Search

Forecasting academic performance of student has been a substantial research inquest in the Educational Data-Mining that utilizes Machine-learning (ML) procedures to probe the data of educational setups. Quantifying student academic performance is challenging because academic performance of students hinges on several factors. The in hand research work focuses on students’ grade and marks prediction utilizing supervised ML approaches. The data-set utilized in this research work has been obtained from the Board of Intermediate & Secondary Education (B.I.S.E) Peshawar, Khyber Pakhtunkhwa. There are 7 areas in BISEP i.e., Peshawar, FR-Peshawar, Charsadda, Khyber, Mohmand and Upper and Lower Chitral. This paper aims to examine the quality of education that is closely related to the aims of sustainability. The system has created an abundance of data which needs to be properly analyzed so that most useful information should be obtained for planning and future development. Grade and marks forecasting of students with their historical educational record is a renowned and valuable application in the EDM. It becomes an incredible information source that could be utilized in various ways to enhance the standard of education nationwide. Relevant research study reveals that numerous methods for academic performance forecasting are built to carryout improvements in administrative and teaching staff of academic organizations. In the put forwarded approach, the acquired data-set is pre-processed to purify the data quality, the labeled academic historical data of student (30 optimum attributes) is utilized to train regression model and DT-classifier. The regression will forecast marks, while grade will be forecasted by classification system, eventually analyzed the results obtained by the models. The results obtained show that machine learning technology is efficient and relevant for predicting students performance.

Groundwater is more prone to contamination due to its extensive usage. Different methods are applied to study vulnerability of groundwater including widely used DRASTIC method, SI and GOD. This stu...

Textile industry represents a pollution problem worldwide due to the accidental discharge or dumping of polluted wastewater into the waterways, which is having a major influence on the quality of water resources. Around 17–20% of industrial water pollution arises from textile dyeing and treatment according to the World Bank report. This represents a large environmental challenge for textile manufacturers. With growing environmental awareness, there is a need for environmentally-friendly technology to remove dyes from the industrial and local wastewater. The photo decolorization of dyes is considered as a favorable technology for industrial wastewater treatment techniques owing to its environmentally friendly method, low cost, and lack of secondary pollution. The efficiency of photocatalysis system depends on the operational parameters that govern the adsorption and photodegradation of dye molecules. This comprehensive review examines the operational factors influencing the photo decolorization of dye molecules. Our study aims to review and summarize the previously published works and R&D progress in the field of photocatalysis of various water pollutants such as the toxic organic compounds (cationic and anionic dyes) using various semiconductor nanoparticles under visible, solar and UV irradiation. This paper examines the effects of operating parameters on the photocatalytic degradation of textile dyes using various photocatalysts. Our findings showed that various parameters, like initial pH of the solution to be degraded, photocatalyst concentration, reaction temperature, dye concentration and dopants content exert their individual influence on the photocatalytic degradation of any dye. By investigating previous research to elucidate the most significant active species for optimal photo decolorization reactions, this review provides guidelines that can be applied to the development of effective photodegradation systems. The results of our study will help determine the most effective and economical options for removal of dyes in industrial wastewater.

The early detection of a driver’s intention prior to the initiation of actual maneuvering is to offer effective means of assisting the driver in times of safety. Conventional approaches in predicting a driver’s intention include framing the motion parameters of the car and driver as well as the eye gaze sequence of the driver into the Hidden Markov Model (HMM) for analysis. However, their power of describing driver behavior is not only limited but also their performance, indicated by the recognition rate relative to the amount of preceding time in early detection, is not satisfactory and needs further improvement. This paper presents an approach for early detection of a driver’s intention by modeling and analyzing driver behavior by using structural pattern recognition based on context-free and context-sensitive grammars. We specifically structured a sequence of the driver’s eye fixations as well as of the vehicle speed, steering angle and signaling into a sequence of symbolic vectors to form sentences representing a specific driver behavior. It turns out that the proposed approach resulted in an average of 70.5% and 80% recognition rates at the respective 2 and 1 second preceding time to the actual initiation of maneuvering behavior. This performance can be compared to 56.8% and 69% by the state-of-the-art conventional results.

The vertical field-effect phototransistor (VFEPT) has received great attention because of its large current density and the low operation voltage required to achieve the desirable photodetector per...

The CdSe/ZnS quantum dots (QDs) have drawn the attention of the researchers due to their superior photophysical properties and their applications in QD-based light-emitting diodes (QLEDs). The conv...

Background and objectives Nonalcoholic steatohepatitis (NASH) is strongly associated with obesity. A weight loss of ≥10% is necessary to improve NASH severity, but this goal has rarely been achieved in published studies using different diet protocols. The effect of a ketogenic, hypocaloric, commercial diet (“Ideal Protein,” IP) on body weight, metabolic markers, and liver tests in a group of NASH patients is evaluated in this study. Daily calorie intake was tailored to achieve a weight loss of ≥10%. Methods We analyzed 38 patients with NASH who were placed on the IP diet between 2014 and 2018 and compared their outcomes with 6 control patients who declined the diet. All patients were evaluated by a trained health coach in weekly intervals throughout the study period. Clinical and laboratory data obtained before and at 6.5 months after intervention were compared using paired t-testing. Results The patients on the IP diet experienced a significant weight reduction (217 ± 8 lb vs. 194 ± 7 lb; mean ± S.E.M.), corresponding to an average weight loss of 9.7% ± 1.6%. Significant changes in systolic blood pressure (133 ± 3 mmHg vs. 123 ± 3 mmHg), triglycerides (200 ± 21 mmol/L vs. 132 ± 11 mmol/L), hemoglobin A1c (6.71% ± 0.29% vs. 5.74% ± 0.19%), SGPT (97.3 ± 11.1 IU/L vs. 44.2 ± 5.9 IU/L), SGOT (82.4 ± 10.5 IU/L vs. 32.8 ± 5.2 IU/L), and Fib-4 scores (2.25 ± 0.23 vs. 1.40 ± 0.13) were also observed (P Conclusions A ketogenic, hypocaloric resulted in striking weight loss and significant improvements in metabolic parameters and liver tests, suggesting that this approach carries promise for the dietary management of patients with NASH.

CdSe/ZnS quantum dots (QDs) have attracted great consideration from investigators owing to their excellent photo-physical characteristics and application in quantum dot light-emitting diodes (QD-LEDs). The CdSe/ZnS-based inverted QD-LEDs structure uses high-quality semiconductors electron transport layers (ETLs), a multilayered hole transporting layers (HTLs). In QD-LED, designing a device structure with a minimum energy barrier between adjacent layers is very important to achieve high efficiency. A high mobility polymer of poly (9,9-dioctylfluorene-co-N-(4-(3-methylpropyl)) diphenylamine (TFB) was doped with 4,4′-bis-(carbazole-9-yl) biphenyl (CBP) with deep energy level to produce composite TFB:CBP holes to solve energy mismatch (HTL). In addition, we also improved the QD-LED device structure by using zinc tin oxide (ZTO) as ETL to improve device efficiency. The device turn-on voltage Vt (1 cd m−2) with ZTO ETL reduced from 2.4 V to 1.9 V significantly. Furthermore, invert structure devices exhibit luminance of 4296 cd m−2, current-efficiency (CE) of 7.36 cd A−1, and external-quantum efficiency (EQE) of 3.97%. For the QD-LED based on ZTO, the device efficiency is improved by 1.7 times.

Nanotechnology has opened a new era for scientists and engineers to build nanomaterials with diverse applications. Nowadays, nanotechnology plays a vital role in each and every sector due to its extraordinary physical and chemical properties. It deals with development and synthesis of variety of nanoparticles (NPs), which ranging from 1 to 100 nm. The major approaches used for the synthesis of NPs are top to bottom and bottom to up which mainly included physical, chemical and biological methodologies. This mini review highlights synthesis of NPs through various approaches specifically targeted biological route.

Multiple energy carriers can be coupled as an Integrated Energy System (IES) through interconnection technologies. Unexpected risks will be transferred with the growing coupling of energy systems, mainly stemming from the uncertainties in different energy sectors. It is imperative to coordinate the operation of different energy systems to improve energy efficiency and ensure energy security. With the close integration of different energy systems, it is necessary to couple these different energy markets to achieve the holistic energy supply economy. On the other hand, uncertainties in the energy systems will bring the financial risk for the operator of IES. A risk-averse stochastic market clearing model for the IES is proposed to study the operating strategy aiming at minimizing the operation cost. While the financial risk imposed by the wind power uncertainties is restricted to a predefined level. Simulations results are provided to verify that the proposed model can improve market efficiency and handle the trade-off between cost and risk.

Melanoma is considered a fatal type of skin cancer. However, it is sometimes hard to distinguish it from nevus due to their identical visual appearance and symptoms. The mortality rate because of this disease is higher than all other skin-related consolidated malignancies. The number of cases is growing among young people, but if it is diagnosed at an earlier stage, then the survival rates become very high. The cost and time required for the doctors to diagnose all patients for melanoma are very high. In this paper, we propose an intelligent system to detect and distinguish melanoma from nevus by using the state-of-the-art image processing techniques. At first, the Gaussian filter is used for removing noise from the skin lesion of the acquired images followed by the use of improved K-mean clustering to segment out the lesion. A distinctive hybrid superfeature vector is formed by the extraction of textural and color features from the lesion. Support vector machine (SVM) is utilized for the classification of skin cancer into melanoma and nevus. Our aim is to test the effectiveness of the proposed segmentation technique, extract the most suitable features, and compare the classification results with the other techniques present in the literature. The proposed methodology is tested on the DERMIS dataset having a total number of 397 skin cancer images: 146 are melanoma and 251 are nevus skin lesions. Our proposed methodology archives encouraging results having 96% accuracy.

Objective: To determine the frequency of bleeding with Tirofiban during percutaneous coronary intervention Methodology: In this case series (Descriptive) at Mayo Hospital, Cardiology Deptt. Lahore during the year 2018 and 2019, we enrolled a total of 385 cases of either gender with acute coronary syndrome(ACS) and undergoing percutaneous coronary intervention(PCI)were included. Preloading with aspirin 300 mg and clopidogrel 600 mg was done. Intravenous Tirofiban was given keeping in mind the current guidelines. Tirofiban was given as I/V bolus of 0.25 mcg/kg over 5 minutes during/before the start of PCI. It was followed by a continuous infusion of 0.125 mcg/kg/min for up to eighteen hours. Bleeding during and within 24 hours of percutaneous coronary intervention was noted according to BARC bleeding type Results: Mean age was 50.750± 5.63years. Male gender was dominant i.e. 85.7% as compare to 14.3% females. Bleeding was observed in 3.9% patients Conclusion: In acute coronary syndrome patients undergoing PCI, Tirofiban use was associated with bleeding. In the modern era of PCI, the judicious use of Tirofiban is safe. Keywords: Percutaneous coronary intervention, Tirofiban, Bleeding, Acute coronary syndrome

INTRODUCTION: We assessed the influence of a best practice alert (BPA) embedded within the electronic medical record on improving hepatitis C virus (HCV) birth-cohort screening by primary care physicians (PCPs). METHODS: Screening by 155 PCPs was monitored during 2 consecutive 9-month periods before and after implementation of the BPA. All tests were reviewed to differentiate true screening from other testing indications. RESULTS: Of 155 PCPs, 131 placed screening orders before and after BPA. Twenty-two PCPs started testing after BPA (P = 0.02). The number of tests placed and screening rates per PCP increased from 16 to 84 and from 3.3% to 13.2%, respectively (P < 0.0001). Before BPA, most PCPs rarely ordered screening HCV tests, whereas a small group of physicians generated most tests, indicative of an underlying power-law distribution. After the BPA, a new group of high-performing PCPs emerged, whose screening patterns were again characterized by a power-law distribution. However, pre-BPA test rates of individual PCPs were not predictive of their post-BPA rates. Overall, the introduction of the BPA narrowed the gap between low- and high-performing testers, indicating that modest increases in testing by a large number of low-performing PCPs could drive substantial improvement in program implementation. DISCUSSION: HCV birth-cohort screening by PCPs was shaped by an underlying power-law distribution. This distribution was preserved after the implementation of a BPA, although pre-BPA test rates were not predictive of post-BPA rates. Increases in test rates by high- and low-performing PCPs both contributed to the overall success of the BPA.

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. Chisquare 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 majorpDDIs with men as compared with female (OR=1.9; p=0.007) and >12 drugs as compared with

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.

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.

Abnormal behaviors of tumors pose a risk to human survival. Thus, the detection of cancers at their initial stage is beneficial for patients and lowers the mortality rate. However, this can be difficult due to various factors related to imaging modalities, such as complex background, low contrast, brightness issues, poorly defined borders and the shape of the affected area. Recently, computer-aided diagnosis (CAD) models have been used to accurately diagnose tumors in different parts of the human body, especially breast, brain, lung, liver, skin and colon cancers. These cancers are diagnosed using various modalities, including computed tomography (CT), magnetic resonance imaging (MRI), colonoscopy, mammography, dermoscopy and histopathology. The aim of this review was to investigate existing approaches for the diagnosis of breast, brain, lung, liver, skin and colon tumors. The review focuses on decision-making systems, including handcrafted features and deep learning architectures for tumor detection.

Background Idiopathic ventricular arrhythmias (IVAs) from the left ventricular (LV) summit may be successfully ablated from the distal great cardiac vein (dGCV). Using a 12-lead electrocardiogram (ECG) to localize IVAs that can be ablated from the dGCV is valuable for ablation planning. Objective To determine if a "w" wave, a notch in the Q wave in lead I, and other ECG features can identify IVAs that can be successfully ablated from the dGCV. Methods We reviewed outflow tract premature ventricular contraction (PVC) ablations performed at two centers between September 2010 and June 2018. Successful PVC ablations, in which the PVCs were mapped from the right ventricular outflow tract, coronary cusps, commissures, endocardial LV, and the coronary venous system including the dGCV were included. ECG characteristics were compared between patients with successful ablations in the dGCV and non-dGCV sites. Results Of the 120 patients (age 56.8 ± 13.8 years, 45% female) that met the inclusion criteria, the dGCV was the successful ablation site in 18 patients (15%). Multivariate analysis with binary logistic regression showed that a "w" in lead I in combination with an early precordial pattern break and a maximum deflection index (MDI) ≥ 0.5 had sensitivity and specificity for a successful ablation in the dGCV of 94.4% and 96.1%, respectively. Conclusion Combining a "w" wave in lead I with an early precordial pattern break and an MDI ≥ 0.5 is highly sensitive and specific for identifying the dGCV as a successful ablation site for PVCs.

Universal Verification Methodology (UVM) is getting attention of researchers and functional verification community due to its advance flexibility, reusability and reliability features for design verification of multifaceted embedded systems. This is the reason that different tool vendors like Mentor Graphics support UVM-based simulation for design verification. Similarly, researchers frequently explore / utilize UVM to enhance the verification capabilities for embedded systems. In this context, there is a strong need to summarize the latest advancements, tools and techniques for UVM standard. Therefore, this article performs a Systematic Literature Review (SLR) to identify 27 studies (i.e. 2017-2019) pertaining to UVM standard. Subsequently, 21 UVM-based frameworks and 9 tools are identified. Moreover, key benefits of UVM standard are investigated. Finally, a comparative analysis of UVM with OVM (Open Verification Methodology) is performed. It is concluded that UVM provides advanced phasing mechanism, reporting, callbacks, objections, sequence libraries and control over simulation as compared to OVM. Researchers and practitioners of domain can highly benefit from findings of this article.

Background: During the novel coronavirus-2019 (COVID-19) pandemic, physicians in residency and fellowshitraining programs are serving as essential healthca

The advancement of layered two-dimensional (2D) materials is accelerated by significant interest and their potential applications. The atomically thin 2D materials contribute a broad range of basic constituents with exclusive optical, electrical, and thermal properties, which cannot be found in their bulk forms. Conversion of three-dimensional (3D) materials to 2D material structure introduces the effect of quantum confinement, which leads to a broader bandgaps and narrower peak PL emission compared to their 3D analogues. 2D material structures provide unique optical and electrical properties that derive from the surface effects and quantum confinement arises during the conversion of indirect bandgap to a direct bandgap as a result of scaled down of bulk structure to monolayers. The present tunable bandgap is accompanied by a large exciton-binding energy and intensified PL, which make them a potential candidate for various optoelectronic devices like light-emitting diodes, light-emitting transistors, and other optically pumped light–emitting devices.

Moxifloxacin is widely used for the treatment of a number of infectious diseases because of its favorable pharmacological profile and high clinical success rate. However, it is often criticized for its higher risk of QTc interval prolongation (QTIP) and torsades de pointes (TdP).A review of published literature on moxifloxacin-related QTIP and TdP. Readers will be provided with a comprehensive overview of the prevalence, cellular mechanism, risk factors, and magnitude of QTIP of moxifloxacin.In healthy subjects, moxifloxacin prolongs the QTc interval by 11.5-19.5 ms, it binds at the Tyr652 residue in the S6 pore domain of the human ether a-go-go gene related potassium channel. Considerable QTIP (30-60 ms) have also been reported in some patients, for instance the incidence of QTIP (30-60 ms) in elderly pneumonia patients was 15.5%. Moxifloxacin-induced QTIP may be of little clinical importance in healthy individuals. However, marked QTIP (60 ms) and TdP have been reported in high-risk patients (patients who have multiple QT prolonging risk factors). Patients must be thoroughly assessed prior to the use of moxifloxacin and high-risk patients must be identified using risk assessment tools to ensure safe use of moxifloxacin and to safeguard patients' health.

All-inorganic perovskite light-emitting diode (PeLED) has a high stability in ambient atmosphere, but it is a big challenge to achieve high performance of the device. Basically, device design, control of energy-level alignment, and reducing the energy barrier between adjacent layers in the architecture of PeLED are important factors to achieve high efficiency. In this study, we report a CsPbBr3-based PeLED with an inverted architecture using lithium-doped TiO2 nanoparticles as the electron transport layer (ETL). The optimal lithium doping balances the charge carrier injection between the hole transport layer and ETL, leading to superior device performance. The device exhibits a current efficiency of 3 cd A–1, a luminance efficiency of 2210 cd m–2, and a low turn-on voltage of 2.3 V. The turn-on voltage is one of the lowest values among reported CsPbBr3-based PeLEDs. A 7-fold increase in device efficiencies has been obtained for lithium-doped TiO2 compared to that for undoped TiO2-based devices.

In wireless sensor networks (WSNs), the energy and computational capacity of the sensor nodes are limited and they are deployed in a hostile environment. An adversary can easily compromise a sensor node and injects false data into the network. This injection of false data drastically depletes the energy of the nodes designated on the route for forwarding the source data. Many filtering methods have been proposed to tackle the security issues but they also increase the communication cost by exchanging the control keying messages which consumes more energy with in the network. Fuzzy logic for TICK was proposed to reduce the communication cost and increase the energy efficiency of the en-route nodes by selecting the re-encrypting nodes efficiently and avoiding the exchange of control keying messages in the network. Membership functions in the fuzzy system need to be optimized in order to use the fuzzy inferencing more efficiently. We propose an optimized fuzzy membership functions method by using genetic algorithm. The genetic algorithm determines the optimal membership functions which help in selecting the most favourite re-encrypting nodes in TICK based wireless sensor network. Simulation results show that the proposed method optimizes the membership functions and achieves better energy conservation at sensor nodes.

One of the important resources required for various Natural Language Processing (NLP) applications like machine translation, information retrieval and text mining, is annotated text corpora. Text corpora annotation process requires parts of speech (POS) tags to mark different parts of text with grammatical annotations in order to identify linguistic properties of a word, sentence or discourse. The process of marking text items is based on two main features 1) grammatical category and 2) context of text (word, sentence or discourse) i.e. relationship with adjacent and related text. Saraiki being one of oldest languages is still resource scarce language in recorded literature as well as in computational context. According to our study, at present, there is no tagset defined for Saraiki language. This work presents first hierarchical POS (MPOST) tag set for the Saraiki language which is designed to be used in morphological, syntactic and lexical annotations of Saraiki language corpora.

Prolonged QT interval may lead to a lethal form of arrhythmia, torsades de pointes (TdP), which is associated with cardiovascular mortality. Therefore, we aimed to identify prevalence of QT interval prolongation, compare clinical characteristics of patients with normal and prolonged QT interval, and identify predictors of QT interval prolongation. A prospective observational study was conducted in cardiology wards of two teaching hospitals in Pakistan. Bazett’s correction formula was used for the calculation of QTc interval. Prevalence of QT prolongation and pro-QTc scores were calculated. Comparative analysis was performed with respect to various clinical characteristics by applying t test and chi-square test. Odds ratios were calculated using regression analysis. Among 417 patients, 44.6% were found having prolonged QT interval, of which, 17.3% presented with an abnormally high QTc interval (> 500 ms). Significant difference was recorded between the groups (normal vs. prolonged) with respect to age, all prescribed medications, QT drugs, number of risk factors, QT-DDIs (QT-prolonging drug-drug interactions), gender, and diuretics use. Multivariate logistic regression analysis showed significant results for various predictors such as male gender (p = 0.03), various age categories 41–50 years (p = 0.04), 51–60 years (p = 0.01), and > 60 years (p

Population coding has been established as the key mechanism for decoding sensory information received from periphery organs such as retinas and cochlear. In this paper a novel architecture is presented to embed population coding in neuromorphic hardware. A resonance based mechanism between two layers of neuron is utilized in the presented work. The mechanism discussed in this paper facilitates selective triggering of higher layer neurons which serves as target ensemble for evaluation of a particular input of interest. It has been shown that presented model can be used to detect any physical quantity (light intensity, temperature, etc.) feed to the sensor on the basis of population coding.

Metal halide perovskites have received substantial attention in research communities due to their outstanding efficiency achievements in the field of photovoltaics, optoelectronics and electronics, exhibiting extraordinary optical, electrical and mechanical properties. The exceptional structural tunability enables perovskite material to possess low-dimensional form at the atomic level and extends their applications into optoelectronic and photonic fields. This review discusses the recent progress of synthetic routes and fundamental optoelectronic properties of low-dimensional metal halide perovskites. In addition, the focus is to highlight the potential applications of perovskites in various devices including solar cells, light-emitting diodes, lasers, waveguides and memory devices. Finally, outlooks and the challenges that face the development of the perovskite materials in the near future are also presented.

The cables failures in power systems utilities have been given great attention for reliability, economic aspects and safety of power utility operation. Such failures are caused by electrical, mechanical, and environmental stresses. Power cables might experience some serious damages particularly during the partial discharge activities. Therefore, the early localization of the exact defective cable section has become of extreme importance. The contribution of this study is to analyze electrical parameters behavior and its effects caused by a spheroidal cavity within the high voltage Cross-Linked Polyethylene (XLPE) cables. Also it investigates the correlation between electrical parameters and the size and location of voids inside the dielectric insulator using Finite Elements Analysis (FEA) environment. The results is intended to show that the location of the void inside the XLPE insulated power cables has a higher impact on the electric field and current density distribution than the void size.

Delay Tolerant Network (DTN) is a challenge network that can tolerate long delays during connections. It is different from traditional networks because traditional networks cannot meet the needs of disrupted and challenged networks. In this article, we will discuss the delay-tolerant network bundling protocol, which is located between the application layer and the transport layer. It is used as a communication system to meet the needs of the Internet. Delay Tolerant Network (DTN) has a coordinated, long-term and profitable surplus. Therefore, most systems use the “Transfer by Key” policy for data transfer, but the main problem with this strategy is to choose the best queue and the best commit time. Therefore, in order to solve these problems, social systems are used to delay the network. After a detailed discussion of social relationship, three routing strategies were proposed based on location, conference-based routing, and community-based approaches. We have chosen a routing strategy for three of these protocols to compare socially sensitive, ie popular routing protocols, routing protocols and spray waiting for prophets and routing protocols. These protocols are compared using a simulator based on discount rate, average latency, overload rate and hop count used. After comparison, we conclude that the spray and hold routing protocol is based on the best choice of transfer rate, overload rate and hop count.

It has been shown that mucus hypersecretion is associated with greater susceptibility for chronic obstructive pulmonary disease (COPD), excess forced expiratory volume in 1 s decline, hospitalisations and excess mortality. The effects of mucoactive drugs on outcomes have been reviewed in several meta-analyses, the largest one including 26 studies. 21 studies were performed in patients with chronic bronchitis and five in patients with COPD. The majority of these trials were performed with N-acetylcysteine (n = 13) and carbocysteine (n = 3). Overall, there was a significant reduction in exacerbations (0.05 per patient per month) and the number of days with disability (0.56 days per patient per month). Mucolytics were well tolerated and the number of adverse events was lower than with placebo (odds ratio 0.78). In the largest and best designed study with N-acetylcysteine in 523 patients with COPD, the reduction in exacerbations was only observed in patients not taking inhaled corticosteroids. In addition, a 374 mL reduction in functional residual capacity was found. A recent large study (n = 709) with high-dose carbocysteine (1,500 mg·day−1) demonstrated a significant effect on exacerbations (25% reduction) and also reported an improvement in health-related quality of life (-4.06 units in St George9s Respiratory Questionnaire). It is unclear what the mechanisms underlying these effects may be and which phenotypes benefit from this treatment. On the basis of this evidence mucoactive drugs may deserve consideration in the long-term treatment of COPD.

Although all-inorganic perovskite light emitting diodes (PeLED) have satisfactory stability under an ambient atmosphere, producing devices with high performance is challenging. A device architecture with a reduced energy barrier between adjacent layers and optimized energy level alignment in the PeLED is critical to achieve high electroluminescence efficiency. In this study, we report the optimization of a CsPbBr3-based PeLED device structure with Li-doped TiO2 nanoparticles as the electron transport layer (ETL). Optimal Li doping balances charge carrier injection between the hole transport layer (HTL) and ETL, leading to superior performance in both devices. The turn-on voltages for devices with Li-doped TiO2 nanoparticles were significantly reduced from 7.7 V to 4.9 V and from 3 V to 2 V in the direct and inverted PeLED structures, respectively. The low turn-on voltage for green emission is one of the lowest values among the reported CsPbBr3-based PeLEDs. Further investigations show that the device with an inverted structure is superior to the device with a direct structure because the energy barrier for carrier injection was minimized. The inverted structure devices exhibited a current efficiency of 5.6 cd A-1 for the pristine TiO2 ETL, while it was 15.2 cd A-1 for the Li-doped TiO2 ETL, a factor of ∼2.7 enhancement at 5000 cd m-2.

Antipsychotic Drugs (APDs) are being widely prescribed to treat various disorders, including schizophrenia and bipolar disorder; however, abnormal glucose metabolism and weight gain have been reported with Atypical Anti-Psychotic drugs (AAPDs) that can lead to insulin-resistance and type 2 diabetes mellitus. The study was designed to assess various biochemical parameters including insulin and blood sugar before and after exposure to APDs in order to exclude the involvement of psychiatric disorders and certain other factors in metabolic dysregulations. Fifty seven APDs-naïve patients with first episode psychosis were divided into six groups who received olanzapine, quetiapine, risperidone, aripiprazole, haloperidol or combination of olanzapine with escitalopram and haloperidol. The serum samples were taken before the intake of the first dose and then on follow-up. Decrease in the level of elevated insulin and glucose was observed post-treatment in some patients, while others were observed whose insulin and glucose levels increased post-treatment, yet some patients did not show any disturbance in the insulin and glucose levels. It is concluded that psychiatric disorders by itself, narcotics, cigarette smoking and use of oral snuff may be also be implicated in metabolic dysregulations. The effects of APDs on insulin and glucose in healthy volunteers might be different than in patients with psychiatric disorders.

Two-dimensional (2D) materials are considered to be next-generation materials due to their extraordinary electronic and optical properties. Particularly, the moderate band gap and high carrier mobility of 2D materials are highly desired for nano-electronics applications. Herein, we explore the structural, electronic and optical properties of 2D Si3X (X=S or O) monolayers. The anisotropic monolayers are predicted to have direct bandgaps of 0.94 eV (Si3S) and 1.19 eV (Si3O) (determined using the Heyd, Scuseria, and Ernzerhof screened hybrid method) and exhibt strong optical absorption in the range of 106 cm−1. They are also predicted to have high electron and hole mobilities up to 0.5 × 103 cm2 V−1 s−1and 2.2 × 103 cm2 V−1 s−1. Due to the distinctive structural, electronic and optical properties, the 2D anisotropic Si3X monolayer is a promising material for future optoelectronic and nano-electronic applications.

Structural geometry, electronic band gaps, density of states, optical and mechanical properties of double perovskite halides Cs2InBiX6 (X = F, Cl, Br, I) are investigated using the density functional theory. These compounds possess genuine perovskite stoichiometry, evaluated using various geometry-based indices like tolerance factor, octahedral factor, and formation energy. The fundamental electronic band gaps are direct and valued in the range 0.80–2.79 eV. These compounds have narrow band gaps (except Cs2InBiF6) due to strong orbital coupling of the cations. The valence band maximum and conduction band minimum are confirmed to be essentially of In 5s and Bi 6p characters, respectively. The splitting of Bi 6p bands due to strong spin-orbit coupling causes reduction in the band gaps. These compounds have large dispersion in their bands and very low carrier effective masses. The substitution of halogen atoms has great influence on the optical properties. The mechanical properties reveal that Cs2InBiX6 (X = F, Cl, Br, I) satisfy the stability criteria in cubic structures.

Optoelectronic applications based on the perovskites always face challenges due to the inherent chemical composition volatility of perovskite precursors. The efficiency of perovskite-based light-emitting diodes (Pe-LEDs) can be enhanced by improving the perovskite film via solvent engineering. A dual solvent post-treatment strategy was applied to the perovskite film, which provides a synchronous effect of passivating surface imperfections and reduces exciton quenching, as evidenced by improved surface morphology and photoluminance. Thus, the optimized Pe-LEDs reach 17,866 cd·m−2 maximum brightness, 45.8 cd·A−1 current efficiency, 8.3% external quantum efficiency, and relatively low turn-on voltage of 2.0 V. Herein, we present a simple technique for the fabrication of stable and efficient Pe-LEDs.

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. Electronic supplementary material The online version of this article (10.1186/s12913-018-3579-7) contains supplementary material, which is available to authorized users.

Tracking drivers’ eyes and gazes is a topic of great interest in the research of advanced driving assistance systems (ADAS). It is especially a matter of serious discussion among the road safety researchers’ community, as visual distraction is considered among the major causes of road accidents. In this paper, techniques for eye and gaze tracking are first comprehensively reviewed while discussing their major categories. The advantages and limitations of each category are explained with respect to their requirements and practical uses. In another section of the paper, the applications of eyes and gaze tracking systems in ADAS are discussed. The process of acquisition of driver’s eyes and gaze data and the algorithms used to process this data are explained. It is explained how the data related to a driver’s eyes and gaze can be used in ADAS to reduce the losses associated with road accidents occurring due to visual distraction of the driver. A discussion on the required features of current and future eye and gaze trackers is also presented.

Control signaling is mandatory for the operation and management of all types of communication networks, including the Third Generation Partnership Project (3GPP) mobile broadband networks. It has been widely reported in white papers and technical reports, published in the Telecom industry, that as 3GPP wireless broadband networks evolve to an all IP architecture to meet growing data access demands, control signaling also keeps growing alarmingly. When the intensity of these control signals goes beyond the network can handle, they turn in to signaling storms. This may in turn compromise smooth network operations and valuable customer satisfaction while bringing Telecom operators big financial losses. These signaling storms might bring a 3G/4G network to a standstill. Such incidents have already been reported by different network operators around the globe. Therefore the signaling storm problem poses a serious threat to the smooth operations of the modern day 3GPP mobile broadband networks. There are several factors for signaling storms including mobile broadband network architecture evolution, unprecedented increase in data demands, increased use of smart phones and chatty or polling nature of social network applications, to name some. This paper presents a survey of the causes, of the signaling storm problems in 3GPP mobile broadband networks and also discusses their possible solutions.

Disclosures on Corporate Social Responsibility (CSR) practices of business organizations have heightened over the past few decades due to increased awareness. Major contributions in the literature on CSR practices and their disclosures come from the studies conducted in the developed world, while many developing economies like Pakistan remain under-researched and fewer revelations have been made about their CSR practices. Therefore, the present study aims to explore various aspects of CSR practices of Pakistani firms and their reporting trends. A multimethod approach has been adopted to measure CSR practices with respect to both approaches, quantitative and qualitative, for 170 listed firms from 2008 to 2015. First, content analysis is employed to develop a CSR Disclosure Index (CSRD Index) as well as five sub indices, i.e., community welfare, health and education, environment and energy, product, and customer and workforce. Second, a multidimensional financial approach is used to calculate firm&rsquo, s CSR monetary spending ratio (CSR-MSR) using the monetary data of CSR activities. Results suggested that most Pakistani firms disclose more information about their product-, customer-, and stakeholder-related CSR activities and put less emphasis on health and education responsibilities. Moreover, there is a strong impact of government reforms on both the firm&rsquo, s CSR disclosures and monetary giving.

Background and Objectives Hepatitis C virus (HCV) testing rates among U.S. birth-cohort patients have been studied extensively, limited data exists to differentiate birth-cohort screening from risk- or liver disease-based testing. This study aims to identify factors associated with HCV antibody (HCV-Ab) testing in a group of insured birth cohort patients, to determine true birth cohort testing rates, and to determine whether an electronic medical record (EMR)-driven Best Practice Alert (BPA) would improve birth cohort testing rates. Methods All birth-cohort outpatients between 2010 and 2015 were identified. HCV-Ab test results, clinical, and demographic variables were extracted from the EMR, and factors associated with testing were analyzed by logistic regression. True birth-cohort HCV screening rates were determined by detailed chart review for all outpatient visits during one calendar month. An automated Best Practice Alert was used to identify unscreened patients at the point of care, and to prompt HCV testing. Screening rates before and after system-wide implementation of the BPA were compared. Results The historic HCV-Ab testing rate was 11.2% (11,976/106,753). Younger age, female gender, and African American, Asian, or Hispanic ethnicity, and medical comorbidities such as chronic hemodialysis, HIV infection, and rheumatologic and psychiatric comorbidities were associated with higher testing rates. However, during the one-month sampling period, true age cohort-based testing was performed in only 69/10,089 patients (0.68%). Following the system-wide implementation of the HCV BPA, testing rates increased from 0.68% to 10.76% (P Conclusions We documented low HCV-Ab testing rates in our baby boomers population. HCV testing was typically performed in the presence of known risk factors or established liver disease. The implementation of an EMR-based HCV BPA resulted in a marked increase in testing rates. Our study highlights current HCV screening gaps, and the utility of the EMR to improve screening rates and population health.

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

Flexible quantum dot light emitting diodes (QLEDs) have attracted extensive attention owing to the advantages of foldability and their broad application in flexible display devices. In this work, we report high performance, mechanically flexible QLEDs based on ZnO nanoparticles used as an electron transfer layer (ETL). The QLEDs have been fabricated on poly(ethylene-terephthalate) (PET) substrates utilizing a unique structure consisting of bilayered hole transport films and ZnO nanoparticles acting as an ETL to improve the device performance owing to its appropriate energy band position and high charge mobility. The QLEDs exhibited high performance, such as a lowered turn on voltage of 1.6 V and improved current and power efficiencies of 5.20 cd A−1 and 1.80 lm W−1, respectively. They presented good flexibility with a critical bending radius of 4.5 mm, suggesting the broad application potential of flexible QLEDs.

With the development of a hybrid system, flexible AC transmission system (FACTS) and high voltage direct current (HVDC) system are using to provide the control technique in the hybrid power system. In distributed power generation systems, the DC networks have more importance to handle the problem related to the DC power flow control in DC networks. Interline Power Flow Controller (IPFC) is a FACTS device used to control power flow in multi-line and parallel transmission lines. In this paper, a new topology has been proposed to control DC power flow through an Interline DC Power flow controller (IDCPFC) with Solid State Transformer (SST). In the proposed method, the boost converter is used to achieve increased output voltage from the input voltage and its current is regulated through the duty cycle of the converter. The control algorithm of the proposed technique is smooth and easy to deploy. To justify the topology, simulation results of proposed topology are investigated in this paper through the Simulink.

Objective To determine whether advanced cirrhosis - defined by the detection of nodular liver contours or portal venous collaterals on imaging studies - could be predicted by fibrosis algorithms, calculated using laboratory and demographic features extracted from patients’ electronic medical records. To this end, we compared seven EMR-based fibrosis scores with liver imaging studies in a cohort of HCV patients. Methods A search of our health system’s patient data warehouse identified 867 patients with chronic HCV infection. A total of 565 patients had undergone at least one liver imaging study and had no confounding medical condition affecting the imaging features or fibrosis scores. Demographic and laboratory data were used to calculate APRI, Fib4, Fibrosis Index, Forns, GUCI, Lok Index and Vira-HepC scores for all viremic patients who had undergone liver imaging. Data points selected for the calculation of these scores were based on laboratory results obtained within the shortest possible time from the imaging study. Areas under the receiver operating curves (AUROC), optimum cut-offs, sensitivities, specificities and positive and negative predictive values were calculated for each score. Results Seven algorithms were performed similarly in predicting cirrhosis. Sensitivities ranged from 0.65 to 1.00, specificities from 0.67 to 0.90, positive predictive values from 0.33 to 0.38, and negative predictive values from 0.93 to 1.00. No individual test was superior, as the confidence intervals of all AUROCs overlapped. Conclusions EMR-based scoring systems performed relatively well in ruling out advanced, radiologically-defined cirrhosis. However, their moderate sensitivity and positive predictive values limit their reliability for EMR-based diagnosis.