bluuebunny/crossref_metadata_2025 huggingface dataset:
Nutraceutical Combinations in Hypercholesterolemia: Evidence from Randomized, Placebo-Controlled Clinical Trials
Authors: Protic Olga , Bonfigli Anna Rita , Antonicelli Roberto
Published: September 2021

There is an increasing number of nutraceutical combinations (NCs) on the market for hypercholesterolemia, although clinical trials to verify their safety and efficacy are scarce. We selected fourteen randomized, placebo-controlled clinical trials (RCTs) on different lipid-lowering NCs in hypercholesterolemic subjects. We described each compound′s mechanism of action and efficacy in the mixtures and summarized the clinical trials settings and NCs safety and efficacy results. Almost all NCs resulted efficient against hypercholesterolemia; only one reported no changes. Interestingly, red yeast rice (RYR) was present in eleven mixtures. It is not clear whether the lipid-lowering efficacy of these combinations derives mainly from the RYR component monacolin K “natural statin” single effect. Up to now, few RCTs have verified the efficacy of every single compound vs. NCs to evaluate possible additive or synergistic effects, probably due to the complexity and the high resources request. In conclusion, to manage the arising nutraceutical tide against hypercholesterolemia, it could be helpful to increase the number and robustness of clinical studies to verify the efficacy and safety of the new NCs.
Positive Effects of Exercise Intervention without Weight Loss and Dietary Changes in NAFLD-Related Clinical Parameters: A Systematic Review and Meta-Analysis
Authors: Babu Ambrin Farizah , Csader Susanne , Lok Johnson , Gómez-Gallego Carlos , Hanhineva Kati , El-Nezami Hani , Schwab Ursula
Published: September 2021

One of the focuses of non-alcoholic fatty liver disease (NAFLD) treatment is exercise. Randomized controlled trials investigating the effects of exercise without dietary changes on NAFLD-related clinical parameters (liver parameters, lipid metabolism, glucose metabolism, gut microbiota, and metabolites) were screened using the PubMed, Scopus, Web of Science, and Cochrane databases on 13 February 2020. Meta-analyses were performed on 10 studies with 316 individuals who had NAFLD across three exercise regimens: aerobic exercise, resistance training, and a combination of both. No studies investigating the role of gut microbiota and exercise in NAFLD were found. A quality assessment via the (RoB)2 tool was conducted and potential publication bias, statistical outliers, and influential cases were identified. Overall, exercise without significant weight loss significantly reduced the intrahepatic lipid (IHL) content (SMD: −0.76, 95% CI: −1.04, −0.48) and concentrations of alanine aminotransaminase (ALT) (SMD: −0.52, 95% CI: −0.90, −0.14), aspartate aminotransaminase (AST) (SMD: −0.68, 95% CI: −1.21, −0.15), low-density lipoprotein cholesterol (SMD: −0.34, 95% CI: −0.66, −0.02), and triglycerides (TG) (SMD: −0.59, 95% CI: −1.16, −0.02). The concentrations of high-density lipoprotein cholesterol, total cholesterol (TC), fasting glucose, fasting insulin, and glycated hemoglobin were non-significantly altered. Aerobic exercise alone significantly reduced IHL, ALT, and AST; resistance training alone significantly reduced TC and TG; a combination of both exercise types significantly reduced IHL. To conclude, exercise overall likely had a beneficial effect on alleviating NAFLD without significant weight loss. The study was registered at PROSPERO: CRD42020221168 and funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 813781.
Approaches to Integrated Parasite Management (IPM) for Theileria orientalis with an Emphasis on Immunity
Authors: Emery David Lyall
Published: September 2021

Integrated parasite management (IPM) for pests, pathogens and parasites involves reducing or breaking transmission to reduce the impact of infection or infestation. For Theileria orientalis, the critical impact of infection is the first wave of parasitaemia from the virulent genotypes, Ikeda and Chitose, associated with the sequelae from the development of anaemia. Therefore, current control measures for T. orientalis advocate excluding the movement of naïve stock from non-endemic regions into infected areas and controlling the tick Haemaphysalislongicornis, the final host. In Australia, treatment of established infection is limited to supportive therapy. To update and expand these options, this review examines progress towards prevention and therapy for T. orientalis, which are key elements for inclusion in IPM measures to control this parasite.
Interactome Analysis of the Nucleocapsid Protein of SARS-CoV-2 Virus
Authors: Zheng Xiaoqin , Sun Zeyu , Yu Liang , Shi Danrong , Zhu Miaojin , Yao Hangping , Li Lanjuan
Published: September 2021

SARS-CoV-2 infection has caused a global pandemic that has severely damaged both public health and the economy. The nucleocapsid protein of SARS-CoV-2 is multifunctional and plays an important role in ribonucleocapsid formation and viral genome replication. In order to elucidate its functions, interaction partners of the SARS-CoV-2 N protein in human cells were identified via affinity purification and mass spectrometry. We identified 160 cellular proteins as interaction partners of the SARS-CoV-2 N protein in HEK293T and/or Calu-3 cells. Functional analysis revealed strong enrichment for ribosome biogenesis and RNA-associated processes, including ribonucleoprotein complex biogenesis, ribosomal large and small subunits biogenesis, RNA binding, catalysis, translation and transcription. Proteins related to virus defence responses, including MOV10, EIF2AK2, TRIM25, G3BP1, ZC3HAV1 and ZCCHC3 were also identified in the N protein interactome. This study comprehensively profiled the viral–host interactome of the SARS-CoV-2 N protein in human cells, and the findings provide the basis for further studies on the pathogenesis and antiviral strategies for this emerging infection.
Distinct Characteristics of Escherichia coli Isolated from Patients with Urinary Tract Infections in a Medical Center at a Ten-Year Interval
Authors: Lin Wei-Hung , Zhang Yen-Zhen , Liu Po-Yao , Chen Po-Shun , Wang Shining , Kuo Pei-Yun , Thuy Tran Thi Dieu , Duong Tran Thi Thuy , Wen Li-Li , Hsieh Yi-Hsien , Wang Ming-Cheng , Kao Cheng-Yen
Published: September 2021

Escherichia coli causing urinary tract infections (UTIs) are one of the most common outpatient bacterial infections. This study aimed to compare the characteristics of E. coli isolated from UTI patients in a single medical center in 2009–2010 (n = 504) and 2020 (n = 340). The antimicrobial susceptibility of E. coli was determined by the disk diffusion method. PCRs were conducted to detect phylogenetic groups, ST131, K1 capsule antigen, and 15 virulence factors. Phylogenetic group B2 dominated in our 2009–2010 and 2020 isolates. Moreover, no phylogenetic group E strains were isolated in 2020. E. coli isolates in 2020 were more susceptible to amoxicillin, ampicillin/sulbactam, cefuroxime, cefmetazole, ceftazidime, cefoxitin, tetracycline, and sulfamethoxazole/trimethoprim, compared to the isolates in 2009–2010. Extensively drug-resistant (XDR)-E. coli in 2009–2010 were detected in groups B1 (5 isolates), B2 (12 isolates), F (8 isolates), and unknown (1 isolate). In 2020, XDR-E. coli were only detected in groups A (2 isolates), B2 (5 isolates), D (1 isolate), and F (4 isolates). The prevalence of virulence factor genes aer and fimH were higher in E. coli in 2009–2010 compared to those in 2020. In contrast, afa and sat showed higher frequencies in E. coli isolates in 2020 compared to E. coli in 2009–2010.
Real-Time Fluorometric Isothermal LAMP Assay for Detection of Chlamydia pecorum in Rapidly Processed Ovine Abortion Samples: A Veterinary Practitioner’s Perspective
Authors: Clune Tom , Anstey Susan , Kasimov Vasilli , Jacobson Caroline , Jelocnik Martina
Published: September 2021

Traditional methods of detecting Chlamydia pecorum in tissue samples such as polymerase chain reaction or cell culture are laborious and costly. We evaluated the use of a previously developed C. pecorum LAMP assay using minimally processed ovine samples. Cotyledon (n = 16), foetal liver (n = 22), foetal lung (n = 2), and vaginal (n = 6) swabs, in addition to cotyledon (n = 6) and foetal liver (n = 8) tissue samples, were rapidly processed and used for LAMP testing without DNA extraction. Overall, LAMP test results were highly congruent with the in-house reference qPCR, with 80.43% (37/46; 72.73% positive agreement (PA); 84.75% negative agreement (NA)) overall agreeance for swab samples, and 85.71% (12/14; 80% PA; 88.89% NA) overall agreeance for tissue samples. Out of the 11 total discrepant results, discrepancy was mainly observed in samples (n = 10) with less than 100 copies/µL C. pecorum DNA. While sensitivity could be improved, the simplicity, low cost, and accuracy of detection makes this test amenable for use at point-of-care for detecting C. pecorum in sheep.
Spontaneously Self-Assembled Microgel Film as Co-Delivery System for Skincare Applications
Authors: Aguirre Garbine , Taboada Pablo , Billon Laurent
Published: September 2021

Nowadays, the design of innovative delivery systems is driving new product developments in the field of skincare. In this regard, serving as potential candidates for on-demand drug delivery and fulfilling advanced mechanical and optical properties together with surface protection, spontaneously self-assembled microgel films can be proposed as ideal smart skincare systems. Currently, the high encapsulation of more than one drug simultaneously in a film is a very challenging task. Herein, different ratios (1:1, 3:1, 9:1) of different mixtures of hydrophilic/hydrophobic UVA/UVB-absorbers working together in synergy and used for skin protection were encapsulated efficiently into spontaneously self-assembled microgel films. In addition, in vitro release profiles show a controlled release of the different active molecules regulated by the pH and temperature of the medium. The analysis of the release mechanisms by the Peppas–Sahlin model indicated a superposition of diffusion-controlled and swelling-controlled releases. Finally, the distribution of active molecule mixtures into the film was studied by confocal Raman microscopy imaging corroborating the release profiles obtained.
Study on Aberration Correction of Adaptive Optics Based on Convolutional Neural Network
Authors: Li Jin , Wang Luwei , Guo Yong , Huang Yangrui , Yang Zhigang , Yan Wei , Qu Junle
Published: September 2021

The existence of aberrations has always been an important limiting factor in the imaging field. Especially in optical microscopy imaging, the accumulated aberration of the optical system and the biological samples distorts the wavefront on the focal plane, thereby reducing the imaging resolution. Here, we propose an adaptive optical aberration correction method based on convolutional neural network. By establishing the relationship between the Zernike polynomial and the distorted wavefront, with the help of the fast calculation advantage of an artificial intelligence neural network, the distorted wavefront information can be output in a short time for the reconstruction of the wavefront to achieve the purpose of improving imaging resolution. Experimental results show that this method can effectively compensate the aberrations introduced by the system, agarose and HeLa cells. After correcting, the point spread function restored the doughnut-shape, and the resolution of the HeLa cell image increased about 20%.
Effect of the Epoxide Contents of Liquid Isoprene Rubber as a Processing Aid on the Properties of Silica-Filled Natural Rubber Compounds
Authors: Ryu Gyeongchan , Kim Donghyuk , Song Sanghoon , Hwang Kiwon , Kim Wonho
Published: September 2021

In this study, we examined the feasibility of using epoxidized liquid isoprene rubber (E-LqIR) as a processing aid for truck and bus radial (TBR) tire treads and investigated the effects of the epoxide content on the wear resistance, fuel efficiency, and resistance to extraction of the E-LqIRs. The results confirmed that, compared to the treated distillate aromatic extract (TDAE) oil, the E-LqIRs could enhance the filler–rubber interactions and reduce the oil migration. However, the consumption of sulfur by the E-LqIRs resulted in a lower crosslink density compared to that of the TDAE oil, and the higher epoxide content decreased the wear resistance and fuel efficiency because of the increased glass-transition temperature (Tg). In contrast, the E-LqIR with a low epoxide content of 6 mol% had no significant effect on the Tg of the final compound and resulted in superior wear resistance and fuel efficiency, compared to those shown by TDAE oil, because of the higher filler–rubber interactions.
Connecting Gas-Phase Computational Chemistry to Condensed Phase Kinetic Modeling: The State-of-the-Art
Authors: Edeleva Mariya , Van Steenberge Paul H.M. , Sabbe Maarten K. , D’hooge Dagmar R.
Published: September 2021

In recent decades, quantum chemical calculations (QCC) have increased in accuracy, not only providing the ranking of chemical reactivities and energy barriers (e.g., for optimal selectivities) but also delivering more reliable equilibrium and (intrinsic/chemical) rate coefficients. This increased reliability of kinetic parameters is relevant to support the predictive character of kinetic modeling studies that are addressing actual concentration changes during chemical processes, taking into account competitive reactions and mixing heterogeneities. In the present contribution, guidelines are formulated on how to bridge the fields of computational chemistry and chemical kinetics. It is explained how condensed phase systems can be described based on conventional gas phase computational chemistry calculations. Case studies are included on polymerization kinetics, considering free and controlled radical polymerization, ionic polymerization, and polymer degradation. It is also illustrated how QCC can be directly linked to material properties.
Advanced Photocatalysts Based on Conducting Polymer/Metal Oxide Composites for Environmental Applications
Authors: Tran Vinh Van , Nu Truong Thi Vu , Jung Hong-Ryun , Chang Mincheol
Published: September 2021

Photocatalysts provide a sustainable method of treating organic pollutants in wastewater and converting greenhouse gases. Many studies have been published on this topic in recent years, which signifies the great interest and attention that this topic inspires in the community, as well as in scientists. Composite photocatalysts based on conducting polymers and metal oxides have emerged as novel and promising photoactive materials. It has been demonstrated that conducting polymers can substantially improve the photocatalytic efficiency of metal oxides owing to their superior photocatalytic activities, high conductivities, and unique electrochemical and optical properties. Consequently, conducting polymer/metal oxide composites exhibit a high photoresponse and possess a higher surface area allowing for visible light absorption, low recombination of charge carriers, and high photocatalytic performance. Herein, we provide an overview of recent advances in the development of conducting polymer/metal oxide composite photocatalysts for organic pollutant degradation and CO2 conversion through photocatalytic processes.
Fostering Awareness on Environmentally Sustainable Technological Solutions for the Post-Harvest Food Supply Chain
Authors: Fernandez Carlos M. , Alves Joel , Gaspar Pedro Dinis , Lima Tânia M.
Published: September 2021

This study presents a current status and future trends of innovative and environmentally sustainable technological solutions for the post-harvest food supply chain and the food industry, in terms of ecological packaging, active, and/or intelligent packaging. All these concerns are currently highlighted due to the strong increase in the purchase/sale of products on online platforms, as well as the requirements for stricter food security and safety. Thus, this study aims to increase the global awareness of agro-industrial micro, small, and medium size enterprises for the adoption of innovative food solutions though industry digitalization (Industry 4.0), associated logistics and circular economy, with a concern for cybersecurity and products information, communication and shelf-life extension. The adoption of these guidelines will certainly foster along the complete food chain (from producer to consumer, with all intermediary parties) the awareness on environmentally sustainable technological solutions for the post-harvest food supply chain, and thus, promoting the future food sustainability required by the population increase, the climate change, the exodus of rural population to urban areas, and food loss and waste.
Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press
Authors: Huang Yan-Shu , Sheriff M. Ziyan , Bachawala Sunidhi , Gonzalez Marcial , Nagy Zoltan K. , Reklaitis Gintaras V.
Published: September 2021

The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-model mismatch, careful monitoring and continuous improvement strategies are studied. When moving horizon estimation (MHE) is integrated with NMPC, historical data in the past time window together with real-time data from the sensor network enable state estimation and accurate tracking of the highly sensitive model parameters. The adaptive model used in the NMPC strategy can compensate for process uncertainties, further reducing plant-model mismatch effects. The nonlinear mechanistic model used in both MHE and NMPC can predict the essential but complex powder properties and provide physical interpretation of abnormal events. The adaptive NMPC implementation and its real-time control performance analysis and practical applicability are demonstrated through a series of illustrative examples that highlight the effectiveness of the proposed approach for different scenarios of plant-model mismatch, while also incorporating glidant effects.
Mathematical Simulation of Forest Fuel Pyrolysis in One-Dimensional Statement Taking into Account Soot Formation
Authors: Baranovskiy Nikolay , Kirienko Viktoriya
Published: September 2021

Pyrolysis (thermal decomposition) is considered as the most important stage of a forest fire before direct forest fuel ignition. This process is accompanied by soot particle formation. Such particles have a negative impact on public health in the vicinity of forest fires. The purpose of this article was to investigate the heat and mass transfer process occurring in a typical forest fuel element (birch leaf). The pyrolysis and soot formation processes were taken into account, and various forest fire scenarios were considered. Computational experiments were carried out using the high-level programming language Delphi. Heat and mass transfer processes were described by nonlinear non-stationary differential heat conduction equations with corresponding initial and boundary conditions. The differential equations were solved by the finite difference method. Nonlinearity was resolved using a simple iteration. The main results of the research were (1) physical and mathematical models proposed for modeling forest fuel pyrolysis, taking into account soot formation and conditions corresponding to various forest fires; (2) a computer program coded in the high-level programming language Delphi; (3) the obtained temperature distributions over leaf thickness; (4) volume fractions obtained for various components dependent on time and space coordinates. The qualitative analysis of the dependencies showed that the temperature distributions in the birch leaf structure are similar for all forest fire types and differ only in absolute value. The intensity of the soot formation process directly depends on the forest fire type. The presented results should be useful in predicting and assessing forest fire danger, including near the facilities of the Russian Railways.
Comprehensive Analysis of IPT v/s CPT for Wireless EV Charging and Effect of Capacitor Plate Shape and Foreign Particle on CPT
Authors: Lin Chang-Hua , Amir Mohammad , Tariq Mohd , Shahvez Mohd , Alamri Basem , Alahmadi Ahmad , Siddiqui Mobashshir , Beig Abdul
Published: September 2021

In this paper, the analysis and discussion are presented for two prominent types of wireless charging, namely inductive power transfer (IPT) and capacitive power transfer (CPT). The paper presents a comparative analysis between CPT and IPT. A comparison between different geometries of plates used in CPT is performed and it is shown that rectangular-shaped plates have the best power transfer efficiency. The effect of foreign particles between the capacitor plates of a single-module as well as a double-module CPT system on capacitance and energy transfer density are also investigated in the paper. The case of ceramic coating on the capacitor plates and its effects on the capacitance and energy transfer density with varying thickness are analyzed and presented. Different naturally occurring particles such as water, sand and wet sand have been simulated between the capacitor plates of the CPT system and their respective impact on power transfer is analyzed and the simulation results are demonstrated.
Feature Learning for SAR Target Recognition with Unknown Classes by Using CVAE-GAN
Authors: Hu Xiaowei , Feng Weike , Guo Yiduo , Wang Qiang
Published: September 2021

Even though deep learning (DL) has achieved excellent results on some public data sets for synthetic aperture radar (SAR) automatic target recognition(ATR), several problems exist at present. One is the lack of transparency and interpretability for most of the existing DL networks. Another is the neglect of unknown target classes which are often present in practice. To solve the above problems, a deep generation as well as recognition model is derived based on Conditional Variational Auto-encoder (CVAE) and Generative Adversarial Network (GAN). A feature space for SAR-ATR is built based on the proposed CVAE-GAN model. By using the feature space, clear SAR images can be generated with given class labels and observation angles. Besides, the feature of the SAR image is continuous in the feature space and can represent some attributes of the target. Furthermore, it is possible to classify the known classes and reject the unknown target classes by using the feature space. Experiments on the MSTAR data set validate the advantages of the proposed method.
Real-Time Underwater Maritime Object Detection in Side-Scan Sonar Images Based on Transformer-YOLOv5
Authors: Yu Yongcan , Zhao Jianhu , Gong Quanhua , Huang Chao , Zheng Gen , Ma Jinye
Published: September 2021

To overcome the shortcomings of the traditional manual detection of underwater targets in side-scan sonar (SSS) images, a real-time automatic target recognition (ATR) method is proposed in this paper. This method consists of image preprocessing, sampling, ATR by integration of the transformer module and YOLOv5s (that is, TR–YOLOv5s), and target localization. By considering the target-sparse and feature-barren characteristics of SSS images, a novel TR–YOLOv5s network and a down-sampling principle are put forward, and the attention mechanism is introduced in the method to meet the requirements of accuracy and efficiency for underwater target recognition. Experiments verified the proposed method achieved 85.6% mean average precision (mAP) and 87.8% macro-F2 score, and brought 12.5% and 10.6% gains compared with the YOLOv5s network trained from scratch, and had the real-time recognition speed of about 0.068 s per image.
Horizon Picking from SBP Images Using Physicals-Combined Deep Learning
Authors: Feng Jie , Zhao Jianhu , Zheng Gen , Li Shaobo
Published: September 2021

Horizon picking from sub-bottom profiler (SBP) images has great significance in marine shallow strata studies. However, the mainstream automatic picking methods cannot handle multiples well, and there is a need to set a group of parameters manually. Considering the constant increase in the amount of SBP data and the high efficiency of deep learning (DL), we proposed a physicals-combined DL method to pick the horizons from SBP images. We adopted the DeeplabV3+ net to extract the horizons and multiples from SBP images. We generated a training dataset from the Jiaozhou Bay survey (Shandong, China) and the Zhujiang estuary survey (Guangzhou, China) to increase the applicability of the trained model. After the DL processing, we proposed a simulated Radon transform method to eliminate the surface-related multiples from the prediction by combining the designed pseudo-Radon transform and correlation analysis. We verified the proposed method using actual data (not involved in the training dataset) from Jiaozhou Bay and Zhujiang estuary. The positions of picked horizons are accurate, and multiples are suppressed.
Testing the Height Variation Hypothesis with the R rasterdiv Package for Tree Species Diversity Estimation
Authors: Tamburlin Daniel , Torresani Michele , Tomelleri Enrico , Tonon Giustino , Rocchini Duccio
Published: September 2021

Forest biodiversity is a key element to support ecosystem functions. Measuring biodiversity is a necessary step to identify critical issues and to choose interventions to be applied in order to protect it. Remote sensing provides consistent quality and standardized data, which can be used to estimate different aspects of biodiversity. The Height Variation Hypothesis (HVH) represents an indirect method for estimating species diversity in forest ecosystems from the LiDAR data, and it assumes that the higher the variation in tree height (height heterogeneity, HH), calculated through the ’Canopy Height Model’ (CHM) metric, the more complex the overall structure of the forest and the higher the tree species diversity. To date, the HVH has been tested exclusively with CHM data, assessing the HH only with a single heterogeneity index (the Rao’s Q index) without making use of any moving windows (MW) approach. In this study, the HVH has been tested in an alpine coniferous forest situated in the municipality of San Genesio/Jenesien (eastern Italian Alps) at 1100 m, characterized by the presence of 11 different tree species (mainly Pinus sylvestris, Larix decidua, Picea abies followed by Betula alba and Corylus avellana). The HH has been estimated through different heterogeneity measures described in the new R rasterdiv package using, besides the CHM, also other LiDAR metrics (as the percentile or the standard deviation of the height distribution) at various spatial resolutions and MWs (ALS LiDAR data with mean point cloud density of 2.9 point/m2). For each combination of parameters, and for all the considered plots, linear regressions between the Shannon’s H′ (used as tree species diversity index based on field data) and the HH have been derived. The results showed that the Rao’s Q index (singularly and through a multidimensional approach) performed generally better than the other heterogeneity indices in the assessment of the HH. The CHM and the LiDAR metrics related to the upper quantile point cloud distribution at fine resolution (2.5 m, 5 m) have shown the most important results for the assessment of the HH. The size of the used MW did not influence the general outcomes but instead, it increased when compared to the results found in the literature, where the HVH was tested without MW approach. The outcomes of this study underline that the HVH, calculated with certain heterogeneity indices and LiDAR data, can be considered a useful tool for assessing tree species diversity in considered forest ecosystems. The general results highlight the strength and importance of LiDAR data in assessing the height heterogeneity and the related biodiversity in forest ecosystems.
The Use of Satellite Data to Determine the Changes of Hydrodynamic Parameters in the Gulf of Gdańsk via EcoFish Model
Authors: Janecki Maciej , Dybowski Dawid , Jakacki Jaromir , Nowicki Artur , Dzierzbicka-Glowacka Lidia
Published: September 2021

Using mathematical models alone to describe the changes in the parameters characterizing the analyzed reservoir may be insufficient due to the complexity of ocean circulation. One of the ways to improve the accuracy of models is to use data assimilation based on remote sensing methods. In this study, we tested the EcoFish numerical model that was developed for the Gulf of Gdańsk area, under the FindFish Knowledge Transfer Platform. In order to improve the model results and map local phenomena occurring in the studied water, which would be difficult to simulate using only mathematical equations, EcoFish was extended with a satellite data assimilation module that assimilates the sea surface temperature data from a medium-resolution imaging spectroradiometer and an advanced ultrahigh-resolution radiometer. EcoFish was then statistically validated, which resulted in high correlations for water temperature and salinity as well as low errors in comparison with in situ experimental data.
A Systematic Review of the Protective and Risk Factors Influencing the Mental Health of Forced Migrants: Implications for Sustainable Intercultural Mental Health Practice
Authors: Farahani Hadi , Joubert Natalie , Anand Janet Carter , Toikko Timo , Tavakol Mohamad
Published: September 2021

This systematic review followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. The primary aim of this research was to identify risks and protective factors for the mental health of forced migrants. The secondary aim was to suggest an alternative, more comprehensive approach in social work that surpasses usual diagnoses and intrinsically contradicts the medicalization of mental health issues of forced migrants. The search was conducted between January 2015 and January 2021. As a result, 29 studies met inclusion criteria. Medicalizing mental health issues by relying solely on the effectiveness of medicine was a controversial risk factor that negatively affected daily life activities of refugees and reduced their willingness for seeking professional mental health services. Empowering vulnerable minorities by giving them back their power and agency to be able to speak for themselves and raise voices of trauma and recovery was the missing protective factor for a sustainable mental health practice. The benefits of group-based interventions were highlighted in which communities and individuals address mental health issues as well as isolation through building collective identities and support networks. Information and communication technologies (ICTs) can add more strength to any kind of mental health interventions. Finally, the benefits of applying an ecological perspective for the study of the mental health of refugees, and its implications for a sustainable intercultural practice, were discussed. Social workers in this model are the representatives of at-risk groups, and thus require more agency and creativity in reflecting client’s concrete needs.
The Response to COVID-19 by the Italian Populist Government: Is It Populism or Neo-Liberalism That Makes the Response to the Pandemic Inadequate?
Authors: Talani Leila Simona , De Bellis Fabiana
Published: September 2021

The COVID-19 crisis caused unprecedented disruption in terms of human losses, economic damages, social isolation, and general malaise. It seems that, although the advice of the scientific communities to adopt rigorous measures of track and tracing, mass testing, and lock down was often considered at odds with economic performance, eventually it was precisely that kind of advice that avoided the economic debacle. This article will try and find out the reasons why Italy was more efficient and effective in implementing the measures suggested by national and transnational scientific communities. The article will do so by answering the following questions: (1) What are the political determinants of the different state responses to the pandemic? (2) Why have epistemic communities’ receipts to exit the COVID-19 crisis been ignored in some countries to follow a misguided economic logic? (3) Has the state response to the crisis anything to do with the importance of neo-liberalism and neo-liberal forces in the organization of the economy or have populist countries been less efficient than others as suggested in the recent literature on the subject?
Mathematical Standard-Parameters Dual Optimization for Metal Hip Arthroplasty Wear Modelling with Medical Physics Applications
Authors: Casesnoves Francisco
Published: September 2021

Total hip metal arthroplasty (THA) constitutes an important proportion of the standard clinical hip implant usage in Medical Physics and Biomedical Engineering. A computational nonlinear optimization is performed with two commonly metal materials in Metal-on-Metal (MoM) THA. Namely, Cast Co-Cr Alloy and Titanium. The principal result is the numerical determination of the K adimensional-constant parameter of the model. Results from a new more powerful algorithm than previous contributions, show significant improvements. Numerical standard figures for dual optimization give acceptable model-parameter values with low residuals. These results are demonstrated with 2D and 3D Graphical/Interior Optimization also. According to the findings/calculations, the standard optimized metal-model parameters are mathematically proven and verified. Mathematical consequences are obtained for model improvements and in vitro simulation methodology. The wear magnitude for in vitro determinations with these model parameter data constitute the innovation of the method. In consequence, the erosion prediction for laboratory experimental testing in THA adds valuable information to the literature. Applications lead to medical physics improvements for material/metal-THA designs.
How Is Ultrasonic-Assisted CO2 EOR to Unlock Oils from Unconventional Reservoirs?
Authors: Wang Hengli , Tian Leng , Zhang Kaiqiang , Liu Zongke , Huang Can , Jiang Lili , Chai Xiaolong
Published: September 2021

CO2 enhanced oil recovery (EOR) has proven its capability to explore unconventional tight oil reservoirs and the potential for geological carbon storage. Meanwhile, the extremely low permeability pores increase the difficulty of CO2 EOR and geological storage processing in the actual field. This paper initiates the ultrasonic-assisted approach to facilitate oil–gas miscibility development and finally contributes to excavating more tight oils. Firstly, the physical properties of crude oil with and without ultrasonic treatments were experimentally analyzed through gas chromatography (GC), Fourier-transform infrared spectroscopy (FTIR) and viscometer. Secondly, the oil–gas minimum miscibility pressures (MMPs) were measured from the slim-tube test and the miscibility developments with and without ultrasonic treatments were interpreted from the mixing-cell method. Thirdly, the nuclear-magnetic resonance (NMR) assisted coreflood tests were conducted to physically model the recovery process in porous media and directly obtain the recovery factor. Basically, the ultrasonic treatment (40 KHz and 200 W for 8 h) was found to substantially change the oil properties, with viscosity (at 60 °C) reduced from 4.1 to 2.8 mPa·s, contents of resin and asphaltene decreased from 27.94% and 6.03% to 14.2% and 3.79%, respectively. The FTIR spectrum showed that the unsaturated C-H bond, C-O bond and C≡C bond in macromolecules were broken from the ultrasonic, which caused the macromolecules (e.g., resin and asphaltenes) to be decomposed into smaller carbon-number molecules. Accordingly, the MMP was determined to be reduced from 15.8 to 14.9 MPa from the slim-tube test and the oil recovery factor increased by an additional 11.7%. This study reveals the mechanisms of ultrasonic-assisted CO2 miscible EOR in producing tight oils.
Inoculation of ACC Deaminase-Producing Brevibacterium linens RS16 Enhances Tolerance against Combined UV-B Radiation and Heat Stresses in Rice (Oryza sativa L.)
Authors: Choi Jeongyun , Roy Choudhury Aritra , Park Song-Yi , Oh Myung-Min , Sa Tongmin
Published: September 2021

UV-B radiation and high temperature have detrimental effects on plant physiological and biochemical processes. The use of bacterial inoculants for stress alleviation has been regarded as a sustainable and eco-friendly approach. Hence, this study was conducted to evaluate the ability of 1-aminocyclopropane-1-caboxylate (ACC) deaminase-producing Brevibacterium linens RS16 in enhancing stress tolerance in rice against combined UV-B radiation and heat stresses. A combination of 0.5 Wm−2 UV-B radiation and 40 °C of temperature were imposed on rice plants for 5 days. The plants imposed with combined stress had shown significantly higher ethylene emissions compared to the plants grown under normal conditions. In addition, the stress imposition had shown negative effects on the photosynthetic traits, biomass, and genetic material of rice plants. The inoculation of bacteria had shown a 26.5% and 31.8% decrease in ethylene emissions at 3 and 4 days of stress imposition compared to the non-inoculated plants. Additionally, bacterial inoculation had also enhanced plant biomass and photosynthetic traits, and had proved to be effective in restricting DNA damage under stress conditions. Taken together, the current study has shown the effective strategy of enhancing stress tolerance against the interactive effects of UV-B radiation and heat stresses by regulation of ethylene emissions through inoculating ACC deaminase-producing bacteria.
Competition and Exploitation for Ecological Capital Embodied in International Trade: Evidence from China and Its Trade Partners
Authors: Li Zhaohua , Zhu Zhiyun , Xu Shilei
Published: September 2021

In order to identify ecological relationships of participating countries in the transfer system of ecological capital embodied in global trade, this paper takes the international trade of China and its partners from 2002 to 2017 as a case, and uses the ecological footprint (EF) measured by the optimized product land-use matrix (PLUM) method to quantify ecological capital for the value of macro-ecological resources, then uses the ecological network analysis (ENA) method to construct a complete transfer network of trade-embodied ecological capital and uses a utility analysis to identify ecological relationships between trading countries. Our results show that: (1) Throughout the study period, competition relationships with 61% dominated in the network, and the countries that have a pair-wise competition relationship with China are mainly located in central and western Europe, northeastern Europe, North America, southern Asia and eastern Asia. (2) Indirect utility determines the dominant ecological relationship in system, and it mainly converts dominant ecological relationships from control to competition by transforming exploit into competition. (3) China is looking to creating a more mutually beneficial trading environment at the expense of its own interests. (4) A global crisis event is likely to result in the control of ecological capital in more countries, and in its aftermath, the world is likely to be in a highly competitive environment. Reducing ecological capital consumption by improving energy efficiency and optimizing the global trading environment into a trading system dominated by mutualism relationships can be effective ways for countries around the world to achieve sustainable development post-COVID-19 crisis.
Towards Micro-Level Green Growth: A Framework to Recognize Corporate Growth Status, Path and Adopt Eco-Innovations
Authors: Zhang Wujie , Gu Fu
Published: September 2021

Despite the substantial attention paid to green growth in recent years, how to achieve green growth is still underexamined because it is usually advocated as a political motto or development scheme at the macro level. This study aims to scrutinize the meanings of green growth, growth statuses, and growth paths at the corporate level. Meanwhile, eco-process, eco-product, and eco-system innovations were reviewed, and an adoption strategy that involves the concept of life cycle was put forward to support the choice of suitable eco-innovations and to realize micro-level green growth. Finally, 54 enterprises out of the top 500 enterprises in China were used for a multi-case study. The results demonstrate that the improvements in energy consumption were better than those of greenhouse gas (GHG) emissions in the sample enterprises. However, only five firms achieved continuous green growth. For the majority of the enterprises, their significant economic growth was not certainly related to evident drops in unit energy consumption and GHG emissions. In addition, four firms obtained continuous grey growth, and the enterprises in manufacturing sectors exhibited inferior eco-efficiency. Corporate growth statuses and paths should not only be determined by considering a single environmental or economic measure. Enterprises in manufacturing sectors must develop specific eco-innovations that can greatly enhance their environmental performance. This study adds to the literature by expounding micro-level green growth as well as its relation to eco-innovations. This study also offers a quantitative and integrated view to advance corporate eco-innovations and green development.
Exploring the Relationship between Leisure and Sustainability in a Chinese Hollow Village
Authors: Zhou Lijun , Liu Lucen , Wang Yan , Ou Yuxian , Zhao Zijing
Published: September 2021

This study explores the relationship between a for-profit leisure program and sustainability issues in the context of a hollow village in China. We studied what forms of relation between leisure and sustainability could be identified through the operation of ‘Mount Qi and the hermit master’ at a hollow village, and to what extent, ‘Mount Qi and the hermit master’ can be considered as a sustainable leisure program. Fieldwork and focus groups were used to collect data. Theoretically, the analyses adopt a comprehensive model of sustainability, which integrates the concepts of weak and strong sustainability, as well as considers the sustainability of human needs. Our findings demonstrate that the leisure program has contributed to a comprehensive sustainable development and helped to meet the villagers’ needs. This study also critically points out the uncertain aspects relating to the sustainability of human needs at the current stage of the program implementation.
Evidence-Based Educational Innovation Model Linked to Digital Information Competence in the Framework of Education 4.0
Authors: Sarango-Lapo Celia Paola , Mena Juanjo , Ramírez-Montoya María Soledad
Published: September 2021

Education 4.0 promotes visualizing how teachers’ traditional digital competencies adopt innovative practices. The present research analyzes the relationship between the perceived digital information competencies (DICs) of university teachers and the implementation of evidence-based, innovative actions (EBEI) in a model that supports innovative practices. The research method applied was the mixed method. In the quantitative phase, the final sample consisted of 271 teachers. The ad hoc digital competency-open educational resource scale (DC-OER) was applied to measure their perception of DIC. In the qualitative phase, 15 teachers were interviewed. The results showed (a) a close relationship between the fulfillment of EBEI and the support of DIC; (b) in quantitative results, in most cases, the means are close to the central value 3, and the standard deviation is close to 1, which indicates higher DIC; (c) the qualitative results indicate that teachers search, select, evaluate information, and produce new knowledge; and (d) the theoretical model of EBEI links DIC to the formation of digital citizenship. The data can be of value to the academic community in relevant environments within the framework of Education 4.0. As a future line of research, we envision analyzing the perceived digital competencies of teachers versus their effective behavior.
Synthesis of C2-Symmetrical Bis-(β-Enamino-Pyran-2,4-dione) Derivative Linked via 1,6-Hexylene Spacer: X-ray Crystal Structures, Hishfeld Studies and DFT Calculations of Mono- and Bis-(Pyran-2,4-diones) Derivatives
Authors: Boraei Ahmed T. A. , Haukka Matti , Sarhan Ahmed A. M. , Soliman Saied M. , Al-Majid Abdullah Mohammed , Barakat Assem
Published: September 2021

The synthesis of C2-symmetrical bis(β-enamino-pyran-2,4-dione) derivative 3 connected via 1,6-hexylene linker was reported for the first time. X-ray structures and Hirshfeld studies of the new bis- β-enamino-pyran-2,4-dione derivative 3 along with two structurally related pyran-2,4-dione derivatives 2a,b were discussed. A comparative analysis of the different intermolecular contacts affecting the crystal stability was presented. Generally, the H…H, O…H, and H…C interactions are common in all compounds and are considered the most abundant contacts. In addition, DFT calculations were used to compute the electronic properties as well as the 1H and 13C NMR spectra of the studied systems. All compounds (except 3) are polar where 2a (3.540 Debye) has a higher dipole moment than 2b (2.110 Debye). The NMR chemical shifts were calculated and excellent correlations between the calculated and experimental data were obtained (R2 = 0.93–0.94).
Addressing Class Overlap under Imbalanced Distribution: An Improved Method and Two Metrics
Authors: Li Zhuang , Qin Jingyan , Zhang Xiaotong , Wan Yadong
Published: September 2021

Class imbalance, as a phenomenon of asymmetry, has an adverse effect on the performance of most machine learning and overlap is another important factor that affects the classification performance of machine learning algorithms. This paper deals with the two factors simultaneously, addressing the class overlap under imbalanced distribution. In this paper, a theoretical analysis is firstly conducted on the existing class overlap metrics. Then, an improved method and the corresponding metrics to evaluate the class overlap under imbalance distributions are proposed based on the theoretical analysis. A well-known collection of the imbalanced datasets is used to compare the performance of different metrics and the performance is evaluated based on the Pearson correlation coefficient and the ξ correlation coefficient. The experimental results demonstrate that the proposed class overlap metrics outperform other compared metrics for the imbalanced datasets and the Pearson correlation coefficient with the AUC metric of eight algorithms can be improved by 34.7488% in average.