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The purpose of this study is to investigate the impact of intellectual capital (IC) on financial distress (FD) as well as the moderating role of CEO Power (CEO_P) in Pakistan and India's comparative study. A quantitative approach is used in the study and secondary data is collected from financial reports of 110 firms registered at the Pakistan Stock Exchange (PSX) and also 110 firms at the Bombay Stock Exchange (BSX) from the study period 2016 to 2023. Panel data techniques are used for analysis. Both countries with stronger IC are less likely to face FD and CEO_P partially moderate this relationship IC_FD. Findings support this argument. Resource-based view (RBV) theory and managerial discretion theory (MDT) are used in this study. This study uses the modified value-added intellectual coefficient (MVAIC) method, which incorporates relational capital (RC) in measuring IC. This study investigates two economies with varying socioeconomic development and stresses the importance of IC in both countries in reducing the risk of FD. It also evaluates whether powerful CEOs use business resources for their benefit or not. This study has some implications for stakeholders, policymakers, and managers of business. These findings suggest that managers should prioritize IC to reduce the risk of default and accounting bodies should formulate strategies to reduce the powers of CEOs to protect the rights of stakeholders.

OBJECTIVE: To evaluate the therapeutic effectiveness of fluoroscopy-guided genicular nerve radiofrequency ablation for treating refractory knee osteoarthritis. METHODOLOGY: This quasi-experimental study was conducted in Peoples Medical College Hospital from July 2020 to June 2022 on patients suffering from refractive knee osteoarthritis treated by fluoroscopy-guided genicular nerve radiofrequency ablation (FGGNRA). Eighty-six patients enrolled using a convenient sampling technique. The outcome measures included a reduction in pain scores assessed by the Visual Analog Scale (VAS) at 1, 2, 4, 6, and 12 weeks, though follow-up at six and nine months intervals. Data was collected on a predesigned proforma and analyzed using SPSS version 26, and a P value of less than 0.05 was considered significant. RESULTS: A total of 86 patients were treated, with the highest number of patients in the age group of 41-50 years (n=30, 34.9%, Mean. 54.3, Min. 35, Max. 85) having ASA Status-I (n=81, 94.2%). VAS score before the therapeutics block was at an average of 6.6 (±0.8); however, after the procedure, the average score was 2.0 (±0.8). The consequent observation after 1, 2, 4, 6, 12 weeks, six, and nine months showed an average VAS score of 1.9 (±0.8), 1.9 (±0.8), 1.8 (±0.8), 1.8 (±0.8), and 1.9 (±0.9), 2.5 (±0.8) and 2.5 (±0.9) respectively. Major complications after the procedure were numbness (43.0%, n=37), weakness (37.2%, n=32), vascular injury (12.8%, n=11), and paresthesia (7.0%, n=6). CONCLUSION: The FGGNRA technique for refractory knee osteoarthritis can be a promising option for treating knee pain with minor complications and long-term effects.

Abstract Background It is well-known that serum uric acid (SUA) can increase the risk of hypertension, diabetes, obesity and dyslipidemia. However, its independent association with the risk of cardiovascular diseases (CVD) is controversial particularly in different populations. Hence, this study was aimed to assess an independent association of SUA with CVD risk in a Punjabi Pakistani cohort. Methods This is a retrospective observational study in which 502 human subjects having CVD, hypertension and/or diabetes were grouped based on SUA levels as normouricemia (n = 266) and hyperuricemia (n = 236). Role of SUA was assessed in increasing the risk of CVD independent of other key confounding factors (i.e. age, gender, dyslipidemia, hypertension, diabetes, dietary and life-style habits). All clinical and biochemical data were analyzed in SPSS (ver. 20). Results Subjects aged 55 ± 13 years were of both genders (males: 52%). SUA levels were significantly different among clinical subtypes of CVD [i.e. acute coronary syndrome (ACS), myocardial infarction (MI) and heart failure (HF)]. Spearman correlation showed a significantly positive association between CVD and SUA (rho = 0.149, p

Linguistic complex intuitionistic fuzzy aggregation operators are a novel idea for the description of intuitionistic fuzzy information, where linguistic complex concepts are used to describe membership and non-membership. This can convey the hazy information more clearly, and some findings on linguistic complex intuitionistic fuzzy aggregation operators have been attained. Nonetheless, several linguistic complex intuitionistic fuzzy aggregation operators in the literature are founded on conventional operational principles, which have certain limitations when used to multi-attribute group decision-making (MAGDM). In this study, we presented some improved operating rules based on linguistic complex intuitionistic fuzzy variables (LCIFVs) and changed their features to address these issues. Next, we created a few aggregation operators, such as the enhanced linguistic complex intuitionistic fuzzy weighted average (LCIFWA) and the linguistic complex intuitionistic fuzzy ordered weighted averaging (LCIFOWA) operator, to fuse the decision information represented by LCIFVs. We also demonstrated that they had a few favorable qualities. We introduced many novel approaches to address the MAGDM issues in the context of the linguistic complex intuitionistic fuzzy environment, based on the LCIFOWA and linguistic complex intuitionistic fuzzy ordered weighted geometric (LCIFOWG) operators. In short, we employed few real-world scenarios to demonstrate the viability and soundness of the suggested techniques through comparison with other approaches. This unique technique has been applied to plastic waste management selection, and the results are more accurate than the previously used materials and methods.

Atmospheric pressure microplasma is a simple, cost-effective, efficient, and eco-friendly procedure, which is superior to the traditional nanomaterials synthesis techniques. It generates high yields and allows for a controlled growth rate and morphology of nanomaterials. The silver (Ag) nanomaterials, with their unique physical and chemical properties, exhibit outstanding antibacterial and antifungal properties. Similarly, zinc oxide (ZnO) nanomaterials, known for their low toxicity and relatively lower cost, find wide applications in wound repair, bone healing, and antibacterial and anticancer applications. The use of core–shell nanomaterials in certain situations where some nanoparticles can cause serious harm to host tissues or organs is a testament to their potential. A benign material is coated over the core to reduce toxicity in these cases. This review compares the numerous configurations of microplasma systems used for synthesizing nanomaterials and their use in producing Ag, ZnO, and their core–shell (Ag-ZnO) nanomaterials for biomedical applications. The summary also includes the effect of control parameters, including cathode diameter, gas flow rate, precursor concentration, voltage, and current, on the nanomaterial’s characteristics and applications. In addition, it provides a research gap in the synthesis of Ag, ZnO, and core–shell nanomaterials by this technique, as well as the development and limitations of this technique and the use of these nanoparticles for biomedical applications.

Abstract The red palm weevil (RPW), Rhynchophorus ferrugineus Olivier, is a devastating insect-pest of 29 plants including date palm. It feeds inside the tree bark thus it is difficult to manage using insecticides. Only a few insecticides have been found effective against RPW. Among these insecticide, emamectin benzoate (EMB) is widely used. This insecticide can pose threat human and environmental health as it is used in the form of tree injection. Thus, keeping in view its possible, its sublethal effect on RPW was studied using Age-stage, two sex life table. Life table parameters of the progeny of exposed larvae to LC10, LC25, and LC50 of EMB were computed. Statistically higher fecundity (161.12 per female) was observed in control treatment, while less fecundity was observed in LC50 treatment. Significantly higher values for intrinsic rate of increase (r), finite rate of increase (λ), and net reproductive rate (R o ) (0.0376, 1.0383, and 67.13 per day, respectively) were recorded for the control treatment. Contrarily, lower values for r, R o , and λ i.e. 0.0318, 23.82, and 1.0324 per day, respectively were recorded in the LC50 treatment. Decreased population parameters suggest that EMB can be successfully used in for the management of RPW.

Nowadays, waste discharge and contaminants in drinking water have emerged as a significant global problem. Therefore, it is necessary to remove these pollutants from the water and photocatalysis is the best technique for this purpose. The co-precipitation technique was employed to produce NiMn2O4 and ZnMn2O4 and a photocatalyst containing NiMn2O4/ZnMn2O4 heterostructure nanocomposite. Various analytical techniques have been ascribed to examine the physical, morphological and optical features of the fabricated catalysts. XRD diffraction peak patterns were utilized to confirm the presence of cubic NiMn2O4, tetragonal ZnMn2O4 and NiMn2O4/ZnMn2O4 phases in a nanocomposite. In photodegradation tests, the nanocomposite catalyst outperformed the individual catalysts. After 60 minutes of visible light exposure, this nanocomposite catalyst eliminated the methylene blue (MB) dye, attaining substantially higher degradation rates than pure NiMn2O4 (66%) and ZnMn2O4 (77%). The nanocomposite catalyst was highly effective against methylene blue (MB) dye with a degradation efficiency of 92%.

Morus nigra fruit has therapeutic significance against several clinical manifestations due to polyphenols, flavonoids, and anthocyanins. This research aimed to investigate the antioxidative and anti-inflammatory effects of ultrasound-assisted ethanolic (UAE) extract of M. nigra fruit against cholesterol-fed and cigarette smoke-exposed hypertensive rats. The in vitro antioxidant capacity of UAE extract of M. nigra fruit showed higher antioxidant potential against free radicals through DPPH and FRAP assays. The in vivo administration of UAE extract of M. nigra fruit significantly (p ≤ 0.05) alleviated serum total oxidant status while significantly (p ≤ 0.05) improved total antioxidant capacity. Moreover, the qRT-PCR analysis revealed increased expression of Keap1/Nrf2 signaling pathway genes (NFR-1 and Keap-1) while reduced expression of JAK/STAT (JAK-2, STAT-1, STAT-3) signaling cascade and dual oxidases (Duox-1 and Duox-2) genes. Histopathological findings indicated the mild destruction of cardiac fibers and necrosis. Conclusively, UAE extract of M. nigra fruit exerted antioxidant and anti-inflammatory properties against cholesterol and cigarette smoke-associated oxidative damage and inflammation.

Abstract In the present work, a simple intelligence-based computation of artificial neural networks with the Levenberg-Marquardt backpropagation algorithm is developed to analyze the new ferromagnetic hybrid nanofluid flow model in the presence of a magnetic dipole within the context of flow over a stretching sheet. A combination of cobalt and iron (III) oxide (Co-Fe2O3) is strategically selected as ferromagnetic hybrid nanoparticles within the base fluid, water. The initial representation of the developed ferromagnetic hybrid nanofluid flow model, which is a system of highly nonlinear partial differential equations, is transformed into a system of nonlinear ordinary differential equations using appropriate similarity transformations. The reference data set of the possible outcomes is obtained from bvp4c for varying the parameters of the ferromagnetic hybrid nanofluid flow model. The estimated solutions of the proposed model are described during the testing, training, and validation phases of the backpropagated neural network. The performance evaluation and comparative study of the algorithm are carried out by regression analysis, error histograms, function fitting graphs, and mean squared error results. The findings of our study analyze the increasing effect of the ferrohydrodynamic interaction parameter $$\beta$$ β to enhance the temperature and velocity profiles, while increasing the thermal relaxation parameter $$\alpha$$ α decreases the temperature profile. The performance on MSE was shown for the temperature and velocity profiles of the developed model about 9.1703e−10, 7.1313ee−10, 3.1462e−10, and 4.8747e−10. The accuracy of the artificial neural networks with the Levenberg-Marquardt algorithm method is confirmed through various analyses and comparative results with the reference data. The purpose of this study is to enhance understanding of ferromagnetic hybrid nanofluid flow models using artificial neural networks with the Levenberg-Marquardt algorithm, offering precise analysis of key parameter effects on temperature and velocity profiles. Future studies will provide novel soft computing methods that leverage artificial neural networks to effectively solve problems in fluid mechanics and expand to engineering applications, improving their usefulness in tackling real-world problems.

Abstract QSPR mathematically links physicochemical properties with the structure of a molecule. The physicochemical properties of chemical molecules can be predicted using topological indices. It is an effective method for eliminating costly and time-consuming laboratory tests. We established a QSPR between mev-degree and mve-degree-based indices and the physical properties of benzenoid hydrocarbons. To compute these indices, we designed a program using Maple software and the correlation between indices and physical properties was developed using the SPSS software. Our study reveals that the mve-degree-based sum-connectivity $$(\chi ^{mve})$$ ( χ mve ) and atom bond connectivity ( $$ABC^{mve}$$ A B C mve ) index, mev-degree-based Randić ( $$R^{mev}$$ R mev ) and Zagreb ( $$M^{mev}$$ M mev ) index are the three most significant parameters and have good prediction ability for the physicochemical properties. We examined that $$R^{mev}$$ R mev predicts the molar refractivity and boiling point, $${\chi }^{mve}$$ χ mve predicts the LogP and enthalpy, $$ABC^{mve}$$ A B C mve predicts the molecular weight, $$M^{mev}$$ M mev predicts the Gibb’s energy, Pie-electron energy and Henry’s law. Moreover, we computed the indices for the linear [n]-phenylen.

Abstract Cyclodextrin, a potent anti-tumor medication utilized predominantly in ovarian and breast cancer treatments, encounters significant challenges such as poor solubility, potential side effects, and resistance from tumor cells. Combining cyclodextrin with biocompatible substrates offers a promising strategy to address these obstacles. Understanding the atomic structure and physicochemical properties of cyclodextrin and its derivatives is essential for enhancing drug solubility, modification, targeted delivery, and controlled release. In this study, we investigate the topological indices of cyclodextrin using algebraic polynomials, specifically the degree-based M-polynomial and neighbor degree-based M-polynomial. By computing degree-based and neighbor degree-based topological indices, we aim to elucidate the structural characteristics of cyclodextrin and provide insights into its physicochemical behavior. The computed indices serve as predictive tools for assessing the health benefits and therapeutic efficacy of cyclodextrin-based formulations. In addition, we examined that the computed indices showed a significant relationship with the physicochemical characteristics of antiviral drugs. Graphical representations of the computed results further facilitate the visualization and interpretation of cyclodextrin's molecular structure, aiding researchers in designing novel drug delivery systems with improved pharmacological properties.

Cooperative communication through energy harvested relays in Cognitive Internet of Things (CIoT) has been envisioned as a promising solution to support massive connectivity of Cognitive Radio (CR) based IoT devices and to achieve maximal energy and spectral efficiency in upcoming wireless systems. In this work, a cooperative CIoT system is contemplated, in which a source acts as a satellite, communicating with multiple CIoT devices over numerous relays. Unmanned Aerial Vehicles (UAVs) are used as relays, which are equipped with onboard Energy Harvesting (EH) facility. We adopted a Power Splitting (PS) method for EH at relays, which are harvested from the Radio frequency (RF) signals. In conjunction with this, the Decode and Forward (DF) relaying strategy is used at UAV relays to transmit the messages from the satellite source to the CIoT devices. We developed a Multi-Objective Optimization (MOO) framework for joint optimization of source power allocation, CIoT device selection, UAV relay assignment, and PS ratio determination. We formulated three objectives: maximizing the sum rate and the number of admitted CIoT in the network and minimizing the carbon dioxide emission. The MOO formulation is a Mixed-Integer Non-Linear Programming (MINLP) problem, which is challenging to solve. To address the joint optimization problem for an epsilon optimal solution, an Outer Approximation Algorithm (OAA) is proposed with reduced complexity. The simulation results show that the proposed OAA is superior in terms of CIoT device selection and network utility maximization when compared to those obtained using the Nonlinear Optimization with Mesh Adaptive Direct-search (NOMAD) algorithm.

In this study, we employ the Laplace Variational Iterational Method (LVIM) as a sophisticated mathematical tool to investigate into the complex dynamics of cancer cells under the influence of chemotherapy. The LVIM, a method combining Laplace transformations and variational iteration techniques, is specifically adapted to address a system of time fractional differential equations (FDEs) that characterizes the temporal behavior of cancer cells. To enhance the efficacy of our approach, we introduce a semi-analytic version of LVIM, which proves to be a powerful and versatile tool for solving mathematical problems involving fractional derivatives. The focus of our analysis centers on elucidating the impact of chemotherapy, with a particular emphasis on drug diffusion within cancer cells and the fractality of DNA walks. Through numerical exploration encompassing varying fractional order derivatives, our study exposes nonlinear behaviors that remain secret in systems featuring only integer order derivatives. Notably, the methodology we propose is not only applicable to the specific cases examined in this research but also exhibits broad versatility, making it suitable for exploring the effects of different drugs and types of cancers. This research contributes valuable insights into the dynamics of cancer cells, aiding in the understanding of the implications for therapeutic strategies in the context of cancer treatment.

Abstract Background Three Amino acid Loop Extension (TALE) belongs to the homeobox group of genes that are important constituents of plant systems. The TALE gene family is instrumental not only in growth and development but also plays an essential role in regulating plant response to environmental adversaries. Results In the present study, we isolated 21 CsTALE genes from the cucumber (Cucumis sativus L.) genome database. Bioinformatics tools were put in place to understand the structural and functional components of the CsTALE gene family. The evolutionary analysis dissected them into seven subclades (KNOX-I, KNOX-II, and BELL-I to BELL-V). The cis-acting elements in the promoter region of CsTALE genes disclosed that they are key regulators of hormonal and stress-related processes. Additionally, the STRING database advocated the concerting role of CsTALE proteins with other key transcription factors potent in plant developmental biology. The CsmiR319 and CsmiR167a-3p targeting the CsTALE15 and CsTALE16, respectively, further assert the importance of the CsTALE gene family posttranscriptional-related processes. Tissue-specific gene expression unfolded the fundamental involvement of CsTALE genes as they were expressed throughout the developmental stages. Under waterlogging stress, the CsTALE17 expressed significantly higher values in WL, WL-NAA, and WL-ETH but not in WL-MeJA-treated samples. Conclusions The present study reveals the evolution and functions of the CsTALE gene family in cucumber. Our work will provide a platform that will help future researchers address the issue of waterlogging stress in the Yangtze River Delta.

Abstract Artificial intelligence (AI) broadly influences different aspects of human life, especially human communication. One of the main concerns of the broad use of AI in daily interactions among different people could be whether it helps them interact easily or complicates their interactions. To answer the mentioned question, this study assessed the impacts of AI on intercultural communication among postgraduate students in a multicultural university environment. A newly developed survey instrument was used to conduct this study. The participants of this study were 115 postgraduate students from nine different countries. The descriptive statistics, reliability analysis, and Bivariate correlation tests of the 29th version of IBM-SPSS software were used to analyze the quantitative data, and inductive coding and conceptual content analysis were used to code and analyze the qualitative data. Based on descriptive results, the vast majority (93%) of the participants already used and experienced AI in their daily lives, and the majority of them believed that AI and AI technologies connect different cultures, reduce language and cultural barriers, and help people of different cultures to interact and be connected. Based on the results from the correlation test, there were strong positive correlations between AI attitudes and AI benefits, and also between AI regulation and AI benefits.

Abstract Background Optically active D-amino acids are widely used as intermediates in the synthesis of antibiotics, insecticides, and peptide hormones. Currently, the two-enzyme cascade reaction is the most efficient way to produce D-amino acids using enzymes DHdt and DCase, but DCase is susceptible to heat inactivation. Here, to enhance the enzymatic activity and thermal stability of DCase, a rational design software “Feitian” was developed based on k cat prediction using the deep learning approach. Results According to empirical design and prediction of “Feitian” software, six single-point mutants with high k cat value were selected and successfully constructed by site-directed mutagenesis. Out of six, three mutants (Q4C, T212S, and A302C) showed higher enzymatic activity than the wild-type. Furthermore, the combined triple-point mutant DCase-M3 (Q4C/T212S/A302C) exhibited a 4.25-fold increase in activity (29.77 ± 4.52 U) and a 2.25-fold increase in thermal stability as compared to the wild-type, respectively. Through the whole-cell reaction, the high titer of D-HPG (2.57 ± 0.43 mM) was produced by the mutant Q4C/T212S/A302C, which was about 2.04-fold of the wild-type. Molecular dynamics simulation results showed that DCase-M3 significantly enhances the rigidity of the catalytic site and thus increases the activity of DCase-M3. Conclusions In this study, an efficient rational design software “Feitian” was successfully developed with a prediction accuracy of about 50% in enzymatic activity. A triple-point mutant DCase-M3 (Q4C/T212S/A302C) with enhanced enzymatic activity and thermostability was successfully obtained, which could be applied to the development of a fully enzymatic process for the industrial production of D-HPG.

Microplastics are an emerging pollutant of marine environments, affecting fish and other marine biota such as copepods and rotifers. The current study assesses the impact of plastic microbeads on the growth of roho (Labeo rohita) in a 4-month feeding experiment under laboratory conditions. Over a period of 120 days, roho fingerlings were exposed to different concentrations of plastic microbeads (50 mg to 200 mg/kg of feed) mixed into their feed. It was found that the ingestion of plastic microbeads negatively affected the growth of roho and that the concentration of the plastic microbeads directly influenced the growth rate of the fish.

Bismuth based MOFs have appealed much curiosity in different catalytic processes due to their remarkable properties, which include their porous structure, less toxicity, abundance and high specific surface area. With their distributed active sites and constrained reaction regions, Bi based MOFs have a bright future as catalysts for extremely focused CO2 reduction by electrocatalysis reactions (ECO2RR). Formic acid (HCOOH), one of the byproducts of these processes, is notable because of its high economic worth. An extensive summary of Bi-MOFs and their derivatives used in ECO2RR and the photocatalytic reduction of CO2 into useful compounds is given in this review. Bi-MOFs synthesis methods for both electro and photocatalyst applications are discussed, along with an analysis of their unique benefits. Interestingly, a variety of Bi-MOFs and related offshoots are highlighted, including bimetallic catalysts and Bi-based MOF-derived nanocomposites. Bi-MOFs catalysts’ catalytic efficacy is demonstrated to be closely related to the MOF structure blocks-metal ions and organic linkers as well as particular circumstances controlling their derivatization. As a result, Bi-MOFs catalysts have a wide range of functions and provide the possibility of controlling the catalytic performance. This review describes the current obstacles in this area and makes recommendations for future research paths to advance the use of Bi-MOFs as electro- and photocatalysts.

The surgical site infections cost 0.5 % of the annual budget of the hospitals. Therefore, present research aimed to develop and evaluate antibacterial Neem/chitosan-coated silk braided sutures to reduce the risk of hospital-acquired surgical site infections. The silk braided sutures were coated by dip-coating technique by using 5, 10, 15 and 20 % concentrations of ethanolic Neem extract and chitosan. Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and tensile strength measurements were used to examine the surface morphology, chemical composition, and tensile strength of the coated sutures. At a 20 % concentration, the sutures showed strong antibacterial action against Escherichia coli and Staphylococcus aureus, with inhibition zones of 15 and 19 mm, respectively. Additionally, the sutures demonstrated low cytotoxicity in the MTT assay, good radical scavenging activity, and hemolytic activity of less than 2 % at all concentrations. The sutures for the in vivo investigation were coated at a concentration of 20 % since this concentration showed the best antibacterial action. The rats were incised on both sides of their spine, with the left side stitched with uncoated sutures, and the right side stitched with coated sutures. The wound was inoculated with E. coli and S. aureus and examined for 7 days. The results indicated complete healing of the wound at the site where the coated sutures were applied. On other hand, wound with uncoated suture was still not completely healed and revealed signs of infection. The in vivo study revealed the efficacy of Neem/chitosan-coated sutures in wound healing and infection control.

Drawing on the conservation of resource (COR) theory principles, this study demonstrates how despotic leadership (DL) negatively impacts employee career success (ECS) in the pharmaceutical industry. Since this is a serious growing concern in emerging research and a threat to the career therefore we aimed to investigate the relationship between (DL) and (ECS). Parallel mediating effects of job insecurity (JI) and emotional exhaustion (EE) are also tested which was overlooked in previous literature. Data were collected from 325 working employees. The target population of this study was managers, middle managers, and administrative staff facing DL. The results revealed a significant negative relationship between DL and ECS. Furthermore, JI and EE partially mediate the relationship between DL and ECS. Present research advances literature theoretically and practically in the field of organization behavior, specifically in the pharmaceutical industry. As it explored the connection between DL and employees’' career success under stressful working conditions. Thus, top management should develop leadership programs that focus on improving their behavior toward employees and leading to positive outcomes in the reduction of JI and EE. Secondly, the industry should formulate and implement clear policies and guidelines to curtail the detrimental effects of DL by inculcating open communication, employee empowerment, a supportive work environment, and shared growth of leaders and followers. Thirdly, include qualitative and quantitative methods (i.e., 360 feedback) to evaluate leaders’ behavior, which may give deeper insight into leadership behavior.

Limited research in Saudi Arabia has devolved into the prevalence and genetic diversity of begomoviruses. Utilizing Illumina MiSeq sequencing, we obtained 21 full-length begomovirus sequences (2.7–2.8 kb) from eight cucumber plants grown in fields and greenhouses. We found that two complete begomovirus genomes were variants of the Boushehr strain of tomato yellow leaf curl virus (TYLCV) with nucleotide (nt) sequence identities of 94.7-95.9%. Another full-length genome was a variant of TYLCV-Iran with 94.6% identity. Five full-length sequences closely matched the DNA-A of watermelon chlorotic stunt virus (WmCSV) isolates with 97.9-98.7% nt sequence identities, while five sequences had their highest nt sequence identities (95.8-96.3%) with the DNA-B of WmCSV isolates. Simultaneously, four sequences were 99.1-99.6% identical to the DNA-A of tomato leaf curl Palampur virus (ToLCPalV). Four sequences matched the DNA-B of ToLCPalV reported from Iran and Saudi Arabia with identities ranging from 96.2-100%. Four plants showed a mixed infection of these begomoviruses. Most ORFs showed evidence of negative selection pressure, suggesting that purifying selection plays a crucial role in shaping the diversity of these begomoviruses. Additionally, potential intra- and interspecies recombination events were detected in the TYLCV and WmCSV DNA-B genomic regions. The ToLCPalV isolates identified in this study formed a cluster with the other ToLCPalV isolates reported from Saudi Arabia, Iran and Iraq, representing a unique lineage distinct from ToLCPalV reported from Southeast Asia. High mutation rate and robust selection facilitated the independent evolution of ToLCPalV without recombination. Overall, this study offers valuable insights into the diversity and evolutionary dynamics of begomoviruses infecting cucumber crops in Al-Ahsa, Saudi Arabia.

Background and aim: As the spleen plays a significant role in immunity, the aim was to investigate the associations of different body composition markers derived from various sources with spleen volume in a general population sample. Materials and methods: Cross-sectional data of 1095 individuals (570 women; 52%) aged between 30 and 90 years were collected in the Study of Health in Pomerania (SHIP-START-2). We measured spleen volume by magnetic resonance imaging (MRI).Body composition markers were derived from classic anthropometry, bioelectrical impedance analysis, including absolute fat mass (FM) and fat-free mass (FFM), as well as from MRI, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and liver fat content. Sex-stratified-adjusted linear regression models were used to analyze the associations of body composition markers with spleen volumes. Results: We observed positive associations of body mass index, body weight, waist circumference, hip circumference, waist-to-height ratio, absolute FM, absolute FFM, and VAT and SAT with spleen volume in men and women. An 8.12 kg higher absolute FFM was associated with a 38.4 mL (95% confidence interval [CI]: 26.7–50.1) higher spleen volume in men and a 5.21 kg higher absolute FFM with a 42.6 mL (95% CI: 26.2–59.0) higher spleen volume in women. Conclusion: Our findings indicate that obesity-related body composition markers and FFM are associated with a higher spleen volume. Particularly, higher absolute FFM showed a strong association with a larger spleen volume in both men and women. Further studies are warranted to understand the clinical significance of body composition markers on large spleen volume.

Abstract In this article, examine the performance of a physics informed neural networks (PINN) intelligent approach for predicting the solution of non-linear Lorenz differential equations. The main focus resides in the realm of leveraging unsupervised machine learning for the prediction of the Lorenz differential equation associated particle swarm optimization (PSO) hybridization with the neural networks algorithm (NNA) as ANN-PSO-NNA. In particular embark on a comprehensive comparative analysis employing the Lorenz differential equation for proposed approach as test case. The nonlinear Lorenz differential equations stand as a quintessential chaotic system, widely utilized in scientific investigations and behavior of dynamics system. The validation of physics informed neural network (PINN) methodology expands to via multiple independent runs, allowing evaluating the performance of the proposed ANN-PSO-NNA algorithms. Additionally, explore into a comprehensive statistical analysis inclusive metrics including minimum (min), maximum (max), average, standard deviation (S.D) values, and mean squared error (MSE). This evaluation provides found observation into the adeptness of proposed AN-PSO-NNA hybridization approach across multiple runs, ultimately improving the understanding of its utility and efficiency.

Chromium (Cr) toxicity hampers ornamental crops’ growth and post-harvest quality, especially in cut flower plants. Nano-enabled approaches have been developing with phenomenal potential towards improving floricultural crop production under heavy metal-stressed conditions. The current pot experiment aims to explore the ameliorative impact of silicon nanoparticles (Si-NPs; 10 mM) and indole butyric acid (IBA; 20 mM) against Cr stress (0.8 mM) in Freesia refracta. The results showed that Cr stress significantly reduced morphological traits, decreased roots-stems biomass, abridged chlorophyll (14.7%) and carotenoid contents (27.2%), limited gas exchange attributes (intercellular CO2 concentration (Ci) 24.8%, stomatal conductance (gs) 19.3% and photosynthetic rate (A) 28.8%), condensed proline (39.2%) and total protein (40%) contents and reduced vase life (15.3%) of freesia plants by increasing oxidative stress. Contrarily, antioxidant enzyme activities, MDA and H2O2 levels, and Cr concentrations in plant parts were remarkably enhanced in Cr-stressed plants than in the control. However, foliar supplementation of Si-NPs + IBA (combined form) to Cr-stressed plants increased defense mechanism and tolerance as revealed by improved vegetative and reproductive traits, increased biomass, photosynthetic pigments (chlorophyll 30.3%, carotenoid 57.2%) and gaseous exchange attributes (Ci 33.3%, gs 25.6%, A 31.1%), proline (54.5%), total protein (55.1%), and vase life (34.9%) of metal contaminated plants. Similarly, the improvement in the activities of peroxidase, catalase, and superoxide dismutase was recorded by 30.8%, 52.4%, and 60.8%, respectively, compared with Cr-stressed plants. Meanwhile, MDA (54.3%), H2O2 (32.7%) contents, and Cr levels in roots (43.3), in stems (44%), in leaves (52.8%), and in flowers (78.5%), were remarkably reduced due to combine application of Si-NPs + IBA as compared with Cr-stressed nontreated freesia plants. Thus, the hypothesis that the synergistic application of Si-NPs + IBA will be an effective approach in ameliorating Cr stress is authenticated from the results of this experiment. Furthermore, the study will be significant since it will demonstrate how Si-NPs and IBA can work synergistically to combat Cr toxicity, and even when added separately, they can improve growth characteristics both under stressed and un-stressed conditions.

Alanine is the most abundant chiral amino acid that exists into the D-alanine or L-alanine forms with diverse applications in the biomedical, pharmaceutical, plastics, and food industries. D/L-alanine production can be carried out through chemical, microbial fermentation, and biocatalytic methods and not much effective due to complicated processes or purification issues and is still challenging to achieve a higher yield. In the present study, biobrick method was utilized for efficient production of D/L-alanine in the recombinant Escherichia coli BL21(DE3) with tandem three-gene co-expression plasmid. Firstly, the co-expression plasmid pET-22bNS-DadX-Ald-Gdh containing three genes, alanine dehydrogenase (ald), alanine racemase (dadX), and glucose dehydrogenase (gdh) from Bacillus pseudofirmus OF4 were successfully constructed and introduced into the E. coli BL21(DE3) strain. Then, under optimized conditions in the whole-cell biocatalytic reaction [20 mM Na2CO3-NaHCO3 (pH 10.1), 200 mM D-glucose, 200 mM sodium pyruvate, and 200 mM ammonium chloride], the concentration of D-alanine and L-alanine reached the maximum value (6.48 g/L and 7.05 g/L) after 3.0 h reaction time at 37°C under 180 rpm rotation. Meanwhile, promoter replacement experiments and Western blot analysis revealed that the expression level of protein OF4Ald had a significant effect on the production of D/L-alanine, indicating that alanine dehydrogenase might be the rate-limiting enzyme for D/L-alanine synthesis. This study provides a simple, feasible, and efficient biosynthesis process of D/L-alanine, which could explore emerging applications for large-scale production of industrial bioproducts.

Ultrasound-assisted extraction (UAE) is an innovative process for recovering valuable substances and compounds from plants and various biomaterials. This technology holds promise for resource recovery while maintaining the quality of the extracted products. The review comprehensively discusses UAE’s mechanism, applications, advantages, and limitations, focusing on extracting essential oils (EOs) from diverse terrestrial plant materials. These oils exhibit preservation, flavor enhancement, antimicrobial action, antioxidant effects, and anti-inflammatory benefits due to the diverse range of specific compounds in their composition. Conventional extraction techniques have been traditionally employed, and their limitations have prompted the introduction of novel extraction methods. Therefore, the review emphasizes that the use of UAE, alone or in combination with other cutting-edge technologies, can enhance the extraction of EOs. By promoting resource recovery, reduced energy consumption, and minimal solvent use, UAE paves the way for a more sustainable approach to harnessing the valuable properties of EOs. With its diverse applications in food, pharmaceuticals, and other industries, further research into UAE and its synergies with other cutting-edge technologies is required to unlock its full potential in sustainable resource recovery and product quality preservation.

The development on entropy generation in fluid flows has applications in many medical equipment such as cryogenic devices and therapeutic heat apparatus. This study looks at how porous medium, multi-slips, and entropy formation affect the pumping of Jeffrey nanofluid flow through an asymmetric channel containing motile microorganims. A lubrication theory is used to neglect the fluctuation effects in the flow. Numerical simulations are utilized to generate data for specific physical features of the problem utilizing the Shooting approach on Mathematica. Following a thorough research, it is appropriate to conclude that the porous medium's permeability reduces flow speed along the walls while increases at the center of the flow region. Graphical representation of the results further reveals that entropy production can be decreased by including high thermal slip and low viscous slip elements. It is also worth noting that the Brinkman number reduces the thermal distribution in the flow while it helps in increasing the flow speed.

Widespread ecosystem degradation from noxious substances like industrial waste, toxic dyes, pesticides, and herbicides poses serious environmental risks. For remediation of these hazardous problems, present study introduces an innovative Cu-doped Ce₂Zr₂O₇ nano-photocatalyst, fabricated via a simple, eco-friendly hydrothermal method, designed to degrade toxic textile dye methylene blue. Harnessing Cu doping for pyrochlore Ce2Zr2O7, structure engineering carried out through a hydrothermal synthesis method to achieve superior photocatalytic performance, addressing limitations of rapid charge carrier recombination in existing photocatalysts. Photoluminescence analysis showed that doped pyrochlore slows charge carrier recombination, boosting dye degradation efficiency. UV–Visible analysis demonstrated an impressive 96 % degradation of methylene blue by Cu-doped Ce2Zr2O7 within 50 min, far exceeding the performance of pristine materials. Trapping experiments clarified the charge transfer mechanism, deepening our understanding of the photocatalytic process. These findings highlight the potential for developing innovative, highly efficient photocatalysts for environmental remediation, offering sustainable solutions to combat pollution. This study not only addresses the limitations of existing photocatalysts but also opens new avenues for enhancing photocatalytic performance through strategic material design.

The refutation of Orientalist thoughts has been a subject of critical importance within scholarly discourse, particularly in the context of defending the integrity of the Prophet Muhammad (PBUH) and addressing the false acusations and allegations put forth by Orientalists. Notable work and efforts in this regard have been done by scholars from different Muslim countries, including Egypt, Syria, Sudan, Algeria, India, Pakistan, and Saudi Arabia. Saudi Arabian scholars have made significant contributions at the individual level to this endeavor. Through numerous means, such as authoring and publishing books, producing research articles, delivering lectures, engaging in debates, and establishing specialized institutions, Saudi Arabian scholars have actively participated in the critique and rebuttal of Orientalist narratives. Central to the investigation is an in-depth analysis of the scholarly initiatives undertaken by Saudi Arabian academics in the defense of the Holy Prophet Muhammad (PBUH) against Orientalist perspectives. The paper meticulously examines the diverse mechanisms employed by Saudi scholars to interrogate and refute Orientalist contentions, providing a nuanced understanding of their intellectual interventions. Furthermore, this research paper furnishes an exhaustive catalog of books authored by Saudi scholars and research articles penned by them, offering a comprehensive overview of their scholarly output. By meticulously documenting these scholarly contributions, this paper aims to enrich the academic discourse surrounding the critique of Orientalist thought and the defense of the Prophet Muhammad (PBUH) within the Saudi Arabian intellectual landscape.

Anthracyclines exert cytotoxic effects on cancer cells through genotoxicity, inducing damage to their genetic material and impeding their reproductive capacity. The compound possesses a molecular framework consisting of an anthracycline ring system, which confers its pharmacological activity against cancer. Adriamycin is an anthracycline chemotherapeutic agent characterized by a structurally intricate chemical composition. In this article, we computed irregularity indices like the Albertson index, total irregularity index, Randić irregularity index and other degree-based irregularity indices to estimate the biological and chemical properties of Adriamycin. The findings are illustrated through the use of numerical figures and graphical representations. Further, we proposed the relationship between irregularity indices and the physicochemical properties of emetic drugs. We examined that the irregularity indices showed a statistically significant relationship with Molecular Weight, Monoisotopic Mass, Polar Surface Area, Heavy Atom Count, Complexity, Boiling Point, Enthalpy of Vaporization, Flash Point, Molar Refractivity and Polarizability based on the p-value (

Polyvinylidene fluoride (PVDF) and its copolymers present extensive application prospects, especially in the field of wearable electronics. However, utilizing nanofillers for enhanced β‐phase and piezoelectric properties faces challenges like noncontinuous interfaces, poor compatibility between nanofillers and PVDF matrix, and the requirement of high‐voltage polarization, hindering extensive domain alignment on a large scale. Herein, a method is proposed to synthesize high‐performance PVDF composites by introducing hydroxylated barium titanate (H@BTO) nanoparticles and a directional freeze‐drying method to enhance β‐phase content and piezoelectric properties without polarization. Molecular dynamics simulations reveal robust binding interactions between Ba and F atoms along with OH surface terminations on H@BTO, facilitating hydrogen bonding within the PVDF matrix, resulting in dipole alignment and increased spontaneous polarization. The composite film achieves an 86.69% β phase content and a piezoelectric coefficient of ≈14.49 pm V−1 without electric polarization. The freeze‐drying PVDF‐H@BTO composite film paired with a PA6 membrane is used to fabricate triboelectric nanogenerator, demonstrating a current density of ≈107.5 mA m−2 and an output voltage of ≈832 V. Results demonstrate that the utilization of strong binding interactions between various atoms, the hydroxyl anchoring effect, and directional freeze‐drying method as a strategy holds promising prospects for synthesizing high‐performance piezoelectric composites.

Pakistan has a conducive condition for the development of a wide range of scrumptious fruits. As a result, the country grows a diverse assortment of tropical and subtropical fruits; the most prized and top-ranked fruit among all fruits grown in Pakistan is citrus. Citrus is the principal fruit that contributes significantly to Pakistan’s export earnings and national income. In this study, the cross-border determinants influencing Pakistan’s citrus exports to its topmost 22 trading partners are examined using a gravity model technique. This is the first large study from Pakistan by using gravity model to check the impact of various cross-border factors on citrus fruit export. The analysis is based on a panel dataset covering the years 2003 to 2021. To estimate the results, the study used fixed effect regression with time and country fixed effects. The results signify that per capita income, population, and some regional dummies are positively associated with citrus exports from Pakistan. Citrus price, distance, exchange rate, and other regional dummies are observed to have an adverse effect on citrus exports. Trade agreements between Pakistan and trade partners such as free trade agreements, preferential trade agreements, and SAFTA, have been observed as important determinants of citrus exports. Citrus exporters in Pakistan can also benefit from understanding the factors that influence export markets. By addressing the challenges identified in this study, Pakistan can enhance its citrus exports and boost its agricultural sector.

The food sector produces immense amounts of waste daily, which is a great threat to the food system's sustainability. The great volume of waste generated by the food sector is a valuable source of different essential substances. The conversion of tonnes of waste into valuable substances by using various innovative ‘green’ technologies is a novel approach. Ohmic heating is a sustainable and green technology based on the utilization of electric energy, which is converted into thermal energy to heat the substance. It has wide-ranging applications in the food sector, particularly for processing i.e. as pasteurization, sterilization, blanching, extraction, and many more. It is a high energy-efficient technology, which requires less processing time and allows precise control of temperature, which makes it suitable for various purposes. Ohmic heating-assisted extraction (OHAE), an innovative approach, presents an opportunity to extract numerous valuable substances from waste materials by the application of electric current. This review provides a critical assessment of investigations centered on the recovery of various substances by the implementation of OHAE from waste materials of fruits, vegetables, poultry, fish, and cereals. The impact of various parameters used in OHAE on the effectiveness of the extraction process and yield of extracted products are discussed. The substances extracted from these waste materials encompass bioactive compounds, pectin, essential oils, proteins, and cellulose fibers, all of which find substantial applications in the food and related industries. Overall, the implementation of ohmic heating, either alone or in combination with other novel technologies, is very effective for the extraction of valuable substances from the waste of the food industries.

Objective: To evaluate the effectiveness of the Modified Kenneth Jones Scoring System as a screening tool for diagnosing pulmonary tuberculosis in children. Methodology: A cross sectional study was conductedto assess the symptoms of tuberculosis among 100 pediatric patients with male to female ratio was 67:33. through Modified Kenneth Jones Scoring System (MKJSC) at Gulab Devi Tertiary Care Hospital, Lahore from June-December, 2022. The study included symptoms based on gender, drug usage and microbial load. Patients diagnosed with TB were included in this study to assess the system's effectiveness in identifying specific symptoms and clinical manifestations of TB. This inclusion allowed for a comprehensive evaluation of the MKJSC's diagnostic accuracy and its potential utility in early detection and intervention in pediatric TB cases. The Data was analyzed using SPSS to identify specific symptoms. Results: The Modified Kenneth Jones Criteria diagnosed 65 patients out of 100 with one false positive. The sensitivity for TB detection was 84.2% (95% CI: 73.6% - 91.2%), specificity was 95.8% (95% CI: 76.8% - 99.7%), positive predictive value was 98.4% (95% CI: 90.5% - 99.9%), and negative predictive value was 65.7% (95% CI: 47.7% - 80.3%). Statistical analysis with 5% confidence interval revealed a medium of age of 73 months and a mode of 120 months among patients. While cough prevalence varied, all patients had a history of prolonged fever. Meningeal irritation was observed in 52% of participants and 77% had contact with TB patients. Other findings included malnutrition 50%, pneumonia 48% and BCG screening 24%. Conclusion: The Modified Kenneth Jones Scoring System demonstrated high sensitivity and specificity in detecting tuberculosis, outperforming previous methods. It proves to be an effective tool in resource-limited healthcare settings for diagnosing TB in children.

Neuroscience is a swiftly progressing discipline that aims to unravel the intricate workings of the human brain and mind. Brain tumors, ranging from non-cancerous to malignant forms, pose a significant diagnostic challenge due to the presence of more than 100 distinct types. Effective treatment hinges on the precise detection and segmentation of these tumors early. We introduce a cutting-edge deep-learning approach employing a binary convolutional neural network (BCNN) to address this. This method is employed to segment the 10 most prevalent brain tumor types and is a significant improvement over current models restricted to only segmenting four types. Our methodology begins with acquiring MRI images, followed by a detailed preprocessing stage where images undergo binary conversion using an adaptive thresholding method and morphological operations. This prepares the data for the next step, which is segmentation. The segmentation identifies the tumor type and classifies it according to its grade (Grade I to Grade IV) and differentiates it from healthy brain tissue. We also curated a unique dataset comprising 6,600 brain MRI images specifically for this study. The overall performance achieved by our proposed model is 99.36%. The effectiveness of our model is underscored by its remarkable performance metrics, achieving 99.40% accuracy, 99.32% precision, 99.45% recall, and a 99.28% F-Measure in segmentation tasks.

Rearing camels in intensive production systems started in the last 20 years. This led to a considerable change in camel feeding and nutrition including the use of new feeds (i.e. gains, agricultural by-products, supplements). Therefore, research was conducted to determine the effect of using these feeds in camel meat and milk production. The existing studies on camel feeding and nutrition are scattered and lack both an appraisal and comprehensive summary. This systematic review analyses the ability of published feeding and nutrition studies to guide researchers, extension workers, and farmers in formulating rations for smart feeding of camels. The Web of Science database was used to collect all published and peer-reviewed articles on the effects of feeding options on camel meat and milk production using the following Boolean: camel AND (milk OR growth OR meat). The first search yielded 2475 unique entries. Screening of the title shortlisted 278 relevant articles and the summary and full text assessment identified 41 relevant articles (27 fattening studies and 14 milk production studies) that were reviewed in depth. The experimental diets in only two studies (out of 41 studies) were formulated considering camel feeding standards. It is concluded that the published peer-reviewed literature in the field of camel nutrition is limited in both quantity and quality in informing the camel production sector to design rations for smart feeding for meat and milk production.

Background: As humans are gifted by a defense system, Plants also possess a specialized system of defense that helps them to combat attacking microorganisms and harsh environmental conditions. This defense system is in the form of secondary metabolites that are present in the form of antimicrobial peptides. Antimicrobial peptides are specialized cysteine rich residues that play their marked protective role in plant defense systems. Material methods: In this study, we have extracted antimicrobial peptides from seeds and roots of three medicinal plants Ricinus communis, Cassia fistula, and Acacia nilotica. Extraction was carried out in two pharmaceutical buffers Tris NaCl and PBS buffer. Results: Results indicated that the extracts with PBS buffer without freeze thaw yield more concentrations of 2353 μg/ml, 1508 μg/ml, and 1553 μg/ml of proteins in Cassia fistula roots, Ricinus communis (seeds), and Cassia fistula (seeds) respectively. These concentrations were higher than the proteins extracted by Tris NaCl and PBS buffer with freeze thaw cycles. Conclusion: Extraction of these peptides from important medicinal plants and incorporating them in other plants with lesser immunity, can boost the immune system of receptive plants.

Abstract Background Zinc (Zn) and nickel (Ni) are nutrients that are crucial for plant growth; however, when they are present at higher concentrations, they can cause toxicity in plants. The present study aimed to isolate plant growth promoting endophytic bacteria from Viburnum grandiflorum and assess its plant and defense promoting potential alone and in combination with RP in zinc (Zn) and nickel (Ni) toxic soil. The isolated endophytic bacteria were identified using 16s rRNA gene sequencing. For the experiment, twelve different treatments were applied using Zn, Ni, isolated endophytic Bacillus mycoides (Accession # MW979613), and rock phosphate (RP). The Ni, Zn and RP were used at the rate of (100 mg/kg) and (0.2 g/kg) respectively. A pot experiment with three replicates of each treatment was conducted using a complete randomized design (CRD). Results The results indicated that Ni (T5 = seed + 100 mg/kg Ni and T9 = seed + 100 mg/kg Zn) and Zn concentrations inhibited plant growth, but the intensity of growth inhibition was higher in Ni-contaminated soil. Bacillus mycoides and RP at 100 mg/Kg Zn (T12 = inoculated seed + 100 mg/kg Zn + RP0.2 g/kg.) increased the shoot length, leaf width, protein and sugar content by 57%, 13%, 20% and 34%, respectively, compared to the control. The antioxidant enzymes superoxide dismutases (SOD), peroxidase (POD) were decreased in contaminated soil. Furthermore, Ni and Zn accumulation was inhibited in T11 (seed + 100 mg/kg Zn + RP0.2 g/Kg) and T12 (inoculated seed + 100 mg/kg Zn + RP0.2 g/Kg) by 62 and 63% respectively. The Cu, Ca, and K, contents increased by 128, 219 and 85, Mn, Na, and K by 326, 449, and 84% in (T3 = inoculated seed) and (T4 = inoculated seed + RP 0.2 g/Kg) respectively. Conclusions Ni was more toxic to plants than Zn, but endophytic bacteria isolated from Viburnum grandiflorum, helped wheat (Triticum aestivum) plants and reduced the toxic effects of Ni and Zn. The effect of Bacillus mycoides was more prominent in combination with RP which promoted and suppressed heavy-metal toxicity. The reported combination of Bacillus mycoides and RP may be useful for improving plant growth and overcoming metal stress.

A novel idea called bipolar complex fuzzy set makes it simple to represent difficult and ambiguous information in practical issues. Confidence levels, bipolar fuzzy set, and complex fuzzy set are three distinct theories that were combined to form the basic theory of the Confidence levels bipolar complex fuzzy set. Confidence levels bipolar complex fuzzy set (CLBCFS)is used as a method for resolving perplexing and suspect circumstances that occur in daily life. In this article, we define idea of bipolar complicated fuzzy collection of confidence levels. To do this, we developed a number of operational laws. Further, utilizing bipolar complex fuzzy operational laws, we diagnose the theories of confidence level bipolar complex fuzzy averaging and geometric operators. We reviewed some significant findings and some features of the developed operators in order to reduce the impact of this study. In addition, we computed a multiple-attribute decision-making rule while the initiated approaches were present and attempted to support it with specific examples. Finally, we contrasted our defined work with numerous prevalent methodologies and also detailed their geometrical representations in order to assess the influence and supremacy of the defined work.

In this research study, a metamaterial (MTM) based $1\times4$ linear antenna array is designed with an integrated butler matrix (BM) beamforming network (BFN) to execute the switched-beam antenna array (SAA) operation, which can be employed for sub-6 GHz 5G applications. The proposed SAA is designed and simulated using CST microwave studio and then fabricated using FR4 epoxy glass substrate with the thickness ( $h$ ) = 1.6mm and dielectric constant ( $\varepsilon _{r}$ ) = 4.3. The MTM-BM BFN has shown excellent performance in both simulated and measured results, having return-loss of below 14 dB and insertion-loss at ports 5–8 to be 7 ± 2dB between the frequency range of 3.2-3.75GHz, respectively. Moreover, the phase difference between the output ports of the BM is simulated and measured. The $0.5\lambda $ spaced complementary split-ring resonator (CSRR) based antenna array integrated with MTM-BM BFN achieved a measured gain of 4.8-6.1 dB when each input port of BM was excited. The SAA analysis has been performed to identify the variation of gain and grating lobes; the distance between MTM antennas was altered by $0.3\lambda $ , $0.5\lambda $ , and $0.7\lambda $ , respectively. Depending on the BM input ports excitation, the main beam of the SAA is steered in four different directions −40°, −15°, +15°, and +45°, respectively. These radiation pattern studies have shown that the MTM-BM connected with four linear MTM antennas has successfully generated four beams in four different directions, which can be utilized for 5G applications to improve the channel capacity and enhance the transmission quality.

Advances in deep reinforcement learning have made it possible to create artificial intelligence-based agents for games that use visual information to make decisions as accurately as humans. Novel procedures are often evaluated in two-dimensional games. However, they are relatively easy compared to three-dimensional games, which have a significantly larger state and action space and, more prominently, contain partially observable states. Thus, this paper trains agents with different reinforcement learning algorithms that work fine in contradiction of human players and in-built agents by evaluating them in the first-person shooter (FPS) game Doom using the VizDoom platform. The agents learned in three different scenarios (maps): ’ Defend the Center,’ ‘Deadly Corridor,’ and ‘Health gathering.’ C51-DDQN, DFP, and REINFORCE algorithms have been proven effective in this study. To assess how well the trained agents performed using various reinforcement learning algorithms, we compared the results of our research with other findings in the literature. Finally, this paper presents a comparative analysis and future research directions.

Abstract Maize (Zea mays) is an influential crop in its production across the world. However, the invasion of many phytopathogens greatly affects the maize crop yield at various hotspot areas. Of many diseases, bacterial stalk rot of maize caused by Dickeya zeae results in severe yield reduction, thus the need for efficient management is important. Further, to produce epidemiological information for control of disease outbreaks in the hot spot regions of Sialkot District, Punjab Pakistan, extensive field surveys during 2021 showed that out of 266 visited areas, the highest disease incidence ranging from 66.5 to 78.5% while the lowest incidence was ranging from 9 to 20%. The Maxent modeling revealed that among 19 environmental variables, four variables including temperature seasonality (bio-4), mean temperature of the wettest quarter (bio-8), annual precipitation (bio-12), and precipitation of driest month (bio-14) were significantly contributing to disease distribution in current and coming years. The study outcomes revealed that disease spread will likely increase across four tehsils of Sialkot over the years 2050 and 2070. Our findings will be helpful to policymakers and researchers in devising effective disease management strategies against bacterial stalk rot of maize outbreaks in Sialkot, Pakistan.

In recent eras, the complexity and fluctuations of the global crude oil prices have affected the economic progress of society. It is therefore, the oil price prediction has hauled the attention of scholars and policymakers. Driven by this critical concern for forecasting of crude oil prices, we introduces a novel hybrid model keeping in mind the primary objective of enhancing prediction accuracy while considering the specific characteristics as inherent in the data. To achieve this achievement, the trend is eliminated, allowing the scrutiny of whether the residual component validates the assurance of a series ran by stochastic trends. Following the removal of the trend, the residual component undergoes rigorous evaluation through autoregressive model following the decomposition model. Then we got support from the support vector machine, autoregressive integrated moving average and long-short term memory. The predictions accuracy can be evaluated by using the various performance metrics. The proposed hybrid model’s robustness and forecasting performance are rigorously evaluated through Diebold-Mariano test in comparison to competing models. Furthermore, the forecasting ability is evaluated via directional forecast. Ultimately, the empirical findings explicitly determine the superior predictive capabilities of the proposed hybrid model over alternative approaches.

Real-time audio/video transmission through Internet media is an important part of communication. Due to bandwidth limitations and a noisy environment, delivery of multimedia content to a remote location is not 100% guaranteed. These limitations are the basic cause of missing packets which affect the Quality of Service (QoS). A protocol for the recovery of lost packets is described in [Maxemchuk, Nicholas F., K. Padmanabhan, and S. Lo. “A cooperative packet recovery protocol for multicast video.” Network Protocols, 1997. Proc. of 1997 International Conference on. IEEE]. This protocol claims significant improvement in QoS. We formally specify the protocol in a network of timed automata. By model-checking (A mathematical technique), we find that packet recovery is not always there. In this article, We report such scenarios of malfunctioning in the protocol when the size of multimedia contents is known (e.g., live video/audio broadcasting) and middle-level servers have different rates of data sending and receiving. We formulate the effect of inter-packet delay and transmission speed difference on a buffer.

Abstract In this research, we analyze the complex dynamics of hydro-magnetic flow and heat transport under Sorent and Dofour effects within wedge-shaped converging and diverging channels emphasizing its critical role in conventional system design, high-performance thermal equipment. We utilized artificial neural networks (ANNs) to investigation the dynamics of the problem. Our study centers on unraveling the intricacies of energy transport and entropy production arising from the pressure-driven flow of a non-Newtonian fluid within both convergent and divergent channel. The weights of ANN based fitness function ranging from − 10 to 10. To optimize the weights and biases of artificial neural networks (ANNs), employ a hybridization of advanced evolutionary optimization algorithms, specifically the artificial bee colony (ABC) optimization integrated with neural network algorithms (NNA). This approach allows us to identify and fine-tune the optimal weights within the neural network, enabling accurate prediction. We compare our results against the established different analytical and numerical methods to assess the effectiveness of our approach. The methodology undergoes a rigorous evaluation, encompassing multiple independent runs to ensure the robustness and reliability of our findings. Additionally, we conduct a comprehensive analysis that includes metrics such as mean squared error, minimum values, maximum values, average values, and standard deviation over these multiple independent runs. The minimum fitness function value is 1.32 × 10−8 computed across these multiple runs. The absolute error, between the HAM and machine learning approach addressed ranging from 3.55 × 10−7 to 1.90 × 10−8. This multifaceted evaluation ensures a thorough understanding of the performance and variability of our proposed approach, ultimately contributing to our understanding of entropy management in non-uniform channel flows, with valuable implications for diverse engineering applications.

Abstract This manuscript proposes the concept of Schweizer–Sklar operational laws under the consideration of the complex interval-valued intuitionistic fuzzy (CIVIF) set theory, where the Schweizer–Sklar norms are the essential and valuable modification of many norms, such as algebraic, Hamacher, and Lukasiewicz norms. Moreover, keeping the dominancy of the presented laws, we derive the concept of CIVIF Schweizer–Sklar power averaging (CIVIFSSPA), CIVIF Schweizer–Sklar power ordered averaging (CIVIFSSPOA), CIVIF Schweizer–Sklar power geometric (CIVIFSSPG), and CIVIF Schweizer–Sklar power ordered geometric (CIVIFSSPOG) operators, which are the combination of the three different structures for evaluating three different problems. Further, some reliable and feasible properties and results for derived work are also invented. Additionally, we also illustrate an application, called multi-attribute decision-making (MADM) scenario for evaluating some real-world problems with the help of discovered operators for showing the reliability and stability of the evaluated operators. Finally, we compare our mentioned operators with various prevailing operators for enhancing the worth and stability of the evaluated approaches.