bluuebunny/crossref_metadata_2025 huggingface dataset:
Sulfation of Wheat Straw Soda Lignin with Sulfamic Acid over Solid Catalysts
Authors: Kazachenko Aleksandr , Akman Feride , Vasilieva Natalya , Malyar Yuriy , Fetisova Olga , Lutoshkin Maxim , Berezhnaya Yaroslava , Miroshnikova Angelina , Issaoui Noureddine , Xiang Zhouyang
Published: July 2022

Soda lignin is a by-product of the soda process for producing cellulose from grassy raw materials. Since a method for the industrial processing of lignin of this type is still lacking, several research teams have been working on solving this problem. We first propose a modification of soda lignin with sulfamic acid over solid catalysts. As solid catalysts for lignin sulfation, modified carbon catalysts (with acid sites) and titanium and aluminum oxides have been used. In the elemental analysis, it is shown that the maximum sulfur content (16.5 wt%) was obtained with the Sibunit-4® catalyst oxidized at 400 °C. The incorporation of a sulfate group has been proven by the elemental analysis and Fourier-transform infrared spectroscopy. The molecular weight distribution has been examined by gel permeation chromatography. It has been demonstrated that the solid catalysts used in the sulfation process causes hydrolysis reactions and reduces the molecular weight and polydispersity index. It has been established by the thermal analysis that sulfated lignin is thermally stabile at temperatures of up to 200 °C. According to the atomic force microscopy data, the surface of the investigated film consists of particles with an average size of 50 nm. The characteristics of the initial and sulfated β-O-4 lignin model compounds have been calculated and recorded using the density functional theory.
Clinical Outcomes after Immunotherapies in Cancer Setting during COVID-19 Era: A Systematic Review and Meta-Regression
Authors: Kamal Mona , Baudo Massimo , Joseph Jacinth , Geng Yimin , Qdaisat Aiham
Published: July 2022

Background: This study aims to describe COVID-19–related clinical outcomes after immunotherapies (ICIs) for cancer patients. Methods: In this meta-analysis, we searched databases to collect data that addressed outcomes after immunotherapies (ICIs) during the COVID-19 pandemic. The primary endpoint was COVID-19–related mortality. Secondary endpoints included COVID-related hospital readmission, emergency room (ER) visits, opportunistic infections, respiratory complications, need for ventilation, and thrombo-embolic events. Pooled event rates (PERs) were calculated and a meta-regression analysis was performed. Results: A total of 262 studies were identified. Twenty-two studies with a total of forty-four patients were eligible. The PER of COVID-19–related mortality was 39.73%, while PERs of COVID-19–related ER visits, COVID-19–related pulmonary complications, and COVID-19–related ventilator needs were 40.75%, 40.41%, and 34.92%, respectively. The PER of opportunistic infections was 34.92%. The PERs of the use of antivirals, antibiotics, steroids, prophylactic anticoagulants, and convalescent plasma were 62.12%, 57.12%, 51.36%, 41.90%, and 26.48%, respectively. There was a trend toward an association between previous respiratory diseases and COVID-19–related mortality. Conclusion: The rates of COVID-19–related mortality, ER visits, pulmonary complications, need for a ventilator, and opportunistic infections are still high after ICIs during the COVID-19 pandemic. There was a trend toward an association between previous respiratory diseases and COVID-19–related mortality.
Framework to Extract Extreme Phytoplankton Bloom Events with Remote Sensing Datasets: A Case Study
Authors: Lu Wenfang , Gao Xinyu , Wu Zelun , Wang Tianhao , Lin Shaowen , Xiao Canbo , Lai Zhigang
Published: July 2022

The chlorophyll-a concentration (CHL) is an essential climate variable. Extremes of CHL events directly reflect the condition of marine ecosystems. Here, we applied the statistical framework for defining marine heatwaves to study the extremes of winter CHL blooms off the Luzon Strait (termed as LZB), northeastern South China Sea (SCS), from a set of remote sensing data. The application was enabled by a recent gap-free CHL dataset, the SCSDCT data. We present the basic properties and the long-term trends of these LZB events, which had become fewer but stronger in recent years. We further statistically analyze the LZB events’ controlling factors, including the submesoscale activity quantified by a heterogeneous index or surface temperature gradients. It was revealed that the submesoscale activity was also a vital modulating factor of the bloom events in addition to the well-understood wind and upwelling controls. This modulation can be explained by the stratification introduced by submesoscale mixed-layer instabilities. In the winter, the intensified winter monsoon provides a background front and well-mixed upper layer with replenished nutrients. During the wind relaxation, submesoscale baroclinic instabilities developed, leading to rapid stratification and scattered submesoscale fronts. Such a scenario is favorable for the winter blooms. For the first time, this study identifies the bloom events in a typical marginal sea and highlights the linkage between these events and submesoscale activity. Furthermore, the method used to identify extreme blooms opens up the possibility for understanding trends of multiple marine extreme events under climate change.
A Cascade Defense Method for Multidomain Adversarial Attacks under Remote Sensing Detection
Authors: Xue Wei , Chen Zhiming , Tian Weiwei , Wu Yunhua , Hua Bing
Published: July 2022

Deep neural networks have been widely used in detection tasks based on optical remote sensing images. However, in recent studies, deep neural networks have been shown to be vulnerable to adversarial examples. Adversarial examples are threatening in both the digital and physical domains. Specifically, they make it possible for adversarial examples to attack aerial remote sensing detection. To defend against adversarial attacks on aerial remote sensing detection, we propose a cascaded adversarial defense framework, which locates the adversarial patch according to its high frequency and saliency information in the gradient domain and removes it directly. The original image semantic and texture information is then restored by the image inpainting method. When combined with the random erasing algorithm, the robustness of detection is further improved. Our method is the first attempt to defend against adversarial examples in remote sensing detection. The experimental results show that our method is very effective in defending against real-world adversarial attacks. In particular, when using the YOLOv3 and YOLOv4 algorithms for robust detection of single-class targets, the AP60 of YOLOv3 and YOLOv4 only drop by 2.11% and 2.17%, respectively, under the adversarial example.
Annual Maps of Built-Up Land in Guangdong from 1991 to 2020 Based on Landsat Images, Phenology, Deep Learning Algorithms, and Google Earth Engine
Authors: Xu Han , Xiao Xiangming , Qin Yuanwei , Qiao Zhi , Long Shaoqiu , Tang Xianzhe , Liu Luo
Published: July 2022

Accurate mapping of built-up land is essential for urbanization monitoring and ecosystem research. At present, remote sensing is one of the primary means used for real-time and accurate surveying and mapping of built-up land, due to the long time series and multi-information advantages of existing remote sensing images and the ability to obtain highly precise year-by-year built-up land maps. In this study, we obtained feature-enhanced data regarding built-up land from Landsat images and phenology-based algorithms and proposed a method that combines the use of the Google Earth Engine (GEE) and deep learning approaches. The Res-UNet++ structural model was improved for built-up land mapping in Guangdong from 1991 to 2020. Experiments show that overall accuracy of built-up land map in the study area in 2020 was 0.99, the kappa coefficient was 0.96, user accuracy of built-up land was 0.98, and producer accuracy was 0.901. The trained model can be applied to other years with good results. The overall accuracy (OA) of the assessment results every five years was above 0.97, and the kappa coefficient was above 0.90. From 1991 to 2020, built-up land in Guangdong has expanded significantly, the area of built-up land has increased by 71%, and the proportion of built-up land has increased by 3.91%. Our findings indicate that the combined approach of GEE and deep learning algorithms can be developed into a large-scale, long time-series of remote sensing classification techniques framework that can be useful for future land-use mapping research.
Bayesian Sea Ice Detection Algorithm for CFOSAT
Authors: Li Zhen , Verhoef Anton , Stoffelen Ad
Published: July 2022

This paper describes the adaptation of the Bayesian sea ice detection algorithm for the rotating fan-beam scatterometer CSCAT onboard the China–France Oceanography Satellite (CFOSAT). The algorithm was originally developed and applied for fixed fan-beam and rotating pencil-beam scatterometers. It is based on the probability of the wind and ice backscatter distances from the measurements to their corresponding geophysical model functions (GMFs). The new rotating Ku-band fan-beam design introduces very diverse geometry distributions across the swath, which leads to three main adaptations of the algorithm: (1) a new probability distribution function fit for the backscatter distances over open sea; (2) a linear ice GMF as a function of incidence angle; (3) the separation of outer swath wind vector cells ((WVCs) number 1, 2, 41, 42) from the other WVCs to form two sets of probability distribution function fits for these two WVC groups. The results are validated against sea ice extents from the active microwave ASCAT and the passive microwave SSMI. The validation shows good agreement with both instruments, despite the discrepancies with SSMI during the melting season, and this discrepancy is caused by the lower sensitivity of the passive microwave to detect the ice at a low concentration with a mixed water/ice state, while the scatterometer is more tolerant regarding this situation. We observed that the sea-ice GMF regression between HH and VV sea-ice backscatter at low and high incidence angles decorrelates at around −12 dB (28) and −20 dB (50) and an experiment with truncated backscatter values at these incidence angles is executed, which significantly improves the year-long average sea ice extents. In conclusion, the adapted algorithm for CSCAT works effectively and yields consistent sea ice extents compared with active and passive microwave instruments. As such, it can, in principle, contribute to the long-term global scatterometer sea ice record, and as the algorithm was adapted for a rotating fan-beam scatterometer, it also can serve as a guideline for the recently launched, dual-frequency, rotating fan-beam scatterometer WindRAD.
A Blueprint for the Estimation of Seagrass Carbon Stock Using Remote Sensing-Enabled Proxies
Authors: Simpson Jamie , Bruce Eleanor , Davies Kevin P. , Barber Paul
Published: July 2022

Seagrass ecosystems sequester carbon at disproportionately high rates compared to terrestrial ecosystems and represent a powerful potential contributor to climate change mitigation and adaptation projects. However, at a local scale, rich heterogeneity in seagrass ecosystems may lead to variability in carbon sequestration. Differences in carbon sequestration rates, both within and between seagrass meadows, are related to a wide range of interrelated biophysical and environmental variables that are difficult to measure holistically using traditional field surveys. Improved methods for producing robust, spatially explicit estimates of seagrass carbon storage across large areas would be highly valuable, but must capture complex biophysical heterogeneity and variability to be accurate and useful. Here, we review the current and emerging literature on biophysical processes which shape carbon storage in seagrass beds, alongside studies that map seagrass characteristics using satellite remote sensing data, to create a blueprint for the development of remote sensing-enabled proxies for seagrass carbon stock and sequestration. Applications of satellite remote sensing included measuring seagrass meadow extent, estimating above-ground biomass, mapping species composition, quantifying patchiness and patch connectivity, determining broader landscape environmental contexts, and characterising seagrass life cycles. All of these characteristics may contribute to variability in seagrass carbon storage. As such, remote sensing methods are uniquely placed to enable proxy-based estimates of seagrass carbon stock by capturing their biophysical characteristics, in addition to the spatiotemporal heterogeneity and variability of these characteristics. Though the outlined approach is complex, it is suitable for accurately and efficiently producing a full picture of seagrass carbon stock. This review has drawn links between the processes of seagrass carbon sequestration and the capabilities of remote sensing to detect and characterise these processes. These links will facilitate the development of remote sensing-enabled proxies and support spatially explicit estimates of carbon stock, ensuring climate change mitigation and adaptation projects involving seagrass are accounted for with increased accuracy and reliability.
Calibration of MIMO Radar Transmitting and Receiving Array Using Scene Object Measurement
Authors: Maślikowski Łukasz
Published: July 2022

The paper describes two simple methods allowing phase offsets to be aligned between radiators of transmitting and receiving antenna arrays in a collocated MIMO (Multiple Input Multiple Output) radar. One method uses normalization with averaging, while the second applies SVD (Singular Value Decomposition) of a measurement matrix. To calibrate phase offsets, the measurement of a calibration target at a known angular position must be done. The paper shows numerical comparison to already known method based on normalization by a single element of MIMO measurement matrix and experimental results obtained through the application of the proposed methods to measurement data.
Mapping Soil Organic Carbon in Low-Relief Farmlands Based on Stratified Heterogeneous Relationship
Authors: Wu Zihao , Chen Yiyun , Yang Zhen , Zhu Yuanli , Han Yiran
Published: July 2022

Accurate mapping of farmland soil organic carbon (SOC) provides valuable information for evaluating soil quality and guiding agricultural management. The integration of natural factors, agricultural activities, and landscape patterns may well fit the high spatial variation of SOC in low-relief farmlands. However, commonly used prediction methods are global models, ignoring the stratified heterogeneous relationship between SOC and environmental variables and failing to reveal the determinants of SOC in different subregions. Using 242 topsoil samples collected from Jianghan Plain, China, this study explored the stratified heterogeneous relationship between SOC and natural factors, agricultural activities, and landscape metrics, determined the dominant factors of SOC in each stratum, and predicted the spatial distribution of SOC using the Cubist model. Ordinary kriging, stepwise linear regression (SLR), and random forest (RF) were used as references. SLR and RF results showed that land use types, multiple cropping index, straw return, and percentage of water bodies are global dominant factors of SOC. Cubist results exhibited that the dominant factors of SOC vary in different cropping systems. Compared with the SOC of paddy fields, the SOC of irrigated land was more affected by irrigation-related factors. The effect of straw return on SOC was diverse under different cropping intensities. The Cubist model outperformed the other models in explaining SOC variation and SOC mapping (fitting R2 = 0.370 and predicted R2 = 0.474). These results highlight the importance of exploring the stratified heterogeneous relationship between SOC and covariates, and this knowledge provides a scientific basis for farmland zoning management. The Cubist model, integrating natural factors, agricultural activities, and landscape metrics, is effective in explaining SOC variation and mapping SOC in low-relief farmlands.
A Novel Design and Development of a Strip-Fed Circularly Polarized Rectangular Dielectric Resonator Antenna for 5G NR Sub-6 GHz Band Applications
Authors: Illahi Usman , Iqbal Javed , Irfan Muhammad , Ismail Sulaiman Mohamad , Khan Muhammad Abbas , Rauf Abdul , Bari Inam , Abdullah Mujeeb , Muhammad Fazal , Nowakowski Grzegorz , Glowacz Adam
Published: July 2022

In this article, a rectangular dielectric resonator antenna (RDRA) with circularly polarized (CP) response is presented for 5G NR (New Radio) Sub-6 GHz band applications. A uniquely shaped conformal metal feeding strip is proposed to excite the RDRA in higher-order mode for high gain utilization. By using the proposed feeding mechanism, the degenerate mode pair of the first higher-order, i.e., TEδ13x at 4.13 GHz and TE1δ3y,  at 4.52 GHz is excited to achieve a circularly polarized response. A circular polarization over a bandwidth of ~10%, in conjunction with a wide impedance matching over a bandwidth of ~17%, were attained by the antenna. The CP antenna proposed offers a useful gain of ~6.2 dBic. The achieved CP bandwidth of the RDRA is good enough to cover the targeted 5G NR bands around 4.4–4.8 GHz, such as n79. The proposed antenna configuration is modelled and optimized using computer simulation technology (CST). A prototype was built to confirm (validate) the performance estimated through simulation. A good agreement was observed between simulated and measured results.
Efficient and Accurate Synthesis for Array Pattern Shaping
Authors: Kang Minseok , Baek Jaemin
Published: July 2022

Array pattern synthesis (APS) aims to create the desired array pattern as closely as possible to the prescribed mask template by varying the element excitations of the array. Herein, an efficient approach for the APS to control the sidelobe level is proposed. After designing the mask template to meet the prescribed sidelobe requirements and the waveform pattern, a set of element excitations is calculated through the Fourier transform performed on the projection the waveform pattern onto the mask template. Then, a desired array pattern can be synthesized from this updated set of excitation coefficients. The proposed APS approach directly presents a mathematical formulation of the exact set of excitations without any iterative optimization process. The proposed method is particularly suited for many array elements in linear antenna array. Thus, the proposed APS achieves substantial improvements in terms of computation complexity, performance, and ease of implementation in the algorithm when compared with conventional methods. Several simulation results are provided to verify the efficacy and effectiveness of the proposed method.
Relation between Cortical Activation and Effort during Robot-Mediated Walking in Healthy People: A Functional Near-Infrared Spectroscopy Neuroimaging Study (fNIRS)
Authors: Bonnal Julien , Monnet Fanny , Le Ba-Thien , Pila Ophélie , Grosmaire Anne-Gaëlle , Ozsancak Canan , Duret Christophe , Auzou Pascal
Published: July 2022

Force and effort are important components of a motor task that can impact rehabilitation effectiveness. However, few studies have evaluated the impact of these factors on cortical activation during gait. The purpose of the study was to investigate the relation between cortical activation and effort required during exoskeleton-mediated gait at different levels of physical assistance in healthy individuals. Twenty-four healthy participants walked 10 m with an exoskeleton that provided four levels of assistance: 100%, 50%, 0%, and 25% resistance. Functional near-infrared spectroscopy (fNIRS) was used to measure cerebral flow dynamics with a 20-channel (plus two reference channels) device that covered most cortical motor regions bilaterally. We measured changes in oxyhemoglobin (HbO2) and deoxyhemoglobin (HbR). According to HbO2 levels, cortical activation only differed slightly between the assisted conditions and rest. In contrast, bilateral and widespread cortical activation occurred during the two unassisted conditions (somatosensory, somatosensory association, primary motor, premotor, and supplementary motor cortices). A similar pattern was seen for HbR levels, with a smaller number of significant channels than for HbO2. These results confirmed the hypothesis that there is a relation between cortical activation and level of effort during gait. This finding should help to optimize neurological rehabilitation strategies to drive neuroplasticity.
Survey and Comparative Study of LoRa-Enabled Simulators for Internet of Things and Wireless Sensor Networks
Authors: Idris Sadiq , Karunathilake Thenuka , Förster Anna
Published: July 2022

The Internet of Things (IoT) is one of the most important emerging technologies, spanning a myriad of possible applications, especially with the increasing number and variety of connected devices. Several network simulation tools have been developed with widely varying focuses and used in many research fields. Thus, it is critical to simulate the work of such systems and applications before actual deployment. This paper explores the landscape of available IoT and wireless sensor networks (WSNs) simulators and compares their performance using the Low Power Wide Area Network (LPWAN) communication technology called LoRa (Long Range), which has recently gained a lot of interest. Using a systematic approach, we present a chronological survey of available IoT and WSNs simulation tools. With this, we categorized and content-analyzed published scientific papers in the IoT and WSNs simulation tools research domain by highlighting the simulation tools, study type, scope of study and performance measures of the studies. Next, we present an overview of LoRa/LoRaWAN technology by considering its architecture, transmission parameters, device classes and available simulation tools. Furthermore, we discussed three popular open-source simulation tools/frameworks, namely, NS-3, OMNeT++ (FLoRa) and LoRaSim, for the simulation of LoRa/LoRaWAN networks. Finally, we evaluate their performance in terms of Packet Delivery Ratio (PDR), CPU utilization, memory usage, execution time and the number of collisions.
Near-Field High-Resolution SAR Imaging with Sparse Sampling Interval
Authors: Zhao Chengyi , Xu Leijun , Bai Xue , Chen Jianfeng
Published: July 2022

Near-field high-resolution synthetic aperture radar (SAR) imaging is mostly accompanied by a large number of data acquisition processes, which increases the system complexity and device cost. According to extensive reports, reducing the number of sampling points of a radar in space can greatly reduce the amount of data. However, when spatial sparse sampling is carried out, a ghost normally appears in the imaging results due to the high side lobes generated in the azimuth. To address this issue, a technique is introduced in this paper to recover the blank data through amplitude and phase compensation based on the correlation between sparse array sampling through adjacent points. Firstly, the data sampled by the sparse array is compressed in the range direction to obtain the expected data slices in the same range direction. Then, the blank element of the slice is compensated for with amplitude and phase to obtain full aperture data. Finally, the matched filter method is used to aid in the image reconstruction. The simulation results verified that the method proposed in this paper can effectively reconstruct the image under two kinds of sparse sampling conditions. Thus, a simple single-input single-output (SISO) synthetic aperture radar imaging test bench is established. Compared with the results of a 1 mm (1/4 λ) sampling interval, the quality of the reconstructed image under the condition of a 4 mm (1 λ) sampling interval still stands using our proposed method. Demonstrated by the experiment, the normalized root-mean-square error(NMSE) is 5.75%. Additionally, when the spatial sampling points are sampled randomly with 30% of the full sampling condition, this method can also restore and reconstruct the image with high quality. Due to the decrease of sampling points, the data volume can be reduced, which is beneficial for improving the scanning speed and alleviating the pressure of data transmission for near-field high resolution SAR imaging systems.
Software-Defined Networking: Categories, Analysis, and Future Directions
Authors: Hussain Mudassar , Shah Nadir , Amin Rashid , Alshamrani Sultan S. , Alotaibi Aziz , Raza Syed Mohsan
Published: July 2022

Software-defined networking (SDN) is an innovative network architecture that splits the control and management planes from the data plane. It helps in simplifying network manageability and programmability, along with several other benefits. Due to the programmability features, SDN is gaining popularity in both academia and industry. However, this emerging paradigm has been facing diverse kinds of challenges during the SDN implementation process and with respect to adoption of existing technologies. This paper evaluates several existing approaches in SDN and compares and analyzes the findings. The paper is organized into seven categories, namely network testing and verification, flow rule installation mechanisms, network security and management issues related to SDN implementation, memory management studies, SDN simulators and emulators, SDN programming languages, and SDN controller platforms. Each category has significance in the implementation of SDN networks. During the implementation process, network testing and verification is very important to avoid packet violations and network inefficiencies. Similarly, consistent flow rule installation, especially in the case of policy change at the controller, needs to be carefully implemented. Effective network security and memory management, at both the network control and data planes, play a vital role in SDN. Furthermore, SDN simulation tools, controller platforms, and programming languages help academia and industry to implement and test their developed network applications. We also compare the existing SDN studies in detail in terms of classification and discuss their benefits and limitations. Finally, future research guidelines are provided, and the paper is concluded.
Multivariate Global-Local Priors for Small Area Estimation
Authors: Ghosh Tamal , Ghosh Malay , Maples Jerry J. , Tang Xueying
Published: July 2022

It is now widely recognized that small area estimation (SAE) needs to be model-based. Global-local (GL) shrinkage priors for random effects are important in sparse situations where many areas’ level effects do not have a significant impact on the response beyond what is offered by covariates. We propose in this paper a hierarchical multivariate model with GL priors. We prove the propriety of the posterior density when the regression coefficient matrix has an improper uniform prior. Some concentration inequalities are derived for the tail probabilities of the shrinkage estimators. The proposed method is illustrated via both data analysis and simulations.
Sustainable Production of Biodiesel Using UV Mutagenesis as a Strategy to Enhance the Lipid Productivity in R. mucilaginosa
Authors: Tensingh Joseph Antony Sundarsingh , Shankar Vijayalakshmi
Published: July 2022

The future of petroleum-based fuel is biodiesel. Biodiesel is an eco-friendly fuel that can be used in any diesel engine without any alterations. Researchers have focused on biodiesel that can be produced from microbial lipids extracted from high lipid-yielding microbes. In this study, microbial cultures were screened for high lipid-yielding capabilities and mutated using UV radiation at three different time intervals of 30, 75, and 90 min. The Nile red fluorescence method was used to analyze high lipid-yielding microbes. An outstanding increase in biomass and lipid productivity was noted when the microbes were exposed to UV for 30 min. For example, an M30-8 UV-mutated strain produced a lipid yield of 68.5%. The lipids produced from the wild and mutated strains were analyzed using GCMS and FTIR spectrophotometric analysis. Then, the lipids extracted from both wild VS3 and UV-mutated M30-8 strains were transesterified using a base catalyst and the produced biodiesel was analyzed using ASTM standards. The aim and objective of the research was to mutate high lipid-yielding microbes by using UV radiation and produce biodiesel from the lipids extracted from both wild and UV-mutated strains.
Travel Behaviour and Barriers to Active Travel among Adults in Yaoundé, Cameroon
Authors: Tatah Lambed , Wasnyo Yves , Pearce Matthew , Oni Tolu , Foley Louise , Mogo Ebele , Obonyo Charles , Mbanya Jean Claude , Woodcock James , Assah Felix
Published: July 2022

The literature on urban travel behaviour in Africa is sparse, limiting our understanding of how urban transport policies respond to human and planetary needs. We conducted a cross-sectional household telephone survey on 1334 participants, using a 24 h time-use diary, to investigate travel behaviour and barriers to active travel (walking and cycling) in Yaoundé, Cameroon. We found that two-thirds of all participants reported at least one trip; the median (IQR) numbers of trips per capita and per participant with trips were 2 (0–3) and 2 (2–3), respectively. The main trip modes were shared taxi (46%), walking (27%), private cars (11%), and motorcycle taxis (10%), with 25%, 56%, and 45% of all participants reporting the use of active, motorised, and public transport, respectively. The mean (IQR) trip duration was 48 (30–60) min; for participants who reported trips, the daily overall and active travel durations were 121 (60–150) and 28 (0–45) min, respectively. Women were less likely to travel, making fewer and shorter trips when they did. Participants in less wealthy households were more likely to travel. The primary barriers to both walking and cycling were the fear of road traffic injuries and the inconvenience of active travel modes. Therefore, local urban transport authorities need to improve the safety and convenience of active mobility and promote gender equity in transport. Restrictions to movements during the COVID-19 pandemic and the relatively small survey sample might have biased our results; thus, a representative travel survey could improve current estimates. More generally, high-quality research on travel behaviours and their correlates is needed in low-resource settings.
Water Yield Alteration in Thailand’s Pak Phanang Basin Due to Impacts of Climate and Land-Use Changes
Authors: Janta Rungruang , Khwanchum Laksanara , Ditthakit Pakorn , Al-Ansari Nadhir , Thi Thuy Linh Nguyen
Published: July 2022

Climate and land-use change are important factors in the hydrological process. Climatic and anthropic changes have played a crucial role in surface runoff changes. The objective of this research was to apply land-use change and future climate change to predict runoff change in the Pak Phanang River Basin. The Cellular Automata (CA)-Markov model was used to predict the land-use change, while the climate data from 2025 to 2085 under RPC2.6, RPC4.5, and RPC8.5 were generated using the MarkSim model. Additionally, the Soil and Water Assessment Tool (SWAT) combined land-use change and the generated meteorological data to predict the runoff change in the study area. The results showed that the annual runoff in the area would increase in the upcoming year, which would affect the production of field crops in the lowland area. Therefore, a good water drainage system is required for the coming years. Since the runoff would be about 50% reduced in the middle and late 21st century, an agroforestry system is also suggested for water capturing and reducing soil evaporation. Moreover, the runoff change’s overall impact was related to GHG emissions. This finding will be useful for the authorities to determine policies and plans for climate change adaptation in the Malay Peninsula.
Power Factor Prediction in Three Phase Electrical Power Systems Using Machine Learning
Authors: Gámez Medina José Manuel , de la Torre y Ramos Jorge , López Monteagudo Francisco Eneldo , Ríos Rodríguez Leticia del Carmen , Esparza Diego , Rivas Jesús Manuel , Ruvalcaba Arredondo Leonel , Romero Moyano Alejandra Ariadna
Published: July 2022

The power factor in electrical power systems is of paramount importance because of the influence on the economic cost of energy consumption as well as the power quality requested by the grid. Low power factor affects both electrical consumers and suppliers due to an increase in current requirements for the installation, bigger sizing of industrial equipment, bigger conductor wiring that can sustain higher currents, and additional voltage regulators for the equipment. In this work, we present a technique for predicting power factor variations in three phase electrical power systems, using machine learning algorithms. The proposed model was developed and tested in medium voltage installations and was found to be fairly accurate thus representing a cost reduced approach for power quality monitoring. The model can be modified to predict the variation of the power factor, taking into account removable energy sources connected to the grid. This new way of analyzing the behavior of the power factor through prediction has the potential to facilitate decision-making by customers, reduce maintenance costs, reduce the probability of injecting disturbances into the network, and above all affords a reliable model of behavior without the need for real-time monitoring, which represents a potential cost reduction for the consumer.
Tourism Destination Competitiveness: Analysis and Strategy of the Miyagi Zaō Mountains Area, Japan
Authors: Murayama Takatoshi , Brown Graham , Hallak Rob , Matsuoka Kohsuke
Published: July 2022

This paper uses the tourism destination competitiveness framework to support the formulation of a tourism development strategy for the Miyagi Zaō mountains area in Japan. The study area experienced major disruptions associated with the 2011 earthquake, the Fukushima nuclear accident, and the 2015 and 2018 volcanic eruption warnings. The disasters had a significant impact on tourism, which plays a key role in the sustainability of Zaō town and the surrounding region. Zaō town is faced with an aging population and a shrinking economy. A survey of visitors (demand side) and local company representatives (supply side) was conducted to determine perceived strengths and weaknesses of the regional tourism destination. Nature-based activities were awarded the highest scores by both sides. Based on the findings from the destination competitiveness analysis, a nature-centric tourism development strategy is proposed to achieve destination competitiveness and sustainability of the local society and the natural environment.
Choosing a Mode in Bangkok: Room for Shared Mobility?
Authors: Ayaragarnchanakul Eva , Creutzig Felix , Javaid Aneeque , Puttanapong Nattapong
Published: July 2022

Individual motorized vehicles in urban environments are inefficiently oversupplied both from the perspective of transport system efficiency and from the perspective of local and global environmental externalities. Shared mobility offers the promise of more efficient use of four-wheeler vehicles, while maintaining flexible routing. Here, we aim to understand the travel mode choices of commuters in Bangkok and explore the potential demand for shared mobility through examining both revealed and stated choices, based on our survey (n = 1239) and a systematic comparison of mode choice situations. Our multinomial logistic regression analysis indicates that commuters value time in their vehicles and accept fuel costs, but that they dislike wasting time walking, waiting, and searching for parking or pay for road use and parking. Our model results imply that shared taxi has a higher chance of being used as a door-to-door mode rather than as a competitor to motorcycle taxis as a feeder to the metro stations. Ride sharing gains substantial potential when private motorized cars are charged with the social external costs they cause via congestion charges and parking fees. Replacing cars with shared taxis as the daily choice for those living in detached houses will result in a 24–36% reduction of car trips on Bangkok roads.
Pilot-Scale Radio Frequency-Assisted Pasteurization of Chili Powders Prepacked by Different Packaging Films
Authors: Ma Shaojie , Li Rui , Li Qingye , Zhang Qing , Qin Wen , Liu Shuxiang
Published: July 2022

Radio frequency (RF) can penetrate most packaging films and has the advantages of pasteurizing prepackaged low-moisture foods and avoiding secondary contamination. The suitable films for prepacking chili powders and the corresponding pasteurization process are unclear. This study aimed to select a suitable film for prepackaging chili powders, optimize the parameters of RF heating prepackaged chili powders, and evaluate the effects of RF-assisted pasteurization on the quality of chili powders. The results showed that the non-woven fabric (NWF) is suitable for prepackaging chili powders by evaluating the influence of RF heating on packaging films (appearance, sealing performance, mechanical properties.). Using NWF, chili powders inoculated with Salmonella enterica Enteritidis PT 30 still achieved 6.81 ± 0.64 log CFU/g reduction, treated by RF heating at an average temperature of 67.06 °C for 7.5 min with an electrode gap of 110 mm, held for 12.5 min at a hot-air convection oven. The pasteurization process had no significant (p > 0.05) effect on the quality (appearance, volatile, and capsaicin) of chili powders. The results indicated that chili powders packed with NWF could still be effectively pasteurized by RF-assisted hot air. This study proposed a viable approach to avoid secondary contamination by adding packaging before pasteurization.
Three-Dimensional Conflict Resolution Strategy Based on Network Cooperative Game
Authors: Yang Wenda , Wen Xiangxi , Wu Minggong , Bi Kexin , Yue Longfei
Published: July 2022

Aiming at the problems of difficult handling of three-dimensional flight conflicts and unfair distribution of resolution costs, we propose a multi-aircraft conflict resolution method based on the network cooperative game. Firstly, we establish a flight conflict network model with aircraft as nodes and the conflict relationship between node pairs as edges. After that, we propose a comprehensive network index that can evaluate the effect of resolution strategy. Based on the concept of “nucleolus solution”, we establish a conflict network alliance with all nodes as participants, and balance the interests of all participants through the resolution cost function. In order to improve the timeliness of the method, we propose two optimization methods: adjusting high-priority nodes and customizing the initial resolution scheme. Finally, we combine the NSGA-II algorithm to solve the optimal conflict resolution scheme. The simulation results show that our method can adjust 10 aircraft in 15.17 s and resolve 12 flight conflicts in a complex conflict scenario containing 40 aircraft; our method reduces the resolution cost by more than 22.1% on average compared with the method without considering the resolution cost. The method ensures both the conflict resolution capability and the reduction in resolution cost.
A Differential Operator Associated with q-Raina Function
Authors: Attiya Adel A. , Ibrahim Rabha W. , Albalahi Abeer M. , Ali Ekram E. , Bulboacă Teodor
Published: July 2022

The topics studied in the geometric function theory of one variable functions are connected with the concept of Symmetry because for some special cases the analytic functions map the open unit disk onto a symmetric domain. Thus, if all the coefficients of the Taylor expansion at the origin are real numbers, then the image of the open unit disk is a symmetric domain with respect to the real axis. In this paper, we formulate the q-differential operator associated with the q-Raina function using quantum calculus, that is the so-called Jacksons’ calculus. We establish a new subclass of analytic functions in the unit disk by using this newly developed operator. The theory of differential subordination inspired our approach; therefore, we geometrically explore the most popular properties of this new operator: subordination properties, coefficient bounds, and the Fekete-Szegő problem. As special cases, we highlight certain well-known corollaries of our primary findings.
BK Virus Nephropathy in Kidney Transplantation: A State-of-the-Art Review
Authors: Kant Sam , Dasgupta Alana , Bagnasco Serena , Brennan Daniel C.
Published: July 2022

BK virus maintains a latent infection that is ubiquitous in humans. It has a propensity for reactivation in the setting of a dysfunctional cellular immune response and is frequently encountered in kidney transplant recipients. Screening for the virus has been effective in preventing progression to nephropathy and graft loss. However, it can be a diagnostic and therapeutic challenge. In this in-depth state-of-the-art review, we will discuss the history of the virus, virology, epidemiology, cellular response, pathogenesis, methods of screening and diagnosis, evidence-based treatment strategies, and upcoming therapeutics, along with the issue of re-transplantation in patients.
Recombinant Bovine Herpesvirus Type I Expressing the Bovine Viral Diarrhea Virus E2 Protein Could Effectively Prevent Infection by Two Viruses
Authors: Liu Chun-Yu , Guo Hao , Zhao Hong-Zhe , Hou Li-Na , Wen Yong-Jun , Wang Feng-Xue
Published: July 2022

Bovine respiratory disease complex (BRDC) is a comprehensive disease in cattle caused by various viral and bacterial infections. Among them, bovine herpesvirus type I (BoHV−1) and bovine viral diarrhea virus (BVDV) play important roles and have caused huge financial losses for the cattle industry worldwide. At present, vaccines against BRDC include trivalent attenuated BoHV−1, BVDV−1, and BVDV−2 live vaccines, BoHV−1 live attenuated vaccines, and BoHV−1/BVDV bivalent live attenuated vaccines, which have limitations in terms of their safety and efficacy. To solve these problems, we optimized the codon of the BVDV−1 E2 gene, added the signal peptide sequence of the BoHV−1 gD gene, expressed double BVDV−1 E2 glycoproteins in tandem at the BoHV−1 gE gene site, and constructed a BoHV−1 genetics-engineered vectored vaccine with gE gene deletion, named BoHV−1 gE/E2−Linker−E2+ and BoHV−1 ΔgE. This study compared the protective effects in BoHV−1, BoHV−1 ΔgE, BoHV−1 gE/E2−Linker−E2+, and BVDV−1 inactivated antigen immunized guinea pigs and calves. The results showed that BoHV−1 gE/E2−Linker−E2+ could successfully induce guinea pigs and calves to produce specific neutralizing antibodies against BVDV−1. In addition, after BoHV−1 and BVDV−1 challenges, BoHV−1 gE/E2−Linker−E2+ can produce a specific neutralizing antibody response against BoHV−1 and BVDV−1 infections. Calves immunized with this type of virus can be distinguished as either vaccinated animals (gE-) or naturally infected animals (gE+). In summary, our data suggest that BoHV−1 gE/E2−Linker−E2+ and BoHV−1 ΔgE have great potential to prevent BVDV−1 or BoHV−1 infection.
Virulent Phages Isolated from a Smear-Ripened Cheese Are Also Detected in Reservoirs of the Cheese Factory
Authors: Paillet Thomas , Lossouarn Julien , Figueroa Clarisse , Midoux Cédric , Rué Olivier , Petit Marie-Agnès , Dugat-Bony Eric
Published: July 2022

Smear-ripened cheeses host complex microbial communities that play a crucial role in the ripening process. Although bacteriophages have been frequently isolated from dairy products, their diversity and ecological role in such this type of cheese remain underexplored. In order to fill this gap, the main objective of this study was to isolate and characterize bacteriophages from the rind of a smear-ripened cheese. Thus, viral particles extracted from the cheese rind were tested through a spot assay against a collection of bacteria isolated from the same cheese and identified by sequencing the full-length small subunit ribosomal RNA gene. In total, five virulent bacteriophages infecting Brevibacterium aurantiacum, Glutamicibacter arilaitensis, Leuconostoc falkenbergense and Psychrobacter aquimaris species were obtained. All exhibit a narrow host range, being only able to infect a few cheese-rind isolates within the same species. The complete genome of each phage was sequenced using both Nanopore and Illumina technologies, assembled and annotated. A sequence comparison with known phages revealed that four of them may represent at least new genera. The distribution of the five virulent phages into the dairy-plant environment was also investigated by PCR, and three potential reservoirs were identified. This work provides new knowledge on the cheese rind viral community and an overview of the distribution of phages within a cheese factory.
Reconstruction of the Vertical Dynamic Running Load from the Registered Body Motion
Authors: Van Nimmen Katrien , Vanwanseele Benedicte , Van den Broeck Peter
Published: July 2022

In view of in-field applications, this paper introduces a methodology that uses the registered body motion to reconstruct the vertical dynamic running load. The principle of the reconstruction methodology is to use the time-variant pacing rate that is identified from the body motion together with a generalized single-step load model available in the literature. The methodology is reasonably robust against measurement noise. The performance of the methodology is evaluated by application to an experimental dataset where the running load and the body motion were registered simultaneously. The results show that a very good fit is found with the measured forces, with coefficients of determination of 95% in the time domain and 98% for the amplitude spectrum. Considering a 90% confidence interval, the fundamental harmonic is shown to be reconstructed with a maximum error of 12%. With nearly 90% of the energy concentrated around the fundamental harmonic, this harmonic is the dominant component of the running load. Due to the large inter-person variability in the single-step load pattern, a generalized single-step load model does not arrive at a good fit for the higher harmonics: the reproduction errors easily exceed 50% for a 90% confidence interval. Finally, the methodology is applied to reproduce the dynamic running load induced during full-scale tests on a flexible footbridge. The tests are designed such that the structural response is governed by the (near-)resonant contribution of the fundamental harmonic of the running load. The results show that even when a 12% uncertainty bound is taken into account, the structural response is significantly over-estimated by the numerical simulations (up to 50%). These results suggest a non-negligible impact of other phenomena, such as human–structure interaction, that are not accounted for in current load models.
THE PSYCHOLINGUISTIC BASIS OF THE LINGUISTIC CONCEPTUALIZATION
Authors: Yuanze Zhao , Kudinova Gulnara F. , Kudinov Ilya V. , Aitov Valery F.
Published: July 2022

The object of this article is the methodology of psycholinguistics concerning analyzing concepts. The article's relevance is due to the need to apply new approaches to linguistic phenomena analysis, for which a purely linguistic methodology is not enough. The com­pilation method, a comparative method, and a linguistic modeling method are utilized to fulfill the study's aim. The author describes in detail the research gaps that exist at the moment in psycholinguistics, in particular, the structure of the relationship between sen­sory, short-term and long-term memory is still not fully defined, and therefore the basis for a deep analysis of conceptualization is not fully clear. The author concludes that the psycholinguistic methodology has the greatest explanatory power concerning the cognitive process of conceptualization. At the same time, in the case of comparative analysis of va­rious linguistic cultures, the need for additional use of the conceptual and methodological apparatus of cultural studies and ethnology is actualized.