A facilitating framework for a developing country to adopt smart waste management in the context of circular economy.

To achieve higher standards of sustainability, the waste management sector now requires the incorporation of circular economy (CE) principles. However, an easy transition toward the particular goal would require the use of smart waste technologies. To achieve the aforementioned goal, this study aims to provide a facilitating framework for the adoption of smart waste management in the context of CE for Pakistan.

Brain MR Image Enhancement for Tumor Segmentation Using 3D U-Net.

MRI images are visually inspected by domain experts for the analysis and quantification of the tumorous tissues. Due to the large volumetric data, manual reporting on the images is subjective, cumbersome, and error prone. To address these problems, automatic image analysis tools are employed for tumor segmentation and other subsequent statistical analysis.

Understanding Variations in the Tracking and Erosion Performance of HTV-SR-Based Composites due to AC-Stressed Aging.

Among the polymeric family, high-temperature-vulcanized silicone rubber (HTV-SR) is the most deployed material for high voltage insulation applications. However, in an outdoor environment, due to contamination and wetting-induced dry band arcing, consequently SR experiences surface tracking and erosion. From a practical standpoint, the tracking and erosion performance under multi-stress aging is required to be known.

Impact Toughness of Hybrid Carbon Fiber-PLA/ABS Laminar Composite Produced through Fused Filament Fabrication.

Nowadays, the components of carbon fiber-reinforced polymer composites (an important material) are directly produced with 3D printing technology, especially Fused Filament Fabrication (FFF). However, such components suffer from poor toughness. The main aim of this research is to overcome this drawback by introducing an idea of laying down a high toughness material on the 3D-printed carbon fiber-reinforced polymer composite sheet, thereby making a hybrid composite of laminar structure.

Dual function Li-reactive coating from residual lithium on Ni-rich NCM cathode material for Lithium-ion batteries.

In this study, lithium phosphate (LiPO) is coated on the surface of Ni-rich LiNiCoMnO cathode material to enhance its cyclability and rate performance. The process is carried-out by achieving dual benefits, reduction of residual lithium compounds by converting them into LiPO coating material. The 0.

Multiple Sclerosis Lesion Segmentation in Brain MRI Using Inception Modules Embedded in a Convolutional Neural Network.

Multiple sclerosis (MS) is a chronic and autoimmune disease that forms lesions in the central nervous system. Quantitative analysis of these lesions has proved to be very useful in clinical trials for therapies and assessing disease prognosis. However, the efficacy of these quantitative analyses greatly depends on how accurately the MS lesions have been identified and segmented in brain MRI.

Application of MXenes in Perovskite Solar Cells: A Short Review.

Application of MXene materials in perovskite solar cells (PSCs) has attracted considerable attention owing to their supreme electrical conductivity, excellent carrier mobility, adjustable surface functional groups, excellent transparency and superior mechanical properties. This article reviews the progress made so far in using TiCT MXene materials in the building blocks of perovskite solar cells such as electrodes, hole transport layer (HTL), electron transport layer (ETL) and perovskite photoactive layer. Moreover, we provide an outlook on the exciting opportunities this recently developed field offers, and the challenges faced in effectively incorporating MXene materials in the building blocks of PSCs for better operational stability and enhanced performance.

Compositionally graded AlGaN hole source layer for deep-ultraviolet nanowire light-emitting diode without electron blocking layer.

The electron blocking layer (EBL) plays a vital role in blocking the electron overflow from an active region in the AlGaN-based deep-ultraviolet light-emitting diode (DUV-LED). Besides the blocking of electron overflow, EBL reduces hole injection toward the active region. In this work, we proposed a DUV nanowire (NW) LED structure without EBL by replacing it with a compositionally continuous graded hole source layer (HSL).

Adoption of circular economy for food waste management in the context of a developing country.

Food wastage is a global concern with high economic, social and environmental impacts. Pakistan, a developing country, is also significantly affected by the adverse impacts of food wastage. For overcoming this problem, the transition from a Linear to a Circular Economy (CE) for the management of food wastage can serve as a viable strategy.

Social Media for Knowledge Acquisition and Dissemination: The Impact of the COVID-19 Pandemic on Collaborative Learning Driven Social Media Adoption.

During the COVID-19 outbreak, educational institutions were closed, and students worldwide were confined to their homes. In an educational environment, students depend on collaborative learning (CL) to improve their learning performance. This study aimed to increase the understanding of social media adoption among students during the COVID-19 pandemic for the purpose of CL.

A Novel Poly-N-Epoxy Propyl Carbazole Based Memory Device.

Generally, polymer-based memory devices store information in a manner distinct from that of silicon-based memory devices. Conventional silicon memory devices store charges as either zero or one for digital information, whereas most polymers store charges by the switching of electrical resistance. For the first time, this study reports that the novel conducting polymer Poly-N-Epoxy-Propyl Carbazole (PEPC) can offer effective memory storage behavior.

Assessing the performance of computational predictors for estimating protein stability changes upon missense mutations.

Understanding how a mutation might affect protein stability is of significant importance to protein engineering and for understanding protein evolution genetic diseases. While a number of computational tools have been developed to predict the effect of missense mutations on protein stability protein stability upon mutations, they are known to exhibit large biases imparted in part by the data used to train and evaluate them. Here, we provide a comprehensive overview of predictive tools, which has provided an evolving insight into the importance and relevance of features that can discern the effects of mutations on protein stability.

The marvelous optical performance of AlGaN-based deep ultraviolet light-emitting diodes with AlInGaN-based last quantum barrier and step electron blocking layer.

The optoelectronic characteristics of AlGaN-based deep ultraviolet light-emitting diodes (DUV LEDs) with quaternary last quantum barrier (QLQB) and step-graded electron blocking layer (EBL) are investigated numerically. The results show that the internal quantum efficiency (IQE) and radiative recombination rate are remarkably improved with AlInGaN step-graded EBL and QLQB as compared to conventional or ternary AlGaN EBL and last quantum barrier (LQB). This significant improvement is assigned to the optimal recombination of electron-hole pairs in the multiple quantum wells (MQWs).

Imagined character recognition through EEG signals using deep convolutional neural network.

Electroencephalography (EEG)-based brain computer interface (BCI) enables people to interact directly with computing devices through their brain signals. A BCI typically interprets EEG signals to reflect the user's intent or other mental activity. Motor imagery (MI) is a commonly used technique in BCIs where a user is asked to imagine moving certain part of the body such as a hand or a foot.

Effective epileptic seizure detection by using level-crossing EEG sampling sub-bands statistical features selection and machine learning for mobile healthcare.

Mobile healthcare is an emerging approach which can be realized by using cloud-connected biomedical implants. In this context, a level-crossing sampling and adaptive-rate processing based innovative method is suggested for an effective and automated epileptic seizures diagnosis. The suggested solution can achieve a significant real-time compression in computational complexity and transmission activity reduction.

Suppressing the efficiency droop in AlGaN-based UVB LEDs.

The optoelectronic properties of semiconducting aluminum gallium nitride (AlGaN)-based ultraviolet-B (UVB) light-emitting diodes (LEDs) are crucial for real-world medical applications such as cancer therapy and immunotherapy. However, the performance of AlGaN-based UVB LED devices is still poor due to the low hole injection efficiency. Therefore, we have numerically investigated the performance of AlGaN-based UVB LEDs for the suppression of efficiency droop as well as for the enhancement of hole injection in the multiquantum wells (MQWs).

Evaluating humidity sensing response of graphene quantum dots synthesized by hydrothermal treatment of glucose.

Graphene quantum dots (GQDs) were prepared using a single-step hydrothermal treatment of glucose (CHO) powder. X-ray diffraction patterns confirmed the random stacking or amorphous character of GQDs. Additionally, the UV-vis spectra confirmed the formation of GQDs with evident absorption peaks at 237 and 305 nm, which is attributed to-* and-* transitions correspondingly.

Suppressing the efficiency droop in the AlGaN-based UVB LED.

Optoelectronic properties of semiconducting aluminum gallium nitride (AlGaN) - based ultraviolet - B (UVB) light-emitting diodes (LEDs) are crucial for the real-world medical applications such as cancer and immunotherapy. Therefore, we have numerically investigated the performances of AlGaN-based UVB LEDs for the suppression of efficiency droop as well as for the enhancement of hole injection in the multiquantum wells (MQWs). The influence of the undoped (ud)-AlGaN final barrier (FB) as well as Mg-doped multiquantum barrier electron blocking layer (p-MQB EBL) on the efficiency droop has been specifically focused.

mmW Rotman Lens-Based Sensing: An Investigation Study.

A Rotman lens is a wideband true-time delay device. Due to its simplistic structure with wave/signal routing capabilities, it has been widely utilized as a beamforming device in numerous communication systems. Since the basic Rotman lens design incorporates multiple input, output, and dummy ports, in this study, and for the first time, we utilized a Rotman lens as a sensor.

Sustainable production of diapers and their potential outputs for the Pakistani market in the circular economy perspective.

One of the challenging issues of any country's agenda today is the management of solid waste in the circular economy and eco-efficiency perspective. In this context, there has been much debate about the disposal of diapers, but the current research lacks data for developing countries. Furthermore, the research lacks quantification of data, in terms of output products generated through sustainable waste management practices particularly for diapers.

Hysteresis Analysis of Hole-Transport-Material-Free Monolithic Perovskite Solar Cells with Carbon Counter Electrode by Current Density-Voltage and Impedance Spectra Measurements.

Due to the tremendous increase in power conversion efficiency (PCE) of organic-inorganic perovskite solar cells (PSCs), this technology has attracted much attention. Despite being the fastest-growing photovoltaic technology to date, bottlenecks such as current density-voltage () hysteresis have significantly limited further development. Current density measurements performed with different sweep scan speeds exhibit hysteresis and the photovoltaic parameters extracted from the current density-voltage measurements for both scan directions become questionable.

Chitosan-capped ternary metal selenide nanocatalysts for efficient degradation of Congo red dye in sunlight irradiation.

Wastewater emerging from the industries containing organic pollutants is a severe threat to humans' health and aquatic life. Therefore, the degradation of highly poisonous organic dye pollutants is necessary to ensure public health and environmental protection. To tackle this problem, visible-light-driven ternary metal selenide nanocomposites were synthesized successfully by the solvothermal method and supported by chitosan microspheres (FeNiSe-CHM).

A novel and stable ultraviolet and infrared intensity sensor in impedance/capacitance modes fabricated from degraded CHNHPbI-Cl perovskite materials.

The present situation of COVID-19 diverted our focus towards utilizing the degraded solar cells for sensor application, this will help in global energy harvesting. So, here is our successful effort to reuse already degraded solar cells as ultraviolet (UV) and infrared (IR) sensor. The spin-coated perovskite (CHNHPbICl) has been already tested for visible light spectrum, as an extension to that now it is utilized as UV and IR intensity sensors to cover the whole spectrum.