bluuebunny/crossref_metadata_2025 huggingface dataset:
Determination of Susceptibility Breakpoint for Cefquinome against Streptococcus suis in Pigs
Authors: Mi Kun , Li Mei , Sun Lei , Hou Yixuan , Zhou Kaixiang , Hao Haihong , Pan Yuanhu , Liu Zhenli , Xie Changqing , Huang Lingli
Published: August 2021

Streptococcus suis (S. suis), a zoonotic pathogen, causes severe diseases in both pigs and human beings. Cefquinome can display excellent antibacterial activity against gram-negative and gram-positive bacteria. The aim of this study was to derive an optimal dosage of cefquinome against S. suis with a pharmacokinetic/pharmacodynamic (PK/PD) integration model in the target infection site and to investigate the cutoffs monitoring the changes of resistance. The minimum inhibitory concentration (MIC) distribution of cefquinome against 342 S. suis strains was determined. MIC50 and MIC90 were 0.06 and 0.25 μg/mL, respectively. The wild-type cutoff was calculated as 1 μg/mL. A two-compartmental model was applied to calculate the main pharmacokinetic parameters after 2 mg/kg cefquinome administered intramuscularly. An optimized dosage regimen of 3.08 mg/kg for 2-log10 CFU reduction was proposed by ex vivo PK/PD model of infected swine. The pharmacokinetic-pharmacodynamic cutoff was calculated as 0.06 μg/mL based on PK/PD targets. Based on the clinical effectiveness study of pathogenic MIC isolates, the clinical cutoff was calculated as 0.5 μg/mL. A clinical breakpoint was proposed as 1 μg/mL. In conclusion, the results offer a reference for determining susceptibility breakpoint of cefquinome against S. suis and avoiding resistance emergence by following the optimal dosage regimen.
Antibiotic Use and Fatal Outcomes among Critically Ill Patients with COVID-19 in Tacna, Peru
Authors: Copaja-Corzo Cesar , Hueda-Zavaleta Miguel , Benites-Zapata Vicente A. , Rodriguez-Morales Alfonso J.
Published: August 2021

Overuse of antibiotics during the Coronavirus Disease 2019 (COVID-19) pandemic could increase the selection of extensively resistant bacteria (XDR). However, it is unknown what impact they could have on the evolution of patients, particularly critically ill patients. This study aimed to evaluate the characteristics and impact of ICU-acquired infections in patients with COVID-19. A retrospective cohort study was conducted, evaluating all patients with critical COVID-19 admitted to the intensive care unit (ICU) of a hospital in Southern Peru from 28 March 2020 to 1 March 2021. Of the 124 patients evaluated, 50 (40.32%) developed a healthcare-associated infection (HAI), which occurred at a median of 8 days (IQR 6–17) after ICU admission. The proportion of patients with HAI that required ceftriaxone was significantly higher; the same was true for the use of dexamethasone. Forty bacteria isolations (80%) were classified as XDR to antibiotics, with the most common organisms being Acinetobacter baumannii (54%) and Pseudomonas aeruginosa (22%); 33% (41/124) died at the ICU during the follow-up. In the adjusted analysis, healthcare-associated infection was associated with an increased risk of mortality (aHR= 2.7; 95% CI: 1.33–5.60) and of developing acute renal failure (aRR = 3.1; 95% CI: 1.42–6.72). The incidence of healthcare infection mainly by XDR pathogens is high in critically ill patients with COVID-19 and is associated with an increased risk of complications or death.
Assessment of Oxidative Stress Markers in Hypothermic Preservation of Transplanted Kidneys
Authors: Tejchman Karol , Sierocka Anita , Kotfis Katarzyna , Kotowski Maciej , Dolegowska Barbara , Ostrowski Marek , Sienko Jerzy
Published: August 2021

Ischemia-reperfusion injury (IRI) after renal transplantation is a complex biochemical process. The first component is an ischemic phase during kidney storage. The second is reperfusion, the main source of oxidative stress. This study aimed to analyze the activity of enzymes and concentrations of non-enzymatic compounds involved in the antioxidant defense mechanisms: glutathione (GSH), glutathione peroxidase (GPX), catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR), glutathione transferase (GST), thiobarbituric acid reactive substances (TBARS), malondialdehyde (MDA), measured in preservation fluid before transplantation of human kidneys (KTx) grafted from brain dead donors. The study group (N = 66) was divided according to the method of kidney storage: Group 1—hypothermic machine perfusion (HMP) in LifePort perfusion pump, n1 = 26, and Group 2—static cold storage (SCS), n2 = 40. The measurements of kidney function parameters, blood count, and adverse events were performed at constant time points during 7-day hospitalization and 3-month follow-up. Kidney perfusate in Group 2 was characterized by significantly more acidic pH (p < 0.0001), higher activity of GPX [U/mgHb] (p < 0.05) and higher concentration of MDA [μmol/L] (p < 0.05). There was a statistically significant improvement of kidney function and specific blood count alterations concerning storage method in repeated measures. There were aggregations of significant correlations (p < 0.05) between kidney function parameters after KTx and oxidative stress markers: diuresis & CAT, Na+ & CAT, K+ & GPX, urea & GR. There were aggregations of significant correlations (p < 0.05) between recipient blood count and oxidative stress markers: CAT & MON, SOD & WBC, SOD & MON. Study groups demonstrated differences concerning the method of kidney storage. A significant role of recipient’s gender, gender matching, preservation solution, and perfusate pH was not confirmed, however, basing on analyzed data, the well-established long-term beneficial impact of HMP on the outcome of transplanted kidneys might partially depend on the intensity of IRI ischemic phase and oxidative stress, reflected by the examined biomarkers.
A Novel Bio-Fertilizer Produced by Prickly Ash Seeds with Biochar Addition Induces Soil Suppressiveness against Black Shank Disease on Tobacco
Authors: Zhang Xifen , Wang Yaochen , Han Xiaobin , Gou Jianyu , Li Wei , Zhang Chengsheng
Published: August 2021

A novel bio-fertilizer, produced from prickly ash seeds (PAS), Bacillus subtilis and biochar, was evaluated for its disease-preventing potential on tobacco black shank caused by Phytophthora nicotianae. The results showed that biochar promoted the growth of Tpb55 in PAS and increased the pH of the organic fertilizer. The final concentration of B. subtilis could reach 1.7 × 1010 cfu g−1 in the biological organic fertilizer (PBB) under the optimal medium under conditions of solid-state fermentation. PBB exhibited a strong fumigation effect on P. nicotianae, including inhibiting mycelium growth, reducing the disease severity and decreasing the pathogen population in rhizospheric soil. PBB treatment also could significantly increase the pH of acidified soil and improve soil nutrition content such as available K, alkali hydrolysable N and organic carbon. High-throughput pyrosequencing of 16S and 18S rRNA genes revealed that 4% PBB addition in soil had significant effects on the diversity and richness of fungi but not on that of bacteria. The microbial community structure was also shifted after PBB treatment. Some potentially beneficial microbes such as Bacillus, Mucor, Cunninghamella, Chitinophaga and Phenylobacterium were enriched, while potential pathogen Fusarium was significantly decreased. In conclusion, the agricultural waste PAS combined with biochar can replace soybean as a source for the production of biocontrol B. subtilis Tpb55, and the novel bio-fertilizer could effectively control tobacco black shank by pathogen inhibition, soil nutrient improvement and shifting the rhizomicrobial community.
Fighting the COVID-19 Infodemic in News Articles and False Publications: The NeoNet Text Classifier, a Supervised Machine Learning Algorithm
Authors: Abdeen Mohammad A. R. , Hamed Ahmed Abdeen , Wu Xindong
Published: August 2021

The spread of the Coronavirus pandemic has been accompanied by an infodemic. The false information that is embedded in the infodemic affects people’s ability to have access to safety information and follow proper procedures to mitigate the risks. This research aims to target the falsehood part of the infodemic, which prominently proliferates in news articles and false medical publications. Here, we present NeoNet, a novel supervised machine learning algorithm that analyzes the content of a document (news article, a medical publication) and assigns a label to it. The algorithm was trained by Term Frequency Inverse Document Frequency (TF-IDF) bigram features, which contribute a network training model. The algorithm was tested on two different real-world datasets from the CBC news network and COVID-19 publications. In five different fold comparisons, the algorithm predicted a label of an article with a precision of 97–99%. When compared with prominent algorithms such as Neural Networks, SVM, and Random Forests NeoNet surpassed them. The analysis highlighted the promise of NeoNet in detecting disputed online contents, which may contribute negatively to the COVID-19 pandemic.
Context-Based Structure Mining Methodology for Static Object Re-Identification in Broadcast Content
Authors: Thirukokaranam Chandrasekar Krishna Kumar , Verstockt Steven
Published: August 2021

Technological advancement, in addition to the pandemic, has given rise to an explosive increase in the consumption and creation of multimedia content worldwide. This has motivated people to enrich and publish their content in a way that enhances the experience of the user. In this paper, we propose a context-based structure mining pipeline that not only attempts to enrich the content, but also simultaneously splits it into shots and logical story units (LSU). Subsequently, this paper extends the structure mining pipeline to re-ID objects in broadcast videos such as SOAPs. We hypothesise the object re-ID problem of SOAP-type content to be equivalent to the identification of reoccurring contexts, since these contexts normally have a unique spatio-temporal similarity within the content structure. By implementing pre-trained models for object and place detection, the pipeline was evaluated using metrics for shot and scene detection on benchmark datasets, such as RAI. The object re-ID methodology was also evaluated on 20 randomly selected episodes from broadcast SOAP shows New Girl and Friends. We demonstrate, quantitatively, that the pipeline outperforms existing state-of-the-art methods for shot boundary detection, scene detection, and re-identification tasks.
Influence of Infill Patterns Generated by CAD and FDM 3D Printer on Surface Roughness and Tensile Strength Properties
Authors: Lalegani Dezaki Mohammadreza , Ariffin Mohd Khairol Anuar Mohd , Serjouei Ahmad , Zolfagharian Ali , Hatami Saghi , Bodaghi Mahdi
Published: August 2021

Fused deposition modeling (FDM) is a capable technology based on a wide range of parameters. The goal of this study is to make a comparison between infill pattern and infill density generated by computer-aided design (CAD) and FDM. Grid, triangle, zigzag, and concentric patterns with various densities following the same structure of the FDM machine were designed by CAD software (CATIA V5®). Polylactic acid (PLA) material was assigned for both procedures. Surface roughness (SR) and tensile strength analysis were conducted to examine their effects on dog-bone samples. Also, a finite element analysis (FEA) was done on CAD specimens to find out the differences between printing and simulation processes. Results illustrated that CAD specimens had a better surface texture compared to the FDM machine while tensile tests showed patterns generated by FDM were stronger in terms of strength and stiffness. In this study, samples with concentric patterns had the lowest average SR (Ra) while zigzag was the worst with the value of 6.27 µm. Also, the highest strength was obtained for concentric and grid samples in both CAD and FDM procedures. These techniques can be useful in producing highly complex sandwich structures, bone scaffolds, and various combined patterns to achieve an optimal condition.
Noise Reduction in the Swept Sine Identification Procedure of Nonlinear Systems
Authors: Burrascano Pietro , Ciuffetti Matteo
Published: August 2021

The Hammerstein model identification technique based on swept sine excitation signals proved in numerous applications to be particularly effective for the definition of a model for nonlinear systems. In this paper we address the problem of the robustness of this model parameter estimation procedure in the presence of noise in the measurement step. The relationship between the different functions that enter the identification procedure is analyzed to assess how the presence of additive noise affects model parameters estimation. This analysis allows us to propose an original technique to mitigate the effects of additive noise in order to improve the accuracy of model parameters estimation. The different aspects addressed in the paper and the technique for mitigating the effects of noise on the accuracy of parameter estimation are verified on both synthetic and experimental data acquired with an ultrasonic system. The results of both simulations and experiments on laboratory data confirm the correctness of the assumptions made and the effectiveness of the proposed mitigation methodology.
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data
Authors: de Oliveira Raphael Mazzine Barbosa , Martens David
Published: August 2021

Counterfactual explanations are viewed as an effective way to explain machine learning predictions. This interest is reflected by a relatively young literature with already dozens of algorithms aiming to generate such explanations. These algorithms are focused on finding how features can be modified to change the output classification. However, this rather general objective can be achieved in different ways, which brings about the need for a methodology to test and benchmark these algorithms. The contributions of this work are manifold: First, a large benchmarking study of 10 algorithmic approaches on 22 tabular datasets is performed, using nine relevant evaluation metrics; second, the introduction of a novel, first of its kind, framework to test counterfactual generation algorithms; third, a set of objective metrics to evaluate and compare counterfactual results; and, finally, insight from the benchmarking results that indicate which approaches obtain the best performance on what type of dataset. This benchmarking study and framework can help practitioners in determining which technique and building blocks most suit their context, and can help researchers in the design and evaluation of current and future counterfactual generation algorithms. Our findings show that, overall, there’s no single best algorithm to generate counterfactual explanations as the performance highly depends on properties related to the dataset, model, score, and factual point specificities.
Tensile Buckling of a Rod with an End Moving along a Circular Guide: Improved Experimental Investigation Based on a Dynamic Approach
Authors: Blostotsky Boris , Efraim Elia , Ribakov Yuri
Published: August 2021

Investigation of buckling under tension is highly important from theoretical and practical viewpoints to ensure safety and the proper performance of mechanical systems. In the present work, tensile buckling is investigated experimentally, and the critical force is measured in systems where one end of an elastic tensile rod slides along a straight guide, while the other slides along a curve. An experimental setup is proposed and developed for determining the critical tensile load of the elastic rod by a dynamic method. This setup allows measuring free vibrations and frequency with the required accuracy. Improvement of the critical load accuracy is achieved by approaching the maximum load to the critical one. Limitations in selecting the test parameters are found according to the required extrapolation accuracy of the dominant natural vibration frequency dependence on tensile load. Theoretical analysis and tests are performed for the rod connection schemes pinned–rigid, rigid–pinned, and rigid–rigid, considering imperfections in the fixation of the rod ends. It is experimentally shown that the system buckling at tensile load is possible and that experimental and theoretical values of the critical load are in good agreement. The achieved accuracy, estimated by the discrepancy between the calculated and the experimental values, is 2.1–3.5%.
UV Light Application as a Mean for Disinfection Applied in the Dairy Industry
Authors: Chawla Arpit , Lobacz Adriana , Tarapata Justyna , Zulewska Justyna
Published: August 2021

Thermal treatment is the most popular decontamination technique used in the dairy industry to ensure food protection and prolong shelf life. But it also causes nutrient and aroma degradation, non-enzymatic browning, and organoleptic changes of dairy products. Non-thermal solutions, on the other hand, have been extensively explored in a response to rising market demand for more sustainable and safe goods. For a long time, the use of ultraviolet (UV) light in the food industry has held great promise. Irradiation with shortwave UV light has excellent germicidal properties, which can destroy a variety of microbial pathogens (for example bacteria, fungi, molds, yeasts, and viruses), at low maintenance and installation costs with minimal use of energy to preserve food without undesirable effects of heat treatment. The purpose of this review is to update the studies made on the possibilities of UV-C radiation while also addressing the essential processing factors involved in the disinfection. It also sheds light on the promise of UV light-emitting diodes (UV-LEDs) as a microbial inactivation alternative to conventional UV lamps.
Improving the Safe Operation of Platoon Lane Changing for Connected Automated Vehicles: A Novel Field-Driven Approach
Authors: Wu Renfei , Li Linheng , Lu Wenqi , Rui Yikang , Ran Bin
Published: August 2021

Connected and automated vehicles (CAVs) platoons have been widely researched because of their efficiency advantages. However, most studies mainly focus on the stability control of platoon and there is a lack of in-depth consideration of platoon lane changing. In order to make up for this vacancy, this study focused on the dynamic gap in the platoon lane changing process. First, an intra-platoon potential field of vehicles in the platoon was established by combining the repulsive force under vehicle safety and the gravity inside the platoon, which can effectively characterize the risk distribution around vehicles. Second, the platoon lane changing process was designed and critical distances of platoon vehicles under different conflict situations were analyzed. Based on this, this study proposed a critical distance model of platoon lane changing. Furthermore, we also found that the critical distances for platoon lane changing were within an interval with upper and lower bounds, which was different from the minimum distance of non-platoon vehicles. Finally, experiments were conducted and the results showed that the proposed model could effectively represent the relationship between the distance between vehicles in the platoon and the motion state of the surrounding vehicles. Moreover, the proposed method could also be applied to the lane-changing maneuver of a self-organizing platoon at a strategic level in a CAVs system.
Formulation Development, Statistical Optimization, In Vitro and In Vivo Evaluation of Etoricoxib-Loaded Eucalyptus Oil-Based Nanoemulgel for Topical Delivery
Authors: Alhakamy Nabil A. , Kotta Sabna , Ali Javed , Alam Md Shoaib , Hosny Khaled M. , Shaik Rasheed A. , Eid Basma G. , Riadi Yassine , Asfour Hani Z. , Ashy Noha , Md Shadab
Published: August 2021

Pain is a common distress in chronic inflammatory diseases, and etoricoxib (ETB) is frequently used in its management. It possesses fewer adverse effects when compared with other non-steroidal anti-inflammatory drugs (NSAIDs). In the present study, ETB-loaded nanoemulsion (ETB-NE) was formulated and optimized. Eucalyptus oil, Tween 20, and PEG 200 were chosen as the oil, surfactant, and co-surfactant, respectively. The formulation was optimized using the Box–Behnken design. The optimized ETB-NE contained oil, Smix, and water in concentrations of 11.5, 38, and 50% respectively. It had droplet size, polydispersity index, and zeta potential values of 179.6 ± 4.21 nm, 0.373 ± 0.02, and −10.9 ± 1.01 mV, respectively. The optimized ETB-NE sample passed the thermodynamic stability and dispersibility tests. Transmission electron microscopy confirmed the spherical morphology of the NE droplets. The ETB-NE showed a biphasic drug release pattern and released 85.3 ± 1.8% of ETB at 12 h. The ETB-NE was formulated into nanoemulsion gel (NEG) by using 1% carbopol 934. ETB-NEG was characterized for pH, viscosity, drug content, and percentage entrapment efficiency. During in vitro permeation studies, the apparent permeability coefficient value was 0.072 cm−2 h−1 for ETB-NEG, while it was only 0.047 cm−2 h−1 for the ETB gel. The skin histopathology study results confirmed that the ETB-NEG formulation was non-irritant and safe for topical use. The maximum possible analgesia observed for ETB-NEG was significantly high (p < 0.05) with a value of 47.09% after 60 min. Similarly, a formalin-induced acute inflammatory pain study in rats also demonstrated higher analgesia for the ETB-NEG, with % inhibition values of 37.37 ± 5.9 and 51.95 ± 4.4 in the acute and late phases, respectively. Further, ETB-NEG showed 78.4 ± 3.5% inhibition at 8 h in the in vivo anti-inflammatory testing by rat paw edema method. The ETB-NEG was found to enhance the in vivo analgesic and anti-inflammatory effects of ETB. The study results could stimulate further studies in this area for establishing a clinically successful NEG formulation of ETB.
Risk-Sensitive Rear-Wheel Steering Control Method Based on the Risk Potential Field
Authors: Kojima Toshinori , Raksincharoensak Pongsathorn
Published: August 2021

Various driving assistance systems have been developed to reduce the number of automobile accidents. However, the control laws of these assistance systems differ based on each situation, and the discontinuous control command value may be input instantaneously. Therefore, a seamless and unified control law for driving assistance systems that can be used in multiple situations is necessary to realize more versatile autonomous driving. Although studies have been conducted on four-wheel steering that steers the rear wheels, these studies considered the role of the rear wheels only to improve vehicle dynamics and not to contribute to autonomous driving. Therefore, in this study, we define the risk potential field as a uniform control law and propose a rear-wheel steering control system that actively steers the rear wheels to contribute to autonomous driving, depending on the level of the perceived risk in the driving situation. The effectiveness of the proposed method is verified by a double lane change test, which is performed assuming emergency avoidance in simulations, and subject experiments using a driving simulator. The results indicate that actively steering the rear wheels ensures a safer and smoother drive while simultaneously improving the emergency avoidance performance.
Factors Influencing the Action Point of the Collision Avoidance Manoeuvre
Authors: Przywarty Marcin , Boć Renata , Brcko Tanja , Perkovič Marko
Published: August 2021

Perhaps the most problematic issue regarding navigation safety management is the unknown, or unknowable, is the navigator’s decision made in the face of a dangerous situation. This applies particularly to collision-avoidance. The aim of the article is to identify factors that influence the moment of decision during a collision-avoidance manoeuvre and to define theoretical distributions that can be used during modelling of a navigator’s behaviour. The applicable research was divided into two stages. In the first, the distance between ships and the time to closest point of approach (TCPA) were analysed. In the second, the influence of the size of the target ships and relative speed were investigated. The advantage of the paper is its use of actual observations collected in real situations. The proposed approach allows for a better understanding of the navigator’s actual decision-making, which will be instructive in measures taken to improve navigational safety.
Molecular Tools to Exploit the Biotechnological Potential of Brettanomyces bruxellensis: A Review
Authors: Di Canito Alessandra , Foschino Roberto , Mazzieri Martina , Vigentini Ileana
Published: August 2021

The Brettanomyces bruxellensis species plays various roles in both the industrial and food sectors. At the biotechnological level, B. bruxellensis is considered to be a promising species for biofuel production. Its presence in alcoholic beverages can be detrimental or beneficial to the final product; B. bruxellensis can contribute to spoilage of wine and beer, but can also produce good aromas. However, little is known about its genetic characteristics and, despite the complete sequencing of several B. bruxellensis genomes and knowledge of its metabolic pathways, the toolkits for its efficient and easy genetic modification are still underdeveloped. Moreover, the different ploidy states and the high level of genotype diversity within this species makes the development of effective genetic manipulation tools challenging. This review summarizes the available tools for the genetic manipulation of B. bruxellensis and how they may be employed to improve the quality of wine and beer.
Early Neighbor Rejection-Aided Tabu Search Detection for Large MIMO Systems
Authors: Ummatov Uzokboy , Park Jin-Sil , Jang Gwang-Jae , Lee Ju-Dong
Published: August 2021

In this study, a low complexity tabu search (TS) algorithm for multiple-input multiple-output (MIMO) systems is proposed. To reduce the computational complexity of the TS algorithm, early neighbor rejection (ENR) and layer ordering schemes are employed. In the proposed ENR-aided TS (ENR-TS) algorithm, the least promising k neighbors are excluded from the neighbor set in each layer, which reduces the computational complexity of neighbor examination in each TS iteration. For efficient computation of the neighbors’ metrics, the ENR scheme can be incorporated into QR decomposition-aided TS (ENR-QR-TS). To further reduce the complexity and improve the performance of the ENR-QR-TS scheme, a layer ordering scheme is employed. The layer ordering scheme determines the order in which layers are detected based on their expected metrics, which reduces the risk of excluding likely neighbors in early layers. The simulation results show that the ENR-TS achieves nearly the same performance as the conventional TS while providing up to 82% complexity reduction.
Is Microfracture Alone Enough?
Authors: Borodi Paul-Gabriel , Russu Octav Marius , Feier Andrei Marian , Georgeanu Vlad Alexandru , Zuh Sándor-György , Pop Tudor Sorin
Published: August 2021

The technique of microfracture (MFX) was first performed 40 years ago and served for many years as the main procedure for repairing cartilage defects. There is a need to improve microfractures because the regenerated cartilage differs from the original histological aspect; it is less hyaline and more fibrocartilaginous. In addition, and more importantly, the benefits do not persist and the long-term results are unsatisfactory. Adjunctive treatments include platelet-rich plasma (PRP), cell-free-based scaffolds, adipose-derived mesenchymal stem cells (ADSCs), and bone marrow aspirate concentrate (BMAC). The aim of this review was to provide an overview and a perspective of the available data regarding MFX and the principal adjunctive treatments from recent years and also to challenge the traditional MFX procedure. We found that cell-free scaffolds, platelet-rich plasma, and bone marrow aspirate concentrate, although they are relatively novel therapies, showed great potential and maintained their clinical benefits for longer periods of time compared to microfracture alone. As for chitosan-based therapy and adipose-derived mesenchymal stem cells, we were not able to form a definitive conclusion. We believe that the available data show promising results, and future research should be done on each topic discussed. Moreover, investigators involved in bone marrow stimulation techniques should focus on conducting prospective comparative studies, performing second-look arthroscopy, and rely on a single enhancement procedure that can be adequately compared with MFX alone.
Long-Lifetime Event-Driven Wireless Monitoring System for Pole-Mounted Transformers
Authors: Kwak Seung Soo , Im Yun Chan , Kim Yong Sin
Published: August 2021

As smart grids develop rapidly, low-cost monitoring systems for pole-mounted transformers increase in demand. Even though battery-powered wireless monitoring systems appear to provide optimal solutions, they consume large amounts of energy for continuous sampling and data transmission. Operation and maintenance costs then increase owing to reduced battery lifetime and battery replacement. To overcome this problem, this paper presents an event-driven battery-powered wireless monitoring system that monitors abnormalities of a transformer and transmits data only if an abnormality occurs. When the proposed event controller detects an abnormality, it enables a root mean square (RMS) converter and a peak detector for sampling and transmitting the maximum RMS value of the abnormal signal and then falls into sleep mode until the next event to save energy. Simulation and experimental results show that the proposed system enhances battery lifetime by up to two orders of magnitude compared to a conventional battery-powered wireless monitoring system.
Data Reduction of Digital Twin Simulation Experiments Using Different Optimisation Methods
Authors: Raska Pavel , Ulrych Zdenek , Malaga Miroslav
Published: August 2021

The paper presents possible approaches for reducing the volume of data generated by simulation optimisation performed with a digital twin created in accordance with the Industry 4.0 concept. The methodology is validated using an application developed for controlling the execution of parallel simulation experiments (using client–server architecture) with the digital twin. The paper describes various pseudo-gradient, stochastic, and metaheuristic methods used for finding the global optimum without performing a complete pruning of the search space. The remote simulation optimisers reduce the volume of generated data by hashing the data. The data are sent to a remote database of simulation experiments for the digital twin for use by other simulation optimisers.
Analysis of the Influence of Age Stages on Static Plantar Pressure Indicators for Karate Do Practitioners (Preliminary Report)
Authors: Mocanu George Danut , Murariu Gabriel , Iordan Daniel Andrei , Sandu Ion
Published: August 2021

The investigation aims at static examination and determination of differences for three age groups: under 13, 13–15 years old and over 15, all practitioners of the martial art karate do. This investigation occured at the level of the main parameters, measured using the FreeMed baropodometric platform and Free Step software by Sensor Medica: plantar surface areas, location of the pressure center (C) inside the support polygon, imbalances noticed at the level of the plantar areas, Pmax value, weight distribution on each foot and at the level of the rearfoot and forefoot areas, misalignments of the pressure centers of each foot, etc. Results: subjects under the age of 13 had the highest number of cases related to the off-centered positioning of the pressure center (C); the groups of those under 13 and over 15 years old located in most cases Pmax at the level of the left retropodal part, and those between 13–15 years old have a location on the dominant leg, at the level of the right retropodal part. The highest numbers of cases of normal bilateral leg are for the group under 13 years, and the other groups have a higher incidence of various plantar imbalances. The analysis of variance (F) identified only two situations in which the independent variable, “age stages,” significantly influences the resulting parameters, at the level of the non-dominant foot: forefoot_left_surface and total_left_surface. The data differences for the right/left pairs within each batch generate insignificant values of |Z| for most cases, with the superiority of the dominant foot parameters for the first two age groups, but in the case of the group over 15 years old, some results are atypical, with higher average values of left/non-dominant foot parameters in the following cases: total_left_Pmax, total_left_Pavg, rearfoot_left_load_percent, rearfoot_left_weight_ratio_percent. The comparison between the data pairs for all three batches (between the forefoot and rearfoot plantar areas) generated significant values of |Z| only for the area of the plantar surfaces. The older the subjects, the more obvious the plantar load on the forefoot area, which is similar to the results of some martial arts studies analyzed here, and is determined by the long use of the non-dominant foot as a support base, during kicks with the dominant one.
Globally Optimal Facility Locations for Continuous-Space Facility Location Problems
Authors: Gao Xuehong , Park Chanseok , Chen Xiaopeng , Xie En , Huang Guozhong , Zhang Dingli
Published: August 2021

The continuous-space single- and multi-facility location problem has attracted much attention in previous studies. This study focuses on determining the globally optimal facility locations for two- and higher-dimensional continuous-space facility location problems when the Manhattan distance is considered. Before we propose the exact method, we start with the continuous-space single-facility location problem and obtain the global minimizer for the problem using a statistical approach. Then, an exact method is developed to determine the globally optimal solution for the two- and higher-dimensional continuous-space facility location problem, which is different from the previous clustering algorithms. Based on the newly investigated properties of the minimizer, we extend it to multi-facility problems and transfer the continuous-space facility location problem to the discrete-space location problem. To illustrate the effectiveness and efficiency of the proposed method, several instances from a benchmark are provided to compare the performances of different methods, which illustrates the superiority of the proposed exact method in the decision-making of the continuous-space facility location problems.
Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia
Authors: Zaman Nurul Amalin Fatihah Kamarul , Kanniah Kasturi Devi , Kaskaoutis Dimitris G. , Latif Mohd Talib
Published: August 2021

Southeast Asia (SEA) is a hotspot region for atmospheric pollution and haze conditions, due to extensive forest, agricultural and peat fires. This study aims to estimate the PM2.5 concentrations across Malaysia using machine-learning (ML) models like Random Forest (RF) and Support Vector Regression (SVR), based on satellite AOD (aerosol optical depth) observations, ground measured air pollutants (NO2, SO2, CO, O3) and meteorological parameters (air temperature, relative humidity, wind speed and direction). The estimated PM2.5 concentrations for a two-year period (2018–2019) are evaluated against measurements performed at 65 air-quality monitoring stations located at urban, industrial, suburban and rural sites. PM2.5 concentrations varied widely between the stations, with higher values (mean of 24.2 ± 21.6 µg m−3) at urban/industrial stations and lower (mean of 21.3 ± 18.4 µg m−3) at suburban/rural sites. Furthermore, pronounced seasonal variability in PM2.5 is recorded across Malaysia, with highest concentrations during the dry season (June–September). Seven models were developed for PM2.5 predictions, i.e., separately for urban/industrial and suburban/rural sites, for the four dominant seasons (dry, wet and two inter-monsoon), and an overall model, which displayed accuracies in the order of R2 = 0.46–0.76. The validation analysis reveals that the RF model (R2 = 0.53–0.76) exhibits slightly better performance than SVR, except for the overall model. This is the first study conducted in Malaysia for PM2.5 estimations at a national scale combining satellite aerosol retrievals with ground-based pollutants, meteorological factors and ML techniques. The satisfactory prediction of PM2.5 concentrations across Malaysia allows a continuous monitoring of the pollution levels at remote areas with absence of measurement networks.
Spatial Concentration of Carbon Components in Indoor PM2.5 of School Classrooms in a Large City of Korea
Authors: Heo Sujeong , Kwoun Jiyou , Lee Sumin , Kim Doyoon , Lee Taejung , Jo Youngmin
Published: August 2021

On increasing the importance of indoor air quality in urban schools of Korea, a comprehensive investigation of PM2.5 was carried out focusing on carbon contents. According to the analysis results, PM2.5 of the classrooms distributed 14.5 μg/m3 to 40.2 μg/m3, which was lower than National Guidelines (35 μg/m3 for 24 h average), and it contained 45.4 ± 10.9% of carbonaceous matters including organic carbon (OC) and elemental carbon (EC). Carbons were proportionally correlated with externally occurring ion species, but OC was found more inside (9.5 μg/m3) than outside (5.9 μg/m3). This indicates that school children are exposed to a variety of polymeric chemicals in the classroom. The current data obtained in this study can be used to inform the establishment of a national school air quality management policy.
Seven Level Voltage Source Converter Based Static Synchronous Compensator with a Constant DC-Link Voltage
Authors: Gadupudi L. Narayana , Rao Gudapati Sambasiva , Devarapalli Ramesh , García Márquez Fausto Pedro
Published: August 2021

Flexible alternating current transmission system (FACTS) controllers are important to enhance the quality of power in power systems. The stability of a system is achieved via a FACTS device (a Static Synchronous Compensator (STATCOM)). This paper aims to control the losses in the transmission system during peak energy demand circumstances with minimal losses in the economical and functional efficiency of the system. The STATCOM operation of a seven level voltage source converter (VSC) with binary-weighted transformers is proposed for controlling the reactive power variations and terminal voltage changes at dynamic circumstances in the transmission system. The STATCOM is operated at 132 kV and is a 50 Hz AC system with a single DC-Link capacitance and two VSC power circuits. Each VSC circuit consists of three H-bridges with specific switching angle control in order to achieve low total harmonic distortion at the fundamental frequency. The coupled control circuit phenomenon is imperative for computing the switching angle for a stable performance. The dynamic functional improvement efficiency is harvested with a minimum number of switches and transformers used in high voltage and high-power applications. The number of switches, transformers, and capacitors for 132 kV are optimized with a proposed STATCOM operation in seven level VSC with binary-weighted transformers. The simulated results prove that the proposed model significantly improved system performance and stability.
A Simple Model for Wildland Fire Vortex–Sink Interactions
Authors: Quaife Bryan , Speer Kevin
Published: August 2021

A model is developed to explore fire–atmosphere interactions due to the convective sink and vorticity sources in a highly simplified and idealized form, in order to examine their effect on spread and the stability of various fire front geometries. The model is constructed in a cellular automata framework, is linear, and represents a background flow, convective sink, and vortices induced by the fire plume at every burning cell. We use standard techniques to solve the resulting Poisson equations with careful attention to the boundary conditions. A modified Bresenham algorithm is developed to represent convection. The three basic flow types—large-scale background flow, sink flow, and vortex circulation—interact in a complex fashion as the geometry of the fire evolves. Fire-generated vortex–sink interactions produce a range of fire behavior, including unsteady spread rate, lateral spreading, and dynamic fingering. In this simplified framework, pulsation is found associated with evolving fire-line width, a fire-front acceleration in junction fires, and the breakup of longer initial fire lines into multiple head fires. Fuel is very simply represented by a single burn time parameter. The model fuel is uniform yet patchiness occurs due to a dynamic interaction of diffusive and convective effects. The interplay of fire-induced wind and the geometry of the fire front depends also on the fuel burn time.
Intra-Annual Variation of Stem Circumference of Tree Species Prevailing in Hemi-Boreal Forest on Hourly Scale in Relation to Meteorology, Solar Radiation and Surface Ozone Fluxes
Authors: Augustaitis Algirdas
Published: August 2021

(1) Background: Continuous monitoring of the tree stem increment throughout the year is crucial for the understanding of trees’ reactions to changes in meteorology, solar radiation and surface ozone and evaluating the adaptive capacity of prevailing tree species to recent environmental global changes; (2) Methods: Data on tree intra-annual sequences based on electronic dendrometer data of Picea abies (L.) Karst, Pinus sylvestris L., Betula pendula, and Betula pubescens, growing under different nutritional and humidity conditions in the north-eastern part of Lithuania, together with their stem sap flow intensity, common meteorology and O3 fluxes, were used to meet the objectives of the study; (3) Results: Stem shrinking/contraction during the day, due to transpiration, and the swelling/expansion during the night was significantly related to meteorology, sun activity and O3 flux intensity. These variations were negatively related to current time and temperature, but positively to precipitation and relative humidity. O3 fluxed through the stomata stimulated the shrinking process more intensively than it inhibited the swelling process, but only for pine and birch trees. Spruce trees demonstrated the highest sensitivity to O3 impact due to its significant effect on the stem swelling process. Pine trees were less sensitive to O3 damages and birch trees were the least sensitive. An over-moisture regime at measoeutrophic organic soil forest site increased the significance of the effect of O3 on the tree increment of the considered tree species; (4) Conclusion: The most intensive tree ring formation of Scots pine trees in relation to recent environmental changes indicated their high resiliencies and adaptations to a local specific condition. Reduced tree growth intensity and weak relationships between the birch tree radios increment and main meteorological parameters indicated the lowest adaptive capacity of this tree species to recent environmental changes.
Evaluation of Using Satellite-Derived Aerosol Optical Depth in Land Use Regression Models for Fine Particulate Matter and Its Elemental Composition
Authors: Huang Chun-Sheng , Liao Ho-Tang , Lin Tang-Huang , Chang Jung-Chi , Lee Chien-Lin , Yip Eric Cheuk-Wai , Wu Yee-Lin , Wu Chang-Fu
Published: August 2021

This study introduced satellite-derived aerosol optical depth (AOD) in land use regression (LUR) modeling to predict ambient concentrations of fine particulate matter (PM2.5) and its elemental composition. Twenty-four daily samples were collected from 17 air quality monitoring sites (N = 408) in Taiwan in 2014. A total of 12 annual LUR models were developed for PM2.5 and 11 elements, including aluminum, calcium, chromium, iron, potassium, manganese, sulfur, silicon, titanium, vanadium, and zinc. After applied AOD and a derived-predictor, AOD percentage, in modeling, the number of models with leave-one-out cross-validation R2 > 0.40 significantly increased from 5 to 9, indicating the substantial benefits for the construction of spatial prediction models. Sensitivity analyses of using data stratified by PM2.5 concentrations revealed that the model performances were further improved in the high pollution season.
On the Relationship of Cold Pool and Bulk Shear Magnitudes on Upscale Convective Growth in the Great Plains of the United States
Authors: Hiris Zachary A. , Gallus William A.
Published: August 2021

Upscale convective growth remains a poorly understood aspect of convective evolution, and numerical weather prediction models struggle to accurately depict convective morphology. To better understand some physical mechanisms encouraging upscale growth, 30 warm-season convective events from 2016 over the United States Great Plains were simulated using the Weather Research and Forecasting (WRF) model to identify differences in upscale growth and non-upscale growth environments. Also, Bryan Cloud Model (CM1) sensitivity tests were completed using different thermodynamic environments and wind profiles to examine the impact on upscale growth. The WRF simulations indicated that cold pools are significantly stronger in cases that produce upscale convective growth within the first few hours following convective initiation compared to those without upscale growth. Conversely, vertical wind shear magnitude has no statistically significant relationship with either MCS or non-MCS events. This is further supported by the CM1 simulations, in which tests using the WRF MCS sounding developed a large convective system in all tests performed, including one which used the non-MCS kinematic profile. Likewise, the CM1 simulations of the non-upscale growth event did not produce an MCS, even when using the MCS kinematic profile. Overall, these results suggest that the near-storm and pre-convective thermodynamic environment may play a larger role than kinematics in determining upscale growth potential in the Great Plains.
A Novel Framework for Forecasting, Evaluation and Early-Warning for the Influence of PM10 on Public Health
Authors: Yang Wendong , Tang Guolin , Hao Yan , Wang Jianzhou
Published: August 2021

PM2.5 has attracted widespread attention since the public has become aware of it, while attention to PM10 has started to wane. Considering the significance of PM10, this study takes PM10 as the research object and raises a significant question: when will the influence of PM10 on public health end? To answer the abovementioned question, two promising research areas, i.e., air pollution forecasting and health effects analysis, are employed, and a novel hybrid framework is developed in this study, which consists of one effective model and one evaluation model. More specifically, this study first introduces one advanced optimization algorithm and cycle prediction theory into the grey forecasting model to develop an effective model for multistep forecasting of PM10, which can achieve reasonable forecasting of PM10. Then, an evaluation model is designed to evaluate the health effects and economic losses caused by PM10. Considering the significance of providing the future impact of PM10 on public health, we extend our forecasting results to evaluate future changes in health effects and economic losses based on our proposed health economic losses evaluation model. Accordingly, policymakers can adjust current air pollution prevention plans and formulate new plans according to the results of forecasting, evaluation and early-warning. Empirical research shows that the developed framework is applicable in China and may become a promising technique to enrich the current research and meet the requirements of air quality management and haze governance.