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We propose and develop a high-sensitivity fiber Bragg grating (FBG) accelerometer based on a flexible hinge for vibration sensing. The proposed method employs a 1 mm FBG that is inscribed pointwise using a femtosecond laser such that the resultant stress concentration at the FBG is improved significantly by reducing the distance between the two bonding points of the FBG structure. Through theoretical calculations and finite element simulations, the relationship between sensitivity and distance was found to be inversely proportional. Using this structure, the sensitivity was enhanced to 804 pm/g at 15 Hz and 30 Hz. The resonant frequency of the proposed accelerometer is 102 Hz, and the working frequency bandwidth is from 10 to 50 Hz. The performance of the accelerometer allows detection of vibrations in seismic explorations with high reliability.

Transdermal drug delivery helps to circumvent the first-pass effect of drugs and to avoid drug-induced gastrointestinal tract irritation, compared with oral administration. With the extensive application of ethosomes in transdermal delivery, the shortages of them have been noticed continuously. Due to the high concentration of volatile ethanol in ethosomes, there are problems of drug leakage, system instability, and ethosome-induced skin irritation. Thus, there is a growing interest in the development of new generations of ethosomal systems. Functionalized ethosomes have the advantages of increased stability, improved transdermal performances, an extended prolonged drug release profile and site-specific delivery, due to their functional materials. To comprehensively understand this novel carrier, this review summarizes the properties of functionalized ethosomes, their mechanism through the skin and their modifications with different materials, validating their potential as promising transdermal drug delivery carriers. Although functionalized ethosomes have presented a greater role for enhanced topical delivery, challenges regarding their design and future perspectives are also discussed.

S. Fluhrer, I. Mantin and A. Shamir (FMS) had put forward a fascinating attack of the key of RC4 in Wired Equivalent Privacy (WEP) protocol on the basis of special initialization vectors (IVs) of pattern (3, 255, v). Inspired by the FMS attack, this paper tries to find new pattern of IVs that can be used for recovering the key of RC4 in WEP. We discovered that IVs of new pattern (v, 257-v, 255) can also be used in the FMS attack in a very similar way. Combining the new pattern with the previous pattern (3, 255, v) could result in a higher proportion of IVs that can be exploited in the FMS attack.

OBJECTIVE The clinical utility of screening for pediatric metabolic syndrome (MetS) in children and adolescents is still controversial. We examined the performance of pediatric MetS vs. clustering of cardiovascular risk factors (which are the components of MetS) for predicting high carotid intima-media thickness (cIMT) in children and adolescents. METHODS Participants included 2427 children and adolescents aged 6-17 years from population-based studies in three countries (Brazil, China and Italy). Pediatric MetS was defined using either the modified National Cholesterol Education Program Adult Treatment Panel III criteria or the modified International Diabetes Federation criteria. Clustering of cardiovascular risk factors was calculated as the sum of five components of MetS (i.e. central obesity, elevated blood pressure, elevated triglycerides, reduced HDL-cholesterol and elevated fasting blood glucose). High cIMT was defined as cIMT at least 95th percentile values for sex and age developed from European children. RESULTS Presence of one, two or at least three cardiovascular risk factors (using the National Cholesterol Education Program Adult Treatment Panel III criteria), as compared with none, was associated with gradually increasing odds of high cIMT [odds ratios (95% confidence intervals): 1.60 (1.29-1.99), 2.89 (2.21-3.78) and 4.24 (2.81-6.39), respectively]. High cIMT was also associated with presence (vs. absence) of MetS (odds ratio = 2.88, 95% confidence interval = 1.95-4.26). However, clustering of cardiovascular risk factors predicted high cIMT markedly better than MetS (area under the curve of 0.66 vs. 0.54, respectively). Findings were similar using the International Diabetes Federation criteria for pediatric MetS. CONCLUSION In children and adolescents, a graded score based on five cardiovascular risk factors (used to define MetS) predicted high cIMT markedly better than MetS. These findings do not support the clinical utility of MetS for screening youth at increased cardiovascular risk, as expressed in this study by high cIMT.

Metaphor plays an important role in human communication, which often conveys and evokes sentiments. Numerous approaches to sentiment analysis of metaphors have thus gained attention in natural language processing (NLP). The primary focus of these approaches is on linguistic features and text rather than other modal information and data. However, visual features such as facial expressions also play an important role in expressing sentiments. In this paper, we present a novel neural network approach to sentiment analysis of metaphorical expressions that combines both linguistic and visual features and refer to it as the multimodal model approach. For this, we create a Chinese dataset, containing textual data from metaphorical sentences along with visual data on synchronized facial images. The experimental results indicate that our multimodal model outperforms several other linguistic and visual models, and also outperforms the state-of-the-art methods. The contribution is realized in terms of novelty of the approach and creation of a new, sizeable, and scarce dataset with linguistic and synchronized facial expressive image data. The dataset is particularly useful in languages other than English and the approach addresses one of the most challenging NLP issue: sentiment analysis in metaphor.

Edge computing is a product of the evolution of IoT and the development of cloud computing technology, providing computing, storage, network, and other infrastructure close to users. Compared with the centralized deployment model of traditional cloud computing, edge computing solves the problems of extended communication time and high convergence traffic, providing better support for low latency and high bandwidth services. With the increasing amount of data generated by users and devices in IoT, security and privacy issues in the edge computing environment have become concerns. Blockchain, a security technology developed rapidly in recent years, has been adopted by many industries, such as finance and insurance. With the edge computing capability, deploying blockchain platforms/applications on edge computing platforms can provide security services for network edge environments. Although there are already solutions for integrating edge computing with blockchain in many IoT application scenarios, they slightly lack scalability, portability, and heterogeneous data processing. In this paper, we propose a trusted edge platform to integrate the edge computing framework and blockchain network for building an edge security environment. The proposed platform aims to preserve the data privacy of the edge computing client. The design based on the microservice architecture makes the platform lighter. To improve the portability of the platform, we introduce the Edgex Foundry framework and design an edge application module on the platform to improve the business capability of Edgex. Simultaneously, we designed a series of well-defined security authentication microservices. These microservices use the Hyperledger Fabric blockchain network to build a reliable security mechanism in the edge environment. Finally, we build an edge computing network using different hardware devices and deploy the trusted edge platform on multiple network nodes. The usability of the proposed platform is demonstrated by testing the round-trip time (RTT) of several important workflows. The experimental results demonstrate that the platform can meet the availability requirements in real-world usage scenarios.

To determine the safety of hydromorphone hydrochloride solution for long term use in patient controlled analgesia by comparing the microbial contamination of preparations made under hospital ward dispensing room and pharmacy intravenous admixture service operating environment. Hydromorphone hydrochloride solutions were prepared in the patient controlled analgesia pump using 0.9 % sodium chloride under ward dispensing room or pharmacy intravenous admixture service operating environments. The solutions were stored at 25° and 37° and inspected for clarity and tested for bacterial endotoxin contamination for 15 d. The hydromorphone hydrochloride solution prepared under the ward dispensing room remained clear and endotoxin levels were below detection limits for 9 d. On d 11, this solution appeared turbid with slightly increased bacterial endotoxin levels. No remarkable observations were noted in the solution prepared under the pharmacy intravenous admixture service environment for the duration of the experiment. Hydromorphone hydrochloride solution prepared under the ward dispensing room conditions remained safe for use for only 9 d after preparation. On the other hand, the solution prepared under pharmacy intravenous admixture service remained suitable for use for longer as no contamination was observed for the duration of the study.

Information dissemination matters, both on an individual and group level. For college students who are physically and mentally immature, they are more sensitive and susceptible to unnormal information like rumors. However, current researches focus on large-scale online message sharing networks like Facebook and Twitter, rather than profile the information dissemination on campus, which fail to provide any references for daily campus management. Against this background, we propose a framework to generate the information dissemination network on campus, named ANSWER (cAmpus iNformation diSsemination netWork gEneRation), based on multimodal data including behavior data, appearance data, and psychological data. The construction of the ANSWER is listed as four steps. First, we use a convolutional autoencoder to extract the students’ facial features. Second, we process the behavior data to construct a friendship network. Third, heterogeneous information is embedded in the low-dimensional vector space by using network representation learning to obtain embedding vectors. Fourth, we use the deep learning model to predict. The experiment results show that ANSWER outperforms other methods in multiple feature fusion and prediction of information dissemination relationship performance.

Facial appearance matters in social networks. Individuals frequently make trait judgments from facial clues. Although these face-based impressions lack the evidence to determine validity, they are of vital importance, because they may relate to human network-based social behavior, such as seeking certain individuals for help, advice, dating, and cooperation, and thus they may relate to centrality in social networks. However, little to no work has investigated the apparent facial traits that influence network centrality, despite the large amount of research on attributions of the central position including personality and behavior. In this paper, we examine whether perceived traits based on facial appearance affect network centrality by exploring the initial stage of social network formation in a first-year college residential area. We took face photos of participants who are freshmen living in the same residential area, and we asked them to nominate community members linking to different networks. We then collected facial perception data by requiring other participants to rate facial images for three main attributions: dominance, trustworthiness, and attractiveness. Meanwhile, we proposed a framework to discover how facial appearance affects social networks. Our results revealed that perceived facial traits were correlated with the network centrality and that they were indicative to predict the centrality of people in different networks. Our findings provide psychological evidence regarding the interaction between faces and network centrality. Our findings also offer insights in to a combination of psychological and social network techniques, and they highlight the function of facial bias in cuing and signaling social traits. To the best of our knowledge, we are the first to explore the influence of facial perception on centrality in social networks., 11 pages, 8 figures

Ion funnel is a new-style ion guider which can reduce spatial divergence and energy dispersity of the transmission ions by using radio frequency (RF) electric field to confine the ions radially and the direct current (DC) axial electric field to move the ions toward the exit, and thus it can greatly increase the ion transmission efficiency and improve the sensitivity of the mass spectrometry. Since ion funnel was invented in 1997, it has attracted a close attention of mass spectrometry scientists all over the world. Ion funnel has been used in various kinds of mass spectrometry, and built a bridge with high efficiency ion transmission between low vacuum ionization source and high vacuum mass analyzer. In this paper, the principle, technology development, and application progress of ion funnel are reviewed, and the future prospects are prospected.

Signal enhancement technology (sub-pixel interpolation) is used to obtain SO2 column concentrations for Guangdong Province in China from 2005 to 2016. The high resolution (2 km × 2 km) data used was obtained via a remote sensing satellite (Ozone Monitoring Instrument) and verified by comparing it with average annual SO2 data recorded in ground monitoring stations. The correlation was found to be up to 0.95. Moreover, the data was cross-correlated with national and regional inventories of pollution sources. The results show that the regional characteristics of the spatial distribution obtained are consistent and the detailed characteristics are highly coincidental. Based on this, the new and detailed spatiotemporal variation was analyzed and the effect of emission reduction in urban agglomerations on the SO2 concentration in the Pearl River Delta (PRD) region of China investigated. The results demonstrate that the distribution of SO2 pollution in the PRD has been transformed over the period studied. In the early stages, it had a traditional high-concentration type of distribution (with agglomeration areas like Guangzhou and Foshan as high-concentration pollution centers) and this has changed to the currently-observed low-concentration decentralized type of distribution (mainly distributed along administrative boundaries). In the last 10 years, significant SO2 emission reduction has occurred in prefecture-level cities, e.g., Foshan, Zhongshan, and Guangzhou (with emission-reduction amplitudes of 71%, 65%, and 57%, respectively). Foshan and Zhongshan are the top two prefecture-level cities in the PRD region in terms of significant reduction in rate of SO2 contribution. The SO2 contribution rate fell from 17% to 13% in Foshan and from 16% to 10% in Zhongshan. However, the relative contribution rates in Zhaoqing and Huizhou increased from 7% to 11% and from 6% to 10%, respectively. The size of the emission reduction and changes in SO2 contribution rates in the prefecture-level cities in the PRD region show that the government’s efforts to improve air quality have had a significant effect.

OBJECTIVE It has been argued that metabolically healthy obesity (MHO) does not increase cardiovascular disease (CVD) risk. This study examines the association of MHO with carotid intima-media thickness (cIMT), a proxy of CVD risk, in children and adolescents. RESEARCH DESIGN AND METHODS Data were available for 3,497 children and adolescents aged 6–17 years from five population-based cross-sectional studies in Brazil, China, Greece, Italy, and Spain. Weight status categories (normal, overweight, and obese) were defined using BMI cutoffs from the International Obesity Task Force. Metabolic status (defined as “healthy” [no risk factors] or “unhealthy” [one or more risk factors]) was based on four CVD risk factors: elevated blood pressure, elevated triglyceride levels, reduced HDL cholesterol, and elevated fasting glucose. High cIMT was defined as cIMT ≥90th percentile for sex, age, and study population. Logistic regression model was used to examine the association of weight and metabolic status with high cIMT, with adjustment for sex, age, race/ethnicity, and study center. RESULTS In comparison with metabolically healthy normal weight, odds ratios (ORs) for high cIMT were 2.29 (95% CI 1.58–3.32) for metabolically healthy overweight and 3.91 (2.46–6.21) for MHO. ORs for high cIMT were 1.44 (1.03–2.02) for unhealthy normal weight, 3.49 (2.51–4.85) for unhealthy overweight, and 6.96 (5.05–9.61) for unhealthy obesity. CONCLUSIONS Among children and adolescents, cIMT was higher for both MHO and metabolically healthy overweight compared with metabolically healthy normal weight. Our findings reinforce the need for weight control in children and adolescents irrespective of their metabolic status.

A threshold visual cryptography scheme, denoted as ( k, n )-VCS for short, can encrypt a secret image into n share images. The physical stacking of any k share images can reveal the secret content while any less than k share images will leak no information of the secret content. Besides the threshold access structure, general access structure VCSs are studied in the following works. In this paper, we first build a hyper star access structure VCS from a hyper star without center access structure VCS. Then we build a normal form hyper star access structure VCS from a full threshold VCS, and prove that its pixel expansion is optimal. At last, we propose a method of constructing general access structure VCS from its several decomposed normal form hyper star access structure VCSs.

Educational big data is becoming a strategic educational asset, exceptionally significant in advancing educational reform. The term educational big data stems from the rapidly growing educational data development, including students' inherent attributes, learning behavior, and psychological state. Educational big data has many applications that can be used for educational administration, teaching innovation, and research management. The representative examples of such applications are student academic performance prediction, employment recommendation, and financial support for low-income students. Different empirical studies have shown that it is possible to predict student performance in the courses during the next term. Predictive research for the higher education stage has become an attractive area of study since it allowed us to predict student behavior. In this survey, we will review predictive research, its applications, and its challenges. We first introduce the significance and background of educational big data. Second, we review the students' academic performance prediction research, such as factors influencing students' academic performance, predicting models, evaluating indices. Third, we introduce the applications of educational big data such as prediction, recommendation, and evaluation. Finally, we investigate challenging research issues in this area. This discussion aims to provide a comprehensive overview of educational big data.

In this paper, a hot-wire flowmeter based on the Extrinsic Fabry–Perot Interferometer cascaded with a Fiber Bragg Grating (FBG-EFPI) is presented. The flowmeter measured the flow velocity by measuring the temperature variation based on the hot-wire effect. The FBG-EFPI sensor spectrum has a high peak slope (169.47 dB/nm), which makes it excellent for measuring temperature. The detection range of the sensor is 100-3100 L/h and the resolution of the sensor is 10 L/h.

In the past decade, the researchers paid more attention to the cheating problem in visual cryptography (VC) so that many cheating prevention visual cryptography schemes (CPVCS) have been proposed. In this paper, the authors propose a novel method, which first makes use of Latin square to prevent cheating in VC. Latin squares are utilised to guide the choosing of authentication regions in different rows and columns of each divided block of the shares, which ensures that the choosing of authentication regions is both random and uniform. Without pixel expansion, the new method provides random regions authentication in each divided block of all shares. What is important is that the proposed method is applicable to both ( k , n )-deterministic visual cryptography scheme (( k , n )-DVCS) and ( k , n )-probabilistic visual cryptography scheme (( k , n )-PVCS). Experimental results and properties analysis are given to show the effectiveness of the proposed method.

An optical fiber Fabry–Perot interferometer (FPI) based on poly (ethyleneimine) (PEI)/ poly (vinyl alcohol) (PVA) blend membrane is proposed and realized experimentally as a sensor for the pressure of CO $_{2}$ in the atmosphere. The functional material layer based on PEI/PVA blend polymer exhibits reversible optical path difference change because of absorption and release of CO $_{2}$ gas molecules. The cavity of the FPI is fabricated by coating a 15- $\mu$ m PEI/PVA blend film on the end-face of a cleaved single-mode fiber. An interference spectrum with fringe contrast of 19.5 dB and free spectra range of 33.15 nm is obtained. The proposed FPI sensor is sensitive to the changes of concentration of CO $_{2}$ , as well as a sensitivity of 0.281 nm/ $\%$ within an interval which ranges from 7.6 $\%$ to 86.9 $\%$ .

Prediction of drug candidates for mutagenicity is a regulatory requirement since mutagenic compounds could pose a toxic risk to humans. The aim of this investigation was to develop a novel prediction model of mutagenicity by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test sets. For comparison, the recursive partitioning classifier prediction model was also established and other various reported prediction models of mutagenicity were collected. Among these methods, the prediction performance of naïve Bayes classifier established here displayed very well and stable, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set I set were 89.1±0.4% and 77.3±1.5%, respectively. The concordance of the external test set II with 446 marketed drugs was 90.9±0.3%. In addition, four simple molecular descriptors (e.g., Apol, No. of H donors, Num-Rings and Wiener) related to mutagenicity and five representative substructures of mutagens (e.g., aromatic nitro, hydroxyl amine, nitroso, aromatic amine and N-methyl-N-methylenemethanaminum) produced by ECFP_14 fingerprints were identified. We hope the established naïve Bayes prediction model can be applied to risk assessment processes; and the obtained important information of mutagenic chemicals can guide the design of chemical libraries for hit and lead optimization.

A compact fiber-optic accelerometer was proposed and demonstrated experimentally based on Fabry–Perot interference (FPI). The device consists of a suspended-core fiber embedded in a hollow-core fiber, forming an enclosed cavity structure. A short section of multi-mode fiber (MMF) was spliced on the leading-in single-mode fiber (SMF), which worked as a micro lens to focus the light to decrease the transmission loss. A well-defined interference spectrum was achieved by a low-fitness FP interferometer formed by both the end-face of lead-in fiber and the end-face of suspended-core fiber. Thanks to the outstretched FP cavity by suspended-core fiber, the sensor is highly sensitive to vibration along the fiber axis. Moreover, a one-dimensional mechanical transducer was used to improve the frequency band of the sensor. By the side-band filtering technology, the vibration was detected and analyzed by a simple intensity interrogation technology.

A compact optical fiber Fabry-Perot interferometer is proposed and demonstrated for ultrasound wave (UW) measurement. The sensor consists of a suspended cantilever in a sealed hollow-core fiber, while the end-face of the leading-in fiber together with the end-face of the suspended fiber act as two reflection mirrors and form an air cavity. A short section of graded index fiber is also employed as a micro-lens to improve the fringe contrast of the interference spectral pattern. Due to the suspended fiber structure, the sensor presents high sensitivity to UW loading, which allows the freely suspended fiber to be stretched and compressed easily. By spectral side-band filtering technology, a simple intensity interrogation technology is used for UW demonstration. Moreover, the sealed sensor structure avoids disturbance from other environment parameters, thus presenting good stability for UW detection.

We share experiences and lessons learned in participating the annual Agile Robotics for Industrial Automation Competition (ARIAC). ARIAC is a simulation-based competition focusing on pushing the agility of robotic systems for handling industrial pick-and-place challenges. Team RuBot started competing from 2019, placing 2nd place in ARIAC 2019 and 3rd place in ARIAC 2020. The article also discusses the difficulties we faced during the contest and our strategies for tackling them. Video of system sketches: https://youtu.be/7H7YLeJz2zE .

There is much interest in double rotor electric machines due to their versatile configurations and performance characteristics arising from the flexibility of having a pair of rotors. Double rotor machines show promising application prospects in advanced hybrid electric vehicle powertrains due to the requirement of dual electromechanical ports in such systems. Integrating these powertrain systems with double rotor machines not only brings design freedom in component layout, but also reduces the number of parts and thus improves compactness. The switched reluctance family of double rotor machines offers unique characteristics in terms of simple structure and no permanent magnets and thus is a strong candidate for such applications. By introducing the segmented rotor design to double rotor switched reluctance machines, a unique design with shared stator back-iron is made possible, achieving increased machine compactness. This paper discusses the design, analysis, and experimental validation of a double segmented rotor switched reluctance machine and compares the design against a target double rotor SRM specification.

A novel optical fiber strain sensor, consisting of a section of fiber Bragg grating cascaded with a Fabry–Perot interferometer is proposed and experimentally demonstrated. The sensing principle relies on the detection of strain-induced changes of the optical intensity. With the assistance of a 3d printed spring, our sensor structure enables a large strain measuring range up to 1.5^107 μ e . the temperature response has also been detected, and the temperature-induced intensity perturbation is less than 0.01dB/ ∘ C from 20 °C to 100 °C. The proposed strain sensor has many advantages such as large measuring range, low temperature cross-sensitivity, simple structure, and ease of fabrication, which make it a competitive candidate for strain measurement under a certain temperature.

This study describes the development of a new methodology for assessment of indoor comfort in buildings. The assessment not only includes the objective environmental information but also subjective feeling information. It is based on the calculation of two indexes: objective assessment (OA) and subjective assessment (SA). The results of OA and SA are standardized in a unified scale by fuzzy fusion and adaptive fusion separately. Starting from the values of OA and SA indexes, both of them are integrated by fuzzy inference decision to comprehensive comfort results. The proposed method allows the classification of the indoor comfort level. The methodology would therefore help for an assessment in the context of building assessment, where satisfactory indoor conditions are sought, improving environmental and economic performance of the building.

Li-doped TiO2/SO42− nanoparticles was successfully synthesized via a simple calcinination process in a vacuum environment using Ti(SO4)2 and LiBr as precursors, and were characterized by TEM, XRD, IR, DLS, XPS and UV-vis (DRS). Li doping can reduce the diameters of TiO2 nanoparticles and affect the surface chemical forms and structures. The as-prepared photocatalysts with different LiBr contents exhibited a notably enhanced degradation efficiency for methylene blue, and exhibited the highest photocatalytic activity under UV light when the molar doping ratio of Li was 0.0125. Moreover, the most photocatalytically efficient sample also showed much higher activity for eliminating methylene blue under visible light (380 < λ < 700 nm) by applying a negative bias than P25 and the control samples without applying a negative bias. The introduced negative bias electrostatic fields could not only render TiO2 responsive to visible light, but was also able to increase the lifetime of the photo-excited charges in the doped semiconductor. This provides a facile, fast and universal method to rapidly degrade organic materials based on the Franz–Keldysh effect and the synergetic effects of the electrostatic force.

Novel drug delivery systems have previously never been used in the formulation of any crude unfractionated traditional Chinese medicine. In the present study, a multi-unit drug delivery system (MUDDS) for a Chinese medicine Niuhuang Xingxiao Wan (NXW) was prepared using micro/nanotechnologies to enhance the bioavailability and efficacy. NXW was formulated into four units, that is, realgar, frankincense and myrrh oil (FMO), musk, and bezoar. The four units were processed using the wet ball milling, high-pressure homogenization, liquid nitrogen freezing-ultracentrifugation trituration, and dry grinding methods, respectively. After formulation, the four independent units prepared were encapsulated together to obtain the final NXW-MUDDS. Pharmacokinetic studies showed that the area under the plasma concentration-time curve (AUC), terminal half-life (T1/2), and time to reach the peak plasma concentration (Tmax) following administration of NXW-MUDDS were 5.21, 1.96, and 1.99 times higher, respectively, than that of NXW. The in vivo antitumor activity assay showed that the efficacy of NXW-MUDDS was significantly higher (P

Drug-induced myelotoxicity usually leads to decrease the production of platelets, red cells, and white cells. Thus, early identification and characterization of myelotoxicity hazard in drug development is very necessary. The purpose of this investigation was to develop a prediction model of drug-induced myelotoxicity by using a Naive Bayes classifier. For comparison, other prediction models based on support vector machine and single-hidden-layer feed-forward neural network methods were also established. Among all the prediction models, the Naive Bayes classification model showed the best prediction performance, which offered an average overall prediction accuracy of $$94 \pm 0.9~\%$$ for the training set and $$82 \pm 2.5~\%$$ for the external test set. The significant contributions of this study are that we first developed a Naive Bayes classification model of drug-induced myelotoxicity adverse effect using a larger scale dataset, which could be employed for the prediction of drug-induced myelotoxicity. In addition, several important molecular descriptors and substructures of myelotoxic compounds have been identified, which should be taken into consideration in the design of new candidate compounds to produce safer and more effective drugs, ultimately reducing the attrition rate in later stages of drug development.

An optical fiber humidity sensor based on an optical Fabry–Perot interferometer is proposed and experimentally demonstrated. The sensor is constructed by a short section of hollow-core fiber coated with a polyimide (PI) film. Taking advantage of the direct response of the PI film, a sensitivity of up to 1.309 nm/%RH can be achieved in the humidity change range from 40% RH to 80% RH. The temperature sensitivity is measured to be 43.57 pm/°C when the temperature changes from 25°C to 55°C. Because of its simple structure, fast response time, convenient production, and good reproducibility, the proposed sensor will be competitive in the field of cultural relic humidity monitoring and pharmaceutical storage.

Background: Pediatric blood pressure (BP) levels are typically assigned to categories when they exceed sex-, age-, and height-specific 90th (elevated) and 95th percentile (high) cutoffs. Given the number of stratum, there are hundreds of cutoffs for defining elevated and high BP that make it cumbersome to use in clinical practice. In 2017 the American Academy of Pediatrics (AAP) recommended simplified cutoffs of ≥120/80 mmHg and ≥130/80 mmHg be used to diagnose elevated BP and high BP, respectively, in clinical practice for adolescents aged 13-17 years. Accordingly, we suggest cutoffs of ≥110/70 mmHg and ≥120/80 mmHg be used for elevated BP and high BP among children aged 6-12 years. The aim of this study was to evaluate the utility of the simplified cutoffs for pediatric BP in determining high carotid intima-media thickness (cIMT) in children and adolescents. Methods: Data were from 6 population-based cross-sectional studies in Brazil, China, Greece, Italy, Spain and the UK. A total of 4280 children and adolescents aged 6-17 years were included. High cIMT was defined as cIMT ≥sex-, age- and cohort-specific 90th percentile cutoffs. Logistic regression model, receiver operating characteristic (ROC) curve and net reclassification improvement (NRI) methods were used to compare the performance of the simplified definition with three established complex definitions (i.e. 2017 AAP guideline, 2004 Fourth Report, and 2016 international BP references) in determining high cIMT (≥sex-, age- and cohort-specific 90th percentile of cIMT) in children and adolescents. Results: Compared with those who had normal BP, participants with high BP defined using either of the three complex definitions or simplified definition had similar odds of high cIMT, with odds ratios and 95% confidence intervals of 1.46 (1.15-1.86), 1.47 (1.10-1.96), 1.42 (1.12-1.80), and 1.65 (1.25-2.17), respectively, after adjustment for sex, age, race/ethnicity, body mass index, high density lipoprotein-cholesterol, triglyceride, and fasting blood glucose. The similar utility of all four high BP definitions in determining high cIMT were further confirmed by area under the ROC curve and NRI methods (all p for difference >0.05). Interpretation: The simplified BP definition performed similarly with three complex definitions in determining high cIMT in children and adolescents. The simplified definition offers a similarly accurate but more convenient means to identify pediatric high BP in clinical practice. Funding: Dr Bo Xi was supported by the National Natural Science Foundation of China (81673195). Dr. Costan G. Magnussen was supported by a National Heart Foundation of Australia Future Leader Fellowship (100849). Declaration of Interest: None Ethical Approval: Each study was approved by the corresponding institutional review board, and written informed consent was obtained from all study participants and their parents or guardians.

In this paper, we analyze the problems faced by current video surveillance systems in the safety detection of port operators, and systematically research the methods of information extraction and operator behavior warnings. We collect a large number of port operation videos, and establish a large-scale port operations scene dataset named Harbor Dataset. We propose a deep learning based object detection algorithm to carry out the safety detection of the operator in the harbor scene. By comparing the detected personnel position and the location of the calibration area, we can judge the violation of the operator. We also use real-time tracking and data retention of offending operators to reduce the operation of illegal operators. Experiments show that our method yields a competitive result on Harbor Dataset in detecting the safety of the operating personnel and calibrating the dangerous operation areas.

According to the problem that the cohesiveness and durability of permeable asphalt pavement is poorer than common dense gradation asphalt mixtures, on the premise of improving the permeability, in order to meet the service performance and durability of permeable asphalt pavement, through the investigation of technical requirements on permeable asphalt pavement raw material in Japan and several endemic standards of China where permeable pavement technology is mature, combined with climatic characteristics in Tianjin, the technical requirements suggested values of permeable asphalt mixture suitable for Tianjin are put forward.

This paper presents a method of human detection by Meanshift based on depth map. By analyzing and comprehensively applying segmentation method based on height information to extract moving target and remove the background information from depth map, then find the region of interest (ROIs) with moving target, thus through mean shift method to achieve real-time detection of targets (pedestrian). Depth image has nothing to do with color space and not suffer from the factors such as illumination, shadow effect. In this paper, using the depth image pattern recognition is a good way to overcome the difficulties of visible light image pattern recognition often encountered.

A (k, n) visual cryptographic scheme (VCS) is a secret sharing method, which encodes a secret image S into n share images in such a way that the stacking of any more than or equal to k share images will reveal S, while any less than k share images provide no information about S. Kafri and Keren (1987) firstly implements (2,2)-VCS by random grids (RG-based VCS). Compared to conventional solutions of VCS, RG-based VCSs need neither extra pixel expansion nor complex codebook design. However, for a long period, RG-based VCSs are confined to (2,2) access structure. Until recently, Chen and Tsao (2011) proposed the first (k, n) RG-based VCS. In this paper, we improve the contrast of Chen and Tsao (2011)'s threshold scheme. The experimental results show that the proposed scheme outperforms Chen and Tsao (2011)'s scheme significantly in visual quality.

In order to reduce the pixel expansion of visual cryptography scheme (VCS), many size invariant visual cryptography schemes (SIVCS's) were proposed. However, most of the known SIVCS's have bad visual quality and thin line problems, hence the known SIVCS's are only suitable to encrypt coarse secret images. In this paper, we notice that the variance of the darkness levels of the pixels also reflects the visual quality of the recovered secret image, as well as the average contrast. We verify, analytically and experimentally, the effectiveness of the variance to be a criterion for evaluating the visual quality of the recovered secret image. Furthermore, we propose two multi-pixel encryption size invariant visual cryptography schemes (ME-SIVCS's) which improve the visual quality of the recovered secret image by reducing the variance of the darkness levels. In addition, the proposed ME-SIVCS's can be used to encrypt fine secret images since they avoid some known thin line problems. Experimental results and comparisons are also given to show the effectiveness of the proposed ME-SIVCS's. Finally, we give suggestions on obtaining good visual quality for the recovered secret image.

In traditional visual cryptography scheme (VCS), each pixel of secret image is encrypted into m(\( \geqslant 1 \)) subpixels in the share images. Unfortunately, recovered image will be distorted when the pixel expansion is not a square number. In order to reveal the information of the secret image faithfully, aspect ratio of the recovered image should be kept invariant in VCS. In this paper, we investigate the encryption process of traditional VCS and find that it is able to be divided into mapping stage and size invariant VCS (SIVCS) stage. By improving algorithms of these two stages respectively, we propose a novel construction of aspect ratio invariant VCS (ARIVCS) with flexible pixel expansion. Experimental results show the effectiveness of our scheme that it avoids the defects found in previous research works such as the details distortion problem, thin line problems and blurry edge problem. Meanwhile, our scheme eliminates the jaggy phenomenon to a certain extent when the pixel expansion is large which contributes to improving the visual quality of ARIVCS significantly.

A visual cryptography scheme VCS encodes a secret image into several share images, such that stacking sufficient number of shares will reveal the secret while insufficient number of shares provide no information about the secret. The beauty of VCS is that the secret can be decoded by human eyes without needing any cryptography knowledge nor any computation. Variance is first introduced by Hou et al. in 2005 to evaluate the visual quality of size invariant VCS. Liu et al. in 2012 thoroughly verified this idea and significantly improved the visual quality of previous size invariant VCSs. In this paper, we first point out the security defect of Hou et al.'s multi-pixel encoding method MPEM that if the secret image has simple contours, each single share will reveal the content of that secret image. Then we use variance to explain the above security defect.

License Plate Recognition (LPR) which has been extensively studied recently is becoming one important part of Intelligent Transportation Systems (ITS). It is not only applied to public security monitoring, but also applied to a red light shot, speeding violation paparazzi, parking system and so on. The present paper introduces an intelligent parking management system based on LPR, recognizing license plate automatically at the parking lot access and realizing vehicle information integrated management conveniently. The software part is developed with VC++, QT and Microsoft Office Access Database. In the system, LPR is carried out through video streaming frame by frame to choose the best result with a high speed. After accurate LPR, the vehicle information, such as LP number, LP color, car type and access time, will be stored in system database. In addition, the system interface is designed very friendly and simple for administrators to operate, which can largely improve the whole performance of LPR system. Experimental results show that this parking management system can achieve high correct rate at 95%, and can be applied to real-time implementation

Conventional moving objects detection algorithm associated with visible image is often affected by the change of moving objects’ shapes, illumination conditions and is also influenced by complex backgrounds, shadow of moving objects, moving objects of self-occlusion or mutual-occlusion phenomenon. This paper presents a method of human detection by mean shift based on depth map. By analyzing and comprehensively applying segmentation method based on height information to extract moving target and remove the background information from depth map, the region of interest (ROI) with moving target should be found, then through mean shift method the goal of real-time objects (pedestrian) detection can be achieved eventually. In this paper, using the depth image pattern recognition is a good way to overcome the difficulties that visible light image pattern recognition often encounters. The depth image pixel value is only related to the distance from the surface of the object to the view window plane. Therefore, depth image has nothing to do with color space and does not suffer from the factors such as illumination, shadow effect. In addition, the mean shift targets detection method with high efficiency and fast speed features can solve the problems of low identification efficiency and poor real-time performance based on traditional pedestrian detection system to a certain extent. Our algorithm using mean shift method based on depth information has been tested on several image sequences and shown to achieve robust and real-time detection.

For visual cryptography scheme (VCS), normally, the size of the recovered secret image will be expanded by m( ≥ 1) times of the original secret image. In most cases, m is not a square number, hence the recovered secret image will be distorted. Sometimes, m is too large that will bring much inconvenience to the participants to carry the share images. In this paper, we propose two visual cryptography schemes which simulated the principle of fountains. The proposed schemes have two advantages: non-distortion and flexible (with respect to the pixel expansion). Furthermore, the proposed schemes can be applied to any VCS that is under the pixel by pixel encryption model, such as VCS for general access structure, color VCS and extended VCS, and our VCS does not restrict to any specific underlying operation. Compared with other non-distortion schemes, the proposed schemes are more general and simpler, real flexible and has competitive visual quality for the recovered secret image.

This paper presents an intelligent parking system for detecting and recognizing license plates automatically, programming with VC++ and QT. In the proposed algorithm, License Plate (LP) location and correction is realized by using high vertical edge characteristic of image and method of horizontal edge detection. After LP segmentation and recognition, the vehicle information which taking LP as the primary key will be stored in system database. Experimental results show that the proposed system can realize License Plate Recognition (LPR) accurately and is applied to real-time implementation for a very short execution time.

Visual cryptography is a type of secret sharing which encodes a secret image into several shadow images in such a way that the stacking of certain images printed on transparencies will reveal the secret. The decryption is done directly by the human visual system without any extra calculations. Most of previous researches essentially handle only binary images, as the underling encoding matrices are all Boolean matrices. For gray-level image, we need to halftone it into binary image before encoding. Although binary image can be used to simulate gray-level image, its visual quality is deteriorated, especially for fine images. The first part of this paper presents a method to provide much more gray-levels than previous schemes, given the same pixel expansion, and thus establishes the visual cryptography scheme suitable for natural images. The second part of this paper presents a visual voting scheme that need no counting process and guarantees anonymity.

3D video representation with depth maps is one efficient framework of 3DTV/free viewpoint television (FTV). 3D effect can be reconstructed based on human visional principle of binocular disparity. Texture image plus depth map provides an efficient solution of 3DTV application and real-time depth estimation is one barrier due to huge processing time consumption on complexity algorithm in the processing. An efficient hardware implementation of depth estimation is proposed for real time execution in this paper. The estimation system includes dual-channel video capture, image preprocessing, density pixel matching, pixel correlation and post processing. Each step of the system takes advantage of the hardware resource and adopts pipeline architecture to reduce the latency of combinational logic module at every stage and increase the throughput of the disparity extraction module. Experimental results demonstrate that the proposed method reduces the processing time and improves the ability of high resolution processing. The system can reach 131fps and Full HD (1920×1080) resolution, is suitable for adaptive real-time depth estimation and can be used as a subsystem embedded in the capture system of stereo vision.

A novel printed compact wide-band diversity antenna for mobile handsets is proposed in this paper. The antenna comprises two back-to-back G-shaped monopoles placed symmetrically with respect to a T-shaped and dual inverted-L-shaped ground plane. The measured results show that the proposed diversity antenna operates in a very wide bandwidth of 1200 MHz starting from 1700 MHz to 2900 MHz. In the above bands, the isolations of the prototype are better than -15 dB. The antenna can provide pattern diversity to combat multipath fading.

A visual cryptography scheme (VCS) is a secret sharing method, for which the secret can be decoded by human eyes without needing any cryptography knowledge nor any computation. To the best of our knowledge, there are two different definitions of basis matrix (k,n)-VCS. The definition of unconditional secure basis matrix (k,n)-VCS is the generally accepted one, and has been widely used since the pioneer work of Naor and Shamir in 1994, while the definition of stacking secure basis matrix (k,n)-VCS is relatively new, and has been used in many studies in recent years. Our study shows that the above two definitions are actually equivalent. Furthermore, we generalize the equivalence relation to general access structure basis matrix VCS and general access structure size invariant VCS. But the equivalence relation does not hold for non-basis matrix (k,n)-VCS.

For visual cryptography scheme (VCS), normally, the size of the recovered secret image will be expanded by m(≥1) times of the original secret image. In most cases, m is not a square number, hence the recovered secret image will be distorted. Sometimes, m is too large that will bring much inconvenience to the participants to carry the share images. In this paper, we propose a visual cryptography scheme which simulated the principle of fountains. The proposed scheme has two advantages: non-distortion and flexible (with respect to the pixel expansion). Furthermore, the proposed scheme can be applied to any VCS that is under the pixel by pixel encryption model, such as VCS for general access structure, color VCS and extended VCS, and our VCS does not restrict to any specific underlying operation. Compared with other non-distortion schemes, the proposed scheme is more general and simpler, real flexible and has competitive visual quality for the recovered secret image.

A visual cryptography scheme (VCS) is a secret sharing method, for which the secret can be decoded by human eyes without needing any cryptography knowledge nor any computation. In their pioneer work, Naor and Shamir mentioned that encrypting a block of pixels simultaneously may result in better result. Inspired by that idea, we first define multi-pixel encryption visual cryptography scheme (ME-VCS), which encrypts a block of t (1≤t) pixels at a time. Then we give an upper bound of the overall contrast of ME-VCS. We also give a lower bound of the pixel expansion of (n,n,t)-ME-VCS. At last, we built a contrast-optimal ME-VCS from a contrast-optimal VCS and built an optimal (n,n,t)-ME-VCS from an optimal (n,n)-VCS.

A dual-band printed diversity antenna for UMTS and 2.4/5.2-GHz WLAN operation is proposed. The antenna consists of two back-to-back F-shaped monopoles placed symmetrically with respect to a protruding T-shaped ground plane. Across the two bands, the antenna has two highly decoupled ports and can provide pattern diversity to combat multipath fading.

Considering the importance of pedestrian detection in a variety of applications such as advanced robots and intelligent surveillance systems, this paper presents an improved pedestrian detection method through integrating Haar-like features, AdaBoost algorithm, histogram of oriented gradients (HOG) descriptor, and support vector machine (SVM) classifiers, in which the head and shoulder information is utilized especially. Due to the fast training speed of Haar-like features and the high detection efficiency of HOG features, the proposed method can classify pedestrians precisely with higher speed. Experimental results validated the efficiency and effectiveness of the proposed algorithm.