bluuebunny/crossref_metadata_2025 huggingface dataset:
A Low-Cost Information Monitoring System for Smart Farming Applications
Authors: Saqib Muhammad , Almohamad Tarik Adnan , Mehmood Raja Majid
Published: April 2020

A low-cost, low-power, and low data-rate solution is proposed to fulfill the requirements of information monitoring for actual large-scale agricultural farms. A small-scale farm can be easily managed. By contrast, a large farm will require automating equipment that contributes to crop production. Sensor based soil properties measurement plays an integral role in designing a fully automated agricultural farm, also provides more satisfactory results than any manual method. The existing information monitoring solutions are inefficient in terms of higher deployment cost and limited communication range to adapt the need of large-scale agriculture farms. A serial based low-power, long-range, and low-cost communication module is proposed to confront the challenges of monitoring information over long distances. In the proposed system, a tree-based communication mechanism is deployed to extend the communication range by adding intermediate nodes. Each sensor node consists of a solar panel, a rechargeable cell, a microcontroller, a moisture sensor, and a communication unit. Each node is capable to work as a sensor node and router node for network traffic. Minimized data logs from the central node are sent daily to the cloud for future analytics purpose. After conducting a detailed experiment in open sight, the communication distance measured 250 m between two points and increased to 750 m by adding two intermediate nodes. The minimum working current of each node was 2 mA, and the packet loss rate was approximately 2–5% on different packet sizes of the entire network. Results show that the proposed approach can be used as a reference model to meet the requirements for soil measurement, transmission, and storage in a large-scale agricultural farm.
Performance Evaluation of RTS/CTS Scheme in Beacon-Enabled IEEE 802.15.6 MAC Protocol for Wireless Body Area Networks
Authors: Ullah  Sana , Hassan Mohammad Mehedi , Hossain M. Shamim , Alelaiwi Abdulhameed
Published: April 2020

The IEEE 802.15.6 standard has the potential to provide cost-effective and unobtrusive medical services to individuals with chronic health conditions. It is a low-power standard developed for wireless body area networks and enables wireless communication inside or near a human body. This standard utilizes a Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol to improve network performance under different channel access priorities. However, the CSMA/CA proposed in the IEEE 802.15.6 standard has poor throughput performance and link reliability when some of the nodes deployed on a human body are hidden from each other. We employ the RTS/CTS scheme to solve hidden node problems in IEEE 802.15.6 networks over a lossy channel. To improve performance of the RTS/CTS scheme, we adjust transmission power levels of the nodes according to transmission failures. We estimate throughput and energy consumption of the proposed model by differentiating several parameters, such as contention window size, values of bit error ratios, number of nodes in different priority classes. The performance results are obtained through analytical approximations and simulations. We observe that the proposed model significantly improves performance of the IEEE 802.15.6 CSMA/CA by resolving hidden node problems.
Ultra-Wideband Diversity MIMO Antenna System for Future Mobile Handsets
Authors: Ojaroudi Parchin Naser , Jahanbakhsh Basherlou Haleh , I. A. Al-Yasir Yasir , M. Abdulkhaleq Ahmed , A. Abd-Alhameed Raed
Published: April 2020

A new ultra-wideband (UWB) multiple-input/multiple-output (MIMO) antenna system is proposed for future smartphones. The structure of the design comprises four identical pairs of compact microstrip-fed slot antennas with polarization diversity function that are placed symmetrically at different edge corners of the smartphone mainboard. Each antenna pair consists of an open-ended circular-ring slot radiator fed by two independently semi-arc-shaped microstrip-feeding lines exhibiting the polarization diversity characteristic. Therefore, in total, the proposed smartphone antenna design contains four horizontally-polarized and four vertically-polarized elements. The characteristics of the single-element dual-polarized UWB antenna and the proposed UWB-MIMO smartphone antenna are examined while using both experimental and simulated results. An impedance bandwidth of 2.5–10.2 GHz with 121% fractional bandwidth (FBW) is achieved for each element. However, for S11 ≤ −6 dB, this value is more than 130% (2.2–11 GHz). The proposed UWB-MIMO smartphone antenna system offers good isolation, dual-polarized function, full radiation coverage, and sufficient efficiency. Besides, the calculated diversity performances of the design in terms of the envelope correlation coefficient (ECC) and total active reflection coefficient (TARC) are very low over the entire operating band.
Use of High-Field Electron Injection into Dielectrics to Enhance Functional Capabilities of Radiation MOS Sensors
Authors: Andreev Dmitrii V. , Bondarenko Gennady G. , Andreev Vladimir V. , Stolyarov Alexander A.
Published: April 2020

The paper suggests a design of radiation sensors based on metal-oxide-semiconductor (MOS) structures and p-channel radiation sensitive field effect transistors (RADFET) which are capable to function under conditions of high-field tunnel injection of electrons into the dielectric. We demonstrate that under these conditions, the dose sensitivity of the sensor can be significantly raised, and, besides, the intensity of radiation can be monitored in situ on the basis of determining the ionization current arising in the dielectric film. The paper proposes the model allowing to make a quantitative analysis of charge effects taking place in the radiation MOS sensors under concurrent influence of ionization radiation and high-field tunnel injection of electrons. Use of the model allows to properly interpret results of the radiation control. In order to test the designed sensors experimentally, we have utilized γ-rays, α-particle radiation, and proton beams. We have acquired experimental results verifying the enhancement of function capabilities of the radiation MOS sensors when these have been under high-field injection of electrons into the dielectric.
Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges
Authors: Lim Jia Zheng , Mountstephens James , Teo Jason
Published: April 2020

The ability to detect users’ emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality.
Erratum: Aulestia Viera, M., et al. A Time–Frequency Acoustic Emission-Based Technique to Assess Workpiece Surface Quality in Ceramic Grinding with PZT Transducer. Sensors 2019, 19, 3913
Authors: Aulestia Viera Martin A. , Aguiar Paulo R. , Oliveira Junior Pedro , Alexandre Felipe A. , Lopes Wenderson N. , Bianchi Eduardo C. , da Silva Rosemar Batista , D’addona Doriana , Andreoli Andre
Published: April 2020

The authors wish to make the following erratum to this paper [...]
Design and Simulation of a High-Speed Star Tracker for Direct Optical Feedback Control in ADCS
Authors: Marin Mikaël , Bang Hyochoong
Published: April 2020

Star Trackers are often the most accurate instrument in an Attitude Determination and Control Systems, but often present a slow update rate, requiring additional sensor and sensor fusion algorithms to provide a smoother and faster output. However, the available rate gyros are either noisy, or expensive and heavy. The proposed work investigates the feasibility of high-speed star trackers with modern optics, sensors, and computing systems. Firstly, we investigate the sensitivity of an optoelectrical acquisition system stimulated by dim stars, secondly, we propose and evaluate an algorithm designed to operate at high speed and to be compatible with an Field-Programmable Gate Array implementation, before evaluating the performance of the implementation on FPGA. Finally, we debate the usability of such a system, both in terms of compatibility with a mission and CubeSat ecosystems, and in terms of performance. As a result, aside from removing the need for a rate gyro, Attitude Determination and Control Systems overall pointing performances can be increased. The proposed attitude determination system achieved a 0.001° accuracy, with a 99.1% sky coverage and an ability to reject false-positive while performing a single-frame lost-in-space star identification at a 50 Hz update rate with a total delay of 19 ms, including 13 ms.
Symmetry Analysis of Amputee Gait Based on Body Center of Mass Trajectory and Discrete Fourier Transform
Authors: Ochoa-Diaz Claudia , Padilha L. Bó Antônio
Published: April 2020

The calculation of symmetry in amputee gait is a valuable tool to assess the functional aspects of lower limb prostheses and how it impacts the overall gait mechanics. This paper analyzes the vertical trajectory of the body center of mass (CoM) of a group formed by transfemoral amputees and non-amputees to quantitatively compare the symmetry level of this parameter for both cases. A decomposition of the vertical CoM into discrete Fourier series (DFS) components is performed for each subject’s CoM trajectory to identify the main components of each pattern. A DFS-based index is then calculated to quantify the CoM symmetry level. The obtained results show that the CoM displays different patterns along a gait cycle for each amputee, which differ from the sine-wave shape obtained in the non-amputee case. The CoM magnitude spectrum also reveals more coefficients for the amputee waveforms. The different CoM trajectories found in the studied subjects can be thought as the manifestation of developed compensatory mechanisms, which lead to gait asymmetries. The presence of odd components in the magnitude spectrum is related to the asymmetric behavior of the CoM trajectory, given the fact that this signal is an even function for a non-amputee gait. The DFS-based index reflects this fact due to the high value obtained for the non-amputee reference, in comparison to the low values for each amputee.
Evaluation of the Sheet Resistance of Inkjet-Printed Ag-Layers on Flexible, Uncoated Paper Substrates Using Van-der-Pauw’s Method
Authors: Zikulnig Johanna , Roshanghias Ali , Rauter Lukas , Hirschl Christina
Published: April 2020

With the growing significance of printed sensors on the electronics market, new demands on quality and reproducibility have arisen. While most printing processes on standard substrates (e.g., Polyethylene terephthalate (PET)) are well-defined, the printing on substrates with rather porous, fibrous and rough surfaces (e.g., uncoated paper) contains new challenges. Especially in the case of inkjet-printing and other deposition techniques that require low-viscous nanoparticle inks the solvents and deposition materials might be absorbed, inhibiting the formation of homogeneous conductive layers. As part of this work, the sheet resistance of sintered inkjet-printed conductive silver (Ag-) nanoparticle cross structures on two different, commercially available, uncoated paper substrates using Van-der-Pauw’s method is evaluated. The results are compared to the conductivity of well-studied, white heat stabilised and treated PET foil. While the sheet resistance on PET substrate is highly reproducible and the variations are solely process-dependent, the sheet resistance on uncoated paper depends more on the substrate properties themselves. The results indicate that the achievable conductivity as well as the reproducibility decrease with increasing substrate porosity and fibrousness.
Effect of the Elastomer Matrix on Thermoplastic Elastomer-Based Strain Sensor Fiber Composites
Authors: Georgopoulou Antonia , Kummerlöwe Claudia , Clemens Frank
Published: April 2020

In this study, a thermoplastic elastomer sensor fiber was embedded in an elastomer matrix. The effect of the matrix material on the sensor properties and the piezoresistive behavior of the single fiber-matrix composite system was investigated. For all composites, cycling test (dynamic test) and the relaxation behavior at different strains (quasi-static test) were investigated. In all cases, dynamic properties and quasi-static significantly changed after embedding, compared to the pure fiber. The composite with the silicone elastomer PDMS (Polydimethylsiloxane) as matrix material exhibited deviation from linear response of the resistivity at low strains and proved an unsuitable choice compared to natural rubber. The addition of a spring construct in the embedded sensor fiber natural rubber composite improved the linearity at low strains but increased the mechanical and electrical hysteresis of the soft matter sensor composite. Using pre-vulcanized natural rubber improved linearity at low strains and reduced significantly the stress and relative resistance relaxation as well as the resistance hysteresis, especially if the resistance remained low. In both cases of the pre-vulcanized rubber and the spring structure, the piezoresistive behavior was improved, and at the same time, the stiffness of the system was increased indicating that using a stiffer matrix can be a strategy for improving the sensor properties.
Interoperable Open Specifications Framework for the Implementation of Standardized Urban Platforms
Authors: Hernández José L. , García Rubén , Schonowski Joachim , Atlan Daniel , Chanson Guillaume , Ruohomäki Timo
Published: April 2020

The current cities’ urban challenges go through digitalization and integration of new technologies under the perspective of actual and future ecological, as well as socio-economic commitments. This process is translated into the Open Standardized Urban Data Platform, which plays a pivotal role. Within its main functionalities, data ingestion, analytics and services as vertical domains become necessary to create more environmentally friendly cities. However, there still exist some deficits. Among them, openness and interoperability are outlined. On the one hand, there is a lack of open data initiatives for increasing the smart services stock. On the other hand, interoperability depends upon vendors and integrators, reducing the possibilities of Smart City growth. In this context, under the mySMARTLife project (GA #731297) umbrella, an Open Specifications Framework has been developed in order to address four main issues: (1) data interoperability; (2) services or verticals interoperability; (3) openness; and (4) replicability. It enlightens the implementation and integration of multiple city domains (like infrastructures, mobility, energy, buildings) for smart management and big-data analytics. Its applicability is demonstrated in the three lighthouse cities of the project, Nantes (France), Hamburg (Germany) and Helsinki (Finland).
Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
Authors: Browarczyk Jakub , Kurowski Adam , Kostek Bozena
Published: April 2020

The aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was performed on obtained signals. Welch’s method, autoregressive modeling, and discrete wavelet transform were used for feature extraction. Principal component analysis (PCA) was performed in order to reduce the dimensionality of feature vectors. k-Nearest Neighbors (kNN), Support Vector Machines (SVM), and Neural Networks (NN) were employed for classification. Precision, recall, F1 score, as well as a discussion based on statistical analysis, were shown. The paper also contains code utilized in preprocessing and the main part of experiments.
Torque Ripple Minimization of the Permanent Magnet Synchronous Machine by Modulation of the Phase Currents
Authors: Jędryczka Cezary , Danielczyk Dawid , Szeląg Wojciech
Published: April 2020

This paper deals with the torque ripple minimization method based on the modulation of the phase currents of the permanent-magnet synchronous motor (PMSM) drive. The shape of the supply current waveforms reducing the torque ripple of the machine considered was determined on the basis of finite element analysis (FEA). In the proposed approach, the machine is supplied by a six-leg inverter in order to allow for the injection of zero sequence current harmonics. Two test PMSMs with fractional-slot concentrated windings (FSCW) and surface-mounted permanent magnets (SPMs) have been examined as a case study problem. Wide-range fractional analyses were performed using developed numerical models of the electromagnetic field distribution in the considered machines. The results obtained show that the level of torque ripple in FSCW PMSMs can be effectively reduced by the modulation of the phase currents under the six-leg inverter supply.
3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm
Authors: Pan Jeng-Shyang , Chai Qing-Wei , Chu Shu-Chuan , Wu Ning
Published: April 2020

In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH algorithm is verified by the CEC 2013 test suit, and shows better results than the original BH. In addition, the EBH and other celebrated algorithms can be used to solve node coverage problems of Wireless Sensor Network (WSN) in 3-D terrain with satisfactory performance.
Acoustic Emission Analysis of Corroded Reinforced Concrete Columns under Compressive Loading
Authors: Li Qiang , Jin Xianyu , Wu Dan , Ye Hailong
Published: April 2020

In this work, the failure process of non-corroded and corroded reinforced concrete (RC) columns under eccentric compressive loading is studied using the acoustic emission (AE) technique. The results show that reinforcement corrosion considerably affects the mechanical failure process of RC columns. The corrosion of reinforcement in RC columns leads to highly active AE signals at the initial stage of loading, in comparison to the non-corroded counterparts. Also, a continuous AE hit pattern with a higher number of cumulative hits is observed for corroded RC columns. The spatial distribution and evolution of AE events indicate that the reinforcement corrosion noticeably accelerates the initiation and propagation of cracking in the RC columns during compressive loading. The AE characteristics of corroded RC columns are in agreement with the macroscopic failure behaviors observed during the damage and failure process. A damage evolution model of corroded RC columns based on the AE parameters is proposed.
Space Matters? Exploring Gender Differentials in the Age at Marriage, Greece (1980–2017)
Authors: Rontos Kostas , Salvati Luca
Published: April 2020

Although local context is considered a key factor shaping differences in the age at marriage between spouses, spatially explicit investigations of the gender gap in marriage timing were scarce in Europe, especially in more traditional societies. The present study analyses the spatial distribution of the gender age gap at marriage in Greece, a country experiencing a late demographic transition compared with other European societies. Analysis of prefecture-level data between 1980 and 2017 indicates a continuous increase in the age at marriage, with a moderate reduction in the gender age gap (5 and 3 years respectively in 1980 and 2017). While in the early 1980s age differentials at marriage between men and women diverged in rural and urban areas, a reduced gender gap and greater spatial heterogeneity were observed in 2017, indicating social modernization in most rural communities. These findings highlight the role of local contexts in shaping attitudes toward marriage postponement in Greece, suggesting that the spatial diffusion of marriage homogamy—as an indicator of social change—is influenced by the emergence of ‘permeable’ and ‘resistant’ communities with characteristic socioeconomic profiles. Going beyond the traditional urban–rural divide, space has become an important mediator of gender power dynamics, evidencing the progressive fragmentation of social processes and the increasing heterogeneity of the related demographic patterns at the local community scale. Spatial analysis contributes to delineate such complex processes, integrating results from approaches that assess individual behaviors with a refined investigation of macro-scale patterns of change.
Using Si, Al and Fe as Tracers for Source Apportionment of Air Pollutants in Lake Baikal Snowpack
Authors: Semenov Mikhail Yu. , Silaev Anton V. , Semenov Yuri M. , Begunova Larisa A.
Published: April 2020

The aim of this study was to select chemical species characterized by distinctly different proportions in natural and anthropogenic particulate matter that could be used as tracers for air pollutant sources. The end-member mixing approach, based on the observation that the chemical species in snow closely correlated with land use are those that exhibit differences in concentrations across the different types of anthropogenic wastes, was used for source apportionment. The concentrations of Si and Fe normalized to Al were used as tracers in the mixing equations. Mixing diagrams showed that the major pollution sources (in descending order) are oil, coal, and wood combustion. The traces of several minor sources, such as aluminum production plants, pulp and paper mills, steel rust, and natural aluminosilicates, were also detected. It was found that the fingerprint of diesel engines on snow is similar to that of oil combustion; thus, future research of the role of diesel engines in air pollution will be needed. The insufficient precision of source apportionment is probably due to different combinations of pollution sources in different areas. Thus, principles for the delineation of areas affected by different source combinations should be the subject of further studies.
Inter-Provincial Market Fragmentation and Regional Economic Development in China
Authors: Luo Fuzheng , Luo Nengsheng
Published: April 2020

This paper measures inter-provincial market fragmentation by adopting an adjusted priced-based approach from the Law of One Price using a three-dimensional panel of annual price on eight goods across 31 provinces in Mainland China during 1999–2015. By using the system Generalized Moment Estimation (GMM) approach, we analyze the non-linear effect of inter-provincial market fragmentation on regional economic development and its differences in various regions and periods. By constructing a Cross-Terms Model, we analyze the influence of various motivations of provincial governments on the non-linear relationship between inter-provincial market fragmentation and regional economic development. The results show that (1) Chinese domestic market fragmentation appears to have caused a fluctuating decline during 1999–2015. (2) The inter-provincial market fragmentation imposes an inverted U-shaped influence on regional economic development. It is necessary to maintain moderate market fragmentation for the promotion of regional economic development. (3) It is beneficial to maintain a lower degree of market fragmentation as time goes on. It is necessary to maintain a lower degree of market fragmentation in Eastern and Central China compared with Western China. (4) Compared with Social Stability and Official Positions Promotion, the motivation of Fiscal Revenue Enhancement requires the maintenance of a lower degree of inter-provincial market fragmentation for regional economic development.
Assuming the Best: Individual Differences in Compensatory “Green” Beliefs Predict Susceptibility to the Negative Footprint Illusion
Authors: MacCutcheon Douglas , Holmgren Mattias , Haga Andreas
Published: April 2020

Recent years have seen a marked increase in carbon emissions despite pledges made by the international community at the Paris Accord in 2015 to reduce fossil fuel production and consumption. Rebound effects could contribute to this phenomenon as, in which attempts to curb carbon emissions might have inadvertently led to an upswing in fossil fuel usage. The present study hypothesizes that rebound effects are driven by a misapplication of compensatory balancing heuristics, with the unintended outcome of producing inaccurate estimates of the environmental impact of “green” or environmentally friendly labelled products or behaviors. The present study therefore aims to investigate the relationship between participants’ degree of compensatory thinking (e.g., “Recycling compensates for driving a car”) and their susceptibility to the Negative Footprint Illusion, a widely replicated phenomenon demonstrating that the presence of “green” products biases carbon footprint estimations. One hundred and twelve participants were asked to complete a 15-item Compensatory Green Beliefs scale and to estimate the total carbon footprint of a set of 15 conventional houses, followed by a set that included 15 “green” houses in addition to 15 conventional houses. Results indicated that participants, on average, believed that the “green” houses were carbon neutral, and that susceptibility to the Negative Footprint Illusion was predicted by performance on the Compensatory Green Beliefs scale. This is the first study confirming that individual differences in cognitive processes (i.e., Compensatory Green Beliefs) are indeed related to inaccurate estimates of “green” products, providing a foundation for further investigation of the influence of “green” and compensatory beliefs on carbon footprint estimates.
Climatic Changes, Water Systems, and Adaptation Challenges in Shawi Communities in the Peruvian Amazon
Authors: Torres-Slimming Paola A. , Wright Carlee J. , Lancha Guillermo , Carcamo Cesar P. , Garcia Patricia J. , Ford James D. ,   IHACC Research Team, Harper Sherilee L.
Published: April 2020

Climate change impacts on water systems have consequences for Indigenous communities. We documented climatic changes on water systems observed by Indigenous Shawi and resultant impacts on health and livelihoods, and explored adaptation options and challenges in partnership with two Indigenous Shawi communities in the Peruvian Amazon. Qualitative data were collected via PhotoVoice, interviews, focus group discussions, and transect walks, and analyzed using a constant comparative method and thematic analysis. Quantitative data were collected via a household survey and analyzed descriptively. Households observed seasonal weather changes over time (n = 50; 78%), which had already impacted their family and community (n = 43; 86%), such as more intense rainfall resulting in flooding (n = 29; 58%). Interviewees also described deforestation impacts on the nearby river, which were exacerbated by climate-related changes, including increased water temperatures (warmer weather, exacerbated by fewer trees for shading) and increased erosion and turbidity (increased rainfall, exacerbated by riverbank instability due to deforestation). No households reported community-level response plans for extreme weather events, and most did not expect government assistance when such events occurred. This study documents how Indigenous peoples are experiencing climatic impacts on water systems, and highlights how non-climatic drivers, such as deforestation, exacerbate climate change impacts on water systems and community livelihoods in the Peruvian Amazon.
Municipal Solid Waste and Utility Consumption in Taiwan
Authors: Sung Hsin-Chen , Sheu Yiong-Shing , Yang Bing-Yuan , Ko Chun-Han
Published: April 2020

In Taiwan, 3,130,735 t of refuse for disposal and 4,113,808 t of recycled recyclable waste were generated in 2017. The government of Taiwan has been actively promoting a resource recycling program since July 1998. To pursue sustainability and locate waste minimization opportunities, the correlation between utility consumption and population and the quantity of refuse and recyclable waste from municipalities in Taiwan was studied. There are six special municipalities and 16 cities and counties covering a great variety of urbanization and settlement characteristics, such as registered populations, electricity, and water consumption. The above parameters of the municipalities were correlated with the quantities of refuse and recycled urban waste. Residential electricity consumption, overall population, and business electricity consumption were found to be major parameters correlating the generation of refuse and recycled urban waste. Due to their higher levels of business activities, the waste generation behaviours of these six special municipalities are more diverse than those of the 16 municipalities. Due to the discrepancy of the registered population system, the utility consumption values within administrative boundaries can better predict municipal solid waste, (MSW) generation than utility consumption at a per capita. Utility consumption within administrative boundaries is more convenient as a measure to predict refuse and recycled urban waste than other complex social–economic indicators.
Impact Model of Tourism Production and Consumption in Nanjing Yunjin: The Perspective of Cultural Heritage Reproduction
Authors: Zhang Ke , Zhang Mu , Law Rob , Chen Xuanyu , Wang Qiongyao
Published: April 2020

Nanjing Yunjin was included in “the first batch of non-material cultural heritage list in China” in 2006, and the city was also selected as “a list of representatives of human intangible cultural heritage” by the United Nations in September 2009. Nanjing Yunjin is now a scarce tourism resource on the verge of extinction. Carrying out effective cultural tourism development and production, and informing consumers about its cultural connotation are problems worth studying. This study aims to explore and analyze the cultural reproduction process of Nanjing Yunjin in the cultural tourism production-consumption closed-cycle model. Based on the review, the study introduces word cloud tools and explores the cultural production links of heritage by means of narrative analysis, applies quantitative methods to verify the relationship among production, consumption, and reproduction, and finally, constructs the production-consumption impact model of Nanjing Yunjin cultural tourism. Results indicate that the cultural tourism production of Nanjing Yunjin has a significant positive impact on cultural tourism consumption, which, in turn, positively affects cultural reproduction. In addition, cultural tourism production has a significant impact on its cultural reproduction part, and consumption plays a mediating role in the impact of cultural tourism production on its reproduction.
Joint Emission Reduction Strategy in Green Supply Chain under Environmental Regulation
Authors: Zhang Wensi , Xiao Jing , Cai Lingfei
Published: April 2020

Under the threat of global warming, joint emission reduction strategy has been widely adopted as an effective solution for the industry to guarantee environmental sustainability. In the practice of supply chain, environmental regulations and supply chain contracts are applied with the attempt to improve environmental performance. However, whether these measures are actually effective remains unanswered. In this paper, we study a supply chain with one manufacturer and one retailer adopting joint emission reduction strategy. We first investigate under what circumstance the environmental regulation can effectively result in higher emission reduction efforts. The result shows that when the cost coefficient satisfies certain conditions, the increase of penalty or subsidy can lead to more investment in emission reduction. In addition, if the environmental impact caused by the production process is extremely high, the enforcement of the regulation is ineffective. We also explore how the cost-revenue-sharing contract affects the emission reduction strategy and the coordination of the members in the supply chain. The results suggest that the incentive effect of environmental regulation is more effective when the supply chain coordination contract exists. Numerical experiments are also presented to verify our analytical conclusions.
Sustainable Development with Smart Meter Data Analytics Using NoSQL and Self-Organizing Maps
Authors: Oprea Simona-Vasilica , Bâra Adela , Tudorică Bogdan George , Dobrița (Ene) Gabriela
Published: April 2020

The smart metered electricity consumption data and high dimensional questionnaires provide useful information for designing the tariffs aimed at reducing electricity consumption and peak. The volume of data generated by smart meters for a sample of around four thousand residential consumers requires Not only Structured Query Language (NoSQL) solutions, data management and artificial neural network clustering algorithms, such as Self-Organizing Maps. In this paper, we propose a novel methodology that handles a large volume of data and extracts information from electricity consumption measured at 30 min and from complex questionnaires. Five three-level Time-of-Use tariffs are altered and investigated to minimize the consumers’ payment. Then, input data analysis revealed that the peak consumption is influenced by a segment of consumers that can be targeted to flatten the peak. Based on simulations, more than 23% of the peak consumption can be reduced by shifting it from peak to off-peak hours.
The Development and Assessment of Free-Flow Speed Models under Heterogeneous Traffic in Facilitating Sustainable Inter Urban Multilane Highways
Authors: Leong Lee Vien , Azai Tuti Azmalia , Goh Wins Cott , Mahdi Mohammed Bally
Published: April 2020

The desired speed that drivers can drive without being obstructed or influenced by other road users is characterized as free-flow speed. However, free-flow speed can be influenced by other factors such as the characteristics of the vehicle, driver, road conditions, weather, and speed limits. Due to the country’s heterogeneous traffic conditions, this study aims to develop and assess free-flow speed models based on different vehicle classes and road characteristics in Malaysia. Data were sampled at 16 sites of multilane highways in Malaysia. Analyses of free-flow speed were conducted based on individual and grouped vehicle classes. Subsequently, multiple regression analyses were conducted based on these grouped vehicle classes to develop free-flow speed models. The findings show that the model with the grouping of all vehicles, which includes heavy vehicles and motorcycles, is the most suitable model as it yields the best results based on the performance indicators. The development of a free-flow speed model based on local traffic conditions, which can accurately estimate free-flow speed without having to conduct field measurements, is essential for saving time and costs in data collection. The findings from this study will contribute to improving the design of multilane highways and, ultimately, ensuring the sustainable environment of road networks.
A Novel Learning Rate Schedule in Optimization for Neural Networks and It’s Convergence
Authors: Park Jieun , Yi Dokkyun , Ji Sangmin
Published: April 2020

The process of machine learning is to find parameters that minimize the cost function constructed by learning the data. This is called optimization and the parameters at that time are called the optimal parameters in neural networks. In the process of finding the optimization, there were attempts to solve the symmetric optimization or initialize the parameters symmetrically. Furthermore, in order to obtain the optimal parameters, the existing methods have used methods in which the learning rate is decreased over the iteration time or is changed according to a certain ratio. These methods are a monotonically decreasing method at a constant rate according to the iteration time. Our idea is to make the learning rate changeable unlike the monotonically decreasing method. We introduce a method to find the optimal parameters which adaptively changes the learning rate according to the value of the cost function. Therefore, when the cost function is optimized, the learning is complete and the optimal parameters are obtained. This paper proves that the method ensures convergence to the optimal parameters. This means that our method achieves a minimum of the cost function (or effective learning). Numerical experiments demonstrate that learning is good effective when using the proposed learning rate schedule in various situations.
Dark Matter Candidates with Dark Energy Interiors Determined by Energy Conditions
Authors: Dymnikova Irina
Published: April 2020

We outline the basic properties of regular black holes, their remnants and self-gravitating solitons G-lumps with the de Sitter and phantom interiors, which can be considered as heavy dark matter (DM) candidates generically related to a dark energy (DE). They are specified by the condition T t t = T r r and described by regular solutions of the Kerr-Shild class. Solutions for spinning objects can be obtained from spherical solutions by the Newman-Janis algorithm. Basic feature of all spinning objects is the existence of the equatorial de Sitter vacuum disk in their deep interiors. Energy conditions distinguish two types of their interiors, preserving or violating the weak energy condition dependently on violation or satisfaction of the energy dominance condition for original spherical solutions. For the 2-nd type the weak energy condition is violated and the interior contains the phantom energy confined by an additional de Sitter vacuum surface. For spinning solitons G-lumps a phantom energy is not screened by horizons and influences their observational signatures, providing a source of information about the scale and properties of a phantom energy. Regular BH remnants and G-lumps can form graviatoms binding electrically charged particles. Their observational signature is the electromagnetic radiation with the frequencies depending on the energy scale of the interior de Sitter vacuum within the range available for observations. A nontrivial observational signature of all DM candidates with de Sitter interiors predicted by analysis of dynamical equations is the induced proton decay in an underground detector like IceCUBE, due to non-conservation of baryon and lepton numbers in their GUT scale false vacuum interiors.
Pancreatic Cancer Early Detection Using Twin Support Vector Machine Based on Kernel
Authors: Sadewo Wismaji , Rustam Zuherman , Hamidah Hamidah , Chusmarsyah Alifah Roudhoh
Published: April 2020

Early detection of pancreatic cancer is difficult, and thus many cases of pancreatic cancer are diagnosed late. When pancreatic cancer is detected, the cancer is usually well developed. Machine learning is an approach that is part of artificial intelligence and can detect pancreatic cancer early. This paper proposes a machine learning approach with the twin support vector machine (TWSVM) method as a new approach to detecting pancreatic cancer early. TWSVM aims to find two symmetry planes such that each plane has a distance close to one data class and as far as possible from another data class. TWSVM is fast in building a model and has good generalizations. However, TWSVM requires kernel functions to operate in the feature space. The kernel functions commonly used are the linear kernel, polynomial kernel, and radial basis function (RBF) kernel. This paper uses the TWSVM method with these kernels and compares the best kernel for use by TWSVM to detect pancreatic cancer early. In this paper, the TWSVM model with each kernel is evaluated using a 10-fold cross validation. The results obtained are that TWSVM based on the kernel is able to detect pancreatic cancer with good performance. However, the best kernel obtained is the RBF kernel, which produces an accuracy of 98%, a sensitivity of 97%, a specificity of 100%, and a running time of around 1.3408 s.
Symmetry Classes and Matrix Representations of the 2D Flexoelectric Law
Authors: Abdoul-Anziz Houssam , Auffray Nicolas , Desmorat Boris
Published: April 2020

We determine the different symmetry classes of bi-dimensional flexoelectric tensors. Using the harmonic decomposition method, we show that there are six symmetry classes. We also provide the matrix representations of the flexoelectric tensor and of the complete flexoelectric law, for each symmetry class.
Treatment of Blepharospasm and Oromandibular Dystonia with Botulinum Toxins
Authors: Hassell Travis J.W. , Charles David
Published: April 2020

Blepharospasm and oromandibular dystonia are focal dystonias characterized by involuntary and often patterned, repetitive muscle contractions. There is a long history of medical and surgical therapies, with the current first-line therapy, botulinum neurotoxin (BoNT), becoming standard of care in 1989. This comprehensive review utilized MEDLINE and PubMed and provides an overview of the history of these focal dystonias, BoNT, and the use of toxin to treat them. We present the levels of clinical evidence for each toxin for both, focal dystonias and offer guidance for muscle and site selection as well as dosing.
Editorial to the Special Issue “Probing New Physics with Black Holes”
Authors: Barrau Aurélien
Published: April 2020

Black holes are fantastic laboratories for probing new physics. Both theoretically and experimentally, many new ideas are emerging to use them as tools for understanding better quantum gravity or classical gravity beyond general relativity. I briefly review some new results.
On the Analyticity of Static Solutions of a Field Equation in Finsler Gravity
Authors: Caponio Erasmo , Masiello Antonio
Published: April 2020

It is well-known that static vacuum solutions of Einstein equations are analytic in suitable coordinates. We ask here for an extension of this result in the context of Finsler gravity. We consider Finsler spacetimes that retain several properties of static Lorentzian spacetimes, are Berwald and have vanishing Ricci scalar.
RSV Reprograms the CDK9•BRD4 Chromatin Remodeling Complex to Couple Innate Inflammation to Airway Remodeling
Authors: Brasier Allan R.
Published: April 2020

Respiratory syncytial virus infection is responsible for seasonal upper and lower respiratory tract infections worldwide, causing substantial morbidity. Self-inoculation of the virus into the nasopharynx results in epithelial replication and distal spread into the lower respiratory tract. Here, respiratory syncytial virus (RSV) activates sentinel cells important in the host inflammatory response, resulting in epithelial-derived cytokine and interferon (IFN) expression resulting in neutrophilia, whose intensity is associated with disease severity. I will synthesize key findings describing how RSV replication activates intracellular NFκB and IRF signaling cascades controlling the innate immune response (IIR). Recent studies have implicated a central role for Scg1a1+ expressing progenitor cells in IIR, a cell type uniquely primed to induce neutrophilic-, T helper 2 (Th2)-polarizing-, and fibrogenic cytokines that play distinct roles in disease pathogenesis. Molecular studies have linked the positive transcriptional elongation factor-b (P-TEFb), a pleiotrophic chromatin remodeling complex in immediate-early IIR gene expression. Through intrinsic kinase activity of cyclin dependent kinase (CDK) 9 and atypical histone acetyl transferase activity of bromodomain containing protein 4 (BRD4), P-TEFb mediates transcriptional elongation of IIR genes. Unbiased proteomic studies show that the CDK9•BRD4 complex is dynamically reconfigured by the innate response and targets TGFβ-dependent fibrogenic gene networks. Chronic activation of CDK9•BRD4 mediates chromatin remodeling fibrogenic gene networks that cause epithelial mesenchymal transition (EMT). Mesenchymal transitioned epithelial cells elaborate TGFβ and IL6 that function in a paracrine manner to expand the population of subepithelial myofibroblasts. These findings may account for the long-term reduction in pulmonary function in children with severe lower respiratory tract infection (LRTI). Modifying chromatin remodeling properties of the CDK9•BRD4 coactivators may provide a mechanism for reducing post-infectious airway remodeling that are a consequence of severe RSV LRTIs.
Shedding Light on the Effect of Natural Anti-Herpesvirus Alkaloids on SARS-CoV-2: A Treatment Option for COVID-19
Authors: Hassan Sherif T. S.
Published: April 2020

The whole world is currently facing an unseen enemy, called coronavirus disease 2019 (COVID-19), which is causing a global pandemic. This disease is caused by a novel single-stranded enveloped RNA virus, known as the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Although huge efforts are being made to produce effective therapies to combat this disease, it continues to be one of the greatest challenges in medicine. There is no doubt that herpesviruses are one of the most important viruses that infect humans and animals, and infections induced by these pathogens have developed into a great threat to public health. According to the currently available evidence, the correlation between herpesviruses and coronaviruses is limited to the induced complications following the infections. For instance, the inflammation that is induced at the sites of infection could tie these viruses to each other in a relationship. Another example, bovine herpesvirus 1, which is an important pathogen of cattle, can cause a severe respiratory infection; the same way in which SARS-CoV-2 affects humans. Considering the current circumstances related to the COVID-19 crisis, this editorial paper, which belongs to the Special Issue “Recent Advances in Herpesviruses Research: What’s in the Pipeline?” aims to draw attention to some natural anti-herpesvirus alkaloid compounds, which have recently been proven to have excellent inhibitory efficacy against SARS-CoV-2 replication. Thus, this special focus is an attempt to hunt down various treatment options to combat COVID-19 based on repurposing drugs that are known to have multiple antiviral properties, including against herpesvirus.