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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.

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.

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.

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.

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.

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.

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.

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.

Dielectric fluids or commonly oils serve as the protection of any power utility components, which make it selection crucial for utility. Due to its significance, consistent research has been performed and new insulants have been introduced for power utilities to attain better, reliable, and a longer lifespan than the former one. Nanotechnology-based insulating liquids are still under research but show the potential to achieve the objective of smart and futuristic insulation. This paper provides the critical review for the development of insulating liquid and promising results shown by the nanoparticles dispersed fluid termed nanofluids. The state-of-the-art research illustration includes synthesis, experimental investigation, and dielectric and physio-mechanical characterization of nanofluids. The enhancements in the characteristics of nanofluids are elucidated along with its possible mechanisms and shortcomings.

Background/Purpose: Medical inpatients are at increased risk of QT interval prolongation due to multiple risk actors and QT prolonging drugs. This study aimed to identify the prevalence of risk factors for QT prolongation; QT prolonging medications; associated drug-drug interactions (QT-DDIs); their predictors; and TdP (torsades de pointes) risks of drugs. Methods: This cohort study was carried out in medical wards of two tertiary hospitals in Khyber Pakhtunkhwa, Pakistan. The QT-DDIs were identified using Micromedex DrugReax® and AZCERT (Arizona Center for Education and Research on Therapeutics) QT drugs lists. AZCERT QT drugs lists were used to identify TdP risks. Logistic regression analysis was performed to identify predictors of QT-DDIs. Results: Total 400 patients were included in this study. The most frequent QT prolonging risk factors included use of ≥1 QT prolonging drugs (74.5%), female gender (55%) and diabetes mellitus (36.3%). Total 487 QT prolonging drugs were identified. According to AZCERT classification, 33.8% of the interacting drugs were included in list-1 (known risk of TdP), 0.9% in list-2 (possible risk of TdP) and 58.8% in list-3 (conditional risk of TdP). The occurrence of QT-DDIs was significantly associated with ≥10 prescribed medications (p = 0.01), chronic liver disease (p = 0.05), chronic obstructive pulmonary disease (p = 0.03), gastroenteritis (p = 0.02), antimicrobials (p

Hospitalized patients with left ventricular failure (LVF) are at high risk for potential drug-drug interactions (pDDIs) and its related adverse effects owing to multiple risk factors such as old age, comorbidities and polypharmacy. This cross-sectional study conducted in two tertiary care hospitals aim to identify frequency, levels and predictors of pDDIs in LVF patients. Data about patients’ demographic, hospital stay, medication therapy, sign/symptoms and laboratory test results were collected for 385 patients with LVF. Micromedex Drug-Reax® was used to screen patients’ medication profiles for pDDIs. Overall prevalence and severity-wise prevalence of pDDIs were identified. Chi-square test was performed for comparative analysis of various variables. Logistic regression was applied to determine the odds-ratios (OR) for predictors of pDDIs. The prevalence of pDDIs was 96.4% (n=371). Overall 335 drug-interacting pairs were detected, which were presented in a total of 2870 pDDIs. Majority of pDDIs were of major- (48.9%) and moderate-severity (47.5%). Logistic regression analysis shows significant association of >6 all types of pDDIs with >12 drugs as compared with 4 major-pDDIs with men as compared with female (OR=1.9; p=0.007) and >12 drugs as compared with

Abstract Background Potential drug–drug interactions (pDDIs) are one of the preventable drug related problems having the risk of serious adverse events or therapeutic failure. In developing countries like Pakistan, this issue remains poorly addressed. The objective of this study was to explore prevalence of pDDIs in the Outpatient Department (OPD) of a tertiary care hospital in Pakistan. The secondary aim was to describe the levels of reported pDDIs and develop a list of widespread clinically relevant interactions. Methods Prescriptions of 2400 OPD patients were analyzed for pDDIs through Micromedex Drug-Reax®. Prevalence, severity- and documentation-levels and widespread clinically relevant interactions were reported. Results Of total 2400 prescriptions, pDDIs were present in 22.3%. Whereas, moderate- and major-pDDIs were found in 377 (15.7%) and 225 (9.4%), respectively. PDDIs were more prevalent in Medicine (9.2%) and Cardiology (2.6%) as compared with other OPD specialties. Total 942 pDDIs were identified, of which, the majority were either moderate- (61.9%) or major-pDDIs (32.1%). Some of the most common interactions were ibuprofen + levofloxacin (n = 50), ciprofloxacin + diclofenac (32), aspirin + atenolol (24), and diclofenac + levofloxacin (19). The potential adverse outcomes of widespread interactions were seizures, bleeding, QT-interval prolongation, arrhythmias, tendon rupture, hypoglycemia/hyperglycemia, serotonin syndrome, drug toxicity, and decreased therapeutic response. Conclusions OPD patients were at risk to pDDIs, particularly to major- and moderate-pDDIs. Screening of prescriptions for pDDIs and monitoring of pharmacotherapy in terms of response and associated adverse drug events will contribute to patient safety.

Abstract Background Cancer patients may receive a high number of medications with the potential to prolong QT interval and subsequent TdP (torsades de pointes). This study aimed to identify the prevalence of QT prolonging drugs, their TdP risk, QT prolonging drug-drug interactions (QT-DDIs), levels, predictors, and TdP risk of drugs involved in QT-DDIs. Methods This multicenter study included cancer patients from three major tertiary care hospitals of Khyber-Pakhtunkhwa, Pakistan. Micromedex DrugReax® was used for identification of QT-DDIs. TdP risks were identified by AZCERT (Arizona Center for Education and Research on Therapeutics) classification. Logistic regression analysis was performed to identify predictors of QT-DDIs. Results Of 555 patients, 51% were females. Mean age was 46.9 ± 15.7 years. Total 28 distinct QT prolonging drugs were identified in 92.6% of the patients. Overall 21.8% patients were presented with QT-DDIs. Of total 288 identified QT-DDIs, all were of major-severity and fair-documentation. According to AZCERT classification, 59.9% of the interacting drugs were included in list-1 (known risk of TdP), 4.7% in list-2 (possible risk of TdP) and 6.8% in list-3 (conditional risk of TdP). Univariate logistic regression analysis showed significant results for various predictors such as, 8–9 prescribed medications (p 8 supportive care drugs (p

For future pollution-free renewable energy production, platinum group metal (PGM)-free electrocatalysts are highly required for oxygen reduction reaction (ORR) to avoid all possible Fenton reactions and to make fuel cell more economical. Therefore, in this study, to overcome traditional electrocatalyst limitations, we applied facile method to synthesize robust mesoporous CrN-reduced graphene oxide (rGO) nanocomposite with MnO (thereafter, Cr/rGO composite with MnO) as an electrocatalyst by efficient one-step sol-gel method by ammonolysis at 900°C for 9 h. Synthesized porous structures of Cr/rGO nanocomposite with MnO have the highest estimated surface area of 379 m2·g−1, higher than that of the carbon black (216 m2·gcat-1) support, and almost uniform pore size distribution of about 4 nm. The Cr/rGO nanocomposites with MnO exhibit enhanced electrocatalytic ORR properties with estimated high half-wave potential of 0.89 V vs. the reversible hydrogen electrode (RHE) and current density of 5.90 mA·cm−2, compared with that of benchmark 20% Pt/C electrode (0.84 V, 5.50 mA·cm−2), with noticeable methanol tolerance and significantly enhanced stability in alkaline media. Hence, the Cr/rGO nanocomposites with MnO showed superior performance to 20 wt.% Pt/C; their half-wave potentials were 50 mV high, and the limiting current density was 0.40 mA·cm−2 high. In alkaline anion exchange membrane fuel cell (AAEMFC) setup, this cell delivers a power density of 309 mW·cm−2 for Cr/rGO nanocomposite with MnO, demonstrating its potential use for energy conversion applications. The nanosized Cr/rGO metallic crystalline nanocomposites with MnO gave a large active surface area owing to the presence of rGO, which also has an effect on the charge distribution and electronic states. Hence, it may be the reason that Cr/rGO nanocomposites with MnO, acting as more active and more stable catalytic materials, boosted the electrocatalytic properties. The synergistic consequence in nanosized Cr/rGO composite with MnO imparts the materials' high electron mobility and thus robust ORR activity in 0.1 M of KOH solution. This potential method is highly efficient for synthesis of large-scale, non-noble-metal-based electrocatalytic (NNME) materials (i.e., Cr/rGO nanocomposite with MnO) on the gram level and is efficient in preparing novel, low-cost, and more stable non-PGM catalysts for fuel cells.

The insulation as the root source of failure and ageing assessor makes it a crucial point for any power equipment design. The transformer's insulation requires an efficient dielectric fluid that acts as an ideal electrical insulant and better thermal transporter. The objective of attaining that idealism in dielectric medium leads to the addition of solvents (i.e. additive and other fluids) in the conventional medium as one of its approach. This study presents addition of new magnetic nanoparticle iron phosphide (Fe(3)P) in insulating oil to achieve improved dielectric strength and withstand capability of the same conventional oil. A comparative study of nanofluids with different concentrations of nanofluids based on different insulating medium (i.e. synthetic ester and natural ester) has been performed. The concentration of additives and role of surfactant positively influences the dielectric characteristics of the base oil. The increase in breakdown strength is observed with a slight concentration of Fe(3)P nanoparticles added in the insulating medium.

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Groundwater constitutes an important part of the available water resources in arid areas. Knowledge of the quantitative and qualitative status of groundwater is a key aspect in optimal groundwater management. The purpose of this study was to provide technical information on the groundwater in the sand aquifer of two neighboring areas in the United Arab Emirates to support stakeholders working towards sustainable groundwater development. The chemical characteristics of the groundwater have been used to identify the processes controlling groundwater chemistry and assess the suitability of the groundwater for agricultural purposes. Despite tapping into the same aquifer, considerable differences in groundwater quality were found between the two study areas. The area with a shallower water table showed clear indications of irrigation return flow deteriorating the groundwater quality. Using standard agricultural indices, the groundwater at both study areas is classified as unfit for agricultural purposes. However, considering that groundwater is the only available water source for irrigation, it will continue to be used for agriculture. This indicates the need for improved irrigation management and the development of new strategies for sustainable groundwater development in arid areas in the context of food security.

Drought is a continuous process in Thar Desert, Pakistan. The extent of this drought needs to be assessed for future land use and adaptation. The effect of previous drought on vegetation cover of the Thar region was studied, through combined use of drought indices and geographic information (GIS) techniques. Five years (2002, 2005, 2008, 2011 and 2014) were selected to analyze the drought conditions and land use pattern of the Thar region. The drought indices used in this study included the Normalized Difference Vegetation Index (NDVI) and the Standard Precipitation Index (SPI). Images of past drought were compared with post-drought images of our targeted area and land use maps were developed for spatio-temporal analysis. The results of the study revealed that vegetation in Thar showed an improving trend from 2002 to 2011 and then declined from 2011 to 2014. The rainfall occurred at a below average rate and SPI values for each year were calculated to be negative, indicating below average rainfall. This actual precipitation data was then compared with the data obtained from the Tropical Rainfall Measuring Mission (TRMM) satellite and R2; Pearson correlation coefficients were also calculated. The R2 values for the years 2002 and 2014 were 0.519 and 0.670 respectively. In the same manner, the Pearson correlation coefficient values for the years 2002 and 2014 were 0.721 and 0.867 respectively. The results showed the TRMM satellite’s over-estimation in calculating rainfall data. Further, the average temperature for the five years under study was analyzed by graphical representation and it was revealed that the temperature of Thar has increased by almost 1 °C during the last decade.