bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbon-Based Quantum Dots for Supercapacitors: Recent Advances and Future Challenges
Authors: Permatasari Fitri Aulia , Irham Muhammad Alief , Bisri Satria Zulkarnaen , Iskandar Ferry
Published: January 2021

Carbon-based Quantum dots (C-QDs) are carbon-based materials that experience the quantum confinement effect, which results in superior optoelectronic properties. In recent years, C-QDs have attracted attention significantly and have shown great application potential as a high-performance supercapacitor device. C-QDs (either as a bare electrode or composite) give a new way to boost supercapacitor performances in higher specific capacitance, high energy density, and good durability. This review comprehensively summarizes the up-to-date progress in C-QD applications either in a bare condition or as a composite with other materials for supercapacitors. The current state of the three distinct C-QD families used for supercapacitors including carbon quantum dots, carbon dots, and graphene quantum dots is highlighted. Two main properties of C-QDs (structural and electrical properties) are presented and analyzed, with a focus on the contribution to supercapacitor performances. Finally, we discuss and outline the remaining major challenges and future perspectives for this growing field with the hope of stimulating further research progress.
Thermally Conductive Film Fabricated Using Perforated Graphite Sheet and UV-Curable Pressure-Sensitive Adhesive
Authors: Lee Hee-Jin , Lim Gayoung , Yang Eunseong , Kim Young-Seok , Kwak Min-Gi , Kim Youngmin
Published: January 2021

Thermally conductive films play a crucial role in expanding the lifetime of electronics by dissipating concentrated heat to heatsinks. In this work, a thermally conductive film (g-TC film) was manufactured using a perforated graphite sheet (p-GS) and a UV-curable pressure-sensitive adhesive (PSA) by lamination. A novel UV-curable PSA was prepared by incorporating a UV-curable abietic acid ester into a PSA composition. The UV-curable PSA became a tack-free film upon UV irradiation; thus, a flexible g-TC film with a 52-μm thickness was obtained. The defects in the g-TC film caused by air bubbles were removed by treating the p-GS with oxygen plasma. As the UV-cured PSA made a joint through the holes in the p-GS, cleavage of the graphite was not observed after 10,000 U-folding test cycles with a folding radius of 1 mm. The calculated in-plane thermal conductivity of the fabricated g-TC film was 179 W∙m−1K−1, which was stable after the U-folding tests.
Simplicity Out of Complexity: Band Structure for W20O58 Superconductor
Authors: Slobodchikov A.A. , Nekrasov I.A. , Pavlov N.S. , Korshunov M.M.
Published: January 2021

The band structure, density of states, and the Fermi surface of a recently discovered superconductor, oxygen-deficient tungsten oxide WO2.9 that is equivalent to W20O58, is studied within the density functional theory (DFT) in the generalized gradient approximation (GGA). Here we show that despite the extremely complicated structure containing 78 atoms in the unit cell, the low-energy band structure is quite feasible. Fermi level is crossed by no more than 10 bands per one spin projection (and even 9 bands per pseudospin projection when the spin-orbit coupling is considered) originating from the t2g 5d-orbitals of tungsten atoms forming zigzag chains. These bands become occupied because of the specific zigzag octahedra distortions. To demonstrate the role of distortions, we compare band structures of W20O58 with the real crystal structure and with the idealized one. We also propose a basis for a minimal low-energy tight-binding model for W20O58.
3D Urchin-Like CuO Modified W18O49 Nanostructures for Promoted Photocatalytic Hydrogen Evolution under Visible Light Irradiation
Authors: Ma Hongyu , Tan Yaqi , Liu Zhifei , Wei Jianhong , Xiong Rui
Published: January 2021

Photocatalytic hydrogen evolution is a promising “green chemistry” route driven by sunlight for the direct water splitting into value-added hydrogen energy. Herein, with the object of exploring the effect of CuO loading on W18O49 photocatalytic activity, a 3D Urchin-like CuO modified W18O49 (CuO/W18O49) microspheres with different CuO loadings were synthesized via thermochemical precipitation combined with solvent-thermal method. The obtained CuO/W18O49 microspheres were analyzed by means of X-ray diffraction (XRD), scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS) and photoluminescence (PL), etc. The results infer that the urchin-like 3D morphology with a high surface area and abundant 1D nanowires promotes electron transfer, the introduction of CuO further increases the number of active sites, thereby ensuring fast interfacial charge transfer to improve photocatalytic performance. During photocatalytic H2 evolution from water splitting, 5 wt.% CuO/W18O49 shows the optimal performance, the H2 yield is almost 3.22 times that of the undoped counterparts. This work presents that oxygen-vacancy-rich heterojunction nanocomposites can be used as a new strategy to design materials with high photocatalytic activity.
Beneficial Effects of Citrus-Derived Polymethoxylated Flavones for Central Nervous System Disorders
Authors: Matsuzaki Kentaro , Ohizumi Yasushi
Published: January 2021

The number of patients with central nervous system disorders is increasing. Despite diligent laboratory and clinical research over the past 30 years, most pharmacologic options for the prevention and long-term treatment of central nervous system disorders and neurodegenerative disorders have been unsuccessful. Therefore, the development of drugs and/or functional foods to prevent the onset of neurodegenerative disorders is highly expected. Several reports have shown that polymethoxylated flavones (PMFs) derived from citrus fruit, such as nobiletin, tangeretin, and 3,3′,4′,5,6,7,8-heptamethoxyflavone, are promising molecules for the prevention of neurodegenerative and neurological disorders. In various animal models, PMFs have been shown to have a neuroprotective effect and improve cognitive dysfunction with regard to neurological disorders by exerting favorable effects against their pathological features, including oxidative stress, neuroinflammation, neurodegeneration, and synaptic dysfunction as well as its related mechanisms. In this review, we describe the profitable and ameliorating effects of citrus-derived PMFs on cognitive impairment and neural dysfunction in various rat and murine models or in several models of central nervous system disorders and identify their mechanisms of action.
Towards Laser-Based Calibration-Free Quantification of Trace Elements
Authors: Gerhard Christoph
Published: January 2021

It is told that Theodore Maiman called the first operating laser source he and his co-worker Charles Asawa realized 60 years ago [...]
Felid Cardiopulmonary Nematodes: Dilemmas Solved and New Questions Posed
Authors: Traversa Donato , Morelli Simone , Di Cesare Angela , Diakou Anastasia
Published: January 2021

In the past decade cardiopulmonary nematodes affecting felids have become a core research topic in small animal parasitology. In the late 2000s, an increase in studies was followed by unexpected findings in the early 2010s, which have stimulated research teams to start investigating these intriguing parasites. Prolific scientific debate and exchanges have then fostered field and laboratory studies and epizootiological surveys. New data have improved basic and applied knowledge, solved dilemmas and posed new questions. This article discusses the past and present background to felid cardiopulmonary nematodes after the last few years of intense scientific research. New data which have demonstrated the key role of Aelurostrongylus abstrusus and Troglostrongylus brevior in causing respiratory infections in domestic cats, and on the nil to negligible current importance of other species, i.e., Troglostrongylus subcrenatus, Oslerus rostratus and Angiostrongylus chabaudi, are presented. Biological information and hypothesized alternative routes of infection are analysed and discussed. Novel identification and taxonomical data and issues are reported and commented upon. On the whole, recent biological, ecological and epizootiological information on felid metastrongyloids is critically analysed, with the aim to answer outstanding questions, stimulate future studies, and underline new research perspectives.
Evidence of Autonomic Dysfunction in Patients with Relapsing-Remitting Multiple Sclerosis: Heart Rate Variability and Cardiovascular Parameters
Authors: Gerasimova-Meigal Liudmila , Sirenev Ilya , Meigal Alexander
Published: January 2021

This study was aimed at evaluation of autonomic dysfunction in patients with multiple sclerosis (MS) by means of time- and frequency-domain parameters of heart rate variability (HRV) and conventional cardiovascular tests (deep breathing (DB) and active orthostatic test (AOT)). The study group enrolled 32 patients with the relapsing-remitting MS (17 m, 15 f, aged 29 ± 4.9 years, disease duration 4.2 ± 2.7 years, EDSS scores less than 3.0 and 26 subjects in good health (HC, 15 m, 11 f, aged 30.1 ± 2.7 years). In the MS group, at rest the variability of heart rate was decreased in comparison to the HC group seen by time- (SDNN, RMSSD, pNN50, CV, p < 0.01) and frequency-domain (TP, HF, LF, p < 0.05) parameters, what was indicative of the general decrease of the autonomic neurogenic control of the heart rate, both sympathetic and parasympathetic. The functional tests (DB and AOT) showed reduced cardiovascular reactivity in the MS group. Additionally, the cardio-respiratory synchronization was impaired in the MS group at rest and DB. The severity of HRV deficit in the MS group correlated with the activity of MS. In conclusion, the comprehensive assessment of time- and frequency-domain HRV parameters studied with functional tests provides better insight to understanding autonomic dysfunction in subjects with relapsing-remitting MS.
COVID-19 in Pediatric Granulomatosis with Polyangiitis
Authors: Saeed Amir , Shorafa Eslam , Seratishirazi Zahra , Abootalebi Seyedenarjes
Published: January 2021

The confirmed cases with COVID-19 in children account for just 1% of the overall confirmed cases. Severe COVID-19 in children is rare. Case Presentation: Our patient was 16 years old with a severe case of COVID-19 and did not survive due to the presence of Granulomatosis with polyangiitis and being treated with immunosuppressive drugs. We used lopinavir, ritonavir, hydroxy chloroquine, intravenous immunoglobulin and continuous veno-venous hemodialysis for treatment. Conclusion: In this patient, an underlying disease and delayed admission to the hospital were two factors complicating his condition.
Complete Cocrystal Formation during Resonant Acoustic Wet Granulation: Effect of Granulation Liquids
Authors: Tanaka Ryoma , Osotprasit Supisara , Peerapattana Jomjai , Ashizawa Kazuhide , Hattori Yusuke , Otsuka Makoto
Published: January 2021

The manufacturing of solid pharmaceutical dosage forms composed of cocrystals requires numerous processes during which there is risk of dissociation into parent molecules. Resonant acoustic wet granulation (RAG) was devised in an effort to complete theophylline–citric acid (THPCIT) cocrystal formation during the granulation process, thereby reducing the number of operations. In addition, the influence of granulation liquid was investigated. A mixture of anhydrous THP (drug), anhydrous CIT (coformer), and hydroxypropyl cellulose (granulating agent) was processed by RAG with water or ethanol as a granulation liquid. The purposes were to (i) form granules using RAG as a breakthrough method; (ii) accomplish the cocrystallization during the integrated unit operation; and (iii) characterize the final solid product (i.e., tablet). The RAG procedure achieved complete cocrystal formation (>99%) and adequately sized granules (d50: >250 μm). The granulation using water (GW) facilitated formation of cocrystal hydrate which were then transformed into anhydrous cocrystal after drying, while the granulation using ethanol (GE) resulted in the formation of anhydrous cocrystal before and after drying. The dissolution of the highly dense GW tablet, which was compressed from granules including fine powder due to the dehydration, was slower than that of the GE tablet.
Effects of Technical Textiles and Synthetic Nanofibers on Environmental Pollution
Authors: Aldalbahi Ali , El-Naggar Mehrez , El-Newehy Mohamed , Rahaman Mostafizur , Hatshan Mohammad , Khattab Tawfik
Published: January 2021

Textile manufacturing has been one of the highest polluting industrial sectors. It represents about one-fifth of worldwide industrial water pollution. It uses a huge number of chemicals, numerous of which are carcinogenic. The textile industry releases many harmful chemicals, such as heavy metals and formaldehyde, into water streams and soil, as well as toxic gases such as suspended particulate matter and sulphur dioxide to air. These hazardous wastes, may cause diseases and severe problems to human health such as respiratory and heart diseases. Pollution caused by the worldwide textile manufacturing units results in unimaginable harm, such as textile polymers, auxiliaries and dyes, to the environment. This review presents a systematic and comprehensive survey of all recently produced high-performance textiles; and will therefore assist a deeper understanding of technical textiles providing a bridge between manufacturer and end-user. Moreover, the achievements in advanced applications of textile material will be extensively studied. Many classes of technical textiles were proved in a variety of applications of different fields. The introductory material- and process-correlated identifications regarding raw materials and their transformation into yarns, fibers and fabrics followed by dyeing, printing, finishing of technical textiles and their further processing will be explored. Thus, the environmental impacts of technical textiles on soil, air and water are discussed.
Protein Unfolding and Aggregation near a Hydrophobic Interface
Authors: March David , Bianco Valentino , Franzese Giancarlo
Published: January 2021

The behavior of proteins near interfaces is relevant for biological and medical purposes. Previous results in bulk show that, when the protein concentration increases, the proteins unfold and, at higher concentrations, aggregate. Here, we study how the presence of a hydrophobic surface affects this course of events. To this goal, we use a coarse-grained model of proteins and study by simulations their folding and aggregation near an ideal hydrophobic surface in an aqueous environment by changing parameters such as temperature and hydrophobic strength, related, e.g., to ions concentration. We show that the hydrophobic surface, as well as the other parameters, affect both the protein unfolding and aggregation. We discuss the interpretation of these results and define future lines for further analysis, with their possible implications in neurodegenerative diseases.
Deriving Tree Size Distributions of Tropical Forests from Lidar
Authors: Taubert Franziska , Fischer Rico , Knapp Nikolai , Huth Andreas
Published: January 2021

Remote sensing is an important tool to monitor forests to rapidly detect changes due to global change and other threats. Here, we present a novel methodology to infer the tree size distribution from light detection and ranging (lidar) measurements. Our approach is based on a theoretical leaf–tree matrix derived from allometric relations of trees. Using the leaf–tree matrix, we compute the tree size distribution that fit to the observed leaf area density profile via lidar. To validate our approach, we analyzed the stem diameter distribution of a tropical forest in Panama and compared lidar-derived data with data from forest inventories at different spatial scales (0.04 ha to 50 ha). Our estimates had a high accuracy at scales above 1 ha (1 ha: root mean square error (RMSE) 67.6 trees ha−1/normalized RMSE 18.8%/R² 0.76; 50 ha: 22.8 trees ha−1/6.2%/0.89). Estimates for smaller scales (1-ha to 0.04-ha) were reliably for forests with low height, dense canopy or low tree height heterogeneity. Estimates for the basal area were accurate at the 1-ha scale (RMSE 4.7 tree ha−1, bias 0.8 m² ha−1) but less accurate at smaller scales. Our methodology, further tested at additional sites, provides a useful approach to determine the tree size distribution of forests by integrating information on tree allometries.
A Genetic Optimization Resampling Based Particle Filtering Algorithm for Indoor Target Tracking
Authors: Zhou Ning , Lau Lawrence , Bai Ruibin , Moore Terry
Published: January 2021

In indoor target tracking based on wireless sensor networks, the particle filtering algorithm has been widely used because of its outstanding performance in coping with highly non-linear problems. Resampling is generally required to address the inherent particle degeneracy problem in the particle filter. However, traditional resampling methods cause the problem of particle impoverishment. This problem degrades positioning accuracy and robustness and sometimes may even result in filtering divergence and tracking failure. In order to mitigate the particle impoverishment and improve positioning accuracy, this paper proposes an improved genetic optimization based resampling method. This resampling method optimizes the distribution of resampled particles by the five operators, i.e., selection, roughening, classification, crossover, and mutation. The proposed resampling method is then integrated into the particle filtering framework to form a genetic optimization resampling based particle filtering (GORPF) algorithm. The performance of the GORPF algorithm is tested by a one-dimensional tracking simulation and a three-dimensional indoor tracking experiment. Both test results show that with the aid of the proposed resampling method, the GORPF has better robustness against particle impoverishment and achieves better positioning accuracy than several existing target tracking algorithms. Moreover, the GORPF algorithm owns an affordable computation load for real-time applications.
Surface Tradeoffs and Elevational Shifts at the Largest Italian Glacier: A Thirty-Years Time Series of Remotely-Sensed Images
Authors: Alessi Nicola , Wellstein Camilla , Rocchini Duccio , Midolo Gabriele , Oeggl Klaus , Zerbe Stefan
Published: January 2021

Biodiversity loss occurring in mountain ecosystems calls for integrative approaches to improve monitoring processes in the face of human-induced changes. With a combination of vegetation and remotely-sensed time series data, we quantitatively identify the responses of land-cover types and their associated vegetation between 1987 and 2016. Fuzzy clustering of 11 Landsat images was used to identify main land-cover types. Vegetation belts corresponding to such land-cover types were identified by using species indicator analysis performed on 80 vegetation plots. A post-classification evaluation of trends, magnitude, and elevational shifts was done using fuzzy membership values as a proxy of the occupied surfaces by land-cover types. Our findings show that forests and scrublands expanded upward as much as the glacier retreated, i.e., by 24% and 23% since 1987, respectively. While lower alpine grassland shifted upward, the upper alpine grassland lost 10% of its originally occupied surface showing no elevational shift. Moreover, an increase of suitable sites for the expansion of the subnival vegetation belt has been observed, due to the increasing availability of new ice-free areas. The consistent findings suggest a general expansion of forest and scrubland to the detriment of alpine grasslands, which in turn are shifting upwards or declining in area. In conclusion, alpine grasslands need urgent and appropriate monitoring processes ranging from the species to the landscape level that integrates remotely-sensed and field data.
Calibrations of Low-Cost Air Pollution Monitoring Sensors for CO, NO2, O3, and SO2
Authors: Han Pengfei , Mei Han , Liu Di , Zeng Ning , Tang Xiao , Wang Yinghong , Pan Yuepeng
Published: January 2021

Pollutant gases, such as CO, NO2, O3, and SO2 affect human health, and low-cost sensors are an important complement to regulatory-grade instruments in pollutant monitoring. Previous studies focused on one or several species, while comprehensive assessments of multiple sensors remain limited. We conducted a 12-month field evaluation of four Alphasense sensors in Beijing and used single linear regression (SLR), multiple linear regression (MLR), random forest regressor (RFR), and neural network (long short-term memory (LSTM)) methods to calibrate and validate the measurements with nearby reference measurements from national monitoring stations. For performances, CO > O3 > NO2 > SO2 for the coefficient of determination (R2) and root mean square error (RMSE). The MLR did not increase the R2 after considering the temperature and relative humidity influences compared with the SLR (with R2 remaining at approximately 0.6 for O3 and 0.4 for NO2). However, the RFR and LSTM models significantly increased the O3, NO2, and SO2 performances, with the R2 increasing from 0.3–0.5 to >0.7 for O3 and NO2, and the RMSE decreasing from 20.4 to 13.2 ppb for NO2. For the SLR, there were relatively larger biases, while the LSTMs maintained a close mean relative bias of approximately zero (e.g., <5% for O3 and NO2), indicating that these sensors combined with the LSTMs are suitable for hot spot detection. We highlight that the performance of LSTM is better than that of random forest and linear methods. This study assessed four electrochemical air quality sensors and different calibration models, and the methodology and results can benefit assessments of other low-cost sensors.
Detection of Dementia-Related Abnormal Behaviour Using Recursive Auto-Encoders
Authors: Arifoglu Damla , Wang Yan , Bouchachia Abdelhamid
Published: January 2021

Age-related health issues have been increasing with the rise of life expectancy all over the world. One of these problems is cognitive impairment, which causes elderly people to have problems performing their daily activities. Detection of cognitive impairment at an early stage would enable medical doctors to deepen diagnosis and follow-up on patient status. Recent studies show that daily activities can be used to assess the cognitive status of elderly people. Additionally, the intrinsic structure of activities and the relationships between their sub-activities are important clues for capturing the cognitive abilities of seniors. Existing methods perceive each activity as a stand-alone unit while ignoring their inner structural relationships. This study investigates such relationships by modelling activities hierarchically from their sub-activities, with the overall goal of detecting abnormal activities linked to cognitive impairment. For this purpose, recursive auto-encoders (RAE) and their linear vs. greedy and supervised vs. semi-supervised variants are adopted to model the activities. Then, abnormal activities are systematically detected using RAE’s reconstruction error. Moreover, to apply RAEs for this problem, we introduce a new sensor representation called raw sensor measurement (RSM) that captures the intrinsic structure of activities, such as the frequency and the order of sensor activations. As real-world data are not accessible, we generated data by simulating abnormal behaviour, which reflects on cognitive impairment. Extensive experiments show that RAEs can be used as a decision-supporting tool, especially when the training set is not labelled to detect early indicators of dementia.
Selected Papers from the First International Symposium on Future ICT (Future-ICT 2019) in Conjunction with the 4th International Symposium on Mobile Internet Security (MobiSec 2019)
Authors: Pau Giovanni , Chen Hsing-Chung , Leu Fang-Yie , You Ilsun
Published: January 2021

The International Symposium on the Future ICT (Future-ICT 2019) in conjunction with the 4th International Symposium on Mobile Internet Security (MobiSec 2019) has been held on 17–19 October 2019 in Taichung, Taiwan [...]
A Dynamic Hysteresis Model and Nonlinear Control System for a Structure-Integrated Piezoelectric Sensor-Actuator
Authors: Shan Xiaobiao , Song Henan , Cao Han , Zhang Lanshuang , Zhao Xuhang , Fan Jizhuang
Published: January 2021

The piezoelectric sensor-actuator plays an important role in micro high-precision dynamic systems such as medical robots and micro grippers. These mechanisms need high-precision position control, while the size of the sensor and actuator should be as small as possible. For this paper, we designed and manufactured a structure-integrated piezoelectric sensor-actuator and proposed its PID (Proportion Integral Differential) control system based on the dynamic hysteresis nonlinear model and the inverse model. Through simplifying the structure of the piezoelectric sensor-actuator by the centralized parameter method, this paper establishes its dynamic model and explores the input–output transfer function by taking the relationship between the output force and displacement as the medium. The experiment shows the maximum distance of the hysteresis curve is 0.26 μm. By parsing the hysteresis curve, this paper presents a dynamic hysteresis nonlinear model and its inverse model based on a 0.5 Hz quasi-static model and linear transfer function. Simulation results show that the accuracy of the static model is higher than that of the dynamic model when the frequency is 0.5 Hz, but the compensation accuracy of the dynamic model is obviously better than that of the static model with the increase of the frequency. This paper also proposes a control system for the sensor-actuator by means of the inverse model. The simulation results indicate that the output root mean square error was reduced to one-quarter of the original, which proves that the structure-integrated piezoelectric sensor-actuator and its control system have a great significance for signal sensing and output control of micro high-precision dynamic systems.
Real-Time Multi-Modal Sensing and Feedback for Catheterization in Porcine Tissue
Authors: Heunis Christoff , Šuligoj Filip , Fambuena Santos Carlos , Misra Sarthak
Published: January 2021

Objective: In this study, we introduce a multi-modal sensing and feedback framework aimed at assisting clinicians during endovascular surgeries and catheterization procedures. This framework utilizes state-of-the-art imaging and sensing sub-systems to produce a 3D visualization of an endovascular catheter and surrounding vasculature without the need for intra-operative X-rays. Methods: The catheterization experiments within this study are conducted inside a porcine limb undergoing motions. A hybrid position-force controller of a robotically-actuated ultrasound (US) transducer for uneven porcine tissue surfaces is introduced. The tissue, vasculature, and catheter are visualized by integrated real-time US images, 3D surface imaging, and Fiber Bragg Grating (FBG) sensors. Results: During externally-induced limb motions, the vasculature and catheter can be reliably reconstructed at mean accuracies of 1.9±0.3 mm and 0.82±0.21 mm, respectively. Conclusions: The conventional use of intra-operative X-ray imaging to visualize instruments and vasculature in the human body can be reduced by employing improved diagnostic technologies that do not operate via ionizing radiation or nephrotoxic contrast agents. Significance: The presented multi-modal framework enables the radiation-free and accurate reconstruction of significant tissues and instruments involved in catheterization procedures.
Adaptive Traffic Signal Control: Game-Theoretic Decentralized vs. Centralized Perimeter Control
Authors: Elouni Maha , Abdelghaffar Hossam M. , Rakha Hesham A.
Published: January 2021

This paper compares the operation of a decentralized Nash bargaining traffic signal controller (DNB) to the operation of state-of-the-art adaptive and gating traffic signal control. Perimeter control (gating), based on the network fundamental diagram (NFD), was applied on the borders of a protected urban network (PN) to prevent and/or disperse traffic congestion. The operation of gating control and local adaptive controllers was compared to the operation of the developed DNB traffic signal controller. The controllers were implemented and their performance assessed on a grid network in the INTEGRATION microscopic simulation software. The results show that the DNB controller, although not designed to solve perimeter control problems, successfully prevents congestion from building inside the PN and improves the performance of the entire network. Specifically, the DNB controller outperforms both gating and non-gating controllers, with reductions in the average travel time ranging between 21% and 41%, total delay ranging between 40% and 55%, and emission levels/fuel consumption ranging between 12% and 20%. The results demonstrate statistically significant benefits of using the developed DNB controller over other state-of-the-art centralized and decentralized gating/adaptive traffic signal controllers.
Robust Inferential Techniques Applied to the Analysis of the Tropospheric Ozone Concentration in an Urban Area
Authors: Hernandez Wilmar , Mendez Alfredo , González-Posadas Vicente , Jiménez-Martín José Luis , Camejo Iván Menes
Published: January 2021

This paper analyzes 12 years of tropospheric ozone (O3) concentration measurements using robust techniques. The measurements were taken at an air quality monitoring station called Belisario, which is in Quito, Ecuador; the data collection time period was 1 January 2008 to 31 December 2019, and the measurements were carried out using photometric O3 analyzers. Here, the measurement results were used to build variables that represented hours, days, months, and years, and were then classified and categorized. The index of air quality (IAQ) of the city was used to make the classifications, and robust and nonrobust confidence intervals were used to make the categorizations. Furthermore, robust analysis methods were compared with classical methods, nonparametric methods, and bootstrap-based methods. The results showed that the analysis using robust methods is better than the analysis using nonrobust methods, which are not immune to the influence of extreme observations. Using all of the aforementioned methods, confidence intervals were used to both establish and quantify differences between categories of the groups of variables under study. In addition, the central tendency and variability of the O3 concentration at Belisario station were exhaustively analyzed, concluding that said concentration was stable for years, highly variable for months and hours, and slightly changing between the days of the week. Additionally, according to the criteria established by the IAQ, it was shown that in Quito, the O3 concentration levels during the study period were not harmful to human health.
Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors
Authors: Costache Romulus , Arabameri Alireza , Blaschke Thomas , Pham Quoc Bao , Pham Binh Thai , Pandey Manish , Arora Aman , Linh Nguyen Thi Thuy , Costache Iulia
Published: January 2021

There is an evident increase in the importance that remote sensing sensors play in the monitoring and evaluation of natural hazards susceptibility and risk. The present study aims to assess the flash-flood potential values, in a small catchment from Romania, using information provided remote sensing sensors and Geographic Informational Systems (GIS) databases which were involved as input data into a number of four ensemble models. In a first phase, with the help of high-resolution satellite images from the Google Earth application, 481 points affected by torrential processes were acquired, another 481 points being randomly positioned in areas without torrential processes. Seventy percent of the dataset was kept as training data, while the other 30% was assigned to validating sample. Further, in order to train the machine learning models, information regarding the 10 flash-flood predictors was extracted in the training sample locations. Finally, the following four ensembles were used to calculate the Flash-Flood Potential Index across the Bâsca Chiojdului river basin: Deep Learning Neural Network–Frequency Ratio (DLNN-FR), Deep Learning Neural Network–Weights of Evidence (DLNN-WOE), Alternating Decision Trees–Frequency Ratio (ADT-FR) and Alternating Decision Trees–Weights of Evidence (ADT-WOE). The model’s performances were assessed using several statistical metrics. Thus, in terms of Sensitivity, the highest value of 0.985 was achieved by the DLNN-FR model, meanwhile the lowest one (0.866) was assigned to ADT-FR ensemble. Moreover, the specificity analysis shows that the highest value (0.991) was attributed to DLNN-WOE algorithm, while the lowest value (0.892) was achieved by ADT-FR. During the training procedure, the models achieved overall accuracies between 0.878 (ADT-FR) and 0.985 (DLNN-WOE). K-index shows again that the most performant model was DLNN-WOE (0.97). The Flash-Flood Potential Index (FFPI) values revealed that the surfaces with high and very high flash-flood susceptibility cover between 46.57% (DLNN-FR) and 59.38% (ADT-FR) of the study zone. The use of the Receiver Operating Characteristic (ROC) curve for results validation highlights the fact that FFPIDLNN-WOE is characterized by the most precise results with an Area Under Curve of 0.96.
Design of Flexible Pressure Sensor Based on Conical Microstructure PDMS-Bilayer Graphene
Authors: Cheng Lixia , Wang Renxin , Hao Xiaojian , Liu Guochang
Published: January 2021

As a new material, graphene shows excellent properties in mechanics, electricity, optics, and so on, which makes it widely concerned by people. At present, it is difficult for graphene pressure sensor to meet both high sensitivity and large pressure detection range at the same time. Therefore, it is highly desirable to produce flexible pressure sensors with sufficient sensitivity in a wide working range and with simple process. Herein, a relatively high flexible pressure sensor based on piezoresistivity is presented by combining the conical microstructure polydimethylsiloxane (PDMS) with bilayer graphene together. The piezoresistive material (bilayer graphene) attached to the flexible substrate can convert the local deformation caused by the vertical force into the change of resistance. Results show that the pressure sensor based on conical microstructure PDMS-bilayer graphene can operate at a pressure range of 20 kPa while maintaining a sensitivity of 0.122 ± 0.002 kPa−1 (0–5 kPa) and 0.077 ± 0.002 kPa−1 (5–20 kPa), respectively. The response time of the sensor is about 70 ms. In addition to the high sensitivity of the pressure sensor, it also has excellent reproducibility at different pressure and temperature. The pressure sensor based on conical microstructure PDMS-bilayer graphene can sense the motion of joint well when the index finger is bent, which makes it possible to be applied in electronic skin, flexible electronic devices, and other fields.
Evaluation of Agricultural Extension Service for Sustainable Agricultural Development Using a Hybrid Entropy and TOPSIS Method
Authors: Wang Zhiguo , Wang Junbin , Zhang Guoping , Wang Zhixiong
Published: January 2021

Agricultural extension service is the foundation of sustainable agricultural development. The evaluation and analysis of the agricultural extension service for sustainable agricultural development can provide an effective analytical tool for sustainable agriculture. This paper analyzes the influence of agricultural extension service on sustainable agricultural development, and constructs an evaluation system for sustainable agricultural development from the four dimensions of agricultural environment, society, economy, and agricultural extension service. This work proposes a framework based on the combination of technique for order performance by similarity to ideal solution (TOPSIS) and entropy method to evaluate the performance of the evaluation system. Taking three national modern agriculture demonstration zones in Suzhou in Jiangsu Province as a case study, the method was verified. Moreover, the main factors affecting sustainable agricultural development are discussed, and the improvement measures and management suggestions are also put forward to reduce the obstacles to sustainable agricultural development and improve sustainable agriculture practice.
Assessment of Land Ecological Security and Analysis of Influencing Factors in Chaohu Lake Basin, China from 1998–2018
Authors: Wen Mingxin , Zhang Ting , Li Long , Chen Longqian , Hu Sai , Wang Jia , Liu Weiqiang , Zhang Yu , Yuan Lina
Published: January 2021

The land ecosystem provides essential natural resources for the survival and development of human beings. Therefore, land ecological security (LES) acts as a vital part of the sustainable development of human society and economy. This study included a dynamic analysis of land use change in Chaohu Lake Basin (CLB) in China from 1998 to 2018, evaluating the spatiotemporal patterns of LES at both the administrative district scale and grid scale (200 m × 200 m). Then, geographic detector was applied to analyze the influence of the assessment index on LES. The results show that in the 2008–2018 period, land use changed more significantly compared to the 1998–2008 period. The continuous extension of urban land led to a decrease in the areas of other land use types. In the CLB (administrative district scale), the LES levels varied throughout the study period. In Changfeng, Feixi, and the other three regions, the LES has been significantly improved. However, the LES in six other regions showed different degrees of decline, particularly in Hexian and Urban Hefei. Simultaneously, the LES showed a gradual improvement at a 200 m × 200 m grid scale level. The influence of anthropogenic factors on the LES was stronger than natural factors. Findings from this study provide reliable guidance for improving the ecosystem environment in ecologically fragile areas.
Challenges and Threats Faced in 2020 by International Logistics Companies Operating on the Polish Market
Authors: Brdulak Halina , Brdulak Anna
Published: January 2021

The main aim of the article is to present an analysis of the current challenges and threats to the Transport-Forwarding-Logistics (TFL) sector in Poland based on internet surveys. The aim of the article is, therefore, to investigate whether the challenges and threats described by managers in a two-year perspective are related to sustainable development. This area primarily concerns external conditions. On the other hand, in the surveys that were the subjects of the analyses, a section related to sustainable development in economic, environmental, and social terms was identified, in which the focus was primarily on the internal activities of the company. The article has a practical dimension. The article analyzes comments from managers posted in an internet survey. They constitute a separate part of the questionnaire, which mainly concerns financial indicators and other factors that determine the company’s competitiveness. Half of the respondents are companies with foreign capital, and half-Polish companies. Based on the comments over a three-year period with over sixty managers from logistics companies in Poland, an analysis of the most important challenges that companies in the logistics industry have to face in the near future was presented. The survey is a part of a broader research project that has been conducted in the form of a quantitative survey among approximately sixty TFL companies for twenty-five years on an annual basis. The results of the survey are supplemented with an attempt to analyze the current situation in 2020 related to the impending economic recession as a result of the coronavirus disease 2019 (COVID-19) threat. The surveyed companies constitute a significant part of the TFL market in Poland. Thus, they are the benchmark for the entire industry. Therefore, an important value of the presented analysis is the up-to-date research, as well as the ability to relate the results and developed scenarios to the entire TFL sector.
Multi-Scenario Evolutionary Game of Rumor-Affected Enterprises under Demand Disruption
Authors: Zhao Chuan , Li Luyao , Sun Hongxia , Yang Hongji
Published: January 2021

Rumors regarding food, medicine, epidemic diseases, and public emergencies greatly impact consumers’ purchase intention, disrupt market demand, affect enterprises’ operating strategies, and eventually increase the risk of market chaos. Governments must play an active role with limited resources under the situation of rumor spreading and demand disruption to maintain stable and sustainable market development. To identify the optimal evolutionary stable strategy (ESS) of both small and large enterprises when facing rumors, this paper investigates the following two choices of enterprises: reasonable and unreasonable pricing. The results reveal that government supervision priority should be set based on the rumor severity, collusion in markup and the endogeneity of the enterprises. From an exogenous perspective, rumor spreading induces enterprises to overcharge, and government supervision has the opposite effect. However, the demand disruption ratio is proven to motivate enterprises to implement reasonable pricing. The profit and loss ratio and homoplasy are two endogenous factors affecting enterprise decisions. Small enterprises are more likely to take advantage of public panic and overcharge, while large enterprises are inclined to choose reasonable pricing in consideration of their corporate image. In addition, the evidence indicates that the ESS of large firms has a stronger impact on small firms.
Transitions in Urban Waterfronts: Imagining, Contesting, and Sustaining the Aquatic/Terrestrial Interface
Authors: Taufen Anne , Yocom Ken
Published: January 2021

Urban waterfronts represent hybrid locations of ecological, economic, and social zones of transition and dispersal, spatially reified between land and water. Yet, through advancements in technology and the emergence of globally linked economies, the structure and function of urban waterfronts as economic and industrial drivers is becoming increasingly complex. As cities seek to redevelop their waterfronts in response to these changes, recent research and scholarship has focused on understanding the ecological, social, and economic benefits derived from urban waterfronts. This research reveals that their benefits are unevenly distributed among local and regional populations as sites of accumulated inequity and inaccessibility that are generative for only a relatively small percentage of the people living in a metropolitan area. Set within this paradoxical nexus, this paper frames a call to scientists, planners, academics, and waterfront activists to expand urban waterfront research from an indicator and benefits model to incorporate three conceptual tools for better understanding key dimensions of waterfront reclamation within the context of green infrastructure research: urban hybridity, functional performance and hierarchies of access. We explore these key dimensions in relation to the waterfront redevelopment of Tacoma, Washington, USA. By acknowledging the hybridity of urban waterfronts, we illustrate that their relative performance and accessibility require ongoing empirical study and practical intervention. Our theoretical explorations plot some of the potential areas of investigation for examining the structural and functional transitions of urban waterfronts as critical locations for green infrastructure development for the 21st century.
The Role of Government Financial Support Programmes, Risk-Taking Propensity, and Self-Confidence on Propensity in Business Ventures
Authors: Yusoff Mohd Nor Hakimin Bin , Zainol Fakhrul Anwar , Ismail Mohammad , Redzuan Razman Hafifi , Abdul Rahim Merican Rooshihan Merican , Razik Muhammad Ashlyzan , Afthanorhan Asyraf
Published: January 2021

This study identifies the effect of government financial support services (GFSS) on the relationship between two dimensions of psychological factors in business ventures. As such, the study uses small and medium enterprises (SMEs) of various Malaysian sectors as samples, with two constructs used to represent the dimensions of psychological factors, namely, risk-taking (RT) propensity and self-confidence (SC). The study results revealed that both constructs had a significant influence on the propensity to venture into business (PVB). However, GFSS had an insignificant moderating effect on the relationship between the two dimensions and provided input for policy makers to enhance GFSS efficiency in order to positively affect the growth rate of new businesses in Malaysia. Hence, this study bridged the research gap by identifying the influence of GFSS on PVB. As GFSS are an important tool for stimulating growth of the new business venture, the findings of this study have implications for policy makers to improve the quality and effectiveness, especially the delivery of GFSS to the targeted group.
Chronic Antibody-Mediated Liver Rejection: More than Meets the Eye
Authors: Rita Claudia , Iturrieta-Zuazo Ignacio , Ballester-González Rubén , Alonso-Alarcón Nieves , Moreno-Moreno Esther , Castañer-Alabau José , Nieto-Gañán Israel
Published: January 2021

Understanding the role of donor-specific antibodies (DSAs) in liver transplantation remains an investigative priority. Acute and chronic rejection associated with DSAs have been described. However, most transplant protocols did not consider the presence of DSAs at the moment of liver transplantation (LTx) or for the follow-up. A 65-year-old man received an ABO-compatible LTx for cirrhosis. Ten years after the LTx, he presented with a progressive elevation of liver enzymes and bilirubin. The single antigen Luminex bead assay showed the presence of DSAs against several DQ2, DQ7, and DQ8 alleles. The patient received several desensitization treatments regarding the persistence of DSAs. The anatomopathological study confirms chronic rejection. Although in this case the immunohistochemical deposits of C4d were negative, the data revealed morphological criteria of chronic graft injury and DSAs’ incompatibilities explained by structural analysis. These data support an antibody-mediated rejection (AMR). It could be reasonable to establish a protocol for human leukocyte antigen (HLA) typing of every LTx donor and recipient as well as a periodic follow-up to assess the presence of DSAs. This will make it possible to carry out studies of donor–recipient incompatibility and to confirm the existence of probable cases of AMR.
Origin and Spread of the Dengue Virus Type 1, Genotype V in Senegal, 2015–2019
Authors: Dieng Idrissa , Cunha Marielton dos Passos , Diagne Moussa Moïse , Sembène Pape Mbacké , Zanotto Paolo Marinho de Andrade , Faye Ousmane , Faye Oumar , Sall Amadou Alpha
Published: January 2021

Dengue virus (DENV) is the most widespread arthropod-borne virus, with the number and severity of outbreaks increasing worldwide in recent decades. Dengue is caused by genetically distinct serotypes, DENV-1–4. Here, we present data on DENV-1, isolated from patients with dengue fever during an outbreak in Senegal and Mali (Western Africa) in 2015–2019, that were analyzed by sequencing the envelope (E) gene. The emergence and the dynamics of DENV-1 in Western Africa were inferred by using maximum likelihood and Bayesian methods. The DENV-1 grouped into a monophyletic cluster that was closely related to those from Southeast Asia. The virus appears to have been introduced directly into Medina Gounass (Suburb of Dakar), Senegal (location probability = 0.301, posterior = 0.76). The introduction of the virus in Senegal occurred around 2014 (95% HPD = 2012.88–2014.84), and subsequently, the virus moved to regions within Senegal (e.g., Louga and Fatick), causing intense outbreaks in the subsequent years. The virus appears to have been introduced in Mali (a neighboring country) after its introduction in Senegal. In conclusion, we present evidence that the outbreak caused by DENV-1 in urban environments in Senegal and Mali after 2015 was caused by a single viral introduction from Asia.