Crystallographic structure, antibacterial effect, and catalytic activities of fig extract mediated silver nanoparticles.

Silver nanoparticles (Ag NPs) play a pivotal role in the current research landscape due to their extensive applications in engineering, biotechnology, and industry. The aim is to use fig ( Linn. f.

Revealing the full potential of CsPbIBr perovskite solar cells: advancements towards enhanced performance.

Cesium lead iodide bromide (CsPbIBr) perovskite solar cells (PSCs) have improved stability compared to other perovskite compositions. However, they still face significant challenges due to their poor photovoltaic performance parameters, which limit the devices' power conversion efficiencies (PCEs). This study proposes a novel device design to tailor the potential of CsPbIBr PSCs by improving their optoelectronic properties.

A machine learning approach for vocal fold segmentation and disorder classification based on ensemble method.

In the healthcare domain, the essential task is to understand and classify diseases affecting the vocal folds (VFs). The accurate identification of VF disease is the key issue in this domain. Integrating VF segmentation and disease classification into a single system is challenging but important for precise diagnostics.

BananaSet: A dataset of banana varieties in Bangladesh.

This article introduces a primary dataset sourced from diverse marketplaces in Bangladesh, encompassing six distinct banana varieties predominantly consumed locally. The dataset comprises the following banana types: . High-resolution images of bananas from each category were acquired using a smartphone camera.

An experimental investigation of spin-on doping optimization for enhanced electrical characteristics in silicon homojunction solar cells: Proof of concept.

The pursuit of enhancing the performance of silicon-based solar cells is pivotal for the progression of solar photovoltaics as the most potential renewable energy technologies. Despite the existence of sophisticated methods like diffusion and ion implantation for doping phosphorus into p-type silicon wafers in the semiconductor industry, there is a compelling need to research spin-on doping techniques, especially in the context of tandem devices, where fabricating the bottom cell demands meticulous control over conditions. The primary challenge with existing silicon cell fabrication methods lies in their complexity, cost, and environmental concerns.

Biosynthesis and characterizations of silver nanoparticles by using green banana peel extract: Evaluation of their antibacterial and electrical performances.

Biosynthesized silver nanoparticles (Ag NPs) hold tremendous promise in nano-bioscience, with applications spanning engineering, science, and industry. This study delves into their fabrication process, crystallographic characteristics, and nanostructures. Employing green banana peel extract (GBPE), Ag NPs were synthesized.

Development of a recycling machine for constructing synthetic yarn from plastic waste.

A major challenge in plastic recycling is to convert plastic waste into a useful product. For this transformation, sustainable technologies such as plastic recycling machines are required. Current technological concepts of plastic recycling are fairly similar.

Investigating the Z-scan technique for quantifying circulating cell-free DNA (ccfDNA) extracted from blood plasma as a potential biomarker for various cancers.

The Z-scan technique is a nonlinear optical method that has found applications in characterizing various materials, particularly those exhibiting nonlinear optical response (NLOR). This study applies the continuous wave (CW) Z-scan technique to examine the NLOR in terms of the nonlinear optical phase shifts(ΔΦ0) exhibited by the ccfDNA extracted from blood plasma samples collected from a group constituting 30 cancer-diagnosed patients and another group constituting 30 non-diagnosed individuals. The cancer group exhibited significantly higherΔΦ0versus incident power slopes compared to the non-cancer group (0.

Exploring cigarette butts pollution in Saint Martin Island: A marine protected area.

Saint Martin Island (SMI), the only coral island in Bangladesh, is located in the Bay of Bengal and has been identified as a marine protected area (MPA). Littering cigarette butts (CBs) waste in an ecologically sensitive environment can have numerous adverse effects. The purpose of this research is to investigate the abundance and density of CBs in SMI and to assess the pollution status using the Cigarette Butt Pollution Index (CBPI).

Tea leaf age quality: Age-stratified tea leaf quality classification dataset.

The "Tea Leaf Age Quality" dataset represents a pioneering agricultural and machine-learning resource to enhance tea leaf classification, detection, and quality prediction based on leaf age. This comprehensive collection includes 2208 raw images from the historic Malnicherra Tea Garden in Sylhet and two other gardens from Sreemangal and Moulvibajar in Bangladesh. The dataset is systematically categorized into four distinct classes (T1: 1-2 days, T2: 3-4 days, T3: 5-7 days, and T4: 7+ days) according to age-based quality criteria.

Cauli-Det: enhancing cauliflower disease detection with modified YOLOv8.

Cauliflower cultivation plays a pivotal role in the Indian Subcontinent's winter cropping landscape, contributing significantly to both agricultural output, economy and public health. However, the susceptibility of cauliflower crops to various diseases poses a threat to productivity and quality. This paper presents a novel machine vision approach employing a modified YOLOv8 model called Cauli-Det for automatic classification and localization of cauliflower diseases.

A Topical Review on Enabling Technologies for the Internet of Medical Things: Sensors, Devices, Platforms, and Applications.

The Internet of Things (IoT) is still a relatively new field of research, and its potential to be used in the healthcare and medical sectors is enormous. In the last five years, IoT has been a go-to option for various applications such as using sensors for different features, machine-to-machine communication, etc., but precisely in the medical sector, it is still lagging far behind compared to other sectors.

A multimodal approach to cross-lingual sentiment analysis with ensemble of transformer and LLM.

Sentiment analysis is an essential task in natural language processing that involves identifying a text's polarity, whether it expresses positive, negative, or neutral sentiments. With the growth of social media and the Internet, sentiment analysis has become increasingly important in various fields, such as marketing, politics, and customer service. However, sentiment analysis becomes challenging when dealing with foreign languages, particularly without labelled data for training models.

RETRACTED: Nobel et al. Modern Subtype Classification and Outlier Detection Using the Attention Embedder to Transform Ovarian Cancer Diagnosis. 2024, , 105-132.

The Editorial Office retracts the article "Modern Subtype Classification and Outlier Detection Using the Attention Embedder to Transform Ovarian Cancer Diagnosis" [...

Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders.

Background: Hair and scalp disorders present a significant challenge in dermatology due to their clinical diversity and overlapping symptoms, often leading to misdiagnoses. Traditional diagnostic methods rely heavily on clinical expertise and are limited by subjectivity and accessibility, necessitating more advanced and accessible diagnostic tools. Artificial intelligence (AI) and deep learning offer a promising solution for more accurate and efficient diagnosis.

Effect of silver doping on the band gap tuning of tungsten oxide thin films for optoelectronic applications.

In the cutting-edge world, semiconductor metal oxides usually tend to have a high optical band gap (>3.0 eV), significantly acceptable for potential optoelectronic applications. The present study discusses the synthesize of pristine tungsten trioxide (WO) and Silver (Ag) doped WO (Ag: WO) thin films onto a glass substrate at 450 °C, with varying concentrations of Ag doping (2, 4, 6, 8 and 10 at.

Impaired sleep, multimorbidity, and self-rated health among Canadians: Findings from a nationally representative survey.

Background: Self-rated health (SRH) is a globally recognized measure of health status. Both impaired sleep (IS) and the presence of multimorbidity are related to poorer SRH, but the precise nature of these associations remains unclear. This study explored the association between IS, multimorbidity, and SRH among Canadian adults.

BaitBuster-Bangla: A comprehensive dataset for clickbait detection in Bangla with multi-feature and multi-modal analysis.

This study presents a large multi-modal Bangla YouTube clickbait dataset consisting of 253,070 data points collected through an automated process using the YouTube API and Python web automation frameworks. The dataset contains 18 diverse features categorized into metadata, primary content, engagement statistics, and labels for individual videos from 58 Bangla YouTube channels. A rigorous preprocessing step has been applied to denoise, deduplicate, and remove bias from the features, ensuring unbiased and reliable analysis.

Detection of COVID-19, pneumonia, and tuberculosis from radiographs using AI-driven knowledge distillation.

Chest radiography is an essential diagnostic tool for respiratory diseases such as COVID-19, pneumonia, and tuberculosis because it accurately depicts the structures of the chest. However, accurate detection of these diseases from radiographs is a complex task that requires the availability of medical imaging equipment and trained personnel. Conventional deep learning models offer a viable automated solution for this task.

SegX-Net: A novel image segmentation approach for contrail detection using deep learning.

Contrails are line-shaped clouds formed in the exhaust of aircraft engines that significantly contribute to global warming. This paper confidently proposes integrating advanced image segmentation techniques to identify and monitor aircraft contrails to address the challenges associated with climate change. We propose the SegX-Net architecture, a highly efficient and lightweight model that combines the DeepLabV3+, upgraded, and ResNet-101 architectures to achieve superior segmentation accuracy.

MedLingua: A conceptual framework for a multilingual medical conversational agent.

This study introduces a hybrid model for an advanced medical chatbot addressing crucial healthcare communication challenges. Leveraging a hybrid ML model, the chatbot aims to provide accurate and prompt responses to users' health-related queries. The proposed model will overcome limitations observed in previous medical chatbots by integrating a dual-stemming approach, P-Stemmer and NLTK-Stemmer, accommodating both semitic and non-semitic languages.

Structural, thermodynamic, and magnetic properties of SrFeO hexaferrite modified by co-substitution of Cu and Gd.

A hard magnetic system of SrFeO nanomaterial was modified according to the composition of SrGdFeCuO with = 0.0, 0.30, and 0.

Comprehensive watermelon disease recognition dataset.

Plant diseases pose a significant obstacle to global agricultural productivity, impacting crop quality yield and causing substantial economic losses for farmers. Watermelon, a commonly cultivated succulent vine plant, is rich in hydration and essential nutrients. However, it is susceptible to various diseases due to unfavorable environmental conditions and external factors, leading to compromised quality and substantial financial setbacks.

Perovskite materials in X-ray detection and imaging: recent progress, challenges, and future prospects.

Perovskite materials have attracted significant attention as innovative and efficient X-ray detectors owing to their unique properties compared to traditional X-ray detectors. Herein, chronologically, we present an in-depth analysis of X-ray detection technologies employing organic-inorganic hybrids (OIHs), all-inorganic and lead-free perovskite material-based single crystals (SCs), thin/thick films and wafers. Particularly, this review systematically scrutinizes the advancement of the diverse synthesis methods, structural modifications, and device architectures exploited to enhance the radiation sensing performance.

LuffaFolio: A Multidimensional Image Dataset of Smooth Luffa.

This article introduces a comprehensive dataset designed for researchers to classify diseases in Luffa leaves, determine the grade of Luffa from Luffa images, and identify different growth stages throughout the year. The dataset is meticulously organized into three sections, each concentrating on specific facets of Luffa Aegyptiaca, commonly known as Smooth Luffa (Dhundol/). These images were captured in various village fields in Faridpur, Bangladesh.