bluuebunny/crossref_metadata_2025 huggingface dataset:
Immunological Separation of Bioactive Natural Compounds from Crude Drug Extract and Its Application for Cell-Based Studies
Authors: Uto Takuhiro , Ohta Tomoe , Fujii Shunsuke , Shoyama Yukihiro
Published: December 2021

In this study, we present a review on a useful approach, namely, immunoaffinity column coupled with monoclonal antibodies (MAbs), to separate natural compounds and its application for cell-based studies. The immunoaffinity column aids in separating the specific target compound from the crude extract. The column capacity was stable even after more than 10 purification cycles of use under the same conditions. After applying the crude extract to the column, the column was washed with washing buffer and eluted with elution buffer. The elution fraction contained the target compound bound to MAb, whereas the washing fraction was the crude extract, which contained all compounds except a group of target compounds; therefore, the washing fraction was referred to as a knockout (KO) crude extract. Cell-based studies using the KO extract revealed the actual effects of the natural compounds in the crude extract. One-step separation of natural compounds using the immunoaffinity column coupled with MAbs may help in determining the potential functions of natural compounds in crude extracts.
Evaluating the Inappropriate Prescribing and Utilization of Caspofungin, a Four-Year Analysis at a Teaching Hospital in Saudi Arabia
Authors: Aldrees Abdulwahab , Ghonem Leen , Almajid Fahad , Barry Mazin , Mayet Ahmed , Almohaya Abdulellah M.
Published: December 2021

The appropriate use of antimicrobial agents improves clinical outcomes and reduces antimicrobial resistance. Nevertheless, data on inappropriate prescription and negative outcomes are inconsistent. The objective of this study was to assess the prescription appropriateness of Caspofungin at a tertiary teaching hospital in Saudi Arabia and the impact on mortality at 30 days. A retrospective chart review was performed for patients who received Caspofungin from May 2015 to December 2019 to obtain prescription information and culture and susceptibility tests. The appropriateness of the dosage (ApD), initiation time (ApI), agent selection (ApS), and duration of therapy (ApDUR) was evaluated based on recommendations of the infectious diseases society of America. 355 eligible patients who received 3458 Caspofungin doses were identified. Their median age was 54 years (range 18–96). Overall, 270 (76.1%) patients received empirical prescriptions, of which 74.4% had the appropriate dose, and 56.3% had received it for more than five days, despite no proven Candida infection. This was not influenced by past medical history (p = 0.394). Only 39% of patients who received definitive prescriptions met all four study criteria for appropriate prescription. Therefore, antimicrobial stewardship programs can improve the appropriate utilization of antifungal therapies.
How to Combat Gram-Negative Bacteria Using Antimicrobial Peptides: A Challenge or an Unattainable Goal?
Authors: Barreto-Santamaría Adriana , Arévalo-Pinzón Gabriela , Patarroyo Manuel A. , Patarroyo Manuel E.
Published: December 2021

Antimicrobial peptides (AMPs) represent a promising and effective alternative for combating pathogens, having some advantages compared to conventional antibiotics. However, AMPs must also contend with complex and specialised Gram-negative bacteria envelops. The variety of lipopolysaccharide and phospholipid composition in Gram-negative bacteria strains and species are decisive characteristics regarding their susceptibility or resistance to AMPs. Such biological and structural barriers have created delays in tuning AMPs to deal with Gram-negative bacteria. This becomes even more acute because little is known about the interaction AMP–Gram-negative bacteria and/or AMPs’ physicochemical characteristics, which could lead to obtaining selective molecules against Gram-negative bacteria. As a consequence, available AMPs usually have highly associated haemolytic and/or cytotoxic activity. Only one AMP has so far been FDA approved and another two are currently in clinical trials against Gram-negative bacteria. Such a pessimistic panorama suggests that efforts should be concentrated on the search for new molecules, designs and strategies for combating infection caused by this type of microorganism. This review has therefore been aimed at describing the currently available AMPs for combating Gram-negative bacteria, exploring the characteristics of these bacteria’s cell envelop hampering the development of new AMPs, and offers a perspective regarding the challenges for designing new AMPs against Gram-negative bacteria.
l-Arginine Alleviates LPS-Induced Oxidative Stress and Apoptosis via Activating SIRT1-AKT-Nrf2 and SIRT1-FOXO3a Signaling Pathways in C2C12 Myotube Cells
Authors: Zhao Ye , Jiang Qin , Zhang Xuefei , Zhu Xiaoxiao , Dong Xia , Shen Linyuan , Zhang Shunhua , Niu Lili , Chen Lei , Zhang Ming , Jiang Jun , Chen Daiwen , Zhu Li
Published: December 2021

l-arginine (l-Arg) has been reported to possess a wide range of functions, including anti-inflammatory, anti-oxidative, and anti-apoptosis. However, the role of l-Arg in LPS-induced muscle injury and its potential protective mechanism has not been well elucidated. This study aimed to investigate the effects of l-Arg on the LPS-induced oxidative stress and apoptosis in differentiated C2C12 myotube cells. Our results demonstrated that myotube cells treated with 0.2 mg/mL LPS significantly decreased cell viability. l-Arg treatment significantly suppressed LPS induced ROS accumulation and cell apoptosis. Furthermore, l-Arg improved antioxidant-related enzymes’ activities; increased antioxidant ability via Akt-Nrf2 signaling pathway; maintained the mitochondrial membrane potential (MMP); and enhanced FOXO3a expression, leading to a decrease in the mitochondrial-associated apoptotic proteins. In addition, l-Arg exposure dramatically increased the mRNA and protein expressions of SIRT1. The cytoprotective effect of l-Arg was restricted by the SIRT1 inhibitor EX527, which led to an increase in ROS level, apoptosis rate, and decreased cell MMP. The results also demonstrated that EX527 treatment significantly eliminated the effect of l-Arg on LPS-induced oxidative damage and mitochondria-mediated cell apoptosis. Our findings revealed that l-Arg could be used as a potential nutraceutical in reducing muscle injury via regulating SIRT1-Akt-Nrf2 and SIRT1-FOXO3a-mitochondria apoptosis signaling pathways.
Jak2 Inhibitor AG490 Improved Poststroke Central and Peripheral Inflammation and Metabolic Abnormalities in a Rat Model of Ischemic Stroke
Authors: Wang Ya-Yu , Lin Shih-Yi , Chang Cheng-Yi , Wu Chih-Cheng , Chen Wen-Ying , Liao Su-Lan , Chen Yu-Fan , Wang Wen-Yi , Chen Chun-Jung
Published: December 2021

Poststroke hyperglycemia and inflammation have been implicated in the pathogenesis of stroke. Janus Kinase 2 (Jak2), a catalytic signaling component for cytokine receptors such as Interleukin-6 (IL-6), has inflammatory and metabolic properties. This study aimed to investigate the roles of Jak2 in poststroke inflammation and metabolic abnormality in a rat model of permanent cerebral ischemia. Pretreatment with Jak2 inhibitor AG490 ameliorated neurological deficit, brain infarction, edema, oxidative stress, inflammation, caspase-3 activation, and Zonula Occludens-1 (ZO-1) reduction. Moreover, in injured cortical tissues, Tumor Necrosis Factor-α, IL-1β, and IL-6 levels were reduced with concurrent decreased NF-κB p65 phosphorylation, Signal Transducers and Activators of Transcription 3 phosphorylation, Ubiquitin Protein Ligase E3 Component N-Recognin 1 expression, and Matrix Metalloproteinase activity. In the in vitro study on bEnd.3 endothelial cells, AG490 diminished IL-6-induced endothelial barrier disruption by decreasing ZO-1 decline. Metabolically, administration of AG490 lowered fasting glucose, with improvements in glucose intolerance, plasma-free fatty acids, and plasma C Reactive Proteins. In conclusion, AG490 improved the inflammation and oxidative stress of neuronal, hepatic, and muscle tissues of stroke rats as well as impairing insulin signaling in the liver and skeletal muscles. Therefore, Jak2 blockades may have benefits for combating poststroke central and peripheral inflammation, and metabolic abnormalities.
Increased Kynurenine Indicates a Fatal Course of COVID-19
Authors: Mangge Harald , Herrmann Markus , Meinitzer Andreas , Pailer Sabine , Curcic Pero , Sloup Zdenka , Holter Magdalena , Prüller Florian
Published: December 2021

(1) Background: An inefficient immune response accompanied by an overwhelming inflammatory reaction is involved in severe courses of COVID-19. Kynurenine (KYN) has important immune-modulatory functions and may contribute to a failure in controlling SARS-CoV-2. The present study aims to explore biomarkers that hint at a fatal outcome of COVID-19 early on. (2) Methods: We established a cohort of 148 hospitalized COVID-19 patients for this study. Thirty-one patients died due to a severe COVID-19 course, and 117 recovered within 90 days. We built a biobank by collecting left-over material from these patients whenever blood arrived at the central laboratory of our University hospital for analysis of routine markers. The scientific laboratory analysis comprised KYN, Tryptophan (TRP), KYN/TRP ratio, ferritin, interleukin-6 (IL-6), C-reactive protein (CRP), creatinine, N-terminal pro-natriuretic peptide (NTproBNP), troponin T (TnT), fibrinogen, D-Dimer, prothrombin time (PT), activated partial thromboplastin time (aPTT), antithrombin (AT), protein C, protein S, factor XIII, lupus aPTT, angiotensin-2, vitamin D metabolites, and telomeres in all COVID-19 patients. Basic clinical characteristics and anteceding diseases including cardiovascular, oncologic, renal, hypertension, pulmonary, metabolic (diabetes, obesity) were recorded in a database together with the laboratory data. (3) Results: At the time of diagnosis of SARS-CoV-2 infection those patients who deceased within 90 days afterwards due to COVID-19, had a significantly higher age, higher KYN, KYN/TRP ratio, ferritin, creatinine, and NTproBNP values than SARS-CoV-2 patients who survived COVID-19 along the same time span. In a Kaplan-Meier analysis the variables age, KYN, ferritin, D-Dimer, TnT, NTproBNP, and creatinine showed a significant influence on survival time. Gender, however, showed no influence. In a combined Cox regression analysis KYN had the highest hazard ratio (1.188, 95% CI: 1.071–1.319) followed by age (1.041, 95% CI: 1.011–1.073). In a ROC analysis, KYN values above the cut off limit of 4.82 nmol/l (as specified by Youden index) had a sensitivity of 82% (95% CI: 66–95%) and a specificity of 72% (95% CI: 65–82%) to predict COVID-19 related death within 90 days observation time. (4) Conclusions: Kynurenine is a promising blood biomarker to predict an increased risk of mortality in SARS-CoV-2 infected people already at the time of the first positive SARS-CoV-2 verification detected in these persons.
Formation of Cyclobutane Pyrimidine Dimers after UVA Exposure (Dark-CPDs) Is Inhibited by an Hydrophilic Extract of Polypodium leucotomos
Authors: Portillo-Esnaola Mikel , Rodríguez-Luna Azahara , Nicolás-Morala Jimena , Gallego-Rentero María , Villalba María , Juarranz Ángeles , González Salvador
Published: December 2021

Exposure to sun and especially to ultraviolet radiation (UVR) exerts well known detrimental effects on skin which are implicated in malignancy. UVR induces production of cyclobutane pyrimidine dimers (CPDs), immediately during exposure and even hours after the exposure, these latter being called dark-CPDs, as consequence of the effects of different reactive species that are formed. Fernblock® (FB), an aqueous extract of Polypodium leucotomos, has proven to have photoprotective and antioxidant effects on skin. The aim of our work was to investigate the potential photoprotective effect of FB against dark-CPD formation. Murine melanocytes (B16-F10) were exposed to UVA radiation and the production of dark-CPDs and different reactive oxygen and nitrogen species (ROS and RNS) was measured. Significant dark-CPD formation could be seen at 3 h after UVA irradiation, which was inhibited by the pre-treatment of cells with FB. Formation of nitric oxide, superoxide and peroxynitrite was increased after irradiation, consistent with the increased CPD formation. FB successfully reduced the production of these reactive species. Hence, these results show how dark-CPDs are formed in UVA irradiated melanocytes, and that FB acts as a potential antioxidant and ROS scavenger, preventing the DNA damage induced by sun exposure.
A Practical Model for the Evaluation of High School Student Performance Based on Machine Learning
Authors: Zafari Mostafa , Sadeghi-Niaraki Abolghasem , Choi Soo-Mi , Esmaeily Ali
Published: December 2021

The objective of this research is to develop an machine learning (ML) -based system that evaluates the performance of high school students during the semester and identify the most significant factors affecting student performance. It also specifies how the performance of models is affected when models run on data that only include the most important features. Classifiers employed for the system include random forest (RF), support vector machines (SVM), logistic regression (LR) and artificial neural network (ANN) techniques. Moreover, the Boruta algorithm was used to calculate the importance of features. The dataset includes behavioral information, individual information and the scores of students that were collected from teachers and a one-by-one survey through an online questionnaire. As a result, the effective features of the database were identified, and the least important features were eliminated from the dataset. The ANN accuracy, which was the best accuracy in the original dataset, was reduced in the decreased dataset. On the contrary, SVM performance was improved, which had the highest accuracy among other models, with 0.78. Moreover, the LR and RF models could provide the same performance in the decreased dataset. The results showed that ML models are influential for evaluating students, and stakeholders can use the identified effective factors to improve education.
Serum MicroRNAs as Biomarkers of Sepsis and Resuscitation
Authors: Oteiza Lorena , Ferruelo Antonio , Nín Nicolás , Arenillas Mario , de Paula Marta , Pandolfi Rachele , Moreno Laura , Herrero Raquel , González-Rodríguez Paloma , Peñuelas Óscar , Pérez-Vizcaíno Francisco , Lorente José A.
Published: December 2021

There is a lack of biomarkers of sepsis and the resuscitation status. Our objective was to prove that the serum expression of certain microribonucleic acids (miRNAs) is differentially regulated in sepsis and is sensitive to different resuscitation regimes. Anesthetized pigs (Sus scrofa domesticus) received no treatment (n = 15) or intravenous live E. coli (n = 24). The septic animals received 0.9% saline at 4 mL/kg/h (n = 8) (low resuscitation group (LoR)) or 10–17 mL/kg/h (high resuscitation group (HiR)) (n = 8 each group). Blood samples were obtained at the end of the experiment for measurement of seven different miRNAs (RT-qPCR, Qiagen, Hilden, Germany). The serum expression of miR-146a-5p and miR-34a-5p increased significantly in the septic group, and miR-146a-5p was significantly lower in the HiR group than in the LoR group. The toll-like receptor signaling pathway involving 22 target proteins was significantly (adjusted p = 3.87 × 10−4) regulated by these two microRNAs (KEGG). Highly significant (p value = 2.22 × 10−16) protein–protein interactions (STRING) were revealed for these 22 hits. MiR-146a-5p and miR-34a-5p were identified as biomarkers of sepsis, and miRNA146a-5p seemed to be a biomarker of the intensity of the resuscitation.
A Sensitivity Analysis Approach for Assessing the Effect of Design Parameters in Reducing Seismic Demand of Base-Isolated Storage Racks
Authors: Álvarez Oscar , Muñoz Enrique , Maureira-Carsalade Nelson , Roco-Videla Ángel
Published: December 2021

The most used global sensitivity analysis (GSA) method is based on variance. This is performed using Monte Carlo Sampling (MCS) or Latin Hypercube Sampling (LHS). It requires a large sample to obtain accurate estimates. Density-based methods, such as the GSA PAWN, have been developed to reduce the sample size without compromising the result. PAWN is simpler than other methods because it uses cumulative density functions (CDF) instead of probability density. This method has been widely used in areas such as environmental engineering with very good results, reducing computation time. However, its use in structural engineering is incipient. The PAWN method was used to classify the design variables of the isolation system in relation to their sensitivity, and in relation to the seismic response of industrial storage racks. The above was analyzed in terms of the effectiveness of each variable to reduce the seismic demand using a novel base isolation kinematic device (BIKD). Racks with different combinations of their structural parameters such as the number of storage levels, the height between them, and isolation period, among others, were studied. The dimensions of the racks were chosen to match those that would later be experimentally tested on shaking table. An earthquake whose response spectrum matched the design spectrum of current Chilean regulations, was considered as seismic forcing. The maximum base shear load, the displacement of the top level of storage and the floor drift were considered as target responses to be studied. Fixed base racks (FBR), as reference, and base-isolated racks (BIR) were analyzed. The results showed the effectiveness of using the BIKD system in reducing all three-target responses up to one order of magnitude. Additionally, it was determined that the parameters that have the greatest influence on the response correspond to the number of storage levels and the height between them, both for FBR and BIR.
Detection of Small Size Traffic Signs Using Regressive Anchor Box Selection and DBL Layer Tweaking in YOLOv3
Authors: Rehman Yawar , Amanullah Hafsa , Saqib Bhatti Dost Muhammad , Toor Waqas Tariq , Ahmad Muhammad , Mazzara Manuel
Published: December 2021

Traffic sign recognition is a key module of autonomous cars and driver assistance systems. Traffic sign detection accuracy and inference time are the two most important parameters. Current methods for traffic sign recognition are very accurate; however, they do not meet the requirement for real-time detection. While some are fast enough for real-time traffic sign detection, they fall short in accuracy. This paper proposes an accuracy improvement in the YOLOv3 network, which is a very fast detection framework. The proposed method contributes to the accurate detection of a small-sized traffic sign in terms of image size and helps to reduce false positives and miss rates. In addition, we propose an anchor frame selection algorithm that helps in achieving the optimal size and scale of the anchor frame. Therefore, the proposed method supports the detection of a small traffic sign with real-time detection. This ultimately helps to achieve an optimal balance between accuracy and inference time. The proposed network is evaluated on two publicly available datasets, namely the German Traffic Sign Detection Benchmark (GTSDB) and the Swedish Traffic Sign dataset (STS), and its performance showed that the proposed approach achieves a decent balance between mAP and inference time.
Photonic Stopband Filters Based on Graphene-Pair Arrays
Authors: Zhao Dong , Wang Liyan , Liu Fangmei , Zhong Dong , Wu Min
Published: December 2021

We investigate the photonic bandgaps in graphene-pair arrays. Graphene sheets are installed in a bulk substrate to form periodical graphene photonic crystal. The compound system approves a photonic band structure as a light impinges on it. Multiple stopbands are induced by changing the incident frequency of light. The stopbands widths and their central frequencies could be modulated through the graphene chemical potential. The number of stopbands decreases with the increase in the spatial period of graphene pairs. Otherwise, two full passbands are realized in the parameter space composed of the incident angle and the light frequency. This investigation has potentials applied in tunable multi-stopbands filters.
Methodology of 3D Scanning of Intangible Cultural Heritage—The Example of Lazgi Dance
Authors: Skublewska-Paszkowska Maria , Powroznik Pawel , Smolka Jakub , Milosz Marek , Lukasik Edyta , Mukhamedova Dilbar , Milosz Elzbieta
Published: December 2021

Traditional dance is one of the key elements of Intangible Culture Heritage (ICH). Many scientific papers concern analysis of dance sequences, classification and recognition of movements, making ICH data public, creating and visualising 3D models or software solutions for learning folklore dances. These works make it possible to preserve this disappearing art. The aim of this article is to propose a methodology for scanning folklore dances. The methodology was developed on the basis of capturing 3D data via an optical motion capture system with a full body Plug-in Gait model that allows for kinematic and kinetic analysis of motion sequences. An additional element of this research was the development of a hand model with which it is possible to precisely analyse the fingers, which play a significant role in many dances. The present methodology was verified on the basis of the Lazgi dance, included in the UNESCO ICH list. The obtained results of movement biomechanics for the dance sequence and the angles of the fingers indicate that it is universal and can be applied to dances that involve the upper and lower body parts, including hand movements.
Application of Absolute Nodal Coordinate Formulation in Calculation of Space Elevator System
Authors: Luo Shihao , Fan Youhua , Cui Naigang
Published: December 2021

The space elevator system is a space tether system used to solve low-cost space transportation. Its high efficiency, large load, reusability and other characteristics have broad application prospects in the aerospace field. Most of the existing mechanical models are based on “chain-bar” and a lumped mass tether model, which cannot effectively reflect the flexible behaviour of the rope of space elevator system. To establish an accurate mechanical model, the gradient deficient beam elements of the absolute nodal coordinate formulation (ANCF) are used to build the mechanical model of the space elevator system. The universal gravitation and centrifugal force in the model are derived. The calculation results of the ANCF model are compared with the results of the finite element method (FEM) and lumped mass (LM) models. The results show that the calculation results of the ANCF method are not very different from the results of the FEM and LM models in the case of axial loading. In the case of lateral loading, the calculation results of the ANCF method are basically the same as the results of the FEM and LM models, but can better reflect the local flexible deformation of the space elevator rope, and have a better calculation stability than FEM. Under the same calculation accuracy, the ANCF method can use fewer elements, and the speed of convergence is faster than the FEM and LM models.
Design of a Mass Air Flow Sensor Employing Additive Manufacturing and Standard Airfoil Geometry
Authors: Pagonis Dimitrios-Nikolaos , Benaki Vasiliki , Kaltsas Grigoris , Pagonis Antonios
Published: December 2021

This work concerns the design, fabrication, and preliminary characterization of a novel sensor for determining the air intake of low and medium power internal combustion engines employed at various applications in the marine industry. The novelty of the presented sensor focuses on the fabrication process, which is based on additive manufacturing combined with PCB technology, and the design of the sensing elements housing geometry, which is derived through suitable CFD simulations and is based on standard airfoil geometry. The proposed process enables low-cost, fast fabrication, effective thermal isolation, and facile electrical interconnection to the corresponding circuitry of the sensor. For initial characterization purposes, the prototype device was integrated into a DIESEL engine testbed while a commercially available mass air flow sensor was employed as a reference; the proper functionality of the developed prototype has been validated. Key features of the proposed device are low-cost, fast on-site manufacturing of the device, robustness, and simplicity, suggesting numerous potential applications in marine engineering.
Quadrotor Attitude Control by Fractional-Order Fuzzy Particle Swarm Optimization-Based Active Disturbance Rejection Control
Authors: Zhang Qi , Wei Yaoxing , Li Xiao
Published: December 2021

In this paper, Active Disturbance Rejection Control (ADRC) is utilized in the attitude control of a quadrotor aircraft to address the problem of attitude destabilization in flight control caused by parameter uncertainties and external disturbances. Considering the difficulty of optimizing the parameter of ADRC, a fractional-order fuzzy particle swarm optimization (FOFPSO) algorithm is proposed to optimize the parameters of ADRC for quadrotor aircraft. Simultaneously, the simulation experiment is designed, which compares with the optimized performance of traditional particle swarm optimization (PSO), fuzzy article swarm optimization (FPSO) and adaptive genetic algorithm-particle swarm optimization (AGA-PSO). In addition, the turbulent wind field model is established to verify the disturbance rejection performance of the controller. Finally, the designed controller is deployed to the actual hardware platform by using the model-based design method. The results show that the controller has a small overshoot and stronger disturbance rejection ability after the parameters are optimized by the proposed algorithm.
Overview and Perspectives for Vehicle-Integrated Photovoltaics
Authors: Commault Benjamin , Duigou Tatiana , Maneval Victor , Gaume Julien , Chabuel Fabien , Voroshazi Eszter
Published: December 2021

On-board photovoltaic (PV) energy generation is starting to be deployed in a variety of vehicles while still discussing its benefits. Integration requirements vary greatly for the different vehicles. Numerous types of PV cells and modules technologies are ready or under development to meet the challenges of this demanding sector. A comprehensive review of fast-changing vehicle-integrated photovoltaic (VIPV) products and lightweight PV cell and module technologies adapted for integration into electric vehicles (EVs) is presented in this paper. The number of VIPV projects and/or products is on a steady rise, especially car-based PV integration. Our analysis differentiates projects according to their development stage and technical solutions. The advantages and drawbacks of various PV cell and module technologies are discussed, in addition to recommendations for wide-scale deployment of the technologies.
Pose Estimation of Driver’s Head Panning Based on Interpolation and Motion Vectors under a Boosting Framework
Authors: Ali Syed Farooq , Aslam Ahmed Sohail , Awan Mazhar Javed , Yasin Awais , Damaševičius Robertas
Published: December 2021

Over the last decade, a driver’s distraction has gained popularity due to its increased significance and high impact on road accidents. Various factors, such as mood disorder, anxiety, nervousness, illness, loud music, and driver’s head rotation, contribute significantly to causing a distraction. Many solutions have been proposed to address this problem; however, various aspects of it are still unresolved. The study proposes novel geometric and spatial scale-invariant features under a boosting framework for detecting a driver’s distraction due to the driver’s head panning. These features are calculated using facial landmark detection algorithms, including the Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). The proposed approach is compared with six existing state-of-the-art approaches using four benchmark datasets, including DrivFace dataset, Boston University (BU) dataset, FT-UMT dataset, and Pointing’04 dataset. The proposed approach outperforms the existing approaches achieving an accuracy of 94.43%, 92.08%, 96.63%, and 83.25% on standard datasets.
Evaluation of Cement Performance Using Industrial Byproducts Such as Nano MgO and Fly Ash from Greece
Authors: Giannakopoulou Panagiota P. , Rogkala Aikaterini , Lampropoulou Paraskevi , Kalpogiannaki Maria , Petrounias Petros
Published: December 2021

The need for environmentally friendly construction materials is growing more and more these days. This paper investigates byproducts from Greece, such as magnesite tailings from Evoia and fly ash from Kardia (Ptolemais), in order to evaluate their suitability as cement additives. For this purpose, the raw materials were tested and studied regarding their mineralogical and chemical components for their morphological characteristics. Different cement specimens of various mixtures of raw materials were produced and tested. These raw materials are considered suitable for cement additives. The effect of nano MgO content seems to have played a more critical role in the physicomechanical performance of produced cement compared to that of the fly ash content. Furthermore, more satisfactory results in the physicomechanical properties of the produced cement gave samples of group II containing 3–4% of nano MgO. Nano MgO content up to 4% seems to have negative influence on the compressive strength of the produced cement, simultaneously reducing its durability. The increase of nano MgO content leads to the increase of the expansion of the produced cement specimens. In the early stage, the expansion rate was intensively larger. With the consumption of nano MgO, the expansion in the later stage gradually slowed down and tended to stabilize.
SARS-CoV-2: Some Aspects of Molecular Evolution, Cellular Pathogenesis, and Immune System Mechanism Elusion
Authors: Quirino Angela , Marascio Nadia , Barreca Giorgio Settimo , Gallo Luigia , Giancotti Aida , Lamberti Angelo Giuseppe , Peronace Cinzia , Trecarichi Enrico Maria , Fusco Paolo , Mazzitelli Maria , Divenuto Francesca , Pavia Grazia , Suraci Angela , Matera Giovanni , Liberto Maria Carla
Published: December 2021

The purpose of this review is to address some of the latest aspects regarding molecular features, pathogenic mechanisms, and immune system response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), based on recent publications in this field from March 2020 to May 2021. Interpretation keys for periodic re-emergence of coronavirus infections and other lethal viral pandemics are suggested. Antibody-dependent enhancement (ADE) and other potential mechanisms of immune system deception are put forward. Therefore, vaccine development must take into account ADE and other unwanted side effects of immune-based medical intervention. Features reported in our review will allow both clinicians and basic science researchers to take home ideas to improve their knowledge about SARS-CoV-2.
Theoretical Framework for Determination of Linear Structures in Multidimensional Geodynamic Data Arrays
Authors: Agayan Sergey , Bogoutdinov Shamil , Kamaev Dmitriy , Kaftan Vladimir , Osipov Maxim , Tatarinov Victor
Published: December 2021

The article addresses the issue of clustering of multidimensional data arrays with a noise using the methods of discrete mathematical analysis (DMA clustering). The theory of DMA clustering through the logical densities calculus is detailed, and the new algorithm Linear Discrete Perfect Sets (LDPS) is described. The main objective of the LDPS algorithm is to identify linearly stretched anomalies in a multidimensional array of geo-spatial data (geophysical fields, geochemistry, satellite images, local topography, maps of recent crustal movements, seismic monitoring data, etc.). These types of anomalies are associated with tectonic structures in the upper part of the Earth’s crust and pose the biggest threat for integrity of the isolation properties of the geological environment, including in regions of high-level radioactive waste disposal. The main advantage of the LDPS algorithm as compared to other cluster analysis algorithms that may be used in arrays with a noise is that it is more focused on searching for clusters that are linear. The LDPS algorithm can apply not only in the analysis of spatial natural objects and fields but also to elongated lineament structures.
Situational Awareness and Problems of Its Formation in the Tasks of UAV Behavior Control
Authors: Igonin Dmitry M. , Kolganov Pavel A. , Tiumentsev Yury V.
Published: December 2021

Situational awareness formation is one of the most critical elements in solving the problem of UAV behavior control. It aims to provide information support for UAV behavior control according to its objectives and tasks to be completed. We consider the UAV to be a type of controlled dynamic system. The article shows the place of UAVs in the hierarchy of dynamic systems. We introduce the concepts of UAV behavior and activity and formulate requirements for algorithms for controlling UAV behavior. We propose the concept of situational awareness as applied to the problem of behavior control of highly autonomous UAVs (HA-UAVs) and analyze the levels and types of this situational awareness. We show the specifics of situational awareness formation for UAVs and analyze its differences from situational awareness for manned aviation and remotely piloted UAVs. We propose the concept of situational awareness as applied to the problem of UAV behavior control and analyze the levels and types of this situational awareness. We highlight and discuss in more detail two crucial elements of situational awareness for HA-UAVs. The first of them is related to the analysis and prediction of the behavior of objects in the vicinity of the HA-UAV. The general considerations involved in solving this problem, including the problem of analyzing the group behavior of such objects, are discussed. As an illustrative example, the solution to the problem of tracking an aircraft maneuvering in the vicinity of a HA-UAV is given. The second element of situational awareness is related to the processing of visual information, which is one of the primary sources of situational awareness formation required for the operation of the HA-UAV control system. As an example here, we consider solving the problem of semantic segmentation of images processed when selecting a landing site for the HA-UAV in unfamiliar terrain. Both of these problems are solved using machine learning methods and tools. In the field of situational awareness for HA-UAVs, there are several problems that need to be solved. We formulate some of these problems and briefly describe them.
Immersive Virtual Reality Experience of Historical Events Using Haptics and Locomotion Simulation
Authors: Chrysanthakopoulou Agapi , Kalatzis Konstantinos , Moustakas Konstantinos
Published: December 2021

Virtual reality (VR) and 3D modeling technologies have become increasingly powerful tools for multiple fields, such as education, architecture, and cultural heritage. Museums are no longer places for only placing and exhibiting collections and artworks. They use such technologies to offer a new way of communicating art and history with their visitors. In this paper, we present the initial results of a proposed workflow towards highlighting and interpreting a historic event with the use of an immersive and interactive VR experience and the utilization of multiple senses of the user. Using a treadmill for navigating and haptic gloves for interacting with the environment, combined with the detailed 3D models, deepens the sense of immersion. The results of our study show that engaging multiple senses and visual manipulation in an immersive 3D environment can effectively enhance the perception of visual realism and evoke a stronger sense of presence, amplifying the educational and informative experience in a museum.
The Impact of Atmospheric Pollutants on Human Health and Economic Loss Assessment
Authors: Zhang Houli , You Shibing , Zhang Miao , Liu Difei , Wang Xuyan , Ren Jingru , Yu Chuanhua
Published: December 2021

The impact of air pollution on human health is becoming increasingly severe, and economic losses are a significant impediment to economic and social development. This paper investigates the impact of air pollutants on the respiratory system and its action mechanism by using information on inpatients with respiratory diseases from two IIIA (highest) hospitals in Wuhan from 2015 to 2019, information on air pollutants, and meteorological data, as well as relevant demographic and economic data in China. This paper describes the specific conditions of air pollutant concentrations and respiratory diseases, quantifies the degree of correlation between the two, and then provides a more comprehensive assessment of the economic losses using descriptive statistical methods, the generalized additive model (GAM), cost of illness approach (COI), and scenario analysis. According to the findings, the economic losses caused by PM2.5, PM10, SO2, NO2, and CO exposure are USD 103.17 million, USD 70.54 million, USD 98.02 million, USD 40.35 million, and USD 142.38 million, for a total of USD 454.46 billion, or approximately 0.20% of Wuhan’s GDP in 2019. If the government tightens control of major air pollutants and meets the WHO-recommended criterion values, the annual evitable economic losses would be approximately USD 69.4 million or approximately 0.03% of Wuhan’s GDP in 2019. As a result, the relevant government departments must strengthen air pollution control to mitigate the impact of air pollution on population health and the associated economic losses.
Properties of Hall-MHD Turbulence at Sub-Ion Scales: Spectral Transfer Analysis
Authors: Papini Emanuele , Hellinger Petr , Verdini Andrea , Landi Simone , Franci Luca , Montagud-Camps Victor , Matteini Lorenzo
Published: December 2021

We present results of a multiscale study of Hall-magnetohydrodynamic (MHD) turbulence, carried out on a dataset of compressible nonlinear 2D Hall-MHD numerical simulations of decaying Alfvénic turbulence. For the first time, we identify two distinct regimes of fully developed turbulence. In the first one, the power spectrum of the turbulent magnetic fluctuations at sub-ion scales exhibits a power law with a slope of ∼−2.9, typically observed both in solar wind and in magnetosheath turbulence. The second regime, instead, shows a slope of −7/3, in agreement with classical theoretical models of Hall-MHD turbulence. A spectral-transfer analysis reveals that the latter regime occurs when the energy transfer rate at sub-ion scales is dominated by the Hall term, whereas in the former regime, the governing process is the dissipation (and the system exhibits large intermittency). Results of this work are relevant to the space plasma community, as they may potentially reconcile predictions from theoretical models with results from numerical simulations and spacecraft observations.
Five Years of Spatially Resolved Ground-Based MAX-DOAS Measurements of Nitrogen Dioxide in the Urban Area of Athens: Synergies with In Situ Measurements and Model Simulations
Authors: Gratsea Myrto , Athanasopoulou Eleni , Kakouri Anastasia , Richter Andreas , Seyler Andre , Gerasopoulos Evangelos
Published: December 2021

Long-term nitrogen dioxide (NO2) slant column density measurements using the MAX-DOAS (multi-axis differential optical absorption spectroscopy) technique were analyzed in order to demonstrate the temporal and horizontal variability of the trace gas in Athens for the period October 2012–July 2017. The synergy with in situ measurements and model simulations was exploited for verifying the MAX-DOAS technique and its ability to assess the spatiotemporal characteristics of NO2 pollution in the city. Tropospheric NO2 columns derived from ground-based MAX-DOAS observations in two horizontal and five vertical viewing directions were compared with in situ chemiluminescence measurements representative of urban, urban background and suburban conditions; a satisfactory correlation was found for the urban (r ≈ 0.55) and remote areas (r ≈ 0.40). Mean tropospheric slant columns retrieved from measurements at the lowest elevation over the urban area ranged from 0.1 to 32 × 1016 molec cm−2. The interannual variability showed a rate of increase of 0.3 × 1016 molec cm−2 per year since 2012 in the urban area, leading to a total increase of 20%. The retrieved annual cycles captured the seasonal variability with lower NO2 levels in summer, highly correlated (r ≈ 0.85) with the urban background and suburban in situ observations. The NO2 diurnal variation for different seasons exhibited varied patterns, indicating the different role of photochemistry and anthropogenic activities in the different seasons. Compared to in situ observations, the MAX-DOAS NO2 morning peak occurred with a one-hour delay and decayed less steeply in winter. Measurements at different elevation angles are shown as a primary indicator of the vertical distribution of NO2 at the urban environment; the vertical convection of the polluted air masses and the enhanced NO2 near-surface concentrations are demonstrated by this analysis. The inhomogeneity of the NO2 spatial distribution was shown using a relevant inhomogeneity index; greater variability was found during the summer period. Comparisons with city-scale model simulations demonstrated that the horizontal light path length of MAX-DOAS covered a distance of 15 km. An estimation of urban sources’ contribution was also made by applying two simple methodologies on the MAX-DOAS measurements. The results were compared to NO2 predictions from the high resolution air quality model to infer the importance of vehicle emissions for the urban NO2 levels; 20–35% of the urban NO2 was found to be associated with road transport.
A Model-Based Climatology of Low-Level Jets in the Weddell Sea Region of the Antarctic
Authors: Heinemann Günther , Zentek Rolf
Published: December 2021

Low-level jets (LLJs) are climatological features in polar regions. It is well known that katabatic winds over the slopes of the Antarctic ice sheet are associated with strong LLJs. Barrier winds occurring, e.g., along the Antarctic Peninsula may also show LLJ structures. A few observational studies show that LLJs occur over sea ice regions. We present a model-based climatology of the wind field, of low-level inversions and of LLJs in the Weddell Sea region of the Antarctic for the period 2002–2016. The sensitivity of the LLJ detection on the selection of the wind speed maximum is investigated. The common criterion of an anomaly of at least 2 m/s is extended to a relative criterion of wind speed decrease above and below the LLJ. The frequencies of LLJs are sensitive to the choice of the relative criterion, i.e., if the value for the relative decrease exceeds 15%. The LLJs are evaluated with respect to the frequency distributions of height, speed, directional shear and stability for different regions. LLJs are most frequent in the katabatic wind regime over the ice sheet and in barrier wind regions. During winter, katabatic LLJs occur with frequencies of more than 70% in many areas. Katabatic LLJs show a narrow range of heights (mostly below 200 m) and speeds (typically 10–20 m/s), while LLJs over the sea ice cover a broad range of speeds and heights. LLJs are associated with surface inversions or low-level lifted inversions. LLJs in the katabatic wind and barrier wind regions can last several days during winter. The duration of LLJs is sensitive to the LLJ definition criteria. We propose to use only the absolute criterion for model studies.
A New Entropy Measurement for the Analysis of Uncertain Data in MCDA Problems Using Intuitionistic Fuzzy Sets and COPRAS Method
Authors: Thakur Parul , Kizielewicz Bartłomiej , Gandotra Neeraj , Shekhovtsov Andrii , Saini Namita , Saeid Arsham Borumand , Sałabun Wojciech
Published: December 2021

In this paper, we propose a new intuitionistic entropy measurement for multi-criteria decision-making (MCDM) problems. The entropy of an intuitionistic fuzzy set (IFS) measures uncertainty related to the data modelling as IFS. The entropy of fuzzy sets is widely used in decision support methods, where dealing with uncertain data grows in importance. The Complex Proportional Assessment (COPRAS) method identifies the preferences and ranking of decisional variants. It also allows for a more comprehensive analysis of complex decision-making problems, where many opposite criteria are observed. This approach allows us to minimize cost and maximize profit in the finally chosen decision (alternative). This paper presents a new entropy measurement for fuzzy intuitionistic sets and an application example using the IFS COPRAS method. The new entropy method was used in the decision-making process to calculate the objective weights. In addition, other entropy methods determining objective weights were also compared with the proposed approach. The presented results allow us to conclude that the new entropy measure can be applied to decision problems in uncertain data environments since the proposed entropy measure is stable and unambiguous.
Genetic Diversity of Armenian Grapevine (Vitis vinifera L.) Germplasm: Molecular Characterization and Parentage Analysis
Authors: Margaryan Kristine , Melyan Gagik , Röckel Franco , Töpfer Reinhard , Maul Erika
Published: December 2021

Armenia is an important country of origin of cultivated Vitis vinifera subsp. vinifera and wild Vitis vinifera subsp. sylvestris and has played a key role in the long history of grape cultivation in the Southern Caucasus. The existence of immense grapevine biodiversity in a small territory is strongly linked with unique relief and diverse climate conditions assembled with millennium-lasting cultural and historical context. In the present in-depth study using 25 nSSR markers, 492 samples collected in old vineyards, home gardens, and private collections were genotyped. For verification of cultivar identity, the symbiotic approach combining genotypic and phenotypic characterization for each genotype was carried out. The study provided 221 unique varieties, including 5 mutants, from which 66 were widely grown, neglected or minor autochthonous grapevine varieties, 49 turned out to be new bred cultivars created within the national breeding programs mainly during Soviet Era and 34 were non-Armenian varieties with different countries of origin. No references and corresponding genetic profiles existed for 67 genotypes. Parentage analysis was performed inferring 62 trios with 53 out of them having not been previously reported and 185 half-kinships. Instability of grapevine cultivars was detected, showing allelic variants, with three and in rare cases four alleles at one loci. Obtained results have great importance and revealed that Armenia conserved an extensive grape genetic diversity despite geographical isolation and low material exchange. This gene pool richness represents a huge reservoir of under-explored genetic diversity.