bluuebunny/crossref_metadata_2025 huggingface dataset:
Water Salinity as Potential Aid for Improving the Carbon Dioxide Replacement Process’ Effectiveness in Natural Gas Hydrate Reservoirs
Authors: Gambelli Alberto Maria , Castellani Beatrice , Nicolini Andrea , Rossi Federico
Published: October 2020

Natural gas hydrates represent a valid opportunity to counteract two of the most serious issues that are affecting humanity this century: climate change and the need for new energy sources, due to the fast and constant increase in the population worldwide. The energy that might be produced with methane contained in hydrates is greater than any amount of energy producible with known conventional energy sources; being widespread in all oceans, they would greatly reduce problems and conflicts associated with the monopoly of energy sources. The possibility of extracting methane and simultaneously performing the permanent storage of carbon dioxide makes hydrate an almost carbon-neutral energy source. The main topic of scientific research is to improve the recovery of technologies and guest species replacement strategies in order to make the use of gas hydrates economically advantageous. In the present paper, an experimental study on how salt can alter the formation process of both methane and carbon dioxide hydrate was carried out. The pressure–temperature conditions existing between the two respective equilibrium curves are directly proportional to the effectiveness of the replacement process and thus its feasibility. Eighteen formation tests were realized at three different salinity values: 0, 30 and 37 g/L. Results show that, as the salinity degree increases, the space between CO2 and CH4 formation curves grows. A further aspect highlighted by the tests is how the carbon dioxide formation process tends to assume a very similar trend in all experiments, while curves obtained during methane tests show a similar trend but with some significant differences. Moreover, this tendency became more pronounced with the increase in the salinity degree.
A Method of Bending Shrinkage Groove on Vortex Suppression and Energy Improvement for a Hydrofoil with Tip Gap
Authors: Hu Zanao , Huang Chuibing , Huang Zhenwei , Zhang Jinsong
Published: October 2020

Hydro energy is a kind of typical renewable energy, which can be converted by hydraulic machinery. However, tip leakage vortex (TLV) has a significant negative influence on the flow pattern and energy performance of hydraulic machinery. In this paper, a bending shrinkage groove (BSG) is proposed to suppress the TLV and improve the energy performance of a hydrofoil first, and then a parametric optimization design method is briefly introduced and applied to determine the optimal configuration of the groove. The main geometric parameters of the groove are selected as optimized variables and three different groove configurations are selected from the optimization result. Finally, the performance improvement of the hydrofoil with groove, the sensitivity analysis of the optimization variables, and the groove impacts on the TLV and flow patterns are investigated. The results demonstrate that the preferred groove reduces the non-dimensional Q criterion vortex isosurfaces area (Qarea = 2 × 107) by 5.13% and increases the lift drag ratio by 17.02%, comparing to the origin hydrofoil. Groove depth d and groove width w are proved to have more significant impacts on the hydrofoil energy performance. The TLV and flow patterns are greatly affected by the different BSG configurations, and the wider BSG contributed to reducing the area of TLV, at the cost of energy performance deterioration.
Real-Time Nanoplasmonic Sensor for IgG Monitoring in Bioproduction
Authors: Tran Thuy , Eskilson Olof , Mayer Florian , Gustavsson Robert , Selegård Robert , Lundström Ingemar , Mandenius Carl-Fredrik , Martinsson Erik , Aili Daniel
Published: October 2020

Real-time monitoring of product titers during process development and production of biotherapeutics facilitate implementation of quality-by-design principles and enable rapid bioprocess decision and optimization of the production process. Conventional analytical methods are generally performed offline/at-line and, therefore, are not capable of generating real-time data. In this study, a novel fiber optical nanoplasmonic sensor technology was explored for rapid IgG titer measurements. The sensor combines localized surface plasmon resonance transduction and robust single use Protein A-modified sensor chips, housed in a flexible flow cell, for specific IgG detection. The sensor requires small sample volumes (1–150 µL) and shows a reproducibility and sensitivity comparable to Protein G high performance liquid chromatography-ultraviolet (HPLC-UV). The dynamic range of the sensor system can be tuned by varying the sample volume, which enables quantification of IgG samples ranging from 0.0015 to 10 mg/mL, without need for sample dilution. The sensor shows limited interference from the sample matrix and negligible unspecific protein binding. IgG titers can be rapidly determined in samples from filtered unpurified Chinese hamster ovary (CHO) cell cultures and show good correlation with enzyme-linked immunosorbent assay (ELISA).
Mathematical Model of COVID-19 Transmission Dynamics in South Korea: The Impacts of Travel Restrictions, Social Distancing, and Early Detection
Authors: Kim Byul Nim , Kim Eunjung , Lee Sunmi , Oh Chunyoung
Published: October 2020

The novel coronavirus disease (COVID-19) poses a severe threat to public health officials all around the world. The early COVID-19 outbreak in South Korea displayed significant spatial heterogeneity. The number of confirmed cases increased rapidly in the Daegu and Gyeongbuk (epicenter), whereas the spread was much slower in the rest of Korea. A two-patch mathematical model with a mobility matrix is developed to capture this significant spatial heterogeneity of COVID-19 outbreaks from 18 February to 24 March 2020. The mobility matrix is taken from the movement data provided by the Korea Transport Institute (KOTI). Some of the essential patch-specific parameters are estimated through cumulative confirmed cases, including the transmission rates and the basic reproduction numbers (local and global). Our simulations show that travel restrictions between the epicenter and the rest of Korea effectively prevented massive outbreaks in the rest of Korea. Furthermore, we explore the effectiveness of several additional strategies for the mitigation and suppression of Covid-19 spread in Korea, such as implementing social distancing and early diagnostic interventions.
Denitrification Control in a Recirculating Aquaculture System—A Simulation Study
Authors: Almeida Pedro , Dewasme Laurent , Vande Wouwer Alain
Published: October 2020

The recirculating aquaculture system (RAS) is a land-based water treatment technology, which allows for farming aquatic organisms, such as fish, by reusing the water in the production (often less than 5%). This technology is based on the use of filters, either mechanical or biological, and can, in principle, be used for any species grown in aquaculture. Due to the low recirculation rate, ammonia accumulates in the system and must be converted into nitrate using nitrification reactors. Although less toxic for fish, nitrate can also be further reduced into nitrogen gas by the use of denitrification biofilters which may create several issues, such as incomplete denitrification, resulting in toxic substances, such as nitrite and nitric oxide, or a waste of carbon source in excess. Control of the added quantity of carbon source in the denitrification biofilter is then mandatory to keep nitrate/nitrite concentrations under toxic levels for fish and in accordance with local effluent regulations, and to reduce costs related to wasted organic carbon sources. This study therefore investigates the application of different control methodologies to a denitrification reactor in a RAS. To this end, a numerical simulator is built to predict the RAS behavior and to allow for the comparison of different control approaches, in the presence of changes in the operating conditions, such as fish density and biofilter removal efficiency. First, a classical proportional-integral-derivative (PID) controller was designed, based on an SIMC tuning method depending on the amount of ammonia excreted by fish. Then, linearizing and cascade controllers were considered as possible alternatives.
Warriors Who Do Not Kill in War: A Buddhist Interpretation of the Warrior’s Role in Relation to the Precept against Killing
Authors: Sugiki Tsunehiko
Published: October 2020

Buddhist scriptures in ancient South Asia include discourses that teach measures by which a warrior can face problems in confrontation with foreign armies and domestic rebel troops without resorting to killing them in battle. These moderate measures have not attracted much attention in previous studies on Buddhist statecraft and warfare. There are eleven kinds, and they can be organized according to the following three types: retreat from the role of warrior, resolution without pitched battle, and fighting in a pitched battle without killing. Similar ideas regarding measures for resolving military confrontations can be found in Indian Classics in the context of statecraft. The compilers of the Buddhist discourses collected ideas about similar measures from common sources and reshaped those borrowed ideas from the perspective of the Buddhist precept against killing. A warrior who implemented such measures did not acquire as much negative karmic potential as intentional killing produces. In premodern warrior societies, religion often provided the institutional basis for both a code of ethics and a soteriology for warriors, for whom fighting was in fulfillment of their social role. The compilation of discourses containing measures that do not involve killing represents an aspect of Buddhism’s function in ancient South Asia.
Nutrition in Reproductive Health: Nutritional Conditioning Factors during Pregnancy and Its Impact on Health
Authors: Martínez-Galiano Juan Miguel , Cano-Ibáñez Naomi , Hernández-Martínez Antonio , Delgado-Rodríguez Miguel
Published: October 2020

During the gestational period, women need to have optimal health to meet fetal requirements for growth and development. Nutrition is one of the most important factors that can ensure a mother`s health and also that of their offspring. The role of maternal diet, before and during pregnancy, has been associated with adverse birth outcomes and a worsening of maternal health. Medical conditions that are closely related to dietary intake and may affect women before or during pregnancy have also been associated with the appearance of pathology in a newborn. To date, several studies have been carried out in order to identify the role of diet as a factor associated with child physiological and psychological health, both in the short and long term. Educating mothers regarding the influence of maternal dietary intake during pregnancy on infants’ health could represent a simple but effective target for public health policies to improve pregnancy nutrition, and therefore help to avoid newborn diseases through the development.
Estimation of Organic Carbon in Anthropogenic Soil by VIS-NIR Spectroscopy: Effect of Variable Selection
Authors: Xu Lu , Hong Yongsheng , Wei Yu , Guo Long , Shi Tiezhu , Liu Yi , Jiang Qinghu , Fei Teng , Liu Yaolin , Mouazen Abdul M. , Chen Yiyun
Published: October 2020

Visible and near-infrared reflectance (VIS-NIR) spectroscopy is widely applied to estimate soil organic carbon (SOC). Intense and diverse human activities increase the heterogeneity in the relationships between SOC and VIS-NIR spectra in anthropogenic soil. This fact results in poor performance of SOC estimation models. To improve model accuracy and parsimony, we investigated the performance of two variable selection algorithms, namely competitive adaptive reweighted sampling (CARS) and random frog (RF), coupled with five spectral pretreatments. A total of 108 samples were collected from Jianghan Plain, China, with the SOC content and VIS-NIR spectra measured in the laboratory. Results showed that both CARS and RF coupled with partial least squares regression (PLSR) outperformed PLSR alone in terms of higher model accuracy and less spectral variables. It revealed that spectral variable selection could identify important spectral variables that account for the relationships between SOC and VIS-NIR spectra, thereby improving the accuracy and parsimony of PLSR models in anthropogenic soil. Our findings are of significant practical value to the SOC estimation in anthropogenic soil by VIS-NIR spectroscopy.
Mapping Ratoon Rice Planting Area in Central China Using Sentinel-2 Time Stacks and the Phenology-Based Algorithm
Authors: Liu Shishi , Chen Yuren , Ma Yintao , Kong Xiaoxuan , Zhang Xinyu , Zhang Dongying
Published: October 2020

Mapping rice cropping systems is important for grain yield prediction and food security assessments. Both single- and double-season rice are the dominant rice systems in central China. However, because of increasing labor shortages and high costs, there has been a gradual decline in double-season rice. Ratoon rice (RR) has been proposed as an alternative system that balances the productivity, cost, and labor requirements of rice cultivation. RR has been expanding in central China, encouraged by the improved cultivars, machinery, and favorable policies. However, to our knowledge, the distribution of RR has not been mapped with remote sensing techniques. This study developed a phenology-based algorithm to map RR at a 10 m resolution in Hubei Province, Central China, using dense time stacks of Sentinel-2 images (cloud cover <80%) in 2018. The key in differentiating RR from the other rice cropping systems is through the timing of maturity. We proposed to use two contrast vegetation indices to identify RR fields. The newly-developed yellowness index (YI) calculated with the reflectance of blue, green, and red bands was used to detect the ripening phase, and the enhanced vegetation index (EVI) was used to detect the green-up of the second-season crop to eliminate the misclassification caused by stubbles left in the field. The RR map demonstrated that RR was mainly distributed in the low alluvial plains of central and southern Hubei Province. The total planting area of RR in 2018 was 2225.4 km2, accounting for 10.03% of the total area of paddy rice fields. The overall accuracy of RR, non-RR rice fields, and non-rice land cover types was 0.76. The adjusted overall accuracy for RR and non-RR was 0.91, indicating that the proposed YI and the phenology-based algorithm could accurately identify RR fields from the paddy rice fields.
An Innovative Approach for Improving the Accuracy of Digital Elevation Models for Cultivated Land
Authors: Ma Yuyang , Liu Huanjun , Jiang Baiwen , Meng Linghua , Guan Haixiang , Xu Mengyuan , Cui Yang , Kong Fanchang , Yin Yue , Wang MengPei
Published: October 2020

The redistribution of solar radiation, temperature, soil moisture and heat by topography affects the physical and chemical properties of the soil and the spatial distribution characteristics of crop growth. Analyses of the relationship between topography and these variables may help to improve the accuracy of digital elevation models (DEMs). The purpose of correcting Shuttle Radar Topography Mission (SRTM) data is to obtain high-precision DEM data in cultivated land. A typical black soil area was studied. A high-precision reference DEM was generated from an unmanned aerial vehicle (UAV) and extensive measured ground elevation data. The normalized differential vegetation index (NDVI), perpendicular drought index (PDI) extracted from SPOT-6 remote sensing images and potential solar radiation (PSR) extracted from SRTM. The interactions between topography and NDVI, PDI, and PSR were analyzed. The NDVI, PDI and PSR in June, July, August and September of 2016 and the SRTM were used as independent variables, and the UAV DEM was used as the dependent variable. Linear stepwise regression (LSR) and a back-propagation neural network (BPNN) were used to establish an elevation prediction model. The results indicated that (1) The correlation between topography and NDVI, PSR, PDI was significant at 0.01 level. The PDI and PSR improved the spatial resolution of SRTM data and reduce the vertical error. (2) The BPNN (R21 = 0.98, root mean square error, RMSE1 = 0.54) yielded a higher SRTM accuracy than did the studied linear model (RMSE1 = 1.00, R21 = 0.90). (3) A series of significant improvements in the SRTM were observed when assessed with the reference DEMs for two different areas, with RMSE reductions of 91% (from 14.95 m to 1.23 m) and 93% (from 15.6 m to 0.94 m). The proposed method improved the accuracy of existing DEMs and could provide support for accurate farmland management.
Investigation of Daytime Total Electron Content Enhancements over the Asian-Australian Sector Observed from the Beidou Geostationary Satellite during 2016–2018
Authors: Jimoh Oluwaseyi , Lei Jiuhou , Huang Fuqing
Published: October 2020

This study focused on the investigation of daytime positive ionospheric disturbances and the recurrence of total electron content (TEC) enhancements. TEC data derived from the Beidou geostationary satellite over the Asian-Australian sector were used to study the occurrence of TEC enhancements during 2016–2018. The occurrence of TEC enhancements under quiet geomagnetic condition was analyzed. Furthermore, the occurrence of TEC enhancements during different geomagnetic storm phases was considered to address the question that relates to the recurrence of TEC enhancements during the recovery phase of geomagnetic storms. The seasonal variation of TEC enhancements displayed equinoctial and solstitial peaks at the middle and low latitudes respectively. Besides, there was no evident systematic latitudinal dependence in the occurrence of TEC enhancements, albeit at the equatorial station, nearly no TEC enhancement was observed under Kp < 3. Meanwhile, the occurrences during the main phases of the geomagnetic storms were significantly above the TEC enhancement baselines except at HKWS. The prominence of TEC enhancements during the main phase in comparison with the initial and recovery phases could be attributed to the effects of prompt penetration electric fields and equator-ward neutral winds. Moreover, the pattern of TEC enhancements during the storm recovery indicates the effects of chemical composition changes, winds, and the possible modulation from the lower atmospheric forcing.
National-Scale Variation and Propagation Characteristics of Meteorological, Agricultural, and Hydrological Droughts in China
Authors: Yao Ning , Zhao Huichao , Li Yi , Biswas Asim , Feng Hao , Liu Fenggui , Pulatov Bakhtiyor
Published: October 2020

The regional and national scales variation and propagation characteristics of different types of droughts are critical for improving drought resilience, while information is limited in China. The objective of this research was to investigate the evolution and propagation characteristics of three types of droughts using standardized indices at multi-timescales in different sub-regions of China. The indices included Standardized Precipitation/Soil Moisture/Runoff Index (SPI/SSI/SRI) using the optimal probability density function, representing meteorological, agricultural, and hydrological droughts based on precipitation, soil water storage, and baseflow-groundwater runoff, respectively. Wavelet analysis was used to reveal their periodical characteristics. Modified Mann-Kendall trend test was used to compare the trend among drought indices. Correlation coefficients between SPI and SSI/SRI were calculated to identify the time-lags of SPI with SSI and SRI. In general, droughts indicated by SPI agreed well with the historical drought events at different sub-regions. The main periods of SSI were closer to SPI than SRI, indicating stronger connections of agricultural drought with meteorological drought. A weaker connection between meteorological and agricultural/hydrological droughts at shorter timescales was observed in northwestern arid and semi-arid regions. The propagation from meteorological to agricultural or hydrological droughts were well denoted by the lagged time (months) from SPI to SSI or SRI at a timescale ranged from 0 (mostly located in south China) to 5 months (mostly located in northeastern China) for 1-, 3-, 6-, 12-, or 24-month timescale; this was a new finding for China. The methods of wavelet combining trend test and Pearson coefficient showed meaningful power for revealing the drought propagation characteristics and the obtained results can be a good reference for other regions of the world since this study compared different climate zones from arid to humid conditions. The study provides crucial information and guidance to develop drought management strategies at regional to national scale and their critical time of action.
The Use of SAR Offset Tracking for Detecting Sand Dune Movement in Sudan
Authors: Mahmoud Ahmed Mutasim Abdalla , Novellino Alessandro , Hussain Ekbal , Marsh Stuart , Psimoulis Panagiotis , Smith Martin
Published: October 2020

Sand movement is one of the main environmental hazards in Northern Sudan that threaten livelihood and rural communities. This paper investigates for the first time the use of the Synthetic Aperture Radar (SAR) offset tracking technique for detecting sand movement in Northern Sudan, and distinguishes the impact of the movement influencing factors: wind speed/direction, vegetation and topography. High-resolution images from the Sentinel-1 satellite were used for the generation of displacement maps. Three different dune fields with different characteristics were investigated for a study period between 4 June and 14 October 2017 (133 days). Dune field 1 is vegetated and near a built-up area, dune field 2 is in an open environment with sand dunes overlaying rocky substrate, and dune field 3 is located near mountains. The cumulative east displacement over the study period was 1.8 m, −1.1 m and 4.8 m for the three dune fields, respectively, while the cumulative north displacement was 0.7 m, 2.9 m and 4.2 m. Large movement is detected in the non-vegetated dune fields, with an average dune velocity of 0.18 m/d, while the vegetated dune field had a velocity of 0.09 m/d, which emphasizes the fact that vegetation is an effective stabiliser of dune movement. The pixel offset results showed a positive correlation between the wind speed/direction and the dune movement. In addition to vegetation, topography also played a major role in diverting the direction of the blown sand mainly near the edges to the mountains and the vegetation barriers. This technique showed high competency in monitoring the movement of sand dunes, in addition to identifying areas exposed to large sand drifting as a risk mapping technique.
Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application
Authors: Szewczak Kamil , Łoś Helena , Pudełko Rafał , Doroszewski Andrzej , Gluba Łukasz , Łukowski Mateusz , Rafalska-Przysucha Anna , Słomiński Jan , Usowicz Bogusław
Published: October 2020

The current Polish Agricultural Drought Monitoring System (ADMS) adopted Climatic Water Balance (CWB) as the main indicator of crop losses caused by drought conditions. All meteorological data needed for CWB assessment are provided by the ground meteorological stations network. In 2018, the network consisted of 665 stations, among which in only 58 stations full weather parameters were registered. Therefore, only these stations offered a possibility to estimate the exact values of potential evapotranspiration, which is a component of the CWB algorithm. This limitation affects the quality of CWB raster maps, interpolated on the basis of the meteorological stations network for the entire country. However, the interpolation process itself may introduce errors; therefore, the adaptation of satellite data (that are spatially continuous) should be taken into account, even if the lack of data due to cloudiness remains a serious problem. In this paper, we involved the remote sensing data from MODIS instrument and considered the ability to integrate those data with values determined by using ground measurements. The paper presents results of comparisons for the CWB index assessed using ground station data and those obtained from potential evapotranspiration as the product from Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing instrument. The comparisons of results were performed for specific points (locations of ground stations) and were expressed by differences in means values. Analysis of Pearson’s correlation coefficient (r), Mann–Kendal trend test (Z-index), mean absolute error (MAE) and root mean square error (RMSE) for ten years’ series were evaluated and are presented. In addition, the basic spatial interpretation of results has been proposed. The correlation test revealed the r coefficient in the range from 0.06 to 0.68. The results show good trend agreement in time between two types of CWB with constantly higher values of this index, which is estimated using ground measurement data. In results for 34 (from 43 analyzed) stations the Mann–Kendal test provide the consistent trend, and only nine trends were inconsistent. Analyses revealed that the disagreement between the two considered indices (determined in different ways) increased significantly in the warmer period with a significant break point between R7 and R8 that falls at the end of May for each examined year. The value of MAE varied from 80 mm to 135 mm.
Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks
Authors: Gul Omer Melih , Erkmen Aydan Muserref
Published: October 2020

In this work, our motivation focuses on an energy-efficient data collection problem by a mobile sink, an unmanned aerial vehicle (UAV) with limited battery capacity, in a robot network divided into several robot clusters. In each cluster, a cluster head (CH) robot allocates tasks to the remaining robots and collects data from them. Our contribution is to minimize the UAV total energy consumption coupled to minimum cost data collection from CH robots by visiting optimally a portion of the CH robots. The UAV decides the subset of CH robots to visit by considering not only the locations of all CH robots but also its battery capacity. If the UAV cannot visit all CH robots, then the CH robots not visited by the UAV transmit their data to another CH robot to forward it. The decision of transmission paths of transmitting robots is included in the cost optimization. Our contribution passes beyond the existing paradigms in the literature by considering the constant battery capacity for the UAV. We derive the optimal approach analytically for this problem. For various numbers of clusters, the performance of our strategy is compared with the approach in the close literature in terms of total energy consumed by CH robots, which affects network lifetime. Numerical results demonstrate that our strategy outperforms the approach in the close literature.
A Wireless Magnetic Resonance Device for Optogenetic Applications in an Animal Model
Authors: Tsai Arthur C. , Huang Andrew Chih Wei , Yu Ying Hao , Kuo Chii-Shyang , Hsu Chih-Chan , Lim Yeou San , Shyu Bai Chuang
Published: October 2020

The currents of optical stimulation devices with tethered or untethered systems have various disadvantages, including optical fiber breakage, disrupted animal movements, heavy batteries carried on heads, and high-frequency electromagnetic impacts. Our novel wireless remote control was developed to address these issues. The novel wireless device uses a magnetic resonance technique to modify the deficits of the conventional magnetic induction or radio-frequency power sources. The present device emits a strong and steady electromagnetic power. It is cheaper than previous versions, and the receiver coil on its head is very light (≦ 1 g). For the present wireless remote-controlled device, the electromagnetic field’s range (i.e., +5 cm and −5 cm of the outside coil) is larger than the range for the magnetic induction and radio-frequency power sources. The present device controls animals’ behavior by the electromagnetic field’s effective range via photostimulation. The novel wireless remote-controlled device with a magnetic resonance technique can be applied in many behavioral tasks in mice and rats. To avoid the adverse effects of high radio frequency and to extend the electromagnetic field’s range, this novel technique serves as a helpful tool to modulate the neuronal activity of target neurons in specific brain areas for optogenetic experiments.
Silicon Photonic Polarization Multiplexing Sensor with Both Large Range and High Resolution
Authors: Yin Shaojie , Wang Xiaoyan , Wang Zhibin , Xiao Sanshui , Guan Xiaowei
Published: October 2020

A silicon photonic polarization multiplexing (PM) sensor featuring both a large range and a high resolution is proposed and experimentally demonstrated. The sensor includes a Fabry–Pérot (FP) resonator and a microring resonator (MRR) functioning as the sensing parts. With PM technology, the FP resonator only works on the transverse-electric mode while the MRR only on the transverse-magnetic mode. Thus, the proposed sensor can simultaneously achieve a large range with a short FP resonator and a high resolution with a high-Q MRR. Measured results show a range of 113 °C and a resolution of 0.06 °C for temperature sensing, and a range of 0.58 RIU (refractive index unit) with the resolution of 0.002 RIU for analyte refractive index sensing.
Functionalized TiO2 Nanotube-Based Electrochemical Biosensor for Rapid Detection of SARS-CoV-2
Authors: Vadlamani Bhaskar S. , Uppal Timsy , Verma Subhash C. , Misra Mano
Published: October 2020

The COronaVIrus Disease (COVID-19) is a newly emerging viral disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Rapid increase in the number of COVID-19 cases worldwide led the WHO to declare a pandemic within a few months after the first case of infection. Due to the lack of a prophylactic measure to control the virus infection and spread, early diagnosis and quarantining of infected as well as the asymptomatic individuals are necessary for the containment of this pandemic. However, the current methods for SARS-CoV-2 diagnosis are expensive and time consuming, although some promising and inexpensive technologies are becoming available for emergency use. In this work, we report the synthesis of a cheap, yet highly sensitive, cobalt-functionalized TiO2 nanotubes (Co-TNTs)-based electrochemical sensor for rapid detection of SARS-CoV-2 through sensing the spike (receptor binding domain (RBD)) present on the surface of the virus. A simple, low-cost, and one-step electrochemical anodization route was used for synthesizing TNTs, followed by an incipient wetting method for cobalt functionalization of the TNTs platform, which was connected to a potentiostat for data collection. This sensor specifically detected the S-RBD protein of SARS-CoV-2 even at very low concentration (range of 14 to 1400 nM (nano molar)). Additionally, our sensor showed a linear response in the detection of viral protein over the concentration range. Thus, our Co-TNT sensor is highly effective in detecting SARS-CoV-2 S-RBD protein in approximately 30 s, which can be explored for developing a point of care diagnostics for rapid detection of SARS-CoV-2 in nasal secretions and saliva samples.
Low Frequency Vibration Visual Monitoring System Based on Multi-Modal 3DCNN-ConvLSTM
Authors: Alimasi Alimina , Liu Hongchen , Lyu Chengang
Published: October 2020

Low frequency vibration monitoring has significant implications on environmental safety and engineering practices. Vibration expressed by visual information should contain sufficient spatial information. RGB-D camera could record diverse spatial information of vibration in frame images. Deep learning can adaptively transform frame images into deep abstract features through nonlinear mapping, which is an effective method to improve the intelligence of vibration monitoring. In this paper, a multi-modal low frequency visual vibration monitoring system based on Kinect v2 and 3DCNN-ConvLSTM is proposed. Microsoft Kinect v2 collects RGB and depth video information of vibrating objects in unstable ambient light. The 3DCNN-ConvLSTM architecture can effectively learn the spatial-temporal characteristics of muti-frequency vibration. The short-term spatiotemporal feature of the collected vibration information is learned through 3D convolution networks and the long-term spatiotemporal feature is learned through convolutional LSTM. Multi-modal fusion of RGB and depth mode is used to further improve the monitoring accuracy to 93% in the low frequency vibration range of 0–10 Hz. The results show that the system can monitor low frequency vibration and meet the basic measurement requirements.
Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm
Authors: Hao Kun , Zhao Jiale , Yu Kaicheng , Li Cheng , Wang Chuanqi
Published: October 2020

In the field of robot path planning, aiming at the problems of the standard genetic algorithm, such as premature maturity, low convergence path quality, poor population diversity, and difficulty in breaking the local optimal solution, this paper proposes a multi-population migration genetic algorithm. The multi-population migration genetic algorithm randomly divides a large population into several small with an identical population number. The migration mechanism among the populations is used to replace the screening mechanism of the selection operator. Operations such as the crossover operator and the mutation operator also are improved. Simulation results show that the multi-population migration genetic algorithm (MPMGA) is not only suitable for simulation maps of various scales and various obstacle distributions, but also has superior performance and effectively solves the problems of the standard genetic algorithm.
Fuzzy Controller Applied to a Remote Energy Harvesting Emulation Platform
Authors: Camboim Marcelo Miranda , Villanueva Juan Moises Maurício , de Souza Cleonilson Protasio
Published: October 2020

In the last decades, a lot of effort has been made in order to improve the use of environmentally friendly and renewable energy sources. In a context of small energy usage, energy harvesting takes place and thermal energy sources are one of its main energy sources because there are several unused heat sources available in the environment that may be used as renewable energy sources. To rapidly evaluate the energy potential of such thermal sources is a hard task, therefore, a way to perform this is welcome. In this work, a thermal pattern emulation system to evaluate potential thermal source in a easy way is proposed. The main characteristics of the proposed system is that it is online and remote, that is, while the thermal-source-under-test is being measured, the system is emulating it and evaluating the generated energy remotely. The main contribution of this work was to replace the conventional Proportional Integral Derivative (PID) controller to a Fuzzy-Proportional Integral (PI) controller. In order to compare both controllers, three tests were carried out, namely: (a) step response, (b) perturbation test, (c) thermal emulation of the thermal pattern obtained from a potential thermal source: tree trucks. Experimental results show that the Fuzzy-PI controller was faster than the PID, achieving a setting time 41.26% faster, and also was more efficient with a maximum error 53% smaller than the PID.
Signal Processing for Parametric Acoustic Sources Applied to Underwater Communication
Authors: Campo-Valera María , Felis-Enguix Ivan , Villó-Pérez Isidro
Published: October 2020

For years, in the field of underwater acoustics, a line of research with special relevance for applications of environmental monitoring and maritime security has been developed that explores the possibilities of non-linear phenomena of sound propagation, especially referring to the so-called parametric effect or self-modulation. This article shows the results of using a new modulation technique based on sine-sweep signals, compared to classical modulations (FSK and PSK). For each of these modulations, a series of 16-bit strings of information with different frequencies and durations have been performed, with the same 200 kHz carrier wave. All of them have been tested in the Hydroacoustic Laboratory of the CTN and, through the application of cross-correlation processing, the limitations and improvements of this novel processing technique have been evaluated. This allows reaching better limits in discrimination of bits and signal-to-noise ratio used in underwater parametric acoustic communications.
Feature Selection Model based on EEG Signals for Assessing the Cognitive Workload in Drivers
Authors: Becerra-Sánchez Patricia , Reyes-Munoz Angelica , Guerrero-Ibañez Antonio
Published: October 2020

In recent years, research has focused on generating mechanisms to assess the levels of subjects’ cognitive workload when performing various activities that demand high concentration levels, such as driving a vehicle. These mechanisms have implemented several tools for analyzing the cognitive workload, and electroencephalographic (EEG) signals have been most frequently used due to their high precision. However, one of the main challenges in implementing the EEG signals is finding appropriate information for identifying cognitive states. Here, we present a new feature selection model for pattern recognition using information from EEG signals based on machine learning techniques called GALoRIS. GALoRIS combines Genetic Algorithms and Logistic Regression to create a new fitness function that identifies and selects the critical EEG features that contribute to recognizing high and low cognitive workloads and structures a new dataset capable of optimizing the model’s predictive process. We found that GALoRIS identifies data related to high and low cognitive workloads of subjects while driving a vehicle using information extracted from multiple EEG signals, reducing the original dataset by more than 50% and maximizing the model’s predictive capacity, achieving a precision rate greater than 90%.
Power-Saving Design of Radio Frequency Identification Sensor Networks in Bus Seatbelt Monitoring Systems
Authors: Sun Sitong , Yang Wen , Wang Wilson
Published: October 2020

Seatbelt state monitoring is important in intercity buses for passenger safety. This paper discusses the issues and challenges in power-saving design of radio frequency identification (RFID) sensor networks in bus seatbelt monitoring. A new design approach is proposed in this work for low-power layout and parameter setting in RFID sensor nodes in hardware and software design. A one-to-many pairing registration method is suggested between the concentrator and the seat nodes. Unlike using extra computer software to write seat identification (ID) into an integrated circuit (IC) card, the node ID in this project can be stored into the concentrator directly, which can reduce intermediate operations and reduce development costs. The effectiveness of the proposed low-power design approach is verified by some experimental tests.
Microfluidic Production of Autofluorescent BSA Hydrogel Microspheres and Their Sequential Trapping for Fluorescence-Based On-Chip Permanganate Sensing
Authors: Liu Linbo , Li Guangming , Xiang Nan , Huang Xing , Shiba Kota
Published: October 2020

Microfabrication technologies have extensively advanced over the past decades, realizing a variety of well-designed compact devices for material synthesis, separation, analysis, monitoring, sensing, and so on. The performance of such devices has been undoubtedly improved, while it is still challenging to build up a platform by rationally combining multiple processes toward practical demands which become more diverse and complicated. Here, we present a simple and effective microfluidic system to produce and immobilize a well-defined functional material for on-chip permanganate (MnO4−) sensing. A droplet-based microfluidic approach that can continuously produce monodispersed droplets in a water-in-oil system is employed to prepare highly uniform microspheres (average size: 102 μm, coefficient of variation: 3.7%) composed of bovine serum albumin (BSA) hydrogel with autofluorescence properties in the presence of glutaraldehyde (GA). Each BSA hydrogel microsphere is subsequently immobilized in a microchannel with a hydrodynamic trapping structure to serve as an independent fluorescence unit. Various anions such as Cl−, NO3−, PO43−, Br−, BrO3−, ClO4−, SCN−, HCO3−, and MnO4− are individually flowed into the microchannel, resulting in significant fluorescence quenching only in the case of MnO4−. Linear correlation is confirmed at an MnO4− concentration from 20 to 80 μM, and a limit of detection is estimated to be 1.7 μM. Furthermore, we demonstrate the simultaneous immobilization of two kinds of different microspheres in parallel microchannels, pure BSA hydrogel microspheres and BSA hydrogel microspheres containing rhodamine B molecules, making it possible to acquire two fluorescence signals (green and yellow). The present microfluidics-based combined approach will be useful to record a fingerprint of complicated samples for sensing/identification purposes by flexibly designing the size and composition of the BSA hydrogel microspheres, immobilizing them in a desired manner and obtaining a specific pattern.
Chick Embryo Growth Modeling Using Near-Infrared Sensor and Non-Linear Least Square Fitting of Egg Opacity Values
Authors: Khaliduzzaman Alin , Kashimori Ayuko , Suzuki Tetsuhito , Ogawa Yuichi , Kondo Naoshi
Published: October 2020

Non-destructive monitoring of chick embryonic growth can provide vital management insights for poultry farmers and other stakeholders. Although non-destructive studies on fertility, hatching time and gender have been conducted recently, there has been no available method for embryonic growth observation, especially during the second half of incubation. Therefore, this work investigated the feasibility of using near-infrared (NIR) sensor-based egg opacity values—the amount of light lost when passing through the egg—for indirectly observing embryo growth during incubation. ROSS 308 eggs were selected based on size, mass and shell color for this experiment. To estimate the embryo size precisely, we fit various mathematical growth functions during incubation, based on the opacity value of incubated eggs. Although all the growth models tested performed similarly in fitting the data, the exponential and power functions had better performances in terms of co-efficient of determination (0.991 and 0.994 respectively) and RMSE to explain embryo growth during incubation. From these results, we conclude that the modeling paradigm adopted provides a simple tool to non-invasively investigate embryo growth. These models could be applied to resolving developmental biology, embryonic pathology, industrial and animal welfare issues in the near future.
Perceptions on Smart Gas Meters in Smart Cities for Reducing the Carbon Footprint
Authors: Hurst William , Tekinerdogan Bedir , Kotze Ben
Published: October 2020

Carbon emission is a prominent issue, and smart urban solutions have the technological capabilities to implement change. The technologies for creating smart energy systems already exist, some of which are currently under wide deployment globally. By investing in energy efficiency solutions (such as the smart meter), research shows that the end-user is able to not only save money, but also reduce their household’s carbon footprint. Therefore, in this paper, the focus is on the end-user, and adopting a quantitative analysis of the perception of 1365 homes concerning the smart gas meter installation. The focus is on linking end-user attributes (age, education, social class and employment status) with their opinion on reducing energy, saving money, changing home behaviour and lowering carbon emissions. The results show that there is a statistical significance between certain attributes of end-users and their consideration of smart meters for making beneficial changes. In particular, the investigation demonstrates that the employment status, age and social class of the homeowner have statistical significance on the end-users’ variance; particularly when interested in reducing their bill and changing their behaviour around the home.
Use of Social Media to Seek and Provide Help in Hurricanes Florence and Michael
Authors: DiCarlo Morgan Faye , Berglund Emily Zechman
Published: October 2020

During hazardous events, communities can use existing social media networks to share information in real time and initiate a local disaster response. This research conducted a web-based survey to explore two behaviors around the use of social media during hurricanes: seeking help and responding to help requests. Through the survey, we sampled 434 individuals across several counties affected by 2018 hurricanes Florence and Michael, which were both designated by the National Oceanic and Atmospheric Administration as billion-dollar weather disasters. The survey questions collected data about demographics, social media use habits, perceptions towards social media, hurricane damages, and actions taken during a hurricane to seek and provide help. The Theory of Planned Behavior (TPB) was used to conceptualize and frame parameters that affect intentions and behaviors regarding the use of social media during hurricanes to seek and provide help. Survey responses are analyzed using statistical regression to evaluate hypotheses about the influence of factors on seeking help and responding to help requests. Regression analyses indicate that attitude and perceived behavioral control predict intention to access social media during a hurricane, partially supporting the TPB. Intention and experiencing urgent damages predict help-seeking behaviors using social media. Posting frequency to social media under normal conditions and the number of help requests seen during the event predict help-responding behaviors. Linear regression equations governing intention and behavior were parameterized using survey results. The factors underlying social media behavior during hurricanes as identified in this research provide insight for understanding how smart information technologies, such as personal devices and social media networks, support community self-sufficiency and hazard resilience.
A Framework of Smart-Home Service for Elderly’s Biophilic Experience
Authors: Lee Eun Ji , Park Sung Jun
Published: October 2020

Smart-home technology and related services can reinforce a person’s experiential nature, promoting sustainable living among the elderly. It is crucial in the housing industry that support “Aging in Place”, contributing to the contact, control, and simulation of nature at home as well as the creation of a high-quality living space instead of mechanical achievement. Further, biophilic experience, the strengthening of inherent human propensity to nature for optimal health and well-being, supports the elderly’s physical, mental, and sociological health. However, despite the continuing emphasis on the benefits of residential nature experiences for the elderly, the application of smart-home technology and services is insufficient. This study presents a theoretical basis for combining biophilia and smart-home technology, providing a framework for smart-home services to ensure elderly residents can have biophilic experiences. In this study, smart-home components and related studies that can support the biophilic experience and the corresponding technology are analyzed. The results suggest the type and content of smart-home service for ensuring a biophilic experience, while also indicating the configuration of supportive input and output devices according to the service framework. Moreover, we recommend the interaction characteristics of smart-home devices from the perspective of residents, space, efficient service provision, and physical application. This paper broadens our understanding of the sustainable, residential-environment nature experience and informs the expansion of the aged-friendly smart-home industry, contributing to smart-home services trends and development.