bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteome Profiling of Exosomes Purified from a Small Amount of Human Serum: The Problem of Co-Purified Serum Components
Authors: Smolarz Mateusz , Pietrowska Monika , Matysiak Natalia , Mielańczyk Łukasz , Widłak Piotr
Published: April 2019

Untargeted proteomics analysis of extracellular vesicles (EVs) isolated from human serum or plasma remains a technical challenge due to the contamination of these vesicles with lipoproteins and other abundant serum components. Here we aimed to test a simple method of EV isolation from a small amount of human serum (<1 mL) using the size-exclusion chromatography (SEC) standalone for the discovery of vesicle-specific proteins by the untargeted LC–MS/MS shotgun approach. We selected the SEC fraction containing vesicles with the size of about 100 nm and enriched with exosome markers CD63 and CD81 (but not CD9 and TSG101) and analyzed it in a parallel to the subsequent SEC fraction enriched in the lipoprotein vesicles. In general, there were 267 proteins identified by LC–MS/MS in exosome-containing fraction (after exclusion of immunoglobulins), yet 94 of them might be considered as serum proteins. Hence, 173 exosome-related proteins were analyzed, including 92 proteins absent in lipoprotein-enriched fraction. In this set of exosome-related proteins, there were 45 species associated with the GO cellular compartment term “extracellular exosome”. Moreover, there were 31 proteins associated with different immune-related functions in this set, which putatively reflected the major role of exosomes released by immune cells present in the blood. We concluded that identified set of proteins included a bona fide exosomes components, yet the coverage of exosome proteome was low due to co-purified high abundant serum proteins. Nevertheless, the approach proposed in current work outperformed other comparable protocols regarding untargeted identification of exosome proteins and could be recommended for pilot exploratory studies when a small amount of a serum/plasma specimen is available.
An Ecumenical Experiment in Colonial Hong Kong: The Start of the Tsuen Wan Ecumenical Social Service Centre (1973 to 1997) and Its Local Praxis
Authors: Wong Wai-Yin Christina
Published: April 2019

Based on both documentary research and a series of interviews, this study retrieves the ecumenical spirit of the beginning of the dismissed Tsuen Wan Ecumenical Social Service Centre (TWESSC), a Christian non-governmental organization. Early ecumenical praxis among six local churches (including one Catholic parish) testified to the need to work for (and with) the poor and to advocate for social justice, as promoted and sponsored by the World Council of Churches in the early 1970s. The TWESSC was recognised as an effective activist group in colonial Hong Kong, but was disbanded in 1997, due to conflict between the executive committee (including church representatives) and its frontline social workers and its service recipients. This article contributes to the study of ecumenism in Hong Kong in two ways. Firstly, it examines the emergence of the ecumenical movement in Hong Kong against the broader background of the involvement of church groups in community development. Secondly, it explores how the Hong Kong churches were occupied by the subvention of frontline services by the government since the 1980s, and how they sought to silence dissenting voices in the ecumenical movement.
Centrality of Religiosity, Schizotypy, and Human Values: The Impact of Religious Affiliation
Authors: Hanel Paul H. P. , Demmrich Sarah , Wolfradt Uwe
Published: April 2019

Previous research has established a reliable link between religiosity and schizotypy as well as schizophrenia. However, past research mainly measured religiosity as a one-dimensional construct. In the present research (N = 189), we aimed to get a better understanding of the religiosity–schizotypy link by measuring religiosity using Huber’s five-dimensional model of Centrality of Religiosity, while also testing for curvilinear relations and potential moderators. We found negative small-to-medium-sized correlations between all five dimensions of religiosity and the schizotypy dimension of impulsive nonconformity, but no reliable associations with the other three dimensions of schizotypy: unusual experiences, cognitive disorganization, and introverted anhedonia. Some of these associations were moderated by religious affiliation: Religiosity and schizotypy correlated positively among non-members, but negatively among members of religious communities, suggesting that affiliation has a positive impact on the well-being of religious people. In line with Huber’s predictions, we found a reversed U-shape association between the religious dimension of private religious practice and schizotypy. Unexpectedly, however, conformity and tradition values did not moderate the relations between religiosity and schizotypy. We discuss our findings in terms of person–environment fit, the prevention hypothesis of the schizotypy-religiosity link, and offer implications for mental health practitioners.
A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring
Authors: Shen Nan , Chen Liang , Liu Jingbin , Wang Lei , Tao Tingye , Wu Dewen , Chen Ruizhi
Published: April 2019

In the past few decades, global navigation satellite system (GNSS) technology has been widely used in structural health monitoring (SHM), and the monitoring mode has evolved from long-term deformation monitoring to dynamic monitoring. This paper gives an overview of GNSS-based dynamic monitoring technologies for SHM. The review is classified into three parts, which include GNSS-based dynamic monitoring technologies for SHM, the improvement of GNSS-based dynamic monitoring technologies for SHM, as well as denoising and detrending algorithms. The significance and progress of Real-Time Kinematic (RTK), Precise Point Position (PPP), and direct displacement measurement techniques, as well as single-frequency technology for dynamic monitoring, are summarized, and the comparison of these technologies is given. The improvement of GNSS-based dynamic monitoring technologies for SHM is given from the perspective of multi-GNSS, a high-rate GNSS receiver, and the integration between the GNSS and accelerometer. In addition, the denoising and detrending algorithms for GNSS-based observations for SHM and corresponding applications are summarized. Challenges of low-cost and widely covered GNSS-based technologies for SHM are discussed, and problems are posed for future research.
A Novel Framework to Harmonise Satellite Data Series for Climate Applications
Authors: Giering Ralf , Quast Ralf , Mittaz Jonathan P. D. , Hunt Samuel E. , Harris Peter M. , Woolliams Emma R. , Merchant Christopher J.
Published: April 2019

Fundamental and thematic climate data records derived from satellite observations provide unique information for climate monitoring and research. Since any satellite only operates over a relatively short period of time, creating a climate data record also requires the combination of space-borne measurements from a series of several (often similar) satellite sensors. Simply combining calibrated measurements from several sensors can, however, produce an inconsistent climate data record. This is particularly true of older, historic sensors whose behaviour in space was often different from their behaviour during pre-launch calibration and more scientific value can be derived from considering the series of historical and present satellites as a whole. Here, we consider harmonisation as a process that obtains new calibration coefficients for revised sensor calibration models by comparing calibrated measurements over appropriate satellite-to-satellite matchups, such as simultaneous nadir overpasses and which reconciles the calibration of different sensors given their estimated spectral response function differences. We present the concept of a framework that establishes calibration coefficients and their uncertainty and error covariance for an arbitrary number of sensors in a metrologically-rigorous manner. We describe harmonisation and its mathematical formulation as an inverse problem that is extremely challenging when some hundreds of millions of matchups are involved and the errors of fundamental sensor measurements are correlated. We solve the harmonisation problem as marginalised errors in variables regression. The algorithm involves computation of first and second-order partial derivatives using Algorithmic Differentiation. Finally, we present re-calibrated radiances from a series of nine Advanced Very High Resolution Radiometer sensors showing that the new time series has smaller matchup differences compared to the unharmonised case while being consistent with uncertainty statistics.
Global White-Sky and Black-Sky FAPAR Retrieval Using the Energy Balance Residual Method: Algorithm and Validation
Authors: Liu Liangyun , Zhang Xiao , Xie Shuai , Liu Xinjie , Song Bowen , Chen Siyuan , Peng Dailiang
Published: April 2019

The fraction of absorbed photosynthetically active radiation by vegetation (FAPAR) is a key variable in describing the light absorption ability of the vegetation canopy. Most global FAPAR products, such as MCD15A2H and GEOV1, correspond to FAPAR under black-sky conditions at the satellite overpass time only. In this paper, we aim to produce both the global white-sky and black-sky FAPAR products based on the moderate resolution imaging spectroradiometer (MODIS) visible (VIS) albedo, leaf area index (LAI), and clumping index (CI) products. Firstly, a non-linear spectral mixture model (NSM) was designed to retrieve the soil visible (VIS) albedo. The global soil VIS albedo and its dynamics were successfully mapped at a resolution of 500 m using the MCD43A3 VIS albedo product and the MCD15A2H LAI product. Secondly, a method based on the energy balance residual (EBR) principle was presented to retrieve the white-sky and black-sky FAPAR using the MODIS broadband VIS albedo (white-sky and black-sky) product (MCD43A3), the LAI product (MCD15A2H) and CI products. Finally, the two EBR FAPAR products were compared with the MCD15A2H and Geoland2/BioPar version 1 (GEOV1) black-sky FAPAR products. A comparison of the results indicates that these FAPAR products show similar spatial and seasonal patterns. Direct validation using FAPAR observations from the Validation of Land European Remote sensing Instrument (VALERI) project demonstrates that the EBR black-sky FAPAR product was more accurate and had a lower bias (R2 = 0.917, RMSE = 0.088, and bias = −2.8 %) than MCD15A2H (R2 = 0.901, RMSE = 0.096, and bias = 7.6 % ) and GEOV1 (R2 = 0.868, RMSE = 0.105, and bias = 6.1%).
Surface Temperature Multiscale Monitoring by Thermal Infrared Satellite and Ground Images at Campi Flegrei Volcanic Area (Italy)
Authors: Caputo Teresa , Bellucci Sessa Eliana , Silvestri Malvina , Buongiorno Maria Fabrizia , Musacchio Massimo , Sansivero Fabio , Vilardo Giuseppe
Published: April 2019

Land Surface Temperature (LST) from satellite data is a key component in many aspects of environmental research. In volcanic areas, LST is used to detect ground thermal anomalies providing a supplementary tool to monitor the activity status of a particular volcano. In this work, we describe a procedure aimed at identifying spatial thermal anomalies in thermal infrared (TIR) satellite frames which are corrected for the seasonal influence by using TIR images from ground stations. The procedure was applied to the volcanic area of Campi Flegrei (Italy) using TIR ASTER and Landsat 8 satellite imagery and TIR ground images acquired from the Thermal Infrared volcanic surveillance Network (TIRNet) (INGV, Osservatorio Vesuviano). The continuous TIRNet time-series images were processed to evaluate the seasonal component which was used to correct the surface temperatures estimated by the satellite’s discrete data. The results showed a good correspondence between de-seasoned time series of surface ground temperatures and satellite temperatures. The seasonal correction of satellite surface temperatures allows monitoring of the surface thermal field to be extended to all the satellite frames, covering a wide portion of Campi Flegrei volcanic area.
Towards Automatic Extraction and Updating of VGI-Based Road Networks Using Deep Learning
Authors: Manandhar Prajowal , Marpu Prashanth Reddy , Aung Zeyar , Melgani Farid
Published: April 2019

This work presents an approach to road network extraction in remote sensing images. In our earlier work, we worked on the extraction of the road network using a multi-agent approach guided by Volunteered Geographic Information (VGI). The limitation of this VGI-only approach is its inability to update the new road developments as it only follows the VGI. In this work, we employ a deep learning approach to update the road network to include new road developments not captured by the existing VGI. The output of the first stage is used to train a Convolutional Neural Network (CNN) in the second stage to generate a general model to classify road pixels. Post-processing is used to correct the undesired artifacts such as buildings, vegetation, occlusions, etc. to generate a final road map. Our proposed method is tested on the satellite images acquired over Abu Dhabi, United Arab Emirates and the aerial images acquired over Massachusetts, United States of America, and is observed to produce accurate results.
Detecting Land Degradation in Eastern China Grasslands with Time Series Segmentation and Residual Trend analysis (TSS-RESTREND) and GIMMS NDVI3g Data
Authors: Liu Caixia , Melack John , Tian Ye , Huang Huabing , Jiang Jinxiong , Fu Xiao , Zhang Zhouai
Published: April 2019

Grassland ecosystems in China have experienced degradation caused by natural processes and human activities. Time series segmentation and residual trend analysis (TSS-RESTREND) was applied to grasslands in eastern China. TSS-RESTREND is an extended version of the residual trend (RESTREND) methodology. It considers breakpoint detection to identify pixels with abrupt ecosystem changes which violate the assumptions of RESTREND. With TSS-RESTREND, in Xilingol (111°59′–120°00′E and 42°32′–46°41′E) and Hulunbuir (115°30′–122°E and 47°10′–51°23′N) grassland, 6% and 3% of the area experienced a decrease in greenness between 1984 and 2009, 80% and 73% had no significant change, 5% and 3% increased in greenness, and 9% and 21% were undetermined, respectively. RESTREND may underestimate the greening trend in Xilingol, but both TSS-RESTREND and RESTREND revealed no significant differences in Hulunbuir. The proposed TSS-RESTREND methodology captured both the time and magnitude of vegetation changes.
Remote Estimation of Mangrove Aboveground Carbon Stock at the Species Level Using a Low-Cost Unmanned Aerial Vehicle System
Authors: Li Zhen , Zan Qijie , Yang Qiong , Zhu Dehuang , Chen Youjun , Yu Shixiao
Published: April 2019

There is ongoing interest in developing remote sensing technology to map and monitor the spatial distribution and carbon stock of mangrove forests. Previous research has demonstrated that the relationship between remote sensing derived parameters and aboveground carbon (AGC) stock varies for different species types. However, the coarse spatial resolution of satellite images has restricted the estimated AGC accuracy, especially at the individual species level. Recently, the availability of unmanned aerial vehicles (UAVs) has provided an operationally efficient approach to map the distribution of species and accurately estimate AGC stock at a fine scale in mangrove areas. In this study, we estimated mangrove AGC in the core area of northern Shenzhen Bay, South China, using four kinds of variables, including species type, canopy height metrics, vegetation indices, and texture features, derived from a low-cost UAV system. Three machine-learning algorithm models, including Random Forest (RF), Support Vector Regression (SVR), and Artificial Neural Network (ANN), were compared in this study, where a 10-fold cross-validation was used to evaluate each model’s effectiveness. The results showed that a model that used all four type of variables, which were based on the RF algorithm, provided better AGC estimates (R2 = 0.81, relative RMSE (rRMSE) = 0.20, relative MAE (rMAE) = 0.14). The average predicted AGC from this model was 93.0 ± 24.3 Mg C ha−1, and the total estimated AGC was 7903.2 Mg for the mangrove forests. The species-based model had better performance than the considered canopy-height-based model for AGC estimation, and mangrove species was the most important variable among all the considered input variables; the mean height (Hmean) the second most important variable. Additionally, the RF algorithms showed better performance in terms of mangrove AGC estimation than the SVR and ANN algorithms. Overall, a low-cost UAV system with a digital camera has the potential to enable satisfactory predictions of AGC in areas of homogenous mangrove forests.
Energy Efficient and Delay Aware 5G Multi-Tier Network
Authors: Islam Nahina , Alazab Ammar , Agbinya Johnson
Published: April 2019

Multi-tier heterogeneous Networks (HetNets) with dense deployment of small cells in 5G networks are expected to effectively meet the ever increasing data traffic demands and offer improved coverage in indoor environments. However, HetNets are raising major concerns to mobile network operators such as complex distributed control plane management, handover management issue, increases latency and increased energy expenditures. Sleep mode implementation in multi-tier 5G networks has proven to be a very good approach for reducing energy expenditures. In this paper, a Markov Decision Process (MDP)-based algorithm is proposed to switch between three different power consumption modes of a base station (BS) for improving the energy efficiency and reducing latency in 5G networks. The MDP-based approach intelligently switches between the states of the BS based on the offered traffic while maintaining a prescribed minimum channel rate per user. Simulation results show that the proposed MDP algorithm together with the three-state BSs results in a significant gain in terms of energy efficiency and latency.
Modelling Site Index in Forest Stands Using Airborne Hyperspectral Imagery and Bi-Temporal Laser Scanner Data
Authors: Bollandsås Ole Martin , Ørka Hans Ole , Dalponte Michele , Gobakken Terje , Næsset Erik
Published: April 2019

In forest management, site index information is essential for planning silvicultural operations and forecasting forest development. Site index is most commonly expressed as the average height of the dominant trees at a certain index age, and can be determined either by photo interpretation, field measurements, or projection of age combined with height estimates from remote sensing. However, recently it has been shown that site index can be accurately predicted from bi-temporal airborne laser scanner (ALS) data. Furthermore, single-time hyperspectral data have also been shown to be correlated to site index. The aim of the current study was to compare the accuracy of modelling site index using (1) data from bi-temporal ALS; (2) single-time hyperspectral data with different types of preprocessing; and (3) combined bi-temporal ALS and single-time hyperspectral data. The period between the ALS acquisitions was 11 years. The preprocessing of the hyperspectral data included an atmospheric correction and/or a normalization of the reflectance. Furthermore, a selection of pixels was carried out based on NDVI and compared to using all pixels. The results showed that bi-temporal ALS data explained about 70% (R2) of the variation in the site index, and the RMSE values from a cross-validation were 3.0 m and 2.2 m for spruce- and pine-dominated plots, respectively. Corresponding values for the different single-time hyperspectral datasets were 54%, 3.9 m, and 2.5 m. With bi-temporal ALS data and hyperspectral data used in combination, the results indicated that the contribution from the hyperspectral data was marginal compared to just using bi-temporal ALS. We also found that models constructed with normalized hyperspectral data produced lower RMSE values compared to those constructed with atmospherically corrected data, and that a selection of pixels based on NDVI did not improve the results compared to using all pixels.
Distributed Acoustic Sensing of Strain at Earth Tide Frequencies
Authors: Becker Matthew W. , Coleman Thomas I.
Published: April 2019

The solid Earth strains in response to the gravitational pull from the Moon, Sun, and other planetary bodies. Measuring the flexure of geologic material in response to these Earth tides provides information about the geomechanical properties of rock and sediment. Such measurements are particularly useful for understanding dilation of faults and fractures in competent rock. A new approach to measuring earth tides using fiber optic distributed acoustic sensing (DAS) is presented here. DAS was originally designed to record acoustic vibration through the measurement of dynamic strain on a fiber optic cable. Here, laboratory experiments demonstrate that oscillating strain can be measured with DAS in the microHertz frequency range, corresponding to half-day (M2) lunar tidal cycles. Although the magnitude of strain measured in the laboratory is larger than what would be expected due to earth tides, a clear signal at half-day period was extracted from the data. With the increased signal-to-noise expected from quiet field applications and improvements to DAS using engineered fiber, earth tides could potentially be measured in deep boreholes with DAS. Because of the distributed nature of the sensor (0.25 m measurement interval over kilometres), fractures could be simultaneously located and evaluated. Such measurements would provide valuable information regarding the placement and stiffness of open fractures in bedrock. Characterization of bedrock fractures is an important goal for multiple subsurface operations such as petroleum extraction, geothermal energy recovery, and geologic carbon sequestration.
Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations
Authors: He Chaofeng , Wang Yiyin , Yu Wenbin , Song Lei
Published: April 2019

A distributed single-input multiple-output (SIMO) sonar system is composed of a sound source and multiple underwater receivers. It provides an important framework for underwater target localization. However, underwater hostile environments bring more challenges for underwater target localization than terrestrial target localization, such as the difficulties of synchronizing all the underwater receiver clocks, the varying underwater sound speed and the uncertainties of the locations of the underwater receivers. In this paper, we take the sound speed variation, the time synchronization and the uncertainties of the receiver locations into account, and propose the underwater target localization and synchronization (UTLS) algorithm for the distributed SIMO sonar system. In the distributed SIMO sonar system, the receivers are organized in a star topology, where the information fusion is carried out in the central receiver (CR). All the receivers are not synchronized and their positions are known with uncertainties. Moreover, the underwater sound speed is approximately modeled by a depth-dependent sound speed profile (SSP). We evaluate our proposed UTLS algorithm by comparing it with several benchmark algorithms via numerical simulations. The simulation results reveal the superiority of our proposed UTLS algorithm.
Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things
Authors: Thamilarasu Geethapriya , Chawla Shiven
Published: April 2019

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.
Review on Wearable Technology Sensors Used in Consumer Sport Applications
Authors: Aroganam Gobinath , Manivannan Nadarajah , Harrison David
Published: April 2019

This review paper discusses the trends and projections for wearable technology in the consumer sports sector (excluding professional sport). Analyzing the role of wearable technology for different users and why there is such a need for these devices in everyday lives. It shows how different sensors are influential in delivering a variety of readings that are useful in many ways regarding sport attributes. Wearables are increasing in function, and through integrating technology, users are gathering more data about themselves. The amount of wearable technology available is broad, each having its own role to play in different industries. Inertial measuring unit (IMU) and Global Positioning System (GPS) sensors are predominantly present in sport wearables but can be programmed for different needs. In this review, the differences are displayed to show which sensors are compatible and which ones can evolve sensor technology for sport applications.
Doppler Data Association Scheme for Multi-Target Tracking in an Active Sonar System
Authors: Yao Yu , Zhao Junhui , Wu Lenan
Published: April 2019

In many wireless sensors, the target kinematic states include location and Doppler information that can be observed from a time series of range and velocity measurements. In this work, we present a tracking strategy for comprising target velocity components as part of the measurement supplement procedure and evaluate the advantages of the proposed scheme. Data association capability can be considered as the key performance for multi-target tracking in an active sonar system. Then, we proposed an enhanced Doppler data association (DDA) scheme which exploits target range and target velocity components for linear multi-target tracking. If the target velocity measurements are not incorporated into target kinematic state tracking, the linear filter bank for the combination of target velocity components can be implemented. Finally, a significant enhancement in the multi-target tracking capability provided by the proposed DDA scheme with the linear multi-target combined probabilistic data association method is demonstrated in a sonar underwater scenario.
Parallel Transmission of Distributed Sensor Based on SCTP and TCP for Heterogeneous Wireless Networks in IoT
Authors: Sun Weifeng , Yu Shumiao , Xing Yuanxun , Qin Zhenquan
Published: April 2019

Sensors in the Internet of Things (IoT) generate large amounts of data, which requires high-speed data transmission. In order to achieve the parallel transmissions of the wireless sensor network on the transmission layer, the performance of stream control transmission protocol (SCTP) and transmission control protocol (TCP) in the wireless sensor network under different packet error rates was simulated and compared. A dynamic multipath handover method for SCTP (MS-SCTP) was proposed to improve the transmission performance, which selects the transmission path according to the packet error rate and the retransmission ratio in the sender’s buffer. The TCP and SCTP protocol switching method (TCP-SCTP) was proposed to detect the current network traffic and adjust the MS-SCTP or TCP method. Analysis and simulation results show that MS-SCTP and TCP-SCTP could improve network throughput and reduce packet loss rate. MS-SCTP and TCP-SCTP can be combined with other technologies and channel allocation algorithms to improve network traffic.
An Advanced Algorithm for Higher Network Navigation in Social Internet of Things Using Small-World Networks
Authors: Amin Farhan , Abbasi Rashid , Rehman Abdul , Choi Gyu
Published: April 2019

The Internet of Things (IoT) is a recent evolutionary technology that has been the primary focus of researchers for the last two decades. In the IoT, an enormous number of objects are connected together using diverse communications protocols. As a result of this massive object connectivity, a search for the exact service from an object is difficult, and hence the issue of scalability arises. In order to resolve this issue, the idea of integrating the social networking concept into the IoT, generally referred as the Social Internet of Things (SIoT) was introduced. The SIoT is gaining popularity and attracting the attention of the research community due to its flexible and spacious nature. In the SIoT, objects have the ability to find a desired service in a distributed manner by using their neighbors. Although the SIoT technique has been proven to be efficient, heterogeneous devices are growing so exponentially that problems can exist in the search for the right object or service from a huge number of devices. In order to better analyze the performance of services in an SIoT domain, there is a need to impose a certain set of rules on these objects. Our novel contribution in this study is to address the link selection problem in the SIoT by proposing an algorithm that follows the key properties of navigability in small-world networks, such as clustering coefficients, path lengths, and giant components. Our algorithm empowers object navigability in the SIoT by restricting the number of connections for objects, eliminating old links or having fewer connections. We performed an extensive series of experiments by using real network data sets from social networking sites like Brightkite and Facebook. The expected results demonstrate that our algorithm is efficient, especially in terms of reducing path length and increasing the average clustering coefficient. Finally, it reflects overall results in terms of achieving easier network navigation. Our algorithm can easily be applied to a single node or even an entire network.
A Lightweight Three-Factor Authentication and Key Agreement Scheme in Wireless Sensor Networks for Smart Homes
Authors: Shin Sooyeon , Kwon Taekyoung
Published: April 2019

A wireless sensor network (WSN) is used for a smart home system’s backbone that monitors home environment and controls smart home devices to manage lighting, heating, security and surveillance. However, despite its convenience and potential benefits, there are concerns about various security threats that may infringe on privacy and threaten our home life. For protecting WSNs for smart homes from those threats, authentication and key agreement are basic security requirements. There have been a large number of proposed authentication and key agreement scheme for WSNs. In 2017, Jung et al. proposed an efficient and security enhanced anonymous authentication with key agreement scheme by employing biometrics information as the third authentication factor. They claimed that their scheme resists on various security attacks and satisfies basic security requirements. However, we have discovered that Jung et al.’s scheme possesses some security weaknesses. Their scheme cannot guarantee security of the secret key of gateway node and security of session key and protection against user tracking attack, information leakage attack, and user impersonation attack. In this paper, we describe how those security weaknesses occur and propose a lightweight three-factor authentication and key agreement scheme in WSNs for smart homes, as an improved version of Jung et al.’s scheme. We then present a detailed analysis of the security and performance of the proposed scheme and compare the analysis results with other related schemes.
Adaptive Selection of Truncation Radius in Calderon’s Method for Direct Image Reconstruction in Electrical Capacitance Tomography
Authors: Sun Shijie , Xu Lijun , Cao Zhang , Sun Jiangtao , Tian Wenbin
Published: April 2019

Calderon’s method has been successfully used for the direct image reconstruction in electrical capacitance tomography. In the method, the truncation radius adopted in numerical integral greatly influences the reconstruction results. In the past, the truncation radius is selected as a constant empirically according to the permittivity distribution pattern and noise level. In this paper, the influence of the truncation radius in Calderon’s method on the reconstruction results was first analyzed by numerical simulation. Then, a strategy for adaptive selection of the truncation radius was proposed. The amplitude information of the elements in the scattering transform matrix computed from the Dirichlet-to-Neumann (DN) map was used to determine the range for the truncation radius selection, and the phase information was further used to select a proper truncation radius value within this selection range. Finally, experiments were carried out to verify the strategy. Experimental results showed that small relative image error and good visual effect could be obtained by using the truncation radius selected by the proposed strategy.
Active PZT Composite Microfluidic Channel for Bioparticle Manipulation
Authors: Janusas Tomas , Pilkauskas Kestutis , Janusas Giedrius , Palevicius Arvydas
Published: April 2019

The concept of active microchannel for precise manipulation of particles in biomedicine is reported in this paper. A novel vibration-assisted thermal imprint method is proposed for effective formation of a microchannel network in the nanocomposite piezo polymer layer. In this method, bulk acoustic waves of different wavelengths excited in an imprinted microstructure enable it to function in trapping–patterning, valve, or free particle passing modes. Acoustic waves are excited using a special pattern of electrodes formed on its top surface and a single electric ground electrode formed on the bottom surface. To develop the microchannel, we first started with lead zirconate titanate (PZT) nanopowder [Pb (Zrx, Ti1−x) O3] synthesis. The PZT was further mixed with three different binding materials—polyvinyl butyral (PVB), poly(methyl methacrylate) (PMMA), and polystyrene (PS)—in benzyl alcohol to prepare a screen-printing paste. Then, using conventional screen printing techniques, three types of PZT coatings on copper foil substrates were obtained. To improve the voltage characteristics, the coatings were polarized. Their structural and chemical composition was analyzed using scanning electron microscope (SEM), while the mechanical and electrical characteristics were determined using the COMSOL Multiphysics model with experimentally obtained parameters of periodic response of the layered copper foil structure. The hydrophobic properties of the PZT composite were analyzed by measuring the contact angle between the distilled water drop and the three different polymer composites: PZT with PVB, PZT with PMMA, and PZT with PS. Finally, the behavior of the microchannel formed in the nanocomposite piezo polymer was simulated by applying electrical excitation signal on the pattern of electrodes and then analyzed experimentally using holographic interferometry. Wave-shaped vibration forms of the microchannel were obtained, thereby enabling particle manipulation.
Risk Analysis and Safer Layout Design Solutions for Bicycles in Four-Leg Urban Intersections
Authors: Cantisani Giuseppe , Moretti Laura , De Andrade Barbosa Yessica
Published: April 2019

The road safety of vulnerable users is a current issue; in densely populated areas, the use of alternative and light mobility vehicles is growing in popularity, and their users conflict with vehicles having larger dimensions and masses. This study focuses on the risk analysis of collision between bicyclists and motorized vehicles in urban intersections. Twenty-five urban four-leg intersections, with and without bike paths, were considered in order to identify the conflict points, calculate their hazardousness, and assess the risk of collision using a probabilistic approach. Traffic light setup, yield line retraction, design of areas, and counter-clockwise circulation reserved for bicyclists are the geometrical and functional approaches proposed to mitigate the risk of collision. Two risk-based approaches proposed by the authors were implemented—the first examines all identified conflict points, while the second assesses the risk condition of the overall intersection. The obtained results show that the number of conflict points varied between 32 and 112 and the risk of collision varied between 4.57 × 10−2 and 2.46 × 10−1. The proposed assessment allowed us to make an objective comparison between the possible layouts for various traffic mixes and design conditions, and to identify the most effective solutions. Significant differences in terms of risk were found. Each mitigation strategy should be motivated by a reasoned decision considering the different needs of all road users, traffic demand, and geometrical and functional constraints.
Effects of the Use of Good Agricultural Practices on Aflatoxin Levels in Maize Grown in Nandi County, Kenya
Authors: Marete Grace , Kanja Laetitia , Mbaria James , Okumu Mitchel , Ateku Penina , Korhonen Hannu , Joutsjoki Vesa
Published: April 2019

Aflatoxin contaminated maize is of public health concern in Kenya. Training farmers on good agricultural practice (GAP) has been touted as a mitigative measure. Little is known of the effect of such training on aflatoxin levels in maize grown in Kenya. This study evaluated what effect training farmers on GAP has on aflatoxin levels in maize grown in Kaptumo, Kilibwoni, and Kipkaren divisions in Nandi County, Kenya. Ninety farmers were recruited into farmer field schools and a questionnaire on GAP administered to each farmer. Maize samples were collected from the farmers and analyzed for aflatoxins using competitive enzyme-linked immunosorbent assay (c-ELISA). All farmers weeded their farms before planting, prepared the land, correctly spaced the seedlings, sorted the maize after shelling, cleaned stores before use and knew that aflatoxins were harmful to humans and animals. Eighty-one farmers did early planting, 88/90 did stooking after harvesting, 89/90 applied fertilizer, 89/90 cleared bushes around the stores, 87/90 used wooden pallets to store maize, 89/90 dried maize after harvesting, 83/90 did crop rotation, and 89/90 used clean transport. Moreover, 62/90 had a relative who had died from liver cancer, 13/90 had fed damaged/rotten seeds to animals, and 45/90 had stored harvested seeds on the ground. The mean aflatoxin levels in season 1 were significantly different from season 2 (1.918 ± 1.065; 1.301 ± 1.501). Our findings suggest that some aspects of the training on GAP were better received than others. Training farmers on GAP results in a decrease in aflatoxin levels in maize grown in Nandi County. Farmers in other maize growing areas of Kenya may benefit from similar training on GAP.
Three Bizarre Presidential-Election Scenarios: The Perils of Simplism
Authors: Potthoff Richard F.
Published: April 2019

The 1968, 2000, and (future) 2024 U.S. presidential elections provide settings for deliberately provocative, offbeat scenarios that might have happened or could happen. Throughout, the Electoral College and plurality voting both receive blame. Scenario 1 exposes a quirk previously unnoticed: Under (albeit special) conditions, certain 1968 Humphrey voters could have made Humphrey rather than Nixon the election victor had they voted strategically for Wallace instead of Humphrey. In Scenario 2, overlooked nonidentifiability of undervotes would have plagued the 2000 Florida recount had the U.S. Supreme Court not halted it, thus raising questions about the foresightfulness of almost everyone involved; but, in addition, Gore missed an opportunity that, through use of proper statistical sampling, could have propelled him to victory. In Scenario 3, National Popular Vote Interstate Compact supporters fail to foresee that even one state, by changing its method for presidential voting, can wreck this innovative and widely promoted compact.
Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon
Authors: Reis Cláudia , Lopes António
Published: April 2019

The increase and optimization of urban vegetation has been considered an effective mitigation measure of an urban heat island (UHI), with positive effects on human thermal comfort. In this study, the cooling potential of all green spaces in Lisbon was estimated. For that, several mobile measurements of air temperature data were made in a single park (Gulbenkian’s Garden). These measurements were used for the interpolation of air temperature. Furthermore, urban biomass was estimated using remote sensing products, namely Landsat satellite images. Ultimately, a linear regression model was built from the relation between vegetation density and air temperature. Results regarding the estimation of biomass (AGB) in the city of Lisbon were higher in winter than in summer. The urban green spaces cooling potential model showed that for every decrease of 1 °C in air temperature between a measuring point and a reference station we need to increase the area covered by vegetation by 50 m2 (planar measure). This methodology can be applied in other urban areas for the quantification of the cooling effect provided by vegetation in order to improve urban climate thermal conditions and human well-being and, consequently, to mitigate some consequences of future climate change.
Do Transformational Leaders Engage Employees in Sustainable Innovative Work Behaviour? Perspective from a Developing Country
Authors: Yi Li , Uddin Md. , Das Anupam , Mahmood Monowar , Sohel Shanewaz
Published: April 2019

Inadequate and inconclusive studies of the role of transformational leadership (TL) on employee creative process engagement (CPE) and sustainable innovative work behaviour (IWB) have motivated the authors to further advance knowledge in this aspect of the workplace. In doing so, the present study seeks to extend the understanding of innovative work behaviour by the involvement of TL and its subordinates through engaging employees in the creative process. The authors adopted the deductive reasoning approach to measure the observed relationships using structural equation modelling (SEM) through SmartPLS 2, a second-generation integrated regression model for statistical measurement. The results from self-report and others’ reported questionnaires reveal that transformational leaders can engage their subordinates in the creative process and sustainable innovative outcomes by influencing employee intrinsic motivation and proactive behaviour. However, the mediating effect of CPE on TL and IWB is not supported. Lastly, the authors discuss the findings and contributions of these empirical findings in theory and practice. In addition to the potential implications of the examined results, this study also recommends directions for further research in the light of its limitations.
Measurement of Rural Residents’ Mobility in Western China: A Case Study of Qingyang, Gansu Province
Authors: Liu Chunfang , Yu Bin , Zhu Yue , Liu Licheng , Li Pengjie
Published: April 2019

Mobility is a popular topic in the fields of humanities and social sciences. China’s rapid urbanization has resulted in the acceleration of urban–rural mobility. Moreover, the implementation of the New Urbanization and Rural Revitalization Strategy has demonstrated the prospects of urban–rural integration and development. However, research on rural mobility is mainly focused in the fields of economics and sociology, with insufficient attention paid to spatial mobility. The main purpose of this study is to introduce a new theoretical explanation of the four dimensions of rural mobility based on a complete understanding of the current socio-economic background, namely, network mobility, green mobility, people-oriented mobility, and smart mobility. On this basis, a rural mobility evaluation index system is proposed by attempting to build a synthetic rural mobility index from the four aforementioned dimensions. Qingyang, a typical city in Western China located in the Loess Hilly Region, is taken as an example. Accordingly, the comprehensive rural and four-dimensional mobilities are analyzed and evaluated, and the effectiveness of the index system is verified. Results show that Qingyang’s rural mobility is at a low level, but differences in the types of rural residents, districts and counties, and dimensions of mobility are observed. At the end of this paper, the inclusion of mobility promotion in the policy system of rural revitalization is emphasized.
The White Marbles of the Tomb of Christ in Jerusalem: Characterization and Provenance
Authors: Moropoulou Antonia , Delegou Ekaterini T. , Apostolopoulou Maria , Kolaiti Aikaterini , Papatrechas Christos , Economou George , Mavrogonatos Constantinos
Published: April 2019

In this work, samples of the white marbles enclosing the Tomb of Christ, as well as samples from the interior marble facades of the Holy Aedicule structure surrounding the Tomb of Christ in the Church of Resurrection in Jerusalem, are investigated using petrographic and isotopic analysis. The aim is to characterize the marble samples and investigate their provenance. The results demonstrate that all examined marble samples originate from Proconnesos (Marmara island), and can be attributed to the so-called Proconnesos-1 variety. Published maximum grain size (MGS) and isotopic (δ18O and δ13C) values of Proconessos quarries are compared with the respective values displayed by the marble samples of the Holy Aedicule, aiming to achieve—to a certain degree—intra-site discriminations. A number of ancient quarries are excluded through this double parameter criterion as sources for the examined Holy Aedicule marbles. The discussion of petrographic and isotopic results in relation to historical testimonies and previously published archaeometry results, regarding the mortars of the Holy Aedicule, reveal that Proconnesos marble was the material of choice used at different construction phases of the Holy Aedicule, from the time of Constantine the Great and throughout the centuries, both for the cladding of the Holy Tomb and the interior facings of the Tomb Chamber and the Chapel of the Angel.