bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Community Discovery Method Based on Phylogenetic Planted Partition in Temporal Networks
Authors: Liu Xiaoyang , Ding Nan , Fiumara Giacomo , De Meo Pasquale , Ficara Annamaria
Published: April 2022

As most of the community discovery methods are researched by static thought, some community discovery algorithms cannot represent the whole dynamic network change process efficiently. This paper proposes a novel dynamic community discovery method (Phylogenetic Planted Partition Model, PPPM) for phylogenetic evolution. Firstly, the time dimension is introduced into the typical migration partition model, and all states are treated as variables, and the observation equation is constructed. Secondly, this paper takes the observation equation of the whole dynamic social network as the constraint between variables and the error function. Then, the quadratic form of the error function is minimized. Thirdly, the Levenberg–Marquardt (L–M) method is used to calculate the gradient of the error function, and the iteration is carried out. Finally, simulation experiments are carried out under the experimental environment of artificial networks and real networks. The experimental results show that: compared with FaceNet, SBM + MLE, CLBM, and PisCES, the proposed PPPM model improves accuracy by 5% and 3%, respectively. It is proven that the proposed PPPM method is robust, reasonable, and effective. This method can also be applied to the general social networking community discovery field.
Multi-Modal X-ray Imaging and Analysis for Characterization of Urinary Stones
Authors: Saghamanesh Somayeh , Richter Henning , Neels Antonia , Zboray Robert
Published: April 2022

Backgound: The composition of stones formed in the urinary tract plays an important role in their management over time. The most common imaging method for the non-invasive evaluation of urinary stones is radiography and computed tomography (CT). However, CT is not very sensitive, and cannot differentiate between all critical stone types. In this study, we propose the application, and evaluate the potential, of a multi-modal (or multi-contrast) X-ray imaging technique called speckle-based imaging (SBI) to differentiate between various types of urinary stones. Methods: Three different stone samples were extracted from animal and human urinary tracts and examined in a laboratory-based speckle tracking setup. The results were discussed based on an X-ray diffraction analysis and a comparison with X-ray microtomography and grating-based interferometry. Results: The stones were classified through compositional analysis by X-ray diffraction. The multi-contrast images obtained using the SBI method provided detailed information about the composition of various urinary stone types, and could differentiate between them. X-ray SBI could provide highly sensitive and high-resolution characterizations of different urinary stones in the radiography mode, comparable to those by grating interferometry. Conclusions: This investigation demonstrated the capability of the SBI technique for the non-invasive classification of urinary stones through radiography in a simple and cost-effective laboratory setting. This opens the possibility for further studies concerning full-field in vivo SBI for the clinical imaging of urinary stones.
Comparison of Ionospheric Response to Two Types of Electron Concentration Disturbances
Authors: Yakovets Artur F. , Gordiyenko Galina I. , Kryakunova Olga N. , Litvinov Yurii G.
Published: April 2022

Based on the data of vertical sounding of the ionosphere in Almaty in 2000–2008, the paper deals with the response of the F2-layer to the passage of large-scale traveling ionospheric disturbances (LSTIDs) and the formation of the nighttime enhancements in the electron concentration of the F2-layer. For these two types of perturbations, we compared behavior in the time of the following layer parameters: the height of maximum of the layer (hmF), the height of the bottom of the layer (hbotF), the half-thickness of the layer (Δh = hmF − hbotF), the electron concentration at fixed heights and at the maximum of the layer (NmF), the height profiles of the nighttime enhancement peak-to-peak value of the F2-layer (A), and the height hAm corresponding to the maximum enhancement amplitude. The parameters hmF, hbotF and Δh demonstrate similar dependences associated with the temporal expansion and upward rise of the ionospheric layer and its lowering, accompanied by layer compression, giving an NmF peak at the moment of maximum compression. The common features of the profiles of two types of disturbances are found: the height hAm is always below hmF, there is a good correlation between hAm and hmF, and the difference between hAm and hmF increases linearly with hmF.
Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
Authors: Chalyan Tatevik , Magnus Indy , Konstantaki Maria , Pissadakis Stavros , Diamantakis Zacharias , Thienpont Hugo , Ottevaere Heidi
Published: April 2022

Due to its physical, chemical, and structural properties, oakwood is widely used in the production of barrels for wine ageing. When in contact with the wine, oak continuously releases aromatic compounds such as lignin, tannin, and cellulose to the liquid. Due to the release process, oak loses its characteristic aromatic compounds in time; hence, the flavour that it gives to the enclosed wine decreases for repeated wine refills and a barrel replacement is required. Currently, the estimation of the maximum number of refills is empirical and its underestimation or overestimation can impose unnecessary costs and impair the quality of the wine. Therefore, there is a clear need to quantify the presence of the aforementioned aromatic compounds in an oak barrel prior to a refill. This work constitutes a study to examine noninvasive optical biosensing techniques for the characterization of an oak barrel used in wine ageing, towards the development of a model to unveil its lifespan without inducing structural damage. Spectroscopic diagnostic techniques, such as reflectance, fluorescence, and Raman scattering measurements are employed to assess the change in the chemical composition of the oakwood barrel (tannin and lignin presence) and its dependence on repeated refills. To our knowledge, this is the first time that we present a benchmarking study of oak barrel ageing characteristics through spectroscopic methods for the wine industry. The spectroscopic data are processed using standard chemometric techniques, such as Linear Discriminant Analysis and Partial Least Squares Discriminant Analysis. Results of a study of fresh, one-time-used, and two-times-used oak barrel samples demonstrate that reflectance spectroscopy can be a valuable tool for the characterization of oak barrels. Moreover, reflectance spectroscopy has demonstrated the most accurate classification performance. The highest accuracy has been obtained by a Partial Least Squares Discriminant Analysis model that has been able to classify all the oakwood samples from the barrels with >99% accuracy. These preliminary results pave a way for the application of cost-effective and non-invasive biosensing techniques based on reflectance spectroscopy for oak barrels assessment.
Lysosomes Dysfunction Causes Mitophagy Impairment in PBMCs of Sporadic ALS Patients
Authors: Bordoni Matteo , Pansarasa Orietta , Scarian Eveljn , Cristofani Riccardo , Leone Roberta , Fantini Valentina , Garofalo Maria , Diamanti Luca , Bernuzzi Stefano , Gagliardi Stella , Carelli Stephana , Poletti Angelo , Cereda Cristina
Published: April 2022

Mitochondria alterations are present in tissues derived from patients and animal models, but no data are available for peripheral blood mononuclear cells (PBMCs) of ALS patients. This work aims to investigate mitophagy in PBMCs of sporadic (sALS) patients and how this pathway can be tuned by using small molecules. We found the presence of morphologically atypical mitochondria by TEM and morphological abnormalities by MitoTracker™. We found a decreased number of healthy mitochondria in sALS PBMCs and an impairment of mitophagy with western blot and immunofluorescence. After rapamycin treatment, we found a higher increase in the LC3 marker in sALS PBMCs, while after NH4Cl treatment, we found a lower increase in the LC3 marker. Finally, mTOR-independent autophagy induction with trehalose resulted in a significant decrease in the lysosomes level sALS PBMCs. Our data suggest that the presence of morphologically altered mitochondria and an inefficient turnover of damaged mitochondria in PBMCs of sALS patients rely on the impairment of the mitophagy pathway. We also found that the induction of the mTOR-independent autophagy pathway leads to a decrease in lysosomes level, suggesting a more sensitivity of sALS PBMCs to trehalose. Such evidence suggests that trehalose could represent an effective treatment for ALS patients.
Mechanistic Origin of Different Binding Affinities of SARS-CoV and SARS-CoV-2 Spike RBDs to Human ACE2
Authors: Zhang Zhi-Bi , Xia Yuan-Ling , Shen Jian-Xin , Du Wen-Wen , Fu Yun-Xin , Liu Shu-Qun
Published: April 2022

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (RBDCoV2) has a higher binding affinity to the human receptor angiotensin-converting enzyme 2 (ACE2) than the SARS-CoV RBD (RBDCoV). Here, we performed molecular dynamics (MD) simulations, binding free energy (BFE) calculations, and interface residue contact network (IRCN) analysis to explore the mechanistic origin of different ACE2-binding affinities of the two RBDs. The results demonstrate that, when compared to the RBDCoV2-ACE2 complex, RBDCoV-ACE2 features enhanced dynamicsand inter-protein positional movements and increased conformational entropy and conformational diversity. Although the inter-protein electrostatic attractive interactions are the primary determinant for the high ACE2-binding affinities of both RBDs, the significantly enhanced electrostatic attractive interactions between ACE2 and RBDCoV2 determine the higher ACE2-binding affinity of RBDCoV2 than of RBDCoV. Comprehensive comparative analyses of the residue BFE components and IRCNs between the two complexes reveal that it is the residue changes at the RBD interface that lead to the overall stronger inter-protein electrostatic attractive force in RBDCoV2-ACE2, which not only tightens the interface packing and suppresses the dynamics of RBDCoV2-ACE2, but also enhances the ACE2-binding affinity of RBDCoV2. Since the RBD residue changes involving gain/loss of the positively/negatively charged residues can greatly enhance the binding affinity, special attention should be paid to the SARS-CoV-2 variants carrying such mutations, particularly those near or at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2.
Stem-Cell Therapy for Bronchopulmonary Dysplasia (BPD) in Newborns
Authors: Omar Said A. , Abdul-Hafez Amal , Ibrahim Sherif , Pillai Natasha , Abdulmageed Mohammed , Thiruvenkataramani Ranga Prasanth , Mohamed Tarek , Madhukar Burra V. , Uhal Bruce D.
Published: April 2022

Premature newborns are at a higher risk for the development of respiratory distress syndrome (RDS), acute lung injury (ALI) associated with lung inflammation, disruption of alveolar structure, impaired alveolar growth, lung fibrosis, impaired lung angiogenesis, and development of bronchopulmonary dysplasia (BPD) with severe long-term developmental adverse effects. The current therapy for BPD is limited to supportive care including high-oxygen therapy and pharmacotherapy. Recognizing more feasible treatment options to improve lung health and reduce complications associated with BPD is essential for improving the overall quality of life of premature infants. There is a reduction in the resident stem cells in lungs of premature infants with BPD, which strongly suggests a critical role of stem cells in BPD pathogenesis; this warrants the exploration of the potential therapeutic use of stem-cell therapy. Stem-cell-based therapies have shown promise for the treatment of many pathological conditions including acute lung injury and BPD. Mesenchymal stem cells (MSCs) and MSC-derived extracellular vesicles (EVs) including exosomes are promising and effective therapeutic modalities for the treatment of BPD. Treatment with MSCs and EVs may help to reduce lung inflammation, improve pulmonary architecture, attenuate pulmonary fibrosis, and increase the survival rate.
Distinct CholinomiR Blood Cell Signature as a Potential Modulator of the Cholinergic System in Women with Fibromyalgia Syndrome
Authors: Erbacher Christoph , Vaknine Shani , Moshitzky Gilli , Lobentanzer Sebastian , Eisenberg Lina , Evdokimov Dimitar , Sommer Claudia , Greenberg David S. , Soreq Hermona , Üçeyler Nurcan
Published: April 2022

Fibromyalgia syndrome (FMS) is a heterogeneous chronic pain syndrome characterized by musculoskeletal pain and other key co-morbidities including fatigue and a depressed mood. FMS involves altered functioning of the central and peripheral nervous system (CNS, PNS) and immune system, but the specific molecular pathophysiology remains unclear. Anti-cholinergic treatment is effective in FMS patient subgroups, and cholinergic signaling is a strong modulator of CNS and PNS immune processes. Therefore, we used whole blood small RNA-sequencing of female FMS patients and healthy controls to profile microRNA regulators of cholinergic transcripts (CholinomiRs). We compared microRNA profiles with those from Parkinson’s disease (PD) patients with pain as disease controls. We validated the sequencing results with quantitative real-time PCR (qRT-PCR) and identified cholinergic targets. Further, we measured serum cholinesterase activity in FMS patients and healthy controls. Small RNA-sequencing revealed FMS-specific changes in 19 CholinomiRs compared to healthy controls and PD patients. qRT-PCR validated miR-182-5p upregulation, distinguishing FMS patients from healthy controls. mRNA targets of CholinomiRs bone morphogenic protein receptor 2 and interleukin 6 signal transducer were downregulated. Serum acetylcholinesterase levels and cholinesterase activity in FMS patients were unchanged. Our findings identified an FMS-specific CholinomiR signature in whole blood, modulating immune-related gene expression.
Rheological Properties of Cement Paste Containing Ground Fly Ash Based on Particle Morphology Analysis
Authors: Ma Juntao , Zhang Huifang , Wang Daguang , Wang Huixian , Chen Gonglian
Published: April 2022

Separating finer particles from raw fly ash is a popular method to produce high-performance admixture of concrete. However, the supply of separated fly ash is obviously behind the demand and the residue fly ash is difficult to be disposed. Ground fly ash is another method to improve the particle size and reactivity, but the change of particle morphology during grinding may affect the rheological properties of cement paste and concrete, which limits the application of ground fly ash in concrete projects. In this study, the raw fly ash, separated fly ash, and ground fly ash of the same particle size range were studied and the particle morphology was analyzed by Image-Pro Plus process and spherical particles proportion calculation. On this basis, the fluidity and rheological properties of cement paste with different fly ash content were tested and the mechanism was discussed by packing density and zeta potential analysis. The results showed that the total amount of spherical particles in fly ash-cement paste system was reduced due to the spherical particles of ground fly ash being destroyed during the grinding process. Thus, compared with the separated fly ash of similar particle size range, the fluidity of ground fly ash was significantly decreased while the yield stress and plastic viscosity increased significantly, which indicated that the rheological properties of fly ash cement paste are closely related to the particle morphology of fly ash. The results provide theoretical basis and technology support to the application of ground fly ash.
Classification of Building Types in Germany: A Data-Driven Modeling Approach
Authors: Bandam Abhilash , Busari Eedris , Syranidou Chloi , Linssen Jochen , Stolten Detlef
Published: April 2022

Details on building levels play an essential part in a number of real-world application models. Energy systems, telecommunications, disaster management, the internet-of-things, health care, and marketing are a few of the many applications that require building information. The essential variables that most of these models require are building type, house type, area of living space, and number of residents. In order to acquire some of this information, this paper introduces a methodology and generates corresponding data. The study was conducted for specific applications in energy system modeling. Nonetheless, these data can also be used in other applications. Building locations and some of their details are openly available in the form of map data from OpenStreetMap (OSM). However, data regarding building types (i.e., residential, industrial, office, single-family house, multi-family house, etc.) are only partially available in the OSM dataset. Therefore, a machine learning classification algorithm for predicting the building types on the basis of the OSM buildings’ data was introduced. Although the OSM dataset is the fundamental and most crucial one used for modeling, the machine learning algorithm’s training was performed on a dataset that was prepared by combining several features from three other datasets. The generated dataset consists of approximately 29 million buildings, of which about 19 million are residential, with 72% being single-family houses and the rest multi-family ones that include two-family houses and apartment buildings. Furthermore, the results were validated through a comparison with publicly available statistical data. The comparison of the resulting data with official statistics reveals that there is a percentage error of 3.64% for residential buildings, 13.14% for single-family houses, and −15.38% for multi-family houses classification. Nevertheless, by incorporating the building types, this dataset is able to complement existing building information in studies in which building type information is crucial.
Medical Drone Managing System for Automated External Defibrillator Delivery Service
Authors: Purahong Boonchana , Anuwongpinit Thanavit , Juhong Aniwat , Kanjanasurat Isoon , Pintaviooj Chuchart
Published: April 2022

One of the common causes of a heart attack is fibrillation, a condition that causes an irregular and often abnormally fast heart rate. There is scientific evidence that the survival rate of sudden cardiac arrest patients who are rescued with cardiopulmonary resuscitation (CPR) and with the use of an automated external defibrillator (AED) is significantly increased. Despite the recommendation that automated external defibrillators should be installed in the workplace, along with a proper management system and training for employees on how to use the device, less than 70% of non-residential areas have an AED installed. The situation is even worse in residential areas, with less than 30% having an AED installed. This research concerns the development of a medical drone managing system that can deliver an AED in case of emergency. An application was developed that can be installed on the mobile phone and/or tablet of the patient or the accompanying person. In the event of a heart attack, the patient or the accompanying person can call a medical drone by sending coordinates to the drone station and a notification to medical staff. The drone station administrator can respond by sending the drone, which automatically lands at the patient’s location. After being tested in a simulation situation, the operational field test yielded satisfactory results. The medical drone can land within 1.5 m of the destination. The designed AED drone can be used not only to deliver AEDs, but also first aid kits and prescribed drugs suitable for medical care. Such a system is especially useful in the current context of the COVID-19 pandemic.
Multitasking Learning Model Based on Hierarchical Attention Network for Arabic Sentiment Analysis Classification
Authors: Alali Muath , Mohd Sharef Nurfadhlina , Azmi Murad Masrah Azrifah , Hamdan Hazlina , Husin Nor Azura
Published: April 2022

Limited approaches have been applied to Arabic sentiment analysis for a five-point classification problem. These approaches are based on single task learning with a handcrafted feature, which does not provide robust sentence representation. Recently, hierarchical attention networks have performed outstandingly well. However, when training such models as single-task learning, these models do not exhibit superior performance and robust latent feature representation in the case of a small amount of data, specifically on the Arabic language, which is considered a low-resource language. Moreover, these models are based on single task learning and do not consider the related tasks, such as ternary and binary tasks (cross-task transfer). Centered on these shortcomings, we regard five ternary tasks as relative. We propose a multitask learning model based on hierarchical attention network (MTLHAN) to learn the best sentence representation and model generalization, with shared word encoder and attention network across both tasks, by training three-polarity and five-polarity Arabic sentiment analysis tasks alternately and jointly. Experimental results showed outstanding performance of the proposed model, with high accuracy of 83.98%, 87.68%, and 84.59 on LABR, HARD, and BRAD datasets, respectively, and a minimum macro mean absolute error of 0.632% on the Arabic tweets dataset for five-point Arabic sentiment classification problem.
Performance Analysis of Root Anycast Nodes Based on Active Measurement
Authors: Li Chao , Cheng Yanan , Men Hao , Zhang Zhaoxin , Li Ning
Published: April 2022

The root server is at the top of the domain name hierarchical structure. To improve root service performance, each root deploys anycast nodes worldwide. What is the actual service performance of these nodes after deployment? We analyze the service performance of the root anycast nodes deployed in China based on the active measurement data detected by the VPs of different ISPs in different geographical locations. From the analysis, we find that the resolution performance of the roots with anycast nodes deployed in China is higher than that of roots without deployment. However, users of different operators have significant differences in accessing the root servers, such as parsing time, hitting anycast nodes, and most anycast nodes only providing services for one operator, limiting the service scope and reducing the service performance. The analysis results can help the root management and introduction institutions master the actual service status of the root servers, which can be used to optimize the performance of the existing root anycast nodes and provide a basis for deploying new root anycast nodes in the next step. Finally, we find that 67 top-level domain names are hijacked on the resolution path based on the measured data.
A New Self-Adaptive Teaching–Learning-Based Optimization with Different Distributions for Optimal Reactive Power Control in Power Networks
Authors: Alghamdi Ali S.
Published: April 2022

Teaching–learning-based optimization has the disadvantages of weak population diversity and the tendency to fall into local optima, especially for multimodal and high-dimensional problems such as the optimal reactive power dispatch problem. To overcome these shortcomings, first, in this study, a new enhanced TLBO is proposed through novel and effective θ-self-adaptive teaching and learning to optimize voltage and active loss management in power networks, which is called the optimal reactive power control problem with continuous and discontinuous control variables. Voltage and active loss management in any energy network can be optimized by finding the optimal control parameters, including generator voltage, shunt power compensators, and the tap positions of tap changers, among others. As a result, an efficient and powerful optimization algorithm is required to handle this challenging situation. The proposed algorithms utilized in this research were improved by introducing new mutation operators for multi-objective optimal reactive power control in popular standard IEEE 30-bus and IEEE 57-bus networks. The numerical simulation data reveal potential high-quality solutions with better performance and accuracy using the proposed optimization algorithms in comparison with the basic teaching–learning-based optimization algorithm and previously reported results.
Hybrid Vehicles as a Transition for Full E-Mobility Achievement in Positive Energy Districts: A Comparative Assessment of Real-Driving Emissions
Authors: Pignatta Gloria , Balazadeh Navid
Published: April 2022

Air pollution is a major concern, particularly in developing countries. Road transport and mobile sources are considered the root causes of air pollutants. With the implementation of zero-carbon and zero-energy concepts at the district scale, cities can make great strides towards sustainable development. Urban planning schemes are moving from mere building solutions to the larger positive energy district (PED) scale. Alongside other technology systems in PEDs, increased uptake of electro-mobility solutions can play an important role in CO2 mitigation at the district level. This paper aims to quantify the exhaust emissions of six conventional and two fully hybrid vehicles using a portable emission measurement system (PEMS) in real driving conditions. The fuel consumption and exhaust pollutants of the conventional and hybrid vehicles were compared in four different urban and highway driving routes during autumn 2019 in Iran. The results showed that hybrid vehicles presented lower fuel consumption and produced relatively lower exhaust emissions. The conventional group’s fuel consumption (CO2 emissions) was 11%, 41% higher than that of the hybrids. In addition, the hybrid vehicles showed much better fuel economy in urban routes, which is beneficial for PEDs. Micro-trip analysis showed that although conventional vehicles emitted more CO2 at lower speeds, the hybrids showed a lower amount of CO2. Moreover, in conventional vehicles, NOx emissions showed an increasing trend with vehicle speed, while no decisive trend was found for NOx emissions versus vehicle speed in hybrid vehicles.
Test and Modelling of Solid Oxide Fuel Cell Durability: A Focus on Interconnect Role on Global Degradation
Authors: Spotorno Roberto , Bianchi Fiammetta Rita , Paravidino Daniele , Bosio Barbara , Piccardo Paolo
Published: April 2022

High-temperature fuel cells are a promising technology due to their high energy efficiency and low environmental impacts compared to conventional engines. Nevertheless, they have a limited lifetime which reduces the use to a few application fields. Among them, Solid Oxide Fuel Cells (SOFCs) have had a recent development at the industrial level in two possible configurations: anode- and electrolyte-supported design. Considering the impossibility to experimentally distinguish the effects of every degradation mechanism on global cell performance, each layer should be tested singularly through ex situ tests and then assembled into a virgin cell to evaluate its role on the whole system by in situ tests. However, this procedure results as quite complex, and some further microstructural changes could occur during cell sintering. In order to overcome these constraints, the proposed approach paired ex situ experimental observations on a single element with modelling results on global SOFC. As a case study, CoMnO/Crofer22 APU and CuMnO/AISI 441 interconnect samples were tested, measuring their resistance variation for some hundreds of hours, followed by a detailed post-mortem microstructural analysis. Based on a previously validated local model, SIMFC (SIMulation of Fuel Cells), the durability of commercial anode- and electrolyte-supported cells was simulated, adding specific degradation functions only for the interconnects in order to highlight their influence on SOFC performance.
An Impedance Matching Solution to Increase the Harvested Power and Efficiency of Nonlinear Piezoelectric Energy Harvesters
Authors: Bonnin Michele , Traversa Fabio L. , Bonani Fabrizio
Published: April 2022

Circuit theory and nonlinear dynamics are instrumental to design efficient energy harvesters for ambient mechanical vibrations. In this work, we show that an impedance matching networks can be designed that maximizes the harvested power, and improves the power efficiency. The proposed matching network achieves impedance matching at a single frequency, that can be chosen at will by the designer, and does not need to coincide with the resonant frequency of the harvester. Moreover, the matching network also increases the harvested power over a wide frequency bandwidth. According to our numerical simulations, the matching network increases the maximum harvested power by a factor greater than 3, and the power harvested over the whole frequency spectrum by a factor of 6. The frequency bandwidth can be further extended considering nonlinear energy harvesters. Even using the matching network designed for the linear case, performance is significantly nonetheless improved for the nonlinear harvester.
Numerical Determination of the Accuracy of Gravity Center Coordinates and Stability of a Model Concept of Harvester with the Rigid Frame
Authors: Mergl Václav , Kašpárek Jaroslav
Published: April 2022

The paper deals with the verification of the stability of a new design concept of a hybrid harvester intended for thinning and with the determination of deviation between two methods of measuring the machine’s center of gravity, i.e., between the methods of determining the center of gravity using the SolidWorks software made by Dassault Systems and using portable vehicle scales with the function of gravity center calculation. The machine was measured in five different positions from going up or down the slope or driving along the contour line. The new prototype of a harvester with a non-conventional rigid frame and both axles steered was found to be unstable at the maximum reach of hydraulic boom if it is situated at a right angle (±90°) to the machine longitudinal axis. A comparison of the two methods of determining the center of gravity resulted in a total deviation of 8.41%, with the deviation for x being on average 14.36% and for y only 3.08%.
Influence of Natural Polysaccharides on Intestinal Microbiota in Inflammatory Bowel Diseases: An Overview
Authors: Li Qi , Li Linyan , Li Qiqiong , Wang Junqiao , Nie Shaoping , Xie Mingyong
Published: April 2022

The incidence of inflammatory bowel disease (IBD) has increased in recent years. Considering the potential side effects of conventional drugs, safe and efficient treatment methods for IBD are required urgently. Natural polysaccharides (NPs) have attracted considerable attention as potential therapeutic agents for IBD owing to their high efficiency, low toxicity, and wide range of biological activities. Intestinal microbiota and their fermentative products, mainly short-chain fatty acids (SCFAs), are thought to mediate the effect of NPs in IBDs. This review explores the beneficial effects of NPs on IBD, with a special focus on the role of intestinal microbes. Intestinal microbiota exert alleviation effects via various mechanisms, such as increasing the intestinal immunity, anti-inflammatory activities, and intestinal barrier protection via microbiota-dependent and microbiota-independent strategies. The aim of this paper was to document evidence of NP–intestinal microbiota-associated IBD prevention, which would be helpful for guidance in the treatment and management of IBD.
Certain Hybrid Matrix Polynomials Related to the Laguerre-Sheffer Family
Authors: Nahid Tabinda , Choi Junesang
Published: April 2022

The main goal of this article is to explore a new type of polynomials, specifically the Gould-Hopper-Laguerre-Sheffer matrix polynomials, through operational techniques. The generating function and operational representations for this new family of polynomials will be established. In addition, these specific matrix polynomials are interpreted in terms of quasi-monomiality. The extended versions of the Gould-Hopper-Laguerre-Sheffer matrix polynomials are introduced, and their characteristics are explored using the integral transform. Further, examples of how these results apply to specific members of the matrix polynomial family are shown.
New Riemann–Liouville Fractional-Order Inclusions for Convex Functions via Interval-Valued Settings Associated with Pseudo-Order Relations
Authors: Srivastava Hari Mohan , Sahoo Soubhagya Kumar , Mohammed Pshtiwan Othman , Kodamasingh Bibhakar , Hamed Yasser S.
Published: April 2022

In this study, we focus on the newly introduced concept of LR-convex interval-valued functions to establish new variants of the Hermite–Hadamard (H-H) type and Pachpatte type inequalities for Riemann–Liouville fractional integrals. By presenting some numerical examples, we also verify the correctness of the results that we have derived in this paper. Because the results, which are related to the differintegral of the ϱ1+ϱ22 type, are novel in the context of the LR-convex interval-valued functions, we believe that this will be a useful contribution for motivating future research in this area.
Design and Application of an Interval Estimator for Nonlinear Discrete-Time SEIR Epidemic Models
Authors: Khan Awais , Bai Xiaoshan , Ilyas Muhammad , Rauf Arshad , Xie Wei , Yan Peiguang , Zhang Bo
Published: April 2022

This paper designs an interval estimator for a fourth-order nonlinear susceptible-exposed-infected-recovered (SEIR) model with disturbances using noisy counts of susceptible people provided by Public Health Services (PHS). Infectious diseases are considered the main cause of deaths among the top ten worldwide, as per the World Health Organization (WHO). Therefore, tracking and estimating the evolution of these diseases are important to make intervention strategies. We study a real case in which some uncertain variables such as model disturbances, uncertain input and output measurement noise are not exactly available but belong to an interval. Moreover, the uncertain transmission bound rate from the susceptible towards the exposed stage is not available for measurement. We designed an interval estimator using an observability matrix that generates a tight interval vector for the actual states of the SEIR model in a guaranteed way without computing the observer gain. As the developed approach is not dependent on observer gain, our method provides more freedom. The convergence of the width to a known value in finite time is investigated for the estimated state vector to prove the stability of the estimation error, significantly improving the accuracy for the proposed approach. Finally, simulation results demonstrate the satisfying performance of the proposed algorithm.
Knockdown of CDR1as Decreases Differentiation of Goat Skeletal Muscle Satellite Cells via Upregulating miR-27a-3p to Inhibit ANGPT1
Authors: Kyei Bismark , Odame Emmanuel , Li Li , Yang Liu , Zhan Siyuan , Li Juntao , Chen Yuan , Dai Dinghui , Cao Jiaxue , Guo Jiazhong , Zhong Tao , Wang Linjie , Zhang Hongping
Published: April 2022

Myogenesis is a complex process controlled by several coding and non-coding RNAs (ncRNAs), such as circular RNAs (circRNAs) that are known to function as endogenous microRNAs (miRNAs) sponges. Cerebellar Degeneration-Related protein 1 antisense (CDR1as) is the most spotlighted circRNA that is known as an miR-7 sponge, which has bloomed circRNAs’ research in animal disease and physiology. Here, we screened for miRNAs and mRNA associated with CDR1as and further characterized their regulatory function during muscle differentiation. We found that a total of 43 miRNAs (including miR-107-3p, miR-125b-5p, miR-140-5p, miR-29a-3p, and miR-27a-3p upregulated) and 789 mRNAs (including ANGPT1, E2F2, CCN1, FGFR1, and MEF2C downregulated) were differentially expressed in goat skeletal muscle satellite cells (SMSCs). Further, knockdown of CDR1as and ANGPT1 inhibited SMSCs differentiation. miR-27a-3p was differentially upregulated after the knockdown of CDR1as in SMSCs. Overexpressed miR-27a-3p decreased SMSCs differentiation. Via RNAhybrid and luciferase, miR-27a-3p was identified to regulate ANGPT1. We discovered that miR-27a-3p has an inverse relationship with CDR1as and decreases the expression level of ANGPT1 during SMSCs differentiation. In summary, our study demonstrates that siCDR1as inhibits myoblast differentiation by downregulating ANGPT1 mRNA via miR-27a-3p in SMSCs.
Identification and Characterization of Variants in Intron 6 of the LPL Gene Locus among a Sample of the Kuwaiti Population
Authors: Al-Shammari Reem T. , Al-Serri Ahmad E. , Barhoush Sahar A. , Al-Bustan Suzanne A.
Published: April 2022

Lipoprotein lipase (LPL) is responsible for the hydrolysis of lipoproteins; hence defective LPL is associated with metabolic disorders. Here, we identify certain intronic insertions and deletions (InDels) and single nucleotide polymorphisms (SNPs) in intron 6 of the LPL gene and investigate their associations with different phenotypic characteristics in a cohort of the general Kuwaiti population. Two specific regions of intron 6 of the LPL gene, which contain InDels, were amplified via Sanger sequencing in 729 subjects. Genotypic and allelic frequencies were estimated, and genetic modeling was used to investigate genetic associations of the identified variants with lipid profile, body mass index (BMI), and risk of coronary heart disease (CHD). A total of 16 variants were identified, including 2 InDels, 2 novel SNPs, and 12 known SNPs. The most common variants observed among the population were rs293, rs274, rs295, and rs294. The rs293 “A” insertion showed a significant positive correlation with elevated LDL levels, while rs295 was significantly associated with increased BMI. The rs274 and rs294 variants showed a protective effect of the minor allele with decreased CHD prevalence. These findings shed light on the possible role of LPL intronic variants on metabolic disorders.
Use of Artificial Neural Networks as a Predictive Tool of Dissolved Oxygen Present in Surface Water Discharged in the Coastal Lagoon of the Mar Menor (Murcia, Spain)
Authors: García del Toro Eva M. , Mateo Luis Francisco , García-Salgado Sara , Más-López M. Isabel , Quijano Maria Ángeles
Published: April 2022

The Mar Menor is a Mediterranean coastal saltwater lagoon (Murcia, Spain) that represents a unique ecosystem of vital importance for the area, from both an economic and ecological point of view. During the last decades, the intense agricultural activity has caused episodes of eutrophication due to the contribution of inorganic nutrients, especially nitrates. For this reason, it is important to control the quality of the water discharged into the Mar Menor lagoon, which can be performed through the measurement of dissolved oxygen (DO). Therefore, this article aimed to predict the DO in the water discharged into this lagoon through the El Albujón watercourse, for which two theoretical models consisting of a multiple linear regression (MLR) and a back-propagation neural network (RPROP) were developed. Data of temperature, pH, nitrates, chlorides, sulphates, electrical conductivity, phosphates and DO at the mouth of this watercourse, between January 2014 and January 2021, were used. A preliminary statistical study was performed to discard the variables with the lowest influence on DO. Finally, both theoretical models were compared by means of the coefficient of determination (R2), the root mean square errors (RMSE) and the mean absolute error (MAE), concluding that the neural network made a more accurate prediction of DO.
Transition to Labor Market among Young Adults with Serious Mental Illness
Authors: Boaz Inbal , Ben Ari Eynat , Lipskaya-Velikovsky Lena , Ratzon Navah Z.
Published: April 2022

Background: The research on job attainment and retention among young adults with serious mental illness (SMI) is limited. The objective of this study was to investigate the contributions of emotional, cognitive, motor, demographic, and work-related factors to the transition into supported employment (SE) and retention. Methods: This cross-sectional study included young adults with SMI involved in prevocational (N = 21) services or those who have transferred to SE (N = 21) following prevocational services. Work-related self-efficacy, executive functions, and motor skills were approached with standard and well-established tools. Results: There was a significant difference between groups in most dimensions of work-related self-efficacy, job history and experience, cognitive strategies, and general independence in daily life. The multivariate analysis demonstrates that holding a profession, experiencing self-efficacy in general work skills, cognitive strategies, and independence in living situations explained the between-group differences (χ2(4) = 34.62, p < 0.001; correct classification–90.2%). Conclusions: The study identifies the factors contributing to a sustainable transition to employment among young adults with SMI, suggesting the importance of a comprehensive approach to address a range of personal factors in an integrative way. The augmentation of prevocational training with continued employment support may be beneficial to meet the unique needs of young adults with SMI.
Breastfeeding Experience among Mothers during the COVID-19 Pandemic
Authors: Badr Hanan , Alghamdi Salmah
Published: April 2022

When health experts declared COVID-19 to be a global pandemic, they recognized the virus as a major environmental factor that could affect the practice of breastfeeding. A few studies focused on the effect of COVID-19 on mothers who gave birth during the pandemic. The purpose of this study is to explore the experience of Saudi Arabian breastfeeding mothers during the COVID-19 pandemic. This study used a descriptive phenomenology qualitative design and a convenience sample of 18 mothers who breastfed their children beginning in March 2020. Data were collected through semi-structured, open-ended phone interviews and analyzed using thematic analysis. The mothers were between 27 and 36 years old, and most of them had previous breastfeeding experience. Four main themes emerged regarding breastfeeding experiences during the COVID-19 pandemic: breastfeeding experience (positive and negative), support, facilitators, and challenges. Most mothers felt their experience with breastfeeding during the pandemic encouraged them to continue. It is important to reassure and educate breastfeeding mothers about the nature of COVID-19 and its mode of transmission. The findings from this study lay the foundation for future research to support the practice of breastfeeding and overcome the challenges that arose during the pandemic.
Effects of Parent Brand Equity on Perceived Fit and Customer Behavior of Extended Brand—Focused on MICE Destination
Authors: Lee Jiwon , Yoon Eunjoo
Published: April 2022

This study aims to examine the relationship among tourism destination brand equity (as parent brand), perceived fit, and customer behavior intention toward the extended MICE destination brand. It also identifies the moderating effect of place attachment between brand equity and customer behavior by adopting the brand extension concept in tourism and MICE destinations. The analysis of data collected from 381 respondents revealed that perceived fit is the most important factor influencing customer behavior, even though tourism brand equity and place attachment both had a positive effect on customer behavior, supporting all hypotheses. The theoretical implication of broadening the brand extension concept in MICE destinations and DMO marketing strategies is discussed.
Visual Analysis of Vessel Behaviour Based on Trajectory Data: A Case Study of the Yangtze River Estuary
Authors: Li Ye , Ren Hongxiang
Published: April 2022

The widespread of shipborne Automatic Identification System (AIS) equipment will continue to produce a large amount of spatiotemporal trajectory data. In order to explore and understand the hidden behaviour patterns in the data, an interactive visual analysis method combining multiple views is proposed. The method mainly includes four parts: using a trajectory compression algorithm that takes into account the vessel motion characteristics to preprocess the vessel trajectory data; displaying and replaying vessel trajectories based on Electronic Chart System (ECS), and proposing a detection algorithm for vessel stay points based on the principle of spatiotemporal density to semantically label vessel trajectories; using the Fast Dynamic Time Warping (FastDTW) similarity measurement algorithm and the Ordering Points to Identify the Clustering Structure (OPTICS) clustering algorithm to cluster vessel trajectories to show the differences and similarities between vessel traffic flows; and showing the distribution of vessels and the variation trend of vessel density based on the vessel heatmap. Based on the AIS data of the Yangtze River Estuary, three cases are used to prove the usefulness and effectiveness of the system in vessel behaviour analysis.
JAK-STAT1 Signaling Pathway Is an Early Response to Helicobacter pylori Infection and Contributes to Immune Escape and Gastric Carcinogenesis
Authors: Li Xue , Pan Kaifeng , Vieth Michael , Gerhard Markus , Li Wenqing , Mejías-Luque Raquel
Published: April 2022

Helicobacter pylori infection induces a number of pro-inflammatory signaling pathways contributing to gastric inflammation and carcinogenesis and has been identified as a major risk factor for the development of gastric cancer (GC). Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling mediates immune regulatory processes, including tumor-driven immune escape. Programmed death ligand 1 (PD-L1) expressed on gastric epithelium can suppress the immune system by shutting down T cell effector function. In a human cohort of subjects with gastric lesions and GC analyzed by proteomics, STAT1 increased along the cascade of progression of precancerous gastric lesions to GC and was further associated with a poor prognosis of GC (Hazard Ratio (95% confidence interval): 2.34 (1.04–5.30)). We observed that STAT1 was activated in human H. pylori-positive gastritis, while in GC, STAT1, and its target gene, PD-L1, were significantly elevated. To confirm the dependency of H. pylori, we infected gastric epithelial cells in vitro and observed strong activation of STAT1 and upregulation of PD-L1, which depended on cytokines produced by immune cells. To investigate the correlation of immune infiltration with STAT1 activation and PD-L1 expression, we employed a mouse model of H. pylori-induced gastric lesions in an Rnf43-deficient background. Here, phosphorylated STAT1 and PD-L1 were correlated with immune infiltration and proliferation. STAT1 and PD-L1 were upregulated in gastric tumor tissues compared with normal tissues and were associated with immune infiltration and poor prognosis based on the TCGA-STAD database. H. pylori-induced activation of STAT1 and PD-L1 expression may prevent immune surveillance in the gastric mucosa, allowing premalignant lesions to progress to gastric cancer.