bluuebunny/crossref_metadata_2025 huggingface dataset:
Technical Determinants of On-Water Rowing Performance
Authors: Holt Ana C. , Aughey Robert J. , Ball Kevin , Hopkins William G. , Siegel Rodney
Published: December 2020

Purpose: Research establishing relationships between measures of rowing technique and velocity is limited. In this study, measures of technique and their effect on rowing velocity were investigated.

Methods: Ten male singles, eight female singles, three male pairs, and six female pairs participated. Data from each stroke for forty-seven 2,000 m races were collected using Peach PowerLine and OptimEye S5 GPS units. General linear mixed modeling established modifying effects on velocity of two within-crew SD of predictor variables for each boat class, with subsequent adjustment for power, and for power and stroke rate in separate analyses. Twenty-two predictor variables were analyzed, including measures of boat velocity, gate force, and gate angle. Results were interpreted using superiority and inferiority testing with a smallest important change in velocity of 0.3%.

Results: Substantial relationships with velocity were found between most variables assessed before adjustment for power, and for power and stroke rate. Effect magnitudes were reduced for most variables after adjustment for power and further reduced after adjustment for stroke rate and power, with precision becoming inadequate in many effects. The greatest modifying effects were found for stroke rate, mean and peak force, and power output before adjustment, and for catch angle after adjustment for stroke rate and power. Substantial between-crew differences in effects were evident for most predictors in some boat classes before adjustment and in some predictors and some boat classes after adjustment for stroke rate and power.

Conclusion: The results presented reveal variables associated with improvements in rowing performance and can be used to guide technical analysis and feedback by practitioners. Higher stroke rates and greater catch angles should be targeted to improve rowing performance, and rower force development for the improvement of power output. Relationships between rowing technique and velocity can be crew-dependent and are best assessed on an individual basis for some variables.
Possible Prophylactic Approach for SARS-CoV-2 Infection by Combination of Melatonin, Vitamin C and Zinc in Animals
Authors: Fatima Sabiha , Zaidi Syed Shams , Alsharidah Ashwag Saleh , Aljaser Feda S. , Banu Naheed
Published: December 2020

SARS-CoV-2, an epidemic, causes severe stress in both human and animals and may induce oxidative stress (OS) and increases susceptibility to infection. Domestic animals are found infected by their COVID-2 suffering owners. Chronic immobilization stress (CIS), a model of psychological and physical stress of confinement, can trigger depression and anxiety in animals. We evaluated the ameliorative effect of the proposed SARS-CoV-2 prophylactic drugs melatonin, vitamin C, and zinc on CIS-induced OS, inflammation, and DNA damage in rats. Forty male Swiss albino rats (200–250 g, 7–9 weeks old) were divided into five groups as controls, CIS, treated with melatonin (20 mg/kg), and vitamin C plus zinc [VitC+Zn (250 + 2.5 mg/kg)] alone or in combination (melatonin+VitC+zinc) subjected to CIS for 3 weeks. CIS was induced by immobilizing the whole body of the rats in wire mesh cages of their size with free movement of head. Exposure to CIS significantly compromised the circulatory activities of superoxide dismutase, catalase, and glutathione with enhanced malondialdehyde, inflammatory markers (IL-6, IL10, and TNFα), and lymphocyte DNA damage in comparison to controls. Treatment with melatonin and VitC+Zn alone or in combination significantly restored the altered biochemical parameters and DNA damage of stressed rats to their respective control values. However, the cumulative action of melatonin with VitC+Zn was more effective in alleviating the CIS-induced OS, inflammation, and DNA damage. The present study indicates that the antioxidant combination can be an effective preventive measure to combat severe psychological and confinement stress-induced biochemical changes in animals due to abnormal conditions such as SARS-CoV-2.
Habituation to Transport Helps Reducing Stress-Related Behavior in Donkeys During Loading
Authors: Dai Francesca , Mazzola Silvia , Cannas Simona , Heinzl Eugenio Ugo Luigi , Padalino Barbara , Minero Michela , Dalla Costa Emanuela
Published: December 2020

Adopting proper animal management strategies, including training, might reduce to a substantial extent the adverse effects of transport-related stress in animals. The aim of this study was to evaluate the effect of habituation to transport on stress-related behaviors and physiological indicators during loading and unloading in donkeys. Fourteen donkeys were recruited and divided in two treatment groups: Habituation (H; M = 5, F = 2) and Control (C; M = 5, F = 2). H donkeys were gradually habituated to be transported, traveling together with their mothers and other adult donkeys well-accustomed to transport, while C donkeys had never been transported before. Loading and unloading phases were video recorded and behavior was analyzed. Saliva samples for cortisol concentration determination were collected at rest and after unloading. Latency time to load was significantly shorter for H donkeys than C donkeys (Mann-Whitney;p= 0.004). C donkeys also showed significantly more stress-related behaviors (Mann-Whitney;p= 0.026) and required a higher but not statistically significant number of human interventions to load. Cortisol concentration increased in both groups, but no differences were found between them (Mann-Whitney;p> 0.05). These results suggest that habituation to transport could mitigate stress during loading procedures in donkeys reducing loading time, frequency of stress-related behaviors and diminishing the need of human intervention.
Deep Feature Learning with Manifold Embedding for Robust Image Retrieval
Authors: Chen Xin , Li Ying
Published: December 2020

Conventionally, the similarity between two images is measured by the easy-calculating Euclidean distance between their corresponding image feature representations for image retrieval. However, this kind of direct similarity measurement ignores the local geometry structure of the intrinsic data manifold, which is not discriminative enough for robust image retrieval. Some works have proposed to tackle this problem by re-ranking with manifold learning. While benefiting better performance, algorithms of this category suffer from non-trivial computational complexity, which is unfavorable for its application to large-scale retrieval tasks. To address the above problems, in this paper, we propose to learn a robust feature embedding with the guidance of manifold relationships. Specifically, the manifold relationship is used to guide the automatic selection of training image pairs. A fine-tuning network with those selected image pairs transfers such manifold relationships into the fine-tuned feature embedding. With the fine-tuned feature embedding, the Euclidean distance can be directly used to measure the pairwise similarity between images, where the manifold structure is implicitly embedded. Thus, we maintain both the efficiency of Euclidean distance-based similarity measurement and the effectiveness of manifold information in the new feature embedding. Extensive experiments on three benchmark datasets demonstrate the robustness of our proposed method, where our approach significantly outperforms the baselines and exceeds or is comparable to the state-of-the-art methods.
Generative Model for Skeletal Human Movements Based on Conditional DC-GAN Applied to Pseudo-Images
Authors: Xi Wang , Devineau Guillaume , Moutarde Fabien , Yang Jie
Published: December 2020

Generative models for images, audio, text, and other low-dimension data have achieved great success in recent years. Generating artificial human movements can also be useful for many applications, including improvement of data augmentation methods for human gesture recognition. The objective of this research is to develop a generative model for skeletal human movement, allowing to control the action type of generated motion while keeping the authenticity of the result and the natural style variability of gesture execution. We propose to use a conditional Deep Convolutional Generative Adversarial Network (DC-GAN) applied to pseudo-images representing skeletal pose sequences using tree structure skeleton image format. We evaluate our approach on the 3D skeletal data provided in the large NTU_RGB+D public dataset. Our generative model can output qualitatively correct skeletal human movements for any of the 60 action classes. We also quantitatively evaluate the performance of our model by computing Fréchet inception distances, which shows strong correlation to human judgement. To the best of our knowledge, our work is the first successful class-conditioned generative model for human skeletal motions based on pseudo-image representation of skeletal pose sequences.
Special Issue on Bio-Inspired Algorithms for Image Processing
Authors: Szénási Sándor , Kertész Gábor
Published: December 2020

In the field of image processing, there are several difficult issues that do not have exact solutions due to incomplete or imperfect information and limited computation capacity [...]
On a Controlled Se(Is)(Ih)(Iicu)AR Epidemic Model with Output Controllability Issues to Satisfy Hospital Constraints on Hospitalized Patients
Authors: De la Sen Manuel , Ibeas Asier
Published: December 2020

An epidemic model, the so-called SE(Is)(Ih)(Iicu)AR epidemic model, is proposed which splits the infectious subpopulation of the classical SEIR (Susceptible-Exposed-Infectious-Recovered) model into four subpopulations, namely asymptomatic infectious and three categories of symptomatic infectious, namely slight infectious, non-intensive care infectious, and intensive care hospitalized infectious. The exposed subpopulation has four different transitions to each one of the four kinds of infectious subpopulations governed under eventually different proportionality parameters. The performed research relies on the problem of satisfying prescribed hospitalization constraints related to the number of patients via control interventions. There are four potential available controls which can be manipulated, namely the vaccination of the susceptible individuals, the treatment of the non-intensive care unit hospitalized patients, the treatment of the hospitalized patients at the intensive care unit, and the transmission rate which can be eventually updated via public interventions such as isolation of the infectious, rules of groups meetings, use of face masks, decrees of partial or total quarantines, and others. The patients staying at the non-intensive care unit and those staying at the intensive care unit are eventually, but not necessarily, managed as two different hospitalized subpopulations. The controls are designed based on output controllability issues in the sense that the levels of hospital admissions are constrained via prescribed maximum levels and the measurable outputs are defined by the hospitalized patients either under a joint consideration of the sum of both subpopulations or separately. In this second case, it is possible to target any of the two hospitalized subpopulations only or both of them considered as two different components of the output. Different algorithms are given to design the controls which guarantee, if possible, that the prescribed hospitalization constraints hold. If this were not possible, because the levels of serious infection are too high according to the hospital availability means, then the constraints are revised and modified accordingly so that the amended ones could be satisfied by a set of controls. The algorithms are tested through numerically worked examples under disease parameterizations of COVID-19.
Compound Fault Diagnosis and Sequential Prognosis for Electric Scooter with Uncertainties
Authors: Yu Ming , Lu Haotian , Wang Hai , Xiao Chenyu , Lan Dun
Published: December 2020

This paper addresses diagnosis and prognosis problems for an electric scooter subjected to parameter uncertainties and compound faults (i.e., permanent fault and intermittent fault with non-monotonic degradation). First, the diagnostic bond graph in linear fractional transformation form is used to model the uncertain electric scooter and derive the analytical redundancy relations incorporating the nominal part and uncertain part, based on which the adaptive thresholds for robust fault detection and the fault signature matrix for fault isolation can be obtained. Second, an adaptive enhanced unscented Kalman filter is proposed to identify the fault magnitudes and distinguish the fault types where an auxiliary detector is introduced to capture the appearing and disappearing moments of intermittent fault. Third, a dynamic model with usage dependent degradation coefficient is developed to describe the degradation process of intermittent fault under various usage conditions. Due to the variation of degradation coefficient and the presence of non-monotonic degradation characteristic under some usage conditions, a sequential prognosis method is proposed where the reactivation of the prognoser is governed by the reactivation events. Finally, the proposed methods are validated by experiment results.
Evolution of Physico-Chemical Properties, Microbial Biomass and Microbial Activity of an Urban Soil after De-Sealing
Authors: Renella Giancarlo
Published: December 2020

Recovery of soil fertility after de-sealing of urban soils is still poorly known. This work studied the time-related dynamics of soil physico-chemical and biochemical endpoints of urban soil in the city in Naples (Southern Italy), de-sealed for different time during construction works, that underwent colonization by volunteer plants. The results showed de-sealing decreased the soil bulk density and the soil pH value, increased the electrical conductivity (EC), total organic C (TOC) and extractable carbohydrates (TEC), total and inorganic N contents, soil basal respiration (SBR), soil microbial biomass C (MBC) and soil microbial biomass N (MBN), the substrate induced respiration (SIR) value, and enzyme activities involved in C, N, P and S mineralization. The TEC, total and inorganic N, SBR and microbial biochemical endpoints were higher in the de-sealed soils than those of an arable soil of the same area. The results show that de-sealed urban soils rapidly increase their physical, chemical and biological fertility even with no intervention, especially when they are colonized by volunteer plants.
Yield, Agronomic and Forage Quality Traits of Different Quinoa (Chenopodium quinoa Willd.) Genotypes in Northeast China
Authors: Shah Syed Sadaqat , Shi Lianxuan , Li Zhijian , Ren Guixing , Zhou Bangwei , Qin Peiyou
Published: December 2020

Quinoa (Chenopodium quinoa Willd.) grain is well known as a source of nutritious human food, but the nutritional properties of quinoa as animal fodder has not been well explored. Fifteen quinoa accessions were assessed for grain and forage yields, and morphological and quality traits during anthesis and grain filling, with the aim of selecting superior genotypes for greater production and quality traits that are well adapted to northeastern China. Variations were significant among the tested genotypes for all traits. The highest grain weight was recorded in Rainbow (27.51 g plant−1), followed by the local Chinese genotypes Longli 3, YY28 and Mengli 1. Correlation analysis revealed a significant positive association of grain yield with branches and a negative association with culm thickness and inflorescence length, whereas more branches and moderate plant height were the main yield components affecting yield. Forage shoot weight was 37.2–81.6 g plant−1, with JQ3 and ZQ1 exhibiting the highest yields. Forage yield was strongly and positively correlated with most of the morphological traits, except plant height, and was negatively associated with chlorophyll content and the fresh/dry matter ratio. Quality traits and the neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents of quinoa were significantly lower than alfalfa (Medicago sativa L.), oats (Avena sativa L.) or Leymus chinensis (Trin.) Tzvel, and the crude protein (CP) content was significantly higher than all three species, reaching above 20%. The saponin content of the whole plant was higher during anthesis than during grain filling. In conclusion, genotypes having more branches and shorter and more compact main inflorescences achieved higher grain yields, whereas genotypes possessing thick stems, more branches and moderate plant height produced more forage. Hence, the results indicate that superior quinoa genotypes have great potential to solve fodder shortages in China.
Comprehensive Statistical Evaluation of Etest®, UMIC®, MicroScan and Disc Diffusion versus Standard Broth Microdilution: Workflow for an Accurate Detection of Colistin-Resistant and Mcr-Positive E. coli
Authors: García-Meniño Isidro , Lumbreras Pilar , Valledor Pablo , Díaz-Jiménez Dafne , Lestón Luz , Fernández Javier , Mora Azucena
Published: December 2020

Four colistin susceptibility testing methods were compared with the standard broth microdilution (BMD) in a collection of 75 colistin-susceptible and 75 mcr-positive E. coli, including ST131 isolates. Taking BMD as reference, all methods showed similar categorical agreement rates (CA) of circa 90%, and a low number of very major errors (VME) (0% for the MicroScan system and Etest®, 0.7% for UMIC®), except for the disc diffusion assay (breakpoint ≤ 11 mm), which yielded false-susceptible results for 8% of isolates. Of note is the number of mcr-positive isolates (17.3%) categorized as susceptible (≤2 mg/L) by the BMD method, but as resistant by the MicroScan system. ST131 mcr-positive E. coli were identified as colistin-resistant by all MIC-based methods. Our results show that applying the current clinical cut-off (>2 mg/L), many mcr-positive E. coli remain undetected, while applying a threshold of >1 mg/L the sensitivity of detection increases significantly without loss of specificity. We propose two possible workflows, both starting with the MicroScan system, since it is automated and, importantly, it categorized all mcr-positive isolates as colistin-resistant. MicroScan should be followed by either BMD or MIC-based commercial methods for colistin resistance detection; or, alternatively, MicroScan, followed by PCR for the mcr screening.
Antimicrobial Resistance and Genomic Characterization of OXA-48- and CTX-M-15-Co-Producing Hypervirulent Klebsiella pneumoniae ST23 Recovered from Nosocomial Outbreak
Authors: Shaidullina Elvira , Shelenkov Andrey , Yanushevich Yuri , Mikhaylova Yulia , Shagin Dmitriy , Alexandrova Irina , Ershova Olga , Akimkin Vasiliy , Kozlov Roman , Edelstein Mikhail
Published: December 2020

Multidrug resistance (MDR) and hypervirulence (hv) have been long considered distinct evolutionary traits for Klebsiella pneumoniae (Kp), a versatile human pathogen. The recent emergence of Kp strains combining these traits poses a serious global threat. In this article, we describe the phenotypic and genomic characteristics of an MDR hvKp isolate, MAR14-456, representative of a nosocomial outbreak in Moscow, Russia, that was recovered from a postoperative wound in a patient who later developed multiple abscesses, fatal sepsis, and septic shock. Broth microdilution testing revealed decreased susceptibility of MAR14-456 to carbapenems (MICs 0.5–2 mg/L) and a high-level resistance to most β-lactams, β-lactam-β-lactamase-inhibitor combinations, and non-β-lactam antibiotics, except ceftazidime-avibactam, amikacin, tigecycline, and colistin. Whole-genome sequencing using Illumina MiSeq and ONT MinION systems allowed to identify and completely assemble two conjugative resistance plasmids, a typical ‘European’ epidemic IncL/M plasmid that carries the gene of OXA-48 carbapenemase, and an IncFIIK plasmid that carries the gene of CTX-M-15 ESBL and other resistance genes. MLST profile, capsular, lipopolysaccharide, virulence genes encoded on chromosome and IncHI1B/FIB plasmid, and the presence of apparently functional type I-E* CRISPR-Cas system were all characteristic of hvKp ST23, serotype K1-O1v2. Phylogenetic analysis showed the closest relatedness of MAR14-456 to ST23 isolates from China. This report highlights the threat of multiple resistance acquisition by hvKp strain and its spread as a nosocomial pathogen.
Prevalence of OXA-Type β-Lactamase Genes among Carbapenem-Resistant Acinetobacter baumannii Clinical Isolates in Thailand
Authors: Thirapanmethee Krit , Srisiri-a-nun Thayapa , Houngsaitong Jantana , Montakantikul Preecha , Khuntayaporn Piyatip , Chomnawang Mullika
Published: December 2020

Carbapenem-resistant Acinetobacter baumannii (CRAB) is a critical health concern for the treatment of infectious diseases. The aim of this study was to investigate the molecular epidemiology of CRAB emphasizing the presence of oxacillinase (OXA)-type β-lactamase-encoding genes, one of the most important carbapenem resistance mechanisms. In this study, a total of 183 non-repetitive CRAB isolates collected from 11 tertiary care hospitals across Thailand were investigated. As a result, the blaoxa-51-like gene, an intrinsic enzyme marker, was detected in all clinical isolates. The blaoxa-23-like gene was presented in the majority of isolates (68.31%). In contrast, the prevalence rates of blaoxa-40/24-like and blaoxa-58-like gene occurrences in CRAB isolates were only 4.92% and 1.09%, respectively. All isolates were resistant to carbapenems, with 100% resistance to imipenem, followed by meropenem (98.91%) and doripenem (94.54%). Most isolates showed high resistance rates to ciprofloxacin (97.81%), ceftazidime (96.72%), gentamicin (91.26%), and amikacin (80.87%). Interestingly, colistin was found to be a potential drug of choice due to the high susceptibility of the tested isolates to this antimicrobial (87.98%). Most CRAB isolates in Thailand were of ST2 lineage, but some belonged to ST25, ST98, ST129, ST164, ST215, ST338, and ST745. Further studies to monitor the spread of carbapenem-resistant OXA-type β-lactamase genes from A. baumannii in hospital settings are warranted.
In Vitro Activity of Dalbavancin against Refractory Multidrug-Resistant (MDR) Staphylococcus aureus Isolates
Authors: Bongiorno Dafne , Lazzaro Lorenzo Mattia , Stefani Stefania , Campanile Floriana
Published: December 2020

The high prevalence of methicillin-resistant Staphylococcus aureus (MRSA) infections, always treated with vancomycin and daptomycin, has led to the emergence of vancomycin-intermediate (VISA), heteroresistant vancomycin-intermediate (hVISA) and daptomycin non-susceptible (DNS) S. aureus. Even if glycopeptides and daptomycin remain the keystone for treatment of resistant S. aureus, the need for alternative therapies that target MRSA has now become imperative. The in vitro antibacterial and bactericidal activity of dalbavancin was evaluated against clinically relevant S. aureus showing raised antibiotic resistance levels, from methicillin-susceptible to Multidrug-Resistant (MDR) MRSA, including hVISA, DNS and rifampicin-resistant (RIF-R) strains. A total of 124 S. aureus strains were tested for dalbavancin susceptibility, by the broth microdilution method. Two VISA and 2 hVISA reference strains, as well as a vancomycin-resistant (VRSA) reference strain and a methicillin-susceptible Staphylococcus aureus (MSSA) reference strain, were included as controls. Time–kill curves were assayed to assess bactericidal activity. Dalbavancin demonstrated excellent in vitro antibacterial and bactericidal activity against all S. aureus resistance classes, including hVISA and DNS isolates. The RIF-R strains showed the highest percentage of isolates with non-susceptibility, reflecting the correlation between rpoB mutations and VISA/hVISA emergence. Our observations suggest that dalbavancin can be considered as an effective alternative for the management of severe MRSA infections also sustained by refractory phenotypes.
Inter-Relationship between Platelet-Derived Microparticles and Oxidative Stress in Patients with Venous Thromboembolism
Authors: Signorelli Salvatore Santo , Conti Gea Oliveri , Fiore Maria , Elfio Maria Grazia , Cristaldi Antonio , Nicolosi Ilenia , Zuccarello Pietro , Zanoli Luca , Gaudio Agostino , Di Raimondo Domenico , Ferrante Margherita
Published: December 2020

Background: Hypercoagulative conditions play a key role in venous thromboembolism (VTE). Inflammation is currently linked to VTE, but the potential role of circulating microparticles and oxidative stress (OxS) must be elucidated. The aim of this study was to evaluate platelet-derived microparticles and surrogate OxS biomarkers in patients diagnosed with VTE through a case–control study. Methods: Platelet-derived microparticles (MPs), pro-thrombinase-induced clotting time assay (PiCT), phospholipids (PLPs), malondialdehyde (MDA), 4-hydroxynonenale (4-HNE), thiobarbituric acid reactive substances (TBARs), superoxide dismutase (SOD), and galectin-3 (Gal-3) were measured in VTE patients and in healthy controls. Results: PLPs, 4-HNE, TBARs, and Gal-3 were higher in VTE patients compared to controls; conversely, SOD was lower. A significant non-linear regression between OxS biomarkers and the markers of platelet degranulation was found. Conclusion: Our results suggest that OxS and platelet degranulation are concomitant pathophysiological mechanisms in VTE.
Electrical Energy Prediction in Residential Buildings for Short-Term Horizons Using Hybrid Deep Learning Strategy
Authors: Khan Zulfiqar Ahmad , Ullah Amin , Ullah Waseem , Rho Seungmin , Lee Miyoung , Baik Sung Wook
Published: December 2020

Smart grid technology based on renewable energy and energy storage systems are attracting considerable attention towards energy crises. Accurate and reliable model for electricity prediction is considered a key factor for a suitable energy management policy. Currently, electricity consumption is rapidly increasing due to the rise in human population and technology development. Therefore, in this study, we established a two-step methodology for residential building load prediction, which comprises two stages: in the first stage, the raw data of electricity consumption are refined for effective training; and the second step includes a hybrid model with the integration of convolutional neural network (CNN) and multilayer bidirectional gated recurrent unit (MB-GRU). The CNN layers are incorporated into the model as a feature extractor, while MB-GRU learns the sequences between electricity consumption data. The proposed model is evaluated using the root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE) metrics. Finally, our model is assessed over benchmark datasets that exhibited an extensive drop in the error rate in comparison to other techniques. The results indicated that the proposed model reduced errors over the individual household electricity consumption prediction (IHEPC) dataset (i.e., RMSE (5%), MSE (4%), and MAE (4%)), and for the appliances load prediction (AEP) dataset (i.e., RMSE (2%), and MAE (1%)).
Investigation of the Characteristics of NLS-PNA: Influence of NLS Location on Invasion Efficiency
Authors: Aiba Yuichiro , Urbina Gerardo , Shibata Masanari , Shoji Osami
Published: December 2020

Peptide nucleic acid can recognise sequences in double-stranded DNA (dsDNA) through the formation of a double-duplex invasion complex. This double-duplex invasion is a promising method for the recognition of dsDNA in cellula because peptide nucleic acid (PNA) invasion does not require the prior denaturation of dsDNA. To increase its applicability, we developed PNAs modified with a nuclear localisation signal (NLS) peptide. In this study, the characteristics of NLS-modified PNAs were investigated for the future design of novel peptide-modified PNAs.
Rapid Sequentially Palladium Catalyzed Four-Component Synthesis of Novel Fluorescent Biaryl-Substituted Isoxazoles
Authors: Deden Tobias , May Lars , Reiss Guido J. , Müller Thomas J. J.
Published: December 2020

A series of novel 3- and 5-biaryl-substituted isoxazoles was prepared by a rapid microwave-assisted four-component three-step synthesis: concatenating Sonogashira coupling, cyclocondensation, and Suzuki coupling in a one-pot fashion. The Pd-catalyst was successfully employed in the sense of a sequentially catalyzed process, i.e., without the addition of further catalyst loading. Biaryl-substituted isoxazoles with donor–acceptor decoration possess remarkable photophysical properties, such as high fluorescence quantum yields in solution up to ΦF = 0.86 and large Stokes shifts up to 10,000 cm−1. The experimental absorption and emission characteristics can be reproduced and rationalized by computations on the DFT (density functional theory) and TDDFT (time-dependent density functional theory) level of theory.
SILP Materials as Effective Catalysts in Selective Monofunctionalization of 1,1,3,3-Tetramethyldisiloxane
Authors: Kukawka Rafal , Pawlowska-Zygarowicz Anna , Januszewski Rafal , Dzialkowska Joanna , Pietrowski Mariusz , Zielinski Michal , Maciejewski Hieronim , Smiglak Marcin
Published: December 2020

Functionalized siloxanes are one of the most important classes of organosilicon compounds, thus the enhancement of current methods of its synthesis is an important issue. Herein, we present the selective and highly effective reaction between 1,1,3,3-tetramethyldisiloxane (TMDSO) and 1-octene (1-oct), using SILP (supported ionic liquid phase) materials containing a rhodium catalyst immobilized in three phosphonium ionic liquids (ILs) differing in the structure of cation. Studies have shown high potential for using SILP materials as catalysts due to their high catalytic activity and selectivity, easy separation process, and the possibility of reusing the catalyst in subsequent reaction cycles without adding a new portion of the catalyst. Using the most active SILP material SiO2/[P66614][NTf2]/[{Rh(μ-OSiMe3)(cod)}2] allows for reuse of the catalyst at least 50 times in an efficient and highly selective monofunctionalization of TMDSO.
Long-Term Trend Analysis in Annual and Seasonal Precipitation, Maximum and Minimum Temperatures in the Southwest United States
Authors: Djaman Koffi , Koudahe Komlan , Bodian Ansoumana , Diop Lamine , Ndiaye Papa Malick
Published: December 2020

The objective of this study is to perform trend analysis in the historic data sets of annual and crop season [May–September] precipitation and daily maximum and minimum temperatures across the southwest United States. Eighteen ground-based weather stations were considered across the southwest United States for a total period from 1902 to 2017. The non-parametric Mann–Kendall test method was used for the significance of the trend analysis and the Sen’s slope estimator was used to derive the long-term average rates of change in the parameters. The results showed a decreasing trend in annual precipitation at 44.4% of the stations with the Sen’s slopes varying from −1.35 to −0.02 mm/year while the other stations showed an increasing trend. Crop season total precipitation showed non-significant variation at most of the stations except two stations in Arizona. Seventy-five percent of the stations showed increasing trend in annual maximum temperature at the rates that varied from 0.6 to 3.1 °C per century. Air cooling varied from 0.2 to 1.0 °C per century with dominant warming phenomenon at the regional scale of the southwest United States. Average annual minimum temperature had increased at 69% of the stations at the rates that varied from 0.1 to 8 °C over the last century, while the annual temperature amplitude showed a decreasing trend at 63% of stations. Crop season maximum temperature had significant increasing trend at 68.8% of the stations at the rates varying from 0.7 to 3.5 °C per century, while the season minimum temperature had increased at 75% of the stations.
Assessment of Hydroxyapatite Nanospheres Incorporated Dentin Adhesive. A SEM/EDX, Micro-Raman, Microtensile and Micro-Indentation Study
Authors: Al-Hamdan Rana S , Almutairi Basil , Kattan Hiba F , Alresayes Saad , Abduljabbar Tariq , Vohra Fahim
Published: December 2020

Hydroxyapatite (HA) delivery with resin adhesives has potential for re-mineralization of resin–dentin interface. The study prepared an adhesive containing HA and confirmed its presence in adhesive and interaction with the dentin using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Micro-Raman spectroscopy. The aim was to assess the influence of HA incorporation in dentin adhesive on its microtensile bond strength (μ-tbs) and Knoop microhardness (KHN). Thirty teeth each were bonded with CA and HA adhesive using a 10-s smear and photo-polymerized. The specimens in each adhesive group (CA and HA) were divided into sub-groups of 24 h, 8 weeks, and 16 weeks (n = 10) aging durations. μ-tbs was assessed at a crosshead speed of 0.5 mm/minute and bonded interface was analyzed using SEM (n = 20) and Raman spectroscopy (n = 10). Softening of HA adhesive and CA was assessed using KHN. HA adhesive presented higher μ-tbs compared to CA. With an increase in storage time, HA adhesive presented with 100% adhesive failure. Softening was less and KHN was higher for HA adhesive compared to CA (p < 0.05). KHN reduction was higher in CA [19.6 (5.1)%] compared to the HA adhesives [9.7 (4.5)%]. HA adhesive showed superior μTBS and microhardness compared to CA. In the absence of nanoleakage, HA modified adhesive exhibited enhanced bond integrity and better durability of resin dentin bond compared to control adhesive.
ESCA as a Tool for Exploration of Metals’ Surface
Authors: Bolli Eleonora , Kaciulis Saulius , Mezzi Alessio
Published: December 2020

The main principles and development of electron spectroscopy for chemical analysis (ESCA) are briefly reviewed. The role of ESCA techniques (X-ray photoelectron spectroscopy and Auger electron spectroscopy) in the investigation of metallic surfaces is discussed, evidencing their importance and analytical potentiality. An overview is given of a series of recent experimental cases of ESCA application for the characterization of different metals and metallic alloys, illustrating the main results and various phenomena, such as the formation of impurity defects, corrosion, migration of constituent elements in various alloys, clustering in liquid alloy, etc., that can occur on the surface and the interface of investigated materials. These materials comprise the collection coins of noble metals, some metal alloys and Ni-based superalloys, nitride coatings on stainless steel, composite material with TiAlV alloy, treated austenitic steels, and graphene interface with polycrystalline metal foils. The present review could be particularly recommended for the newcomers to the research field of surface analysis and its application for various metals, their treatments, and possible modifications in operating conditions.
Biometry, Distribution and Genetic Characterization of Blue Jack Mackerel Trachurus picturatus (Bowdich, 1825), a Rare Pelagic Fish Species in the Adriatic Sea
Authors: Zorica Barbara , Bušelić Ivana , Čikeš Keč Vanja , Vuletin Vedran , Pleić Ivana Lepen , Isajlović Igor , Radonić Ivana , Vrgoč Nedo
Published: December 2020

The blue jack mackerel Trachurus picturatus (Bowdich, 1825) specimens (N = 155) were collected during the MEDITS survey, done along the eastern side, precisely, of the Croatian fishing ground in July 2018. Biometrical analysis of ten morphometric and five meristic characters, as well as genetic analysis proved that the collected specimens were blue jack mackerel. The total length (TL) and weight (W) of all observed specimens ranged from 9.2 to 33.7 cm (12.15 ± 2.95 cm) and from 5.79 to 384.94 g (17.64 ± 39.42 g), respectively. All calculated length–length relationships were linear (r > 0.923). Sex was determined only on two larger specimens (28 cm < TL < 32.8 cm), which were females. In the length–weight relationship, positive allometry was established (b = 3.1789). Based on 37 partial cytochrome b sequences, the overall haplotype diversity (h) of 0.812 ± 0.048 and nucleotide diversity (π) of 0.0064 ± 0.0007 indicated high levels of haplotype and low nucleotide diversity. The obtained sequences were compared to previously published research within the Northeast Atlantic Ocean and the Mediterranean Sea, confirming the absence of genetic structure among these populations.
Hormonal Environment and HER2 Status in Extra-Mammary Paget’s Disease (eMPD): A Systematic Literature Review and Meta-Analysis with Clinical Considerations
Authors: Angelico Giuseppe , Santoro Angela , Inzani Frediano , Straccia Patrizia , Arciuolo Damiano , Mulè Antonino , Valente Michele , Spadola Saveria , D’Alessandris Nicoletta , Garganese Giorgia , Cianfrini Federica , Piermattei Alessia , Scambia Giovanni , Zannoni Gian Franco
Published: December 2020

Background. Extra-mammary Paget’s disease (EMPD) is a rare neoplasm of epithelial origin, whose precise incidence is not clear. Starting from what is already known, we performed a systematic review and meta-analysis to investigate in male and female patients the immunohistochemical expression of biological markers that could serve as potential prognostic/therapeutic factors, including only human epidermal growth factor receptor 2 (HER2/neu), Estrogen Receptor (ER), Progesterone Receptor (PR), and Androgen Receptor (AR). Methods. A literature search was performed of the PubMed, Scopus, and Web of Science databases for English-language studies published from January 2000 to June 2020. Results. A total of 27 studies with 713 patients assessed the role of HER2/neu, AR, ER, and PR expression in male and female with EMPD. The overall rate of HER2/neu expression was 30%, the expression’s rate for ER and AR was 13% and 40%, respectively, and the overall rate for PR was 8%. The subgroup analysis revealed that there is a different expression of molecular markers between male and female patients. Conclusions. This study revealed that AR status and HER2/neu overexpression/amplification have been shown as two fundamental pathogenetic pathways in both female and male patients affected by EMPD.
Skew Convolutional Codes
Authors: Sidorenko Vladimir , Li Wenhui , Günlü Onur , Kramer Gerhard
Published: December 2020

A new class of convolutional codes, called skew convolutional codes, that extends the class of classical fixed convolutional codes, is proposed. Skew convolutional codes can be represented as periodic time-varying convolutional codes but have a description as compact as fixed convolutional codes. Designs of generator and parity check matrices, encoders, and code trellises for skew convolutional codes and their duals are shown. For memoryless channels, one can apply Viterbi or BCJR decoding algorithms, or a dualized BCJR algorithm, to decode skew convolutional codes.
Semiotic Aggregation in Deep Learning
Authors: Muşat Bogdan , Andonie Răzvan
Published: December 2020

Convolutional neural networks utilize a hierarchy of neural network layers. The statistical aspects of information concentration in successive layers can bring an insight into the feature abstraction process. We analyze the saliency maps of these layers from the perspective of semiotics, also known as the study of signs and sign-using behavior. In computational semiotics, this aggregation operation (known as superization) is accompanied by a decrease of spatial entropy: signs are aggregated into supersign. Using spatial entropy, we compute the information content of the saliency maps and study the superization processes which take place between successive layers of the network. In our experiments, we visualize the superization process and show how the obtained knowledge can be used to explain the neural decision model. In addition, we attempt to optimize the architecture of the neural model employing a semiotic greedy technique. To the extent of our knowledge, this is the first application of computational semiotics in the analysis and interpretation of deep neural networks.
Circuit Model and Analysis of Molded Case Circuit Breaker Interruption Phenomenon
Authors: Lee Kun-A , Cho Young-Maan , Lee Ho-Joon
Published: December 2020

There are complex physical phenomena for the interpretation of a molded case circuit breaker (MCCB) in a distribution system. Most of the studies of MCCB interruption phenomena were conducted with numerical analysis and experiments. This traditional approach may help improve the performance of the MCCB itself, but it is difficult to find connectivity with other systems. In this paper, the circuit model is proposed and the interruption phenomenon of MCCB is analyzed. The interruption of the MCCB is divided into three sections to deal with physical phenomena occurring in each area. A simplified model is proposed considering the characteristics of each section. Based on this model, the circuit model is proposed. To implement the features of each section, the calculation of physical phenomena is carried out, and this is expressed in the circuit model with resistance and zener diode. Comparing the results of the simulation with the experimental results is as follows. For 7-plates (basic state), the error rate is −5.6% in section II and 16.8% in section III. For 1-plate, the error rate is 36.5% in section II and −17.0% in section III. This case shows much difference from the simplified model in this paper, resulting in the largest error rate. The 7-plates and 5-plates cases, which are available in the general MCCB owing to the shortest distance from the arc, represent a relatively small error rate. Using the proposed circuit model, it is expected that the entire system, including the interruption phenomenon, can be interpreted as a single circuit model.
Design of an Enhanced FLC-Based Controller for Selective Harmonic Compensation in Active Power Filters
Authors: de Barros Junior Odair , Amorim Thiago Silva , Carletti Daniel , Frizera Neto Anselmo , Encarnação Lucas Frizera
Published: December 2020

The increasing number of electronic loads has introduced several harmonics into the power system, leading to a growth in the importance of filters intended for their mitigation. Thus, it is important to have the knowledge to select operational limits of each new filter connected in the power grid. Likewise, obtaining these harmonics requires robust tracking systems that provide enough information for better filter selectivity. This paper proposes a selective harmonic active filter control based on Fourier linear combiner (FLC) algorithms for a three-phase electrical grid. The presented system is enabled to track each harmonic order and sequence components with great robustness, extracting positive, negative, and zero sequence information from each harmonic for further filter selectivity. It also proposes a new strategy to improve the FLC-based algorithms in tracking frequencies in power grid disturbances. Simulated results of the algorithm and a real-time simulation of a selective active power filter (SAPF) were presented, validating the performance in several scenarios.
An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery
Authors: Duan Wenxian , Song Chuanxue , Peng Silun , Xiao Feng , Shao Yulong , Song Shixin
Published: December 2020

An accurate state-of-charge (SOC) can not only provide a safe and reliable guarantee for the entirety of equipment but also extend the service life of the battery pack. Given that the chemical reaction inside the lithium-ion battery is a highly nonlinear dynamic system, obtaining an accurate SOC for the battery management system is very challenging. This paper proposed a gated recurrent unit recurrent neural network model with activation function layers (GRU-ATL) to estimate battery SOC. The model used deep learning technology to establish the nonlinear relationship between current, voltage, and temperature measurement signals and battery SOC. Then the online SOC estimation was carried out on different testing sets using the trained model. The experiments in this paper showed that the GRU-ATL network model could realize online SOC estimation under different working conditions without relying on an accurate battery model. Compared with the gated recurrent unit recurrent neural (GRU) network model and long short-term memory (LSTM) network model, the GRU-ATL network model had more stable and accurate SOC prediction performance. When the measurement data contained noise, the experimental results showed that the SOC prediction accuracy of GRU-ATL model was 0.1–0.4% higher than the GRU model and 0.3–0.7% higher than the LSTM model. The mean absolute error (MAE) of SOC predicted by the GRU-ATL model was stable in the range of 0.7–1.4%, and root mean square error (RMSE) was stable between 1.2–1.9%. The model still had high prediction accuracy and robustness, which could meet the SOC estimation in complex vehicle working conditions.
Electrical Modelling of Switching Arcs in a Low Voltage Relay at Low Currents
Authors: Najam Ammar , Pieterse Petrus , Uhrlandt Dirk
Published: December 2020

The arc behaviour of short, low current switching arcs is not well understood and lacks a reliable model. In this work, the behaviour of an arc in the air is studied during contact separation at low DC currents (0.5 A to 20 A) and for small gap lengths (0 mm to 6 mm). The experiments are performed on a low voltage relay with two different electrode configurations. The arc voltage is measured during the opening of the contacts at constant current. The arc length is determined optically by tracing the mean path of the arc over time from a series of high-speed images. From the synchronised data of voltage vs. distance, first a sudden jump of the voltage at the start of contact opening is observed. Secondly, a sudden change in the voltage gradient occurs as the arc is elongated. Short arcs with a length up to approximately 1.25 mm show an intense radiation in the overall gap region and high voltage gradients. An unexpected behaviour never reported before was observed for longer arcs at low current: Two characteristic regions occur, a region in front of the cathode, with a length of approximately 1.25 mm, having an intense radiation and a high voltage gradient as well as a region of much lower radiation intensity and a comparatively lower voltage gradient in the remaining gap area despite a small anode spot region. The characteristic border of approximately 1.25 mm is almost independent of the current. A generalised arc voltage model is proposed based on the assumption that a constant sheath voltage and two discrete field regions exist, which are modelled as two independent linear functions of voltage vs. length. The data for various currents is combined to yield a general non-linear function for predicting the arc voltage vs. arc length and current.