bluuebunny/crossref_metadata_2025 huggingface dataset:
A Compact CPW-Fed Dual-Band Planar Monopole Antenna for LTE/2.4-GHz/WiMAX, C-Band and HiperLAN/2 Applications
Authors: Manouare Ahmed Zakaria , Ibnyaich Saida , Idrissi Abdelaziz EL , Ghammaz Abdelilah
Published: December 2018

In this paper, we present the design of a compact planar monopole antenna for dual-band wireless communication applications. The proposed antenna is based on a planar structure composed by a CPW feed line and a rectangular ring with a vertical strip. The designed antenna has a small overall size of [Formula: see text][Formula: see text]mm3. Dual-band characteristics can be obtained by adjusting the distance between the rectangular ring and the ground plane of the CPW feed line, as well as the dimensions of the rectangular ring and the length of the vertical strip. A prototype of the proposed antenna which was fabricated and measured to validate the design reveals that there is a good agreement between the simulation and the experiment. The measured result shows that the antenna has the impedance bandwidths of 610[Formula: see text]MHz (2–2.61[Formula: see text]GHz) and 2600[Formula: see text]MHz (3.18–5.78[Formula: see text]GHz) with a reflection coefficient less than [Formula: see text]10[Formula: see text]dB covering all the LTE 2300, 2.4-GHz band, WiMAX, C-band and HiperLAN/2 applications. In addition, the dual-band monopole antenna exhibits almost omnidirectional radiation patterns and an appreciable gain over the operating frequency bands. Details of the proposed antenna design and both simulated and experimental results are analyzed and discussed.
Selected topics in scalar–tensor theories and beyond
Authors: Quiros Israel
Published: December 2018

Scalar fields have played an important role in the development of the fundamental theories of physics as well as in other branches of physics such as gravitation and cosmology. For a long time, these escaped detection until 2012 when the Higgs boson was observed for the first time. Since then, alternatives to the general theory of relativity like the Brans–Dicke (BD) theory, scalar–tensor theories of gravity and their higher derivative generalizations — collectively known as Horndeski theories — have acquired renewed interest. In the present review, we discuss several selected topics regarding these theories, mainly from the theoretical perspective but with due mention of the observational aspect. Among the topics covered in this review, we pay special attention to the following: (1) the asymptotic dynamics of cosmological models based on the BD, scalar–tensor and Horndeski theories, (2) inflationary models, extended quintessence and the Galileons, with emphasis in causality and stability issues, (3) the chameleon and Vainshtein screening mechanisms that may allow the elusive scalar field to evade the tight observational constraints implied by the solar system experiments, (4) the conformal frames conundrum with a brief discussion on the disformal transformations and (5) the role of Weyl symmetry and scale invariance in the gravitation theories. The review is aimed at specialists as well as at nonspecialists in the subject, including postgraduate students.
MULTI-OBJECTIVE OPTIMIZATION OF EDM PROCESS PARAMETERS FOR MACHINING OF HYBRID ALUMINUM METAL MATRIX COMPOSITES (Al7075/TiC/B4C) USING GENETIC ALGORITHM
Authors: PONAPPA K. , SASIKUMAR K. S. K. , SAMBATHKUMAR M. , UDHAYAKUMAR M.
Published: December 2018

This study deals with the investigation on the effect of Electrical Discharge Machining (EDM) parameters during machining of hybrid composite (Al 7075/TiC/B4C). The optimum process parameters of die sinking EDM like pulse current, pulse duration and gap voltage on metal removal rate, tool wear rate and surface finish were investigated. Full factorial experimental design was selected for experiments. Analysis of variance was employed to study the influence of process parameters and their interactions on response variables. Among the process parameters considered, it was observed that the pulse current was found to be more influential in affecting MRR, TWR and SR. The other parameters have little effect on the response variable. Multi-objective optimization study was also performed using genetic algorithm to find the optimum parameter setting for controversial objective function combination such as high MRR and low SR and High MRR and low TWR. Scanning electron microscope study was performed to study the surface characteristics.
Post-Buckling Analysis of a Uniform Self-Weight Beam with Application to Catenary Riser
Authors: Punjarat Ong-Art , Chucheepsakul Somchai
Published: December 2018

This paper focused on a simply supported beam under uniform self-weight, subjected to an axial force at the roller end. The principle of virtual work-energy was used to formulate the equation for the nonlinear deformation of the beam, which involves the bending strain energy, the virtual work due to self-weight, and the virtual work of the axial force applied at the free-sliding roller end. The work–energy functional was expressed in terms of the arc-length coordinate. The functional vanished, yielding the static equilibrium configuration of the beam — a highly nonlinear problem. Finite element and Newton–Raphson iterative methods were used to solve the problem. The beam theory was extended to large sag analysis of a catenary riser. With this, some interesting features of the various configurations of the catenary riser under various end forces were evaluated.
Effect of substrate temperature on structural and thermoelectric properties of RF magnetron sputtered SnSe thin film
Authors: Chen Zijie , Shen Tong , Li Kangyin , Si Jianxiao
Published: December 2018

SnSe is a potential thermoelectric material, but there are few reports about the thermoelectric properties of the film. In this work, SnSe thin films were deposited on glass substrates by RF magnetron sputtering from SnSe alloy target. The effect of substrate temperature on the structural and thermoelectric properties was investigated. It was found that the columnar grains and the surface roughness of the films increase with increasing the substrate temperature. The film deposited at 558 K exhibited a high crystalline quality and stoichiometric composition, which has a maximum power factor of 1.4[Formula: see text]uWcm[Formula: see text]K[Formula: see text] at 575[Formula: see text]K. The results of this work demonstrate the importance of high substrate temperature to obtain high thermoelectric performance SnSe films.
Finite element analysis of 3D-Printed Acrylonitrile Styrene Acrylate (ASA) with Ultrasonic material characterization
Authors: Yap Yee Ling , Toh William , Koneru Rahul , Chua Zhong Yang , Lin Kehua , Yeoh Kirk Ming , Lim Chin Mian , Lee Jia Shing , Plemping Nur Adilah , Lin Rongming , Ng Teng Yong , Chan Keen Ian , Guang Huanyu , Chan Wai Yew Brian , Teong Soo Soon , Zheng Guoying
Published: December 2018

This paper investigates the orthotropic properties of Fused Deposition Modeling (FDM)-printed Acrylonitrile Styrene Acrylate (ASA) material with different raster configurations. The elastic properties were determined using a non-destructive ultrasonic technique. This technique allows us to deduce the orthotropic elastic constants from the material density and the velocities of the longitudinal and shear waves propagating through the material along different directions. Tensile tests were performed in addition to ultrasonic tests to obtain the yield properties of the ASA material and to validate the elastic constants determined by the ultrasonic tests, which have shown very close correspondence. Finally, numerical verification was performed by comparing the experimental results of the three-point and four-point bending tests with the finite element simulation results which have as input the material properties from the ultrasonic testing. The simulation results have shown excellent agreement with the experimental results, implying that the material properties obtained from the ultrasonic testing were highly accurate comparing to the actual orthotropic elastic properties of the 3D-printed ASA material.
Coherent Integration in Astronomical Interferometry: Theory and Practice
Authors: Mozurkewich David , Jorgensen Anders , van Belle Gerard T.
Published: December 2018

Ground-based long-baseline astronomical interferometry operates in a regime where short integration exposures are demanded by working in the presence of a turbulent atmosphere. To reduce piston noise to less than one radian per aperture, these exposure times are on order 10 milliseconds or less in the visible. It has long been recognized that, in the low signal-to-noise ratio (SNR) regime, the visibility SNR is improved by co-adding frames, each rotated by an estimate of its phase. However, implementation of this technique is challenging. Where it is most needed, on low SNR baselines and when combining multiple phases to estimate the phase for a lower SNR baseline, phase errors reduce the amplitude by a large amount and in a way that has proven difficult to calibrate. In this paper, an improved coherent integration algorithm is presented. A parameterized model for the phase as a function of time and wavelength is fit to the entire data set. This framework is used to build a performance model which can be used in two ways. First, it can be used to test the algorithm; by comparing its performance to theory, one can test how well the parameter fitting has worked. Also, when designing future systems, this model provides a simple way to predict performance and compare it to alternative techniques such as hierarchical fringe tracking. This technique has been applied to both simulated and stellar data.
Amateur
Authors: Cao Chu , Li Zhenjiang , Zhou Pengfei , Li Mo
Published: December 2018

This paper presents Amateur, an augmented reality based vehicle navigation system using commodity smart phones. Amateur reads the navigation information from a digital map, matches it into live road condition video captured by smart phone, and directly annotates the navigation instructions on the video stream. The Amateur design entails two major challenges, including the lane identification and the intersection inference so as to correctly annotate navigation instructions for lane-changing and intersection-turning. In this paper, we propose a particle filter based design, assisted by inertial motion sensors and lane markers, to tolerate incomplete and even erroneous detection of road conditions. We further leverage traffic lights as land markers to estimate the position of each intersection to accurately annotate the navigation instructions. We develop a prototype system on Android mobile phones and test our system in a total number of more than 300km travel distance on different taxi cabs in a city. The evaluation results suggest that our system can timely provide correct instructions to navigate drivers. Our system can identify lanes in 2s with 92.7% accuracy and detect traffic lights with 95.29% accuracy. Overall, the accuracy of the navigation signs placement is less than 105 pixels on the screen throughout the experiments. The feedback from 50 taxi drivers indicates that Amateur provides an improved experience compared to traditional navigation systems.
Mobile Money
Authors: Centellegher Simone , Miritello Giovanna , Villatoro Daniel , Parameshwar Devyani , Lepri Bruno , Oliver Nuria
Published: December 2018

Access to financial institutions is difficult in developing economies and especially for the poor. However, the widespread adoption of mobile phones has enabled the development of mobile money systems that deliver financial services through the mobile phone network. Despite the success of mobile money, there is a lack of quantitative studies that unveil which factors contribute to the adoption and sustained usage of such services. In this paper, we describe the results of a quantitative study that analyzes data from the world's leading mobile money service, M-Pesa. We analyzed millions of anonymized mobile phone communications and M-Pesa transactions in an African country. Our contributions are threefold: (1) we analyze the customers' usage of M-Pesa and report large-scale patterns of behavior; (2) we present the results of applying machine learning models to predict mobile money adoption (AUC=0.691), and mobile money spending (AUC=0.619) using multiple data sources: mobile phone data, M-Pesa agent information, the number of M-Pesa friends in the user's social network, and the characterization of the user's geographic location; (3) we discuss the most predictive features in both models and draw key implications for the design of mobile money services in a developing country. We find that the most predictive features are related to mobile phone activity, to the presence of M-Pesa users in a customer's ego-network and to mobility. We believe that our work will contribute to the understanding of the factors playing a role in the adoption and sustained usage of mobile money services in developing economies.
What is That in Your Hand?
Authors: Fan Junjun , Fan Xiangmin , Tian Feng , Li Yang , Liu Zitao , Sun Wei , Wang Hongan
Published: December 2018

Knowing the object in hand can offer essential contextual information revealing a user's fine-grained activities. In this paper, we investigate the feasibility, accuracy, and robustness of recognizing the uninstrumented object in a user's hand by sensing and decoding her forearm muscular activities via off-the-shelf electromyography (EMG) sensors. We present results from three studies to advance our fundamental understanding of the opportunities that EMG brings in object interaction recognition. In the first study, we investigated the influence of physical properties of objects such as shape, size, and weight on EMG signals. We also conducted a thorough exploration of the feature spaces and sensor positions which can provide a solid base to rely on for future designers and practitioners for such interactive technique. In the second study, we assessed the feasibility and accuracy of inferring the types of grasped objects via using forearm muscular activity as a cue. Our results indicate that the types of objects can be recognized with up to 94.2% accuracy by employing user-dependent training. In the third study, we investigated the robustness of this approach in a realistic office setting where users were allowed to interact with objects as they would naturally. Our approach achieved up to 82.5% accuracy in discriminating 15 types of objects, even when training and testing phrases were purposefully performed on different days to incorporate changes in EMG patterns over time. Overall, this work contributes a set of fundamental findings and guidelines on using EMG technologies for object-based activity tracking.
Painting an Apple with an Apple
Authors: Fujinami Kaori , Kosaka Mami , Indurkhya Bipin
Published: December 2018

We introduce UnicrePaint, a digital painting system that allows the user to paint with physical objects by acquiring three parameters from the interacting object: the form, the color pattern and the contact pressure. The design of the system is motivated by a hypothesis that integrating direct input from physical objects with digital painting offers unique creative experiences to the user. A major technical challenge in implementing UnicrePaint is to resolve the conflict between input and output, i.e., to be able to capture the form and color pattern of contacting objects from a camera, while at the same time be able to present the captured data using a projector. We present a solution for this problem. We implemented a prototype and carried out a user study with fifteen novice users. Additionally, five professional users with art-related backgrounds participated in a user study to obtain insights into how professionals might view our system. The results show that UnicrePaint offers unique experiences with painting in a creative manner. Also, its potentials beyond mere artwork are suggested.
Detecting Conversing Groups Using Social Dynamics from Wearable Acceleration
Authors: Gedik Ekin , Hung Hayley
Published: December 2018

In this paper, we propose a method for detecting conversing groups. More specifically, we detect pairwise F-formation membership using a single worn accelerometer. We focus on crowded real life scenarios, specifically mingling events, where groups of different sizes naturally occur and evolve over time. Our method uses the dynamics of interaction, derived from people's coordinated social actions and movements. The social actions, speaking, head and hand gesturing, are inferred from wearable acceleration with a transfer learning approach. These automatically labeled actions, together with the raw acceleration, are used to define joint representations of interaction between people through the extraction of pairwise features. We present a new feature set based on the overlap patterns of social actions and utilize some others that were previously proposed in other domains. Our approach considers various interaction patterns of different sized groups by training multiple classifiers with respect to cardinality. The final estimation is then dynamically performed by meta-classifier learning using the local neighborhood of the current test sample. We experimentally show that the proposed method outperforms state of the art approaches. Finally, we show how the accuracy of the social action detection affects group detection performance, analyze the effectiveness of features for different group sizes in detail, discuss how different types of features contribute to the final performance and evaluate the effects of using the local neighborhood for meta-classifier learning.
Butterfly
Authors: Han Jinsong , Qian Chen , Yang Yuqin , Wang Ge , Ding Han , Li Xin , Ren Kui
Published: December 2018

RFID tag authentication is challenging because most commodity tags cannot run cryptographic algorithms. Prior research demonstrates that physical layer information based authentication is a promising solution, which uses special features from the physical backscatter signals from tags as their fingerprints. However, our recent studies show that existing physical-layer authentication may fail if feature collection and authentication are conducted in different locations, due to location-dependent noises, environmental factors, or reader hardware differences.

This paper presents a new physical layer authentication scheme, called Butterfly, which is resilient to environment and location changes. Butterfly utilizes a pair of adjacent tags as an identifier of each object. By using the difference between the RF signals of the two tags as their fingerprint, the environmental factors can be effectively canceled. Butterfly is fully compatible with commodity RFID systems and standards. We set up a prototype Butterfly using commodity readers, tags, and RF devices. Extensive experiments show that Butterfly achieves high authentication accuracy for substantially different environments and device changes.
Evolving Needs in IoT Control and Accountability
Authors: Jakobi Timo , Stevens Gunnar , Castelli Nico , Ogonowski Corinna , Schaub Florian , Vindice Nils , Randall Dave , Tolmie Peter , Wulf Volker
Published: December 2018

A key issue for smart home systems is supporting non-expert users in their management. Whereas feedback design on use cases (such as energy feedback) have gained attention, current approaches to providing awareness on the system state typically provide a rather technical view. Long-term investigations of the practices and resources needed for maintaining Do-It-Yourself smart home systems, are particularly scarce. We report on a design case study in which we equipped 12 households with DIY smart home systems for two years and studied participants' strategies for maintaining system awareness, from learning about its workings to monitoring its behavior. We find that people's needs regarding system accountability changed over time. Their privacy needs were also affected over the same period. We found that participants initially looked for in-depth awareness information from the dedicated web-based dashboard. In the later phases of appropriation, however, their interaction and information needs shifted towards management by exception on mobile or ambient displays -- only focusing on the system when things were 'going wrong'. In terms of system accountability, we find that a system's self-declaration should focus on being socially meaningful rather than technically complete, for instance by relating itself to people's activities and the home routines.
Interrupting Drivers for Interactions
Authors: Kim Auk , Choi Woohyeok , Park Jungmi , Kim Kyeyoon , Lee Uichin
Published: December 2018

Auditory-verbal interactions with in-vehicle information systems have become increasingly popular for improving driver safety because they obviate the need for distractive visual-manual operations. This opens up new possibilities for enabling proactive auditory-verbal services where intelligent agents proactively provide contextualized recommendations and interactive decision-making. However, prior studies have warned that such interactions may consume considerable attentional resources, thus negatively affecting driving performance. This work aims to develop a machine learning model that can find opportune moments for the driver to engage in proactive auditory-verbal tasks by using the vehicle and environment sensor data. Given that there is a lack of definition about what constitutes interruptibility for auditory-verbal tasks, we first define interruptible moments by considering multiple dimensions and then iteratively develop the experimental framework through an extensive literature review and four pilot studies. We integrate our framework into OsmAnd, an open-source navigation service, and perform a real-road field study with 29 drivers to collect sensor data and user responses. Our machine learning analysis shows that opportune moments for interruption can be conservatively inferred with an accuracy of 0.74. We discuss how our experimental framework and machine learning models can be used to design intelligent auditory-verbal services in practical deployment contexts.
V-Speech
Authors: Maruri Héctor A. Cordourier , Lopez-Meyer Paulo , Huang Jonathan , Beltman Willem Marco , Nachman Lama , Lu Hong
Published: December 2018

Smart glasses are often used in public environments or industrial scenarios that are relatively noisy. Background noise and sound from competing speakers deteriorate voice communication or performance of automatic speech recognition (ASR). Typically, signal processing techniques are used to reduce noise and enhance voice quality, but they have limitations in performance, hardware and/or computing resources. Voice capturing techniques using bone conducting on the head have been proposed in some experimental and commercial devices, with good robustness against environmental noise, but limited by signal distortions inherent to the capturing method. We present V-Speech, a novel sensing and signal processing solution that enables speech recognition and human-to-human communication in very noisy environments. It captures the voice signal with a vibration sensor located in the nasal pads of smart glasses and performs a transformation to the sensor signal in order to mimic that of a regular microphone in low noise conditions. The signal transformation is key, as it eliminates the "nasal distortion" that is introduced for nasal phonemes in the speech induced vibrations of the nasal bone. The output of V-Speech has low noise, sounds natural, and can be used in voice communication or as input to an off-the-shelf ASR service. We evaluated V-Speech in noise-free and noisy conditions with 30 volunteer speakers uttering 145 phrases and validated its performance on ASR engines and with assessments of voice quality using the Perceptual Evaluation of Speech Quality (PESQ) metric. The results show in extreme noise conditions a mean improvement of 50% for Word Error Rate (WER), and 1.0 on a scale of 5.0 for PESQ. In addition, real life recordings were made under various representative noise conditions, some with sound pressure levels of 93 dBA, which require hearing protection. Subjective listening tests were conducted according to a modified ITU P.835 approach to determine intelligibility, naturalness and overall quality. Under these extreme conditions, where V-Speech achieved 30 dB SNR, subjective results show the speech is intelligible, and the naturalness of the speech is rated as fair to good. This enables clear voice communication in challenging work environments, for example in places with industrial, factory, mining and construction noise. With our proposed smart switching technique between a regular microphone signal and V-Speech, the optimal quality can be maintained from low to high noise conditions.
A Data-Driven Misbehavior Detection System for Connected Autonomous Vehicles
Authors: Sarker Ankur , Shen Haiying
Published: December 2018

In a Connected and Autonomous Vehicle (CAV) system, some malicious CAVs may send out false information in vehicle-to-vehicle communication to gain benefits or cause safety-related accidents. Previous false data detection methods are not sufficient to meet the accuracy and real-time requirements. In this paper, we propose a data-driven misbehavior detection system (MDS) (running by each CAV) that checks the consistency between the estimated and actually reported driving state (i.e., velocity, acceleration, brake status, steering angle) of an alerting CAV. First, MDS predicts the driving state using Gaussian mixture model based Mixture Density Network incorporating Recurrent Neural Network that can catch the driving behavior patterns of a CAV. Second, MDS extends the existing Krauss traffic flow model and uses it to consider the overall traffic flow of the road to make the predicted driving state more accurate. Finally, for a given received alert, a CAV validates the alert by checking the consistency between the predicted and actually reported driving states of the alerting CAV. We conduct extensive simulation studies based on a real driving dataset we collected from 29 participants and the Simulator for Urban MObility (SUMO) traffic simulator. The experimental results show that the false information detection rate of the proposed MDS is higher than other existing systems in different alert scenarios.
A Cuttable Wireless Power Transfer Sheet
Authors: Takahashi Ryo , Sasatani Takuya , Okuya Fuminori , Narusue Yoshiaki , Kawahara Yoshihiro
Published: December 2018

We propose a cuttable wireless power transfer sheet which allows users to modify its size and shape. This intuitive manipulation allows users to easily add wireless power transmission capabilities to everyday objects. The properties of the sheet such as thinness, flexibility, and lightness make our sheet highly compatible with various configurations. We contribute a set of technical principles for the design of circuitry, which integrates H-tree wiring and time division power supply techniques. H-tree wiring allows the sheet to remain functional even when cut from the outside of the sheet, whereas time division power supply avoids the reduction in power transfer efficiency caused by the magnetic interference between adjacent transmitter coils. Through the evaluations, we found that our time division power supply scheme mitigates the degradation of power transfer efficiency and successfully improves the average efficiency. Furthermore, we present four applications which integrates our sheet into daily objects: wireless charging furniture, bag, jacket, and craft; these applications confirmed the feasibility of our prototype.
HeadGesture
Authors: Yan Yukang , Yu Chun , Yi Xin , Shi Yuanchun
Published: December 2018

We propose HeadGesture, a hands-free input approach to interact with Head Mounted Display (HMD) devices. Using HeadGesture, users do not need to raise their arms to perform gestures or operate remote controllers in the air. Instead, they perform simple gestures with head movement to interact with the devices. In this way, users' hands are free to perform other tasks, e.g., taking notes or manipulating tools. This approach also reduces the hand occlusion of the field of view [11] and alleviates arm fatigue [7]. However, one main challenge for HeadGesture is to distinguish the defined gestures from unintentional movements. To generate intuitive gestures and address the issue of gesture recognition, we proceed through a process of Exploration - Design - Implementation - Evaluation. We first design the gesture set through experiments on gesture space exploration and gesture elicitation with users. Then, we implement algorithms to recognize the gestures, including gesture segmentation, data reformation and unification, feature extraction, and machine learning based classification. Finally, we evaluate user performance of HeadGesture in the target selection experiment and application tests. The results demonstrate that the performance of HeadGesture is comparable to mid-air hand gestures, measured by completion time. Additionally, users feel significantly less fatigue than when using hand gestures and can learn and remember the gestures easily. Based on these findings, we expect HeadGesture to be an efficient supplementary input approach for HMD devices.
Socioeconomic Factors and Inequality in the Prevalence and Treatment of Diabetes among Middle-Aged and Elderly Adults in China
Authors: Wang Zhonghua , Li Xiangjun , Chen Mingsheng
Published: December 2018

Background. In China, the prevalence of diabetes has increased significantly over recent decades, owing to the county’s rapidly aging population. Although many studies have examined the prevalence of diabetes worldwide, there has been little analysis of the inequalities in its prevalence and treatment among middle-aged and elderly people. Objectives. This study evaluates influence factors and inequality in respect to the prevalence of diabetes and medication treatment among middle-aged and elderly Chinese adults. Methods. Data were obtained from the China Health and Retirement Longitudinal Study, a nationally representative household survey of middle-aged and elderly people (i.e., 45 years of age or older). Logistic regression models and the concentration index were used to estimate socioeconomic factors and inequalities in diabetes prevalence and treatment. Results. The prevalence of self-reported diabetes among middle-aged and elderly Chinese adults was 8.4%; this figure was significantly higher in urban areas than in rural areas. Concentrations of prevalence were observed among the poor in urban areas and among the rich in rural areas. Overall, the incidence of receiving antidiabetic medication among diabetes patients was 64.3%; this was significantly higher for individuals in urban areas than those in rural areas, suggesting that awareness of diabetes treatment in urban areas is better than that in rural areas. A disproportionate concentration of incidence of receiving antidiabetic medication was observed among the rich in both urban and rural areas. Socioeconomic factors significantly affected the prevalence of diabetes and the likelihood of receiving medication and are major contributors to inequality. Conclusion. In China, policies and strategies regarding diabetes prevention and control should further focus on associated socioeconomic factors and major contributors to reduce diabetes prevalence, improve diabetes treatment and management, and alleviate current inequality in the prevalence and treatment of diabetes among middle-aged and elderly adults.
Prognostic Value of Lactate Dehydrogenase in Patients with Hepatocellular Carcinoma: A Meta-Analysis
Authors: Kong Weihao , Zuo Xiaomin , Liang Hao , Hu Jingxiong , Zhang Huabing , Wang Xingyu , Chen Wei
Published: December 2018

Background. Previous studies have shown the prognostic value of lactate dehydrogenase (LDH) in hepatocellular carcinoma (HCC), but the results are not persuasive. Therefore, the purpose of our study was to quantitatively explore the prognostic value of LDH in hepatocellular carcinoma.Methods. We searched the Web of Science, Embase, PubMed, and the Cochrane Library for literature published before October 2018 on the prognostic value of LDH in patients with hepatocellular carcinoma. The combined hazard ratios (HRs) and 95% confidence intervals (CIs) were utilized to assess the prognostic value of LDH in overall survival (OS), recurrence-free survival (RFS), and progression-free survival (PFS) of HCC. Subgroup analysis, sensitivity analysis, and metaregression were used to explore the source of heterogeneity. Funnel plots with Begg’s test and Egger’s test were used to detect potential publication biases. Furthermore, combined odds ratios (ORs) were utilized to assess the correlation between LDH and clinicopathological features.Results. A total of 10 nonrandomized controlled studies were included in this meta-analysis. The combined effects of LDH on HCC patients’ OS, RFS/DFS, and PFS were HR = 2.07, 95% CI: 1.63-2.62, P < 0.001; HR = 1.62, 95% CI: 1.37-1.90, P < 0.001; and HR = 1.96, 95% CI: 1.14-3.36, P = 0.014, respectively. Subgroup analysis and sensitivity analysis showed that the outcome was stable, and the results of the metaregression also identified statistical models as an important source of heterogeneity. Potential publication bias was detected in the OS studies, so the trim-and-fill method was used to explore publication bias, and the results showed stability. Furthermore, the combined OR suggests that LDH was significantly correlated with gender, Child-Pugh grade, alpha-fetoprotein, vascular invasion, and tumor size.Conclusions. Preoperative LDH elevation is significantly associated with poor prognosis in patients with HCC, which may be a promising factor in assessing the prognosis of patients with HCC.
Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System
Authors: Wang Lina , Zhang Haihui
Published: December 2018

Fuzzy sliding mode control as a robust and intelligent nonlinear control technique is proposed to control processes with severe nonlinearity and unknown models. This paper proposes a new adaptive tracking fuzzy sliding mode controller for nonlinear systems in the presence of fuzzy compensation. The main contribution of the proposed method is that the fuzzy system is used to realize the adaptive approximation of the unknown part of the model, and the fuzzy gain can be reduced effectively. The fuzzy self-adaptive rate is derived through the Lyapunov method, and the stability and convergence of the whole closed-loop system are guaranteed by adjusting the adaptive weight value. The performance of the proposed approach is evaluated for double joint rigid manipulator problems. The simulation results illustrate the effectiveness of our proposed controller.
Weed Control in White Bean with Pethoxamid Tank-Mixes Applied Preemergence
Authors: Soltani Nader , Brown Lynette R. , Sikkema Peter H.
Published: December 2018

Six field experiments were conducted during 2015 to 2017 in Ontario, Canada, to determine the efficacy of pethoxamid applied alone, and in combination with broadleaf herbicides, for the control of annual grass and broadleaved weeds in white navy bean. Visible injury was generally minimal (0 to 8%) with herbicide treatments evaluated. Weed control was variable depending on the weed species evaluated. Pethoxamid,S-metolachlor, halosulfuron, imazethapyr, sulfentrazone, pethoxamid + halosulfuron, pethoxamid + imazethapyr, and pethoxamid + sulfentrazone controlled redroot pigweed 82 to 98%; common ragweed 19 to 93%; common lambsquarters 49 to 84%; and green foxtail 47 to 92% in white bean. Weed biomass and weed density reductions were similar to visible control ratings for herbicides evaluated. Weed interference delayed white bean maturity and reduced yield by 50% in this study. Weed interference in plots sprayed with pethoxamid,S-metolachlor, and sulfentrazone reduced white bean yield 36%. White bean yield was similar to the weed-free with other herbicides evaluated. This study concludes that there is potential for the tank-mix of pethoxamid with halosulfuron, imazethapyr, or sulfentrazone for weed control in white bean production.
Simulation and Statistical Modeling of Acoustic Scattering of Bubble Wakes
Authors: Ling-Guo Zhu , An-Bang Zhao , Jin Wang , Zhong-Cheng Ma , Qing-Gang Cao , Bao-Shan Yang
Published: December 2018

Ship wakes are large, exist for a long time, and are difficult to disguise or conceal. These characteristics can be used as an important basis for ship tracking and recognition. However, distinguishing between wakes, underwater targets, and sea surface is a difficult problem that currently limits acoustic wake homing technology. To solve this problem, in this study, from the viewpoint of feature recognition, the effects of bubble radius, air volume fraction, frequency, depth, and other parameters on the group bubble were first investigated. The volume scattering intensity of acoustic wakes at different frequencies and depths was also calculated and analyzed, and the results of our theoretical calculations were verified through an experiment using a multifrequency single wave sonar dock. Subsequently, through the single frequency and multibeam sonar sea trial test, a statistical model of target characteristics with a clear physical mechanism was developed. The developed model can be utilized for the guidance and recognition of acoustic wake targets. Thus, this study lays the foundation for the practical application of acoustic wake guidance.
Matrix Generation by First-Order Taylor Expansion in a Localized Manner
Authors: Hu Jun , Zhang Wen , Qiu Tong-Tong , Lan Xue
Published: December 2018

The method of moments is widely used, but its matrix generation is time-consuming. In the present paper, a localized multifrequency matrix-filling method is proposed. The method is based on the retarded first-order Taylor expansion of Green’s functions on each field point, which can reduce the number of callback Green’s functions and hence can solve double-surface integrals quickly. It is also based on the extraction of the common factors of different frequencies, and hence can sweep the frequency points quickly. Numerical examples are provided to validate the efficiencies of the proposed method.
An Optimal Hybrid Control Method for Energy-Saving of Chilled Water System in Central Air Conditioning
Authors: Zhang Yan , Chu Xiaoli , Liu Yongqiang
Published: December 2018

Chilled water system of central air conditioning is a typical hybrid system; variable frequency behavior with amplitude limited of pumps reflects continuous and discrete dynamic characteristics. The way of energy-saving is variable water volume, via variable frequency behavior of pumps to gain adjustment of power consumption. Facing the situation of the variable frequency pumps with parallel operation, single continuous or discrete modeling cannot reflect the hybrid features. Thus, the control method will have some questions, such as bad energy-saving effect, difficult accurate adjustment of cold capacity, and low running energy efficiency. However, hybrid system modeling can reflect hybrid dynamic behavior of pumps, which is combining continuous and discrete features. The questions of nonlinear and multiparameters can be solved by control method based on hybrid system. Here, an optimum control method is proposed with the principle of the minimum, by setting the minimum power consumption as the performance function in fixed time, which realizes variable control of pumps and accurate adjustment of temperature inside room. At last, it shows the system characteristics and energy-saving affection by hybrid system modeling and the optimum control method.
An Overview of Methods for Blast Load Testing and Devices for Pressure Measurement
Authors: Draganić H. , Varevac D. , Lukić S.
Published: December 2018

A brief review of experimental methods for testing blast effects on structures is presented. Methods are classified in four groups: field tests, shock tubes, pendulum systems, and new techniques (blast simulator). Description of each method is given together with overall specification of possible instruments used in each test. In today’s modern era of computers which are becoming powerful tool implemented in all aspects of life and also scientific research, comparison of experimental and numerical techniques is also given. Comparison of data obtained from different experimental methods show that careful planning and execution leads to reliable results in terms of pressure, impulse, stress, and damage quantification.
Biofilm Formation by Methicillin-Resistant and Methicillin-SensitiveStaphylococcus aureusStrains from Hospitalized Patients in Poland
Authors: Piechota Małgorzata , Kot Barbara , Frankowska-Maciejewska Aneta , Grużewska Agata , Woźniak-Kosek Agnieszka
Published: December 2018

Biofilm-mediated infections in the hospital environment have a significant negative impact on patient health. This study aimed to investigate biofilm production in vitro and the presence oficaABCDgenes in methicillin-resistantS. aureus(MRSA) and methicillin-sensitiveS. aureus(MSSA) strains isolated from hospitalized patients. MRSA (73) and MSSA (57) strains were evaluated for biofilm production by the microtiter plate method. The presence oficaoperon was investigated by PCR. Out of 130 strains, 99.2% were biofilm producers. Strong biofilms were formed by 39.7% of MRSA and 36.8% of MSSA strains. The highest percentage of strong biofilm producers was found among the strains isolated from sputum and tracheostomy tube (66.7%), nose and catheter (50%), throat (44.4%), and bronchoalveolar washings (43.8%). The strains isolated from bronchoalveolar washings produced significantly more biofilm than strains isolated from wound and anus. The ability of biofilm forming by fecal strains was significantly lower compared to strains from other materials. MRSA strains had significantly higher ability of biofilm formation than MSSA strains (P= 0.000247). The presence oficaoperon in MRSA was detected in all strains. Comparison of strong biofilm biomass of the strains withicaABCD,icaABD, andicaADrevealed that strains withicaABCDandicaABDproduced highly significantly more biofilm than strains withicaAD. Biofilm forming by both MRSA and MSSA strains indicates high ability of theses strains to persist in hospital environment which increases the risk of disease development in hospitalized patients.
Evaluation of Novel 3-Hydroxyflavone Analogues as HDAC Inhibitors against Colorectal Cancer
Authors: Biswas Subhankar , Reddy Neetinkumar D. , Jayashree B. S. , Rao C. Mallikarjuna
Published: December 2018

Alteration of epigenetic enzymes is associated with the pathophysiology of colon cancer with an overexpression of histone deacetylase 8 (HDAC8) enzyme in this tissue. Numerous reports suggest that targeting HDAC8 is a viable strategy for developing new anticancer drugs. Flavonols provide a rich source of molecules that are effective against cancer; however, their clinical use is limited. The present study investigated the potential of quercetin and synthetic 3-hydroxyflavone analogues to inhibit HDAC8 enzyme and evaluated their anticancer property. Synthesis of the analogues was carried out, and cytotoxicity was determined using MTT assay. Nonspecific and specific HDAC enzyme inhibition assays were performed followed by the expression studies of target proteins. Induction of apoptosis was studied through annexin V and caspase 3/7 activation assay. Furthermore, the analogues were assessed against in vivo colorectal cancer. Among the synthesized analogues, QMJ-2 and QMJ-5 were cytotoxic against HCT116 cells with an IC50 value of 68 ± 2.3 and 27.4 ± 1.8 µM, respectively. They inhibited HDAC enzyme in HCT116 cells at an IC50 value of 181.7 ± 22.04 and 70.2 ± 4.3 µM, respectively, and inhibited human HDAC8 and 1 enzyme at an IC50 value of <50 µM with QMJ-5 having greater specificity towards HDAC8. A reduction in the expression of HDAC8 and an increase in acetyl H3K9 expression were observed with the synthesized analogues. Both QMJ-2 and QMJ-5 treatment induced apoptosis through the activation of caspase 3/7 evident from 55.70% and 83.55% apoptotic cells, respectively. In vivo studies revealed a significant decrease in colon weight to length ratio in QMJ-2 and QMJ-5 treatment groups compared to DMH control. Furthermore, a reduction in aberrant crypt foci formation was observed in the treatment groups. The present study demonstrated the potential of novel 3-hydroxyflavone analogues as HDAC8 inhibitors with anticancer property against colorectal cancer.
Strata Movement and Fracture Propagation Characteristics due to Sequential Extraction of Multiseam Longwall Panels
Authors: Zhang Xiangyang , Ghabraie Behrooz , Ren Gang , Tu Min
Published: December 2018

Multiseam longwall mining‐induced strata deformation and fracture propagation patterns are different from those of single‐seam mining. This difference is due to interaction of the caved zones as a result of longwall mining activity at different coal seams, which severely impacts formation of subsidence and permeability of the strata after multiseam mining. Understanding this phenomenon is of great importance in order to predict the multiseam subsidence reliably, evaluate the risk of water inrush and take suitable preventive measures, and determine suitable locations for placing gas drainage boreholes. In this study, scaled physical modelling techniques are utilised to investigate strata deformation, fracture propagation characteristics, and vertical subsidence above multiseam longwall panels. The results show that magnitude of the incremental multiseam subsidence increases significantly after multiseam extraction in comparison with single‐seam mining. This increase occurs to different extent depending on the multiseam mining configuration. In addition, interstrata fractures above the abutment areas of the overlapping panels propagate further towards the ground surface in multiseam extractions compared with single‐seam extractions. These fractures increase the risk of water inrush in presence of underground/surface water and create highly permeable areas suitable for placing gas drainage boreholes.
Strengthening of Precast RC Frame to Mitigate Progressive Collapse by Externally Bonded CFRP Sheets Anchored with HFRP Anchors
Authors: Pan Jianwu , Wang Xian , Wu Fang
Published: December 2018

Currently, the robustness of precast reinforced concrete frames is attracting wide attention. However, avoiding “strong beams and weak columns” during strengthening against progressive collapse is a key problem. To discuss this problem, an experimental study on two 1/2‐scale precast frame subassemblages under a pushdown loading regime was carried out in this paper. One specimen was strengthened with carbon fibre‐reinforced polymer (CFRP) sheets on the beam sides. The middle parts of the CFRP sheets were anchored with hybrid fibre‐reinforced polymer (HFRP) anchors. Another specimen was not strengthened. The failure mechanisms, failure modes, and strengthening effect are discussed. The strengthening effect is very obvious in the early catenary action stage. No shearing failure develops on HFRP anchors, which proves that the anchoring method is effective. Based on the experimental results, analytical models and preventive strengthening design and construction measures to mitigate progressive collapse of the precast RC frame are proposed.