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Objective: To investigate epidemiological characteristics of outpatients and disease spectrum in the dermatology department during the COVID-19 epidemic Methods: A retrospective comparison of outpatient visits, gender, age and disease types in the dermatology department of Wuhan No.1 Hospital was performed between COVID-19 epidemic period (from 23th January 2020 to 15th April 2020) and the same period in 2019. Enumeration data were analyzed by Pearson's chi-square test. Results: During the COVID-19 epidemic, the number of outpatient visits to the dermatology department of the hospital decreased markedly, and the average daily number of outpatient visits (236 visits/day) was only 8.81% of that during the same period in 2019 (2 678 visits/day) ;the ratio of male to female patients was reversed from 1:1.37 in 2019 to 1.16:1 in 2020;the proportions of patients aged 0-6, 7-12, 13-17 and 18-45 years significantly decreased compared with those in 2019 (all P 69 years significantly increased (both P < 0.001). During the COVID-19 epidemic, there were 171 types of skin diseases in the dermatology outpatient department, and the number of disease categories decreased compared with that during the same period in 2019 (442 types) ;the number of patient visits for allergic skin diseases, erythematous papulosquamous skin diseases, viral infectious skin diseases and bacterial infectious skin diseases significantly increased compared with that during the same period in 2019 (all P < 0.001), while the number of patient visits for sebaceous and sweat gland disorders, pigmented skin diseases and physical skin diseases significantly decreased (all P < 0.001). Conclusion: Compared with the same period in 2019, the number of outpatient visits, patient sex ratio, age distribution and disease types in the dermatology department have undergone marked changes during the COVID-19 epidemic, and this study provides a reference for healthcare workers in dermatology department to respond to various epidemics and natural disasters in the future. Copyright © 2021 by the Chinese Medical Association.

The focal plane camera is the core component of the Wide Field-of-view Cherenkov/fluorescence Telescope Array (WFCTA) of the Large High-Altitude Air Shower Observatory (LHAASO). Because of the capability of working under moonlight without aging, silicon photomultipliers (SiPM) have been proven to be not only an alternative but also an improvement to conventional photomultiplier tubes (PMT) in this application. Eighteen SiPM-based cameras with square light funnels have been built for WFCTA. The telescopes have collected more than 100 million cosmic ray events and preliminary results indicate that these cameras are capable of working under moonlight. The characteristics of the light funnels and SiPMs pose challenges (e.g. dynamic range, dark count rate, assembly techniques). In this paper, we present the design features, manufacturing techniques and performances of these cameras. Finally, the test facilities, the test methods and results of SiPMs in the cameras are reported here., Comment: 45 pages, 21 figures, article

Patients with persistent asthma often show poor adherence to inhaled corticosteroids (ICS). Shared decision-making can improve adherence rates in this population. Patient decision aids (PDAs) are tools to facilitate shared decision-making. To date, only one PDA, developed in a Canadian French-speaking population, exists for patients considering ICS maintenance therapy. This PDA has been culturally adapted in this study to contextualize to the needs of multi-ethnic Asian patients in Singapore. This study explored the views of local clinicians on the content, design and implementation of this newly-adapted PDA.24 clinicians, who were purposively sampled from polyclinics and a tertiary institution, were interviewed on the content, design and implementation of the PDA. The interviews were audio-recorded, transcribed and analyzed via thematic analysis.Clinicians generally accepted the design of the PDA. They suggested for the target users to be patients on Step 2 of GINA guidelines and the number of options to be reduced from four to two (do nothing or start inhaled corticosteroids). Moreover, they supported including a list of values for patients to select from given that Asian patients often do not articulate their values readily. The addition of more visual aids, the production of multilingual Asian editions and the involvement of nurses to administer the PDA was also suggested.The PDA was culturally-adapted with local clinicians' perspectives to target multi-ethnic Asian patients with persistent asthma (Step 2 GINA guidelines). The main changes include a list of values and addition of visual aids.

Background Cutaneous lupus erythematosus (CLE) is a heterogeneous autoimmune disease with clinical sequelae such as itching, dyspigmentation and scarring. Objectives We applied a previously described modular analysis approach to assess the molecular heterogeneity of patients with CLE. Methods Whole-blood transcriptomes of RNA sequencing data from a racially and ethnically diverse group of patients with CLE (n = 62) were used to calculate gene co-expression module scores. An unsupervised cluster analysis and k-means clustering based on these module scores were then performed. We used Fisher's exact tests and Kruskal-Wallis tests to compare characteristics between patient clusters. Results Six unique clusters of patients with CLE were identified from the cluster analysis. We observed that seven inflammation modules were elevated in two clusters of patients with CLE. Additionally, these clusters were characterized by interferon, neutrophil and cell-death signatures, suggesting that interferon-related proteins, neutrophils and cell-death processes could be driving the inflammatory response in these subgroups. Three different clusters had a predominant T-cell signature, which were supported by lymphocyte counts. Conclusions Our data support a diverse molecular profile in CLE that further adds to the clinical variations of this skin disease, and may affect disease course and treatment selection. Future studies with a larger and diverse cohort of patients with CLE are warranted to confirm these findings.

The main scientific goal of the LHAASO WFCTA experiment is to measure the cosmic ray energy spectra and composition from 10 TeV to 1 EeV. Cherenkov photons in the extensive air shower measured by the SiPM camera of Cherenkov telescopes can be used to reconstruct the cosmic ray energy. The absolute calibration of the camera is a crucial step to achieve the accurate measurement of the cosmic ray energy spectrum. A multi-wavelength cylindrical illuminator based on LEDs is developed and mounted inside the telescope to calibrate and monitor the camera, and the illuminator’s stability is better than 0.5% under the temperature variation from -26 to 26 ° C. A portable probe with a single photoelectron resolution of 21.6% is developed. After calibration by National Institute of Metrology, China (NIM), the probe is taken to the LHAASO site to measure the absolute photon density of the cylindrical illuminator inside the telescope. Based on the illuminator with known photon density, the photon conversion factor of the camera can be calibrated, and the overall calibration uncertainty is less than 2.6%.

Purpose To investigate whether computer-aided design (CAD) and 3-dimensional printing technology can assist in accurate completion of ulna-radius proximal rotational osteotomy in congenital radioulnar synostosis (CRUS). Methods We treated 1 right arm and 4 left arms of 4 boys with a mean age of 5.2 years (range, 4.3–6.0 years) between July 2018 and April 2019. Computed tomography (CT) scans of the forearm were performed on the children before surgery. Using the CT data, the pronation angle of the forearm was measured. An individualized dial with a matching forearm diameter was designed before surgery to control the angle of the rotational osteotomy . Ulna and radius models, and individualized dials, were prepared for each patient using 3-dimensional printing technology. Preoperative simulated surgery was performed using the 3-dimensional printed models. During the surgery, 2 Kirschner wires were used as operating levers for rotation, and rotational angle correction was precisely controlled using the dial. The cast and internal fixation were removed after x-ray examination showed that the osteotomy had healed, about 5 weeks after surgery. Results The rotational osteotomies were completed in a single operation, and the correction angle was 60°. No complications occurred after the operation. All patients showed functional improvements in activities of daily living. Conclusions For CRUS patients, models and dials made with CAD and 3-dimensional printing technology can assist in precise rotational osteotomy. Type of study/level of evidence Therapeutic V.

Thermal imaging is an essential tool in a wide variety of research areas. In this work we demonstrate high-throughput double-wavelength temperature distribution imaging using a modified single-pixel camera without the requirement of a beam splitter (BS). A digital micro-mirror device (DMD) is utilized to display binary masks and split the incident radiation, which eliminates the necessity of a BS. Because the spatial resolution is dictated by the DMD, this thermal imaging system has the advantage of perfect spatial registration between the two images, which limits the need for the pixel registration and fine adjustments. Two bucket detectors, which measures the total light intensity reflected from the DMD, are employed in this system and yield an improvement in the detection efficiency of the narrow-band radiation. A compressive imaging algorithm is utilized to achieve under-sampling recovery. A proof-of-principle experiment was presented to demonstrate the feasibility of this structure.

Conventional compressive sampling methods cannot efficiently exploit structured sparsity for sampling multidimensional signals like video sequences. In this paper, we propose a fully decomposable compressive sampling model that adopts the Kronecker product framework to exploit the structured sparsity spanning multidimensional signals. It enables efficient sampling in a progressive fashion by retaining the block-diagonal feature of Kronecker products. A synthetic sensing matrix is developed for joint optimization over sampling signals with multiple dimensions. Instead of adjusting global Gram matrix, separable minimization of mutual coherence in multiple dimensions is jointly formulated for a stable recovery with enhanced convergence rate. Sampling rate allocation is considered to improve recovery performance based on the decomposable compressive sampling. The proposed model is employed in video acquisition for temporal sparsity along motion trajectory. Experiment results show that the proposed model can improve the recovery performance with a reduced number of necessary samples in comparison to the state-of-the-art methods.

An increasing number of healthcare issues arise from unsafe abnormal behaviors such as falling and staggering of a rapidly aging population. These abnormal behaviors, often coming with abrupt movements, could potentially be life-threatening if unnoticed; real-time, accurate detection of this sort of behavior is essential for timely response. However, it is challenging to achieve generic, while accurate, abnormal behavior detection in real time with moderate sensing devices and processing power. This paper presents an innovative system as a solution. It utilizes primarily visual data for detecting various types of abnormal behaviors due to accuracy and generality of computer vision technologies. Unfortunately, the volume of the recorded video data is huge, which is preventive to process all in real time. We propose to use elder-carried mobile devices either by a dedicated design or by a smartphone, equipped with inertial sensor to trigger the selection of relevant video data. In this way, the system operates in a trigger verify fashion, which leads to selective utilization of video data to guarantee both accuracy and efficiency in detection. The system is designed and implemented using inexpensive commercial off-the-shelf sensors and smartphones. Experimental evaluations in real-world settings illustrate our system’s promise for real-time accurate detection of abnormal behaviors.

The LHAASO-WFCTA experiment, which aims to observe cosmic rays in the sub-EeV range using the fluorescence technique, uses a new generation of high-performance telescopes. To ensure that the experiment has excellent detection capability associated with the measurement of the energy spectrum, the primary composition of cosmic rays, and so on, an accurate geometrical reconstruction of air-shower events is fundamental. This paper describes the development and testing of geometrical reconstruction for stereo viewed events using the WFCTA (Wide Field of view Cherenkov/Fluorescence Telescope Array) detectors. Two approaches, which take full advantage of the WFCTA detectors, are investigated. One is the stereo-angular method, which uses the pointing of triggered SiPMs in the shower trajectory, and the other is the stereo-timing method, which uses the triggering time of the fired SiPMs. The results show that both methods have good geometrical resolution; the resolution of the stereo-timing method is slightly better than the stereo-angular method because the resolution of the latter is slightly limited by the shower track length.

Massive visual traffic data have become available recently. Though it opens the realm of intelligent traffic analysis, processing the data in a timely manner is difficult yet critical to time sensitive decisions, which are typical to traffic related management. In this paper, we study time-bounded aggregation analytics on large visual traffic data including traffic images and videos. We first find that current MapReduce framework can not work well due to two challenges: first, significant dual diversities exist on data distributions and processing time; second, apriori knowledge on these distributions and time costs are not always available. However, we also observe spatial and temporal locality on data values and processing time. Based on the examination, we design Traffic At-a-Glance (TaG), an augmented MapReduce framework for time-bounded traffic analytics jobs. Particularly, we propose a novel sampling algorithm that exploits traffic data localities and stratifies samples based on data distributions and processing time. It runs in an iterative, adaptive manner without apriori knowledge. Moreover, we propose a heuristic scheduling algorithm with considerations of batch processing overhead. Further, we refine the load balancing mechanism based on data processing time locality to respect job time bounds. In addition, we extend TaG to well handle traffic videos by sampling video data based on motion information encoded in the videos. We implement TaG on Hadoop and conduct extensive experiments on a large visual traffic dataset. The evaluations on different data sizes show TaG is able to achieve high accuracy within time bounds.

This paper presents a transductive multicomponent video segmentation algorithm, which is capable of segmenting the predefined object of interest in the frames of a video sequence. To ensure temporal consistency, a temporal coherent parametric min-cut algorithm is developed to generate segmentation hypotheses based on visual cues and motion cues. Furthermore, each hypothesis is evaluated by an energy function from foreground resemblance, foreground/background divergence, boundary strength, and visual saliency. In particular, the state-of-the-art R-convolutional neural network descriptor is leveraged to encode the visual appearance of the foreground object. Finally, the optimal segmentation of the frame can be attained by assembling the segmentation hypotheses through the Monte Carlo approximation. In particular, multiple foreground components are built to capture the variances of the foreground object in shapes and poses. To group the frames into different components, a tree-structured graphical model named temporal tree is designed, where visually similar and temporally coherent frames are arranged in branches. The temporal tree can be constructed by iteratively adding frames to the active nodes by probabilistic clustering. In addition, each component, consisting of frames in the same branch, is characterized by a support vector machine classifier, which is learned in a transductive fashion by jointly maximizing the margin over the labeled frames and the unlabeled frames. As the frames from the same video sequence follow the same distribution, the transductive classifiers achieve stronger generalization capability than inductive ones. Experimental results on the public benchmarks demonstrate the effectiveness of the proposed method in comparison with other state-of-the-art supervised and unsupervised video segmentation methods.

The two life-threatening signs of anaphylactic shock (AS) are severe arterial hypotension and bronchospasm. Guidelines recommend epinephrine as first-line treatment. Arginine vasopressin (AVP) has been proposed as an alternative if epinephrine does not correct arterial hypotension. These two drugs may have beneficial, neutral or deleterious effects on airflow either directly or by modifying factors that regulate vasodilatation and/or edema in the bronchial wall.To compare the effects of epinephrine and AVP on airflow and airway leakage in a rat model of AS.Thirty-two ovalbumin-sensitized rats were randomized into four groups: control (CON), AS without treatment (OVA), AS treated with epinephrine (EPI), and AS treated with AVP (AVP). Mean arterial pressure (MAP), respiratory resistance and elastance and microvascular leakage in the airways were measured.All OVA rats died within 20 minutes following ovalbumin injection. Ovalbumin induced severe arterial hypotension and airway obstruction (221 ± 36 hPa.s.LEpinephrine was superior to AVP for alleviating the airway response in a rat model of AS. When bronchospasm and severe arterial hypotension are present during AS, epinephrine should be the drug of choice.

“© © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”; International audience; In a complex project, an organization is often not able to manage all aspects alone, since it does not have all the required competences, skills or resources. In this case, alliance formation can be a solution for project development. Apart from simply managing complex projects, firms also find it important to increase innovativeness by sharing knowledge between partners in alliances. However, in alliances one of the difficulties is achieving effective collaboration: mis-communication, missing skills or missing resources create a high risk that the project fails to achieve its goals. In order to decrease the risk of failure, and to overcome potential collaboration inefficiency, partner selection takes place among firms that are able to communicate well while at the same time having the required knowledge to achieve their objectives. The important role of partner selection in alliances justifies the increased attention given to substantial criteria in alliance formation. Proposing a knowledge-based framework aimed at increasing the understanding of partner selection in alliances is the contribution of this paper. This knowledge can be gained by evaluating projects from a technological point of view to estimate their challenging degrees, and studying the partners background in past projects or partnerships. This paper structured to propose hypotheses based on a systematic literature review. At the heart of the hypotheses is a consideration of the needs of the project, and starting there allows us to characterize alliance formation and partner selection using a new typology. Finally, a novel framework is proposed that could help decision-makers in the managerial aspects of partner selection in alliance formation. The framework also presents considerable potential for future studies.

To cope with the higher prevalence of asthma and other non-communicable diseases without compromising on quality of care, a Singapore public primary care institution has adopted the Chronic Care Model (CCM). This retrospective cohort study aimed to describe the proportion of patients with well-controlled asthma (based on Asthma Control Test score ≥20) between 2010 and 2016 in association with their management based on the CCM (which covers the polyclinic clinical information system, self-management measures, system re-design and decision support). Data were retrieved from the Singapore National Asthma Programme (SNAP) and institutional clinical quality databases of eight local polyclinics in eastern and southern Singapore. The data were aggregated, analysed and presented in proportions against monthly polyclinic attendances for asthma. From 2010 to 2016, the total asthma attendances increased by 31% from 27,345 to 35,731, with the highest rise among patients aged ≥60 years. The proportion of patients with good asthma control rose from 71.4% to 80.9%; those who received rescue therapy for acute exacerbations fell from 15.8% to 11.7% and those referred to emergency departments after failed rescue therapy decreased from 0.7% to 0.6%. The proportion of patients with updated asthma action plans increased from 66.7% to 73.4% (proxy for self-management). The overall health and process outcomes of asthma seemed to have improved with multiplex of system-based interventions relating to the introduction of CCM in a public primary healthcare institution in Singapore.

Miles procedure is often necessary for patients with low rectal carcinoma. However, this operation often affects the quality of life of patients, to evaluate the advantages of improved operation (anal reconstruction), the quality of life and survival between patients undergoing anal reconstruction and patients undergoing traditional lower abdominal stoma after radical resection were analyzed. The clinical data of 43 patients with low situated rectal carcinoma were retrospectively analyzed. 23 patients with left lower abdominal stoma after radical resection (Miles procedure) were divided into group A, and 20 patients with reconstruction of the anus in situ after radical resection were in group B. All patients were investigated by the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 and QLQ-CR38 questionnaire, the clinical data are recorded. Independent sample T test was used to analyze the difference in quality of life between group A and group B at 3, 6, and 12 months after surgery, and Kaplan–Meier was used to compare the difference in overall survival between group A and group B. The results of T test showed that there were statistical significance in global health status and physical functioning between group A and group B at 3 and 6 months, but no statistical significance at 12 months (P = 0.024, P = 0.019, P = 0.115 for global health status; P = 0.004, P = 0.006, P = 0.065 for physical functioning, respectively). Emotional functioning and social functioning were also statistically significant between group A and group B at 3, 6, and 12 months (P = 0.041, P = 0.040, P = 0.034 for Emotional functioning; P = 0.020, P = 0.009, P = 0.032 for social functioning, respectively). This study also found that there was no statistical significance in body image and sexual functioning between group A and group B at 3 months, but there was statistical significance at 6 and 12 months(P = 0.098, P = 0.035, P = 0.045 for body image; P = 0.110, P = 0.048, P = 0.047 for sexual functioning, respectively). There were statistically significant about sexual enjoyment and defecation problems at 3, 6, and 12 months (P = 0.023, P = 0.028, P = 0.050 for sexual enjoyment; P = 0.013, P = 0.011, P = 0.050 for defecation problems, respectively).The results of Kaplan–Meier showed that the overall survival (OS) between group A and group B was not statistically significant (χ2 = 0.600, P = 0.439). There was no difference in survival time between group A and group B, but compared with the patients with left lower abdominal stoma(group A), the quality of life was better in patients with reconstruction of the anus in situ (group B). It is significant to improve the traditional lower abdominal stoma operation.

Compared with the traditional geosynchronous orbit earth and medium earth orbit satellite communication systems, the low earth orbit (LEO) satellite communication system has the real-time communication capability of all time, all weather and all terrain, which is the only way to achieve seamless coverage of global mobile communication. A seasonal autoregressive integrated moving average (S-ARIMA) model is used for satellite load forecast. Traffic load measured by the first N satellites is processed to obtain stationary sequence via difference and seasonal difference. Then on the basis of traffic load forecast, the corresponding resource management strategy is selected in light load scenario or heavy load scenario. Light load scenario is limited-coverage, satellite parameter adjustment can enlarge the coverage of beams to reduce resource waste as far as possible. Heavy load scenario is limited-capacity, satellite parameter adjustment can narrow beam coverage and reduce the amount of traffic load. Simulation results show that S-ARIMA model can accurately forecast the load of satellites, and the proposed method can improve resource utilization and reduce energy consumption of satellites.

The technology of arranging particles by ultrasound has matured. In recent years, this technology has been used as a basis for arranging particles in a photocurable resin for stereolithography (SL). In order to process the resin doped with particles to obtain a variety of particle arrangement patterns, most of the previous work chose to use different polygonal containers to obtain single-layer fiber angles. In this adjustment mode, the selectivity of the fiber angle is very poor, usually 45°, 90° and other common angles. In this work, we designed and manufactured a new ultrasound-assisted 3D printing platform that can flexibly adjust the thickness of the sandwich and the rotation angle of the sandwich. We will introduce the basic working principle and matching usage of the device, and show some basic print samples.

As a traditional Chinese folk art, Yangliuqing Woodcut New Year (YWNY) paintings with unique artistic symbols and rich artistic values have formed varied artistic styles since century. The purpose of this study is to explore the innovative application of traditional folk art combined with other technologies in the field of fashion and art design. Through literature research and object investigation methods, this paper analyses the subject and artistic characteristics of YWNY paintings, classifies the paintings and creates an image bank. Using the image extraction technology, we extract the characteristic elements with cultural symbols and representative colours and construct the corresponding elements resource libraries. Based on the modern design aesthetic and clothing craft design means, YWNY paintings are flexibly applied to fashion design and other design fields. Fashion trends in combination with the elements in YWNY paintings create works that have regional characteristics, which achieve the creative transformation of Tianjin folk art in fashion clothing design.

The rapid growth of web images presents new challenges as well as opportunities to the task of image understanding. Conventional approaches rely heavily on fine-grained annotations, such as bounding boxes and semantic segmentations, which are not available for web-scale images. In general, images over the Internet are accompanied with descriptive texts, which are relevant to their contents. To bridge the gap between textual and visual analysis for image understanding, this paper presents an algorithm to learn the relations between scenes, objects, and texts with the help of image-level annotations. In particular, the relation between the texts and objects is modeled as the matching probability between the nouns and the object classes, which can be solved via a constrained bipartite matching problem. On the other hand, the relations between the scenes and objects/texts are modeled as the conditional distributions of their co-occurrence. Built upon the learned cross-domain relations, an integrated model brings together scenes, objects, and texts for joint image understanding, including scene classification, object classification and localization, and the prediction of object cardinalities. The proposed cross-domain learning algorithm and the integrated model elevate the performance of image understanding for web images in the context of textual descriptions. Experimental results show that the proposed algorithm significantly outperforms conventional methods in various computer vision tasks.

Human-following robots are important for home, industrial and battlefield applications. To effectively interact with human, a robot needs to locate a person's position and understand his/her motion. Vision based techniques are widely used. However, due to the close distance between human and robot, and the limitation in a camera's field of view, only part of a human body can be observed most of the time. As such, the human motion observed by a robot is inherently ambiguous. Simultaneously identifying the body part being observed and the motion the person undergoing is a challenging problem, and has not been well studied in the past. In this paper, we propose a novel method solving the body part and motion identification problem in a unified framework. The relative position of an observed part with respect to the whole body and the motion type are treated as continuous and discrete labels, respectively, and the most probable labeling is inferred by structured learning. A fast part-distribution estimation is introduced to reduce the computational cost. The proposed approach is able to identify different body parts without explicitly building models for each single part, and to recognize the motion with only partial body observations. The proposed approach is evaluated using actual videos captured by a human-following robot as well as the synthesized videos from the public UCF50 dataset, originally developed for action recognition. The result demonstrates the effectiveness of the approach. HighlightsWe propose a method achieving body part and motion identification simultaneously.Part and motion are treated as combined continuous and discrete labels.We formulate the problem into a structured learning framework.The evaluation is done on actual videos and videos from the public datasets.

SUMMARY Background Few information about the occupational exposures to blood and body fluid (BBF) among blood service workers (BSWs) in blood stations in China are available currently. Objectives To assess current status of occupational exposure to BBF and assess the knowledge about occupational blood-borne pathogen exposures and universal precaution among BSWs in blood donations in China. To understand the incidence of occupational exposure in five blood centres in China. Methods A cross-sectional study was conducted from January 2008 to December 2013. Results There were a total of 99 BBF exposures reported during the study period. The total incidence of BBF exposures was 4·4 per 100 person-years. Higher rates were observed for persons employed less than 5 years and persons less than 45 years old. Nurses have the highest percentage (49·5%) of BBF exposures. BBF exposures occurred most commonly during the afternoon (62·7%). Percutaneous injuries were the most commonly BBF exposures. Most incidents occurred during sharps use (73·4%). The major cause of occupational exposure was that there was no continuous training (48·4%) and improper use of equipment (23·2%). Only 56·6% of BBF exposures have appropriate first aid measures. During this research work, one staff was reported to have seroconvert to syphilis after BBF exposure. Conclusions To reduce BBF exposures, it is urgent to take several effective actions in China, including improved occupational health system, adequate education, administrative support, increased use of standard precautions, better safety devices/products and work practices.

InGaAs/InP avalanche photodiodes (APD) are usually employed as Geiger-mode single photon detector at near-infrared wavelength between 1.0 μm and 1.7 μm. In order to work in the free-running regime rather than gated regime, we demonstrate a feedback quenching integrated circuit to rapidly quench the avalanche and reset the APD. Because this IC is close to the APD, parasitic capacitance is largely reduced, thus reducing the quench-time, reset-time and also the afterpulsing probability. We investigated the free-running single photon detector׳s afterpulsing effect, de-trapping time, dark count rate and detection efficiency and also compared with gated regime operation. After corrected for deadtime and afterpulse, we found the free-running detector performance is comparable with gated regime.

This paper presents a novel video-based face recognition algorithm by using a sequential sampling and updating scheme, named sequential sample consensus. The proposed algorithm aims at providing a sequential scheme that can be applied to streaming video data. Different from existing approaches, the training video sequences serve as the sample space, and the person’s identity in the testing sequence is characterized using an identity probability mass function (PMF) that is sequentially updated. For each testing frame, samples are randomly drawn from the sample space, and the numbers of samples for each identity are determined by the identity PMF. The testing frame is evaluated against the drawn samples to calculate the weights, and the sample weights are used for updating the identity PMF. Benefiting from the sampling procedure, the change in both the numbers and the weights of the samples for each individual leads to quick reaction of the algorithm. The proposed algorithm is robust against misclassification caused by pose variations, and sensitive to identity switching during recognition. The algorithm is evaluated using both public and self-made datasets, and shows better performance than other video-based face recognition approaches.

Coupling beam is a very important component in shear wall structure. However, the reinforced concrete coupling beam does not have an efficient energy dissipation capacity and a stable hysteretic behavior. A new type energy-dissipating coupling beam is proposed in the paper, which has a large energy dissipation capacity and a stable hysteretic behavior. It can be constructed and repaired easily. Models with different shapes were established in a Finite Element Analysis program to simulate the performance of the damper. The hysteretic behaviors of the damper were also numerical analyzed.

BACKGROUND: In contrast to other types of shock, anaphylactic shock decreases cerebral blood flow more than would be expected from severe arterial hypotension, thus potentially affecting survival through brain ischaemia/hypoxia. We hypothesised that epinephrine (EPI) used as a first-line treatment of anaphylactic shock and arginine vasopressin (AVP) proposed in case of EPI refractoriness may have different effects on brain oxygenation. OBJECTIVES: To compare the effect of EPI and AVP on brain oxygenation under similar macro-haemodynamic target values in an anaphylactic shock model. DESIGN: Prospective laboratory study. SETTING: University laboratory. ANIMALS: Male brown Norway rats (n = 27). INTERVENTIONS: Twenty-seven rats were sensitised with ovalbumin (OVA). Twenty rats had anaphylactic shock induced with OVA and were resuscitated with either 0.9% saline (OVA group), EPI (EPI group) or AVP (AVP group). Sensitised control rats received only 0.9% saline and no OVA (CON group). MAIN OUTCOME MEASURES: Mean arterial pressure (MAP), carotid artery blood flow (CaBF), cerebral cortical blood flow (CBF) and hippocampal oxygen partial pressure (PtiO2) were recorded. RESULTS: All rats in the OVA group died within 15 min. EPI and AVP restored comparable levels of MAP, carotid artery blood flow and CBF, and extended survival time. EPI was associated with biologically relevant and significantly (P < 0.05) higher PtiO2 values (nadir values at 20 min: 25.0 ± 2.2 mmHg) compared with the AVP group (14.9 ± 2.0 mmHg). The slopes of the correlations of MAP vs. PtiO2 and CBF were significantly steeper with AVP (more pressure dependence) compared with EPI. By the end of the experiment, hippocampal PtiO2 values between the EPI (24.1 ± 2.1 mmHg) and the AVP (20.8 ± 2.0 mmHg) groups were similar. CONCLUSION: At early, but not at late time points, resuscitation of anaphylactic shock with EPI or AVP to similar MAP and CBF endpoints resulted in hippocampal PtiO2 being significantly higher after EPI. In addition, the PtiO2 after EPI always remained above the threshold for brain hypoxia, whereas PtiO2 after AVP was below the hypoxic threshold most of the time. Because of this early brain hypoxia, AVP may not be the drug of first choice for resuscitation of anaphylactic shock.

In this paper, we present an innovative method of double balanced differential configuration, in which two adjacent single photon avalanche diodes (SPADs) from the same wafer are configured as the first balanced structure, and the output signal from the first balanced stage is subtracted by the attenuated gate driving signal as the second balanced stage. The compact device is cooled down to 236 K to be characterized. At a gate repetition rate of 400 MHz and a 1 550 nm laser repetition rate of 10 MHz, the maximum photon detection efficiency of 13.5% can be achieved. The dark count rate is about 10−4 ns−1 at photon detection efficiency of 10%. The afterpulsing probability decreases with time exponentially. It is shown that this configuration is effective to discriminate the ultra-weak avalanche signal in high speed gating rates.

In this paper, we briefly introduce the history of the Defense Advanced Research Projects Agency (DARPA) Grand Challenge programs with particular focus on the 2012 Robotics Challenge. As members of team DRC-HUBO, we propose different approaches for the Rough-Terrain task, such as enlarged foot pedals and a transformation into quadruped walking. We also introduce a new gait for humanoid robot locomotion to improve stability performance, called the Ski-Type gait. We analyze the stability performance of this gait and use the stability margin to choose between two candidate step sequences, Crawl-1 and Crawl-2. Next, we perform a force/torque analysis for the redundant closed-chain system in the Ski-Type gait, and determine the joint torques by minimizing the total energy consumption. Based on the stability and force/torque analysis, we design a cane length to support a feasible and stable Crawl-2 gait on the HUBO2 humanoid robot platform. Finally, we compare our experimental results with biped walking to validate the Ski-Type gait. We also present our team performance in the trials of the Robotics Challenge.

Radiation induced deterioration in the performance of lithium-ion (Li-ion) batteries can result in functional failures of electronic devices in modern electronic systems. The stability of the Li-ion battery under a radiation environment is of crucial importance. In this work, the surface morphology of the cathode material of a commercial Li-ion battery before and after neutron and gamma ray irradiation was characterized by atomic force microscopy (AFM). We found growth in the particle size of the cathode material in the range of 36–45% as a result of the irradiation. In addition, X-ray diffraction (XRD) patterns revealed a disordering of the crystal structure occurring in the post-irradiation sample. All of these led to a 8.4% capacity loss of the battery for the maximum received irradiation dose (2.744 Mrad) at post-irradiation. The effects of the radiation on the Li-ion battery are discussed in this paper.

In this paper, a new radar waveform based on wavelet packets is proposed. This waveform shows significant advantages over conventional linear frequency modulated waveforms for range and velocity detections of moving targets. The proposed waveform can decouple its envelope and carrier for range and velocity estimations, respectively, because of which the Doppler spread term can be totally removed when estimating velocity and the Doppler effect ignored when estimating range. This way, the proposed waveform produces higher resolution in range or velocity detection. The proposed waveform can be applied to the synthetic aperture radar for improved performance.

Robot follower, a robot following its human operator, has found its application in many areas such as senior care, manufacturing, transportation, and etc. Tracking the target person is a key technique for the follower. In this paper, we present a new method for partial human body tracking, namely human feet tracking. Human feet tracking suffers from weak visual features and appearance variations, making it more critical to continuously update the foot appearance model. We propose to utilize the human motion model to predict foot appearance. It is achieved by first defining a motion phase to each human foot appearance. Due to the fact that the foot appearance across different motion cycles with the same motion phase is similar, we can predict the target appearance using the current motion phase and the target images stored from previous walking cycles. A phase labeled exemplar pool is built to serve the motion phase indexed appearance searching. We combine this phase labeled exemplar pool into particle filtering and have achieved robust human feet tracking.

Nuclear power is playing an important role in energy supply in modern society. The safety of nuclear power plant is thus an important issue. Due to the harmful effects of radiation to human body, robots are used when and where the radiation level in the plant is high. Thus study of the radiation effects on robots, especially on the critical components of robots becomes an urgent issue. In this paper, we investigate the impact of the radiated lithium-ion battery to mobile robots. Mobile robots especially visual tracking guided robot can be used to perform multiple tasks in a nuclear environment. Under radiation, the lithium-ion battery will degrade in terms of capacity, which means if the battery is used as a normal battery, the mobile robot will not perform satisfactorily. We first present the result on the battery degradation due to radiation. Then we study the impact to the robot if it is powered by a radiated battery. The performance of the robot is evaluated under two different conditions, before and after the radiation, and by three different experiments. The radiation effects on the robot performance are shown and analyzed.

A typical robotic system includes a few key components, which are motor, speed reducer, drive, controller, power supply, and mechanical frame, in both robot manipulators and/or mobile robots (wheeled or legged). While all the components are necessary, three individuals are critical and stand out, which are speed reducer, motor, and battery (especially Lithium-ion battery), respectively. The reason for those is twofold: failure of any of them will fail the entire system, and the cost of the three takes more than 80% of the total cost. In the robotic field, we have seen numerous works studying/improving the performance of a robot at the system level but very few focusing at the component level, especially when a robot operates in the nuclear environment. Radiation damage to electronic devices (including H-bridge drives) has long been studied in both theory and experiment. The study on the three critical components has received much less attention. In this talk we report our current studies on the radiation impact to harmonic drive (a speed reducer used in high-end robotic systems), brushless DC motor, and Lithium-ion battery. Our studies have invented new approaches for evaluating the performance of individual components, and reveal how the radiation will affect the performance of the latter. Both theoretical and experimental studies will be presented. The degraded performance of the components may impact or even fail the entire system, regardless of it being a robot manipulator or a mobile robot. We will therefore discuss how to design and develop radiation-hardened components, which can endure a robot in radiation-filled environments.

Nowadays, more and more objects can be represented with electronic identifiers, e.g., people can be recognized from their laptops' MACs, and products can be identified by their RFID numbers. Localizing electronic identifiers is more and more important for a fully digitalized life. However, traditional wireless localization techniques are not satisfactory in performance to determine these electronic identifiers' positions. Some of them require costly hardware to achieve high accuracy and, hence, are not practical. The others are inaccurate and not robust against environmental noises, e.g., RSSI-based localization. Therefore, an accurate and practical approach for localizing electronic identifiers is needed. In this paper, we propose a new localization technique called EV-Loc. In EV-Loc, we make use of visual signals to help improve the accuracy of wireless localization. Our technique fully takes advantage of the high accuracy of visual signals and pervasiveness of electronic signals. To effectively couple these two signals together, we have designed an E-V match engine to find the correspondence between an object's electronic identifier and its visual appearance. We have implemented our technique on mobile devices and evaluated it in the real world. The localization error is less than 1 m. We have also evaluated our approach using large-scale simulations. The results show that our approach is accurate and robust.

Detecting generic object categories in images and videos are a fundamental issue in computer vision. However, it faces the challenges from inter and intraclass diversity, as well as distortions caused by viewpoints, poses, deformations, and so on. To solve object variations, this paper constructs a structure kernel and proposes a multiscale part-based model incorporating the discriminative power of kernels. The structure kernel would measure the resemblance of part-based objects in three aspects: 1) the global similarity term to measure the resemblance of the global visual appearance of relevant objects; 2) the part similarity term to measure the resemblance of the visual appearance of distinctive parts; and 3) the spatial similarity term to measure the resemblance of the spatial layout of parts. In essence, the deformation of parts in the structure kernel is penalized in a multiscale space with respect to horizontal displacement, vertical displacement, and scale difference. Part similarities are combined with different weights, which are optimized efficiently to maximize the intraclass similarities and minimize the interclass similarities by the normalized stochastic gradient ascent algorithm. In addition, the parameters of the structure kernel are learned during the training process with regard to the distribution of the data in a more discriminative way. With flexible part sizes on scale and displacement, it can be more robust to the intraclass variations, poses, and viewpoints. Theoretical analysis and experimental evaluations demonstrate that the proposed multiscale part-based representation model with structure kernel exhibits accurate and robust performance, and outperforms state-of-the-art object classification approaches.

Many mobile robots are expected to work for or interact with humans indoors in applications such as guided shopping, policing, and senior care. Mobile robots' sensors alone are insufficient in order to realize these applications, infrastructural support is needed. Existing support for mobile robots requires heavy or expensive infrastructures with limited scalability or deployment of unsightly lines or magnetic strips. This paper presents S-Mirror, a novel approach that "reflects" various ambient signals towards mobile robots, greatly extending their sensing abilities. S-Mirror forms a network of S-Mirror nodes that mainly reflect visual signals (as well as electronic and acoustic signals) to assist mobile robots. To illustrate the advantages of S-Mirror, we develop a localization approach for mobile robots that integrates S-Mirror and robots' on-board motion sensors. We implement S-Mirror and a mobile robot prototype on commercial off-the-shelf hardware. Our real-world experimental validation shows that S-Mirror achieves accurate timely localization with low network bandwidth consumption as well as robustness and scalability to many mobile robots.

Anaphylactic shock is a rare, but potentially lethal complication, combining life-threatening circulatory failure and massive fluid shifts. Treatment guidelines rely on adrenaline and volume expansion by intravenous fluids, but there is no solid evidence for the choice of one specific type of fluid over another. Our purpose was to compare the time to achieve target mean arterial pressure upon resuscitation using adrenaline alone versus adrenaline with different resuscitation fluids in an animal model and to compare the tissue oxygen pressures (PtiO2) with the various strategies. Twenty-five ovalbumin-sensitised Brown Norway rats were allocated to five groups after anaphylactic shock induction: vehicle (CON), adrenaline alone (AD), or adrenaline with isotonic saline (AD+IS), hydroxyethyl starch (AD+HES) or hypertonic saline (AD+HS). Time to reach a target mean arterial pressure value of 75 mmHg, cardiac output, skeletal muscle PtiO2, lactate/pyruvate ratio and cumulative doses of adrenaline were recorded. Non-treated rats died within 15 minutes. The target mean arterial pressure value was reached faster with AD+HES (median: 10 minutes, range: 7.5 to 12.5 minutes) and AD+IS (median: 17.5 minutes, range: 5 to 25 minutes) versus adrenaline alone (median: 25 minutes, range: 20-30 minutes). There were also reduced adrenaline requirements in these groups. The skeletal muscle PtiO2 was restored only in the AD+HES group. Although direct extrapolation to humans should be made with caution, our results support the combined use of adrenaline and volume expansion for resuscitation from anaphylactic shock. When used with adrenaline the most effective fluid was hydroxyethyl starch, whereas hypertonic saline was the least effective.