bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of L-Band SAOCOM InSAR Coherence and Its Comparison with C-Band: A Case Study over Managed Forests in Argentina
Authors: Seppi Santiago Ariel , López-Martinez Carlos , Joseau Marisa Jacqueline
Published: November 2022

The objective of this work is to analyze the behavior of short temporal baseline interferometric coherence in forested areas for L-band spaceborne SAR data. Hence, an exploratory assessment of the impacts of temporal and spatial baselines on coherence, with emphasis on how these effects vary between SAOCOM-1 L-band and Sentinel-1 C-band data is presented. The interferometric coherence is analyzed according to different imaging parameters. In the case of SAOCOM-1, the impacts of the variation of the incidence angle and the ascending and descending orbits over forested areas are also assessed. Finally, short-term 8-day interferometric coherence maps derived from SAOCOM-1 are especially addressed, since this is the first L-band spaceborne mission that allows us to acquire SAR images with such a short temporal span. The analysis is reported over two forest-production areas in Argentina, one of which is part of the most important region in terms of forest plantations at the national level. In the case of SAOCOM, interferometric configurations are characterized by a lack of control on the spatial baseline, so a zero-baseline orbital tube cannot be guaranteed. Nevertheless, this spatial baseline variability is crucial to exploit volume decorrelation for forest monitoring. The results from this exploratory analysis demonstrates that SAOCOM-1 short temporal baseline interferograms, 8 to 16 days, must be considered in order to mitigate temporal decorrelation effects and to be able to experiment with different spatial baseline configurations, in order to allow appropriate forest monitoring.
Feature Engineering of Geohazard Susceptibility Analysis Based on the Random Forest Algorithm: Taking Tianshui City, Gansu Province, as an Example
Authors: Ling Xiao , Zhu Yueqin , Ming Dongping , Chen Yangyang , Zhang Liang , Du Tongyao
Published: November 2022

In this paper, Feature Engineering (FE) was applied to Landslide Susceptibility Mapping (LSM), while the most suitable conditioning feature dataset and analysis method were tested and analyzed. Tianshui city was taken as the study area, three types of geohazard (collapse, landslide, and unstable slopes) were used, while a total of twenty-three conditioning features were generated; two dimensionless methods (normalization and standardization) were tested afterward. Four Random-Forest-based (RF-based) feature selection methods using different indicators (Gini Impurity, GI; Out of Bag Accuracy, OOBA) were proposed and tested separately. The LSMs of four models were carried out under the guidance results of FE, namely Classification and Regression Tree (CART), Random Forest (RF), Logistic Regression (LR), and Support Vector Machine for Classification (SVC). For feature enhancement, standardization had significant advantages over normalization. All RF-based methods were proven effective, lifting the AUC by 0.01~0.02. The RF model achieved the highest LSM accuracies, respectively, 0.949 (landslide), 0.957, and 0.949 (unstable slopes), improved by 0.008 (landslide), 0.005 (collapse), and 0.013 (unstable slopes). This proved that the FE helped to improve LSM and can help to decide the dominant conditioning factors for regional geohazards.
Development of Snow Cover Frequency Maps from MODIS Snow Cover Products
Authors: Riggs George , Hall Dorothy , Vuyovich Carrie , DiGirolamo Nicolo
Published: November 2022

With a decade scale record of global snow cover extent (SCE) at up to 500 m from the Moderate-resolution Imaging Spectroradiometer (MODIS), the dynamics of snow cover can be mapped at local to global scales. We developed daily snow cover frequency maps from 2001–2020 using a ~5 km resolution MODIS snow cover map. For each day of the year the maps show the frequency of snow cover for the 20-year period on a per-grid cell basis. Following on from other work to develop snow frequency maps using MODIS snow cover products, we include spatial filtering to reduce errors caused by ‘false snow’ that occurs primarily due to cloud-snow confusion. On our snow frequency maps, there were no regions or time periods with a noticeable absence of snow where snow was expected. In one example, the MODIS derived frequency of snow cover on 25 December compares well with NOAA’s historical probability of snow on the same day. Though the MODIS derived snow frequency and NOAA probabilities are computed from very different data sources, they compare well. Though this preliminary research is promising, much future evaluation is needed.
Tectonism of Late Noachian Mars: Surface Signatures from the Southern Highlands
Authors: Ruj Trishit , Komatsu Goro , Schmidt Gene , Karunatillake Suniti , Kawai Kenji
Published: November 2022

Upwelling mantle plumes often instigate extensional stress within the continental crust of Earth. When stress exceeds crustal strength, extensional structures develop, reducing the effective stress and trigger magmatic processes at the crust–mantle boundary. However, such processes and their relationship to the formation of many surface structures remain poorly characterized on Mars. We identified a series of extensional structures in the southern highlands of Mars which collectively resemble continental rift zones on Earth. We further characterized these extensional structures and their surrounding region (area of ~1.8 M km2) by determining the surface mineralogy and bulk regional geochemistry of the terrain. In turn, this constrains their formation and yields a framework for their comparison with extensional structures on Earth. These terrains are notable for olivine and high-Ca pyroxene with a high abundance of potassium and calcium akin to alkali basalts. In the case of Mars, this Earth-like proto-plate tectonic scenario may be related to the plume-induced crustal stretching and considering their distribution and temporal relationship with the Hellas basin, we conclude that the plume is impact-induced. Overall, the findings of this work support the presence of mantle plume activity in the Noachian, as suggested by thermal evolution models of Mars.
Real-Time Phaseless Microwave Frequency-Diverse Imaging with Deep Prior Generative Neural Network
Authors: Wu Zhenhua , Zhao Fafa , Zhang Man , Qian Jun , Yang Lixia
Published: November 2022

The millimeter-wave frequency-diverse imaging regime has recently received considerable attention in both the security screening and synthetic aperture radar imaging literature. Considering that the minor systematic errors and alignment errors could still produce heavily corrupted images, these complex-based imaging reconstructions rely heavily on the precise measurement of both phase and amplitude of radiation field patterns and echo signals. In the literature, it is shown that by leveraging phase-retrieval techniques, salient reconstruction images can still be acquired, even in the presence of significant phase errors, which could ease the phase error calibration pressure to a large extent in practical imaging applications. In this paper, in the regime of phaseless frequency-diverse imaging, with the powerful feature inference and generation power of unsupervised generative models, an end-to-end deep prior generative neural network is designed to achieve near real-time imaging. The harsh imaging reconstruction with both the high radiation mode correlations and extremely low scene compression sampling ratio, which are extremely troublesome to tackle for generally applied matched-filter and compressed sensing approach in the current frequency-diverse imaging literature, can still be preferably handled with our reconstruction network. The well-trained reconstruction network is constituted by prior inference and deep generative modules with excellent generative capabilities and significant prior inference abilities. Using simulation experiments with radiation field data, we verify that the integration of phase-free frequency-change imaging with deep learning networks can effectively improve reconstruction capabilities and improve robustness to systematic phase errors. Compared with existing imaging methods, our imaging method has high imaging performance and can even reconstruct targets under low compression ratio conditions, which is somewhat competitive with current state-of-the-art algorithms. Moreover, we find that the proposed method has good anti-noise and stability.
Correction: Martinez et al. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. Remote Sens. 2020, 12, 4156
Authors: Martinez Elodie , Brini Anouar , Gorgues Thomas , Drumetz Lucas , Roussillon Joana , Tandeo Pierre , Maze Guillaume , Fablet Ronan
Published: November 2022

The authors wish to make the following corrections to the paper [...]
The Supply–Demand Budgets of Ecosystem Service Response to Urbanization: Insights from Urban–Rural Gradient and Major Function-Oriented Areas
Authors: Li Zuzheng , Hu Baoan , Ren Yufei
Published: November 2022

The differentiation in the urbanization level’s impact on the supply–demand budgets of ecosystem services (ESs) from the perspective of the major function-oriented areas is of great significance for formulating sustainable development strategies at the regional level. This study first constructed the research framework of the supply, demand, and supply–demand ratios (ESDRs) of ESs responding to urbanization from the perspective of major function-oriented zoning, and then took the rapidly urbanized Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA) of China as a case from 2000 to 2020. The relationships between three urbanization indicators, gross domestic production (GDP), population density (PD), and artificial land proportion (ALP), as well as ESDRs of ESs were investigated using Pearson Correlation analysis across three major functional areas. The sensitivity of ESDRs to urbanization was further evaluated using the Random Forest model. The results showed that the supply of carbon fixation, water provision, and food provision increased, whereas their demands far exceeded their supplies, resulting in an increased imbalance between ES supply and demand. With the exception of soil conservation, significantly negative relationships were observed between urbanization indicators and the other three ES supply–demand budgets. The ESDRs of water provision, carbon fixation, and food provision were the most sensitive variables that depended on the population density (PD) in almost all functional areas, whereas the ESDR of carbon fixation exhibited the highest sensitivity to GDP in developed urban areas and rural areas within the preferred development area (PDA) and key development area (KDA). This study could provide comprehensive information for decision making and ES management in different functional areas.
Part Affinity Fields and CoordConv for Detecting Landmarks of Lumbar Vertebrae and Sacrum in X-ray Images
Authors: An Chang-Hyeon , Lee Jeong-Sik , Jang Jun-Su , Choi Hyun-Chul
Published: November 2022

With the prevalence of degenerative diseases due to the increase in the aging population, we have encountered many spine-related disorders. Since the spine is a crucial part of the body, fast and accurate diagnosis is critically important. Generally, clinicians use X-ray images to diagnose the spine, but X-ray images are commonly occluded by the shadows of some bones, making it hard to identify the whole spine. Therefore, recently, various deep-learning-based spinal X-ray image analysis approaches have been proposed to help diagnose the spine. However, these approaches did not consider the characteristics of frequent occlusion in the X-ray image and the properties of the vertebra shape. Therefore, based on the X-ray image properties and vertebra shape, we present a novel landmark detection network specialized in lumbar X-ray images. The proposed network consists of two stages: The first step detects the centers of the lumbar vertebrae and the upper end plate of the first sacral vertebra (S1), and the second step detects the four corner points of each lumbar vertebra and two corner points of S1 from the image obtained in the first step. We used random spine cutout augmentation in the first step to robustify the network against the commonly obscured X-ray images. Furthermore, in the second step, we used CoordConv to make the network recognize the location distribution of landmarks and part affinity fields to understand the morphological features of the vertebrae, resulting in more accurate landmark detection. The proposed network was evaluated using 304 X-ray images, and it achieved 98.02% accuracy in center detection and 8.34% relative distance error in corner detection. This indicates that our network can detect spinal landmarks reliably enough to support radiologists in analyzing the lumbar X-ray images.
DOA Estimation for Massive MIMO Systems with Unknown Mutual Coupling Based on Block Sparse Bayesian Learning
Authors: Liu Yang , Dong Na , Zhang Xiaohui , Zhao Xin , Zhang Yinghui , Qiu Tianshuang
Published: November 2022

Obtaining accurate angle parameters using direction-of-arrival (DOA) estimation algorithms is crucial for acquiring channel state information (CSI) in massive multiple-input multiple-output (MIMO) systems. However, the performance of the existing algorithms deteriorates severely due to mutual coupling between antenna elements in practical engineering. Therefore, for solving the array mutual coupling, the array output signal vector is modeled by mutual coupling coefficients and the DOA estimation problem is transformed into block sparse signal reconstruction and parameter optimization in this paper. Then, a novel sparse Bayesian learning (SBL)-based algorithm is proposed, in which the expectation-maximum (EM) algorithm is used to estimate the unknown parameters iteratively, and the convergence speed of the algorithm is enhanced by utilizing the approximate approximation. Moreover, considering the off-grid error caused by discretization processes, the grid refinement is carried out using the polynomial roots to realize the dynamic update of the grid points, so as to improve the DOA estimation accuracy. Simulation results show that compared with the existing algorithms, the proposed algorithm is more robust to mutual coupling and off-grid error and can obtain better estimation performance.
A Quasi-Intelligent Maritime Route Extraction from AIS Data
Authors: Onyango Shem Otoi , Owiredu Solomon Amoah , Kim Kwang-Il , Yoo Sang-Lok
Published: November 2022

The rapid development and adoption of automatic identification systems as surveillance tools have resulted in the widespread application of data analysis technology in maritime surveillance and route planning. Traditional, manual, experience-based route planning has been widely used owing to its simplicity. However, the method is heavily dependent on officer experience and is time-consuming. This study aims to extract shipping routes using unsupervised machine-learning algorithms. The proposed three-step approach: maneuvering point detection, waypoint discovery, and traffic network construction was used to construct a maritime traffic network from historical AIS data, which quantitatively reflects ship characteristics by ship length and ship type, and can be used for route planning. When the constructed maritime traffic network was compared to the macroscopic ship traffic flow, the Symmetrized Segment-Path Distance (SSPD) metric returned lower values, indicating that the constructed traffic network closely resembles the routes ships transit. The result indicates that the proposed approach is effective in extracting a route from the maritime traffic network.
A Highly Sensitive Molecularly Imprinted Polymer (MIP)-Coated Microwave Glucose Sensor
Authors: Omidvar Amir Hossein , Amanati Shahri Atena , Serrano Ariana Lacorte Caniato , Gruber Jonas , Pamplona Rehder Gustavo
Published: November 2022

A novel, low-cost, sensitive microwave microfluidic glucose detecting biosensor incorporating molecularly imprinted polymer (MIP) is presented. The sensing device is based on a stub resonator to characterize water glucose solutions. The tip of one of the stubs is coated with MIP to increase the selectivity of the sensor and hence the sensitivity compared to the uncoated or to the coated with non-imprinted polymer (NIP) sensor. The sensor was fabricated on a FR4 substrate for low-cost purposes. In the presence of the MIP, the sensor loaded with a glucose solution ranging from 50 mg/dL to 400 mg/dL is observed to experience an absorption frequency shift of 73 MHz when the solutions flow in a microfluidic channel passing sensing area, while the lower limit of detection (LLD) of the sensor is discovered to be 2.4 ng/dL. The experimental results show a high sensitivity of 1.3 MHz/(mg/dL) in terms of absorption frequency.
Measurements and Models of 915 MHz LoRa Radio Propagation in an Underground Gold Mine
Authors: Branch Philip
Published: November 2022

Underground mining increasingly relies on wireless communications for its operations. The move to automating many underground mining processes makes an understanding of the propagation characteristics of key wireless technologies underground a topic of considerable importance. LoRa has great potential for communications in underground mines, but data on its propagation are quite scarce. In this paper, we describe our measurements of LoRa radio propagation in an underground gold mine. We took measurements in an extraction tunnel with line of sight and in extraction and access tunnels without line of sight. We observed excellent propagation, both with and without line of sight. Our observations support claims by others that the steel-lined tunnels act as a waveguide. As well as reporting measurements, we also developed models of propagation. For line of sight, we show that pathloss is well modelled by a power law with pathloss index of 1.25 and that variability of signal strength is well modelled by a lognormal distribution. We also successfully modelled propagation without line of sight over short distances using a Fresnel Diffraction and Free Space model.
Rapid Detection of Fraudulent Rice Using Low-Cost Digital Sensing Devices and Machine Learning
Authors: Aznan Aimi , Gonzalez Viejo Claudia , Pang Alexis , Fuentes Sigfredo
Published: November 2022

Rice fraud is one of the common threats to the rice industry. Conventional methods to detect rice adulteration are costly, time-consuming, and tedious. This study proposes the quantitative prediction of rice adulteration levels measured through the packaging using a handheld near-infrared (NIR) spectrometer and electronic nose (e-nose) sensors measuring directly on samples and paired with machine learning (ML) algorithms. For these purposes, the samples were prepared by mixing rice at different ratios from 0% to 100% with a 10% increment based on the rice’s weight, consisting of (i) rice from different origins, (ii) premium with regular rice, (iii) aromatic with non-aromatic, and (iv) organic with non-organic rice. Multivariate data analysis was used to explore the sample distribution and its relationship with the e-nose sensors for parameter engineering before ML modeling. Artificial neural network (ANN) algorithms were used to predict the adulteration levels of the rice samples using the e-nose sensors and NIR absorbances readings as inputs. Results showed that both sensing devices could detect rice adulteration at different mixing ratios with high correlation coefficients through direct (e-nose; R = 0.94–0.98) and non-invasive measurement through the packaging (NIR; R = 0.95–0.98). The proposed method uses low-cost, rapid, and portable sensing devices coupled with ML that have shown to be reliable and accurate to increase the efficiency of rice fraud detection through the rice production chain.
A New Quantitative Gait Analysis Method Based on Oscillatory Mechanical Energies Measured near Body Center of Mass
Authors: Cheung Derek , Cheung Jeff , Cheung Vicky , Jin Li
Published: November 2022

Human locomotion involves the modulation of whole-body mechanical energy, which can be approximated by the motion dynamics at the body’s center of mass (BCOM). This study introduces a new method to measure gait efficiency based on BCOM oscillatory kinetic energy patterns using a single inertia measurement unit (IMU). Forty-seven participants completed an overground walk test at a self-selected speed. The average oscillatory energy (OE) at BCOM during walking was derived from measured acceleration data. The total OE showed a positive correlation with forward-walking velocity. The ratio of total OE to constant forward kinetic energy for healthy adults varied from ~1–5%, which can be considered the percent of oscillatory energy required to maintain gait posture for a given forward-walking velocity. Mathematically, this ratio is proportional to the square of the periodic peak-to-peak displacement of BCOM. Individuals with gait impairments exhibited a higher percentage of oscillatory energy, typically >6%. This wearable IMU-based method has the potential to be an effective tool for the rapid, quantitative assessment of gait efficiency in clinical and rehabilitation settings.
Low-Error Soil Moisture Sensor Employing Spatial Frequency Domain Transmissometry
Authors: Saito Tadaomi , Oishi Takahiro , Inoue Mitsuhiro , Iida Sachio , Mihota Norihito , Yamada Atsushi , Shimizu Kohei , Inumochi Satoru , Inosako Koji
Published: November 2022

A new type of soil moisture sensor using spatial frequency domain transmissometry (SFDT) was evaluated. This sensor transmits and receives ultrawideband (1 to 6 GHz) radio waves between two separated antennas and measures the propagation delay time in the soil related to the dielectric constant. This method is expected to be less affected by air gaps between the probes and the soil, as well as being less affected by soil electrical conductivity (EC), than typical commercial sensors. The relationship between output and volumetric water content (θ), and the effects of air gaps and EC were evaluated through experiments using sand samples and the prototype SFDT sensor. The output of the SFDT sensor increased linearly with θ and was not affected by even a high salt concentration for irrigation water, such that the EC of the pore water was 9.2 dS·m−1. The SFDT sensor was almost unaffected by polyethylene tapes wrapped around the sensor to simulate air gaps, whereas a commercially available capacitance sensor significantly underestimated θ. Theoretical models of the SFDT sensor were also developed for the calibration equation and the air gaps. The calculation results agreed well with the experimental results, indicating that analytical approaches are possible for the evaluation of the SFDT sensor.
Small UAS Online Audio DOA Estimation and Real-Time Identification Using Machine Learning
Authors: Kyritsis Alexandros , Makri Rodoula , Uzunoglu Nikolaos
Published: November 2022

The wide range of unmanned aerial system (UAS) applications has led to a substantial increase in their numbers, giving rise to a whole new area of systems aiming at detecting and/or mitigating their potentially unauthorized activities. The majority of these proposed solutions for countering the aforementioned actions (C-UAS) include radar/RF/EO/IR/acoustic sensors, usually working in coordination. This work introduces a small UAS (sUAS) acoustic detection system based on an array of microphones, easily deployable and with moderate cost. It continuously collects audio data and enables (a) the direction of arrival (DOA) estimation of the most prominent incoming acoustic signal by implementing a straightforward algorithmic process similar to triangulation and (b) identification, i.e., confirmation that the incoming acoustic signal actually emanates from a UAS, by exploiting sound spectrograms using machine-learning (ML) techniques. Extensive outdoor experimental sessions have validated this system’s efficacy for reliable UAS detection at distances exceeding 70 m.
Multi-Gas Analyzer Based on Tunable Filter Non-Dispersive Infrared Sensor: Application to the Monitoring of Eco-Friendly Gas Insulated Switchgears
Authors: Kim Yera , Goo Sun-geun , Lim Jeong Sik
Published: November 2022

This study presents a multi-gas analyzer based on tunable filter non-dispersive IR (TF-NDIR) sensors that operate with a wide dynamic range of wavelength and concentration. A pyroelectric sensor coupled with a microsized Fabry–Perot interferometer, namely a tunable filter, enables sensing within a narrowly selected wavelength band. Three detectors capable of tuning the bandpass wavelength with a range of 3.8–5.0 μm, 5.5–8.0 μm, and 8.0–10.5 μm are combined to encompass the entire mid-IR region. single-pass cell with an optical path length (OPL) of 5 cm and a multi-pass cell with an OPL of 10.5 m is selected to encompass a concentration range from ppmv to percent. The TF-NDIR sensors and gas cells can be reconfigured by manipulating the beam path. A homemade lock-in amplifier is used to enhance the signal-to-noise ratio 88 times greater than that of the bare signal. The performance of the gas analyzer is evaluated by measuring the SF6 and Novec-4710/CO2 mixture, which are the dielectric gas medium for a gas-insulated switch (GIS). The mixing ratio of the Novec-4710/CO2 mixture is measured within a range of 3–7% using premixes. The measurement precision is 0.72% for 0.5 s. Trace level measurements of Novec-4710, CO2, SF6, which are measurands for detecting gas leakage from the GIS, CO, and SO2 which are measurands for detecting product generated by the arc or thermal decomposition in the switching electrode, are conducted based on dynamic partial pressure adjustment using 1000 ppmv mother premixes in N2. The limit of detection is 54.7 ppmv for Novec-4710, 112.8 ppmv for CO, 118.1 ppmv for CO2, 69.5 ppmv for SO2, and 33.5 ppmv for SF6.
Reflectance Measurement Method Based on Sensor Fusion of Frame-Based Hyperspectral Imager and Time-of-Flight Depth Camera
Authors: Rahkonen Samuli , Lind Leevi , Raita-Hakola Anna-Maria , Kiiskinen Sampsa , Pölönen Ilkka
Published: November 2022

Hyperspectral imaging and distance data have previously been used in aerial, forestry, agricultural, and medical imaging applications. Extracting meaningful information from a combination of different imaging modalities is difficult, as the image sensor fusion requires knowing the optical properties of the sensors, selecting the right optics and finding the sensors’ mutual reference frame through calibration. In this research we demonstrate a method for fusing data from Fabry–Perot interferometer hyperspectral camera and a Kinect V2 time-of-flight depth sensing camera. We created an experimental application to demonstrate utilizing the depth augmented hyperspectral data to measure emission angle dependent reflectance from a multi-view inferred point cloud. We determined the intrinsic and extrinsic camera parameters through calibration, used global and local registration algorithms to combine point clouds from different viewpoints, created a dense point cloud and determined the angle dependent reflectances from it. The method could successfully combine the 3D point cloud data and hyperspectral data from different viewpoints of a reference colorchecker board. The point cloud registrations gained 0.29–0.36 fitness for inlier point correspondences and RMSE was approx. 2, which refers a quite reliable registration result. The RMSE of the measured reflectances between the front view and side views of the targets varied between 0.01 and 0.05 on average and the spectral angle between 1.5 and 3.2 degrees. The results suggest that changing emission angle has very small effect on the surface reflectance intensity and spectrum shapes, which was expected with the used colorchecker.
Force Plate-Derived Countermovement Jump Normative Data and Benchmarks for Professional Rugby League Players
Authors: McMahon John J. , Ripley Nicholas J. , Comfort Paul
Published: November 2022

The countermovement jump (CMJ) is an important test in rugby league (RL), and the force plate is the recommended assessment device, as it permits the calculation of several variables that explain jump strategy, alongside jump height. The purpose of this study was to produce normative CMJ data and objective benchmarks for professional RL forwards and backs. Normative data for jump height, modified reactive strength index, and jump momentum are provided for 121 professional RL players (66 forwards and 55 backs) who completed CMJ testing on a portable force plate during preseason training. Standardized T-scores (scaled from 0 to 100) were calculated from the respective positional group mean and standard deviation to create CMJ performance bands that were combined with a qualitative description (ranging from extremely poor to excellent) and a traffic light system to facilitate data interpretation and objective benchmark setting by RL practitioners. The jump height and modified reactive strength index benchmarks were larger for the lighter backs, whereas the jump momentum benchmarks were larger for the heavier forwards. The presented novel approach to compiling and presenting normative data and objective benchmarks may also be applied to other data (i.e., from other tests or devices) and populations.
Gas-Sensitive Characteristics of Graphene Composite Tungsten Disulfide to Ammonia
Authors: Zhao Fei , Li Zhongxue , Fu Yongzhong , Wang Quan
Published: November 2022

Two-dimensional materials have outstanding application prospects in gas sensing. By constructing composite structures of various gas-sensitive materials, more-efficient and sensitive gas sensors can be further developed. After graphene is compounded with WS2, the composite material can improve the gas detection performance. In this work, the adsorption energy and the electronic properties of a graphene/WS2 structure were calculated by first-principles before and after adsorption of NH3. The calculation results indicate that the bandgap of the material was appreciably reduced after NH3 was adsorbed. In addition, a graphene/WS2 gas sensor was prepared. The response of the sensor to NH3 at a concentration of 100 ppm was 2.42% and 1.73% at 30 °C and 60 °C, respectively. Combining simulation with experiment, it is feasible to use graphene composite WS2 to detect NH3, which provides a new idea for applications of graphene and other composite materials in gas sensing.
Evaluation of Anti-Venom Potential of Areca catechu Seed Extract on Bungarus caeruleus Venom
Authors: More Veena , Muhsinah Abdullatif , Latha G. , Alhazmi Abdulfattah , Ibrahim Osama , S. Binshaya Abdulkarim , Mahnashi Mater , Almasoudi Hassan , Gangadharappa Harshitha , Maruthi Sahana , Rao Sindhoora , Janardhan Bhavya , Khan Aejaz , Muddapur Uday , Shaikh Ibrahim , More Sunil
Published: November 2022

Areca catechu seeds and their extract/s are currently used to treat various ailments and infections including snakebites. The purpose of this investigation was to assess the inhibiting/neutralizing effect of ethyl acetate and aqueous ethanolic seed extracts of A. catechu on Bungarus caeruleus (krait) venom. The enzyme activities and their inhibition were evaluated using standard procedures (in vitro). In vivo studies were conducted using chick embryos and murine models. The extracts inhibited hyaluronidase and phospholipase A2 activities. Protease activity was neutralized by the aqueous ethanolic extract only. The IC50 value of aqueous ethanolic extract for hyaluronidase was 0.001 g/mL, while that for the ethyl acetate extract for phospholipase A2 was 0.006 g/mL. In addition, both the extracts neutralized the indirect hemolysis and fibrinogenolytic activity induced by B. caeruleus venom. The LD50 for the chick embryos was 4.9 µg/egg. The 50 and 100 µg aqueous ethanolic extracts neutralized the LD50 and the challenging dose (3LD50) of venom effectively in the chick embryo model. The LD50 of B. caeruleus venom in mice was 0.1927 µg/kg; the extract extended the survival time of the mice from 25 min to 30 and 35 min in 1:10 and 1:20 ((w/w) venom:extract) ratios, respectively. The extract also neutralized myotoxic activity. The A. catechu seed extract showed promising inhibitory properties against B. caeruleus venom. In this regard, academia and industries should work collaboratively to develop and formulate a cost-effective first-aid drug.
Evaluating the Applicability of High-Speed Air Flotation Technology for Water Supply: A Case Study in Tianjin Binhai New Area
Authors: Gong Shuyan , Wang Hongpeng , Zhang Shuang , Jiang Shaohong , Zhao Xinjuan , Hou Qidong
Published: November 2022

The development and application of advanced water purification technology is crucial to guarantee a sufficient supply of clean water. However, conventional water purification technology consumes large amounts of coagulants, with the formation of intractable sludge. Herein, the applicability of high-speed air flotation technology for the purification of actual water sources was evaluated in Tianjin Binhai New Area. During a three-year survey, the raw water exhibited periodic pollution characteristics with algae cells as the main removal targets in all seasons. The raw water had both low temperatures and low turbidity in winter, another obstacle for water treatment. Based on the scientific analysis of the water’s quality, the water purification process was comprehensively optimized via regulating the dosage of agents and operating parameters and using high-speed air flotation equipment. The results showed that a dissolved air pressure of 0.40 MPa, reflux ratio of 8%, and SUEZ-1# dissolved air release head combined with pre-chlorination with PACl plus FeCl3 (PACl/FeCl3 ratio = 2:1) were suitable for attaining a good purification performance. High turbidity removal rates (80.9–86.2%) and algae cell removal rates (92.5–98.1%) were obtained even in the high algae period of summer and low turbidity period in the winter, proving the superior stability and applicability of the high-speed air flotation system.
Catholic Arguments against Homosexual Acts and Relationships: Emotional Revulsion or Rational Argument?
Authors: Lawler Michael G. , Salzman Todd A.
Published: November 2022

Most men engaging in homosexual sex have been socially construed as pariahs for much of human history, and women engaging in such sex in the modern age are subject to similar social disapproval. Same-sex marriage has, therefore, been similarly disapproved, and there are several arguments offered in objection to it. The thesis of this essay is that those arguments are not rationally probative and that they are, in fact, cloaks to hide the emotion of revulsion toward homosexual sex. We consider that emotion of revulsion, neuroscientific data related to it, and the arguments of the Catholic Church against homosexual acts, and conclude that those arguments arise, at least in part, from that emotion of revulsion and are not rationally probative.
Specific Incremental Test for Aerobic Fitness in Trail Running: IncremenTrail
Authors: Doucende Grégory , Chamoux Maxime , Defer Thomas , Rissetto Clément , Mourot Laurent , Cassirame Johan
Published: November 2022

Trail running (TR) is performed in a natural environment, including various ranges of slopes where maximal oxygen consumption is a major contributor to performance. The aim of this study is to investigate the validity of tests performed in uphill conditions named the “IncremenTrail” (IncT), based on the incremental ascending speed (AS) to evaluate trail runners’ cardiorespiratory parameters. IncT protocol included a constant gradient slope set at 25% during the whole test; the starting speed was 500 m·h−1 (25% slope and 2.06 km·h−1) and increased by 100 m·h−1 every minute (0.41 km·h−1). Twenty trail runner specialists performed the IncT and a supramaximal exercise bout to exhaustion with intensity set at 105% of maximal AS (Tlim). Oxygen consumption, breathing frequency, ventilation, respiratory exchange ratio (RER), and heart rate were continuously recorded during the exercises. The blood lactate concentration and rate of perceived exertion were collected at the end of the exercises. During the IncT test, 16 athletes (80%) reached a plateau of maximal oxygen uptake (65.5 ± 7.6 mL·kg−1·min−1), 19 athletes (95%) reached RER values over 1.10 (1.12 ± 0.02) and all the athletes achieved blood lactate concentration over 8.0 mmol·L−1 (17.1 ± 3.5 mmol·L−1) and a maximal heart rate ≥90% of the theoretical maximum (185 ± 11 bpm). Maximal values were not significantly different between IncT and Tlim. In addition, ventilatory thresholds could be determined for all runners with an associated AS. IncT provided a suitable protocol to evaluate trail runners’ cardiorespiratory limitations and allowed us to obtain specific intensities based on the ascending speed useful for training purposes in specific conditions.
A Study on the Propagation Trend of Underground Coal Fires Based on Night-Time Thermal Infrared Remote Sensing Technology
Authors: Du Xiaomin , Sun Dongqi , Li Feng , Tong Jing
Published: November 2022

Underground coal fires in coal fields endanger the mine surface ecological environment, endanger coal resources, threaten mine safety and workers’ health, and cause geological disasters. The study of methods by which to monitor the laws that determine the way underground coal fires spread is helpful in the safe production of coal and the smooth execution of fire extinguishing projects. Based on night-time ASTER thermal infrared images of 2002, 2003, 2005 and 2007 in Huangbaici and Wuhushan mining areas in the Wuda coalfield, an adaptive-edge-threshold algorithm was used to extract time-series for underground coal fire areas. A method of time-series dynamic analysis for geometric centers of underground coal fire areas was proposed to study the propagation law and development trend of underground coal fires. The results indicate that, due to the effective prevention of the external influences of solar irradiance, topographic relief and land cover, the identification accuracy of coal fires via the use of a night-time ASTER thermal infrared image was higher by 7.70%, 13.19% and 14.51% than that of the daytime Landsat thermal infrared image in terms of producer accuracy, user accuracy and overall accuracy, respectively. The propagation direction of the geometric center of the time-series coal fire areas can be used to represent the propagation direction of underground coal fires. There exists a linear regression relationship between the migration distance of the geometric center of coal fire areas and the variable-area of coal fires in adjacent years, with the correlation coefficient reaching 0.705, which indicates that the migration distance of the geometric center of a coal fire area can be used to represent the intensity variation of underground coal fires. This method can be applied to the analysis of the trends of underground coal fires under both natural conditions and human intervention. The experimental results show that the Wuda underground coal fires spread to the southeast and that the area of the coal fires increased by 0.71 km2 during the period of 2002–2003. From 2003 to 2005, Wuda’s underground coal fires spread to the northwest under natural conditions, and the area of coal fires decreased by 0.30 km2 due to the closure of some small coal mines. From 2005 to 2007, due to increased mining activities, underground coal fires in Wuda spread to the east, south, west and north, and the area of coal fires increased dramatically by 1.76 km2.
Multi-Criteria Decision Methods for Selecting a Wind Farm Site Using a Geographic Information System (GIS)
Authors: Moltames Rahim , Naghavi Mohammad Sajad , Silakhori Mahyar , Noorollahi Younes , Yousefi Hossein , Hajiaghaei-Keshteli Mostafa , Azizimehr Behzad
Published: November 2022

Wind energy is an economically, technically, and environmentally attractive option due to its cheapness and availability in different regions. The most important obstacle to developing renewable resources in Iran is subsidies for fossil fuels. The Iranian government has recently decided to reduce subsidies for electricity and fossil fuels, which has led to an increase in the prices of fossil fuels and electricity and makes renewable technologies more attractive to use. This study uses a multi-criteria decision method to identify wind energy potential in Khuzestan province. A GIS is used to determine the wind energy potential in this province. The technical, environmental, and economic criteria, which are a total of 14 layers of information, were examined by considering different values for each and from a Boolean point of view. The results show that, from the economic point of view, Shadegan city has the most potential and, from the technical point of view, Khorramshahr city has the highest amount of electricity production through wind energy. Furthermore, Dasht-e Azadegan city, due to its population, can supply the maximum amount of electricity it needs through wind energy. Among the three 550, 2500, and 8000 kW turbines, the 550 kW turbine has the most potential in the region.
Effects of Public Transport Accessibility and Property Attributes on Housing Prices in Polycentric Beijing
Authors: Zhou Yuchen , Tian Yuhong , Jim Chi Yung , Liu Xu , Luan Jingya , Yan Mengxuan
Published: November 2022

The public transit system is often developed in tandem with urban growth, bringing improved accessibility and raising housing prices around stations. The impact of public transport accessibility on housing prices demand in-depth empirical studies to understand the underlying factors. The confounding influence of polycentric cities, contrasting with monocentric ones, deserves more attention. We studied the effects of metro and bus accessibility on housing prices along metro lines 6, 7, 9 and 14 in Beijing under the polycentric scenario. Other property attributes, including building features, location characteristics and neighborhood amenities, served as explanatory variables. Ordinary least squares (OLS) and geographically weighted regression (GWR) were used to build the global (whole-study area) and local hedonic price models, respectively. The results indicated that GWR performed better than OLS in predicting the effects of public transport accessibility on housing prices. Residential properties with access to more metro lines and stations and bus stops were associated with higher housing prices, with metro stations exerting more effects. The premiums of monocentric and polycentric models showed similar spatial patterns. In polycentric Beijing, the premiums of metro accessibility were higher in the eastern part, and the effect of bus accessibility showed circular distribution. Beijing could be regarded as a monocentric city on a global scale, but the influence of subcenters should be considered in a local polycentric regression model. The findings can inform urban planning concerning land use and public transport provision in Beijing and selecting research models in cognate studies.
Mapping the Knowledge Domain of Affected Local Community Participation Research in Megaproject-Induced Displacement
Authors: Zhang Shuang , Mackee Jamie , Sing Michael , Tang Liyaning Maggie
Published: November 2022

Megaproject-induced displacement of populations will now occur more frequently due to massive infrastructure investment in the post-COVID-19 era. The participatory process for megaprojects starts with those in the vicinity; local communities who are directly involved. However, few studies have attempted to map the global knowledge of local community participation in the planning stage of megaprojects. A systematic literature review of public participation in the context of megaproject-induced displacement was conducted to determine these features, and to provide local community insights which are useful for managing social issues around megaprojects and the effects of participation. A total of 32 journal publications were analyzed from the Web of Science (WoS) database, drawing from an initial group of 456 based on citations from 2012 to 2022 to identify the evolution of knowledge trends. It was found that the nonfulfillment participatory process always fails to recognize groups of residents and assess the impacts of megaproject-induced displacement caused to local communities. This lack of recognition at the governmental level contributes to conflict; placing the local community at risk of uncertain megaproject environments. Broader public participation involves local communities, who be harmed by the development strategies of megaprojects, catalyzing their willingness to participate and encourage greater inclusiveness in their interactions, as well as balancing the megaproject’s economic, ecologic, and social interests. The study results demonstrate a consensus was reached, and the effects of megaproject-induced displacement can be mediated.
Bibliometric Network Analysis of Trends in Cyclone Separator Research: Research Gaps and Future Direction
Authors: Alex Frimpong J. , Tan Gangfeng , Agyeman Philip K. , Ansah Prince O. , Olayode Isaac O. , Fayzullayevich Jamshid V. , Liang Shuang
Published: November 2022

Cyclone separators are used extensively in diverse applications and research domains to collect particle-laden flows. Despite the technological advances in this field, no bibliometric reports on this topic have been documented. Understanding the state of the art in this field is crucial for future research. Using bibliometric mapping techniques, this study examined the quality, quantity, and development of research on cyclone separators. Relevant data were extracted in plain text formats through search queries refined by publication year (2000–2021) and document type (article and review articles). A sample of 487 publications, limited to the Web of Science Core Collection (WoSCC) database was used for the bibliometric analysis. Data analysis was performed using RStudio software package (R Bibliometrix tool). Of the 487 publications that appeared during this period, China had the highest number, followed by the Islamic Republic of Iran, whereas chemical engineering journals dominated the cyclone separator research publications. Collaboration among the researchers was low (MCPR < 0.5000). Furthermore, the pattern of single-author publications was found to outstrip that of the multiple-author publications. The findings suggest that researchers in various parts of the world, particularly Africa and the Middle East, should route their research efforts towards this field, in light of the lack of publications from these regions on this subject. The aim of this study was to serve as a seminal reference for potential technological research directions and collaboration among researchers in this and other related fields.
Risk Perception in the Post COVID-19 Pandemic Era: An Analysis of Tourist Accommodation and Travel Behavior in the New Normal Era
Authors: Maulana Noveri , Astuti Rifelly Dewi , Sukamdani Hariyadi B. , Tjiptoherijanto Prijono
Published: November 2022

After two years of the COVID-19 pandemic, research on travel risk perception has been dominated by the study of health risks as a significant factor that influences tourists’ purchase behavior toward tourism and hospitality products, such as accommodation selection. However, research on other travel-risk-related factors remains limited. This study aimed to fill this gap in the literature. Through exploratory factor analysis, the study explored various risk perception factors toward staying in tourist accommodation among tourists during the easing of travel restrictions in Indonesia. Through a survey of 411 foreign and domestic tourists, the study identified 22 risk items and categorized the items into the following 5 dimensions of risk perception: potential loss risk (six items, 39.9% variance), psychological risk (five items, 9.1% variance), health risk (four items, 5.7% variance), social risk (three items, 5.3% variance), and financial risk (four items, 4.7% variance). This study is one of the few studies on risk perception that proposes a multi-dimensional approach rather than a single-dimension approach to risk perception in the hospitality context. These findings may enhance the literature on travel risk perception amidst the crisis and contribute to tourism recovery strategies in the post-pandemic era.