bluuebunny/crossref_metadata_2025 huggingface dataset:
Heat Treatment Induced Specified Aggregation Morphology of Metoprolol Tartrate in Poly(ε-caprolactone) Matrix and the Drug Release Variation
Authors: Liu Zhiyu , Song Hangling , Chen Xia , Han Aichun , Chen Rong , Liu Guiting , Guo Shaoyun
Published: September 2021

Hot-melt blending has been widely used in the pharmaceutical industry to produce drug delivery systems, however, realizing the controlled drug release behavior of a hot-melt blended medicament it is still a tough challenge. In this study, we developed a simple and effective heat treatment method to adjust the drug release behavior, without the addition of any release modifiers. Thin metoprolol tartrate (MPT)/poly(ε-caprolactone) (PCL) tablets were prepared through hot-melt processing, and different morphologies of MPT were obtained by altering processing temperatures and the following heat treatment. MPT particles with different particle sizes were obtained under different processing temperatures, and fibrous crystals of MPT were fabricated during the following heat treatment. Different morphological structures of MPT adjusted the drug diffusion channel when immersed in phosphate-buffered saline (PBS), and various drug release behaviors were approached. After being immersed for 24 h, 7% of the MPT was released from the blend processed at 130 °C, while more than 95% of the MPT were released after the following heat treatment of the same sample. Thus, flexible drug release behaviors were achieved using this simple and effective processing manufacture, which is demonstrated to be of profound importance for biomedical applications.
Synthesis and Heavy-Metal Sorption Studies of N,N-Dimethylacrylamide-Based Hydrogels
Authors: Akhmetzhan Ayatzhan , Abeu Nurgeldi , Longinos Sotirios Nik. , Tashenov Ayezkhan , Myrzakhmetova Nurbala , Amangeldi Nurgul , Kuanyshova Zhanar , Ospanova Zhanar , Toktarbay Zhexenbek
Published: September 2021

In this work, a hydrogel system was produced via radical polymerization of N,N-dimethylacrylamide and 2-acrylamido-2-methylpropanesulfonic acid in the presence of N,N-methylene-bis-acrylamide as a crosslinker and ammonium persulfate as an initiator. Parameters that impact the conversion of copolymerization (such as initial concentration of monomers, temperature, initiator dose, and time) were studied. The swelling degree of the hydrogel was investigated with the addition of a crosslinker and initiator at different pH levels. A hydrogel with high conversion and high swelling degree was selected to investigate their ability for adsorption of Pb(II) ions from solutions. Adsorption behavior of Pb(II) ions in a hydrogel was examined as a function of reaction time and concentration of lead ions from a solution of Pb(II) ions.
Analysis of the Anti-Corrosion Performance of Dextrin and Its Graft Copolymer on J55 Steel in Acid Solution
Authors: Liu Mingxing , Xia Dayu , Singh Ambrish , Lin Yuanhua
Published: September 2021

This paper studies the corrosion inhibition performance and mechanism of dextrin (Dxt) and its graft copolymer with caprolactam (Dxt-g-CPL) on J55 steel in 1 M HCl solution. Caprolactam is grafted and copolymerized with dextrin by a chemical synthesis method, to obtain a dextrin graft copolymer corrosion inhibitor. The composition of the synthesized graft copolymer was characterized by FTIR to identify whether the grafting was successful. Through weightlessness, electrochemical impedance spectroscopy (EIS), potentiodynamic polarization curve (TAFEL), scanning electrochemical microscope (SECM), scanning electron microscope (SEM), and contact angle experiments, the graft copolymer to J55 steel in 1 M HCl solution and the corrosion inhibition performance were evaluated. Moreover, we discuss its corrosion inhibition mechanism. The dextrin graft copolymer has good corrosion inhibition performance for J55 in 1 M HCl solution. When the concentration of the corrosion inhibitor increases, the corrosion inhibition efficiency will also increase. At a certain concentration, when the temperature rises, the corrosion inhibition efficiency will gradually decrease. When the concentration is 300 mg/L, it has a better corrosion inhibition effect, and the corrosion inhibition efficiency is 82.38%. Potential polarization studies have shown that Dxt-g-CPL is a mixed corrosion inhibitor, which inhibits both the cathode and the anode of the electrode reaction. SEM, SECM, and contact angle analysis results show that Dxt-g-CPL can significantly inhibit corrosion. Compared with Dxt, Dxt-g-CPL has a better inhibitory effect.
Multi-Performance Optimization in Electrical Discharge Machining of Al2O3 Ceramics Using Taguchi Base AHP Weighted TOPSIS Method
Authors: Zeng Yue-Peng , Lin Chiang-Lung , Dai Hong-Mei , Lin Yan-Cherng , Hung Jung-Chou
Published: September 2021

The main application of electrical discharge machining in ceramic processing is limited to conductive ceramics. However, the most commonly used non-conductive potteries in modern industry, such as aluminum oxide (Al2O3), also reveal the limitations of choosing a suitable process. In this study, Taguchi based TOPSIS coupled with AHP weight method to optimize the machining parameters of EDM on Al2O3 leads to better multi-performance. The results showed that the technique is suitable for tackling multi-performance machining parameter optimization. The adhesive foil had a significant impact on material removal rate, electrode wear rate, and surface roughness, according to the findings. In addition, the response graph of relative closeness is used to determine the optimal combination levels of machining parameters. A confirmation test revealed a good agreement between predicted and experimental preference values at an optimum combination of the input parameters. The suggested experimental and statistical technique is a simple, practical, and reliable methodology for optimizing EDM process parameters on Al2O3 ceramics. This approach might be utilized to optimize and improve additional process parameters in the future.
Medical Device Regulation from a Health Service Provider’s Perspective
Authors: Kwong Man Ting , Stell David , Akinluyi Emmanuel
Published: September 2021

Unfamiliarity with medical device regulations can sometimes be a barrier to deploying technology in a clinical setting for researchers and innovators. Health service providers recognise that innovation can happen within smaller organisations, where regulatory support may be limited. This article sets out to increase transparency and outline key considerations on medical device regulations from a UK healthcare provider’s perspective. The framework used by Guy’s and St Thomas’ NHS Foundation Trust (GSTFT) for assessing research devices is presented to give an overview of the routes that R&D medical devices take to enter a clinical setting. Furthermore, current trends on research studies involving medical devices were extracted from the GSTFT internal R&D database and presented as the following categories (i) commercial vs. non-commercial, (ii) assessment type and (iii) software vs. non-software. New medical devices legislation will be introduced within the UK in July 2023. It is anticipated regulating software as a medical device may become more challenging for healthcare providers and device manufacturers alike. It is therefore important for different stakeholders involved to work together to ensure this does not become a barrier to innovation.
Ethnoarchaeology of Introducing Agriculture and Social Continuity among Sedentarised Hunter–Gatherers: The Transition from the Jomon to the Yayoi Period
Authors: Ikeya Kazunobu
Published: September 2021

This study was conducted to elucidate the introduction of agriculture and social continuity from the Jomon to the Yayoi period, from an ethnoarchaeological perspective. The Yayoi period has been divided into two types: a broad spectrum economy that relied on many kinds of resources, such as rice, millet, and nuts, and a selective economy that specialised in rice and wild boar. However, it is not clear how the livelihoods shifted from the Jomon to the Yayoi period. In this study, ethnohistorical materials were examined first. Ethnohistorical reference materials gathered worldwide have revealed three relationships between hunter–gatherers and farmers: coexistence, fusion, and assimilation. Focusing on fusion, this study examined situations of hunting, gathering, and fishing, as inferred from ruins of the Late and Final Jomon period, and assessed their relationships with agriculture using ethnohistorical reference materials of the Early Edo period. There were not many social changes caused by the introduction of field farming; however, the introduction of paddy rice cultivation had different effects on society depending on the level of investment in obtaining water from streams and springs and creating irrigation features.
‘Wife, Mommy, Pastor and Friend’: The Rise of Female Evangelical Microcelebrities
Authors: Gaddini Katie Christine
Published: September 2021

The popularity of digital media has spurred what has been called a “crisis of authority”. How do female evangelical microcelebrities figure in this crisis? Many of these women belong to churches led by male pastors, have amassed a large following online, and are sought-after speakers and teachers. This paper analyses how gender, religious authority, and the digital sphere collide through the rise of female evangelical microcelebrities. Bringing together ethnographic data, textual analysis, and social media analysis of six prominent women, I emphasize the power of representation to impact religious practices and religious meaning. This article examines how evangelical women are performing and negotiating their legitimacy as the Internet and fluid geographical boundaries challenge local models of religious authority. Moving away from a binary perspective of “having” or “not having” authority, this paper considers the various spheres of authority that evangelical microcelebrities occupy, including normative womanhood, prosperity theology, and politics. Finally, by examining the social media content put forth by female evangelical microcelebrities, I interrogate the political stakes of evangelical women’s authority.
Option Pricing, Zero Lower Bound, and COVID-19
Authors: Morelli Giacomo , Petrella Lea
Published: September 2021

This paper provides a quantitative assessment of equity options priced at the Zero Lower Bound, i.e., when interest rates are set essentially to zero. We obtain closed form formulas for American options when the Zero Lower Bound policy holds. We perform numerical implementation of American put options written on the stock Federal National Mortgage Association (FNMA) and of related bounds for the optimal exercise. The results show similarities with the corresponding European options priced at the Zero Lower Bound during the COVID-19 crisis.
3D Point Cloud Semantic Augmentation: Instance Segmentation of 360° Panoramas by Deep Learning Techniques
Authors: Karara Ghizlane , Hajji Rafika , Poux Florent
Published: September 2021

Semantic augmentation of 3D point clouds is a challenging problem with numerous real-world applications. While deep learning has revolutionised image segmentation and classification, its impact on point cloud is an active research field. In this paper, we propose an instance segmentation and augmentation of 3D point clouds using deep learning architectures. We show the potential of an indirect approach using 2D images and a Mask R-CNN (Region-Based Convolution Neural Network). Our method consists of four core steps. We first project the point cloud onto panoramic 2D images using three types of projections: spherical, cylindrical, and cubic. Next, we homogenise the resulting images to correct the artefacts and the empty pixels to be comparable to images available in common training libraries. These images are then used as input to the Mask R-CNN neural network, designed for 2D instance segmentation. Finally, the obtained predictions are reprojected to the point cloud to obtain the segmentation results. We link the results to a context-aware neural network to augment the semantics. Several tests were performed on different datasets to test the adequacy of the method and its potential for generalisation. The developed algorithm uses only the attributes X, Y, Z, and a projection centre (virtual camera) position as inputs.
Quantitative Contributions of Climate Change and Human Activities to Vegetation Changes in the Upper White Nile River
Authors: Ma Bo , Wang Shanshan , Mupenzi Christophe , Li Haoran , Ma Jianye , Li Zhanbin
Published: September 2021

Vegetation changes in the Upper White Nile River (UWNR) are of great significance to the maintenance of local livelihoods, the survival of wildlife, and the protection of species habitats. Based on the GIMMS NDVI3g and MODIS normalized difference vegetation index (NDVI) data, the temporal and spatial characteristics of vegetation changes in the UWNR from 1982 to 2020 were analyzed by a Theil-Sen median trend analysis and Mann-Kendall test. The future trend of vegetation was analyzed by the Hurst exponential method. A partial correlation analysis was used to analyze the relationship of the vegetation and climate factors, and a residual trend analysis was used to quantify the influence of climate change and human activities on vegetation change. The results indicated that the average NDVI value (0.75) of the UWNR from 1982 to 2020 was relatively high. The average coefficient of variation for the NDVI was 0.059, and the vegetation change was relatively stable. The vegetation in the UWNR increased 0.013/10 year on average, but the vegetation degradation in some areas was serious and mainly classified as agricultural land. The results of a future trend analysis showed that the vegetation in the UWNR is mainly negatively sustainable, and 62.54% of the vegetation will degrade in the future. The NDVI of the UWNR was more affected by temperature than by precipitation, especially on agricultural land and forestland, which were more negatively affected by warming. Climate change and human activities have an impact on vegetation changes, but the spatial distributions of the effects differ. The relative impact of human activities on vegetation change accounted for 64.5%, which was higher than that of climate change (35.5%). Human activities, such as the large proportion of agriculture, rapid population growth and the rapid development of urbanization were the main driving forces. Establishing a cross-border drought joint early warning mechanism, strengthening basic agricultural research, and changing traditional agricultural farming patterns may be effective measures to address food security and climate change and improve vegetation in the UWNR.
LiDAR-Based SLAM under Semantic Constraints in Dynamic Environments
Authors: Wang Weiqi , You Xiong , Zhang Xin , Chen Lingyu , Zhang Lantian , Liu Xu
Published: September 2021

Facing the realistic demands of the application environment of robots, the application of simultaneous localisation and mapping (SLAM) has gradually moved from static environments to complex dynamic environments, while traditional SLAM methods usually result in pose estimation deviations caused by errors in data association due to the interference of dynamic elements in the environment. This problem is effectively solved in the present study by proposing a SLAM approach based on light detection and ranging (LiDAR) under semantic constraints in dynamic environments. Four main modules are used for the projection of point cloud data, semantic segmentation, dynamic element screening, and semantic map construction. A LiDAR point cloud semantic segmentation network SANet based on a spatial attention mechanism is proposed, which significantly improves the real-time performance and accuracy of point cloud semantic segmentation. A dynamic element selection algorithm is designed and used with prior knowledge to significantly reduce the pose estimation deviations caused by SLAM dynamic elements. The results of experiments conducted on the public datasets SemanticKITTI, KITTI, and SemanticPOSS show that the accuracy and robustness of the proposed approach are significantly improved.
Measurements and Modelling of Aritificial Sky Brightness: Combining Remote Sensing from Satellites and Ground-Based Observations
Authors: Kolláth Zoltán , Száz Dénes , Kolláth Kornél
Published: September 2021

In recent decades, considerable research has been carried out both in measuring and modelling the brightness of the sky. Modelling is highly complex, as the properties of light emission (spatial and spectral distribution) are generally unknown, and the physical state of the atmosphere cannot be determined independently. The existing radiation transfer models lack the focus on light pollution and model only a narrow spectral range or do not consider realistic atmospheric circumstances. In this paper, we introduce a new Monte Carlo simulation for modelling light pollution, including the optical density of the atmosphere and multiple photon scattering, then we attempt to combine the available information of satellite and ground-based measurements to check the extent to which it is possible to verify our model. It is demonstrated that we need all the separate pieces of information to interpret the observations adequately.
Understanding the Links between LULC Changes and SUHI in Cities: Insights from Two-Decadal Studies (2001–2020)
Authors: Derdouri Ahmed , Wang Ruci , Murayama Yuji , Osaragi Toshihiro
Published: September 2021

An urban heat island (UHI) is a serious phenomenon associated with built environments and presents threats to human health. It is projected that UHI intensity will rise to record levels in the following decades due to rapid urban expansion, as two-thirds of the world population is expected to live in urban areas by 2050. Nevertheless, the last two decades have seen a considerable increase in the number of studies on surface UHI (SUHI)—a form of UHI quantified based on land surface temperature (LST) derived from satellite imagery—and its relationship with the land use/cover (LULC) changes. This surge has been facilitated by the availability of freely accessible five-decade archived remotely sensed data, the use of state-of-art analysis methods, and advancements in computing capabilities. The authors of this systematic review aimed to summarize, compare, and critically analyze multiple case studies—carried out from 2001 to 2020—in terms of various aspects: study area characteristics, data sources, methods for LULC classification and SUHI quantification, mechanisms of interaction coupled with linking techniques between SUHI intensity with LULC spatial and temporal changes, and proposed alleviation actions. The review could support decision-makers and pave the way for scholars to conduct future research, especially in vulnerable cities that have not been well studied.
Visible-Thermal Image Object Detection via the Combination of Illumination Conditions and Temperature Information
Authors: Zhou Hang , Sun Min , Ren Xiang , Wang Xiuyuan
Published: September 2021

Object detection plays an important role in autonomous driving, disaster rescue, robot navigation, intelligent video surveillance, and many other fields. Nonetheless, visible images are poor under weak illumination conditions, and thermal infrared images are noisy and have low resolution. Consequently, neither of these two data sources yields satisfactory results when used alone. While some scholars have combined visible and thermal images for object detection, most did not consider the illumination conditions and the different contributions of diverse data sources to the results. In addition, few studies have made use of the temperature characteristics of thermal images. Therefore, in the present study, visible and thermal images are utilized as the dataset, and RetinaNet is used as the baseline to fuse features from different data sources for object detection. Moreover, a dynamic weight fusion method, which is based on channel attention according to different illumination conditions, is used in the fusion component, and the channel attention and a priori temperature mask (CAPTM) module is proposed; the CAPTM can be applied to a deep learning network as a priori knowledge and maximizes the advantage of temperature information from thermal images. The main innovations of the present research include the following: (1) the consideration of different illumination conditions and the use of different fusion parameters for different conditions in the feature fusion of visible and thermal images; (2) the dynamic fusion of different data sources in the feature fusion of visible and thermal images; (3) the use of temperature information as a priori knowledge (CAPTM) in feature extraction. To a certain extent, the proposed methods improve the accuracy of object detection at night or under other weak illumination conditions and with a single data source. Compared with the state-of-the-art (SOTA) method, the proposed method is found to achieve superior detection accuracy with an overall mean average precision (mAP) improvement of 0.69%, including an AP improvement of 2.55% for the detection of the Person category. The results demonstrate the effectiveness of the research methods for object detection, especially temperature information-rich object detection.
A National-Scale 1-km Resolution PM2.5 Estimation Model over Japan Using MAIAC AOD and a Two-Stage Random Forest Model
Authors: Jung Chau-Ren , Chen Wei-Ting , Nakayama Shoji F.
Published: September 2021

Satellite-based models for estimating concentrations of particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) have seldom been developed in islands with complex topography over the monsoon area, where the transport of PM2.5 is influenced by both the synoptic-scale winds and local-scale circulations compared with the continental regions. We validated Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol optical depth (AOD) with ground observations in Japan and developed a 1-km-resolution national-scale model between 2011 and 2016 to estimate daily PM2.5 concentrations. A two-stage random forest model integrating MAIAC AOD with meteorological variables and land use data was applied to develop the model. The first-stage random forest model was used to impute the missing AOD values. The second-stage random forest model was then utilised to estimate ground PM2.5 concentrations. Ten-fold cross-validation was performed to evaluate the model performance. There was good consistency between MAIAC AOD and ground truth in Japan (correlation coefficient = 0.82 and 74.62% of data falling within the expected error). For model training, the model showed a training coefficient of determination (R2) of 0.98 and a root mean square error (RMSE) of 1.22 μg/m3. For the 10-fold cross-validation, the cross-validation R2 and RMSE of the model were 0.86 and 3.02 μg/m3, respectively. A subsite validation was used to validate the model at the grids overlapping with the AERONET sites, and the model performance was excellent at these sites with a validation R2 (RMSE) of 0.94 (1.78 μg/m3). Additionally, the model performance increased as increased AOD coverage. The top-ten important predictors for estimating ground PM2.5 concentrations were day of the year, temperature, AOD, relative humidity, 10-m-height zonal wind, 10-m-height meridional wind, boundary layer height, precipitation, surface pressure, and population density. MAIAC AOD showed high retrieval accuracy in Japan. The performance of the satellite-based model was excellent, which showed that PM2.5 estimates derived from the model were reliable and accurate. These estimates can be used to assess both the short-term and long-term effects of PM2.5 on health outcomes in epidemiological studies.
Prototyping a Generic Algorithm for Crop Parameter Retrieval across the Season Using Radiative Transfer Model Inversion and Sentinel-2 Satellite Observations
Authors: Tomíček Jiří , Mišurec Jan , Lukeš Petr
Published: September 2021

In this study, Sentinel-2 data were used for the retrieval of three key biophysical parameters of crops: leaf area index (LAI), leaf chlorophyll content (LCC), and leaf water content (LWC) for dominant crop types in the Czech Republic, including winter wheat (Triticum aestivum), spring barley (Hordeum vulgare), winter rapeseed (Brassica napus subsp. napus), alfalfa (Medicago sativa), sugar beet (Beta vulgaris), and corn (Zea mays subsp. Mays) in different stages of crop development. Artificial neural networks were applied in combination with an approach using look-up tables that is based on PROSAIL simulations to retrieve the biophysical properties tailored for each crop type. Crop-specific PROSAIL model optimization and validation were based upon a large dataset of in situ measurements collected in 2017 and 2018 in lowland of Central Bohemia region. For LCC and LAI, respectively, low relative root mean square error (rRMSE; 25%, 37%) was achieved. Additionally, a relatively strong correlation with in situ measurements (r = 0.80) was obtained for LAI. On the contrary, the results of the LWC parameter retrieval proved to be unsatisfactory. We have developed a generic tool for biophysical monitoring of agricultural crops based on the interpretation of Sentinel-2 satellite data by inversion of the radiation transfer model. The resulting crop condition maps can serve as precision agriculture inputs for selective fertilizer and irrigation application as well as for yield potential assessment.
Improved Photoresponse Characteristics of a ZnO-Based UV Photodetector by the Formation of an Amorphous SnO2 Shell Layer
Authors: Yoo Junhyuk , Jung Uijin , Jung Bomseumin , Shen Wenhu , Park Jinsub
Published: September 2021

Although ZnO nanostructure-based photodetectors feature a well-established system, they still present difficulties when being used in practical situations due to their slow response time. In this study, we report on how forming an amorphous SnO2 (a-SnO2) shell layer on ZnO nanorods (NRs) enhances the photoresponse speed of a ZnO-based UV photodetector (UV PD). Our suggested UV PD, consisting of a ZnO/a-SnO2 NRs core–shell structure, shows a rise time that is 26 times faster than a UV PD with bare ZnO NRs under 365 nm UV irradiation. In addition, the light responsivity of the ZnO/SnO2 NRs PD simultaneously increases by 3.1 times, which can be attributed to the passivation effects of the coated a-SnO2 shell layer. With a wide bandgap (~4.5 eV), the a-SnO2 shell layer can successfully suppress the oxygen-mediated process on the ZnO NRs surface, improving the photoresponse properties. Therefore, with a fast photoresponse speed and a low fabrication temperature, our as-synthesized, a-SnO2-coated ZnO core–shell structure qualifies as a candidate for ZnO-based PDs.
ConAnomaly: Content-Based Anomaly Detection for System Logs
Authors: Lv Dan , Luktarhan Nurbol , Chen Yiyong
Published: September 2021

Enterprise systems typically produce a large number of logs to record runtime states and important events. Log anomaly detection is efficient for business management and system maintenance. Most existing log-based anomaly detection methods use log parser to get log event indexes or event templates and then utilize machine learning methods to detect anomalies. However, these methods cannot handle unknown log types and do not take advantage of the log semantic information. In this article, we propose ConAnomaly, a log-based anomaly detection model composed of a log sequence encoder (log2vec) and multi-layer Long Short Term Memory Network (LSTM). We designed log2vec based on the Word2vec model, which first vectorized the words in the log content, then deleted the invalid words through part of speech tagging, and finally obtained the sequence vector by the weighted average method. In this way, ConAnomaly not only captures semantic information in the log but also leverages log sequential relationships. We evaluate our proposed approach on two log datasets. Our experimental results show that ConAnomaly has good stability and can deal with unseen log types to a certain extent, and it provides better performance than most log-based anomaly detection methods.
Development and Validation of a Railway Safety System for Nordic Trains in Isolated Territories of Northern Quebec Based on IEEE 802.15.4 Protocol
Authors: Ferrier Laurent , Ibrahim Hussein , Issa Mohamad , Ilinca Adrian
Published: September 2021

Connected objects are deployed all over the world. Thus, they are contributing to improving communications. In urban areas, technological challenges are gradually being overcome, and advances in this area are exponential. Unfortunately, isolated territories such as northern Quebec do not beneficiate from this technological progress. Yet, northern Quebec relies on abundant natural resources, with notably its huge hydroelectric dams and iron mines, and therefore, the region’s economic life revolves essentially around the exploitation of these resources and is heavily reliant on rail transportation. However, according to Transport Canada, 1246 railroad accidents were reported in 2019 to the Transportation Safety Board (TSB). Thirty-eight people described as trespassers lost their lives, and five railroad employees were fatally injured. In this context, we present the implementation of a security system in an isolated environment for employees intervening on the railroad track to warn them of the imminent arrival of a train. Due to the context of the isolated environment, i.e., without an electrical network, without internet, and without an LTE network, a solution for employees has been developed using a Zigbee telecommunication system and a connected watch. A case study on a train operating in a remote and isolated area in northern Quebec is presented to validate the performance of the proposed system based on an open-source and customizable solution.
Error Analysis of the Combined-Scan High-Speed Atomic Force Microscopy
Authors: Liu Lu , Kong Ming , Wu Sen , Xu Xinke , Wang Daodang
Published: September 2021

A combined tip-sample scanning architecture can improve the imaging speed of atomic force microscopy (AFM). However, the nonorthogonality between the three scanners and the nonideal response of each scanner cause measurement errors. In this article, the authors systematically analyze the influence of the installation and response errors of the combined scanning architecture. The experimental results show that when the probe in the homemade high-speed AFM moves with the Z-scanner, the spot position on the four-quadrant detector changes, thus introducing measurement error. Comparing the experimental results with the numerical and theoretical results shows that the undesired motion of the Z-scanner introduces a large error. The authors believe that this significant error occurs because the piezoelectric actuator not only stretches along the polarization direction but also swings under nonuniform multifield coupling. This article proposes a direction for further optimizing the instrument and provides design ideas for similar high-speed atomic force microscopes.
Immigrant Health Inequities: Exposing Diversions and White Supremacy
Authors: García San Juanita , Trummel Taylor , Cornejo Monica , Maldonado Katherine , Ojeda Ana , Flores Humberto , Link Bruce G.
Published: September 2021

Diversions occur when research disregards the inequality-generating actions of advantaged groups and instead focuses attention on the actions and behaviors of disadvantaged groups. We incorporate important insights from COVID-19 to illustrate historical and contemporary examples of diversions. This paper highlights US immigrant health inequities—a burgeoning subfield within the broader health inequalities canon—to explore: (1) if and how diversions appear in immigrant health studies; (2) how often white supremacy and intersectionality are explicitly named in grants, publicly available datasets, and published research. The data derive from: NIH R01 grants (17), publicly available datasets that focus on immigrant health (7), and research published in three health journals (14). Using a qualitative content analysis approach, we analyzed these data as evidence concerning the knowledge production cycle, and investigate whether: (a) the role of advantaged groups in generating inequalities is explicitly mentioned; (b) disadvantaged groups are asked about discriminatory actions perpetuated by advantaged groups; (c) health inequalities are placed on the conditions of disadvantaged groups; (d) if white supremacy and intersectionality are explicitly mentioned in grants, publicly available datasets, and research articles. The findings demonstrate the prevalence of diversions in immigrant health research, given an overemphasis on health behaviors and cultural explanations towards explaining immigrant health inequities. There was no mention of white supremacy across the knowledge production cycle. Intersectionality was mentioned once in a research article. We argue that understanding white supremacy’s role in the knowledge production cycle illuminates how diversions occur and prevail. We provide suggestions on moving away from diversionary research, toward adopting an intersectional approach of the study of immigrant health inequities.
Intra- and Inter-Limb Strength Asymmetry in Soccer: A Comparison of Professional and Under-18 Players
Authors: Bishop Chris , Coratella Giuseppe , Beato Marco
Published: September 2021

(1) Background: the present study examined the isokinetic peak torque exerted by both knee extensors and flexors, anterior–posterior imbalance and the magnitude and direction of inter-limb asymmetry in professional and academy soccer players. (2) Methods: one hundred soccer players (professional = 50, elite academy = 50) volunteered to take part in this investigation. An isokinetic dynamometer was used to measure the knee extensor (quadriceps) and flexors muscle (hamstrings) torques of the limbs as well as inter-limb asymmetries—using a standard percentage difference equation. (3) Results: professional players exhibited significantly greater (effect size [ES] = large) strength levels in the quadriceps and hamstrings under both testing conditions, significantly higher (small to moderate) intra-limb ratio values for 60°·s−1 but not for the 300°·s−1 test condition, significantly (small to moderate) lower inter-limb asymmetry values for all test conditions, with the exception of the hamstrings at 60°·s−1 and the direction of asymmetry was poor to slight, indicating that limb dominance was rarely the same between groups. (4) Conclusions: this study shows that isokinetic assessments, i.e., peak torque exerted by both knee extensors and flexors and intra-limb ratio, and the subsequent inter-limb asymmetry, i.e., magnitude and direction, can differentiate between professional and academy soccer players.
Workforce Development and Multiagency Collaborations: A Presentation of Two Case Studies in Child Welfare
Authors: McDonald Chad , Campbell Kristine A. , Benson Cole , Davis Matthew J. , Frost Caren J.
Published: September 2021

Background: Two disciplines that work in the child welfare arena, social welfare and healthcare, are crucial for addressing families’ and children’s needs in social, emotional, and physical healthcare situations. How child welfare workers are trained and how healthcare teams collaborate with other stakeholders in the child welfare system is crucial in meeting and sustaining the needs of families and children. Methods: We demonstrate two case examples, one focusing on enhanced learning tools through virtual reality (VR) and the other on strengthening collaborations between healthcare teams and the child welfare system. Results: For the VR training tool, 79% of participants indicated they would recommend the VR learning tool as effective in developing skills in the child welfare workforce. In response to the learning collaborative project, child welfare participants reported positive impressions regarding collaborative practices while identifying system-level barriers to implementation. Conclusion: Findings from these two case studies provide insights from which to consider system development for designing and implementing sustainable improvements in child welfare approaches to families and children referred for suspected maltreatment.
Use of Remote Sensing to Assess the Water-Saving Effect of Winter Wheat Fallow
Authors: Zhai Liang , Gu Xianghui , Feng Yajing , Wu Dongqing , Wang Tengbo
Published: September 2021

Winter wheat fallow policy has a greater effect on water resource management, and the water-saving effect in the fallow process of winter wheat can provide data support for precise water resource utilization planning. In order to evaluate the water resource consumption of winter wheat and the related effect from winter wheat fallow, this study searched the changing trends of cultivated land evapotranspiration under five different scenarios through the object-oriented extraction method and a SEBS model based on multi-source data. The results indicated that the evapotranspiration during winter wheat growing period was higher than that of winter wheat fallow land, and there was no big difference in evapotranspiration between the fallow land during harvesting and the emergence of new crops. The evapotranspiration of winter wheat was higher than that of various fallow land, and the evapotranspiration of abandoned land was higher than other fallow land in the winter wheat growing season. From this point, this study concludes that the fallow land policy can effectively reduce evapotranspiration during the growing of winter wheat, which is conducive to the sustainable exploiting of water resources.
Volatility and Risk in the Energy Market: A Trade Network Approach
Authors: Creamer Germán G. , Ben-Zvi Tal
Published: September 2021

This paper evaluates the effect of energy trade networks on the price volatility of coal, oil, natural gas, and electricity. This research conducts a longitudinal analysis using a time series of static coal trade networks to generate a dynamic trade network. It uses the component causality index as a leading indicator of the price volatility of the energy market. This research finds out that the component causality index, based on degree centrality, anticipates or moves together with coal volatility and, to a lesser degree, with natural gas and electricity volatility for the period 1998–2014. The proposed index could be integrated into a risk management system for investors and regulators. The broad impact of this research lies in the understanding of mechanisms of the instability and risk of the energy sector as a result of a complex interaction of the network of producers and traders.
KOH-Based Modified Solvay Process for Removing Na Ions from High Salinity Reject Brine at High Temperatures
Authors: Mourad Aya A-H. I. , Mohammad Ameera F. , Al-Marzouqi Ali H. , El-Naas Muftah H. , Al-Marzouqi Mohamed H. , Altarawneh Mohammednoor
Published: September 2021

The traditional Solvay process and other modifications that are based on different types of alkaline material and waste promise to be effective in the reduction of reject brine salinity and the capture of CO2. These processes, however, require low temperatures (10–20 °C) to increase the solubility of CO2 and enhance the precipitation of metallic salts, while reject brine is usually discharged from desalination plants at relatively high temperatures (40–55 °C). A modified Solvay process based on potassium hydroxide (KOH) has emerged as a promising technique for simultaneously capturing carbon dioxide (CO2) and reducing ions from reject brine in a combined reaction. In this study, the ability of the KOH-based Solvay process to reduce brine salinity at relatively high temperatures was investigated. The impact of different operating conditions, including pressure, KOH concentration, temperature, and CO2 gas flowrate, on CO2 uptake and ion removal was investigated and optimized. The optimization was performed using the response surface methodology based on a central composite design. A CO2 uptake of 0.50 g CO2/g KOH and maximum removal rates of sodium (Na+), chloride (Cl−), calcium (Ca2+), and magnesium (Mg2+) of 45.6%, 29.8%, 100%, and 91.2%, respectively, were obtained at a gauge pressure, gas flowrate, and KOH concentration of 2 bar, 776 mL/min, and 30 g/L, respectively, and at high temperature of 50 °C. These results confirm the effectiveness of the process in salinity reduction at a relatively high temperature that is near the actual reject brine temperature without prior cooling. The structural and chemical characteristics of the produced solids were investigated, confirming the presence of valuable products such as sodium bicarbonate (NaHCO3), potassium bicarbonate (KHCO3) and potassium chloride (KCl).
Citizen Science in Sweden’s Stigmatized Neighborhoods
Authors: Fell Terence , Rydenstam Tove , Buli Benti Geleta , King Abby C. , Bälter Katarina
Published: September 2021

Based on the synthesis of outside versus inside perspectives, this paper weighs the positive attributes of the so-called deprived place against its negative media image. Applying the concept of territorial stigmatization, small-scale citizen science was conducted to gain a unique understanding of the Swedish neighborhood from within. With the United Nations’ Sustainable Development Goal 11 in mind, this approach enables researchers to reach otherwise difficult to access young urban outcasts and probe the potential to overcome their community’s lack of political influence. An overlap between local media narratives and urban outcasts’ perceptions of “drug and crime” and “football and school” was revealed. Yet, this first-generation study also painted a somewhat different picture of the stigmatized neighborhood, supplying new insights about places that matter most for marginalized young males. In this Swedish case, their pictures revealed that the local corner market, football court and youth club act as an antidote for the effects of stigmatization. This Our Voice citizen science initiative proved to be a good measure of two communities’ abilities to withstand stigmatization, which is either tainted by false perceptions from the outside or weakened by crime from within. Finally, attempting to bypass structural discrimination, citizen scientists’ findings and researchers’ conclusions were made available to students, colleagues and guests at a poster presentation hosted by Mälardalen University and to concerned politicians from Eskilstuna City Hall as well as the broader public via a local Swedish television station.
UAV Based Spatiotemporal Analysis of the 2019–2020 New South Wales Bushfires
Authors: Ullah Fahim , Khan Sara Imran , Munawar Hafiz Suliman , Qadir Zakria , Qayyum Siddra
Published: September 2021

Bushfires have been a key concern for countries such as Australia for a long time. These must be mitigated to eradicate the associated harmful effects on the climate and to have a sustainable and healthy environment for wildlife. The current study investigates the 2019–2020 bushfires in New South Wales (NSW) Australia. The bush fires are mapped using Geographical Information Systems (GIS) and remote sensing, the hotpots are monitored, and damage is assessed. Further, an Unmanned Aerial Vehicles (UAV)-based bushfire mitigation framework is presented where the bushfires can be mapped and monitored instantly using UAV swarms. For the GIS and remote sensing, datasets of the Australian Bureau of Meteorology and VIIRS fire data products are used, whereas the paths of UAVs are optimized using the Particle Swarm Optimization (PSO) algorithm. The mapping results of 2019–2020 NSW bushfires show that 50% of the national parks of NSW were impacted by the fires, resulting in damage to 2.5 million hectares of land. The fires are highly clustered towards the north and southeastern cities of NSW and its border region with Victoria. The hotspots are in the Deua, Kosciu Sako, Wollemi, and Yengo National Parks. The current study is the first step towards addressing a key issue of bushfire disasters, in the Australian context, that can be adopted by its Rural Fire Service (RFS), before the next fire season, to instantly map, assess, and subsequently mitigate the bushfire disasters. This will help move towards a smart and sustainable environment.
How Does Inter-Organizational Relational Governance Propel Firms’ Open Innovation? A Conditional Process Analysis
Authors: Liu Liu , Zhang Hua
Published: September 2021

To successfully implement open innovation, it is essential for firms to build close relationships with external innovators. Although many studies have suggested that relational governance, also known as social control, can effectively manage inter-organizational relationships, the role of relational governance on firms’ open innovation remains equivocal. Using a survey of 318 manufacturing firms from China, this study used a conditional process model to analyze the interplay of relational governance, open innovation, and firms’ innovation performance and examine the influence of environmental dynamism. The results demonstrate that relational governance has a positive impact on firms’ open innovation (both inbound and outbound) and innovation performance. We also found that open innovation mediates the association between relational governance and firms’ innovation performance. A high level of environmental dynamism enhances the indirect effect of relational governance on firms’ innovation performance through open innovation. These findings help clarify the interaction between relational governance and open innovation. They also deepen understanding of the value co-creation principle of open innovation.
A Comprehensive Review on Biofuels from Oil Palm Empty Bunch (EFB): Current Status, Potential, Barriers and Way Forward
Authors: Dolah Rozzeta , Karnik Rohit , Hamdan Halimaton
Published: September 2021

Biomass is an important renewable energy resource which primarily contributes to heating and cooling end use sectors. It is also a promising alternative source of biofuels to replace the depleting supply of fossil fuels. Surprisingly, few writers have been able to draw on the feedstock significance for oil palm empty fruit bunch (EFB) as the biomass resource for biofuels compared to the other types of biomass waste. Therefore, this paper presents a comprehensive review of EFB as a biomass resource presented in four major parts. First, the introduction covers the demand for bio-oil and describes the different kinds of feedstock, the relevance and potential of EFB biomass. Second, the characteristics of biomass are explained before it is upgraded as biofuel, drawing similarities and contrasts between EFB and other sources of biomass. Pyrolysis processes and reactors used for EFB conversion are described, and the factors affecting the bio-oil yield and quality are discussed. Major reactor parameters are summarized and reactor optimization is discussed. Third, comparison on the properties of the bio-oil vs. petroleum in transportation, power generation, and heating are compared followed by prioritizing the bio-oil properties from the most to least critical, revealing the most promising methods for upgrading. Fourth, the environmental impact, including CO2 emission, of the use of EFB as a promising renewable energy resource and a cleaner alternative fuel is recommended. This paper has comprehensively reviewed the conversion of oil palm empty fruit bunches into biofuels, including the similarities and differences between biomasses, the best reactors, its comparison with fossil fuels, and bio-oil upgrading methods. The upgrading mapping matrix is created to present the best upgrading strategies for the optimum quality of biofuels. This paper serves as a one-stop center for EFB conversion into biofuels.