bluuebunny/crossref_metadata_2025 huggingface dataset:
Determination of Antidepressants and Antipsychotics in Dried Blood Spots (DBSs) Collected from Post-Mortem Samples and Evaluation of the Stability over a Three-Month Period
Authors: Moretti Matteo , Freni Francesca , Valentini Beatrice , Vignali Claudia , Groppi Angelo , Visonà Silvia Damiana , Osculati Antonio Marco Maria , Morini Luca
Published: October 2019

An LC-MS/MS method for the identification and quantification of antidepressants and antipsychotics was developed on dried blood spots (DBSs). Moreover, analyte stability on DBSs within a 3-month period was monitored. Aliquots of 85 µL of blood from autopsy cases were pipetted onto DBS cards, which were dried and stored at room temperature. DBSs were analyzed in triplicate immediately, within the following 3 weeks, and after 3 months. For each analysis, a whole blood stain was extracted in phosphate buffer and purified using Solid Phase Extraction (SPE) cartridges in order to avoid matrix effects and injected in the LC-MS/MS system. Thirty-nine molecules were screened. Limits of detection (LODs) ranged between 0.1 and 3.2 ng/mL (g) and 0.1 and 5.2 ng/mL (g) for antidepressants and antipsychotics, respectively. Limits of quantification (LOQs) varied from 5 to 10.0 ng/mL for both. Sixteen cases among the 60 analyzed resulted positive for 17 different analytes; for 14 of these the method was fully validated. A general good agreement between the concentrations on DBSs and those measured in conventional blood samples (collected concurrently and stored at −20 °C) was observed. The degradation/enhancement percentage for most of the substances was lower than 20% within the 3-month period. Our results, obtained from real post-mortem cases, suggest that DBSs can be used for routine sample storage.
Auriculatone Sulfate Effectively Protects Mice Against Acetaminophen-Induced Liver Injury
Authors: Lin Liangcai , Guan Huanyu , Li Rui , Liao Xiangming , Zhao Feifei , Wang Min , Li Jing , Xu Guobo , He Xun , Zhang Jinjuan , Li Yongjun , Wang Yonglin , Zhou Meng , Liao Shanggao
Published: October 2019

Acetaminophen (APAP) overdose is very common worldwide and has been widely recognized as the leading cause of drug-induced liver injury in the Western world. In our previous investigation, auriculatone, a natural product firstly obtained from Aster auriculatus, has demonstrated a potent protective effect against APAP-induced hepatotoxicity in HL-7702 cells. However, the poor water solubility and low bioavailability restrict its application. Auriculatone sulfate (AS) is a sulfated derivative of auriculatone with highly improved water-solubility. Hepatoprotective effects against APAP-induced liver injury (AILI) showed that intragastric pretreatment with AS at 50 mg/kg almost completely prevented mice against APAP-induced increases of serum alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase and ATPase. Histological results showed that AS could protect the liver tissue damage. In addition, AS pretreatment not only significantly retained hepatic malondialdehyde and the activities of glutathione, superoxide dismutase, and glutathione peroxidase at normal levels, but also markedly suppressed the increase of pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 levels in mouse liver caused by overdose APAP. Immunohistochemical analysis showed that AS obviously attenuated the expression of CD45 and HNE in liver tissue. Further mechanisms of action investigation showed that inhibition of cytochrome P450 3A11 (CYP 3A11) and CYP2E1 enzymatic activities (but not that of CYP1A2) was responsible for APAP bioactivation. In conclusion, AS showed a hepatoprotective effect against AILI through alleviating oxidative stress and inflammation and inhibiting CYP-mediated APAP bioactivation. It may be an effective hepatoprotective agent for AILI and other forms of human liver disease.
Distribution Pattern, Emission Characteristics and Environmental Impact of Polycyclic Aromatic Hydrocarbons (PAHs) in Download Ash and Dust from Iron and Steel Enterprise
Authors: Sun Youmin , Chen Chunzhu , Ding Chun , Liu Guanghui , Zhang Guiqin
Published: October 2019

Download ash and emission dust samples were collected from sintering, coking, ironmaking and steelmaking processes of iron and steel enterprises in Laiwu. Sixteen kinds of polycyclic aromatic hydrocarbons (PAHs) in the United States Environmental Protection Agency (USEPA) priority controlled lists were quantitatively analyzed using Gas Chromatography-Mass Spectrometer (GC-MS). Laser particle size analyzer was used to obtain the distribution pattern of download ash. It was found that the diameter distribution pattern from four production processes was quite different. The proportion of fine particulate (0–2.5 μm) was the highest (72.62%) in the steelmaking refining process, and was 28.962% in the ironmaking process. Moreover, the particle size in download ash from steelmaking refining is all less than 10 μm and that from the ironmaking process was 52.92%. The medium-sized particles (10–100 μm) were dominant in sinter and coking download ashes. The total PAHs (∑16PAHs) mass concentration ranged from 0.49 ± 0.06 to 69.63 ± 5.57 μg·g−1 in download ash samples, and varied from 2.815 ± 0.253 to 19.429 ± 2.545 μg·m−3 in emission dust samples. The ∑16PAHs values were both largest in download ash and dust emission from the coking process (69.63 ± 5.57 μg·g−1 and 19.429 ± 2.545 μg·m−3, respectively). The most abundant individual PAHs were benzo[b]fluoranthene, benzo[k]fluoranthene, phenanthrene, benzo[a]anthracene in ash samples, and benzo[a]anthracene, benzo[k]fluoranthene, benzo[b]fluoranthene and indeno[1,2,3-cd]pyrene in emission dust samples. Dominant compounds were high-molecular weight (four- to six-ring) PAHs in both ash and dust samples. The concentration order of individual compounds in PM10 and PM2.5 in ambient air around the steel plant was completely consistent with each other, and the concentration of ∑16PAHs was the highest in the steel plant and lowest in Daqin village because of upwind of the steel plant. The concentrations of benzo[b]fluoranthene and fluoranthene in ambient air were comparatively high, and were in accordance with the higher concentration of the two monomers in the download ash samples, which suggested that the effect of the emission flue gas from the steel plant on ambient air was necessary to concern.
A Review of Recent Advances of Dielectric Barrier Discharge Plasma in Catalysis
Authors: Li Ju , Ma Cunhua , Zhu Shengjie , Yu Feng , Dai Bin , Yang Dezheng
Published: October 2019

Dielectric barrier discharge plasma is one of the most popular methods to generate nanthermal plasma, which is made up of a host of high-energy electrons, free radicals, chemically active ions and excited species, so it has the property of being prone to chemical reactions. Due to these unique advantages, the plasma technology has been widely used in the catalytic fields. Compared with the conventional method, the heterogeneous catalyst prepared by plasma technology has good dispersion and smaller particle size, and its catalytic activity, selectivity and stability are significantly improved. In addition, the interaction between plasma and catalyst can achieve synergistic effects, so the catalytic effect is further improved. The review mainly introduces the characteristics of dielectric barrier discharge plasma, development trend and its recent advances in catalysis; then, we sum up the advantages of using plasma technology to prepare catalysts. At the same time, the synergistic effect of plasma technology combined with catalyst on methanation, CH4 reforming, NOx decomposition, H2O2 synthesis, Fischer–Tropsch synthesis, volatile organic compounds removal, catalytic sterilization, wastewater treatment and degradation of pesticide residues are discussed. Finally, the properties of plasma in catalytic reaction are summarized, and the application prospect of plasma in the future catalytic field is prospected.
New Insights into the Interaction between Graphene Oxide and Beta-Blockers
Authors: Deng Yuehua , Li Yani , Nie Wenjie , Gao Xiang , Liu Shentan , Tan Xiaochun , Chen Mingming , Hou Dongzhuang
Published: October 2019

As a nano-adsorbent, magnetic graphene oxide (GO/Fe3O4) was synthesized to potentially adsorb propranolol (PRO) from water. The synthetic material was characterized by SEM, TEM, VSM, FTIR, XRD, zeta potential, and XPS. The environmental factors, such as pH, humic acid concentration, PRO concentration, and contact time, were investigated regarding their effect on the adsorption process. The kinetics data fitted the pseudo first-order and second-order kinetics equations. The Langmuir equation, the Freundlich equation, and the Sips equation were used to analyze the adsorption isotherms. Electrostatic attraction, hydrogen bonding, and the π–π interaction all contributed to the adsorption process of PRO onto GO/Fe3O4. The discovery of this study emphasized the feasibility of GO/Fe3O4 removal of PRO and expanded the scope of the application of GO.
Celiac Disease and the Microbiome
Authors: Valitutti Francesco , Cucchiara Salvatore , Fasano Alessio
Published: October 2019

Growing evidence supports the hypothesis that changes in both the composition and function of the intestinal microbiome are associated with a number of chronic inflammatory diseases including celiac disease (CD). One of the major advances in the field of microbiome studies over the last few decades has been the development of culture-independent approaches to identify and quantify the components of the human microbiota. The study of nucleic acids DNA and RNA found in feces or other biological samples bypasses the need for tissue cultures and also allows the characterization of non-cultivable microbes. Current evidence on the composition of the intestinal microbiome and its role as a causative trigger for CD is highly heterogeneous and sometimes contradictory. This review is aimed at summarizing both pre-clinical (basic science data) and clinical (cross-sectional and prospective studies) evidence addressing the relationship between the intestinal microbiome and CD.
Morphological and Molecular Characterization of Three Endolichenic Isolates of Xylaria (Xylariaceae), from Cladonia curta Ahti & Marcelli (Cladoniaceae)
Authors: Cañón Ehidy Rocio Peña , de Albuquerque Margeli Pereira , Alves Rodrigo Paidano , Pereira Antonio Batista , Victoria Filipe de Carvalho
Published: October 2019

Endophyte biology is a branch of science that contributes to the understanding of the diversity and ecology of microorganisms that live inside plants, fungi, and lichen. Considering that the diversity of endolichenic fungi is little explored, and its phylogenetic relationship with other lifestyles (endophytism and saprotrophism) is still to be explored in detail, this paper presents data on axenic cultures and phylogenetic relationships of three endolichenic fungi, isolated in laboratory. Cladonia curta Ahti & Marcelli, a species of lichen described in Brazil, is distributed at three sites in the Southeast of the country, in mesophilous forests and the Cerrado. Initial hyphal growth of Xylaria spp. on C. curta podetia started four days after inoculation and continued for the next 13 days until the hyphae completely covered the podetia. Stromata formation and differentiation was observed, occurring approximately after one year of isolation and consecutive subculture of lineages. Phylogenetic analyses indicate lineages of endolichenic fungi in the genus Xylaria, even as the morphological characteristics of the colonies and anamorphous stromata confirm this classification. Our preliminary results provide evidence that these endolichenic fungi are closely related to endophytic fungi, suggesting that the associations are not purely incidental. Further studies, especially phylogenetic analyses using robust multi-locus datasets, are needed to accept or reject the hypothesis that endolichenic fungi isolated from Xylaria spp. and X. berteri are conspecific.
Aminoacids and Flavonoids Profiling in Tempranillo Berries Can Be Modulated by the Arbuscular Mycorrhizal Fungi
Authors: Torres Nazareth , Hilbert Ghislaine , Antolín María Carmen , Goicoechea Nieves
Published: October 2019

(1) Background: Vitis vinifera L. cv. Tempranillo is cultivated over the world for its wine of high quality. The association of Tempranillo with arbuscular mycorrhizal fungi (AMF) induced the accumulation of phenolics and carotenoids in leaves, affected the metabolism of abscisic acid (ABA) during berry ripening, and modulated some characteristics and quality aspects of grapes. The objective of this study was to elucidate if AMF influenced the profiles and the content of primary and secondary metabolites determinants for berry quality in Tempranillo. (2) Methods: Fruit-bearing cuttings inoculated with AMF or uninoculated were cultivated under controlled conditions. (3) Results: Mycorrhizal symbiosis modified the profile of metabolites in Tempranillo berries, especially those of the primary compounds. The levels of glucose and amino acids clearly increased in berries of mycorrhized Tempranillo grapevines, including those of the aromatic precursor amino acids. However, mycorrhizal inoculation barely influenced the total amount and the profiles of anthocyanins and flavonols in berries. (4) Conclusions: Mycorrhizal inoculation of Tempranillo grapevines may be an alternative to the exogenous application of nitrogen compounds in order to enhance the contents of amino acids in grapes, which may affect the aromatic characteristics of wines.
Recent Advances in Polymeric Nanocomposites of Metal-Organic Frameworks (MOFs)
Authors: Zhong Jun , Kankala Ranjith Kumar , Wang Shi-Bin , Chen Ai-Zheng
Published: October 2019

Recently, metal-organic frameworks (MOFs) have garnered enormous attention from researchers owing to their superior physicochemical properties, which are of particular interest in various fields such as catalysis and the diverse areas of biomedicine. Despite their position in the utilization for various applications compared to other innovative nanocarriers such as dendrimers and mesoporous silica nanoparticles (MSNs), in terms of advantageous physicochemical attributes, as well as attractive textural properties, ease of characterization, and abundant surface chemistry for functionalization and other benefits, MOFs yet suffer from several issues such as poor degradability, which might lead to accumulation-induced biocompatibility risk. In addition, some of the MOFs suffer from a shortcoming of poor colloidal stability in the aqueous solution, hindering their applicability in diverse biomedical fields. To address these limitations, several advancements have been made to fabricate polymeric nanocomposites of MOFs for their utility in various biomedical fields. In this review, we aim to provide a brief emphasis on various organic polymers used for coating over MOFs to improve their physicochemical attributes considering a series of recently reported intriguing studies. Finally, we summarize with perspectives.
Facile Liquid-Exfoliation Process of Boron Nitride Nanosheets for Thermal Conductive Polyphthalamide Composite
Authors: Ryu Seokgyu , Oh Hyunwoo , Kim Jooheon
Published: October 2019

In this study, we describe the fabrication of thermally conductive composites based on a polyphthalamide (PPA) matrix by the exfoliation of hexagonal BN nanosheets (BNNs) via the melt-mixing method. Boron nitride (BN) particles were hydroxyl groups surface-treated with sodium hydroxide (NaOH). Compared with existing BN peeling experiments, we successfully produced BNNs that are simpler, more economical, and have an excellent aspect ratio. For the same weight content of BN and BNNs, PPA/BN composites surface-treated with high aspect ratio BNNs have a high in-plane and through-plane thermal conductivity because of the intercalation of the hydroxyl group surface treatments between BN and PPA, which not only increases the wettability but also provides a good heat transfer path. Moreover, wide and thin BNNs are evenly dispersed inside the PPA/BN composite to provide excellent heat transfer paths in both in-plane and through-plane directions.
XPS and FTIR Studies of Polytetrafluoroethylene Thin Films Obtained by Physical Methods
Authors: Piwowarczyk Joanna , Jędrzejewski Roman , Moszyński Dariusz , Kwiatkowski Konrad , Niemczyk Agata , Baranowska Jolanta
Published: October 2019

Two methods—attenuated total reflection Fourier infrared spectroscopy (ATR-FTIR) and X-ray photoelectron spectroscopy (XPS)—have been used to analyze the chemical structure of polytetrafluorethylene (PTFE) thin coatings deposited by pulsed laser (PLD) and pulsed electron beam (PED) ablations. The volume of the analyzed materials is significantly different in these techniques which can be of great importance in the characterization of highly heterogeneous thin films. Optical microscopy, atomic force microscopy (AFM) and scanning electron microscopy (SEM) have been additionally used to examine the coating surface morphology. The studies have shown that in the case of thin polymer coatings deposited by physical methods, the application for chemical structure evaluation of complementary techniques, with different surface sensitivity, together with the use of surface topography imaging, provide unique insight into the film morphology. The results can provide information contributing to an in-depth understanding of the deposition mechanism of polymer coatings.
Clinical Importance of Drug Adherence during Tyrosine Kinase Inhibitor Therapy for Chronic Myelogenous Leukemia in Chronic Phase
Authors: Maeda Yasuhiro , Okamoto Atsushi , Yamamoto Kenta , Eguchi Go , Kanai Yoshitaka
Published: October 2019

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm constituting approximately 15% of newly diagnosed leukemia in adult patients. Development of tyrosine kinase inhibitors (TKIs) have dramatically improved outcomes in patients with chronic CML in chronic phase. However, adverse drug events (ADEs) associated with TKI therapy have influenced drug adherence, resulting in adverse clinical outcomes and a decline in the quality of life (QoL). In this study, we carried out a unique questionnaire survey to evaluate ADEs, which comprised 14 adverse events. We compared drug adherence rates between patients using imatinib and those who switched from imatinib to nilotinib, a second-generation TKI. Following the switch, the total number of ADEs decreased considerably in most cases. Simultaneously, better QoL was observed in the nilotinib group than in the imatinib group. Drug adherence was measured using Morisky’s 9-item Medication Adherence Scale (MMAS). MMAS increased significantly after switching to nilotinib in all cases. Drug adherence is a critical factor for achieving molecular response in patients with CML. In fact, our results showed a strong inverse correlation between clinical outcome (international scale (IS)) and adherence (MMAS), with a stronger tendency in the nilotinib group than in the imatinib group. In conclusion, low occurrence of ADEs induced a high level of QoL and a good clinical response with second-generation TKI nilotinib treatment.
Bidirectional Convolutional LSTM Neural Network for Remote Sensing Image Super-Resolution
Authors: Chang Yunpeng , Luo Bin
Published: October 2019

Single-image super-resolution (SR) is an effective approach to enhance spatial resolution for numerous applications such as object detection and classification when the resolution of sensors is limited. Although deep convolutional neural networks (CNNs) proposed for this purpose in recent years have outperformed relatively shallow models, enormous parameters bring the risk of overfitting. In addition, due to the different scale of objects in images, the hierarchical features of deep CNN contain additional information for SR tasks, while most CNN models have not fully utilized these features. In this paper, we proposed a deep yet concise network to address these problems. Our network consists of two main structures: (1) recursive inference block based on dense connection reuse of local low-level features, and recursive learning is applied to control the model parameters while increasing the receptive fields; (2) a bidirectional convolutional LSTM (BiConvLSTM) layer is introduced to learn the correlations of features from each recursion and adaptively select the complementary information for the reconstruction layer. Experiments on multispectral satellite images, panchromatic satellite images, and nature high-resolution remote-sensing images showed that our proposed model outperformed state-of-the-art methods while utilizing fewer parameters, and ablation studies demonstrated the effectiveness of a BiConvLSTM layer for an image SR task.
Wide-Area InSAR Survey of Surface Deformation in Urban Areas and Geothermal Fields in the Eastern Trans-Mexican Volcanic Belt, Mexico
Authors: Cigna Francesca , Tapete Deodato , Garduño-Monroy Víctor Hugo , Muñiz-Jauregui Jesús Arturo , García-Hernández Oscar Humberto , Jiménez-Haro Adrián
Published: October 2019

This paper provides the first wide-area Interferometric Synthetic Aperture Radar (InSAR) survey of the whole eastern Trans-Mexican Volcanic Belt (42,200 km2). The aims are to identify ground deformation hotspots within major urbanized areas and rural valleys, establish baselines in geothermal exploration sites, and analyze deformation at geothermal exploitation sites and its relationship with energy production. The whole 2003–2010 ENVISAT C-band SAR archive available over the region was processed with the Small BAseline Subset (SBAS) InSAR method to retrieve over 840,000 coherent targets and estimate their ground displacement rates and time series. Land subsidence hotspots due to aquifer drawdown are found within the city of Puebla (up to −53 mm/year vertical rates, groundwater pumping for industrial use), Tlaxcala and Apizaco (−17 mm/year, industrial and public), the valley of Tecamachalco (−22 mm/year, agricultural), Tulancingo (−55 mm/year, public, industrial and agricultural), and in the eastern Mexico City metropolitan area (−44 mm/year, agricultural). The baseline for the Acoculco caldera complex shows widespread ground stability. Conversely, localized subsidence patterns of −5 to −10 mm/year exist around Las Derrumbadas and Cerro Pinto in the Serdán-Oriental basin, due to intense groundwater pumping for agriculture. A well-defined land subsidence area with −11 mm/year maximum rates is found at Los Humeros volcanic complex within Los Potreros collapse, correlating well with energy production infrastructure location and historical steam production rates. Field surveys carried out in Acoculco and Los Humeros in 2018 provide supporting evidence for the identification of hydrothermal manifestations, and understanding of the landscape and surface deformation patterns within the geothermal fields.
Gold-Film-Thickness Dependent SPR Refractive Index and Temperature Sensing with Hetero-Core Optical Fiber Structure
Authors: Zhang Rui , Pu Shengli , Li Xinjie
Published: October 2019

A simple hetero-core optical fiber (MMF-NCF-MMF) surface plasmon resonance (SPR) sensing structure was proposed. The SPR spectral sensitivity, full width of half peak (FWHM), valley depth (VD), and figure of merit (FOM) were defined to evaluate the sensing performance comprehensively. The effect of gold film thickness on the refractive index and temperature sensing performance was studied experimentally. The optimum gold film thickness was found. The maximum sensitivities for refractive index and temperature measurement were obtained to be 2933.25 nm/RIU and −0.91973 nm/°C, respectively. The experimental results are helpful to design the SPR structure with improved sensing performance. The proposed SPR sensing structure has the advantages of simple structure, easy implementation, and good robustness, which implies a broad application prospect.
Machine Learning for LTE Energy Detection Performance Improvement
Authors: Wasilewska Małgorzata , Bogucka Hanna
Published: October 2019

The growing number of radio communication devices and limited spectrum resources are drivers for the development of new techniques of dynamic spectrum access and spectrum sharing. In order to make use of the spectrum opportunistically, the concept of cognitive radio was proposed, where intelligent decisions on transmission opportunities are based on spectrum sensing. In this paper, two Machine Learning (ML) algorithms, namely k-Nearest Neighbours and Random Forest, have been proposed to increase spectrum sensing performance. These algorithms have been applied to Energy Detection (ED) and Energy Vector-based data (EV) to detect the presence of a Fourth Generation (4G) Long-Term Evolution (LTE) signal for the purpose of utilizing the available resource blocks by a 5G new radio system. The algorithms capitalize on time, frequency and spatial dependencies in daily communication traffic. Research results show that the ML methods used can significantly improve the spectrum sensing performance if the input training data set is carefully chosen. The input data sets with ED decisions and energy values have been examined, and advantages and disadvantages of their real-life application have been analyzed.
Beehive-Inspired Information Gathering with a Swarm of Autonomous Drones
Authors: Viseras Alberto , Wiedemann Thomas , Manss Christoph , Karolj Valentina , Shutin Dmitriy , Marchal Juan
Published: October 2019

This paper presents a beehive-inspired multi-agent drone system for autonomous information collection to support the needs of first responders and emergency teams. The proposed system is designed to be simple, cost-efficient, yet robust and scalable at the same time. It includes several unmanned aerial vehicles (UAVs) that can be tasked with data collection, and a single control station that acts as a data accumulation and visualization unit. The system also provides a local communication access point for the UAVs to exchange information and coordinate the data collection routes. By avoiding peer-to-peer communication and using proactive collision avoidance and path-planning, the payload weight and per-drone costs can be significantly reduced; the whole concept can be implemented using inexpensive off-the-shelf components. Moreover, the proposed concept can be used with different sensors and types of UAVs. As such, it is suited for local-area operations, but also for large-scale information-gathering scenarios. The paper outlines the details of the system hardware and software design, and discusses experimental results for collecting image information with a set of 4 multirotor UAVs at a small experimental area. The obtained results validate the concept and demonstrate robustness and scalability of the system.
Indoor Positioning on Disparate Commercial Smartphones Using Wi-Fi Access Points Coverage Area
Authors: Ashraf Imran , Hur Soojung , Park Yongwan
Published: October 2019

The applications of location-based services require precise location information of a user both indoors and outdoors. Global positioning system’s reduced accuracy for indoor environments necessitated the initiation of Indoor Positioning Systems (IPSs). However, the development of an IPS which can determine the user’s position with heterogeneous smartphones in the same fashion is a challenging problem. The performance of Wi-Fi fingerprinting-based IPSs is degraded by many factors including shadowing, absorption, and interference caused by obstacles, human mobility, and body loss. Moreover, the use of various smartphones and different orientations of the very same smartphone can limit its positioning accuracy as well. As Wi-Fi fingerprinting is based on Received Signal Strength (RSS) vector, it is prone to dynamic intrinsic limitations of radio propagation, including changes over time, and far away locations having similar RSS vector. This article presents a Wi-Fi fingerprinting approach that exploits Wi-Fi Access Points (APs) coverage area and does not utilize the RSS vector. Using the concepts of APs coverage area uniqueness and coverage area overlap, the proposed approach calculates the user’s current position with the help of APs’ intersection area. The experimental results demonstrate that the device dependency can be mitigated by making the fingerprinting database with the proposed approach. The experiments performed at a public place proves that positioning accuracy can also be increased because the proposed approach performs well in dynamic environments with human mobility. The impact of human body loss is studied as well.
Performance Analysis of Positioning Solution Using Low-Cost Single-Frequency U-Blox Receiver Based on Baseline Length Constraint
Authors: Lu Liguo , Ma Liye , Wu Tangting , Chen Xiaoyong
Published: October 2019

With the rapid development of the satellite navigation industry, low-cost and high-precision Global Navigation Satellite System (GNSS) positioning has recently become a research hotspot. The traditional application of GNSS may be further extended thanks to the low cost of measuring instruments, but effective methods are also desperately needed due to the low quality of the data obtained using these instruments. Thus, in this paper, we propose the analysis and evaluation of the ambiguity fixed-rate and positioning accuracy of single-frequency Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) data, collected from a low-cost u-blox receiver, based on the Constrained LAMBDA (CLAMBDA) method with a baseline length constraint, instead of the classical LAMBDA method. Three sets of experiments in different observation environments, including two sets of static short-baseline experiments and a set of dynamic vehicle experiments, are adopted in this paper. The experiment results show that, compared to classical LAMBDA method, the CLAMBDA method can significantly improve the success rate of the GNSS ambiguity resolution. When the ambiguity is fixed correctly, the baseline solution accuracy reaches 0.5 and 1 cm in a static scenario, and 1 and 2 cm on a dynamic platform.
Recent Progress in Wireless Sensors for Wearable Electronics
Authors: Park Young-Geun , Lee Sangil , Park Jang-Ung
Published: October 2019

The development of wearable electronics has emphasized user-comfort, convenience, security, and improved medical functionality. Several previous research studies transformed various types of sensors into a wearable form to more closely monitor body signals and enable real-time, continuous sensing. In order to realize these wearable sensing platforms, it is essential to integrate wireless power supplies and data communication systems with the wearable sensors. This review article discusses recent progress in wireless technologies and various types of wearable sensors. Also, state-of-the-art research related to the application of wearable sensor systems with wireless functionality is discussed, including electronic skin, smart contact lenses, neural interfaces, and retinal prostheses. Current challenges and prospects of wireless sensor systems are discussed.
Real-Time Human-In-The-Loop Simulation with Mobile Agents, Chat Bots, and Crowd Sensing for Smart Cities
Authors: Bosse Stefan , Engel Uwe
Published: October 2019

Modelling and simulation of social interaction and networks are of high interest in multiple disciplines and fields of application ranging from fundamental social sciences to smart city management. Future smart city infrastructures and management are characterised by adaptive and self-organising control using real-world sensor data. In this work, humans are considered as sensors. Virtual worlds, e.g., simulations and games, are commonly closed and rely on artificial social behaviour and synthetic sensor information generated by the simulator program or using data collected off-line by surveys. In contrast, real worlds have a higher diversity. Agent-based modelling relies on parameterised models. The selection of suitable parameter sets is crucial to match real-world behaviour. In this work, a framework combining agent-based simulation with crowd sensing and social data mining using mobile agents is introduced. The crowd sensing via chat bots creates augmented virtuality and reality by augmenting the simulated worlds with real-world interaction and vice versa. The simulated world interacts with real-world environments, humans, machines, and other virtual worlds in real-time. Among the mining of physical sensors (e.g., temperature, motion, position, and light) of mobile devices like smartphones, mobile agents can perform crowd sensing by participating in question–answer dialogues via a chat blog (provided by smartphone Apps or integrated into WEB pages and social media). Additionally, mobile agents can act as virtual sensors (offering data exchanged with other agents) and create a bridge between virtual and real worlds. The ubiquitous usage of digital social media has relevant impact on social interaction, mobility, and opinion-making, which has to be considered. Three different use-cases demonstrate the suitability of augmented agent-based simulation for social network analysis using parameterised behavioural models and mobile agent-based crowd sensing. This paper gives a rigorous overview and introduction of the challenges and methodologies used to study and control large-scale and complex socio-technical systems using agent-based methods.
Single-Nanowire Fuse for Ionization Gas Detection
Authors: Liu Hai , Zhu Wenhuan , Han Yutong , Yang Zhi , Huang Yizhong
Published: October 2019

Local electric field enhancement is crucial to detect gases for an ionization gas sensor. Nanowires grown collectively along the identical lattice orientation have been claimed to show a strong tip effect in many previous studies. Herein, we propose a novel ionization gas detector structure by using a single crystalline silicon nanowire as one electrode that is placed above the prepatterned nanotips. A significant improvement of the local electric field in its radical direction was obtained leading to an ultralow operation voltage for gas breakdown. Different from the tip of the nanowire in the reported ionization gas sensors, the gaseous discharge current in this device flows towards the sidewall in the case of a trace amount of gas environment change. Technically, this discharge current brings about a sudden temperature rise followed by a fusion of the silicon nanowire. Such unique fusibility of a single nanowire in this gas detection device suggests a novel architecture that is portable and in-site executable and can be used as an integrated gas environmental monitor.
An Automatic Stationary Water Color Parameters Observation System for Shallow Waters: Designment and Applications
Authors: Li Wenkai , Tian Liqiao , Guo Shanshan , Li Jian , Sun Zhaohua , Zhang Li
Published: October 2019

Measurements of the above-water spectrum and concerned water color parameters (WCPs) are crucial for research and applications in water environment remote sensing. Due to the lack of system integration and automatization, conventional methods are labor-intensive, time-consuming, and prone to subjective influences. To obtain a highly accurate and long-term consistent spectrum and concurrent WCPs (Chl-a (chlorophyll-a), turbidity, and CDOM (Colored Dissolved Organic Matter)) data with a relatively low cost, an Automatic Stationary Water Color Parameters Observation System (AFWCPOS) was developed. Controlled by an automatic platform, the spectral and WCPs data were collected by TriOS RAMSES hyperspectral spectroradiometers and WETLabs ECO (Environmental Characterization Optics) fluorometers following the measurement protocol. Experiment and initial validations of AFWCPOS were carried out in Poyang Lake, the largest freshwater lake in China, from 20 to 28 July 2013. Results proved that the spectral data from AFWCPOS were highly consistent with the commonly used portable SVC (Spectra Vista Corporation) HR-1024 field spectroradiometer, with the coefficient of determination (R2) of 0.96, unbiased percent difference (UPD) of 0.14, and mean relative difference (MRD) of 0.078. With advantages of continuous and high degrees of automation monitoring, the AFWCPOS has great potential in capture diurnal and inter-diurnal variations in the test site of Poyang Lake, as well as another high-dynamic shallow coastal and inland waters, which will benefit routine water quality monitoring with high quality and high-frequency time-series observations. In addition, a successful case based on Landsat 8 OLI (Operational Land Imager) image and in-situ data collected by AFWCPOS showed it’s potential in remote sensing applications. The spatial distribution of Chl-a, turbidity, and CDOM were mapped, which were explainable and similar to previous researches. These results showed our system was able to obtain reliable and valuable data for water environment monitoring.
Uncertainty Quantification for Space Situational Awareness and Traffic Management
Authors: Hilton Samuel , Cairola Federico , Gardi Alessandro , Sabatini Roberto , Pongsakornsathien Nichakorn , Ezer Neta
Published: October 2019

This paper presents a sensor-orientated approach to on-orbit position uncertainty generation and quantification for both ground-based and space-based surveillance applications. A mathematical framework based on the least squares formulation is developed to exploit real-time navigation measurements and tracking observables to provide a sound methodology that supports separation assurance and collision avoidance among Resident Space Objects (RSO). In line with the envisioned Space Situational Awareness (SSA) evolutions, the method aims to represent the navigation and tracking errors in the form of an uncertainty volume that accurately depicts the size, shape, and orientation. Simulation case studies are then conducted to verify under which sensors performance the method meets Gaussian assumptions, with a greater view to the implications that uncertainty has on the cyber-physical architecture evolutions and Cognitive Human-Machine Systems required for Space Situational Awareness and the development of a comprehensive Space Traffic Management framework.
Satellite-Based Wireless Sensor Development and Deployment Studies for Surface Wave Testing
Authors: Xu Pengju , Wang Wentao
Published: October 2019

Although cable-based seismic sensing systems have provided reliable data in the past several decades, they become a bottleneck for large-area monitoring and critical environmental (volcanic eruptions) sensing because of their cost, difficulty in deploying and expanding, and lack of accurate three-dimensional geographic information. In this paper, a new wireless sensing system is designed consisting of a portable satellite device, a self-sustaining power source, a low-cost computational core, and a high-precision sensor. The emphasis of this paper is to implement in low-cost hardware without requirements of highly specialized and expensive data acquisition instruments. Meanwhile, a computational-core-embedded algorithm based on compressive sensing (CS) is also developed to compress data size for transmission and encrypt the measured data preventing information loss. Seismic data captured by the accelerometer sensor are coded into compressive data packages and then transferred via satellite communication to a cloud-based server for storage. Acceleration and GPS information is decrypted by the ℓ1-norm minimization optimization algorithm for further processing. In this research, the feasibility of the proposed sensing system for the acquisition of seismic testing is investigated in an outdoor field surface wave testing. Results indicate the proposed low-cost wireless sensing system has the capability of collecting ground motions, transferring data, and sharing GPS information via satellite communication for large area monitoring. In addition, it has a great potential of recovering measurements even with significant data package loss.
L-VTP: Long-Term Vessel Trajectory Prediction Based on Multi-Source Data Analysis
Authors: Liu Chao , Guo Shuai , Feng Yuan , Hong Feng , Huang Haiguang , Guo Zhongwen
Published: October 2019

With the rapid development of marine IoT (Internet of Things), ocean MDTN (Mobile Delay Tolerant Network) has become a research hot spot. Long-term trajectory prediction is a key issue in MDTN. There are no long-term fine-grained trajectory prediction methods proposed for ocean vessels because a vessel’s mobility pattern lacks map topology support and can be easily influenced by the fish moratorium, sunshine duration, etc. A traditional on-land trajectory prediction algorithm cannot be directly utilized in this field because trajectory characteristics of ocean vessels are far different from that on land. To address the problem above, we propose a novel long-term trajectory prediction algorithm for ocean vessels, called L-VTP, by utilizing multiple sailing related parameters and K-order multivariate Markov Chain. L-VTP utilizes multiple sailing related parameters to build multiple state-transition matrices for trajectory prediction based on quantitative uncertainty analysis of trajectories. Trajectories’ sparsity of ocean vessels results in a critical state missing problem of a high-order state-transition matrix. L-VTP automatically traverses other matrices in a specific sequence in terms of quantitative uncertainty results to overcome this problem. Furthermore, the different mobility models of the same vessel during the day and the night are also exploited to improve the prediction accuracy. Privacy issues have been taken into consideration in this paper. A quantitative model considering Markov order, training metadata and privacy leak degree is proposed to help the participant make the trade-off based on their customized requirements. We have performed extensive experiments on two years of real-world trajectory data that include more than two thousand vessels. The experiment results demonstrate that L-VTP can realize fine-grained long-term trajectory prediction with the consideration of privacy issues. The average error of 4.5-hour fine-grained prediction is less than 500 m. In addition, the proposed method can be extended to 10-hour prediction with an average error of 2.16 km, which is also far less than the communication range of ocean vessel communication devices.
Renovation Construction Process Scheduling for Long-Term Performance of Buildings: An Application Case of University Campus
Authors: Shiue Fang-Jye , Zheng Meng-Cong , Lee Hsin-Yun , Khitam Akhmad F.K. , Li Pei-Ying
Published: October 2019

Renovation construction is employed for maintaining the long-term performance of buildings. For the occupants, the building users, renovation contributes to the acceptable levels of convenience and quality of the buildings. However, if the operation continues during the renovation for an area containing several buildings, such as a university campus, the impacts on the occupants are unavoidable. The complicated schedule plan is needed due to the various types of buildings and types of renovation under limited resources. The goal of this study is to build a model that can help the planners to make the renovation schedule plan. Taking a university campus as an example, the occupants’ convenience rate and the long-term quality of the building are analyzed in this paper. Based on the key attributes of building renovation, this study proposes a model integrating the genetic algorithm and simulation to provide the optimal schedule plan to the planners. The model is demonstrated by an application case of a university campus of 11 buildings remaining in operation. It helps the university maintain a good level of long-term performance of buildings.
The Structure of Idempotents in Neutrosophic Rings and Neutrosophic Quadruple Rings
Authors: Ma Yingcang , Zhang Xiaohong , Smarandache Florentin , Zhang Juanjuan
Published: October 2019

This paper aims to reveal the structure of idempotents in neutrosophic rings and neutrosophic quadruple rings. First, all idempotents in neutrosophic rings ⟨ R ∪ I ⟩ are given when R is C , R , Q , Z or Z n . Secondly, the neutrosophic quadruple ring ⟨ R ∪ T ∪ I ∪ F ⟩ is introduced and all idempotents in neutrosophic quadruple rings ⟨ C ∪ T ∪ I ∪ F ⟩ , ⟨ R ∪ T ∪ I ∪ F ⟩ , ⟨ Q ∪ T ∪ I ∪ F ⟩ , ⟨ Z ∪ T ∪ I ∪ F ⟩ and ⟨ Z n ∪ T ∪ I ∪ F ⟩ are also given. Furthermore, the algorithms for solving the idempotents in ⟨ Z n ∪ I ⟩ and ⟨ Z n ∪ T ∪ I ∪ F ⟩ for each nonnegative integer n are provided. Lastly, as a general result, if all idempotents in any ring R are known, then the structure of idempotents in neutrosophic ring ⟨ R ∪ I ⟩ and neutrosophic quadruple ring ⟨ R ∪ T ∪ I ∪ F ⟩ can be determined.
Scaling Relationships between Leaf Shape and Area of 12 Rosaceae Species
Authors: Yu Xiaojing , Hui Cang , Sandhu Hardev S. , Lin Zhiyi , Shi Peijian
Published: October 2019

Leaf surface area (A) and leaf shape have been demonstrated to be closely correlated with photosynthetic rates. The scaling relationship between leaf biomass (both dry weight and fresh weight) and A has been widely studied. However, few studies have focused on the scaling relationship between leaf shape and A. Here, using more than 3600 leaves from 12 Rosaceae species, we examined the relationships of the leaf-shape indices including the left to right side leaf surface area ratio (AR), the ratio of leaf perimeter to leaf surface area (RPA), and the ratio of leaf width to length (RWL) versus A. We also tested whether there is a scaling relationship between leaf dry weight and A, and between PRA and A. There was no significant correlation between AR and A for each of the 12 species. Leaf area was also found to be independent of RWL because leaf width remained proportional to leaf length across the 12 species. However, there was a negative correlation between RPA and A. The scaling relationship between RPA and A held for each species, and the estimated scaling exponent of RPA versus A approached −1/2; the scaling relationship between leaf dry weight and A also held for each species, and 11 out of the 12 estimated scaling exponents of leaf dry weight versus A were greater than unity. Our results indicated that leaf surface area has a strong scaling relationship with leaf perimeter and also with leaf dry weight but has no relationship with leaf symmetry or RWL. Additionally, our results showed that leaf dry weight per unit area, which is usually associated with the photosynthetic capacity of plants, increases with an increasing A because the scaling exponent of leaf dry weight versus A is greater than unity. This suggests that a large leaf surface area requires more dry mass input to support the physical structure of the leaf.
Integral Inequalities of Chebyshev Type for Continuous Fields of Hermitian Operators Involving Tracy–Singh Products and Weighted Pythagorean Means
Authors: Ploymukda Arnon , Chansangiam Pattrawut
Published: October 2019

In this paper, we establish several integral inequalities of Chebyshev type for bounded continuous fields of Hermitian operators concerning Tracy-Singh products and weighted Pythagorean means. The weighted Pythagorean means considered here are parametrization versions of three symmetric means: the arithmetic mean, the geometric mean, and the harmonic mean. Every continuous field considered here is parametrized by a locally compact Hausdorff space equipped with a finite Radon measure. Tracy-Singh product versions of the Chebyshev-Grüss inequality via oscillations are also obtained. Such integral inequalities reduce to discrete inequalities when the space is a finite space equipped with the counting measure. Moreover, our results include Chebyshev-type inequalities for tensor product of operators and Tracy-Singh/Kronecker products of matrices.