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Background Stroke survivors often experience upper‐limb motor deficits and achieve limited motor recovery within six months after the onset of stroke. We aimed to systematically review the effects of robot‐assisted therapy (RT) in comparison to usual care on the functional and health outcomes of subacute stroke survivors. Methods Randomized controlled trials (RCTs) published between January 1, 2000 and December 31, 2019 were identified from six electronic databases. Pooled estimates of standardized mean differences for five outcomes, including motor control (primary outcome), functional independence, upper extremity performance, muscle tone, and quality of life were derived by random effects meta‐analyses. Assessments of risk of bias in the included RCTs and the quality of evidence for every individual outcomes were conducted following the guidelines of the Cochrane Collaboration. Results Eleven RCTs involving 493 participants were included for review. At post‐treatment, the effects of RT when compared to usual care on motor control, functional independence, upper extremity performance, muscle tone, and quality of life were nonsignificant (all ps ranged .16 to .86). The quality of this evidence was generally rated as low‐to‐moderate. Less than three RCTs assessed the treatment effects beyond post‐treatment and the results remained nonsignificant. Conclusion Robot‐assisted therapy produced benefits similar, but not significantly superior, to those from usual care for improving functioning and disability in patients diagnosed with stroke within six months. Apart from using head‐to‐head comparison to determine the effects of RT in subacute stroke survivors, future studies may explore the possibility of conducting noninferiority or equivalence trials, given that the less labor‐intensive RT may offer important advantages over currently available standard care, in terms of improved convenience, better adherence, and lower manpower cost. PRISMA flow chart of study selection. Articles included in the review met all inclusion criteria and with satisfactory methodological validity and clarity (n = 11).

The Taiwan Strait contains a vast potential for wind energy. However, the power grid balance is challenging due to wind energy’s uncertainty and intermittent nature. Wind speed forecasting reduces this risk, increasing the penetration rate. Machine learning (ML) models are adopted in this study for the short-term prediction of wind speed based on the complex nonlinear relationships among wind speed, terrain, air pressure, air temperature, and other weather conditions. Feature selection is crucial for ML modeling. Finding more valuable features in observations is the key to improving the accuracy of prediction models. The random forest method was selected because of its stability, interpretability, low computational cost, and immunity to noise, which helps maintain focus on investigating the essential features from vast data. In this study, several new exogenous features were found on the basis of physics and the spatiotemporal correlation of surrounding data. Apart from the conventional input features used for wind speed prediction, such as wind speed, wind direction, air pressure, and air temperature, new features were identified through the feature importance of the random forest method, including wave height, air pressure difference, air-sea temperature difference, and hours and months, representing the periodic components of time series analysis. The air–sea temperature difference is proposed to replace the wind speed difference to represent atmosphere stability due to the availability and adequate accuracy of the data. A random forest and an artificial neural network model were created to investigate the effectiveness and generality of these new features. Both models are superior to persistence models and models using only conventional features. The random forest model outperformed all models. We believe that time-consuming and tune-required sophisticated models may also benefit from these new features.

Chronic stress significantly contributes to the development of depressive disorders, with the hypothalamic–pituitary–adrenal (HPA) axis playing a central role in mediating stress responses. This review examines the neurobiological alterations in the hippocampus linked to HPA axis dysregulation in chronic stress-associated depressive disorders. The prolonged activation of the HPA axis disrupts cortisol regulation, leading to the decline of both physical and mental health. The chronic stress-induced HPA axis dysfunction interacts with inflammatory pathways and generates oxidative stress, contributing to cellular damage and neuroinflammation that further aggravates depressive symptoms. These processes result in structural and functional alterations in the hippocampus, which is essential for emotional regulation and cognitive function. Comprehending the impact of chronic stress on the HPA axis and associated neurobiological pathways is essential for formulating effective interventions for depressive disorders. This review summarises the existing findings and underscores the necessity for future investigations into intervention strategies to improve physical and psychological wellbeing targeting at HPA axis dysregulation for the betterment of psychological wellbeing and human health.

Interferons (IFNs) are important in controlling the innate immune response to viral infections. Besides that, studies have found that IFNs also have antimicrobial, antiproliferative/antitumor and immunomodulatory effects. IFNs are divided into Type I, II and III. Type I IFNs, in particular IFN-α, is an approved treatment for hepatitis C. However, patients developed neuropsychological disorders during treatment. IFN-α induces proinflammatory cytokines, indoleamine 2,3-dioxygenase (IDO), oxidative and nitrative stress that intensifies the body’s inflammatory response in the treatment of chronic inflammatory disease. The severity of the immune response is related to behavioral changes in both animal models and humans. Reactive oxygen species (ROS) is important for synaptic plasticity and long-term potentiation (LTP) in the hippocampus. However, excess ROS will generate highly reactive free radicals which may lead to neuronal damage and neurodegeneration. The limbic system regulates memory and emotional response, damage of neurons in this region is correlated with mood disorders. Due to the drawbacks of the treatment, often patients will not complete the treatment sessions, and this affects their recovery process. However, with proper management, this could be avoided. This review briefly describes the different types of IFNs and its pharmacological and clinical usages and a focus on IFN-α and its implications on depression.

Perimenopausal depression, occurring shortly before or after menopause, is characterized by symptoms such as emotional depression, anxiety, and stress, often accompanied by endocrine dysfunction, particularly hypogonadism and senescence. Current treatments for perimenopausal depression primarily provide symptomatic relief but often come with undesirable side effects. The development of agents targeting the specific pathologies of perimenopausal depression has been relatively slow. The erratic fluctuations in estrogen and progesterone levels during the perimenopausal stage expose women to the risk of developing perimenopausal-associated depression. These hormonal changes trigger the production of proinflammatory mediators and induce oxidative stress, leading to progressive neuronal damage. This review serves as a comprehensive overview of the underlying mechanisms contributing to perimenopausal depression. It aims to shed light on the complex relationship between perimenopausal hormones, neurotransmitters, brain-derived neurotrophic factors, chronic inflammation, oxidative stress, and perimenopausal depression. By summarizing the intricate interplay between hormonal fluctuations, neurotransmitter activity, brain-derived neurotrophic factors, chronic inflammation, oxidative stress, and perimenopausal depression, this review aims to stimulate further research in this field. The hope is that an increased understanding of these mechanisms will pave the way for the development of more effective therapeutic targets, ultimately reducing the risk of depression during the menopausal stage for the betterment of psychological wellbeing.

The impairment of the ovarian response in in vitro fertilization (IVF) cycles after salpingectomy remains contentious. Therefore, we investigated whether a history of salpingectomy affects the number of oocytes retrieved in women undergoing IVF in comparison with the number in women without underlying tubal disease. Case-control study (Canadian Task Force Classification II-2). A tertiary hospital-affiliated fertility center. Fifty-four women aged <35 years with a history of salpingectomy and 59 age-matched women without tubal disease. Gonadotropin-releasing hormone antagonist protocol for controlled ovarian stimulation and transvaginal oocyte retrieval. The antral follicle count (AFC), anti-Müllerian hormone (AMH) levels, and the number of retrieved oocytes were significantly lower in women with prior salpingectomy than in women without tubal disease. Day-3 follicle-stimulating hormone (FSH) levels, total gonadotropin dosage, and stimulation days did not significantly differ between the groups. The indications of salpingectomy (i.e., hydrosalpinx and ectopic pregnancy) did not differ significantly in terms of ovarian response or reserve among women with salpingectomy history. A history of salpingectomy and other factors related to ovarian response in IVF, such as age, AMH, AFC, day-3 FSH, and total gonadotropin dose, were significantly correlated with the number of oocytes retrieved by univariate regression analysis. In the multivariate-adjusted model after controlling all the above-mentioned variables, only AFC and AMH levels continued to exhibit significant associations with the number of retrieved oocytes. In a subgroup analysis, the negative impact of prior salpingectomy on the number of retrieved oocytes was especially significant in women with suboptimal ovarian reserves (defined as AMH < 4 ng/mL), regardless of the indication of salpingectomy or whether salpingectomy was bilateral or unilateral. A negative effect on the number of retrieved oocytes in the subsequent IVF cycle after salpingectomy is more likely in women aged <35 years with suboptimal ovarian reserve. Nevertheless, postsurgical AMH and AFC levels still possess a more direct predictive value on ovarian response than the history of salpingectomy.

Renewable energy is crucial for achieving net zero emissions. Taiwan has abundant wind resources and most major wind farms are offshore over the Taiwan Strait due to a lack of space on land. A thorough study that includes time series modeling of wind speed and sea breeze identification and evaluation for Taiwan’s offshore wind farms was conducted. The time series modeling identified two periodic (annual and diurnal) components and an autoregressive model for multiple-year wind speed time series. A new method for sea breeze type identification and magnitude evaluation is proposed. The method (named as EACH) utilizes a vector and an ellipse to represent the wind condition of a day. Verification of the type identification determined by the new method in two cases of different seasons has been conducted by using surface weather charts and wind data measured by lidar. It is a concise, effective, and programmable way to filter a number of dates for type identification and speed change precursor of sea breeze. We found that the typical daily wind power production of corkscrew sea breeze in Central Taiwan is more than 33 times that of pure sea breeze and more than 9 times that of backdoor sea breeze, which highlights the impact of sea breeze types on wind power.

This study analyzed the wind speed data of the met mast in the first commercial-scale offshore wind farm of Taiwan from May 2017 to April 2018. The mean wind speed and standard deviation, wind rose, histogram, wind speed profile, and diurnal variation of wind speed with associated changes in wind direction revealed some noteworthy findings. First, the standard deviation of the corresponding mean wind speed is somewhat high. Second, the Hellmann exponent is as low as 0.05. Third, afternoons in winter and nights and early mornings in summer have the highest and lowest wind speed in a year, respectively. Regarding the histogram, the distribution probability of wind is bimodal, which can be depicted as a mixture of two gamma distributions. In addition, the corresponding change between the hourly mean wind speed and wind direction revealed that the land–sea breeze plays a significant role in wind speed distribution, wind profile, and wind energy production. The low Hellmann exponent is discussed in detail. To further clarify the effect of the land–sea breeze for facilitating future wind energy development in Taiwan, we propose some recommendations.

Recreational use of alcohol is a social norm in many communities worldwide. Alcohol use in moderation brings pleasure and may protect the cardiovascular system. However, excessive alcohol consumption or alcohol abuse are detrimental to one’s health. Three million deaths due to excessive alcohol consumption were reported by the World Health Organization. Emerging evidence also revealed the danger of moderate consumption, which includes the increased risk to cancer. Alcohol abuse and periods of withdrawal have been linked to depression and anxiety. Here, we present the effects of alcohol consumption (acute and chronic) on important brain structures—the frontal lobe, the temporal lobe, the limbic system, and the cerebellum. Apart from this, we also present the link between alcohol abuse and withdrawal and mood disorders in this review, thus drawing a link to oxidative stress. In addition, we also discuss the positive impacts of some pharmacotherapies used. Due to the ever-rising demands of life, the cycle between alcohol abuse, withdrawal, and mood disorders may be a never-ending cycle of destruction. Hence, through this review, we hope that we can emphasise the importance and urgency of managing this issue with the appropriate approaches.

Electrochemical reduction of CO2 (CO2ER) into fuels is a crucial strategy for mitigating climate change and meeting sustainable energy demands. Among catalytic materials, copper stands out due to its ability to convert CO2 into a diverse range of hydrocarbons and oxygenates with significant current density. Quantum mechanical studies have greatly advanced the understanding of CO2ER on copper surfaces; however, most have focused on thermodynamics and/or kinetics to elucidate reaction mechanisms or explain experimental trends, leaving orbital‐level insights largely unexplored. In this study, density functional theory calculations combined with intrinsic bond orbital analysis to track orbital evolution across 13 protonation steps involved in CO2ER to methane are employed. Based on these results, an arrow‐pushing diagram is constructed to illustrate the electron flow for each step. This methodology allows to identify the key orbital used by each CO2ER intermediate to accommodate the transferred proton. Furthermore, this approach also reveals that the copper electrode actively participates in six protonation steps by exchanging pairs of electrons with CO2ER intermediates that are either selectivity‐determining or rate‐determining steps. These insights deepen the understanding of CO2ER mechanisms and provide a foundation for developing strategies to enhance its efficiency and selectivity. Electrochemical CO2 reduction (CO2ER) on copper produces diverse fuels, yet orbital‐level insights remain limited. Using density functional theory and intrinsic bond orbital analysis, electron flow in 13 steps toward methane is tracked. The approach reveals how intermediates accept protons and how copper actively participates in key steps, offering a new framework to improve CO2ER efficiency.