bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical Significance and Systematic Expression Analysis of the Thyroid Receptor Interacting Protein 13 (TRIP13) as Human Gliomas Biomarker
Authors: Chen Ssu-Han , Lin Hong-Han , Li Yao-Feng , Tsai Wen-Chiuan , Hueng Dueng-Yuan
Published: May 2021

The prognosis of malignant gliomas such as glioblastoma multiforme (GBM) has remained poor due to limited therapeutic strategies. Thus, it is pivotal to determine prognostic factors for gliomas. Thyroid Receptor Interacting Protein 13 (TRIP13) was found to be overexpressed in several solid tumors, but its role and clinical significance in gliomas is still unclear. Here, we conducted a comprehensive expression analysis of TRIP13 to determine the prognostic values. Gene expression profiles of the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and GSE16011 dataset showed increased TRIP13 expression in advanced stage and worse prognosis in IDH-wild type lower-grade glioma. We performed RT-PCR and Western blot to validate TRIP13 mRNA expression and protein levels in GBM cell lines. TRIP13 co-expressed genes via database screening were regulated by essential cancer-related upstream regulators (such as TP53 and FOXM1). Then, TCGA analysis revealed that more TRIP13 promoter hypomethylation was observed in GBM than in low-grade glioma. We also inferred that the upregulated TRIP13 levels in gliomas could be regulated by dysfunction of miR-29 in gliomas patient cohorts. Moreover, TRIP13-expressing tumors not only had higher aneuploidy but also tended to reduce the ratio of CD8+/Treg, which led to a worse survival outcome. Overall, these findings demonstrate that TRIP13 has with multiple functions in gliomas, and they may be crucial for therapeutic potential.
TrkA Interacts with and Phosphorylates STAT3 to Enhance Gene Transcription and Promote Breast Cancer Stem Cells in Triple-Negative and HER2-Enriched Breast Cancers
Authors: Regua Angelina T. , Aguayo Noah R. , Jalboush Sara Abu , Doheny Daniel L. , Manore Sara G. , Zhu Dongqin , Wong Grace L. , Arrigo Austin , Wagner Calvin J. , Yu Yang , Thomas Alexandra , Chan Michael D. , Ruiz Jimmy , Jin Guangxu , Strowd Roy , Sun Peiqing , Lin Jiayuh , Lo Hui-Wen
Published: May 2021

JAK2–STAT3 and TrkA signaling pathways have been separately implicated in aggressive breast cancers; however, whether they are co-activated or undergo functional interaction has not been thoroughly investigated. Herein we report, for the first time that STAT3 and TrkA are significantly co-overexpressed and co-activated in triple-negative breast cancer (TNBC) and HER2-enriched breast cancer, as shown by immunohistochemical staining and data mining. Through immunofluorescence staining–confocal microscopy and immunoprecipitation–Western blotting, we found that TrkA and STAT3 co-localize and physically interact in the cytoplasm, and the interaction is dependent on STAT3-Y705 phosphorylation. TrkA–STAT3 interaction leads to STAT3 phosphorylation at Y705 by TrkA in breast cancer cells and cell-free kinase assays, indicating that STAT3 is a novel substrate of TrkA. β-NGF-mediated TrkA activation induces TrkA–STAT3 interaction, STAT3 nuclear transport and transcriptional activity, and the expression of STAT3 target genes, SOX2 and MYC. The co-activation of both pathways promotes breast cancer stem cells. Finally, we found that TNBC and HER2-enriched breast cancer with JAK2–STAT3 and TrkA co-activation are positively associated with poor overall metastasis-free and organ-specific metastasis-free survival. Collectively, our study uncovered that TrkA is a novel activating kinase of STAT3, and their co-activation enhances gene transcription and promotes breast cancer stem cells in TNBC and HER2-enriched breast cancer.
Pharmacological or TRIB3-Mediated Suppression of ATF4 Transcriptional Activity Promotes Hepatoma Cell Resistance to Proteasome Inhibitor Bortezomib
Authors: Örd Tiit , Örd Daima , Kaikkonen Minna U. , Örd Tõnis
Published: May 2021

The proteasome is an appealing target for anticancer therapy and the proteasome inhibitor bortezomib has been approved for the treatment of several types of malignancies. However, the molecular mechanisms underlying cancer cell resistance to bortezomib remain poorly understood. In the current article, we investigate how modulation of the eIF2α–ATF4 stress pathway affects hepatoma cell response to bortezomib. Transcriptome profiling revealed that many ATF4 transcriptional target genes are among the most upregulated genes in bortezomib-treated HepG2 human hepatoma cells. While pharmacological enhancement of the eIF2α–ATF4 pathway activity results in the elevation of the activities of all branches of the unfolded protein response (UPR) and sensitizes cells to bortezomib toxicity, the suppression of ATF4 induction delays bortezomib-induced cell death. The pseudokinase TRIB3, an inhibitor of ATF4, is expressed at a high basal level in hepatoma cells and is strongly upregulated in response to bortezomib. To map genome-wide chromatin binding loci of TRIB3 protein, we fused a Flag tag to endogenous TRIB3 in HepG2 cells and performed ChIP-Seq. The results demonstrate that TRIB3 predominantly colocalizes with ATF4 on chromatin and binds to genomic regions containing the C/EBP–ATF motif. Bortezomib treatment leads to a robust enrichment of TRIB3 binding near genes induced by bortezomib and involved in the ER stress response and cell death. Disruption of TRIB3 increases C/EBP–ATF-driven transcription, augments ER stress and cell death upon exposure to bortezomib, while TRIB3 overexpression enhances cell survival. Thus, TRIB3, colocalizing with ATF4 and limiting its transcriptional activity, functions as a factor increasing resistance to bortezomib, while pharmacological over-activation of eIF2α–ATF4 can overcome the endogenous restraint mechanisms and sensitize cells to bortezomib.
Membrane Interference Against HIV-1 by Intrinsic Antiviral Factors: The Case of IFITMs
Authors: Marziali Federico , Cimarelli Andrea
Published: May 2021

HIV-1 is a complex retrovirus that is adapted to replicate in cells of the immune system. To do so, HIV-1, like other viruses, developed strategies to use several cellular processes to its advantage, but had also to come to terms with an arsenal of cellular innate defense proteins, or antiviral factors, that target more or less efficiently, virtually every step of the virus replicative cycle. Among antiviral restriction factors, the family of interferon-induced transmembrane proteins (IFITMs) has emerged as a crucial component of cellular innate defenses for their ability to interfere with both early and late phases of viral replication by inhibiting cellular and viral membranes fusion. Here, we review the enormous advances made since the discovery of IFITMs as interferon-regulated genes more than thirty years ago, with a particular focus on HIV-1 and on the elements that modulate its susceptibility or resistance towards members of this family. Given the recent advances of the field in the elucidation of the mechanism of IFITM inhibition and on the mechanism(s) of viral resistance, we expect that future years will bring novel insights into the definition of the multiple facets of IFITMs and on their possible use for novel therapeutical approaches.
Perinatal Inflammation: Could Partial Blocking of Cell Adhesion Molecule Function Be a Solution?
Authors: Vrachnis Nikolaos , Zygouris Dimitrios , Vrachnis Dionysios , Roussos Nikolaos , Loukas Nikolaos , Antonakopoulos Nikolaos , Paltoglou Georgios , Barbounaki Stavroula , Valsamakis Georgios , Iliodromiti Zoi
Published: May 2021

In spite of the great advances made in recent years in prenatal and perinatal medicine, inflammation can still frequently result in injury to vital organs and often constitutes a major cause of morbidity. It is today well established that in neonates—though vulnerability to infection among neonates is triggered by functional impairments in leukocyte adhesion—the decreased expression of cell adhesion molecules also decreases the inflammatory response. It is also clear that the cell adhesion molecules, namely, the integrins, selectins, and the immunoglobulin (Ig) gene super family, all play a crucial role in the inflammatory cascade. Thus, by consolidating our knowledge concerning the actions of these vital cell adhesion molecules during the prenatal period as well as regarding the genetic deficiencies of these molecules, notably leukocyte adhesion deficiency (LAD) I, II, and III, which can provoke severe clinical symptoms throughout the first year of life, it is anticipated that intervention involving blocking the function of cell adhesion molecules in neonatal leukocytes has the potential to constitute an effective therapeutic approach for inflammation. A promising perspective is the potential use of antibody therapy in preterm and term infants with perinatal inflammation and infection focusing on cases in which LAD is involved, while a further important scientific advance related to this issue could be the combination of small peptides aimed at the inhibition of cellular adhesion.
Newborn Screening and Treatment of Phenylketonuria: Projected Health Outcomes and Cost-Effectiveness
Authors: Chen Huey-Fen , Rose Angela M. , Waisbren Susan , Ahmad Ayesha , Prosser Lisa A.
Published: May 2021

The objective of this study was to evaluate the cost-effectiveness of newborn screening and treatment for phenylketonuria (PKU) in the context of new data on adherence to recommended diet treatment and a newly available drug treatment (sapropterin dihydrochloride). A computer simulation model was developed to project outcomes for a hypothetical cohort of newborns with PKU. Four strategies were compared: (1) clinical identification (CI) with diet treatment; (2) newborn screening (NBS) with diet treatment; (3) CI with diet and medication (sapropterin dihydrochloride); and (4) NBS with diet and medication. Data sources included published literature, primary data, and expert opinion. From a societal perspective, newborn screening with diet treatment had an incremental cost-effectiveness ratio of $6400/QALY compared to clinical identification with diet treatment. Adding medication to NBS with diet treatment resulted in an incremental cost-effectiveness ratio of more than $16,000,000/QALY. Uncertainty analyses did not substantially alter the cost-effectiveness results. Newborn screening for PKU with diet treatment yields a cost-effectiveness ratio lower than many other recommended childhood prevention programs even if adherence is lower than previously assumed. Adding medication yields cost-effectiveness results unlikely to be considered favorable. Future research should consider conditions under which sapropterin dihydrochloride would be more economically attractive.
The Role of Trust in the Care of Young Children with Type 1 Diabetes
Authors: DeCosta Patricia , Skinner Timothy Charles , Grabowski Dan
Published: May 2021

Using the theoretical framework of Guido Möllering conceptualising trust as a mental process composed of three elements—expectation, interpretation and suspension—we examined the role of trust in relation to young children’s (age ≤ 7 years) psychosocial needs when diagnosed with type 1 diabetes. Based on qualitative interviews with health care professionals (HPCs) from paediatric diabetes clinics in all regions of Denmark, we identified four main themes: trust through meaningful interaction, trust as a key factor at the time of diagnosis, trust in a long-term perspective and caregivers as the bridge to trust. We conclude that trust between young children and HCPs is central to children’s psychosocial experience, as well as a primary need, when children are diagnosed with type 1 diabetes. Trusting relationships counteract children’s experience of fear, anxiety and needle phobia and reinforce HCPs’ experience of providing good psychosocial as well as medical care. The present study offers insights into how trust can positively affect young children’s experience of diagnosis. This study also points out some key barriers to and facilitators of creating trusting relationships. This research is a first step towards a greater understanding that can inform collective future guidelines on the psychosocial care of young children.
Global Surface Temperature: A New Insight
Authors: Valipour Mohammad , Bateni Sayed M. , Jun Changhyun
Published: May 2021

This paper belongs to our Special Issue “Application of Climate Data in Hydrologic Models” [...]
Secondary Serpentine Forests of Poland as a Refuge for Vascular Flora
Authors: Bubel Karol , Reczyńska Kamila , Pech Paweł , Świerkosz Krzysztof
Published: May 2021

The aim of present study was to determine the role of secondary, serpentine forests in Poland in the protection of rare vascular plant species. On the basis of 95 phytosociological relevés collected between 2009 and 2020, we identified the main types of serpentine forest communities and assessed their diversity indices. Ordination methods were used to determine the relationship between the degree of transformation of forest communities (reflected by the occurrence of alien and nitrophilic species) and the presence of endangered species in their undergrowth including the environmental background. We distinguished four types of communities: thermophilic and mesophilic pine plantations (both secondary in origin) as well as thermophilous oak forest and acidophilous oak–hornbeam forest (semi-natural and close to natural in character, respectively). Rare and endangered species were unevenly distributed and concentrated in oak forest (16 species) and thermophilic pine plantation (nine species). The endangered species mainly preferred sites at higher altitudes and with higher slope inclination, light availability, and soil reaction. We did not confirm that the presence of alien or nitrophilic species negatively influenced the ability of studied forests to preserve rare plants. As secondary forests can still harbor endangered species, they should fulfil complementary functions in the nature protection system.
Sentiment Analysis of Persian Movie Reviews Using Deep Learning
Authors: Dashtipour Kia , Gogate Mandar , Adeel Ahsan , Larijani Hadi , Hussain Amir
Published: May 2021

Sentiment analysis aims to automatically classify the subject’s sentiment (e.g., positive, negative, or neutral) towards a particular aspect such as a topic, product, movie, news, etc. Deep learning has recently emerged as a powerful machine learning technique to tackle the growing demand for accurate sentiment analysis. However, the majority of research efforts are devoted to English-language only, while information of great importance is also available in other languages. This paper presents a novel, context-aware, deep-learning-driven, Persian sentiment analysis approach. Specifically, the proposed deep-learning-driven automated feature-engineering approach classifies Persian movie reviews as having positive or negative sentiments. Two deep learning algorithms, convolutional neural networks (CNN) and long-short-term memory (LSTM), are applied and compared with our previously proposed manual-feature-engineering-driven, SVM-based approach. Simulation results demonstrate that LSTM obtained a better performance as compared to multilayer perceptron (MLP), autoencoder, support vector machine (SVM), logistic regression and CNN algorithms.
Low-Toxicity Perovskite Applications in Carbon Electrode Perovskite Solar Cells—A Review
Authors: Bidikoudi Maria , Simal Carmen , Stathatos Elias
Published: May 2021

Perovskite solar cells (PSCs) with earth-abundant carbon as an effective replacer for unstable hole-transporting materials and expensive electrodes is a recently proposed structure promising better air and moisture stability. In this review paper, we report on the latest advances and state of the art of Pb-free and low-Pb-content perovskites, used as absorbers in carbon-based perovskite solar cells. The focus is on the implementation of these, environmentally friendly and non-toxic, structures in PSCs with a carbon electrode as a replacement of the noble metal electrode typically used (C-PSCs). The motivation for this study has been the great potential that C-PSCs have shown for the leap towards the commercialization of PSCs. Some of their outstanding properties include low cost, high-stability, ambient processability and compatibility with most up-scaling methods (e.g., printing). By surpassing the key obstacle of toxicity, caused by the Pb content of the highest-performing perovskites, and by combining the advantages of C-PSCs with the Pb-free perovskites low toxicity, this technology will move one step further; this review summarizes the most promising routes that have been reported so far towards that direction.
A High-Reliability Redundancy Scheme for Design of Radiation-Tolerant Half-Duty Limited DC-DC Converters
Authors: Banteywalu Solomon Mamo , Bekele Getachew , Khan Baseem , De Smedt Valentijn , Leroux Paul
Published: May 2021

Redundancy techniques are commonly used to design radiation- and fault-tolerant circuits for space applications, to ensure high reliability. However, higher reliability often comes at a cost of increased usage of hardware resources. Triple Modular Redundancy (TMR) ensures full single fault masking, with a >200% power and area overhead cost. TMR/Simplex ensures full single fault masking with a slightly more complicated circuitry, inefficient use of resource and a >200% power and area overhead cost, but with higher reliability than that of TMR. In this work, a high-reliability Spatial and Time Redundancy (TR) hybrid technique, which does not abandon a working module and is applicable for radiation hardening of half-duty limited DC-DC converters, is proposed and applied to the design of a radiation-tolerant digital controller for a Dual-Switch Forward Converter. The technique has the potential of double fault masking with a <2% increase in resource overhead cost compared to TMR. Moreover, for a Simplex module failure rate, λ, of 5%, the Reliability Improvement Factor (RIF) over the Simplex system is 20.8 and 500 for the proposed technique’s two- and three-module implementations, respectively, compared to a RIF over the Simplex system of only 7.25 for TMR and 14.3 for the regular TMR/Simplex scheme.
PF-TL: Payload Feature-Based Transfer Learning for Dealing with the Lack of Training Data
Authors: Jung Ilok , Lim Jongin , Kim Huy Kang
Published: May 2021

The number of studies on applying machine learning to cyber security has increased over the past few years. These studies, however, are facing difficulties with making themselves usable in the real world, mainly due to the lack of training data and reusability of a created model. While transfer learning seems like a solution to these problems, the number of studies in the field of intrusion detection is still insufficient. Therefore, this study proposes payload feature-based transfer learning as a solution to the lack of training data when applying machine learning to intrusion detection by using the knowledge from an already known domain. Firstly, it expands the extracting range of information from header to payload to accurately deliver the information by using an effective hybrid feature extraction method. Secondly, this study provides an improved optimization method for the extracted features to create a labeled dataset for a target domain. This proposal was validated on publicly available datasets, using three distinctive scenarios, and the results confirmed its usability in practice by increasing the accuracy of the training data created from the transfer learning by 30%, compared to that of the non-transfer learning method. In addition, we showed that this approach can help in identifying previously unknown attacks and reusing models from different domains.
Implementation of QR Code Recognition Technology Using Smartphone Camera for Indoor Positioning
Authors: Kim Ji-In , Gang Hui-Seon , Pyun Jae-Young , Kwon Goo-Rak
Published: May 2021

Numerous studies on positioning technology are ongoing for recognizing the positions of objects accurately. Vision-, sensor-, and signal-based technologies are combined for recognizing the positions of objects outdoors and indoors. While positioning technologies involving wireless communication based on sensors and signals are commonly used in outdoor environments, the performance becomes degraded in indoor environments. Therefore, a vision-based indoor positioning method using a QR code is proposed in this study. A user’s position is measured by determining the current position of a smartphone device accurately based on the QR code recognized with a smartphone camera. The direction, distance, and position are acquired using the relationship between the three-dimensional spatial coordinate information of the camera and the center point coordinates of a two-dimensional planar QR code obtained through camera calibration.
Stator Non-Uniform Radial Ventilation Design Methodology for a 15 MW Turbo-Synchronous Generator Based on Single Ventilation Duct Subsystem
Authors: Li Ruiye , Cheng Peng , Lan Hai , Li Weili , Gerada David , Hong Yingyi
Published: May 2021

Within large turboalternators, the excessive local temperatures and spatially distributed temperature differences can accelerate the deterioration of electrical insulation as well as lead to deformation of components, which may cause major machine malfunctions. In order to homogenise the stator axial temperature distribution whilst reducing the maximum stator temperature, this paper presents a novel non-uniform radial ventilation ducts design methodology. To reduce the huge computational costs resulting from the large-scale model, the stator is decomposed into several single ventilation duct subsystems (SVDSs) along the axial direction, with each SVDS connected in series with the medium of the air gap flow rate. The calculation of electromagnetic and thermal performances within SVDS are completed by finite element method (FEM) and computational fluid dynamics (CFD), respectively. To improve the optimization efficiency, the radial basis function neural network (RBFNN) model is employed to approximate the finite element analysis, while the novel isometric sampling method (ISM) is designed to trade off the cost and accuracy of the process. It is found that the proposed methodology can provide optimal design schemes of SVDS with uniform axial temperature distribution, and the needed computation cost is markedly reduced. Finally, results based on a 15 MW turboalternator show that the peak temperature can be reduced by 7.3 °C (6.4%). The proposed methodology can be applied for the design and optimisation of electromagnetic-thermal coupling of other electrical machines with long axial dimensions.
Stakeholders’ Recount on the Dynamics of Indonesia’s Renewable Energy Sector
Authors: Yudha Satya Widya , Tjahjono Benny , Longhurst Philip
Published: May 2021

The study described in this paper uses direct evidence from processes applied for the developing economy of Indonesia, as it defines the trajectory for its future energy policy and energy research agenda. The paper addresses the research gap to make explicit the process undertaken by key stakeholders in assessing and determining the suitability, feasibility, and dynamics of the renewable energy sector. Barriers and enablers that are key in selecting the most suitable renewable energy sources for developing economies for the renewable energy development have been identified from extensive analyses of research documents alongside qualitative data from the Focus Group Discussions (FGD). The selected FGD participants encompass the collective views that cut across the political, economic, social, technological, legal, and environmental aspects of renewable energy development in Indonesia. The information gained from the FGD gives insights into the outlook and challenges that are central to energy transition within the country, alongside the perceptions of renewable energy development from the influential stakeholders contributing to the process. It is notable that the biggest barriers to transition are centred on planning and implementation aspects, as it is also evident that many in the community do not adhere to the same vision.
Renewable Energy Attitudes and Behaviour of Local Governments in Poland
Authors: Rakowska Joanna , Ozimek Irena
Published: May 2021

The deployment of renewable energy at the local level can contribute significantly to mitigating climate change, improving energy security and increasing social, economic and environmental benefits. In many countries local authorities play an important role in the local development, but renewable energy deployment is not an obligatory task for them. Hence there are two research questions: (1) Do local governments think investments in renewable energy (RE) are urgent and affordable within the local budgets? (2) How do they react to the public aid co-financing investments in renewable energy? To provide the answer we performed qualitative analysis and non-parametric tests of data from a survey of 252 local authorities, analysis of 292 strategies of local development and datasets of 1170 renewable energy projects co-financed by EU funds under operational programs 2007–2013 and 2014–2020 in Poland. Findings showed that local authorities’ attitudes were rather careful, caused by financial constraints of local budgets and the scope of obligatory tasks, which made renewable energy investments not the most urgent. Public aid was a factor significantly affecting local authorities’ behavior. It triggered local authorities’ renewable energy initiatives, increasing the number and scope of renewable energy investments as well cooperation with other municipalities and local communities. Despite this general trend, there were also considerable regional differences in local authorities’ renewable energy behavior.
Improving the Irradiance Data Measured by Silicon-Based Sensors
Authors: Mubarak Riyad , Schilke Holger , Seckmeyer Gunther
Published: May 2021

Silicon-based sensors are widely used for monitoring solar irradiance, in particular, in the field of Photovoltaic (PV) applications. We present a method to correct the global horizontal irradiance measured by silicon-based sensors that reduces the difference to the standard thermopile sensor measurements. A major motivation to use silicon-based sensors for the measurements of irradiance is their lower cost. In addition, their response time is much lower, and their spectral response is much closer to that of the PV systems. The analysis of the differences is based on evaluating four parameters that influence the sensor measurements, namely the temperature, cosine error, spectral mismatch, and calibration factor. Based on the analysis, a correction model is applied to the silicon sensors measurements. The model separates measurements under a clear sky and cloudy sky by combining the clearness index and the solar zenith angle. By applying the correction model on the measurements of the silicon-based sensor, the differences between sensor readings have been reduced significantly. The relative root mean squared difference (rRMSD) between the daily solar irradiation measured by both sensors decreased from 10.6% to 5.4% after applying the correction model, while relative mean absolute difference (rMAD) decreased from 7.4% to 2.5%. The difference in total annual irradiation decreased from 70 KWh/m2 (6.5%) to 15 kWh/m2 (1.5%) by the correction. The presented correction method shows promising results for a further improvement in the accuracy of silicon-based sensors.
Lighting System Modernization as a Source of Green Energy
Authors: Kotulski Leszek , Basiura Artur , Wojnicki Igor , Siuchta Sebastian
Published: May 2021

The use of formal methods and artificial intelligence has made it possible to automatically design outdoor lighting. Quick design for large cities, in a matter of hours instead of weeks, and analysis of various optimization criteria enables to save energy and tune profit stream from lighting retrofit. Since outdoor lighting is of a large scale, having luminaires on every street in urban areas, and since it needs to be retrofitted every 10 to 15 years, choosing proper parameters and light sources leads to significant energy savings. This paper presents the concept and calculations of Levelized Cost of Electricity for outdoor lighting retrofit. It is understood as cost of energy savings, it is in the range from 23.06 to 54.64 EUR/MWh, based on real-world cases. This makes street and road lighting modernization process the best green “energy source” if compared with the 2018 Fraunhofer Institute cost of electricity renewable energy technologies ranking. This indicates that investment in lighting retrofit is more economically and ecologically viable than investment in new renewable energy sources.
Implementation of Variable Blade Inertia in OpenFAST to Integrate a Flywheel System in the Rotor of a Wind Turbine
Authors: Alhrshy Laurence
Published: May 2021

In this paper, the integration of the dynamic behavior of the flywheel system into the load simulation tool OpenFAST is presented. The flywheel system enables a wind turbine to vary the inertia of its rotor blades to control the power production and, most importantly, to affect the vibratory behavior of wind turbine components. Consequently, in order to simulate the behavior of a wind turbine with a flywheel system in its rotor, the variable blade characteristics need to be considered in the load simulation tool. Currently, computer-aided engineering tools for simulating the mechanical loads of wind turbines are not designed to simulate variable blade inertia. Hence, the goal of this paper is to explain how variable inertias of rotor blades are implanted in such load simulation tools as OpenFAST. OpenFAST is used because of it is free, publicly available, and well documentation. Moreover, OpenFAST is open source, which allows modifications in its source code. This add-on in the load simulation is applied to correct rotor mass imbalance. It can also be applied in many cases related to the change in the inertia of wind turbine rotor blades during its operation as, for example, atmospheric ice accretion on the blades, smart blades, etc.
Towards Practical Applications in Modeling Blockchain System
Authors: Vladyko Andrei , Spirkina Anastasia , Elagin Vasiliy
Published: May 2021

Like multiservice networks, blockchain technology is currently experiencing significant development because of its decentralization and ability to organize secure, seamless, reliable data exchange and storage. Due to the significant demand for the technology, there is a need to analyze the impact of these technology processes on network characteristics to predict traffic behavior and ensure required quality indicators, as well as on the stability of public communication network elements when blockchain technology operates. Conducting a full-scale experiment is a time-consuming task that cannot always be accomplished, so in this paper, the authors propose considering approaches to modeling these systems and, as an example, propose to use a simulation system to assess the performance of the network and its elements.
Reducing Videoconferencing Fatigue through Facial Emotion Recognition
Authors: Rößler Jannik , Sun Jiachen , Gloor Peter
Published: May 2021

In the last 14 months, COVID-19 made face-to-face meetings impossible and this has led to rapid growth in videoconferencing. As highly social creatures, humans strive for direct interpersonal interaction, which means that in most of these video meetings the webcam is switched on and people are “looking each other in the eyes”. However, it is far from clear what the psychological consequences of this shift to virtual face-to-face communication are and if there are methods to alleviate “videoconferencing fatigue”. We have studied the influence of emotions of meeting participants on the perceived outcome of video meetings. Our experimental setting consisted of 35 participants collaborating in eight teams over Zoom in a one semester course on Collaborative Innovation Networks in bi-weekly video meetings, where each team presented its progress. Emotion was tracked through Zoom face video snapshots using facial emotion recognition that recognized six emotions (happy, sad, fear, anger, neutral, and surprise). Our dependent variable was a score given after each presentation by all participants except the presenter. We found that the happier the speaker is, the happier and less neutral the audience is. More importantly, we found that the presentations that triggered wide swings in “fear” and “joy” among the participants are correlated with a higher rating. Our findings provide valuable input for online video presenters on how to conduct better and less tiring meetings; this will lead to a decrease in “videoconferencing fatigue”.
User Acceptance of Smart Watch for Medical Purposes: An Empirical Study
Authors: Al-Maroof Rana Saeed , Alhumaid Khadija , Alhamad Ahmad Qasim , Aburayya Ahmad , Salloum Said
Published: May 2021

This study aims to investigate the most effective and interesting variables that urge use of the smartwatch (SW) in a medical environment. To achieve this aim, the study was framed using an innovative and integrated research model, which is based on combining constructs from a well-established theoretical model’s TAM and other features that are critical to the effectiveness of SW which are content richness and personal innovativeness. The Technology Acceptance Model (TAM) is used to detect the determinants affecting the adoption of SW. The current study depends on an online questionnaire that is composed of (20) items. The questionnaire is distributed among a group of doctors, nurses, and administration staff in medical centers within the UAE. The total number of respondents is (325). The collected data were implemented to test the study model and the proposed constructs and hypotheses depending on the Smart PLS Software. The results of the current study show that the main constructs in the model contribute differently to the acceptance of SW. Based on the previous assumption, content richness and innovativeness are critical factors that enrich the user’s perceived usefulness. In addition, perceived ease of use was significantly predictive of either perceived usefulness or behavioral intention. Overall findings suggest that SW is in high demand in the medical field and is used as a common channel among doctors and their patients and it facilitates the role of transmitting information among its users. The outcomes of the current study indicate the importance of certain external factors for the acceptance of the technology. The genuine value of this study lies in the fact that it is based on a conceptual framework that emphasizes the close relationship between the TAM constructs of perceived usefulness and perceived ease of use to the construct of content richness, and innovativeness. Finally, this study helps us recognize the embedded motives for using SW in a medical environment, where the main motive is to enhance and facilitate the effective roles of doctors and patients.
Use of Essential Oils and Volatile Compounds as Biological Control Agents
Authors: De Clerck Caroline , Genva Manon , Jijakli M. Haissam , Fauconnier Marie-Laure
Published: May 2021

Plants containing essential oils have been used for centuries as spices, remedies or for their pleasant odor [...]
WPI Gel Microstructure and Mechanical Behaviour and Their Influence on the Rate of In Vitro Digestion
Authors: Homer Stephen , Williams Roderick , Williams Allison , Logan Amy
Published: May 2021

The influence of microstructure and mechanical properties on the in vitro digestibility of 15% whey protein isolate (WPI) gels was investigated. Gels were prepared via heat set gelation at three pH values (pH 3, 5 and 7), which produced gels with distinct microstructures and mechanical properties. The gels were minced to simulate an oral/chewing phase, which led to the formation particles of various sizes and textures. The minced gels were passed through either an Infogest (pre-set pH of 3) or Glass stomach (dynamic pH) protocol. Gels were digested in the gastric phase for up to 120 min, at which point the extent of digestion was measured by the amount of filterable nitrogen passing through a sieve. The digesta from both gastric methods were passed through an in vitro simulated intestinal phase. A strong link was found between the elasticity of the initial gel and the gel particle size following simulated oral processing, which significantly (p < 0.01) affected the rate of digestion in the gastric phase. A weaker correlation was also found between the pH of the gels and the extent of gastric digestion. This work highlights the differences in the rate of gastric digestion, arising from oral processing, which can be attributed to the material properties of the substrate.
Dairy By-Products: A Review on the Valorization of Whey and Second Cheese Whey
Authors: Pires Arona Figueroa , Marnotes Natalí Garcia , Rubio Olga Díaz , Garcia Angel Cobos , Pereira Carlos Dias
Published: May 2021

The search for new food products that promote consumers health has always been of great interest. The dairy industry is perhaps the best example regarding the emergence of new products with claimed health benefits. Cheese whey (CW), the by-product resulting from cheese production, and second cheese whey (SCW), which is the by-product of whey cheese manufacture, have proven to contain potential ingredients for the development of food products with improved nutritional characteristics and other functionalities. Nowadays, due to their nutritional quality, whey products have gained a prominent position among healthy food products. However, for a long time, CW and SCW were usually treated as waste or as animal feed. Due to their high organic content, these by-products can cause serious environmental problems if discarded without appropriate treatment. Small and medium size dairy companies do not have the equipment and structure to process whey and second cheese whey. In these cases, generally, they are used for animal feed or discarded without an appropriate treatment, being the cause of several constraints. There are several studies regarding CW valorization and there is a wide range of whey products in the market. However, in the case of SCW, there remains a lack of studies regarding its nutritional and functional properties, as well as ways to reuse this by-product in order to create economic value and reduce environmental impacts associated to its disposal.
Fabrication of Caseinate Stabilized Thymol Nanosuspensions via the pH-Driven Method: Enhancement in Water Solubility of Thymol
Authors: Zhou Wei , Zhang Yun , Li Ruyi , Peng Shengfeng , Ruan Roger , Li Jihua , Liu Wei
Published: May 2021

Thymol has been applied as a spice and antibacterial agent in commercial products. However, the utilization of thymol in the food and pharmaceutical field has recently been limited by its poor water solubility and stability. In this work, a caseinate-stabilized thymol nanosuspension was fabricated by pH-driven methods to overcome those limitations. Firstly, the chemical stability of thymol at different pH value conditions was investigated. The physiochemical properties of thymol nanosuspensions were then characterized, such as average particle size, zeta potential, encapsulation efficiency, and loading capacity. Meanwhile, the X-ray diffraction results showed that thymol was present as an amorphous state in the nanosuspensions. The thermal stability of thymol was slightly enhanced by encapsulation through this process, and the thymol nanosuspensions were stable during the long-term storage, and the average particle size of nanosuspensions showed that there was no aggregation of nanosuspensions during storage and high temperature. Finally, the antimicrobial activity of thymol nanosuspensions was evaluated by investigating the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) against Salmomella enterca, Staphlococcus aureus, Escherichia coli, and Listeria monocytogenes. These results could provide useful information and implications for promoting the application of thymol in food, cosmetic, and pharmaceutical commercial products.
Making Sense of Genetic Information: The Promising Evolution of Clinical Stratification and Precision Oncology Using Machine Learning
Authors: Baptiste Mahaly , Moinuddeen Sarah Shireen , Soliz Courtney Lace , Ehsan Hashimul , Kaneko Gen
Published: May 2021

Precision medicine is a medical approach to administer patients with a tailored dose of treatment by taking into consideration a person’s variability in genes, environment, and lifestyles. The accumulation of omics big sequence data led to the development of various genetic databases on which clinical stratification of high-risk populations may be conducted. In addition, because cancers are generally caused by tumor-specific mutations, large-scale systematic identification of single nucleotide polymorphisms (SNPs) in various tumors has propelled significant progress of tailored treatments of tumors (i.e., precision oncology). Machine learning (ML), a subfield of artificial intelligence in which computers learn through experience, has a great potential to be used in precision oncology chiefly to help physicians make diagnostic decisions based on tumor images. A promising venue of ML in precision oncology is the integration of all available data from images to multi-omics big data for the holistic care of patients and high-risk healthy subjects. In this review, we provide a focused overview of precision oncology and ML with attention to breast cancer and glioma as well as the Bayesian networks that have the flexibility and the ability to work with incomplete information. We also introduce some state-of-the-art attempts to use and incorporate ML and genetic information in precision oncology.
Terraces of the Ohře River in Žatec Area, Czech Republic: When Models of Holocene Fluvial Development Are Not Sufficient
Authors: Grygar Tomáš Matys , Elznicová Jitka , Sipos György , Kiss Tímea
Published: May 2021

The development of the Ohře River near Žatec between the Late Glacial Maximum (LGM) and present time was studied to obtain its natural trajectory and thus to understand the role of human impact on floodplain development. The study was based on geomorphic research, sampling and dating fluvial sediments by optically stimulated luminescence (OSL) and anthropogenic contamination by Sn since 16th century. During the LGM and the Pleistocene/Holocene transition (P/H), the river valley was shaped by large, incising meanders creating the entire valley floor. The Holocene river, due to decreased channel forming discharges, only slowly continued the LGM and P/H trajectory by cut-offs of the large palaeomeander necks and channel belt narrowing and incision. The last Holocene incision step was likely triggered by hydrological extremes of the Little Ice Age. The LGM and P/H Ohře River consequently changed from meandering to low sinuous, incised in the valley floor; this incision was completed by river engineering in the 20th century. The Ohře River development can thus be rationalised neither by traditional terrace-step formation model nor by model of the Anthropogenic aggradation.
Effects of Self RehAbilitation Video Exercises (SAVE) on Functional Restorations in Patients with Subacute Stroke
Authors: Jung Seung-Hwan , Park Eunhee , Kim Ju-Hyun , Park Bi-Ang , Yu Ja-Won , Kim Ae-Ryoung , Jung Tae-Du
Published: May 2021

Background: Additional exercise therapy has been shown to positively affect acute stroke rehabilitation, which requires an effective method to deliver increased exercise. In this study, we designed a 4-week caregiver-supervised self-exercise program with videos, named “Self rehAbilitation Video Exercises (SAVE)”, to improve the functional outcomes and facilitate early recovery by increasing the continuity of rehabilitation therapy after acute stroke. Methods: This study is a non-randomized trial. Eighty-eight patients were included in an intervention group (SAVE group), who received conventional rehabilitation therapies and an additional self-rehabilitation session by watching bedside exercise videos and continued their own exercises in their rooms for 60 min every day for 4 weeks. Ninety-six patients were included in a control group, who received only conventional rehabilitation therapies. After 4 weeks of hospitalization, both groups assessed several outcome measurements, including the Berg Balance Scale (BBS), Modified Barthel Index (MBI), physical component summary (PCS) and the mental component summary of the Short-Form Survey 36 (SF-36), Mini-Mental State Examination, and Beck Depression Inventory. Results: Differences in BBS, MBI, and PCS components in SF-36 were more statistically significant in the SAVE group than that in the control group (p < 0.05). Patients in the SAVE group showed more significant improvement in BBS, MBI, and PCS components in SF-36 as compared to that in the control group. Conclusions: This evidence-based SAVE intervention can optimize patient recovery after a subacute stroke while keeping the available resources in mind.
Music Connects Us: Development of a Music-Based Group Activity Intervention to Engage People Living with Dementia and Address Loneliness
Authors: O’Rourke Hannah M. , Hopper Tammy , Bartel Lee , Archibald Mandy , Hoben Matthias , Swindle Jennifer , Thibault Danielle , Whynot Tynisha
Published: May 2021

There is a need for intervention research to understand how music-based group activities foster engagement in social interactions and relationship-building among care home residents living with moderate to severe dementia. The purpose of this conceptual paper is to describe the design of ‘Music Connects Us’, a music-based group activity intervention. Music Connects Us primarily aims to promote social connectedness and quality of life among care home residents living with moderate to severe dementia through engagement in music-making, supporting positive social interactions to develop intimate connections with others. To develop Music Connects Us, we adapted the ‘Music for Life’ program offered by Wigmore Hall in the United Kingdom, applying an intervention mapping framework and principles of engaged scholarship. This paper describes in detail the Music Connects Us program, our adaptation approach, and key adaptations made, which included: framing the project to focus on the engagement of the person living with dementia to ameliorate loneliness; inclusion of student and other community-based musicians; reduced requirements for care staff participation; and the development of a detailed musician training approach to prepare musicians to deliver the program in Canada. Description of the development, features, and rationale for Music Connects Us will support its replication in future research aimed to tests its effects and its use in clinical practice.
Feature-Based Point Cloud-Based Assessment of Heritage Structures for Nondestructive and Noncontact Surface Damage Detection
Authors: Wood Richard L. , Mohammadi Mohammad Ebrahim
Published: May 2021

Assessment and evaluation of damage in cultural heritage structures are conducted primarily using nondestructive and noncontact methods. One common deployment is laser scanners or ground-based lidar scanners that produce a point cloud containing information at the centimeter to the millimeter level. This type of data allows for detecting surface damage, defects, cracks, and other anomalies based only on geometric surface descriptors using a single dataset, which does not rely on a change detection approach. Moreover, geometric features are not influenced by color, which is essential for heritage structures because they are nonuniform in color due to anthropologic and environmental effects (e.g., painting or moisture). In this work, a damage detection method developed based on local geometric features is evaluated and expanded for crack detection within the example fresco walls of Sala degli Elementi in the Palazzo Vecchio. The workflow’s performance is then compared in a qualitative manner to that of manual crack mapping results identified using images.