bluuebunny/crossref_metadata_2025 huggingface dataset:
Antiviral Effect of Lithium Chloride and Diammonium Glycyrrhizinate on Porcine Deltacoronavirus In Vitro
Authors: Zhai Xiaofeng , Wang Shilei , Zhu Mengyan , He Wei , Pan Zhongzhou , Su Shuo
Published: September 2019

Porcine deltacoronavirus (PDCoV) is an emerging global swine virus that has a propensity for interspecies transmission. It was identified in Hong Kong in 2012. Given that neither specific antiviral drugs nor vaccines are available for newly emerging porcine deltacoronavirus, searching for effective antiviral drugs is a high priority. In this study, lithium chloride (LiCl) and diammonium glycyrrhizinate (DG), which are host-acting antivirals (HAAs), were tested against PDCoV. We found that LiCl and DG inhibited PDCoV replication in LLC-PK1 cells in a dose-dependent manner. The antiviral effects of LiCl and DG occurred at the early stage of PDCoV replication, and DG also inhibited virus attachment to the cells. Moreover, both drugs inhibited PDCoV-induced apoptosis in LLC-PK1 cells. This study suggests LiCl and DG as new drugs for the treatment of PDCoV infection.
Comprehensive Analysis of the Safety Profile of a Single-Stranded RNA Nano-Structure Adjuvant
Authors: Park Hyeong-Jun , Ko Hae Li , Won Dong-Hoon , Hwang Da-Bin , Shin Yoo-Sub , Kwak Hye-Won , Kim Hye-Jung , Yun Jun-Won , Nam Jae-Hwan
Published: September 2019

Adjuvants enhance the efficacy of vaccines by stimulating immune response-related gene expression and pathways. Although some adjuvants have been approved for commercial use in human vaccines (e.g., Alum, MF59, and AS03), they might elicit adverse side effects, such as autoimmune diseases. Recently, we developed a novel single-stranded RNA (ssRNA) nano-structure adjuvant, which can stimulate both Th1 and Th2 responses. In this study, we evaluated the safety and toxicological profiles of this ssRNA nano-structure adjuvant in vitro and in vivo. Mice were intramuscularly immunized with the ssRNA nano-structure adjuvant three times, once every 2 weeks. The results indicate no significant differences in hematological and serum biochemistry parameters between the ssRNA-treated groups and the control group. From a histopathological perspective, no evidence of tissue damage was found in any group. The levels of IgE and anti-nuclear antibodies, which are markers of autoimmune disease, were not different between the ssRNA-treated groups and the control group. The findings of this study suggest that the ssRNA nano-structure can be used as a safe adjuvant to increase vaccine efficacies.
Affective Embodiment and the Transmission of Affect in Ex Machina
Authors: Fahn Chia Wei
Published: September 2019

The focus of posthuman thought centers on a shift in the humanistic paradigm; focusing on a state of existence that lies beyond being “human”, including bioengineering, artificial intelligence, and synthetic embodiment. Inspired by continuous breakthroughs in the research and creation of artificial intelligence, science fiction has moved beyond the realm of portraying artificial intelligence that is capable of conscious thought to speculate upon a future creation of machines that feel, and initiate feeling in return. The influence of posthuman discourse is prevalent in science fiction film narratives and demonstrates a heavy emphasis on the deconstruction of humanity’s belief in our unique emotional capabilities. This paper draws upon Alex Garland’s 2015 original film and screenplay Ex Machina as textual reference to explore posthuman prospects in AI by envisioning possibilities where emotional capacity no longer separates humans and machines. In a world where artificial intelligence could be given artificial life, how is affect addressed, and redressed? This paper argues the importance of affective embodiment and material experiences in AI that shape the future of posthuman becoming.
Photonic Time-Stretch Technology with Prismatic Pulse Dispersion towards Fast Real-Time Measurements
Authors: Yang Lei , Chen Hui , Ma Jun , Zhu Qian , Yang Tong , Xie Hongbo
Published: September 2019

Photonic time-stretch (PTS) technology enables revolutionary technical breakthroughs in ultrafast electronic and optical systems. By means of employing large chromatic dispersion to map the spectrum of an ultrashort optical pulse into a stretched time-domain waveform (namely, using the dispersive Fourier transformation), PTS overcomes the fundamental speed limitations of conventional techniques. The chromatic dispersion utilized in PTS can be implemented using multiple optical prism arrays, which have the particular advantages of low loss in the extended spectrum outside of the specific telecommunication band, flexibility, and cost-effectiveness. In this article, we propose and demonstrate the PTS technology established for a pair of prisms, which works as a data acquisition approach in ultrafast digitizing, imaging, and measurement regimes.
Preparation of Chitosan Stacking Membranes for Adsorption of Copper Ions
Authors: Zhang Xiaoxiao , Shi Xuejuan , Ma Liang , Pang Xuan , Li Lili
Published: September 2019

Chitosan (CS) stacking mats with excellent performance for adsorption of copper ions (Cu(II)) in wastewater were fabricated by alternating electrospinning/electrospraying. The hierarchical structure of the stacking membranes was designed by CS micro-hemispheres sandwiched between CS fibers. The CS stack membranes prepared by the electrospinning technology could effectively increase the specific surface area, and thus, facilitate the adsorption of copper ions. CS stacking membranes with three layers reached adsorption equilibrium within 60 min, and had a maximum absorbance of 276.2 mg/g. The absorbance performance was superior to most of the reported CS adsorbents. Compared with CS fiber mats which were dominated by CS chemical structure during adsorption, the stacking structure of CS membranes contributed to the high efficient capability, and exhibited the multilayer adsorption behavior. This study may develop a promising method for the design of environmentally-friendly natural polymer adsorbents to remove Cu(II) in wastewater.
Study on the Preparation and Conjugation Mechanism of the Phosvitin-Gallic Acid Complex with an Antioxidant and Emulsifying Capability
Authors: Jiang Bin , Wang Xiaojing , Wang Linlin , Wu Shuang , Li Dongmei , Liu Chunhong , Feng Zhibiao
Published: September 2019

To develop a novel emulsifier with an antioxidant capacity, a phosvitin-gallic acid (Pv–GA) complex was prepared via a free-radical method. This emulsifier characterizes some key technologies. Changes in the molecular weight of the Pv–GA complex were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE) and the matrix-assisted laser desorption/ionization time of light mass spectrometry (MALDI-TOF-MS). Fourier transform infrared spectroscopy (FTIR) indicated that C=O, C–N and N–H groups were also likely to be involved in the formation of the complex. A redshift was obtained in the fluorescence spectrogram, thereby proving that the covalent combination of Pv and GA was a free radical-forming complex. The results indicated that Pv and GA were successfully conjugated. Meanwhile, the secondary structure of Pv showed significant changes after conjugation with GA. The antioxidant activity and emulsifying properties of the Pv–GA complex were studied. The antioxidant activity of the Pv–GA complex proved to be much higher than that of the Pv, via assays of the scavenging activities of 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radicals and because of their ability to reduce power. The emulsification activity of the Pv–GA complex was also slightly higher than that of Pv. To function with the most demanding antioxidant and emulsification activities, the optimum conjugation condition was Pv (5 mg/mL) conjugated 1.5 mg/mL GA. Furthermore, the mechanism of Pv–GA conjugation was studied. This study indicated that GA could quench the inner fluorescence of Pv, and this quenching was static. There was a strong interaction between GA and Pv, which was not obviously affected by the temperature. Furthermore, several binding sites were close to 1, indicating that there was an independent class of binding sites on Pv for GA at different temperatures. The conjugation reaction was a spontaneous reaction, and the interaction forces of GA and Pv were hydrogen bonds and van der Waals force.
Remotely Sensed Variables of Ecosystem Functioning Support Robust Predictions of Abundance Patterns for Rare Species
Authors: Arenas-Castro Salvador , Regos Adrián , Gonçalves João F. , Alcaraz-Segura Domingo , Honrado João
Published: September 2019

Global environmental changes are affecting both the distribution and abundance of species at an unprecedented rate. To assess these effects, species distribution models (SDMs) have been greatly developed over the last decades, while species abundance models (SAMs) have generally received less attention even though these models provide essential information for conservation management. With population abundance defined as an essential biodiversity variable (EBV), SAMs could offer spatially explicit predictions of species abundance across space and time. Satellite-derived ecosystem functioning attributes (EFAs) are known to inform on processes controlling species distribution, but they have not been tested as predictors of species abundance. In this study, we assessed the usefulness of SAMs calibrated with EFAs (as process-related variables) to predict local abundance patterns for a rare and threatened species (the narrow Iberian endemic ‘Gerês lily’ Iris boissieri; protected under the European Union Habitats Directive), and to project inter-annual fluctuations of predicted abundance. We compared the predictive accuracy of SAMs calibrated with climate (CLI), topography (DEM), land cover (LCC), EFAs, and combinations of these. Models fitted only with EFAs explained the greatest variance in species abundance, compared to models based only on CLI, DEM, or LCC variables. The combination of EFAs and topography slightly increased model performance. Predictions of the inter-annual dynamics of species abundance were related to inter-annual fluctuations in climate, which holds important implications for tracking global change effects on species abundance. This study underlines the potential of EFAs as robust predictors of biodiversity change through population size trends. The combination of EFA-based SAMs and SDMs would provide an essential toolkit for species monitoring programs.
Re-Discovering Ancient Landscapes: Archaeological Survey of Mound Features from Historical Maps in Northwest India and Implications for Investigating the Large-Scale Distribution of Cultural Heritage Sites in South Asia
Authors: Green Adam S. , Orengo Hector A. , Alam Aftab , Garcia-Molsosa Arnau , Green Lillian M. , Conesa Francesc , Ranjan Amit , Singh Ravindra N. , Petrie Cameron A.
Published: September 2019

Incomplete datasets curtail the ability of archaeologists to investigate ancient landscapes, and there are archaeological sites whose locations remain unknown in many parts of the world. To address this problem, we need additional sources of site location data. While remote sensing data can often be used to address this challenge, it is enhanced when integrated with the spatial data found in old and sometimes forgotten sources. The Survey of India 1” to 1-mile maps from the early twentieth century are one such dataset. These maps documented the location of many cultural heritage sites throughout South Asia, including the locations of numerous mound features. An initial study georeferenced a sample of these maps covering northwest India and extracted the location of many potential archaeological sites—historical map mound features. Although numerous historical map mound features were recorded, it was unknown whether these locations corresponded to extant archaeological sites. This article presents the results of archaeological surveys that visited the locations of a sample of these historical map mound features. These surveys revealed which features are associated with extant archaeological sites, which were other kinds of landscape features, and which may represent archaeological mounds that have been destroyed since the maps were completed nearly a century ago. Their results suggest that there remain many unreported cultural heritage sites on the plains of northwest India and the mound features recorded on these maps best correlate with older archaeological sites. They also highlight other possible changes in the large-scale and long-term distribution of settlements in the region. The article concludes that northwest India has witnessed profound changes in its ancient settlement landscapes, creating in a long-term sequence of landscapes that link the past to the present and create a foundation for future research and preservation initiatives.
Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data
Authors: Berninger Anna , Lohberger Sandra , Zhang Devin , Siegert Florian
Published: September 2019

Globally available high-resolution information about canopy height and AGB is important for carbon accounting. The present study showed that Pol-InSAR data from TS-X and RS-2 could be used together with field inventories and high-resolution data such as drone or LiDAR data to support the carbon accounting in the context of REDD+ (Reducing Emissions from Deforestation and Forest Degradation) projects.
NurseNet: Monitoring Elderly Levels of Activity with a Piezoelectric Floor
Authors: Minvielle Ludovic , Audiffren Julien
Published: September 2019

Monitoring the activity of elderly individuals in nursing homes is key, as it has been shown that physical activity leads to significant health improvement. In this work, we introduce NurseNet, a system that combines an unobtrusive, affordable, and robust piezoelectric floor sensor with a convolutional neural network algorithm, which aims at measuring elderly physical activity. Our algorithm is trained using signal embedding based on atoms of a pre-learned dictionary and focuses the network’s attention on step-related signals. We show that NurseNet is able to avoid the main limitation of floor sensors by recognizing relevant signals (i.e., signals produced by patients) and ignoring events related to the medical staff, offering a new tool to monitor elderly activity in nursing homes efficiently.
Leveraging a Publish/Subscribe Fog System to Provide Collision Warnings in Vehicular Networks
Authors: Patra Subhadeep , Manzoni Pietro , T. Calafate Carlos , Zamora Willian , Cano Juan-Carlos
Published: September 2019

Fog computing, an extension of the Cloud Computing paradigm where routers themselves may provide the virtualisation infrastructure, aims at achieving fluidity when distributing in-network functions, in addition to allowing fast and scalable processing, and exchange of information. In this paper we present a fog computing architecture based on a “content island” which interconnects sets of “things” to exchange and process data among themselves or with other content islands. We then present a use case that focuses on a smartphone-based forward collision warning application for a connected vehicle scenario. This application makes use of the optical sensor of smartphones to estimate the distance between the device itself and other vehicles in its field of view. The vehicle travelling directly ahead is identified relying on the information from the GPS, camera, and inter-island communication. Warnings are generated at both content islands, if the driver does not maintain a predefined safe distance towards the vehicle ahead. Experiments performed with the application show that with the developed method, we are able to estimate the distance between vehicles, and the inter-island communication has a very low overhead, resulting in improved performance. On comparing our proposed solution based on edge/fog computing with a cloud-based api, it was observed that our solution outperformed the cloud-based api, thus making us optimistic of the utility of the proposed architecture.
Risk-Aware Resource Management in Public Safety Networks
Authors: Vamvakas Panagiotis , Tsiropoulou Eirini Eleni , Papavassiliou Symeon
Published: September 2019

Modern Public Safety Networks (PSNs) are assisted by Unmanned Aerial Vehicles (UAVs) to provide a resilient communication paradigm during catastrophic events. In this context, we propose a distributed user-centric risk-aware resource management framework in UAV-assisted PSNs supported by both a static UAV and a mobile UAV. The mobile UAV is entitled to a larger portion of the available spectrum due to its capability and flexibility to re-position itself, and therefore establish better communication channel conditions to the users, compared to the static UAV. However, the potential over-exploitation of the mobile UAV-based communication by the users may lead to the mobile UAV’s failure to serve the users due to the increased levels of interference, consequently introducing risk in the user decisions. To capture this uncertainty, we follow the principles of Prospect Theory and design a user’s prospect-theoretic utility function that reflects user’s risk-aware behavior regarding its transmission power investment to the static and/or mobile UAV-based communication option. A non-cooperative game among the users is formulated, where each user determines its power investment strategy to the two available communication choices in order to maximize its expected prospect-theoretic utility. The existence and uniqueness of a Pure Nash Equilibrium (PNE) is proven and the convergence of the users’ strategies to it is shown. An iterative distributed and low-complexity algorithm is introduced to determine the PNE. The performance of the proposed user-centric risk-aware resource management framework in terms of users’ achievable data rate and spectrum utilization, is achieved via modeling and simulation. Furthermore, its superiority and benefits are demonstrated, by comparing its performance against other existing approaches with regards to UAV selection and spectrum utilization.
Multiple-Antenna Cooperative Spectrum Sensing Based on the Wavelet Transform and Gaussian Mixture Model
Authors: Zhang Shunchao , Wang Yonghua , Yuan Hantao , Wan Pin , Zhang Yongwei
Published: September 2019

Spectrum sensing is a core technology in cognitive radio (CR) systems. In this paper, a multiple-antenna cooperative spectrum sensor based on the wavelet transform and Gaussian mixture model (MAWG) is proposed. Compared with traditional methods, the MAWG method avoids the derivation of the threshold and improves the performance of single secondary user (SU) spectrum sensing in cases of channel loss and hidden terminal. The MAWG method reduces the noise of the signal which collected by the multiple-antenna SUs through the wavelet transform. Then, the fusion center (FC) extracts the statistical features from the signals that are pre-processed by the wavelet transform. To extract the statistical features, an sensing data fusion method is proposed. The MAWG method divides all SUs that are involved in the cooperative spectrum sensing into two clusters and extracts a two-dimensional feature vector. In order to avoid complicated decision threshold derivation, the Gaussian mixture model (GMM) is used to train a classifier for spectrum sensing according to these two-dimensional feature vectors. Simulation experiments are performed in the κ − μ channel model. The simulation shows that the MAWG can effectively improve spectrum sensing performance under the κ − μ channel model.
A Smart Tongue Depressor-Based Biosensor for Glucose
Authors: Luo Xiaojin , Shi Weihua , Liu Yiqun , Sha Pengju , Chu Yanan , Cui Yue
Published: September 2019

The development of new bioelectronic platforms for direct interactions with oral fluid could open up significant opportunities for healthcare monitoring. A tongue depressor is a widely used medical tool that is inserted into the mouth, where it comes into close contact with saliva. Glucose is a typical salivary biomarker. Herein, we report—for the first time—a tongue depressor-based biosensor for the detection of glucose in both phosphate buffer and real human saliva. Carbon nanotubes (CNTs) are attractive electronic materials, with excellent electrochemical properties. The sensor is constructed by printing CNTs and silver/silver chloride (Ag/AgCl) to form three electrodes in an electrochemical cell: Working, reference, and counter electrodes. The enzyme glucose oxidase (GOD) is immobilized on the working electrode. The glucose detection performance of the sensor is excellent, with a detection range of 7.3 μM to 6 mM. The glucose detection time is about 3 min. The discretion between healthy people’s and simulated diabetic patients’ salivary samples is clear and easy to tell. We anticipate that the biosensor could open up new opportunities for the monitoring of salivary biomarkers and advance healthcare applications.
Performance Assessment of an Ultra Low-Cost Inertial Measurement Unit for Ground Vehicle Navigation
Authors: Gonzalez Rodrigo , Dabove Paolo
Published: September 2019

Nowadays, navigation systems are becoming common in the automotive industry due to advanced driver assistance systems and the development of autonomous vehicles. The MPU-6000 is a popular ultra low-cost Microelectromechanical Systems (MEMS) inertial measurement unit (IMU) used in several applications. Although this mass-market sensor is used extensively in a variety of fields, it has not caught the attention of the automotive industry. Moreover, a detailed performance analysis of this inertial sensor for ground navigation systems is not available in the previous literature. In this work, a deep examination of one MPU-6000 IMU as part of a low-cost navigation system for ground vehicles is provided. The steps to characterize the performance of the MPU-6000 are divided in two phases: static and kinematic analyses. Besides, an additional MEMS IMU of superior quality is also included in all experiments just for the purpose of comparison. After the static analysis, a kinematic test is conducted by generating a real urban trajectory registering an MPU-6000 IMU, the higher-grade MEMS IMU, and two GNSS receivers. The kinematic trajectory is divided in two parts, a normal trajectory with good satellites visibility and a second part where the Global Navigation Satellite System (GNSS) signal is forced to be lost. Evaluating the attitude and position inaccuracies from these two scenarios, it is concluded in this preliminary work that this mass-market IMU can be considered as a convenient inertial sensor for low-cost integrated navigation systems for applications that can tolerate a 3D position error of about 2 m and a heading angle error of about 3 °.
A Temperature-Insensitive Resonant Pressure Micro Sensor Based on Silicon-on-Glass Vacuum Packaging
Authors: Yan Pengcheng , Lu Yulan , Xiang Chao , Wang Junbo , Chen Deyong , Chen Jian
Published: September 2019

This paper presents a temperature-insensitive resonant pressure sensor, which is mainly composed of a silicon-on-insulator (SOI) wafer for pressure measurements and a silicon-on-glass (SOG) cap for vacuum packaging. The variations of pressure under measurement bend the pressure sensitive diaphragm and regulate the intrinsic frequencies of the resonators in the device layer. While, variations of temperature cannot significantly change the intrinsic frequencies of the resonators, due to the SOG cap to offset generated thermal stress. Numerical simulations, based on finite element analysis, were conducted to calculate the residual thermal stress and optimize the sensing structures. Experimental results show that the Q-factors of the resonators are higher than 16,000, with a differential pressure sensitivity of 11.89 Hz/kPa, a nonlinearity of 0.01% F.S and a low fitting error of 0.01% F.S with the pressure varying from 100 kPa to 1000 kPa. In particular, a temperature sensitivity of ~1 Hz/°C was obtained in the range of −45 °C to 65 °C, which is one order of magnitude lower than the previously reported counterparts.
A Novel Message-Preserving Scheme with Format-Preserving Encryption for Connected Cars in Multi-Access Edge Computing
Authors: Oh Insu , Kim Taeeun , Yim Kangbin , Lee Sun-Young
Published: September 2019

In connected cars with various electronic control unit (ECU) modules, Ethernet is used to communicate data received by the sensor in real time, but it is partially used alongside a controller area network (CAN) due to the cost. There are security threats in the CAN, such as replay attacks and denial-of-service attacks, which can disrupt the driver or cause serious damage, such as a car accident through malicious manipulation. Although several secure protocols for protecting CAN messages have been proposed, they carry limitations, such as combining additional elements for security or modifying CAN messages with a limited length. Therefore, in this paper, we propose a method for encrypting the data frame, including real data in the CAN message structure, using format-preserving encryption (FPE), which ensures that the plaintext and ciphertext have the same format and length. In this way, block ciphers such as AES-128 must be divided into two or three blocks, but FPE can be processed simultaneously by encrypting them according to the CAN message format, thus providing better security against denial-of-service attacks. Based on the 150 ms CAN message, a normal message was received from a malicious message injection of 180 ms or more for AES-128 and a malicious message injection of 100 ms or more for FPE. Finally, based on the proposed scheme, a CAN transmission environment is constructed for analyzing the encryption/decryption rate and the process of transmitting and processing the encrypted message for connected cars in multi-access edge computing (MEC). This scheme is compared with other algorithms to verify that it can be used in a real environment.
A Two-Stage Interference Suppression Scheme Based on Antenna Array for GNSS Jamming and Spoofing
Authors: Zhang Jiaqi , Cui Xiaowei , Xu Hailong , Lu Mingquan
Published: September 2019

Jamming and spoofing are the two main types of intentional interference for global navigation satellite system (GNSS) receivers. Due to the entirely different signal characteristics they have, a few techniques can deal with them simultaneously. This paper proposes a two-stage interference suppression scheme based on antenna arrays, which can detect and mitigate jamming and spoofing before the despreading of GNSS receivers. First, a subspace projection was adopted to eliminate the high-power jamming signals. The output signal is still a multi-dimensional vector so that the spatial processing technique can be used in the next stage. Then, the cyclostationarity of GNSS signals were fully excavated to reduce or even remove the noise component in the spatial correlation matrix. Thus, the signal subspace, including information of the power and the directions-of-arrival (DOAs) of the GNSS signals, can be obtained. Next, a novel cyclic correlation eigenvalue test (CCET) algorithm was proposed to detect the presence of a spoofing attack, and the cyclic music signal classification (Cyclic MUSIC) algorithm was employed to estimate the DOAs of all the navigation signals. Finally, this study employed a subspace projection again to eliminate the spoofing signals and provide a higher gain for authentic satellite signals through beamforming. All the operations were performed on the raw digital baseband signal so that they did not introduce additional computational complexity to the GNSS receiver. The simulation results show that the proposed scheme not only suppresses jamming and spoofing effectively but also maximizes the power of the authentic signals. Nonetheless, the estimated DOA of spoofing signals may be helpful for the interference source positioning in some applications.
Self-Referenced Optical Fiber Sensor for Hydrogen Peroxide Detection Based on LSPR of Metallic Nanoparticles in Layer-by-Layer Films
Authors: Goicoechea Javier , Rivero Pedro J. , Sada Samuel , Arregui Francisco J.
Published: September 2019

Intensity-based optical fiber sensors are one of the most studied sensor approaches thanks to their simplicity and low cost. Nevertheless, their main issue is their lack of robustness since any light source fluctuation, or unexpected optical setup variation is directly transferred to the output signal, which, significantly reduces their reliability. In this work, a simple and robust hydrogen peroxide (H2O2) optical fiber sensor is proposed based on the Localized Surface Plasmon Resonance (LSPR) sensitivity of silver and gold metallic nanoparticles. The precise and robust detection of H2O2 concentrations in the ppm range is very interesting for the scientific community, as it is a pathological precursor in a wide variety of damage mechanisms where its presence can be used to diagnose important diseases such as Parkinson’s disease, diabetes, asthma, or even Alzheimer’s disease). In this work, the sensing principle is based the oxidation of the silver nanoparticles due the action of the hydrogen peroxide, and consequently the reduction of the efficiency of the plasmonic coupling. At the same time, gold nanoparticles show a high chemical stability, and therefore provide a stable LSPR absorption band. This provides a stable real-time reference that can be extracted from the spectral response of the optical fiber sensor, giving a reliable reading of the hydrogen peroxide concentration.
Fast Method for Liquid Crystal Cell Spatial Variations Estimation Based on Modeling the Spectral Transmission
Authors: Shmilovich Shauli , Revah Liat , Oiknine Yaniv , August Isaac , Abdulhalim Ibrahim , Stern Adrian
Published: September 2019

Liquid crystal phase retarders are utilized by photonic devices and imaging systems for various applications, such as tunable filtering, light modulation, polarimetric imaging, remote sensing and quality inspection. Due to technical difficulties in the manufacturing process, these phase retarders may suffer from spatial non-uniformities, which degrade the performance of the systems. These non-uniformities can be characterized by measuring the spectral transmission at each voltage and each point on the liquid crystal cell, which is time consuming. In this work, we present a new fast and simple method for measuring and computationally estimating the spatial variations of a liquid crystal phase retarder with planar alignment. The method is based on measuring the spectral transmission of the phase retarder at several spatial locations and estimating it at others. The experimental results show that the method provides an accurate spatial description of the phase retarder and can be employed for calibrating relevant systems.
High Efficiency Crumpled Carbon Nanotube Heaters for Low Drift Hydrogen Sensing
Authors: Park Jeonhyeong , Jang Il Ryu , Lee Kyungtaek , Kim Hoe Joon
Published: September 2019

This work presents the fabrication of crumpled carbon nanotubes (C-CNTs) thin film heaters and their application towards high sensitivity and low drift hydrogen gas sensing. Utilizing a spray coating of pristine multi-walled carbon nanotubes (MWCNTs) and thermal shrinkage of polystyrene (PS) substrate, we have fabricated C-CNTs with closely packed junctions. Joule heating of C-CNTs gives higher temperature at a given input voltage compared to as-deposited CNTs. In addition, temperature coefficient of resistance (TCR) is analyzed for accurate temperature control and measurement of the heater. The C-CNT heaters are capable of hydrogen gas sensing while demonstrating higher measurement sensitivities along with lower drift compared to as-deposited CNT devices. In addition, the self-heating of C-CNT heaters help rapid desorption of hydrogen, and thus allowing repetitive and stable sensor operation. Our findings reveal that both CNT morphologies and heating temperatures affect the hydrogen sensing performances.
A Smartphone-Based Whole-Cell Array Sensor for Detection of Antibiotics in Milk
Authors: Lu Mei-Yi , Kao Wei-Chen , Belkin Shimshon , Cheng Ji-Yen
Published: September 2019

We present an integral smartphone-based whole-cell biosensor, LumiCellSense (LCS), which incorporates a 16-well biochip with an oxygen permeable coating, harboring bioluminescent Escherichia coli bioreporter cells, a macro lens, a lens barrel, a metal heater tray, and a temperature controller, enclosed in a light-impermeable case. The luminescence emitted by the bioreporter cells in response to the presence of the target chemicals is imaged by the phone’s camera, and a dedicated phone-embedded application, LCS_Logger, is employed to calculate photon emission intensity and plot it in real time on the device’s screen. An alert is automatically given when light intensity increases above the baseline, indicating the presence of the target. We demonstrate the efficacy of this system by the detection of residues of an antibiotic, ciprofloxacin (CIP), in whole milk, with a detection threshold of 7.2 ng/mL. This value is below the allowed maximum as defined by European Union regulations.
Predictive Maintenance with Sensor Data Analytics on a Raspberry Pi-Based Experimental Platform
Authors: Chuang Shang-Yi , Sahoo Nilima , Lin Hung-Wei , Chang Yeong-Hwa
Published: September 2019

Predictive maintenance techniques can determine the conditions of equipment in order to evaluate when maintenance should be performed. Thus, it minimizes the unexpected device downtime, lowers the maintenance costs, extends equipment lifecycle, etc. Therefore, this article developed a predictive maintenance mechanism with the construction of a test platform and data analysis along with machine learning. The information transmission of sensors was based on Raspberry Pi via the TCP/IP (Transmission Control Protocol/Internet Protocol) communication protocol. The sensors used for environmental sensing were implemented on the programmable interface controller and the data were stored in time sequence. A statistical analysis software platform was adopted for data preprocessing, modelling, and prediction to provide necessary maintenance decision. Using multivariate analysis users can obtain more information about the equipment’s status, and the administrator can also determine the operational situation before unexpected device anomalies. The developed modules are decisively helpful in preventing unpredictable losses, thus improving the quality of services.
A Calibration-Free Method Based on Grey Relational Analysis for Heterogeneous Smartphones in Fingerprint-Based Indoor Positioning
Authors: Zhang Shuai , Guo Jiming , Luo Nianxue , Zhang Di , Wang Wei , Wang Lei
Published: September 2019

The fingerprint method has been widely adopted in Wi-Fi indoor positioning because of its advantage in non-line-of-sight channels between access points (APs) and mobile users. However, the received signal strength (RSS) during the fingerprint positioning process generally varies due to the dissimilar hardware configurations of heterogeneous smartphones. This difference may degrade the accuracy of fingerprint matching between fingerprint and test data. Thus, this paper puts forward a fingerprint method based on grey relational analysis (GRA) to approach the challenge of heterogeneous smartphones and to improve positioning accuracy. Initially, the grey relational coefficient (GRC) between the RSS comparability sequence of each reference point (RP) and the RSS reference sequence of the test point (TP) is calculated. Subsequently, the grey relational degree (GRD) between each RP and TP is determined on the basis of GRC, and the K most relational RPs are selected in accordance with the value of GRD. Finally, the user location is determined by weighting the K most relational RPs that correspond to the coordinates. The main advantage of this GRA method is that it does not require device calibration when handling heterogeneous smartphone problems. We further carry out extensive experiments using heterogeneous Android smartphones in an office environment to verify the positioning performance of the proposed method. Experimental results indicate that the proposed method outperforms the existing ones no matter whether heterogeneous smartphones are used.
Correction: Wang, Y.; et al. Magnesium Alloy Matching Layer for High-Performance Transducer Applications. Sensors 2018, 18, 4424
Authors: Wang Yulei , Tao Jingya , Guo Feifei , Li Shiyang , Huang Xingyi , Dong Jie , Cao Wenwu
Published: September 2019

The authors wish to make the following corrections to this paper [...]
Improved Solid-Contact Nitrate Ion Selective Electrodes Based on Multi-Walled Carbon Nanotubes (MWCNTs) as an Ion-to-Electron Transducer
Authors: S. M. Hassan Saad , Galal Eldin Ahmed , E. Amr Abd El-Galil , A. Al-Omar Mohamed , H. Kamel Ayman , Khalifa Nagy M.
Published: September 2019

Possible improvement of the performance characteristics, reliability and selectivity of solid-contact nitrate ion-selective electrodes (ISE) (SC/NO3−-ISE) is attained by the application of a nitron-nitrate (Nit+/NO3−) ion association complex and inserting multi-walled carbon nanotubes (MWCNTs) as an ion-to-electron transducer between the ion sensing membrane (ISM) and the electronic conductor glassy carbon (GC) substrate. The potentiometric performance of the proposed electrode revealed a Nernstian slope −55.1 ± 2.1 (r² = 0.997) mV/decade in the range from 8.0 × 10−8–1 × 10−2 M with a detection limit of 2.8 × 10−8 (1.7 ng/mL). Selectivity, repeatability and reproducibility of the proposed sensors were considerably improved as compared to the coated disc electrode (GC/NO3−-ISE) without insertion of a MWCNT layer. Short-term potential stability and capacitance of the proposed sensors were tested using a current-reversal chronopotentiometric technique. The potential drift in presence of a MWCNT layer decreased from 167 μVs−1 (i.e., in absence of MWCNTs) to 16.6 μVs−1. In addition, the capacitance was enhanced from 5.99 μF (in absence of MWCNTs) to 60.3 μF (in the presence of MWCNTs). The presented electrodes were successfully applied for nitrate determination in real samples with good accuracy.
The Social Welfare Service Delivery System to Reinforce Sustainable Social Participation
Authors: Lee Mikyoung , Majer Marko , Kim Boyoung
Published: September 2019

Structural social changes and population aging are emerging as important policy issues in many countries around the world. In particular, although early retirees aged 50 or older are left behind from social welfare services and suffer from worsening social problems, policies have often only focused on elderly people aged 65 or older and vulnerable groups. Based on the theory of a welfare service delivery system, the present study analyzed the case of the Seoul 50 Plus Project in South Korea, which was established to enhance service professionalism and integrate various services to keep up with a changing environment, considering four factors: ‘integration’, ‘accessibility’, ‘systematic function distribution’, and ‘participation’. The case analysis revealed that interconnected service content, which can improve leisure activities, hobbies, and self-development, is very important along with job creation from social services to the 50 plus generation.
Managerial Overconfidence and Cost Behavior of R&D Expenditures
Authors: Hur Kang Sung , Kim Dong Hyun , Cheung Joon Hei
Published: September 2019

This study examines the impact of a CEO’s confidence level on decisions regarding research and development (R&D) expenditures. R&D is an important part of a company’s strategy for achieving long-term sustainable growth. However, due to its discretionary nature, some CEOs choose to reduce R&D costs to enhance short-term performance. In other words, R&D cost behavior may vary depending on CEO characteristics. This study examines whether, in an effort to improve their firm’s future performance, CEOs who are highly overconfident tend not to actively decrease R&D expenditures even when sales decrease. We posit that CEO overconfidence affects the cost behavior of R&D spending that is not related to their personal privileges. A cost behavior model was utilized to verify the relationship between CEOs’ propensity for overconfidence and R&D expenditures. Our findings show that highly overconfident CEOs tend not to take actions to reduce R&D costs even if sales decrease because CEO overconfidence tends to be positively related to R&D. Since R&D represents both costs and long-term investments, policy support for capitalizing R&D costs can be considered as enhancing the sustainability of businesses.
CO2 Flux Characteristics of Different Plant Communities in a Subtropical Urban Ecosystem
Authors: Zhang Kaidi , Gong Yuan , Fa Hao , Zhao Min
Published: September 2019

Shanghai, China, is a city that is relatively representative of various cities in China due to its geographical location and socio-economic dynamics. The role of urban vegetation in the carbon cycle of urban developments in these types of cities is now being studied. We focus on identifying which urban plant community types have a greater influence on CO2 flux in cities, thus providing a scientific basis for low-carbon urban greening. Based on the eddy covariance (EC) observation system, ART Footprint Tool, plant inventory, and ecological community classification, we show that the CO2 flux characteristics of different plant communities vary temporally. The carbon sink duration during summer was the longest (up to 10 h) and the carbon sink duration was the shortest during winter (7.5 h). In addition, we discovered that the CO2 flux contribution rates of different plant community types are distinct. The annual average CO2 contribution rates of the Cinnamomum camphora-Trachycarpus fortunei community and the Metasequoia glyptostroboides+Sabina chinensis community are 11.88% and 0.93%, respectively. The CO2 flux contribution rate of the same plant community differs according to season. The CO2 contribution rate of the Cinnamomum camphora-Trachycarpus fortunei community exhibits local maxima during winter and summer, with a maximum difference of 11.16%. In contrast, the Metasequoia glyptostroboides+Sabina chinensis community has a CO2 contribution rate of 0.35% during the same period. In general, summer is the season with the lowest CO2 flux contribution rate of plant communities, and winter is the season with the highest CO2 flux contribution rate. However, the Cinnamomum camphora+Salix babylonica community and the Cinnamomum camphora+Sabina chinensis community present the opposite pattern. Finally, the diurnal variation characteristics of CO2 flux in different communities have the same trend, but the peak values differ significantly. Overall, daily CO2 flux peak value of the Metasequoia glyptostroboides community and the Cinnamomum camphora-Trachycarpus fortunei community indicate that these two plant communities exhibit a strong capacity for CO2 absorption in the study area. According to these research results, urban greening efforts in subtropical climates can increase the green space covered by the Cinnamomum camphora-Trachycarpus fortunei and the Metasequoia glyptostroboides community types when urban greening, so as to appropriately reduce the CO2 emitted into the atmosphere.
Business Model Design for Latecomers in Biopharmaceutical Industry: The Case of Korean Firms
Authors: Song Changhyeon , Shin Kwangsoo
Published: September 2019

Given high business risks and interdependency with various organizations in biopharmaceutical industry, business model has become a key element for firms that aim to be more sustainable and profitable. Despite its growing importance, research on the business model design in biopharmaceutical industry is limited. In particular, there is a lack of research dealing with business models or strategies for latecomers. In the face of drastic changes such as market expansion and patent expiration, there has been growing interest in latecomer’s business model in the biopharmaceutical industry. This study identifies different types of business model designs using hierarchical clustering. Based on an empirical study of 313 biopharmaceutical firms in Korea, we find three types of business models: business diversified research firm, non-diversified research firm, and mature firm. We then compare the general characteristics and performances of each cluster. The findings indicate that business diversification of biopharmaceutical firms is beneficial in terms of profit. This implies that the biopharmaceutical firms in latecomer countries such as Korea are recommended to consider business diversification for sustainable management.
Positioning Axes of Sustainable Tourist Destinations: The Case of Aragón
Authors: García-Madurga Miguel-Ángel , Esteban-Navarro Miguel-Ángel , Delgado-de Miguel Juan-Francisco , Buil-López Menchero Tamar
Published: September 2019

The purpose of this research is to determine the optimal positioning strategies of Aragón as a sustainable tourist destination. An exploratory research is carried out based on the analysis of statistical information sources, the identification of global and multisectoral macro-trends with direct impact on the evolution of the tourist sector, and the use of the qualitative technique of the focus group. The main and secondary axes to provide a basis for the positioning strategy of the autonomous community are presented as a result.
GIS Crime Mapping to Support Evidence-Based Solutions Provided by Community-Based Organizations
Authors: Yang Byungyun
Published: September 2019

This study explored geospatial technologies to support efforts of community organizations and of the Chicago Gun Violence Research Collaboration to reduce gun-related crimes. It entailed (1) identification of spatial trends in gun-related crimes during 2012 to 2017 in each of the following four areas: Austin, East Garfield, North Lawndale, and Englewood; (2) investigation of changes in crime patterns near safe school zones in the areas before and after the establishment of the city’s safe passage routes in 2009 to protect the youth from street violence when traveling to school; and (3) development of a web-enabled mobile application to provide researchers and residents with spatial information on local crime incidents and to enable community members to collect and share their information in a GIS environment. The results of this research revealed that, although the number of safe passage routes has increased in these areas over the past several years, hotspot trends for gun-related crimes have intensified in most of the communities in these areas, which include school zones and safe passage routes. Accordingly, it turned out that GIS can serve as an ideal platform supporting collaborative efforts between communities and researchers.
Contextualized Property Market Models vs. Generalized Mass Appraisals: An Innovative Approach
Authors: Morano Pierluigi , Rosato Paolo , Tajani Francesco , Manganelli Benedetto , Di Liddo Felicia
Published: September 2019

The present research takes into account the current and widespread need for rational valuation methodologies, able to correctly interpret the available market data. An innovative automated valuation model has been simultaneously implemented to three Italian study samples, each one constituted by two-hundred residential units sold in the years 2016–2017. The ability to generate a “unique” functional form for the three different territorial contexts considered, in which the relationships between the influencing factors and the selling prices are specified by different multiplicative coefficients that appropriately represent the market phenomena of each case study analyzed, is the main contribution of the proposed methodology. The method can provide support for private operators in the assessment of the territorial investment conveniences and for the public entities in the decisional phases regarding future tax and urban planning policies.