A stronger association of mental disorders with smaller particulate matter and a modifying effect of air temperature.

Mental disorders (MDs) can be triggered by adverse weather conditions and particulate matter (PM) such as PM2.5 and PM10 (aerodynamic diameter ≤2.5 µm and ≤10 µm). However, there is a dearth of evidence on the role of smaller PM (e.g. PM1, aerodynamic diameter ≤1 µm) and the potential modifying effects of weather conditions. We aimed to collect daily data on emergency department visits and hospitalisations for schizophrenia-, mood-, and stress-related disorders in a densely populated Chinese city (Hefei) between 2016 and 2019. A time-stratified case-crossover analysis was used to examine the short-term association of MDs with PM1, PM2.5, and PM10. The potential modifying effects of air temperature conditions (cold and warm days) were also explored. The three size-fractioned PMs were all associated with an increased risk of MDs; however, the association differed between emergency department visit and hospitalisation. Specifically, PM1 was primarily associated with an increased risk of emergency department visit, whereas PM2.5 was primarily associated with an increased risk of hospitalisation, and PM10 was associated with an increased risk of both emergency department visit and hospitalisation. The PM-MD association appeared to be greatest (although not significant) for PM1 (odds ratio range: 1.014-1.055), followed by PM2.5 (odds ratio range: 1.001-1.009) and PM10 (odds ratio range: 1.001-1.006). Furthermore, the PM-MD association was observed on cold days; notably, the association between PM and schizophrenia-related disorders was significant on both cold and warm days. Our results suggest that the smaller the PM, the greater the risk of MDs, and that the PM-MD association could be determined by air temperature conditions.

Seasonal peak and the role of local weather in schizophrenia occurrence: A global analysis of epidemiological evidence.

BACKGROUND: Many studies have shown that the onset of schizophrenia peaked in certain months within a year and the local weather conditions could affect the morbidity risk of schizophrenia. This study aimed to conduct a systematic analysis of schizophrenia seasonality in different countries of the world and to explore the effects of weather factors globally. METHODS: We searched three databases (PubMed, Web of Science, and China National Knowledge Infrastructure) for eligible studies published up to September 2022. Schizophrenia seasonality was compared between hemispheres and within China. A meta-analysis was conducted to pool excess risk (ER, absolute percentage increase in risk) of the onset of schizophrenia associated with various weather factors including temperature (an increase or decrease of temperature as a reflection of high or low temperature; heatwave; temperature variation), precipitation, etc. RESULTS: We identified 84 relevant articles from 22 countries, mainly in China. The seasonality analysis found that the onset of schizophrenia mostly peaked in the cold season in the southern hemisphere but in the warm season in the northern hemisphere. Interestingly in China, schizophrenia seasonality presented two peaks, respectively in the late cold and warm seasons. The meta-analysis further revealed an increased risk of schizophrenia after short-term exposure to high temperature [ER%: 0.45 % (95 % confidence interval (CI): 0.14 % to 0.76 %)], low temperature [ER%: 0.52 % (95%CI: 0.29 % to 0.75 %)], heatwave [ER%: 7.26 % (95%CI: 4.45 % to 10.14 %)], temperature variation [ER%: 1.02 % (95%CI: 0.55 % to 1.50 %)], extreme precipitation [ER%: 3.96 % (95%CI: 2.29 % to 5.67 %)]. The effect of other weather factors such as sunlight on schizophrenia was scarcely investigated with inconsistent findings. CONCLUSION: This study provided evidence of intra- and inter-country variations in schizophrenia seasonality, especially the double-peak seasons in China. Exposure to local weather conditions mainly temperature changes and precipitation could affect the onset risk of schizophrenia.

A systematic review and meta-analysis of air pollution and angina pectoris attacks: identification of hazardous pollutant, short-term effect, and vulnerable population.

We conducted a systematic review and meta-analysis of global epidemiological studies of air pollution and angina pectoris, aiming to explore the deleterious air pollutant(s) and vulnerable sub-populations. PubMed and Web of Science databases were searched for eligible articles published between database inception and October 2021. Meta-analysis weighted by inverse-variance was utilized to pool effect estimates based on the type of air pollutant, including particulate matters (PM2.5 and PM10: particulate matter with an aerodynamic diameter ≤ 2.5 µm and ≤ 10 µm), gaseous pollutants (NO2: nitrogen dioxide; CO: carbon monoxide; SO2: sulfur dioxide, and O3: ozone). Study-specific effect estimates were standardized and calculated with percentage change of angina pectoris for each 10 µg/m3 increase in air pollutant concentration. Twelve studies involving 663,276 angina events from Asia, America, Oceania, and Europe were finally included. Meta-analysis showed that each 10 µg/m3 increase in PM2.5 and PM10 concentration was associated with an increase of 0.66% (95%CI: 0.58%, 0.73%; p < 0.001) and 0.57% (95%CI: 0.20%, 0.94%; p = 0.003) in the risk of angina pectoris on the second day of exposure. Adverse effects were also observed for NO2 (0.67%, 95%CI: 0.33%, 1.02%; p < v0.001) on the second day, CO (0.010%, 95%CI: 0.006%, 0.014%; p < 0.001). The elderly and patients with coronary artery disease (CAD) appeared to be at higher risk of angina pectoris. Our findings suggest that short-term exposure to PM2.5, PM10, NO2, and CO was associated with an increased risk of angina pectoris, which may have implications for cardiologists and patients to prevent negative cardiovascular outcomes.

Abnormal ambient temperature change increases the risk of out-of-hospital cardiac arrest: A systematic review and meta-analysis of exposure types, risk, and vulnerable populations.

BACKGROUND: There is growing evidence in support of a short-term association between ambient temperature and cardiac arrest attacks that is a serious manifestation of cardiovascular disease and has a high incidence and low survival rate. However, it remains unrecognized about the hazardous temperature exposure types, exposure risk magnitude, and vulnerable populations. OBJECTIVES: We comprehensively summarize prior epidemiological studies looking at the short-term associations of out-of-hospital cardiac arrest (OHCA) with various temperature exposures among different populations. METHODS: We searched PubMed and Web of Science databases from inception to October 2021 for eligible English language. Temperature exposure was categorized into three types: heat (included high temperature, extreme heat, and heatwave), cold (included low temperature and extreme cold), and temperature variation (included diurnal temperature range and temperature change between two adjacent days). Meta-analysis weighted by inverse variance was used to pool effect estimates. RESULTS: This study included 15 studies from 8 countries, totaling around 1 million OHCA events. Extreme heat and extreme cold were significantly associated with an increased risk of OHCA, and the pooled relative risks (RRs) were 1.071 [95 % confidence interval (CI): 1.019-1.126] and 1.662 (95%CI: 1.138-2.427), respectively. The risk of OHCA was also elevated by heatwaves (RR = 1.248, 95%CI: 1.091-1.427) and more intensive heatwaves had a greater effect. Notably, the elderly and males seemed to be more vulnerable to the effects of heat and cold. However, we did not observe a significant association between temperature variation and the risk of OHCA (1.005, 95%CI: 0.999-1.012). CONCLUSION: Short-term exposure to heat and cold may be novel risk factors for OHCA. Considering available studies in limited regions, the temperature effect on OHCA should be urgently confirmed in different regions.

Graph-Attention-Based Casual Discovery With Trust Region-Navigated Clipping Policy Optimization.

In many domains of empirical sciences, discovering the causal structure within variables remains an indispensable task. Recently, to tackle unoriented edges or latent assumptions violation suffered by conventional methods, researchers formulated a reinforcement learning (RL) procedure for causal discovery and equipped a REINFORCE algorithm to search for the best rewarded directed acyclic graph. The two keys to the overall performance of the procedure are the robustness of RL methods and the efficient encoding of variables. However, on the one hand, REINFORCE is prone to local convergence and unstable performance during training. Neither trust region policy optimization, being computationally expensive, nor proximal policy optimization (PPO), suffering from aggregate constraint deviation, is a decent alternative for combinatory optimization problems with considerable individual subactions. We propose a trust region-navigated clipping policy optimization method for causal discovery that guarantees both better search efficiency and steadiness in policy optimization, in comparison with REINFORCE, PPO, and our prioritized sampling-guided REINFORCE implementation. On the other hand, to boost the efficient encoding of variables, we propose a refined graph attention encoder called SDGAT that can grasp more feature information without priori neighborhood information. With these improvements, the proposed method outperforms the former RL method in both synthetic and benchmark datasets in terms of output results and optimization robustness.

A systematic review and meta-analysis of intraday effects of ambient air pollution and temperature on cardiorespiratory morbidities: First few hours of exposure matters to life.

BACKGROUND: A growing number of studies have reported an increased risk of cardiovascular disease (CVD) and respiratory disease (RD) within hours after exposure to ambient air pollution or temperature. We assemble published evidence on the sub-daily associations of CVD and RD with ambient air pollution and temperature. METHODS: Databases of PubMed and Web of Science were searched for original case-crossover and time-series designs of English articles examining the intra-day effects of ambient air pollution [particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5), ≤10 µm (PM10), 2.5-10µm (PM10-2.5), and < 7 µm (SPM), O3, SO2, NO2, CO, and NO] and temperatures (heat and cold) on cardiorespiratory diseases within 24 h after exposure in the general population by comparing with exposure at different exposure levels or periods. Meta-analyses were conducted to pool excess risks (ERs, absolute percentage increase in risk) of CVD and RD morbidities associated with an increase of 10 µg/m3 in particulate matters, 0.1 ppm in CO, and 10 ppb in other gaseous pollutants. FINDINGS: Final analysis included thirty-three papers from North America, Europe, Oceania, and Asia. Meta-analysis found an increased risk of total CVD morbidity within 3 h after exposure to PM2.5 [ER%: 2.65% (95% CI: 1.00% to 4.34%)], PM10-2.5 [0.31% (0.02% to 0.59%)], O3 [1.42% (0.14% to 2.73%)], and CO [0.41% (0.01% to 0.81%)]. The risk of total RD morbidity elevated at lag 7-12 h after exposure to PM2.5 [0.69% (0.14% to 1.24%)] and PM10 [0.38% (0.02% to 0.73%)] and at lag 12-24 h after exposure to SO2 [2.68% (0.94% to 4.44%)]. Cause-specific CVD analysis observed an increased risk of myocardial infarction morbidity within 6 h after exposure to PM2.5, PM10, and NO2, and an increased risk of out-of-hospital cardiac arrest morbidity within 12 h after exposure to CO. Risk of total CVD also increased within 24 h after exposure to heat. INTERPRETATION: This study supports a sudden risk increase of cardiorespiratory diseases within a few hours after exposure to air pollution or heat, and some acute and highly lethal diseases such as myocardial infarction and cardiac arrest could be affected within a shorter time. FUNDING: The National Natural Science Foundation of China (Grant No. 42105165; 81773518), the High-level Scientific Research Foundation of Anhui Medical University (Grant No. 0305044201), and the Discipline Construction of Anhui Medical University (Grant No. 0301001836).

Topology-Dependent Brownian Gyromotion of a Single Skyrmion.

Noninteracting particles exhibiting Brownian motion have been observed in many occasions of sciences, such as molecules suspended in liquids, optically trapped microbeads, and spin textures in magnetic materials. In particular, a detailed examination of Brownian motion of spin textures is important for designing thermally stable spintronic devices, which motivates the present study. In this Letter, through using temporally and spatially resolved polar magneto-optic Kerr effect microscopy, we have experimentally observed the thermal fluctuation-induced random walk of a single isolated Néel-type magnetic skyrmion in an interfacially asymmetric Ta/CoFeB/TaO_{x} multilayer. An intriguing topology-dependent Brownian gyromotion behavior of skyrmions has been identified. The onset of Brownian gyromotion of a single skyrmion induced by thermal effects, including a nonlinear temperature-dependent diffusion coefficient and topology-dependent gyromotion are further formulated based on the stochastic Thiele equation. The experimental and numerical demonstration of topology-dependent Brownian gyromotion of skyrmions can be useful for understanding the nonequilibrium magnetization dynamics and implementing spintronic devices.

Monolithic integrated cyclic 64-channel AWG with MZI filters and arrayed vertical reflecting mirrors for WDM-PON application.

The paper introduces a silica-on-silicon monolithic integrated cyclic arrayed waveguide grating (AWG) with Mach-Zehnder interference (MZI) filters and arrayed vertical reflecting mirrors in silicon to realize effective and stable optical transmission between waveguides and photodiodes. The cyclic AWG acts as both multiplexer over the L-band for upstream traffic and demultiplexer over the C-band for downstream traffic. The integrated chip, including AWG, MZI filters, and arrayed reflecting mirrors, has been made successfully with a 6.0 dB insertion loss, which is less than the discrete devices. At the same time, the arrayed reflecting mirrors are more stable than separate reflectors.

Learn to Steer through Deep Reinforcement Learning.

It is crucial for robots to autonomously steer in complex environments safely without colliding with any obstacles. Compared to conventional methods, deep reinforcement learning-based methods are able to learn from past experiences automatically and enhance the generalization capability to cope with unseen circumstances. Therefore, we propose an end-to-end deep reinforcement learning algorithm in this paper to improve the performance of autonomous steering in complex environments. By embedding a branching noisy dueling architecture, the proposed model is capable of deriving steering commands directly from raw depth images with high efficiency. Specifically, our learning-based approach extracts the feature representation from depth inputs through convolutional neural networks and maps it to both linear and angular velocity commands simultaneously through different streams of the network. Moreover, the training framework is also meticulously designed to improve the learning efficiency and effectiveness. It is worth noting that the developed system is readily transferable from virtual training scenarios to real-world deployment without any fine-tuning by utilizing depth images. The proposed method is evaluated and compared with a series of baseline methods in various virtual environments. Experimental results demonstrate the superiority of the proposed model in terms of average reward, learning efficiency, success rate as well as computational time. Moreover, a variety of real-world experiments are also conducted which reveal the high adaptability of our model to both static and dynamic obstacle-cluttered environments. A video of our experiments is available at https://youtu.be/yixnmFXIKf4 and http://v.youku.com/vshow/idXMzg1ODYwMzM5Ng.

Integrated athermal arrayed-waveguide grating multiplexer and demultiplexer with all-metal compensating rod for broadband temperature application.

In this paper, a unique device that can act as both multiplexer and demultiplexer is proposed with two all-metal compensating rods that makes the compensated chip almost the same spectrum profile as the original one. In this way a flat-top athermal arrayed-waveguide grating module of 100-GHz×40-ch is successfully fabricated. A small center wavelength shift of ±25 pm is achieved for the ultra-wide temperature range from -40°C to 85°C with the low insertion loss change of less than ±0.14 dB.

Development of a compact continuum tubular robotic system for nasopharyngeal biopsy.

Traditional posterior nasopharyngeal biopsy using a flexible nasal endoscope has the risks of abrasion and injury to the nasal mucosa and thus causing trauma to the patient. Recently, a new class of robots known as continuum tubular robots (CTRs) provide a novel solution to the challenge with miniaturized size, curvilinear maneuverability, and capability of avoiding collision within the nasal environment. This paper presents a compact CTR which is 35 cm in total length, 10 cm in diameter, 2.15 kg in weight, and easy to be integrated with a robotic arm to perform more complicated operations. Structural design, end-effector design, and workspace analysis are described in detail. In addition, teleoperation of the CTR using a haptic input device is developed for position control in 3D space. Moreover, by integrating the robot with three electromagnetic tracking sensors, a navigation system together with a shape reconstruction algorithm is developed. Comprehensive experiments are conducted to test the functionality of the proposed prototype; experiment results show that under teleoperation, the system has an accuracy of 2.20 mm in following a linear path, an accuracy of 2.01 mm in following a circular path, and a latency time of 0.1 s. It is also found that the proposed shape reconstruction algorithm has a mean error of around 1 mm along the length of the tubes. Besides, the feasibility and effectiveness of the proposed robotic system being applied to posterior nasopharyngeal biopsy are demonstrated by a cadaver experiment. The proposed robotic system holds promise to enhance clinical operation in transnasal procedures.