bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of the Liquid Steel Flow Behavior in the Tundish through Water Model Experiment, Numerical Simulation and Industrial Trial
Authors: Liu Junda , Zhou Ping , Zuo Xiaotan , Wu Di , Wu Dongling
Published: September 2022

A reasonable tundish flow behavior could improve liquid steel cleanliness by promoting floating and removal of the inclusions. The flow behaviors of the tundish could be obtained by water model experiments and numerical simulations, respectively. However, the difference in density between the tracer and water in the experiment can contribute to notable errors. A new type of tracer, which is a mixture of potassium chloride (KCl) and ethanol, was proposed in this study to reduce the errors. The numerical simulation model was validated by the experimental data and its error was below 2%. By comparing the flow behaviors in seven tundishes with different inner structures obtained by simulation, it is found that the C1 can significantly reduce the dead volume ratio and C4 can improve the uniformity of liquid steel charged though each outlet. The structural strength of the baffle in C1 scheme was not considered, resulting in a crack of the baffle in the industrial trial. Industrial trials of the molten steel flow in the C4-based tundish were conducted and reported a reduction of 43.81% in the inclusions over the prototype.
Comprehensive Metabolic Profiling of Euphorbiasteroid in Rats by Integrating UPLC-Q/TOF-MS and NMR as Well as Microbial Biotransformation
Authors: Xiao Sijia , Xu Xike , Wei Xintong , Xin Jiayun , Li Shanshan , Lv Yanhui , Chen Wei , Yuan Wenlin , Xie Bin , Zu Xianpeng , Shen Yunheng
Published: September 2022

Euphorbiasteroid, a lathyrane-type diterpene from Euphorbiae semen (the seeds of Euphorbia lathyris L.), has been shown to have a variety of pharmacological effects such as anti-tumor and anti-obesity. This study aims to investigate the metabolic profiles of euphorbiasteroid in rats and rat liver microsomes (RLMs) and Cunninghamella elegans bio-110930 by integrating ultra-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-Q/TOF-MS), UNIFI software, and NMR techniques. A total of 31 metabolites were identified in rats. Twelve metabolites (M1–M5, M8, M12–M13, M16, M24–M25, and M29) were matched to the metabolites obtained by RLMs incubation and the microbial transformation of C. elegans bio-110930 and their structures were exactly determined through analysis of NMR spectroscopic data. In addition, the metabolic pathways of euphorbiasteroid were then clarified, mainly including hydroxylation, hydrolysis, oxygenation, sulfonation, and glycosylation. Finally, three metabolites, M3 (20-hydroxyl euphorbiasteroid), M24 (epoxylathyrol) and M25 (15-deacetyl euphorbiasteroid), showed significant cytotoxicity against four human cell lines with IC50 values from 3.60 μM to 40.74 μM. This is the first systematic investigation into the in vivo metabolic pathways of euphorbiasteroid and the cytotoxicity of its metabolites, which will be beneficial for better predicting the metabolism profile of euphorbiasteroid in humans and understanding its possible toxic material basis.
Geochemical Characteristics and Chemostratigraphic Analysis of Wufeng and Lower Longmaxi Shales, Southwest China
Authors: Yin Shitao , Zhang Zhifeng , Huang Yongjian
Published: September 2022

The demand for shale gas has propelled researchers to focus on precise and high-resolution stratigraphic divisions for homogeneous shales, of which the late-Ordovician Wufeng (O3w) and the early-Silurian Longmaxi (S1l) formations in southwest China are two of the best candidates for shale gas exploration in China. However, systematic chemostratigraphic work for these strata is still sparse, and the existing chemostratigraphic work either lack representativeness in terms of the proxies used or are subjective during their division procedures. Thus, automatic division process based on multi proxies and an objective statistical technique was applied to establish a quantitative, high-resolution, and robust chemostratigraphic scheme for the Wufeng and lower Longmaxi shales. The geochemical analysis unveils that the Wufeng and Lower Longmaxi shales show prominent heterogeneities in terrigenous inputs, redox conditions, and paleoproductivity, enabling the potential application of chemostratigraphy to these strata. Based on these heterogeneities, the chemostratigraphic scheme for the Wufeng and Lower Longmaxi shales has been established, and the whole strata could be divided into 13 chemozones using constrained clustering analysis. The chemostratigraphic scheme could not only be comparable to the regional sequence stratigraphic scheme but also more objective and higher-resolution. The high TOC content and brittle minerals within chemozone C1 makes it the most preferable layer for shale gas exploration and development. This research gives a systematic chemostratigraphic analysis on Wufeng and Lower Longmaxi shales, which testifies the feasibility and potential of usage of chemostratigraphy for Chinese shale gas exploration and development.
Response Surface Methodology for Copper Flotation Optimization in Saline Systems
Authors: Arancibia-Bravo María P. , Lucay Freddy A. , Sepúlveda Felipe D. , Cortés Lorena , Cisternas Luís A.
Published: September 2022

Response surface methodology (RSM) is one of the most effective tools for optimizing processes, and it has been used in conjunction with the Analysis of Variance (ANOVA) test to establish the effect of input factors on output factors. However, when this methodology is used in mineral flotation, its polynomial model usually performs poorly. An alternative is to use artificial neural networks (ANNs) in such situations. Within this context, the ANOVA test is not the best option for these model types; moreover, it requires statistical assumptions that are difficult to satisfy in flotation. This work proposes replacing the polynomial model of the RSM with ANNs and the Sobol methods to determine the influential input factors instead of the ANOVA test. This proposal is applied to two porphyry copper ores with a high content of pyrite, clay, and dilution media. In addition, this study shows how other computational intelligence techniques, such as swarm intelligence, can be incorporated into this type of problem to improve the learning process of ANNs. The results gave an adjustment of over 0.98 for R2 using ANNs, in comparison to values of around 0.5 when the polynomial model of RSM was utilized. On the other hand, the application of Global Sensitivity Analysis (GSA) identified the aeration rate and P80 size as the most influential variables in copper recovery under the conditions studied. Additionally, we identified significant interactions that affect the recovery of copper, with the interactions between the aeration rate, frother concentration, and P80 size being the most important.
Assessment of Zinc-Bound Phosphate-Based Glass-Coated Denture-Relining Material with Antifungal Efficacy for Inhibiting Denture Stomatitis
Authors: Oh Sang-Hwan , Jung Yun-Sook , Lee Myung-Jin
Published: September 2022

This study investigated the surface properties, biocompatibility, and antifungal activity against Candida albicans of a denture-relining material coated with zinc-bound phosphate-based glass. First, zinc-bound phosphate-based glass was fabricated. A polymerized denture-relining disk was coated with zinc-bound phosphate-based glass (2%, 4%, and 6%). The surface properties of the control and experimental groups were measured, including the wettability, microhardness, color difference, and gloss. The biocompatibility was evaluated using the MTT assay according to ISO 10993-5. The antifungal activity was investigated by counting the number of colony-forming units of Candida albicans. The results were analyzed using a one-way ANOVA and Tukey’s test (p = 0.05). The results of this study indicate that, despite the antimicrobial effect of zinc-bound phosphate-based glass, a coated denture-relining material does not degrade the surface properties and biocompatibility. Therefore, this novel material is considered promising for use as a dental material with antimicrobial properties that can potentially prevent denture stomatitis.
Simplified Limp Frame Model for Application to Nanofiber Nonwovens (Selection of Dominant Biot Parameters)
Authors: Sakamoto Shuichi , Shintani Tetsushi , Hasegawa Tsukasa
Published: September 2022

This study aimed to discover an easy and precise prediction model for the acoustic properties of nanofiber nonwoven fabrics. For this purpose, a prediction model focusing on the two dominant parameters in the Limp frame model—bulk density and flow resistivity—was suggested. The propagation constant and characteristic impedance was generated from the effective density and effective volume modulus generated by the predictive model and treated as a one-dimensional transfer matrix. The sound absorption coefficient was then estimated using the transfer matrix approach. The trend of the normal Incident sound absorption coefficient measured and the sound absorption coefficient obtained from the predictive model were consistent. Thus, it is suggested that the predictive model for the proposed nanofiber nonwoven composite sheet is valid.
Development of Ag-Doped ZnO Thin Films and Thermoluminescence (TLD) Characteristics for Radiation Technology
Authors: Thabit Hammam Abdurabu , Kabir Norlaili A. , Ismail Abd Khamim , Alraddadi Shoroog , Bafaqeer Abdullah , Saleh Muneer Aziz
Published: September 2022

This work examined the thermoluminescence dosimetry characteristics of Ag-doped ZnO thin films. The hydrothermal method was employed to synthesize Ag-doped ZnO thin films with variant molarity of Ag (0, 0.5, 1.0, 3.0, and 5.0 mol%). The structure, morphology, and optical characteristics were investigated using X-ray diffraction (XRD), scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDX), photoluminescence (PL), and UV–vis spectrophotometers. The thermoluminescence characteristics were examined by exposing the samples to X-ray radiation. It was obtained that the highest TL intensity for Ag-doped ZnO thin films appeared to correspond to 0.5 mol% of Ag, when the films were exposed to X-ray radiation. The results further showed that the glow curve has a single peak at 240–325 °C, with its maximum at 270 °C, which corresponded to the heating rate of 5 °C/s. The results of the annealing procedures showed the best TL response was found at 400 °C and 30 min. The dose–response revealed a good linear up to 4 Gy. The proposed sensitivity was 1.8 times higher than the TLD 100 chips. The thermal fading was recorded at 8% for 1 Gy and 20% for 4 Gy in the first hour. After 45 days of irradiation, the signal loss was recorded at 32% and 40% for the cases of 1 Gy and 4 Gy, respectively. The obtained optical fading results confirmed that all samples’ stored signals were affected by the exposure to sunlight, which decreased up to 70% after 6 h. This new dosimeter exhibits good properties for radiation measurement, given its overgrowth (in terms of the glow curve) within 30 s (similar to the TLD 100 case), simple annealing procedure, and high sensitivity (two times that of the TLD 100).
Synthesis of Porous Hierarchical In2O3 Nanostructures with High Methane Sensing Property at Low Working Temperature
Authors: Zhang Huiju , Chang Jiangnan , Wang Yan , Cao Jianliang
Published: September 2022

Different hierarchical porous In2O3 nanostructures were synthesized by regulating the hydrothermal time and combining it with a self-pore-forming method. The gas-sensing test results show that the response of the sensor based on In2O3 obtained after hydrothermal reaction for 48 h is about 10.4 to 500 ppm methane. Meanwhile, it possesses good reproducibility, stability, selectivity and moisture resistance as well as a good exponential linear relationship between the response to methane and its concentration. In particular, the sensor based on In2O3 can detect a wide range of methane (10~2000 ppm) at near-room temperature (30 °C). The excellent methane sensitivity of the In2O3 sensor is mainly due to its unique nanostructure, which has the advantages of both porous and hierarchical structures. Combined with the DFT calculation, it is considered that the sensitive mechanism is mainly controlled by the surface adsorbed oxygen model. This work provides a feasible strategy for enhancing the gas sensitivity of In2O3 toward methane at low temperatures.
Circularly Polarized Antenna Array with Decoupled Quad Vortex Beams
Authors: Xu Shuo , Xu He-Xiu , Wang Yanzhao , Xu Jian , Wang Chaohui , Pang Zhichao , Luo Huiling
Published: September 2022

Achieving multiple vortex beams with different modes in a planar microstrip array is pivotal, yet still extremely challenging. Here, a hybrid method combining both Pancharatnam−Berry (PB) phase that is induced by the rotation phase and excitation phase of a feeding line has been proposed for decoupling two orthogonal circularly polarized vortex beams. Theoretical analysis is derived for array design to generate quad vortex beams with different directions and an arbitrary number of topological charges. On this basis, two 8 × 8 planar arrays were theoretically designed in an X band, which are with topological charges of l1 = −1, l2 = 1, l3 = −1, and l4 = 1 in Case I and topological charges of l1 = −1, l2 = 1, l3 = −1, and l4 = 1 in Case II. To further verify the above theory, the planar array in Case I is fabricated and analyzed experimentally. Dual-LP beams are realized by using rectangular patch elements with two orthogonally distributed feeding networks on different layers based on two types of feeding: proximity coupling and aperture coupling. Both the numerical simulation and experimental measurement results are in good agreement and showcase the corresponding quad-vortex-beam characteristics within 8~12 GHz. The array achieves a measured S11 < −10 dB and S22 < −10 dB bandwidth of more than 33.4% and 29.2%, respectively. In addition, the isolation between two ports is better than −28 dB. Our strategy provides a promising way to achieve large capacity and high integration, which is of great benefit to wireless and radar communication systems.
High-Magnetic-Sensitivity Magnetoelectric Coupling Origins in a Combination of Anisotropy and Exchange Striction
Authors: Zeng Zhuo , He Xiong , Song Yujie , Niu Haoyu , Jiang Dequan , Zhang Xiaoxing , Wei Meng , Liang Youyuan , Huang Hao , Ouyang Zhongwen , Cheng Zhenxiang , Xia Zhengcai
Published: September 2022

Magnetoelectric (ME) coupling is highly desirable for sensors and memory devices. Herein, the polarization (P) and magnetization (M) of the DyFeO3 single crystal were measured in pulsed magnetic fields, in which the ME behavior is modulated by multi-magnetic order parameters and has high magnetic-field sensitivity. Below the ordering temperature of the Dy3+-sublattice, when the magnetic field is along the c-axis, the P (corresponding to a large critical field of 3 T) is generated due to the exchange striction mechanism. Interestingly, when the magnetic field is in the ab-plane, ME coupling with smaller critical fields of 0.8 T (a-axis) and 0.5 T (b-axis) is triggered. We assume that the high magnetic-field sensitivity results from the combination of the magnetic anisotropy of the Dy3+ spin and the exchange striction between the Fe3+ and Dy3+ spins. This work may help to search for single-phase multiferroic materials with high magnetic-field sensitivity.
Relevance of Vitamin D and Its Deficiency for the Ovarian Follicle and the Oocyte: An Update
Authors: Grzeczka Arkadiusz , Graczyk Szymon , Skowronska Agnieszka , Skowronski Mariusz T. , Kordowitzki Paweł
Published: September 2022

For many years, vitamin D (VD) has been known to be an essential micronutrient with important relevance not only for the skeletal system, but also for numerous other mammalian organ systems. Low levels of VD result in a VD deficiency, which is a global health problem. Moreover, VD deficiencies are linked to several pathologies, for instance, diseases of the cardiovascular system, diabetes mellitus, or sub- and infertility. In the past two decades, an increasing body of evidence has shown that adequate physiological levels of VD are crucial for the female gamete and its microenvironment, and VD deficiency has been associated with decreased live birth rates among women undergoing in vitro fertilization (IVF). With regard to the female reproductive tract, VD receptors (VDRs) have been detected in the ovary, endometrium, and the placenta. Although it has been reported that VD seems to be relevant for both calcium-dependent and independent pathways, its relevance for the oocyte’s developmental competence and life span remains elusive. Therefore, herein, we aim to provide an update on the importance of VD and VD deficiency for the oocyte and the follicular microenvironment.
The Burnout of Nurses in Intensive Care Units and the Impact of the Pandemic of SARS-CoV-2: Protocol of a Scoping Review
Authors: Lima Andreia , Moreira Maria , Fernandes Carla , Ferreira Margarida , Teixeira Joana , Parola Vítor , Coelho Adriana
Published: September 2022

Background: The SARS-CoV-2 pandemic has brought multiple challenges for health institutions and their professionals. The requirement of this disease forced nurses to confront organizational and clinical challenges to maintain the quality standards of care they provide. These requirements may have contributed to increased burnout symptoms. This study aims to map the scientific evidence related to nurses’ burnout in intensive care units. Methods: A scoping review will be conducted according to the Joanna Briggs Institute methodology. Relevant databases will be used as well as grey literature, where the following words will be used: burnout, nurses, intensive care units and SARS-CoV-2. Results: This scoping review will include all types of studies—quantitative, qualitative and mixed—and all types of reviews that focus on the objective of this review. Conclusions: It is vital to determine the impact of the burnout caused by the pandemic of SARS-CoV-2 to assess amending measures of risk and protection factors. This will help in the implementation of guidelines according to the available evidence. Additionally, this will help to improve the skills of these professionals as well as to reduce their emotional and physical exhaustion. This protocol is registered with the Open Science Framework.
Emerging Roles of Noncoding RNAs in Bovine Mastitis Diseases
Authors: Oyelami Favour Oluwapelumi , Usman Tahir , Suravajhala Prashanth , Ali Nawab , Do Duy N.
Published: September 2022

Non-coding RNAs (ncRNAs) are an abundant class of RNA with varying nucleotide lengths. They have been shown to have great potential in eutherians/human disease diagnosis and treatments and are now gaining more importance for the improvement of diseases in livestock. To date, thousands of ncRNAs have been discovered in the bovine genome and the continuous advancement in deep sequencing technologies and various bioinformatics tools has enabled the elucidation of their roles in bovine health. Among farm animals’ diseases, mastitis, a common inflammatory disease in cattle, has caused devastating economic losses to dairy farmers over the last few decades. Here, we summarize the biology of bovine mastitis and comprehensively discuss the roles of ncRNAs in different types of mastitis infection. Based on our findings and relevant literature, we highlighted various evidence of ncRNA roles in mastitis. Different approaches (in vivo versus in vitro) for exploring ncRNA roles in mastitis are emphasized. More particularly, the potential applications of emerging genome editing technologies, as well as integrated omics platforms for ncRNA studies and implications for mastitis are presented.
Comment on Alfassam et al. Development of a Colorimetric Tool for SARS-CoV-2 and Other Respiratory Viruses Detection Using Sialic Acid Fabricated Gold Nanoparticles. Pharmaceutics 2021, 13, 502
Authors: Zandi Milad , Soltani Saber
Published: September 2022

In a published article in Pharmaceutics, researchers developed a sialic acid (SA) stabilized Au nanoparticle system based on SA’s binding ability that exists on the surface of lungs epithelial cells. The authors reported that many respiratory viruses including influenza, Middle-East respiratory syndrome (MERS-CoV), and the current coronavirus (SARS-CoV-2) bind to SA as one of the main binding targets of the surface protein hemagglutinin (HA).
Enhancement in Structural and Electroluminescence Properties of Green Light Emission for Semipolar (11–22) InGaN/GaN Based Grown on m-Plane Sapphire via Low Temperature Ammonia Treatment (LTAT)
Authors: Tan Gary , Shuhaimi Ahmad , Norhaniza Rizuan , Zahir Norhilmi , Low Yan Jie , Wong Yew Hoong , Majid Wan Haliza Abd
Published: September 2022

Research on enhancement green light emitter is important to obtain a perfect red-green-blue (RGB) induced white light source. Unfortunately the present of mixed phase in deposition of InGaN/GaN limited the potential LED efficiency. Therefore, we introduce a new method called as Low Temperature Ammonia Treatment (LTAT) to eliminate the mixed phase and to enhance the structure properties of InGaN/GaN. Two samples have been prepared, with LTAT (LED A) and without LTAT (LED B). Both samples have been characterized using optical microscope (OM), Atomic Force Microscope (AFM), X-ray rocking curve (XRC) and Electroluminescence (EL). On the structural characterization, the OM results show the present 3D island on LED B sample while sample LED A only shows 2D surface. The RMS surface roughness from AFM are 10.3 ± 0.4 nm and 13.5 ± 10.7 nm for LED A and LED B respectively. XRC analysis proved the LED A with LTAT has a homogenous XRD curve while LED B without LTAT has a mixed phase. The BSFs streak length measured as 1.42 nm−1 and 1.61 nm−1 for LED A and LED B respectively shows low crystallographic defect in LED A compared to LED B. For the EL characteristic, LED A shows a single sharp peak near 538.2 nm wavelength, while LED B shows a broad multi-peak profile at 435.7 nm, 480.6 nm and 520.5 nm. The single sharp peak shows enhancement in green light emission when LTAT is applied during deposition. Successful enhancement is structural and electroluminescence properties shows the effectiveness of LTAT proposed in this work for perfect RGB.
Control of Self-Assembly of Amphiphilic Wedge-Shaped Mesogens Using a Combination of Magnetic Field and Temperature Treatment
Authors: Anokhin Denis V. , Gur’eva Ludmila L. , Grafskaia Kseniia N. , Pikalov Evgeniy S. , Abukaev Ainur F. , Tarasov Viktor P. , Ivanov Dimitri A.
Published: September 2022

The report elucidates for the first time a significant effect of a strong magnetic field combined with thermal treatment on the texture of thin liquid-crystalline films in a smectic state. The metastable texture generated in the magnetic field was arrested via the crystallization of mesogens while they cooled to room temperature. The effect was demonstrated on a series of wedge-shaped amphiphilic mesogens based on 1,2,3-tris-(dodecyloxy)benzene (TDOB): asymmetric 2,3,4-tris-(dodecyloxy)benzenesulfonic acid (TDOBSH) and its sodium (TDOBSNa) and pyridine (TDOBSPyr) salts. The thermotropic properties and the structure of the liquid crystal phases of the synthesized compounds were studied using differential scanning calorimetry, polarized optical microscopy and X-ray diffraction. It was shown that, depending on the type of counterion, the synthesized mesogens formed different supramolecular structures. The largest effect of the intense magnetic field was observed for the pyridine salt for which an ordered primitive cubic phase texture was generated upon the normal application of the magnetic field with respect to the film. In contrast, for the corresponding acid, an improvement of the gyroid cubic phase orientation was detected with the magnetic field oriented along the film. A highly ordered columnar phase of the sodium salt was affected only minimally by the magnetic field.
Formulation of Modified-Release Bilayer Tablets of Atorvastatin and Ezetimibe: An In-Vitro and In-Vivo Analysis
Authors: Mubeen Iqra , Zaman Muhammad , Farooq Muhammad , Mehmood Asim , Azeez Fahad Khan , Rehman Wajiha , Akhtar Sohail , Chaudhry Mueen Ahmad , Butt Muhammad Hammad , Shamim Qurat-ul-ain , Adnan Sherjeel , Khan Muhammad Rizwan , Atta-ur-Rehman
Published: September 2022

The objective of this work was to formulate co-loaded bilayer tablets containing ezetimibe (EZB) and atorvastatin (ATC). ATC loaded in the immediate-release (IR) layer is an HMG CoA reductase inhibitor, while EZB, added in the sustained-release (SR) layer, is a lipid-lowering agent. This study was conducted to evaluate the effects of polymer on the formulation and characterization of bilayer tablets, as well as the therapeutic impact of the concurrent use of both drugs having a sequential release pattern. To obtain the optimized results, four different formulations with variable compositions were developed and evaluated for different parameters. The drug release studies were carried out using a type II dissolution apparatus, using phosphate buffer solution (PBS) of 1.2 pH for IR of EZB for an initial 2 h, followed by 24 h studies for ATC in PBS 6.8 pH. The IR layer showed rapid drug release (96%) in 2 h, while 80% of the ATC was released in 24 h from the SR layer. Locally obtained, 6-week-old female albino rats were selected for in vivo studies. Both preventive and curative models were applied to check the effects of the drug combination on the lipid profile, atherosclerosis and physiology of different organs. Studies have shown that the administration of both drugs with different release patterns has a better therapeutic effect (p < 0.05), both in preventing and in curing hyperlipidemia. Conclusively, through the sequential release of ATC and EZB, a better therapeutic response could be obtained.
Underwater Object Detection Based on Improved EfficientDet
Authors: Jia Jiaqi , Fu Min , Liu Xuefeng , Zheng Bing
Published: September 2022

Intelligent detection of marine organism plays an important part in the marine economy, and it is significant to detect marine organisms quickly and accurately in a complex marine environment for the intelligence of marine equipment. The existing object detection models do not work well underwater. This paper improves the structure of EfficientDet detector and proposes the EfficientDet-Revised (EDR), which is a new marine organism object detection model. Specifically, the MBConvBlock is reconstructed by adding the Channel Shuffle module to enable the exchange of information between the channels of the feature layer. The fully connected layer of the attention module is removed and convolution is used to cut down the amount of network parameters. The Enhanced Feature Extraction module is constructed for multi-scale feature fusion to enhance the feature extraction ability of the network to different objects. The results of experiments demonstrate that the mean average precision (mAP) of the proposed method reaches 91.67% and 92.81% on the URPC dataset and the Kaggle dataset, respectively, which is better than other object detection models. At the same time, the processing speed reaches 37.5 frame per second (FPS) on the URPC dataset, which can meet the real-time requirements. It can provide a useful reference for underwater robots to perform tasks such as intelligent grasping.
Characterization of the Land Deformation Induced by Groundwater Withdrawal and Aquifer Parameters Using InSAR Observations in the Xingtai Plain, China
Authors: Song Sha , Bai Lin , Yang Chengsheng
Published: September 2022

Long-term overexploitation of groundwater has led to significant land subsidence and ground fissures in the Xingtai plain. These geo-hazards have threatened the safety of buildings and infrastructures. It is extremely important to investigate the coupling relationship between land deformation and hydraulic head change for controlling land subsidence and mitigating ground fissures. In this study, we obtained the spatial and temporal evolution of land deformation in the Xingtai plain by using Envisat/ASAR data during 2009~2010 and Sentinel-1A data during 2015~2021. Combining InSAR results, head observations and geological data, we investigated the response of land deformation to head change and estimate the aquifer parameters. First, joint analysis of displacement time series and head changes infers that land subsidence was mainly caused by the inelastic compaction in aquitards. Compared with the subsidence patterns during 2009~2010, both the rate and spatial extent of land subsidence increased obviously during 2015~2021. Second, seasonal fluctuations in hydraulic head resulted in significant seasonal deformation with an amplitude of 10~30 mm and peak time of January~March, of which the spatial–temporal distribution was consistent with that of the rapid subsidence. Third, obvious differences in the deformation rate and seasonal amplitude were observed across the Longyao ground fissures and other three potential fissures during 2015~2021, suggesting that the activity of ground fissures increased compared with that during 2009~2010. Finally, using InSAR results and head observations, we estimated the elastic and inelastic skeletal storativity, with values ranging from 0.9 × 10−3 to 12.4 × 10−3 and 6.2 × 10−3 to 88.0 × 10−3, respectively. The comparison between elastic and inelastic skeletal storativity suggests that ~84.5% of total subsidence was irreversible and permanent.
MapCleaner: Efficiently Removing Moving Objects from Point Cloud Maps in Autonomous Driving Scenarios
Authors: Fu Hao , Xue Hanzhang , Xie Guanglei
Published: September 2022

Three-dimensional (3D) point cloud maps are widely used in autonomous driving scenarios. These maps are usually generated by accumulating sequential LiDAR scans. When generating a map, moving objects (such as vehicles or moving pedestrians) will leave long trails on the assembled map. This is undesirable and reduces the map quality. In this paper, we propose MapCleaner, an approach that can effectively remove the moving objects from the map. MapCleaner first estimates a dense and continuous terrain surface, based on which the map point cloud is then divided into a noisy part below the terrain, the terrain, and the object part above the terrain. Next, a specifically designed moving points identification algorithm is performed on the object part to find moving objects. Experiments are performed on the SemanticKITTI dataset. Results show that the proposed MapCleaner outperforms state-of-the-art approaches on all five tested SemanticKITTI sequences. MapCleaner is a learning-free method and has few parameters to tune. It is also successfully evaluated on our own dataset collected with a different type of LiDAR.
Evaluating Road Lighting Quality Using High-Resolution JL1-3B Nighttime Light Remote Sensing Data: A Case Study in Nanjing, China
Authors: Xu Nuo , Xu Yongming , Yan Yifei , Guo Zixuan , Wang Baizhi , Zhou Xiang
Published: September 2022

A good lighting environment for roads at night is essential for traffic safety. Accurate and timely knowledge of road lighting quality is meaningful for the planning and management of urban road lighting systems. Traditional field observations and mobile observations have limitations for road lightning quality evaluation at a large scale. This study explored the potential of 0.92 m resolution JL1-3B nighttime light remote sensing images to evaluate road lighting quality in Nanjing, China. Combined with synchronous field measurements and JL1-3B data, multiple regression and random forest regression with several independent variable combinations were developed and compared to determine the optimal model for surface illuminance estimation. Cross validation results showed that the random forest model with Hue, saturability, ln(Intensity), ln(Red), ln(Green) and ln(Blue) as the input independent variables had the best performance (R2 = 0.75 and RMSE = 9.79 lux). Then, this model was used to map the surface illuminance. The spatial scopes of roads were extracted from Google Earth images, and the illuminance within roads was derived to calculate the average, standard deviation and coefficient of variation to indicate the overall brightness level and brightness uniformity of the roads. This study provides a quantitative and effective reference for road lighting evaluation.
Polyphonic Sound Event Detection Using Temporal-Frequency Attention and Feature Space Attention
Authors: Jin Ye , Wang Mei , Luo Liyan , Zhao Dinghao , Liu Zhanqi
Published: September 2022

The complexity of polyphonic sounds imposes numerous challenges on their classification. Especially in real life, polyphonic sound events have discontinuity and unstable time-frequency variations. Traditional single acoustic features cannot characterize the key feature information of the polyphonic sound event, and this deficiency results in poor model classification performance. In this paper, we propose a convolutional recurrent neural network model based on the temporal-frequency (TF) attention mechanism and feature space (FS) attention mechanism (TFFS-CRNN). The TFFS-CRNN model aggregates Log-Mel spectrograms and MFCCs feature as inputs, which contains the TF-attention module, the convolutional recurrent neural network (CRNN) module, the FS-attention module and the bidirectional gated recurrent unit (BGRU) module. In polyphonic sound events detection (SED), the TF-attention module can capture the critical temporal–frequency features more capably. The FS-attention module assigns different dynamically learnable weights to different dimensions of features. The TFFS-CRNN model improves the characterization of features for key feature information in polyphonic SED. By using two attention modules, the model can focus on semantically relevant time frames, key frequency bands, and important feature spaces. Finally, the BGRU module learns contextual information. The experiments were conducted on the DCASE 2016 Task3 dataset and the DCASE 2017 Task3 dataset. Experimental results show that the F1-score of the TFFS-CRNN model improved 12.4% and 25.2% compared with winning system models in DCASE challenge; the ER is reduced by 0.41 and 0.37 as well. The proposed TFFS-CRNN model algorithm has better classification performance and lower ER in polyphonic SED.
Review of Ethanol Intoxication Sensing Technologies and Techniques
Authors: Paprocki Szymon , Qassem Meha , Kyriacou Panicos A
Published: September 2022

The field of alcohol intoxication sensing is over 100 years old, spanning the fields of medicine, chemistry, and computer science, aiming to produce the most effective and accurate methods of quantifying intoxication levels. This review presents the development and the current state of alcohol intoxication quantifying devices and techniques, separated into six major categories: estimates, breath alcohol devices, bodily fluid testing, transdermal sensors, mathematical algorithms, and optical techniques. Each of these categories was researched by analyzing their respective performances and drawbacks. We found that the major developments in monitoring ethanol intoxication levels aim at noninvasive transdermal/optical methods for personal monitoring. Many of the “categories” of ethanol intoxication systems overlap with each other with to a varying extent, hence the division of categories is based only on the principal operation of the techniques described in this review. In summary, the gold-standard method for measuring blood ethanol levels is through gas chromatography. Early estimation methods based on mathematical equations are largely popular in forensic fields. Breath alcohol devices are the most common type of alcohol sensors on the market and are generally implemented in law enforcement. Transdermal sensors vary largely in their sensing methodologies, but they mostly follow the principle of electrical sensing or enzymatic reaction rate. Optical devices and methodologies perform well, with some cases outperforming breath alcohol devices in terms of the precision of measurement. Other estimation algorithms consider multimodal approaches and should not be considered alcohol sensing devices, but rather as prospective measurement of the intoxication influence. This review found 38 unique technologies and techniques for measuring alcohol intoxication, which is testament to the acute interest in the innovation of noninvasive technologies for assessing intoxication.
Water Resources and Health Tourism in Val di Sole: Key Elements for Innovating with Nature in the Italian Inner Territories
Authors: Favargiotti Sara , Pasquali Margherita , Chioni Chiara , Pianegonda Angelica
Published: September 2022

The contexts addressed by the Italian National Strategy for Inner Areas (SNAI) often lack successful regional policies and systemic territorial approaches to achieve effective transformations towards resilient territories. These issues are addressed by the ongoing project “B4R Branding4Resilience.” This contribution aims to present and discuss its first results in the focus area of Val di Sole, Trentino-Alto Adige Region (Italy). The main goal of the University of Trento unit is to pursue leadership in innovating with nature in small thermal villages. The aim is to create a territorial strategy based on the value of the water resources and thermal systems by promoting the enhancement of their natural capital. An interdisciplinary and multi-scalar methodology has been adopted to combine qualitative and quantitative approaches; a data collection process was used to explore the natural identity of Val di Sole to comprehend the ecological and spatial elements; a co-design activity was conducted with the local community’s engagement to propose a resilient territorial strategic vision. As a result, the “Val di Sole Blueprint” represents a strategic tool to implement thermal landscapes as ecological design resources for the territory and to support sustainable territorial development for a better quality of life.
Investigating the Strategic Role of Digital Transformation Path of SMEs in the Era of COVID-19: A Bibliometric Analysis Using R
Authors: Ragazou Konstantina , Passas Ioannis , Sklavos Georgios
Published: September 2022

The COVID-19 pandemic and the subsequent increased use of digital tools can be seen as an incentive for small and medium-sized enterprises (SMEs) to adapt to the digital age. SMEs, whose resilience and adaptability had already been tested during the previous period of the global financial crisis, were called upon to face a new emergency. The aim of this paper is twofold: (i) to investigate the evolution of digital transformation in small and medium enterprises during the pandemic of COVID-19 and (ii) to highlight the main research trends of digital transformation in the post-pandemic era. To approach these issues, a bibliometric analysis based on R package was conducted and examined 765 articles that were published in the timespan of 2014–2022. In the current bibliometric analysis, a range of indicators were applied, such as co-citation analysis of both sources and institutions, the annual scientific production, country collaboration map, world tree map and Multiple Correspondence Analysis. The bibliometric software of Biblioshiny and VOSviewer were used as the main tools to process the data and contributed to the visualization of the results. Findings of the research show that emerging technologies such as blockchain, artificial intelligence, machine learning and 3D printing have started integrating SMEs in their business models. In addition, the technology–organization–environment framework (TOE) has emerged as a niche theme in the research field of digital transformation of SMEs. The above reveals the willingness and the effort of SMEs to adapt to the new circumstances created by the pandemic of COVID-19, by transforming their business models from conventional to digital one. The social media model is also highlighted, as a new product development of SMEs during the crisis of pandemic of COVID-19. The intention to adopt both TOE business model and social media are significantly influenced by emerging technologies and can raise the awareness of government to support SMEs in this effort.
An Examination of the Variables Affecting the Growth of the Tourist Sector in Guizhou Province
Authors: Zhang Weidi , Wen Lei
Published: September 2022

The tourist industry is consistent with the new development paradigm and plays a crucial role in regional economic growth. At the same time, several areas of China have developed tourism as a vital industrial pillar. Analysing and examining the elements that affect the tourist industry in this setting has significant theoretical and practical implications. The dependent variable for this study is the tourist income for Guizhou Province from 2006 to 2019. A total of Eight variables are chosen as independent variables, including the distance travelled by rail and by road, the number of civil flights, the number of travel agencies, the overall number of tourists, the disposable incomes of both urban and rural residents, the number of tertiary industry workers, and the volume of foreign direct investment. The eight independent variables are discovered to favourably impact tourist revenue through the use of factor and regression analysis. Based on the study’s findings, this article suggests that (1) crisis management should be strengthened, and tourist businesses should be advised to become more active rather than passive, (2) infrastructure development should be enhanced for supporting tourism and directing the growth of the rural tourist industry in the area, and (3) the use of digital technologies should be enhanced and the speed of building intelligent tourism should be increased.
The State-Level Nonlinear Effects of Government Spending Shocks in the US: The Role of Partisan Conflict
Authors: Sheng Xin , Gupta Rangan
Published: September 2022

Utilising a nonlinear (regime-switching) mixed-frequency panel vector autoregression model, we study the effects of government spending shocks in the United States (US) over the business cycle, while considering the role of partisan conflict. In particular, we investigate whether partisan conflict is relevant to the differences in fiscal spending multipliers in expansionary and recessionary business cycle phases upon the impact of annual government spending shocks, using quarterly state-level data covering 1950:Q1 to 2016:Q4. We find new evidence that fiscal multipliers can vary with economic and political conditions. The cumulated effects of government spending shocks are strong and persistent in recessions when the level of partisan conflict is low.
Effect of Deforestation on Climate Change: A Co-Integration and Causality Approach with Time Series
Authors: Leon Marcelo , Cornejo Gino , Calderón Micaela , González-Carrión Erika , Florez Hector
Published: September 2022

Climate change is one of the greatest threats of the 21st century due to its global economic, social, and environmental causes and consequences, which affect developing countries to a greater extent. It is worrying that climate models project a temperature increase of more than 2 °C if the current trend in emissions continues, so it is necessary to progressively reduce the annual flow of emissions from approximately seven tons to two tons per capita in the next 40 years. In this sense, this research is aimed at evaluating the effect of deforestation on climate change in Ecuador between 1990–2020, based on data from the Food and Agriculture Organization of the United Nations, for which control variables were added (livestock and agriculture). The Johansen co-integration test, a VAR Model, a VEC Model, and Granger causality were estimated to examine the short-term and long-term relationships and the direction of causality of the variables. The results showed that deforestation does not directly affect climate change; however, it does so indirectly as the existence of a short- and long-term relationship between the variables included in the model was determined. In addition, a causal relationship was determined that goes from agriculture to deforestation and in conjunction with livestock and climate change. It is worrying that variations in climate change occur in the short term because it is in danger to comply with the objectives proposed at the global level regarding climate change. Finally, intensive reforestation is recommended in conjunction with public and educational institutions, as well as the implementation of green buildings. In addition to this, government support in terms of credits, subsidies, training, and technology allow the emission of polluting gases to be reduced as much as possible.
The Chemistry and Health Outcomes of Electronic Waste (E-Waste) Leachate: Exposure to E-Waste Is Toxic to Atlantic Killifish (Fundulus heteroclitus) Embryos
Authors: Igbo Juliet Kelechi , Chukwu Lucian Obinna , Oyewo Emmanuel Olusegun , Blum Jason L. , Schanzer Ariana , Wirgin Isaac , Meltzer Gabriella Y. , Roy Nirmal K. , Zelikoff Judith T.
Published: September 2022

Although there is rising global concern over the environmental, ecological, and human health risks associated with the discharge of leachates from e-waste dumpsites into the aquatic ecosystems, little is known in this research area. Thus, for this study, we first defined the chemistry of the test leachate, followed by assessment of the leachate on the development of a model aquatic organism (Fundulus heteroclitus) used extensively as a bioassay organism in pollution studies. Chemical analyses revealed that levels of phosphate (20.03 mg/L), cadmium (Cd) (0.4 mg/L), lead (Pb) (0.2 mg/L), and chromium (Cr) (0.4 mg/L) were higher than the 2009 US EPA and the 2009 National Environmental Standards and Regulations Enforcement Agency (NESREA) permissible limits. Polycyclic aromatic hydrocarbon (PAH) burdens were dominated mainly by the high molecular weight congeners, specifically the ∑4rings (73 µg/L). Total polychlorinated biphenyls (PCB) levels ranged from 0.00 to 0.40 µg/L with the ∑deca PCBs reaching the highest concentration. For the biological studies, F. heteroclitus embryos (48-h post-fertilization) were divided randomly into groups and exposed to one of six e-waste leachate concentrations (10, 1, 0.1, 0.01, 0.001, 0.0001%). Significant differences (p ≤ 0.05) between treated and control groups were observed in standard and total length, and head size. Further analysis using Duncan’s post-hoc test of multiple comparison also revealed specific differences within and between specific treatment groups. We conclude that e-waste leachate arising from indiscriminate dumping into aquatic ecosystems in Nigeria contains mixtures of toxic constituents that can threaten ecosystem and public health.
Impact of Vermicomposting on Greenhouse Gas Emission: A Short Review
Authors: Panda Amrita Kumari , Mishra Rojita , Dutta Joystu , Wani Zishan Ahmad , Pant Shreekar , Siddiqui Sazada , Alamri Saad Abdulrahman , Alrumman Sulaiman A. , Alkahtani Mohammed Ali , Bisht Satpal Singh
Published: September 2022

The implementation of cutting-edge agricultural practices provides tools and techniques to drive climate-smart agriculture, reduce carbon emissions, and lower the carbon footprint. The alteration of climate conditions due to human activities poses a serious threat to the global agricultural systems. Greenhouse gas emissions (GHG) from organic waste management need urgent attention to optimize conventional composting strategies for organic wastes. The addition of various inorganic materials such as sawdust and fly ash mitigate GHG during the vermicomposting process. This paper critically investigates the factors responsible for GHG emissions during vermicomposting so that possible threats can be managed.