Negative Prognostic Factors and Clinical Improvement Prediction Modeling for ESWT in Calcific Shoulder Tendinitis Using Artificial Intelligence Techniques.

Background: The efficacy of extracorporeal shockwave therapy (ESWT) for treating shoulder calcific tendinitis can be influenced by various prognostic factors. This study aimed to identify prognostic factors associated with the failure of ESWT for symptom relief and to evaluate the predictive capability of the eXtreme Gradient Boosting (XGBoost) algorithm of artificial intelligence techniques in this context.

Methods: This retrospective study enrolled patients with persistent shoulder pain attributed to calcific tendinitis who underwent ESWT after failed conservative treatment between January 1998 and December 2022.

Screening prediction models using artificial intelligence for moderate-to-severe obstructive sleep apnea in patients with acute ischemic stroke.

Background: Obstructive sleep apnea (OSA) is common after stroke. Still, routine screening of OSA with polysomnography (PSG) is often unfeasible in clinical practice, primarily because of how limited resources are and the physical condition of patients. In this study, we used several artificial intelligence techniques to predict moderate-to-severe OSA and identify its features in patients with acute ischemic stroke.

Unravelling a Latent Pathobiome Across Coral Reef Biotopes.

Previous studies on disease in coral reef organisms have neglected the natural distribution of potential pathogens and the genetic factors that underlie disease incidence. This study explores the intricate associations between hosts, microbial communities, putative pathogens, antibiotic resistance genes (ARGs) and virulence factors (VFs) across diverse coral reef biotopes. We observed a substantial compositional overlap of putative bacterial pathogens, VFs and ARGs across biotopes, consistent with the 'everything is everywhere, but the environment selects' hypothesis.

Development and validation of an experimental life support system to study coral reef microbial communities.

In the present study, we developed and validated an experimental life support system (ELSS) designed to investigate coral reef associated bacterial communities. The microcosms in the ELSS consisted of coral reef sediment, synthetic seawater, and specimens of five benthic reef species. These included two hard corals Montipora digitata and Montipora capricornis, a soft coral Sarcophyton glaucum, a zoanthid Zoanthus sp.

From hate to harmony: Leveraging large language models for safer speech in times of COVID-19 crisis.

This study investigates the rampant spread of offensive and derogatory language during the COVID-19 pandemic and aims to mitigate it through machine learning. Employing advanced Large Language Models (LLMs), the research develops a sophisticated framework adept at detecting and transforming abusive and hateful speech. The project begins by meticulously compiling a dataset, focusing specifically on Chinese language abuse and hate speech.

Formability Prediction Using Machine Learning Combined with Process Design for High-Drawing-Ratio Aluminum Alloy Cups.

Deep drawing has been practiced in various manufacturing industries for many years. With the aid of stamping equipment, materials are sheared to different shapes and dimensions for users. Meanwhile, through artificial intelligence (AI) training, machines can make decisions or perform various functions.

Computer-aided detection of retinopathy of prematurity severity assessment via vessel tortuosity measurement in preterm infants' fundus images.

Objective: To develop a computer-aided diagnostic system for retinopathy of prematurity (ROP) disease using retinal vessel morphological features.

Methods: A total of 200 fundus images from 136 preterm infants with stage 1 to 3 ROP were analysed. Two methods were developed to measure vessel tortuosity: the peak-and-valley method and the polynomial curve fitting method.

Assessment of Anti-Prostate Cancer Activity among Four Seaweeds, with Focus on J.Agardh.

In response to a global shift towards health-conscious and environmentally sustainable food choices, seaweed has emerged as a focus for researchers due to its large-scale cultivation potential and the development of bioactive substances. This research explores the potential anticancer properties of seaweed extracts, focusing on analyzing the impact of four common edible seaweeds in Taiwan on prostate cancer (PCa) cells' activity. The study used bioassay-guided fractionation to extract Cl80 from various seaweeds with androgen receptor (AR)-inhibitory activity.

Maximum Power Point Tracking of Photovoltaic Generation System Using Improved Quantum-Behavior Particle Swarm Optimization.

This study introduces an improved quantum-behavior particle swarm optimization (IQPSO), tailored for the task of maximum power point tracking (MPPT) within photovoltaic generation systems (PGSs). The power stage of the MPPT system comprises a series of buck-boost converters, while the control stage contains a microprocessor executing the biomimetic algorithm. Leveraging the series buck-boost converter, the MPPT system achieves optimal operation at the maximum power point under both ideal ambient conditions and partial shade conditions (PSCs).

Comparison of double chevron-cut and biplanar distal femoral osteotomy techniques: A biomechanical study.

Objective: This study aimed to compare the stability and mechanical properties of the double chevron-cut (DCC) and biplanar (BP) distal femoral osteotomy (DFO) techniques, along with analyzing their respective contact surface areas.

Methods: Biomechanical testing was performed using sawbone and 3D modeling techniques to assess axial and torsional stability, torsional stiffness, and maximum torque of both osteotomy configurations. Additionally, 3D models of the sawbone femur were created to calculate and compare the contact surface area of the DCC, BP, and conventional single-plane DFO techniques.

Treatment Algorithm for the Resorption of Calcific Tendinitis Using Extracorporeal Shockwave Therapy: A Data Mining Study.

Background: Although evidence indicates that extracorporeal shockwave therapy (ESWT) is effective in treating calcifying shoulder tendinitis, incomplete resorption and dissatisfactory results are still reported in many cases. Data mining techniques have been applied in health care in the past decade to predict outcomes of disease and treatment.

Purpose: To identify the ideal data mining technique for the prediction of ESWT-induced shoulder calcification resorption and the most accurate algorithm for use in the clinical setting.

Differential Diagnostic Value of Machine Learning-Based Models for Embolic Stroke.

Cancer-associated thrombosis (CAT) and atrial fibrillation (AF)-related stroke are two subtypes of acute embolic stroke with distinct lesion patterns on diffusion weighted imaging (DWI). This pilot study aimed to evaluate the feasibility and performance of DWI-based machine learning models for differentiating between CAT and AF-related stroke. Patients with CAT and AF-related stroke were enrolled.

Exploring the critical factors influencing the outlying island talent recruitment and selection evaluation model: Empirical evidence from Penghu, Taiwan.

The declining birth rate, population ageing and the outbound migration of young people in recent years have created obstacles for local companies in recruiting skilled personnel. Similar factors have also affected recruitment in the outlying island of Penghu, Taiwan. Multiple-attribute decision-making (MADM) techniques for evaluation model development were incorporated in the present research to investigate the key determinants of talent recruitment by the coffee house operators in the outlying island of Penghu.

Prediction of vancomycin initial dosage using artificial intelligence models applying ensemble strategy.

Background: Antibiotic resistance has become a global concern. Vancomycin is known as the last line of antibiotics, but its treatment index is narrow. Therefore, clinical dosing decisions must be made with the utmost care; such decisions are said to be "suitable" only when both "efficacy" and "safety" are considered.

Effect of Load Carriage Lifestyle on Kinematics and Kinetics of Gait.

Backpacks are commonly worn by many people for multiple purposes. This study investigated the effects of habitual wearing of backpacks on lower limb kinematics and kinetics. Fourteen participants were recruited for analysis.

New 3,4--3,19-Dinor- and Spongian-Based Diterpenoid Lactones from the Marine Sponge sp.

Continuing chemical investigation of the Red Sea sponge sp. led to the isolation of four new 3,4--3,19-dinorspongian diterpenoid lactones, secodinorspongins A-D (-), along with a classical spongian diterpenoid lactone, sponginolide (). The chemical structures, including the absolute configurations of these compounds, were elucidated using the extensive spectroscopic study composed of 1D and 2D NMR data analyses, and a comparison between calculated-electronic-circular-dichroism (ECD) and experimental-circular-dichroism (CD) spectra.

Marine Sponge and Octocoral-Associated Bacteria Show Versatile Secondary Metabolite Biosynthesis Potential and Antimicrobial Activities against Human Pathogens.

Marine microbiomes are prolific sources of bioactive natural products of potential pharmaceutical value. This study inspected two culture collections comprising 919 host-associated marine bacteria belonging to 55 genera and several thus-far unclassified lineages to identify isolates with potentially rich secondary metabolism and antimicrobial activities. Seventy representative isolates had their genomes mined for secondary metabolite biosynthetic gene clusters (SM-BGCs) and were screened for antimicrobial activities against four pathogenic bacteria and five pathogenic strains.

Identification of fish species through tRNA-based primer design.

Background: The correct establishment of the barcode classification system for fish can facilitate biotaxonomists to distinguish fish species, and it can help the government to verify the authenticity of the ingredients of fish products or identify unknown fish related samples. The Cytochrome c oxidation I (COI) gene sequence in the mitochondria of each species possesses unique characteristics, which has been widely used as barcodes in identifying species in recent years. Instead of using COI gene sequences for primer design, flanking tRNA segments of COI genes from 2618 complete fish mitochondrial genomes were analyzed to discover suitable primers for fish classification at taxonomic family level.

Dimensionality reduction approach for many-objective epistasis analysis.

In epistasis analysis, single-nucleotide polymorphism-single-nucleotide polymorphism interactions (SSIs) among genes may, alongside other environmental factors, influence the risk of multifactorial diseases. To identify SSI between cases and controls (i.e.

Artificial-intelligence robot umpires in sailing race.

Today, many maritime nations have been promoting boat sports proactively, including sailing races. As sailing races are large-scale regattas that require massive workforces to monitor the game fairly; however, with limited match budgets and labors, Internet of Things (IoT) technology supports monitoring games has become a trend. This article proposes a robot umpire system in sailing races based on Artificial Intelligence (AI) techniques, using drones and AIoT technology to monitor sailing matches.

Applying DEMATEL-ANP approach to explore the intention to hold roadside wedding banquets in Penghu: A consumers' perspective.

Most people associate Penghu with the roadside banquet, an iconic banquet in the area. Nevertheless, market demand for these banquets has lately fallen drastically, causing a severe impact on the industry. In this study, the critical factors influencing the choice to conduct roadside wedding banquets were investigated from the consumer's standpoint.

Assessing the genomic composition, putative ecological relevance and biotechnological potential of plasmids from sponge bacterial symbionts.

Plasmid-mediated transfer of genes can have direct consequences in several biological processes within sponge microbial communities. However, very few studies have attempted genomic and functional characterization of plasmids from marine host-associated microbial communities in general and those of sponges in particular. In the present study, we used an endogenous plasmid isolation method to obtain plasmids from bacterial symbionts of the marine sponges Stylissa carteri and Paratetilla sp.

Spongenolactones A-C, Bioactive 5,5,6,6,5-Pentacyclic Spongian Diterpenes from the Red Sea Sponge sp.

Three new 5,5,6,6,5-pentacyclic spongian diterpenes, spongenolactones A-C (-), were isolated from a Red Sea sponge sp. The structures of the new metabolites were elucidated by extensive spectroscopic analysis and the absolute configurations of were determined on the basis of comparison of the experimental circular dichroism (CD) and calculated electronic circular dichroism (ECD) spectra. Compounds - are the first 5,5,6,6,5-pentacyclic spongian diterpenes bearing an -hydroxy group at C-1.