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Electrochromic (EC) thin films have received considerable attention due to their potential applications in various fields such as smart windows, electrochromic displays, and energy storage devices. This review highlights various methods used for the fabrication and functionalization of EC films for various applications. Various techniques for EC thin film deposition ranging from solution-processable, low-temperature approaches such as sol-gel, spin coating, dip coating, and spray pyrolysis, to advanced techniques for deposition such as physical vapor deposition, chemical vapor deposition, and sputtering are summarized in this review. In addition, various applications of EC thin films and the outcome of different deposition approaches on the opto-electrochromic properties of EC thin films have been discussed elaborately. This review has the potential to spark the interest of researchers from a broad range of disciplines, including photocatalysis, electrocatalysis, nanotechnology and materials science.

For many years, Pakistan’s economic progress and development have primarily depended on agriculture. However, widespread rural poverty impairs agricultural productivity, which worsens the outlook for growth for both the agricultural sector and the nation as a whole. Raising farmers’ incomes through rural development is a key component of agricultural reform, and the prime objective of this study is to identify how government policies and foreign aid affect Pakistan’s degree of rural poverty. This research aims to check the mediating role of rural development for the relationship of foreign aid, agricultural production, and corporate social responsibility with poverty reduction. This research also examines the moderating role of government support in the relationship of rural development with poverty reduction. In this regard, the current study proposes four hypotheses of direct relationships, three mediating relationships, and one moderating relationship. The population comprised farmers. The sample size of 119 was determined using G*Power with medium effect size settings, ensuring a robust representation of the target group. To gather primary data, a close-ended structured questionnaire was administered, employing a 7-point Likert scale to gather respondents’ opinions. This study investigates the Punjab province’s agricultural landscape from a quantitative perspective, using convenient sampling to identify the characteristics that contribute to reducing poverty, and was conducted from January to December 2023. Analytical procedures utilizing Smart PLS 4.0.9.6 for SEM testing reveal that all proposed hypotheses, including direct, mediating, and moderating, are accepted. The main results show that rural development significantly mediates the relationship between foreign aid, agricultural production, and corporate social responsibility with poverty reduction. Furthermore, government support positively moderates the relationship between rural development and poverty reduction. The findings underscore the significance of rural development, coupled with government support, as a pivotal factor in effectively reducing poverty in Pakistan’s economic landscape.

Entrepreneurship drives economic growth in the modern knowledge-based economy. Furthermore, entrepreneurial orientation (EO) and small and medium-sized enterprises (SMEs) Efficiency, combined with government financial and non-financial incentives, play a vital role in fostering the growth of SMEs. Therefore, this study aims to investigate the impact of EO with government incentives as moderators on SMEs efficiency from the perspective of Pakistan. The primary data were collected from 412 top-level managers of SMEs across three cities. A structural equation modeling was used for analysis. Results showed that risk-taking, innovativeness, and proactiveness had a positive and significant impact on SMEs efficiency, and autonomy had a negative and significant impact. It was found that government financial incentives had a significant positive moderating impact on risk-taking, proactiveness, and competitive aggressiveness. Moreover, government non-financial incentives as a moderating variable positively and significantly influenced risk-taking, proactiveness, innovativeness, and competitive aggressiveness. The positive and significant impact of government financial incentives on risk-taking, proactiveness, and competitive aggressiveness emphasizes the potential to amplify SMEs efficiency and growth through enhanced promotion of such incentives. Governments should deliberate on delivering more targeted financial support to encourage entrepreneurial activities. Complementary to this, government non-financial incentives positively and significantly influenced key entrepreneurial factors such as risk-taking, proactiveness, innovativeness, and competitive aggressiveness. Consequently, augmenting SMEs efficiency and competitiveness can be achieved by implementing non-financial incentives such as mentorship programs, technological access, and market insights.

This present study reports the biogenic synthesis of silver nanoparticles (AgNPs), gold nanoparticles (AuNPs) and Ag/Au bimetallic nanoparticles (BNPs) using bark extract of plant Tamarix aphylla (T.A). The bark extract contained total polyphenolic compounds and total flavonoids as 0.0362 mg/mg and 0.2928 mg/mg of the dried bark extract respectively. Silver nitrate (AgNO3) and hydrogen tetra chloroaurate trihydrate (HAuCl4.3H2O) were used as precursors while deionised water and methanol (CH3OH) were used as solvents. Synthesized nanoparticles were characterized through UV–visible spectroscopy, SEM (scanning electron microscopy), TEM (transmission electron microscopy) and FTIR (Fourier transform infrared) for their morphology, structure, and identification of different functional groups. The UV–visible spectra of AgNPs, AuNPs and Ag/Au BNPs showed peaks at 436, 532 and 527 nm respectively due to the excitation of Surface Plasmon Resonance. SEM and TEM images showed spherical and well distributed nanoparticles (NPs) with particle size as 29 nm (AgNPs), 13 nm (AuNPs) and 26 nm (Ag/Au BNPs). The synthesized NPs are significantly active against inhibition of free radicals, α-amylase, α-glucosidase and have anti inflammatory potential with AgNPs having the highest percent activity at 400 μg/ml, followed by Ag/Au BNPs. The same trend (AgNPs > Ag/AuBNPs > AuNPs) has been observed at all concentrations i.e. 100 μg/ml, 200 μg/ml and 400 μg/ml. AuNPs have shown lowest activity at all concentrations. So the current study strongly confirms use of T.A bark extract as reducing agent for synthesis of metal NPs and opens up a new possibility of using these green synthesized NPs as biomedicines. We also suggest further in vivo investigation to report any side effects if present.

Abstract Background Klebsiella pneumoniae is a major bacterial and opportunistic human pathogen, increasingly recognized as a healthcare burden globally. The convergence of resistance and virulence in K. pneumoniae strains has led to the formation of hypervirulent and multidrug-resistant strains with dual risk, limiting treatment options. K. pneumoniae clones are known to emerge locally and spread globally. Therefore, an understanding of the dynamics and evolution of the emerging strains in hospitals is warranted to prevent future outbreaks. Methods In this study, we conducted an in-depth genomic analysis on a large-scale collection of 328 multidrug-resistant (MDR) K. pneumoniae strains recovered from 239 patients from a single major hospital in the western coastal city of Jeddah in Saudi Arabia from 2014 through 2022. We employed a broad range of phylogenetic and phylodynamic methods to understand the evolution of the predominant clones on epidemiological time scales, virulence and resistance determinants, and their dynamics. We also integrated the genomic data with detailed electronic health record (EHR) data for the patients to understand the clinical implications of the resistance and virulence of different strains. Results We discovered a diverse population underlying the infections, with most strains belonging to Clonal Complex 14 (CC14) exhibiting dominance. Specifically, we observed the emergence and continuous expansion of strains belonging to the dominant ST2096 in the CC14 clade across hospital wards in recent years. These strains acquired resistance mutations against colistin and extended spectrum β-lactamase (ESBL) and carbapenemase genes, namely bla OXA-48 and bla OXA-232, located on three distinct plasmids, on epidemiological time scales. Strains of ST2096 exhibited a high virulence level with the presence of the siderophore aerobactin (iuc) locus situated on the same mosaic plasmid as the ESBL gene. Integration of ST2096 with EHR data confirmed the significant link between colonization by ST2096 and the diagnosis of sepsis and elevated in-hospital mortality (p-value

AbstractThe fields of agronomy and pesticides have assumed significant roles in contemporary society. Pesticides can have adverse effects on human health, both in the short and long term. We have conducted a comprehensive analysis of the various categories of pesticides, providing a thorough examination of their modes of operation, prevalence, and global utilization. A critical review of reported research has been conducted to investigate the carcinogenic effects of agricultural pesticide use on human health. The widespread utilization of malathion and parathion for pest management indicates that individual occupational choices significantly impact their exposure to these chemicals. Pesticides can cause neurological abnormalities, reproductive problems, respiratory irritations, ecological disturbance, and the emergence of pest resistance, among other sublethal consequences beyond their carcinogenicity (breast cancer, lymphomas, multiple myeloma, bladder cancer, and leukemia). Ultimately, there is an anticipation for a forthcoming surge in endeavors to mitigate the utilization of hazardous pesticides and the consequent peril they pose to human well-being and the ecosystem.

ABSTRACTThe quality of water significantly affects the health and walefare of all orginisms, highlighting the importance to develop low-cost and efficient wastewater treatment methods. Herein, we report the fabrication, characterization, and utilization of a polymer-based ternary nanocomposite (CuO–SiO2/PVA) for the removal of Nile Blue (NB) and Methylene Blue (MB) contaminants from wastewater, along with exploring its potential biological activities. We have successfully employed the cost-effective sol–gel and in-situ polymerization approaches to fabricate the CuO–SiO2/PVA based ternary composite, utilizing Cu(NO3)2·3H2O:Glycerol:TEOS:PVA in a ratio of 8:2:3:4. The desired fabrication of nanocomposite was confirmed through UV-Visible spectroscopy, SEM (scanning electron microscope), TEM (transmission electron microscope), EDX (energy dispersive X-ray diffraction), FTIR (Fourier transform infrared), DSC (differential scanning calorimetry), and TGA (thermogravimetric analysis). In addition to its biological potentialthe performance of the nanocomposite in catalytic / photocatalytic removal of NB and MB dyes is investigated and compared. The higher photodegradation performance of the composite for NB (85%) dye than for MB (76%) dye indicates that variables such as chemical structure, charge, molecular mass, and pH sensitivity of the dyes can influence the catalyst's removal potential. This composite is considered to have a higher capability for removing pollutants and microorganisms from wastewater.

This article presents the notion about Slow Invariant Manifold (SIM) and their fundamental role in model reduction techniques (MRTs) for challenges encountered in mechanical engineering within dissipative systems of chemical kinetics. Focusing on the reaction routes of complex mechanisms, we construct and compare primary approximations of the SIM through MRTs, including the Spectral Quasi Equilibrium Manifold (SQEM) and Intrinsic Low Dimensional Manifold (ILDM). These methods effectively transform high-dimensional complex problems into lower dimensions, solving them without compromising crucial information about the complex systems modified for homogeneous reactive systems. Employing the sensitivity analysis by using the MATLAB's toolbox, we present the numerical findings in a tabular format obtained through MRTs. This study provides the understanding about the accessible exploration of numerical solutions, improving insights of the complex variation within the system.

Supervisory feedback to stimulate research and development (R&D) employee creativity is a management issue that concerns scholars and practitioners. However, there are divergences and contradictions regarding whether negative feedback promotes or hinders employee creativity. Integrating the feedback intervention and cognitive appraisal theories, we developed a double-edged sword model for negative supervisory feedback's influence on creativity. We tested the proposed model using a field sample of 513 R&D employees from seven science and technology enterprises. The results indicated that R&D employee challenge and threat appraisal moderated negative supervisory feedback's effect on prevention focus and the distal consequences for creativity. Individuals with high (low) levels of challenge (threat) appraisal have decreased prevention focus, thereby increasing their creativity when receiving negative supervisory feedback. In contrast, individuals with low (high) challenge (threat) appraisal have increased prevention focus, thereby decreasing their creativity when receiving negative supervisory feedback. These findings offer interesting implications for research on negative feedback and stimulation of science and technology R&D employee creativity in organizations.

This study employs a Model Reduction Technique (MRT) to simplify the four-step catalytic carbon monoxide (CO) oxidation reaction. The C-matrix method identifies key elements, key/non key components, and key reactions, while the Intrinsic Low-Dimensional Manifold (ILDM) pinpoints a Slow-Invariant Manifold (SIM) important for understanding key species behavior. Sensitivity analysis can be considered for measuring the efficiency of the chemical species in detailed mechanism. This systematic approach contributes to optimizing and controlling complex reactions offering broad application potential. In addition to the mathematical proof, the validation of the given chemical model is rectified. The comparison between the slow invariant manifold of both reaction routes is reported and the computational based results performed in this study are obtained through MATLAB.

As conventional kiwifruit production began to face sustainability challenges, the adoption of the green food certification (GFC) has emerged as an eco-innovative solution to promote sustainable production practices beneficial to the environment and farming communities. However, the implementation of this sustainable alternative has stagnated. Therefore, this research investigated the factors influencing the adoption and intergenerational gaps in the adoption of the GFC based on a primary survey with 404 farmers in the major kiwifruit production belt of China. To ensure disaggregated analyses through bivariate Probit, kiwifruit farmers' adoption was divided into two stages: adoption willingness and adoption behavior. The results revealed that the common factors influencing both the willingness and adoption of GFC were farmers' participation in training, education, farm labor, perceived benefits, perceived risk, and farmers' access to information through organizational, farmer, and network channels. The factor specifically affecting the willingness was perceived cost, while age of kiwi trees affected the farmers’ adoption behavior. Furthermore, the research findings demonstrated significant intergenerational gaps in the factors affecting the willingness and behavior to adopt the GFC. Therefore, it is crucial to promote the GFC through institutional support that can organize training programs, increase awareness of the benefits of GFC, and broaden information channels across generations.

In this study, different metal hydroxyapatite (HAP) nanoparticles were synthesized at a laboratory scale. All the methods used were very economical because all reagents used in this work were cheap and easily available in laboratories. The synthesized products were characterized by X-ray diffractometer (XRD), Brunauer–Emmett–Teller and Barrett–Joyner–Halenda, scanning electron microscopy, and Fourier transform infrared spectroscopy analysis to confirm the synthesis of respective products by ensuring the presence of phosphate and hydroxyl functional groups. These metal HAP nanoparticles were applied in water treatment applications as adsorbents for the elimination of turquoise blue dye from the aqueous solution. Batch experiments were performed, and all effective parameters were optimized. Their optimized values were as follows: pH = 8, dosage of adsorbent = 0.05 g, contact time = 75 min, temperature = 30 °C, and dye concentration = 75 ppm. The order of adsorption capacity of four different metal HAP products was determined as calcium-HAP (Ca-HAP) > lead-HAP (Pb-HAP) > strontium-HAP (Sr-HAP) > barium-HAP (Ba-HAP). Ca-HAP, Ba-HAP, Sr-HAP, and Pb-HAP have the highest concentration of 0.5 N, giving 54–69.29% desorption. Moreover, the effect of surfactants and electrolytes was also studied. Langmuir isotherm and pseudo-second-order kinetic model were best fitted for turquoise blue dye adsorption. The reaction was exothermic and spontaneous in nature. HIGHLIGHTS Synthesis of nano metal hydroxyapatite (HAP) by the wet precipitation method.; Applications of HAP as a useful material in turquoise blue dye adsorption.; The order of adsorption capacity of four different metal HAP products was determined as Ca-HAP > Pb-HAP > Sr-HAP > Ba-HAP.; The Langmuir model and pseudo-second-order kinetic model were best fitted.;

The onset of the COVID-19 pandemic has significantly disrupted the traditional pedagogical educational system worldwide. The story of Pakistan is also not different from that of the rest of the world. Pakistan’s higher education institutes were closed for classes due to the outbreak. Some universities started the virtual education system, and it is critically important to assess the behavioral intentions of university students toward online education during the COVID-19 pandemic in Pakistan. This is the first study investigating students' responses to online education during the COVID-19 pandemic. For this purpose, an online survey was conducted to obtain the students' responses from the higher institutions providing online classes during COVID-19. The results were evaluated using multivariate analysis and descriptive statistics. It was observed that there is a significant difference between male and female students concerning the positive consequences of COVID-19 on students. According to the findings, the students' intentions for online education are more concerned with saving time to complete the degree program. Higher education institutions should also provide online educational opportunities to students besides traditional physical modes. Online educational interventions will be helpful for students during unavoidable circumstances like political instabilities, natural disasters, viral disease outbreaks, etc. to complete degrees and diplomas. Doi: 10.28991/ESJ-2024-SIED1-02 Full Text: PDF

Cervical spine fractures are a medical emergency that can cause permanent paralysis and even death. Traditional fracture detection techniques, such as manual radiography image interpretation, are time-consuming and prone to human error. Deep learning algorithms have shown promising results in various medical imaging applications i.e., disease diagnosis, including fracture detection of bones. In this study, we propose a two-stage approach for detecting cervical spine fractures. The first stage employs a convolutional neural network (CNN) model to determine the presence or absence of a fracture in the cervical spine, using a dataset of cervical spine Computed Tomography (CT) scan images as well as Grad-CAM for enhanced visualization and interpretation. In the second stage, our focus shifts to specific vertebrae within the cervical spine. To accomplish this task, we trained and evaluated the performance of the YOLOv5 and YOLOv8 models with 9170 images consisting of seven vertebrae. The detection results of both YOLO versions are compared and evaluated. The precision, recall, mAP50, and mAP50-90 were 0.900, 0.890, 0.935, 0.872, respectively. The results of this research demonstrate the potential of deep learning-based approaches for cervical spine fracture detection. By automating the detection process, these algorithms can assist radiologists and healthcare professionals in making accurate and timely diagnoses, leading to improved patient outcomes.

ABSTRACT: This study assessed the adoption level of essential oil extraction practices among lemon growers in the Pothwar region of Punjab, Pakistan. A well-structured questionnaire was used to collect data from 138 smallholders using the interview method by trained remunerators. Descriptive statistics and econometrics; logit and Poisson regression were employed for data analysis. Results of farmers’ perceptions of adopting new practices indicated that 10.1% of the farmers are not adopting any one, 22.5% are adopting any three, and 26.8% are adopting all four practices. Moreover, farmers’ age, farming experience, land holding, skill, training participation, and receptivity proved to be statistically significant determinants in improving the likelihood of adopting all four practices under the logit and Poisson models, respectively. Hence, it is recommended that the provision of an effective package in the form of literature concerning essential oil extraction practices to the doorsteps of smallholders during demonstration sessions, along with adequate professional training, could help in improving farmers’ perceptions toward adoption and strengthening the essential oil sector.

This study aims to achieve the computational results for the oxidation of carbon monoxide using the spectral quasi-equilibrium manifold and the intrinsic low-dimensional manifold techniques, enabling the identification of the slow invariant manifold and subsequent simulation of the solutions. In addition, the application of Gibbs’ rule facilitates the reduction of the system, thereby effectively transforming higher dimensions into lower dimensions, ultimately revealing the underlying 1D manifold dynamics. This research serves to elucidate the intricacies of phase-shifting behaviors in the context of key species within the overarching and interconnected multi-step reaction mechanisms, contributing significantly to the advancement of understanding in this complex field.

In this work, we present the analytical closed forms of the Balaban index for anthracene and catacondensed benzenoid systems using group theoretic techniques. The Balaban index is a distance-based topological index that provides valuable information about the properties of chemical structures. We emphasize the importance of determining analytical closed forms of the Balaban index for catacondensed benzenoid systems and linear chains of anthracene, as it enables a deeper understanding of these systems and their behavior. Our analysis utilizes the group action of the automorphism group of these chains on the set of vertices, which refer to the points where the chains intersect. In future work, we plan to determine the Balaban index of other polymeric linear chains using group theoretic techniques and extend the applications of this index to other fields, such as materials science and biology. It is clear that the Balaban index remains a valuable tool in theoretical and computational chemistry, and its applications are constantly evolving.

The low solubility and enhanced fixation of zinc (Zn) in semi-arid and dry climates limits Zn uptake in plants. Zn deficiency in soil impairs crop production and human health, necessitating agricultural biofortification. A pot experiment was conducted to evaluate the effect of Zn and various types of manure on the Zn biofortification of lentils. The treatments, consisting of a control (Con), normal manure (NM), composted manure (CM), and acidified manure (AM), were applied under saline soil (EC 8.00 dS m−1) and non-saline soil (EC 1.48 dS m−1) conditions along with two levels of Zn, including Zn at 0 kg ha−1 (native soil Zn = 2.2 mg kg−1) and Zn at 25 kg ha−1 (62.2 mg Zn kg−1 soil was achieved). The AM was prepared by adding sulfur and sulfur-oxidizing bacteria to the composted manure. All the manures were applied at 1% (w/w), and ZnSO4 (33% Zn) was used as a Zn source. Lentil variety Masoor 2021 was cultivated as a test crop in five replications of each treatment arranged in a completely randomized design. Applying AM with Zn considerably increased the lentils’ growth, yield, and Zn content under saline and non-saline conditions. Under non-saline soils, the treatment of AM + Zn significantly promoted the Zn content in the root (132.5%), shoot (91.7%), grain (49.1%), root length (79.7%), plant height (33.7%), and SPAD value (29.9%). Under saline conditions, application of AM + Zn promoted uptake of Zn in the root (218.5%), Zn content in the shoot (175.7%), Zn accumulation in the grain (107.7%), root length (109.7%), plant height (37.8%), and SPAD value (52.8%) compared to the control. According to the results, lentils should be grown with AM and Zn to increase their growth, yield, and Zn content significantly. This is a cost-effective and sustainable way to combat Zn deficiency in lentils.

Abstract The non-biodegradable nature of waste emitted from the agriculture and industrial sector contaminates freshwater reserves. Fabrication of highly effective and low-cost heterogeneous photocatalysts is crucial for sustainable wastewater treatment. The present research study aims to construct a novel photocatalyst using a facile ultrasonication-assisted hydrothermal method. Metal sulphides and doped carbon support materials work well to fabricate hybrid sunlight active systems that efficiently harness green energy and are eco-friendly. Boron-doped graphene oxide-supported copper sulphide nanocomposite was synthesized hydrothermally and was assessed for sunlight-assisted photocatalytic degradation of methylene blue dye. BGO/CuS was characterized through various techniques such as SEM–EDS, XRD, XPS, FTIR, BET, PL, and UV–Vis DRS spectroscopy. The bandgap of BGO-CuS was found to be 2.51 eV as evaluated through the tauc plot method. The enhanced dye degradation was obtained at optimum conditions of pH = 8, catalyst concentration (20 mg/100 mL for BGO-CuS), oxidant dose (10 mM for BGO-CuS), and optimum time of irradiation was 60 min. The novel boron-doped nanocomposite effectively degraded methylene blue up to 95% under sunlight. Holes and hydroxyl radicals were the key reactive species. Response surface methodology was used to analyze the interaction among several interacting parameters to remove dye methylene blue effectively.

Corporate social responsibility (CSR) and technological innovation (TI) are two fundamental driving forces for sustainable development. The importance of the CSR-TI relationship has grown in prominence over recent years. This study is motivated by two research questions: (1) What makes the CSR-TI relationship conclusions different? (2) Which emerging themes in the literature will likely set the stage for future work? Using VOSviewer for co-occurrence analysis, this research examines 67 scholarly works in related research fields from 1996 to 2023 in 36 leading journals to answer these questions. This paper is a systematic literature review of the CSR-TI relationship from different perspectives. Addressing these two research questions helps us clarify the internal logic of the existing research in the CSR-TI relationship, deepens the understanding of the relationship between CSR and TI, and provides a glimpse of the future.

Objective: To find out the association of total ischemic time with no-reflow phenomenon, in terms of Thrombolysis in Myocardial Infarction (TIMI) flow grade, in patients presenting with ST-Elevation Myocardial Infarction and undergoing Primary Percutaneous Coronary Intervention(PPCI). Study Design: Analytical Cross-Sectional study. Place and Duration of Study: Armed Forces Institute of Cardiology/National Institute of Heart Diseases Rawalpindi Pakistan, from Nov, 2022 to Jan, 2023. Methodology: This analytical cross-sectional study was conducted on n=184 patients, recruited through consecutive sampling technique to collect data prospectively. Patients were divided into no-reflow and normal flow group. Patients’ total ischemic time was documented and pre & post-procedural TIMI flow was noted. SPSS version-24:00 was used to enter and analyze data. Chi-square, Fisher exact test and t-test were applied and p-value≤0.05 was taken as statistically significant. Results: Out of 184 study participants, 17(9.2%) were females as compared to 167(90.8%) males. The mean age was 60.23±10.28 years. No-reflow phenomenon was observed in 20(10.9%) patients. The mean age was higher in the no-reflow group than that of the normal flow group (62.65±11.61 vs 59.94±10.12 years). Total ischemic time, pre & post-procedural TIMI flow were found to be significantly associated with no-reflow phenomenon (p

The livestock sector plays a crucial role in sustaining the livelihoods of millions of families across the world, especially in developing countries. However, farming households that rely on agriculture and livestock are particularly susceptible to the impacts of various infectious diseases and natural disasters. This study focuses on estimating the economic burden imposed on households by lumpy skin disease (LSD) in Pakistan and explores the effect of various socioeconomic factors on mortality ratio. Data were collected through a questionnaire survey from 406 farmers and were analyzed through descriptive statistics to calculate the monetary losses. In addition, the study employed fractional probit regression to identify factors affecting mortality ratio. The results demonstrate significant economic impacts of LSD on farm households in Pakistan, leading to direct and indirect losses and reduced milk productivity. Exotic cows were found to be more susceptible to mortality compared to indigenous cows. The study also found that farmers’ education, experience, household income per month, vaccination, domestic-commercial, commercial animals, and access to information were negatively associated with mortality. The findings of this study emphasize the need for preventative measures such as affordable vaccines, treatment, and improved livestock health and welfare to mitigate the negative effects of LSD on farmers’ income and the local economy.

This research study describes the development of new small molecules based on 2,4-thiazolidinedione (2,4-TZD) and their aldose reductase (AR) inhibitory activities. The synthesis of 17 new derivatives of 2,4-TZDs hybrids was feasible by incorporating two known bioactive scaffolds, benzothiazole heterocycle, and nitro phenacyl moiety. The most active hybrid (8b) was found to inhibit AR in a non-competitive manner (0.16 µM), as confirmed by kinetic studies and molecular docking simulations. Furthermore, the in vivo experiments demonstrated that compound 8b had a significant hypoglycaemic effect in mice with hyperglycaemia induced by streptozotocin. Fifty milligrams per kilogram dose of 8b produced a marked decrease in blood glucose concentration, and a lower dose of 5 mg/kg demonstrated a noticeable antihyperglycaemic effect. These outcomes suggested that compound 8b may be used as a promising therapeutic agent for the treatment of diabetic complications.

This work explores the existence and uniqueness criteria for the solution of hybrid Caputo–Hadamard fractional sequential differential equations (HCHFSDEs) by employing Darbo’s fixed-point theorem. Fractional differential equations play a pivotal role in modeling complex phenomena in various areas of science and engineering. The hybrid approach considered in this work combines the advantages of both the Caputo and Hadamard fractional derivatives, leading to a more comprehensive and versatile model for describing sequential processes. To address the problem of the existence and uniqueness of solutions for such hybrid fractional sequential differential equations, we turn to Darbo’s fixed-point theorem, a powerful mathematical tool that establishes the existence of fixed points for certain types of mappings. By appropriately transforming the differential equation into an equivalent fixed-point formulation, we can exploit the properties of Darbo’s theorem to analyze the solutions’ existence and uniqueness. The outcomes of this research expand the understanding of HCHFSDEs and contribute to the growing body of knowledge in fractional calculus and fixed-point theory. These findings are expected to have significant implications in various scientific and engineering applications, where sequential processes are prevalent, such as in physics, biology, finance, and control theory.

The outbreak of SARS-CoV-2, also known as the COVID-19 pandemic, is still a critical risk factor for both human life and the global economy. Although, several promising therapies have been introduced in the literature to inhibit SARS-CoV-2, most of them are synthetic drugs that may have some adverse effects on the human body. Therefore, the main objective of this study was to carry out an in-silico investigation into the medicinal properties of Petiveria alliacea L. (P. alliacea L.)-mediated phytocompounds for the treatment of SARS-CoV-2 infections since phytochemicals have fewer adverse effects compared to synthetic drugs. To explore potential phytocompounds from P. alliacea L. as candidate drug molecules, we selected the infection-causing main protease (Mpro) of SARS-CoV-2 as the receptor protein. The molecular docking analysis of these receptor proteins with the different phytocompounds of P. alliacea L. was performed using AutoDock Vina. Then, we selected the three top-ranked phytocompounds (myricitrin, engeletin, and astilbin) as the candidate drug molecules based on their highest binding affinity scores of −8.9, −8.7 and −8.3 (Kcal/mol), respectively. Then, a 100 ns molecular dynamics (MD) simulation study was performed for their complexes with Mpro using YASARA software, computed RMSD, RMSF, PCA, DCCM, MM/PBSA, and free energy landscape (FEL), and found their almost stable binding performance. In addition, biological activity, ADME/T, DFT, and drug-likeness analyses exhibited the suitable pharmacokinetics properties of the selected phytocompounds. Therefore, the results of this study might be a useful resource for formulating a safe treatment plan for SARS-CoV-2 infections after experimental validation in wet-lab and clinical trials.

Fractional integro-differential equations (FIDEs) of both Volterra and Fredholm types present considerable challenges in numerical analysis and scientific computing due to their complex structures. This paper introduces a novel approach to address such equations by employing a Cubic B-spline collocation method. This method offers a robust and systematic framework for approximating solutions to the FIDEs, facilitating precise representations of complex phenomena. Within this research, we establish the mathematical foundations of the proposed scheme, elucidate its advantages over existing methods, and demonstrate its practical utility through numerical examples. We adopt the Caputo definition for fractional derivatives and conduct a stability analysis to validate the accuracy of the method. The findings showcase the precision and efficiency of the scheme in solving FIDEs, highlighting its potential as a valuable tool for addressing a wide array of practical problems.

SARS-CoV-2 infections, commonly referred to as COVID-19, remain a critical risk to both human life and global economies. Particularly, COVID-19 patients with weak immunity may suffer from different complications due to the bacterial co-infections/super-infections/secondary infections. Therefore, different variants of alternative antibacterial therapeutic agents are required to inhibit those infection-causing drug-resistant pathogenic bacteria. This study attempted to explore these bacterial pathogens and their inhibitors by using integrated statistical and bioinformatics approaches. By analyzing bacterial 16S rRNA sequence profiles, at first, we detected five bacterial genera and taxa (Bacteroides, Parabacteroides, Prevotella Clostridium, Atopobium, and Peptostreptococcus) based on differentially abundant bacteria between SARS-CoV-2 infection and control samples that are significantly enriched in 23 metabolic pathways. A total of 183 bacterial genes were found in the enriched pathways. Then, the top-ranked 10 bacterial genes (accB, ftsB, glyQ, hldD, lpxC, lptD, mlaA, ppsA, ppc, and tamB) were selected as the pathogenic bacterial key genes (bKGs) by their protein–protein interaction (PPI) network analysis. Then, we detected bKG-guided top-ranked eight drug molecules (Bemcentinib, Ledipasvir, Velpatasvir, Tirilazad, Acetyldigitoxin, Entreatinib, Digitoxin, and Elbasvir) by molecular docking. Finally, the binding stability of the top-ranked three drug molecules (Bemcentinib, Ledipasvir, and Velpatasvir) against three receptors (hldD, mlaA, and lptD) was investigated by computing their binding free energies with molecular dynamic (MD) simulation-based MM-PBSA techniques, respectively, and was found to be stable. Therefore, the findings of this study could be useful resources for developing a proper treatment plan against bacterial co-/super-/secondary-infection in SARS-CoV-2 infections.

Histone deacetylases (HDACs) are enzymes that remove acetyl groups from ɛ-amino of histone, and their involvement in the development and progression of cancer disorders makes them an interesting therapeutic target. This study seeks to discover new inhibitors that selectively inhibit HDAC enzymes which are linked to deadly disorders like T-cell lymphoma, childhood neuroblastoma, and colon cancer. MOE was used to dock libraries of ZINC database molecules within the catalytic active pocket of target HDACs. The top three hits were submitted to MD simulations ranked on binding affinities and well-occupied interaction mechanisms determined from molecular docking studies. Inside the catalytic active site of HDACs, the two stable inhibitors LIG1 and LIG2 affect the protein flexibility, as evidenced by RMSD, RMSF, Rg, and PCA. MD simulations of HDACs complexes revealed an alteration from extended to bent motional changes within loop regions. The structural deviation following superimposition shows flexibility via a visual inspection of movable loops at different timeframes. According to PCA, the activity of HDACs inhibitors induces structural dynamics that might potentially be utilized to define the nature of protein inhibition. The findings suggest that this study offers solid proof to investigate LIG1 and LIG2 as potential HDAC inhibitors.

ABSTRACT: Inclusion of rural youth is of great importance to facilitate nutritional security and make the food chain more sustainable. A positive attitude is necessary for active participation in agricultural activities. This case study was an attempt to check the attitude of rural youth regarding sustainable farming and its contributing factors. The study was carried out in the Punjab province of Pakistan and a transverse research design was used for this quantitative study. An interview schedule was used for getting the face-to-face response of rural youth. To make the unknown population of rural youth in Punjab, the Fisher formula was used and a sample of 413 was selected from purposely selected three districts of Punjab. After recording data, Statistical Package for Social Sciences (SPSS) was used to analyze the data. Descriptive Statistics was used to explain the response of rural youth for the decision on the base of data. Only 53 young farmers said that they have never been part of the formal education system and maximum number of farmers was close to 24 years of age or more than that. Rural youth of Punjab is lacking in non-formal education for acquiring or maintaining their skills & interests. Unemployment and having limited farm income are the biggest challenges that rural youth is facing. Rural youth show a strong inclination towards opting for sustainable farming alongside the availability of a supportive network. Regarding to learning capacities rural youth is lacking related to knowledge, communication means, novel approaches and in promoting sustainable farming initiatives. To achieve the goal of sustainability in changing environment, rural youth must have access to continuous training, communication sources, membership, or association with organizations with novel ideas covering all the changes happening in the farming business.

Humans have a natural tendency to express their emotions, but they are also skilled at using sarcasm to shape their feelings. In cognitive computing and natural language processing research, sentiment analysis and sarcasm detection are typically treated as separate tasks, with each text analyzed in isolation. However, this approach overlooks the connection between sentiment and sarcasm. We believe that sentiment and sarcasm are closely related and should be analyzed together to achieve a better understanding of context and natural language. In this paper, we propose a new framework that leverages the Cognitive Relationship (CR) between sarcasm and sentiment to improve the accuracy of classification. By taking into account the relationship between these two factors, we can achieve better results in sentiment analysis and sarcasm detection. We have also created a new and nearly balanced dataset for sentiment and sarcasm classification in standard Urdu that contains 7,000 tweets, which make up over 210K tokens. To gain a better understanding of the data, we conducted exploratory data analysis on words, hashtags, and emojis. The proposed methodology conducted a variety of classical machine learning classifiers and tested them with different variations of the dataset. After a thorough analysis of the results and errors, we found that the CR-based approach for sarcasm and sentiment classification performed better than the traditional stand-alone (SA) approach. Among the classifiers, Linear Regression and eXtreme Gradient Boosting proved to be the most effective. The sentiment classification based on CR has demonstrated a 9.3% enhancement compared to the stand-alone (SA) method while maintaining an overall improvement of approximately 22% compared to the baseline distribution. In the same way, the sarcasm classification based on CR has shown a 9.1% improvement over the SA approach and approximately 23.6% improvement over the baseline distribution.

Fodder crops have to compete with those of field crops, and the majority of farmers are smallholders in the circumstances of Pakistan. Therefore, this study was planned to search for the best maize hybrid which would serve dual purposes, i.e. for grain production as well as its later usage as fodder and silage. So, seven maize hybrids most commonly grown in the vicinity were selected and compared for their forage production. Maize hybrids were sown on ridges followed by all cultural operations as carried out by farmers. At harvest, plant morphological parameters were measured before ensiling the whole maize plant. For ensiling, fodder was harvested and chopped into 3-4 cm long discs using a chaff cutter. The fodder was then transferred to plastic jars, pressed hard to remove air, sealed, and kept airtight for 40 days. Samples were taken after the ensiling period and subjected to different quantity and quality parameters. It was observed that Monsanto DK-6789 showed the best performance in agronomic; plant height at harvest, number of leaves per plant, dry weight per plant, fresh forage yield at harvest, and dry matter yield, and quality parameters; crude protein, fiber, and total ash percentage. DK-6789 also showed superiority in lactic acid, pH, dry matter, crude protein, neutral detergent fiber, acid detergent fiber, hemicellulose, and cellulose. Therefore, this maize hybrid may be recommended for grain production in the irrigated areas, while its leftovers can be utilised as forage or ensiled for quality silage.

Abstract Water constitutes ≈70–90% of the organism's body by mass and is highly important for its survival. Water contains a variety of chemical contaminants introduced by various sectors, resulting in contamination that has a direct impact on the ecosystem. Various approaches are in practice to tackle these issues. Among these, semiconductor photocatalysis appears to be the cutting‐edge technology for the degradation of wastewater contaminants. Herein, the fabrication of Fe3O4−SiO2 nanocomposite via facile co‐precipitation and Stober methods are reported. Various characterization techniques are employed for the structural elucidation, morphology, crystallinity, and stability of the as‐prepared composite. The nanocomposite is employed in catalytic and photocatalytic applications toward the removal of methylene blue (MB) and methyl orange (MO) dyes from a comparative perspective. It is observed that the composite can remove about 93% of MB and 51% of MO within 7 and 6 h, respectively. These findings indicate that the nanocomposite has a higher MB removal effectiveness than the MO. This trend can be accredited to the difference in the chemical structure of both dyes. The nanocomposite is also evaluated for antioxidant and antileishmanial activity, and it is shown to be quite effective even at very low concentrations.

In the context of tropical monsoonal dwarf forest restoration, it is well known that the interaction between soil properties and plant functional traits influences the dynamics and forest composition of plant communities. The main aim of this study was to determine the relationships and variations between the plant functional traits and environmental variables in tropical coastal secondary forests. However, it is undisputed whether trait variation is coordinated and whether there is a relationship between the community-weighted mean (CWM) traits and soil variables. TNNR conducted a ground survey to collect actual ground data on the biophysical characteristics of individual trees and shrubs, along with soil sample data. All soil samples and plant materials were collected at the end of June, in the 2020 growing season (July and August), in each quadrat with a 400-m2 area. To gain insight into these questions, a total of 4 plant functional traits of 167 species and 5 soil nutrients from 128 soil samples were analyzed from 128 plots in a tropical evergreen monsoon forest on Hainan Island. Using SMA (standardized major axis), wood density (WD), and leaf thickness (LT), as well as specific leaf area (SLA) and relative leaf water content (RLWC), were significantly positively correlated. Using Pearson correlation analysis, leaf thickness (LT) was significantly positively correlated with soil organic matter (OM). Using principal component analysis (PCA), we also found that soil TN and OM were the strongest predictors for functional traits, i.e., WD and LT. Moreover, using path analysis, OM and TN have a major impact on plant CWM traits, e.g., SLA and RLWC. Our results show a significant relationship between functional traits and soil pH and soil nutrients in tropical coastal secondary forests. Our results highlight that plant traits can be used to predict specific soil nutrients and ecosystem functioning in tropical secondary forests, but we are concerned about how variation in the physical structure of plant affect ecosystem function in forest communities. This research can help us to better understand the restoration of habitats and green infrastructure design, suggesting that selecting different species across multiple trait axes can help ensure functionality at the maximum level.

Imidazothiadiazole is a fundamental fused heterocyclic compound containing imidazole and thiadiazole ring systems. This versatile framework has significant applications in pharmaceutical chemistry and also possessed a remarkable biological profile. The derivatives of imidazo[2,1-b][1,3,4]thiadiazole have a broad spectrum of biological applications such as antitumor, tubulin inhibitor, anticancer, antifungal, anti-inflammatory, antimicrobial, antitubercular, anticonvulsant, antibacterial and as enzyme inhibitors. These derivatives also play a significant role in the development of non-linear optics and photo-electronics. Synthesis of this fused bicyclic compound mainly involved the reaction between 2-amino-1,3,4-thiadiazoles and α-haloketones, with different substitutions at the 2, 5, and 6 positions of the ring system. Moreover, microwave assisted multicomponent and C–C coupling reactions in the presence of catalysts or under solvent free reaction conditions were found to be reliable and valuable approaches. This review is a concerted approach to describe the synthesis and applications of imidazo[2,1-b][1,3,4] thiadiazole derivatives reported during 2015–2022.

IntroductionThe quick pace of technological advancement and urbanization has led to a significant increase in waste production, severely damaging environmental quality and human health. The sorting of waste is a viable option to reduce environmental hazards and attain high recovery rates in the cities. This research extended the theory of planned behavior (TPB) by integrating information publicity (IP) and moral norms (MNs).MethodsA conceptual model has been developed to explore the predictors of waste-sorting intention of households. The data from 361 Pakistani households have been collected using the purposive sampling method and analyzed via PLS-SEM.Results and discussionThe study's results revealed that IP is important in creating awareness and establishing moral norms regarding waste sorting among households. The findings further confirm that MN, attitude (ATD), subjective norms (SNs), and perceived behavioral control (PBC) sequentially mediate between IP and WSI. The findings of the current study provides useful practical implications to the practitioners and academicians to combat environmental pollution.

Potentilla nepalensis belongs to the Rosaceae family and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in earlier studies. However, the PCs affecting human genes and their roles in the body have not previously been disclosed. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDSs), and MMGBSA methodologies. The SMILES format of PCs from the PubChem was used as input to DIGEP-Pred, with 764 identified as the inducing genes. Their enrichment studies have shown inducing genes’ gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analyzing parameters performed in Cytoscape v3.10 revealed three therapeutic targets: TP53 from MS-, NR-, and NS-induced genes; HSPCB and Nf-kB1 from MR-induced genes. From 40 PCs, two PCs, 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of −8.6 and −8.0, and three PCs, 3a, (NR) 4a, and 4c (NS), with HSP protein of −9.6, −8.7, and −8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Therapeutic targets identified in this study have a prominent role in numerous cancers. Thus, further investigations such as in vivo and in vitro studies should be carried out to find the molecular functions and interlaying mechanism of the identified therapeutic targets on numerous cancer cell lines in considering the PCs of P. nepalensis.

Background: Advancements in nanoscience have led to a profound paradigm shift in the therapeutic applications of medicinally important natural drugs. The goal of this research is to develop a nano-natural product for efficient cancer treatment. Methods and Results: For this purpose, mesoporous silica nanoparticles (MSNPs) were formulated, characterized, and loaded with caffeine to develop a targeted drug delivery system, i.e., caffeine-coated nanoparticles (CcNPs). In silico docking studies were conducted to examine the binding efficiency of the CcNPs with different apoptotic targets followed by in vitro and in vivo bioassays in respective animal models. Caffeine, administered both as a free drug and in nanomedicine form, along with doxorubicin, was delivered intravenously to a benzene-induced AML model. The anti-leukemic potential was assessed through hematological profiling, enzymatic biomarker analysis, and RT-PCR examination of genetic alterations in leukemia markers. Docking studies show strong inter-molecular interactions between CcNPs and apoptotic markers. In vitro analysis exhibits statistically significant antioxidant activity, whereas in vivo analysis exhibits normalization of the genetic expression of leukemia biomarkers STMN1 and S1009A, accompanied by the restoration of the hematological and morphological traits of leukemic blood cells in nanomedicine-treated rats. Likewise, a substantial improvement in hepatic and renal biomarkers is also observed. In addition to these findings, the nanomedicine successfully normalizes the elevated expression of GAPDH and mTOR induced by exposure to benzene. Further, the nanomedicine downregulates pro-survival components of the NF-kappa B pathway and upregulated P53 expression. Additionally, in the TRAIL pathway, it enhances the expression of pro-apoptotic players TRAIL and DR5 and downregulates the anti-apoptotic protein cFLIP. Conclusions: Our data suggest that MSNPs loaded with caffeine, i.e., CcNP/nanomedicine, can potentially inhibit transformed cell proliferation and induce pro-apoptotic TRAIL machinery to counter benzene-induced leukemia. These results render our nanomedicine as a potentially excellent therapeutic agent against AML.

Rapid industrialization and urbanization are the two significant issues causing environmental pollution. The polluted water from various industries contains refractory organic materials such as dyes. Heterogeneous photocatalysis using semiconductor metal oxides is an effective remediation technique for wastewater treatment. In this research, we used a co-precipitation-assisted hydrothermal method to synthesize a novel I-FeWO4/GO sunlight-active nanocomposite. Introducing dopant reductive iodine species improved the catalytic activity of FeWO4/GO. I− ions improved the catalytic performance of H2O2 by doping into FeWO4/GO composite. Due to I− doping and the introduction of graphene as a support medium, enhanced charge separation and transfer were observed, which is crucial for efficient heterogeneous surface reactions. Various techniques, like FTIR, SEM-EDX, XRD, and UV–Vis spectroscopy, were used to characterize composites. The Tauc plot method was used to calculate pristine and iodine-doped FeWO4/GO bandgap. Iodine doping reduced the bandgap from 2.8 eV to 2.6 eV. The degradation of methylene blue (MB) was evaluated by optimizing various parameters like catalyst concentration, oxidant dose, pH, and time. The optimum conditions for photocatalysts where maximum degradation occurred were pH = 7 for both FeWO4/GO and I-FeWO4/GO; oxidant dose = 9 mM and 7 mM for FeWO4/GO and I-FeWO4/GO; and catalyst concentration = 30 mg and 35 mg/100 mL for FeWO4/GO and I-FeWO4/GO; the optimum time was 120 min. Under these optimum conditions, FeWO4/GO and I-FeWO4/GO showed 92.0% and 97.0% degradation of MB dye.

This paper introduces a novel collocation scheme based on an extended cubic B-spline for approximating the solution of a second-order partial integro-differential equation. The proposed scheme employs new extended cubic B-splines to discretize the second-order derivatives in the spatial domain, while discretization of spatial derivatives of lower orders is achieved using extended cubic B-spline functions. Temporal derivatives are discretized using the forward difference formula. The stability of the algorithm is assessed using the von Neumann stability method to ensure that error magnification is avoided. Furthermore, convergence analysis of the scheme is provided. Numerical experiments are conducted to validate the effectiveness and efficiency of the proposed scheme. The free parameter is optimized using L2 and L∞ norms. The computed results are compared with those obtained from various standard numerical schemes found in the literature. Mathematical 12 is used to obtain numerical results.

Burgers’ equation is a nonlinear partial differential equation that appears in various areas of physics and engineering. Finding accurate and efficient numerical methods to solve this equation is crucial for understanding complex fluid flow phenomena. In this study, we propose a spline-based numerical technique for the numerical solution of Burgers’ equation. The space derivative is discretized using cubic B-splines with new approximations for the second order. Typical finite differences are used to estimate the time derivative. Additionally, the scheme undergoes a stability study to ensure minimal error accumulation, and its convergence is investigated. The primary advantage of this scheme is that it generates an approximate solution as a smooth piecewise continuous function, enabling approximation at any point within the domain. The scheme is subjected to a numerical study, and the obtained results are compared to those previously reported in the literature to demonstrate the effectiveness of the proposed approach. Overall, this study aims to contribute to the development of efficient and accurate numerical methods for solving Burgers’ equation. The spline-based approach presented herein has the potential to advance our understanding of complex fluid flow phenomena and facilitate more reliable predictions in a range of practical applications.

Marek’s disease virus (MDV) is a highly contagious and persistent virus that causes T-lymphoma in chickens, posing a significant threat to the poultry industry despite the availability of vaccines. The emergence of new virulent strains has further intensified the challenge of designing effective antiviral drugs for MDV. In this study, our main objective was to identify novel antiviral phytochemicals through in silico analysis. We employed Alphafold to construct a three-dimensional (3D) structure of the MDV DNA polymerase, a crucial enzyme involved in viral replication. To ensure the accuracy of the structural model, we validated it using tools available at the SAVES server. Subsequently, a diverse dataset containing thousands of compounds, primarily derived from plant sources, was subjected to molecular docking with the MDV DNA polymerase model, utilizing AutoDock software V 4.2. Through comprehensive analysis of the docking results, we identified Disalicyloyl curcumin as a promising drug candidate that exhibited remarkable binding affinity, with a minimum energy of −12.66 Kcal/mol, specifically targeting the DNA polymerase enzyme. To further assess its potential, we performed molecular dynamics simulations, which confirmed the stability of Disalicyloyl curcumin within the MDV system. Experimental validation of its inhibitory activity in vitro can provide substantial support for its effectiveness. The outcomes of our study hold significant implications for the poultry industry, as the discovery of efficient antiviral phytochemicals against MDV could substantially mitigate the economic losses associated with this devastating disease.

Lexical Similarity (LS) between two languages uncovers many interesting linguistic insights such as phylogenetic relationship, mutual intelligibility, common etymology, and loan words. There are various methods through which LS is evaluated. This paper presents a method of Phonetic Edit Distance (PED) that uses a soft comparison of letters using the articulatory features associated with their International Phonetic Alphabet (IPA) transcription. In particular, the comparison between the articulatory features of two letters taken from words belonging to different languages is used to compute the cost of replacement in the inner loop of edit distance computation. As an example, PED gives edit distance of 0.82 between German word ‘vater’ ([fa:tər]) and Persian word ‘ ’ ([pedær]), meaning ‘father,’ and, similarly, PED of 0.93 between Hebrew word ‘ ’ ([ʃəɭam]) and Arabic word ‘ ’ ([səɭa:m], meaning ‘peace,’ whereas classical edit distances would be 4 and 2, respectively. We report the results of systematic experiments conducted on six languages: Arabic, Hindi, Marathi, Persian, Sanskrit, and Urdu. Universal Dependencies (UD) corpora were used to restrict the comparison to lists of words belonging to the same part of speech. The LS based on the average PED between pair of words was then computed for each pair of languages, unveiling similarities otherwise masked by the adoption of different alphabets, grammars, and pronunciations rules.

Fluorescence probes for detecting tumours during surgery can suffer from poor accumulation and short imaging windows. Here, the author develop fluorescence probes with multiple motifs that permit enhanced circulation times, tumour targeting and use the probes to image pancreatic cancer in mice

Organic food has gained much importance due to consumers' rising environmental and health concerns. Purchase intention of organic food has been explored widely, but the repurchase intention of organic food has gained little attention among researchers. So, it has become important to explore repurchase intention among generation Z; a generation considered more educated and aware of rising environmental concerns. Generation Z is more tech-savvy and brand conscious, so its impact on repurchase intention through consumer satisfaction has been explored. The data in this paper was collected from 400 respondents through a structured questionnaire in Islamabad, Pakistan. We used the PLS-SEM approach for data analysis and results; we found that social media influence and brand purchase impact brand awareness and positively impact brand awareness on consumer satisfaction. Moreover, it is also found that consumer satisfaction positively impacts the repurchase intention of organic food. Our study found that Generation Z has a strong social media influence, so marketers' managers must consider and address the issues when consumers consider social media for their concerns and suggestion.

To investigate the water-deficit tolerance, 45 cotton genotypes were grown under normal irrigation and water-deficit conditions for 2 years. Genotype × treatment × year interaction was determined for seed cotton yield, number of bolls, boll weight, chlorophyll fluorescence, proline contents, and total soluble proteins. Apart from proline levels, all traits showed a reduction under water-deficit conditions. The mean percentage reduction in seed cotton yield due to water deficit conditions was 52.83% and 42.19%, for number of bolls was 48.44% and 39.30%, for boll weight was reduced by 8.94% and 6.03% in 2013 and 2014 respectively. Reduction in chlorophyll fluorescence was 13.87% and 16.46% while soluble protein levels decreased by 25.57% and 21.09% during 2013 and 2014 respectively. For proline contents went up by 38.68% and 37.70% in 2013 and 2014 respectively. Relatively small changes in these parameters under water-deficit conditions were recorded for varieties FH-155, FH-207, FH-322, FH-329 IUB-13 and IUB-222 making these genotypes best suited for cultivation under water-deficit conditions. The positive correlation of seed cotton yield with proline contents and chlorophyll fluorescence under water-deficit condition indicates that these two traits can be considered to select cotton genotypes at early growth stages.

Water pollution by synthetic dyes and other organic contaminants is a serious issue of the present days for both mankind and scientists. From the past few years, much attention has been given to the graphene oxide nanocomposites due to their greater ability to adsorb and degrade the industrial pollutants and greater suitability to the environment. In the present research, polymeric graphene oxide (GO) nanocomposites such as GO/polyaniline (PAN), GO/polypyrrole (PPy) and GO/polystyrene (PS) were utilized as promising adsorbents for removal of actacid orange RL (AO-RL) dye. Characterization of synthesized nanocomposites was done by Fourier transform infrared spectroscopy and scanning electron microscopy techniques. Higher adsorption rates were achieved at pH values 2, 6 and 3 for all three nanocomposite GO/PAN, GO/PPy, and GO/PSty. Maximum removal 39.54, 44.76 and 21.43 mg/g were achieved, respectively when optimum adsorbent dose of 0.01 g was used at 35 °C. The maximum adsorption of 39.65, 43.99, and 21.10 mg/g for all three nanocomposites were obtained at the equilibrium contact time of 60 min. For GO/PAN and GO/PPy the maximum adsorption rates were attained when 150 mg/L of initial dye concentration was used and for GO/PSty nanocomposite the maximum removal 54.34 mg/g was obtained when 100 mg/L of initial dye concentration was used. Obtained results showed that removal of AO-RL dye was best fit by the pseudo 2nd order kinetic model and Langmuir adsorption isotherm with R2 values 0.99, 0.997, and 0.986, respectively. Negative values of enthalpy variation: −40.95,-62.95 and −55.52 kJ/mol, respectively, show the spontaneity and exothermic nature of the reaction. So, results indicated that the synthesized polymeric GO nanocomposites have a good perspective for the treatment of wastewater.

The volatiles chemical composition and biological attributes of coriander ( Coriandrum sativum L.) leaves essential oil obtained by two extraction techniques namely supercritical fluid extraction and hydro-distillation is appraised. The coriander essential oil yield (.12%) by hydro-distillation was slightly higher than that of supercritical fluid extraction (.09%). The physico-chemical variables of the essential oil obtained from both the techniques varied in significantly (P < .05). GC-MS analysis identified 23 different components in supercritical fluid extracted oil and 18 components in hydro-distilled essential oil having linalool as major component (51.32% and 61.78%, respectively) followed by phytol (12.71%). The oil recovered by supercritical fluid extraction exhibited greater DPPH radical scavenging activity as well as reducing power as compared to the essential oil obtained by hydro-distillation technique along with a stronger biofilm inhibition and least hemolysis. The results of antimicrobial activity revealed that super critical fluid extracted essential oil has potent antifungal and antibacterial activity against P. multocida and A alternata , whereas hydro-distilled essential oil displayed better antimicrobial potential against E coli and A niger . Overall, these results depict that supercritical fluid extraction is superior than hydro-distillation with regard to isolation of better-quality coriander essential oil for nutra-pharmaceutical developments.