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Abstract Floods accompanied by thunderstorms in developed cities are hazardous, causing damage to infrastructure. To secure infrastructure, it is important to employ an integrated approach, combining remote sensing, GIS and precipitation data. The model was developed based on the estimation of event-based runoff and investigated the relationship between runoff and impervious surfaces. The novel approach of combining Hydrologic Engineering Center’s River Analysis System (HEC-GeoRAS) along with satellite imagery was utilized, where spatial data was combined with real-time values to run the model. As a first step, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was fed with information about precipitation, slope, soil type, as well as land use and land cover. The results reveal that the subbasins of Deira, Nief and Jumeirah have the largest impervious area and, thus, a higher probability of flood occurrence. The model was calibrated and validated using previous runoff events and by comparing observed and simulated streak flow and peak discharge against those reported in previous studies. It was found that the model is efficient and can be used in similar regions.

In literature, it is usually very difficult to investigate the analytical and numerical solutions of fractional integro-differential equations (FIDEs). In the current work, the solutions to linear and non-linear FIDEs and their systems have been analyzed by using the Aboodh transform decomposition method (ATDM). The Aboodh transformation is first utilized to simplify the given problem, and then the decomposition method is implemented to obtain the required results. The Adomian polynomials and Daftardar–Jafari polynomials are used to control the non-linear term in the system. The obtained results are compared with both polynomials and with different fractional orders. We show that Daftardar–Jafari polynomials work more accurately for the proposed method than Adomian polynomials. The graphical and tabular representations are made to show the effectiveness of the proposed technique. The accuracy of ATDM is remarkable while using the proposed technique. It is observed that ATDM solutions very closed to the exact solutions of the problems. ATDM has a lower computation cost and higher rate of convergence and thus can be used to solve other non-linear fractional order integro-differential equations and their systems. Finally, we propose some future research directions by utilizing ATDM.

In hepatorenal syndrome-acute kidney injury (HRS-AKI), accurate and early diagnosis is crucial. HRS is a severe condition seen in advanced cirrhosis, requiring prompt recognition and proper management to enhance patient outcomes. Diagnosis of HRS-AKI relies on serum creatinine elevations, similar to other AKI cases in cirrhosis. However, distinguishing HRS-AKI from other renal impairments in these patients can be challenging. Biomarkers and clinical criteria aid in diagnosis and guide treatment. The management of HRS-AKI initially involves improving the haemodynamic profile using albumin and vasoconstrictors like terlipressin, a synthetic vasopressin analogue. Despite some reports linking terlipressin to increased adverse events compared with norepinephrine, it remains the preferred choice in HRS-AKI and acute-on-chronic liver failure due to its faster, stronger response and improved survival. Additional therapies like midodrine (alpha-1 adrenergic agonist), octreotide (somatostatin analogue) and transjugular intrahepatic portosystemic shunt are proposed as adjuvant treatments for HRS-AKI, aiming to improve vasoconstriction and renal blood flow. However, these adjunctive therapies cannot replace the definitive treatment for HRS-AKI—liver transplantation (LT). In cases unresponsive to medical management, LT is the only option to restore liver function and improve renal outcomes. Current evidence favours combined liver and kidney transplantation (CLKT) in certain situations. This review aims to evaluate the present evidence and recommendations on AKI in patients with cirrhosis, the pathophysiology of HRS-AKI, different treatments and indications for LT and CLKT. Understanding the complexities of managing HRS-AKI is crucial for optimising patient care and achieving better outcomes in this challenging clinical setting.

This article implements an efficient analytical technique within three different operators to investigate the solutions of some fractional partial differential equations and their systems. The generalized schemes of the proposed method are derived for every targeted problem under the influence of each fractional derivative operator. The numerical examples of the non-homogeneous fractional Cauchy equation and three-dimensional Navier-Stokes equations are obtained using the new iterative transform method. The obtained results under different fractional derivative operators are found to be identical. The 2D and 3D plots have confirmed the close connection between the exact and obtained results. Moreover, the table shows the higher accuracy of the proposed method.

Objective: To determine the role of Neutrophil Lymphocyte Ratio as an inflammatory marker in Rheumatoid Arthritis. Study Design: Cross-sectional analytical study. Place and Duration of Study: Rheumatology Department, National Hospital and Medical Center, Lahore Pakistan, from Mar to Sep 2021. Methodology: After approval from Institutional Ethical Review Board, 160 patients diagnosed with rheumatoid arthritis, aged 21-80 years, were enrolled. Demographic information and medical history were obtained and divided into two groups: Active disease (DAS-28 score>3.2) and LDA/remission (DAS-28 score

Objectives: Smoking is a potent risk factor for coronary artery disease, but there is controversy about its protective nature in terms of prognosis in ST-elevation acute coronary syndrome patients undergoing primary percutaneous coronary intervention. So, the main objective of this study is to unfold this controversy in a South Asian population in terms of clinical angiographic parameters and its in-hospital outcomes. Methods: In this study, we included 1756 consecutive patients diagnosed with ST-elevation acute coronary syndrome undergoing primary percutaneous coronary intervention. Patients were classified into smokers and non-smokers, and the in-hospital mortality rate was compared. Multivariable logistic regression analysis was performed to evaluate the paradoxical role of smoking. Results: Smokers were younger (53.78 ± 11.16 years vs 56.43 ± 11.17 years; p

Integrating nanotechnology in dielectric fluid significantly inhibits losses and boosts overall dielectric fluid performance. There has been research done on the effects of introducing various nanoparticles, such as titania, alumina, silica nanodiamonds, etc. In this paper, a novel nanoparticle, Ceria (CeO2), has been used, and its properties were examined using the FTIR (Fourier Transform Infrared) spectrum, the XRD (X-ray Diffraction) spectrum, the SEM (Scanning Electron Microscopy), and the TEM (Transmission Electron Microscopy). This paper illustrates an efficient dielectric fluid prepared by the successful dispersion of Cerium Oxide (CeO2) nanoparticles in various concentrations into four commercial oils, namely mineral oil, rapeseed oil, synthetic ester oil, and soybean oil, to enhance and improve their dielectric characteristics. The performance investigation emphasises breakdown strength enhancement and other dielectric properties of the colloidal solution comprising different nanoparticle (NP) concentrations. Various commercial oils are used as a base in nano-oil to diversify their applicability as dielectric fluids by measuring the correlation in dielectric parameters and statistically assessing their applicability with normal and Weibull distributions. The obtained experimental data sets were analyzed using the Statistics and Machine Learning Toolbox in MATLAB. The aging measurement has been done only on mineral oil, and results were matched using a predictive model of statistics and the Machine Learning Toolbox in MATLAB. Well-dispersed CeO2 NPs in the insulating oils lead to a significant increase in AC breakdown strength. The effect of ageing on the dielectric properties of nano oils yields better results than conventionally aged oil. It has been observed that the breakdown voltage is enhanced by up to 30% for mineral oil at an optimal concentration of 0.01 g/L, 9% for synthetic ester oil at 0.03 g/L, 18% for rapeseed oil at 0.02 g/L, and 19% for soybean oil at 0.03 g/L nanoparticle concentration. Following the dispersion of CeO2 nanoparticles, the dielectric constant of all insulating oils has also significantly improved.The overall experimental results are promising and show the potential of the CeO2 NPs-based nano oil as an efficient and highly performing dielectric oil for different power applications.

Vision Transformers (ViT) are commonly utilized in image recognition and related applications. It delivers impressive results when it is pre-trained using massive volumes of data and then employed in mid-sized or small-scale image recognition evaluations such as ImageNet and CIFAR-100. Basically, it converts images into patches, and then the patch encoding is used to produce latent embeddings (linear projection and positional embedding). In this work, the patch encoding module is modified to produce heterogeneous embedding by using new types of weighted encoding. A traditional transformer uses two embeddings including linear projection and positional embedding. The proposed model replaces this with weighted combination of linear projection embedding, positional embedding and three additional embeddings called Spatial Gated, Fourier Token Mixing and Multi-layer perceptron Mixture embedding. Secondly, a Divergent Knowledge Dispersion (DKD) mechanism is proposed to propagate the previous latent information far in the transformer network. It ensures the latent knowledge to be used in multi headed attention for efficient patch encoding. Four benchmark datasets (MNIST, Fashion-MNIST, CIFAR-10 and CIFAR-100) are used for comparative performance evaluation. The proposed model is named as SWEKP-based ViT, where the term SWEKP stands for Stochastic Weighted Composition of Contrastive Embeddings & Divergent Knowledge Dispersion (DKD) for Heterogeneous Patch Encoding. The experimental results show that adding extra embeddings in transformer and integrating DKD mechanism increases performance for benchmark datasets. The ViT has been trained separately with combination of these embeddings for encoding. Conclusively, the spatial gated embedding with default embeddings outperforms Fourier Token Mixing and MLP-Mixture embeddings.

Adults who have brain tumors face a serious and potentially fatal challenge since the tumors rapidly growing malignant cells can seriously impair their physiological ability. In clinical practice, imaging techniques such as MRI, PET, and CT scans are widely used to determine the size, kind, and location of tumors. The goal of this research is to create a Computer-Aided Diagnostic (CAD) system that can automatically segment and classify brain tumors utilizing T1W-CE Magnetic Resonance Imaging (MRI) of the brain. The CAD system will involve two primary tasks: tumor classification, which determines the type of tumor depicted in the image, and tumor segmentation, which involves accurately determine the tumor region from the surrounding healthy tissue. By automating these processes, the proposed system aims to enhance the accuracy and effectiveness of brain tumor diagnosis and treatment planning. The classification of brain tumors into multiple classes is recognized as a complex challenge within the field of medical imaging. This research article proposes a model named VS-BEAM that can be used efficiently for clinical decision-making. The proposed VS-BEAM (Voting Based Semi-Supervised Bayesian Ensemble Attention Mechanism) model has been examined for a brain tumor’s multi-class classification. The VS-BEAM model achieved the highest level of accuracy possible. The proposed work achieves maximum sensitivity, specificity, and diagnostic accuracy compared to existing models using T1W-CE MRI images. A convolutional autoencoder is utilized for extracting tumors from MRI images. The accuracy obtained from testing data of 264 brain tumors was 98.91%, indicating that the method is effective and can be used in the clinical context to assist in detecting larger or even smaller tumors.

Abstract The Emirate of Abu Dhabi has relied on groundwater as a source of fresh water for several decades, which has resulted in the deterioration of non-renewable groundwater aquifers. This has led to the installation of desalination plants for fresh water supply. This research aims to increase strategic water reserves in the eastern district of Abu Dhabi by analyzing the best locations for aquifer storage and recovery (ASR). The ASR technology offers an opportunity to store large volumes of water for later beneficial use. This study explores an option of using excess desalination water for ASR recharge in the eastern district Al Ain region of Abu Dhabi. A limiting factor in the application of the ASR technology is the lack of suitable sites. Detailed hydrogeological and operational knowledge of the studied areas helped in identifying potential sites for ASR based on a scoring system. Determining best locations for managed aquifer recharge is a crucial design step. Five scenarios were studied at Al-Khrair and Al-Shuwaib sites in Al Ain region. Results show that a wider distribution of injection wells with intervals more than 1200 m is more suitable to overcome the excessive head buildup. Based on the adopted criteria, Al-Khrair was the best site for recharge followed by Al-Shuwaib. Al-Khrair site can be recharged at 64,000 m3 d−1 for seven years, while Al-Shuwaib site can be recharged at 64,000 m3 d−1 for only two years.

Objective: to determine the frequency of joint hypermobility in paramedical students and staff at National Hospital Lahore. Study Design: Cross-sectional study. Place and Duration of Study: Department of Rheumatology, National Hospital and Medical Center, Lahore Pakistan, from Mar to Sep 2021. Methodology: Two hundred fifty paramedical students and staff of either gender, aged between 16 years to 35 years were enrolled. Localized Joint Hypermobility was defined as 4 scores on the Beighton Score Scale. Demographic information was obtained from each participant, and joint hypermobility was assessed by using the Beighton score. Results: Mean age of the study participnats was 26.6±4.6 years with 146(58.24%) females. Mean BMI was 23.9±4.0 kg/m2. Generalized Joint Hypermobility was seen in 51(20.4%), and 31(12.4%) had localized hypermobility. Out of 250 participants, 33 (13.2%) had musculoskeletal pain, while among 51 patients with generalized hypermobility, 12(23.5%) had musculoskeletal pain. Conclusion: One out of every five young healthy paramedics enrolled had generalized joint hypermobility. One-third of subjects had at least one clinically documented hypermobile joint. Almost every fourth person with generalized joint hypermobility has musculoskeletal pain compared to 1 in 10 persons without generalized hypermobility. Keywords: Beighton score scale, Generalized joint hypermobility, Localized joint hypermobility, Musculoskeletal pain.

Post‐transplant diabetes mellitus (PTDM) is a significant contributor to morbidity and mortality in liver transplant recipients (LTRs). With concurrent comorbidities and use of various immunosuppression medications, identifying a safe and personalized regimen for management of PTDM is needed. There are many comorbidities associated with the post‐transplant course including chronic kidney disease, cardiovascular disease, allograft steatosis, obesity, and de novo malignancy. Emerging data suggest that available diabetes medications may carry beneficial or, in some cases, harmful effects in the setting of these co‐existing conditions. Sodium‐glucose co‐transporter 2 inhibitors and glucagon‐like peptide 1 receptor agonists have shown the most promising beneficial results. Although there is a deficiency of LTR‐specific data, they appear to be generally safe. Effects of other medications are varied. Metformin may reduce the risk of malignancy. Pioglitazone may be harmful in patients combatting obesity or heart failure. Insulin may exacerbate obesity and increase the risk of developing malignancy. This review thoroughly discusses the roles of these extra‐glycemic effects and safety considerations in LTRs. Through weighing the risks and benefits, we conclude that alternatives to insulin should be strongly considered, when feasible, for personalized long‐term management based on risk factors and co‐morbidities.

Abstract Modern‐day society requires advanced technologies based on renewable and sustainable energy resources to face the challenges regarding environmental remediation. Solar‐inspired photocatalytic applications for water purification, hydrogen and oxygen evolution, carbon dioxide reduction, nitrogen fixation, and removal of bacterial species seem to be unique solutions based on green and efficient technologies. Considering the unique electronic features and larger surface area, 2D photocatalysts have been broadly explored for the above‐mentioned applications in the past few years. However, their photocatalytic potential has not been optimized yet to the adequate level of practical and commercial applications. Among many strategies available, surface and interface engineering and the hybridization of different materials have revealed pronounced potential to boost the photocatalytic potential of 2D materials. This feature review recapitulates recent advancements in engineered materials that are 2D for various photocatalysis applications for environmental remediation. Various surface and interface engineering technologies are briefly discussed, like anion–cation vacancies, pits, distortions, associated vacancies, etc., along with rules and parameters. In addition, several hybridization approaches, like 0D/2D, 1D/2D, 2D/2D, and 3D/2D hybridization, etc., are also deeply investigated. Lastly, the application of these engineered 2D materials for various photocatalytic applications, challenges, and future perspectives is extensively explored.

In the current note, we broaden the utilization of a new and efficient analytical computational scheme, approximate analytical method for obtaining the solutions of fractional-order Fokker-Planck equations. The approximate solution is obtained by decomposition technique along with the property of Riemann-Liouuille fractional partial integral operator. The Caputo-Riemann operator property for fractional-order partial differential equations is calculated through the utilization of the provided initial source. This analytical scheme generates the series form solution which is fast convergent to the exact solutions. The obtained results have shown that the new technique for analytical solutions is simple to implement and very effective for analyzing the complex problems that arise in connected areas of science and technology.

A new technique of the Adomian decomposition method is developed and applied in this research article to solve two-term diffusion wave and fractional telegraph equations with initial-boundary conditions. The proposed technique is used to solve problems of both fractional and integer orders of the telegraph equations. The fractional-order solutions provide useful information about the data transmission from one point to another. The solutions are obtained in the form of an infinite series, demonstrating a high rate of accuracy from fractional to integer orders of the problems. The technique’s accuracy is verified by drawing various fractional and integer order plots and tables. The fractional-order plots demonstrate that the solutions have a higher rate of accuracy, and the different dynamical behaviors of the problems are revealed as a result. It is discovered that the new Adomian decomposition method is the best option for solving initial-boundary value problems. The new approximations of each solution improve the method’s accuracy. As a result, it is suggested that the method can be applied to other problems with initial-boundary conditions.

BackgroundThe storage of antimicrobials at home is frequently in-practice in various developing countries, resulting an irrational use, antibiotic resistance, and toxicities. This condition may worsen more in conflict zones where health facilities are limited. This study aimed to determine the storage and use of leftover antibiotics among households (HHs) along with knowledge and awareness about antibiotics and antibiotic resistance (ABR).MethodsA descriptive cross-sectional study design was employed. Members of HHs were invited to participate in the survey while using a convenient sampling technique. The data were obtained using a validated questionnaire and analyzed through SPSS.ResultsA total of 96 HHs were randomly selected from two districts (n = 50, n = 46), with most of the participants being men between the ages of 18 and 28 (n = 45, 46.9%) years. The majority of HHs (n = 32, 33.3%) had six to eight total family members, with one to two chronic diseases (n = 63, 65.6%), individual families (n = 60, 62.5%), and with (n = 35, 36.5%) LRTIs (lower respiratory tract infections). The HHs were aware of the word “antibiotic” (n = 59, 61.5%) and gave correct replies to amoxicillin as an antibiotic (n = 42, 43.8%); on the other hand, HHs also thought of paracetamol as an antibiotic (n = 45, 47.9%). They identified the most common brands of antibiotics easily, and a majority of them (n = 69, 71.9%) had never heard of ABR before and had lower levels of awareness. The most stored antibiotic at home (n=38, 39.6%) was azithromycin (J01FA10). In addition, they had multiple needless (1–2, n = 62, 64.6%; 3–4, n = 29, 30.2%) and antibiotics in their houses. Age had a strong association (p = 0.017, H = 12) affected the mean knowledge scores related to antibiotic use. Association of education levels (p = 0.001, H = 52.8) and occupation (p = 0.04, H = 10) with proper antibiotics use were found to be significant. However, family members with more than one chronic illness (p = 0.09, H = 0.8) showed a significant relationship with their awareness of antibiotics.ConclusionParticipants generally stored various antibiotics of different classes in their homes. Lack of knowledge related to the appropriate usage of antibiotics, use of leftover antibiotics, and awareness related to ABR were unknown to the participants.

Abstract Nanotechnology has been applied in the electrical industry for the enhancement of insulation properties. The compactness of the electrical machines has resulted in the requirement and creation of next‐generation insulating fluid with inflated dielectric properties. In this study, the magnetic nanoparticles are used in different concentrations to form stable nanofluids comprising ester‐based oils and two different electrode structures. The host fluids are synthetic ester oil and rapeseed oil, and magnetic nanoparticles used are iron (II, III) oxide, cobalt (II, III) oxide, and iron phosphide. Furthermore, the breakdown tests are analysed using Weibull statistical distribution.

The solutions to fractional differentials equations are very difficult to investigate. In particular, the solutions of fractional partial differential equations are challenging tasks for mathematicians. In the present article, an extension to this idea is presented to obtain the solutions of non-linear fractional Korteweg–de Vries equations. The solutions comparison of the proposed problems is done via two analytical procedures, which are known as the Residual power series method (RPSM) and q-HATM, respectively. The graphical and tabular analysis are presented to show the reliability and competency of the suggested techniques. The comparison has shown the greater contact between exact, RPSM, and q-HATM solutions. The fractional solutions are in good control and provide many important dynamics of the given problems.

In this article, a new modification of the Adomian decomposition method is performed for the solution fractional order convection–diffusion equation with variable coefficient and initial–boundary conditions. The solutions of the suggested problems are calculated for both fractional and integer orders of the problems. The series of solutions of the problems with variable coefficients have been provided for the first time. To verify and illustrate our new technique, four numerical examples are presented and solved by using the proposed technique. The derived results are plotted, and the dynamics are shown for both fractional and integer orders of the problems. An excellent variation among the solutions at various fractional orders is observed. It is analyzed that the new technique based on the Adomian decomposition method is accurate and effective. The present method fits both the initial and boundary conditions with double approximations simultaneously, which increases the accuracy of the present method. For the first time, the present technique is used for the solutions of the problems with variable coefficients along with initial and boundary conditions. It is therefore suggested to apply the present procedure for the solutions of other problems with variable order and coefficients along with initial and boundary conditions.

In this research article the residual power series method is implemented for the solution of the Navier-stokes equations with two and three dimensions having the initial conditions. Caputo operator is used for the fractional derivative. The formulation is made in general form and then applied to the specific problems to check the validity of the suggested method. The solution of some numerical examples of the Navier-stokes equations are presented for both fractional and integer orders of the problems. The comparison of the obtained and exact solution is provided by using 2D and 3D plots of the solutions which confirmed the higher accuracy of the proposed method. Tables are drawn to show the results obtained, exact solutions and absolute error of the suggested method for each problem. It is investigated that as the number of terms increase in the series solution of the problems, the obtained solutions have the closed contact with actual solutions of each problem. From the calculated values it is cleared that the method is accurate and easy and therefore can be extended further to linear and nonlinear problems.

In the present work, an Elzaki transformation is combined with a decomposition technique for the solutions of fractional dynamical systems. The targeted problems are related to the systems of fractional partial differential equations. Fractional differential equations are useful for more accurate modeling of various phenomena. The Elzaki transform decomposition method is implemented in a very simple and straightforward manner to solve the suggested problems. The proposed technique requires fewer calculations and needs no discretization or parametrization. The derivative of fractional order is represented in a Caputo form. To show the conclusion, which is drawn from the results, some numerical examples are considered for their approximate analytical solution. The series solutions to the targeted problems are obtained having components with a greater rate of convergence toward the exact solutions. The new results are represented by using tables and graphs, which show the sufficient accuracy of the present method as compared to other existing techniques. It is shown through graphs and tables that the actual and approximate results are very close to each other, which shows the applicability of the presented method. The fractional-order solutions are in best agreement with the dynamics of the given problems and provide infinite choices for an optimal solution to the suggested mathematical model. The novelty of the present work is that it applies an efficient procedure with less computational cost and attains a higher degree of accuracy. Furthermore, the proposed technique can be used to solve other nonlinear fractional problems in the future, which will be a scientific contribution to research society.

A document’s keywords provide high-level descriptions of the content that summarize the document’s central themes, concepts, ideas, or arguments. These descriptive phrases make it easier for algorithms to find relevant information quickly and efficiently. It plays a vital role in document processing, such as indexing, classification, clustering, and summarization. Traditional keyword extraction approaches rely on statistical distributions of key terms in a document for the most part. According to contemporary technological breakthroughs, contextual information is critical in deciding the semantics of the work at hand. Similarly, context-based features may be beneficial in the job of keyword extraction. For example, simply indicating the previous or next word of the phrase of interest might be used to describe the context of a phrase. This research presents several experiments to validate that context-based key extraction is significant compared to traditional methods. Additionally, the KeyBERT proposed methodology also results in improved results. The proposed work relies on identifying a group of important words or phrases from the document’s content that can reflect the authors’ main ideas, concepts, or arguments. It also uses contextual word embedding to extract keywords. Finally, the findings are compared to those obtained using older approaches such as Text Rank, Rake, Gensim, Yake, and TF-IDF. The Journals of Universal Computer (JUCS) dataset was employed in our research. Only data from abstracts were used to produce keywords for the research article, and the KeyBERT model outperformed traditional approaches in producing similar keywords to the authors’ provided keywords. The average similarity of our approach with author-assigned keywords is 51%.

This comparative study of fractional nonlinear fractional Burger’s equations and their systems has been done using two efficient analytical techniques. The generalized schemes of the proposed techniques for the suggested problems are obtained in a very sophisticated manner. The numerical examples of Burger’s equations and their systems have been solved using Laplace residual power series method and Elzaki transform decomposition method. The obtained results are compared through graphs and tables. The error tables have been constructed to show the associated accuracy of each method. The procedures of both techniques are simple and attractive and, therefore, can be extended to solve other important fractional order problems.

Abstract In recent years, emerging two-dimensional (2D) platinum diselenide (PtSe2) has quickly attracted the attention of the research community due to its novel physical and chemical properties. For the past few years, increasing research achievements on 2D PtSe2 have been reported toward the fundamental science and various potential applications of PtSe2. In this review, the properties and structure characteristics of 2D PtSe2 are discussed at first. Then, the recent advances in synthesis of PtSe2 as well as their applications are reviewed. At last, potential perspectives in exploring the application of 2D PtSe2 are reviewed.

Abstract Background QT interval prolongation is a growing concern worldwide, posing psychiatric patients to life-threatening fatal arrhythmias i.e., torsade de pointes. This study aimed to identify the prevalence of QT interval prolongation, its associated risk factors and prescribing patterns of QT prolonging drugs among psychiatric patients. Method A prospective observational study was conducted that included psychiatric patients from a tertiary care hospital and a psychiatry clinic in Peshawar, Khyber Pakhtunkhwa, Pakistan. Electrocardiogram was recorded of those patients who were using psychotropic medications for ≥7 days, aged 18 years or more, and of either gender, male or female. The Fredericia correction formula was used for measuring QTc values (corrected QT). Chi-square test was applied to estimate differences between patients with or without prolonged QTc interval whereas, logistic regression analysis was performed to identify various predictors of QT interval prolongation. Results Out of 405 patients, the QTc interval was prolonged in 23 (5.7%) patients including 1 (0.2%) patient with highly abnormal prolonged QTc interval (> 500 ms). QT drugs (91.6%), female sex (38.7%) and hypertension (10.6%) were the most common QT prolonging risk factors. Prolonged QTc interval was significantly higher among male patients (p = 0.007). Conclusion In the present study, QT interval prolongation was observed in a considerable number of psychiatric patients. While, the high prevalence of QT prolonging risk factors among these patients warrants the increased risk of fatal arrhythmias. Therefore, risk assessment and electrocardiographic monitoring, and prescription of safer alternatives are highly recommended.

Background & Objectives Stool ova and parasite (O&P) examinations are routinely ordered initial tests in patients admitted to the hospital with acute diarrhea, despite low test positivity rates. We examined the diagnostic yield of inpatient stool O&P exams and identified risk factors associated with positive tests. Methods A retrospective, case-control analysis of inpatients admitted with diarrhea, who underwent O&P examination, was conducted. Clinical and demographic variables of cases were compared with age-and gender-matched controls via uni- and multivariate conditional logistic regression analyses. Results The yield of inpatient O&P exams was 2.15% (37/1723). Blastocystisspp. represented the most common parasites. All patients with positive tests, excluding Blastocystisspp., had at least one of the following risk factors: smoking, prior parasitic disease, HIV-positive status, travel to an endemic area, and institutionalization. Conclusions Superfluous inpatient stool O&P exams confer a financial and labor burden to hospital systems. Stool O&P exams should be restricted to individuals admitted to the hospital for 7 days and possessing at least one of the following risk factors: smoking, prior parasitic disease, HIV-positive status, travel to an endemic area, and institutionalization. Such selective testing can confer a 51% reduction in testing, costs, and labor.

Abstract Thermoelectric generators have attracted a wide research interest owing to their ability to directly convert heat into electrical power. Moreover, the thermoelectric properties of traditional inorganic and organic materials have been significantly improved over the past few decades. Among these compounds, layered two-dimensional (2D) materials, such as graphene, black phosphorus, transition metal dichalcogenides, IVA–VIA compounds, and MXenes, have generated a large research attention as a group of potentially high-performance thermoelectric materials. Due to their unique electronic, mechanical, thermal, and optoelectronic properties, thermoelectric devices based on such materials can be applied in a variety of applications. Herein, a comprehensive review on the development of 2D materials for thermoelectric applications, as well as theoretical simulations and experimental preparation, is presented. In addition, nanodevice and new applications of 2D thermoelectric materials are also introduced. At last, current challenges are discussed and several prospects in this field are proposed.

Recently, nanofluids are introduced in the power utilities for the dielectric performance enhancement of power transformer oil. The compactness and fault improvement of the power transformers has resulted in the necessity of next-generation insulating fluid with inflated dielectric properties. This article investigates the dielectric performance of the novel ester oil-based magnetic nanofluids with different nanoparticles under different electric stress conditions. Two biodegradable fluids used as the base liquid for the experiment are synthetic ester oil and natural ester oil while three magnetic nanoparticles used to synthesize nanofluids are iron (II, III) oxide, cobalt (II, III) oxide, and iron phosphide. The concentrations of the nanoparticles are varied to optimize the characteristics of the prepared nanofluids. The dielectric breakdown and relative permittivity of the nanofluids have been experimentally investigated. Further, the breakdown predictions have been performed using Weibull statistical distribution-based regression analysis. The experimental results show the improvement in the characteristics of prepared nanofluids with the change in nanoparticle concentration as compared with the host fluids.

In this paper, the higher nonlinear problems of fractional advection-diffusion equations and systems of nonlinear fractional Burger’s equations are solved by using two sophisticated procedures, namely, the q-homotopy analysis transform method and the residual power series method. The proposed methods are implemented with the Caputo operator. The present techniques are utilised in a very comprehensive and effective manner to obtain the solutions to the suggested fractional-order problems. The nonlinearity of the problem was controlled tactfully. The numerical results of a few examples are calculated and analyzed. The tables and graphs are constructed to understand the higher accuracy and applicability of the current method. The obtained results that are in good contact with the actual dynamics of the given problem, which is verified by the graphs and tables. The present techniques require fewer calculations and are associated with a higher degree of accuracy, and therefore can be extended to solve other high nonlinear fractional problems.

Floods are among the devastating types of disasters in terms of human life, social and financial losses. Authoritative data from flood gauges are scarce in arid regions because of the specific type of dry climate that dysfunctions these measuring devices. Hence, social media data could be a useful tool in this case, where a wealth of information is available online. This study investigates the reliability of flood related data quality collected from social media, particularly for an arid region where the usage of flow gauges is limited. The data (text, images and videos) of social media, related to a flood event, was analyzed using the Machine Learning approach. For this reason, digital data (758 images and 1413 video frames) was converted into numeric values through ResNet50 model using the VGG-16 architecture. Numeric data of images, videos and text was further classified using different Machine Learning algorithms. Receiver operating characteristics (ROC) curve and area under curve (AUC) methods were used to evaluate and compare the performance of the developed machine learning algorithms. This novel approach of studying the quality of social media data could be a reliable alternative in the absence of real-time flow gauges data. A flash flood that occurred in the United Arab Emirates (UAE) from March 7–11, 2016 was selected as the focus of this study. Random forest showed the highest accuracy of 80.18% among the five other classifiers for images and videos. Precipitation/rainfall data were used to validate social media data, which showed a significant relationship between rainfall and the number of posts. The validity of the machine learning models was assessed using the area under the curve, precision-recall curve, root mean square error, and kappa statistics to confirm the validity and accuracy of the model. The data quality of YouTube videos was found to have the highest accuracy followed by Facebook, Flickr, Twitter, and Instagram. These results showed that social media data could be used when gauge data is unavailable.

In general, solving fractional partial differential equations either numerically or analytically is a difficult task. However, mathematicians have tried their best to make the task easy and promoted various techniques for their solutions. In this regard, a very prominent and accurate technique, which is known as the new technique of the Adomian decomposition method, is developed and presented for the solution of the initial-boundary value problem of the diffusion equation with fractional view analysis. The suggested model is an important mathematical model to study the behavior of degrees of memory in diffusing materials. Some important results for the given model at different fractional orders of the derivatives are achieved. Graphs show the obtained results to confirm the accuracy and validity of the suggested technique. These results are in good contact with the physical dynamics of the targeted problems. The obtained results for both fractional and integer orders problems are explained through graphs and tables. Tables and graphs support the physical behavior of each problem and the best of physical analysis. From the results, it is concluded that as the fractional order derivative is changed, the graphs or paths of dynamics are also changed. Therefore, we now choose the best solution or dynamic of the problem at a particular derivative order. It is analyzed that the present technique is one of the best techniques to handle the solutions of fractional partial differential equations having initial and boundary conditions (BCs), which are very rare in literature. Furthermore, a small number of calculations are done to achieve a very high rate of convergence, which is the novelty of the present research work. The proposed method provides the series solution with twice recursive formulae to increase the desired accuracy and is preferred among the best techniques to find the solution of fractional partial differential equations with mixed initials and BCs.

Modular multilevel converters (MMCs) have been conceived as an alternative in front-end converter applications to enhance the converter system’s reliability, minimize total harmonic distortion, and improve power quality. These converters utilize several DC-link capacitors and power electronic switches, along with switches operating with high switching frequencies, to attain the desired characteristics. Thereby, this paper systematically proposes a novel three-phase asymmetric hybrid modular multilevel converter (AHMMC) for front-end converters used in lower-medium-voltage applications. The AHMMC configuration is based on a three-phase converter connected to a per-phase series arrangement with a cascaded converter module (CCM). The study investigates the AHMMC and proposes a control scheme, which minimizes the voltage range on switches and maintains the current to its reference value. Furthermore, the study also introduces an active balancing of voltage across DC-link capacitors based on the phase opposition disposition PWM (POD-PWM) method. Our new configuration has features such as low switching loss, reduced DC-link voltage, a wider modulation range for the unity power factor (PF), and low voltage and current harmonic distortion. The simulation results are added to verify the performance of the new AHMMC topology and the usefulness of the modular control scheme. In addition, a low-voltage laboratory prototype based on customized control and power boards is built to validate the proposed converter and its control scheme in practice.

Abstract We present a comparative study of the toxicity of polyethylene glycol (PEG)–coated cobalt ferrite nanoparticles and nanospheres. Nanoparticles were prepared by hydrothermal method while nanospheres were prepared by solvothermal technique. The surface of nanomaterials was successfully modified with polyethylene glycol. To investigate the morphology of the prepared samples, X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, thermogravimetric analysis (TGA), and electron microscopy techniques were employed. Structural analyses confirmed the formation of polycrystalline cobalt ferrite nanoparticles with diameters in the range 20–25 nm and nanospheres in the range 80–100 nm, respectively. Kunming SPF mice (female, 6–8 weeks old) were used to investigate the toxicity induced by cobalt ferrite nanoparticles and nanospheres in different organs of the mice. Biodistribution studies, biochemical indices, histopathological assessments, inflammatory factors, oxidation and antioxidant levels, and cytotoxicity tests were performed to assess the toxicity induced by cobalt ferrite nanoparticles and nanospheres in mice. Cobalt ferrite nanospheres were found to be more toxic than the nanoparticles and curcumin was proved to be a good healing agent for the toxicity induced by PEG-coated cobalt ferrite nanomaterials in mice.

Abstract Since the last decades, non-precious metal catalysts (NPMC), especially iron based electrocatalysts show sufficient activity, potentially applicant in oxygen reduction reaction (ORR), however they only withstand considerable current densities at low operating potentials. On the other hand iron based electrocatalysts are not stable at elevated cathode potentials, which is essential for high energy competence, and its remains difficult to deal. Therefore, via this research a simple approach is demonstrated that allows synthesis of nanosize Fe-doped mayenite electride, [Ca24Al28O64]4+·(e−)4 (can also write as, C12A7−xFex:e−, where doping level, x = 1) (thereafter, Fe-doped C12A7:e−), consist of abundantly available elements with gram level powder material production, based on simple citrate sol-gel method. The maximum achieved conductivity of this first time synthesized Fe-doped C12A7:e− composite materials was 249 S/cm. Consequently, Fe-doped C12A7:e− composite is cost-effective, more active and highly durable precious-metal free electrocatalyst, with 1.03 V onset potential, 0.89 V (RHE) half-wave potential, and ~5.9 mA/cm2 current density, which is higher than benchmark 20% Pt/C (5.65 mA/cm2, and 0.84 V). The Fe-doped C12A7:e− has also higher selectivity for desired 4e− pathway, and more stable than 20 wt% Pt/C electrode with higher immunity towards methanol poisoning. Fe-doped C12A7:e− loses was almost zero of its original activity after passing 11 h compared to the absence of methanol case, indicates that to introduce methanol has almost negligible consequence for ORR performance, which makes it highly desirable, precious-metal free electrocatalyst in ORR. This is primarily described due to coexistence of Fe-doped C12A7:e− related active sites with reduced graphene oxide (rGO) with pyridinic-nitrogen, and their strong coupling consequence along their porous morphology textures. These textures assist rapid diffusion of molecules to catalyst active sites quickly. In real system maximum power densities reached to 243 and 275 mW/cm2 for Pt/C and Fe-doped C12A7:e− composite, respectively.

Combination anti-retroviral therapy has drastically improved solid organ transplantation outcomes in persons living with HIV. DAA therapy has led to the successful eradication of HCV. While recent data have suggested improvement in outcomes in HIV/HCV-coinfected liver transplant recipients, temporal trends in patient survival within pre- and post-DAA eras are yet to be elucidated. The UNOS database was utilized to identify deceased donor liver transplant recipients between 1 January 2000 and 30 September 2020 and stratify them by HIV and HCV infection status. A total of 85,730 patients met the inclusion criteria. One-year and five-year patient survival improved (93% and 80%, respectively) for all transplants performed post-2015. For HIV/HCV-coinfected recipients, survival improved significantly from 78% (pre-2015) to 92% (post-2015). Multivariate regression analyses identified advanced recipient age, Black race, diabetes mellitus and decompensated cirrhosis as risk factors associated with higher one-year mortality. Liver transplant outcomes in HIV/HCV-coinfected liver transplant recipients have significantly improved over the last quinquennium in the setting of the highly effective combination of ART and DAA therapy. The presence of HIV, HCV, HIV/HCV-coinfection and active HCV viremia at the time of transplant do not cause higher mortality risk in liver transplant recipients in the current era.

Computing software plays an essential role in almost every sector of the digital age, but the process of efficient software development still faces several challenges. Effective software development methodology can be the difference between the success and failure of a software project. This research aims to evaluate the overall impact of Agile Software Development (ASD) on the individual, organizational, software development, and project management dimensions. For this purpose, we surveyed several software development professionals from a variety of backgrounds (experience, location, and job ranks) to explore the impact of ASD on the IT industry of Pakistan. Our analysis of the collected information is two folds. First, we summarized the findings from our surveys graphically clearly show the opinions of our survey respondents regarding the effectiveness of the Agile methodology for software development. Secondly, we utilized quantitative measures to analyze the same data statistically. A comparison is drawn between the graphical and statistical analysis to verify the reliability of our findings. Our findings suggest the existence of a strong relationship between effective software development and the use of Agile processes. Our analysis shows that the job fit of software development professionals and ASD are critical factors for software development project success in terms of cost, quality, stakeholders satisfaction, and time. Although the study focuses on the IT industry of Pakistan, the findings can be generalized easily to other developing IT industries worldwide.

As a retailer between the energy suppliers and end users, the integrated energy service provider (IESP) can effectively coordinate the energy supply end and the energy use end by setting energy prices and energy management. Because most of the current research focuses on the pricing of electricity retailers, there are few studies on IESP energy pricing and management, which are still at the initial stage. At the same time, the existing research often does not consider the impact of demand response (DR) and uncertainties, such as natural gas and electricity wholesale prices, on the pricing of IESP. It is necessary to model the DR and uncertainties in the integrated energy system. Aiming at the inadequacy of the existing research and to address the energy pricing and management of IESP, this paper develops a two-stage stochastic hierarchical framework, which comprehensively considers the DR strategy of the user end, characteristics of the electricity/gas/heat storage and the uncertainties of electricity and gas wholesale prices. The proposed hierarchical model for energy pricing and management is a two-layer model: the upper layer is the problem of maximizing the benefits of IESP, and the lower layer is the problem of minimizing the energy cost of user agents. Through the complementary transformation, the linearization method and the strong duality principle in the optimization theory, the model is transformed into a mixed-integer linear programing (MILP) problem, which can be easily solved by the off-shelf commercial solver. Finally, the simulation results are provided to demonstrate the interactive operation between the IESP and user agent through energy prices setting, DR strategy and energy management.

Background: Diabetic-foot syndrome is a difficult & debilitating complication of inadequately regulated Diabetes Mellitus. Attributed to neural & vascular pathology, the condition is further potentiated by glycemic healing impairment. A wide array of microorganisms have been implicated & sensitivity-guided antibiotics are essential to save both limb as well as to minimize rampant microbial resistance. Present study aims to determine the culture & sensitivity pattern of bacteria in stated cohort of patients at a Surgical Unit. Materials & Methods: This prospective cohort study was conducted over a period of 1 year-duration at a tertiary-care-Hospital. All patients presenting with diabetic-foot who had not been subjected to empiric antibiotic-therapy were enrolled. Demographic & lesion-based variables were studied and the Culture & Sensitivity pattern was evaluated and statistically analyzed. Results:100 patients were included in the study,of which 80 were male (mean-age 60.8±12.7 years) & rest female (mean-age 58.4±11.3-years).35% cultures yielded no growth. Remaining cases showed following pathogens in descending order of incidence. Maximal sensitivity was also reported as mentioned. 1) Staphylococcus-aureus & Klebseilla-Pneumoenae– Piperacillin/Tazobactam,2) Pseudomonas-Aerugionas-Cefotaxime,3)E-coli–Amikacin& Sulbactam,4) Proteus -Gentamicin, 5) Streptococci– Amikacin and 6) Bacteroides – Cefoperazone & Aztreonam. Of 71 cases, 70 had aerobic-organisms isolates & only 1 had anaerobic-isolate. Conclusions: Six pathogens were identified in present study of which Staphylococcus-Aureus was the most prevalent as well as the most resistant. Streptococci & Gram-negative Organisms were observed in remaining cases. While formulation of an adequate antibiotic regime is rendered difficult by resistance & mixed infections, targeted antibiotic administration is decisively crucial to achieve optimal & timely outcome in diabetic foot.