bluuebunny/crossref_metadata_2025 huggingface dataset:
Salt Stress Induces Differentiated Nitrogen Uptake and Antioxidant Responses in Two Contrasting Barley Landraces from MENA Region
Authors: Ben Azaiez Fatma Ezzahra , Ayadi Sawsen , Capasso Giorgia , Landi Simone , Paradisone Valeria , Jallouli Salma , Hammami Zied , Chamekh Zoubeir , Zouari Inès , Trifa Youssef , Esposito Sergio
Published: September 2020

The interaction between salinity and nitrogen metabolism has been investigated in two barley landraces, one tolerant (“100/1B”) and one susceptible to salinity (“Barley medenine”) from the Middle East and North Africa (MENA) region. Barley plants were exposed to 50 mM NaCl for 7 days; then, salinity was increased to 150 mM NaCl in the presence (10 mM) or limitation (1 mM) of ammonium as a nitrogen source. Upon salinity, “100/1B” was shown to support N assimilation by enhancing the glutamine synthetase (GS) and glutamine oxoglutarate aminotransferase (GOGAT) cycle under high N, and the stimulation of the glutamate dehydrogenase (GDH) pathway under low N treatment. In “Barley medenine”, salinity reduced the GS/GOGAT cycle, and increased GDH activity. Upon salinity, Heat Shock Proteins 70 and PEPC remained unchanged in “100/1B”, while they decreased in “Barley medenine”. The tolerance degree is a determining factor in enzymes’ occurrence and regulation: exposed to salinity, “100/1B” rapidly increased APX and PEPC activities, while this was delayed in “Barley medenine”. Salinity increased cyt-G6PDH levels in “100/1B”, while “Barley medenine” showed a decrease in G6PDH isoforms. Correlation analyses confirm GOGAT was related to G6PDH; GDH and APX with PEPC in “100/1B” under moderate salinity; severe salinity correlated GDH with G6PDH and PEPC. In “Barley medenine” under salinity, GOGAT was correlated with G6PDH, while APX showed a relation with PEPC. Therefore, specific enzymatic activities and occurrence can be used to determine stress responsiveness of different landraces. We suggest that the rapid increase in G6PDH, APX, and nitrogen assimilation enzymes activities represents an index of tolerance in “100/1B” and a stress symptom in “Barley medenine”.
Ethical and Societal Issues Occasioned by Xenotransplantation
Authors: Rollin Bernard E.
Published: September 2020

There are three sorts of issues associated with genetic engineering and, by implication, with xenotransplantation. These are dangers associated with the technology, animal welfare issues, and the claim that genetic engineering represents a technology that humans should not embark upon. Using the hearts of pigs for humans in need of transplants has been a major issue in xenotransplantation. There are dangers associated with such use, such as immunological rejection of the organ, endogenous viruses infecting the recipients, and issues of privacy. In addition, the issue of fair distribution of organs arises. Animal welfare issues also arise, most notably the living conditions of the donor animals, issues notably present in confinement agriculture. A major issue emerges from animals’ being kept under conditions that fail to meet the needs dictated by the animals’ biological and psychological natures. Xenotransplantation animals will be kept under deprived laboratory conditions that similarly fail to meet the animals’ natures. This is a significant concern for society in general. There are also issues of “bad ethics” arising from scientists’ disavowal of ethical concerns in science. This in turn, coupled with societal ignorance of science, creates a climate for proliferation of religious and other non-rational concerns, such as the claim that xenotransplantation violates God’s will. These spurious concerns can only be ameliorated when public understanding of science improves, and scientific understanding of ethics increases.
Dystocia after Unwanted Mating as One of the Risk Factors in Non-Spayed Bitches—A Retrospective Study
Authors: Dejneka Grzegorz Jakub , Ochota Małgorzata , Bielas Wiesław , Niżański Wojciech
Published: September 2020

This article presents a retrospective study on dystocia cases in bitches that were unintentionally mated and carried an unwanted pregnancy in the last 39 years. The evaluated medical records include 76 cases of difficult labour, which is 8.3% of 914 dystocia cases recorded during the period. Of these bitches, 38.2% (29/76) were 8 years, and 18.4% (14/76) were younger than 12 months. In 67/76 cases (88.2%), conservative (pharmacological and manual) obstetrical assistance proved to be unsuccessful, and caesarian section (CS) had to be performed, in contrast to the remaining recorded cases of dystocia (in which the pregnancy was intended and expected) when CS was performed significantly less often, in 71.5% (599/838) of cases. In unplanned pregnancies, 46.6% (110/236) of delivered pups were dead compared to only 26.4% (864/3273) dead pups in planned pregnancies. p value < 0.05 was considered significant. Despite the widespread availability of the spaying procedure nowadays and its safety, unplanned and unwanted pregnancies in dogs are still a concern in clinical practice. However, throughout the years investigated here, we observed an apparent decrease in the occurrence of dystocia after unintended mating, with much less recorded cases from year 2004 (71 vs. 5). Most probably, this is due to the increasing popularity of surgical castration in both females and males, and rising societal awareness of its importance, giving hope that some improvement in the welfare of dogs has already been achieved.
Chemometric Strategies for Spectroscopy-Based Food Authentication
Authors: Biancolillo Alessandra , Marini Federico , Ruckebusch Cyril , Vitale Raffaele
Published: September 2020

In the last decades, spectroscopic techniques have played an increasingly crucial role in analytical chemistry, due to the numerous advantages they offer. Several of these techniques (e.g., Near-InfraRed—NIR—or Fourier Transform InfraRed—FT-IR—spectroscopy) are considered particularly valuable because, by means of suitable equipment, they enable a fast and non-destructive sample characterization. This aspect, together with the possibility of easily developing devices for on- and in-line applications, has recently favored the diffusion of such approaches especially in the context of foodstuff quality control. Nevertheless, the complex nature of the signal yielded by spectroscopy instrumentation (regardless of the spectral range investigated) inevitably calls for the use of multivariate chemometric strategies for its accurate assessment and interpretation. This review aims at providing a comprehensive overview of some of the chemometric tools most commonly exploited for spectroscopy-based foodstuff analysis and authentication. More in detail, three different scenarios will be surveyed here: data exploration, calibration and classification. The main methodologies suited to addressing each one of these different tasks will be outlined and examples illustrating their use will be provided alongside their description.
Healthcare Applications of Artificial Intelligence and Analytics: A Review and Proposed Framework
Authors: Azzi Sabrina , Gagnon Stéphane , Ramirez Alex , Richards Gregory
Published: September 2020

Healthcare is considered as one of the most promising application areas for artificial intelligence and analytics (AIA) just after the emergence of the latter. AI combined to analytics technologies is increasingly changing medical practice and healthcare in an impressive way using efficient algorithms from various branches of information technology (IT). Indeed, numerous works are published every year in several universities and innovation centers worldwide, but there are concerns about progress in their effective success. There are growing examples of AIA being implemented in healthcare with promising results. This review paper summarizes the past 5 years of healthcare applications of AIA, across different techniques and medical specialties, and discusses the current issues and challenges, related to this revolutionary technology. A total of 24,782 articles were identified. The aim of this paper is to provide the research community with the necessary background to push this field even further and propose a framework that will help integrate diverse AIA technologies around patient needs in various healthcare contexts, especially for chronic care patients, who present the most complex comorbidities and care needs.
Estimation of Free Fatty Acids in Stored Paddy Rice Using Multiple-Kernel Support Vector Regression
Authors: Wang Qiyang , Han Feng , Wu Zidan , Lan Tianyi , Wu Wenfu
Published: September 2020

Grain quality changes during the storage period, and an important grain quality indictor is the free fatty acid (FFA) content. Understanding real-time change of FFA content in stored grain is significant for grain storage safety. However, the FFA content requires manual detection with time-consuming and complex procedures. Thus, this paper is dedicated to developing a method to estimate FFA content in stored grain accurately. We proposed a machine learning approach—multiple-kernel support vector regression—to complete this goal, which improved the accuracy and robustness of the FFA estimation. The effectiveness of the proposed approach was validated by the grain storage data collected from northeast China. To show the merits of the proposed method, several prevailing prediction methods, such as single-kernel support vector regression, multiple linear regression, and back propagation neural network, were introduced for comparative purposes, and several quantitative statistical indexes were adopted to evaluate the performance of different models. The results showed that the proposed approach can achieve a high accuracy with mean absolute error of 0.341 mg KOH/100 g, root mean square error of 0.442 mg KOH/100 g, and mean absolute percentage error of 2.026%. Among the four models tested, the multiple-kernel support vector regression model performed best and made the most robust forecasts of FFA content in stored grain.
Group Pile Effect on Temperature Distributions inside Energy Storage Pile Foundations
Authors: Sailauova Dilnura , Mamesh Zhamilya , Zhang Dichuan , Lee Deuckhang , Shon Chang-Seon , Kim Jong R.
Published: September 2020

Energy storage pile foundations are being developed for storing renewable energy by utilizing compressed air energy storage technology. Previous studies on isolated piles indicate that compressed air can result in pressure and temperature fluctuations in the pile, which can further affect safety of the pile foundation. Meanwhile, the temperature changes and distributions for the pile and surrounding soil also are influenced by adjacent piles in typical group pile constructions. Therefore, dynamic thermal transfer simulations were conducted in this paper to investigate the temperature changes and distributions in the concrete pile and surrounding soil for group pile construction. The main parameter in this study is the spacing of the piles. The analysis results show that the group pile effect significantly increases the temperature up to more than 100 °C depending on the location and changes its distribution in both concrete and soil due to the heat transferred from the adjacent piles. The final stabilized temperature can be as high as 120 °C in the concrete pile and 110 °C in the soil after numerous loading cycles, which is about 4 times higher than typical thermo-active energy pile applications. Thus, it is important to include the group pile effect for design and analysis of the energy storage pile foundation.
Scheduling in Heterogeneous Distributed Computing Systems Based on Internal Structure of Parallel Tasks Graphs with Meta-Heuristics
Authors: Velarde Martinez Apolinar
Published: September 2020

The problem of scheduling parallel tasks graphs (PTGs) represented by directed acyclic graphs (DAGs) in heterogeneous distributed computing systems (HDCSs) is considered an nondeterministic polynomial time (NP) problem due to the diversity of characteristics and parameters, generally opposed, intended to be optimized. The PTGs are scheduled by a scheduler that determines the best location for the sub-tasks that constitute the PTGs and is responsible for allocating the resources of the HDCS to the sub-tasks of the PTGs. To optimize scheduling and allocations, the scheduler extracts characteristics from the internal structure of the PTGs. The prevailing characteristic in existing research is the critical path (CP), which is limited to providing execution paths of PTGs; considering this limitation, we extend the array method proposed in Velarde, which extracts two additional characteristics to the CP: the layering and the density of the graph for scheduling. These characteristics are represented as integer values of the PTGs to be scheduled; the values obtained from the characteristics are stored in arrays representing populations that are evaluated with the heuristic univariate marginal distribution algorithm (UMDA) and in terms of comparison with the genetic algorithm. With the best allocations produced by the algorithms, two performance parameters are evaluated: makespan and waiting time. The results indicate that when more PTGs characteristics are considered, resource allocations are optimized, and scheduling times are reduced. The results obtained with the heuristic algorithms show that UMDA provides shorter scheduling and allocation times compared with the genetic algorithm; UMDA widely distributes the sub-tasks in the clusters, whereas the genetic algorithm compacts the assignments of the PTGs in the clusters with a longer convergence time that translates into longer scheduling and allocation times. Extensive explanations of these conclusions are provided in this work, based on the conducted experiments.
Sea Breeze Front and Outdoor Thermal Comfort during Summer in Northeastern Brazil
Authors: Anjos Max , Lopes António , Lucena Andrews José de , Mendonça Francisco
Published: September 2020

Characterizing the behaviour of the sea breeze phenomenon is the foremost factor in the reduction in the heat stress and the achievement of the pleasant environment in coastal cities globally. However, this seminal study shows that the Sea Breeze Front (SBF) development can be related to an increase in outdoor thermal discomfort in a northeastern Brazilian city during summer. We explored the relationship between SBF and thermal comfort conditions using in situ meteorological observations, the SBF identification method, local climate zones (LCZs) classification, and the Physiological Equivalent Temperature (PET) thermal comfort index. SBF days and Non-SBF days were characterized in terms of weather conditions, combining meteorological data and technical bulletins. SBF days included hot and sunny days associated with the centre of the Upper Tropospheric Cyclonic Vortices (UTCV). In contrast, Non-SBF days were observed in UTCV’s periphery because of cloudy sky and rainfall. The results showed that the mean temperature and PET in the SBF days were 2.0 °C and 3.8 °C higher, respectively, compared to Non-SBF days in all LCZ sites. The highest PET, of 40.0 °C, was found on SBF days. Our findings suggest that SBF development could be an aggravating factor for increasing heat stress of the people living in the northeastern coast of the Brazilian city, after SBF passage.
Assessment of the Impact of PM2.5 Exposure on the Daily Mortality of Circulatory System in Shijiazhuang, China
Authors: Guiqin Guiqin , Xingqin Xingqin , Huayue Huayue , Yaqin Yaqin , Pengpeng Pengpeng
Published: September 2020

Air pollution can increase the morbidity and mortality of cardiovascular and cerebrovascular diseases, but there are few related studies in counties and cities with serious pollution in China. China is at a critical stage of environmental pollution control. Assessing the health impact of PM2.5 (particulate matter with a diameter equal or lower than 2.5 micrometers) on the death toll from cardiovascular and cerebrovascular diseases in heavily polluted counties and cities is of great importance to the formulation of air defense policies related to PM 2.5. Generalized additive models (GAMs) were used to analyze the effects of PM2.5 exposure on the death toll of circulatory system diseases in 16 districts, counties and cities in Shijiazhuang from 2014 to 2016 after controlling the long-term trend of the time series, seasonal effects, holiday effects, air temperature, relative humidity and other factors. The average PM2.5 concentration was 121.2 ± 96.6 μg/m3; during the corresponding period, the daily mean mortality of circulatory system diseases in Shijiazhuang was 4.6 ± 4.7. With the increase of PM2.5 by 10 μg/m3, the risk of total death from circulatory system diseases with a lag of two days (lag02) increased by 3.3‰ (95% confidence interval (CI): 1.0025, 1.0041). The relative risk (RR) of the effect of PM2.5 exposure on the death toll of the circulatory system in Shijiazhuang is consistent with the spatial distribution of the PM2.5 concentration and the mortality of circulatory system diseases: the RR of the eastern plain with heavy pollution and a relatively dense population is high, while the RR of the western mountainous area with relatively light pollution and a relatively sparse population is low. For every 10-μg/m3 increase of PM2.5, the risk of the increasing death toll from circulatory system diseases in Luancheng of the eastern plain is the highest at 11.9‰ (95% CI: 1.0071, 1.0168), while the RR of Pingshan of the western mountainous area is the lowest at 2.1‰ (95% CI: 0.9981, 1.0062). Conclusions: Based on the epidemiological analysis and GAMs model, after controlling for other confounding factors, PM2.5 exposure increased the death risk of the circulatory system in Shijiazhuang, and the risk is higher in heavily polluted plain areas. It provides a scientific basis for formulating scientific air pollution prevention and control policies and provides a reference for improving the prevention awareness of sensitive groups.
Salt Stress-Induced Structural Changes Are Mitigated in Transgenic Tomato Plants Over-Expressing Superoxide Dismutase
Authors: Bogoutdinova Liliya R. , Lazareva Elena M. , Chaban Inna A. , Kononenko Neonila V. , Dilovarova Tatyana , Khaliluev Marat R. , Kurenina Ludmila V. , Gulevich Alexander A. , Smirnova Elena A. , Baranova Ekaterina N.
Published: September 2020

Various abiotic stresses cause the appearance of reactive oxygen species (ROS) in plant cells, which seriously damage the cellular structures. The engineering of transgenic plants with higher production of ROS-scavenging enzyme in plant cells could protect the integrity of such a fine intracellular structure as the cytoskeleton and each cellular compartment. We analyzed the morphological changes in root tip cells caused by the application of iso-osmotic NaCl and Na2SO4 solutions to tomato plants harboring an introduced superoxide dismutase gene. To study the roots of tomato plants cultivar Belyi Naliv (WT) and FeSOD-transgenic line, we examined the distribution of ROS and enzyme-linked immunosorbent detection of α-tubulin. In addition, longitudinal sections of the root apexes were compared. Transmission electronic microscopy of atypical cytoskeleton structures was also performed. The differences in the microtubules cortical network between WT and transgenic plants without salt stress were detected. The differences were found in the cortical network of microtubules between WT and transgenic plants in the absence of salt stress. While an ordered microtubule network was revealed in the root cells of WT tomato, no such degree of ordering was detected in transgenic line cells. The signs of microtubule disorganization in root cells of WT plants were manifested under the NaCl treatment. On the contrary, the cytoskeleton structural organization in the transgenic line cells was more ordered. Similar changes, including the cortical microtubules disorganization, possibly associated with the formation of atypical tubulin polymers as a response to salt stress caused by Na2SO4 treatment, were also observed. Changes in cell size, due to both vacuolization and impaired cell expansion in columella zone and cap initials, were responsible for the root tip tissue modification.
Voluntary Language Switching in the Context of Bilingual Aphasia
Authors: Grunden Nicholas , Piazza Giorgio , García-Sánchez Carmen , Calabria Marco
Published: September 2020

As studies of bilingual language control (BLC) seek to explore the underpinnings of bilinguals’ abilities to juggle two languages, different types of language switching tasks have been used to uncover switching and mixing effects and thereby reveal what proactive and reactive control mechanisms are involved in language switching. Voluntary language switching tasks, where a bilingual participant can switch freely between their languages while naming, are being utilized more often due to their greater ecological validity compared to cued switching paradigms. Because this type of task had not yet been applied to language switching in bilingual patients, our study sought to explore voluntary switching in bilinguals with aphasia (BWAs) as well as in healthy bilinguals. In Experiment 1, we replicated previously reported results of switch costs and mixing benefits within our own bilingual population of Catalan-Spanish bilinguals. With Experiment 2, we compared both the performances of BWAs as a group and as individuals against control group performance. Results illustrated a complex picture of language control abilities, indicating varying degrees of association and dissociation between factors of BLC. Given the diversity of impairments in BWAs’ language control mechanisms, we highlight the need to examine BLC at the individual level and through the lens of theoretical cognitive control frameworks in order to further parse out how bilinguals regulate their language switching.
Deciphering the Role of Innate Immune NF-ĸB Pathway in Pancreatic Cancer
Authors: Khurana Namrata , Dodhiawala Paarth B. , Bulle Ashenafi , Lim Kian-Huat
Published: September 2020

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with no effective treatment option. A predominant hallmark of PDAC is the intense fibro-inflammatory stroma which not only physically collapses vasculature but also functionally suppresses anti-tumor immunity. Constitutive and induced activation of the NF-κB transcription factors is a major mechanism that drives inflammation in PDAC. While targeting this pathway is widely supported as a promising therapeutic strategy, clinical success is elusive due to a lack of safe and effective anti-NF-κB pathway therapeutics. Furthermore, the cell type-specific contribution of this pathway, specifically in neoplastic cells, stromal fibroblasts, and immune cells, has not been critically appraised. In this article, we highlighted seminal and recent literature on molecular mechanisms that drive NF-κB activity in each of these major cell types in PDAC, focusing specifically on the innate immune Toll-like/IL-1 receptor pathway. We reviewed recent evidence on the signaling interplay between the NF-κB and oncogenic KRAS signaling pathways in PDAC cells and their collective contribution to cancer inflammation. Lastly, we reviewed clinical trials on agents that target the NF-κB pathway and novel therapeutic strategies that have been proposed in preclinical studies.
Butane Isomerization as a Diagnostic Tool in the Rational Design of Solid Acid Catalysts
Authors: Potter Matthew E. , Le Brocq Joshua J.M. , Oakley Alice E. , McShane Evangeline B. , Vandegehuchte Bart D. , Raja Robert
Published: September 2020

The growing demand for isobutane as a vital petrochemical feedstock and chemical intermediate has for many decades surpassed industrial outputs that can be supplied through liquified petroleum gases. Alternative methods to resource the isobutane market have been explored, primarily the isomerization of linear n-butane to the substituted isobutane. To date the isobutane market is valued at over 20 billion US dollars, enticing researchers to seek unique and novel catalytic materials to improve on current commercial practices. Two main classes of catalysts have dominated the butane isomerization literature in the last few decades; namely microporous zeolites and sulfated zirconia. Both have been widely researched for butane isomerization, to the point where key catalytic descriptors such as acidity, framework topology and metal doping are becoming well understood. While this provides new researchers with a roadmap for developing new materials, it is has also begun developing into an invaluable tool for diagnosing and understanding the effect of these individual descriptors on catalytic properties. In this review we explore the different factors that influence the active site behavior of particularly zeolites and sulfated zirconia catalysts towards understanding the use of butane isomerization as a diagnostic tool for solid-acid catalysts.
Transcriptional Regulation of Wnt/β-Catenin Pathway in Colorectal Cancer
Authors: Bian Jia , Dannappel Marius , Wan Chunhua , Firestein Ron
Published: September 2020

The Wnt/β-catenin signaling pathway exerts integral roles in embryogenesis and adult homeostasis. Aberrant activation of the pathway is implicated in growth-associated diseases and cancers, especially as a key driver in the initiation and progression of colorectal cancer (CRC). Loss or inactivation of Adenomatous polyposis coli (APC) results in constitutive activation of Wnt/β-catenin signaling, which is considered as an initiating event in the development of CRC. Increased Wnt/β-catenin signaling is observed in virtually all CRC patients, underscoring the importance of this pathway for therapeutic intervention. Prior studies have deciphered the regulatory networks required for the cytoplasmic stabilisation or degradation of the Wnt pathway effector, β-catenin. However, the mechanism whereby nuclear β-catenin drives or inhibits expression of Wnt target genes is more diverse and less well characterised. Here, we describe a brief synopsis of the core canonical Wnt pathway components, set the spotlight on nuclear mediators and highlight the emerging role of chromatin regulators as modulators of β-catenin-dependent transcription activity and oncogenic output.
Primary Cardiac Intimal Sarcoma Visualized on 2-[18F]FDG PET/CT
Authors: Andersen Kim Francis , Someh Nahid Sharghi , Loft Annika , Brittain Jane Maestri
Published: September 2020

Primary cardiac tumors are extremely rare, with an incidence of 0.001–0.03%. Twenty-five percent of these tumors are malignant, with sarcomas accounting for approximately 95%. Cardiac intimal sarcoma is the least reported subtype of primary cardiac sarcoma. These endocardial mesenchymal tumors most often arise from great arterial vessels, and are rarely located in the heart. They often present with an aggressive clinical course and have a poor prognosis, with surgical resection with achievement of free margins being the mainstay of treatment. This emphasizes the importance of an early, correct diagnosis and timely intervention. We report a 60-year-old Caucasian male with several former cardiac surgical procedures due to congenital aortic stenosis, presenting with functional mitral stenosis/insufficiency and left ventricular outflow tract obstruction (LVOTO) due to massive masses in the left ventricle and atrium of the heart. Hybrid imaging with 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) was performed prior to surgery to characterize the intracardiac masses and estimate tumor burden, as well as to identify a potential extracardiac primary malignancy.
The Advantages of New Multimodality Imaging in Choosing the Optimal Management Strategy for Patients with Hypertrophic Cardiomyopathy
Authors: Anghel Larisa , Stătescu Cristian , Șerban Ionela-Lăcrămioara , Mărănducă Minela Aida , Butcovan Doina , Clement Alexandra , Bostan Mădălina , Sascău Radu
Published: September 2020

In recent years, significant advances have been made in the diagnosis and therapeutic management of hypertrophic cardiomyopathy (HCM) patients, which has led to an important improvement in their longevity and quality of life. The use of multimodality imaging has an essential role in the diagnosis, assessing the regional distribution and severity of the disease, with important prognostic implications. At the same time, imaging contributes to the identification of optimal treatment for patients with hypertrophic cardiomyopathy, whether it is pharmaceutical, interventional or surgical treatment. Novel pharmacotherapies (like myosin inhibitors), minimally invasive procedures (such as transcatheter mitral valve repair, high-intensity focused ultrasound or radiofrequency ablation) and gene-directed approaches, may soon become alternatives for HCM patients. However, there are only few data on the early diagnosis of patients with HCM, in order to initiate treatment as soon as possible, to reduce the risk of sudden cardiac death (SCD). The aim of our review is to highlight the advantages of contemporary imaging in choosing the optimal management strategies for HCM patients, considering the novel therapies which are currently applied or studied for these patients.
Development of CT Effective Dose Conversion Factors from Clinical CT Examinations in the Republic of Korea
Authors: Lee Sang-Kyung , Kim Jung Su , Yoon Sang-Wook , Kim Jung Min
Published: September 2020

The aim of this study was to determine the conversion factors for the effective dose (ED) per dose length product (DLP) for various computed tomography (CT) protocols based on the 2007 recommendations of the International Commission on Radiological Protection (ICRP). CT dose data from 369 CT scanners and 13,625 patients were collected through a nationwide survey. Data from 3793 patients with a difference in height within 5% of computational human phantoms were selected to calculate ED and DLP. The anatomical CT scan ranges for 11 scan protocols (adult-10, pediatric-1) were determined by experts, and scan lengths were obtained by matching scan ranges to computational phantoms. ED and DLP were calculated using the NCICT program. For each CT protocol, ED/DLP conversion factors were calculated from ED and DLP. Estimated ED conversion factors were 0.00172, 0.00751, 0.00858, 0.01843, 0.01103, 0.02532, 0.01794, 0.02811, 0.02815, 0.02175, 0.00626, 0.00458, 0.00308, and 0.00233 mSv∙mGy−1∙cm−1 for the adult brain, intra-cranial angiography, C-spine, L-spine, neck, chest, abdomen and pelvis, coronary angiography, calcium scoring, aortography, and CT examinations of pediatric brain of <2 years, 4–6 years, 9–11 years, and 13–15 years, respectively. We determined ED conversion factors for 11 CT protocols using CT data obtained from a nationwide survey in Korea and Monte Carlo-based dose calculations.
Software Requirements Classification Using Machine Learning Algorithms
Authors: Dias Canedo Edna , Cordeiro Mendes Bruno
Published: September 2020

The correct classification of requirements has become an essential task within software engineering. This study shows a comparison among the text feature extraction techniques, and machine learning algorithms to the problem of requirements engineer classification to answer the two major questions “Which works best (Bag of Words (BoW) vs. Term Frequency–Inverse Document Frequency (TF-IDF) vs. Chi Squared (CHI2)) for classifying Software Requirements into Functional Requirements (FR) and Non-Functional Requirements (NF), and the sub-classes of Non-Functional Requirements?” and “Which Machine Learning Algorithm provides the best performance for the requirements classification task?”. The data used to perform the research was the PROMISE_exp, a recently made dataset that expands the already known PROMISE repository, a repository that contains labeled software requirements. All the documents from the database were cleaned with a set of normalization steps and the two feature extractions, and feature selection techniques used were BoW, TF-IDF and CHI2 respectively. The algorithms used for classification were Logist Regression (LR), Support Vector Machine (SVM), Multinomial Naive Bayes (MNB) and k-Nearest Neighbors (kNN). The novelty of our work is the data used to perform the experiment, the details of the steps used to reproduce the classification, and the comparison between BoW, TF-IDF and CHI2 for this repository not having been covered by other studies. This work will serve as a reference for the software engineering community and will help other researchers to understand the requirement classification process. We noticed that the use of TF-IDF followed by the use of LR had a better classification result to differentiate requirements, with an F-measure of 0.91 in binary classification (tying with SVM in that case), 0.74 in NF classification and 0.78 in general classification. As future work we intend to compare more algorithms and new forms to improve the precision of our models.
A New Measure to Characterize the Degree of Self-Similarity of a Shape and Its Applicability
Authors: Lee Sang-Hee , Park Cheol-Min , Choi UJin
Published: September 2020

We propose a new measure (Γ) to quantify the degree of self-similarity of a shape using branch length similarity (BLS) entropy which is defined on a simple network consisting of a single node and its branches. To investigate the properties of this measure, we computed the Γ values for 70 object groups (20 shapes in each group) in the MPEG-7 shape database and performed grouping on the values. With relatively high Γ values, identical groups had visually similar shapes. On the other hand, the identical groups with low Γ values had visually different shapes. However, the aspect of topological similarity of the shapes also warrants consideration. The shapes of statistically different groups exhibited significant visual difference from each other. Also, in order to show that the Γ can have a wide variety of applicability when properly used with other variables, we showed that the finger gestures in the (Γ, Z) space are successfully classified. Here, the Z means a correlation coefficient value between entropy profiles for gesture shapes. As shown in the applications, Γ has a strong advantage over conventional geometric measures in that it captures the geometrical and topological properties of a shape together. If we could define the BLS entropy for color, Γ could be used to characterize images expressed in RGB. We briefly discussed the problems to be solved before the applicability of Γ can be expanded to various fields.
Industrial Applications of Power Electronics
Authors: Rodrigues Eduardo M. G. , Godina Radu , Pouresmaeil Edris
Published: September 2020

Electronic applications use a wide variety of materials, knowledge, and devices, which pave the road to creative design, development, and the creation of countless electronic circuits with the purpose of incorporating them in electronic products. Therefore, power electronics have been fully introduced in industry, in applications such as power supplies, converters, inverters, battery chargers, temperature control, variable speed motors, by studying the effects and the adaptation of electronic power systems to industrial processes. Recently, the role of power electronics has been gaining special significance regarding energy conservation and environmental control. The reality is that the demand for electrical energy grows in a directly proportional manner with the improvement in quality of life. Consequently, the design, development, and optimization of power electronics and controller devices are essential to face forthcoming challenges. In this Special Issue, 19 selected and peer-reviewed papers discussing a wide range of topics contribute to addressing a wide variety of themes, such as motor drives, AC-DC and DC-DC converters, electromagnetic compatibility and multilevel converters.
FASSD: A Feature Fusion and Spatial Attention-Based Single Shot Detector for Small Object Detection
Authors: Jiang Deng , Sun Bei , Su Shaojing , Zuo Zhen , Wu Peng , Tan Xiaopeng
Published: September 2020

Deep learning methods have significantly improved object detection performance, but small object detection remains an extremely difficult and challenging task in computer vision. We propose a feature fusion and spatial attention-based single shot detector (FASSD) for small object detection. We fuse high-level semantic information into shallow layers to generate discriminative feature representations for small objects. To adaptively enhance the expression of small object areas and suppress the feature response of background regions, the spatial attention block learns a self-attention mask to enhance the original feature maps. We also establish a small object dataset (LAKE-BOAT) of a scene with a boat on a lake and tested our algorithm to evaluate its performance. The results show that our FASSD achieves 79.3% mAP (mean average precision) on the PASCAL VOC2007 test with input 300 × 300, which outperforms the original single shot multibox detector (SSD) by 1.6 points, as well as most improved algorithms based on SSD. The corresponding detection speed was 45.3 FPS (frame per second) on the VOC2007 test using a single NVIDIA TITAN RTX GPU. The test results of a simplified FASSD on the LAKE-BOAT dataset indicate that our model achieved an improvement of 3.5% mAP on the baseline network while maintaining a real-time detection speed (64.4 FPS).
Distributed Power Quality Conditioning System for Three-Phase Four-Wire Low Voltage Networks
Authors: Dovgun Valery , Temerbaev Sergei , Chernyshov Maxim , Novikov Viktor , Boyarskaya Natalia , Gracheva Elena
Published: September 2020

This paper presents distributed power quality conditioning system to compensate current and voltage distortions in three-phase four-wire networks caused by unbalanced non-linear single-phase loads. The proposed conditioning system consists of several hybrid filter units installed in various nodes for compensation of excessive neutral currents and voltage distortions in a selected area of the distribution network. The system is open and it can be easily modified by installation of new filter units. A novel hybrid filter design procedure based on filter frequency characteristics optimization in the parameters of passive and active parts is presented. A digital system of control signal computation for active filters based on the use of modern methods of spectral analysis is considered. The proposed digital control system enables selective compensation of fundamental and harmonic components. The mathematical model of the proposed power quality conditioning system is developed in the MatLab software. The simulated results show that the presented conditioning system reduces the level of neutral conductor currents and the voltage unbalance as well ensures harmonic compensation in three-phase four-wire networks.
A Predictive Model for Coal Coking Based on Product Yield and Energy Balance
Authors: Sciazko Marek , Mertas Bartosz , Kosyrczyk Ludwik , Sobolewski Aleksander
Published: September 2020

A series of experimental coal pyrolysis studies were conducted to define the parameters of a kinetic model to enable complete mass and energy balances by identifying basic process products. The developed model determines the chemical enthalpy of pyrolytic reactions, making it possible to determine the share of exothermic conversions in the coking process. To validate the model, a series of experimental pyrolysis tests of coking coals used in the coke plant and their blends were conducted, including TGA, retort, and industrial coke oven scale. Despite significant differences in the chemical composition of various coal types, element balancing allowed detection of the difference in product composition and the heat effects of the chemical conversion of such a complex substance as coal. Analysis of the heat effects of pyrolytic coal decomposition indicates substantial variability. In the first coking period, there are endothermic reactions; in the second, exothermic reactions occur. Average heat effect of the pyrolytic reaction for whole coking period is exothermic and, depending on the coal type, ranges from −5 to −50 kJ/kg. The model herein can be used to analyze many other pyrolytic processes because it also takes into account the heating rate.
Analysis of Energy Saving Effect and Cost Efficiency of ECMs to Upgrade the Building Energy Code
Authors: Kim Hye Gi , Kim Hyun Jun , Jeon Chae Hwan , Chae Myeong Won , Cho Young Hum , Kim Sun Sook
Published: September 2020

Building energy codes are key policy tools for improving building energy efficiency by defining the minimum requirement for the energy performance of new buildings. In Korea, the building energy code was focused on prescriptive criteria for a long time but is now gradually introducing performance criteria. However, switching to performance criteria is not straightforward because of the resistance of the market to abandoning the well-consolidated prescriptive criteria. The objective of this study is to derive appropriate measures to strengthen the prescriptive criteria and the performance criteria, considering both the energy-saving effect and the economic efficiency for new office buildings and educational buildings to increase the market acceptance of the building energy codes. To this end, the energy-saving effects of reference buildings resulting from the reinforcement of the prescriptive criteria in the past have been first analyzed. Then, based on the collected energy performance parameters and cost data, the economic efficiency relative to the energy saving deriving from the application of passive and active energy conservation measures (ECMs) were analyzed, and future building energy code’s reinforcement measures were derived.
RETRACTED: Fault Diagnosis of Traction Transformer Based on Bayesian Network
Authors: Xiao Yong , Pan Weiguo , Guo Xiaomin , Bi Sheng , Feng Ding , Lin Sheng
Published: September 2020

As the core equipment of a traction power supply system, the traction transformer is very important to ensure the safe and reliable operation of the system. At present, the three-ratio method is mainly used to distinguish transformer faults, whereas such a method has some defects, such as insufficient coding and over-general fault classification. At the same time, on-site maintenance personnel make an empirical judgment based on various test data, which is subjective and uncertain to a certain extent. For cases with multiple abnormal data and relatively complex conditions, on-site personnel often need to discuss and even dismantle the transformer to identify the fault, which is time-consuming and costly. In order to improve the effect of fault diagnosis for traction transformer, this paper uses Bayesian network to correlate the cause and effect of various tests and faults. By combining the results of field tests, the fault is diagnosed by the causal probability of the Bayesian network, rather than relying on the exception that occurred in a single experiment to judge its fault. The diagnosis results are more accurate and objective by using the Bayesian network. In this paper, the frequent test anomalies of the traction transformer are taken into account in the network, so that the network can more comprehensively analyze the operation situation of the traction transformer and judge the type of fault. According to field situations, based on the existing set of symptoms of the Bayesian network fault diagnosis, this paper further considers the insulation resistance, dielectric loss tangent value, oil and gas, power frequency voltage, and leakage current. By combining the association rules algorithm and the experience of the field operators, the cause–effect relationship of test data and the conditional probability parameters of the network are obtained. Then, the Bayesian network is constructed and used for traction transformer fault diagnosis. The case study shows that the four types of fault diagnosed using the Bayesian network model proposed in this paper are consistent with the fault types inspected by on-site operators, which shows promising engineering application prospects.
Effect of Silica, Activated Carbon, and Alumina Supports on NiMo Catalysts for Residue Upgrading
Authors: Kohli Kirtika , Prajapati Ravindra , Maity Samir K. , Sharma Brajendra Kumar
Published: September 2020

The effect of different supports such as silica (SBA-15), activated carbon (AC), and mesoporous alumina (Al2O3) on catalytic activities of hydrotreating nickel molybdenum (NiMo) catalysts was demonstrated for upgrading vacuum residue. Nitrogen adsorption-desorption analysis showed that SBA-15 and the AC-supported NiMo catalyst possessed a very high surface area compared to the alumina-supported catalyst. However, NiMo/Al2O3 catalyst possesses a higher pore diameter and pore volume with an appropriate surface area. X-ray diffraction (XRD) analysis showed that active metals were dispersed in the catalytic supports. Transmission electron microscopy (TEM) analysis revealed the presence of type II active MoS2 sites in the NiMo/Al2O3 catalyst, which showed weak metal-support interactions having a high intrinsic activity. Catalyst activities such as hydrodesulfurization (HDS), hydrodemetallization (HDM) and asphaltene conversion (HDAs), and hydrocracking conversions of a vacuum residue were evaluated. The highest hydrotreating and hydrocracking conversions were observed with the NiMo catalyst supported on mesoporous alumina. The results also supported that the catalyst that has a large pore diameter, high pore volume, and better active metals dispersion is highly desirable for the upgrading of a vacuum residue.
Utilization of Water-Cooled and Air-Cooled Slag Aggregate in Concrete: A Solution to the Secular Economy
Authors: El-Tair Ahmed Maher , Bakheet Ramez , El-Feky Mohamed Samy , Kohail Mohamed , Akib Shatirah
Published: September 2020

Aggregates are generally thought of as inert filler within a concrete mix, and a typical concrete mix is comprised of as much as 70–80% of them. They play an essential role in the properties of both fresh and hardened concrete. Nowadays, scientists are aiming to use waste materials, thereby replacing natural aggregates for economic and environmental considerations. This study investigates the effect of the utilization of steel slag by-product aggregates (air- and water-cooled slag) as concrete aggregates on the behavior characteristics of concrete. Various concrete mixtures, with different levels of replacement of slag aggregate (50, 75, and 100%), were conducted in order to find the optimum percentages to improve the microstructure and different properties of concrete (fresh and hardened). The results showed that increasing the fine aggregate replacement percentage led to a decrease in compressive strength values, in contrast with coarse aggregate replaced with slag aggregate. The steel slag aggregates showed potential to be used as replacement for natural aggregate with comparable compressive strength and acceptable workability.
A Systematic AQbD Approach for Optimization of the Most Influential Experimental Parameters on Analysis of Fish Spoilage-Related Volatile Amines
Authors: Freitas Jorge , Silva Pedro , Vaz-Pires Paulo , Câmara José S.
Published: September 2020

The volatile amines trimethylamine (TMA) and dimethylamine (DMA) could be used as important spoilage indices for seafood products, assisting in the determination of the rejection period. In the present study, a systematic analytical duality-by-design (AQbD) approach was used as a powerful strategy to optimize the most important experimental parameters of headspace solid-phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC-MS) conditions for the quantification of TMA and DMA in Sparus aurata. This optimization enabled the selection of the best points in the method operable design region for HS-SPME extraction (30 min; 35 °C; NaOH 15 M and NaCl 35%, w/v) and GC-MS analysis (80 °C; gradient 50 °C/min; flow rate 1 mL/min and splitless mode). The rejection day, estimated through the TMA concentration (>12 mg/100 g, at days 9–10), was compared with sensory (quality index method: day 7–8), physical (Torrymeter: day 8–9), and microbial (day 9–10) analysis, corroborating the suitability of the proposed approach for estimating the period for which they will retain an acceptable level of eating quality from a safety and sensory perspective.