This enzymatic activity is lost in primates. The full-length rat GULO has been previously produced in plants and demonstrated to be active. In this study, we compare activity of two variants of GULO produced in Escheriachia coli cells, full-length rat GULO (fGULO) and its C-terminal catalytic domain (cGULO). The expression and purification of the recombinant proteins were optimised and their biological activity was confirmed by two methods, the GULO activity assay in the protein extracts and the ‘in-gel’ staining for GULO activity. Both variants of recombinant GULO were biologically active in both assays. However, cGULO is more promising than fGULO for ascorbic acid production because it is more efficiently produced by bacteria.

Land degradation monitoring and assessment in the Sahel zone has relied substantially on temporal trends of remote sensing-based vegetation indices, which are proxies for the bioproductivity of the land. However, prior studies have shown that negative or positive trends in bioproductivity are not necessarily associated with degradation or improvement of land condition. In this short communication, while acknowledging the contributions of remote sensing-based indices and global-scale datasets to dismantling an outdated desertification narrative, we argue that local land users have much to contribute to our understanding of land degradation, and particularly to ensuring that scientific assessments of degradation capture variables relevant to them. We used the participatory photo elicitation method in three sites in the Senegalese Ferlo in order to elicit local pastoralists’ perspectives on land degradation and identify the indicators that they use to characterize pasture quality, while empowering them to lead the discussion. The discussion revealed indicators far beyond bioproductivity, including livestock performance as well as composition and quality of the herbaceous and woody vegetative cover, invasive species, soil quality and water availability. We found that the pastoralists’ knowledge and interest in the issue could potentially be harnessed more systematically, and at larger scales, in order to build a spatially explicit field-based knowledge base of land degradation complementary to remote sensing-based maps of trends in bioproductivity. Such a dataset could serve as a standalone product or as a reference dataset for development and validation of remote sensing-based indicators.

In wheeled vehicles, there exists a challenge concerning the alignment of the front wheels during turns. When both wheels are turned to the same extent, the inner wheel experiences lateral slippage on the road surface, resulting in reduced steering efficiency. Such problems can be solved by using the Ackermann principle. There are two approaches: through the steering mechanism or by employing autonomous wheel control. From a technical standpoint, it is achievable to synthesize a steering mechanism that fulfills the Ackermann condition, ensuring as accurately as possible for any given turning radius. This research paper focuses on synthesizing a steering mechanism, specifically a two-circuit linkage that links the left and right wheels. The structure and kinematics of this mechanism are being investigated. Following the principles of Ackermann, an objective function for the kinematic synthesis of the mechanism has been formulated. The synthesis process of the mechanism is conducted using the analytical method of interpolation in four parameters. A dedicated method has been developed, and kinematic analysis of the mechanism using the synthesized parameters has been performed. The simulation results have demonstrated high accuracy in achieving the desired implementation of the Ackermann condition.

Digital transformation systems generate a substantial volume of data, creating opportunities for potential innovation, particularly those driven by artificial intelligence. This study focuses on the intricate relationship between artificial intelligence and innovation as foundational elements in the digital transformation framework for sustained growth and operational excellence. This study provides a holistic perspective on the cultivation and pillars of AI-powered innovation, highlighting their pivotal role in revolutionizing industries, including healthcare, education, finance, manufacturing, transportation, and agriculture. The work emphasizes the key pillars essential for fostering AI-powered innovation, including monitoring performance measurement to use the power of the present, continuous learning and innovation, data analytics and insights, predictive analytics, and innovative product development. This study investigates how these pillars serve as the foundation for groundbreaking advancements, driving efficiency, enhancing decision-making processes, and fostering creativity within organizations. This study explores the significance of continuous learning, interdisciplinary collaboration, and industry partnerships in nurturing a thriving AI-powered innovation ecosystem. By understanding and harnessing these fundamental elements, businesses can navigate the complexities of the digital age, fostering innovation that not only optimizes processes but also enhances the overall human experience, ushering in a new era of technological excellence and societal progress.

The proliferation of mobile and IoT devices, coupled with the advances in the wireless communication capabilities of these devices, have urged the need for novel communication paradigms for such heterogeneous hybrid networks. Researchers have proposed opportunistic routing as a means to leverage the potentials offered by such heterogeneous networks. While several proposals for multiple opportunistic routing protocols exist, only a few have explored fuzzy logic to evaluate wireless links status in the network to construct stable and faster paths towards the destinations. We propose FQ-AGO, a novel Fuzzy Logic Q-learning Based Asymmetric Link Aware and Geographic Opportunistic Routing scheme that leverages the presence of long-range transmission links to assign forwarding candidates towards a given destination. The proposed routing scheme utilizes fuzzy logic to evaluate whether a wireless link is useful or not by capturing multiple network metrics, the available bandwidth, link quality, node transmission power, and distance progress. Based on the fuzzy logic evaluation, the proposed routing scheme employs a Q-learning algorithm to select the best candidate set toward the destination. We implement FQ-AGO on the NS-3 simulator and compare the performance of the proposed routing scheme with three other relevant protocols: AODV, DSDV, and GOR. For precise analysis, we consider various network metrics to compare the performance of the routing protocols. Our simulation result validates our analysis and demonstrates remarkable performance improvements in terms of total network throughput, packet delivery ration, and end-to-end delay.

Despite the successful reconciliation of special relativity and quantum mechanics (QM), a good century ago, general relativity (GR) in its current classical formulation still does not compile with QM. While GR gives precise sensical predictions at large scales, QM is obviously dominated at small scales! We think that the everlasting battle for exploring and understanding the Universe and for privileging a consistent perception of reality is therefore awaiting a consolidator rather than a conqueror. This should be capable of either unifying the two different benchmarks or at least bringing one closer to the other! The latter describes the consolidating approach, which is based on extending QM to relativistic energies and gravitational fields and generalizing Riemann to discretized Finsler geometry. Some properties of the additional geometric structures and curvatures which are disclosed by the proposed quantization and apparently overlooked in Einstein's GR, are analytically and numerically characterized. The analytical analyses introduce dynamics with possible nonlinear connections. We conclude that i) additional geometric structures and curvatures are intrinsic essential and ii) the spacetime at the quantum scale is no longer smooth or continuous. A maximal proper force is predicted, which maximally gravitationally accelerates a test particle and importantly manifests the quantum geometric nature of the generalized spacetime curvature.

In this paper, we study singularities of the spherical indicatrix and evolute of spacelike ruled surface with spacelike ruling. Finally, we give an example to illustrate our results.

In this study, we mainly focus on the behavior of an electron gas produced by argon plasma that is bounded by a moving rigid flat plate. The effects of an external magnetic field on the electrons collected with each other, with positive ions, and with neutral atoms in the plasma fluid are investigated. We used the BGK model of the Boltzmann kinetic equation, which is fundamental in the study of the gas dynamics from the continuum flow to the free-molecular regimes with Maxwellian velocity distribution functions of the various species. An exact analytical solution of the model equations for the unsteady flow is given using the moment and the traveling wave methods. The behavior of the mean velocity of electrons is illustrated, which compatible with the variation of the shear stress, viscosity coefficient, and the initial and boundary conditions. Besides, the thermodynamic prediction is investigated by applying the principles of irreversible thermodynamics and Gibbs formula. It is found that the thermodynamic variables verify the Boltzmann’s H–theorem, the principle of Le Chatelier, and the Thermodynamics Second Law for the non-equilibrium processes of the system. Qualitative agreements with previous related papers are introducing. 3-Dimensional graphics for the calculating variables are offering, and their behavior is deeply discussed.

This study investigated the evolution of density, gas permeability and thermal conductivity of sugar maple wood during the thermo-hygro-mechanical densification process. The results suggested that the oven-dry average density of densified samples was significantly higher than that of the control samples. However, the oven-dry density did not show a linear increase with the decrease of wood samples thickness. The radial intrinsic gas permeability of the control samples was 5 to 40 times higher than that of densified samples, which indicated that the void volume of wood was reduced notably after the densification process. The thermal conductivity increased by 0.5 - 1.5% per percent increase of moisture content for densified samples. The thermal conductivity of densified wood was lower than that of the control samples. The densification time had significant effects on the oven-dry density and gas permeability. Both the densification time and the moisture content had significant effects on thermal conductivity, but their interaction effect was not significant.

A major health threat for children in the 21st century is physical inactivity in conjunction with the elevated prevalence of obesity. In Malaysia, low physical activity among children is a major concern. The objective of the study was to analyze the day to day variation of step count in a sample of obese children using the activPAL^TM monitor. This was a cross sectional study conducted in Kuala Terengganu, Terengganu. The sample compromised 41 boys and 24 girls between the ages of 9-11 years. Number of steps was objectively measured using an activPAL^TM accelerometer over a period of 4-7 days and had their height and weight measured. Mean step count from this sample of obese children was 8861 ± 3157steps. Steps per day were significantly higher for boys compared to girls (p=0.034). Obese children took significantly more steps at weekdays than on weekends (p=0.001). Steps/hour were significantly higher in weekday compared to weekend between 0600 to 0700 (p<0.001), 0700 to 0800 (p<0.001), 0800 to 0900 am (p<0.001), 0900 to 1000 (p=0.032), 1000 to 1100 (p=0.046), 1100 to 1200 (p<0.001), 1300 to 1400 (p=0.002), 1400 to 1500 (p<0.001), 1800 to 1900 (p=0.026) and 2000 to 2100 (p=0.019). Detailed daily patterns of physical activity are required to fully understand the differences across days that help future interventions to target those falling short particularly during weekend.

Single-molecule magnets (SMMs) have garnered significant interest in the field of molecular magnetism due to their unique magnetic properties at the nanoscale. These molecular systems exhibit magnetisation behaviour reminiscent of conventional bulk magnets but with distinct advantages such as size-dependent properties and potential applications in quantum computing and high-density data storage. However, challenges remain in harnessing their properties for practical applications, including their susceptibility to degradation and limited control over their assembly and organisation.

Researches are moving to iron and ammonia elimination from ground water. Here, we are using poly acrylic–poly acrylamide hydrogel which grafted with 3-chloroaniline. This copolymer was synthesized by addition polymerization. Effect of agitation time, dosage and adsorbents temperature on the removal process sensitivity has been investigated. The copolymer was described experientially and theoretically. Isothermal, kinetic adsorption models and were discussed. This hydrogel could be regenerated efficiently (98.3%removal of iron and 100% removal of ammonia). Density functional theory DFT method using B3LYP/6-311G(d,p),LANL2DZ level of the theory were managed to investigate stationary states of grafted co-polymer and the complexation energy of the hydrogel with the studied cations. NBO analysis is using DFT to investigate the negative centers on the hydrogel. The complexation energy showed selectively of hydrogel to studied cations.

Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle’s range of functions and considerably reducing the distance the vehicle can travel on a single charge. Next-generation onboard AI systems need an even higher power since they collect and process even larger amounts of data in real time. This problem cannot be solved using the traditional computing devices since they become more and more power-consuming. In this review article, we discuss the perspectives of development of onboard neuromorphic computers that mimic the operation of a biological brain using nonlinear-dynamical properties of natural physical environments surrounding autonomous vehicles. Previous research also demonstrated that quantum neuromorphic processors (QNPs) can conduct computations with the efficiency of a standard computer while consuming less than 1% of the onboard battery power. Since QNPs is a semi-classical technology, their technical simplicity and low, compared with quantum computers, cost make them ideally suitable for application in autonomous AI system. Providing a perspective view on the future progress in unconventional physical reservoir computing and surveying the outcomes of more than 200 interdisciplinary research works, this article will be of interest to a broad readership, including both students and experts in the fields of physics, engineering, quantum technologies and computing.

Due to its built-up chemoresistance after prolonged usage, the demand for replacing platinum in metal-based drugs (MBD) is rising. The first MBD approved by the FDA for cancer therapy was cisplatin in 1978. Even after nearly four and a half decades of trials, there has been no significant improvement in osteosarcoma (OS) therapy. In fact, many MBD have been developed, but the chemoresistance problem raised by platinum remains unresolved. This motivates us to elucidate the possibilities of the copper and zinc (CuZn) combination to replace platinum in MBD. Thus, the anti-chemoresistance properties of CuZn and their physiological functions for OS therapy are highlighted. Herein, we summarise their chelators, main organic solvents, and ligand functions in their structures that are involved in anti-chemoresistance properties. Through this review, it is rational to discuss their ligands’ roles as biosensors in drug delivery systems. Hereafter, an in-depth understanding of their redox and photoactive function relationships is provided. The disadvantage is that the other functions of biosensors cannot be elaborated on here. As a result, this review is being developed, which is expected to intensify OS drugs with higher cure rates. Nonetheless, this advancement intends to solve the major chemoresistance obstacle towards clinical efficacy.

Breast cancer stands as a predominant health concern for women globally. As mammography is the primary screening tool for breast cancer detection, improving the detection of breast cancer at screening could save more lives. This mammography re-view paper provides a systematic review of computer-aided techniques during a specific time frame for the segmentation and classification of microcalcification, evaluating image processing, machine learning, and deep learning techniques. The systematic review is meticulously carried out, adhering closely to the preferred reporting items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. This article focuses on mammographic breast cancer detection approaches based on automated systems, discussed chronologically from 1970 through 2023. This article encompasses the breadth of artificial intelligence-based methods from the most primitive to the most sophisticated models. Image processing and machine learning-based methods are compre-hensively reviewed. The evaluation of a deep learning architecture based on self-extracted features for classification tasks demonstrated outclass performance. Large-scale datasets required for a broader and in-depth analysis of novel methods for breast cancer detection are also discussed in this article. This research work is aligned with the United Nations' sustainability de-velopment goals.

In this work, zinc oxide (ZnO) thin film has been fabricated on glass substrate using pulse laser ablation (PLA) technique. The effect of laser pulses of 1000, 1500, 2000 pulses at laser energy 700 mJ as well as, laser energy of 600, 700, and 800 mJ at fixed laser pulses of 1500 pulse, with methanol as a solvent on the structural properties of prepared films using XRD, SEM and EDX. XRD results revealed that the ZnO thin films have hexagonal structure with polycrystalline in nature with preferred orientation of (002). Crystalline size was increased with the increasing of the pulses and at energy of 700 mJ and pulse of 1500 pulse seemed nanostructure like tree leaf. In addition, narrow FWHM and no phase change have been observed in all cases. SEM images showed that for all cases the films were homogenous with some island and cluster then cracking started to obtain with the increasing of increase the pulse number. EDX analysis showed that the prepared films were free of defects and contaminations.

Economic valuations of ecosystem services often transfer previously estimated global unit values to the geographical setting of interest. While this approach produces quick results, its reliability depends on how representative the large-scale average unit values are for the given local context. Here, we estimate the values of three ecosystem services (ES) – water filtration, nutrient cycling and carbon sequestration – in the Grand River watershed (GRW) of southern Ontario, Canada. The watershed covers nearly 7000 km2, has a humid continental climate and a population of close to one million people. Land cover is dominated by agriculture. We compare ES valuations using locally derived (i.e., GRW-specific) unit values to valuations based on unit values from a regional database and those compiled in the global Ecosystem Services Valuation Database (ESVD). The regional database includes mean unit values from three case studies within southern Ontario and one boreal watershed in British Columbia. As expected, the regional database yields average monetary values for the three ES that are close to those obtained with the local unit values but with larger associated uncertainties. Using the ESVD, however, results in significantly higher monetary values for the ES. For water filtration, the ESVD value is more than five times higher than the regional and local estimates. We further illustrate the effect of the extent of aggregation of forested and agricultural land categories on the ES values. For example, by subdividing the forest category into three sub-categories (deciduous, coniferous, and mixed forest), the estimated value of the carbon sequestration ES of forested areas within the GRW increases by 15%. Overall, our results emphasize the importance of critically assessing the origin of unit values and the land cover resolution in ES valuation, especially when the latter is used as a policy-guiding tool.

Listwaenite rocks are widely spread in Fenja area of the Semail ophiolite of Oman and in Islam Abad area of the Neyriz ophiolite of Iran. There are three types of listwaenites found in these regions: silica-, carbonate-, and carbonate-silica (which includes dolomite, calcite, and magnesite. The alteration of host harzburgites started with hydrothermal alteration to serpentinite, followed by carbonation and silicification of serpentinite. Calcite- and magnesite-dolomite- listwaenites are more abundant in the Fenja area of Oman, while dolomite-listwaenites are more abundant in Islam Abad area in Iran. The mineralogy of listwaenites varies in both Iran and Oman; common minerals include quartz, calcite, goethite, magnesite, dolomite, serpentine, hematite, magnetite, Cr-mica, and Cr-spinel The major element chemistry of the different types of listwaenites in both Fenja and Islam Abad area generally comparable, and is largely similar to that of hydrothermally carbonated harzburgites, serpentinite, and listwaenites worldwide, despite spanning extraordinary and highly variable contents in major oxides, such as CaO, SiO2, MgO and LOI. Relict texture and common occurrence of Cr-spinel as well as the high concentrations of Cr, Ni and Co suggest that the protolith of the listwaenites in both regions was serpentinized harzburgites and serpentines. In comparison to the primary mantle and chondrite in spider diagrams, the Neyriz listwaenites have higher trace and REE element abundances than comparable listwaenites in the Fenja region. Harzburgite-normalized patterns of trace elements and REE in serpentinite and listwaenites overlap the average composition of harzburgite. PM-normalized trace element and REE patterns for serpentinized harzburgite and serpentinite show enrichment in Cs, U, Pb and Sr, with no Eu anomaly, comparable to mantle wedge serpentinites. The variable and high abundances of Ca, Mg, Ba, Zr, Sr, Pb, Zn, Mo and W in the carbonate- and silica-carbonate listwaenites, with unique Si enrichment and Mg, Na2O, Zr, Y, Ba, Sr, Rb, Cu, Pb, Sc, Cs, Nb, Mo and W. depletion in silica listwaenites are indicative of large fluctuations in major and trace element mobility. Cr, Ni and Co were immobile during alteration Enrichment in Ca and Si could occur by internal or late outside supply. Ca, Mg and Si are conceivably the foremost mobile major components amid harzburgite and serpentinite carbonation with mobilization confirmed by formation of quartz and Mg-carbonate in silica-carbonate listwaenites and quartz in silica listwaenites. The listwaenites in Islam Abad and Fenja area were formed due to hydrothermal alteration of serpentinite along thrust faults and shear zones which acted as pathway for Ca and/or Si rich fluids. The intensity of deformation in Islamabad listwaenites has been higher than Fenja listwaenites as indicated by higher abundance of trace elements.

Sodium glucose cotransporter 2 inhibitors (SGLT2i) are currently available for the management of type 2 diabetes mellitus. SGLT2i act by inhibiting renal SGLT2, thereby increasing glucosuria and lowering serum glucose. Recent trials are emerging supporting a role for SGLT2i irrespective of the diabetic status pointing towards that SGLT2i have other mechanisms of actions beyond blood sugar control. In this review, we will shed light on the role of this group of medications that act as SGLT2i in non-diabetics focusing on pre-clinical and clinical data highlighting the mechanism of renoprotection and effects of SGLT2i in the non-diabetic kidneys.

Generalized Bayesian (GB) is a Bayesian approach based on the learning rate parameter (LRP) () as a fraction of the power of the likelihood function. In this paper, we consider the GB method to perform inference studies for a class of exponential distributions. Generalized Bayesian estimators (GBE) and generalized empirical Bayesian estimators (GEBE) for the parameters of the considered distributions were obtained based on the censored type II samples. In addition, generalized Bayesian prediction (GBP) and generalized empirical Bayesian prediction (GEBP) were considered using a one-sample prediction scheme. Monte Carlo simulations were performed to compare the performance of the GBE and GEBE estimation results and the GBP and GEBP prediction results for different values of the LRP.

The study titled "Molecular Choreography of DNA: Insights and Innovations" explores the intricate dance of DNA, shedding light on its structure, function, and regulation. This comprehensive review delves into the historical significance of DNA research, from Watson and Crick's double helix discovery to recent innovations in genomics and molecular biology. The review highlights DNA's roles in replication, repair, gene regulation, and chromatin dynamics, emphasizing the precision and complexity of its molecular choreography. Innovations like CRISPR-Cas9 gene editing and advanced sequencing technologies have revolutionized our understanding of DNA, opening new avenues for scientific exploration. This study aims to provide readers with a deeper appreciation of DNA's central role in life's choreographed processes.

There has been no significant efficacy in treatment for osteosarcoma (OS) metastasis after nearly four decades of trials. This motivates us to elucidate OS therapies according to their four bidirectional mutation stages. To refresh the OS therapy status quo, the historical developments and clinical advancements are briefly described. However, the main issue of metastasis remains unresolved, accounting for 90% of pulmonary metastasis deaths. Thus, this metastasis problem is related to immune evasion and chemoresistance that are being induced after long-term treatment by the use of immunotherapy for tumorigenesis. Therefore, it is rationale to discuss the relationship cycles of mutation stages including tumorigenesis, metastasis, immune evasion, and chemoresistance. Even though many combinational and targeted therapies have been developed to intensify these mutation treatments, successful clinical translations with higher cure rates are still rare. Through this review, an in-depth understanding of the bidirectional relationship between the four OS mutation stages and their respective therapies is provided. Herein, we summarise the medicines used to treat tumorigenesis, including COLGALT2 inhibitors, Tra2B, and AGAP1, miR-148a and miR-21-5p EVs, and the lncRNA LIFR-AS1. Following the medicines used to treat metastasis are AXL, miR-135a-5p, mRNA BCL6, TGFβ1, Tim-3, SOCS5, CASC15, KLF3-AS1, PDCD4, ATG5, and Rab22a-NeoF1. Then the medicines used to treat immune evasion are N-cadherin, anti-IL-9, USP12 inhibitor, IgG-4+ B-cells, LAP inhibitor, anti-Wnt2 mAb, anti-αvβ8 integrin, HK2-mediated IκBα, IDO inhibitor with NO, and TGF-βRII with anti-IgG1. Finally, the medicines used to treat chemoresistance are DHFR, FPGS, HSP-90AA1, XCT-790, ATKI, and IGF1. As a result, this contribution is expected to serve as a reference and guide for scientists and clinicians.

Snakebite envenomation remains a major cause of morbidity and mortality in rural populations. This study aimed to identify factors associated with complications from snakebite envenomation reported in health facilities in the Cascades region of Burkina Faso. This cross-sectional study used routine data of patients admitted for snakebite envenomation in five health facilities between January 1, 2016, and December 31, 2021. Data were collected on sociodemographic, clinical, and therapeutic characteristics of patients showing signs of envenomation. Bivariate and multivariate analyses were conducted to determine factors associated with complications. Among the 846 patients with envenomation, 355 (42%) experienced complications. Local complications at the bite site included wounds (21.5%) and skin necrosis (12.5%). Systemic complications included hemorrhage (30.5%), shock (16.3%), and coma (4.3%), with a mortality rate of 3.2%. Factors significantly associated with complications were rural residence (AOR: 4.80; 95% CI: 2.21-11.4), incision at the bite site (AOR: 4.31; 95% CI: 2.51-7.52), tourniquet application (AOR: 5.52; 95% CI: 1.42-30.8), bleeding (AOR: 14.2; 95% CI: 8.80-23.4), abnormal vital signs (AOR: 14.3; 95% CI: 9.22-22.7), and non-administration of antivenom serum (AOR: 2.92; 95% CI: 1.8-4.8). These findings highlight the importance of antivenom availability and public awareness to reduce complications from snakebite envenomation.

Water pollutants removal by biomass adsorbent has been considered innovative and cost effective, thus commendable for application in industrial applications. However, certain important aspects have been overlooked by researchers, namely the efficiency in the operation time and pollutant removal. In this research, landfill leachate samples with organic components were treated using bentonite-enriched with sawdust augmented (SBR) process. By modifying the pH, the sawdust samples were categorized into three: the acidic, the alkaline, and the neutral. To bentonite samples, the pH-adjusted sawdust was added at 10%, 20%, and 30% amounts by mass respectively. At the optimum aeration rate of 7.5 L/min and contact period of 22 h, the treatment achieved 99.28% and 95.41% removal of COD and NH₃-N with bentonite respectively. For both pollutants, in the presence of sawdust, the removal reduced by about 17% with contact period reduced to 2 h which was a considerable achievement.

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

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.

The vast rise in the number of Internet-connected devices necessitates a more accessible spectrum. As a result, Cognitive Radio was already proposed as a solution to the problem of restricted spectrum resources by utilizing available spectrum which is assigned to primary users. This method allows the secondary user to utilize the spectrum whenever the primary user is not using it, and it does so without intruding with the primary user. Whenever the secondary user detects the spectrum, it faced some issues, such as complexity in sensing leading to a lack of noise value, and the primary user is hidden to all secondary users. In order to tackle these challenges, an adaptive threshold matched filter detector and a cooperative matched filter detector are utilized in this paper to detect the spectrum. The probability of detection (Pd), probability of miss detection (Pm), and probability of false alarm (Pf) are the metrics used to assess sensing accuracy. To simulate suggested detectors, the MATLAB R2020a software was utilized. In comparison to earlier studies, the simulation conclusions reveal that the detection process starts with lower SNR values.

The potato tuber moth PTM, Phthorimaea operculella, is one of the most economically important potato pests worldwide. In the present study, the potential of Steinernema feltiae and Steinernema carpocapsae for controlling PTM in potato tubers was evaluated compared to alpha-cypermethrin. Steinernema carpocapsae in both concentrations (12.6×10⁶IJs and 6.2×10⁶IJs) showed a lower number of emerged insects than alpha-cypermethrin (10 mg ai l^-1). Alpha-cypermethrin (20 mg ai l^-1) showed the highest efficacy against PTM (81.17%), S.carpocapsae (12.6×10⁶IJs), and alpha-cypermethrin (10 mg ai l^-1) showed similar efficacy (72.53%) while S. feltiae (6.2×10⁶IJs) showed the lowest efficacy (39.04%). The results showed that S.carpocapsae in both concentrations and S. feltiae (12.6×10⁶IJs) were efficient the same as alpha-cypermethrin (10 mg ai l^-1) having no environmental and health adverse impacts issued in the chemical insecticides usage. Both concentrations of alpha-cypermethrin and S. carpocapsae showed the least tuber damage with no significant differences, while it was as high as the control (59.26%) in both concentrations of S. feltiae. This promising finding introduces EPNs as a part of the potato tuber protection program in storage. Accordingly, EPNs can be considered as an appropriate alternative to synthetic chemicals for PTM control without any residue and health problems.

The research aims to improve some of the physical and hydro-physical properties of some Vertisols in the southern region (part of the eastern Houran Plateau) in Sweda Governorate at the south of Syria. Using different quantities of volcanic ash, soil samples were collected from the Al-Thahallah village from a depth of (0-30) cm, The experiment was designed according to the complete random design with one factor that represents the ash quantity (1.25, 2.5, 5) %, with three replicates for each treatment in addition to the control treatment a0. The experiment was carried out within the plastic pots during agricultural season 2018/2019, in which the wheat of the Sham variety 3 were cultivated as a cover plant. The results showed that the addition of volcanic ash at the quantity of 5% led to a significant increase in the infiltration rate by (328.60) %,%, where the filtration rate increased from 0.42 cm/hr -1 to 1.80 cm.h-1, as well as for each of the air porosity by (89) % and the volume of infiltrate water by (40) %, compared with the control. The above-mentioned addition also resulted in a decrease in both dry bulk density, total soil porosity and volumetric swelling coefficient by (18.60, 5.80, 314) % Respectively, compared to the control. The addition also contributed to the reduce in the weighted moisture content when saturation and the field capacity, at the level of significance of 5%. The research recommends adding volcanic ash to the soil at a quantity of 5%, and adding enhancements with volcanic ash at various levels such as organic waste.

In the upper charged layers of the atmosphere, the plasma is very rarefied. The collisions between its molecules are almost non-existent, and the driving forces behind them are the Lorentz forces resulting from the electric and magnetic fields. For this reason, we are interested in studying the behavior of non-collision plasmas because of its essential applications, such as the movement of satellites in the charged atmosphere. In this paper, the flow problem of collisionless gaseous plasma is examined. For that propose, we solve the unsteady Vlasov-Maxwell system of non-linear partial differential equations analytically. Methods of moments and traveling wave parameters are used to acquire an exact solution. Specific macroscopic properties of collisionless gaseous plasma are calculated along with electrical and magnetic fields. Further, thermodynamic estimation, such as entropy and entropy production, is presented. Those calculations allow us to measure the consistency with the laws of non-equilibrium thermodynamics. Relations between internal energy modification participations are predicted using Gibbs' equation for collisionless plasma. The modification effect of internal energies due to electro-magnetic fields is found to be small compared with the internal energy change due to the effect of entropy. That is because these fields are self-induced by plasma particles due to the sudden movement of the rigid plane plate. The results are accomplished according to the typical argon gaseous plasma model. Three-dimensional diagrams showing the measured variables are drawn to investigate and discuss their behavior. The problem has many commercial applications for the movement of objects in the charged atmosphere.

Since December 2019, a rapid increase in the number of SARS-CoV-2 (COVID-19) cases was reported worldwide, despite strict infection control and lock down measures. Current paper investigated the actual facts behind this rapid increase in the number of cases. Study of genomic sequence reveals that domestic and wild animals were likely ancestors and zoonotic source for SARS-CoVs, MERS-CoVs, and SARS-CoV-2. Strong evidence suggest that these viruses already existed and replicated in animals and humans during past several decades, exhibiting diverse mutations, evolutions and self-limiting diseases, except during outbreaks. Serious zoonotic reservoir investigations are required to investigate animal transmission of SARS-CoVs and SARS-CoV-2 to limit current pandemic. This might be the reason of increasing number of cases via animals. SARS-CoV-2 has been retrospectively isolated in different studies in August 2019, several months before Wuhan announced. Hence, there is a possibility that viruses existed, went undetected, infecting subclinically, in past several years, and SARS-CoV-2 antigens and neutralizing antibodies may have been present in humans since long time. This might be another reason of increasing number of cases by screening as mass screening and antigen or antibody testing was not carried out in the past years. Randomized controlled trials are required to investigate human to human transmission by touch, as the current evidence is limited with conflicting results. As all SARS-CoVs are basically respiratory viruses, droplet precautions and infection control measures are essential, especially for hospital staff. Increased number of SARS-CoV-2 asymptomatic, or subclinical cases are detected worldwide. This silent phase of transmission can be beneficial for humans. Lack of symptoms eventually lessen virus transmission and reduce the pathogen's long-term survival and provide humoral herd immunity up to several years. Hence, seropositivity with diverse antibodies develops against mutating SARS-CoVs which will confer strong immunity during epidemics. Strategies such as identification, contact tracing and quarantine are costly and practically difficult. Hence, asymptomatic persons can continue their work with droplet precautions and standard infection control procedures, while symptomatic or sick persons can isolate themselves in their homes without the need for strict quarantine until clinical recovery, with reduced hospital visits and minimizing chances of hospital acquired infections. RT-PCR has low sensitivity and specificity, carries a high risk of handling live virus antigens, and requires difficult protocols. As viral load also sharply declines after few days of onset of infection, this technique might overlook infection. Furthermore, SARS-CoV-2 infection may be present in blood when oropharyngeal swabs are negative by RT-PCR. Additionally, RT-PCR usually gives false negative and false positive results and must be interpreted cautiously. This might be again a reason of increasing number of cases by false positive RT-PCR reporting. Moreover, antibodies against SARS-CoVs develop robustly in serum even by reduced amount of antigens. In contrast to RT-PCR, ELISA for diagnosing antibodies against SARS-CoV-2 demonstrates 100% specificity and 100% sensitivity, even in clinically asymptomatic individuals. These antibodies can be used for serologic surveys, monitoring and screening. However, screening tests for SARS-COV-2 should be avoided in unhygienic public places by nasopharyngeal swabs, which carry a high risk of further transmission, co-infection or superinfection. Such highly infectious virus must be isolated and tested in highly sterilized laboratory. Further strict international laws and policies are required to stop the possible spread of experimental viruses, biological warfare and bioterrorism.

This article will briefly review the progress of h-BN based solid-state metal semiconductor metal (MSM) neutron detectors. In the last decade, several groups have been working on hexagonal boron nitride (h-BN) based solid-state neutron detectors. Recently, the detection efficiency of 59% has been reported. Efficient, low-cost neutron detectors made from readily available materials are essential for various applications. Neutron detectors are widely used to detect fissile materials and nuclear power plants for security applications. The most common and widely used neutron detectors are 3He based, which are sometimes bulky, difficult to transport, have high absorption length, need relatively high bias voltage (>1000 V), and have low Q-value (0.764 MeV). Also, 3He is not readily available material. Thus, there is a strong need to find an alternative detection material. 10B isotope has a high neutron absorption cross-section, and it has been tested as a coating on the semiconducting materials. Due to the two-step process, neutron capture through 10B, and then electron-hole pair generation in a typical semiconducting material, the efficiency of these devices is not up to the mark. The progress in h-BN based detectors requires a review to envision the further improvement in this technology.

The formation of a rigid tough interface based on a nacre-like structure in carbon fiber (CF) composites is a promising way to eliminate low delamination resistance. An effective method of coating CFs is electrophoretic deposition (EPD), which, in the case of dissimilar components like graphene oxide (GO) and polymeric glue, usually requires their chemical bonding/ strong interactions. In this work, we focus on chitin nanocrystals (ChNCs), leading to an excellent mechanical performance of artificial nacre, where favorable interactions and bonding with GO were controlled by degrees of deacetylation (5, 15 and 30 %). We have prepared coatings based on GO/ChNCs adducts with 95/5, 90/10,50/50 and 25/75 ratios using optimized EPD conditions (pH, concentration, voltage and time). The prepared materials were characterized using FTIR, TEM, XPS, SEM, DLS, and XRD. SEM evaluation indicates the formation of a homogeneous interlayer, which possesses a fair ability of chemical bonding with the epoxy matrix. Short beam testing of epoxy matrix composites indicates that coating does not decrease stiffness and its relatively low dependence on composition. Therefore, all coatings are promising for a detailed study of delamination resistance using laminate samples. Moreover, facile EPD from water solution/ suspension has a fair potential for industrial applications.

this paper focuses on a scientific study of the restoration, rehabilitation and reuse of the great throne hall, the most important hall in al-jawhara palace. it also aims to study the most important factors and forces of damage that affected the great throne hall, natural, biological, and human, and the resulting damage. field tests were performed, laboratory tests to determine fracture stress, liquidity and spandex limits tests, chemical analysis on soil samples and geoelectrical testing of the soil, and the results did not show caves or voids in the ground until a depth of 10.00 m, construc-tion materials were studied and tested using x-ray, (xrd), mechanical tests (tensile, shear, com-pression), and a study of the effect of seismic loads on the walls; the results showed horizontal and vertical cracks; based on the study and analysis of these cracks, it was possible to present modern techniques in restoration and reinforcement methods, and in conclusion, the researcher's recommendations.

Generalized Bayes is a Bayesian approach based on the learning rate parameter η. In this study, we examine the effect of parameter η on the estimation results considering joint type-I and type-II hybrid censored samples from k exponential populations. In addition to the learning rate parameter, we consider two loss functions, the Linex and general entropy loss functions in the Bayesian approach. Monte Carlo simulations are performed to compare the performances of the estimation results under losses and different values of η. An illustrative example is performed to study the effect of the learning rate parameter and the different losses with different parameters.

Nanofibres have gained increasing attention due to their advantages of having a high porous structure, narrow pore size and distribution, and a high specific surface area. One of the most efficient techniques for producing nanofibres is via electrospinning. Nanofibres are currently being used in various fields, including water filtration. Although nanofibres possess the ability to filter various components, the fibres generally have a low mechanical strength that can mitigate the performance over time. Therefore, in overcoming this issue, several studies have focused on improving the strength of the nanofibre membranes for a water filtration application. This review discusses the advantages and challenges of nanofibres for water filtration membranes and summarises the methods to increase the strength of the membranes, including solvent vapour, thermal treatment, and chemical crosslinking.

Tea and coffee are the most commonly used beverages throughout the world. Both decoctions are rich in small organic molecules such as phenolics/polyphenolics, purine alkaloids, many methylxanthines, substituted benzoic and cinnamic acids. Many of these molecules are physiologically chemopreventive and chemoprotective agents against many severe conditions such as cancer, Alzheimer, Parkinsonism, inflammation, sleep apnea, cardiovascular disorders, bradycardia, fatigue, muscular relaxation, and oxidative stress. Caffeine, a purine alkaloid, is a common metabolite of both tea and coffee aqueous decoctions and its concentration in tea/coffee depends on the fermentation process, preparation of the water extract and quality of tea leaves/coffee beans. A 250 ml of a coffee cup contains 100-150 mg caffeine while the same volume of strong tea contains 25-40 mg caffeine. The present paper presents the potential of caffeine as a potent chemopreventive agent that can be used for numerous physiological disorders.

Beta thalassemia is an inherited blood disorder that results in inefficient erythropoiesis due to genetic mutation that leads to reduction or absence of the hemoglobin beta-globulin protein. Approximately 8.5% of UAE residents suffer from β-thalassemia, a significant health and financial problem. The treatment options available for β-Thalassemia major are limited and associated with a wide range of complications. β-thalassemia gene therapy is emerging as a potential novel treatment option that eliminates the complications caused by the current long-term treatment modalities and the associated economic burden. This paper reviews the scientific literature related to emerging gene-therapy for β-Thalassemia by analyzing all the articles published from January 2010 to December 2023 in the English language on Databases like PubMed, Scopus, ProQuest, and CINAHL. The use of gene therapy has demonstrated promising outcomes for a permanent cure of β-Thalassemia. ZYNTEGLO (Betibeglogene autotemcel) is the only cell-based gene therapy which was approved by the FDA on 19th August, 2018. To conclude, Gene therapy is an innovative solution. It demonstrates a promising future, but does come with its own set-backs and is something that must be tackled in-order to revolutionize it in the medical world. FDA approved ZYNTEGLO is a potentially one-time curative treatment for β-Thalassemia. Although cutting-edge, its use is limited because of the high cost; a price of $2.8million per patient.

Keywords: Innovation ecosystems, Economic sustainability, Hydrocarbon-based economies, Economic diversification, Qualitative approach

The purpose of this paper is to develop an index system for measuring the compliance of high-rise residential buildings with fire requirements and also to develop an index system for measuring the fire response efficiency, which is linked to the index of compliance with fire requirements. The higher the compliance rate, the greater the chance of a successful response. The two systems de-pend on the automation of the firefighting system management processes using the techniques of the fourth industrial revolution and developed based on the consultation of subject matter experts in the field. The main elements of the indexes were identified, which were based mainly on several variables, including the fire administrative system, the firefighting system, the residents, the loca-tion of the high-rise residential buildings from the fire extinguishing station, and the height of the high-rise residential building. The two systems can contribute to improving emergency prepared-ness in high-rise residential buildings in the Emirate of Sharjah and are also considered as a measurement index for compliance with fire requirements in the Emirate of Sharjah.

The world’s human population is reaching record longevities. Consequently, our societies are experiencing the impacts of prolonged longevity, such as increased retirement age. A major hypothesised influence on ageing patterns is resource limitation, formalised under calorie restriction theory. This theory predicts extended organismal longevity due to reduced calorie intake without malnutrition. However, several challenges face current calorie restriction (CR) research and, although several attempts have been made to overcome these challenges, there is still a lack of holistic understanding of how CR shapes organismal vitality. Here, we conduct a literature review of 222 CR peer-reviewed publications to summarise the state-of-the-art in the field. We use this summary to highlight challenges of CR research in our understanding of its impacts on longevity. Our review demonstrates that experimental research in this field is biased towards short-lived species (98.2% of studies examine species with <5 years of mean life expectancy) and lacks realism in key areas, such as stochastic environments or interactions with other environmental drivers such as temperature. We argue that only by considering a range of short- and long-lived species and by taking more realistic approaches can the impacts of CR on longevity be examined and validated in natural settings. We conclude by proposing experimental designs and study species that will allow the discipline to gain a much-needed understanding of how restricting caloric intake affects long-lived species in realistic settings. Through incorporating more experimental realism, we anticipate crucial insights that will ultimately shape the myriad of socio-bio-economic impacts of senescence in humans and other species across the Tree of Life.

With the rapid surge in technological advancements, an equal amount of investment in technology-embedded teaching has become vital to pace up with the ongoing educational needs. Distance education has evolved from the era of postal services to the use of ICT tools in current times. With the aid of globally updated content across the board, technology usage ensures all students receive equal attention without any discrimination. Importantly, web-based teaching allows all kind of students to learn at their own pace, without the fear of being judged, including professionals who can learn remotely without disturbing their job schedules. Having web-based content allows low-cost and robust implementation of the content upgradation. An improved, yet effective, version of the education using such tools is Hybrid Learning (HL). This learning mode aims to provide luxurious reinforcement to its legitimate candidates while maintaining the quality standards of various elements. Incorporated with both traditional and distance learning methods, along with exploiting social media tools for increased comfort level and peer-to-peer collaboration, HL ultimately facilitates the end user and educational setup. The structure of such a hybrid model is realized by delivering the study material via a learning management system (LMS) designed in compliance with quality standards, which is one of the fundamental tackling techniques for controlling quality constraints. In this paper, we present the recently piloted project by COMSATS University Islamabad (previously known as COMSATS Institute of Information Technology) which is driven by technology-embedded teaching model. This model is an amalgam of the traditional class room model with the aid of state-of-the-art online learning technologies. The students are enrolled as full-time students, with all the courses in traditional classroom mode, except one course offered as hybrid course. This globally adapted model helps the students to benefit from both face-to-face learning as well as gaining hands-on experience on technology-enriched education model providing flexibility of timings, learning pace, and boundaries. Our HL model is equipped with two major synchronous and asynchronous blocks. The synchronous block delivers real-time live interaction scenarios using discussion boards, thereby providing a face-to-face environment. Interactions via social network has witnessed equally surging improvement in the output performance. The asynchronous block refers to the lecture videos, slides and handouts, prepared by imminent professors, available 24/7 for students. To ensure quality output, our HL model follows the course learning outcomes (CLOs), and program learning outcomes (PLOs) as per international standards. As a proof of concept, we have deployed a mechanism at the end of each semester to verify the effectiveness of our model. This mechanism fundamentally surveys the satisfaction levels of all the students enrolled in the HL courses. With the surveys already conducted, a significant level of satisfaction has been noted. Extensive results from these surveys are presented in the paper to further validate the efficiency and robustness of our proposed HL model.

Stroke is a significant global health concern, ranking among the top causes of death and disability. Timely post-stroke recovery hinges on structured upper limb rehabilitation within the first 24–48 hours. Although virtual reality (VR) rehabilitation is promising, its accessibility is complex and cost-limited, especially in less developed regions. In this study, we developed and assessed nonimmersive VR rehabilitation games using the Kinect Xbox One and UNITY game engine, targeting upper limb movement sequences vital for post-stroke recovery. The developed games involved simple to progressively challenging movements, engaging the deltoid, biceps, and triceps muscles, and aligning with post-stroke rehabilitation criteria. We used peak-to-peak electromyography signal detection with a 20% threshold and three distinct feature extractions to represent muscle contractions during gameplay. Our cosine similarity analysis revealed the efficacy of games in meeting movement sequence criteria, benefiting mostly the shoulder motor and deltoid muscles (93% improvement) with more moderate improvements in the biceps (73%) and triceps (47%). Our results suggest that these games could contribute to upper limb stroke rehabilitation, particularly that of the deltoid muscle. This study highlights the potential of VR-based rehabilitation games in post-stroke upper limb recovery, emphasizing muscle engagement, target distances, and rehabilitation criteria in game design. Although healthy participants were involved here, future research involving post-stroke patients and the exploration of more immersive, multiplanar movements hold the potential for a more comprehensive rehabilitation experience. Our study contributes to advancing the common knowledge related to VR-based stroke rehabilitation, focusing on upper limb movement sequences with implications for therapeutic engagement and recovery.

This paper evaluates the global sustainable competitiveness of three blocks of power (US, China and EU) based on OGT (Organic Growth Theory) structure. In addition, a sensitivity analysis of COVID-19 on three measures of global sustainable competitiveness, economy, environment and social is also presented. OGT is a well-thought-through and standard framework for evaluation of any type of organiza-tion in their pathway to experience truly sustainable growth. GDP (Gross Domestic Product) is used as an economic measure; total carbon emissions equivalent is used as an environmental measure and HMI (Human Development Index) as a social measure. It is concluded that the pandemic has paused the evolution of countries to be truly world centric countries. However, the recovery plans seem to be highly aligned with the OGT scores and it is expected that the scores to improve dramatically.