The impact of the COVID-19 pandemic on dyslipidemia in peritoneal dialysis patients.

Background: The coronavirus disease 2019 (COVID-19) pandemic has had a profound impacted on various aspects of society, including the healthcare system and patient care. In this context, this study aimed to evaluate the impact of COVID-19 control strategies on the lipid profile and blood sugar levels of peritoneal dialysis (PD) patients in Taiwan, a crucial focus for understanding the pandemic's influence on individuals with chronic kidney disease (CKD).

Methods: A retrospective cohort study was conducted, analyzing data from the medical records of 170 PD patients who visited the nephrology division of Taipei Veterans General Hospital in 2021.

Learn Zero-Constraint-Violation Safe Policy in Model-Free Constrained Reinforcement Learning.

We focus on learning the zero-constraint-violation safe policy in model-free reinforcement learning (RL). Existing model-free RL studies mostly use the posterior penalty to penalize dangerous actions, which means they must experience the danger to learn from the danger. Therefore, they cannot learn a zero-violation safe policy even after convergence.

Robust Approximate Dynamic Programming for Nonlinear Systems With Both Model Error and External Disturbance.

Model error and external disturbance have been separately addressed by optimizing the definite H performance in standard linear H control problems. However, the concurrent handling of both introduces uncertainty and nonconvexity into the H performance, posing a huge challenge for solving nonlinear problems. This article introduces an additional cost function in the augmented Hamilton-Jacobi-Isaacs (HJI) equation of zero-sum games to simultaneously manage the model error and external disturbance in nonlinear robust performance problems.

Optimization Landscape of Policy Gradient Methods for Discrete-Time Static Output Feedback.

In recent times, significant advancements have been made in delving into the optimization landscape of policy gradient methods for achieving optimal control in linear time-invariant (LTI) systems. Compared with state-feedback control, output-feedback control is more prevalent since the underlying state of the system may not be fully observed in many practical settings. This article analyzes the optimization landscape inherent to policy gradient methods when applied to static output feedback (SOF) control in discrete-time LTI systems subject to quadratic cost.

Socioeconomic factors, perceived stress, and social support effect on neonatal nurse burnout in China: a cross-sectional study.

Background: Neonatal nurses' working environments are highly stressful, and burnout is common. This study examines the effect of socioeconomic factors, perceived stress, and social support on neonatal nurse burnout.

Methods: A total of 311 neonatal nurses participated in this study.

Policy-Iteration-Based Finite-Horizon Approximate Dynamic Programming for Continuous-Time Nonlinear Optimal Control.

The Hamilton-Jacobi-Bellman (HJB) equation serves as the necessary and sufficient condition for the optimal solution to the continuous-time (CT) optimal control problem (OCP). Compared with the infinite-horizon HJB equation, the solving of the finite-horizon (FH) HJB equation has been a long-standing challenge, because the partial time derivative of the value function is involved as an additional unknown term. To address this problem, this study first-time bridges the link between the partial time derivative and the terminal-time utility function, and thus it facilitates the use of the policy iteration (PI) technique to solve the CT FH OCPs.

Exploration of "Zhang" in functional gastrointestinal disorders: A cross-cultural challenge in Chinese clinical setting.

Objectives: In China, four symptoms of functional gastrointestinal disorders, postprandial fullness, early satiety, bloating, and abdominal distension are commonly and interchangeably expressed as a single chief complaint, "Zhang". In this study we aimed to explore the most efficient method of determining the characteristics of symptoms in such patients.

Methods: Consecutive patients with the chief complaint of abdominal "Zhang" from December 2017 to June 2018 were included.

Lifestyle and Social Factors Exacerbated on the Prevalence of Mood Disorders and Functional Dyspepsia Among Neonatal Nurses in China.

Background: Nursing is a high-stress occupation that can have an impact on mental health, particularly for neonatal nurses. Job-related stress factors and work-related behaviors have played a critical role in nurses' mental health. This study aimed to explore the prevalence of mood disorders and the impact of social factors, lifestyle on mood disorders among neonatal nurses.

Model-Based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian.

Safety is essential for reinforcement learning (RL) applied in the real world. Adding chance constraints (or probabilistic constraints) is a suitable way to enhance RL safety under uncertainty. Existing chance-constrained RL methods, such as the penalty methods and the Lagrangian methods, either exhibit periodic oscillations or learn an overconservative or unsafe policy.

Human papillomavirus seroprevalence and seroconversion following baseline detection of nine human papillomavirus types in young women.

Background: Estimates of the humoral immune response to incident human papillomavirus (HPV) infections are limited.

Methods: In this post hoc analysis of 3875 women aged 16-23 years from a 4-valent HPV vaccine trial (NCT00092482), HPV seroprevalence on day 1 was measured with a 9-valent HPV (HPV 6/11/16/18/31/33/45/52/58) competitive Luminex immunoassay and compared with cervical/external genital HPV detection by polymerase chain reaction. In the control group, among women who were HPV DNA‒negative on day 1, seroconversion following initial HPV detection was estimated using Kaplan-Meier methods.

Integrated Decision and Control: Toward Interpretable and Computationally Efficient Driving Intelligence.

Decision and control are core functionalities of high-level automated vehicles. Current mainstream methods, such as functional decomposition and end-to-end reinforcement learning (RL), suffer high time complexity or poor interpretability and adaptability on real-world autonomous driving tasks. In this article, we present an interpretable and computationally efficient framework called integrated decision and control (IDC) for automated vehicles, which decomposes the driving task into static path planning and dynamic optimal tracking that are structured hierarchically.

Effects of a nursing home telehealth program on spending and utilization for Medicare residents.

Objective: To assess the effects of eLongTermCare (eLTC), a telehealth program implemented by an integrated health system in 45 nursing homes across the Midwest, on the use of acute hospital services and total expenditures for Medicare residents.

Data Sources: Minimum Data Set, Medicare fee-for-service claims, and enrollment data from 2013 to 2018.

Study Design: We used a longitudinal difference-in-differences design to estimate the changes in outcomes for treatment beneficiaries before and after participating in the eLTC program, relative to changes for the matched comparison beneficiaries over the same period.

Bcl-2 Interacts with Beclin 1 and Regulates Autophagy in 7, 12-Dimethylbenz[a]anthracene-Induced Hamster Buccal-Pouch Squamous-Cell Tumorigenesis.

Objective: Autophagy is a programmed cell death procedure, which has essential functions in tumorigenesis. However, its temporal expression and function under different status are yet to be determined. This study aims to investigate the temporal expression of autophagy and its possible function in 7,12-dimethylbenz[a]anthracene (DMBA)-induced hamster buccal-pouch cancer model (HBPCM).

Electronic-structure evolution of SrFeOduring topotactic phase transformation.

Oxygen-vacancy-induced topotactic phase transformation between the ABObrownmillerite structure and the ABOperovskite structure attracts ever-increasing attention due to the perspective applications in catalysis, clean energy field, and memristors. However, a detailed investigation of the electronic-structure evolution during the topotactic phase transformation for understanding the underlying mechanism is highly desired. In this work, multiple analytical methods were used to explore evolution of the electronic structure of SrFeOthin films during the topotactic phase transformation.

Engineered Nanomaterials Suppress the Soft Rot Disease () and Slow Down the Loss of Nutrient in Sweet Potato.

About 45% of the world's fruit and vegetables are wasted, resulting in postharvest losses and contributing to economic losses ranging from $10 billion to $100 billion worldwide. Soft rot disease caused by leads to postharvest storage losses of sweet potatoes. Nanoscience stands as a new tool in our arsenal against these mounting challenges that will restrict efforts to achieve and maintain global food security.

Use of M-M-R II outside of the routinely recommended age range - a systematic literature review.

M-M-R® (M-M-R II) is routinely used in many countries at 12-15 months with a second dose at 4 to 6 years of age. However, the vaccine may need to be administered at other ages due to delays in the immunization schedule or in certain situations such as outbreaks or international travel. A systematic literature review was conducted to evaluate efficacy, immunogenicity and safety of M-M-R II among 6- to 11-month-olds and persons ≥7 years of age.

Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors.

In reinforcement learning (RL), function approximation errors are known to easily lead to the Q -value overestimations, thus greatly reducing policy performance. This article presents a distributional soft actor-critic (DSAC) algorithm, which is an off-policy RL method for continuous control setting, to improve the policy performance by mitigating Q -value overestimations. We first discover in theory that learning a distribution function of state-action returns can effectively mitigate Q -value overestimations because it is capable of adaptively adjusting the update step size of the Q -value function.

-monosubstituted thiosemicarbazide as novel Ure inhibitors: synthesis, biological evaluation and molecular docking.

Identification of novel Ure inhibitors with high potency has received considerable attention. Ure inhibition was determined using the indophenol method, the affinities to Ure were estimated via surface plasmon resonance. Seventeen new plus ten known -monosubstituted thiosemicarbazides were synthesized and identified as novel Ure inhibitors.

Human Papillomavirus Genotypes From Vaginal and Vulvar Intraepithelial Neoplasia in Females 15-26 Years of Age.

Objective: To estimate the proportion of vulvar and vaginal low-grade and high-grade squamous intraepithelial lesions (LSILs and HSILs) in females 15-26 years of age attributable to 14 human papillomavirus (HPV) genotypes (6, 11, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59).

Methods: A post hoc analysis of prospectively diagnosed vulvar and vaginal LSILs and HSILs among females 15-26 years of age enrolled in the placebo arms of two phase 3, randomized HPV vaccine trials assessed 14 prespecified HPV genotypes associated with cervical cancers or anogenital warts using a type-specific multiplex polymerase chain reaction assay. The frequency of lesions associated with specific HPV genotypes was estimated by proportional and other attribution methods.

Driver braking behavior analysis to improve autonomous emergency braking systems in typical Chinese vehicle-bicycle conflicts.

Bicycling is one of the fundamental modes of transportation especially in developing countries. Because of the lack of effective protection for bicyclists, vehicle-bicycle (V-B) accident has become a primary contributor to traffic fatalities. Although AEB (Autonomous Emergency Braking) systems have been developed to avoid or mitigate collisions, they need to be further adapted in various conflict situations.

A Highly Sensitive Nonenzymatic Glucose Biosensor Based on the Regulatory Effect of Glucose on Electrochemical Behaviors of Colloidal Silver Nanoparticles on MoS₂†.

A novel and highly sensitive nonenzymatic glucose biosensor was developed by nucleating colloidal silver nanoparticles (AgNPs) on MoS₂. The facile fabrication method, high reproducibility (97.5%) and stability indicates a promising capability for large-scale manufacturing.

Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions.

This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn)featuresfromfixedslidingwindowsonreal-timesteeringwheelanglestimeseries. Afterthat, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation.