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Introduction: Elderly stroke survivors usually experience various psychology disorders, such as post-stroke depression (PSD), which may be associated with high empirical avoidance (EA) and can seriously affect their quality of life. To date, the efficacy of group-based acceptance and commitment therapy (ACT) for elderly stroke survivors has not been established. The aim of this study is to investigate the effectiveness of group-based ACT on EA, PSD, psychological distress, and quality of life in elderly stroke survivors after group-based ACT. Methods and analysis: This study is a randomized, single-blind, wait-list controlled, parallel-arm trial. A total of 66 stroke survivors will be randomly assigned to wait-list control group or intervention group. Participants in wait-list control group will receive treatment as usual (TAU), while the intervention group will receive group-based ACT once a week for eight weeks. The primary outcome measure being EA, and the secondary outcome measures being PSD, psychological distress, and quality of life. Results of the two groups will be blindly assessed by professional evaluators at baseline (T0), post-treatment (T1), and one-month follow up (T2). Discussion: The results of this study will provide the first evidence for the effectiveness of a group-based ACT intervention in reducing EA, PSD, psychological stress, and improving quality of life for post-stroke survivors. Trial Registration: ChiCTR2200066361.

Video as information carrier has gained overwhelming popularity in city surveillance and social networks, such as WeChat, Weibo, and TikTok. To bridge the semantic gap between video content (e.g., user and landmark building) and textual information (e.g., user location), video captioning has emerged as an attracting technique in recent years. Existing works mostly focus on sentence-level Part-of-Speech (POS) information and use Long Short-Term Memory (LSTM) as encoder, which neglects word or phrase-level POS information and also fails to globally consider long-range temporal relations among video frames. To address the drawbacks, we leverage multi-granularity POS guidance to learn Graph Convolutional Network (GCN) via meta-learning, abbreviated as GMMP (GCN Meta-learning with Multi-granularity POS), for generating high-quality captions for videos. It models temporal dependency by treating frames as nodes in the graph, and captures POS information of words and phrases by multi-granularity POS attention mechanism. We adopt meta-learning to better learn GCN by maximizing the reward of generated caption in a reinforcement task and also the probability of ground-truth caption in a supervised task, simultaneously. Experiments have verified the advantages of our GMMP model on several benchmark data sets.

The thermal management of lithium-sulfur batteries with high specific energy has become one of the critical issues for their applications. Carbon-based nanotubes are widely used to construct composite sulfur cathodes. This paper focuses on the thermal transport properties of sulfur-coated and sulfur-embedded boron carbide nanotubes (BCNTs) and carbon nanotubes (CNTs) and their composites using molecular dynamics. It is found that phonon softening and localization play a role in making BCNT exhibit a lower thermal conductivity (TC) than CNT. Furthermore, it is discovered that the sulfur embedded inside the carbon-based nanotube has a greater negative impact on carbon-based nanotube phonon transport. Moreover, the effective medium theory model is not suitable for predicting the effective thermal conductivity of coated sulfur composites, in contrast to its good applicability to embedded sulfur composites. These findings provide an in-depth understanding of the thermal transport properties of composite sulfur cathodes in lithium-sulfur batteries.

Energy harvesting technology has been applied to power nodes in a wireless sensor networks (WSNs). However, it suffers from the dynamic nature of the ambient energy. Wireless charging, on the contrary, offers an additional choice to charge the sensor nodes (SNs) with a mobile charger (MC) which is often implemented to move within the network. Nevertheless, the energy spent on moving among sensors accounts for a considerable proportion of the whole energy the MC can take. To this end, we consider combining these two sources of energy to carry out the energy neutral operation for the WSNs. In this paper, we formulate the problem of minimizing the number of nodes for perpetual coverage of targets under the constraint of the energy capacity of a MC and the distribution of the energy harvesting rate across the monitoring field which generates great difficulty. We designed two approximation algorithms to tackle this problem. We conduct extensive simulations to evaluate the performance of our proposed algorithms. The results showed performance of these two algorithms with respect to impact of different parameters.

Background Effective pain management is closely related to nurses' knowledge and attitudes toward pain. Limited studies have been performed related to nurses’ knowledge and attitudes toward pain in hospitals in low-income areas. Aims This study surveyed the knowledge and attitudes of nurses toward pain management in county hospitals from low-income areas in Hunan Province, China. Setting and participants The study included 4,668 registered nurses working in 48 county hospitals in low-income areas in China. Methods A cross-sectional study examined the knowledge and attitudes of nurses with regard to pain using the Chinese version of the Knowledge and Attitude Survey Regarding Pain (KASRP) via the WeChat application. Results The 4,668 registered nurses completed the survey; of these, 43.6% indicated they had never received continuing education for pain. The mean percentage score for KASRP was (40.3 ± 7.95), and none of the respondents achieved a percentage score of >80%. Further, of the 40 items, only two had a correct rate of >80%. Continuing pain education did not significantly affect KASRP. Multiple stepwise linear regression showed that education level, ethnicity, professional title, position, and department were independent influencing factors for KASRP scores. Conclusion Almost all nurses in county hospitals of low-income areas had deficiencies in various aspects of pain management knowledge. Better educated nurses with higher professional title or management position, those from the Han ethnicity, and those from the oncology department had higher mean KASRP scores. Current continuing education programs for pain did not improve the pain management capability of the nurse. High-quality and standardized pain educational programs should be implemented to improve pain management.

Video summarization has established itself as a fundamental technique for generating compact and concise video, which alleviates managing and browsing large-scale video data. Existing methods fail to fully consider the local and global relations among frames of video, leading to a deteriorated summarization performance. To address the above problem, we propose a graph convolutional attention network (GCAN) for video summarization. GCAN consists of two parts, embedding learning and context fusion, where embedding learning includes the temporal branch and graph branch. In particular, GCAN uses dilated temporal convolution to model local cues and temporal self-attention to exploit global cues for video frames. It learns graph embedding via a multi-layer graph convolutional network to reveal the intrinsic structure of frame samples. The context fusion part combines the output streams from the temporal branch and graph branch to create the context-aware representation of frames, on which the importance scores are evaluated for selecting representative frames to generate video summary. Experiments are carried out on two benchmark databases, SumMe and TVSum, showing that the proposed GCAN approach enjoys superior performance compared to several state-of-the-art alternatives in three evaluation settings.

The tubesheet is the key part of the steam generator, and the quality of the tubesheet hole is the key characteristic of the steam generator. The inspection of tubesheet holes includes defects on the surface of the tubesheet holes and the geometric dimensions of the tubesheet holes. The geometric dimensions of the tubesheet hole mainly include hole diameter, perpendicularity, hole bridge, position and roughness, etc. The perpendicularity of tubesheet hole is an important characteristic, which directly affects the size of tubesheet secondary hole bridge and heat exchange tube installation. This paper describes a device for measuring the perpendicularity of tubesheet hole, discusses the principle and measurement method of the tubesheet hole perpendicularity measuring device, and analyzes the error and proposes measures to improve the measurement accuracy of the device. Analysis of data processing provides a basis for the measurement device and measurement method to meet the requirements of specifications. The results show that the designed measuring device to measure perpendicularity has the advantages of simple operation, simple measurement and high accuracy of measurement results. It is beneficial to ensure the quality of heat exchange tube installation of the steam generator, which can speed up the manufacturing progress of the steam generator.

Humic substances acting as an electron shuttle and nitrogen transformation process influence remarkably the electron transfer in anaerobic reaction systems and thus may affect the reductive dechlorination of hexachlorobenzene (HCB). In order to develop an efficient agricultural strategy for the remediation of organochlorine-contaminated soils, a batch incubation experiment was conducted to study the effects of humic acid, urea, and their interaction on the reductive dechlorination of HCB in a Hydragric Acrisol with high iron oxide content. After 44 d of anaerobic incubation, the five treatments, sterile control, control, humic acid, urea, and humic acid + urea decreased HCB residues by 28.8%, 47.8%, 64.7%, 57.8%, and 71.3%, respectively. The amendment of humic acid or urea significantly decreased soil Eh values and accelerated Fe(III) reduction to Fe(II), thus promoting markedly reductive dechlorination of HCB. Humic acid had a larger dechlorination effect than urea. Since there was a synergistic interaction between humic acid and urea that accelerated HCB dechlorination, the treatment having both amendments together was the most efficient for HCB dechlorination. The results showed that the combination of NH4+-N supplied by a fertilizer and humic substance is a feasible strategy for the remediation of organochlorine-contaminated soils with abundant iron oxide.

We collected 682 topsoil samples (0-20cm) from agricultural lands of Luhe County in East China, and analyzed the spatial distribution patterns and potential sources of four major heavy metals. High Pb and Cr were mainly in the southeast adjacent to the Yangtze River, and Cd were characterized by an increasing trend from northwest to southeast, while high Hg mainly occurred in the areas near downtown. Spatially-continuous sources dominated the soil heavy metal concentrations. Contributions of spatially-continuous natural source (soil parent material) to Cr and Cd were 97.0% and 77.7%, respectively, whereas contributions of spatially-continuous anthropogenic source such as diffuse pollution to Pb and Hg were 75.7% and 86.7%, respectively. The distance to factories was the most influential anthropogenic factor for localized anomaly patterns of Pb, Cd, and Cr, while the intensive agricultural land uses associated with the rapid urban expansion were particularly relevant to the anomaly patterns of Hg.

Background To investigate the clinical effects of norepinephrine versus dopamine in treatment of septic shock by pooling the data form open published clinical trials. Material and Methods The clinical trials relevant to norepinephrine versus dopamine in treatment of septic shock were electronically searched in the databases of Pubmed, Embase, the Cochrane Library, Web of Science, Google scholar and CNKI. The original data related to the treatment effects such as death risk, oxygen metabolism and hemodynamics index were extracted from the included original studies. The death risk was pooled by the effect size of relative risk (RR), the oxygen metabolism and hemodynamics index were pooled by standard mean difference (SMD) and the corresponding 95% confidence interval (95%CI). The publication bias was evaluated by Begg's funnel plot and Egger's line regression test. Results Thirteen clinical trials were included in the meta-analysis. The pooled results demonstrated the death risk was significantly decreased (RR=0.89, 95%CI:0.81 to 0.98, p=0.024) in septic shock patients who received norepinephrine compared to those receiving dopamine. The HR (SMD=−1.84, 95%CI: −2.86 to −0.81, p Conclusions Based on the present evidence, norepinephrine was superior to dopamine in the aspects of death risk reducing and hemodynamics.

Because of its high specific surface area, metal foam is expected to further enhance the flow and thermal performance of a minichannel heatsink. In this study, fully developed flow in minichannels with porous fins was studied. The porous geometry was constructed based on Laguerre-Voronoi tessellation and simulated in a pore scale, which eliminated the influence of parameter selection in a macroscale method. The influence of porosity, filling ratio, and Reynolds number on velocity field and pressure drop was analyzed. The general relationship between the Poiseuille number and filling ratio was determined, and a correlation was obtained using the study results. The results of this study were compared with those of the macroscale method, and finally, the influence of effective viscosity was discussed.

Vapor compression heat pump technology has great potential in future space thermal management application. Considering microgravity in space, this paper proposes using aerostatic bearings for the lubrication of the heat pump compressor. An experimental apparatus was built to study the performance of a rotor supported by aerostatic bearings subjected to microgravity. The gravity-independent experiment was conducted by changing the angle between the rotor axis and the direction of gravity on the ground. The gas consumption and rotor stability at different rotor orientations were investigated and compared. Results showed that the largest difference in gas consumption due to the change in rotor orientation was 3% for the journal bearing and 5.56% for thrust bearings. The difference in rotation speed at the second peak amplitude under different rotor orientations was smaller than 4.2%. The experimental results imply that the aerostatic bearing-rotor system is independent of gravity. Aerostatic gas lubrication technology is thus a viable option for the vapor compression heat pump used in a space thermal management system.

Sensing coverage has attracted considerable attention in wireless sensor networks. Existing work focuses mainly on the 0/1 disk model which provides only coarse approximation to real scenarios. In this article, we study the connected target coverage problem which concerns both coverage and connectivity. We use directional probabilistic sensors, and combine probabilistic and directional sensing model features to characterize the quality of coverage more accurately in an energy efficient manner. Based on the analysis of the collaborative detection probability with multiple sensors, we formulate the minimum energy connected target ϵ -probability coverage problem, aiming at minimizing the total energy cost while satisfying the requirements of both coverage and connectivity. By a reduction from a unit disk cover, we prove that the problem is nondeterministic polynomial (NP)-hard, and present an approximation algorithm with provable time complexity and approximation ratio. To evaluate our design, we analyze the performance of our algorithm theoretically and also conduct extensive evaluations to demonstrate its effectiveness.

Recommendation technology is an important part of the Internet of Things (IoT) services, which can provide better service for users and help users get information anytime, anywhere. However, the traditional recommendation algorithms cannot meet user's fast and accurate recommended requirements in the IoT environment. In the face of a large-volume data, the method of finding neighborhood by comparing whole user information will result in a low recommendation efficiency. In addition, the traditional recommendation system ignores the inherent connection between user's preference and time. In reality, the interest of the user varies over time. Recommendation system should provide users accurate and fast with the change of time. To address this, we propose a novel recommendation model based on time correlation coefficient and an improved K-means with cuckoo search (CSK-means), called TCCF. The clustering method can cluster similar users together for further quick and accurate recommendation. Moreover, an effective and personalized recommendation model based on preference pattern (PTCCF) is designed to improve the quality of TCCF. It can provide a higher quality recommendation by analyzing the user's behaviors. The extensive experiments are conducted on two real datasets of MovieLens and Douban, and the precision of our model have improved about 5.2 percent compared with the MCoC model. Systematic experimental results have demonstrated our models TCCF and PTCCF are effective for IoT scenarios.

Modeling and simulation of thermal-fluid systems are very important in industrial numerical simulation and play key roles in their design and control. In this paper, the modeling and simplification method of one-dimensional thermal-fluid network with variable-property are presented, including matrix representation of the network, simplification algorithm for series/parallel connection based on matrix operation and generation of flow equations based on system topology. This simplification is suitable for the simulation of thermal-fluid systems with arbitrary topological structure. The method to treat reflux during iteration is proposed. The outstanding features of the simplification algorithm are the significant reduction in the thermal-fluid network and therefore the number of the related governing equations, as well as the computation burden. The example in this paper shows that the number of the governing equations for flow is reduced by about 45% and the calculation time of flow calculation is reduced by an average of 32% after the simplification.

Big sensing data is commonly encountered from various surveillance or sensing systems. Sampling and transferring errors are commonly encountered during each stage of sensing data processing. How to recover from these errors with accuracy and efficiency is quite challenging because of high sensing data volume and unrepeatable wireless communication environment. While Cloud provides a promising platform for processing big sensing data, however scalable and accurate error recovery solutions are still need. In this paper, we propose a novel approach to achieve fast error recovery in a scalable manner on cloud. This approach is based on the prediction of a recovery replacement data by making multiple data sources based approximation. The approximation process will use coverage information carried by data units to limit the algorithm in a small cluster of sensing data instead of a whole data spectrum. Specifically, in each sensing data cluster, a Euclidean distance based approximation is proposed to calculate a time series prediction. With the calculated time series, a detected error can be recovered with a predicted data value. Through the experiment with real world meteorological data sets on cloud, we demonstrate that the proposed error recovery approach can achieve high accuracy in data approximation to replace the original data error. At the same time, with MapReduce based implementation for scalability, the experimental results also show significant efficiency on time saving.

Short videos are popular information carriers on the Internet, and detecting events from them can well benefit widespread applications, e.g., video browsing, management, retrieval and recommendation. Existing video analysis methods always require decoding all frames of videos in advance, which is very costly in time and computation power. These short videos are often untrimmed, noisy and even incomplete, adding much difficulty to event analysis. Unlike previous works focusing on actions, we target short video event detection and propose Recurrent Compressed Convolutional Networks (RCCN) for discovering the underlying event patterns within short videos possibly including a large proportion of non-event videos. Instead of using the whole videos, RCCN performs representation learning at much lower cost within the compressed domain where the encoded motion information reflecting the spatial relations among frames can be easily obtained to capture dynamic tendency of event videos. This alleviates the information incompleteness problem that frequently emerges in user-generated short videos. In particular, RCCN leverages convolutional networks as the backbone and the Long Short-Term Memory components to model the variable-range temporal dependency among untrimmed video frames. RCCN not only learns the common representation shared by the short videos of the same event, but also obtains the discriminative ability to detect dissimilar videos. We benchmark the model performance on a set of short videos generated from publicly available event detection database YLIMED, and compare RCCN with several baselines and state-of-the-art alternatives. Empirical studies have verified the preferable performance of RCCN.

The aim of this study was to identify the symptom burden of perioperative oral cancer patients, its trajectory, and the factors influencing it.A longitudinal, repeated measures design with consecutively identified sampling was used to recruit oral cancer patients scheduled for surgical treatment. Data collected included sociodemographic and clinical information, nutritional risk by the Nutritional Risk Screening 2002, and symptom burden by M. D. Anderson Symptom Inventory-Head and Neck Module (MDASI-HN) at preoperation, 7 days postsurgery, and 1 month postsurgery.Perioperative patients with oral cancer had multiple symptoms. Pain, difficulty swallowing/chewing, and mouth/throat sores (61.9%-76.1%) were the most prevalent symptoms before surgery. The symptom burden was the highest at 7 days after surgery, with the most prevalent symptoms, including difficulty swallowing/chewing, difficulty with voice/speech, and problems with mucus (87.8%-95.4%). At 1 month postsurgery, the 3 main symptoms were numbness or tingling, difficulty swallowing/chewing, and difficulty with voice/speech (all 87.8%). Treatment stage, job, comorbidity, cancer stage, adjuvant therapy, and Nutritional Risk Screening 2002 score were correlated with symptom burdens.Our study illustrates that perioperative oral cancer patients have multiple symptoms and high symptom burdens, especially at 7 days postsurgery, with prominent symptoms and symptom burdens varying with the treatment stage.

IntroductionWith the worsening of population ageing globally, the number of the elderly with chronic and incurable diseases such as malignant tumours is gradually increasing, and the need for palliative care is growing. As a primary task in the end-of-life phase, symptom management is an essential aspect of palliative care, which aims to alleviate distressing symptoms of terminally ill patients and improve their quality of life. Virtual reality (VR) technology, which allows the creation of simulated environments in which a three-dimensional experience is generated, has been increasingly used in palliative care for symptom management. Therefore, we aim to conduct a systematic review to investigate the effects of VR-based interventions on end-of-life patients.Methods and analysisThis protocol for conducting a systematic review and meta-analysis will be prepared following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. We will conduct a series of searches from inception to 31 July 2022 in the following databases: PubMed, Embase, Web of Science, the Cochrane Library, JBI, EBSCO, CNKI, Wanfang and SinoMed. The key concepts of ‘virtual reality’ and ‘end-of-life’ will be combined in each database using both free-text terms and controlled vocabulary terms (eg, MeSH/Emtree terms), if available. Two independent reviewers will use raw data to explore the effectiveness of VR for symptom management in end-of-life patients. The Cochrane Risk-of-Bias tool will be used to assess the risk of bias of included studies. Disagreements will be resolved by a third independent reviewer to reach a consensus. For the included articles, Review Manager software will be used for data synthesis and I2statistics will be used to measure the heterogeneity. Subgroup analyses and sensitivity analyses will be used to identify the source of heterogeneity.Ethics and disseminationAs this is a protocol for a systematic review and meta-analysis, patients will not be included in this study. For this reason, ethical approval is not required. In order to disseminate the research findings, the results and conclusions of this review will be submitted to a worldwide journal.PROSPERO registration numberCRD42022344679.

ObjectiveThe purpose of this study was to investigate death anxiety status among Chinese patients with cancer and identify factors that affect death anxiety.DesignCross-sectional study.SettingChangsha, Hunan Province, China.ParticipantsA total of 286 inpatients diagnosed with cancer were randomly recruited from a tertiary cancer centre and completed the questionnaires between January and June 2021.Primary and secondary outcome measuresThe primary outcome was the status of death anxiety. The secondary outcomes were the factors that affect death anxiety among Chinese patients with cancer.MethodsA total of 286 Chinese patients with cancer were recruited from a tertiary cancer hospital to complete the demographic and clinical characteristics questionnaire, Templer’s Death Anxiety Scale, Acceptance and Action Questionnaire-second edition, and Meaning in Life Questionnaire from January to June 2021. Data were analysed using t-test, analysis of variance, Kruskal-Wallis H test, Pearson correlation analysis and multiple linear regression analysis.ResultsOn average, patients with cancer scored 7.72±4.17 for death anxiety, 25.71±9.69 for experiential avoidance and 45.19±8.22 for meaning in life. Ultimately, the statistically significant factors influencing death anxiety were education levels, insurance, pain scores, experiential avoidance and meaning in life. These factors explained 40.6% of the difference in death anxiety.ConclusionsPatients with cancer in China experienced a high level of death anxiety. This study showed that experiential avoidance and meaning in life were important factors that affected death anxiety in patients with cancer. Further studies should be conducted to explore effective interventions to prevent experiential avoidance and increase meaning in life for patients with cancer. Attention should be paid to patients without insurance but with lower education levels and higher pain scores to ultimately relieve death anxiety and improve their quality of life.

Molecular dynamics simulation method is carried out to study influence of GaAs crystal anisotropy on deformation behavior and residual stress distribution of nanoscratching. The scratching process of three crystal orientations of GaAs[100], GaAs[110] and GaAs[111] is investigated, respectively. It is found that there exists significant crystal anisotropy of the deformation behavior and residual stress distribution. Meanwhile, atomic pile-up, destruction depth, scratching force, surface topography, internal structure, residual stress are closely related to the GaAs crystal orientations. A new method to study the residual stress distribution of nanoscratching is proposed. It is observed that the residual stress is focused on the scratching region and its limits, and the two sides of the scratch are distributed symmetrically. The component of residual stress at the GaAs[100] scratching bottom is mainly the compressive stress in the y-axis direction. The average scratching force for the GaAs[110] scratch is the smallest and the pile-up height on the upper surface of the GaAs[110] workpiece is the largest. Eventually, the destruction depth of the crystal structure of the GaAs[110] workpiece by the abrasive in the scratching process is the smallest among three crystal orientations, while that of the GaAs[100] scratch is the largest among three crystal orientations.

Mechanical vapor recompression (MVR) technology has broad prospects for application in saving energy. The compression in the MVR system often involves mixing vapor and liquid, and therefore, studies of the process can help establish a theoretical model to solve the problem of controlling compression temperature and improving the compression process's efficiency. However, the mixed phase-change in water vapor compression is complex and differs from that in air wet compression. In this paper, we studied droplets' effect on water vapor compression performance and the mechanism of heat and mass transfer during the process. A 2D single droplet evaporation model for water vapor compression was established and analyzed with Python, and a 3D numerical simulation was solved with CFD software to investigate the effect on water vapor compression of droplet diameter, ambient pressure and temperature, spray flow rate, and flow velocity. The results showed that the compressor's outlet temperature can be reduced by reducing the droplet diameter and increasing the spray flow rate, thus decreasing the work required for compression. The results also indicated that a high pressure ratio and superheat can enhance the cooling effect greatly.

Barrier Coverage is an important sensor deployment issue in many industrial, consumer and military applications.The barrier coverage in bistatic radar sensor networks has attracted many researchers recently. The Bistatic Radars (BR) consist of radar signal transmitters and radar signal receivers. The effective detection area of bistatic radar is a Cassini oval area that determined by the distance between transmitter and receiver and the predefined detecting SNR threshold. Many existing works on bistatic radar barrier coverage mainly focus on homogeneous radar sensor networks. However, cooperation among different types or different physical parameters of sensors is necessary in many practical application scenarios. In this paper, we study the optimal deployment problem in heterogeneous bistatic radar networks.The object is how to maximize the detection ability of bistatic radar barrier with given numbers of radar sensors and barrier’s length. Firstly, we investigate the optimal placement strategy of single transmitter and multiple receivers, and propose the patterns of aggregate deployment. Then we study the optimal deployment of heterogeneous transmitters and receivers and introduce the optimal placement sequences of heterogeneous transmitters and receivers. Finally, we design an efficient greedy algorithm, which realize optimal barrier deployment of M heterogeneous transmitters and N receivers on a L length boundary, and maximizing the detection ability of the barrier. We theoretically proved that the placement sequence of the algorithm construction is optimal deployment solution in heterogeneous bistatic radar sensors barrier. And we validate the algorithm effectiveness through comprehensive simulation experiments.

Detection and recognition of road traffic signs constitute an important element in Advanced Driver Assistance Systems (ADAS), which can provide real-time road sign perception information to vehicles. In this paper, we proposed a new traffic sign detection method based on adaptive color threshold segmentation and the hypothesis testing of shape symmetry by leveraging traffic signs and image data. First, we calculated an adaptive segmentation threshold using the cumulative distribution function of the image histogram. Based on this, we designed an approximate maximum and minimum normalization method, which is used to suppress the interference of high brightness area and background in image thresholding processes. Secondly, we transformed the highlight shape feature of thresholding image into a connected domain feature vector. And we formulated a shape symmetry detection algorithm based on statistical hypothesis testing to efficiently extract the ROI of traffic signs based on traffic data analysis. We performed some comprehensive experiments on the GTSDB (German Traffic Sign Detection Benchmark) dataset. The accuracy of traffic sign detection exceeded 94%. This method has higher detection accuracy and time efficiency than other methods, and better robustness under complex traffic environment.

Tensor data (i.e., the data having multiple dimensions) are quickly growing in scale in many practical applications, which poses new challenges for data modeling and analysis approaches, such as high-order relations of large complexity, gross noise, and varying data scale. Existing low-rank data analysis methods, which are effective at analyzing matrix data, may fail in the regime of tensor data due to these challenges. A robust and scalable low-rank tensor modeling method is heavily desired. In this paper, we develop an online robust low-rank tensor modeling (ORLTM) method to address these challenges. The ORLTM method leverages the high-order correlations among all tensor modes to model an intrinsic low-rank structure of streaming tensor data online and can effectively analyze data residing in a mixture of multiple subspaces by virtue of dictionary learning. ORLTM consumes a very limited memory space that remains constant regardless of the increase of tensor data size, which facilitates processing tensor data at a large scale. More concretely, it models each mode unfolding of streaming tensor data using the bilinear formulation of tensor nuclear norms. With this reformulation, ORLTM employs a stochastic optimization algorithm to learn the tensor low-rank structure alternatively for online updating. To capture the final tensors, ORLTM uses an average pooling operation on folded tensors in all modes. We also provide the analysis regarding computational complexity, memory cost, and convergence. Moreover, we extend ORLTM to the image alignment scenario by incorporating the geometrical transformations and linearizing the constraints. Extensive empirical studies on synthetic database and three practical vision tasks, including video background subtraction, image alignment, and visual tracking, have demonstrated the superiority of the proposed method.

Silicon (Si) plays important roles in improving rice growth and mitigating rice arsenic (As) uptake. In the present study, a pot experiment was carried out to investigate effects of Si application on uptake of As and phosphorus (P) and formation of iron (Fe) plaque on root surface of two rice cultivars (Zhendao 10 and Nanjing 44) grown in a high As-contaminated soil. The results showed that dry weights of shoots and roots for both rice cultivars didn't significantly varied under low Si level, but significantly increased for Zhendao 10, while decreased for Nanjing 44 under high Si level (p 0.05). As concentrations in shoots and roots of Nanjing 44 significantly decreased for low Si level, while significantly increased for high Si level (p 0.05). Different from Nanjing 44, effect of Si application on As concentrations in the plants of Zhendao 10 wasn't significant (p 0.05). Si significantly increased concentrations of P in shoots and roots of both rice cultivars (p 0.05). However, Si didn't significantly affect formation of Fe plaque on root surface. These results suggest that the effects of Si application on rice growth and As uptake in As-contaminated soils may depend on type of rice cultivar and Si application level. Rice cultivar and Si application rate should be considered when Si application is used to mitigate As accumulation in rice.

Spay cooling is a complicated flow and heat transfer process affected by multi-factors among which the environmental pressure is extremely important. However the influence of pressure is not investigated sufficiently, especially the reduced pressure. In the present study, spray cooling under low initial environmental partial pressures and vapor partial pressures with R21 are investigated with a closed spray and condensation system. To study the influence of initial environmental partial pressure, different amounts of nitrogen are inflated into the vacuum flash chamber, while the vapor partial pressure is kept constant. To study the influence of vapor partial pressure, a cascade refrigerator is used to condense the vapor with different condensation temperatures so that the vapor partial pressure can be maintained or adjusted, while the initial environmental partial pressure is kept constant. The experimental results show that the spray cooling power increases monotonically with the increasing spray flow rate in the experimental range, while the cooling efficiency decreases with the increasing spray flow rate. The spray cooling power and cooling efficiency vary with the initial environmental partial pressure or the vapor partial pressure non-monotonously, which indicates there is an optimal pressure for the heat transfer performance. Besides, the mechanism of the non-monotonous variation trend is discussed based on the key aspects including flash evaporation, convection and boiling. Especially, the boiling heat transfer curve is applied to explain the trend.

Objective To explore quality of life (QOL) in patients with colorectal cancer and a stoma and factors associated with their QOL. Methods A quantitative cross-sectional study was carried out in the stoma and wound care clinic of a cancer hospital in China. Participants were recruited from clinic patients. Investigators collected demographic data and clinical information; QOL was measured using a Chinese version of the stoma-QOL scale. Results In total, 359 participants took part; 161 (44.8%) had an ileostomy, whereas the others had a colostomy, and about half of the participants (46.5%) had a permanent stoma. The mean age was 57.86 ± 11.92 years. The QOL scores of most participants were poor, with a median value of 49.44. Participants whose stoma was cared for by others had a significantly lower QOL score than those who cared for their own stomas (odds ratio [OR], 1.58; 95% confidence interval [CI], 1.05-2.38; P = .029). Participants with a temporary stoma had a lower QOL score than those with a permanent stoma (OR, 2.08; 95% CI, 1.275-3.40; P = .004). Further, participants with a complication had a lower QOL score than those without (OR, 1.62; 95% CI, 1.07-2.43; P = .022). Conclusions These findings suggest a need for well-developed interventions to improve the QOL of these patients. This study provides valuable insights to inform the development of future clinical practice and research in this area in China and beyond.

Background: The past decade has witnessed the preliminary development of pre-hospital emergency. We analyzed the scientific output related to pre-hospital emergency in the past two decades, aiming to evaluate the publication status of the literature related to pre-hospital emergency through bibliometrics analysis, and hope to provide enlightenment of trends and hotspots for the development of pre-hospital emergency. Method: By web of science, all literature on pre-hospital emergency from 2000 to 2 October 2020 was retrieved and screened by two researchers. Excel, Social Sciences Statistics Package (SPSS, version 24) and software GraphPad Prism 8 were used to analyze the publication trend in related fields. Besides, VOSviewer, Citespace were also applied to visualize the research trends and study the co-occurring keywords in pre-hospital emergency. Results: As of 2 October 2020, a total of 1839 pre-hospital emergency publications with total citation of 32800 times were identified. The United States accounted for the largest number of publications (36.7%) and the highest number of citations (12825), but its H-index was fourth (20.17). In the aspects of journals and articles, Prehospital Emergency Care is the most published journal in pre-hospital emergency (256), while the articles from Smith K presented the highest citation frequency (751). We can also obtain the information that the overall trend is upward, and developed countries contribute most. “Complications” is a hot research field in intensive care. In the identification research cluster, “acute ischemic stroke” was determined to be the hotspot, while “secondary outcome” was the new trend in the first-aid cluster. As for the management, “embase” was noted as new topics. Conclusion: In the past decade, researches on pre-hospital emergency has increased rapidly. However, the related articles were mainly published in developed countries, the United States has absolute advantages especially. Moreover, first-aid studies may become hotspots in the near future.

Diabetic patients have an increased risk of invasive aspergillosis (IA), but the mechanism is still unclear. Reactive oxygen species (ROS) produced by neutrophils play a key role in defense against Aspergillus infection. Since diabetes mellitus affects the production of ROS from neutrophils, the purpose of this study is to investigate whether this effect is related to the susceptibility of diabetic mice to IA. C57BL/6 mice were used to establish type 2 diabetes mellitus (T2DM) model, and IA was induced by airway infection with Aspergillus fumigatus. After infection, the fungal load, neutrophil count and ROS content in the lung tissues of T2DM mice were higher than those in the control mice, and the inflammation of the lung tissue was more serious. After being exposed to hyphae in vitro, compared with the control group, neutrophils in T2DM mice had higher apoptosis rate and intracellular ROS content, as well as lower viability, extracellular ROS content and fungicidal ability. In summary, after T2DM mice are infected with A. fumigatus, the reduction of extracellular ROS produced by neutrophils may lead to a decrease in fungicidal ability, while the increase of intracellular ROS is related to neutrophil and lung tissue damage.

Open-cell metal foam mini-channel evaporator (OMFME) is proposed to enhance heat transfer in electronics cooling. In present study, flow boiling in an OMFME is investigated using R134a. The OMFME has nine channels, which are 507 μm in width and 1097 μm in depth. Comparing with a mini-channel evaporator (ME) with the same footprint area, the heat transfer coefficient (HTC) is enhanced up to 1.5 times and the dry out is delayed. Flow patterns are presented and compared with an existed flow patterns map. HTCs generally increases with the quality, the heat flux and it is slightly influenced by the mass flow rate. Nucleate boiling and evaporation in the porous fins are the two heat transfer mechanisms in different quality range. A correlation is presented to calculate frictional pressure drop.

The transient heat transfer performance of spray cooling with R21 is studied experimentally. Three variation patterns of surface temperature depending on the initial surface temperature are observed. There is only one rapid temperature drop at lower initial surface temperature and two drops with a shoulder transition at higher initial surface temperature. Further increasing the initial surface temperature will deteriorate heat transfer. Based on the pool boiling heat transfer curve and one-dimensional transient heat conduction model, the temperature variation patterns and processes are discussed which relate to nucleate boiling, transition boiling and film boiling, respectively. The experimental results reveal that the deterioration temperature decreases with increase of the heating flux and nozzle-to-heater distance, while increases with the spray flow rate. Based on the experimental results a region map of temperature variation patterns in transient spray cooling is given.

Spiritual needs are important for many patients with life-limiting illnesses. Knowledge of spiritual needs is a first step to their fulfillment; however, such knowledge is lacking for patients with cancer in mainland China. This study evaluated spiritual needs among patients with cancer in China and analyzed their associations with demographic and clinical characteristics. A descriptive, cross-sectional study was performed. A general information questionnaire and a Chinese version of the Spiritual Needs Scale were used to collect information about patients with cancer. A total of 200 participants were recruited, and 182 completed the survey. The overall average spiritual needs score was 3.15. Of five dimensions investigated, the highest and lowest scores were for “hope and peace” (mean = 3.31) and “relationship with transcendence” (mean = 2.96). Of specific needs, “to be accepted,” “to take responsibility for my life,” and “to alleviate my suffering” (means = 3.36–3.38) were valued as most important by participants. “To talk to someone,” “to pray and participate in religious rituals and services,” and “to feel God with me during my struggle against disease” (means = 2.71–2.91) were considered least important. Participants’ spiritual needs differed significantly according to disease stage (p

In this paper, the performance of a concentrating photovoltaic/thermal solar system is numerically analyzed with a mathematical and physical model. The variations of the electrical efficiency and the thermal efficiency with the operation parameters are calculated. It is found that the electrical efficiency increases at first and then decreases with increasing concentration ratio of the sunlight, while the thermal efficiency acts in an opposite manner. When the velocity of the cooling water increases, the electrical efficiency increases. Considering the solar system, the surface of the sun, the atmosphere and the environment, we can get a coupled energy system, which is analyzed with the entropy generation minimization and the entransy theory. This is the first time that the entransy theory is used to analyze photovoltaic/thermal solar system. When the concentration ratio is fixed, it is found that both the minimum entropy generation rate and the maximum entransy loss rate lead to the maximum electrical output power, while both the minimum entropy generation numbers and the maximum entransy loss coefficient lead to the maximum electrical efficiency. When the concentrated sunlight is not fixed, it is shown that neither smaller entropy generation rate nor larger entransy loss rate corresponds to larger electrical output power. Smaller entropy generation numbers do not result in larger electrical efficiency, either. However, larger entransy loss coefficient still corresponds to larger electrical efficiency.

Experiments are carried out on the frost and defrost characteristics of fine tube bundles under coolant temperature between −20 and −58 °C. The diameter of the tube is 2 mm. The frost and defrost processes are observed by taking photos and measuring pressure drops. The results indicate that the frost layer thickness on the tube surface increases with decreasing coolant temperature, but decreases with increasing air humidity. A model is given to explain the variation of frost thickness. The experiments verified that spraying ethanol is effective on inhibiting the formation of the frost.

Amateur videos always contain focusing issues. A focusing mistake may produce out-of-focus blur, which seriously degrades the expressive force of the video. In this paper, we propose a patch-based method to remove the out-of-focus blur of a video and build an all-in-focus video. We assume that the out-of-focus blurry region in one frame will be clear in a portion of other frames; thus, the clear corresponding regions can be used to reconstruct the blurry one. We divide each video frame into a grid of patches and track each patch in the surrounding frames. We independently reconstruct each video frame by building a Markov random field model to identify the optimal target patches that are sharp, similar to the original patches, and are coherent with their neighboring patches within the overlapped regions. To recover an all-in-focus video, an iterative framework is utilized, in which the reconstructed video of each iteration is substituted in the next iteration. Finally, we employ the idea of a bilateral filter to temporally smooth the reconstructed video. The experimental results and the comparison with the previous works demonstrate the effectiveness of our method.

To introduce a novel laparoscopic training system with a continuously perfused ex-vivo porcine liver for hepatobiliary surgery. Existing models for laparoscopic training, such as box trainers and virtual reality simulators, often fail to provide holistic training and real haptic feedback. We have formulated a new training system that addresses these problems. Real-Liver Laptrainer consists of a porcine liver, customized mannequin, ex-vivo machine perfusion system, and monitoring software. We made a detailed comparison of Real-Liver Laptrainer with the LapSim virtual reality simulator and the FLS Trainer Box systems. Five laparoscopic surgeons assessed the new system on multiple features. We assessed the performances of 43 trainees who used the new system to perform laparoscopic cholecystectomy (LC) three times. Real-Liver Laptrainer offered more functions and better tactile feedback than the FLS or LapSim system. All five surgeons graded the quality of the new system as realistic. The utility of the system for training was scored as 3.6 ± 1.1 on a scale of 1–5. Between the first and third attempts, the number of successfully performed LCs increased (9 vs 14 vs 23; P = .011), while the numbers of liver damage incidents (25 vs. 21 vs. 18, P = .303) and gallbladder perforations decreased (17 vs. 12 vs. 9, P = .163). The mean LC operation time significantly decreased (63 vs. 50 vs. 44, P

The influence of gravity on flow boiling poses a challenge to the development of two-phase thermal systems for space applications. The present study investigates the heat transfer coefficient of flow boiling in a mini-channel evaporator in both horizontal and vertically downward flow directions to observe the effect of gravity. The evaporator has 23 channels that are 624 μm in width and 923 μm in depth. The experiments show that nucleate boiling dominates the heat transfer. The heat transfer and flow patterns for the two directions differ when the mass flow rate is less than 264.3 kg/m2 s and the heat flux is less than 3.0 W/cm2. The experimental results are compared with five general correlations. The outlet Froude number is more suitable for correlating the results than existing gravity-independent criteria. Gravity may influence the heat transfer through instabilities and changes in the flow patterns.

An experiment was conducted to investigate the effect of dietary pyridoxine on the gene expression of appetite-regulating peptides in the hypothalamus and gastrointestinal tract of rabbits. Thirty-two rabbits were randomly divided into 2 treatments for 8 weeks (16 replicates/group and 1 rabbit/replicate). The treatments were fed a basal diet (control, measured pyridoxine content is 4.51 mg/kg) and the basal diet with a pyridoxine supplementation at 10 mg/kg (pyridoxine, measured pyridoxine content is 14.64 mg/kg). The results showed that dietary pyridoxine did not significantly alter the mRNA levels of neuropeptide Y, agouti related peptide, pro-opiomelanocortin and cocaine, amphetamine regulated transcript, peptide YY and cholecystokinin in arcuate nucleus, peptide YY in jejunum and ileum, and cholecystokinin in duodenum, jejunum and ileum (P > 0.05). Compared with the control, the mRNA levels of corticotropin-releasing hormone and melanocortin 4 receptor in paraventricular nuclei and peptide YY in duodenum were significantly decreased after pyridoxine treatment (P 0.05). In conclusion, the appetite genes of melanocortin 4 receptor and corticotropin-releasing hormone in paraventricular nuclei and peptide YY in duodenum are involved in the pyridoxine-caused hyperphagia.

Heterogeneous Bistatic Radars (BR) have different sensing ranges and couplings of sensing regions, which provide more flexible coverage for the boundary at complex terrain such as across rivers and valleys. Due to the Cassini oval sensing region of a BR and the coupling of sensing regions among different BRs, the coverage problem of BR sensor networks is very challenging. Existing works in BR barrier coverage focus mainly on homogeneous BR sensor networks. This paper studies the heterogeneous BR placement problem on a line barrier to achieve optimal coverage. 1) We investigate coverage differences of the basic placement sequences of heterogeneous BRs on the line barrier, and prove the optimal basic placement spacing patterns of heterogeneous BRs. 2) We study the coverage coupling effect among adjacent BRs on the line barrier, and determine that different placement sequences of heterogeneous BR transmitters will affect the barrier&rsquo, s coverage performance and length. The optimal placement sequence of heterogeneous BR barrier cannot be solved through the greedy algorithm. 3) We propose an optimal BRs placement algorithm on a line barrier when the heterogeneous BR transmitters&rsquo, placement sequence is predetermined on the barrier, and prove it to be optimal. Through simulation experiments, we determine that the different placement sequences of heterogeneous BR transmitters have little influence on the barrier&rsquo, s maximum length. Then, we propose an approximate algorithm to optimize the BR placement spacing sequence on the heterogeneous line barrier. 4) As a heterogeneous barrier case study, a minimum cost coverage algorithm of heterogeneous BR barrier is presented. We validate the effectiveness of the proposed algorithms through theory analysis and extensive simulation experiments.

© 2018 Association for Computing Machinery. In a contemporary data center, Linux applications often generate a large quantity of real-time system call traces, which are not suitable for traditional host-based intrusion detection systems deployed on every single host. Training data mining models with system calls on a single host that has static computing and storage capacity is time-consuming, and intermediate datasets are not capable of being efficiently handled. It is cumbersome for the maintenance and updating of host-based intrusion detection systems (HIDS) installed on every physical or virtual host, and comprehensive system call analysis can hardly be performed to detect complex and distributed attacks among multiple hosts. Considering these limitations of current system-call-based HIDS, in this article, we provide a review of the development of system-call-based HIDS and future research trends. Algorithms and techniques relevant to system-call-based HIDS are investigated, including feature extraction methods and various data mining algorithms. The HIDS dataset issues are discussed, including currently available datasets with system calls and approaches for researchers to generate new datasets. The application of system-call-based HIDS on current embedded systems is studied, and related works are investigated. Finally, future research trends are forecast regarding three aspects, namely, the reduction of the false-positive rate, the improvement of detection efficiency, and the enhancement of collaborative security.