bluuebunny/crossref_metadata_2025 huggingface dataset:
Melatonin: Regulation of Biomolecular Condensates in Neurodegenerative Disorders
Authors: Loh Doris , Reiter Russel J.
Published: September 2021

Biomolecular condensates are membraneless organelles (MLOs) that form dynamic, chemically distinct subcellular compartments organizing macromolecules such as proteins, RNA, and DNA in unicellular prokaryotic bacteria and complex eukaryotic cells. Separated from surrounding environments, MLOs in the nucleoplasm, cytoplasm, and mitochondria assemble by liquid–liquid phase separation (LLPS) into transient, non-static, liquid-like droplets that regulate essential molecular functions. LLPS is primarily controlled by post-translational modifications (PTMs) that fine-tune the balance between attractive and repulsive charge states and/or binding motifs of proteins. Aberrant phase separation due to dysregulated membrane lipid rafts and/or PTMs, as well as the absence of adequate hydrotropic small molecules such as ATP, or the presence of specific RNA proteins can cause pathological protein aggregation in neurodegenerative disorders. Melatonin may exert a dominant influence over phase separation in biomolecular condensates by optimizing membrane and MLO interdependent reactions through stabilizing lipid raft domains, reducing line tension, and maintaining negative membrane curvature and fluidity. As a potent antioxidant, melatonin protects cardiolipin and other membrane lipids from peroxidation cascades, supporting protein trafficking, signaling, ion channel activities, and ATPase functionality during condensate coacervation or dissolution. Melatonin may even control condensate LLPS through PTM and balance mRNA- and RNA-binding protein composition by regulating N6-methyladenosine (m6A) modifications. There is currently a lack of pharmaceuticals targeting neurodegenerative disorders via the regulation of phase separation. The potential of melatonin in the modulation of biomolecular condensate in the attenuation of aberrant condensate aggregation in neurodegenerative disorders is discussed in this review.
Aryl Hydrocarbon Receptor and Cysteine Redox Dynamics Underlie (Mal)adaptive Mechanisms to Chronic Intermittent Hypoxia in Kidney Cortex
Authors: Correia Maria João , Pimpão António B. , Lopes-Coelho Filipa , Sequeira Catarina O. , Coelho Nuno R. , Gonçalves-Dias Clara , Barouki Robert , Coumoul Xavier , Serpa Jacinta , Morello Judit , Monteiro Emília C. , Pereira Sofia A.
Published: September 2021

We hypothesized that an interplay between aryl hydrocarbon receptor (AhR) and cysteine-related thiolome at the kidney cortex underlies the mechanisms of (mal)adaptation to chronic intermittent hypoxia (CIH), promoting arterial hypertension (HTN). Using a rat model of CIH-HTN, we investigated the impact of short-term (1 and 7 days), mid-term (14 and 21 days, pre-HTN), and long-term intermittent hypoxia (IH) (up to 60 days, established HTN) on CYP1A1 protein level (a sensitive hallmark of AhR activation) and cysteine-related thiol pools. We found that acute and chronic IH had opposite effects on CYP1A1 and the thiolome. While short-term IH decreased CYP1A1 and increased protein-S-thiolation, long-term IH increased CYP1A1 and free oxidized cysteine. In addition, an in vitro administration of cystine, but not cysteine, to human endothelial cells increased Cyp1a1 expression, supporting cystine as a putative AhR activator. This study supports CYP1A1 as a biomarker of obstructive sleep apnea (OSA) severity and oxidized pools of cysteine as risk indicator of OSA-HTN. This work contributes to a better understanding of the mechanisms underlying the phenotype of OSA-HTN, mimicked by this model, which is in line with precision medicine challenges in OSA.
An Ascorbate Bluetooth© Analyzer for Quality Control of Fresh-Cut Parsley Supply Chain
Authors: Spissu Ylenia , Barberis Antonio , D’hallewin Guy , Orrù Germano , Scano Alessandra , Serra Gavina Rita , Pinna Milo , Pinna Cristian , Marceddu Salvatore , Serra Pier Andrea
Published: September 2021

This work provides companies in the fresh-cut produce sector with an Ascorbate Bluetooth© Analyzer (ABA), a screen-printed sensor-based device for ascorbic acid (AA) detection, for quality control all along the supply chain. The amperometric detection of AA on fresh and fresh-cut parsley, under correct and incorrect storage temperature, allowed us to investigate the kinetics of AA decay in response to oxidative stress. The role of ascorbate oxidase (AOx) and ascorbate peroxidase (APx) was studied. ABA was used in situ by unskilled personnel. Treatments influenced AA decay kinetics, which were linear in fresh parsley, and non-linear in fresh-cut. Two hours at 28 °C immediately after chopping, the resilience of the fresh-cut parsley was reduced, even though the cold chain was restored. Two hours at −2 °C caused a rapid loss of AA until its complete decay after 72 h. Significant differences between treatments were observed in both the expression and activity of AOx and APx. ABA registered sudden changes of parsley AA following unpredicted variations of temperature during processing or transport. It was useful to remedy the effects of unexpected flaws in the cold chain, which can be proposed for quality preservation of different fresh-cut produce.
Glyoxal-Lysine Dimer, an Advanced Glycation End Product, Induces Oxidative Damage and Inflammatory Response by Interacting with RAGE
Authors: Lee Hee-Weon , Gu Min Ji , Kim Yoonsook , Lee Jee-Young , Lee Seungju , Choi In-Wook , Ha Sang Keun
Published: September 2021

The glyoxal-lysine dimer (GOLD), which is a glyoxal (GO)-derived advanced glycation end product (AGE), is produced by the glycation reaction. In this study, we evaluated the effect of GOLD on the oxidative damage and inflammatory response in SV40 MES 13 mesangial cells. GOLD significantly increased the linkage with the V-type immunoglobulin domain of RAGE, a specific receptor of AGE. We found that GOLD treatment increased RAGE expression and reactive oxygen species (ROS) production in mesangial cells. GOLD remarkably regulated the protein and mRNA expression of nuclear factor erythroid 2-related factor 2 (NRF2) and glyoxalase 1 (GLO1). In addition, mitochondrial deterioration and inflammation occurred via GOLD-induced oxidative stress in mesangial cells. GOLD regulated the mitogen-activated protein kinase (MAPK) and the release of proinflammatory cytokines associated with the inflammatory mechanism of mesangial cells. Furthermore, oxidative stress and inflammatory responses triggered by GOLD were suppressed through RAGE inhibition using RAGE siRNA. These results demonstrate that the interaction of GOLD and RAGE plays an important role in the function of mesangial cells.
Diosmetin Ameliorates Vascular Dysfunction and Remodeling by Modulation of Nrf2/HO-1 and p-JNK/p-NF-κB Expression in Hypertensive Rats
Authors: Meephat Sariya , Prasatthong Patoomporn , Potue Prapassorn , Bunbupha Sarawoot , Pakdeechote Poungrat , Maneesai Putcharawipa
Published: September 2021

Diosmetin is a citrus flavonoid that has antioxidant and anti-inflammatory effects. This study examined the effect of diosmetin on blood pressure and vascular alterations and its underlying mechanisms in experimentally hypertensive rats. Male Sprague rats were administered Nω-nitro-l-arginine methyl ester L-NAME for five weeks and were given diosmetin at doses of 20 or 40 mg/kg or captopril (5 mg/kg) for two weeks. Diosmetin alleviated hypertension, improved endothelial dysfunction, and suppressed the overactivity of sympathetic nerve-mediated vasoconstriction in aorta and mesentery hypertensive rats (p < 0.05). Increases in plasma and aortic tissue malondialdehyde (MDA) and carotid superoxide generations and reductions of plasma superoxide dismutase, catalase, and nitric oxide in hypertensive rats were ameliorated by diosmetin (p < 0.05). Diosmetin increased the protein expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) in hypertensive rats. Furthermore, diosmetin mitigated hypertrophy and collagen accumulation of the aortic wall in L-NAME rats. It exhibited an anti-inflammatory effect by reducing interleukin-6 (IL-6) accumulation and by overexpressing the phospho-c-Jun N-terminal kinases (p-JNK) and the phospho-nuclear factor-kappaB (p-NF-κB) proteins in the aorta (p < 0.05). Captopril was a positive control substance and had similar effects to diosmetin. In summary, diosmetin reduced blood pressure and alleviated vascular abnormalities in L-NAME-treated rats. These effects might be related to antioxidant and anti-inflammatory effects as well as to the modulation of the expression of the Nrf2/HO1 and p-JNK/NF-κB proteins.
Operation and Challenges of Multi-Infeed LCC–HVDC System: Commutation Failure, AC/DC Power Flow, and Voltage Stability
Authors: Rehman Bilawal , Rehman Atiq ur , Khan Waqar Ahmad , Sami Irfan , Ro Jong-Suk
Published: September 2021

This paper presents a detailed analysis of commutation failure, AC/DC power flow, and voltage stability of multi-infeed high-voltage direct current (HVDC). The use of HVDC power transmission technology has become common in modern power systems. During the past two decades, HVDC technology has been extensively used for long-distance bulk power transmission to remote areas. Throughout the world, the demand for power has drastically increased in recent years due to industrialization; such situations make HVDC an economic candidate because the distance between power generation plants and load areas is significantly very long. The line-commutated converter (LCC) technology-based HVDC system is well more mature than other available conversion schemes (i.e., voltage source converters), and it is widely used in high-power projects. China had approximately 50 HVDC–LCC links in 2020, and a single LCC-based link with the highest capacity is 12 GW. The installation of several HVDC links in an existing power network has led to a situation where two or more HVDC links terminate in the electric vicinity of each other’s AC network or even in same AC busbar. Such scenarios are termed multi-infeed HVDC system. Multi-infeed HVDC systems bring various challenges related to voltage stability, local and concurrent commutation failure, and AC/DC power flow. Here, the literature available on these phenomena of LCC-based HVDC is discussed for future research. The assumptions and drawbacks of various techniques used for investigating the mentioned phenomena are also highlighted.
An Attention Enhanced Spatial–Temporal Graph Convolutional LSTM Network for Action Recognition in Karate
Authors: Guo Jianping , Liu Hong , Li Xi , Xu Dahong , Zhang Yihan
Published: September 2021

With the increasing popularity of artificial intelligence applications, artificial intelligence technology has begun to be applied in competitive sports. These applications have promoted the improvement of athletes’ competitive ability, as well as the fitness of the masses. Human action recognition technology, based on deep learning, has gradually been applied to the analysis of the technical actions of competitive sports athletes, as well as the analysis of tactics. In this paper, a new graph convolution model is proposed. Delaunay’s partitioning algorithm was used to construct a new spatiotemporal topology which can effectively obtain the structural information and spatiotemporal features of athletes’ technical actions. At the same time, the attention mechanism was integrated into the model, and different weight coefficients were assigned to the joints, which significantly improved the accuracy of technical action recognition. First, a comparison between the current state-of-the-art methods was undertaken using the general datasets of Kinect and NTU-RGB + D. The performance of the new algorithm model was slightly improved in comparison to the general dataset. Then, the performance of our algorithm was compared with spatial temporal graph convolutional networks (ST-GCN) for the karate technique action dataset. We found that the accuracy of our algorithm was significantly improved.
Heat Triggered Release Behavior of Eugenol from Tobacco Leaf
Authors: Song Xuyan , Wei Min , Pan Xi , He Yunlu , Cui Xinjiao , Du Xiaodi , Li Junsheng
Published: September 2021

Fragrance is a commonly used substance in a number of commercial products, and fine control over the release behavior of the fragrance is essential for its successful application. Understanding the release behavior of the fragrance is the key to realizing the control of its release. Herein, we use tobacco leaf as the model substrate and investigate the mechanism of eugenol release from tobacco leaf. Our results show that interaction between eugenol and tobacco leaf is weak physical adsorption, and the eugenol release from tobacco leaf substrate is a temperature-dependent process. Further analysis on the release behavior reveals that eugenol release is closely associated with the morphology change of tobacco leaves under heating conditions. Our results provide insight into the release mechanism of fragrance from polymer substrate and may be useful for the future design of fragrance release systems.
An Investigation of Work-Based Education and Training Needs for Effective BIM Adoption and Implementation: An Organisational Upskilling Model
Authors: Semaan Jalal , Underwood Jason , Hyde Jason
Published: September 2021

Research reveals that organisations in general are keen to provide their staff with the support needed to boost their competency in BIM and subsequently leverage the effectiveness of its implementation. However, employers need a decision-making tool to make better informed investments in specific work-based education and training that addresses the immediate upskilling needs of their employees. Therefore, the aim of this research project is to investigate the significance of Work-Based Education and Training (WBET) needs through the development of an Organisational Upskilling Model (OUM). A comprehensive literature review retrieved 25 hypotheses that were tested for significance from a questionnaire survey completed by 73 AEC professionals working for a large-scale UK engineering consultancy. Based on the current expert sample, the study revealed a holistic inter-organisational agreement that technology training is in high demand. Whereas, the organisational body of knowledge needs only to be better publicised, as employees were unaware of its immediate availability. OUM proved that the most influential variables to BIM Uptake were Attitude (R2 = 0.569 & Q2 = 0.395), User Competency (R2 = 0.523 & Q2 = 0.369), and Organisational Support (R2 = 0.400 & Q2 = 0.233). Informed by their in-house culture, OUM enabled the sponsoring engineering consultant to predict immediate WBET upskilling needs and plan for the required capital investment. However, ‘OUM’ may be applied by any BIM-adopting organisation seeking WBET informed decision-making assistance for better upskilling, continuous improvement, organisational learning, and ultimately business growth.
Polyphasic Characterization of Microbiota of “Mastredda”, a Traditional Wooden Tool Used during the Production of PDO Provola dei Nebrodi Cheese
Authors: Busetta Gabriele , Garofalo Giuliana , Mangione Guido , Botta Luigi , Franciosi Elena , Di Gerlando Rosalia , Todaro Massimo , Licitra Giuseppe , Scatassa Maria Luisa , Gaglio Raimondo , Settanni Luca
Published: September 2021

The biofilms of the wooden tables used for the acidification of the curd were investigated for PDO Provola dei Nebrodi cheese, a traditional stretched cheese made in eastern Sicily (southern Italy) from raw cows’ milk. To this purpose the wooden tables of four dairy facilities were analysed for their microbiota by scanning electron microscopy (SEM) analysis and a combined culture-independent and -dependent microbiological approach. SEM inspection showed an almost continuous biofilm formation. MiSeq Illumina analysis identified 8 phyla, 16 classes, 25 orders, 47 families and 50 genera. Corynebacterium, Bifidobacterium and lactic acid bacteria (LAB) were detected in all samples. In particular, the LAB genera detected on all wooden tables were Lactobacillus, Streptococcus and Lactococcus. LAB dominated the surfaces of all wooden tables with levels higher than 7.0 Log CFU/cm2. In particular, the LAB found at the highest levels were mesophilic cocci. Coagulase positive staphylococci, Salmonella spp., Listeria monocytogenes and Shiga-toxigenic Escherichia coli were never detected. Twenty-seven dominating LAB strains were identified within the genera Enterococcus, Lactobacillus, Lacticaseibacillus, Lactiplantibacillus, Levilactobacillus, Lactococcus, Leuconostoc, Pediococcus and Streptococcus. This work showed that the wooden table used during the production of PDO Provola dei Nebrodi cheese is a safe system and a microbiologically active tool.
The Relationship between Stress Levels Measured by a Questionnaire and the Data Obtained by Smart Glasses and Finger Pulse Oximeters among Polish Dental Students
Authors: Mocny-Pachońska Katarzyna , Doniec Rafał J. , Sieciński Szymon , Piaseczna Natalia J. , Pachoński Marek , Tkacz Ewaryst J.
Published: September 2021

Stress is a physical, mental, or emotional response to a change and is a significant problem in modern society. In addition to questionnaires, levels of stress may be assessed by monitoring physiological signals, such as via photoplethysmogram (PPG), electroencephalogram (EEG), electrocardiogram (ECG), electrodermal activity (EDA), facial expressions, and head and body movements. In our study, we attempted to find the relationship between the perceived stress level and physiological signals, such as heart rate (HR), head movements, and electrooculographic (EOG) signals. The perceived stress level was acquired by self-assessment questionnaires in which the participants marked their stress level before, during, and after performing a task. The heart rate was acquired with a finger pulse oximeter and the head movements (linear acceleration and angular velocity) and electrooculographic signals were recorded with JINS MEME ES_R smart glasses (JINS Holdings, Inc., Tokyo, Japan). We observed significant differences between the perceived stress level, heart rate, the power of linear acceleration, angular velocity, and EOG signals before performing the task and during the task. However, except for HR, these signals were poorly correlated with the perceived stress level acquired during the task.
Using Artificial Neural Network Algorithm and Remote Sensing Vegetation Index Improves the Accuracy of the Penman-Monteith Equation to Estimate Cropland Evapotranspiration
Authors: Liu Yan , Zhang Sha , Zhang Jiahua , Tang Lili , Bai Yun
Published: September 2021

Accurate estimation of evapotranspiration (ET) can provide useful information for water management and sustainable agricultural development. However, most of the existing studies used physical models, which are not accurate enough due to our limited ability to represent the ET process accurately or rarely focused on cropland. In this study, we trained two models of estimating croplands ET. The first is Medlyn-Penman-Monteith (Medlyn-PM) model. It uses artificial neural network (ANN)-derived gross primary production along with Medlyn’s stomatal conductance to compute surface conductance (Gs), and the computed Gs is used to estimate ET using the PM equation. The second model, termed ANN-PM, directly uses ANN to construct Gs and simulate ET using the PM equation. The results showed that the two models can reasonably reproduce ET with ANN-PM showing a better performance, as indicated by the lower error and higher determination coefficients. The results also showed that the performances of ANN-PM without the facilitation of any remote sensing (RS) factors degraded significantly compared to the versions that used RS factors. We also evidenced that ANN-PM can reasonably characterize the time-series changes of ET at sites having a dry climate. The ANN-PM method can reasonably estimate the ET of croplands under different environmental conditions.
Smart Toys in Early Childhood and Primary Education: A Systematic Review of Technological and Educational Affordances
Authors: Komis Vassilis , Karachristos Christofors , Mourta Despina , Sgoura Konstantina , Misirli Anastasia , Jaillet Alain
Published: September 2021

The present paper presents a systematic review of the last 30 years that concerns records on Smart Toys and focuses on toys regarding early childhood and primary education children (3–12 years old). This paper aims to analyse and categorise smart toys (50 articles) in terms of their technological and educational affordances. The results show that the toys are designed based on four main technological affordances and their combinations. The educational affordances of smart toys are studied in terms of different use modes and their learning objectives aimed to identify specific objectives in different subjects and objectives based on transversal competencies such as problem solving, spatial thinking, computational thinking, collaboration and symbolic thinking. Finally, with the multiple correspondence analysis, the correlations between smart toys’ individual technological and educational affordances are grouped with the evolution of affordances related to their development date. In conclusion, in recent years, smart toys concern special sciences (programming) and some 21st-century skills (STEM and computational thinking). In contrast, in the first 20 years, the interest focused more on transverse skills, such as collaboration, emotional thinking, symbolic thinking, story-telling and problem solving.
The Effect of Regular Physical Activity on Muscle and Adipose Tissue in Premenopausal Women
Authors: Kutac Petr , Buzga Marek , Elavsky Steriani , Bunc Vaclav , Jandacka Daniel , Krajcigr Miroslav
Published: September 2021

Regular physical activity (PA) plays an important role in the prevention of several noninfectious chronic diseases, partly due to its positive effects on body composition. The relationship between the amount of weekly PA and body composition in premenopausal women, however, remains unclear. The objective of the study is to assess the relationship between body composition and the volume of PA in full-time employed premenopausal women. The study included 136 women (aged 41.07 ± 2.77 years). The women were divided into tertiles (T1–T3) according to the level of total reported weekly PA. T1 were women with the lowest volume of PA, T2 were women with a medium volume, and T3 were women with the highest PA volume. DXA was used to measure body mass (BM), body fat (BF), visceral fat (VFA), and fat-free mass (FFM). For the comparison of means, we used one-way ANOVA and a t test. Practical significance was verified with effect of size. Significant differences were found between women in T1 vs. T2 and T1 vs. T3. When compared with T2, T1 women had a higher BM (+6.10 kg), BF (+5.98 kg), BF (+5.42%), and VF (+17.49 cm2). When compared with T3, T1 women had a higher BM (+5.99 kg), BF (+6.42 kg), BF (+5.89%), and VFA (+20.71 cm2). We can conclude that a higher volume of weekly PA is associated with lower BF, but appears to have no effect on FFM.
Low-Complexity Recursive Least-Squares Adaptive Algorithm Based on Tensorial Forms
Authors: Fîciu Ionuț-Dorinel , Stanciu Cristian-Lucian , Anghel Cristian , Elisei-Iliescu Camelia
Published: September 2021

Modern solutions for system identification problems employ multilinear forms, which are based on multiple-order tensor decomposition (of rank one). Recently, such a solution was introduced based on the recursive least-squares (RLS) algorithm. Despite their potential for adaptive systems, the classical RLS methods require a prohibitive amount of arithmetic resources and are sometimes prone to numerical stability issues. This paper proposes a new algorithm for multiple-input/single-output (MISO) system identification based on the combination between the exponentially weighted RLS algorithm and the dichotomous descent iterations in order to implement a low-complexity stable solution with performance similar to the classical RLS methods.
Coupling and Optical Analysis of a Round-Cornered Square-Shaped Microresonator
Authors: Panindre Prabodh , Mousavi N.S.Susan , Paredes Bruna , Rasras Mahmoud , Kumar Sunil
Published: September 2021

An on-chip structure consisting of a round-cornered square-shaped (RCSS) resonator as an optical filter is studied via optical experiments, analytical modeling, and numerical techniques. A general coupling model is shown to accurately represent the entire spectral response; the model also provides an understanding of the influence of geometrical and coupling parameters on the resonance characteristics of the RCSS microresonators. The selection of an optimum radius of curvature for rounding off the sharp corners of square microresonators can provide higher quality factors than that of conventional circular resonators. The rotation of the RCSS at the central corner coupling point is also shown to improve the quality factor and remove the minimal phase mismatch requirement and dependency on interaction length. The model results are validated with an electromagnetic finite domain analysis (EMFD) and optical experiments, for which an RCSS on a silicon-on-insulator platform is fabricated. It is shown that the optical performance characteristics (quality factor, transmission ratio, and extinction ratio) of the microresonators are very sensitive to the coupling parameters and must be carefully considered in addition to geometrical length, rotation, and curvature effects. Due to the change in coupling introduced by rotation, the quality factor of the round-cornered square-shaped microresonator can be significantly larger than a circular ring with the same size, thereby establishing RCSS as a competitive alternative to circular microresonators.
Potassium Recovery from Potassium Solution and Seawater Using Different Adsorbents
Authors: Shin Sora , Jho Eun Hea , Park HyunJu , Lee Sungjong , Kim Joon Ha
Published: September 2021

The potassium (K) sorption characteristics with three adsorbents, natural zeolite, ammonium acetate-treated zeolite, and manganese nodule, were studied and compared to see the potential use of manganese nodule as an alternative K adsorbent. In general, the Langmuir isotherm could fit the K sorption in the KCl solutions at different pH conditions better than the Freundlich isotherm. Based on the Langmuir parameters, the maximum K sorption was greater for the zeolite-based adsorbents (i.e., 40–42 mg g−1) than the manganese nodule (i.e., 2.0 mg g−1) at acidic conditions, while the manganese nodule (i.e., 9.7 mg g−1) showed better K sorption at neutral conditions. With the seawater samples, the zeolite-based adsorbents showed higher K recovery (4–14%) than the manganese nodule (0–8.8%). The K sorption on the zeolite-based adsorbents followed the pseudo-second-order kinetics and the K sorption rates were higher for the treated zeolite than the natural zeolite. The repeated sorption tests showed that the natural zeolite could potentially be reused up to three times without any significant loss of K sorption capacity, while the ammonium acetate-treated zeolite lost its K sorption capacity after the single sorption test. Overall, the results show that the manganese nodule may potentially be the alternative to zeolite for K recovery under certain conditions, yet the zeolite-based adsorbents are generally better than the manganese nodule. Thus, more studies to enhance the K recovery using zeolite, including surface modified zeolite, are recommended.
A Study on the Night Visibility Evaluation Method of Color Temperature Convertible Automotive Headlamps Considering Weather Conditions
Authors: Kang Ho-Joon , Kwon Seong-Jin
Published: September 2021

This study evaluated a method of applying color temperature convertible headlamps to improve driving safety in adverse weather conditions such as fog and rain during night driving. The concept of color temperature convertible headlamps is to improve the driver’s visibility by driving with a color temperature of 6000 K on a clear night and switching to a color temperature of 3000 K with better light transmittance at night in adverse weather. Through this study, a method for evaluating the night visibility related to such color temperature convertible headlamps under bad weather at night was suggested. To this end, a method of using a facility that can implement weather conditions such as fog and rain was proposed, and evaluation conditions according to the climatic conditions and the distance of pedestrian targets were set and actual tests were conducted.
Impact of Combine Harvester Technological Operations on Global Warming Potential
Authors: Savickas Dainius , Steponavičius Dainius , Špokas Liudvikas , Saldukaitė Lina , Semenišin Michail
Published: September 2021

The agricultural machinery is making a considerable negative contribution to the acceleration of global warming. In this study, we analyzed the impact of combine harvesters (CHs) on the global warming potential (GWP) by evaluating the telematics data from 67 CHs operating in Lithuania and Latvia between 2016 and 2020. This study examined the use of their technological operations and the associated impacts on ambient air and performed field tests using the same CH model to determine the composition of exhaust gases and the impact of different technological operations on GWP. The data confirmed the release of significant GWP during indirect operation, and it was estimated that considerable lengths of time were spent in idle (~20%) and transport (~13%) modes. During these operations, over 13% of the total GWP (~27.4 t year−1 per CH), affected by emissions, was released. It was calculated that a GWP reduction exceeding 1 t year−1 per machine can be achieved by optimizing the idling and transport operations. The dual telematics/field test data approach facilitates a comprehensive assessment of both the impact of CH exhaust gases on GWP and the methods for reducing the negative impact on the environment.
Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion
Authors: Chen Wen , Ju Chengwei , Li Yanzhou , Hu Shanshan , Qiao Xi
Published: September 2021

The rapid and accurate identification of sugarcane stem nodes in the complex natural environment is essential for the development of intelligent sugarcane harvesters. However, traditional sugarcane stem node recognition has been mainly based on image processing and recognition technology, where the recognition accuracy is low in a complex natural environment. In this paper, an object detection algorithm based on deep learning was proposed for sugarcane stem node recognition in a complex natural environment, and the robustness and generalisation ability of the algorithm were improved by the dataset expansion method to simulate different illumination conditions. The impact of the data expansion and lighting condition in different time periods on the results of sugarcane stem nodes detection was discussed, and the superiority of YOLO v4, which performed best in the experiment, was verified by comparing it with four different deep learning algorithms, namely Faster R-CNN, SSD300, RetinaNet and YOLO v3. The comparison results showed that the AP (average precision) of the sugarcane stem nodes detected by YOLO v4 was 95.17%, which was higher than that of the other four algorithms (78.87%, 88.98%, 90.88% and 92.69%, respectively). Meanwhile, the detection speed of the YOLO v4 method was 69 f/s and exceeded the requirement of a real-time detection speed of 30 f/s. The research shows that it is a feasible method for real-time detection of sugarcane stem nodes in a complex natural environment. This research provides visual technical support for the development of intelligent sugarcane harvesters.
Personalized Scholar Recommendation Based on Multi-Dimensional Features
Authors: Jin Huiying , Zhang Pengcheng , Dong Hai , Shao Mengqiao , Zhu Yuelong
Published: September 2021

The rapid development of social networking platforms in recent years has made it possible for scholars to find partners who share similar research interests. Nevertheless, this task has become increasingly challenging with the dramatic increase in the number of scholar users over social networks. Scholar recommendation has recently become a hot topic. Thus, we propose a personalized scholar recommendation approach, Mul-RSR (Multi-dimensional features based Research Scholar Recommendation), which improves accuracy and interpretability. In this work, Mul-RSR aims to provide personalized recommendation for academic social platforms. Mul-RSR uses the Doc2Vec text model and the random walk algorithm to calculate textual similarity and social relevance to measure the correlation between scholars. It is able to recommend Top-N scholars for each scholar based on multi-layer perception and attention mechanism. To evaluate the proposed approach, we conduct a series of experiments based on public and self-collected ResearchGate datasets. The results demonstrate that our approach improves the recommendation hit rate, and the hit rate reaches 59.31% when the N value is 30. Through these evaluations, we show Mul-RSR can provide a more solid scientific decision-making basis and achieve a better recommendation effect.
Comparative Analysis of Reasoning in Russian Classic Poetry
Authors: Timofeeva Mariya
Published: September 2021

The paper considers the pragmatic textual level and focuses on peculiarities of reasoning realized in the lyric verses written by the representatives of Russian classic poetry. The investigated material of poetic texts includes the verses written by A.K. Tolstoy, K.K. Sluchevsky, and I.F. Annensky. The purposes of the study involve adapting the rhetorical structure theory (RST) to poetic texts, annotating these texts, searching for regularities of poetic reasoning specific to the considered authors. Applying RST to poetic texts was a novel task; the lack of experience made it necessary to adapt the method, that is, to elaborate the adequate set of rhetorical relations and to specify two sets of criteria: segmenting a text and identifying the relations. The resulting set of relations consists of 34 items. After annotating the texts in terms of the adopted RST, several lines of comparison were the objects of investigation. They include collating the frequency spectrums of relations and the semantical groups of relations for the three authors, as well as comparing two periods of creativity for A.K. Tolstoy and K.K. Sluchevsky. The results of the comparative investigation revealed certain regularities both in the distribution of isolated relations and the distribution of semantically grouped relations.
Application of Integrated Geophysical Methods for Site Suitability of Research Infrastructures (RIs) in China
Authors: Shang Yan-Jun , Yang Chang-Gen , Jin Wei-Jun , Chen Yan-Wei , Hasan Muhammad , Wang Yue , Li Kun , Lin Da-Ming , Zhou Min
Published: September 2021

Research Infrastructures (RIs) are essential to achieve excellence in innovative scientific research. However, because of limited land availability and specific geological requirements, evaluating the viability of a site for a new RI can be a challenging task. Stringent safety construction requirements include developing site-specific architectural and geoengineering solutions, minimizing construction disturbances, and reinforcing rock and soil in a timely fashion. For successful development of the RIs in China, such as the Daya Bay Neutrino Laboratory (DBNL) and the China Spallation Neutron Source (CSNS), an integrated approach of joint geophysical methods including the electrical resistivity tomography (ERT), controlled-source audio-frequency magneto telluric (CSAMT)), gravity and seismic refraction methods, and geological mapping and surveys were carried out. Geophysical parameters, such as electrical resistivity, density, and seismic velocity, show inverse proportion to the degree of rock fracturing or weathering. The results show that the low values of geophysical parameters suggest the weathered/fractured rock, while high values reveal the fresh bedrock. The Engineering Geological Suitability Index (EGSI) value can represent the individual EGSI values at a constant and summed over varying depths. EGSI methodology is an improvement on the existing siting process and has been applied to CSNS. Our integrated approach provides clearer insight into the subsurface for site suitability of RIs in challenging geological engineering conditions and removes any ambiguity caused by a single geophysical parameter. The obtained geological knowledge of the area not only provides engineers with much-needed information about the construction conditions of a potential site but also gives scientists the opportunity to explore the local geology. In this study, we demonstrate our innovative approach for siting RIs, as demonstrated by the synthetic evaluation of the site location and utilization for two established RIs (DBNL and CSNS).
Corrosion Behavior of Corrosion-Resistant Spring Steel Used in High Speed Railway
Authors: Li Jinbo , Zhu Ziying , Chen Hongwei , Li Shaojie , Wu Hongyan , Gao Xiuhua , Du Linxiu , Song Liying
Published: September 2021

Corrosion behavior of 60Si2Mn-A and 60Si2Mn-B in simulated industrial atmospheric environment was investigated by alternate immersion corrosion test and electrochemical method. The phase, morphology, characteristics of corrosion products, and the distribution of Cr, Cu, and Ni in the corrosion products of experimental steel were studied by X-ray diffraction (XRD), scanning electron microscopy (SEM), and electron probe microanalyzer (EPMA). The results show that the phase of rust layer is Fe3O4 and γ-FeOOH in the early stage and then changes to α-FeOOH and γ-FeOOH in the later stage; the size of the rust layer with corrosion resistance of 60Si2Mn is less than 60Si2Mn; the Cr element accumulates in the rust layer of the experimental steel in the early stage of corrosion resistance; and Cu, Ni, and Cr in the corrosion resistance 60Si2Mn are concentrated in the rust layer near the substrate In the later stage of corrosion. As the corrosion cycle is prolonged, the corrosion potential and the resistance of the rust layer of the experimental steel increases, and the corrosion current decreases; in the same corrosion cycle, the corrosion potential and corrosion resistance of 60Si2Mn-B are greater than 60Si2Mn, and the corrosion current is less than 60Si2Mn.
Contrastive Learning Based on Transformer for Hyperspectral Image Classification
Authors: Hu Xiang , Li Teng , Zhou Tong , Liu Yu , Peng Yuanxi
Published: September 2021

Recently, deep learning has achieved breakthroughs in hyperspectral image (HSI) classification. Deep-learning-based classifiers require a large number of labeled samples for training to provide excellent performance. However, the availability of labeled data is limited due to the significant human resources and time costs of labeling hyperspectral data. Unsupervised learning for hyperspectral image classification has thus received increasing attention. In this paper, we propose a novel unsupervised framework based on a contrastive learning method and a transformer model for hyperspectral image classification. The experimental results prove that our model can efficiently extract hyperspectral image features in unsupervised situations.
Protective Effect of Quercetin, a Flavonol against Benzo(a)pyrene-Induced Lung Injury via Inflammation, Oxidative Stress, Angiogenesis and Cyclooxygenase-2 Signalling Molecule
Authors: Alzohairy Mohammad A. , Khan Amjad Ali , Ansari Mohammad Azam , Babiker Ali Yousif , Alsahli Mohammed A. , Almatroodi Saleh A. , Rahmani Arshad Husain
Published: September 2021

Quercetin (Qu) is an important polyphenolic flavonoid which exhibits tremendous antioxidant, anti-inflammatory and other health promoting effects. The aim of the current study was to explore the therapeutic role of Qu on benzo(a)pyrene [B(a)P]-induced lung injury in rats. B(a)P was given to the rats at dose of 50 mg/kg b.w. for continues 8 weeks through oral gavage. The rats were treated with Qu at dose of 50 mg/kg b.w prior 30 min before the oral administration of B(a)P. The effects of Qu were studied by measuring the level of lactate dehydrogenase (LDH), anti-oxidant enzymes, lipid peroxidation, inflammatory cytokines, lung tissues architecture and expression of cyclooxygenase-2 (COX-2). The level of pro-inflammatory cytokines such as IL-1β (27.30 vs. 22.80 pg/mL), IL-6 (90.64 vs. 55.49 pg/mL) and TNF-α (56.64 vs. 40.49 pg/mL) increased significantly and antioxidant enzymes decreased significantly in benzopyrene-induced lung injury in comparison to the control group. The treatment with Qu potentially reversed the effects of B(a)P to a great extent, as it led to the enhancement of antioxidant enzymes and decreased proinflammatory cytokines level. A significant surge of VEGF level was noticed in the B(a)P group as compared to the control group, while the Qu treatment groups exhibited less angiogenesis as lower level of VEGF levels, compared with the B(a)P treatment group. The Qu treatment significantly decreased the degrees of histopathological changes and collagen deposition in B(a)P-induced lung injury. The B(a)P-treated group showed higher cytoplasmic expression of COX-2 protein, which significantly decreased in the Qu treatment group. These outcomes recommend an effective role of Qu in the protection of lung injury against B(a)P through the regulation of the inflammatory factors, oxidative stress and the maintenance lung tissue architecture.
Voluntary Muscle Contraction Detection Algorithm Based on LSTM for Muscle Quality Measurement Algorithm
Authors: Song Kwangsub , Choi Sangui , Lee Hooman
Published: September 2021

In this paper, we propose the long–short-term memory (LSTM)-based voluntary and non-voluntary (VNV) muscle contraction classification algorithm in an electrical stimulation (ES) environment. In order to measure the muscle quality (MQ), we employ the non-voluntary muscle contraction signal, which occurs by the ES. However, if patient movement, such as voluntary muscle contractionm, occurs during the ES, the electromyography (EMG) sensor captures the VNV muscle contraction signals. In addition, the voluntary muscle contraction signal is a noise component in the MQ measurement technique, which uses only non-voluntary muscle contraction signals. For this reason, we need the VNV muscle contraction classification algorithm to classify the mixed EMG signal. In addition, when recording EMG while using the ES, the EMG signal is significantly contaminated due to the ES signal. Therefore, after we suppress the artifact noise, which is contained in the EMG signal, we perform VNV muscle contraction classification. For this, we first eliminate the artifact noise signal using the ES suppression algorithm. Then, we extract the feature vector, and then the feature vector is reconstructed through the feature selection process. Finally, we design the LSTM-based classification model and compare the proposed algorithm with the conventional method using the EMG data. In addition, to verify the performance of the proposed algorithm, we quantitatively compared results in terms of the confusion matrix and total accuracy. As a result, the performance of the proposed algorithm was higher than that of the conventional methods, including the support vector machine (SVM), artificial neural network (ANN), and deep neural network (DNN).
3D-Printed Scaffolds from Alginate/Methyl Cellulose/Trimethyl Chitosan/Silicate Glasses for Bone Tissue Engineering
Authors: Fermani Maria , Platania Varvara , Kavasi Rafaela-Maria , Karavasili Christina , Zgouro Paola , Fatouros Dimitrios , Chatzinikolaidou Maria , Bouropoulos Nikolaos
Published: September 2021

Alginate-based hydrogel inks are commonly used in printing due to their biocompatibility, biodegradation, and cell adhesion. In the present work, 3D printing of hydrogels comprising alginate/methyl cellulose (MC)/trimethyl chitosan (TMC) and silicate glasses was investigated. It was found that TMC increased the stability of the scaffolds after immersion in normal saline solution in comparison with alginate/MC 3D constructs. The stability also remained after the incorporation of pure silicate glasses or bioactive glasses. Immersion in simulated body fluid (SBF) resulted in the formation of hydroxyapatite in all samples. Scanning electron microscopy (SEM) analysis revealed a good cell adhesion of pre-osteoblasts on all scaffold compositions, cell viability assessment displayed a proliferation increase up to seven days in culture, and alkaline phosphatase (ALP) activity was similar in all scaffold compositions without significant differences. Total collagen secretion by the pre-osteoblasts after 7 days in culture was significantly higher in scaffolds containing silicate glasses, demonstrating their ability to promote extracellular matrix formation. In conclusion, 3D-printed porous scaffolds based on alginate/methyl cellulose/TMC are promising candidates for bone tissue engineering applications.
Development of a Slit-Type Soundproof Panel for a Reduction in Wind Load and Low-Frequency Noise with Helmholtz Resonators
Authors: Kim Byunghui , Kim Seokho , Park Yejin , Mieremet Marinus , Yang Heungguen , Baek Joonho , Choi Sanghyun
Published: September 2021

With the rapid increase in automobiles, the importance of reducing low-frequency noise is being emphasized for a comfortable urban environment. Helmholtz resonators are widely used to attenuate low-frequency noise over a narrow range. In this study, a slit-type soundproof panel is designed to achieve low-frequency noise attenuation in the range of 500 Hz to 1000 Hz with the characteristics of a Helmholtz resonator and the ability to pass air through the slits on the panel surface for reducing wind load. The basic dimension of the soundproof panel is determined using the classical formula and numerical analysis using a commercial program, COMSOL Multiphysics, for transmission loss prediction. From the numerical study, it is identified that the transmission loss performance is improved compared to the basic design according to the shape change and configuration method of the Helmholtz resonator. Although the correlation according to the shape change and configuration method cannot be derived, it is confirmed that it can be used as an effective method for deriving a soundproof panel design that satisfies the basic performance.
Visual Comfort of Tablet Devices under a Wide Range of Ambient Light Levels
Authors: Huang Hsin-Pou , Wei Minchen , Li Hung-Chung , Ou Li-Chen
Published: September 2021

E-reading devices are becoming more and more common in our daily life, and they are used under a wide range of ambient light levels, from completely dark to extremely bright conditions. In this study, a psychophysical experiment is carried out to investigate how ambient light level affects the visual comfort of an e-reading device. Human observers compare the visual comfort of pairs of different text-background lightness combinations on a tablet device under three ambient light levels (i.e., 150, 1500, and 15,000 lx). With our previous work, the experimental results show that the trend of visual comfort interval scales below 1500 lx (i.e., Dark, 150, 300, and 1500 lx) are similar to each other but not for those under illuminance above the 1500 lx (i.e., 3000 and 15,000 lx). For the same lightness difference between text and background, the observers tend to read the text with a white background compared to a black background, especially for 3000 and 15,000 lx. Moreover, a black text on a light-gray background is the most comfortable combination under these two illuminance levels. An evaluation model is proposed based on ambient illuminance, screen parameters, and visual estimation to design an optimal viewing condition when reading on the tablet display.