Concussion diagnosis and recovery in relation to collegiate athletic department classification: a LIMBIC MATARS consortium investigation.

Purpose: We investigated time to reach concussion diagnosis and recovery milestones in collegiate athletes relative to their schools' National Collegiate Athletic Association (NCAA) classification.

Methods: We retrospectively examined 849 (43.1% female) concussion cases from 11 NCAA institutions (Division I Power 5 [ = 4], Division I Non-Power 5 [ = 4], and Division II/III [ = 3]) from the 2015-16 to 2019-20 athletic seasons.

Deep learning-based tooth segmentation methods in medical imaging: A review.

Deep learning approaches for tooth segmentation employ convolutional neural networks (CNNs) or Transformers to derive tooth feature maps from extensive training datasets. Tooth segmentation serves as a critical prerequisite for clinical dental analysis and surgical procedures, enabling dentists to comprehensively assess oral conditions and subsequently diagnose pathologies. Over the past decade, deep learning has experienced significant advancements, with researchers introducing efficient models such as U-Net, Mask R-CNN, and Segmentation Transformer (SETR).

Classification of benign and malignant pulmonary nodule based on local-global hybrid network.

Background: The accurate classification of pulmonary nodules has great application value in assisting doctors in diagnosing conditions and meeting clinical needs. However, the complexity and heterogeneity of pulmonary nodules make it difficult to extract valuable characteristics of pulmonary nodules, so it is still challenging to achieve high-accuracy classification of pulmonary nodules.

Objective: In this paper, we propose a local-global hybrid network (LGHNet) to jointly model local and global information to improve the classification ability of benign and malignant pulmonary nodules.

How flow and mindfulness interact with each other in mindfulness-based augmented reality mandala coloring activities.

Introduction: This study explores the effects of different types of augmented reality (AR) mandala coloring activities on mindfulness and flow in college students.

Methods: A total of 76 college students participated in the study and were divided into two groups based on their drawing skills: the high-skilled group ( = 38) and the low-skilled group ( = 38). With the help of AR technology, two groups of subjects carried out three mandala coloring experiments with structured mandala, free mandala and cooperative mandala in order.

Double-Strip Array-Based Metasurfaces with BICs for Terahertz Thin Membrane Detection.

A double-strip array-based metasurface that supports the sharp quasi-bound states in the continuum (quasi-BICs) is demonstrated in terahertz regions. By tuning the structural parameters of metal strips, the conversion of BICs and quasi-BICs is controllable. The simulated results exhibit an achieved maximum Q-factor for quasi-BICs that exceeds 500, corresponding to a bandwidth that is less than 1 GHz.

Spatial co-location patterns between early COVID-19 risk and urban facilities: a case study of Wuhan, China.

Introduction: COVID-19, being a new type of infectious disease, holds significant implications for scientific prevention and control to understand its spatiotemporal transmission process. This study examines the diverse spatial patterns of COVID-19 within Wuhan by analyzing early case data alongside urban infrastructure information.

Methods: Through co-location analysis, we assess both local and global spatial risks linked to the epidemic.

Training methods and evaluation of basketball players' agility quality: A systematic review.

Objective: Agility refers to the technical skills and abilities required by athletes to quickly react and adjust direction, speed, or movement patterns when faced with stimuli. This article provides a comprehensive review and evaluation of agility training methods for basketball players, offering valuable insights and references for scientifically enhancing their agility training.

Method: Research literature published from January 1, 2000, to April 1, 2023, was searched in the Web of Science Core Collection, PubMed, and EBSCO databases with basketball, agility, and training as keywords.

The role of basic psychological needs in the relationships between identity orientations and adolescent mental health: A protocol for a longitudinal study.

Research into the role of identity orientations (the relative importance an individual places on different personal and social attributes and characteristics when defining her or his identity) in adolescent mental health is extremely limited. Furthermore, the potential mechanisms that might explain the associations between identity orientations and adolescent mental health are poorly understood. This study protocol describes a one-year longitudinal study across three time points to be initiated with the purpose of investigating the mediating role of basic psychological needs satisfaction and frustration in the relationship between identity orientations and various mental health indicators in adolescence.

Delta-tocotrienol disrupts PD-L1 glycosylation and reverses PD-L1-mediated immune suppression.

PD-L1-mediated immune escape plays an important role in cancer development and progression. Targeting PD-L1 is consider to be an attractive approach for cancer treatment. PD-L1 is a heavily N-linked glycosylated protein, and the glycosylation of PD-L1 is essential for its ability to interact with its receptor PD-1 to mediate immune suppression.

Visual fatigue a comprehensive review of mechanisms of occurrence, animal model design and nutritional intervention strategies.

When the eyes work intensively, it is easy to have eye discomfort such as blurred vision, soreness, dryness, and tearing, that is, visual fatigue. Visual fatigue not only affects work and study efficiency, but long-term visual fatigue can also easily affect physical and mental health. In recent years, with the popularization of electronic products, although it has brought convenience to the office and study, it has also caused more frequent visual fatigue among people who use electronic devices.

Exploring Attitudes Toward "Sugar Relationships" Across 87 Countries: A Global Perspective on Exchanges of Resources for Sex and Companionship.

The current study investigates attitudes toward one form of sex for resources: the so-called sugar relationships, which often involve exchanges of resources for sex and/or companionship. The present study examined associations among attitudes toward sugar relationships and relevant variables (e.g.

Coexistence of Gaussian and non-Gaussian statistics in vector integrable turbulence.

Integrable turbulence studies the complex dynamics of random waves for the nonlinear integrable systems, and it has become an important element in exploring the sophisticated turbulent phenomena. In the present work, based on the coupled nonlinear Schrödinger models, we have shown the coexistence of Gaussian and non-Gaussian single-point statistics in multiple wave components, which might be viewed as an exclusive feature for the vector integrable turbulence. This coexistent statistic can relate to different distributions of the vector solitonic excitations depending on the time-invariant nonlinear spectra.

University lecturers' perceived stress and self-rated health during COVID-19.

Background: In 2022, many universities transitioned from virtual learning back to in-person teaching. Significant changes in working conditions, along with COVID-19-related anxiety during the pandemic, might impact the well-being of lecturers.

Objective: This study aims to assess the perceived stress, self-rated physical and occupational health of Vietnamese lecturers in 2022 compared to the pre-pandemic levels, and to identify their associating factors.

Utilization of gene manipulation system for advancing the biotechnological potential of halophiles: A review.

Halophiles are salt-loving microorganisms known to have their natural resistance against media contamination even when cultivated in nonsterile and continuous bioprocess system, thus acting as promising cell factories for Next Generation of Industrial Biotechnology (NGIB). NGIB - a successor to the traditional industrial biotechnology, is a more sustainable and efficient bioprocess technology while saving energy and water in a more convenient way as well as reducing the investment cost and skilled workforce requirement. Numerous studies have achieved intriguing outcomes during synthesis of different metabolite using halophiles such as polyhydroxyalkanoates (PHA), ectoine, biosurfactants, and carotenoids.

Securing image-based document transmission in logistics and supply chain management through cheating-resistant visual cryptographic protocols.

In today's digital landscape, securing multimedia visual information-specifically color images-is of critical importance across a range of sectors, including the burgeoning fields of logistics and supply chain management. Traditional Visual Cryptography (VC) schemes lay the groundwork for encrypting visual data by fragmenting a secret image into multiple shares, thereby ensuring no single share divulges the secret. Nevertheless, VC faces challenges in ascertaining the integrity of reconstructed images, especially when shares are manipulated maliciously.

Ensemble model for predicting chronic non-communicable diseases using Latin square extraction and fuzzy-artificial neural networks from 2013 to 2019.

Background: The presented study tracks the increase or decrease in the prevalence of seventeen different chronic non-communicable diseases in Serbia. This analysis considers factors such as region, age, and gender and is based on data from two national cross-sectional studies conducted in 2013 and 2019. The research aims to accurately identify the regions with the highest percentage of affected individuals, as well as their respective age and gender groups.

Prevention of STAT3-related pathway in SK-N-SH cells by natural product astaxanthin.

Purpose: Neuroblastoma (NB) is the most common solid malignancy in children. Despite current intensive treatment, the long-term event-free survival rate is less than 50% in these patients. Thus, patients with NB urgently need more valid treatment strategies.

Acute Oral Toxicity Evaluation of Almond Hull Powders in BALB/c Mice.

Almond hull, a substantial byproduct constituting more than half of almond fresh weight, has garnered recent attention due to its abundance in fiber and bioactive content. Despite this huge interest, data on its toxicity remain scarce. In line with the Organization for Economic Cooperation and Development (OECD) 423 guidelines, this study conducted an acute oral toxicity test using almond hull powders processed from three major almond varieties of Butte, Monterey, and Nonpareil on BALB/c female mice, administering dosages of 300 mg/kg body weight (bw), 2000 mg/kg bw, and 5000 mg/kg bw, with observations over a 14-day period.

Comparison of ACE-IQ and CTQ-SF for child maltreatment assessment: Reliability, prevalence, and risk prediction.

Background: Child maltreatment has profound effects on mental health. The Childhood Trauma Questionnaire Short Form (CTQ-SF) and the Adverse Childhood Experiences International Questionnaire (ACE-IQ) are commonly used retrospective assessment tools for evaluating child maltreatment.

Objective: This study aims to conduct a comprehensive comparison of the CTQ-SF and ACE-IQ, encompassing internal consistency, prevalence, and the predictive efficacy of trauma-related outcomes.

AFTR: A Robustness Multi-Sensor Fusion Model for 3D Object Detection Based on Adaptive Fusion Transformer.

Multi-modal sensors are the key to ensuring the robust and accurate operation of autonomous driving systems, where LiDAR and cameras are important on-board sensors. However, current fusion methods face challenges due to inconsistent multi-sensor data representations and the misalignment of dynamic scenes. Specifically, current fusion methods either explicitly correlate multi-sensor data features by calibrating parameters, ignoring the feature blurring problems caused by misalignment, or find correlated features between multi-sensor data through global attention, causing rapidly escalating computational costs.