Search

Abstract Background Ensuring consistent adherence to antiretroviral therapy (ART) is crucial for effective HIV treatment and achieving viral suppression. Within prisons, the prevalence of HIV is notably high, and incarcerated individuals face an increased risk of transmitting the virus both during and after incarceration. However, facilitators and barriers to ART adherence among these individuals in low- and middle-income countries remain inadequately explored. This study applied the Social Ecological Model (SEM) to investigate how various individual, interpersonal, organizational, community and policy-level factors impact ART adherence among incarcerated populations in Iran during and post-incarceration. Methods This study employed a phenomenological qualitative approach using semi-structured interviews to gather insights. The research population consisted of people living with HIV (PLHIV) who had experienced incarceration and had been prescribed ART during their latest incarceration. Eleven PLHIV from two prisons located in Kerman and Tehran, Iran, formed the study group. Qualitative findings from the interviews were analyzed using a thematic approach. The findings were organized within the SEM framework to highlight key themes influencing ART adherence during and after incarceration. Results Participants had an average age of 45.1 years (± 5.6). Various factors influence ART adherence during and post-incarceration. Participants highlighted the individual (e.g., HIV knowledge, previous treatment history, mental and physical health), interpersonal (e.g., family, friends, other incarcerated people, and prison health staff), organizational (e.g., ART treatment interventions, methadone maintenance therapy, and other health protocols), community (e.g., stigma, social isolation, discrimination and lack of access to community health services), and policy (e.g., financial interventions, and providing shelters) level factors influence ART adherence during and post-incarceration. Conclusions This study provides insights into the multi-level approach to ART adherence among PLHIV during and post-incarceration. It recommends implementing public health activities at the proposed multi-levels to maximize the synergies of intervention for the greatest impact.

Complex spherical fuzzy sets (CSFSs) are a theory that addresses confusing and unreliable information in real-life decision-making contexts by integrating elements of two theories: spherical fuzzy sets (SFSs) and complex fuzzy sets (CFSs). CSFSs are classified into three categories, represented by polar coordinates: membership, nonmember, and abstention. These grades are located on a complex plane within a unit disc. It is necessary for the total squares representing the real components of the grades for abstinence, membership, and non-membership to not surpass a certain interval. Several aspects of CSFS and the corresponding operational laws were examined in this work. The key components of this article were based on CSFs, including complex spherical fuzzy Schweizer-Sklar prioritized aggregation (CSFSSPA), complex spherical fuzzy Schweizer-Sklar weighted prioritized aggregation (CSFSSWPA), complex spherical fuzzy Schweizer-Sklar prioritized geometry (CSFSSPG), and complex spherical fuzzy Schweizer-Sklar prioritized weighted geometry (CSFSSWPG). Additionally, the suggested operators' specific instances were examined. The main outcome of this work includes new aggregation techniques for CSFS information, based on t-conorm and t-norm from Schweizer-Sklar (SS). The basic characteristics of the operators were established by this study. We looked at a numerical example centered on efficient mobile e-tourism selection to show the effectiveness and viability of the recommended approaches. Additionally, we carried out a thorough comparative analysis to assess the outcomes of the suggested aggregation approaches in comparison to the current methods. Last, we offer an overview of the planned study and talk about potential directions for the future.

Background/Objectives: Diabetic ketoacidosis (DKA) is a critical complication of diabetes mellitus, posing significant health. While global studies have indicated a concerning lack of awareness regarding DKA among patients with diabetes, research specific to the northern area of Saudi Arabia remains limited. This study aims to explore the level of knowledge and awareness of DKA among patients with diabetes residing in the local region. Methods: A cross-sectional analysis was conducted utilizing a non-probability convenient sampling technique, with 339 participants recruited from March to August 2024. Data were gathered through a self-administered pre-validated questionnaire distributed via different social media platforms to assess demographic characteristics and awareness levels relating to DKA, including knowledge of its symptoms, causes, and treatment options. Results: Although there was moderate awareness of DKA, with 68.4% having heard of the condition, two-thirds of the participants exhibited significant gaps in overall knowledge. Among those aware, 76.3% recognized DKA as an emergency requiring immediate medical intervention. At the same time, 64.6% understood the causes of DKA, and only 25.6% identified insulin deficiency as a major contributing factor. Although 62.5% felt knowledgeable about treatment, 66.0% incorrectly identified oral sugar as a DKA treatment. Notably, 30.1% cited social media as their main information source. Age emerged as an essential factor impacting knowledge, with younger participants (ages 18–30) demonstrating higher awareness than older individuals. Additionally, single participants displayed a higher percentage of good knowledge than married participants (p = 0.000). Non-working individuals showed better overall knowledge about DKA (p = 0.002). The duration of diabetes did not show a significant association with knowledge levels about DKA across the various duration categories. Conclusions: The present findings underscore a substantial knowledge gap concerning DKA among the local community, highlighting a critical need for targeted public health educational interventions.

Abstract Background The connection between psychiatry health, mental health, and lifestyle is under-studied in the Arab world. This study examined whether addictions to smartphones and fast food are associated with severe depressive symptoms in a cohort of Arab Jordanians. Method This research is cross-sectional. The Patient Health Questionnaire-9 was used to measure the severity of depression (PHQ-9), food addiction was assessed using the 9-item Modified Yale Food Addiction Scale (mYFAS), and smartphone addiction was assessed using the Arabic-validated Smartphone Addiction Scale. Using multivariable binary logistic regression, the relationship between food addiction, and depressive symptoms. Results: Data were analyzed from 426 participants, 264 participants (62.0%) reported being addicted to smartphones, and 156 (36.6%) reported severe depressive symptoms. The multivariable binary logistic regression revealed that severe depression was significantly associated with lower income (OR = 2.14, 95% Cl 1.34–3.41, P = 0.001), addiction to smartphones (OR = 2.15, 95% = 1.39–3.32, P = 0.001), and increased addiction to fast food (OR = 1.06, 95% = 1.04–1.08, P =

Abstract Women’s career progression and empowerment in STEM (science, technology, engineering, and mathematics) sectors are critical to attaining SDG 5: Gender Equality because they promote equal access to education, job prospects, and leadership roles, building a more inclusive and equitable society. The purpose of this study is to look into the impact of perceived overqualification (POQ) on career anxiety and career decidedness (CD) among women in STEM disciplines while also considering the function of career identity (CI) and leadership support. With a total sample size of 1,045 participants, two distinct investigations were conducted, one in the educational field (N = 530) and one in an industry setting (N = 515 time-lag). To test the model, the analysis was carried out using the AMOS-24 software program. Our findings show a favorable association between women’s perceptions of overqualification in STEM and their CI. Furthermore, our research shows that a stronger CI among women in STEM corresponds to decreased career anxiety and increased CD. Additionally, we find that a CI is a mediator between POQ and both career anxiety and CD. Our findings also highlight the moderating effect of leadership support in this mediation process. We discuss the theoretical and practical ramifications of these findings.

Abstract The cut method is a computational approach utilized to predict the fundamental activities of physicochemical properties of chemical networks, also called topological indices. The connection number is a new idea, that gives interesting and good results of the topological indices (TIs) and entropy measures (EMs) for structural representation of chemical compounds and networks. The physical density of chemical networks is characterized by these indices. In this paper, we determined the computational results for indices based on connection numbers for a two-dimensional lattice sheet of hydrogen-bonded boric acid. Boric acid, an inorganic compound, is not very harmful when applied to the skin or consumed. Finally, graphical and numerical comparisons of topological numbers including the number of borate hydrogen-bonded double lattice forms are also included in this study.

An examination and study were carried out in order to investigate the beneficial advantages of Drimia maritima aqueous and hydroalcoholic extracts (DmAE/DmHE). The chemical profile was determined using rapid ultrahigh performance liquid chromatography–electrospray ionization tandem mass spectrometry analysis, revealing the presence of 31 bioactive components. Four different methodologies were employed to conduct a series of antioxidant testing. The DmAE and DmHE have exhibited a noteworthy antioxidant capacity, as evidenced by their significant half maximal inhibitory concentration values across several activities, comparable to the performance of DmAE. However, D. maritimia does not exhibit any reduction in power activity. Furthermore, a notable suppression of the critical enzyme (urease), which serves a role in various health conditions, including hyperpigmentation and pathological functional abnormalities, was discovered for the first time. A significant inhibition of the urease enzyme was observed for DmAE at a value of 122.04 ± 1.42. D. maritima had strong sun protection properties and demonstrated effective anti-inflammatory effects. The pharmacological activities of DmAE and DmHE were also conducted in vivo using analgesic and anti-inflammatory tests, and the oral toxicity was determined in accordance with the Organisation for Economic Cooperation and Development 425 Guideline. Intoxication symptoms were not observed in any of the treated animals following oral administration of DmAE and DmHE at 2,000 mg/kg. Conversely, the oral administration of DmAE and DmHE at varying concentrations inhibits the development of paw edema at different concentrations, which results in a substantial reduction in the acetic acid-induced writhing test. Chemical and spectroscopic investigation of D. maritima flowers resulted in the isolation of sucrose, and it was never isolated in this plant species and Scilliphäosidin-3-O-β-d-glucoside, using proton nuclear magnetic resonance and carbon 13 nuclear magnetic resonance spectroscopy. As indicated by these findings, D. maritima has the potential to be utilized in a wide range of applications, including as a nutritional supplement, as an alternative treatment for a variety of physiological conditions and pathologies, and as a preventive and healing agent.

The concept of being uniform strong interval-valued intuitionistic fuzzy (also termed as USIVIF) is an integration of two ideologies, which are called "uniformity" and "strong interval-valued intuitionistic fuzzy sets". Inspired by the study on uniform fuzzy topological indices, it is natural to introduce uniform IVIFTIs. Originally, topological indices were generalized for the fuzzy sets However, the utilization of the interval-valued intuitionistic fuzzy topological indices provides a finer approach, especially if there are multiple uncertainties based on intervals. Consequently, both theories imply that topological indices are not fixed and depend on certain situations or problems in the question. In this article, the generalized results for the uniform degree of the fuzzy sets associated with individual vertices/edges of strong interval-valued intuitionistic fuzzy graphs were presented and results for the total uniform degree of such graphs were also included. In addition, the nature of the implemented methods and models was discussed based on the cellular neural interval-valued intuitionistic fuzzy graphs of sets of membership and non-membership values.

As smart schools increasingly rely on technology, achieving energy efficiency becomes crucial for cost reduction and sustainability. This study investigates energy efficiency strategies in smart schools, focusing on the integration of renewable energy technologies. A quantitative approach using numerical simulations and literature reviews establishes benchmarks for energy-efficient smart schools. The Design Builder software is employed to evaluate system performance, with validation achieved through analysis in the System Advisor Model software. The modeled smart school building in Design Builder consumes 75,385.63 kWh annually, based on the weather conditions of specific location. Further studies indicate that integrating photovoltaics and hot water collectors can generate approximately 86,635 kWh annually. This not only offsets the energy consumption of building but also produces an excess of 11,249 kWh, which can be transferred back to the grid for additional revenue. Validation using SAM software demonstrated a minimal difference (3.2%) in annual energy outputs, confirming the accuracy of the model. The findings suggest that photovoltaics and hot water collectors can significantly contribute to achieving net-zero energy consumption in smart school buildings. Additionally, a focus on rooftop installations promotes sustainability by minimizing land use.

Edible insects have drawn more attention in recent years as a reliable source of nutrition with an opportunity to alleviate a number of issues with the current global food chain. They have the ability to provide small-scale growers and entrepreneurs with economic and livelihood possibilities. As the demand for edible insects rises globally, mopane worms may one day be an important source of nourishment outside of the African regions where they are currently consumed. Mopane worms are attractive as an edible insect due to a number of factors, such as their high nutritional value, minimal environmental impact, and simplicity of cultivation and harvesting, which may increase their sales potential and economic value. Mopane worms provide 58 % protein, 15 % fat, 8 % ash, 8 % carbohydrate, and significant amounts of minerals. The market value of mopane worm is projected to be $2.5–4.0 per kilogram. Mass rearing, gathering, processing, and storage practices that are effective and sustainable can guarantee the safety and quality of products while boosting consumer demand and producer prospects for profit. Mopane worms have an exciting potential as an edible insect, and additional investigation and advancement in these areas may help to realize their full capability as a food source.

Abstract A relatively recent approach in molecular graph theory for analyzing chemical networks and structures is called a modified polynomial. It emphasizes the characteristics of molecules through the use of a polynomial-based procedure and presents numerical descriptors in algebraic form. The Quantitative Structure-Property Relationship study makes use of Modified Polynomials (M-Polynomials) as a mathematical tool. M-Polynomials used to create connections between a material’s various properties and its structural characteristics. In this study, we calculated several modified polynomials and gave a polynomial description of the magnesium iodide structure. Particularly, we computed first, second and modified Zagreb indices based M-polynomials. Randić index, and inverse Randić indices based M-polynomials are also computed in this work.

Abstract Eigenvalues have great importance in the field of mathematics, and their relevance extends beyond this area to include several other disciplines such as economics, chemistry, and numerous fields. According to our study, eigenvalues are utilized in chemistry to express a chemical compound’s numerous physical properties as well as its energy form. It is important to get a comprehensive understanding of the interrelationship underlying mathematics and chemistry. The anti-bonding phase is correlated with positive eigenvalues, whereas the bonding level is connected with negative eigenvalues. Additionally, the non-bonded level corresponds to eigenvalues of zero. This study focuses on the analysis of various structures of anticancer drugs, specifically examining their characteristic polynomials, eigenvalues of the adjacency matrix, matching number and nullity. Consequently, the selected structures of the aforementioned anticancer drugs exhibit stability since they are composed of closed-shell molecules, characterized by a nullity value of zero.

Abstract Fuzzy set theory is a mathematical method for dealing with uncertainty and imprecision in decision-making. Some of the challenges and complexities involved in medical diagnosis can be addressed with the help of fuzzy set theory. Ovarian cancer is a disease that affects the female reproductive system's ovaries, which also make the hormones progesterone and estrogen. The ovarian cancer stages demonstrate how far the disease has spread from the ovaries to other organs. The TOPSIS technique (Technique for Order Preference by Similarity to Ideal Solution) aids in selecting the best option from a selection of choices by taking into account a number of variables. It provides a ranking or preference order after weighing the benefits and drawbacks of each solution. Intuitionistic fuzzy soft set (IFSS) is the framework to deal with the uncertain information with the help of the parameters. The goal of this article is to develop some basic aggregation operators (AOs) based on the IFSS and then use them to diagnose the stages of the ovarian cancer using the TOPSIS technique. Furthermore, the variation of the parameters used in the developed model AOs is also observed and graphically represented.

BackgroundAn estimated 6.7 million persons are living with dementia in the United States, a number expected to double by 2060. Persons experiencing moderate to severe dementia are 4 to 5 times more likely to fall than those without dementia, due to agitation and unsteady gait. Socially assistive robots fail to address the changing emotional states associated with agitation, and it is unclear how emotional states change, how they impact agitation and gait over time, and how social robots can best respond by showing empathy. ObjectiveThis study aims to design and validate a foundational model of emotional intelligence for empathetic patient-robot interaction that mitigates agitation among those at the highest risk: persons experiencing moderate to severe dementia. MethodsA design science approach will be adopted to (1) collect and store granular, personal, and chronological data using Personicle (an open-source software platform developed to automatically collect data from phones and other devices), incorporating real-time visual, audio, and physiological sensing technologies in a simulation laboratory and at board and care facilities; (2) develop statistical models to understand and forecast the emotional state, agitation level, and gait pattern of persons experiencing moderate to severe dementia in real time using machine learning and artificial intelligence and Personicle; (3) design and test an empathy-focused conversation model, focused on storytelling; and (4) test and evaluate this model for a care companion robot (CCR) in the community. ResultsThe study was funded in October 2023. For aim 1, architecture development for Personicle data collection began with a search for existing open-source data in January 2024. A community advisory board was formed and met in December 2023 to provide feedback on the use of CCRs and provide personal stories. Full institutional review board approval was received in March 2024 to place cameras and CCRs at the sites. In March 2024, atomic marker development was begun. For aim 2, after a review of open-source data on patients with dementia, the development of an emotional classifier was begun. Data labeling was started in April 2024 and completed in June 2024 with ongoing validation. Moreover, the team established a baseline multimodal model trained and validated on healthy-person data sets, using transformer architecture in a semisupervised manner, and later retrained on the labeled data set of patients experiencing moderate to severe dementia. In April 2024, empathy alignment of large language models was initiated using prompt engineering and reinforcement learning. ConclusionsThis innovative caregiving approach is designed to recognize the signs of agitation and, upon recognition, intervene with empathetic verbal communication. This proposal has the potential to have a significant impact on an emerging field of computational dementia science by reducing unnecessary agitation and falls of persons experiencing moderate to severe dementia, while reducing caregiver burden. International Registered Report Identifier (IRRID)PRR1-10.2196/55761

This article explores Robert Louis Stevenson’s The Strange Case of Dr. Jekyll and Mr. Hyde using Freud’s theories of psychoanalysis to examine the Gothic nature of the novella. Through a three-stage study, the article highlights the manifestation of the unpresentable in the character of Mr. Hyde, who is depicted as the id, a Freudian hypothetical aspect of the human psyche. The article analyzes the different techniques used to create this character and its relation to the representation it stands for. The article argues that the character of Mr. Hyde and its manifestation of the id reveal a deeper understanding of the human psyche, challenging traditional notions of the self and consciousness. The article concludes that The Strange Case of Dr. Jekyll and Mr. Hyde is a prime example of Gothic literature, presenting the unpresentable in a unique and thought-provoking way that calls for a deeper understanding of both the individual and collective identity of the people and the society

The molecular energy, which is the sum of all eigenvalues, is crucial in determining the total π-electron energy of conjugated hydrocarbon molecules. We used machine learning techniques to calculate the energy, inertia, nullity, signature, and Estrada index of molecular graphs for bismuth tri-iodide and benzene rings embedded in P-type surfaces within 2D networks. We applied MATLAB to extract the actual eigenvalues from the data and developed general equations for these molecular properties. We then used these equations to estimate the values and compared them to the actual values through graphical analysis. Our results demonstrate the potential of data-driven techniques in predicting molecular properties and enhancing our understanding of spectral theory.

The extensive utilization of nitrogen (N) fertilizers within maize cultivation systems has resulted in diminished nitrogen use efficiency (NUE) and contributed to nitrogen pollution on a global scale. To assess the ecological repercussions of excessive fertilization, it is imperative to elucidate both the nitrogen use efficiency and the fate of nitrogenous fertilizers upon application. The current research evaluated the potential of a newly developed slow-release nitrogen fertilizer on maize growth and its behavior in soil under controlled conditions. Six different levels of urea fertilizer (UF) and slow-release nitrogen fertilizer (SRNF) were administered within the field, representing 100%, 85%, and 70% of the recommended application rates. The slow-release nitrogen fertilizer (SRNF) exhibited superior performance regarding growth, yield and nutrient retention in comparison to urea fertilizer (UF). Moreover, minimal ammonia emissions were detected with the employment of the slow-release nitrogen fertilizer (SRNF), while other urea-based fertilizers proved inefficient in mitigating ammonia emissions, despite enhancing various growth and yield parameters. The efficiency in nutrient recovery followed a distinct pattern, with polymer-coated fertilizers demonstrating superiority. The plots treated with SRNF displayed significantly higher growth and yield characteristics compared to those treated with urea fertilizer. In terms of NH3 volatilization, the urea fertilizer (UF) treatment at 100% application rate showed higher emissions (1.99 mg g-1) after a 27-day incubation period, as opposed to the slow-release nitrogen fertilizer (SRNF) treatment (1.68 mg g-1). Leaching data indicated that urea fertilizer treatments led to greater losses of NO3-N (2.01 mg L-1) compared to SRNF treatments (0.88 mg L-1).

Background Myocardial bridging (MB) is accompanied by the dynamic extravascular compression of epicardial coronary arteries, leading to intracoronary hemodynamic disturbance with abnormal coronary flow profiles. We aimed to evaluate the prognostic implications of resistive reserve ratio (RRR), a composite measure of flow and pressure parameters that represents the vasodilatory capacity of the coronary arteries, in patients with angina with nonobstructive coronary artery disease (ANOCA) and MB, in comparison with coronary flow reserve (CFR). Methods and Results In this retrospective cohort study, we included patients with ANOCA who underwent coronary reactivity testing, where MB was identified by transient constriction in coronary artery segments between systole and diastole. Abnormal CFR and RRR were defined as

Papillary fibroelastomas (PFEs) are small, slowly growing benign cardiac tumors with clinically significant risk of embolization. Surgical excision is the definitive treatment of symptomatic PFE and is conventionally performed through a median sternotomy. In this study, we report a series of 12 patients, who underwent robotic-assisted PFE removal at the Mayo Clinic. PFE involved the mitral valve, left atrium, and tricuspid valve. No major complications occurred after the procedure, and most patients were discharged 4 days after the surgery. On follow-up, 1 patient demonstrated pericarditis.

Let $ G = (V, E) $ be a simple, connected graph with vertex set $ V(G) $ and $ E(G) $ edge set of $ G $. For two vertices $ a $ and $ b $ in a graph $ G $, the distance $ d(a, b) $ from $ a $ to $ b $ is the length of shortest path $ a-b $ path in $ G $. A $ k $-ordered partition of vertices of $ G $ is represented as $ {R}{p} = \{{R}{p_1}, {R}{p_2}, \dots, {R}{p_k}\} $ and the representation $ r(a|{R}{p}) $ of a vertex $ a $ with respect to $ {R}{p} $ is the vector $ (d(a|{R}{p_1}), d(a|{R}{p_2}), \dots, d(a|{R}{p_k})) $. The partition is called a resolving partition of $ G $ if $ r(a|{R}{p}) \ne r(b|{R}{p}) $ for all distinct $ a, b\in V(G) $. The partition dimension of a graph, denoted by $ pd(G) $, is the cardinality of a minimum resolving partition of $ G $. Computing precise and constant values for the partition dimension poses a interesting problem; therefore, it is possible to compute an upper bound for the partition dimension within a general family of graphs. In this paper, we studied partition dimension of the some families of convex polytopes, specifically $ \mathbb{T}_n $, $ \mathbb{U}_n $, $ \mathbb{V}_n $, and $ \mathbb{A}_n $, and proved that these graphs have constant partition dimension.

Fossil fuels resources are continually running out due to the rapid rise in industrialization and outgrowth. Moreover, the excessive utilization of fossil fuel has resulted in release of various toxic gases and global warming. Hence, it necessitates the demand to explore for an inexhaustible, renewable and eco-friendly energy sources. In this review, various waste biomasses which are abundantly available throughout the world have been reviewed as a feedstock for obtaining various value added products i.e. bio-oil, gases and biochar etc., using various pyrolysis techniques. The pyrolysis is considered to be the most effective conversion technique in which three stage degradation mechanism is observed leading to the production of valuable hydrocarbons from decomposition of hemicelluloses, cellulose and lignin. The bio-oil obtained if upgraded properly, is served as fuel for commercial use. The study also reviews the composition of lignocellulosic biomass, conversion techniques, and mechanism of conversion to various pyrolytic products, upgradation of bio-oil and effective utilization of biomass for energy generation. This review suggests utilization of lignocellulosic biomass waste as energy resource by converting it to value-added products by low-cost conversion methods which would ultimately lead to overcome the energy crises to some extent.

Abstract Background To stop the spread of the COVID-19 disease, it is crucial to create molecular tools to investigate and diagnose COVID-19. Current efforts focus on developing specific neutralizing monoclonal antibodies (NmAbs) elicited against the receptor-binding domain (RBD). Methods In the present study, recombinant RBD (rRBD) protein was produced in E. coli, followed by immunizing mice with purified rRBD. ELISA was applied to screen the hybridomas for positive reactivity with rRBD protein. The linear and conformational epitopes of the mAbs were subsequently identified using western blot. Finally, the reactivity, affinity, and neutralization activity of the purified mAbs were evaluated using ELISA. Results All mAbs exhibited similar reactivity trends towards both eukaryotic RBD and prokaryotic rRBD in ELISA. Among them, 2E7-D2 and 2B4-G8 mAbs demonstrated higher reactivity than other mAbs. Additionally, in western blot assays, these two mAbs could detect reducing and non-reducing rRBD, indicating recognition of linear epitopes. Notably, five mAbs effectively blocked rRBD- angiotensin-converting enzyme 2 (ACE2) interaction, while two high-affinity mAbs exhibited potent neutralizing activity against eukaryotic RBD. Conclusion In the current study, we generated and characterized new RBD-specific mAbs using the hybridoma technique that recognized linear and conformational epitopes in RBD with neutralization potency. Our mAbs are novel candidates for diagnosing and treating SARS-CoV-2.

HIV causes intense polyclonal activation of B cells, resulting in increased numbers of spontaneously antibody-secreting cells in the circulation and hypergammaglobulinemia. It is accompanied by significant perturbations in various B cell subsets, such as increased frequencies of immature/transitional B cells, activated memory B cells, atypical memory B cells, short-lived plasmablasts and regulatory B cells, as well as by decreased frequencies of resting memory and resting naïve B cells. Furthermore, both memory and antigen-inexperienced naïve B cells show exhausted and immune-senescent phenotypes. HIV also drives the expansion and functional impairment of CD4+ T follicular helper cells, which provide help to B cells, crucial for the generation of germinal center reactions and production of long-lived plasma and memory B cells. By suppressing viral replication, anti-retroviral therapy reverses the virus-induced perturbations and functional defects, albeit inadequately. Due to HIV’s lingering impact on B cells, immune senescence and residual chronic inflammation, people with HIV (PWH), especially immune non-responders, are immunocompromised and mount suboptimal antibody responses to vaccination for SARS-CoV-2. Here, we review how functionally and phenotypically distinct B cell subsets are induced in response to a vaccine and an infection and how HIV infection and anti-retroviral therapy (ART) impact them. We also review the role played by HIV-induced defects and perturbations in B cells in the induction of humoral immune responses to currently used anti-SARS-CoV-2 vaccines in PWH on ART. We also outline different strategies that could potentially enhance the vaccine-induced antibody responses in PWH. The review will provide guidance and impetus for further research to improve the immunogenicity of these vaccines in this human population.

The generalization of strongly convex and strongly m-convex functions is presented in this paper. We began by proving the properties of a strongly modified (h,m)-convex function. The Schur inequality and the Hermite–Hadamard (H-H) inequalities are proved for the proposed class. Moreover, H-H inequalities are also proved in the context of Riemann–Liouville (R-L) integrals. Some examples and graphs are also presented in order to show the existence of this newly defined class.

The current study assessed the effectiveness of an environmental approach-based learning method in developing primary science process skills and enhancing cognitive achievement among children. Utilizing validated instruments, this study involved 62 children who were divided into two groups: an experimental group of 32 children, who received instruction based on the environmental approach, and a control group of 30 children, who were taught using conventional methods. The results indicated that the experimental group achieved significantly higher scores on both the science process skills test and the achievement test compared to the control group. Statistical analyses confirmed these differences, demonstrating the superior performance of the experimental group. These findings provide robust evidence of the effectiveness of environmental approach-based learning in improving science process skills and cognitive achievement. It is recommended that early childhood science educators integrate environmental approach-based learning into their science education practices to enhance scientific understanding and engagement among young learners.

Connection number-based molecular descriptors are one type of quantitative measure that provides insight into the connectivity of atoms and bonds within a molecule. The investigation of skin cancer treatments based on connection number-based molecular descriptors requires quantifying the structural features of these pharmaceuticals based on their atom and bond connections. By employing connection number-based descriptors, it is possible to understand the chemical structure and connectivity patterns of these drugs. In this article, we calculated a few connection number-based molecular descriptors for skin cancer drugs, particularly Cobimetinib, Picato, Vismodegib, Odomzo, Imiquimod, Vemurafenib, Daurismo, Trametinib, Fluorouracil, Dacarbazine, Dabrafenib, Encorafenib, and Binimeinib. To summarise, the practical implementation of the research findings presented in the paper allows Dermathera Pharmaceuticals to effectively address obstacles in the process of discovering and developing drugs for skin cancer. The organization enhances its workflow by including molecular descriptors based on connection numbers. This allows for improved chemical selection, accurate prediction of therapy results, and the development of more efficient and safer treatments for patients with skin cancer. This application highlights the concrete advantages of the research in practical pharmaceutical engineering environments.

هدفت هذه الدراسة إلى دراسة تأثير التغيرات المناخية على مؤشر الأمن الغذائي كمؤشر من مؤشرات التنمية المستدامة في سورية خلال الفترة (2021-1990)، تمثلت التغيرات المناخية بمتغير درجات الحرارة ومتغير الأمطار، وذلك كونها تعتبر من أهم المؤشرات عن حالة المناخ، تناولت هذه الدراسة مؤشر الأمن الغذائي معبراً عنه بمتوسط نصيب الفرد من مؤشر الأمن الغذائي حيث قمنا بحسابه من خلال تقسيم إنتاج القمح (كونه محصول استراتيجي في سورية) على عدد السكان خلال فترة الدراسة، وذلك بناءً على أن سورية بلد زرعي بالدرجة الأولى، والإنتاج الزراعي يشكل حجر أساس في النمو الاقتصادي، إضافةً إلى أن القطاع الزراعي هو من أشد القطاعات حساسية للتغيرات المناخية، قمنا باستخدام طريقة المربعات الصغرى العادية (OLS) لمعرفة تأثير التغيرات المناخية على مؤشر الأمن الغذائي، وتوصلت الدراسة إلى وجود علاقة ذات دلالة إحصائية بين التغيرات المناخية المتمثلة في (درجات الحرارة-الأمطار) ومؤشر الأمن الغذائي في سورية، وأوصت الدراسة باتخاذ الإجراءات الكفيلة بتخفيف تأثيرات التغيرات المناخية، لما لها من تأثيرات سلبية كبيرة على مؤشرات التنمية المستدامة الهامة كمؤشر الأمن الغذائي.

تنتج شركات التشييد حجم ضخم من البيانات التشغيلية يومياً موزعة فيما بين العديد من قواعد البيانات، ولكن هذه البيانات التاريخية لا يتم تجميعها وتنظيمها بالطريقة الصحيحة لدعم قرارات تتبع المشاريع بشكل فعال. تعتبر طريقة المدة المكتسبة (EDM) واحدة من التقنيات الأساسية في تتبع مشاريع التشييد من خلال استخدام مؤشرات مختلفة لقياس تقدم وأداء الخطة الزمنية للمشروع. يهدف البحث الدراسة إلى استخدام الشبكات العصبية الصنعية (ANN) لتطوير نموذج للتنبؤ بمؤشر المدة المكتسبة (EDI) في أية مرحلة زمنية من المشروع بالاعتماد على البيانات التاريخية لمشاريع الشركة. تم تحديد التصميم الأمثل للنموذج المقترح للتنبؤ، وكانت المعايير الإحصائية المستخدمة لتقييم دقة النموذج المقترح هي جذر متوسط مربع الخطأ (RMSE) ومتوسط الخطأ المطلق (MAE). وقد ، وأثبتت نتائج الدراسة قدرة الشبكات العصبية الصنعية للتنبؤ بمؤشر المدة المكتسبة (EDI) في أية مرحلة من دورة حياة المشروع بنتائج مرضية. توصي الدراسة بالتوسع في استخدام الأنظمة الهجينة من نماذج الذكاء الاصطناعي لتحسين كفاءة نماذج التنبؤ بمؤشرات تتبع مشاريع التشييد مما يحسن من قرارات التتبع وبالتالي تحسين الأداء الاقتصادي لهذه المشاريع.

Learned from wrinkle wave motions, we concentrated on bifurcation phenomena in substrate-supported graphene sheets by obtaining the bifurcation solitons of thermophoretic motion equation. We find new soliton solutions by applying the bilinear technique and correctly choosing the auxiliary function involved in the bilinear form. Use of the Hirota bilinear technique combined with symbolic computation yields lump solutions as well as lump-type solutions. The governing model is subject to computation of the lump one strip, lump two strip, Y-type, lump periodic solution, generalised breather, and lump periodic solution. When simulating waves in different physical systems, such as water waves, fibre optics, and plasma physics, lump and lump type solutions are crucial. Rogue waves are studied in relation to large and unforeseen ocean wave phenomena that might affect coastal buildings and ship safety. In communication systems, including optical fibres, generalised breathers are used to comprehend and regulate pulse propagation.

Some active pharmaceutical ingredients (APIs) and excipients can form deep eutectic solvents (DESs), which will lead to severe defects in solid preparations. This work first prepared related typical DESs by mixing APIs and excipients from marketable drugs. Then two different types of the binary eutectic mixtures were investigated, which were composed of menthol (HBD) and citric acid (HBA) (ME/CA) as well as phenyl salicylate (HBA) and benzoic acid (HBD) (Salol/BA). These binary mixtrures were applied to investigate their possible effects on capsules and tablets, which could be liquefaction or the stickiness of the solid formulations. The comprehensive characterizations and studies on phase behaviors of the binary mixtures were carried out, and the spectral analysis confirmed the formation of the eutectic liquids from individual components. Furthermore, the binary mixtures have increased the tablet strength when increasing the compression force, leading to the stickiness of powders during pressing. Moreover, the capsules were softened by the existence of DESs. After morphological observation and quantitative analysis, the corresponding suggestions and countermeasures were provided in the conclusions.

The use of optoelectronic technology in Optical Transposition Interconnection Systems (OTIS) offers an effective solution to the ongoing problem of storing and sending data with comprehensive information. This is due to the reduced power requirements and broad bandwidth capabilities of optoelectronic systems, which make them well-suited for this task. The integration of radio communication and electrical technology has transformed OTIS into a highly valued network, enhancing the efficiency of existing optoelectronic computers. OTIS is characterized by the swapped network that is formed with the help of path graph $\mathfrak {P}_{m}$ and denoted as $B(\mathfrak {P}_{m})$ . This research work focused on certain topological invariants (TIs) about the number of connections between nodes of the graph $B(\mathfrak {P}_{m})$ and its largest subgraph that preserves twin nodes ( $M(B(\mathfrak {P}_{m}))$ ). First Zagreb connection index, geometric-arithmetic connection index, Randić connection index, reduced reciprocal Randić connection index, sum-connectivity connection index, first, second and third redefined Zagreb connection indices are considered in this work two types of biswapped and OTIS networks.

Entropy is a general term for measuring or determining the uncertainty of a system. Because of the advantageous concept of entropy, it has gained interest and attraction from the standpoint of graph theory, as it has been used as applied mathematical chemistry. The first application of graph-based entropy was to determine the structural information of chemical networks or graphs. Networks, like mathematical chemistry, are constructed in the form of nodes and edges to form a network or system graph. Carbon nanotubes, on the other hand, have a long history of use in memory devices and tissue engineering. Carbon nanotubes, a productive chemical structure, are studied here by affixing one-end and both-end caps to them. The entropy of three different carbon nanotube topologies is calculated. Some comparative work is provided in addition to the analytical study of the entropy measure of armchair carbon nanotubes.

Drones are being used for agriculture monitoring in many different crops. Nevertheless, the use of drones for green areas’ evaluation is limited, and information is scattered. In this survey, we focus on the collection and evaluation of existing experiences of using drones for turfgrass monitoring. Despite a large number of initial search results, after filtering the information, very few papers have been found that report the use of drones in green areas. Several aspects of drone use, the monitored areas, and the additional ground-based devices for information monitoring are compared and evaluated. The data obtained are first analysed in a general way and then divided into three groups of papers according to their application: irrigation, fertilisation, and others. The main results of this paper indicate that despite the diversity of drones on the market, most of the researchers are using the same drone. Two options for using cameras in order to obtain infrared information were identified. Moreover, differences in the way that drones are used for monitoring turfgrass depending on the aspect of the area being monitored have been identified. Finally, we have indicated the current gaps in order to provide a comprehensive view of the existing situation and elucidate future trends of drone use in turfgrass management.

Graph theory is a crucial branch of mathematics in fields like network analysis, molecular chemistry, and computer science, where it models complex relationships and structures. Many indices are used to capture the specific nuances in these structures. In this paper, we propose a new index, the weighted asymmetry index, a graph-theoretic metric quantifying the asymmetry in a network using the distances of the vertices connected by an edge. This index measures how uneven the distances from each vertex to the rest of the graph are when considering the contribution of each edge. We show how the index can capture the intrinsic asymmetries in diverse networks and is an important tool for applications in network analysis, optimization problems, social networks, chemical graph theory, and modeling complex systems. We first identify its extreme values and describe the corresponding extremal trees. We also give explicit formulas for the weighted asymmetry index for path, star, complete bipartite, complete tripartite, generalized star, and wheel graphs. At the end, we propose some open problems.

The authenticity of classical Arabic poetry has long been challenged by claims that some part of the pre-Islamic poetic heritage should not be attributed to this era. According to these assertions, some of this legacy was produced after the advent of Islam and ascribed, for different reasons, to pre-Islamic poets. As pre-Islamic poets were illiterate, medieval Arabic literature devotees relied on Bedouin oral transmission when writing down and collecting the poems about two centuries later. This process left the identity of the real poets who composed these poems and the period in which they worked unresolved. In this work, we seek to answer the questions of how and to what extent we can identify the period in which classical Arabic poetry was composed, where we exploit modern-day automatic text processing techniques for this aim. We consider a dataset of Arabic poetry collected from the diwans (‘collections of poems’) of thirteen Arabic poets that corresponds to two main eras: the pre-ʿAbbāsid era (covering the period between the 6th and the 8th centuries CE) and the ʿAbbāsid era (starting in the year 750 CE). Some poems in each diwan are considered ‘original’; i.e., poems that are attributed to a certain poet with high confidence. The diwans also include, however, an additional section of poems that are attributed to a poet with reservations, meaning that these poems might have been composed by another poet and/or in another period. We trained a set of machine learning algorithms (classifiers) in order to explore the potential of machine learning techniques to automatically identify the period in which a poem had been written. In the training phase, we represent each poem using various types of features (characteristics) designed to capture lexical, topical, and stylistic aspects of this poetry. By training and assessing automatic models of period prediction using the ‘original’ poetry, we obtained highly encouraging results, measuring between 0.73–0.90 in terms of F1 for the various periods. Moreover, we observe that the stylistic features, which pertain to elements that characterize Arabic poetry, as well as the other feature types, are all indicative of the period in which the poem had been written. We applied the resulting prediction models to poems for which the authorship period is under dispute (‘attributed’) and got interesting results, suggesting that some of the poems may belong to different eras—an issue to be further examined by Arabic poetry researchers. The resulting prediction models may be applied to poems for which the authorship period is under dispute. We demonstrate this research direction, presenting some interesting anecdotal results.

. Introduction One of the ways to enrich the content of poetry is to use the cultural supports that have existed in Persian poetry for a long time. The range of cultural supports used in Persian poetry is very wide and includes references to the Qur'an and Hadith and use of various scientific terms. Based on this and considering the use of these cultural supports in poetry, which are often used in the form of innovative spiritual arrays, especially allusions, it can be said that they have always been one of the sources of nutrition for poetry and literature.Since Persian and Urdu poetry has always had a close connection with popular culture from ancient times to modern times, there are many evidences of referring to the elements of popular culture, especially its linguistic elements.According to the above explanation, this research using the descriptive-analytical method has tried to compare and analyze the role and function of the most important linguistic elements of culture and popular literature in the poetry of Simin Behbahani and Parveen Shakir with the approach of comparative literature.2.MethodologyThis article is a theoretical research that, with the approach of comparative literature, has tried to analyze and compare the reflection of the linguistic elements of popular culture in the poetry of two contemporary Persian and Urdu poets (Simin Behbahani and Parveen Shaker). 3.DiscussionPoets use cultural supports and lived or learned experiences to strengthen the content of their poems. Undoubtedly, popular culture and literature is one of the most widely used spiritual fountains of official literature. Customs, traditions, beliefs, parables and allusions, stories and legends, etc., are elements of popular culture that can be divided into two parts, linguistic and non-linguistic. Linguistic elements; It includes interpretations, idioms, allusions, insults, proverbs and proverbs, stories and legends and everything that is created with the tool of language. Simin Behbahani and Parveen Shakir are among the well-known female poets in contemporary Persian and Urdu literature who have been influenced by the foundations and elements of folk culture and literature in their poems and have reflected them artistically in their poetry.culture in dictionaries means "a collection of customs and traditions." The collection of sciences, knowledge and arts of a nation". (Moin, 1384: 1176) and also "a complex general phenomenon of manners, customs, thought, art and way of life that is formed during the historical experience of peoples and can be transferred to the next generations" (Anvari, 1381 : 5346) came and said in a clearer definition: "Culture... is the collection of spiritual heritage of a people, whether it is the product of their intellect and understanding or the offspring of their taste and emotion." (Mahjub, 2016: 36)In a more comprehensive definition, culture is referred to "all the material and spiritual institutions in which a human being is born, raised and has a personality." (Velayati, 2010: 19) From the point of view of some researchers, culture is divided into two main parts: material and immaterial (spiritual), and from another point of view, some researchers have divided culture into the official culture and popular culture. material culture, tangible cultural elements; Such as architecture, it includes clothes, tools, etc., and non-material or spiritual culture includes the intangible parts of culture; It refers to beliefs and beliefs, proverbs and allusions, stories and legends, etc. (Chehreghani, 2015 A: 93) As can be seen, the linguistic elements of culture are placed under spiritual culture. The meaning of official culture is a set of cultural elements that are not only reserved for the masses and are also accepted among the elites. From another point of view, Culture can be considered to mean art or at least a source and watering hole for art, because noble, official and elitist art can be more enriched by hanging on the sources of popular culture. (Hall, 2013: 696)In all societies, language is considered the main axis of culture, and since literature is also an application of language, popular culture, which is transmitted orally from one generation to another in different societies, has an inseparable connection with popular literature. (Chehreghani, 2015 B: 3) One of the valid divisions for the constituent elements of popular culture, along with material and spiritual elements or healthy and unhealthy elements, is their division into linguistic and non-linguistic elements. The meaning of linguistic elements is that part of cultural elements that is created on the basis or with the tools of language and includes expressions, terms, allusions, songs and lullabies, work songs, parables and proverbs, stories and legends, etc. and researchers sometimes refer to it as oral literature. (Mirsadeghi, 1998: 12) According to what was said, popular literature is considered a sub-branch of popular culture. Comparative literature, which continued and followed the slogan of "world literature" of the romantics in Europe and started by collecting and comparing the stories and legends of the nations of Asia and the Middle East, "speaks of the research on the relations between the literature of the nations and the different peoples of the world." (ZarrinKub, 1982: 125) The method of comparative literature in the French school is "examining the historical relations of national literature with the literature of other nations written in a language other than the language of that country". (Ghunaymi Hilal, 2014: 7) Research in comparative literature introduces us to other nations and their similarities and differences with each other and their literary or cultural influences. Various topics are included under comparative literature, one of which is folk culture and literature. The importance of this approach lies in the fact that it helps to know the true mood, habits and way of thinking and living of the people of a region and to get to know more about the real face of a nation. For this purpose and to know more precisely the cultural similarities and differences between the nations of Iran and Pakistan, this research has investigated the issue of using language elements of culture and folk literature in the poetry of Simin Behbahani and Parveen Shakir. 3.ConclusionThe research findings show that the two mentioned poets have used the linguistic elements of popular culture in a wide way, considering their gender and female perspective, which is due to the affinities and historical, religious, cultural, etc. links between the two Iranian societies. And Pakistani and the two languages Persian and Urdu, regardless of the existing differences, have many similarities.As seen, Simin Behbahani, a contemporary Iranian poet, and Parveen Shakir, a contemporary Pakistani poet, have benefited from the linguistic elements of popular culture, both in the production and creation of the theme, and in strengthening the meaning and enriching the content of the poem, and in the direction of inducing better meaning and Its greater impact. Among the linguistic elements of popular culture reflected in the poetry of two Urdu and Persian poets, one can find many common elements including words, interpretations, idioms, ironies, proverbs, common stories, legends, etc. Poets have adapted the popular culture of their people and used it correctly in their artistic creations. What attracts the most attention in this matter is the great verbal and semantic similarity between the proverbs and allusions of the two nations, which is due to the ancient connection of the Urdu language and literature with Persian language and literature, and more importantly, the historical influence of Persian culture and literature in the Indian subcontinent. Especially Pakistan tells that in addition to many similarities in meaning and theme, sometimes the words of Urdu proverbs are very similar to the Persian equivalent and sometimes the same; Like the proverb " If the world is washed away, he is still asleep" in Urdu language, only the word "water" has been changed to "flood"; However, among the types of linguistic elements of popular culture used in the poetry of the two selected poets, the reference to legendary stories is less frequent.In addition to the mentioned commonalities and similarities, differences can also be identified in the use of linguistic elements of popular culture in the poetry of the two poets; Including all kinds of explicit insults and sarcasm and children's game songs; Such as Jom Jomak, Atal Matal Tutule, Tab Tab Hambazi, etc., which are common in the Persian-speaking community of Iran, are abundantly seen in Behbahani's poetry. Still, this type of linguistic element does not exist in Parvin Shakir's poetry. In addition to that, the lullaby is also a subject of which there is an example in Behbahani's poem; But in Shakir's poetry, although a poet has the experience of motherhood, it is not seen. Since Parvin Shakir is fully familiar with contemporary Persian poetry and is known as the only translator of Forough Farrokhzad's poetry in the Urdu language, and due to the feminine perspective that dominates the poetry of the two selected poets and their belonging to the space of neo-classical poetry (in Persian language and Urdu) it is expected that Shakir was influenced by Simin Behbahani's poetry; However, based on the findings of this research, apart from the existence of some similarities between the elements of general culture used in the poetry of both poets, the obvious influence of this Urdu language poet on the poetry of Simin Behbahani cannot be proven

Food and nutrition are a steadfast essential to all living organisms. With specific reference to humans, the sufficient and efficient supply of food is a challenge as the world population continues to grow. Artificial Intelligence (AI) could be identified as a plausible technology in this 5th industrial revolution in bringing us closer to achieving zero hunger by 2030—Goal 2 of the United Nations Sustainable Development Goals (UNSDG). This goal cannot be achieved unless the digital divide among developed and underdeveloped countries is addressed. Nevertheless, developing and underdeveloped regions fall behind in economic resources; however, they harbor untapped potential to effectively address the impending demands posed by the soaring world population. Therefore, this study explores the in-depth potential of AI in the agriculture sector for developing and under-developed countries. Similarly, it aims to emphasize the proven efficiency and spin-off applications of AI in the advancement of agriculture. Currently, AI is being utilized in various spheres of agriculture, including but not limited to crop surveillance, irrigation management, disease identification, fertilization practices, task automation, image manipulation, data processing, yield forecasting, supply chain optimization, implementation of decision support system (DSS), weed control, and the enhancement of resource utilization. Whereas AI supports food safety and security by ensuring higher crop yields that are acquired by harnessing the potential of multi-temporal remote sensing (RS) techniques to accurately discern diverse crop phenotypes, monitor land cover dynamics, assess variations in soil organic matter, predict soil moisture levels, conduct plant biomass modeling, and enable comprehensive crop monitoring. The present study identifies various challenges, including financial, infrastructure, experts, data availability, customization, regulatory framework, cultural norms and attitudes, access to market, and interdisciplinary collaboration, in the adoption of AI for developing nations with their subsequent remedies. The identification of challenges and opportunities in the implementation of AI could ignite further research and actions in these regions; thereby supporting sustainable development.

Metamaterial advancements hold promise for compact renewable energy harvesting, capturing acoustic, electromagnetic, mechanical, and solar energy on a modest scale across global industries. Engineered structures surpass natural material limitations, offering capabilities unattainable in traditional counterparts. This investigation explores metamaterials' manipulation of acoustic, electromagnetic, mechanical, and solar energy. Mechanical metamaterials convert strain into electrical energy, applicable from interstellar travel to terrestrial infrastructure. Precision-configured acoustic metamaterials efficiently harness dispersed acoustic energy, improving renewable energy methodologies. Integration into photovoltaic cells showcases metamaterials' solar potential, with innovative designs enhancing solar energy conversion efficiency. Electromagnetic metamaterials efficiently absorb and convert frequencies into usable energy from communications and monitoring systems, in the agricultural and environmental sectors. Comparative analyses highlight noteworthy efficiency advancements, underscoring metamaterials' transformative influence on renewable energy. As they redefine the sector, implications extend to both small-scale devices and large-scale applications, positioning them as pivotal contributors. The paper critically evaluates metamaterial effectiveness in harnessing diverse energy sources, guiding future research. Metamaterial adaptability to different sizes and integration into technology reveals possibilities for compact energy sources. Ongoing research addresses scientific and economic challenges, paving the way for scaling metamaterial applications to commercial operations and emphasizing their importance in incorporating renewable energy into our technological milieu.

Drought stress is an ever‐present threat to wheat growth, development, and productivity, especially in arid and semi-arid areas where rainfall is an essential aid to agriculture. The application of vermicompost has been proven to be an efficient approach to combat the drought-induced growth and developmental limitation of wheat plants and to promote cost-effective and sustainable crop production. A wire-house pot experiment was conducted to examine the effects of cow manure vermicompost on morpho-physiological and biochemical attributes of wheat seedlings under different deficit water levels. The treatments were included: three drought levels; control (70 % of field capacity (FC, D0)), mild drought (45 % of FC, D1), and severe drought (30 % of FC, D1), four vermicompost application rates; control, 4, 6 and 8 t ha−1 (designated as VT0, VT1, VT2 and VT3, respectively), and two contrasting wheat cultivars; Faisalabad-08 (drought tolerant) and Galaxy-13 (drought sensitive). Results showed that vermicompost application improved crop performance under control and drought stress conditions where VT2 depicted significantly higher values in both cultivars, particularly under drought stress. Under severe drought, VT2 increased root fresh weight by 6.13 and 10.63 %, shoot fresh weight by 15.62 % and 23.58 %, root dry weight by 40.81 % and 50 % and shoot dry weight by 20.68 and 22.22 % in Faisalabad-08 and Galaxy-13, respectively. Also, VT2-treated seedlings exhibited significantly higher gas exchange attributes, chlorophyll pigments and antioxidative enzyme activities under drought conditions. Among cultivars, Faisalabad-08 was found comparatively more drought tolerant than Galaxy-13. Our findings demonstrated that drought severely affects morphological, physiological, and biochemical attributes of wheat. However, soil applied vermicompost proved beneficial for improved morphophysiological and biochemical traits under the regime of drought stress in wheat.

Background Recent studies have indicated high rates of future major adverse cardiovascular events in patients with Takotsubo cardiomyopathy (TC), but there is no well‐established tool for risk stratification. This study sought to evaluate the prognostic value of several artificial intelligence‐augmented ECG (AI‐ECG) algorithms in patients with TC. Methods and Results This study examined consecutive patients in the prospective and observational Mayo Clinic Takotsubo syndrome registry. Several previously validated AI‐ECG algorithms were used for the estimation of ECG‐ age, probability of low ejection fraction, and probability of atrial fibrillation. Multivariable models were constructed to evaluate the association of AI‐ECG and other clinical characteristics with major adverse cardiac events, defined as cardiovascular death, recurrence of TC, nonfatal myocardial infarction, hospitalization for congestive heart failure, and stroke. In the final analysis, 305 patients with TC were studied over a median follow‐up of 4.8 years. Patients with future major adverse cardiac events were more likely to be older, have a history of hypertension, congestive heart failure, worse renal function, as well as high‐risk AI‐ECG findings compared with those without. Multivariable Cox proportional hazards analysis indicated that the presence of 2 or 3 high‐risk findings detected by AI‐ECG remained a significant predictor of major adverse cardiac events in patients with TC after adjustment by conventional risk factors (hazard ratio, 4.419 [95% CI, 1.833–10.66], P=0.001). Conclusions The combined use of AI‐ECG algorithms derived from a single 12‐lead ECG might detect subtle underlying patterns associated with worse outcomes in patients with TC. This approach might be beneficial for stratifying high‐risk patients with TC.

The exploration of edge metric dimension and its applications has been an ongoing discussion, particularly in the context of nanosheet graphs formed from the octagonal grid. Edge metric dimension is a concept that involves uniquely identifying the entire edge set of a structure with a selected subset from the vertex set, known as the edge resolving set. Let's consider two distinct edge resolving sets, denoted as Re1 and Re2, where Re1≠Re2. In such instances, it indicates that the graph G possesses a double-edge resolving set. This implies the existence of two different subsets of the vertex set, each capable of uniquely identifying the entire edge set of the graph. In this article, we delve into the edge metric dimension of nanosheet graphs derived from the octagonal grid. Additionally, we initiate a discussion on the exchange property associated with the edge resolving set. The exchange property holds significance in the study of resolving sets, playing a crucial role in comprehending the structure and properties of the underlying graph.

Objective Present study was designed to evaluate the efficacy of Acacia nilotica bark extract as an alternative to antibiotic growth promoters in broilers. Methods Six hundred, day-old broiler chicks were randomly divided into six groups (NC, without any supplementation; AB, NC+Zinc Bacitracin; PB, NC+Safmannan; ANBE1, NC+A. nilotica bark extract 0.1%; ANBE3, NC+A. nilotica bark extract 0.3%; ANBE5, NC+A. nilotica bark extract 0.5%), with ten replicates per group (10 chicks/replicate) and feeding trial was lasted for 35 days. Results Results showed that weight gain (1,296.63 g) and feed conversion ratio (FCR, 1.59) of AB was better than NC, during the finisher phase. Overall FCR of AB (1.53), PB (1.54), and ANBE5 (1.54) was significantly (p

Give us a linked graph, $ G = (V, E). $ A vertex $ w\in V $ distinguishes between two components (vertices and edges) $ x, y\in E\cup V $ if $ d_G(w, x)\neq d_G (w, y). $ Let $ W_{1} $ and $ W_{2} $ be two resolving sets and $ W_{1} $ $ \neq $ $ W_{2} $. Then, we can say that the graph $ G $ has double resolving set. A nanotube derived from an quadrilateral-octagonal grid belongs to essential and extensively studied compounds in materials science. Nano-structures are very important due to their thickness. In this article, we have discussed the metric dimension of the graphs of nanotubes derived from the quadrilateral-octagonal grid. We proved that the generalized nanotube derived from quadrilateral-octagonal grid have three metric dimension. We also check that the exchange property is also held for this structure.

Chemotherapy-induced peripheral neuropathy (CIPN) remains a clinical challenge for up to 80% of breast cancer survivors. In an open-label study, participants underwent three interventions: standard care (duloxetine) for 1 month (Phase 1), oral cannabidiol (CBD) for 2 months (Phase 2), and CBD plus multi-modal exercise (MME) for another 2 months (Phase 3). Clinical outcomes and gut microbiota composition were assessed at baseline and after each phase. We present the case of a 52-year-old female with a history of triple-negative breast cancer in remission for over five years presenting with CIPN. She showed decreased monocyte counts, c-reactive protein, and systemic inflammatory index after each phase. Duloxetine provided moderate benefits and intolerable side effects (hyperhidrosis). She experienced the best improvement and least side effects with the combined (CBD plus MME) phase. Noteworthy were clinically meaningful improvements in CIPN symptoms, quality of life (QoL), and perceived physical function, as well as improvements in pain, mobility, hand/finger dexterity, and upper and lower body strength. CBD and MME altered gut microbiota, showing enrichment of genera that produce short-chain fatty acids. CBD and MME may improve CIPN symptoms, QoL, and physical function through anti-inflammatory and neuroprotective effects in cancer survivors suffering from long-standing CIPN.

A 73-year-old woman presented to the emergency department with a syncopal episode and a history of dizzy spells. A transthoracic echocardiogram demonstrated a large left atrial mass extending into the right upper pulmonary veins. Subsequently, cardiac magnetic resonance imaging and coronary computed tomography angiography with three-dimensional reconstruction and printing of the heart and mass were performed, which demonstrated a high index of suspicion for an atypical left atrial myxoma. The mass was excised robotically, and the pathology report confirmed a diagnosis of myxoma.

An important dietary source of physiologically active compounds, coffee also contains phenolic acids, diterpenes, and caffeine. According to a certain study, some coffee secondary metabolites may advantageously modify a number of anti-cancer defense systems. This research looked at a few coffee chemical structures in terms of edge locating numbers or edge metric size to better understand the mechanics of coffee molecules. Additionally, this research includes graph theoretical properties of coffee chemical structures. The chemicals found in coffee, such as caffeine, diterpene or cafestol, kahweol, chlorogenic, caffeic, gallotannins, and ellagitannins, are especially examined in these publications.

This work explores the complicated realm of fullerene structures by utilizing an innovative algebraic lens to unravel their chemical intricacies. We reveal a more profound comprehension of the structural subtleties of fullerenes by the computation of modified polynomials that are customized to their distinct geometric and electrical characteristics. In addition to enhancing the theoretical underpinnings, the interaction between algebraic characteristics and fullerene structures creates opportunities for real-world applications in materials science and nanotechnology. Our results provide a novel viewpoint that bridges the gap between algebraic abstraction and chemical reality. They also open up new avenues for the manipulation and construction of materials based on fullerenes with customized features. Topological or numerical descriptors are used to associate important physicomolecular restrictions with important molecular structural features such as periodicity, melting and boiling points, and heat content for various 2 and 3D molecular preparation graphs or networking. The degree of an atom in a molecular network or molecular structure is utilized in this study to calculate the degree of atom-based numerics. The modified polynomial technique is a more recent way of assessing molecular systems and geometries in chemoinformatics. It emphasizes the polynomial nature of molecular features and gives numerics in algebraic expression. Particularly in this context, we describe multiple cages topologically based on the fullerene molecular form as polynomials, and several algebraic properties, including the Randić number and the modified polynomials of the first and second Zagreb numbers, are measured. By applying algebraic methods, we computed topological descriptors such as the Randić number and Zagreb indices. Our qualitative analysis shows that these descriptors significantly improve the prediction of molecular behavior. For instance, the Randić index provided insights into the stability and reactivity of fullerene structures, while the Zagreb indices helped us understand their potential in electronic applications. Our results suggest that modified polynomials not only offer a refined perspective on fullerene structures but also enable the design of materials with tailored properties. This study highlights the potential for these algebraic tools to bridge the gap between theoretical models and practical applications in nanotechnology and materials science, paving the way for innovations in drug delivery, electronic devices, and catalysis.