A multi-objective improved horse herd optimizer based on convex lens imaging for stochastic optimization of wind energy resources in distribution networks considering reliability and uncertainty.

In this study, stochastic multi-objective allocation of wind turbines (WTs) in radial distribution networks is performed using a new multi-objective improved horse herd optimizer (MOIHHO) and an unscented transformation (UT) method for modeling the uncertainties of WTs power and network load. The objective function aims to minimize power loss, improve reliability, and reduce the costs associated with wind turbines (WTs), presenting these goals as a three-dimensional function. The Multi-Objective Improved Horse Herd Optimizer (MOIHHO) is derived from an enhanced version of the traditional horse herd optimizer.

Exploring the Psychological Mechanism of How the Multidimensional Service Quality of Fitness Centers Affects Consumer Satisfaction and Loyalty Depending on the Level of Exercise Involvement.

This study aimed to examine the influence of core services and the physical servicescape and social servicescape on consumer satisfaction and loyalty via perceived price fairness, flow experience, and rapport in fitness centers. Additionally, the present study explored how exercise involvement moderates the relationship between perceived price fairness, flow experience, rapport, and consumer satisfaction. For these purposes, targeting adults using fitness centers in South Korea, a total of 763 participants were sampled based on a cross-sectional design and used for data analyses involving confirmatory factor analysis for measurement validation and latent moderated structural equation modeling for hypothesis testing.

A fish fry dataset for stocking density control and health assessment based on computer vision.

Fish farming is a promising economic activity that promotes the social development, protects the ecological environment, and enhances the quality of human life. In recent years, various computer vision models have been established for assessing aquaculture density and monitoring fish health. However, existing datasets are generally characterised by larger fish sizes and low density, making them unsuitable for detecting small targets such as fish fry.

Marine polysaccharides for antibiofilm application: A focus on biomedical fields.

Microbial pathogens such as bacteria and fungi form biofilms, which represent substantial hurdles in treating human illness owing to their adaptive resistance mechanism to conventional antibiotics. Biofilm may cause persistent infection in a variety of bodily areas, including wounds, oral cavity, and vaginal canal. Using invasive devices such as implants and catheters contributes significantly to developing healthcare-associated infections because they offer an ideal surface for biofilm formation.

A hybrid healthy diet recommender system based on machine learning techniques.

Obesity is a chronic disease correlated with numerous risk factors that not only negatively affect all body functions but also increase the chances of developing chronic diseases and the associated morbidity and mortality rates. This study proposes a novel system that bridges the gap between healthcare providers and patients by offering both parties some tools for navigating the intricacies of dietary planning. In this system, machine learning techniques are used to determine the required calories before starting an obesity treatment.

A series of blue phosphorescent iridium complexes with thermally activated delayed fluorescence and efficiency roll-off properties.

Six iridium complexes were designed and studied using the DFT approach, (ppy)Ir(pic) (1), (fppy)Ir(pic) (2), (ppy)Ir(tmd) (3), (fppy)Ir(tmd) (4), (ppy)Ir(tpip) (5) and (fppy)Ir(tpip) (6). Here ppy denotes phenylpyridine, fppy denotes 2-(2,3,4,5-tetrafluorophenyl) pyridine, pic denotes benzoic acid, tmd denotes 5-hydroxy-2,2,6,6-tetramethylhept-4-en-3-one and tpip denotes tetraphenylimido-diphosphinate. The geometries, absorptions, emissions, frontier molecular orbitals, and spin-orbit coupling (SOC) constants of the 6 complexes were evaluated.

Proactive personality and its impact on online learning engagement through positive emotions and learning motivation.

The rapid change in information technology has made online or blended learning a new norm in higher education. However, the problem of low student engagement in online learning is becoming more prominent. This study explores how college students' proactive personality affects their online learning engagement through the mediating effects of positive emotions and learning motivation.

Cellulose nanocrystals/cellulose nanofibrils-combined astaxanthin nanoemulsion for reinforcement of targeted tumor delivery of gastric cancer cells.

Nanoemulsion based nanomaterial (NE) was carried out in the present study to evaluate the efficacy and its antitumor potential of the gastric cancer cells. NE was prepared with astaxanthin/alpha-tocopherol- cellulose nanocrystals/cellulose nanofibrils based nanoemulsions for gastric cancer treatment. The cytotoxic potential was tested against cancer cells and evaluated in terms of its cell proliferation, migration, and cellular uptake by the standard methods.

3D-printed polycaprolactone/collagen/alginate scaffold incorporating phlorotannin for bone tissue regeneration: Assessment of sub-chronic toxicity.

The development of effective scaffolds for bone regeneration is crucial given the increasing demand for innovative solutions to address bone defects and enhance healing process. In this study, a polycaprolactone/fish collagen/alginate (P/FC/A) 3D scaffold incorporating phlorotannin was developed to promote bone tissue regeneration. While the efficacy of the P/FC/A scaffold has been demonstrated through in vitro and in vivo experiments, its sub-chronic toxicity in animal models remains understudied, raising concerns regarding its safety in clinical application.

Control of Staphylococcus aureus infection by biosurfactant derived from Bacillus rugosus HH2: Strain isolation, structural characterization, and mechanistic insights.

Novel antimicrobials are urgently needed to combat methicillin-resistant Staphylococcus aureus (MRSA) infections. This study explores the potential of biosurfactants derived from Bacillus rugosus HH2 as a novel antibacterial agent against MRSA. The biosurfactant, identified as surfactin, demonstrated surface-active properties, reducing surface tension to 37.

Key point trajectory prediction method of human stochastic posture falls.

The human body will show very complex and diversified posture changes in the process of falling, including body posture, limb position, angle and movement trajectory, etc. The coordinates of the key points of the model are mapped to the three-dimensional space to form a three-dimensional model and obtain the three-dimensional coordinates of the key points; The construction decomposition method is used to calculate the rotation matrix of each key point, and the rotation matrix is solved to obtain the angular displacement data of the key points on different degrees of freedom. The method of curve fitting combined with the weight distribution kernel function based on self-organizing mapping theory is used to obtain the motion trajectory prediction equation of the human body falling in different degrees of freedom at random positions in three-dimensional space, determine the key point trajectory of human random fall behaviour.

Alg-MFDL: A multi-feature deep learning framework for allergenic proteins prediction.

The escalating global incidence of allergy patients illustrates the growing impact of allergic issues on global health. Allergens are small molecule antigens that trigger allergic reactions. A widely recognized strategy for allergy prevention involves identifying allergens and avoiding re-exposure.

Identification of Structure-Linked Activity on Bioactive Peptides from Sea Cucumber (): A Compressive Study.

Background: A sea cucumber () is an invertebrate rich in high-quality protein peptides that inhabits the coastal seas around East Asian countries. Such bioactive peptides can be utilized in targeted disease therapies and practical applications in the nutraceutical industry.

Methods: Bioactive peptides were isolated from through ultrafiltration and Sephadex G-10 size exclusion chromatography.

Ammonia Sensing Performance at Room Temperature of Ca-Doped CNFs/AlO Gas Sensor.

When NH in the environment exceeds a certain concentration, it may have adverse effects on human health. Ammonia gas sensors currently on the market usually work under high temperatures and are not only expensive but also have poor performance in terms of selectivity. Therefore, the preparation of an ammonia gas sensor that works at room temperature, is low cost, and has high sensitivity and selectivity is particularly important.

High-Efficiency Clustering Routing Protocol in AUV-Assisted Underwater Sensor Networks.

Currently, underwater sensor networks are extensively applied for environmental monitoring, disaster prediction, etc. Nevertheless, owing to the complicacy of the underwater environment, the limited energy of underwater sensor nodes, and the high latency of hydroacoustic channels, the energy-efficient operation of underwater sensor networks has become an important challenge. In this paper, a high-efficiency clustering routing protocol in AUV-assisted underwater sensor networks (HECRA) is proposed to address the energy limitations and low data transmission reliability in underwater sensor networks.

Therapeutic Effect of Decellularized Extracellular Matrix from Fish Skin for Accelerating Skin Regeneration.

A cellular matrix derived from natural tissue functions as a highly biocompatible and versatile material for wound healing application. It provides a complex and highly organized environment with biological molecules and physical stimuli. Recently, various kinds of tissue/organ decellularized extracellular matrixes (dECMs) from bovine and porcine have been used as biomedical applications to support tissue regeneration but inherit religious restrictions and the risk of disease transmission to humans.

Ascorbic acid mediated fluorescence emission of MnO modified upconversion nanoparticles for anti-counterfeiting.

Anti-counterfeiting ink can prevent important documents from being forged or tampered with. We reported a strategy to improve upconversion luminescence intensity of NaYF:18%Yb,0.5%Tm core nanoparticles (NPs) by coating the NaYF shell.

Preparation, characterization, and stability of chitosan-tremella polysaccharide layer-by-layer encapsulated astaxanthin nanoemulsion delivery system.

In this study, a layer-by-layer (LBL) encapsulated astaxanthin (Ast) nanoemulsion delivery system based on chitosan (CS) and tremella polysaccharide (TP) was successfully developed. The system constructed an Ast-CS-TP emulsion with high encapsulation efficiency and an excellent stability profile by utilizing the opposite charge properties of CS and TP. This study evaluated the effects of different stresses (including temperature, salt addition, pH, UV irradiation, and centrifugal force) on the emulsion's stability.

VotePLMs-AFP: Identification of antifreeze proteins using transformer-embedding features and ensemble learning.

Antifreeze proteins (AFPs) are a unique class of biomolecules capable of protecting other proteins, cell membranes, and cellular structures within organisms from damage caused by freezing conditions. Given the significance of AFPs in various domains such as biotechnology, agriculture, and medicine, several machine learning methods have been developed to identify AFPs. However, due to the complexity and diversity of AFPs, the predictive performance of existing methods is limited.

Automatic Recommender System of Development Platforms for Smart Contract-Based Health Care Insurance Fraud Detection Solutions: Taxonomy and Performance Evaluation.

Background: Health care insurance fraud is on the rise in many ways, such as falsifying information and hiding third-party liability. This can result in significant losses for the medical health insurance industry. Consequently, fraud detection is crucial.

Shaping futures: The impact of family involvement, peer and coach support on the career orientation of indigenous student athletes.

This study explores the impact of family involvement on the career orientation of Indigenous baseball student athletes, considering the mediating roles of peer and coach support. Using Structural Equation Modeling, data were collected from 354 Indigenous student athletes registered on a regional baseball network between October and December 2022. The analysis reveals that family involvement directly influences career orientation significantly and also indirectly affects it through the mechanisms of peer and coach support.

Research on the Behavior Recognition of Beef Cattle Based on the Improved Lightweight CBR-YOLO Model Based on YOLOv8 in Multi-Scene Weather.

In modern animal husbandry, intelligent digital farming has become the key to improve production efficiency. This paper introduces a model based on improved YOLOv8, Cattle Behavior Recognition-YOLO (CBR-YOLO), which aims to accurately identify the behavior of cattle. We not only generate a variety of weather conditions, but also introduce multi-target detection technology to achieve comprehensive monitoring of cattle and their status.