StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.

Hypertension, often known as high blood pressure, is a major concern to millions of individuals globally. Recent studies have demonstrated the significant efficacy of naturally derived peptides in reducing blood pressure. Hypertension is one of the risks associated with cardiovascular disorders and other health problems.

Nickel Nanocluster-Stabilized Unsaturated Ni-N Atomic Sites for Efficient CO-to-CO Electrolysis at Industrial-Level Current.

Unsaturated Ni single-atom catalysts (SACs), Ni-N (x=1,2,3), have been investigated to break the conventional Ni-N structural limitation and provide more unoccupied 3d orbitals for CO reduction reaction (CORR) intermediates adsorption, but their intrinsically low structural stability has seriously hindered their applications. Here, we developed a strategy by integrating Ni nanoclusters to stabilize unsaturated Ni-N atomic sites for efficient CO electroreduction to CO at industrial-level current. Density Functional Theory (DFT) calculations revealed that the incorporation of Ni nanocluster effectively stabilizes the unsaturated Ni-N atomic sites and modulates their electronic structure to enhance the adsorption of the key intermediate *COOH during CORR.

Prevalence of Hand Arm Vibration Syndrome in mine workers of Khewra salt mines.

Background: Hand-arm Vibration Syndrome (HAVS) is a disorder caused by prolonged exposure to hand-held vibrating instruments, commonly observed in industrial contexts such as mining, construction, and manufacturing. It involves symptoms affecting the musculoskeletal, neurological, and vascular systems of the arm and hand.

Purpose: The main aim of this study is to determine the prevalence of HAVS among laborers working in the Khewra salt mines.

COMPARISON OF COMMA INCISION VERSUS MODIFIED WARD'S INCISION IN MANDIBULAR THIRD MOLAR SURGERY-A CLINICAL STUDY.

Background: To evaluate the effectiveness of the two flap/incision techniques, viz. the comma incision versus modified ward's incision in mandibular third molar surgery.

Methods: This randomized research comprised of 126 participants, 63 in every group.

Empowering Tri-Functional Palladium's Catalytic Activity and Durability in Electrocatalytic Formic Acid Oxidation Reaction via Innovative Self-Caging and Alloying Strategies.

Direct formic acid fuel cells (DFAFCs) stand out for portable electronic devices owing to their ease of handling, abundant fuel availability, and high theoretical open circuit potential. However, the practical application of DFAFCs is hindered by the unsatisfactory performance of electrocatalysts for the sluggish anodic formic acid oxidation reaction (FAOR). Palladium (Pd) based nanomaterials have shown promise for FAOR due to their highly selective reaction mechanism, but maintaining high electrocatalytic durability remains challenging.

Thermo-catalytic decomposition of cotton seed press cake over nickel doped zeolite Y, hydrogen: enhanced yield of bio-oil with highly selective fuel-range hydrocarbons.

This research reports the yield of bio-oil from cotton seed press cake (CSPC) an optimized thermo-catalytic pyrolysis using nickel impregnated zeolite Y, hydrogen catalyst. The catalyst, raw biomass and catalyst impregnated biomass were characterized using different analytical techniques. The ideal temperature, duration, and catalyst concentration for pyrolysis experiments were determined to be 300 °C, 20 minutes, and 5% of Ni-doped zeolite Y, hydrogen, respectively, in order to achieve the best bio-oil yield (35%).

Deep learning techniques for Alzheimer's disease detection in 3D imaging: A systematic review.

Background And Aims: Alzheimer's disease (AD) is a degenerative neurological condition that worsens over time and leads to deterioration in cognitive abilities, reduced memory, and, eventually, a decrease in overall functioning. Timely and correct identification of Alzheimer's is essential for effective treatment. The systematic study specifically examines the application of deep learning (DL) algorithms in identifying AD using three-dimensional (3D) imaging methods.

Classification of Alzheimer disease using DenseNet-201 based on deep transfer learning technique.

Alzheimer's disease (AD) is a brain illness that causes gradual memory loss. AD has no treatment and cannot be cured, so early detection is critical. Various AD diagnosis approaches are used in this regard, but Magnetic Resonance Imaging (MRI) provides the most helpful neuroimaging tool for detecting AD.

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features.

Host defense or antimicrobial peptides (AMPs) are promising candidates for protecting host against microbial pathogens for example bacteria, virus, fungi, yeast. Defensins are the type of AMPs that act as potential therapeutic drug agent and perform vital role in various biological process. Conventional Experiments to identify defensin peptides (DPs) are time consuming and expensive.

Molecular Characterization of Lineage-IV Peste Des Petits Ruminants Virus and the Development of In-House Indirect Enzyme-Linked Immunosorbent Assay (IELISA) for its Rapid Detection".

Peste des petits ruminants (PPRV), a highly contagious viral disease, causes significant economic losses concerning sheep and goats. Recently, PPR viruses (PPRVs), have adopted new hosts and lineage IV of PPRVs represents genetic diversity within the same lineage. 350 samples, including blood, swabs, and tissues from sheep/goats, were collected during the 2020-2021 disease outbreaks in Pakistan.

DPI_CDF: druggable protein identifier using cascade deep forest.

Background: Drug targets in living beings perform pivotal roles in the discovery of potential drugs. Conventional wet-lab characterization of drug targets is although accurate but generally expensive, slow, and resource intensive. Therefore, computational methods are highly desirable as an alternative to expedite the large-scale identification of druggable proteins (DPs); however, the existing in silico predictor's performance is still not satisfactory.

An effective tellurium surface modification strategy to enhance the capacity and rate capability of Ni-rich LiNiCoMnO cathode material.

LiNiCoMnO (NCM) layered oxide is contemplated as an auspicious cathode candidate for commercialized lithium-ion batteries. Regardless, the successful commercial utilization of these materials is impeded by technical issues like structural degradation and poor cyclability. Elemental doping is among the most viable strategies for enhancing electrochemical performance.

Sb-Doped Biphasic P2/O3-Type Mn-Rich Layered Oxide Cathode Material for High-Performance Sodium-Ion Batteries.

Mn-rich P2-type layered oxide cathode materials suffer from severe capacity loss caused by detrimental phase transition and transition metal dissolution, making their implementation difficult in large-scale sodium-ion battery applications. Herein, we introduced a high-valent Sb substitution, leading to a biphasic P2/O3 cathode that suppresses the P2-O2 phase transformation in the high-voltage condition attributed to the stronger Sb-O covalency that introduces extra electrons to the O atom, reducing oxygen loss from the lattices and improving structural stability, as confirmed by first-principle calculations. Besides, the enhanced Na diffusion kinetics and thermodynamics in the modified sample are associated with the enlarged lattice parameters.

ML-Based Detection of DDoS Attacks Using Evolutionary Algorithms Optimization.

The escalating reliance of modern society on information and communication technology has rendered it vulnerable to an array of cyber-attacks, with distributed denial-of-service (DDoS) attacks emerging as one of the most prevalent threats. This paper delves into the intricacies of DDoS attacks, which exploit compromised machines numbering in the thousands to disrupt data services and online commercial platforms, resulting in significant downtime and financial losses. Recognizing the gravity of this issue, various detection techniques have been explored, yet the quantity and prior detection of DDoS attacks has seen a decline in recent methods.

G-ACP: a machine learning approach to the prediction of therapeutic peptides for gastric cancer.

Conventional Gastrointestinal (GI) cancer treatments are quite expensive and have major hazards. Nowadays, a different strategy places more emphasis on creating tiny biologically active peptides that do not cause severe poisoning. Anticancer peptides (ACPs) are found through experimental screening, which is time-dependent and frequently fraught with difficulties.

Comprehensive Noise Modeling of Piezoelectric Charge Accelerometer with Signal Conditioning Circuit.

This paper reports on noise modeling of a piezoelectric charge accelerometer with a signal conditioning circuit. The charge output is converted into voltage and amplified using a JFET operational amplifier that has high input resistance and low noise. The noise sources in the whole system include electrical and mechanical thermal noises of the accelerometer, thermal noises of resistors, and voltage and current noises of the operational amplifier.

Tailoring Na Solvation Environment and Electrode-Electrolyte Interphases with Sn(OTf) Additive in Non-flammable Phosphate Electrolytes towards Safe and Efficient Na-S Batteries.

Room-temperature sodium-sulfur (RT Na-S) batteries are promising for low-cost and large-scale energy storage applications. However, these batteries are plagued by safety concerns due to the highly flammable nature of conventional electrolytes. Although non-flammable electrolytes eliminate the risk of fire, they often result in compromised battery performance due to poor compatibility with sodium metal anode and sulfur cathode.

High Genetic Diversity in the Himalayan Common Bean () Germplasm with Divergence from Its Center of Origin in the Mesoamerica and Andes.

The common bean is found in the Himalayan region of Pakistan with substantial morphological variability. Genetic diversity within any crop species is a precursor for genetic improvement; however, little is known about common bean genetic diversity in this region. We explored the genetic diversity in the common bean from the Himalayan region (Khyber Pakhtunkhwa, Gilgit-Baltistan, Kashmir) of Pakistan.

Scalable Precursor-Assisted Synthesis of a High Voltage LiNiCoPO Cathode for Li-Ion Batteries.

A solid-solution cathode of LiCoPO-LiNiPO was investigated as a potential candidate for use with the LiTiO (LTO) anode in Li-ion batteries. A pre-synthesized nickel-cobalt hydroxide precursor is mixed with lithium and phosphate sources by wet ball milling, which results in the final product, LiNiCoPO (LNCP) by subsequent heat treatment. Crystal structure and morphology of the product were analyzed by X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM).

The comparative transcriptome analysis of two green super rice genotypes with varying tolerance to salt stress.

Background: Salinity is one of the main abiotic factors that restrict plant growth, physiology, and crop productivity is salt stress. About 33% of the total irrigated land suffers from severe salinity because of intensive underground water extraction and irrigation with brackish water. Thus, it is important to understand the genetic mechanism and identify the novel genes involved in salt tolerance for the development of climate-resilient rice cultivars.

Lyme rashes disease classification using deep feature fusion technique.

Automatic classification of Lyme disease rashes on the skin helps clinicians and dermatologists' probe and investigate Lyme skin rashes effectively. This paper proposes a new in-depth features fusion system to classify Lyme disease rashes. The proposed method consists of two main steps.

: A promising herbal approach for neurodegenerative disease treatment supported by and research.

Neurodegenerative disorders, caused by progressive neuron loss, are a global health issue. Among the various factors implicated in their pathogenesis, dysregulation of acetylcholinesterase activity has been recognized as a key contributor. Acetylcholinesterase breaks down the neurotransmitter acetylcholine, important for neural transmission.

An Automated Deep Learning Approach for Spine Segmentation and Vertebrae Recognition Using Computed Tomography Images.

Spine image analysis is based on the accurate segmentation and vertebrae recognition of the spine. Several deep learning models have been proposed for spine segmentation and vertebrae recognition, but they are very computationally demanding. In this research, a novel deep learning model is introduced for spine segmentation and vertebrae recognition using CT images.

Synergistic neuroprotection by phytocompounds of Bacopa monnieri in scopolamine-induced Alzheimer's disease mice model.

Background: Millions of people around the globe are affected by Alzheimer's disease (AD). This crippling condition has no treatment despite intensive studies. Some phytocompounds have been shown to protect against Alzheimer's in recent studies.

The Potential of Nanotechnology to Replace Cancer Stem Cells.

Stem cells, which were initially identified in the 1900s, are distinct cells with the potential to replenish themselves as well as differentiate into specialised cells with certain forms and functions. Cancer stem cells play a significant role in the growth and recurrence of the tumours and, similar to normal stem cells, are capable of proliferating and differentiating. Traditional cancer treatments are ineffective against cancer stem cells, which leads to tumour regrowth.