bluuebunny/crossref_metadata_2025 huggingface dataset:
Quercetin- and Rutin-Containing Electrospun Cellulose Acetate and Polyethylene Glycol Fibers with Antioxidant and Anticancer Properties
Authors: Stoyanova Nikoleta , Spasova Mariya , Manolova Nevena , Rashkov Iliya , Georgieva Ani , Toshkova Reneta
Published: December 2022

Innovative fibrous materials from cellulose derivative, cellulose acetate (CA) and water-soluble polyether, polyethylene glycol (PEG) loaded with natural biologically active compounds (BAC), quercetin (QUE) and rutin (RUT), have been successfully fabricated by blend electrospinning and dual electrospinning. Scanning electron microscopy revealed that the mean fiber diameters of all the obtained fibers were in the nanometer range. QUE and RUT incorporated in the fibrous mats were in the amorphous state, as evidenced by the performed differential scanning calorimetry (DSC) and X-ray diffraction (XRD) analysis. The presence of the polyether in the developed fibrous material assisted the in vitro release of the biologically active compounds by improving the hydrophilicity and wettability of the mats. Rutin-containing fibrous materials manifest the highest antioxidative activity, as determined by the 2,2-diphenyl-1-picryl-hydrazyl-hydrate free radical method. The cytotoxicity of the fabricated novel materials was evaluated using a tumor cell line and normal mouse fibroblast cells. The mats containing QUE and QUE/RUT independent of the applied spinning method show a higher cytotoxic effect against cancer cells and 3 to 4.5 times lower cytotoxicity to a noncancer cell line. These features make the quercetin- and rutin-containing fibrous materials promising candidates for pharmaceutical, cosmetic, and biomedical use.
New Building Blocks for Self-Healing Polymers
Authors: Platonova Elena , Ponomareva Polina , Lokiaeva Zalina , Pavlov Alexander , Nelyub Vladimir , Polezhaev Alexander
Published: December 2022

The healing efficiency in self-healing materials is bound by the ability to form blends between the prepolymer and curing agent. One of the problems in the development of self-healing polymers is the reduced affinity of the bismaleimide curing agent for the elastomeric furan-containing matrix. Even when stoichiometric amounts of both components are applied, incompatibility of components can significantly reduce the effectiveness of self-healing, and lead to undesirable side effects, such as crystallization of the curing agent, in the thickness and on the surface. This is exactly what we have seen in the development of linear and cross-linked PUs using BMI as a hardener. In this work, we present a new series of the di- and tetrafuranic isocyanate-related ureas—promising curing agents for the development of polyurethanes-like self-healing materials via the Diels–Alder reaction. The commonly used isocyanates (4,4′-Methylene diphenyl diisocyanate, MDI; 2,4-Tolylene diisocyanate, TDI; and Hexamethylene diisocyanate, HDI) and furfurylamine, difurfurylamine, and furfuryl alcohol (derived from biorenewables) as furanic compounds were utilized for synthesis. The remendable polyurethane for testing was synthesized from a maleimide-terminated prepolymer and one of the T-series urea. Self-healing properties were investigated by thermal analysis. Molecular mass was determined by gel permeation chromatography. The properties of the new polymer were compared with polyurethane from a furan-terminated analog. Visual tests showed that the obtained material has thermally induced self-healing abilities. Resulting polyurethane (PU) has a rather low fusing point and thus may be used as potential material for Fused Deposition Modeling (FDM) 3D printing.
Modeling of Hyper-Viscoelastic Properties of High-Damping Rubber Materials during the Cyclic Tension and Compression Process in the Vertical Direction
Authors: Chen Bowen , Dai Junwu , Shao Zhipeng
Published: December 2022

With the rapid development of the economy and urbanization, the construction of the urban rail transit system has had a great impact on the work, life, and health of residents in buildings along the rail transit line. Thus, it is particularly urgent and necessary to develop base isolation technologies to control and reduce the impact of vibrations of rail transit systems on building structures. High-damping rubber isolation bearings have shown significant effectiveness in the reduction of this impact, and their isolation performance mainly depends on the mechanical and damping energy dissipation characteristics of the high-damping rubber material. This paper aims to investigate the hyper-viscoelastic properties of the high-damping rubber material used for high-damping rubber isolation bearings during the cyclic tension and compression process in the vertical direction. These properties include hyperelastic parameters, viscoelastic coefficients, and the relaxation times of the material. For this purpose, uniaxial cyclic tension and compression tests were conducted. A three-element Maxwell rheological model combining a strain energy density function was proposed for modeling the hyper-viscoelastic behaviors of the materials during the cyclic tension and compression process. Based on the obtained results, an iterative identification procedure was used to determine the constitutive parameters of the material for each loading-unloading cycle. The aforementioned parameters were further expressed as a function of the number of cycles. New insights into hyper-viscoelastic property changes in this high-damping rubber material during the cyclic tension and compression process were gained in this work. These investigations could facilitate the development of computational tools, which would regulate fundamental guidelines for the better controlling and optimization of the isolation performance of the high-damping rubber material used for high-damping rubber isolation bearings, which have a wider perspective of applications in the urban rail transit system.
Numerical Analysis of Heat Transfer Enhancement Due to Nanoparticles under the Magnetic Field in a Solar-Driven Hydrothermal Pretreatment System
Authors: Yu Yang , Wang Kai , Zhao Yurong , Chen Qicheng , Dong Nanhang
Published: December 2022

Solar-driven hydrothermal pretreatment is an efficient approach for the pretreatment of microalgae biomass for biofuel production. In order to enhance the heat transfer, the magnetic fields effects on flow and heat transfer of nanofluids were investigated in a three-dimensional circular pipe. The magnetic fields were applied in different directions and magnetic field intensities to the flow. In this paper, Finite Volume Method was used to simulate flow and heat transfer of nanofluids under a magnetic field, and the Discrete Phase Model was selected to calculate two-phase flow, which was water mixed with metal nanoparticles. The research was also carried out with the various physical properties of nanoparticles, including the volume share of nanoparticles, particle diameter, and particle types. When the magnetic fields were applied along the X, Y, and Z directions and the intensity of magnetic fields was 0.5 T, the heat transfer coefficients of Cu-H2O nanofluids flow were increased evenly by 9.17%, 10.28%, and 10.32%, respectively. When the magnetic field was applied, the heat transfer coefficients and the Nusselt numbers were both increased with the increment of intensities of the magnetic field.
Dynamic Analysis of Extendable Hybrid Voltage Lift DC–DC Converter for DC Microgrid
Authors: Almakhles Dhafer , Jayachandran Divya Navamani , Anbazhagan Lavanya , Hannachi Marwa , Mohamed Ali Jagabar Sathik
Published: December 2022

This paper proposes a novel non-isolated high voltage gain dc–dc converter with a boost2 (B2) technique. The derived single-switch hybrid voltage-lift topology generates a higher voltage conversion ratio with less component counts than traditional voltage-lift converters. Furthermore, to show its superiority, the proposed topology is compared with other recent non-isolated dc–dc converters in terms of the number of power components such as inductors, capacitors, diodes, and switches. Moreover, the voltage stress across the power switch is less than the output voltage, which results in using low-rated components and reducing the converter cost. The steady-state analysis of the proposed topology is carried out with the operating modes in continuous and discontinuous conduction modes. The critical inductance for the proposed converter is derived for design considerations. Compared to the other traditional step-up converters, the stresses across the power diodes are highly reduced. The analysis related to the addition of an expander cell with the topology is performed concerning boundary conditions. An efficiency model with loss calculation is presented. Furthermore, the reliability analysis is performed with the military handbook to determine the failure rate of the converter’s components. Finally, the simulation and 50 W prototype model for experimental validation prove the strength of the proposed topology.
Thought Experiment between Revealed Theology and Narrative
Authors: Savojardo Valentina
Published: December 2022

The paper addresses the problem of the epistemic value of thought experiment, in revealed theology, insofar as it possesses a fundamental trait in common with fiction. Starting from Fehige’s proposal to reread St. Anselm’s ontological argument as a thought experiment of revealed theology and in the light of important differences between the use of scientific and theological thought experiments, it is possible, even in theology, to speak of an indirect or ‘reflexive’ nexus between thought and action. On the basis of this nexus, one can rethink the epistemic role of the theological thought experiment in relation to the art of narration that brings theological thought experiments and fiction closer together. However, it is always the context in which the thought experiment is considered that determines its value and role.
Tidal Rice Yield Assessment in Central Kalimantan, Indonesia, under Different Cultural Practices
Authors: Sulaeman Yiyi , Maftu’ah Eni , Mukhlis Mukhlis , Anwar Khairil , Karolinoerita Vicca , Wakhid Nur , Saleh Muhammad , Khairullah Izhar , Agustiani Mala , Anggara Agus Wahyana , Sasmita Priatna , Rumanti Indrastuti Apri , Sastro Yudi , Ahmad Musyafa , Wurjanto Didy
Published: December 2022

This research aimed to assess the performance of a technology package in relation to rice yield in a B-type tidal rice field in Central Kalimantan province (Indonesia). We selected four areas with different hydrological conditions, soil characteristics, and farmer management systems in Pulangpisau and Kapuas Regency. The introduced technology package covered water management, soil tillage, amelioration and fertilization, adaptive high-yielding varieties, and crop protection. The results showed that, on average, the rice yield of Terusan Karya was 5.52 t ha−1, followed by Belanti B (3.75 t ha−1), Belanti A (3.61 t ha−1), and Talio Hulu (3.27 t ha−1). Rice varieties that yielded more than 5 t ha−1 were Inpara 8 (6.28 t ha−1), Suppadi 89 (5.54 t ha−1), Inpara 3 (5.46 t ha−1), and Inpara 2 (5.36 t ha−1). The implementation of a site-specific technology package combined with intensive guidance for the farmer on its implementation is the key factor in increasing rice productivity in tidal rice farming.
A Method for Detecting Feature-Sparse Regions and Matching Enhancement
Authors: Wang Longhao , Lan Chaozhen , Wu Beibei , Gao Tian , Wei Zijun , Yao Fushan
Published: December 2022

Image matching is a key research issue in the intelligent processing of remote sensing images. Due to the large phase differences or apparent differences in ground features between unmanned aerial vehicle imagery and satellite imagery, as well as the large number of sparsely textured areas, image matching between the two types of imagery is very difficult. Tackling the difficult problem of matching unmanned aerial vehicle imagery and satellite imagery, a feature sparse region detection and matching enhancement algorithm (SD-ME) is proposed in this study. First, the SuperGlue algorithm was used to initially match the two images, and feature-sparse region detection was performed with the help of the image features and initial matching results, with the detected feature sparse areas stored in a linked list one by one. Then, according to the order of storage, feature re-extraction was performed on the feature-sparse areas individually, and an adaptive threshold feature screening algorithm was proposed to filter and screen the re-extracted features. This retains only high-confidence features in the region and improves the reliability of matching enhancement results. Finally, local features with high scores that were re-extracted in the feature-sparse areas were aggregated and input to the SuperGlue network for matching, and thus, reliable matching enhancement results were obtained. The experiment selected four pairs of un-manned aerial vehicle imagery and satellite imagery that were difficult to match and compared the SD-ME algorithm with the SIFT, ContextDesc, and SuperGlue algorithms. The results revealed that the SD-ME algorithm was far superior to other algorithms in terms of the number of correct matching points, the accuracy of matching points, and the uniformity of distribution of matching points. The number of correctly matched points in each image pair increased by an average of 95.52% compared to SuperGlue. The SD-ME algorithm can effectively improve the matching quality between unmanned aerial vehicle imagery and satellite imagery and has practical value in the fields of image registration and change detection.
Hyperspectral Video Target Tracking Based on Deep Edge Convolution Feature and Improved Context Filter
Authors: Zhao Dong , Cao Jialu , Zhu Xuguang , Zhang Zhe , Arun Pattathal V. , Guo Yecai , Qian Kun , Zhang Like , Zhou Huixin , Hu Jianling
Published: December 2022

To address the problem that the performance of hyperspectral target tracking will be degraded when facing background clutter, this paper proposes a novel hyperspectral target tracking algorithm based on the deep edge convolution feature (DECF) and an improved context filter (ICF). DECF is a fusion feature via deep features convolving 3D edge features, which makes targets easier to distinguish under complex backgrounds. In order to reduce background clutter interference, an ICF is proposed. The ICF selects eight neighborhoods around the target as the context areas. Then the first four areas that have a greater interference in the context areas are regarded as negative samples to train the ICF. To reduce the tracking drift caused by target deformation, an adaptive scale estimation module, named the region proposal module, is proposed for the adaptive estimation of the target box. Experimental results show that the proposed algorithm has satisfactory tracking performance against background clutter challenges.
Tree Species Classification Using Plant Functional Traits and Leaf Spectral Properties along the Vertical Canopy Position
Authors: Zhang Yicen , Wang Junjie , Wu Zhifeng , Lian Juyu , Ye Wanhui , Yu Fangyuan
Published: December 2022

Plant functional traits are rarely used in tree species classification, and the impact of vertical canopy positions on collecting samples for classification also remains unclear. We aim to explore the feasibility and effectiveness of leaf traits in classification, as well as to detect the effect of vertical position on classification accuracy. This work will deepen our understanding of the ecological mechanism of natural forest structure and succession from new perspectives. In this study, we collected foliar samples from three canopy layers (upper, middle and lower) and measured their spectra, as well as eight well-known leaf traits. We used a leaf hyperspectral reflectance (LHR) dataset, leaf functional traits (LFT) dataset and LFT + LHR dataset to classify six dominant tree species in a subtropical evergreen broad-leaved forest. Our results showed that the LFT + LHR dataset achieved the highest classification results (overall accuracy (OA) = 77.65% and Kappa = 0.73), followed by the LFT dataset (OA = 74.26% and Kappa = 0.69) and the LHR dataset (OA = 69.06% and Kappa = 0.63). Along the vertical canopy, the OA and Kappa increased from the lower to the upper layers, and the combination data of the three canopy layers achieved the highest accuracy. For the individual tree species, the shade-tolerant species (including Machilus chinensis, Cryptocarya chinensis and Cryptocarya concinna) produced higher accuracies than the light-demanding species (including Schima superba and Castanopsis chinensis). Our results provide an approach for enhancing tree species recognition from the plant physiology and biochemistry perspective and emphasize the importance of vertical direction in forest community research.
Spatial Analysis of Flood Hazard Zoning Map Using Novel Hybrid Machine Learning Technique in Assam, India
Authors: Singha Chiranjit , Swain Kishore Chandra , Meliho Modeste , Abdo Hazem Ghassan , Almohamad Hussein , Al-Mutiry Motirh
Published: December 2022

Twenty-two flood-causative factors were nominated based on morphometric, hydrological, soil permeability, terrain distribution, and anthropogenic inferences and further analyzed through the novel hybrid machine learning approach of random forest, support vector machine, gradient boosting, naïve Bayes, and decision tree machine learning (ML) models. A total of 400 flood and nonflood locations acted as target variables of the flood hazard zoning map. All operative factors in this study were tested using variance inflation factor (VIF) values (<5.0) and Boruta feature ranking (<10 ranks) for FHZ maps. The hybrid model along with RF and GBM had sound flood hazard zoning maps for the study area. The area under the receiver operating characteristics (AUROC) curve and statistical model matrices such as accuracy, precision, recall, F1 score, and gain and lift curve were applied to assess model performance. The 70%:30% sample ratio for training and validation of the standalone models concerning the AUROC value showed sound results for all the ML models, such as RF (97%), SVM (91%), GBM (97%), NB (96%), DT (88%), and hybrid (97%). The gain and lift curve also showed the suitability of the hybrid model along with the RF, GBM, and NB models for developing FHZ maps.
KNN Based Denoising Algorithm for Photon-Counting LiDAR: Numerical Simulation and Parameter Optimization Design
Authors: Ma Rujia , Kong Wei , Chen Tao , Shu Rong , Huang Genghua
Published: December 2022

Photon-counting LiDAR can obtain long-distance, high-precision target3D geographic information, but extracting high-precision signal photons from background noise photons is the key premise of photon-counting LiDAR data processing and application. This study proposes an adaptive noise filtering algorithm that adjusts parameters according to the background photon count rate and removes noise photons based on the local mean Euclidean distance. A simulated photon library that provides different background photon count rates and detection probabilities was constructed. It was then used to fit the distribution relationship between the background photon count rate and the average KNN (K-Nearest Neighbor) distance (k = 2–6) and to obtain the optimal denoising threshold under different background photon count rates. Finally, the proposed method was evaluated by comparing it with the modified density-based spatial clustering (mDBSCAN) and local distance-based statistical methods. The experimental results show that various methods are similar when the background noise rate is high. However, at most non-extreme background photon count rate levels, the F of this algorithm was maintained between 0.97–0.99, which is an improvement over other classical algorithms. The new strategy eliminated the artificial introduction of errors. Due to its low error rates, the proposed method can be widely applied in photon-counting LiDAR signal extraction under various conditions.
Electro-Magnetic Geophysical Dynamics under Conservation and Conventional Farming
Authors: Carrera Alberto , Longo Matteo , Piccoli Ilaria , Mary Benjamin , Cassiani Giorgio , Morari Francesco
Published: December 2022

In the context of global warming, agriculture faces severe challenges such as water scarcity and soil erosion. Key to achieving soil sustainability is the choice of farming practices, the consequences of which are generally site-specific. In this study, the ability of Electrical Resistivity Tomography (ERT) and Electro Magnetic Induction (EMI) methods were assessed for monitoring the effects of conventional (CONV) and conservation (CONS) agricultural practices. The aim is to highlight differences in soil water distribution caused by both short- and long-term effects of the two different practices. Results demonstrated that both ERT and EMI provided sufficient information to distinguish between the effects of CONV and CONS, while traditional direct measurements, being punctual techniques, lacked sufficient spatial resolution. The ERT transects showed that the soil was much more homogeneous as a result of CONS practices, resulting in a higher sensitivity to changes in the water content. Conversely, due to the heterogeneous soil structure under CONV, water distribution was more irregular and difficult to predict. Similar patterns were also observed with the EMI surveys, with a strong link to spatial variability. Finally, we conclude that for CONV soil, the accessible water for the plant is clearly controlled by the soil heterogeneities rather than by the forcing atmospheric conditions. This study is a first step towards paving the way for more refined hydrology models to identify which soil parameters are key to controlling spatial and temporal changes in soil water content.
Streaming Quantiles Algorithms with Small Space and Update Time
Authors: Ivkin Nikita , Liberty Edo , Lang Kevin , Karnin Zohar , Braverman Vladimir
Published: December 2022

Approximating quantiles and distributions over streaming data has been studied for roughly two decades now. Recently, Karnin, Lang, and Liberty proposed the first asymptotically optimal algorithm for doing so. This manuscript complements their theoretical result by providing a practical variants of their algorithm with improved constants. For a given sketch size, our techniques provably reduce the upper bound on the sketch error by a factor of two. These improvements are verified experimentally. Our modified quantile sketch improves the latency as well by reducing the worst-case update time from O(1ε) down to O(log1ε).
Implementation of Non-Contact Temperature Distribution Monitoring Solutions for Railway Vehicles in a Sustainability Development System Transport
Authors: Kampczyk Arkadiusz , Gamon Wojciech , Gawlak Katarzyna
Published: December 2022

The implementation of temperature sensors represented by thermal imaging cameras is becoming increasingly rational. It is playing an important role in the socio-economic environment, in industry, scientific-research work. The main objective of the work is to assess the quality of the railway vehicles in exploitation and their thermal insulation, localise thermal bridges, and the tightness of the body using the FLIR-E6390 thermal inspection camera. An integration of test methods (research methods) was used including a diagnostic method based on a thermographic study integrated with the system approach method and system failure mode effects analysis (SFMEA). The scientific-research work included studies of seven types of railway vehicles in exploitation. A number of conclusions were reached. Specifically providing implementation of innovative and non-contact temperature distribution monitoring solutions for railway vehicles in a sustainability development system transport. Demonstrated the disparities between the different types of vehicles. Next, the identification of critical elements of their thermal insulation, the location of thermal bridges, and the tightness of the body of the rail vehicles, particularly the doors and inter-unit connections. The study covered the state of consumption of stationary electricity (for non-traction needs), implementing innovative indicators for stationary electricity consumption of railway vehicles as a new approach.
Application of Mobile Mapping System to a Cable-Stayed Bridge in Thailand
Authors: Lueangvilai Ekarin , Chaisomphob Taweep
Published: December 2022

Infrastructures must be inspected regularly to ensure serviceability and public safety. In the case of the Thailand expressway, 200 km of an elevated structure must be inspected once a year. Thailand expressway is an elevated reinforced concrete structure. Visual inspection for defects and structural movements such as excessive deflections, transverse movements, or settlements is a cumbersome process. Therefore, a mobile mapping 3D laser scanning (MLS) which is a high-resolution 3D laser scanner (Trimble MX-8) equipped on a vehicle, was introduced. Scanning was performed on live traffic on the expressway. From MLS, both the structure geometry and pavement point cloud data were obtained. A good agreement between elevations of the Rama XI bridge in Bangkok measured by point cloud data using MLS and by a real-time kinematic survey was obtained. The effect of mesh size on the output by MLS was investigated. It was found that a mesh size of 10 cm reduced the computational effort by 75% when compared to a mesh size of 5 cm. However, the International Roughness Index was reduced by 5%. International Roughness Index (IRI) estimated by MLS was close to the IRI values measured by the profilometer. However, a significant overestimation in the case of rutting depth was observed.
Feature Analysis of Scanning Point Cloud of Structure and Research on Hole Repair Technology Considering Space-Ground Multi-Source 3D Data Acquisition
Authors: Pu Xinming , Gan Shu , Yuan Xiping , Li Raobo
Published: December 2022

As one of the best means of obtaining the geometry information of special shaped structures, point cloud data acquisition can be achieved by laser scanning or photogrammetry. However, there are some differences in the quantity, quality, and information type of point clouds obtained by different methods when collecting point clouds of the same structure, due to differences in sensor mechanisms and collection paths. Thus, this study aimed to combine the complementary advantages of multi-source point cloud data and provide the high-quality basic data required for structure measurement and modeling. Specifically, low-altitude photogrammetry technologies such as hand-held laser scanners (HLS), terrestrial laser scanners (TLS), and unmanned aerial systems (UAS) were adopted to collect point cloud data of the same special-shaped structure in different paths. The advantages and disadvantages of different point cloud acquisition methods of special-shaped structures were analyzed from the perspective of the point cloud acquisition mechanism of different sensors, point cloud data integrity, and single-point geometric characteristics of the point cloud. Additionally, a point cloud void repair technology based on the TLS point cloud was proposed according to the analysis results. Under the premise of unifying the spatial position relationship of the three point clouds, the M3C2 distance algorithm was performed to extract the point clouds with significant spatial position differences in the same area of the structure from the three point clouds. Meanwhile, the single-point geometric feature differences of the multi-source point cloud in the area with the same neighborhood radius was calculated. With the kernel density distribution of the feature difference, the feature points filtered from the HLS point cloud and the TLS point cloud were fused to enrich the number of feature points in the TLS point cloud. In addition, the TLS point cloud voids were located by raster projection, and the point clouds within the void range were extracted, or the closest points were retrieved from the other two heterologous point clouds, to repair the top surface and façade voids of the TLS point cloud. Finally, high-quality basic point cloud data of the special-shaped structure were generated.
Identifying the Optimal Parameters to Express the Capacity–Activity Interrelationship of Community-Dwelling Older Adults Using Wearable Sensors
Authors: Wright Emily , Chester Victoria , Kuruganti Usha
Published: December 2022

Mobility is the primary indicator of quality of life among older adults. Physical capacity (PC) and physical activity (PA) are two determinants of mobility; however, PC and PA are complex constructs represented by numerous parameters. This research sought to identify the optimal parameters that may be used to represent PC and PA of older adults, while exploring the interrelationship of these two constructs. Participants were 76 community-dwelling older adults (M age = 74.05 ± 5.15 yrs.). The McRoberts MoveTest was used to objectively measure PC in the laboratory with the following tests: the Short Physical Performance Battery, the Sway test, Sit to Stands, and the Timed Up and Go. PA was then measured at home for one week using the McRoberts USB Dynaport. Correlation analyses resulted in 55% and 65% reductions of PC and PA parameters, respectively. Clustering identified five representative PC parameters and five representative PA parameters. Canonical correlation analysis identified a non-significant correlation between the two sets of parameters. A novel approach was used to define PC and PA by systematically reducing these constructs into representative parameters that provide clinically relevant information, suggesting that they are an accurate representation of one’s PC and PA. A non-significant correlation between PC and PA suggests that there is no relationship between the two in this sample of community-dwelling older adults. The research provided insight into two important determinants of older adult mobility, and how they influence each other.
Track-before-Detect Algorithm for Underwater Diver Based on Knowledge-Aided Particle Filter
Authors: Yue Wenrong , Xu Feng , Xiao Xiongwei , Yang Juan
Published: December 2022

This work studies the underwater detection and tracking of diver targets under a low signal-to-reverberation ratio (SRR) in active sonar systems. In particular, a particle filter track-before-detect based on a knowledge-aided (KA-PF-TBD) algorithm is proposed. Specifically, the original echo data is directly used as the input of the algorithm, which avoids the information loss caused by threshold detection. Considering the prior motion knowledge of the underwater diver target, we established a multi-directional motion model as the state transition model. An efficient method for calculating the statistical characteristics of echo data about the extended target is proposed based on the non-parametric kernel density estimation theory. The multi-directional movement model set and the statistical characteristics of the echo data are used as the knowledge-aided information of the particle filter process: this is used to calculate the particle weight with the sub-area instead of the whole area, and then the particles with the highest weight are used to estimate the target state. Finally, the effectiveness of the proposed algorithm is proved by simulation and sea-level experimental data analysis through joint evaluation of detection and tracking performance.
Constructing Territories of Deterritorialization–Reterritorialization in Clarice Lispector Novels
Authors: Velez de Castro Fátima
Published: December 2022

The importance of geography and literature, as producers of knowledge for society, is undeniable. Both areas are structural pillars for the explanation of contemporary territorial phenomena. In this article, we intend to reflect on the importance of literature for understanding migration, focusing on the deterritorialization–reterritorialization process. Through geographic lenses, we will perform a content analysis of several fictional works by Clarice Lispector, who was hereself a migrant, in several moments of her life. We can consider that this writer’s contribution made a deep contribution to (re)think conceptual and theoretical frames in the geography of migration.
Disparities in COVID-19 Impacts on Work Hours and Career Satisfaction by Gender and Race among Scientists in the US: An Online Survey Study
Authors: Heo Seulkee , Diaz Peralta Pedro , Jin Lan , Pereira Nunes Claudia Ribeiro , Bell Michelle L.
Published: December 2022

The impact of the COVID-19 pandemic on work–life balance may be unequal between female and male scientists. Further information is needed regarding whether the working conditions and career satisfaction for women and racialized scientists are disproportionately affected by the pandemic. This online survey collected data from 1171 scientists in science, technology, engineering, mathematics (STEM), and medicine (STEMM), public health, or other areas of science/engineering working in the US to examine potential disparities in changes in work hours and career satisfaction by gender and race/ethnicity. A significantly higher percentage of women reported increased work hours compared to men. Women, especially racialized women, experienced disproportionately higher increases in teaching and service than the other groups, which contributed to the increased total work hours for women. Satisfaction with the current career progress was lowest for racialized women compared to their counterparts. Our results indicate that the pandemic has inequitably affected allocation of workloads and career satisfaction by gender and race in scientific fields. Institutions of higher education and other research organizations should acknowledge the gender/race differences in science before and during the pandemic to better support the career development and achievement of all scientists, especially women and even more so racialized women.
Facile Preparation of Fe3O4@SiO2 Derived from Iron-Rich Sludge as Magnetic Catalyst for the Degradation of Organic Contaminants by Peroxymonosulfate Activation
Authors: Wang Zhiwei , Zhu Shijun , Deng Jing , Li Haojie , Wang Liang , Luo Haojin , Tang Zehe , Li Xueyan
Published: December 2022

Iron-rich sludge, generated during flocculation/sedimentation processes by using Fe-based coagulant in drinking water treatment plants, could be used as a precursor to prepare an effective peroxymonosulfate (PMS) activator (Fe3O4@SiO2) for the ciprofloxacin (CIP) degradation via facile hydrothermal treatment. The catalytic performances of raw iron-rich sludge and Fe3O4@SiO2 were evaluated. The removal rate of CIP in Fe3O4@SiO2/PMS system increased from 44.7% to 82.8% within 60 min compared with the raw iron-rich sludge. The effects of PMS, catalyst loadings, temperature, and initial pH on the CIP degradation were examined, demonstrating that acidic conditions and higher temperatures were beneficial for CIP degradation. Both sulfate radicals (SO4•−) and hydroxyl radicals (•OH) contributed to the CIP degradation, and SO4•− was predominated in the Fe3O4@SiO2/PMS system, which was confirmed by the result of electron paramagnetic resonance (EPR) analysis and radical quenching tests. The mechanisms of the PMS activation process by Fe3O4@SiO2 were elucidated, and the influencing factors were among which the role of the iron mineral phase was emphatically explored. This study provides a facile method to convert the recycled waste iron-rich sludge to magnetic heterogeneous catalysts for CIP degradation with PMS activation.
Competitive Sustainability: The Intersection of Sustainability and Business Success
Authors: Hull Clyde Eiríkur
Published: December 2022

Sustainability that beats the competition is different from sustainability that does not [...]
Evaluation of the Coordination Degree of Coal and Gas Co-Mining System Based on System Dynamics
Authors: Zhong Shuheng , Lin Dan
Published: December 2022

Coal and gas co-mining is one of the green mining technologies in coal mines. Coal and gas co-mining can reduce environmental pollution and supply-side carbon emissions from the coal industry. It has an important role to play in achieving the goal of carbon peaking and carbon neutrality. The perfect state of safety production and economic efficiency is a “win-win” situation. Therefore, it is of great theoretical and practical importance to evaluate the safety and economic coordination of coal and gas co-mining systems. This study used a system dynamics approach to analyze and evaluate the coordination of coal and gas co-mining systems in a dynamic simulation. A case study was conducted using the Zhuxianzhuang coal mine as an example. The results showed that the coordination degree of the coal and gas co-mining system exhibited dynamic changes. The average value of the system coordination degree is 0.790, which is a good coordination degree. This demonstrates that the system dynamics method is feasible for evaluating the coordination degree of the coal and gas co-mining system. The system dynamics evaluation model can effectively simulate the dynamic changes of different variable factors in the co-mining system. Therefore, these research results can provide corresponding optimization recommendations for practical production needs.
Situation of Physiotherapy Clinics in the Community of Madrid in Relation to the Concept of Sustainability: A Survey Study
Authors: Sánchez Ibáñez Alejandro , Franco Hidalgo-Chacón María de las Mercedes , Sánchez-Romero Eleuterio A. , Cuenca-Zaldivar Juan Nicolás
Published: December 2022

Introduction: Nowadays, it is increasingly urgent to regulate the use of the natural resources of our planet. From the field of physiotherapy, it is necessary to address this issue to ensure that our centers comply as much as possible with the Sustainable Development Goals (SDGs). Objective: To analyze the current situation in physiotherapy clinics in the Community of Madrid so as to identify whether their managers are aware of the concept of sustainability and its levels of application. Material and Methods: A survey study was carried out with the collaboration of 52 physiotherapy clinics in the Community of Madrid (Spain) to collect relevant data on sustainability. The questions were designed by experts in physiotherapy and sustainability with the aim of obtaining as much information as possible, analyzing the knowledge of sustainability and part of the goals established in the 2030 agenda. The procedures were conducted following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and checklist, in addition to following the Declaration of Helsinki. The study was approved by the Local Ethics Committee of the European University of Madrid, Madrid, Spain (CIPI/22.016). Results: A total of 35 questions were answered by 52 physiotherapy clinics in the Autonomous Community of Madrid (Spain) that completed the survey. In addition to the results of each question related to the concept of sustainability, significant differences were observed in the proportion of emotions detected with the NRC dictionary in the question about how waste is removed from the center (p = 0.002 and 0.008, respectively) with a higher proportion of positive feelings with emotions of joy, anticipation, confidence and surprise expressed by participants from clinics of less than 90 m2, while in those from clinics of more than 90 m2, negative feelings predominated with emotions of disgust, fear or sadness; in both cases, the effect of size was large and significant. Conclusions: Most of the physiotherapy clinics in the Community of Madrid that participated in the study are aware of the concept of sustainability. However, in practice, they do not sufficiently apply sustainability protocols in their clinics.
Montmorillonite for Adsorption and Catalytic Elimination of Pollutants from Wastewater: A State-of-the-Arts Review
Authors: Zango Zakariyya Uba , Garba Abdurrahman , Garba Zaharaddeen Nasiru , Zango Muttaqa Uba , Usman Fahad , Lim Jun-Wei
Published: December 2022

Clay minerals have been recognized as one of the cheap and effective materials for wastewater remediation. Among the various clay minerals, montmorillonite (MMT) has received much attention due to its wide availability, low-cost and promising properties such as high porosity, mechanical strength, and cation exchange capacity. Additionally, MMT has high swelling properties. These features make it an ideal material for wastewater remediation applications. In addition, it possessed good cationic exchange capacity, making it easier to interact with various molecules. MMT and its composites exhibited good selectivity and catalytic activity for contaminants elimination from wastewater. Surface modification and functionalization have been identified as a way to improve the MMT’s adsorptive performance and endow it with light and light-harnessing properties. Thus, MMT composites, especially metal and metal-oxide nanoparticles, have shown good adsorption and photocatalytic activity toward the elimination/mineralization of various contaminants such as dyes, pharmaceuticals, heavy metals, and other organic and inorganic species. As such, MMT and its composites can be adopted as potential materials for wastewater remediation.
The Study of the Effect of the Digital Economy on the Low-Carbon Transformation of Urban Economies under Public Attention
Authors: Wang Qiang , Jiang Hongren , Xu Jian
Published: December 2022

Using the panel data of 274 cities from 2011 to 2019, this article studied the impact of the digital economy on the low-carbon transformation and space overflow effect on the city’s low-carbon transformation and used the panel threshold model to calculate the regulatory effect of public attention. Studies found the following: (1) The digital economy, the urban low-carbon transformation level, and public attention show regional differences, manifesting as the distribution of "point clusters" and "decreasing from east to west", and as far as the speed of change, after the year 2015, the annual increase of various indicators increased. (2) The role of digital economy development and urban low-carbon transformation levels have a "U" relationship. At present, most cities across the country have passed the point of inflection, which presents a significant promotion effect. However, in a comparison of regional coefficients, the Eastern region > Western region > Midlands. (3) The development of the digital economy has a significant “siphon effect” on the impact of urban low-carbon transformation. (4) With the increase in public attention in the region, the positive promotion of the digital economy on the urban low-carbon transformation has gradually increased.
The Summary of Nitritation Process in Mainstream Wastewater Treatment
Authors: Zhao Hongjun , Guo Yan , Wang Qunhui , Zhang Ze , Wu Chuanfu , Gao Ming , Liu Feng
Published: December 2022

The application of the mainstream partial nitritation/anammox (PN/A) process is promising due to the huge cost reduction compared to traditional biological nitrogen removal. However, the nitrite production rate (NPR) of a biological nitritation pre-treatment process is relatively lower than the nitrite consumption rate in a pure anammox reactor with a high nitrogen loading rate (NLR). Thus, the NPR is the rate-limiting step for operating the PN/A process with a higher NLR. Various studies have attempted to improve mainstream NPR. A comprehensive review of these processes is needed for the actual application of the PN/A process. This study focuses on: (1) various nitrite production processes that have emerged in recent years; (2) the main microbial species and characteristics involved in biological nitritation; (3) the existing problems and the N2O emission problem of these processes; and (4) a proposed novel and promising PN/A process facilitated with photocatalyst oxidation. This review is expected to provide references and a basis for the research on the nitritation step of the application of the mainstream PN/A process.
The Infrared Radiation Characteristics of Sandstone Fracture Seepage under Coupled Stress-Hydro Effect
Authors: Cui Ruoyu , Cao Kewang , Li Xinci , Khan Rana Muhammad Asad , Khan Naseer Muhammad , Liu Wei , Gao Qiangqiang , Wang Fagang , Yang Yuanzhong , Quan Jiangbo , Alarifi Saad S.
Published: December 2022

Effective monitoring of rock fracture and seepage is an important information means to ensure the safety of geotechnical engineering. Therefore, sandstone samples were subject to uniaxial compression under different hydraulic conditions in the presence of infrared radiation and observation. This study uses the multiple infrared radiation indexes (ΔAIRT, IRV, VDIIT) and image data to analyze the influence of coupled stress-hydro effect of infrared radiation change on sandstone surface. The main findings are: (1) The surface temperature of sandstone samples rises in the compaction and linear elastic stages, keeps stable or decreases in the fracture development stage, and rapidly decreases in the post-peak failure stage. (2) The samples with internal water pressure not more than 0.30 MPa, surface temperature and load curve at the compaction and linear elastic stage have a strong power function relationship, which a coefficient of determination is 0.8900. (3) The IRV curve appears as a pulse jump at the time of water seepage. After that, both the fracture development and the post-peak failure stages have stepped up. The VDIIT curve also appears to be a pulse jump at the time of water seepage, and obvious up and down fluctuations exist before water seepage and fracture. (4) Based on the Pauta Criterion, by analyzing the values of VDIIT during the experiment, the early warning threshold of sandstone fracture seepage is determined to be 0.00559. The research finding can provide an experimental and theoretical basis for the early warning of flood accidents in underground rock engineering.
A PANAS Structure Analysis: On the Validity of a Bifactor Model in Korean College Students
Authors: Park Hongseok , Lee Jeong-Mi , Koo Sohee , Chung So-Youn , Lee Seongki , Cho Young Il
Published: December 2022

The purpose of this study was to determine the best model fit among the six models in the Korean version of Positive and Negative Affect Schedule (K-PANAS). Therefore, this study compared and analyzed the dimensional structure of this schedule for Korean college students. Specifically, the model fitness of six models, which are under debate, were compared: a single model for K-PANAS, a two-factor model (PA&NA) without any factor correlation, a three-factor model (PA, NA-Afraid, NA-Upset), a two-factor bifactor model, a three-factor bifactor model, and a three-factor bifactor model with error correlation. A total of 875 samples were analyzed, and the results show that best model fit is the three-factor bifactor model with error correlation. We named the general factor of the bifactor model “activation (or arousal).” This findings of this study will provide a richer explanation of emotions for researchers analyzing emotional activation (or arousal), a general factor of emotion, PA, and NA future studies that use PANAS.