bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Target Genes Involved in the Effect of Quercetin on the Response to Oxidative Stress in Caenorhabditis elegans
Authors: Ayuda-Durán Begoña , González-Manzano Susana , Miranda-Vizuete Antonio , Sánchez-Hernández Eva , R. Romero Marta , Dueñas Montserrat , Santos-Buelga Celestino , González-Paramás Ana M.
Published: November 2019

Quercetin is one the most abundant flavonoids in the human diet. Although it is well known that quercetin exhibits a range of biological activities, the mechanisms behind these activities remain unresolved. The aim of this work is to progress in the knowledge of the molecular mechanisms involved in the biological effects of quercetin using Caenorhabditis elegans as a model organism. With this aim, the nematode has been used to explore the ability of this flavonoid to modulate the insulin/insulin-like growth factor 1(IGF-1) signaling pathway (IIS) and the expression of some genes related to stress response. Different methodological approaches have been used, i.e., assays in knockout mutant worms, gene expression assessment by RT-qPCR, and C. elegans transgenic strains expressing green fluorescent protein (GFP) reporters. The results showed that the improvement of the oxidative stress resistance of C. elegans induced by quercetin could be explained, at least in part, by the modulation of the insulin signaling pathway, involving genes age-1, akt-1, akt-2, daf-18, sgk-1, daf-2, and skn-1. However, this effect could be independent of the transcription factors DAF-16 and HSF-1 that regulate this pathway. Moreover, quercetin was also able to increase expression of hsp-16.2 in aged worms. This observation could be of particular interest to explain the effects of enhanced lifespan and greater resistance to stress induced by quercetin in C. elegans, since the expression of many heat shock proteins diminishes in aging worms.
Effect of Hydrophilicity of Activated Carbon Electrodes on Desalination Performance in Membrane Capacitive Deionization
Authors: Jo Kyusik , Baek Youngbin , Lee Changha , Yoon Jeyong
Published: November 2019

Membrane capacitive deionization (MCDI) is a modification of capacitive deionization (CDI) using ion-exchange membranes (IEM) in front of the electrodes. Electrode properties, especially the specific surface area, are known to be strongly related with desalination performance in CDI, but the effects of other properties in MCDI are not fully understood. The objective of this study was to investigate the effect of hydrophilicity in activated carbon electrodes on desalination performance in MCDI. Two types of activated carbon (P60 and YS-2) whose specific surface areas were similar were used as electrode materials, but they had different hydrophilicity (i.e., P60 was originally hydrophobic and YS-2 was relatively hydrophilic due to its nitrogen-containing surface chemistry). These hydrophilic electrodes (either the electrode itself or modified with polydopamine (PDA)) led to an increase in the salt adsorption capacity (SAC) in MCDI because they facilitated the access of both ions and water molecules into the electrode pores. In particular, the SAC of the P60 electrode displayed a large increase to almost reach that of the YS-2 electrode due to the improved hydrophilicity with PDA modification and the insignificant effects of PDA modification on an already hydrophilic YS-2 electrode. Additionally, PDA-modified IEM in MCDI reduced the SAC as a result of the additional insulating PDA layer with little changes in hydrophilicity.
Experimental Study on Vertical Shear Behaviors of an Immersion Joint with Steel Shear Keys
Authors: Yuan Yong , Luo Jianhui , Yu Haitao
Published: November 2019

The vertical shear behaviors of an immersion joint with steel shear keys subjected to multidirectional loads are investigated in this paper. An experiment of an immersion joint model is carried out. Two kinds of compression–shear tests of the joint are considered in this experiment. The first kind of compression–shear test applies a specific vertical shear load and five different levels of longitudinal compressive loads on the joint. An additional compression–vertical shear destruction test is also conducted under the minimum longitudinal compressive load, wherein the vertical shear load is incrementally increased until failure of the joint. The other kind of compression–shear test is a bidirectional shear test, in which both the longitudinal compressive load and the transverse shear load are fixed, and the vertical shear load is gradually increased until reaching a target value. The results show that the shear force–displacement curves of the joint in any loading case can be divided into two stages: a non-linear development stage and a quasi-linear development stage. The vertical shear stiffness of the joint is found to increase with increasing longitudinal compressive load, and the existence of a transverse shear load enhances this effect. The ultimate shear capacity of the joint is smaller than the sum of the shear capacities of all vertical steel keys. In addition, the failure of the joint appears at the shear key on one sidewall of the joint.
Association between Gingival Biotype and Facial Typology through Cephalometric Evaluation and Three-Dimensional Facial Scanning
Authors: Valletta Rosa , Pango Ada , Tortora Gregorio , Rongo Roberto , Simeon Vittorio , Spagnuolo Gianrico , D’Antò Vincenzo
Published: November 2019

In dentistry, the assessment of periodontal biotype is considered one of the most important parameters with which to plan treatment, and craniofacial morphology might affect it. The aim of this study was to investigate the association between facial typology and gingival biotype in patients by means of two-dimensional and three-dimensional evaluations of facial typology. This study included 121 participants searching for orthodontic treatment (43 M, 78 F; 20.4 ± 10.4). Gingival biotype was evaluated based on the transparency of the periodontal probe through the gingival margin of the mid-buccal sulcus for both upper (UGB) and lower (LGB) anterior teeth. SellionNasion^GonionGnation (SN^GoGn) and CondylionGonionMenton (CoGoMe^) angles were measured on two-dimensional cephalograms. Three-dimensional face scans were acquired by means of a three-dimensional facial scanner (3dMD system) and successively analyzed to assess the facial typology using the ratio between lower facial height (SNMe) and total facial height (NMe). A chi-squared test and regression analysis were used to evaluate the associations between gingival biotype and facial morphology (p < 0.05). The chi-squared test showed that there was no statistically significant association between facial typology and gingival biotype (UGB p = 0.83; LGB p = 0.75). The logistic regression showed an association between SNMe/NMe and the UGB (p = 0.036), and SNMe/NMe and LGB (p = 0.049). The decreased ratio of SNMe/NMe might be a protective factor for a thin gingival biotype.
The Effect of Carbon Nanofibers Surface Properties in Hydrogenation and Dehydrogenation Reactions
Authors: Cattaneo Stefano , Sanchez Trujillo Felipe J. , Dimitratos Nikolaos , Villa Alberto
Published: November 2019

In this study, carbon nanofiber-supported Pd nanoparticles were used in the hydrogenation of cinnamaldehyde and in the dehydrogenation of cinnamyl alcohol. The different graphitisation of the surface of the nanofibers and the amount of oxygen functionalisation significantly affected both activity and selectivity to the various reaction products. In particular, a decrease in nanoparticle dimensions and oxygen content resulted in an increase in overall activity for both of the studied reactions. Moreover, the selectivity to hydrocinnamaldehyde enhanced with increasing surface oxygen content in the cinnamaldehyde hydrogenation, while the selectivity to cinnamaldehyde was higher with low-functionalised nanofibers in the cinnamyl alcohol dehydrogenation. Finally, the most active catalyst proved also to be stable in consecutive runs.
Effects of Atmospheric Turbulence on OAM-POL-FDM Hybrid Multiplexing Communication System
Authors: Zhao Lin , Liu Hongzhan , Hao Yuan , Sun Haoying , Wei Zhongchao
Published: November 2019

This paper proposes a 32-channel-hybrid-multiplexing system on atmospheric turbulence. With the utilization of the hybrid multiplexing of orbital angular momentum (OAM), polarization, and frequency, the communication speed of the system can be significantly improved, and this system can be well combined with the existing frequency division multiplexing (FDM) optical communication network. Within this communication system, we discuss the effects of different turbulence intensities on the phase, OAM crosstalk, spectrum, and bit error rate (BER) in turbulent channels. Under strong turbulence, 46.8% of the energy leaks to the neighbor OAM and become noise when multiple topological charge states are transmitted. The research reflects the impact of various parameters of the OAM hybrid multiplexing system under turbulence, which is closer to a practical application scenario and is significant for implementing OAM communication in the turbulence channel.
The Teager-Kaiser Energy Cepstral Coefficients as an Effective Structural Health Monitoring Tool
Authors: Civera Marco , Ferraris Matteo , Ceravolo Rosario , Surace Cecilia , Betti Raimondo
Published: November 2019

Recently, features and techniques from speech processing have started to gain increasing attention in the Structural Health Monitoring (SHM) community, in the context of vibration analysis. In particular, the Cepstral Coefficients (CCs) proved to be apt in discerning the response of a damaged structure with respect to a given undamaged baseline. Previous works relied on the Mel-Frequency Cepstral Coefficients (MFCCs). This approach, while efficient and still very common in applications, such as speech and speaker recognition, has been followed by other more advanced and competitive techniques for the same aims. The Teager-Kaiser Energy Cepstral Coefficients (TECCs) is one of these alternatives. These features are very closely related to MFCCs, but provide interesting and useful additional values, such as e.g., improved robustness with respect to noise. The goal of this paper is to introduce the use of TECCs for damage detection purposes, by highlighting their competitiveness with closely related features. Promising results from both numerical and experimental data were obtained.
Heart Attack Detection in Colour Images Using Convolutional Neural Networks
Authors: Rojas-Albarracín Gabriel , Chaves Miguel Ángel , Fernández-Caballero Antonio , López María T.
Published: November 2019

Cardiovascular diseases are the leading cause of death worldwide. Therefore, getting help in time makes the difference between life and death. In many cases, help is not obtained in time when a person is alone and suffers a heart attack. This is mainly due to the fact that pain prevents him/her from asking for help. This article presents a novel proposal to identify people with an apparent heart attack in colour images by detecting characteristic postures of heart attack. The method of identifying infarcts makes use of convolutional neural networks. These have been trained with a specially prepared set of images that contain people simulating a heart attack. The promising results in the classification of infarcts show 91.75% accuracy and 92.85% sensitivity.
Human-Machine Interaction: Adapted Safety Assistance in Mentality Using Hidden Markov Chain and Petri Net
Authors: Chen Chao-Nan , Liu Tung-Kuan , Chen Yenming J.
Published: November 2019

This study proposes a cognition-adaptive approach for the administrative control of human-machine safety interaction through Internet of Things (IoT) data. As part of Industry 4.0, a human operator possesses various characteristics, but cannot be consistently understood as well as a machine. Thus, human-machine interaction plays an important role. This study focuses on incumbent challenges on the basis of estimated mental states. Given the operation logs from data recording hardware, a Hidden Markov model on top of a human cognitive model was trained to capture a production line worker’s sequential faults. Our study found that retaining workers’ attention is insufficient and tracking the state of perception is key to accomplishing production tasks. A safe workflow policy requires attention and perception. Accordingly, our proposed Petri Net enhances operation safety and improves production efficiency.
Effects of Cooling Conditions on Microstructure and Mechanical Properties of Friction Stir Welded Butt Joints of Different Aluminum Alloys
Authors: Bocchi Sara , D’Urso Gianluca , Giardini Claudio , Maccarini Giancarlo
Published: November 2019

The aim of this work is to evaluate the difference between the properties of several aluminum alloy joints welded with the traditional air-cooled friction stir welding process and others obtained by the combination of the traditional friction stir welding setup with a water-cooling system. In particular, precipitation-hardening alloys AA2024-T3, AA6082-T6 and AA7075-T6, and a work-hardening alloy, AA5754-H111, were taken into account. From Rockwell and Vickers hardness maps, it was possible to observe a clear dependence of the hardness distribution on the cooling systems; joints obtained using a water-cooling system showed higher values of hardness, reached in the central zone and a narrow area interested by the hardness reduction for all the tested alloys. From tensile tests executed orthogonally to the welding direction, it was possible to observe that the alloys have responded differently in terms of ultimate tensile strength and final elongation when the water-cooling system was used. The microstructural analysis of the three precipitation-hardening alloys showed a larger average grain size in the nugget zones for the water-cooled condition. Moreover, in the thermo-mechanically altered zones of the water-cooled AA6082 and AA7075 joints, the grains were characterized by a smaller average size than the grains of the same air-cooled welds.
Stepped Spillways and Energy Dissipation: A Non-Uniform Step Length Approach
Authors: Ashoor Abdelwanees , Riazi Amin
Published: November 2019

A stepped spillway, which is defined as a spillway with steps on the chute, can be used to improve the energy dissipation of descending water. Although uniform stepped spillways have been studied comprehensively, non-uniform stepped spillways need more attention. In the interest of maximum energy dissipation, in this study, non-uniform stepped spillways were investigated numerically. To this end, within the range of skimming flow, four different types of non-uniform step lengths, including convex, concave, random, and semi-uniform configurations, were tested in InterFOAM. To evaluate the influence of non-uniform step lengths on energy dissipation, the height and number of steps in all models were fixed and equal to a constant number. The results indicated that in semi-uniform stepped spillways, when the ratio between the lengths of the successive steps is 1:3, a vortex interference region occurs within the two adjacent cavities of the entire stepped chute, and as a result, the energy dissipation increases by up to 20%.
A Novel Optimization Design Method of Form Grinding Wheel for Screw Rotor
Authors: Liu Zongmin , Tang Qian , Liu Ning , Liang Pinghua , Liu Wei
Published: November 2019

The profile accuracy of screw rotors plays a vital role in stabilizing the meshing operation between mated rotors. Such stability can minimize the vibration and noise, as well as improve the sealing performance and wear resistance. This is the main reason why form grinding is extensively applied as a finishing process to maintain high screw rotor profile accuracy. Since the installation parameters for form grinding wheels affect both the grinding wheel profile accuracy and grinding performance, it is essential to obtain reasonable installation parameters to guarantee the high precision and good grinding performance of form grinding wheels. In this paper, a novel optimization design method for form grinding wheels for screw rotors has been proposed. For the first time, the relationship between the grinding wheel installation parameters and profile accuracy is established to evaluate the grinding performance. A parameterized program has been designed based on space engagement theory. The characteristics of the contact line and profile features of form grinding wheels under different installation parameters have been investigated. Then, the proposed method was employed to select the correct range of installation parameters. To validate the proposed method, a set of experiments, including the manufacture and measurement of several screw rotors, was carried out. The results reveal that the precision of the screw profile is significantly improved compared with the empirical method, thus showing the effectiveness of the proposed method.
Haptic Hybrid Prototyping (HHP): An AR Application for Texture Evaluation with Semantic Content in Product Design
Authors: Pardo-Vicente Miguel-Ángel , Rodríguez-Parada Lucía , Mayuet-Ares Pedro F. , Aguayo-González Francisco
Published: November 2019

The manufacture of prototypes is costly in economic and temporal terms and in order to carry this out it is necessary to accept certain deviations with respect to the final finishes. This article proposes haptic hybrid prototyping, a haptic-visual product prototyping method created to help product design teams evaluate and select semantic information conveyed between product and user through texturing and ribs of a product in early stages of conceptualization. For the evaluation of this tool, an experiment was realized in which the haptic experience was compared during the interaction with final products and through the HHP. As a result, it was observed that the answers of the interviewees coincided in both situations in 81% of the cases. It was concluded that the HHP enables us to know the semantic information transmitted through haptic-visual means between product and user as well as being able to quantify the clarity with which this information is transmitted. Therefore, this new tool makes it possible to reduce the manufacturing lead time of prototypes as well as the conceptualization phase of the product, providing information on the future success of the product in the market and its economic return.
PACA-ITS: A Multi-Agent System for Intelligent Virtual Laboratory Courses
Authors: Munawar Saima , Khalil Toor Saba , Aslam Muhammad , Aimeur Esma
Published: November 2019

This paper describes an intensive design leading to the implementation of an intelligent lab companion (ILC) agent for an intelligent virtual laboratory (IVL) platform. An IVL enables virtual labs (VL) to be used as online research laboratories, thereby facilitating and improving the analytical skills of students using agent technology. A multi-agent system enhances the capability of the learning system and solves students’ problems automatically. To ensure an exhaustive Agent Unified Modeling Language (AUML) design, identification of the agents’ types and responsibilities on well-organized AUML strategies is carried out. This work also traces the design challenge of IVL modeling and the ILC agent functionality of six basic agents: the practical coaching agent (PCA), practical dispatcher agent (PDA), practical interaction and coordination agent (PICA), practical expert agent (PEA), practical knowledge management agent (PKMA), and practical inspection agent (PIA). Furthermore, this modeling technique is compatible with ontology mapping based on an enabling technology using the Java Agent Development Framework (JADE), Cognitive Tutor Authoring Tools (CTAT), and Protégé platform integration. The potential Java Expert System Shell (Jess) programming implements the cognitive model algorithm criteria that are applied to measure progress through the CTAT for C++ programming concept task on IVL and successfully deployed on the TutorShop web server for evaluation. The results are estimated through the learning curve to assess the preceding knowledge, error rate, and performance profiler to engage cognitive Jess agent efficiency as well as practicable and active decisions to improve student learning.
Fault Diagnosis of Rotating Electrical Machines Using Multi-Label Classification
Authors: Dineva Adrienn , Mosavi Amir , Gyimesi Mate , Vajda Istvan , Nabipour Narjes , Rabczuk Timon
Published: November 2019

Fault Detection and Diagnosis of electrical machine and drive systems are of utmost importance in modern industrial automation. The widespread use of Machine Learning techniques has made it possible to replace traditional motor fault detection techniques with more efficient solutions that are capable of early fault recognition by using large amounts of sensory data. However, the detection of concurrent failures is still a challenge in the presence of disturbing noises or when the multiple faults cause overlapping features. Multi-label classification has recently gained popularity in various application domains as an efficient method for fault detection and monitoring of systems with promising results. The contribution of this work is to propose a novel methodology for multi-label classification for simultaneously diagnosing multiple faults and evaluating the fault severity under noisy conditions. In this research, the Electrical Signature Analysis as well as traditional vibration data have been considered for modeling. Furthermore, the performance of various multi-label classification models is compared. Current and vibration signals are acquired under normal and fault conditions. The applicability of the proposed method is experimentally validated under diverse fault conditions such as unbalance and misalignment.
Categorization of the Condition of Railway Embankments Using a Multi-Attribute Utility Theory
Authors: Kovačević Meho Saša , Bačić Mario , Stipanović Irina , Gavin Kenneth
Published: November 2019

In the current economic climate, it is crucial to optimize the use of all resources regarding railway infrastructure maintenance. In this paper, a multi-attribute decision support framework is applied to categorize railway embankments in order to prioritize maintenance activities. The paper describes a methodology to first determine the current condition of embankments using a combination of ground penetrating radar (GPR) surveys, visual inspection, and historical data about maintenance activities. These attributes are then used for the development of a multi-attribute utility theory model, which can be used as a support for decision making process for maintenance planning. The methodology is demonstrated for the categorization of 181 km of railway embankments in Croatia.
A High Signal–Noise Ratio UWB Radar for Buried Pipe Location Using Golay Complementary Sequences
Authors: Li Jingxia , Liu Yang , Xu Hang , Wang Bingjie , Liu Li , Chen Xinpeng
Published: November 2019

A Golay-based ultra wideband ground penetrating for underground pipes location is proposed and experimentally demonstrated. Golay complementary codes with the code length of 1024 and frequency of 1 GHz are used as the probe signals. The two-dimensional image of the buried pipes is achieved by a correlation method and a back-projection algorithm. The experimental results show that both the plastic pipe and metallic pipe can be located with a range resolution of 10 cm. Furthermore, as the Golay complementary sequences are a pair of complementary sequences, the sum of their correlation function yields twice the value of the peak at the target position and zero elsewhere. Thus, compared with the stepped frequency signal radar or chaotic signal radar, the Golay-based radar can significantly improve the signal–noise ratio and has the capability of deep detection.
Design of a Novel Electric Diagnostic Technique for Fault Analysis of Centrifugal Pumps
Authors: Irfan Muhammad , A Alwadie , Glowacz Adam
Published: November 2019

Centrifugal pumps are the fundamental components of most industries. They are used in almost every industry to transfer liquid through pipes. The breakdown of a pump causes heavy production losses, and hence, the development of an economical and user-friendly condition monitoring system is vital in order to estimate the health of a pump in a timely manner, and to avoid an unscheduled breakdown. The intrusive condition monitoring techniques (such as vibration analysis and acoustic emission) developed for the fault diagnosis of pumps utilize expensive vibration sensors, and these sensors need to be installed on the pump body for data collection. Non-intrusive techniques (such as motor current analysis) have been proven to be economical, but have limited capabilities for diagnosing the incipient faults in pumps operating in a noisy industrial environment. The electric diagnostic technique (EDT) proposed in this paper does not require the purchase of extra sensors, and instead utilizes the existing sensors, which are usually installed on the machines, to measure and display the motor line current and voltage. The EDT has been developed in the Laboratory Virtual Instrument Engineering Workbench (LabVIEW) so as to measure the three-phase line current, and then transform it into two-phase d–q currents. These d–q currents are plotted as patterns, and the statistical features of these patterns are used to segregate the centrifugal pump fault types. Detailed experiments and evaluations have been performed in order to check the viability of the developed EDT technique.
High-Temperature Mechanical Properties of 4.5%Al δ-TRIP Steel
Authors: Chen Dayu , Cui Heng , Wang Rudong
Published: November 2019

The high-temperature mechanical properties of a 4.5% Al-containing δ-transformation-induced plasticity (TRIP) steel were studied by using the Gleeble 3500 thermomechanical simulator. The zero ductility temperature (ZDT) and the zero strength temperature (ZST) were measured, and the brittle zones were divided. The phase transformation zone was determined by differential scanning calorimetry (DSC). The temperature of the phase transformation and the proportion of the phase were calculated by the Thermo-Calc software. The ZDT and the ZST of the 4.5% Al-containing δ-TRIP steel are 1355 and 1405 °C, respectively. The first brittle zone and the third brittle zone of the steel are 1300–1350 °C and 800–975 °C, respectively. The reason for the embrittlement of the third brittle zone of the 4.5% Al-containing δ-TRIP steel is that the α-ferrite formed at the austenite grain boundary causes the sample to crack along the grain boundary under stress. The ductility of the 4.5% Al-containing δ-TRIP steel decreases first and then increases with the increase of the α-ferrite. When the proportion of the α-ferrite reaches 37%, the reduction of area (RA) of the 4.5% Al-containing δ-TRIP steel is reduced to 44%. The 4.5% Al-containing δ-TRIP steel has good resistance to the high-temperature cracking.
137 Gb/s PAM-4 Transmissions at 850 nm over 40 cm Optical Backplane with 25 G Devices with Improved Neural Network-Based Equalization
Authors: Zhang Qianwu , Jiang Yuntong , Zhou Hai , Deng Chuanlu , Duan Shuaihang , Wang Zicong , Li Yingchun , Song Yingxiong , Chen Jian , Zhang Junjie , Wu Yating , Wang Tingyun , Wang Min
Published: November 2019

An improved neural network-based equalization method is proposed and experimentally demonstrated. The up-to-137 Gb/s transmission of four level pulse amplitude modulation (PAM-4) signals with 25 G class 850 nm optical devices is achieved over an in-house fabricated 40 cm optical backplane. An in-depth investigation is conducted regarding the impact of delayed taps and spans on equalization performance. A performance comparison of the proposed method with the traditional maximum likelihood sequence estimation (MLSE) and decision feedback equalization (DFE) is also undertaken. For the bit rate from 80 to 100 Gb/s, the proposed method achieves an adopted hard-decision forward error correction (HD-FEC) requirement at a received optical power (RoP) of −9 and −8 dBm, while DFE and MLSE cannot meet the HD-FEC requirement. When the bit rate increases from 120 to 137 Gb/s, the proposed equalization method still successfully maintains the acceptable system performance at an RoP of −4 and −2.5 dBm. Furthermore, the specific bit error rate (BER) performances for varied maximum achievable bit rate under different RoPs by applying MLSE and the proposed method are also analyzed. This provides an important potential solution to realize the future data centers.
On Ontology-Based Tourist Knowledge Representation and Recommendation
Authors: Pai Mao-Yuan , Wang Ding-Chau , Hsu Tz-Heng , Lin Guan-Yu , Chen Chao-Chun
Published: November 2019

In the rapid development of the information technology age, many travelers search for travel articles through the Internet. These travel articles include the experience and knowledge of traveler, which can be used as a reference for tourism planning and attraction selection. At present, the most travel experience and knowledge is available in online travel reviews (OTR). OTR and eWOM (electronic word-of-mouth) contain a lot of knowledge of consumers and travelers. Many travelers often look for OTR content through virtual communities, blogs, and search engine, but the search results often cause information overload problems. In addition, through virtual communities, blogs, and search engines, an OTR search still requires using keywords. However, most travelers cannot know the name of the attraction; therefore, travelers cannot use the correct keywords to search. That causes travelers to be unable to get enough information from OTR and unable to make the best travel plan. Therefore, this study focuses on the ontology-based tourist knowledge representation and recommendation method. And the study is to search for popular attractions from the OTR content and construct a tourist knowledge structure for these travelers. When the tourists do not need to know the keywords of the popular attraction name, they just need to get their current location; and then ORT content will recommend the next attraction to the traveler, which helps the traveler make the correct travel decision. The evaluation result showed that the method proposed in this study can help the travelers to quickly make the travel decision and is better than the traditional searching methods.
Investigation on Direct Shear and Energy Dissipation Characteristics of Iron Tailings Powder Reinforced by Polypropylene Fiber
Authors: Jiang Ping , Lv Shaowei , Wang Yue , Li Na , Wang Wei
Published: November 2019

Resource utilization of iron tailings powder is an effective measure to reduce the dam-break risk of an iron tailings reservoir. Adding polypropylene fiber to iron tailings powder can improve its shear performance. Direct shear tests were carried out on reinforced iron tailings powder with polypropylene fiber with dosages of 0%, 0.25%, 0.5%, 0.75%, and 1%, respectively. The normal stresses during the tests were 100, 200, 300, and 400 kPa, respectively. The test results show that with the increase of polypropylene fiber dosage, the cohesive force of iron tailings powder firstly increases and then decreases gradually, and the internal friction angle firstly decreases and then increases. The back propagation (BP)neural network was used to fit the shear force (F) and shear displacement (s) of the test to obtain the F-s function relationship that satisfies the accuracy. Based on the energy dissipation theory, the direct shear energy dissipation of polypropylene-fiber-reinforced iron tailings powder was calculated. The mathematical model of energy dissipation of fiber interfacial failure was derived by the fiber distribution model. The interfacial strength parameters of polypropylene fiber were calculated based on the direct shear test data and the mathematical model of fiber interfacial energy dissipation. The test results show that the addition of polypropylene fiber from the perspective of energy dissipation can improve the shear properties of iron tailings powder.
A Connected and Autonomous Vehicle Reference Architecture for Attack Surface Analysis
Authors: Maple Carsten , Bradbury Matthew , Le Anh Tuan , Ghirardello Kevin
Published: November 2019

Connected autonomous vehicles (CAVs) will be deployed over the next decade with autonomous functionalities supported by new sensing and communication capabilities. Such functionality exposes CAVs to new attacks that current vehicles will not face. To ensure the safety and security of CAVs, it is important to be able to identify the ways in which the system could be attacked and to build defences against these attacks. One possible approach is to use reference architectures to perform an attack surface analysis. Existing research has developed a variety of reference architectures but none for the specific purpose of attack surface analysis. Existing approaches are either too simple for sufficiently detailed modelling or require too many details to be specified to easily analyse a CAV’s attack surface. Therefore, we propose a reference architecture using a hybrid Functional-Communication viewpoint for attack surface analysis of CAVs, including the Devices, Edge and Cloud systems CAVs interact with. Using two case studies, we demonstrate how attack trees can be used to understand the attack surface of CAV systems.
A Novel Approach to Data Extraction on Hyperlinked Webpages
Authors: Shaukat Kamran , Masood Nayyer , Khushi Matloob
Published: November 2019

The World Wide Web has an enormous amount of useful data presented as HTML tables. These tables are often linked to other web pages, providing further detailed information to certain attribute values. Extracting schema of such relational tables is a challenge due to the non-existence of a standard format and a lack of published algorithms. We downloaded 15,000 web pages using our in-house developed web-crawler, from various web sites. Tables from the HTML code were extracted and table rows were labeled with appropriate class labels. Conditional random fields (CRF) were used for the classification of table rows, and a nondeterministic finite automaton (NFA) algorithm was designed to identify simple, complex, hyperlinked, or non-linked tables. A simple schema for non-linked tables was extracted and for the linked-tables, relational schema in the form of primary and foreign-keys (PK and FK) were developed. Child tables were concatenated with the parent table’s attribute value (PK), serving as foreign keys (FKs). Resultantly, these tables could assist with performing better and stronger queries using the join operation. A manual checking of the linked web table results revealed a 99% precision and 68% recall values. Our 15,000-strong downloadable corpus and a novel algorithm will provide the basis for further research in this field.
Design and Implementation of a Monitoring System Using Optical Camera Communication for a Smart Factory
Authors: Cong Hoan Nguyen , Van Hoa Nguyen , Thanh Luan Vu , Jang Yeong Min
Published: November 2019

Wireless technologies that are based on radio frequencies are currently widely used, with numerous applications around the world. However, they pose some disadvantages to human health. High frequencies can have potentially harmful effects on children, hospital patients, and even healthy people if the signal power exceeds the permitted standard. Conversely, the use of visible light for data transmission is a trend that presents new options, including optical wireless communication, optical camera communication, and visible light communication. This paper proposes a modulation scheme based on on-off keying in the time domain, which is applied to a monitoring system using optical camera communication. This scheme has various compatible supports for the global-shutter camera and rolling-shutter camera, which are popular commercially available cameras. Furthermore, this scheme facilitates a low-cost monitoring system. By using small light-emitting diodes (LEDs) and controlling the exposure time in a single camera, the camera, as a receiver, can simultaneously detect signals from up to 10 sensor devices in different positions at a maximum distance of up to 50 m, with a low error rate.
Editorial: Applied Mechanics
Authors: Abdel Wahab Magd
Published: November 2019

Mechanics is a branch of physics that describes the theoretical aspects related to the response of objects to external forces and displacements [...]
Precipitation Atlas for Germany (GePrA)
Authors: Jung Christopher , Schindler Dirk
Published: November 2019

A new approach for modeling daily precipitation (RR) at very high spatial resolution (25 m × 25 m) was introduced. It was used to develop the Precipitation Atlas for Germany (GePrA). GePrA is based on 2357 RR time series measured in the period 1981–2018. It provides monthly percentiles (p) of the large-scale RR patterns which were mapped by a thin plate spline interpolation (TPS). A least-squares boosting (LSBoost) approach and orographic predictor variables (PV) were applied to integrate the small-scale precipitation variability in GePrA. Then, a Weibull distribution (Wei) was fitted to RRp. It was found that the mean monthly sum of RR ( R R ¯ s u m ) is highest in July (84 mm) and lowest in April (49 mm). A great dependency of RR on the elevation (ε) was found and quantified. Model validation at 425 stations showed a mean coefficient of determination (R2) of 0.80 and a mean absolute error (MAE) of less than 10 mm in all months. The high spatial resolution, including the effects of the local orography, make GePrA a valuable tool for various applications. Since GePrA does not only describe R R ¯ s u m , but also the entire monthly precipitation distributions, the results of this study enable the seasonal differentiation between dry and wet period at small scales.
Retrieval of Horizontal Visibility Using MODIS Data: A Deep Learning Approach
Authors: Hu Bo , Zhang Xingying , Sun Rui , Zhu Xianchun
Published: November 2019

Horizontal visibility (HVIS) is a primary index used for assessing air quality. Although satellite images provide information regarding atmospheric aerosols, atmospheric visibility is not directly measured. In this paper, a deep learning approach is proposed to retrieve HVIS using moderate-resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data, the European Centre for Medium-Range Weather Forecasts reanalysis dataset, and ground-based visibility observations. The deep neural network model comprises a multi-layer unsupervised restricted Boltzmann machine (RBM) and a layer for supervised learning. The dropout mechanism was used in the training process to overcome the errors caused by over-fitting. The results demonstrate that the correlation coefficient values between HVIS observations and retrievals during training, pre-validating, and evaluation were 0.74, 0.723, and 0.697, respectively. The retrieved HVIS in Eastern China exhibited a north-to-south increasing trend, increasing and decreasing in summer and winter, respectively. In conclusion, the proposed model presents an effective and more reliable method for HVIS retrieval. However, the small samples, low AOD, low albedo, high total column water, high longitude, and the low vertical wind component at 10 m likely cause HVIS bias.
Design of Novel Haptens and Development of Monoclonal Antibody-Based Immunoassays for the Simultaneous Detection of Tylosin and Tilmicosin in Milk and Water Samples
Authors: Huang Jian-Xin , Yao Chan-Yuan , Yang Jin-Yi , Li Zhen-Feng , He Fan , Tian Yuan-Xin , Wang Hong , Xu Zhen-Lin , Shen Yu-Dong
Published: November 2019

In this work, a monoclonal antibody-based indirect competitive enzyme-linked immunosorbent assay (icELISA) was established to detect tylosin and tilmicosin in milk and water samples. A sensitive and specific monoclonal antibody was prepared by rational designed hapten, which was achieved by directly oxidizing the aldehyde group on the side chain of tylosin to the carboxyl group. Under the optimized conditions, the linear range of icELISA for tylosin and tilmicosin were 1.3 to 17.7 ng/mL and 2.0 to 47.4 ng/mL, with half-maximal inhibition concentration (IC50) values of 4.7 and 9.6 ng/mL, respectively. The cross-reactivity with other analogues of icELISA was less than 0.1%. The average recoveries of icELISA for tylosin and tilmicosin ranged from 76.4% to 109.5% in milk and water samples. Besides, the detection results of icELISA showed good correlations with HPLC-MS/MS. The proposed icELISA was satisfied for rapid and specific screening of tylosin and tilmicosin residues in milk and water samples.
Wasabi Compound 6-(Methylsulfinyl) Hexyl Isothiocyanate Induces Cell Death with Coexisting Mitotic Arrest and Autophagy in Human Chronic Myelogenous Leukemia K562 Cells
Authors: Wu Kun-Ming , Liao Hui-Fen , Chi Chih-Wen , Kou Yu Ru , Chen Yu-Jen
Published: November 2019

A natural compound from Wasabia japonica, 6-(methylsulfinyl) hexyl isothiocyanate (6-MITC) was investigated for its anti-leukemia activity and mechanism of action. It was found that 6-MITC inhibited the viability of human chronic myelogenous leukemia K562 cells along with extensive mitotic arrest, spindle multipolarity, and cytoplasmic vacuole accumulation. The evidence of autophagy included the validation of autophagosomes with double-layered membranes under transmission electron microscopy, LC3I/II conversion, and the induction of G2/M phase arrest observed with acridine orange staining of treated cells, as well as the elevation of phosphorylated-histone H3 expression at the M phase. With regard to the expression of proteins related to mitosis, the down regulation of p-CHK1, p-CHK2, p-cdc25c, and p-cdc2, as well as the upregulation of cyclin B1, p-cdc20, cdc23, BubR1, Mad2, and p-plk-1 was observed. The knockdown of cdc20 was unable to block the effect of 6-MITC. The differentiation of k562 cells into monocytes, granulocytes, and megakaryocytes was not affected by 6-MITC. The 6-MITC-induced unique mode of cell death through the concurrent induction of mitosis and autophagy may have therapeutic potential. Further studies are required to elucidate the pathways associated with the counteracting occurrence of mitosis and autophagy.
Prosopis Plant Chemical Composition and Pharmacological Attributes: Targeting Clinical Studies from Preclinical Evidence
Authors: Sharifi-Rad Javad , Kobarfard Farzad , Ata Athar , Ayatollahi Seyed Abdulmajid , Khosravi-Dehaghi Nafiseh , Jugran Arun Kumar , Tomas Merve , Capanoglu Esra , Matthews Karl R. , Popović-Djordjević Jelena , Kostić Aleksandar , Kamiloglu Senem , Sharopov Farukh , Choudhary Muhammad Iqbal , Martins Natália
Published: November 2019

Members of the Prosopis genus are native to America, Africa and Asia, and have long been used in traditional medicine. The Prosopis species most commonly used for medicinal purposes are P. africana, P. alba, P. cineraria, P. farcta, P. glandulosa, P. juliflora, P. nigra, P. ruscifolia and P. spicigera, which are highly effective in asthma, birth/postpartum pains, callouses, conjunctivitis, diabetes, diarrhea, expectorant, fever, flu, lactation, liver infection, malaria, otitis, pains, pediculosis, rheumatism, scabies, skin inflammations, spasm, stomach ache, bladder and pancreas stone removal. Flour, syrup, and beverages from Prosopis pods have also been potentially used for foods and food supplement formulation in many regions of the world. In addition, various in vitro and in vivo studies have revealed interesting antiplasmodial, antipyretic, anti-inflammatory, antimicrobial, anticancer, antidiabetic and wound healing effects. The phytochemical composition of Prosopis plants, namely their content of C-glycosyl flavones (such as schaftoside, isoschaftoside, vicenin II, vitexin and isovitexin) has been increasingly correlated with the observed biological effects. Thus, given the literature reports, Prosopis plants have positive impact on the human diet and general health. In this sense, the present review provides an in-depth overview of the literature data regarding Prosopis plants’ chemical composition, pharmacological and food applications, covering from pre-clinical data to upcoming clinical studies.
Artificial Neural Network (ANN) as a Tool to Reduce Human-Animal Interaction Improves Senegalese Sole Production
Authors: Martínez-Vázquez Juan M. , Valcarce David G. , Riesco Marta F. , Marco Vicent Sanz , Matsuoka Morito , Robles Vanesa
Published: November 2019

Manipulation is usually required for biomass calculation and food estimation for optimal fish growth in production facilities. However, the advances in computer-based systems have opened a new range of applied possibilities. In this study we used image analysis and a neural network algorithm that allowed us to successfully provide highly accurate biomass data. This developed system allowed us to compare the effects of reduced levels of human-animal interaction on the culture of adult Senegalese sole (Solea senegalensis) in terms of body weight gain. For this purpose, 30 adult fish were split into two homogeneous groups formed by three replicates (n = 5) each: a control group (CTRL), which was standard manipulated and an experimental group (EXP), which was maintained under a lower human-animal interaction culture using our system for biomass calculation. Visible implant elastomer was, for the first time, applied as tagging technology for tracking soles during the experiment (four months). The experimental group achieved a statistically significant weight gain (p < 0.0100) while CTRL animals did not report a statistical before-after weight increase. Individual body weight increment was lower (p < 0.0100) in standard-handled animals. In conclusion, our experimental approach provides evidence that our developed system for biomass calculation, which implies lower human-animal interaction, improves biomass gain in Senegalese sole individuals in a short period of time.
Changes in Retinal OCT and Their Correlations with Neurological Disability in Early ALS Patients, a Follow-Up Study
Authors: Rojas Pilar , de Hoz Rosa , Ramírez Ana , Ferreras Antonio , Salobrar-Garcia Elena , Muñoz-Blanco José , Urcelay-Segura José , Salazar Juan , Ramírez José
Published: November 2019

Background: To compare early visual changes in amyotrophic lateral sclerosis (ALS) patients with healthy controls in a baseline exploration, to follow-up the patients after 6 months, and to correlate these visual changes with neurological disability. Methods: All patients underwent a comprehensive neurological and ophthalmological examination. A linear mixed analysis and Bonferroni p-value correction were performed, testing four comparisons as follows: Control baseline vs. control follow-up, control baseline vs. ALS baseline, control follow-up vs. ALS follow-up, and ALS baseline vs. ALS follow-up. Results: The mean time from the diagnosis was 10.80 ± 5.5 months. The analysis of the optical coherence tomography (OCT) showed: (1) In ALS baseline vs. control baseline, a macular significantly increased thickness of the inner macular ring temporal and inferior areas; (2) in ALS follow-up vs. ALS baseline, a significant macular thinning in the inner and outer macular ring inferior areas; (3) in ALS follow-up vs. ALS baseline, a significant peripapillary retinal nerve fiber layer (pRNFL) thinning in the superior and inferior quadrants; and (4) ALS patients showed a moderate correlation between some OCT pRNFL parameters and Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) score. Conclusion: The OCT showed retinal changes in patients with motoneuron disease and could serve as a complementary tool for studying ALS.