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Motivating older adults to follow up with an outpatient clinician after discharge from emergency departments (ED) is beneficial yet challenging. We aimed to answer whether psychological needs for motivation and discrete emotions observed by care transition coaches would predict this behavioral outcome.Community-dwelling older adults following ED discharge were recruited from three EDs in two U.S. states. We examined home visit notes documented by coaches (N = 725). Retrospective chart reviews of medical records tracked participants' health care utilization for 30 days.Observed knowledge-based competence predicted higher likelihood of outpatient follow-up within 30 days, while observed sadness predicted a lower likelihood of follow-up within seven days following discharge. Moreover, participants who demonstrated happiness were marginally more likely to have an in-person follow-up within seven days, and those who demonstrated knowledge-based competence were more likely to have an electronic follow-up within 30 days.Knowledge-based competence and emotions, as observed and documented in coach notes, can predict older adults' subsequent outpatient follow-up following their ED-discharge.Intervention programs might encourage coaches to check knowledge-based competence and to observe emotions in addition to delivering the content. Coaches could also customize strategies for patients with different recommended timeframes of follow-up.

Tobacco advertising involves a variety of media formats (i.e., print, radio, television, billboards, point-of-sale, movie placement, Internet or social media, direct mail) and applies multiple persuasive tactics (e.g., visual appeal, sex appeal, masculinity and feminism cues, celebrity endorsement, motivational appeal) to encourage tobacco purchase and use. Scientific evidence points to the association between exposure to tobacco advertisements and subsequent increases in tobacco use. Due to the health risks of tobacco use, especially for youth, tobacco advertising is among the most regulated types of advertising. Globally, empirical research found that comprehensive tobacco advertising bans can reduce tobacco consumption, whereas partial tobacco advertising bans will have little or no effect as manufacturers may turn to non-banned media formats of advertisements. Other factors such as transnational tobacco advertising, promotion and sponsorship, as well as electronic word-of-mouth (eWOM) enabled by the Internet, social media, and mobile communication, also pose additional challenges to health communication programs in tobacco control and prevention. This entry consists of five sections: (1) tobacco products and health risks, (2) tobacco advertising and persuasive tactics, (3) regulatory activities, (4) anti-tobacco health communication, and (5) implications for health communication.

Cloud providers offer virtual machines (VM) located in physical machines (PM) using the “pay-as-you-go” model to satisfy emerging demand for online computational services. If the instantaneous utilized capacity requested by VMs exceeds a certain threshold of the total capacity a PM can offer, a hotspot happens and may cause unacceptable VM performance degradation. Hotspots can be resolved by relocating some VMs to other PMs using live migration. However, the problem of selecting which VM(s) to release is challenging because the utilized capacity demanded by VMs changes continuously over time. In this work, we propose a Predicted Mixed Integer Linear Programming (MILP) Robust Solver (PMRS), which predicts the utilized capacity range of each VM and applies the Γ-robustness theory to ensure that PM is hotspot-safe with desired probability. The latter allows us to formulate the hotspot resolution as a Γ-robust knapsack problem (Γ-RKP) that can be solved by a novel MILP model. Extensive experiments based on real-trace data and large-scale synthetic data demonstrate the effectiveness of the PMRS. More encouragingly, the application of the PMRS in the real-production environment benefits Huawei Cloud by resolving all existing and 94%+ potential future hotspots with minimal migration overhead.Cloud providers offer virtual machines (VM) located in physical machines (PM) using the “pay-as-you-go” model to satisfy emerging demand for online computational services. If the instantaneous utilized capacity requested by VMs exceeds a certain threshold of the total capacity a PM can offer, a hotspot happens and may cause unacceptable VM performance degradation. Hotspots can be resolved by relocating some VMs to other PMs using live migration. However, the problem of selecting which VM(s) to release is challenging because the utilized capacity demanded by VMs changes continuously over time. In this work, we propose a Predicted Mixed Integer Linear Programming (MILP) Robust Solver (PMRS), which predicts the utilized capacity range of each VM and applies the Γ-robustness theory to ensure that PM is hotspot-safe with desired probability. The latter allows us to formulate the hotspot resolution as a Γ- robust knapsack problem (Γ-RKP) that can be solved by a novel MILP model. Extensive experiments based on real-trace data and large-scale synthetic data demonstrate the effectiveness of the PMRS. More encouragingly, the application of the PMRS in the real-production environment benefits Huawei Cloud by resolving all existing and 94%+ potential future hotspots with minimal migration overhead.

This paper proposes the modeling and simulation of the unmanned driving system for underground load haul dump vehicles based on Gazebo/Ros. Firstly, the kinematics model of the load haul dump vehicle is derived. Then, the model of each part of the load haul dump vehicle is established based on SolidWorks and the model of the load haul dump vehicle is established by connecting the parts through a unified robot description format (URDF) file. Finally, the laneway model is established by using alpha shape to realize the modeling of the operating environment of the load haul dump vehicle. The speed, angular speed, bucket lifting, and bucket flipping of the load haul dump vehicle are controlled using PID. The experimental results show that: The control errors of the speed and angular speed of the load haul dump vehicle are 0.283 m/s and 0.010 rad/s, respectively. The control error of the lifting bucket is 0.025 m and that of the flipping bucket is 0.015 m. The angular velocity control error of the simulation system relative to the actual system is 0.330 and 0.106 m/s, respectively. The error between the SLAM of the simulation system and the actual system and the measured value is 0.917 and 3.44 m, respectively. The control performance of the load haul dump vehicle in the simulation system is good. Therefore, automatic driving algorithms can be studied and tested in this simulation platform.

Extensive in vitro cancer drug screening datasets have enabled scientists to identify biomarkers and develop machine learning models for predicting drug sensitivity. While most advancements have focused on omics profiles, cancer drug sensitivity scores precalculated by the original sources are often used as-is, without consideration for variabilities between studies. It is well-known that significant inconsistencies exist between the drug sensitivity scores across datasets due to differences in experimental setups and preprocessing methods used to obtain the sensitivity scores. As a result, many studies opt to focus only on a single dataset, leading to underutilization of available data and a limited interpretation of cancer pharmacogenomics analysis. To overcome these caveats, we have developed CREAMMIST (https://creammist.mtms.dev), an integrative database that enables users to obtain an integrative dose-response curve, to capture uncertainty (or high certainty when multiple datasets well align) across five widely used cancer cell-line drug–response datasets. We utilized the Bayesian framework to systematically integrate all available dose-response values across datasets (>14 millions dose-response data points). CREAMMIST provides easy-to-use statistics derived from the integrative dose-response curves for various downstream analyses such as identifying biomarkers, selecting drug concentrations for experiments, and training robust machine learning models.

Impairment of the macroautophagy/autophagy-lysosomal pathway (ALP) can lead to amyloid plaque accumulation in Alzheimer disease (AD); however, the underlying mechanism remains unresolved. This study revealed a mechanism of ALP impairment mediated by gain-of-function of lysosomal TPCN2/TPC2 (two pore segment channel 2) and suggests a molecular target for AD intervention. Using mutant PSEN1/PS1 (presenilin 1)-expressing human neuroblastoma SH-SY5Y and familial AD fibroblasts collected from human patients, we showed lysosomal pH was increased in AD cells due to exaggerated TPCN2-mediated calcium (Ca2+) release which increases lysosomal pH and compromises ALP degradation. Genetic knockdown or pharmacological inhibition of the TPCN2 channel restored lysosomal Ca2+ homeostasis, acidity of the lysosome and ALP function. Furthermore, AD mice (5xFAD) that had received treatment with the TPCN2 inhibitor tetrandrine for 6 months or injection of AAV-shTpcn2 to knock down Tpcn2 showed reduction in amyloid plaques in cortical and hippocampal regions. These treatments also improved spine morphology and density and corrected cognitive deficits in 5xFAD mice assayed by immunohistochemistry, behavioral tests, and electrophysiological measurements, respectively. Taken together, these findings reveal a previously under-appreciated role of lysosomal TPCN2 in ALP impairment of AD. They also suggest targeting the lysosomal TPCN2 can serve as a therapeutic strategy for AD treatment in future drug development. Aβ: β-amyloid; AD: Alzheimer disease; AIF1/IBA1: allograft inflammatory factor 1; ALP: autophagy-lysosomal pathway; APP: amyloid beta precursor protein; ATP6V1B1/V-ATPase V1b1: ATPase H+ transporting V1 subunit B1; AVs: autophagy vacuoles; BAF: bafilomycin A1; CFC: contextual/cued fear conditioning assay; CHX: Ca2+/H+ exchanger; CTF-β: carboxy-terminal fragment derived from β-secretase; CTSD: cathepsin D; fAD: familial Alzheimer disease; GFAP: glial fibrillary acidic protein; LAMP1: lysosomal associated membrane protein 1; LTP: long‐term potentiation; MCOLN1/TRPML1: mucolipin 1; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; MAPT: microtubule associated protein tau; MWM: Morris water maze; NFT: neurofibrillary tangles; PFC: prefrontal cortex; PSEN1: presenilin 1; SQSTM1/p62: sequestosome 1; TBS: theta burst stimulation; TEM: transmission electronic microscopy; TPCN2/TPC2: two pore segment channel 2; WT: wild-type; V-ATPase: vacuolar type H+-ATPase

BACKGROUND Health warnings in tobacco advertisements provide health information while also increasing the perceived risks of tobacco use. However, existing federal laws requiring warnings on advertisements for tobacco products do not specify whether the rules apply to social media promotions. OBJECTIVE This study aims to examine the current state of influencer promotions of little cigars and cigarillos (LCCs) on Instagram and the use of health warnings in influencer promotions. METHODS Instagram influencers were identified as those who were tagged by any of the 3 leading LCC brand Instagram pages between 2018 and 2021. Posts from identified influencers, which mentioned one of the three brands were considered LCC influencer promotions. A novel Warning Label Multi-Layer Image Identification computer vision algorithm was developed to measure the presence and properties of health warnings in a sample of 889 influencer posts. Negative binomial regressions were performed to examine the associations of health warning properties with post engagement (number of likes and comments). RESULTS The Warning Label Multi-Layer Image Identification algorithm was 99.3% accurate in detecting the presence of health warnings. Only 8.2% (n=73) of LCC influencer posts included a health warning. Influencer posts that contained health warnings received fewer likes (incidence rate ratio 0.59, PP CONCLUSIONS Health warnings are rarely used by influencers tagged by LCC brands’ Instagram accounts. Very few influencer posts met the US Food and Drug Administration’s health warning requirement of size and placement for tobacco advertising. The presence of a health warning was associated with lower social media engagement. Our study provides support for the implementation of comparable health warning requirements to social media tobacco promotions. Using an innovative computer vision approach to detect health warning labels in influencer promotions on social media is a novel strategy for monitoring health warning compliance in social media tobacco promotions.

Increasing the popularity of distributed photovoltaic technology among Chinese residents is of great significance to achieve the dual carbon goal (emission peak and carbon neutrality). In this study, we collected 1424 questionnaire samples and used PLS-SEM for group modeling and comparative analysis of bungalow and building residents. The results show that living conditions, costs, risks of installation, maintenance, and economic efficiency are the five significant influencing factors for residents to decide whether to install a distributed residential photovoltaic equipment. Compared with building residents, bungalow residents tend to feel more concerned about the cost and risk of residential photovoltaic equipment during installation, maintenance, and use. On the other hand, bungalow residents show greater sensitivity to the corresponding photovoltaic promotion policies. By contrast, building residents pay more attention to the direct benefit created by the installation of residential photovoltaic equipment. Therefore, adopting the strategy from bungalow residents to building residents could help promote the distributed photovoltaic system progressively. As for the subsidy decline, more attention shall be paid to the progress of a gradual reduction of the subsidies. It is advisable to pay attention to integrating the upstream and downstream industry chains of the distributed photovoltaic systems, thus reducing the concern of residents about the difficulty in installing, maintaining, and protecting the distributed photovoltaic equipment. By clarifying the different impacts of promotion policies on the demand side, this study provides a practical reference for the further adjustment made to distributed photovoltaic promotion policies.

Asphalt pavement is vulnerable to the temperature rising and extremely high-temperature weather caused by climate change. The regulation techniques of asphalt pavement high temperature have become a growing concern to adapt to climate change. This paper reviewed the state of the art on regulating asphalt pavement high temperature. Firstly, the influencing factors and potential regulation paths of asphalt pavement temperature were summarized. The regulation techniques were categorized into two categories. One is to regulate the heat transfer process, including enhancing reflection, increasing thermal resistance, and evaporation cooling. The other is to regulate through heat collection and transfer or conversion, including embedded heat exchange system, phase change asphalt pavement, and thermoelectric system. Then, the regulation techniques in the literature were reviewed one by one in terms of cooling effects and pavement performance. The issues that still need to be improved were also discussed. Finally, the regulation techniques were compared from the perspectives of theoretical cooling effects, construction convenience, and required maintenance. It can provide reference for understanding the development status of asphalt pavement high temperature regulation techniques and technique selection in practice.

The interleukin-6 (IL-6) family cytokines signal through gp130 receptor homodimerization or heterodimerization with a second signaling receptor and play crucial roles in various cellular processes. We determined cryo–electron microscopy structures of five signaling complexes of this family, containing full receptor ectodomains bound to their respective ligands ciliary neurotrophic factor, cardiotrophin-like cytokine factor 1 (CLCF1), leukemia inhibitory factor, IL-27, and IL-6. Our structures collectively reveal similarities and differences in the assembly of these complexes. The acute bends at both signaling receptors in all complexes bring the membrane-proximal domains to a ~30 angstrom range but with distinct distances and orientations. We also reveal how CLCF1 engages its secretion chaperone cytokine receptor–like factor 1. Our data provide valuable insights for therapeutically targeting gp130-mediated signaling.

The cycle of biogenic elements in lakes is intimately linked with particulate organic matter (POM), which plays a critical role in ecosystem restoration and the control of eutrophication. However, little is known regarding the functionality of ecosystem degradation on the source of POM in the water of a karst lake. To fill this knowledge gap, herein we compared the temporal and spatial distribution characteristics of POM prior to and after ecosystem degradation in the karst lake Caohai Lake, located in the southwest of China, and analyzed the source of POM using a combination of carbon and nitrogen stable isotopes (δ13C–δ15N). Our results showed that the dissolved oxygen (DO) concentration and pH values decreased, and the concentrations of POM in water increased by 11% and 31% in the wet and dry seasons, respectively. The decrease in the δ13C value of POM was accompanied by the increase in the δ15N value of POM in the water of Caohai lake. Prior to the ecosystem’s degradation, sediment resuspension (28%) and submerged macrophytes (33%) were the dominant sources of POM in lake water. In contrast, sediment resuspension (51%) was the major source of POM after the ecosystem’s degradation. Environmental factors, including DO, turbidity, water depth, and water temperature, that are related to photosynthesis and sediment resuspension are the main factors controlling the spatiotemporal distribution of POM. The resuspension of sediment reduced the transparency of the water, limiting effective photosynthesis, impeding the survival of submerged macrophytes, and, consequently, deteriorating the ecosystem. We propose that the control of sediment resuspension is important for improving the water transparency that creates an appropriate habitat for the restoration of the submerged macrophyte community.

Combined use of in situ passivation and macrophytes is a valuable technology that exerts remarkable effects on aquatic systems. However, the effectiveness and ecological functions of this combined technology for macrophytes-dominated eutrophic (MDE) lakes with organophosphorus-controlled internal phosphorus (P) loading were poorly understood. In this study, aquatic simulation experiments were performed to study the combination of La-modified materials (LMM; La-modified bentonite (LMB), and La/Al co-modified attapulgite (LAA)) with macrophytes (Myriophyllum verticillatum L. (MVL), Hydrilla verticillata (Linn. f.) royle (HVR), and Ceratophyllum demersum L. (CDL)) for the control of P mobility in the water column, and to investigate the passivator effects on the physiological characteristics of macrophytes. The mineralization of organophosphates (BD−Po, HCl−Po, and Res−Po) is an important factor for maintaining high internal P loadings and overlying water P concentrations in the experiments. Compared with individual treatment groups, the reduction of internal P release flux and porewater SRP concentrations was more obvious in the combined treatments. Moreover, the redox-sensitive P forms transformation is more pronounced in the surface sediments. In the LAA+M group, internal P release flux was reduced by 55% and 55% compared with individual passivators and macrophytes retreatment groups, respectively. In contrast, the LMB+M group decreased by 16% and 46%, respectively. Simultaneously, LMM had less effect on macrophytes traits compared with individual macrophytes group and enhanced the absorption of phosphate by macrophytes. The phosphate content of macrophytes in the LAA+M and LMB+M groups increased by 24% and 11%, respectively, in comparison with the individual macrophytes group. Results concluded that the combination of passivator and macrophytes enhanced the effect of ecological restoration and exerts a synergistic effect on internal P pollution with macrophytes.

Background Tauopathies are neurodegenerative diseases that are associated with the pathological accumulation of tau-containing tangles in the brain. Tauopathy can impair cognitive and motor functions and has been observed in Alzheimer’s disease (AD) and frontotemporal dementia (FTD). The aetiology of tauopathy remains mysterious; however, recent studies suggest that the autophagic-endolysosomal function plays an essential role in the degradation and transmission of pathological tau. We previously demonstrated that tetrandrine could ameliorate memory functions and clear amyloid plaques in transgenic AD mice by restoring autophagic-endolysosomal function. However, the efficacy of tetrandrine and the associated therapeutic mechanism in tauopathies have not been evaluated and elucidated. Methods Novel object recognition, fear conditioning and electrophysiology were used to evaluate the effects of tetrandrine on memory functions in transgenic tau mice. Western blotting and immunofluorescence staining were employed to determine the effect of tetrandrine on autophagy and tau clearance in vivo. Calcium (Ca2+) imaging and flow cytometry were used to delineate the role of pathological tau and tetrandrine in lysosomal Ca2+ and pH homeostasis. Biochemical BiFC fluorescence, Western blotting and immunofluorescence staining were used to evaluate degradation of hyperphosphorylated tau in vitro, whereas coculture of brain slices with isolated microglia was used to evaluate tau clearance ex vivo. Results We observed that tetrandrine treatment mitigated tau tangle development and corrected memory impairment in Thy1-hTau.P301S transgenic mice. Mechanistically, we showed that mutant tau expression disrupts lysosome pH by increasing two-pore channel 2 (TPC2)-mediated Ca2+ release, thereby contributing to lysosome alkalinization. Tetrandrine inhibits TPC2, thereby restoring the lysosomal pH, promotes tau degradation via autophagy, and ameliorates tau aggregation. Furthermore, in an ex vivo assay, we demonstrated that tetrandrine treatment promotes pathological tau clearance by microglia. Conclusions Together, these findings suggest that pathological tau disturbs endolysosomal homeostasis to impair tau clearance. This impairment results in a vicious cycle that accelerates disease pathogenesis. The success of tetrandrine in reducing tau aggregation suggests first, that tetrandrine could be an effective drug for tauopathies and second, that rescuing lysosomal Ca2+ homeostasis, thereby restoring ALP function, could be an effective general strategy for the development of novel therapies for tauopathies.

To develop a clean and sustainable carbon anode material derived from biomass with desirable properties for lithium-ion batteries (LIBs), bio-nitrogen (N)-doped composite carbon nanofibrous mats (CNFMs) were made using natural cellulose (CE) and chitosan (CS) by means of two different electrospinning ways (single-nozzle and coaxial-nozzle) coupled with pyrolysis. The conventional CNFMs that had a CE/CS ratio of 5:5 showed the best electrochemical performance, corresponding to a high specific capacity of 327 mAh g−1 at 100 mA g−1, good rate performance with specific capacity of 399 mAh g−1 at 30 mA g−1 and 210 mA g−1 at 1000 mA g−1, as well as excellent cycling stability after 300 cycles. The core–shell CNFMs with a thick outer layer of CS and large average fiber diameter (316 nm) at the same CE/CS ratio had higher pyridinic-N and pyrrolic-N contents but a lower degree of graphitization and BET surface area compared to the conventional CNFMs. It was concluded that the bio-N in CS was more uniformly doped into the CNFMs by the single-nozzle electrospinning way than by the coaxial one, and thus more effectively promoted a comprehensive electrochemical performance.

Background Health warnings in tobacco advertisements provide health information while also increasing the perceived risks of tobacco use. However, existing federal laws requiring warnings on advertisements for tobacco products do not specify whether the rules apply to social media promotions. Objective This study aims to examine the current state of influencer promotions of little cigars and cigarillos (LCCs) on Instagram and the use of health warnings in influencer promotions. Methods Instagram influencers were identified as those who were tagged by any of the 3 leading LCC brand Instagram pages between 2018 and 2021. Posts from identified influencers, which mentioned one of the three brands were considered LCC influencer promotions. A novel Warning Label Multi-Layer Image Identification computer vision algorithm was developed to measure the presence and properties of health warnings in a sample of 889 influencer posts. Negative binomial regressions were performed to examine the associations of health warning properties with post engagement (number of likes and comments). Results The Warning Label Multi-Layer Image Identification algorithm was 99.3% accurate in detecting the presence of health warnings. Only 8.2% (n=73) of LCC influencer posts included a health warning. Influencer posts that contained health warnings received fewer likes (incidence rate ratio 0.59, P Conclusions Health warnings are rarely used by influencers tagged by LCC brands’ Instagram accounts. Very few influencer posts met the US Food and Drug Administration’s health warning requirement of size and placement for tobacco advertising. The presence of a health warning was associated with lower social media engagement. Our study provides support for the implementation of comparable health warning requirements to social media tobacco promotions. Using an innovative computer vision approach to detect health warning labels in influencer promotions on social media is a novel strategy for monitoring health warning compliance in social media tobacco promotions.

Cross domain object detection is a realistic and challenging task in the wild. It suffers from performance degradation due to large shift of data distributions and lack of instance-level annotations in the target domain. Existing approaches mainly focus on either of these two difficulties, even though they are closely coupled in cross domain object detection. To solve this problem, we propose a novel Target-perceived Dual-branch Distillation (TDD) framework. By integrating detection branches of both source and target domains in a unified teacher-student learning scheme, it can reduce domain shift and generate reliable supervision effectively. In particular, we first introduce a distinct Target Proposal Perceiver between two domains. It can adaptively enhance source detector to perceive objects in a target image, by leveraging target proposal contexts from iterative cross-attention. Afterwards, we design a concise Dual Branch Self Distillation strategy for model training, which can progressively integrate complementary object knowledge from different domains via self-distillation in two branches. Finally, we conduct extensive experiments on a number of widely-used scenarios in cross domain object detection. The results show that our TDD significantly outperforms the state-of-the-art methods on all the benchmarks. Our code and model will be available at https://github.com/Feobi1999/TDD., CVPR2022

This study explores the effects of sentiment of Instagram images and captions on the sentiment of comments. All Instagram posts with the hashtag #mentalhealth and the associated metadata were scraped on World Mental Health Day. A mixed-method approach of a sentiment classifier and a quantitative content analysis of Instagram posts (N = 7,078) was used. Overall, our sample contained more positive sentiment posts and comments than negative ones, indicating a possible connection between mental health-related discourse and positive sentiment on Instagram. Images containing faces elicited more likes, comments and positive comments compared with images without faces. MANCOVA analyses of images with human faces found that emotional contagion from Instagram posts to comments was only observed when considering the sentiment of both images and captions. Congruency effects were seen for posts with both negative captions and images, which elicited more negative comments compared to emotionally incongruent posts. Theoretical implications of emotional contagion and real-life implications for mental health social media campaign design are discussed.

Little is known about the content, promotions, and individuals in cigar-related videos on TikTok. TikTok videos with large cigar and Swisher Sweets-related hashtags between July 2016 and September 2020 were analyzed. Follower count was used to identify influencers. We compared content characteristics and demographics of featured individuals between cigar types, and by influencer status. We also examined the association between content characteristics and video engagement. Compared to large cigar videos, Swisher Sweets videos were more likely to feature arts and crafts with cigar packages, cannabis use, and flavored products. In addition, Swisher Sweets videos were also more likely to feature females, Black individuals, and younger individuals. Both Swisher Sweets and large cigar influencers posted more videos of cigar purchasing behaviors than non-influencers, which was associated with more video views. None of the videos disclosed sponsorship with #ad or #sponsored. Videos containing the use of cigar packages for arts and crafts, and flavored products highlight the importance of colorful packaging and flavors in the appeal of Swisher Sweets cigars, lending support for plain packaging requirements and the prohibition of flavors in cigar products to decrease the appeal of cigars. The presence and broad reach of cigar promotions on TikTok requires stricter enforcement of anti-tobacco promotion policies.

E-cigarette use, or vaping, is undergoing a process of moralization in which issues about vaping evolve from being morally neutral to having discernible moral implications. Using Moral Foundations Theory, this study compared the moral narratives underlying polarized views about e-cigarette use and regulation. We integrated computational and human strategies by conducting the Chow test on the time series data and classification, topic modeling, and Chi-square tests on posts (

Reactive navigation is the most researched navigation technique for underground vehicles. Local path planning is one of the main research difficulties in reactive navigation. At present, no technique can perfectly solve the problem of local path planning for the reactive navigation of underground vehicles. Aiming to address this problem, this paper proposes a new method for local path planning based on 2D LiDAR. First, we convert the LiDAR data into a binary image, and we then extract the skeleton of the binary image through a thinning algorithm. Finally, we extract the centerline of the current laneway from these skeletons and smooth the obtained roadway centerline as the current planned local path. Experiments show that the proposed method has high robustness and good performance. Additionally, the method can also be used for the global path planning of underground maps.

Hydrogen is a renewable energy source with various features, clean, carbon-free, high energy density, which is being recognized internationally as a “future energy.” The US, the EU, Japan, South Korea, China, and other countries or regions are gradually clarifying the development position of hydrogen. The rapid development of the hydrogen energy industry requires more hydrogenation infrastructure to meet the hydrogenation need of hydrogen fuel cell vehicles. Nevertheless, due to the frequent occurrence of hydrogen infrastructure accidents, their safety has become an obstacle to large-scale construction. This paper analyzed five sizes (diameters of 0.068 mm, 0.215 mm, 0.68 mm, 2.15 mm, and 6.8 mm) of hydrogen leakage in the hydrogen fueling station using Quantitative Risk Assessment (QRA) and HyRAM software. The results show that unignited leaks occur most frequently; leaks caused by flanges, valves, instruments, compressors, and filters occur more frequently; and the risk indicator of thermal radiation accident and structure collapse accident caused by overpressure exceeds the Chinese individual acceptable risk standard and the risk indicator of a thermal radiation accident and head impact accident caused by overpressure is below the Chinese standard. On the other hand, we simulated the consequences of hydrogen leak from the 45 MPa hydrogen storage vessels by the physic module of HyRAM and obtained the ranges of plume dispersion, jet fire, radiative heat flux, and unconfined overpressure. We suggest targeted preventive measures and safety distance to provide references for hydrogen fueling stations’ safe construction and operation.

We address a two-sided assembly line balancing problem with the consideration of stochastic task time and multi-product production mode. The objective is to minimize the expected cycle time. In view of the difficulty in evaluating the objective in a stochastic environment, we model the target problem as a simulation optimization problem. A Harmony Search (HS) based algorithm is proposed to solve the problem. Besides, an Optimal Computing Budget Allocation (OCBA) method is adopted to enhance the simulation efficiency. Numerical experiments are conducted to evaluate the performance of the proposed HS-based algorithm against other well-known algorithms in the literature. The results indicate that the proposed algorithm outperforms the benchmark algorithms both in quality and computing efficiency.

It often takes a lot of trial and error to get a quadruped robot to learn a proper and natural gait directly through reinforcement learning. Moreover, it requires plenty of attempts and clever reward settings to learn appropriate locomotion. However, the success rate of network convergence is still relatively low. In this paper, the referred trajectory, inverse kinematics, and transformation loss are integrated into the training process of reinforcement learning as prior knowledge. Therefore reinforcement learning only needs to search for the optimal solution around the referred trajectory, making it easier to find the appropriate locomotion and guarantee convergence. When testing, a PD controller is fused into the trained model to reduce the velocity following error. Based on the above ideas, we propose two control framework - single closed-loop and double closed-loop. And their effectiveness is proved through experiments. It can efficiently help quadruped robots learn appropriate gait and realize smooth and omnidirectional locomotion, which all learned in one model.

Human-robot collaboration is an important area with great potential in intelligent manufacturing. Due to the diversity of collaboration tasks, robot collaboration skills should have the ability to adapt to different skills. However, problems such as skill expression and generalization are challenging. Meanwhile, the differences in the skills of various operators bring difficulties to collaborative robots. This work develops a variable impedance learning method for human-robot collaboration assembly. Unlike most previous work that mainly dis-cussed a special human collaborator with the fixed impedance parameters, this work learns a robot impedance by reinforcement learning. We aim to make the inertia, damping, and stiffness parameters adaptive by Proximal Policy Optimization (PPO) algorithm. Hence, we can let the robot collaborate with various human collaborators to accomplish a high-precision assembly task. Two experiment results illustrate the validity of the proposed method. The detailed experimental videos are available at https://youtu.be/AJyjW2NwA74.

Understanding the mechanism of functional connectivity in neural system is of great benefit to lot of researches and applications. Microfluidics and microelectrode arrays (MEAs) have been frequently utilized for in vitro neural cultures study. However, there are few studies on the functional connectivity of neural cultures grown on a microfluidic chip. It is intriguing to unveil the influences of microfluidic structures on in vitro neuronal networks from the perspective of functional connectivity. Hence, in the present study, a device was established, which comprised a microfluidic chamber for cell growth and a MEA substrate for recording the electrophysiological response of the neuronal networks. The network topology, neural firing rate, neural bursting rate and network burst frequency were adopted as representative characteristics for neuronal networks analysis. Functional connectivity was estimated by means of cross-covariance analysis and graph theory. The results demonstrated that the functional connectivity of the in vitro neuronal networks formed in the microchannel has been apparently reinforced, corresponding to improve neuronal network density and increased small-worldness.

Public responses toward vaping (i.e. electronic cigarette use) and vape bans have been hotly debated on social media. This study investigated vape-ban-related posts (n = 6,547) published between August 15, 2019 and February 15, 2020 on Reddit, a news aggregation social networking site that tolerates discussions that may be self-censored on other platforms. We conducted time series analysis and structural topic modeling to track public responses to the vape ban over a six-month period. Results showed that Google searches for vaping-related information were significantly associated with vape-ban-related posting activity on Reddit; and that eight topics emerged from the data, which included (1) Donald Trump, (2) vaping products, (3) liberty and autonomy, (4) inaccurate media reporting, (5) loopholes in state vape bans, (6) tobacco industry influence and the stupidity of ban, (7) the contrast between vaping and other more dangerous issues (e.g. school shootings, suicides), and (8) encouraging vapers to “vape on” (continue to vape). Each topic was examined in terms of their modelled longitudinal prevalence. All eight topics shared a similar theme of advocating vaping, although Redditors provided nuanced responses across time as the vaping epidemic unfolded. Social media discourse is promising to provide real-time indications of public response for diseases and epidemic surveillance, and to shed light on broader societal issues beyond the specific public health context.

Introduction The public most frequently associates tobacco use solely with pulmonary health risks, despite heart disease being the leading cause of death in smokers. The health perceptions of e-cigarettes, especially cardiovascular health, have not been well studied. We aimed to evaluate the prevalence and health perceptions of tweets related to cardiovascular, pulmonary, and brain health – three organ systems for which tobacco use is a major disease risk factor. Methods We examined the cardiovascular, pulmonary, and brain health perceptions of vaping and JUUL on Twitter, followed by a content analysis of tweets pertaining to the cardiovascular risks. A Twitter firehose API scraped about 6.2 million publicly available tweets from 2015–2019 that contained vaping-related terms, and a separate dataset of about 1.9 million tweets that contained the term JUUL. A quantitative content analysis (n=2145) of tweets was subsequently conducted to assess the health perceptions of vaping and JUUL. Two trained coders independently assessed the posts and Twitter profiles to determine age (

TOP2-poisoning bioflavonoids and pesticides are linked to the copy number variation-related autism and chromosome translocation-related leukemia. On the other hand, the poisoned DNA topoisomerase II (TOP2) can lead to chromosome aberration. However, except a limited number of genes such as the MLL fusion, other poisoned TOP2-targeted genes, as well as their relationships with any specific diseases, are not defined. We applied the γH2A.X antibodies to genome-widely immunoprecipitate the chromatins that were associated with the repair of the TOP2 poison etoposide-induced DNA double strand breaks. We identified many transcriptable protein- and nonprotein-coding DNA sequences that are the candidates of or associated with many gene copy number variation- and/or single nucleotide polymorphism-associated diseases, including but not limited to microdeletion and microduplication syndromes (which are phenotypically presented as developmental, autistic, neurological, psychiatric, diabetic, autoimmune, and neoplastic diseases among many others) as well as stature, obesity, metabolic syndrome, hypertension, coronary artery disease, ischemic stroke, aortic aneurysm and dissection, leukemia, cancer, osteoporosis, Alzheimer disease, Parkinson disease, and Huntington disease. Our data raise the possibility that the poisoned TOP2 might be linked to the specific genetic alterations contributing to these diseases, additional to the known copy number variation-related autism and chromosome translocation-related leukemia. According to our and others’ data, we propose a model that may interpret the features, such as mosaicism, polygenic traits and pleiotropy, of these diseases.Author SummaryFor the past several decades, the morbidity rate of many diseases, including autism, mental disorders, cancer, cardiovascular diseases, diabetes, and senile dementia, has world-widely been rising. Analysis of the genome of the patients and their family members has identified the genes, whose alterations, so called copy number variation (CNV) and single nucleotide polymorphism (SNP), contribute to the diseases. Moreover, the CNVs and SNPs are de novo, that is, they have occurred only in the recent generations. Epidemiologically, this indicates that for the past several decades, there have existed some unknown world-wide etiologies to which human beings are exposed. If the etiologies are identified, avoiding human’s exposure may reduce the morbidity of the diseases. We have found that the repair of the poisoned topoisomerase II involves many genes that contribute to the aforementioned diseases. As the topoisomerase II is known to be located at the genomic sites where the disease-associated CNVs occur, as the poisoned topoisomerase II is susceptible to chromosome aberration, and as the topoisomerase II poisons, such as dietary bioflavonoids, are widely distributed in the environment, our data raise the yet-to-be-confirmed possibility that the environmental topoisomerase II poisons might etiologically contribute to many CNV-associated diseases.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder. Although the pathological hallmarks of AD have been identified, the derived therapies cannot effectively slow down or stop disease progression; hence, it is likely that other pathogenic mechanisms are involved in AD pathogenesis. Intracellular calcium (Ca2+) dyshomeostasis has been consistently observed in AD patients and numerous AD models and may emerge prior to the development of amyloid plaques and neurofibrillary tangles. Thus, intracellular Ca2+ disruptions are believed to play an important role in AD development and could serve as promising therapeutic intervention targets. : One of the disrupted intracellular Ca2+ signaling pathways manifested in AD is attenuated storeoperated Ca2+ entry (SOCE). SOCE is an extracellular Ca2+ entry mechanism mainly triggered by intracellular Ca2+ store depletion. Maintaining normal SOCE function not only provides a means for the cell to replenish ER Ca2+ stores but also serves as a cellular signal that maintains normal neuronal functions, including excitability, neurogenesis, neurotransmission, synaptic plasticity, and gene expression. However, normal SOCE function is diminished in AD, resulting in disrupted neuronal spine stability and synaptic plasticity and the promotion of amyloidogenesis. Mounting evidence suggests that rectifying diminished SOCE in neurons may intervene with the progression of AD. In this review, the mechanisms of SOCE disruption and the associated pathogenic impacts on AD will be discussed. We will also highlight the potential therapeutic targets or approaches that may help ameliorate SOCE deficits for AD treatment.

Few-shot object detection (FSOD) helps detectors adapt to unseen classes with few training instances, and is useful when manual annotation is time-consuming or data acquisition is limited. Unlike previous attempts that exploit few-shot classification techniques to facilitate FSOD, this work highlights the necessity of handling the problem of scale variations, which is challenging due to the unique sample distribution. To this end, we propose a Multi-scale Positive Sample Refinement (MPSR) approach to enrich object scales in FSOD. It generates multi-scale positive samples as object pyramids and refines the prediction at various scales. We demonstrate its advantage by integrating it as an auxiliary branch to the popular architecture of Faster R-CNN with FPN, delivering a strong FSOD solution. Several experiments are conducted on PASCAL VOC and MS COCO, and the proposed approach achieves state of the art results and significantly outperforms other counterparts, which shows its effectiveness. Code is available at https://github.com/jiaxi-wu/MPSR.

Splenic cDCs must be positioned for blood-borne antigen encounter. This study shows that cDC2 localization in bridging channels versus the marginal zone (MZ) is dictated by MZ B cells. Further, it establishes that integrins are necessary for cDC2 retention in blood-exposed regions., The marginal zone (MZ) of the spleen contains multiple cell types that are involved in mounting rapid immune responses against blood-borne pathogens, including conventional dendritic cells (cDCs) and MZ B cells. MZ B cells develop later than other B cell types and are sparse in neonatal mice. Here, we show that cDC2s are abundant in the MZ of neonatal compared with adult mice. We find that conditions associated with reduced MZ B cell numbers in adult mice cause increased cDC2 occupancy of the MZ. Treatment with the S1PR1-modulating drug, FTY720, causes cDC2 movement into the MZ through the indirect mechanism of displacing MZ B cells into follicles. Splenic cDC2s express high amounts of α4β1 and αLβ2 integrins and depend on these integrins and the adaptor Talin for their retention in blood-exposed regions of the spleen. Splenic CD4 T cell activation by particulate antigens is increased in mice with higher cDC2 density in the MZ, including in neonatal mice. Our work establishes requirements for homeostatic cDC2 positioning in the spleen and provides evidence that localization in blood-exposed regions around the white pulp augments cDC2 capture of particulate antigens. We suggest that MZ positioning of cDC2s partially compensates for the lack of MZ B cells during the neonatal period., Graphical Abstract

After the subprime crisis in 2008, with the rapid development of the insurance industry and the continuous close contact with the financial market, the insurance industry and then generate systemic risk. Based on the actual situation of China's insurance industry, this paper selects the stock returns of five listed insurance companies as the object, and measures and ranks the systematic risks with GARCH-CoVaR method.

Summer enrichment and residential programs can provide gifted students with positive social interactions and challenging curricula. However, little research has focused on gifted students’ perceptions of the learning environment in such programs. This research project evaluated the psychometric properties and practical applications of the Student Perceptions of Classroom Quality ( SPOCQ) instrument. The two studies used a total sample of 1,492 diverse, gifted students in Grades 5 through 12 who participated in a university-based enrichment residential program from 2010 through 2013. Confirmatory factor analysis results indicated that although the original model was a moderately good fit for the gifted student participants in 2010 to 2011, some items on the SPOCQ were classroom specific and did not apply to residential programs. Therefore, those items were revised and retested, and results showed that the modified model was a better fit for gifted student participants in 2012 to 2013.

In an exploratory survey that sampled video gamers, participants were asked to indicate why they enjoy playing their favorite video game. On the basis of ESRB ratings, we compare those whose favori...

Deciphering the combinatorial histone codes has been a long-standing interest in the epigenetics field, which requires the reliable and robust characterization of the post-translational modifications (PTMs) coexisting on histones. To this end, weak cation exchange hydrophilic interaction liquid chromatography is commonly used in middle-down liquid chromatography-mass spectrometry approaches for online separation of variously modified histone peptides. Here we provide a novel strategy that combines the selective histone peptide derivatization using N-hydroxysuccinimide propionate ester with reversed-phase liquid chromatography (RPLC) for the robust, sensitive, and reliable characterization of combinatorial histone PTMs. Derivatization amplifies the subtle physical differences between similarly modified histone peptides, thereby allowing baseline separation of these peptides by standard RPLC. Also, the sensitivity of MS is enhanced greatly by derivatization due to the increased peptide hydrophobicity and concentrated charge-state envelope during electrospray ionization. Furthermore, we systematically optimized the dual electron transfer and higher energy collision dissociation and achieved near-complete peptide sequence coverage in MS/MS spectra, allowing highly precise and reliable PTM identification. Using this method, we identified 311 and 293 combinations of histone H3 PTMs from the lymphoma cells Karpas-422 with/without drug treatment, confirming the advantages of our method in serving as a platform for profiling combinatorial histone PTMs.

Introduction Marathon, as a long-distance aerobic exercise, has become a fashionable or popular sport. However, little is known about the holistic metabolic changes occurring within the serum metabolome of athletes after the completion of a marathon. Objectives The goal of current study was to have an in-depth understanding of the impact of marathon on human metabolomics as well as the relationships among a variety of metabolites. Methods The 20 studied subjects were all adult males who participated in a marathon. The serum samples of these participants were collected before and after the marathon and the biochemical metabolites in the serum were identified by an untargeted two-dimensional gas chromatography time-of-flight mass spectrometry. Results All participants completed the marathon within 3 h. Compared to those before exercise, serum urea and creatine kinase, as well as cortisol, elevated significantly (p p p p p p p p 2max, and hemoglobin were correlated with the serum metabonomic indicators, so were serum testosterone and cortisol. Conclusion These results illustrate that the metabolism of glucose and lipid of the athletes was enhanced following the marathon match. In addition, the metabolism of glucosamine was decreased and the metabolism of caffeine was increased. Our data provide new insights for marathon performance and nutritional status.

A new ternary composite BiOIO

The morphology of catalyst is a very important factor influencing the photocatalytic activity of the catalyst. Owing to its scientific and technological importance, controllable preparation of photocatalysts with different morphologies has been studied. In this work, BiOIO