bluuebunny/crossref_metadata_2025 huggingface dataset:
Targeted Lipidomics of Mitochondria in a Cellular Alzheimer’s Disease Model
Authors: Kurokin Irina , Lauer Anna Andrea , Janitschke Daniel , Winkler Jakob , Theiss Elena Leoni , Griebsch Lea Victoria , Pilz Sabrina Melanie , Matschke Veronika , van der Laan Martin , Grimm Heike Sabine , Hartmann Tobias , Grimm Marcus Otto Walter
Published: August 2021

Alzheimer’s disease (AD) is neuropathologically characterized by the accumulation of Amyloid-β (Aβ) in senile plaques derived from amyloidogenic processing of a precursor protein (APP). Recently, changes in mitochondrial function have become in the focus of the disease. Whereas a link between AD and lipid-homeostasis exists, little is known about potential alterations in the lipid composition of mitochondria. Here, we investigate potential changes in the main mitochondrial phospholipid classes phosphatidylcholine, phosphatidylethanolamine and the corresponding plasmalogens and lyso-phospholipids of a cellular AD-model (SH-SY5Y APPswedish transfected cells), comparing these results with changes in cell-homogenates. Targeted shotgun-lipidomics revealed lipid alterations to be specific for mitochondria and cannot be predicted from total cell analysis. In particular, lipids containing three and four times unsaturated fatty acids (FA X:4), such as arachidonic-acid, are increased, whereas FA X:6 or X:5, such as eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA), are decreased. Additionally, PE plasmalogens are increased in contrast to homogenates. Results were confirmed in another cellular AD model, having a lower affinity to amyloidogenic APP processing. Besides several similarities, differences in particular in PE species exist, demonstrating that differences in APP processing might lead to specific changes in lipid homeostasis in mitochondria. Importantly, the observed lipid alterations are accompanied by changes in the carnitine carrier system, also suggesting an altered mitochondrial functionality.
Novel Biomimetic Human TLR2-Derived Peptides for Potential Targeting of Lipoteichoic Acid: An In Silico Assessment
Authors: Devnarain Nikita , Waddad Ayman Y. , de la Torre Beatriz G. , Albericio Fernando , Govender Thirumala
Published: August 2021

Antimicrobial resistance is one of the most significant threats to health and economy around the globe and has been compounded by the emergence of COVID-19, raising important consequences for antimicrobial resistance development. Contrary to conventional targeting approaches, the use of biomimetic application via nanoparticles for enhanced cellular targeting, cell penetration and localized antibiotic delivery has been highlighted as a superior approach to identify novel targeting ligands for combatting antimicrobial resistance. Gram-positive bacterial cell walls contain lipoteichoic acid (LTA), which binds specifically to Toll-like receptor 2 (TLR2) on human macrophages. This phenomenon has the potential to be exploited for the design of biomimetic peptides for antibacterial application. In this study, we have derived peptides from sequences present in human TLR2 that bind to LTA with high affinity. In silico approaches including molecular modelling, molecular docking, molecular dynamics, and thermodynamics have enabled the identification of these crucial binding amino acids, the design of four novel biomimetic TLR2-derived peptides and their LTA binding potential. The outcomes of this study have revealed that one of these novel peptides binds to LTA more strongly and stably than the other three peptides and has the potential to enhance LTA targeting and bacterial cell penetration.
Clostridium butyricum MIYAIRI 588 Modifies Bacterial Composition under Antibiotic-Induced Dysbiosis for the Activation of Interactions via Lipid Metabolism between the Gut Microbiome and the Host
Authors: Ariyoshi Tadashi , Hagihara Mao , Tomono Susumu , Eguchi Shuhei , Minemura Ayaka , Miura Daiki , Oka Kentaro , Takahashi Motomichi , Yamagishi Yuka , Mikamo Hiroshige
Published: August 2021

The gut microbiome is closely related to gut metabolic functions, and the gut microbiome and host metabolic functions affect each other. Clostridium butyricum MIYAIRI 588 (CBM 588) upregulates protectin D1 production in host colon tissue following G protein-coupled receptor (GPR) 120 activation to protect gut epithelial cells under antibiotic-induced dysbiosis. However, how CBM 588 enhances polyunsaturated fatty acid (PUFA) metabolites remains unclear. Therefore, we focused on the metabolic function alterations of the gut microbiome after CBM 588 and protectin D1 administration to reveal the interaction between the host and gut microbiome through lipid metabolism during antibiotic-induced dysbiosis. Consequently, CBM 588 modified gut microbiome and increased the butyric acid and oleic acid content. These lipid metabolic modifications induced GPR activation, which is a trigger of ERK 1/2 signaling and directed differentiation of downstream immune cells in the host colon tissue. Moreover, endogenous protectin D1 modified the gut microbiome, similar to CBM 588. This is the first study to report that CBM 588 influences the interrelationship between colon tissue and the gut microbiome through lipid metabolism. These findings provide insights into the mechanisms of prevention and recovery from inflammation and the improvement of host metabolism by CBM 588.
Developing Activated Carbon Veil Electrode for Sensing Salivary Uric Acid
Authors: Bukharinova Maria A. , Stozhko Natalia Yu. , Novakovskaya Elizaveta A. , Khamzina Ekaterina I. , Tarasov Aleksey V. , Sokolkov Sergey V.
Published: August 2021

The paper describes the development of a carbon veil-based electrode (CVE) for determining uric acid (UA) in saliva. The electrode was manufactured by lamination technology, electrochemically activated and used as a highly sensitive voltammetric sensor (CVEact). Potentiostatic polarization of the electrode at 2.0 V in H2SO4 solution resulted in a higher number of oxygen and nitrogen-containing groups on the electrode surface; lower charge transfer resistance; a 1.5 times increase in the effective surface area and a decrease in the UA oxidation potential by over 0.4 V, compared with the non-activated CVE, which was confirmed by energy dispersive X-ray spectroscopy, electrochemical impedance spectroscopy, chronoamperometry and linear sweep voltammetry. The developed sensor is characterized by a low detection limit of 0.05 µM and a wide linear range (0.09–700 µM). The results suggest that the sensor has perspective applications for quick determination of UA in artificial and human saliva. RSD does not exceed 3.9%, and recovery is 96–105%. UA makes a significant contribution to the antioxidant activity (AOA) of saliva (≈60%). In addition to its high analytical characteristics, the important advantages of the proposed CVEact are the simple, scalable, and cost-effective manufacturing technology and the absence of additional complex and time-consuming modification operations.
Seismic Analysis of the Bell Tower of the Church of St. Francis of Assisi on Kaptol in Zagreb by Combined Finite-Discrete Element Method
Authors: Balić Ivan , Smoljanović Hrvoje , Trogrlić Boris , Munjiza Ante
Published: August 2021

The paper presents a failure analysis of the bell tower of the church of St. Francis of Assisi on Kaptol in Zagreb subjected to seismic activity using the finite-discrete element method—FDEM. The bell tower is a masonry building, and throughout history it has undergone multiple damages and reconstructions. It was significantly damaged during the earthquake in Zagreb which occurred on 22 March 2020 with a magnitude of 5.5. The analysis was performed on a simplified FDEM 2D numerical model which corresponds to the structure in its current pre-disaster state and the structure after the proposed post-disaster reconstruction. The obtained results showed a good agreement of the crack pattern in the numerical model and the cracks that occurred due to these earthquakes. In addition, the conclusions based on the conducted analysis can provide a better insight into the behaviour and serve as guidelines to engineers for the design of such and similar structures.
Comparison of Synthetic and Natural Zeolite Catalysts’ Behavior in the Production of Lactic Acid and Ethyl Lactate from Biomass-Derived Dihydroxyacetone
Authors: Sobuś Natalia , Czekaj Izabela
Published: August 2021

This article presents the results of the conversion of dihydroxyacetone (DHA) to lactic acid (LA) with the use of zeolite catalysts. For this purpose, synthetic zeolite beta (BEA) and natural clinoptilolite (CLI) were used as a matrix. The zeolites were modified with various metals (Sn, Fe, Cu and Zn) during ion exchange under hydrothermal conditions. The DHA conversion process with the participation of metal-functionalized zeolites allowed us to obtain intermediates, i.e., pyruvic aldehyde (PAL), which during the further reaction was transformed into a mixture of products such as ethyl lactate (EL), pyruvic aldehyde (PA), lactic acid and ethyl acetate (EA). The best selectivity towards lactic acid was achieved using Sn-CLI (100%) > Na-BEA (98.7%) > Sn-BEA (95.9%) > Cu-BEA (92.9%), ethyl lactate using Cu-CLI, and pyruvic aldehyde using the Zn-BEA catalyst. In the case of a natural zeolite, modification with Sn is promising for obtaining a pure lactic acid with a relatively good carbon balance.
CalkGH9T: A Glycoside Hydrolase Family 9 Enzyme from Clostridium alkalicellulosi
Authors: Phitsuwan Paripok , Lee Sengthong , San Techly , Ratanakhanokchai Khanok
Published: August 2021

Glycoside hydrolase family 9 (GH9) endoglucanases are important enzymes for cellulose degradation. However, their activity on cellulose is diverse. Here, we cloned and expressed one GH9 enzyme (CalkGH9T) from Clostridium alkalicellulosi in Escherichia coli. CalkGH9T has a modular structure, containing one GH9 catalytic module, two family 3 carbohydrate binding modules, and one type I dockerin domain. CalkGH9T exhibited maximal activity at pH 7.0–8.0 and 55 °C and was resistant to urea and NaCl. It efficiently hydrolyzed carboxymethyl cellulose (CMC) but poorly degraded regenerated amorphous cellulose (RAC). Despite strongly binding to Avicel, CalkGH9T lacked the ability to hydrolyze this substrate. The hydrolysis of CMC by CalkGH9T produced a series of cello-oligomers, with cellotetraose being preferentially released. Similar proportions of soluble and insoluble reducing ends generated by hydrolysis of RAC indicated non-processive activity. Our study extends our knowledge of the molecular mechanism of cellulose hydrolysis by GH9 family endoglucanases with industrial relevance.
Photocatalytic Hydrogen Production from Urine Using Sr-Doped TiO2 Photocatalyst with Subsequent Phosphorus Recovery via Struvite Crystallization
Authors: Sittipunsakda Oranoot , Kemacheevakul Patiya , Laosiripojana Navadol , Chuangchote Surawut
Published: August 2021

Currently, the discharge of wastewater and utilization of phosphorus (P) in human activities cause some environmental problems, such as high organic pollutants in aquatic environments which results in dirty water sources, and a shortage of phosphate rock reserves due to the high demand of P. Therefore, fuel energy and struvite crystallization from waste sources can be considered interesting alternatives. In this work, the modified catalyst for hydrogen production, along with solving environmental problems, was examined. The strontium (Sr) doped-titanium dioxide (TiO2) nanoparticles were synthesized by wetness impregnation method. The synthesized catalyst was characterized using UV-vis spectroscopy (UV-vis), photoluminescence (PL), X-ray diffraction (XRD), photoluminescence (PL), and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS). The Sr-doped TiO2 catalysts had been utilized as the photocatalyst for the hydrogen production from synthetic human urine (a representative of waste source). The doping content of Sr in TiO2 varied from 0.5, 1, 2, and 4%, and the photocatalytic performances were compared with pristine TiO2 nanoparticles. The results showed that 1% Sr-doped TiO2 had the highest photocatalytic activity for hydrogen production and decreased the amount of chemical oxygen demand (COD) in the synthetic human urine. Subsequently, P could be recovered from the treated human urine in the form of struvite.
sFlt-1/PlGF Ratio in Prediction of Short-Term Neonatal Outcome of Small for Gestational Age Neonates
Authors: Witwicki Jacek , Chaberek Katarzyna , Szymecka-Samaha Natalia , Krysiak Adam , Pietruski Paweł , Kosińska-Kaczyńska Katarzyna
Published: August 2021

Background: Small for gestational age is a pregnancy complication associated with a variety of adverse perinatal outcomes. The aim of the study was to investigate if sFlt-1/PlGF ratio is related to adverse short-term neonatal outcome in neonates small for gestational age in normotensive pregnancy. Methods: A prospective observational study was conducted. Serum sFlt-1/PlGF ratio was measured in women in singleton gestation diagnosed with fetus small for gestational age. Short-term neonatal outcome analyzed in the period between birth and discharge home. Results: Eighty-two women were included. Women with sFlt-1/PlGF ratio ≥33 gave birth to neonates with lower birthweight at lower gestational age. Neonates from high ratio group suffered from respiratory disorders and NEC significantly more often. They were hospitalized at NICU more often and were discharged home significantly later. sFlt-1/PlGF ratio predicted combined neonatal outcome with sensitivity of 73% and specificity of 82.2%. Conclusions: sFlt-1/PlGF ratio is a useful toll in prediction of short-term adverse neonatal outcome in SGA pregnancies.
Latency Estimation Tool and Investigation of Neural Networks Inference on Mobile GPU
Authors: Ponomarev Evgeny , Matveev Sergey , Oseledets Ivan , Glukhov Valery
Published: August 2021

A lot of deep learning applications are desired to be run on mobile devices. Both accuracy and inference time are meaningful for a lot of them. While the number of FLOPs is usually used as a proxy for neural network latency, it may not be the best choice. In order to obtain a better approximation of latency, the research community uses lookup tables of all possible layers for the calculation of the inference on a mobile CPU. It requires only a small number of experiments. Unfortunately, on a mobile GPU, this method is not applicable in a straightforward way and shows low precision. In this work, we consider latency approximation on a mobile GPU as a data- and hardware-specific problem. Our main goal is to construct a convenient Latency Estimation Tool for Investigation (LETI) of neural network inference and building robust and accurate latency prediction models for each specific task. To achieve this goal, we make tools that provide a convenient way to conduct massive experiments on different target devices focusing on a mobile GPU. After evaluation of the dataset, one can train the regression model on experimental data and use it for future latency prediction and analysis. We experimentally demonstrate the applicability of such an approach on a subset of the popular NAS-Benchmark 101 dataset for two different mobile GPU.
A Cross-Sectional Survey Exploring the Impact of the COVID-19 Pandemic on the Cancer Care of Adolescents and Young Adults
Authors: Howden Kaitlyn , Glidden Camille , Romanescu Razvan G. , Hatala Andrew , Scott Ian , Deleemans Julie , Chalifour Karine , Eaton Geoff , Gupta Abha A. , Bolton James M. , Mahar Alyson L. , Garland Sheila N. , Oberoi Sapna
Published: August 2021

We aimed to describe the negative and positive impacts of changes in cancer care delivery due to COVID-19 pandemic for adolescents and young adults (AYAs) in Canada, as well as the correlates of negative impact and their perspectives on optimization of cancer care. We conducted an online, self-administered survey of AYAs with cancer living in Canada between January and February 2021. Multiple logistic regression was used to identify factors associated with a negative impact on cancer care. Of the 805 participants, 173 (21.5%) experienced a negative impact on their cancer care including delays in diagnostic tests (11.9%), cancer treatment (11.4%), and appointments (11.1%). A prior diagnosis of mental or chronic physical health condition, an annual income of <20,000 CAD, ongoing cancer treatment, and province of residence were independently associated with a negative cancer care impact (p-value < 0.05). The majority (n = 767, 95.2%) stated a positive impact of the changes to cancer care delivery, including the implementation of virtual healthcare visits (n = 601, 74.6%). Pandemic-related changes in cancer care delivery have unfavorably and favorably influenced AYAs with cancer. Interventions to support AYAs who are more vulnerable to the adverse effects of the pandemic, and the thoughtful integration of virtual care into cancer care delivery models is essential.
Magnetic Resonance Detects Structural Heart Disease in Patients with Frequent Ventricular Ectopy and Normal Echocardiographic Findings
Authors: Scorza Raffaele , Jansson Anders , Sörensson Peder , Rosenqvist Mårten , Frykman Viveka
Published: August 2021

The prognosis of patients with ventricular ectopy and a normal heart, as evaluated by echocardiography, is virtually unknown. Cardiac magnetic resonance (CMR) can detect focal ventricular anomalies that could act as a possible site of origin for premature ventricular contractions (PVCs). The aim of this study was to investigate the presence of cardiac anomalies in patients with normal findings at echocardiogram. Methods: Fifty-one consecutive patients (23 women, 28 men, mean age 59 years) with very high PVC burden (>10,000 PVC/day) and normal findings at standard echocardiography and exercise test were examined with CMR. The outcome was pathologic findings, defined as impaired ejection fraction, regional wall motion abnormalities, abnormal ventricular volume, myocardial edema and fibrosis. Results: Sixteen out of 51 patients (32%) had structural ventricular abnormalities at CMR. In five patients CMR showed impairment of the left ventricular and/or right ventricular systolic function, and six patients had a dilated left and/or right ventricle. Regional wall motion abnormalities were seen in six patients and fibrosis in four. No patient had CMR signs of edema or met CMR criteria for arrhythmogenic right ventricular cardiomyopathy. Five patients had extra-ventricular findings (enlarged atria in three cases, enlarged thoracic aorta in one case and pericardial effusion in one case). Conclusions: In this study 16 out of 51 patients with a high PVC burden and normal findings at echocardiography showed signs of pathology in the ventricles with CMR. These findings indicate that CMR should be considered in evaluating patients with a high PVC burden and a normal standard investigation.
Development and Evaluation of a Set of Spike and Receptor Binding Domain-Based Enzyme-Linked Immunosorbent Assays for SARS-CoV-2 Serological Testing
Authors: Camacho-Sandoval Rosa , Nieto-Patlán Alejandro , Carballo-Uicab Gregorio , Montes-Luna Alejandra , Jiménez-Martínez María C. , Vallejo-Castillo Luis , González-González Edith , Arrieta-Oliva Hugo Iván , Gómez-Castellano Keyla , Guzmán-Bringas Omar U. , Cruz-Domínguez María Pilar , Medina Gabriela , Montiel-Cervantes Laura A. , Gordillo-Marín Maricela , Vázquez-Campuzano Roberto , Torres-Longoria Belem , López-Martínez Irma , Pérez-Tapia Sonia M. , Almagro Juan Carlos
Published: August 2021

The implementation and validation of anti-SARS-CoV-2 IgG serological assays are reported in this paper. S1 and RBD proteins were used to coat ELISA plates, and several secondary antibodies served as reporters. The assays were initially validated with 50 RT-PCR positive COVID-19 sera, which showed high IgG titers of mainly IgG1 isotype, followed by IgG3. Low or no IgG2 and IgG4 titers were detected. Then, the RBD/IgG assay was further validated with 887 serum samples from RT-PCR positive COVID-19 individuals collected at different times, including 7, 14, 21, and 40 days after the onset of symptoms. Most of the sera were IgG positive at day 40, with seroconversion happening after 14–21 days. A third party conducted an additional performance test of the RBD/IgG assay with 406 sera, including 149 RT-PCR positive COVID-19 samples, 229 RT-PCR negative COVID-19 individuals, and 28 sera from individuals with other viral infections not related to SARS-CoV-2. The sensitivity of the assay was 99.33%, with a specificity of 97.82%. All the sera collected from individuals with infectious diseases other than COVID-19 were negative. Given the robustness of this RBD/IgG assay, it received approval from the sanitary authority in Mexico (COFEPRIS) for production and commercialization under the name UDISTEST-V2G®.
Framing Cause-Effect Relationship of Acute Coronary Syndrome in Patients with Chronic Kidney Disease
Authors: Moisi Mădălina Ioana , Bungau Simona Gabriela , Vesa Cosmin Mihai , Diaconu Camelia Cristina , Behl Tapan , Stoicescu Manuela , Toma Mirela Mărioara , Bustea Cristiana , Sava Cristian , Popescu Mircea Ioachim
Published: August 2021

The main causes of death in patients with chronic kidney disease (CKD) are of cardiovascular nature. The interaction between traditional cardiovascular risk factors (CVRF) and non-traditional risk factors (RF) triggers various complex pathophysiological mechanisms that will lead to accelerated atherosclerosis in the context of decreased renal function. In terms of mortality, CKD should be considered equivalent to ischemic coronary artery disease (CAD) and properly monitored. Vascular calcification, endothelial dysfunction, oxidative stress, anemia, and inflammatory syndrome represents the main uremic RF triggered by accumulation of the uremic toxins in CKD subjects. Proteinuria that appears due to kidney function decline may initiate an inflammatory status and alteration of the coagulation—fibrinolysis systems, favorizing acute coronary syndromes (ACS) occurrence. All these factors represent potential targets for future therapy that may improve CKD patient’s survival and prevention of CV events. Once installed, the CAD in CKD population is associated with negative outcome and increased mortality rate, that is the reason why discovering the complex pathophysiological connections between the two conditions and a proper control of the uremic RF are crucial and may represent the solutions for influencing the prognostic. Exclusion of CKD subjects from the important trials dealing with ACS and improper use of the therapeutical options because of the declined kidney functioned are issues that need to be surpassed. New ongoing trials with CKD subjects and platelets reactivity studies offers new perspectives for a better clinical approach and the expected results will clarify many aspects.
Unified Generative Adversarial Networks for Multidomain Fingerprint Presentation Attack Detection
Authors: Sandouka Soha B. , Bazi Yakoub , Alhichri Haikel , Alajlan Naif
Published: August 2021

With the rapid growth of fingerprint-based biometric systems, it is essential to ensure the security and reliability of the deployed algorithms. Indeed, the security vulnerability of these systems has been widely recognized. Thus, it is critical to enhance the generalization ability of fingerprint presentation attack detection (PAD) cross-sensor and cross-material settings. In this work, we propose a novel solution for addressing the case of a single source domain (sensor) with large labeled real/fake fingerprint images and multiple target domains (sensors) with only few real images obtained from different sensors. Our aim is to build a model that leverages the limited sample issues in all target domains by transferring knowledge from the source domain. To this end, we train a unified generative adversarial network (UGAN) for multidomain conversion to learn several mappings between all domains. This allows us to generate additional synthetic images for the target domains from the source domain to reduce the distribution shift between fingerprint representations. Then, we train a scale compound network (EfficientNetV2) coupled with multiple head classifiers (one classifier for each domain) using the source domain and the translated images. The outputs of these classifiers are then aggregated using an additional fusion layer with learnable weights. In the experiments, we validate the proposed methodology on the public LivDet2015 dataset. The experimental results show that the proposed method improves the average classification accuracy over twelve classification scenarios from 67.80 to 80.44% after adaptation.
Classification and Analysis of Pre-Service Teachers’ Errors in Solving Fermi Problems
Authors: Segura Carlos , Ferrando Irene
Published: August 2021

Fermi problems are useful for introducing modelling in primary school classrooms, although teachers’ difficulties in problem solving may hinder their successful implementation. These difficulties are associated with the modelling process, but also with the estimation and measurement skills required by Fermi problems. In this work, a specific categorization of errors for Fermi problems was established, and it allowed us to analyse the errors of N = 224 pre-service primary school teachers. The results showed that prospective teachers make a large number of errors when solving this type of task, especially conceptual ones, which are associated with the process of simplifying/structuring the real situation and the mathematization process. They also showed that there is a significant relationship between the characteristics of the problem context and the error categories. Knowing the types of errors that prospective teachers make and designing task sequences that make them emerge so that prospective teachers learn from them could be an effective way to improve initial teacher education in modelling and estimation problem solving.
Remote and Blended Teacher Education: A Rapid Review
Authors: Perry Thomas , Findon Madeleine , Cordingley Philippa
Published: August 2021

Initial and continuing teacher education are increasingly making use of remote and blended modes of education. Conducted in the summer of 2020 during the COVID-19 pandemic, this rapid review brings together literature and evidence to inform planning for remote and blended teacher education during restrictions in face-to-face teaching activity. The review consists of three main parts: first, a descriptive framework of modes of remote and blended teacher education; second, an exploratory review of the affordances and limitations of remote and blended approaches connecting the literature on effective teacher education with reviews of remote and blended approaches; third, a rapid review of evidence on the efficacy of remote and blended approaches, including of a small number of studies comparing these to face-to-face equivalents. We conclude that remote and blended teacher education is likely to become an increasingly important part of the teacher education landscape and there are plausible theoretical reasons suggesting that it can be effective with suitable design. However, we find too few studies presenting robust evidence to enable firm conclusions to be drawn on the relative effectiveness of modes and approaches. The review provides a foundation for further research and practice in this area.
The Three-Carrier Quasi Switched Boost Inverter Control Technique
Authors: Quach Thanh-Hai , Le Xuan-Vinh , Truong Viet-Anh
Published: August 2021

This paper presents a carrier modulation technique to control the three-phase, two-level quasi switched boost inverter. This PWM algorithm uses three carrier waves, the first of which is for the inverter while the others are for the booster. The boost factor depends on the short circuit interval on the DC/DC booster and the inverter. When the short circuit interval on the DC boost is twice that on the inverter, the modulation index can be enlarged. The new algorithm is analyzed, calculated, simulated, and tested. The analysis and calculation results show that the proposed technique can reduce the voltage on the DC link capacitor compared to a conventional approach. It can reach 22.16% when the ratio of the DC source voltage to the effective reference voltage is 0.5. The modulation index can extend to 29% under these conditions and the current ripple in the boost inductor can be reduced by 4.8%. The simulation and experimental results also show similarities, thereby confirming the analysis and calculation.
Motor Unit Discharges from Multi-Kernel Deconvolution of Single Channel Surface Electromyogram
Authors: Mesin Luca
Published: August 2021

Surface electromyogram (EMG) finds many applications in the non-invasive characterization of muscles. Extracting information on the control of motor units (MU) is difficult when using single channels, e.g., due to the low selectivity and large phase cancellations of MU action potentials (MUAPs). In this paper, we propose a new method to face this problem in the case of a single differential channel. The signal is approximated as a sum of convolutions of different kernels (adapted to the signal) and firing patterns, whose sum is the estimation of the cumulative MU firings. Three simulators were used for testing: muscles of parallel fibres with either two innervation zones (IZs, thus, with MUAPs of different phases) or one IZ and a model with fibres inclined with respect to the skin. Simulations were prepared for different fat thicknesses, distributions of conduction velocity, maximal firing rates, synchronizations of MU discharges, and variability of the inter-spike interval. The performances were measured in terms of cross-correlations of the estimated and simulated cumulative MU firings in the range of 0–50 Hz and compared with those of a state-of-the-art single-kernel algorithm. The median cross-correlations for multi-kernel/single-kernel approaches were 92.2%/82.4%, 98.1%/97.6%, and 95.0%/91.0% for the models with two IZs, one IZ (parallel fibres), and inclined fibres, respectively (all statistically significant differences, which were larger when the MUAP shapes were of greater difference).
WSN Deployment Strategy for Real 3D Terrain Coverage Based on Greedy Algorithm with DEM Probability Coverage Model
Authors: Fu Wendi , Yang Yan , Hong Guoqi , Hou Jing
Published: August 2021

The key to the study of node deployment in Wireless Sensor Networks (WSN) is to find the appropriate location of the WSN nodes and reduce the cost of network deployment while meeting the monitoring requirements in the covered area. This paper proposes a WSN node deployment algorithm based on real 3D terrain, which provides an effective solution to the surface-covering problem. First of all, actual geographic elevation data is adopted to conduct surface modeling. The model can vividly reflect the real terrain characteristics of the area to be deployed and make the deployment plan more visible and easy to adjust. Secondly, a probabilistic coverage model based on DEM (Digital Elevation Model) data is proposed. Based on the traditional spherical coverage model, the influence of signal attenuation and terrain occlusion on the coverage model is added to make the deployment model closer to reality. Finally, the Greedy algorithm based on grid scanning is used to deploy nodes. Simulation results show that the proposed algorithm can effectively improve the coverage rate, reduce the deployment cost, and reduce the time and space complexity in solving the WSN node deployment problem under the complex 3D land surface model, which verifies the effectiveness of the proposed algorithm.
Security Impacts Assessment of Active Distribution Network on the Modern Grid Operation—A Review
Authors: Oladeji Ifedayo , Makolo Peter , Abdillah Muhammad , Shi Jian , Zamora Ramon
Published: August 2021

The future grid will include a high penetration of distributed generation, which will have an impact on its security. This paper discusses the latest trends, components, tools, and frameworks aimed at 100% renewable energy generation for the emerging grid. The technical and economic impacts of renewable energy sources (RES)-based distributed generation (DG) on the emerging grid security are also discussed. Moreover, the latest approaches and techniques for allocating RES-DG into the distribution networks using specific performance indices based on recent literature were reviewed. Most of the methods in recent literature are based on metaheuristic optimization algorithms that can optimally allocate the RES-DGs based on the identified network variables. However, there is a need to extend these methods in terms of parameters considered, objectives, and possible ancillary support to the upstream network. The limitations of existing methods in recent literature aimed at ensuring the security of the integrated transmission-active distribution network under high RES-DG penetration were identified. Lastly, the existing coordination methods for voltage and frequency control at the transmission and active distribution system interface were also investigated. Relevant future research areas with a focus on ensuring the security of the emerging grid with high RES-DG penetration into the distribution networks are also recommended.
Modeling of Average Current in Ideal and Non-Ideal Boost and Synchronous Boost Converters
Authors: Surya Sumukh , Williamson Sheldon
Published: August 2021

This paper provides a modeling approach for average current control (ACC) operating in open-loop configuration. The converters chosen are non-ideal boost and synchronous boost converters operating in continuous conduction mode (CCM). Initially, these converters are mathematically modeled considering all the non-idealities using volt-sec and amp-sec balance equations and simulated using MATLAB and Simulink. The open-loop transfer function of the switch current or inductor current (Gid) to the duty ratio is derived using the state space averaging (SSA) technique and analyzed using MATLAB/Simulink. It is observed that the Gid of the converters is highly stable in open loop. A larger magnitude resonance is observed in ideal boost and synchronous boost converters than the non-ideal converters. However, the low frequency gain and the crossover frequency remained the same. With the increase in the load resistance, higher resonance and lower low frequency gain is observed in non-ideal boost and non-ideal boost synchronous boost converters. The derived transfer function is validated against the standard switch model using LTSpice software.
Phasor Estimation of Transient Electrical Signals Composed of Harmonics and Interharmonics
Authors: Vazquez Jon , Miñambres Jose Felix , Zorrozua Miguel Angel , Lázaro Jorge
Published: August 2021

Numerical relays have become essential tools for carrying out the protection and surveillance tasks of electrical power systems. These relays implement their functions from the phasors of the electrical network signals, estimated by digital processing using digital filters. Digital filters must meet certain requirements, such as providing a fast and effective response to increasingly complex transient signals made up of components that make the estimation process difficult. In addition to the decreasing exponential (decaying dc offset), harmonics, and signal noise, it must be added that the interharmonic components that in recent years have acquired great relevance, mainly because of the increase in non-linear loads and the extensive use of power electronic systems. The presence of these interharmonic components causes a poor response in most of the filters implemented today. This article presents the design of a new digital filter, C-CharmDF (Cleaned Characteristic Harmonic Digital Filter) for phasor estimation on noisy transient signals with decreasing exponential components, harmonics, and interharmonics. A detailed study was carried out for severe transient situations and stationary signals. It was found that the method can be suitable for relays that implement both fault location functions and system protection functions.
Ignition Thresholds and Flame Propagation of Methane/Air Mixtures Ignited via Radiatively Heated Inert Particles
Authors: Ma Junrong , Zhang Changsuo
Published: August 2021

The prevention and evaluation of explosions requires suitable standards of measurement. As such, for this study two ignition thresholds, the ignition temperature and the minimum ignition irradiance were selected as the assessment criteria. These ignition threshold values were experimentally determined by heating stationary inert silicon carbide particles via thermal radiation with a large spot size in order to ignite quiescent methane-air fuel mixtures. A high-speed Schlieren camera was used to capture the progression of the formation and propagation of the flames throughout the experiments. The results of the experiments show that the irradiance and temperature threshold are directly and inversely proportional to the particle size, respectively. Furthermore, the irradiance and temperature thresholds have similar tendencies within the flammability limits; wherein, the minimum value corresponds to fuel mixtures at a stoichiometric ratio, and increases as the equivalence ratio shifts toward the flammability limits. Irradiance thresholds, though, are more sensitive to changes in equivalence ratio than temperature. The temperature histories of the heated particle determined that when the irradiance is lower than its ignition threshold value, the heated particle-fuel mixture system will arrive at a thermal equilibrium, rather than ignition, due to the inability of the particle to reach the ignition temperature. This study also found that longer ignition times will result in a more drastic deformation of the flame fronts caused by natural convection.
Use of CO2 to Cure Steel Slag and Gypsum-Based Material
Authors: Wang Xue , Ni Wen , Li Jiajie , Zhang Siqi , Li Keqing , Hu Wentao
Published: August 2021

To improve the utilization of steel slag (SS) in CO2 capture and making building materials, the paper mainly discussed the effects of desulphurization gypsum (DG) and w/s ratio on strength development and CO2 capture capability of high Al content SS. It showed that 10 wt% DG enhanced the strength of hydration-curing SS by 262% at 28 days. Similarly, adding 6 wt% DG in carbonation-curing SS contributed to increases in strength and CO2 uptake by 283% and 33.54%, reaching 42.68 MPa and 19.12%, respectively. Strength decreases and CO2 uptake increases with w/s. Microanalysis (QXRD, SEM-EDS, TG-DTG, FTIR, XPS, and MIP) revealed that the main hydration products of SS were C-S-H gel and C4AH13, which transformed to ettringite with DG addition. The carbonation products were mainly calcite and aragonite. Additionally, the amount of aragonite, mechanically weaker than calcite, decreased and calcite increased significantly when DG was added in carbonation-curing samples, providing a denser structure and higher strength than those without DG. Furthermore, high Al 2p binding energies revealed the formation of monocarboaluminate in the DG-added carbonation samples, corresponding to higher CO2 uptake. This study provides guidance for the preparation of SS-DG carbide building materials.
A Numerical Investigation of Mixing Models in LES-FMDF for Compressible Reactive Flows
Authors: Chen Wenwu , Liang Jianhan , Zhang Lin , Guan Qingdi
Published: August 2021

The filtered mass density function (FMDF) model has been employed for large-eddy simulations (LES) of compressible high-speed turbulent mixing and reacting flows. However, the mixing model remains a pressing challenge for FMDF methods, especially for compressible reactive flows. In this work, a temporal development mixing layer with two different convective Mach numbers, Mc=0.4 and Mc=0.8, is used to investigate the mixing models. A simplified one-step reaction and a real hydrogen/air reaction are employed to study the mixing and turbulence-chemistry interaction. Two widely used mixing models, interaction by exchange with the mean (IEM) and Euclidean minimum spanning tree (EMST), are studied. Numerical results indicate that no difference is observed between the IEM and EMST models in simple reaction flows. However, for hydrogen/air reactions, the EMST model can predict the reaction more accurately in high-speed flow. For mixing models in compressible reactive flows, the requirement of localness preservation tends to be more essential as the convective Mach number increases. With the increase of compressibility, the sensitivity of the mixing model coefficient is reduced significantly. Therefore, the appropriate mixing model coefficient has a wider range. Results also indicate that a large error may result when using a fixed mixing model coefficient in compressible flows.
Analysis on Influences of Intra-Couplings in a MISO Magnetic Beamforming Wireless Power Transfer System
Authors: Kim Kyungtae , Kim Han-Joon , Seo Dong-Wook , Choi Ji-Woong
Published: August 2021

Magnetic beamforming techniques can enhance the power transfer efficiency using focused magnetic fields by the multiple transmitters to the receivers. However, the intra-couplings that cause power leakage and phase distortion among the arrayed coils inevitably occur due to the deployment of coils having strong couplings between each other. Here, we analyze the adverse influences of intra-couplings and present the advantages of magnetically independent transmitters for multiple-inputs and single-output (MISO) WPT. The independent coil array can achieve focused magnetic fields by simply adjusting the amplitude of the transmitter voltage source without phase adjustment. The system also can eliminate the reactive power with the independent coil array to efficiently use the supplying power from the source. The analytical studies are verified by numerical and circuit simulation and experiments. Our analysis can be generalized to the MISO-WPT with an arbitrary number of transmitters. It can provide insight into designing and implementing the MISO-WPT applying magnetic beamforming.
A Machine Learning-Based Gradient Boosting Regression Approach for Wind Power Production Forecasting: A Step towards Smart Grid Environments
Authors: Singh Upma , Rizwan Mohammad , Alaraj Muhannad , Alsaidan Ibrahim
Published: August 2021

In the last few years, several countries have accomplished their determined renewable energy targets to achieve their future energy requirements with the foremost aim to encourage sustainable growth with reduced emissions, mainly through the implementation of wind and solar energy. In the present study, we propose and compare five optimized robust regression machine learning methods, namely, random forest, gradient boosting machine (GBM), k-nearest neighbor (kNN), decision-tree, and extra tree regression, which are applied to improve the forecasting accuracy of short-term wind energy generation in the Turkish wind farms, situated in the west of Turkey, on the basis of a historic data of the wind speed and direction. Polar diagrams are plotted and the impacts of input variables such as the wind speed and direction on the wind energy generation are examined. Scatter curves depicting relationships between the wind speed and the produced turbine power are plotted for all of the methods and the predicted average wind power is compared with the real average power from the turbine with the help of the plotted error curves. The results demonstrate the superior forecasting performance of the algorithm incorporating gradient boosting machine regression.
Analysis of the Operation of an Unheated Wooden Church to the Shaping of Thermal and Humidity Conditions Using the Numerical Method
Authors: Nawalany Grzegorz , Sokołowski Paweł , Michalik Małgorzata
Published: August 2021

The article deals with the problem of the effects of using a wooden church on thermal and humidity conditions forming inside. Religious services in the studied site were provided several times a year. The building was not used in the remaining time. The analysis of the effects of the frequency of religious services and the number of people at the services on the formation of temperature and humidity conditions in the wooden church is provided in this paper. The effect of the presence of people in the church on CO2 concentration fluctuations was also studied. Analysis of the results showed that external conditions have the greatest effect on internal microclimate substitutions. The presence of people affects temporary fluctuations in internal parameters. Both the number of people attending the service and the time of year are important. An indoor air temperature amplitude of 9.4 °C was recorded during the winter period. The CO2 level in the church during the service exceeded the limit value of 1000 ppm, reaching 1800 ppm in the extreme case, which could result in decreased comfort for people. The high CO2 concentration may have been caused by a lack of effective ventilation in the building. The obtained simulation results showed a high agreement of the theoretical data with the measurement results (correlation 0.91). The analysis of three simulation variants showed that the people attending the services have a significant share in the gains of thermal energy inside the church. In order to meet the assumptions for variant 1, there are no requirements to start the heating system, assuming a similar schedule of services.
Experimental Investigation of Neat Biodiesels’ Saturation Level on Combustion and Emission Characteristics in a CI Engine
Authors: Sharma Vikas , Hossain Abul , Duraisamy Ganesh
Published: August 2021

The fuel qualities of several biodiesels containing highly saturated, mono, and poly unsaturated fatty acids, as well as their combustion and exhaust emission characteristics, were studied. Six biodiesel samples were divided into two groups based on their fatty acid composition, including group 1 (coconut, castor, and jatropha) and group II (palm, karanja, and waste cooking oil biodiesel). All fuels (in both groups) were tested in a single-cylinder off-road diesel engine. Castor and karanja biodiesel, both rich in mono-unsaturation level, have a high viscosity of about 14.5 and 5.04 mm2/s, respectively. The coconut and palm biodiesels are rich in saturation level with cetane numbers of 62 and 60, respectively. In both groups, highly saturated and poly-unsaturated methyl esters presented better combustion efficiency and less formation of polluted emissions than mono-unsaturation. At full load, coconut and palm biodiesel displayed 38% and 10% advanced start of combustion, respectively, which reduced ignition delay by approximately 10% and 3%, respectively. Mono-unsaturated methyl esters exhibited a higher cylinder pressure and heat release rate, which results in higher NOx gas emissions. The group II biodiesels showed about 10–15% lower exhaust emissions owing to an optimum level of fatty acid composition. Our study concluded that highly saturated and poly-unsaturated fatty acid performed better than mono-unsaturated biodiesels for off-road engine application.