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Abstract Background Bigleaf hydrangea (Hydrangea macrophylla) is a widely cultivated ornamental plant species. Leaf spot disease, caused by Corynespora cassiicola, poses a significant threat to the ornamental quality and economic value of hydrangeas. However, the disease resistance breeding of hydrangea is limited due to the lacking of resistant varieties and genes. Results This study evaluated ten hydrangea varieties for their resistance to leaf spot disease. Among them, ‘White Angel’ and ‘Ocean Heart’ were screened out as representative varieties for resistance and susceptibility, respectively, on the basis of evaluation. Physiological and biochemical indices, phytohormones, and transcriptomic changes were measured in the leaves of both varieties at 0 and 24 h post inoculation with C. cassiicola. The results showed that C. cassiicola infection significantly increased abscisic acid (ABA) contents in both varieties; however, the increase was significantly higher in the susceptible variety ‘Ocean Heart’ compared to the resistant variety ‘White Angel’ (p

Abstract The integration of Fintech is revolutionizing global financial engagement, moving away from traditional payment systems. This study, thus, explores the interaction between communication dynamics, Fintech use, intentions, cashless transactions adoption, financial literacy, personal innovativeness, and socioeconomic development in Pakistan. The study employs a dual methodology, encompassing “PLS-SEM and Probit Model alongside Propensity Score Matching technique.” The survey targeted small business owners and individuals involved in informal sectors, encompassing roles such as fruit and vegetable vendors, small shop owners, taxi drivers, and auto rickshaw operators. A total of 394 responses were analyzed. The findings highlight the facilitating role of individuals’ intentions to use cashless transactions, acting as a mediator through which Fintech use fosters actual behavior. Moreover, the study finds financial literacy and personal innovativeness as critical moderating factors. Adopting cashless transactions emerges as a pathway to enhanced financial inclusion, particularly impactful for small business owners. The achieved financial inclusion has the potential for profound financial inclusion implications, as evidenced by its positive effects on sustainable livelihoods, living conditions, and social development among small business owners and individuals operating within the informal sector.

Abstract Codon‐based analyses of the PPARGC1A gene across 38 vertebrate species were deployed to elucidate patterns of evolutionary change. Employing maximum likelihood assessments through MEGA, we scrutinized 447 codon positions addressing the entire coding region, excluding positions mired by gaps or missing data. Distinct codons manifested variance in selection pressures, particularly codons 4, 11, 66, and 123, which exhibited positive dN‐dS values suggestive of positive selection. Codon 137 displayed the most pronounced dN‐dS value, signifying intensified selective advantage. Meanwhile, codons 30 and 90 portrayed near‐neutral scores, indicative of purifying selection. Complementary computational methods (IFEL, REL, FUBAR, and SLAC) confirmed positive selection at specific codon sites, with varying degrees of corroboration. The integration of mixed‐effect modeling (MEME) identified episodic diversifying selection, pinpointing codons that underwent selection episodes in certain lineages. Refined codon model selection lent insight into substitution rates, revealing nuanced degrees of evolutionary conservation among different codons. Supporting these genetic insights, the phylogenetic analysis highlighted relationships among the PPARGC1A sequences and domain analysis confirmed conserved features across species, while protein–protein interaction networks suggested a complex web of functional interdependencies. These findings advance our understanding of the PPARGC1A gene's evolutionary trajectory and underscore the gene's potential adaptive significance within diverse vertebrate lineages.

Objective: The objective of the study was to determine the reasons affecting career choice for post-graduation and decision of studying abroad among undergraduate students in a medical university of Karachi. Methods: A cross-sectional study was conducted among students of 1stto 5th year MBBS program of Baqai Medical University, Karachi from March 2022 to August 2022. A questionnaire was filled by students who voluntarily wished to participate. Statistical Package for Social Sciences version 21 was used for data analysis. Results: The most common clinical fields of choice for post-graduation of medical students were cardiothoracic surgery (14.3%), followed by general surgery (13.6%), whereas the most common non-clinical fields of choice were medical education (53.3%) followed by research (20.0%). A majority of students (54.5%) wished to pursue post-graduation abroad. Among those opting for staying in Pakistan, almost half of them wished to work in rural areas (n=69, 50.4%) and the remaining in urban areas (49.6%). Conclusion: The most popular clinical fields of choice for post-graduation among medical students turned out to be cardiothoracic surgery whereas the non-clinical career switch was mostly towards medical education. Moreover, a majority of students wished to pursue their post-graduation abroad. Key words: Career Choice, Specialty, Medical, Emigration, Students, Medical

Abstract No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

Abstract In family firms the role of CEO is highly significant with reference to devise strategic decisions and deciding if it is feasible to invest in innovation input. This study aims to investigate the behaviour analyses of the diverse types of CEOs in family firms towards innovations. This study also analyzes the moderating role of managerial ability in the nexus of CEO types and innovation input. The data are obtained from Chinese A-share listed family firms from Accounting Research and China Stock Exchange in 2012–2020 and analysed using ordinary least squares regression. Tobit and probit regressions are also employed to confirm the results. Results indicate that non-family and family CEOs (with no controlling rights) show identical behaviour concerning their lower intentions to promote innovations in R&D projects than family CEOs with actual controlling rights. In addition, family CEOs with actual controlling rights exert a positive effect on R&D, indicating that they are more willing to invest in innovative projects. Moreover, we observe the significant moderating role of managerial ability in the nexus of CEO types and innovation activities. We find that high managerial ability alters the behaviour of different CEOs. With the moderation of managerial ability, non-family and family CEOs (without actual controlling rights) also show willingness to invest in innovative projects and without managerial ability, CEOs’ willingness to make innovations decline. This study is a pioneer work that investigates the impact of diverse types of CEOs to unlock notable insights regarding the R&D investment behaviour of Chinese family firms with moderating role of managerial ability. This study is useful to all parties involved with the company, including employees, clients, suppliers and customers. The results of this study can also assist board members in selecting and recruiting non-family CEOs or keeping family CEOs (with or without actual controlling rights).

Solar cells have become the centre of academic research in recent times, primarily owing to their ability to generate cost-effective and environmentally friendly sustainable energy on a commercial and industrial level. In this study, we propose the initiation of a research attempt focused on polymer solar cells that employ PBDB-T/ITIC as the active material. To facilitate this investigation, we have employed SCAPS-1D, a robust simulation program widely recognized for its effectiveness in the field. The objective of this study is to enhance the efficiency of a polymer solar cell composed of PBDB-T/ITIC as the absorber, P3HT as the Hole Transport Layer (HTL), and WS2 as the Electron Transport Layer (ETL) through the utilization of SCAPS simulation techniques. By systematically manipulating various parameters within the SCAPS device simulator, we have successfully incorporated the impact of temperature, thickness, defect density, and metal contacts on key performance parameters such as Open Circuit Voltage (Voc), Short Circuit Current density (Jsc), Fill Factor (FF), and Power Conversion Efficiency (PCE). We have developed a novel polymer-based solar cell utilizing the PBDB-T/ITIC material, which exhibits enhanced efficiency, improved temperature stability, and reduced environmental impact. The findings of our study may have the potential to assist the thin-film photovoltaic industry in the development of economically feasible and highly efficient polymer based solar cells.

Background: Total colonic atresia is an uncommon congenital anomaly associated with neonatal intestinal obstruction, often necessitating prompt diagnosis and surgical intervention to prevent life-threatening complications. Understanding the etiology and optimal management strategies is crucial for ensuring favorable outcomes. Case Presentation: We present a case of a full-term male neonate with total colonic atresia, who presented with failure to pass meconium, abdominal distension, and vomiting. Diagnostic imaging confirmed intestinal obstruction, leading to surgical exploration revealing an atretic colon extending from the Ileocolic Junction to the Rectosigmoid Junction. An ileostomy was performed, followed by meticulous postoperative care, resulting in a successful resolution of symptoms and discharge from the hospital. Conclusion: Timely recognition and staged surgical management are paramount in addressing total colonic atresia, emphasizing the importance of early intervention for optimal patient outcomes. Long-term follow-up and comprehensive care are essential to ensure the overall well-being of affected newborns.

This article reinvestigates the regional convergence in GDP per capita, household expenditure per capita, poverty rate, and average years of schooling in Indonesia at the district level during 2000–2017 using the convergence club method. This article finds that regional inequality in Indonesia at the district level is characterized by two convergence clubs in GDP per capita, five convergence clubs in household expenditure per capita, six convergence clubs in poverty, and five convergence clubs in average years of schooling. This article also confirms the existence of spatial concentration among regions and a development gap between the west and east sides of Indonesia.

Abstract In the technologically changing world, the demand for ultra‐reliable, faster, low power, and secure communication has significantly risen in recent years. Researchers have shown immense interest in emerging quantum computing (QC) due to its potentials of solving the computing complexity in the robust and efficient manner. It is envisioned that QC can act as critical enablers and strong catalysts to considerably reduce the computing complexities and boost the future of sixth generation (6G) and beyond communication systems in terms of their security. In this study, the fundamentals of QC, the evolution of quantum communication that encompasses a wide spectrum of technologies and applications and quantum key distribution, which is one of the most promising applications of quantum security, have been presented. Furthermore, various parameters and important techniques are also investigated to optimise the performance of 6G communication in terms of their security, computing, and communication efficiency. Towards the end, potential challenges that QC and quantum communication may face in 6G have been highlighted along with future directions.

In the backdrop of COVID19 recovery, Pakistan is still struggling to cope with the economic challenges and disruptions caused in the energy supply chain. On one hand where COVID has brought serious socio-economic costs and prolonged delays, it has also provided opportunity for developing countries such as Pakistan to “build-forward-better” their economies in a more sustainable and climate friendly manner. This study particularly highlights the impact of COVID on energy supply and demand sectors of Pakistan, its near- and long-term impacts, and what policy interventions can be adopted to put Pakistan on-track to achieve its Nationally Determined Contributions (NDCs). The economic focus in on “Green Recovery” and what key interventions will foster a rapid transition towards decarbonization in Pakistan. Low Emission Analysis Platform (LEAP) model is used to provide energy sector outlook (2020-2040) of Pakistan under different scenario i.e., Pre COVID growth, Business-as-Usual, Slow Recovery, and Green Recovery from COVID. The results obtained from the model depicts that following a green recovery scenario, Pakistan can reduce around 10 Mtoe (9%) of its total energy use, 53 TWh of electricity, 19 Mt of emissions from demand sectors, and 11 Mt of emissions from the power sector by 2030. For total levelized cost of the power sector, the green recovery scenario represents a generation cost of $13 billion by 2030 which further highlights that energy efficiency could lead to cost savings of approximately $3 billion each year by 2030. Green recovery is however still a daunting task as it would require economic stimulus of $8 billion only to recover to its pre COVID scenario and total investments of $120 billion by 2030.

Although solar cells have the potential to create an endless amount of electrical power, their comparatively low power conversion efficiency draws the curiosity of both academics and industry. The primary goal of this research is to examine the performance of lead-free perovskite solar cells that use methyl ammonium tin iodide (CH3NH3SnI3) as the active material. The SCAPS-1D programme is employed for the simulation and analysis of the solar cells. The solar cell structure was analyzed computationally, and the resulting output was examined by comparing the I-V characteristic curves across different combinations of parameters. Various materials and combinations of parameters were explored in an effort to enhance the power conversion efficiency of solar cells based on CH3NH3SnI3. A series of comprehensive evaluations were undertaken to examine the influence of technical factors, including absorber layer thickness, defect density, and acceptor density, on performance. The acceptor density that yielded the best results was selected in order to improve the performance of the solar cell. The simulation results were acquired across a temperature range spanning from 300K to 450K, revealing enhanced stability within the range of typical ambient temperatures. The study produced encouraging findings, which included a short circuit current density of 30.81mA/cm2, an open circuit voltage of 1.25V, a fill factor of 80.35%, and a power conversion efficiency of 31.11%. This study has the potential to facilitate the development of environmentally sustainable, highly efficient, and cost-effective thin film solar cells based on CH3NH3SnI3, which exhibit noteworthy physical characteristics as alternatives to lead-containing perovskite solar cells.

This research utilizes the fsQCA technique to investigate how a combination of corporate governance conditions or factors collectively influences the performance of banks. Examining key elements such as board size, busy directors, independent directors, CEO duality, and women on the board, the research employs data collected from the annual reports of 30 banks spanning from 2010 to 2020. The necessary condition analysis (NCA) underscores that no individual condition or factor is indispensable for the ultimate outcome. Nevertheless, the sufficiency analysis reveals distinct solutions, each representing a unique set of conditions or factors sufficient to generate the outcome. The study concludes that the relationship between corporate governance characteristics and bank performance is complex and multifaceted, with neither ROA nor ROE reliant on a singular input condition or factor. The theoretical contributions of the findings align with or partially support various theories and propositions within the realm of corporate governance. Notably, the application of fsQCA contributes to enhance the methodological understanding of corporate governance studies in existing literature.

The study attempts to analyze the impact of hybrid energy systems on environmental sustainability in the context of the circular economy network. The hybrid energy sources follow the principle of circular economy, which aims to reduce raw material use and waste which is very fruitful in promoting environmental sustainability. However, the study uses quarterly data from Pakistan from 2011Q1 to 2020Q4 to accomplish the proposed study objective. The study constructs 5 hybrid systems of energy to analyze the impact and applies Auto Regressive Distributive Lag Model (ARDL) to estimate the results. It is found that electricity generation through solar photovoltaic (SPV), wind turbine (WND), hydroelectricity (HYDE) and nuclear power generation (NPG) play a positive role in increasing environment sustainability. The results explain that SPV, NPG, and HYDE contribute 2.29%, 2.04%, and 0.42% to environmental sustainability, respectively. Hybrid systems of energy (Hybrid 1,2,3,4 and 5) positively impact ecological sustainability, but the intensity of each hybrid system in sustaining the environment is different. Among five hybrid systems, the hybrid-5 (SPV-WND-HYDE-NPG) energy system is more environmentally friendly and has the highest contribution towards environmental sustainability. The study suggests incorporating hybrid energy systems provides the means of transition toward a circular economy, ultimately promoting ecological sustainability. The study proposes to the officials of the Pakistani government and policymakers to initiate effective policies to encourage hybrid energy systems because the significance of hybrid systems ensures a low carbon economy and makes a path towards sustainable economic development.

Rapid urban and industrial sectors generate massive amounts of wastewater, creating severe ecological disruption and harming living organisms. The number of harmful pollutants such as dyes, heavy metals, antibiotics, phenolic compounds, and volatile and several organic chemicals discharged into aquatic systems varies depending on the effluent composition of various sectors. MXene-based composites with unique characteristics were spotlighted as newly developed nanomaterials specifically for environmental-related applications. Therefore, this review broadly discusses the properties, basic principles of MXene, and synthesis routes for developing different MXene-based nanomaterials. The most current strategies on the energy and environmental applications of MXene-based nanomaterials, particularly in photocatalysis, adsorption, and water splitting, were deeply explored for the remediation of different pollutants and hydrogen (H2) evolution from wastewater. The detailed mechanism for H2 evolution and the remediation of industrial pollutants via photocatalysis and adsorption processes was elaborated. The multi-roles of MXene-based nanomaterials with their regeneration possibilities were emphasized. Several essential aspects, including the economic, toxicity and ecological power of MXene-based nanomaterials, were also discussed regarding their opportunity for industrialization. Finally, the perspectives and challenges behind newly developed MXene and MXene-based nanomaterials for environmental pollution were reviewed.

Short-term load forecasting plays an essential role in the efficient management of electrical systems. Building an optimization model that will enhance forecasting accuracy is a challenging task and a concern for electrical load prediction. Due to Artificial Neural Networks (ANNs), the final result depends on initial random weights and thresholds that affect the stability of the forecast. Although much devotion is being given to improving the forecast accuracy, convergence, complexity, and resilience need to be considered for stable predictive models. To overcome this limitation, this work has jointly considered the Wavelet Neural Network (WNN) and Self-Adaptive Momentum Factor (SAMF) to achieve fast convergence, stability, and high accuracy. The proposed hybrid model is developed by combining the Feature Engineering (FE) and SAMF with the WNN model. The FE removes the irrelevant data and shallow features to ensure high computational performance. In contrast, the SAMF combines the wavelet transform’s time and frequency domain properties and adjusts the WNN model’s corresponding parameters. This ensures the global optimum solution while returning accurate predictive results. Finally, the SAMF is used to tune the control parameters of WNN by initializing the random weights and thresholds to accelerate the convergence rate and improve the accuracy compared to the Back-Propagation (BP) method. The proposed hybrid model is tested on the real-time datasets taken from the Australian states of (New South Wales (NSW), and Victoria (VIC)). Experimental results show that the developed model outperforms other benchmark models such as WNN-IGA, BPNN, WNN-AMBA, and Enhanced WNN in terms of instability, rate of convergence, and accuracy.

With the rapid increase in the world’s population, the global electricity demand has increased drastically. Therefore, it is required to adopt efficient energy management mechanisms. Since the energy consumption trends are rather dynamic. Therefore, precise energy demand estimation and short and/or long-term forecasting results with higher accuracy are required to develop the optimization and control mechanism. Consequently, the machine learning (ML) techniques along with distributed demand response programs are being adopted to predict the future energy demand requirement with satisfactory results. In this paper, different state-of-the-art ML algorithms such as logistic regression (LR), support vector machines (SVM), naive Bayes (NB), decision tree classifier (DTC), K-nearest neighbor (KNN), and neural networks (NNs), have been implemented to analyze their performance. The main objective of this paper is to present a comparative analysis of ML algorithms for short-term load forecasting (STLF) regarding accuracy and forecast error. Based on the implementation and analysis, we have identified that, among other algorithms, the DTC provides comparatively better results. Therefore, we devised the enhanced DTC (EDTC) by integrating fitting function, loss function, and gradient boosting in DTC mathematical model for fine-tuning the control variables. The implementation results show that the proposed EDTC algorithm provides better forecast results (i.e., 99.9 % recall, 100% F1, 100% precision, 99.21 % training accuracy, and 99.70% testing accuracy.)

Chital is a native animal from South Asia. Chital had been introduced to many countries, including Indonesia. Chital was first introduced to Indonesia in 1811 at Bogor Palace and since had been kept captive around Indonesia. Currently, no research had been done concerning the genetic variation of Indonesian chital. Therefore, the purpose of this research was to analyze genetic variation and phylogenetic relationship of chital from Pusat Inovasi Agroteknologi Universitas Gadjah Mada (PIAT UGM), Prambanan Temple, Gembira Loka Zoo, and Bogor Palace, based on mitochondrial D-loop fragment. This study used a Polymerase Chain Reaction (PCR) method. DNA was extracted from faecal samples and amplified with L15995 and H16498 primers. The analysis used for this research were genetic variations, haplotype networking, and phylogenetic relationships between populations. This study detected 5 haplotypes out of 20 sequences with 10 polymorphic sites and 2 indels. The haplotype diversity and the nucleotide diversity were 0.443 and 0.002 respectively, and the genetic distance was between 0 and 2.03% (average 0.55%). This research also showed one main haplotype, labelled as haplotype 1, which consisted of all individuals from PIAT and Prambanan Temple, four individuals from Bogor Palace, and one individual from Gembira Loka. This grouping proves that the majority of chital population in Indonesia came from Bogor Palace. One individual from Gembira Loka has a considerable genetic divergence from the rest of the samples, which might indicate it originated from a different source population.

This study describes a novel approach to design of a power factor correction (PFC) and total harmonic distortion (THD) reduction-based brushless DC (BLDC) motor drive. The drive was designed to obtain a reduced THD for PFC. The basic design of the BLDC motor drive contains an AC voltage source as input for a diode bridge rectifier. The output DC voltage is filtered out to reduce ripples. The smooth DC output voltage is supplied to the modified Zeta converter. The output voltage of the modified Zeta converter is controlled by using pulse width modulation (PWM). The modified Zeta converter is utilized in discontinuous inductor current mode (DICM) for better power factor. This controlled DC voltage is supplied to the voltage source inverter (VSI) as input. The VSI is designed to convert input DC into a suitable AC voltage source. The output voltage of the VSI depends upon switching patterns applied to power transistors generated by space vector PWM. Additionally, the output of the VSI is supplied to the BLDC motor for speed control. The main purpose of this paper is to simulate and assess BLDC motor function via the MATLAB/Simulink environment, using SimPowerSystems and the Simscape toolbox, with the goals of improved power factor, lower THD, and better speed control. The PFC modified Zeta converter topology produced the best power factor, currently 0.981, which is better than other topologies, with a THD of only 9.81%, the lowest of all three topologies, which demonstrates the significance of the proposed model.

This study investigates the friction-reducing potential of “micro surface texturing” on H-13 steel metal surfaces. Tribological tests were performed on a ball-on-plate reciprocating tribometer using SAE30 oil. Circular micro textures with a 0.1 mm diameter and 5–8 µm depth were applied at varying area densities (5%, 10%, and 15%). The results were compared to identify the most effective area density for the micro textures. A friction reduction of 37.95% was observed compared to the untextured sample at 15% area density. The average friction for all the textures is reduced, which shows the effectiveness of laser surface texturing on tribological performance.

The study aims to conduct a consumer demand analysis of the food market of Pakistan by estimating its own price and cross-price elasticities. This study also examines expenditure and income elasticities to show the influence of relative change in price, total expenditure, and income on the relative change in demanded quantities of the selected food products. The study takes meat, vegetables, fruits, and pulses as different food baskets and estimates income elasticities, including uncompensated (Marshallian) and compensated (Hicksian) own price and cross-price elasticities. The findings are concluded based on Marshallian elasticity as it provides more accurate images of substitutes and complements compared with Hicksian elasticity. The study applies the Linear Approximate Almost Ideal Demand System model to estimate the results by acquiring data from a household integrated economic survey of Pakistan from 2018 to 2019. The findings of expenditure elasticity (uncompensated own price elasticity) reveal that vegetables and pulses are normal (inelastic) goods, whereas meat and fruits are luxury (elastic) goods. The results of uncompensated cross-price elasticities reveal that vegetables and meat, and vegetables and fruits are substitutable commodities. In addition, pulses and vegetables, and pulses and meat are complementary goods. The study suggests fruitful implications for food policymakers.

This study examines the R&D investment behaviour of different types of family-controlled firms with the moderating role of ownership discrepancy between cash-flow rights and excess voting rights by using the sufficiency conditions’ theoretical framework of ability and willingness developed by De Massis. It uses data from family firms that have issued A-shares from 2008 to 2018. They used pooled OLS regression for data analysis and Tobit regression for robustness checks. This study classifies family firm types into two categories, namely, the lone-controller family firms (LCFFs) and the multi-controller family firms (MCFFs), with each being further classified as “excess” or “no excess” voting rights. Both LCFFs without excess voting rights and MCFFs with excess voting rights have the “ability” and “willingness” toward R&D investment. LCFFs with excess voting rights and MCFFs without excess voting rights only have the ability but low willingness to invest in R&D. The study also establishes that Chinese family-controlled firms are heterogeneous toward risky investment. To the best of our knowledge, this study is the first to differentiate Chinese family firms by their unique ownership structure characteristics in investigating the effect of the family firm structure on R&D investment. The study is a novel attempt to test the willingness and ability framework of LCFFs and MCFFs. Previous studies based on agency theory have tacitly assumed that ability and willingness exist in family-controlled firms. However, this study challenges this implicit assumption.

Novel Coronavirus disease 2019 (nCOVID-19) a global pandemic is an ever-remaining threat for patients with Diabetic Mellites (DM). Herein, we have tried to provide brief insight to critically analyze the reasons causing the severity of Coronavirus disease (COVID-19) in patients diagnosed with DM. This, mini review highlights the key investigations starting from binding of COVID-19 at the cellular surface to create sever infection or even death in DM patients. The study further suggested to pay urgent attention towards stabilization of deadly immune response arises as a result of COVID-19. We hope the highlighted investigation will help the researchers to understand and develop a road map to deal DM patients infected with COVID-19 to minimize the severity rate.

Deterioration in the environmental quality is a major threat to the sustainable development of an economy as it results in serious economic problems and the researchers are conscious about the environment sustainability. They have identified several factors including financial development, inflow of foreign aid, and openness of trade to promote environmental sustainability. Unfortunately, their findings remain inconclusive as they have imperfectly measured environmental sustainability. This study, thus, aims to contribute to the ongoing debate of environmental sustainability by testing the role of financial development, trade openness, and foreign direct investment (FDI) in promoting environmental sustainability by using adjusted net savings as a measure of environmental sustainability. To do this, the study collects data from 1996 to 2019. The study uses financial development, trade openness, and FDI as predictors and environmental sustainability as an outcome variable. The study applies Auto Regressive Distributive Lag (ARDL) methodology to analyze the impact. The findings show positive contributions of financial development, trade openness, and foreign direct investment in promoting environment sustainability. We suggest encouraging trade through lower-taxation programs and increasing competition in the financial markets through privatization and domestic and international liberalization to stimulate environmental sustainability. We also recommend imposing high taxes and penalties on such activities that damage the quality of the environment.

The sucrose synthase (SS) is an important enzyme family which play a vital role in sugar metabolism to improve the fruit quality of the plants. In many plant species, the members of SS family have been investigated but the detailed information is not available in legumes particularly and Glycine max specifically. In the present study, we found thirteen SS members (GmSS1-GmSS13) in G. max genome. High conserved regions were present in the GmSS sequences that may due to the selection pressure during evolutionary events. The segmental duplication was the major factor to increase the number of GmSS family members. The identified thirteen GmSS genes were divided into Class I, Class II and Class III with variable numbers of genes in each class. The protein interaction of GmSS gave the co-expression of sucrose synthase with glucose-1-phosphate adenylyltransferase while SLAC and REL test found number of positive sites in the coding sequences of SS family members. All the GmSS family members except GmSS7 and few of class III members, were highly expressed in all the soybean tissues. The expression of the class I members decreased during seed development, whireas, the class II members expression increased during the seed developing, may involve in sugar metabolism during seed development. Solexa sequencing libraries of acidic condition (pH 4.2) stress samples showed that the expression of class I GmSS genes increased 1- to 2-folds in treated samples than control. The differential expression pattern was observed between the members of a paralogous. This study provides detailed genome-wide analysis of GmSS family in soybean that will provide new insights for future evolutionary and soybean breeding to improve the plant growth and development.

Spike (S) glycoprotein is an important virulent factor for coronaviruses (CoVs), and variants of CoVs have been characterized based on S gene analysis. We present phylogenetic relationship of an isolated infectious bronchitis virus (IBV) strain with reference to the available genome and protein sequences based on network, multiple sequence, selection pressure, and evolutionary fingerprinting analysis in People's Republic of China. One hundred and elven strains of CoVs i.e., Alphacoronaviruses (Alpha-CoVs; n = 12), Betacoronaviruses (Beta-CoVs; n = 37), Gammacoronaviruses (Gamma-CoVs; n = 46), and Deltacoronaviruses (Delta-CoVs; n = 16) were selected for this purpose. Phylogenetically, SARS-CoV-2 and SARS-CoVs clustered together with Bat-CoVs and MERS-CoV of Beta-CoVs (C). The IBV HH06 of Avian-CoVs was closely related to Duck-CoV and partridge S14, LDT3 (teal and chicken host). Beluga whale-CoV (SW1) and Bottlenose dolphin-CoVs of mammalian origin branched distantly from other animal origin viruses, however, making group with Avian-CoVs altogether into Gamma-CoVs. The motif analysis indicated well-conserved domains on S protein, which were similar within the same phylogenetic class and but variable at different domains of different origins. Recombination network tree indicated SARS-CoV-2, SARS-CoV, and Bat-CoVs, although branched differently, shared common clades. The MERS-CoVs of camel and human origin spread branched into a different clade, however, was closely associated closely with SARS-CoV-2, SARS-CoV, and Bat-CoVs. Whereas, HCoV-OC43 has human origin and branched together with bovine CoVs with but significant distant from other CoVs like SARS CoV-2 and SARS-CoV of human origin. These findings explain that CoVs' constant genetic recombination and evolutionary process that might maintain them as a potential veterinary and human epidemic threat.

Ruas Jalan yng menghubungkan antara Kota Pekanbaru-Dumai (terdiri dari 2-lajur 2-arah) adalah merupakan urat nadi transportasi penting di Provinsi Riau. Diproyeksikan ruas jalan ini akan over kapasitas pada tahun 2015. Oleh karena itu direncanakan akan diabgun jalan tol untuk mengatasi masalah tersebut. Namun, investasi untuk pembangunan jalan tol melibatkan beberapa tingkat risiko dan ketidakpastian, maka analisis dan pengelolaan risiko diperlukan dalam proses pembangunan jalan tol ini. Tujuan dari penelitian ini adalah untuk mengidentifikasi dan menganalisis risiko proyek (selama proyek tahap konstruksi). Studi ini mengukur nilai probabilitas risiko dan dampak risiko yang mungkin terjadi selama tahap konstruksi jalan tol. Besarnya masing-masing risiko dianalisis dan disimulasikan menggunakan perangkat lunak @ Risk. Dalam rangka untuk mendapatkan input data, survei dilaksnakan dalam dua tahap utama; (i) survei awal, dan (ii) survei detil. Kemudian dilakukan analisis risiko berdasarkan stokastik. Hasil analisis kemudian dibandingkan dengan parameter-parameter risiko yang diterbitkan oleh Puslitbang Pd-T-01-2005-B 2005. Diidentifikasi empat risiko utama yang dipengaruhi selama tahap konstruksi proyek, sebagai berikut; (i) risiko pembiayaan proyek, (ii) risiko pembangunan proyek, (iii) risiko peralatan, dan (iv) force majeure. Besarnya risiko yang mungkin terjadi selama proyek konstruksi jalan

Skin cancer is among the most prevalent and life-threatening forms of cancer that occur worldwide. Traditional methods of skin cancer detection need an in-depth physical examination by a medical professional, which is time-consuming in some cases. Recently, computer-aided medical diagnostic systems have gained popularity due to their effectiveness and efficiency. These systems can assist dermatologists in the early detection of skin cancer, which can be lifesaving. In this paper, the pre-trained MobileNetV2 and DenseNet201 deep learning models are modified by adding additional convolution layers to effectively detect skin cancer. Specifically, for both models, the modification includes stacking three convolutional layers at the end of both the models. A thorough comparison proves that the modified models show their superiority over the original pre-trained MobileNetV2 and DenseNet201 models. The proposed method can detect both benign and malignant classes. The results indicate that the proposed Modified DenseNet201 model achieves 95.50% accuracy and state-of-the-art performance when compared with other techniques present in the literature. In addition, the sensitivity and specificity of the Modified DenseNet201 model are 93.96% and 97.03%, respectively.

Tea (Camellia sinensis L.) leaves synthesize and concentrate a vast array of galloylated catechins (e.g., EGCG and ECG) and non-galloylated catechins (e.g., EGC, catechin, and epicatechin), together constituting 8%–24% of the dry leaf mass. Galloylated catechins account for a major portion of soluble catechins in tea leaves (up to 75%) and make a major contribution to the astringency and bitter taste of the green tea, and their pharmacological activity for human health. However, the catechin galloylation mechanism in tea plants is largely unknown at molecular levels. Previous studies indicated that glucosyltransferases and serine carboxypeptidase-like acyltransferases (SCPL) might be involved in the process. However, details about the roles of SCPLs in the biosynthesis of galloylated catechins remain to be elucidated. Here, we performed the genome-wide identification of SCPL genes in the tea plant genome. Several SCPLs were grouped into clade IA, which encompasses previously characterized SCPL-IA enzymes with an acylation function. Twenty-eight tea genes in this clade were differentially expressed in young leaves and vegetative buds. We characterized three SCPL-IA enzymes (CsSCPL11-IA, CsSCPL13-IA, CsSCPL14-IA) with galloylation activity toward epicatechins using recombinant enzymes. Not only the expression levels of these SCPLIA genes coincide with the accumulation of galloylated catechins in tea plants, but their recombinant enzymes also displayed β-glucogallin:catechin galloyl acyltransferase activity. These findings provide the first insights into the identities of genes encoding glucogallin:catechin galloyl acyltransferases with an active role in the biosynthesis of galloylated catechins in tea plants.

This paper presents an approach based on radio frequency identification (RFID) and machine learning for contamination sensing of food items and drinks such as soft drinks, alcohol, baby formula milk, etc. We employ sticker-type inkjet printed ultra-high-frequency (UHF) RFID tags for contamination sensing experimentation. The RFID tag antenna was mounted on pure as well as contaminated food products with known contaminant quantity. The received signal strength indicator (RSSI), as well as the phase of the backscattered signal from the RFID tag mounted on the food item, are measured using the Tagformance Pro setup. We used a machine-learning algorithm XGBoost for further training of the model and improving the accuracy of sensing, which is about 90%. Therefore, this research study paves a way for ubiquitous contamination/content sensing using RFID and machine learning technologies that can enlighten their users about the health concerns and safety of their food.

Abstract Background Strigolactones (SLs) play important roles in controlling root growth, shoot branching, and plant-symbionts interaction. Despite the importance, the components of SL biosynthesis and signaling have not been unequivocally explored in soybean. Results Here we identified the putative components of SL synthetic enzymes and signaling proteins in soybean genome. Soybean genome contains conserved MORE AXILLARY BRANCHING (MAX) orthologs, GmMAX1s, GmMAX2s, GmMAX3s, and GmMAX4s. The tissue expression patterns are coincident with SL synthesis in roots and signaling in other tissues under normal conditions. GmMAX1a, GmMAX2a, GmMAX3b, and GmMAX4a expression in their Arabidopsis orthologs’ mutants not only restored most characteristic phenotypes, such as shoot branching and shoot height, leaf shape, primary root length, and root hair growth, but also restored the significantly changed hormone contents, such as reduced JA and ABA contents in all mutant leaves, but increased auxin levels in atmax1, atmax3 and atmax4 mutants. Overexpression of these GmMAXs also altered the hormone contents in wild-type Arabidopsis. GmMAX3b was further characterized in soybean nodulation with overexpression and knockdown transgenic hairy roots. GmMAX3b overexpression (GmMAX3b-OE) lines exhibited increased nodule number while GmMAX3b knockdown (GmMAX3b-KD) decreased the nodule number in transgenic hairy roots. The expression levels of several key nodulation genes were also altered in GmMAX3b transgenic hairy roots. GmMAX3b overexpression hairy roots had reduced ABA, but increased JA levels, with no significantly changed auxin content, while the contrast changes were observed in GmMAX3b-KD lines. Global gene expression in GmMAX3b-OE or GmMAX3b-KD hairy roots also revealed that altered expression of GmMAX3b in soybean hairy roots changed several subsets of genes involved in hormone biosynthesis and signaling and transcriptional regulation of nodulation processes. Conclusions This study not only revealed the conservation of SL biosynthesis and signaling in soybean, but also showed possible interactions between SL and other hormone synthesis and signaling during controlling plant development and soybean nodulation. GmMAX3b-mediated SL biosynthesis and signaling may be involved in soybean nodulation by affecting both root hair formation and its interaction with rhizobia.

This unique study examines the alliance between board characteristics and shareholders assessment of risk as revealed in the volatility of stock returns for Pakistani listed companies. For this purpose, a sample of 30 manufacturing companies is used that are listed on Karachi Stock Exchange for the period of 2004 to 2013. The study uses panel data analysis and reports that random effect model is the best results yielding method. Our hypothesis incorporates preceding evidence that the small and large firms have spectacularly diverse constitution of boards, shimmering the firms diverse monitoring and counseling needs. It is hypothesized and locate confirmation with the intention of entrenched the large firms are able to produce affirmative net benefits, in the appearance of lesser risk, form board independence, gender diversity and director ownership. On the other hand the finding of this study showed the board size is negatively associated with the shareholder assessment of risk for large firms and the positive associated with the assessment of risk for small firms. The CEO duality is positive associated with the assessment of risk for large and negative associated amid assessment of risk for small firms. The results have insinuation for regulatory authorities, shareholders and directors to take steps to improve the board competanices for better performance.

The electronic and magnetic properties of X-C2N (X=F, Cl, Br and I) monolayers have been systematically investigated from first-principles calculations. The F atom can be strongly adsorbed on the top of the host carbon atoms, while the Cl, Br and I atoms favor the top of the host nitrogen atoms of C2N monolayers. These functionalized X-C2N (X=F, Cl, Br and I) monolayers exhibit interesting electronic and magnetic features. The F-C2N monolayer system shows a nonmagnetic metallic state, while the X-C2N (X=Cl, Br and I) monolayer systems exhibit the magnetic semiconducting ground state. Moreover, the ferromagnetic state is energetically more stable configuration for the X-C2N (X=Cl, Br and I) monolayer systems. Magnetic analysis further elaborates that the induced magnetism in the X-C2N (X=Cl, Br and I) monolayer systems mainly arises from the local magnetic moments of the halogen adatoms. Thus, the chemical functionalization of nitrogenated honey graphene through halogen atoms adsorption has promising applications in electronic devices.

First-principles calculations have been performed to study the chemically doped platinum diselenide (PtSe2) monolayers. We examine the stability of different doping sites by calculating the formation energy. The different electronic and magnetic characters originate from hybridization between the dopants and nearest local atoms. Exceptional electronic and magnetic characters are observed in the B-, P-, Li-, and Ca-doped cases because of doping site independence. The magnetic behavior of the dopant atoms is found to be complex because of interplay between strong structural relaxation, spin lattice coupling, and crystal field splitting. More interestingly, the ferromagnetic half metallic character obtained in B- and N-doped cases, expected to be very useful because of large half metallic energy bandgap. The interaction between dopants is analyzed as a function of their separation, showing that substitution typically counteracts spin polarization. The long range ferromagnetic behavior can be established with improved stability which suggest the high magnetic transition temperatures, found for the B-, F-, N-, P-, and Li-doped at Pt sites which make them potential candidate for applications in electronic devices as well as in spintronics.

In this paper, by using the concept of belongingness (∈) and quasi-coincidence (q) between fuzzy points and fuzzy sets, we introduce (α, β)-fuzzy positive implicative ideals in BCK-algebras where α, β are any of {∈, q, ∈ V q, ∈ ˄ q} with α ≠ ∈ ˄ q.

In this paper, the concepts of (∈γ,∈γ vqδ)-fuzzy fantastic ideals and (¯∈γ, ¯∈γ v ¯qδ)-fuzzy fantastic ideals in BCH-algebras are introduced and investigate some of their properties.

In this paper, we define the concepts of (∈, ∈ ∨ q) -interval valued fuzzy H-ideals and(∈, ∈ ∨ q) -interval valued fuzzy H-ideals in BCK-algebras and investigated some of theirrelated properties. Some characterizations of these generalized interval valued fuzzy H-idealare derived.

In this paper, the concepts of -fuzzy fantastic ideals and -fuzzy fantastic ideals in BCI-algebras are introduced and investigate some of their properties. The concept of a fuzzy fantastic ideal with thresholds, properties of a fuzzy fantastic ideal, an -fuzzy fantastic ideal and an -fuzzy fantastic ideal are discussed.

In the title compound, C17H25NO2, the morpholine ring adopts a chair conformation. The benzene ring makes a dihedral angle of 39.81 (13)° with the basal plane of the morpholine group.

In the title compound, C18H21NO3, the naphthalene group and the basal plane of the morpholine ring (r.m.s. deviations = 0.0177 and 0.0069 Å, respectively) are oriented at a dihedral angle of 44.0 (2)°. In the crystal, molecules are linked by C—H...π interactions.

The asymmetric unit of title compound, C12H15BrN2O4S, contains two molecules (A and B), with slightly different conformations: the bromophenyl rings and the SO2 planes of the sulfonyl groups are oriented at dihedral angles of 50.2 (2) (molecule A) and 58.24 (7)° (molecule B), and the ethyl acetate groups make dihedral angles of 63.99 (19)° (A) and 65.35 (16)° (B) with their bromophenyl groups. In the crystal, both molecules exist as inversion dimers linked by pairs of N—H...O hydrogen bonds, which generate R22(14) loops. The dimers are linked by C—H...O interactions.

Background: To evaluate the causes and management of emergency ileostomies Methods: In this prospective descriptive study all patients requiring emergency ileostomy were included. Initially patients were resuscitated by administering intravenous fluids and electrolyte replacement. All patients were operated in emergency under general anesthesia. The preoperative indication of ileostomy was noted in all patients. Emergency Laparotomies where primary repair was performed were excluded from the study. Results: Indications for emergency ileostomy creation were the conditions requiring small bowel or proximal colon resection, in which the integrity of a primary anastomosis would be compromised. This was due to a diffuse bowel injury (long-standing peritonitis or obstruction, radiation, Crohn's disease) creating friable tissues that could not hold a suture. Mean age of the patients was 36+12.59 years with a range of 12-61 years. Most common indication for ileostomy was typhoid intestinal perforation followed by tuberculosis of intestine. Skin excoriation was the most frequent complication noted in ileostomy patients. Conclusion: Infective disease is the most common indication for emergency ileostomy