bluuebunny/crossref_metadata_2025 huggingface dataset:
Phosphoproteomics Analysis Reveals a Pivotal Mechanism Related to Amino Acid Signals in Goat Fetal Fibroblast
Authors: Zheng Xu , Su Huimin , Wang Liping , Yao Ruiyuan , Ma Yuze , Bai Linfeng , Wang Yanfeng , Guo Xudong , Wang Zhigang
Published: August 2021

In addition to serving as the building blocks for protein synthesis, amino acids serve as critical signaling molecules in cells. However, the mechanism through which amino acid signals are sensed in cells is not yet fully understood. This study examined differences in the phosphorylation levels of proteins in response to amino acid signals in Cashmere goat fetal fibroblasts (GFb). Amino acid deficiency was found to induce autophagy and attenuate mammalian/mechanistic target of rapamycin complex (mTORC1)/Unc-51-like autophagy activating kinase 1 (ULK1) signaling in GFb cells. A total of 144 phosphosites on 102 proteins positively associated with amino acid signaling were screened using phosphorylation-based proteomics analysis. The mitogen-activated protein kinase (MAPK) signaling pathway was found to play a potentially important role in the interaction network involved in the response to amino acid signals, according to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and MAPK1/3 may serve as a central hub for the entire network. Motif analysis identified three master motifs, xxx_S_Pxx, xxx_S_xxE, and xxx_S_xDx, which were centered on those phosphosites at which phosphorylation was positively regulated by amino acid signaling. Additionally, the phosphorylation levels of three membrane proteins, the zinc transporter SLC39A7, the sodium-dependent neutral amino acid transporters SLC1A5 and SLC38A7, and three translation initiation factors, eukaryotic initiation factor (eIF)5B, eIF4G, and eIF3C, were positively regulated by amino acid signals. These pivotal proteins were added to currently known signaling pathways to generate a novel model of the network pathways associated with amino acid signals. Finally, the phosphorylation levels of threonine 203 and tyrosine 205 on MAPK3 in response to amino acid signals were examined by western blot analysis, and the results were consistent with the data from the phosphoproteomics analysis. The findings of this study provide new evidence and insights into the precise mechanism through which amino acid signals are sensed and conducted in Cashmere goat fetal fibroblasts.
Vibrational Amplitude Frequency Characteristics Analysis of a Controlled Nonlinear Meso-Scale Beam
Authors: Ying Zu-Guang , Ni Yi-Qing
Published: August 2021

Vibration response and amplitude frequency characteristics of a controlled nonlinear meso-scale beam under periodic loading are studied. A method including a general analytical expression for harmonic balance solution to periodic vibration and an updated cycle iteration algorithm for amplitude frequency relation of periodic response is developed. A vibration equation with the general expression of nonlinear terms for periodic response is derived and a general analytical expression for harmonic balance solution is obtained. An updated cycle iteration procedure is proposed to obtain amplitude frequency relation. Periodic vibration response with various frequencies can be calculated uniformly using the method. The method can take into account the effect of higher harmonic components on vibration response, and it is applicable to various periodic vibration analyses including principal resonance, super-harmonic resonance, and multiple stationary responses. Numerical results demonstrate that the developed method has good convergence and accuracy. The response amplitude should be determined by the periodic solution with multiple harmonic terms instead of only the first harmonic term. The damping effect on response illustrates that vibration responses of the nonlinear meso beam can be reduced by feedback control with certain damping gain. The amplitude frequency characteristics including anti-resonance and resonant response variation have potential application to the vibration control design of nonlinear meso-scale structure systems.
Relationship between Maize Seed Productivity in Mexico between 1983 and 2018 with the Adoption of Genetically Modified Maize and the Resilience of Local Races
Authors: Santillán-Fernández Alberto , Salinas-Moreno Yolanda , Valdez-Lazalde José René , Carmona-Arellano Mauricio Antonio , Vera-López Javier Enrique , Pereira-Lorenzo Santiago
Published: August 2021

Mexico depends on maize imports to satisfy its national demand. The use of native maize varieties among subsistence farmers can help to reduce the cereal’s imports. However, the agricultural policy in Mexico to improve the productivity per hectare has centered on the use of improved varieties; among them, the transgenic variety. In this study, the maize productivity in Mexico from 1983 to 2018 was analyzed to determine the influence of agricultural policies in the sector, and the factors that condition the adoption of transgenic maize. It was found that the agricultural policy improved the productivity of those regions with irrigation; however, for rainfed regions, the expected technological changes were not achieved because the ancestral tradition in cultivation, associated with the greater variety of native maize and to a larger indigenous population, was stronger. The adoption of transgenic maize also had low significance in the rainfed regions, since the increase in field yields is not economically profitable with regards to the increase in production costs. Therefore, the agricultural policy to increase productivity ought to be directed at the protection of subsistence farmers, revaluing the use of native varieties that have shown higher resilience to technological and environmental changes.
Emergence of African Swine Fever in Poland (2014–2021). Successes and Failures in Disease Eradication
Authors: Woźniakowski Grzegorz , Pejsak Zygmunt , Jabłoński Artur
Published: August 2021

African swine fever (ASF) in Poland has been a major concern for pig production for the last seven years. The main constrains in ASF eradication in Poland are due to the high density of wild boar in ASF-affected areas of the country. Other factors, responsible for long-distance ASF spread to new regions of the country, are mainly related to human-mediated activity and lack of awareness of the potential disease threat to pig production. In the case of pig holdings, the only effective measure of ASF prevention is strict implementation of biosecurity rules. Despite many efforts to implement these measures, the disease occurred in a number of voivodeships, poviats and counties of Poland, primarily in eastern Poland; however, starting from 2019, also in the western part of the country. Further recommendations to eradicate ASF in Poland or at least to minimize the economic loss caused by ASF in pig production include effective wild boar population management strategies along with the implementation of strict biosecurity measures. The observations from the last seven years of ASF epizootic in Poland clearly indicate that the disease could not have been effectively controlled in wild boar population and could only be restricted in domestic pig population following severe biosecurity rules. As for ASF spread control in wild boar population, the measures applied in other EU countries include active wild boar carcass search and disposal along with sanitary and reduction hunting. These measures have also been shown non-effective. The only solution for future sustainable pig production in Poland seems to be strict collaboration between pig producers, veterinary inspection, and hunting associations.
Deep Learning-Based Growth Prediction System: A Use Case of China Agriculture
Authors: Khan Tamoor , Sherazi Hafiz Husnain Raza , Ali Mubashir , Letchmunan Sukumar , Butt Umair Muneer
Published: August 2021

Agricultural advancements have significantly impacted people’s lives and their surroundings in recent years. The insufficient knowledge of the whole agricultural production system and conventional ways of irrigation have limited agricultural yields in the past. The remote sensing innovations recently implemented in agriculture have dramatically revolutionized production efficiency by offering unparalleled opportunities for convenient, versatile, and quick collection of land images to collect critical details on the crop’s conditions. These innovations have enabled automated data collection, simulation, and interpretation based on crop analytics facilitated by deep learning techniques. This paper aims to reveal the transformative patterns of old Chinese agrarian development and fruit production by focusing on the major crop production (from 1980 to 2050) taking into account various forms of data from fruit production (e.g., apples, bananas, citrus fruits, pears, and grapes). In this study, we used production data for different fruits grown in China to predict the future production of these fruits. The study employs deep neural networks to project future fruit production based on the statistics issued by China’s National Bureau of Statistics on the total fruit growth output for this period. The proposed method exhibits encouraging results with an accuracy of 95.56% calculating by accuracy formula based on fruit production variation. Authors further provide recommendations on the AGR-DL (agricultural deep learning) method being helpful for developing countries. The results suggest that the agricultural development in China is acceptable but demands more improvement and government needs to prioritize expanding the fruit production by establishing new strategies for cultivators to boost their performance.
Nut Allergenicity: Effect of Food Processing
Authors: Cuadrado Carmen , Sanchiz África , Linacero Rosario
Published: August 2021

Nuts are considered healthy foods due to their high content of nutritional compounds with functional properties. However, the list of the most allergenic foods includes tree nuts, and their presence must be indicated on food labels. Most nut allergens are seed storage proteins, pathogenesis-related (PR) proteins, profilins and lipid transfer proteins (LTP). Nut allergenic proteins are characterized by their resistance to denaturation and proteolysis. Food processing has been proposed as the method of choice to alter the allergenicity of foods to ensure their safety and improve their organoleptic properties. The effect of processing on allergenicity is variable by abolishing existing epitopes or generating neoallergens. The alterations depend on the intrinsic characteristics of the protein and the type and duration of treatment. Many studies have evaluated the molecular changes induced by processes such as thermal, pressure or enzymatic treatments. As some processing treatments have been shown to decrease the allergenicity of certain foods, food processing may play an important role in developing hypoallergenic foods and using them for food tolerance induction. This work provides an updated overview of the applications and influence of several processing techniques (thermal, pressure and enzymatic digestion) on nut allergenicity for nuts, namely, hazelnuts, cashews, pistachios, almonds and walnuts.
Therapeutic Approach of Chronic Pseudomonas Infection in Cystic Fibrosis—A Network Meta-Analysis
Authors: Varannai Orsolya , Gede Noémi , Juhász Márk Félix , Szakács Zsolt , Dembrovszky Fanni , Németh Dávid , Hegyi Péter , Párniczky Andrea
Published: August 2021

Pseudomonas infection is a major determinant of morbidity and mortality in cystic fibrosis (CF). Maintaining optimal lung function in CF patients carrying Pseudomonas remains a challenge. Our study aims to investigate the efficacy of antipseudomonal inhaled antibiotics in CF patients with chronic Pseudomonas infection. A Bayesian network meta-analysis of randomized controlled trials was conducted. The main outcomes were changes in: (a) forced respiratory volume (FEV1), (b) Pseudomonas aeruginosa sputum density, and (c) CF Questionnaire Revised Respiratory Symptom Score (CFQR-RSS) at 4 weeks follow-up. Eighteen trials which reported on treatment with aztreonam lysine, tobramycin, colistin, levofloxacin, fosfomycin/tobramycin, and amikacin in various dosages were eligible for inclusion. In terms of change in FEV1%, aztreonam lysine (t.i.d., 75 mg) with a 28-day run in the tobramycin phase, aztreonam lysine (b.i.d., 75 mg) with a 28-day run in the tobramycin phase had the highest probability of being the most effective treatment (SUCRAs were 77, 76%, respectively). Regarding change in Pseudomonas sputum density, aztreonam lysine (b.i.d., 75 mg) with a 28-day run in the tobramycin phase, aztreonam lysine (t.i.d., 75 mg) with a 28-day run in the tobramycin phase had the highest probability of being the most effective treatment (SUCRAs were 90, 86%, respectively). Regarding change in CFQR-RSS, aztreonam lysine (t.i.d., 75 mg) and aztreonam lysine (b.i.d., 75 mg) with a 28-day run in the tobramycin inhalation solution phase had the highest probability of being the most effective treatments (SUCRA:74% and 72%, respectively). Regarding changes in FEV1% and Pseudomonas sputum density, aztreonam lysine with a run in tobramycin phase may be the best treatment option in treating chronic Pseudomonas in CF. According to CFQR-RSS no significant differences were found. Given the limitations of the studies included, validation trials are called for.
Entamoeba histolytica Adaption to Auranofin: A Phenotypic and Multi-Omics Characterization
Authors: Shaulov Yana , Sarid Lotem , Trebicz-Geffen Meirav , Ankri Serge
Published: August 2021

Auranofin (AF), an antirheumatic agent, targets mammalian thioredoxin reductase (TrxR), an important enzyme controlling redox homeostasis. AF is also highly effective against a diversity of pathogenic bacteria and protozoan parasites. Here, we report on the resistance of the parasite Entamoeba histolytica to 2 µM of AF that was acquired by gradual exposure of the parasite to an increasing amount of the drug. AF-adapted E. histolytica trophozoites (AFAT) have impaired growth and cytopathic activity, and are more sensitive to oxidative stress (OS), nitrosative stress (NS), and metronidazole (MNZ) than wild type (WT) trophozoites. Integrated transcriptomics and redoxomics analyses showed that many upregulated genes in AFAT, including genes encoding for dehydrogenase and cytoskeletal proteins, have their product oxidized in wild type trophozoites exposed to AF (acute AF trophozoites) but not in AFAT. We also showed that the level of reactive oxygen species (ROS) and oxidized proteins (OXs) in AFAT is lower than that in acute AF trophozoites. Overexpression of E. histolytica TrxR (EhTrxR) did not protect the parasite against AF, which suggests that EhTrxR is not central to the mechanism of adaptation to AF.
A Blood Biomarker for Duchenne Muscular Dystrophy Shows That Oxidation State of Albumin Correlates with Protein Oxidation and Damage in Mdx Muscle
Authors: Al-Mshhdani Basma A. , Grounds Miranda D. , Arthur Peter G. , Terrill Jessica R.
Published: August 2021

Duchenne muscular dystrophy (DMD) is a severe X-linked muscle wasting disease with no cure. While the precise mechanisms of progressive dystropathology remain unclear, oxidative stress caused by excessive generation of oxidants is strongly implicated. Blood biomarkers that could track oxidant levels in tissues would be valuable to measure the effectiveness of clinical treatments for DMD; our research has focused on developing such biomarkers. One target of oxidants that has the potential to be harnessed as a clinical biomarker is the thiol side chain of cysteine 34 (Cys34) of the blood protein albumin. This study using the mdx mouse model of DMD shows that in plasma, albumin Cys34 undergoes thiol oxidation and these changes correlate with levels of protein thiol oxidation and damage of the dystrophic muscles. A comparison with the commonly used biomarker protein carbonylation, confirmed that albumin thiol oxidation is the more sensitive plasma biomarker of oxidative stress occurring in muscle tissue. We show that plasma albumin oxidation reflects muscle dystropathology, as increased after exercise and decreased after taurine treatment of mdx mice. These data support the use of albumin thiol oxidation as a blood biomarker of dystropathology to assist with advancing clinical development of therapies for DMD.
Urine 5-Eicosatetraenoic Acids as Diagnostic Markers for Obstructive Sleep Apnea
Authors: Shin Hyun-Woo , Cho Kumsun , Rhee Chae-Seo , Hong Il-Hee , Cho Seok Hyun , Kim Sung Wan , Kim Jiyoung , So Daeho , Cho Joo-Youn , Park Jong-Wan
Published: August 2021

Early detection of obstructive sleep apnea (OSA) is needed to reduce cardiovascular sequelae and mortality. Full-night polysomnography has been used for diagnosing OSA, but it is too expensive and inconvenient for patients to handle. Metabolome-wide analyses were performed to find and validate surrogate markers for OSA. We further investigated the mechanism underlying hypoxic induction of the markers in human cells and mice. Arachidonic acid derivatives 5-HETE and 5-oxoETE were detected in urine samples. The levels (mean ± SD, ng per mg creatinine) of 5-HETE and 5-oxoETE were 56.4 ± 26.2 and 46.9 ± 18.4 in OSA patients, respectively, which were significantly higher than those in controls (22.5 ± 4.6 and 18.7 ± 3.6). Both levels correlated with the apnea-hypopnea index and the lowest oxygen saturation on polysomnography. After the treatment with the continuous positive airway pressure, the metabolite levels were significantly reduced compared with those before the treatment. In human mononuclear cells subjected to intermittent hypoxia, 5-HETE and 5-oxoETE productions were induced by hypoxia-inducible factor 1 and glutathione peroxidase. When mice were exposed to intermittent hypoxia, 5-HETE and 5-oxoETE were excreted more in urine. They were identified and verified as new OSA markers reflecting hypoxic stress. The OSA markers could be used for OSA diagnosis and therapeutic evaluation.
Assessment Methods of Usability and Cognitive Workload of Rehabilitative Exoskeletons: A Systematic Review
Authors: La Bara Laura Maria Alessandra , Meloni Luca , Giusino Davide , Pietrantoni Luca
Published: August 2021

Robotic exoskeleton technologies are applied in the medical field to help patients with impaired mobility to recover their motor functions. Relevant literature shows that usability and cognitive workload may influence the patients’ likelihood to benefit from the use of rehabilitative exoskeletons. Following the PRISMA method, the present study aimed to systematically review the assessment methods of usability and cognitive workload in the use of exoskeletal devices for motor rehabilitation. The literature search was conducted in the Scopus and Web of Science bibliographical databases, using 16 keywords that were combined into one search query. A final sample of 23 articles was included in the review, from which 18 distinct assessment methods were identified. Of them, 15 aimed to assess usability, whereas 3 aimed to assess cognitive workload in the use of rehabilitative exoskeletons. Some of the identified methods (e.g., SUS, QUEST, SWAT, and NASA-TLX) showed good psychometric properties and were therefore proven to be appropriate to assess usability and cognitive workload while performing exoskeleton-based rehabilitation. The current study may contribute to the development of guidelines and analytical tools for exoskeletons’ usability and exoskeleton-related patients’ cognitive workload in the domain of medical rehabilitation.
Predicting Success of Outbound Telemarketing in Insurance Policy Loans Using an Explainable Multiple-Filter Convolutional Neural Network
Authors: Gu Jinmo , Na Jinhyuk , Park Jeongeun , Kim Hayoung
Published: August 2021

Outbound telemarketing is an efficient direct marketing method wherein telemarketers solicit potential customers by phone to purchase or subscribe to products or services. However, those who are not interested in the information or offers provided by outbound telemarketing generally experience such interactions negatively because they perceive telemarketing as spam. In this study, therefore, we investigate the use of deep learning models to predict the success of outbound telemarketing for insurance policy loans. We propose an explainable multiple-filter convolutional neural network model called XmCNN that can alleviate overfitting and extract various high-level features using hundreds of input variables. To enable the practical application of the proposed method, we also examine ensemble models to further improve its performance. We experimentally demonstrate that the proposed XmCNN significantly outperformed conventional deep neural network models and machine learning models. Furthermore, a deep learning ensemble model constructed using the XmCNN architecture achieved the lowest false positive rate (4.92%) and the highest F1-score (87.47%). We identified important variables influencing insurance policy loan prediction through the proposed model, suggesting that these factors should be considered in practice. The proposed method may increase the efficiency of outbound telemarketing and reduce the spam problems caused by calling non-potential customers.
Robust Approach to Supervised Deep Neural Network Training for Real-Time Object Classification in Cluttered Indoor Environment
Authors: Endale Bedada , Tullu Abera , Shi Hayoung , Kang Beom-Soo
Published: August 2021

Unmanned aerial vehicles (UAVs) are being widely utilized for various missions: in both civilian and military sectors. Many of these missions demand UAVs to acquire artificial intelligence about the environments they are navigating in. This perception can be realized by training a computing machine to classify objects in the environment. One of the well known machine training approaches is supervised deep learning, which enables a machine to classify objects. However, supervised deep learning comes with huge sacrifice in terms of time and computational resources. Collecting big input data, pre-training processes, such as labeling training data, and the need for a high performance computer for training are some of the challenges that supervised deep learning poses. To address these setbacks, this study proposes mission specific input data augmentation techniques and the design of light-weight deep neural network architecture that is capable of real-time object classification. Semi-direct visual odometry (SVO) data of augmented images are used to train the network for object classification. Ten classes of 10,000 different images in each class were used as input data where 80% were for training the network and the remaining 20% were used for network validation. For the optimization of the designed deep neural network, a sequential gradient descent algorithm was implemented. This algorithm has the advantage of handling redundancy in the data more efficiently than other algorithms.
Experimental Evaluation of Deep Learning Methods for an Intelligent Pathological Voice Detection System Using the Saarbruecken Voice Database
Authors: Lee Ji-Yeoun
Published: August 2021

This work is focused on deep learning methods, such as feedforward neural network (FNN) and convolutional neural network (CNN), for pathological voice detection using mel-frequency cepstral coefficients (MFCCs), linear prediction cepstrum coefficients (LPCCs), and higher-order statistics (HOSs) parameters. In total, 518 voice data samples were obtained from the publicly available Saarbruecken voice database (SVD), comprising recordings of 259 healthy and 259 pathological women and men, respectively, and using /a/, /i/, and /u/ vowels at normal pitch. Significant differences were observed between the normal and the pathological voice signals for normalized skewness (p = 0.000) and kurtosis (p = 0.000), except for normalized kurtosis (p = 0.051) that was estimated in the /u/ samples in women. These parameters are useful and meaningful for classifying pathological voice signals. The highest accuracy, 82.69%, was achieved by the CNN classifier with the LPCCs parameter in the /u/ vowel in men. The second-best performance, 80.77%, was obtained with a combination of the FNN classifier, MFCCs, and HOSs for the /i/ vowel samples in women. There was merit in combining the acoustic measures with HOS parameters for better characterization in terms of accuracy. The combination of various parameters and deep learning methods was also useful for distinguishing normal from pathological voices.
Estimating the Probability Distribution of Construction Project Completion Times Based on Drum-Buffer-Rope Theory
Authors: Liu Xun , Shen Le , Zhang Kun
Published: August 2021

Various factors affecting the construction progress are regarded as bottlenecks giving rise to the project duration overrun. The contractor should combine the project schedule with the plan in order to reduce the uncertainty of the project activities. The present research describes the method derived from the theory of constraints (TOC) attempts to enhance the relationship among activities, to revise and further reduce the uncertainty of construction activities to improve the reliability of project progress. The elements of drum, buffer and rope (DBR) in TOC are added to PERT network schedule; through the identification of schedule in the bottleneck process, the implementation plan of the bottleneck is obtained. By measuring buffer time and calculating network schedule buffer time as well as feeding time, the relationship among activities and uncertainty of duration are also improved. To illustrate the impact of DBR applications on improving project schedule reliability, a case of hydropower station as an example is illustrated to show enhanced reliability of scheduling. As compared to program evaluation and review technique network (PERT) simulation, the simulation results showed that the uncertainty of construction progress could be reduced if the DBR are well cooperated mutually.
Optimization of Technological Parameters of Straw Fiber-Based Plant Fiber Seedling Pot Raw Materials
Authors: Zhang Ying , Zhu Qian-Jin , Gao Shuai , Liu Shuang , Li Long-Hai , Chen Hai-Tao
Published: August 2021

Straw fiber seedling pots are a promising substitute for plastic seedling pots. The mixing mode of straw fiber affects the mechanical properties of the raw material membrane of the seedling pot. To explore the processing technology of making the raw material membrane of the seedling pot with two kinds of plant fibers in a layered manner, the optimal combination of the process parameters of the raw material membrane of the seedling pot without additives in the production process was studied experimentally. Response surface methodology (RSM) was used to analyze the parameters (beating degree of unbleached softwood kraft pulp fiber, beating degree of wheat straw fiber, wheat straw fiber quality percentage content, and film grammage) with regard to the dry tensile index and Z-direction tensile index of the seedling pot body. The optimal process parameter combination with a certain dry tensile index and Z-direction tensile index of seedling pot raw material was obtained by using four factors and five levels of a quadratic regression orthogonal rotation center combination design parameter optimization experiment. The optimal technical parameters were optimized as wheat straw fiber quality percentage content 70%, film grammage 70 g/m2, unbleached softwood kraft pulp fiber beating degree 47–48 °SR, and wheat straw fiber beating degree 65–75 °SR. With the optimal conditions, the dry tensile index of the seedling bowl raw material film was between 21 and 22 N·(m·g−1), and the Z-direction tensile index was greater than 2.1 N·(m·g−1). Using wheat straw fibers and unbleached sulfite wood pulp fibers as raw materials for seedling pots, the raw material membrane of the seedling pots was made in a layered manner. The experimental study proved this feasibility. With this mixing process of raw materials, the straw fiber-based plant fiber seedling pot would meet the demands of a crop nursery after adding chemical additives. The research results provide a theoretical basis and technical support for the manufacture of the raw material membrane of the seedling pot body.
Vibration Damping Behavior of Composite Laminates Interleaved with PZT- and SMA-Particle-Dispersed Resin Mixture Films
Authors: Jung Jae-Min , Lee Da-Som , Kim Sung-Ha , Moon Sung-Nam , Lee Woo-Il , Kim Seung-Mo
Published: August 2021

In this study, functional particles such as piezoelectric (PZT) ceramic and shape memory alloy (SMA) particles have been incorporated in composite laminates to accelerate the loss of vibration energy. PZT ceramic particles and SMA particles are mixed with epoxy resin and rolled into a film shape before they are interleaved between prepreg plies for better distribution of the particles. Loss factor (tan δ) was measured with various particle loadings to verify the effectiveness of interleaving in the vibration damping of laminate specimens. It was observed that there existed an optimal content for maximizing the damping ability avoiding an aggregation of the particles. In addition, when PZT and SMA particles are applied simultaneously, PZT could enhance the vibration damping capability of SMA because PZT particles could generate thermal energy, and it would accelerate the phase change of the SMA particles. In this research, the effective way for enhancing the particle dispersion was suggested, and the particle loading could be controlled by finding an optimal content. Flexural moduli of the specimens were also measured, and they exhibited no change as the content of the particles increases. Therefore, dispersed particles used in this study increased the vibration damping capacity without reducing the mechanical properties.
Measuring Students Acceptance and Usability of a Cloud Virtual Desktop Solution for a Programming Course
Authors: Rodríguez Lera Francisco J. , Fernández González David , Martín Rico Francisco , Guerrero-Higueras Ángel Manuel , Conde Miguel Ángel
Published: August 2021

Virtual desktops in cloud scenarios play a significant role in higher education. Nowadays, the idea of moving laboratories to the cloud seems mandatory and it is necessary to maintain students’ commitment in this new scenario. This paper aims at two targets, customizing a Virtual Desktop platform for delivering the laboratories of a programming course in a Computer Science Bachelor Degree and empirically apply the technology acceptance model and the system usability scale to a set of students that use it. Results obtained in this paper provide insights about the direct effect between the perceived ease of use, perceived usefulness, and attitude to technology following the technology acceptance model (TAM) as well as a comprehensive analysis of the system usability scale (SUS) of our platform.
VivesDebate: A New Annotated Multilingual Corpus of Argumentation in a Debate Tournament
Authors: Ruiz-Dolz Ramon , Nofre Montserrat , Taulé Mariona , Heras Stella , García-Fornes Ana
Published: August 2021

The application of the latest Natural Language Processing breakthroughs in computational argumentation has shown promising results, which have raised the interest in this area of research. However, the available corpora with argumentative annotations are often limited to a very specific purpose or are not of adequate size to take advantage of state-of-the-art deep learning techniques (e.g., deep neural networks). In this paper, we present VivesDebate, a large, richly annotated and versatile professional debate corpus for computational argumentation research. The corpus has been created from 29 transcripts of a debate tournament in Catalan and has been machine-translated into Spanish and English. The annotation contains argumentative propositions, argumentative relations, debate interactions and professional evaluations of the arguments and argumentation. The presented corpus can be useful for research on a heterogeneous set of computational argumentation underlying tasks such as Argument Mining, Argument Analysis, Argument Evaluation or Argument Generation, among others. All this makes VivesDebate a valuable resource for computational argumentation research within the context of massive corpora aimed at Natural Language Processing tasks.
Petri Net-Based Semi-Compiled Code Generation for Programmable Logic Controllers
Authors: Azkarate Igor , Ayani Mikel , Mugarza Juan Carlos , Eciolaza Luka
Published: August 2021

Industrial discrete event dynamic systems (DEDSs) are commonly modeled by means of Petri nets (PNs). PNs have the capability to model behaviors such as concurrency, synchronization, and resource sharing, compared to a step transition function chart or GRAphe Fonctionnel de Commande Etape Transition (GRAFCET) which is a particular case of a PN. However, there is not an effective systematic way to implement a PN in a programmable logic controller (PLC), and so the implementation of such a controller outside a PLC in some external software that will communicate with the PLC is very common. There have been some attempts to implement PNs within a PLC, but they are dependent on how the logic of places and transitions is programmed for each application. This work proposes a novel application-independent and platform-independent PN implementation methodology. This methodology is a systematic way to implement a PN controller within industrial PLCs. A great portion of the code will be validated automatically prior to PLC implementation. Net structure and marking evolution will be checked on the basis of PN model structural analysis, and only net interpretation will be manually coded and error-prone. Thus, this methodology represents a systematic and semi-compiled PN implementation method. A use case supported by a digital twin (DT) is shown where the automated solution required by a manufacturing system is carried out and executed in two different devices for portability testing, and the scan cycle periods are compared for both approaches.
Fault Displacement Hazard Analysis Based on Probabilistic Seismic Hazard Analysis for Specific Nuclear Sites
Authors: Katona Tamás János , Tóth László , Győri Erzsébet
Published: August 2021

Permanent ground displacements/deformations caused by earthquakes can seriously challenge the safety of the nuclear power plants. The state-of-the-art hazard analysis methods provide a fault displacement hazard curve, i.e., the annual probability of given measure of displacement will be exceeded. The evaluation of ground displacement hazard requires great effort, empirical evidence, and sufficient data for the characterization of the fault activity and capability to cause permanent surface displacement. There are practical cases when the fault at the site area revealed to be active, and, despite this, there are no sufficient data for the evaluation of permanent ground displacements hazard and for judging on the safety significance of permanent ground displacement. For these cases, a methodology is proposed that is based on the seismotectonic modelling and results of the probabilistic seismic hazard analysis. The method provides conservative assessment of the annual probability of fault displacement that allows the decision whether permanent displacement hazard is relevant to nuclear power plant safety. The feasibility and applicability of the method is demonstrated for the Paks site, Hungary.
Target Maintenance in Gaming via Saliency Augmentation: An Early-Stage Scotoma Simulation Study Using Virtual Reality (VR)
Authors: Sipatchin Alexandra , García García Miguel , Wahl Siegfried
Published: August 2021

This study addresses the importance of salience placement before or after scotoma development for an efficient target allocation in the visual field. Pre-allocation of attention is a mechanism known to induce a better gaze positioning towards the target. Three different conditions were tested: a simulated central scotoma, a salience augmentation surrounding the scotoma and a baseline condition without any simulation. All conditions were investigated within a virtual reality VR gaming environment. Participants were tested in two different orders, either the salient cue was applied together with the scotoma before being presented with the scotoma alone or the scotoma in the wild was presented before and, then, with the augmentation around it. Both groups showed a change in gaze behaviour when saliency was applied. However, in the second group, salient augmentation also induced changes in gaze behaviour for the scotoma condition without augmentation, gazing above and outside the scotoma following previous literature. These preliminary results indicate salience placement before developing an advanced stage of scotoma can induce effective and rapid training for efficient target maintenance during VR gaming. The study shows the potential of salience and VR gaming as therapy for early AMD patients.
A Form-Finding Method for Branching Structures Based on Dynamic Relaxation
Authors: Tu Guigang , Chen Chen , Gong Zaijing , Wang Yueren
Published: August 2021

Branching structure is often used as a supporting structure of the grid shell due to its geometrical and force-transferring features, and the rationality of its shape is very important. The “physical” and “numerical” hanging models can be used for the joint form-finding of the branching structure and free-form grid shell. However, slack elements may exist in the equilibrium model which corresponds to the inefficient members in the form-found branching structure. To solve this problem, a form-finding method of branching structure based on dynamic relaxation is proposed in this study. The proposed method clusters the elements of the branching model and equalizes the axial forces of the elements in the same cluster, in other words, there are no slack elements in the equilibrium branching model. This method overcomes the defect that the equilibrium branching model may have slack elements and needs many manual adjustments during the procedure of determining the rational shape of a branching structure, and effectively prevents the inefficient members existing in the form-found structure. Numerical examples are provided to demonstrate the characteristics of the proposed method and its effectiveness is verified as well.
The Influence of Hard- and Software Improvement of Intraoral Scanners on the Implant Transfer Accuracy from 2012 to 2021: An In Vitro Study
Authors: Schmidt Alexander , Schlenz Maximiliane Amelie , Liu Haoyu , Kämpe Holger Sebastian , Wöstmann Bernd
Published: August 2021

This study aimed to investigate the transfer accuracy (trueness and precision) of three different intraoral scanning families using different hardware and software versions over the last decade from 2012 to 2021, compared to a conventional impression. Therefore, an implant master model with a reference cube was digitized and served as a reference dataset. Digital impressions of all three scanning families (True definition, TRIOS, CEREC) were recorded (n = 10 per group), and conventional implant impressions were taken (n = 10). The conventional models were digitized, and all models (conventional and digital) were measured. Therefore, it was possible to obtain the deviations between the master model and the scans or conventional models in terms of absolute three-dimensional (3D) deviations, deviations in rotation, and angulation. The results for deviations between the older and newer scanning systems were analyzed using pairwise comparisons (p < 0.05; SPSS 26). The absolute 3D deviations increased with increasing scan path length, particularly for the older hardware and software versions (old vs. new (MW ± SD) True Definition: 355 ± 62 µm vs. 483 ± 110 µm; TRIOS: 574 ± 274 µm vs. 258 ± 100 µm; and CEREC: 1356 ± 1023 µm vs. 110 ± 49 µm). This was also true for deviations in rotation and angulation. The conventional impression showed an advantage only regarding the absolute 3D deviation compared to the older systems. Based on the data of the present study, the accuracy of intraoral scanners is decisively related to hardware and software; though, newer systems or software do not necessarily warrant improvement. Nevertheless, to achieve high transfer accuracy, regular updating of digital systems is recommended. The challenge of increasing errors with increasing scan paths is overcome in the most recent systems. The combination of two different scanning principles in a single device seems to be beneficial.
Large-Eddy Simulation Study of Flow and Heat Transfer in Swirling and Non-Swirling Impinging Jets on a Semi-Cylinder Concave Target
Authors: Xu Liang , Zhao Xu , Xi Lei , Ma Yonghao , Gao Jianmin , Li Yunlong
Published: August 2021

Swirling impinging jet (SIJ) is considered as an effective means to achieve uniform cooling at high heat transfer rates, and the complex flow structure and its mechanism of enhancing heat transfer have attracted much attention in recent years. The large eddy simulation (LES) technique is employed to analyze the flow fields of swirling and non-swirling impinging jet emanating from a hole with four spiral and straight grooves, respectively, at a relatively high Reynolds number (Re) of 16,000 and a small jet spacing of H/D = 2 on a concave surface with uniform heat flux. Firstly, this work analyzes two different sub-grid stress models, and LES with the wall-adapting local eddy-viscosity model (WALEM) is established for accurately predicting flow and heat transfer performance of SIJ on a flat surface. The complex flow field structures, spectral characteristics, time-averaged flow characteristics and heat transfer on the target surface for the swirling and non-swirling impinging jets are compared in detail using the established method. The results show that small-scale recirculation vortices near the wall change the nearby flow into an unstable microwave state, resulting in small-scale fluctuation of the local Nusselt number (Nu) of the wall. There is a stable recirculation vortex at the stagnation point of the target surface, and the axial and radial fluctuating speeds are consistent with the fluctuating wall temperature. With the increase in the radial radius away from the stagnation point, the main frequency of the fluctuation of wall temperature coincides with the main frequency of the fluctuation of radial fluctuating velocity at x/D = 0.5. Compared with 0° straight hole, 45° spiral hole has a larger fluctuating speed because of speed deflection, resulting in a larger turbulence intensity and a stronger air transport capacity. The heat transfer intensity of the 45° spiral hole on the target surface is slightly improved within 5–10%.
Genome-Wide Analysis and Expression Profiling of the Phospholipase D Gene Family in Solanum tuberosum
Authors: Li Long , Zhang Chao , Zhang Mancang , Yang Chenghui , Bao Yanru , Wang Dongdong , Chen Qin , Chen Yue
Published: August 2021

Phospholipase D (PLD) is the most important phospholipid hydrolase in plants, which can hydrolyze phospholipids into phosphatidic acid (PA) and choline. When plants encounter low temperature, drought and high salt stress, phospholipase D and its products play an important role in regulating plant growth and development and coping with stress. In this study, 16 members of StPLD gene family were identified in potato genome, which were distributed in α, β, δ, and ζ subfamilies, and their expression patterns under salt, high temperature, drought, and ABA stress were detected by qRT-PCR method. Gene expression analysis showed that the expression of StPLD genes in potato was upregulated and downregulated to varying degrees under the four stresses, indicating that the PLD gene family is involved in the interaction of potato plant hormones and abiotic stress signals. Chromosome distribution showed that StPLD gene was unevenly distributed on 8 chromosomes, and only one pair of tandem repeat genes was found. All StPLD promoters contain hormone and stress-related cis-regulatory elements to respond to different stresses. Structural analysis showed that StPLD genes in the same subgroup had a similar exon–intron structure. Our study provides a valuable reference for further research of the function and structure of PLD gene.
Mechanism of Ca2+-Dependent Pro-Apoptotic Action of Selenium Nanoparticles, Mediated by Activation of Cx43 Hemichannels
Authors: Turovsky Egor A. , Varlamova Elena G.
Published: August 2021

To date, there are practically no data on the mechanisms of the selenium nanoparticles action on calcium homeostasis, intracellular signaling in cancer cells, and on the relationship of signaling pathways activated by an increase in Ca2+ in the cytosol with the induction of apoptosis, which is of great importance. The study of these mechanisms is important for understanding the cytotoxic effect of selenium nanoparticles and the role of this microelement in the regulation of carcinogenesis. The work is devoted to the study of the role of selenium nanoparticles obtained by laser ablation in the activation of the calcium signaling system and the induction of apoptosis in human glioblastoma cells (A-172 cell line). In this work, it was shown for the first time that the generation of Ca2+ signals in A-172 cells occurs in response to the application of various concentrations of selenium nanoparticles. The intracellular mechanism responsible for the generation of these Ca2+ signals has also been established. It was found that nanoparticles promote the mobilization of Ca2+ ions from the endoplasmic reticulum through the IP3-receptor. This leads to the activation of vesicular release of ATP through connexin hemichannels (Cx43) and paracrine cell activation through purinergic receptors (mainly P2Y). In addition, it was shown that the activation of this signaling pathway is accompanied by an increase in the expression of pro-apoptotic genes and the induction of apoptosis. For the first time, the role of Cx43 in the regulation of apoptosis caused by selenium nanoparticles in glioblastoma cells has been shown. It was found that inhibition of Cx43 leads to a significant suppression of the induction of apoptosis in these cells after 24 h treatment of cells with selenium nanoparticles at a concentration of 5 µg/mL.
The Role of Mesenchymal Stem Cells (MSCs) in Veterinary Medicine and Their Use in Musculoskeletal Disorders
Authors: Prządka Przemysław , Buczak Krzysztof , Frejlich Ewelina , Gąsior Ludwika , Suliga Kamil , Kiełbowicz Zdzisław
Published: August 2021

Regenerative medicine is a dynamically developing field of human and veterinary medicine. The animal model was most commonly used for mesenchymal stem cells (MSCs) treatment in experimental and preclinical studies with a satisfactory therapeutic effect. Year by year, the need for alternative treatments in veterinary medicine is increasing, and other applications for promising MSCs and their biological derivatives are constantly being sought. There is also an increase in demand for other methods of treating disease states, of which the classical treatment methods did not bring the desired results. Cell therapy can be a realistic option for treating human and animal diseases in the near future and therefore additional research is needed to optimize cell origins, numbers, or application methods in order to standardize the treatment process and assess its effects. The aim of the following work was to summarize available knowledge about stem cells in veterinary medicine and their possible application in the treatment of chosen musculoskeletal disorders in dogs and horses.