bluuebunny/crossref_metadata_2025 huggingface dataset:
Acute Effects of Muay Thai on Blood Pressure and Heart Rate in Adolescents with Overweight/Obesity
Authors: Saraiva Bruna Thamyres Ciccotti , Prado Wagner Luiz do , Vanderlei Luiz Carlos Marques , Milanez Vinícius Flávio , Damato Tatiana Machado de Mattos , Santos Amanda Barbosa dos , Tebar William Rodrigues , Christofaro Diego Giulliano Destro
Published: February 2022

Background: To analyze the effects of a single session of Muay Thai (MT) on blood pressure and heart rate in adolescents with overweight/obesity. Methods: A total of 27 adolescents with overweight/obesity (12.85 ± 2.08 years), 13 girls and 14 boys, performed 60 min of MT composed of general and modality-specific exercises, as well as combat at the end. Anthropometric measurements were taken and body fat (BF) was measured using DEXA. Excess weight was attested via the body mass index (BMI) and BF. Systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) were measured by an oscillometric device before, immediately after MT, and 10, 20 and 30 min of recovery. Results: SBP decreased in boys after 20 min (d = −0.73) and 30 min (d = −0.78) of recovery, and in girls after 20 min (d = −0.56). DBP decreased in girls immediately after the session (d = −0.90) and after 10 min (d = −1.00); for the total sample, when analyzed across sex, DBP decreased immediately after the session (d = −0.70) and after 10 min (d = −0.52). No effect of MT on HR recovery was observed. Conclusions: A single MT session induces positive changes in blood pressure, with a greater impact on SBP in girls.
Characterizations and Use of Recycled Optical Components for Polarizing Phase-Shifting Interferometry Applications
Authors: Islas-Islas Juan M. , Reséndiz-López Germán , Ortega-Mendoza José G. , García-Lechuga Luis , Quiroz Adolfo , Serrano-García David-Ignacio , Canales-Pacheco Benito , Toto-Arellano Noel-Ivan
Published: February 2022

In this research, we report using optical components such as cubic beam splitters, lenses, diffraction gratings, and mirrors from broken, obsolete, or disused electronic devices to implement a simultaneous polarization-based phase-shifting interferometric system. The system is composed of a polarized Mach–Zehnder interferometer (PMZI) which generates a sample pattern coupled to a 4f imaging system with a diffraction grating placed on its Fourier plane. Such a diffractive element replicates the pattern generated by the PMZI, and each replica is centered and modulated by each diffraction order generated by the grating. The corresponding individual phase shifts are controlled by placing linear polarizers with known angles in front of each replica. Experimental results are presented using several phase samples such as an oil drop, a pseudoscorpion claw, a microarthropod, and red blood cells. In addition, a comparison of the retrieved phase was conducted by employing two different phase demodulation algorithms.
Antihyperglycemic Effects of Salvia polystachya Cav. and Its Terpenoids: α-Glucosidase and SGLT1 Inhibitors
Authors: Ortega Rocio , Valdés Miguel , Alarcón-Aguilar Francisco J. , Fortis-Barrera Ángeles , Barbosa Elizabeth , Velazquez Claudia , Calzada Fernando
Published: February 2022

The antihyperglycemic activity of ethanolic extract from Salvia polystachya (EESpS) and its products was evaluated using in vivo, ex vivo and in silico assays; additionally, an acute toxicity assay was evaluated. EESpS was classified as a nontoxic class 5 drug. EESpS, ethyl acetate fraction (EtOAcFr), secondary-6-fraction (SeFr6), ursolic acid (UA), and oleanolic acid (OA) reduced the hyperglycemia in DM2 mice. α-glucosidase inhibition was evaluated with oral sucrose and starch tolerance tests (OSuTT and OStTT), an intestinal sucrose hydrolysis (ISH) assay and molecular docking studies using acarbose as control. SGLT1 inhibition was evaluated with oral glucose and galactose tolerance tests (OGTT and OGaTT), an intestinal glucose absorption (IGA) assay and molecular docking studies using canagliflozin as the control. During the carbohydrate tolerance tests, all the treatments reduced the postprandial peak, similar to the control drugs. During the ISH, IC50 values of 739.9 and 726.3 µM for UA and OA, respectively, were calculated. During the IGA, IC50 values of 966.6 and 849.3 for UA, OA respectively, were calculated. Finally, during the molecular docking studies, UA and OA showed ∆G values of −6.41 and −5.48 kcal/mol−1, respectively, on α-glucosidase enzymes. During SGLT1, UA and OA showed ∆G values of −10.55 and −9.65, respectively.
A Core Set of Snap Bean Genotypes Established by Phenotyping a Large Panel Collected in Europe
Authors: García-Fernández Carmen , Jurado Maria , Campa Ana , Brezeanu Creola , Geffroy Valérie , Bitocchi Elena , Papa Roberto , Ferreira Juan Jose
Published: February 2022

Snap beans are a group of bean cultivars grown for their edible immature pods. The objective of this work was to characterize the diversity of pod phenotypes in a snap bean panel (SBP), comprising 311 lines collected in Europe, and establish a core set (Core-SBP) with the maximum diversity of pod phenotypes. Phenotyping of the SBP was carried out over two seasons based on 14 quantitative pod dimension traits along with three qualitative traits: pod color, seed coat color, and growth habit. Phenotypes were grouped into 54 classes using a hierarchical method, and a Core-SBP with one line per phenotype class was established. A further field-based evaluation of the Core-SBP revealed higher diversity index values than those obtained for the SBP. The Core-SBP was also genotyped using 24 breeder-friendly DNA markers tagging 21 genomic regions previously associated with pod trait control. Significant marker-trait associations were found for 11 of the 21 analyzed regions as well as the locus fin. The established Core-SBP was a first attempt to classify snap bean cultivars based on pod morphology and constituted a valuable source of characteristics for future breeding programs and genetic analysis.
Genome-Wide Identification of Cotton (Gossypium spp.) Glycerol-3-Phosphate Dehydrogenase (GPDH) Family Members and the Role of GhGPDH5 in Response to Drought Stress
Authors: Sun Jialiang , Cui Hua , Wu Bingjie , Wang Weipeng , Yang Qiuyue , Zhang Yaxin , Yang Song , Zhao Yuping , Xu Dongbei , Liu Guoxiang , Qin Tengfei
Published: February 2022

Glycerol-3-phosphate dehydrogenase (GPDH) is a key enzyme in plant glycerol synthesis and metabolism, and plays an important role in plant resistance to abiotic stress. Here, we identified 6, 7, 14 and 14 GPDH genes derived from Gossypium arboreum, Gossypium raimondii, Gossypium barbadense and Gossypium hirsutum, respectively. Phylogenetic analysis assigned these genes into three classes, and most of the genes within the family were expanded by whole-genome duplication (WGD) and segmental duplications. Moreover, determination of the nonsynonymous substitution rate/synonymous substitution rate (Ka/Ks) ratio showed that the GPDH had an evolutionary preference for purifying selection. Transcriptome data revealed that GPDH genes were more active in the early stages of fiber development. Additionally, numerous stress-related cis-elements were identified in the potential promoter region. Then, a protein–protein-interaction (PPI) network of GPDH5 in G. hirsutum was constructed. In addition, we predicted 30 underlying miRNAs in G. hirsutum. Functional validation results indicated that silencing GhGPDH5 diminished drought tolerance in the upland cotton TM-1 line. In summary, this study provides a fundamental understanding of the GPDH gene family in cotton, GhGPDH5 exerts a positive effect during drought stress and is potentially involved in stomatal closure movements.
Inline Quality Control through Optical Deep Learning-Based Porosity Determination for Powder Bed Fusion of Polymers
Authors: Schlicht Samuel , Jaksch Andreas , Drummer Dietmar
Published: February 2022

Powder bed fusion of thermoplastic polymers is a powder based additive manufacturing process that allows for manufacturing individualized components with high geometric freedom. Despite achieving higher mechanical properties compared to other additive manufacturing processes, statistical variations in part properties and the occurrence of defects cannot be avoided systematically. In this paper, a novel method for the inline assessment of part porosity is proposed in order to detect and to compensate for inherent limitations in the reproducibility of manufactured parts. The proposed approach is based on monitoring the parameter-specific decay of the optical melt pool radiance during the melting process, influenced by a time dependency of optical scattering within the melt pool. The underlying methodology compromises the regression of the time-dependent optical melt pool properties, assessed in visible light using conventional camera technology, and the resulting part properties by means of artificial neural networks. By applying deep residual neural networks for correlating time-resolved optical process properties and the corresponding part porosity, an inline assessment of the spatially resolved part porosity can be achieved. The authors demonstrate the suitability of the proposed approach for the inline porosity assessment of varying part geometries, processing parameters, and material aging states, using Polyamide 12. Consequently, the approach represents a methodological foundation for novel monitoring solutions, the enhanced understanding of parameter–material interactions and the inline-development of novel material systems in powder bed fusion of polymers.
Steelmaking Process Optimised through a Decision Support System Aided by Self-Learning Machine Learning
Authors: Andreiana Doru Stefan , Acevedo Galicia Luis Enrique , Ollila Seppo , Leyva Guerrero Carlos , Ojeda Roldán Álvaro , Dorado Navas Fernando , del Real Torres Alejandro
Published: February 2022

This paper presents the application of a reinforcement learning (RL) algorithm, concretely Q-Learning, as the core of a decision support system (DSS) for a steelmaking subprocess, the Composition Adjustment by Sealed Argon-bubbling with Oxygen Blowing (CAS-OB) from the SSAB Raahe steel plant. Since many CAS-OB actions are selected based on operator experience, this research aims to develop a DSS to assist the operator in taking the proper decisions during the process, especially less experienced operators. The DSS is intended to supports the operators in real-time during the process to facilitate their work and optimise the process, improving material and energy efficiency, thus increasing the operation’s sustainability. The objective is that the algorithm learns the process based only on raw data from the CAS-OB historical database, and on rewards set according to the objectives. Finally, the DSS was tested and validated by a developer engineer from the CAS-OB steelmaking plant. The results show that the algorithm successfully learns the process, recommending the same actions as those taken by the operator 69.23% of the time. The algorithm also suggests a better option in 30.76% of the remaining cases. Thanks to the DSS, the heat rejection due to wrong composition is reduced by 4%, and temperature accuracy is increased to 83.33%. These improvements resulted in an estimated reduction of 2% in CO2 emissions, 0.5% in energy consumption and 1.5% in costs. Additionally, actions taken based on the operator’s experience are incorporated into the DSS knowledge, facilitating the integration of operators with lower experience in the process.
Individual Tree Crown Delineation Method Based on Multi-Criteria Graph Using Geometric and Spectral Information: Application to Several Temperate Forest Sites
Authors: Deluzet Matthieu , Erudel Thierry , Briottet Xavier , Sheeren David , Fabre Sophie
Published: February 2022

Individual tree crown (ITC) delineation in temperate forests is challenging owing to the presence of broadleaved species with overlapping crowns. Mixed coniferous/deciduous forests with characteristics that differ with the type of tree thus require a flexible method of delineation. The ITC delineation method based on the multi-criteria graph (MCG-Tree) addresses this problem in temperate monospecific or mixed forests by combining geometric and spectral information. The method was used to segment trees in three temperate forest sites with different characteristics (tree types, species distribution, planted or natural forest). Compared with a state-of-the-art watershed segmentation approach, our method increased delineation performance by up to 25%. Our results showed that the main geometric criterion to improve delineation quality is related to the crown radius (performance improvement around 8%). Coniferous/deciduous classification automatically adapts the MCG-Tree criteria to the type of tree. Promising results are then obtained to improve delineation performance for mixed forests.
Where Anthropogenic Activity Occurs, Anthropogenic Activity Dominates Vegetation Net Primary Productivity Change
Authors: Xie Conghui , Wu Shixin , Zhuang Qingwei , Zhang Zihui , Hou Guanyu , Luo Geping , Hu Zengyun
Published: February 2022

Anthropogenic activities and climate change affect the type, structure and function of ecosystems, resulting in important changes in vegetation net primary productivity (NPP). Therefore, in this study we used the vegetation photosynthesis model (VPM) to reveal the spatiotemporal variations in NPP in Xinjiang from 2000 to 2019. The impacts of climate change and anthropogenic activities on NPP changes were quantified and separated by the residual analysis-control variables (RES-CON) method. The results showed that the average NPP in Xinjiang increased by 17.77% from 2000 to 2019. Anthropogenic activities and climate change generally had a positive impact on NPP from 2000 to 2019. The most important anthropogenic activity was land use and land cover (LULC) transformation from grass to arable land, which significantly increased vegetation productivity. Regarding climate change, precipitation has played a significant role in promoting the productivity of vegetation. Overall, the average contribution of climate change (temperature and precipitation) to NPP variation (21.44%) is much greater than the contribution of anthropogenic activities (3.46%), but in areas where anthropogenic activities occur, the average contribution of anthropogenic activities to NPP variation (75.01%) is much greater than the average contribution of climate change (15.53%). Where there are no anthropogenic activities, the average contribution of climate change to NPP variation is 21.72%. In summary, anthropogenic activities are the main driver of NPP variation in areas where anthropogenic activities occur, while the total area in Xinjiang where climate change is the most important driver is larger than the total area where anthropogenic activities are the dominant driver.
Evaluation of Sentinel-2/MSI Atmospheric Correction Algorithms over Two Contrasted French Coastal Waters
Authors: Bui Quang-Tu , Jamet Cédric , Vantrepotte Vincent , Mériaux Xavier , Cauvin Arnaud , Mograne Mohamed Abdelillah
Published: February 2022

The Sentinel-2A and Sentinel-2B satellites, with on-board Multi-Spectral Instrument (MSI), and launched on 23 June 2015 and 7 March 2017, respectively, are very useful tools for studying ocean color, even if they were designed for land and vegetation applications. However, the use of these satellites requires a process called “atmospheric correction”. This process aims to remove the contribution of the atmosphere from the total top of atmosphere reflectance measured by the remote sensors. For the purpose of assessing this processing, seven atmospheric correction algorithms have been compared over two French coastal regions (English Channel and French Guiana): Image correction for atmospheric effects (iCOR), Atmospheric correction for OLI ‘lite’ (ACOLITE), Case 2 Regional Coast Colour (C2RCC), Sentinel 2 Correction (Sen2Cor), Polynomial-based algorithm applied to MERIS (Polymer), the standard NASA atmospheric correction (NASA-AC) and the Ocean Color Simultaneous Marine and Aerosol Retrieval Tool (OC-SMART). The satellite-estimated remote-sensing reflectances were spatially and temporally matched with in situ measurements collected by an ASD FieldSpec4 spectrophotometer. Results, based on 28 potential individual match-ups, showed that the best performance processor is OC-SMART with the highest values for the total score Stot (16.89) and for the coefficient of correlation R2 (ranging from 0.69 at 443 nm to 0.92 at 665 nm). iCOR and Sen2Cor show the less accurate performances with total score Stot values of 2.01 and 7.70, respectively. Since the size of the in situ observation platform can be significant compared to the pixel resolution of MSI onboard Sentinel-2, it can create bias in the pixel extraction process. Thus, to study this impact, we used different methods of pixel extraction. However, there are no significant changes in results; some future research may be necessary.
Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis
Authors: Benson Lauren C. , Räisänen Anu M. , Clermont Christian A. , Ferber Reed
Published: February 2022

Inertial measurement units (IMUs) can be used to monitor running biomechanics in real-world settings, but IMUs are often used within a laboratory. The purpose of this scoping review was to describe how IMUs are used to record running biomechanics in both laboratory and real-world conditions. We included peer-reviewed journal articles that used IMUs to assess gait quality during running. We extracted data on running conditions (indoor/outdoor, surface, speed, and distance), device type and location, metrics, participants, and purpose and study design. A total of 231 studies were included. Most (72%) studies were conducted indoors; and in 67% of all studies, the analyzed distance was only one step or stride or <200 m. The most common device type and location combination was a triaxial accelerometer on the shank (18% of device and location combinations). The most common analyzed metric was vertical/axial magnitude, which was reported in 64% of all studies. Most studies (56%) included recreational runners. For the past 20 years, studies using IMUs to record running biomechanics have mainly been conducted indoors, on a treadmill, at prescribed speeds, and over small distances. We suggest that future studies should move out of the lab to less controlled and more real-world environments.
Towards the World’s Smallest Gravimetric Particulate Matter Sensor: A Miniaturized Virtual Impactor with a Folded Design
Authors: Singh Navpreet , Elsayed Mohannad Y. , El-Gamal Mourad N.
Published: February 2022

The increasing air pollution across the globe has given rise to a global health crisis that is increasing at an alarming rate. Every year, millions of people lose their lives due to health risks caused by air pollutants. Hence, there is a pressing need for better solutions to accurately measure the amount of air pollution. This work is aimed at designing a highly compact, accurate, low-cost, self-resettable, and easy-to-use gravimetric-based particulate matter sensor solution for portable applications. Previous attempts have failed to realize true miniaturization, due to the size constraints of the virtual impactor needed—a mechanism that segregates the particulate matters based on their sizes. Our complete particulate matter sensor solution consists of three components (i) a piezoelectric resonating membrane, (ii) a virtual impactor, and (iii) a thermophoretic mechanism to reset the sensor. This paper presents a novel design of the virtual impactor, based on a folded configuration. This helps realize the entire system in a volume of 20 mm × 20 mm × 10 mm. We report here the design, working principles, fabrication, and experimental results of the virtual impactor.
A Robust 3D-Based Color Correction Approach for Texture Mapping Applications
Authors: Coelho Daniel , Dal’Col Lucas , Madeira Tiago , Dias Paulo , Oliveira Miguel
Published: February 2022

Texture mapping of 3D models using multiple images often results in textured meshes with unappealing visual artifacts known as texture seams. These artifacts can be more or less visible, depending on the color similarity between the used images. The main goal of this work is to produce textured meshes free of texture seams through a process of color correcting all images of the scene. To accomplish this goal, we propose two contributions to the state-of-the-art of color correction: a pairwise-based methodology, capable of color correcting multiple images from the same scene; the application of 3D information from the scene, namely meshes and point clouds, to build a filtering procedure, in order to produce a more reliable spatial registration between images, thereby increasing the robustness of the color correction procedure. We also present a texture mapping pipeline that receives uncorrected images, an untextured mesh, and point clouds as inputs, producing a final textured mesh and color corrected images as output. Results include a comparison with four other color correction approaches. These show that the proposed approach outperforms all others, both in qualitative and quantitative metrics. The proposed approach enhances the visual quality of textured meshes by eliminating most of the texture seams.
Missing-Sheds Granularity Estimation of Glass Insulators Using Deep Neural Networks Based on Optical Imaging
Authors: Chen Wenxiang , Li Yingna , Zhao Zhengang
Published: February 2022

Insulator defect detection is an important task in inspecting overhead transmission lines. However, the surrounding environment is complex, and the detection accuracy of traditional image processing algorithms is low. Therefore, insulator defect detection is still mainly performed manually. In order to improve this situation, we proposed an insulator defect detection method called INSU-YOLO based on deep neural networks. Overexposure points in the image will interfere with insulator detection, so we used image augment to reduce noise and extract the edge information of the insulator. Based on an attention mechanism, we introduced a structure called attention-block where the backbone extracts the feature map, and this aims to improve the ability of our method to detect insulators. Insulators have a variety of specifications, and the location and granularity of defects are also different. Therefore, we proposed an adaptive threat estimation method based on the area ratio between the entire insulator and the defect area. In addition, in order to solve the problem of data shortage, we established a dataset called InsuDetSet for model training. Experiments on the InsuDetSet dataset demonstrated that our model outperforms existing state-of-the-art models regarding both the detection box and speed.
A Comparative Study of Birdcage RF Coil Configurations for Ultra-High Field Magnetic Resonance Imaging
Authors: Seo Jeung-Hoon , Han Yeji , Chung Jun-Young
Published: February 2022

Improvements in transmission and reception sensitivities of radiofrequency (RF) coils used in ultra-high field (UHF) magnetic resonance imaging (MRI) are needed to reduce specific absorption rates (SAR) and RF power deposition, albeit without applying high-power RF. Here, we propose a method to simultaneously improve transmission efficiency and reception sensitivity of a band-pass birdcage RF coil (BP-BC RF coil) by combining a multi-channel wireless RF element (MCWE) with a high permittivity material (HPM) in a 7.0 T MRI. Electromagnetic field (EM-field) simulations, performed using two types of phantoms, viz., a cylindrical phantom filled with oil and a human head model, were used to compare the effects of MCWE and HPM on BP-BC RF coils. EM-fields were calculated using the finite difference time-domain (FDTD) method and analyzed using Matlab software. Next, to improve RF transmission efficiency, we compared two HPM structures, namely, a hollow cylinder shape HPM (hcHPM) and segmented cylinder shape HPM (scHPM). The scHPM and MCWE model comprised 16 elements (16-rad BP-BC RF coil) and this coil configuration demonstrated superior RF transmission efficiency and reception sensitivity along with an acceptable SAR. We expect wider clinical application of this combination in 7.0 T MRIs, which were recently approved by the United States Food and Drug Administration.
Segmentation of Glottal Images from High-Speed Videoendoscopy Optimized by Synchronous Acoustic Recordings
Authors: Kopczynski Bartosz , Niebudek-Bogusz Ewa , Pietruszewska Wioletta , Strumillo Pawel
Published: February 2022

Laryngeal high-speed videoendoscopy (LHSV) is an imaging technique offering novel visualization quality of the vibratory activity of the vocal folds. However, in most image analysis methods, the interaction of the medical personnel and access to ground truth annotations are required to achieve accurate detection of vocal folds edges. In our fully automatic method, we combine video and acoustic data that are synchronously recorded during the laryngeal endoscopy. We show that the image segmentation algorithm of the glottal area can be optimized by matching the Fourier spectra of the pre-processed video and the spectra of the acoustic recording during the phonation of sustained vowel /i:/. We verify our method on a set of LHSV recordings taken from subjects with normophonic voice and patients with voice disorders due to glottal insufficiency. We show that the computed geometric indices of the glottal area make it possible to discriminate between normal and pathologic voices. The median of the Open Quotient and Minimal Relative Glottal Area values for healthy subjects were 0.69 and 0.06, respectively, while for dysphonic subjects were 1 and 0.35, respectively. We also validate these results using independent phoniatrician experts.
A Hybrid Bipolar Active Charge Balancing Technique with Adaptive Electrode Tissue Interface (ETI) Impedance Variations for Facial Paralysis Patients
Authors: Moganti Ganesh Lakshmana Kumar , Siva Praneeth V. N. , Vanjari Siva Rama Krishna
Published: February 2022

Functional electrical stimulation (FES) is a safe, effective, and general approach for treating various neurological disorders. However, in the case of FES usage for implantable applications, charge balancing is a significant challenge due to variations in the fabrication process and electrode tissue interface (ETI) impedance. In general, an active charge balancing approach is being used for this purpose, which has limitations of additional power consumption for residual voltage calibration and undesired neurological responses. To overcome these limitations, this paper presents a reconfigurable calibration circuit to address both ETI variations and charge balancing issues. This reconfigurable calibration circuit works in two modes: An impedance measurement mode (IMM) for treating ETI variations and a hybrid charge balancing mode (HCBM) for handling charge balance issues. The IMM predicts the desired stimulation currents by measuring the ETI. The HCBM is a hybrid combination of electrode shorting, offset regulation, and pulse modulation that takes the best features of each of these techniques and applies them in appropriate situations. From the results, it is proved that the proposed IMM configuration and HCBM configuration have an optimal power consumption of less than 44 μW with a power ratio ranging from 1.74 to 5.5 percent when compared to conventional approaches.
Learning for the Future beyond COVID-19: A Critical Alternative to the Neoliberal Model of Development
Authors: Neilson David
Published: February 2022

This paper reviews how COVID-19 became a global pandemic, why we now have to live with it, and what needs to be done to stop viruses going global in the future. Specifically, it argues that the still prevailing neoliberal model of development combined with related forms of class structure and ideological struggle all but guaranteed that the priorities of global capital and its agents, along with COVID-19, would win out in the end. Vaccinations have become the only path for resolving the tension between neoliberal capitalism and COVID-19 suppression. However, they take time to develop, are hampered by the capitalist model of vaccine production and distribution, and face a resistant alienated precariat. As a critical alternative, this article explores the neoliberal model of development’s democratic socialist transformation with particular reference to the prevention of global pandemics.
Research on the Impact of Merges and Acquisition Type on the Performance of Listed Agricultural Enterprises—An Analysis of Mediator Effect Based on R&D Input
Authors: Hong Xianna , Chen Qiuhua
Published: February 2022

With the development of global economic integration, merges and acquisition has (M&A) increasingly become the main way to enhance the competitiveness of enterprises. Technological innovation plays an important role as an influential factor in the success of merges and acquisition. This research takes 120 merges and acquisition Enterprises of Chinese listed agricultural enterprises from 2009 to 2019 as the research sample, constructs the comprehensive performance evaluation model based on the factor analysis. And on the basis of the baseline regression model, R&D Input is introduced as an intermediate variable, PSM is used to control the endogenous problem. Through a series of robustness checks, we conclude that, different merges and acquisition types have various effects on the performance of listed agricultural enterprises. Horizontal M&A and vertical M&A have significantly positive effects on enterprise performance, while mixed M&A is negative. R&D Input plays a mediating role between merges and acquisition type and its impact on enterprise performance. Vertical M&A is clearer than horizontal M&A. At the same time, less R&D Input after mixed M&A gives rise to worse performance of agricultural enterprises.
Research on Successful Factors and Influencing Mechanism of the Digital Transformation in SMEs
Authors: Zhang Xin , Xu Yaoyu , Ma Liang
Published: February 2022

In the era of the digital economy, digital transformation (DT) has become a new approach for firms to gain competitive advantages in a context of intense and dynamic market competition. Companies in almost all industries have undergone or are currently undergoing DT. Due to limited resources and capabilities, the digitalization process of small and medium-sized enterprises (SMEs) is relatively slow, so it is critical to ascertain the key factors and paths that affect the success of DT for SMEs to optimize the allocation of resources. However, there is very little research on the DT of SMEs. In response to this literature gap, the purpose of this study is to discover the key factors of the DT in SMEs and explore their interaction mechanisms. From a holistic perspective, this study has identified six key factors from three dimensions of technology, organization, and environment, and based on the resource-based view and resource-dependence theory, constructed an action mechanism model. Structural equation modeling was used to analyze the data collected from 180 SMEs in China. The results show that technological and environmental factors have a positive impact on organizational capabilities, and then promote the success of DT of SMEs. Organizational capabilities play an intermediary role in the influence of technological and environmental factors on DT. In addition, employee skills positively moderate the relationship between organizational capabilities and the success of DT. This study contributes to the conceptual framework and management implications in the DT field. Our study provides practitioners with profound insights into the enterprise’s DT and suggests that enterprises attach importance to the improvement of organizational capabilities, and use strategy and talents as important resources to promote the success of enterprise DT.
Systematic Literature Review and Bibliometric Study of Waste Management in Indonesia in the COVID-19 Pandemic Era
Authors: Mangindaan Dave , Adib Azmier , Febrianta Harvey , Hutabarat Donald John Calvien
Published: February 2022

It is globally known that the COVID-19 pandemic affected all aspects of society, including issues pertaining to health, economic, social, and environmental issues. The pandemic has already continued for two years and counting, and we are now advised to live coexisting with COVID-19 in the new normal era. During this new normal era, especially in Indonesia, many medical wastes (face masks, gloves, goggles, etc.) and other type of wastes are being generated due to COVID-19. However, the waste profile (waste management or waste handling) and the specific waste distribution in Indonesia during COVID-19 is not clearly understood. Therefore, in this study we perform a systematic literature review and bibliometric analysis of studies published during COVID-19 to describe the aforementioned issues regarding waste management in Indonesia by extracting data from Scopus as a leading indexing service for peer-reviewed publications. From more than 230,000 titles in Scopus regarding COVID-19, there are only 24 titles related to waste management in Indonesia during COVID-19. From the bibliometric analysis of the extracted data from Scopus, it can be observed that there are four clusters of interest, namely (1) medical waste and its processing, (2) COVID-19-related issues, (3) Indonesia and waste management, and (4) solid waste. The study of these issues is essential to obtain not only a clean environment, but also a sustainable future for an Indonesia that is free from COVID-19 and other related diseases in the future. Moreover, the bibliometric analysis also uncovers the research and publication gap for the topic of waste management in Indonesia in the COVID-19 pandemic era.
PyGEE-SWToolbox: A Python Jupyter Notebook Toolbox for Interactive Surface Water Mapping and Analysis Using Google Earth Engine
Authors: Owusu Collins , Snigdha Nusrat J. , Martin Mackenzie T. , Kalyanapu Alfred J.
Published: February 2022

Continuous monitoring of surface water resources is often challenging due to the lack of monitoring systems in remote areas and the high spatial distribution of water bodies. The Google Earth Engine (GEE) platform, which houses a large set of remote sensing datasets and geospatial processing power, has been applied in various aspects of surface water resources monitoring to solve some of the challenges. PyGEE-SWToolbox is a freely available Google Earth Engine-enabled open-source toolbox developed with Python to be run in Jupyter Notebooks that provides an easy-to-use graphical user interface (GUI) that enables the user to obtain time series of Landsat, Sentinel-1, and Sentinel-2 satellite imagery, pre-process them, and extract surface water using water indices, such as the Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Automated Water Extraction Index (AWEI), and Dynamic Surface Water Extent (DSWE). The validation of the toolbox is carried out at four reservoir and lake locations: Elephant Butte Lake, Hubbard Creek Reservoir, Clearwater Lake, and Neversink Reservoir in the United States. A time series of the water surface area generated from PyGEE-SWToolbox compared to the observed surface areas yielded good results, with R2 ranging between 0.63 and 0.99 for Elephant Butte Lake, Hubbard Creek Reservoir, and Clearwater Lake except the Neversink Reservoir with a maximum R2 of 0.52. The purpose of PyGEE-SWToolbox is to provide water resource managers, engineers, researchers, and students a user-friendly environment to utilize the GEE platform for water resource monitoring and generation of datasets. The toolbox is accompanied by a step-by-step user manual and Readme documentation for installation and usage.
The Importance of Adopting a Safe System Approach—Translation of Principles into Practical Solutions
Authors: Corben Bruce , Peiris Sujanie , Mishra Suryaprakash
Published: February 2022

The 1990s saw the emergence of the Swedish Vision Zero and the Dutch Sustainable Safety philosophies on road safety. At the time, both were considered somewhat radical and ambitious departures from the status quo. The principles that underpinned both the Dutch and Swedish philosophies were combined into an internationalized form, now known more widely as the Safe System. The Safe System came to attention early in the 2000s, when formally adopted by a number of countries committed to preventing severe road trauma. The Safe System defines a new way of thinking about road safety compared with what had commonly been used around the world in the decades before its conception. The Safe System strives to eliminate death and severe injury from the world’s roads. It also underlines the importance of the safe management of kinetic energy and system-based design that seeks to ensure that crashes are prevented or, at worst, crash forces fall within the threshold of human tolerance to severe injury. Once this thinking is embraced by the system designer, new solutions begin to emerge, and existing designs can be seen in a different, more insightful light. The process of transitioning to the ambitious, ethically based philosophy of the Safe System, as a means of addressing the risks of using our roads, has not happened smoothly or quickly. Practitioners have had difficulty in translating the philosophy and principles of the Safe System into practice. It is hoped that by providing examples of the differences in decisions made under Safe System principles when designing and operating roads, large gains will be made toward the lasting elimination of road trauma. A major focus of the discussion is on the Safe System-aligned design of infrastructure, coupled with vehicle operating speeds, while also recognizing the contributions to risk reduction that can come from improved human performance and the evolving safety features and technologies of modern vehicles.
The Effect of CSR Environmental Initiatives on Purchase Decisions—A Cross-Regional Study in Poland and Ukraine
Authors: Sawicka Joanna , Marcinkowska Elżbieta
Published: February 2022

To engage in an effective corporate social responsibility (CSR) action, it is necessary to first recognise its impact on targeted buyers. This study surveyed respondents from Poland and Ukraine to analyse their perception of initiatives related to environmental protection and the effect of such initiatives on purchasing behaviour. The study demonstrated how consumers’ age, education level, or professional position influence their purchasing decisions and feedback on different kinds of CSR actions related to environmental protection. Of the five areas identified in the questionnaire (environmental protection, cooperation with the local community, corruption and bribery, labour and employment, and human rights), environmental protection was found to be the most important to consumers. These results may help in decision making regarding specific environmental CSR initiatives targeted at selected social groups living in this region of Europe.
A Calculation and Decomposition Method Embedding Sectoral Energy Structure for Embodied Carbon: A Case Study of China’s 28 Sectors
Authors: Zhao Yunlong , Ma Linwei , Li Zheng , Ni Weidou
Published: February 2022

The measurement and allocation of carbon emission responsibilities is a fundamental issue in China’s low-carbon development. However, existing studies of embodied carbon do not sufficiently consider the sectoral energy structure. In this work, we developed a high-resolution calculation method for embodied carbon that embeds the sectoral energy structure into traditional input–output methods, thus expanding the driving factors of SDA decomposition. Based on this method, we calculated the quantity, final consumption structure, and energy structure of embodied carbon in China’s 28 sectors from 2002 to 2018, drew a carbon emissions allocation Sankey diagram of China in 2018, and calculated the SDA decomposition results for 2002–2010 and 2010–2018. The results indicate that fixed capital formation was still the top contributor of embodied carbon, and it caused more coal consumption. “Construction for fixed capital formation” and “other services for domestic consumption” were the two most important drivers of carbon emissions. The final consumption quantity and energy intensity were the main factors that promoted and inhibited the growth of embodied carbon, respectively, while the effects of the input–output structure, sectoral energy structure, and carbon emission coefficient on reducing carbon emissions were obvious after 2010. This also revealed that policymakers should formulate differentiated emission reduction strategies according to the carbon emission characteristics of key sectors.
Hydrokinetic Power Resource Assessment in a Combined Estuarine and River Region
Authors: Giannini Gianmaria , Ramos Victor , Rosa-Santos Paulo , Calheiros-Cabral Tomás , Taveira-Pinto Francisco
Published: February 2022

The worldwide river and tidal hydrokinetic power potential is considerable. Harnessing such potential could allow the generation of a significant amount of sustainable electricity for local uses. To the present, most studies on hydrokinetic power have focused on large-scale commercial technology development, large tidal farms planning, and high-intensity resources assessment. Reduced attention was oriented towards investigating possibilities for small to medium-size hydrokinetic plants. However, given the characteristics of rivers and estuaries, in most cases, relevant hydrokinetic power exploitation possibilities exist regardless of the dimensions of the region considered. The planning of small to medium-size hydrokinetic plants for various aspects differs from larger developments. In the present work, a method for assessing the hydrokinetic resource is proposed and applied to the case study of the Douro waterway, which is characterized by moderate flow speeds and limited water depths. A high-resolution shallow-water numerical model is set up using ocean and river inflow boundary conditions. The flow velocities are estimated for the neap-spring period for different freshwater discharges. The spots presenting the highest annual hydrokinetic power average were identified, maximum flow speeds of about 1 m/s were found, and an annual mean power of 0.4 kW/m2 was estimated, indicating that prospects for hydrokinetic energy harvesting exist.
Continuous Yarn Electrospinning
Authors: Zainuddin Shakir , Scheibel Thomas
Published: February 2022

Nanofiber-based nonwoven mats produced in electrospinning setups are usually very fragile, which often limits their applicability. Yarns have the potential to enable the incorporation of nanofibers into other materials using well-established techniques such as sewing, knitting, weaving and embroidering, thus broadening the application of nanofibers. Here, we review the development of continuous yarn electrospinning processes. Amongst several possible approaches, funnel-based collector systems have been widely adopted. Here, we summarize recent developments in the field and highlight studies providing visions on how to expand that field of research in future studies of continuous yarn electrospinning.
Integration of Genotoxic Biomarkers in Environmental Biomonitoring Analysis Using a Multi-Biomarker Approach in Three-Spined Stickleback (Gasterosteus aculeatus Linnaeus, 1758)
Authors: Cant Amélie , Bonnard Marc , Porcher Jean-Marc , Prygiel Jean , Catteau Audrey , Delahaut Laurence , Palluel Olivier , Turiès Cyril , Geffard Alain , Bado-Nilles Anne
Published: February 2022

Water is impacted by a variety of increasing pressures, such as contaminants, including genotoxic pollutants. The proposed multi-biomarker approach at a sub-individual level gives a complementary indicator to the chemical and ecological parameters of the Water Framework Directive (WFD, 2000/60/EC). By integrating biomarkers of genotoxicity and erythrocyte necrosis in the sentinel fish species the three-spined stickleback (Gasterosteus aculeatus) through active biomonitoring of six stations of the Artois-Picardie watershed, north France, our work aimed to improve the already existing biomarker approach. Even if fish in all stations had high levels of DNA strand breaks, the multivariate analysis (PCA), followed by hierarchical agglomerative clustering (HAC), improved discrimination among stations by detecting an increase of nuclear DNA content variation (Etaing, St Rémy du Nord, Artres and Biache-St-Vaast) and erythrocyte necrosis (Etaing, St Rémy du Nord). The present work highlighted that the integration of these biomarkers of genotoxicity in a multi-biomarker approach is appropriate to expand physiological parameters which allow the targeting of new potential effects of contaminants.
Physicochemical, Pharmacokinetic and Cytotoxicity of the Compounds Isolated from an Endophyte Fusarium oxysporum: In Vitro and In Silico Approaches
Authors: Hoque Nazia , Afroz Farhana , Khatun Farjana , Rony Satyajit Roy , Hasan Choudhury Mahmood , Rana Md. Sohel , Sohrab Md. Hossain
Published: February 2022

The present study was intended to characterize the secondary metabolites of the endophyte Fusarium oxysporum isolated from the plant Aglaonema hookerianum Schott. And to investigate the cytotoxic and other pharmacological properties of the isolated compounds as part of the drug discovery and development process. Different chromatographic techniques were adopted to isolate the bioactive compounds that were identified by spectroscopic techniques. The cytotoxic properties of the compounds were assessed in the Vero cell line via the trypan blue method. Moreover, physicochemical, pharmacokinetic, bioactivity and toxicity profiles of the compounds were also investigated through in silico approaches. After careful spectral analysis, the isolated compounds were identified as 3β,5α-dihydroxy-ergosta-7,22-dien-6-one (1), 3β,5α,9α-trihydroxy-ergosta-7,22-dien-6-one (2), p-hydroxybenzaldehyde (3), 3-(R)-7-butyl-6,8-dihydroxy-3-pent-11-enylisochroman-1-one (4) and beauvericin (5). An in vitro study in the Vero cell line revealed that the presence of the compounds reduced the number of cells, as well as the percentage of viable cells, in most cases. An in silico cytotoxic analysis revealed that compounds 1, 2 and 5 might be explored as cytotoxic agents. Moreover, compounds 3 and 4 were found to be highly mutagenic. The present study suggested that further thorough investigations are necessary to use these molecules as leads for the cytotoxic drug development process.
Characteristics of Harmful Algal Species in the Coastal Waters of China from 1990 to 2017
Authors: Hou Wanli , Chen Xi , Ba Menglin , Yu Jianghua , Chen Tiantian , Zhu Yihui , Bai Jie
Published: February 2022

Harmful algal blooms (HABs) have occurred frequently in coastal waters of China, imposing negative effects on the marine ecological environment. A dataset of HABs and terrestrial runoff was collected and analyzed in this study, and factors responsible for HABs were further explored. Frequency and expansion of HABs peaked between 2001 and 2007, and although they have declined slightly since then, they have remained quite high. Frequency and accumulative area of HABs peaked in 2004–2005, and most occurred from April to August during these years. HABs occurred frequently in the Changjiang (Yangtze River) estuary, and Prorocentrum donghaiense, Noctiluca scientillans, Karenia mikimotoi, and Skeletonema costatum were the main algal species. The increases of eutrophication, the abnormal sea surface temperature caused by climate and ocean currents, and the species invasion caused by the discharge of ballast water may be important factors for the long-term outbreak of HABs in the Chinese coastal waters. These findings provide a better understanding of HABs in China, which will be helpful to further prevention and control.