bluuebunny/crossref_metadata_2025 huggingface dataset:
Wildfire Smoke Particle Properties and Evolution, From Space-Based Multi-Angle Imaging II: The Williams Flats Fire during the FIREX-AQ Campaign
Authors: Junghenn Noyes Katherine T. , Kahn Ralph A. , Limbacher James A. , Li Zhanqing , Fenn Marta A. , Giles David M. , Hair Johnathan W. , Katich Joseph M. , Moore Richard H. , Robinson Claire E. , Sanchez Kevin J. , Shingler Taylor J. , Thornhill Kenneth L. , Wiggins Elizabeth B. , Winstead Edward L.
Published: November 2020

Although the characteristics of biomass burning events and the ambient ecosystem determine emitted smoke composition, the conditions that modulate the partitioning of black carbon (BC) and brown carbon (BrC) formation are not well understood, nor are the spatial or temporal frequency of factors driving smoke particle evolution, such as hydration, coagulation, and oxidation, all of which impact smoke radiative forcing. In situ data from surface observation sites and aircraft field campaigns offer deep insight into the optical, chemical, and microphysical traits of biomass burning (BB) smoke aerosols, such as single scattering albedo (SSA) and size distribution, but cannot by themselves provide robust statistical characterization of both emitted and evolved particles. Data from the NASA Earth Observing System’s Multi-Angle Imaging SpectroRadiometer (MISR) instrument can provide at least a partial picture of BB particle properties and their evolution downwind, once properly validated. Here we use in situ data from the joint NOAA/NASA 2019 Fire Influence on Regional to Global Environments Experiment-Air Quality (FIREX-AQ) field campaign to assess the strengths and limitations of MISR-derived constraints on particle size, shape, light-absorption, and its spectral slope, as well as plume height and associated wind vectors. Based on the satellite observations, we also offer inferences about aging mechanisms effecting downwind particle evolution, such as gravitational settling, oxidation, secondary particle formation, and the combination of particle aggregation and condensational growth. This work builds upon our previous study, adding confidence to our interpretation of the remote-sensing data based on an expanded suite of in situ measurements for validation. The satellite and in situ measurements offer similar characterizations of particle property evolution as a function of smoke age for the 06 August Williams Flats Fire, and most of the key differences in particle size and absorption can be attributed to differences in sampling and changes in the plume geometry between sampling times. Whereas the aircraft data provide validation for the MISR retrievals, the satellite data offer a spatially continuous mapping of particle properties over the plume, which helps identify trends in particle property downwind evolution that are ambiguous in the sparsely sampled aircraft transects. The MISR data record is more than two decades long, offering future opportunities to study regional wildfire plume behavior statistically, where aircraft data are limited or entirely lacking.
Green Vegetation Cover Dynamics in a Heterogeneous Grassland: Spectral Unmixing of Landsat Time Series from 1999 to 2014
Authors: He Yuhong , Yang Jian , Guo Xulin
Published: November 2020

The ability to quantify green vegetation across space and over time is useful for studying grassland health and function and improving our understanding of the impact of land use and climate change on grasslands. Directly measuring the fraction of green vegetation cover is labor-intensive and thus only practical on relatively smaller experimental sites. Remote sensing vegetation indices, as a commonly-used method for large-area vegetation mapping, were found to produce inconsistent accuracies when mapping green vegetation in semi-arid grasslands, largely due to mixed pixels including both photosynthetic and non-photosynthetic material. The spectral mixture approach has the potential to map the fraction of green vegetation cover in a heterogeneous landscape, thanks to its ability to decompose a spectral signal from a mixed pixel into a set of fractional abundances. In this study, a time series of fractional green vegetation cover (FGVC) from 1999 to 2014 is estimated using the spectral mixture approach for a semi-arid mixed grassland, which represents a typical threatened, species-rich habitat in Central Canada. The shape of pixel clouds in each of the Landsat images is used to identify three major image endmembers (green vegetation, bare soil/litter, and water/shadow) for automated image spectral unmixing. The FGVC derived through the spectral mixture approach correlates highly with field observations (R2 = 0.86). Change in the FGVC over the study period was also mapped, and green vegetation in badlands and uplands is found to experience a slight increase, while vegetation in riparian zone shows a decrease. Only a small portion of the study area is undergoing significant changes, which is likely attributable to climate variability, bison reintroduction, and wildfire. The results of this study suggest that the automated spectral unmixing approach is promising, and the time series of medium-resolution images is capable of identifying changes in green vegetation cover in semi-arid grasslands. Further research should investigate driving forces for areas undergoing significant changes.
A Brief Analysis of the Triangle Method and a Proposal for its Operational Implementation
Authors: Carlson Toby N.
Published: November 2020

The well-known triangle method in optical/thermal remote sensing, its construction, uncertainties, and the significance of its products are first discussed. These topics are then followed by an outline of how the method can be implemented operationally for practical use, including a suggestion for constructing a dynamic crop moisture index.
Efficient Marginalized Particle Smoother for Indoor CSS–TOF Localization with Non-Gaussian Errors
Authors: Yang Yuan , Wang Manyi , Qiao Yunxia , Zhang Bo , Yang Haoran
Published: November 2020

The time-series state and parameter estimations of indoor localization continue to be a topic of growing importance. To deal with the nonlinear and positive skewed non-Gaussian dynamic of indoor CSS–TOF (Chirp-Spread-Spectrum Time-of-Flight) ranging measurements and position estimations, Monte Carlo Bayesian smoothers are promising as involving the past, present, and future observations. However, the main problems are how to derive trackable smoothing recursions and to avoid the degeneracy of particle-based smoothed distributions. To incorporate the backward smoothing density propagation with the forward probability recursion efficiently, we propose a lightweight Marginalized Particle Smoother (MPS) for nonlinear and non-Gaussian errors mitigation. The performance of the position prediction, filtering, and smoothing are investigated in real-world experiments carried out with vehicle on-board sensors. Results demonstrate the proposed smoother enables a great tool by reducing temporal and spatial errors of mobile trajectories, with the cost of a few sequence delay and a small number of particles. Therefore, MPS outperforms the filtering and smoothing methods under weak assumptions, low computation, and memory requirements. In the view that the sampled trajectories stay numerically stable, the MPS form is validated to be applicable for time-series position tracking.
An Infrastructure-Free Magnetic-Based Indoor Positioning System with Deep Learning
Authors: Fernandes Letícia , Santos Sara , Barandas Marília , Folgado Duarte , Leonardo Ricardo , Santos Ricardo , Carreiro André , Gamboa Hugo
Published: November 2020

Infrastructure-free Indoor Positioning Systems (IPS) are becoming popular due to their scalability and a wide range of applications. Such systems often rely on deployed Wi-Fi networks. However, their usability may be compromised, either due to scanning restrictions from recent Android versions or the proliferation of 5G technology. This raises the need for new infrastructure-free IPS independent of Wi-Fi networks. In this paper, we propose the use of magnetic field data for IPS, through Deep Neural Networks (DNN). Firstly, a dataset of human indoor trajectories was collected with different smartphones. Afterwards, a magnetic fingerprint was constructed and relevant features were extracted to train a DNN that returns a probability map of a user’s location. Finally, two postprocessing methods were applied to obtain the most probable location regions. We asserted the performance of our solution against a test dataset, which produced a Success Rate of around 80%. We believe that these results are competitive for an IPS based on a single sensing source. Moreover, the magnetic field can be used as an additional information layer to increase the robustness and redundancy of current multi-source IPS.
Image Forgery Detection and Localization via a Reliability Fusion Map
Authors: Yao Hongwei , Xu Ming , Qiao Tong , Wu Yiming , Zheng Ning
Published: November 2020

Moving away from hand-crafted feature extraction, the use of data-driven convolution neural network (CNN)-based algorithms facilitates the realization of end-to-end automated forgery detection in multimedia forensics. On the basis of fingerprints acquired by images from different camera models, the goal of this paper is to design an effective detector capable of completing image forgery detection and localization. Specifically, relying on the designed constant high-pass filter, we first establish a well-performing CNN architecture to adaptively and automatically extract characteristics, and design a reliability fusion map (RFM) to improve localization resolution, and tamper detection accuracy. The extensive results from our empirical experiments demonstrate the effectiveness of our proposed RFM-based detector, and its better performance than other competing approaches.
Gyrocardiography: A Review of the Definition, History, Waveform Description, and Applications
Authors: Sieciński Szymon , Kostka Paweł S. , Tkacz Ewaryst J.
Published: November 2020

Gyrocardiography (GCG) is a non-invasive technique of analyzing cardiac vibrations by a MEMS (microelectromechanical system) gyroscope placed on a chest wall. Although its history is short in comparison with seismocardiography (SCG) and electrocardiography (ECG), GCG becomes a technique which may provide additional insight into the mechanical aspects of the cardiac cycle. In this review, we describe the summary of the history, definition, measurements, waveform description and applications of gyrocardiography. The review was conducted on about 55 works analyzed between November 2016 and September 2020. The aim of this literature review was to summarize the current state of knowledge in gyrocardiography, especially the definition, waveform description, the physiological and physical sources of the signal and its applications. Based on the analyzed works, we present the definition of GCG as a technique for registration and analysis of rotational component of local cardiac vibrations, waveform annotation, several applications of the gyrocardiography, including, heart rate estimation, heart rate variability analysis, hemodynamics analysis, and classification of various cardiac diseases.
Fluid Intake Monitoring System Using a Wearable Inertial Sensor for Fluid Intake Management
Authors: Huang Hsiang-Yun , Hsieh Chia-Yeh , Liu Kai-Chun , Hsu Steen Jun-Ping , Chan Chia-Tai
Published: November 2020

Fluid intake is important for people to maintain body fluid homeostasis. Inadequate fluid intake leads to negative health consequences, such as headache, dizziness and urolithiasis. However, people in busy lifestyles usually forget to drink sufficient water and neglect the importance of fluid intake. Fluid intake management is important to assist people in adopting individual drinking behaviors. This work aims to propose a fluid intake monitoring system with a wearable inertial sensor using a hierarchical approach to detect drinking activities, recognize sip gestures and estimate fluid intake amount. Additionally, container-dependent amount estimation models are developed due to the influence of containers on fluid intake amount. The proposed fluid intake monitoring system could achieve 94.42% accuracy, 90.17% sensitivity, and 40.11% mean absolute percentage error (MAPE) for drinking detection, gesture spotting and amount estimation, respectively. Particularly, MAPE of amount estimation is improved approximately 10% compared to the typical approaches. The results have demonstrated the feasibility and the effectiveness of the proposed fluid intake monitoring system.
Design and Validation of an E-Textile-Based Wearable Sock for Remote Gait and Postural Assessment
Authors: Amitrano Federica , Coccia Armando , Ricciardi Carlo , Donisi Leandro , Cesarelli Giuseppe , Capodaglio Edda Maria , D’Addio Giovanni
Published: November 2020

This paper presents a new wearable e-textile based system, named SWEET Sock, for biomedical signals remote monitoring. The system includes a textile sensing sock, an electronic unit for data transmission, a custom-made Android application for real-time signal visualization, and a software desktop for advanced digital signal processing. The device allows the acquisition of angular velocities of the lower limbs and plantar pressure signals, which are postprocessed to have a complete and schematic overview of patient’s clinical status, regarding gait and postural assessment. In this work, device performances are validated by evaluating the agreement between the prototype and an optoelectronic system for gait analysis on a set of free walk acquisitions. Results show good agreement between the systems in the assessment of gait cycle time and cadence, while the presence of systematic and proportional errors are pointed out for swing and stance time parameters. Worse results were obtained in the comparison of spatial metrics. The “wearability” of the system and its comfortable use make it suitable to be used in domestic environment for the continuous remote health monitoring of de-hospitalized patients but also in the ergonomic assessment of health workers, thanks to its low invasiveness.
Semiconductor Gas Sensors: Materials, Technology, Design, and Application
Authors: Nikolic Maria Vesna , Milovanovic Vladimir , Vasiljevic Zorka Z. , Stamenkovic Zoran
Published: November 2020

This paper presents an overview of semiconductor materials used in gas sensors, their technology, design, and application. Semiconductor materials include metal oxides, conducting polymers, carbon nanotubes, and 2D materials. Metal oxides are most often the first choice due to their ease of fabrication, low cost, high sensitivity, and stability. Some of their disadvantages are low selectivity and high operating temperature. Conducting polymers have the advantage of a low operating temperature and can detect many organic vapors. They are flexible but affected by humidity. Carbon nanotubes are chemically and mechanically stable and are sensitive towards NO and NH3, but need dopants or modifications to sense other gases. Graphene, transition metal chalcogenides, boron nitride, transition metal carbides/nitrides, metal organic frameworks, and metal oxide nanosheets as 2D materials represent gas-sensing materials of the future, especially in medical devices, such as breath sensing. This overview covers the most used semiconducting materials in gas sensing, their synthesis methods and morphology, especially oxide nanostructures, heterostructures, and 2D materials, as well as sensor technology and design, application in advance electronic circuits and systems, and research challenges from the perspective of emerging technologies.
Powered Two-Wheeler Riding Profile Clustering for an In-Depth Study of Bend-Taking Practices
Authors: Diop Mohamed , Boubezoul Abderrahmane , Oukhellou Latifa , Espié Stéphane
Published: November 2020

The understanding of rider/vehicle interaction modalities remains an issue, specifically in the case of bend-taking. This difficulty results both from the lack of adequate instrumentation to conduct this type of study and from the variety of practices of this population of road users. Riders have numerous explanations of strategies for controlling their motorcycles when taking bends. The objective of this paper is to develop a data-driven methodology in order to identify typical riding behaviors in bends by using clustering methods. The real dataset used for the experiments is collected within the VIROLO++ collaborative project to improve the knowledge of actual PTW riding practices, especially during bend taking, by collecting real data on this riding situation, including data on PTW dynamics (velocity, normal acceleration, and jerk), position on the road (road curvature), and handlebar actions (handlebar steering angle). A detailed analysis of the results is provided for both the Anderson–Darling test and clustering steps. Moreover, the clustering results are compared with the subjective data of subjects to highlight and contextualize typical riding tendencies. Finally, we perform an in-depth analysis of the bend-taking practices of one subject to highlight the differences between different methods of controlling the motorcycle (steering handlebar vs. rider’s lean) using the rider action measurements made by pressure sensors.
Categorization and Characterization of Time Domain CMOS Temperature Sensors
Authors: Byun Sangjin
Published: November 2020

Time domain complementary metal-oxide-semiconductor (CMOS) temperature sensors estimate the temperature of a sensory device by measuring the frequency, period and/or delay time instead of the voltage and/or current signals that have been traditionally measured for a long time. In this paper, the time domain CMOS temperature sensors are categorized into twelve types by using the temperature estimation function which is newly defined as the ratio of two measured time domain signals. The categorized time domain CMOS temperature sensors, which have been published in literature, show different characteristics respectively in terms of temperature conversion rate, die area, process variation compensation, temperature error, power supply voltage sensitivity and so on. Based on their characteristics, we can choose the most appropriate one from twelve types to satisfy a given specification.
Speed Sensorless Control of Linear Ultrasonic Motors Based on Stator Vibration Amplitude Compensation
Authors: Yan Yuzhao , Yang Ming , Yang Tianyue , Ye Siwei , Jiang Wanlu
Published: November 2020

In some applications of linear ultrasonic motors (LUSMs), not installing speed/position sensors can reduce the size and cost of the system, changes in load will cause fluctuations in the speed of the LUSM. To eliminate the influence of load changes on speed, a speed sensorless control scheme based on stator vibration amplitude compensation (SSCBVC) is proposed. This scheme is implemented under the framework of the stator vibration amplitude-based speed control (VBSC) and frequency tracking. Based on the stator vibration amplitude-speed and the output force-speed curves of the LUSM, the relationship between the load changes and stator vibration amplitude (SVA) to be compensated is established, realizing a speed sensorless control of the LUSM under variable load conditions. The experimental results show that the maximum fluctuation of the speed is about 2.2% when the output force changes from 0 to 6 N with SSCBVC. This scheme can effectively reduce the influence of load changes on the speed of the LUSM without using speed/position sensors.
The Potential Benefit of Beta-Blockers for the Management of COVID-19 Protocol Therapy-Induced QT Prolongation: A Literature Review
Authors: Heriansyah Teuku , Nur Chomsy Indah , Febrianda Lyra , Farahiya Hadi Tjut , Andri Wihastuti Titin
Published: November 2020

The World Health Organization (WHO) officially announced coronavirus disease 2019 (COVID-19) as a pandemic in March 2020. Unfortunately, there are still no approved drugs for either the treatment or the prevention of COVID-19. Many studies have focused on repurposing established antimalarial therapies, especially those that showed prior efficacy against Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV), such as chloroquine and hydroxychloroquine, against COVID-19 combined with azithromycin. These classes of drugs potentially induce prolongation of the QT interval, which might lead to lethal arrhythmia. Beta-blockers, as a β-adrenergic receptor (β-AR) antagonist, can prevent an increase in the sympathetic tone, which is the most important arrhythmia trigger. In this literature review, we aimed to find the effect of administering azithromycin, chloroquine, and hydroxychloroquine on cardiac rhythm disorders and our findings show that bisoprolol, as a cardio-selective beta-blocker, is effective for the management of the QT (i.e., the start of the Q wave to the end of the T wave) interval prolongation in COVID-19 patients.
Automatic Development of Deep Learning Architectures for Image Segmentation
Authors: Nistor Sergiu Cosmin , Ileni Tudor Alexandru , Dărăbant Adrian Sergiu
Published: November 2020

Machine learning is a branch of artificial intelligence that has gained a lot of traction in the last years due to advances in deep neural networks. These algorithms can be used to process large quantities of data, which would be impossible to handle manually. Often, the algorithms and methods needed for solving these tasks are problem dependent. We propose an automatic method for creating new convolutional neural network architectures which are specifically designed to solve a given problem. We describe our method in detail and we explain its reduced carbon footprint, computation time and cost compared to a manual approach. Our method uses a rewarding mechanism for creating networks with good performance and so gradually improves its architecture proposals. The application for the algorithm that we chose for this paper is segmentation of eyeglasses from images, but our method is applicable, to a larger or lesser extent, to any image processing task. We present and discuss our results, including the architecture that obtained 0.9683 intersection-over-union (IOU) score on our most complex dataset.
The Impact of the Technological Capability of a Host Country on Inward FDI in OECD Countries: The Moderating Roles of Institutional Quality
Authors: Kim Seunghyun , Choi Byungchul
Published: November 2020

This empirical study explores the impacts of technological capability on inward foreign direct investment (FDI) with the moderations of institutional quality. We extend the existing literature by contributing the dynamic links between technology trade and institutional quality by using the panel data of 35 Organization for Economic Cooperation and Development (OECD) countries between 2000 and 2015. Based on fixed-effects regression, our results show that there is a U-shape relationship between the net technological capability of a host country and inward FDI. In addition, the institutional quality of a host country, government size and regulation have positive moderations, whereas sound money accessibility and legal system and property protection have negative moderations on the main U-shape relationship. Our study contributes to the literature on the determinants of inward FDI in the context of technological capabilities and institutional quality.
Economic and Human Features for Energy and Environmental Indicators: A Tool to Assess Countries’ Progress towards Sustainability
Authors: Torchio Marco Filippo , Lucia Umberto , Grisolia Giulia
Published: November 2020

Energy and environmental data represent fundamental information for the analysis of sustainable development. On the other hand, these aspects should be associated with economic and human dimensions in order to obtain a more holistic vision. From this perspective, some indicators are discussed and analyzed in this paper in order to assess the performance of a country. As regards the energetic aspects, the data of total primary energy supply and exergy losses were considered. The environmental aspects were taken into account by considering the greenhouse gas emissions and the particulate matter emissions. These energy and environmental data were put in relation to the GDP (gross domestic product) and HDI (human development index, a multidimensional index proposed by United Nations), respectively. So, two sets of indicators were introduced—the set E for economic properties and the set H for human aspects. A case study was conducted by analyzing a group of countries that meet two criteria: the same macro-geographical area and comparable numbers of citizens. The European area—in particular, its six most populous countries—was chosen. From the results obtained, it is possible to point out that some countries present different rankings depending on whether set E or set H is considered. Another important aspect discussed is the temporal evolution of the indicators (the interval from 1990 to 2017 was considered). Political decision-makers can be supported by the use of the indicators of set H in order to evaluate well-being related to their choices on actions related to the energy and environment. These indicators can be used both to analyze the trends of a country and to compare them with the performance of some other similar countries.
Influence of Pavement Structure, Traffic, and Weather on Urban Flexible Pavement Deterioration
Authors: Llopis-Castelló David , García-Segura Tatiana , Montalbán-Domingo Laura , Sanz-Benlloch Amalia , Pellicer Eugenio
Published: November 2020

Various studies have been recently conducted to predict pavement condition, but most of them were developed in a certain region where climate conditions were kept constant and/or the research focused on specific road distresses using single parameters. Thus, this research aimed at determining the influence of pavement structure, traffic demand, and climate factors on urban flexible pavement condition over time. To do this, the Structural Number was used as an indicator of the pavement capacity, various traffic and climate variables were defined, and the Pavement Condition Index was used as a surrogate measure of pavement condition. The analysis was focused on the calibration of regression models by using the K-Fold Cross Validation technique. As a result, for a given pavement age, pavement condition worsens as the Equivalent Single Axle Load and the Annual Average Height of Snow increased. Likewise, a cold Annual Average Temperature (5–15 °C) and a large Annual Average Range of Temperature (20–30 °C) encourage a more aggressive pavement deterioration process. By contrast, warm climates with low temperature variations, which are associated with low precipitation, lead to a longer pavement service life. Additionally, a new classification of climate zones was proposed on the basis of the weather influence on pavement deterioration.
ST-Trie: A Novel Indexing Scheme for Efficiently Querying Heterogeneous, Spatiotemporal IoT Data
Authors: Chu Hawon , Kim Jaeseong , Kim Seounghyeon , Suh Young-Kyoon , Lee Ryong , Jang Rae-Young , Park Minwoo
Published: November 2020

Recently, various environmental data, such as microdust pollution, temperature, humidity, etc., have been continuously collected by widely deployed Internet of Things (IoT) sensors. Although these data can provide great insight into developing sustainable application services, it is challenging to rapidly retrieve such data, due to their multidimensional properties and huge growth in volume over time. Existing indexing methods for efficiently locating those data expose several problems, such as high administrative cost, spatial overhead, and slow retrieval performance. To mitigate these problems, we propose a novel indexing scheme termed ST-Trie, for efficient retrieval over spatiotemporal IoT environment data. Given IoT sensor data with latitude, longitude, and time, the proposed scheme first converts the three-dimensional attributes to one-dimensional index keys. The scheme then builds a trie-based index, consisting of internal nodes inserted by the converted keys and leaf nodes containing the keys and pointers to actual IoT data. We leverage this index to process various types of queries. In our experiments with three real-world datasets, we show that the proposed ST-Trie index outperforms existing approaches by a substantial margin regarding response time. Furthermore, we show that the query processing performance via ST-Trie also scales very well with an increasing time interval. Finally, we demonstrate that when compressed, the ST-Trie index can significantly reduce its space overhead by approximately a factor of seven.
Assessment of Groundwater Resources in Coastal Areas of Pakistan for Sustainable Water Quality Management Using Joint Geophysical and Geochemical Approach: A Case Study
Authors: Hasan Muhammad , Shang Yanjun , Metwaly Mohamed , Jin Weijun , Khan Majid , Gao Qiang
Published: November 2020

Delineation of fresh/saline groundwater is essential for sustainable water quality management, especially in the coastal areas all around the globe. Seawater intrusion causes substantial degradation in quality of freshwater resources in the coastal areas. The main reason for saltwater intrusion is the changing environment in terms of sea-level rise, climate change, and over-extraction of freshwater resources to meet the growing demands. In this study, an integrated approach of geophysical and geochemical methods was used to assess saltwater intrusion in the coastal areas of Bela Plain, Pakistan. The inverted electrical resistivity computed from 50 vertical electrical sounding (VES) constrained the subsurface into five layers and two aquifers through 3D imaging, such as silty clay and sandy clay containing saline water, and sand, sandy gravel, and gravel containing freshwater. However, the narrow range of resistivity values shows an overlap of saline/fresh groundwater. Such ambiguity in the resistivity interpretation was removed by Dar-Zarrouk (D-Z) parameters. D-Z parameters, namely transverse unit resistance (Tr), longitudinal unit conductance (Sc), and longitudinal resistivity (ρL) estimated from VES, marked a clear distinction between saline and fresh aquifers with a wide range of values. The geochemical method was performed using 20 water samples for the main cations (K+, Ca2+ Na+, and Mg2+), anions (SO42−, HCO3−, Cl−, and NO3−), and other parameters (TDS, EC, and pH). Fresh/saline aquifers revealed by D-Z parameters are in good agreement with those delineated by physicochemical parameters and local hydrogeological conditions. This study delineates seawater intrusion of about 13–42 km from Sonmiani Bay in the Arabian Sea towards the inlands of Bela Plain. Therefore, it is expected that this investigation will be helpful in future planning for the management and exploitation of freshwater resources in the study area. Our study suggests that D-Z parameters can be used as the most inexpensive alternative to the traditional geotechnical and environmental tests for the demarcation of fresh/saline groundwater with a large coverage in any coastal or contaminated area under a homogeneous or heterogeneous setting.
Sustainable Design, Construction, Refurbishment and Restoration of Architecture: A Review
Authors: Pons-Valladares Oriol , Nikolic Jelena
Published: November 2020

Considering the serious challenges our planet is facing, the building environment and construction sector must minimize their high negative impacts and maximize their contribution to sustainability. Many alternatives could promote this change, but to effectively optimize our architecture, we must take the step of quantifying and qualifying the sustainability of our constructions by choosing the best assessment alternative in each case. Many assessment methodologies and tools exist and there have been numerous reviews of them. The main objective and novelty of this review is to present an updated critical overview of all the sustainability evaluation alternatives developed in research studies in the fields of architectural design, construction, refurbishment and restoration. To achieve this, the analysis follows a specific methodology based on recent similar reviews. The result is a database with 1242 eligible documents analyzed in this review and attached as supplementary material available for future studies. As a main conclusion, rating tools and life cycle methods were found to be the most commonly applied methodologies, while the most recent tendencies use combined methods and probabilistic scenarios. This review could be useful to move towards a more sustainable building environment.
A Sociological View on Designing a Sustainable Online Community for K–12 Teachers: A Systematic Review
Authors: Lee Dabae , Jung Jiyoon , Shin Suhkyung , Otternbreit-Leftwich Anne , Glazewski Krista
Published: November 2020

As a way to support teachers’ professional development activities and build communities of practice for teachers, education researchers and practitioners have put considerable effort into building an online learning community for K–12 teachers to create a venue to facilitate teachers’ joint knowledge construction. However, a substantial number of such online communities have failed due to lack of participation of members. Therefore, it is critical to understand how to design a sustainable community that fulfills members’ needs and elicits active participation of members. In this literature review, we adopted a sociological framework to investigate how to create a sustainable online community. This framework suggests that the sustainability of a community comes from individual members’ three types of commitments: instrumental, affective, and moral commitments. Such commitments are results of members’ cognitive, cathectic, and evaluative processes and lead to membership retainment, cohesive relationships, and socially regulated participation. Using this framework, we conducted a systematic literature review on online teacher community articles published from 1990 to 2018. Our findings provide insights on factors associated with teacher members’ instrumental, affective, and moral commitment to an online community. Based on these findings, we further provide design suggestions to build a sustainable community for teachers.
Characteristics and Influencing Factors of Green Finance Development in the Yangtze River Delta of China: Analysis Based on the Spatial Durbin Model
Authors: Xie Hualin , Ouyang Zhenyi , Choi Yongrok
Published: November 2020

Based on urban economic data in the Yangtze River Delta region of China from 2011 to 2017, this study empirically explores the characteristics of green finance development and its influencing factors through the establishment of a time fixed effects Durbin model. The empirical results are as follows: (1) The development of green finance in the Yangtze River Delta has a clear spatial cluster effect, and there are large regional differences. (2) The regional GDP, regional innovation level, and air quality are the most important influencing factors, and the degree of financial development and the optimization of the industrial structure are not significant. (3) Regional GDP is positively correlated with the development of green finance, and regional innovation level and air quality are negatively correlated with the development of green finance. (4) Regional GDP, regional innovation level, and air quality are associated with the development level of green finance mainly through direct effects. The degree of financial development and the optimization of industrial structure are associated with the development level of green finance mainly through spillover effects. The degree of financial development has a positive spillover effect; in contrast, the optimization of the industrial structure has a negative spillover effect. Finally, according to the conclusions, countermeasures and suggestions for improving the level of green finance development in the Yangtze River Delta are proposed.
Egyptian and Greek Water Cultures and Hydro-Technologies in Ancient Times
Authors: Ahmed Abdelkader T. , El Gohary Fatma , Tzanakakis Vasileios A. , Angelakis Andreas N.
Published: November 2020

Egyptian and Greek ancient civilizations prevailed in eastern Mediterranean since prehistoric times. The Egyptian civilization is thought to have been begun in about 3150 BC until 31 BC. For the ancient Greek civilization, it started in the period of Minoan (ca. 3200 BC) up to the ending of the Hellenistic era. There are various parallels and dissimilarities between both civilizations. They co-existed during a certain timeframe (from ca. 2000 to ca. 146 BC); however, they were in two different geographic areas. Both civilizations were massive traders, subsequently, they deeply influenced the regional civilizations which have developed in that region. Various scientific and technological principles were established by both civilizations through their long histories. Water management was one of these major technologies. Accordingly, they have significantly influenced the ancient world’s hydro-technologies. In this review, a comparison of water culture issues and hydro-structures was adopted through the extended history of the ancient Egyptians and Greeks. The specific objectives of the work are to study the parallel historical cultures and hydro-technologies, assessing similarities and differences, and to analyze their progress since primitive times. The tools adopted for the research include visits to historical aeras and museums, comments, consultations, correlation and exhibitions available in the cyberspace. Review results herein showed that dams and canals were constructed in ancient Egypt to manage the flood of the Nile river and develop irrigation systems from ca. 6000 BC. In the second millennium BC, Minoans managed the flow of the streams via two dams, to protect arable land from destruction after intense rainfall and to irrigate their farms. Additional results showed that ancient Egyptians and Greeks invented many devices for lifting water for plant irrigation such as the shadouf, sakia and tympanum and pumps, of which some were already in use in Mesopotamia for irrigating small plots. The ancient Egyptians were the first who discovered the principle and the basis of coagulation (after ca. 1500 BC). They used the alum for accelerating the settlement of the particles. Additionally, the ancient Greeks developed several advanced water treatment technologies since the prehistoric times. To sum up, the study captured many similarities between two civilizations in water technologies. In addition, it confirmed the sustainability and durability of several of those hydro-technologies since they are still in use up to now in many places.
Sustainability in Mineral Exploration—Exploring Less Invasive Technologies via Patent Analysis
Authors: Ruiz-Coupeau Stephane , Jürgens Björn , Keßelring Michaela , Herrero-Solana Victor
Published: November 2020

This paper presents a bibliometric study on patents and scientific publications related to airborne electromagnetic methods used as less invasive technologies in mineral exploration. A statistical analysis of the documents reveals the main players, technology trends, and collaboration patterns via bibliometric techniques. The article aims to analyse the gap between the model of sustainable less invasive innovations and the concrete implementation of the technology pull. Special attention is paid to the enablers of sustainable development and their presence in the technology landscape for less invasive exploration technologies.
Effect of a Sustainable Air Heat Pump System on Energy Efficiency, Housing Environment, and Productivity Traits in a Pig Farm
Authors: Jeong Myeong Gil , Rathnayake Dhanushka , Mun Hong Seok , Dilawar Muhammad Ammar , Park Kwang Woo , Lee Sang Ro , Yang Chul Ju
Published: November 2020

High electricity consumption, carbon dioxide (CO2), and elevated noxious gas emission in the global livestock sector have a negative influence on environmental sustainability. This study examined the effects of a heating system using an air heat pump (AHP) on the energy saving, housing environment, and productivity traits of pigs. During the experimental period of 16 weeks, the internal temperature was found to be higher (p < 0.05) in the AHP house than in the conventional house. Moreover, the average electricity consumption and CO2 emission decreased by approximately 40 kWh and 19.32 kg, respectively, in the AHP house compared to the house with the conventional heating system. The average NH3 and H2S emissions were significantly lower in the AHP house (p < 0.05) during the growth stages. The AHP and conventional heating systems did not have a significant influence (p > 0.05) on the average ultra-fine dust (PM2.5) and formaldehyde level fluctuations. Furthermore, both heating systems did not show a significant difference in the average growth performance of pigs (p > 0.05), but the weight gain tended to increase in the AHP house. In conclusion, the AHP system has great potential to reduce energy consumption, greenhouse gas (GHG) emissions, and noxious gas emissions by providing economic benefits and an eco-friendly renewable energy source.
A New Approach for Euler-Lagrange Orbits on Compact Manifolds with Boundary
Authors: Corona Dario , Giannoni Fabio
Published: November 2020

Consider a compact manifold with boundary, homeomorphic to the N-dimensional disk, and a Tonelli Lagrangian function defined on the tangent bundle. In this paper, we study the multiplicity problem for Euler-Lagrange orbits that satisfy the conormal boundary conditions and that lay on the boundary only in their extreme points. In particular, for suitable values of the energy function and under mild hypotheses, if the Tonelli Lagrangian is reversible then the minimal number of Euler-Lagrange orbits with prescribed energy that satisfies the conormal boundary conditions is N. If L is not reversible, then this number is two.
Symmetry/Asymmetry of the NHN Hydrogen Bond in Protonated 1,8-Bis(dimethylamino)naphthalene
Authors: Piękoś Patrycja , Jezierska Aneta , Panek Jarosław J. , Goremychkin Eugene A. , Pozharskii Alexander F. , Antonov Alexander S. , Tolstoy Peter M. , Filarowski Aleksander
Published: November 2020

Experimental and theoretical results are presented based on vibrational spectra and motional dynamics of 1,8-bis(dimethylamino)naphthalene (DMAN) and its protonated forms (DMANH+ and the DMANH+ HSO4− complex). The studies of these compounds have been performed in the gas phase and solid-state. Spectroscopic investigations were carried out by infrared spectroscopy (IR), Raman, and incoherent inelastic neutron scattering (IINS) experimental methods. Density functional theory (DFT) and Car–Parrinello molecular dynamics (CPMD) methods were applied to support our experimental findings. The fundamental investigations of hydrogen bridge vibrations were accomplished on the basis of isotopic substitutions (NH → ND). Special attention was paid to the bridged proton dynamics in the DMANH+ complex, which was found to be affected by interactions with the HSO4− anion.
Interaction Patterns for Staggered Assembly of Fibrils from Semiflexible Chains
Authors: Jongeling Arnoud , Svaneborg Carsten , Vries Renko de
Published: November 2020

The design of colloidal interactions to achieve target self-assembled structures has especially been done for compact objects such as spheres with isotropic interaction potentials, patchy spheres and other compact objects with patchy interactions. Inspired by the self-assembly of collagen-I fibrils and intermediate filaments, we here consider the design of interaction patterns on semiflexible chains that could drive their staggered assembly into regular (para)crystalline fibrils. We consider semiflexible chains composed of a finite number of types of interaction beads (uncharged hydrophilic, hydrophobic, positively charged and negatively charged) and optimize the sequence of these interaction beads with respect to the interaction energy of the semiflexible chains in a number of target-staggered crystalline packings. We find that structures with the lowest interaction energies, that form simple lattices, also have low values of L/D (where L is chain length and D is stagger). In the low interaction energy sequences, similar types of interaction beads cluster together to form stretches. Langevin Dynamics simulations confirm that semiflexible chains with optimal sequences self-assemble into the designed staggered (para)crystalline fibrils. We conclude that very simple interaction patterns should suffice to drive the assembly of long semiflexible chains into staggered (para)crystalline fibrils.
Overview of Pharmacokinetics and Liver Toxicities of Radix Polygoni Multiflori
Authors: Li Dan , Yang Mengbi , Zuo Zhong
Published: November 2020

Radix Polygoni Multiflori (RPM), a traditional Chinese medicine, has been used as a tonic and an anti-aging remedy for centuries. However, its safe and effective application in clinical practice could be hindered by its liver injury potential and lack of investigations on its hepatotoxicity mechanism. Our current review aims to provide a comprehensive overview and a critical assessment of the absorption, distribution, metabolism, excretion of RPM, and their relationships with its induced liver injury. Based on the well-reported intrinsic liver toxicity of emodin, one of the major components in RPM, it is concluded that its plasma and liver concentrations could attribute to RPM induced liver injury via metabolic enzymes alteration, hepatocyte apoptosis, bile acids homeostasis disruption, and inflammatory damage. Co-administered 2,3,5,4′-tetrahydroxystilbene-2-O-β-D-glucopyranoside in RPM and other drugs/herbs could further aggravate the hepatotoxicity of emodin via enhancing its absorption and inhibiting its metabolism. To ensure the safe clinical use of RPM, a better understanding of the toxicokinetics and effect of its co-occurring components or other co-administered drugs/herbs on the pharmacokinetics of emodin is warranted.
Chemical and Biological Study of Novel Aplysiatoxin Derivatives from the Marine Cyanobacterium Lyngbya sp.
Authors: Zhang Hui-Hui , Zhang Xin-Kai , Si Ran-Ran , Shen Si-Cheng , Liang Ting-Ting , Fan Ting-Ting , Chen Wei , Xu Lian-Hua , Han Bing-Nan
Published: November 2020

Since 1970s, aplysiatoxins (ATXs), a class of biologically active dermatoxins, were identified from the marine mollusk Stylocheilus longicauda, whilst further research indicated that ATXs were originally metabolized by cyanobacteria. So far, there have been 45 aplysiatoxin derivatives discovered from marine cyanobacteria with various geographies. Recently, we isolated two neo-debromoaplysiatoxins, neo-debromoaplysiatoxin G (1) and neo-debromoaplysiatoxin H (2) from the cyanobacterium Lyngbya sp. collected from the South China Sea. The freeze-dried cyanobacterium was extracted with liquid–liquid extraction of organic solvents, and then was subjected to multiple chromatographies to yield neo-debromoaplysiatoxin G (1) (3.6 mg) and neo-debromoaplysiatoxin H (2) (4.3 mg). They were elucidated with spectroscopic methods. Moreover, the brine shrimp toxicity of the aplysiatoxin derivatives representing differential structural classifications indicated that the debromoaplysiatoxin was the most toxic compound (half inhibitory concentration (IC50) value = 0.34 ± 0.036 µM). While neo-aplysiatoxins (neo-ATXs) did not exhibit apparent brine shrimp toxicity, but showed potent blocking action against potassium channel Kv1.5, likewise, compounds 1 and 2 with IC50 values of 1.79 ± 0.22 µM and 1.46 ± 0.14 µM, respectively. Therefore, much of the current knowledge suggests the ATXs with different structure modifications may modulate multiple cellular signaling processes in animal systems leading to the harmful effects on public health.