Noninvasive multiclass milk contaminants detection using hyperspectral imaging and hybrid ensemble learning.

Food contamination remains a serious global concern due to its health risks, with milk being one of the most commonly adulterated foods in developing countries such as Pakistan, India, and Bangladesh. Accurate detection of milk contamination is essential for ensuring consumer safety and maintaining food industry standards. This study explores both invasive and noninvasive approaches for contamination analysis.

Epigenetic horizons in aquaculture: unlocking sustainable fish production.

Epigenetics has a profound impact on fish nutrition and aquaculture by regulating gene expression, physiological traits, and growth without altering the underlying DNA sequence. The changes, particularly DNA methylation, can be passed down through generations, enhancing productivity and disease resistance. External factors like temperature, stress, nutrition and illness exposure can also influence epigenetic changes, affecting protein, omega-3 fatty acids, and probiotics.

First-principles study of lead-free NaTmAgCl and NaTmCuCl double halide perovskites for photovoltaic and thermoelectric applications.

This study thoroughly investigates the lead-free halide double perovskites NaTmAeCl (Ae = Ag, Cu) using first-principles density functional theory (DFT) within the CASTEP framework. The formation energies are -3.987 eV for NaTmAgCl and -3.

Pan-cancer analysis of PTPN6: prognostic significance and functional implications in tumor progression.

Background: Cancer remains a leading cause of mortality worldwide, characterized by complex genetic and molecular alterations. The Protein Tyrosine Phosphatase Non-Receptor Type 6 (PTPN6), also known as SHP-1, plays a critical role in regulating immune responses and cellular signaling pathways, with emerging evidence suggesting its involvement in cancer progression. Previous studies have linked aberrant PTPN6 expression to tumorigenesis in specific cancers, such as lymphoma and leukemia, where it acts as a tumor suppressor.

Perylene-based Electron Transport Materials in Perovskite Solar Cells To Improve Power Conversion Efficiency.

Perovskite solar cells (PSCs) are highly efficient and flexible; thus, they have garnered a lot of focus. In the past, many fullerene compounds, such as PCBM, were employed as electron transport layers in PSCs. PCBM has several drawbacks, including surface trapping states, limited electron mobility, poor photochemical as well as thermal stability, a low open-circuit voltage, and significant recombination losses.

Monitoring and investigation to control the brain network disease under immunotherapy by using fractional operator.

Parkinson's disease (PD) is one of the well-known neurodegenerative diseases. The main reason is the death of dopaminergic neurons that release dopamine in the brain region known as the Substantia Nigra pars Compacta (SNc). In this study, we developed a mathematical model of Parkinson's disease incorporating a fractal-fractional operator with the Mittag-Leffler kernel to capture the complex, memory-dependent dynamics of the disease.

Combined effect of thermosonication and natural preservatives on the quality of sugarcane juice.

Sugarcane juice (SCJ) is highly perishable, requiring effective preservation to maintain quality. Traditional methods ensure microbial safety but compromise juice quality, prompting exploration of alternatives. This study evaluated the synergistic effects of thermosonication (TS) and natural preservatives (NP) on SCJ quality, including physicochemical, viscosity, phytochemical, microbial, and sensory attributes.

Strigolactone-biosilica nanoparotectants regulate vacuolar sequestration, phytohormones and oxidative metabolism to enhance cadmium tolerance in Brassica napus.

Cadmium (Cd) contamination severely impairs plant productivity, necessitating effective mitigation strategies. This study investigated the efficacy of strigolactone-conjugated silica nanoparticle (SL-SiO NPs) in regulating Cd-toxicity in Brassica napus L. Foliar application of SL-SiO NPs decreased Cd accumulation (28-22 % in leaves and roots) through enhanced cell wall sequestration, while improving plant height and leaf area.

MXene-nanoparticles foliar application improves wheat morpho-physiological and biochemical traits under cadmium (Cd) stress: A novel sustainable approach.

Cadmium (Cd) pollution is a persistent problem in the agricultural sector. Plants can be treated with nanoparticles (NP) to reduce heavy metal stress. MXene nanoparticles (MX-NPs) were tested for wheat Cd stress relief.

Investigating the use of green synthesized copper oxide nanoparticles from Melia azedarach to combat cadmium stress in wheat.

Wheat (Triticum aestivum L.) is a staple crop that is essential for global food security and nutrition. However, cadmium (Cd) stress significantly impairs plant growth and development by disrupting biological processes.

Synchronization and dynamics of modified fractional order Kawasaki disease model with chaos stability control.

In this paper, fractional calculus has proven to be invaluable in disease transmission dynamics and the creation of control systems, among other real-world problems. To investigate vaccine and treatment dynamics for disease control, this work focuses on Kawasaki illness and uses a unique fractional operator called the modified Atangana-Baleanu-Caputo derivative. The stability analysis, positivity, boundedness, existence, and uniqueness, are treated for the proposed model with novel fractional operators.

Carotid plaque segmentation and classification using MRI-based plaque texture analysis and convolutional neural network.

Background: Accurate segmentation and classification of carotid plaques are critical for assessing stroke risk. However, conventional methods are hindered by manual intervention, inter-observer variability, and poor generalizability across heterogeneous datasets, limiting their clinical utility.

Methods: We propose a hybrid deep learning framework integrating Mask R-CNN for automated plaque segmentation with a dual-path classification pipeline.

Moringa dried leaf extract as bio-foliar fertilizer for revitalizing performance and nutritional status of soybean.

Naturally occurring plant based biostimulants can be used to improve crop productivity and quality as an eco-friendly approach. Moringa oleifera, known as the miracle tree, is a rich source of essential nutrients and beneficial compounds that can act as a potent growth enhancer. Its leaves are nutrient dense that contain rich blends of essential vitamins (A, C, K, and E), riboflavin, iron (Fe) and diverse range of phenolics.

DNA evidence in illicit drug trafficking: A forensic analysis of transfer DNA between packaging materials.

The illicit drug distribution pathway commonly involves powdered substances encapsulated and distributed in small plastic bags via multiple intermediaries. This study investigated the DNA transfer dynamics between individuals involved in the production, packaging, and transportation of such materials through two experimental pathways. In the first experimental design, we established a two-person chain wherein Participant A manufactured and packaged capsules into zip lock bags (ZLBs), which were subsequently transported by Participant C for a four-day period.

Novel conditional tabular generative adversarial network based image augmentation for railway track fault detection.

Railway track fault recognition is a critical aspect of railway maintenance, aiming to identify and rectify defects such as cracks, misalignments, and wear on tracks to ensure safe and efficient train operations. Classical methods for fault detection, including manual inspections and simple sensor-based systems, face significant challenges, such as high labour costs, human error, and limited detection accuracy under varying environmental conditions. These methods are often time-consuming and unable to provide real-time monitoring, leading to potential safety risks and operational inefficiencies.

A kinetic model with analysis for the oxidation of sugars by permanganate in simple aqueous media with sustainable fractional approach.

The development of a recycling method for manganese dioxide, a byproduct of reactions, has made permanganate, a persistent oxidant in organic chemistry, more environmentally benign. This makes permanganate developments in technology more cost-effective and less hazardous to the environment. Understanding the rate and mechanisms of chemical reactions is important in a variety of fields, including chemistry and biology.

Assessing Habitat Suitability for Perris in China: A MaxEnt-Based Predictive Analysis.

Climate change reshapes species distributions, necessitating proactive measures to mitigate ecological impacts. This study investigates the potential spread of , a bark beetle with significant ecological consequences, under future climate scenarios in China. Using the MaxEnt model, we integrated occurrence records and scientific literature with bioclimatic and terrain variables to predict habitat suitability.

Effects of cold storage on the fitness of , as an important parasitoid of palm pests.

The cold storage of biological control agents, such as parasitoids, is a valuable method utilised in mass rearing to ensure the availability of sufficient individuals when needed. This study evaluated the effects of storage temperatures of 9°C and 12°C, along with incubation periods of 7, 14, 21, 28, and 35 days, on the biological fitness of Minamikawa (Hymenoptera: Braconidae). The results demonstrated that the survival rates of adult wasps exceeded 90.

Computational Modelling of the structural, phase stability, electronic, optical, and elastic behaviour of layered perovskites RbAgAsM (M = Cl and F) halide materials for optoelectronics Devices.

The computational modeling of RbAgAsM (M = Cl and F) double perovskite halides is thoroughly examined in this work using the DFT model. RbAgAsM compounds ensured their prospective utility by meeting stability requirements for cubic structures. Formation (-817.

Associations between clinical, biochemical, and nutritional factors in kidney stone formation and recurrence.

This case-control study investigated the relationship between dietary habits and kidney stone development and recurrence at District Headquarters (DHQ) Hospital in Pakistan over a 12-month period. The study included 600 patients with a history of kidney stones and 50 healthy controls aged 18-65. Dietary patterns were evaluated using a 24-hour dietary recall and a semi-quantitative food frequency questionnaire (FFQ), with emphasis on oxalates, calcium, animal protein, fluid consumption, and other nutritional factors.

Above-ground xylem genes and below-ground soil carbon genes analyses provide molecular insights into experimental warming in Phoebe chekiangensis.

Phoebe chekiangensis C. B. Shang is an endemic and endangered species in China, and it is widely used for furniture, building materials and artwork due to its high-quality wood properties and high economic value.

Modeling and computational study of cancer treatment with radiotherapy using real data.

The numerical simulation of biological processes with non-integer ordering is attracting an increasing amount of interest from scientists and academics. Traditional biological systems can be presented in a fixed order, but fractional-order derivative systems are not considered stable orders. When the fractional derivative has a non-fixed order, it becomes more useful for simulating real-world problems.

Advanced Feature Extraction for Cervical Cancer Image Classification: Integrating Neural Feature Extraction and AutoInt Models.

Cervical cancer remains a significant global public health challenge, affecting over half a million women annually, with a mortality rate of approximately 60%, especially in resource-limited regions. This study presents an advanced methodology for cervical cancer diagnosis through deep learning techniques. Utilizing a publicly available cervical cancer image dataset, the research introduces a novel classification framework that integrates a Neural Feature Extractor (NFE) based on a pre-trained VGG16 architecture and an AutoInt model for automatic feature interaction learning.