An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks.

Energy efficiency plays a major role in sustaining lifespan and stability of the network, being one of most critical factors in wireless sensor networks (WSNs). To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. The proposed AVOACS method improves clustering by including four critical terms: communication mode decider, distance of sink and nodes, residual energy and intra-cluster distance.

Matairesinol repolarizes M2 macrophages to M1 phenotype to induce apoptosis in triple-negative breast cancer cells.

Objective: Triple-Negative Breast Cancer (TNBC), the most challenging subtype of Breast Cancer (BC), currently lacks targeted therapy, presenting a significant therapeutic gap in its management. Tumor Associated Macrophages (TAMs) play a significant role in TNBC progression and could be targeted by repolarizing them from M2 to M1 phenotype. Matairesinol (MAT), a plant lignan, has been shown to exhibit anticancer, anti-inflammatory and immunomodulatory activities.

A 7-point evidence-based care discharge protocol for patients hospitalized for exacerbation of COPD: consensus strategy and expert recommendation.

Acute exacerbations of COPD (ECOPD) are an important event in the life of a COPD patient as it causes significant deterioration of physical, mental, and social health, hastens disease progression, increases the risk of dying and causes a huge economic loss. Preventing ECOPD is therefore one of the most important goals in the management of COPD. Before the patient is discharged after hospitalization for ECOPD, it is crucial to offer an evidence-based care bundle protocol that will help minimize the future risk of readmissions and death.

Unseen crisis: Revealing the hidden health impact of indoor air pollution-A scoping review.

Indoor air pollution presents a critical public health challenge, particularly in countries such as India, where millions are exposed to harmful pollutants within their homes and workplaces. This scoping review delves into the multifaceted impacts of indoor air pollution on health outcomes, synthesizing evidence from various study designs and geographical regions A scoping review was conducted. Drawing on a comprehensive search strategy, which yielded 320 records, wherein 120 in PubMed, 108 in Web of Science, and 92 in SCOPUS.

Effectiveness of video assisted teaching program of pranayama on selected physiological parameters among patients with COPD.

Background: According to research on the global burden of illness, chronic obstructive pulmonary disease (COPD) is expected to rank third globally in terms of cause of mortality in the first 20 years of the 20 century and fifth in terms of major cause of impairment. A thorough yoga program can enhance general well-being and respiratory function, which will improve a person's capacity to complete daily chores.

Materials And Methods: One group pretest and posttest design in a quasi-experimental study was applied.

Balancing your mind and gut: Exploring the influence of sleep and gut health on emotional well-being.

Background: The relationship between the mind, gut, and sleep is not static and requires proper harmony for optimal emotional health. Recent evidence suggests that gut health is a key player in regulating mental and physical health via bidirectional communication between the brain and gut.

Materials And Methods: A cross-sectional comparative study was undertaken on 200 participants aged 25-40 years old for two months at a tertiary care hospital.

Therapeutic potential of antibody-drug conjugates possessing bifunctional anti-inflammatory action in the pathogenies of rheumatoid arthritis.

In an age where there is a remarkable upsurge in developing precision medicines, antibody-drug conjugates (ADCs) have emerged as a progressive therapeutic strategy. ADCs typically consist of monoclonal antibodies (mAb) conjugated to the cytotoxic payloads by utilizing a linker, combining the benefits of definitive target specificity of mAbs and potent killing impact of payload to achieve precise and efficient elimination of target cells. In addition to their well-established role in oncology, ADCs are currently demonstrating encouraging potential in addressing the unmet requirements in the treatment of autoimmune conditions such as rheumatoid arthritis (RA).

Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy.

Diabetic Retinopathy (DR) stands as a significant global cause of vision impairment, underscoring the critical importance of early detection in mitigating its impact. Addressing this challenge head-on, this study introduces an innovative deep learning framework tailored for DR diagnosis. The proposed framework utilizes the EfficientNetB0 architecture to classify diabetic retinopathy severity levels from retinal images.

Tri-Ponderal Mass Index-A reliable anthropometric index for early screening of adolescent obesity in a school-based setting: A cross-sectional study.

Objective: This study was designed to examine the reliability of the Tri-Ponderal Mass Index (TMI) for early screening of adolescent obesity compared with anthropometric measures such as hip circumference, neck circumference, waist circumference, waist-height ratio, waist-hip ratio, and body mass index.

Methods: A school-based, cross-sectional study was conducted between July and December 2019 among 1101 school-going adolescents (both sexes) aged 12 to 17 years, in Rudrapur, Uttarakhand, India. Anthropometric measurements were collected using well-calibrated equipment, and age- and sex-specific BMI percentile cutoff values recommended by the Indian Academy of Pediatrics were used to define overweight and obesity.

Extracellular vesicles as standard-of-care therapy: will fast-tracking the regulatory processes help achieve the goal?

Extracellular Vesicles (EVs) became a focus of clinical research when experimental and pre-clinical studies showed that they mimic their parent cells' regenerative and therapeutic effects and their cargo carries disease-specific diagnostic and prognostic biomarkers. Since the publication of data forms an endpoint of the study, this review specifically focused on the done with EVs. For brevity, this review was restricted to the last 10 years.

Multi-objective optimization of laser machining parameters for carbon-glass reinforced hybrid composites: Integrating gray relational analysis, regression, and ANN.

This research aims to improve the accuracy of cutting fiber-reinforced polymers (FRPs) utilizing CO2 laser processing techniques, with a particular focus on carbon-glass fiber-reinforced hybrid composites (CGFRP) using epoxy resin. Establishing CO laser machining as a dependable and effective process for creating superior CGFRP components is the main goal. This research intends to optimize laser machining parameters to enhance surface quality and machining efficiency for these composites by a thorough parametric analysis.

Assessing the efficacy of mind mapping as a learning technique to enhance information retrieval in nursing students.

Background: Nursing education, rooted in conventional methods like didactic lectures and clinical experiences, is evolving to incorporate innovative learning strategies. This study delves into the effectiveness of mind mapping, an interactive technique, in enhancing information retrieval skills among nursing students. Departing from linear note-taking, mind maps visually organize information, aligning with contemporary learning theories emphasizing visual and interactive modalities.

Comparison of Taxonomic Resolutions of Various Typing Methods for and Species Isolated from Landfill Leachate.

Anaerobic bacteria and methanogenic archaea at municipal landfill dumping sites play a vital role in the landfill ecology, waste degradation, global warming and climate change. Although landfill works as a cheap way of solid waste management, unmanaged landfill plays a significant role in spreading pollutants and pathogens in natural ecosystems. The genera and are important groups of anaerobic microbes from a public and environmental health perspective.

Advance drought prediction through rainfall forecasting with hybrid deep learning model.

Drought is a natural disaster that can affect a larger area over time. Damage caused by the drought can only be reduced through its accurate prediction. In this context, we proposed a hybrid stacked model for rainfall prediction, which is crucial for effective drought forecasting and management.

Automated crack localization for road safety using contextual u-net with spatial-channel feature integration.

Accurate and timely crack localization is crucial for road safety and maintenance, but image processing and hand-crafted feature engineering methods, often fail to distinguish cracks from background noise under diverse lighting and surface conditions. This paper proposes a framework utilizing contextual U-Net deep learning model to automatically localize cracks in road images. The framework design considers crack localization as a task of pixel-level segmenting, and analyzing each pixel in a road image to determine if it belongs to a crack or not.

Artificial intelligence and machine learning approaches in cerebral palsy diagnosis, prognosis, and management: a comprehensive review.

Cerebral palsy (CP) is a group of disorders that alters patients' muscle coordination, posture, and movement, resulting in a wide range of deformities. Cerebral palsy can be caused by various factors, both prenatal and postnatal, such as infections or injuries that damage different parts of the brain. As brain plasticity is more prevalent during childhood, early detection can help take the necessary course of management and treatments that would significantly benefit patients by improving their quality of life.

Evaluative comparison of machine learning algorithms for stutter detection and classification.

Stuttering is a neuro-developmental speech disorder that interrupts the flow of speech due to involuntary pauses and sound repetitions. It has profound psychological impacts that affect social interactions and professional advancements. Automatically detecting stuttering events in speech recordings could assist speech therapists or speech pathologists track the fluency of people who stutter (PWS).

A method to enhance privacy preservation in cloud storage through a three-layer scheme for computational intelligence in fog computing.

Recent advancements in cloud computing have heightened concerns about data control and privacy due to vulnerabilities in traditional encryption methods, which may not withstand internal attacks from cloud servers. To overcome these issues about the data privacy and control of transfer on cloud, a novel three-tier storage model incorporating fog computing method has been proposed. This framework leverages the advantages of cloud storage while enhancing data privacy.

Effectiveness of neuro-feedback on Alzheimer's rehabilitation: a bibliometric analysis.

Background: Alzheimer's Disease (AD) is a neurodegenerative disorder with limited treatment options. Neurofeedback, a technique that trains brainwaves, has shown promise in addressing cognitive impairments.

Objectives: To conduct a bibliometric analysis to explore the current research on neurofeedback as a treatment for AD.

Accuracy of femoral tunnel placement using three different techniques in performing arthroscopic all-inside anterior Cruciate Ligament reconstruction; A randomized study.

Background: One of the key steps in arthroscopic Anterior Cruciate Ligament Reconstruction (ACLR) is getting the femoral tunnel at the right position to attach the graft. While the correct position has been described as a low and posterior position behind the bifurcate ridge on the medial surface of lateral femoral condyle, to reproducibly achieve it more than one technique is being used by surgeons. There are no randomized studies in literature which have evaluated the efficacy of these in a surgeon's hand.

Tuning fungal promoters for the expression of eukaryotic proteins.

Fungal systems, yeast as well as filamentous fungi, are effective platforms for producing recombinant eukaryotic proteins because of their efficient secretion, robust development features, and capacity for post-translational modification. However, to achieve optimum protein expression in fungal hosts, a precise regulation of gene expression levels is necessary. Promoters are critical cis-regulatory regions that drive gene expression.

Exploring the efficacy of various CNN architectures in diagnosing oral cancer from squamous cell carcinoma.

Unlabelled: Oral cancer can result from mutations in cells located in the lips or mouth. Diagnosing oral cavity squamous cell carcinoma (OCSCC) is particularly challenging, often occurring at advanced stages. To address this, computer-aided diagnosis methods are increasingly being used.