bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of ChatGPT in Data Science: How AI-Assisted Conversational Interfaces Are Revolutionizing the Field
Authors: Hassani Hossein , Silva Emmanuel Sirmal
Published: March 2023

ChatGPT, a conversational AI interface that utilizes natural language processing and machine learning algorithms, is taking the world by storm and is the buzzword across many sectors today. Given the likely impact of this model on data science, through this perspective article, we seek to provide an overview of the potential opportunities and challenges associated with using ChatGPT in data science, provide readers with a snapshot of its advantages, and stimulate interest in its use for data science projects. The paper discusses how ChatGPT can assist data scientists in automating various aspects of their workflow, including data cleaning and preprocessing, model training, and result interpretation. It also highlights how ChatGPT has the potential to provide new insights and improve decision-making processes by analyzing unstructured data. We then examine the advantages of ChatGPT’s architecture, including its ability to be fine-tuned for a wide range of language-related tasks and generate synthetic data. Limitations and issues are also addressed, particularly around concerns about bias and plagiarism when using ChatGPT. Overall, the paper concludes that the benefits outweigh the costs and ChatGPT has the potential to greatly enhance the productivity and accuracy of data science workflows and is likely to become an increasingly important tool for intelligence augmentation in the field of data science. ChatGPT can assist with a wide range of natural language processing tasks in data science, including language translation, sentiment analysis, and text classification. However, while ChatGPT can save time and resources compared to training a model from scratch, and can be fine-tuned for specific use cases, it may not perform well on certain tasks if it has not been specifically trained for them. Additionally, the output of ChatGPT may be difficult to interpret, which could pose challenges for decision-making in data science applications.
Verification of the Interaction Target Protein of the Effector ApCE22 of Arthrinium phaeospermum in Bambusa pervariabilis × Dendrocalamopsis grandis
Authors: Fang Xinmei , Yan Peng , Owusu Adjei Mark , Zhu Tianhui , Li Shujiang
Published: March 2023

The study of interaction proteins of the pathogen A. phaeospermum effector protein is an important means to analyze the disease-resistance mechanism of Bambusa pervariabilis × Dendrocalamopsis grandis shoot blight. To obtain the proteins interacting with the effector ApCE22 of A. phaeospermum, 27 proteins interacting with the effector ApCE22 were initially identified via a yeast two-hybrid assay, of which four interaction proteins were obtained after one-to-one validation. The B2 protein and the chaperone protein DnaJ chloroplast protein were then verified to interact with the ApCE22 effector protein by bimolecular fluorescence complementation and GST pull-down methods. Advanced structure prediction showed that the B2 protein contained the DCD functional domain related to plant development and cell death, and the DnaJ protein contained the DnaJ domain related to stress resistance. The results showed that both the B2 protein and DnaJ protein in B. pervariabilis × D. grandis were the target interaction proteins of the ApCE22 effector of A. phaeospermum and related to the stress resistance of the host B. pervariabilis × D. grandis. The successful identification of the pathogen effector interaction target protein in B. pervariabilis × D. grandis plays an important role in the mechanism of pathogen–host interaction, thus providing a theoretical basis for the control of B. pervariabilis × D. grandis shoot blight.
Oral Microbiota Signatures in the Pathogenesis of Euthyroid Hashimoto’s Thyroiditis
Authors: Erdem Mustafa Genco , Unlu Ozge , Ates Fatma , Karis Denizhan , Demirci Mehmet
Published: March 2023

One of the most prevalent autoimmune illnesses in the world is Hashimoto’s thyroiditis, whose pathogenesis is still unknown. The gut–thyroid axis is frequently examined, and although oral health affects thyroid functions, there are limited data on how oral microbiota is linked to Hashimoto’s thyroiditis. The study aims to identify the oral microbiota from saliva samples taken from treated (with levothyroxine) and untreated female euthyroid Hashimoto’s thyroiditis patients as well as healthy controls who were age- and sex-matched to compare the oral microbiota across the groups and to contribute preliminary data to the literature. This study was designed as a single-center cross-sectional observational study. Sixty (60) female patients with euthyroid Hashimoto’s thyroiditis (HT) and eighteen (18) age- and gender-matched healthy controls were included in this study. Unstimulated saliva samples were collected. After DNA isolation, sequencing was performed by targeting the V3-V4 gene regions of the 16S rRNA on the MiSeq instrument. R scripts and SPSS were used for bioinformatic and statistical analysis. No significant differences were found in the diversity indices. However, Patescibacteria phylum showed a significantly higher abundance (3.59 vs. 1.12; p = 0.022) in the oral microbiota of HT patients compared to HC. In the oral microbiota, the euthyroid HT group had approximately 7, 9, and 10-fold higher levels of the Gemella, Enterococcus, and Bacillus genera levels than healthy controls, respectively. In conclusion, the results of our study demonstrated that Hashimoto’s thyroiditis causes changes in the oral microbiota, whereas the medicine used to treat the condition had no such effects. Therefore, revealing the core oral microbiota and long-term follow-up of the HT process by conducting extensive and multicenter studies might provide some important data for understanding the pathogenesis of the disease.
In Vitro Effects of PTH (1-84) on Human Skeletal Muscle-Derived Satellite Cells
Authors: Romagnoli Cecilia , Zonefrati Roberto , Lucattelli Elena , Innocenti Marco , Civinini Roberto , Iantomasi Teresa , Brandi Maria Luisa
Published: March 2023

Parathyroid hormone (PTH) is a hormone secreted by the parathyroid glands. Despite its well-known characterized anabolic and catabolic actions on the skeleton, the in vitro effects of PTH on skeletal muscle cells are limited and generally performed on animal models. The aim of this study was to evaluate the effects of a short impulse of PTH (1-84) on the proliferation and the differentiation of skeletal muscle satellite cells isolated from human biopsies. The cells were exposed for 30 min to different concentrations of PTH (1-84), from 10−6 mol/L to 10−12 mol/L. ELISA was used to assay cAMP and the myosin heavy-chain (MHC) protein. The proliferation was assayed by BrdU and the differentiation by RealTime-qPCR. A statistical analysis was performed by ANOVA followed by Bonferroni’s test. No significant variations in cAMP and the proliferation were detected in the isolated cells treated with PTH. On the other hand, 10−7 mol/L PTH on differentiated myotubes has shown significant increases in cAMP (p ≤ 0.05), in the expression of myogenic differentiation genes (p ≤ 0.001), and in the MHC protein (p ≤ 0.01) vs. untreated controls. This work demonstrates for the first time the in vitro effects of PTH (1-84) on human skeletal muscle cells and it opens new fields of investigation in muscle pathophysiology.
Analysis of Respiratory Sinus Arrhythmia and Directed Information Flow between Brain and Body Indicate Different Management Strategies of fMRI-Related Anxiety
Authors: Rassler Beate , Blinowska Katarzyna , Kaminski Maciej , Pfurtscheller Gert
Published: March 2023

Background: Respiratory sinus arrhythmia (RSA) denotes decrease of cardiac beat-to-beat intervals (RRI) during inspiration and RRI increase during expiration, but an inverse pattern (termed negative RSA) was also found in healthy humans with elevated anxiety. It was detected using wave-by-wave analysis of cardiorespiratory rhythms and was considered to reflect a strategy of anxiety management involving the activation of a neural pacemaker. Results were consistent with slow breathing, but contained uncertainty at normal breathing rates (0.2–0.4 Hz). Objectives and methods: We combined wave-by-wave analysis and directed information flow analysis to obtain information on anxiety management at higher breathing rates. We analyzed cardiorespiratory rhythms and blood oxygen level-dependent (BOLD) signals from the brainstem and cortex in 10 healthy fMRI participants with elevated anxiety. Results: Three subjects with slow respiratory, RRI, and neural BOLD oscillations showed 57 ± 26% negative RSA and significant anxiety reduction by 54 ± 9%. Six participants with breathing rate of ~0.3 Hz showed 41 ± 16% negative RSA and weaker anxiety reduction. They presented significant information flow from RRI to respiration and from the middle frontal cortex to the brainstem, which may result from respiration-entrained brain oscillations, indicating another anxiety management strategy. Conclusions: The two analytical approaches applied here indicate at least two different anxiety management strategies in healthy subjects.
A Multi-Objective Carnivorous Plant Algorithm for Solving Constrained Multi-Objective Optimization Problems
Authors: Yang Yufei , Zhang Changsheng
Published: March 2023

Satisfying various constraints and multiple objectives simultaneously is a significant challenge in solving constrained multi-objective optimization problems. To address this issue, a new approach is proposed in this paper that combines multi-population and multi-stage methods with a Carnivorous Plant Algorithm. The algorithm employs the ϵ-constraint handling method, with the ϵ value adjusted according to different stages to meet the algorithm’s requirements. To improve the search efficiency, a cross-pollination is designed based on the trapping mechanism and pollination behavior of carnivorous plants, thus balancing the exploration and exploitation abilities and accelerating the convergence speed. Moreover, a quasi-reflection learning mechanism is introduced for the growth process of carnivorous plants, enhancing the optimization efficiency and improving its global convergence ability. Furthermore, the quadratic interpolation method is introduced for the reproduction process of carnivorous plants, which enables the algorithm to escape from local optima and enhances the optimization precision and convergence speed. The proposed algorithm’s performance is evaluated on several test suites, including DC-DTLZ, FCP, DASCMOP, ZDT, DTLZ, and RWMOPs. The experimental results indicate competitive performance of the proposed algorithm over the state-of-the-art constrained multi-objective optimization algorithms.
Experimental Study of an Industrial Tower-Type Supporting Frame with Facades Subjected to the Stationary Wind Effect
Authors: Frishter Lyudmila , Lukin Maxim
Published: March 2023

Aerodynamic studies of canceled structures are important for design of buildings, analysis of air flows inside buildings, evaluation of buildings’ effects on air flow patterns of the adjoining area, and optimal choice of enclosing structures. The analysis of wind effects during the design of canceled structures is governed by codes and standards of general purpose. These statutory documents do not regulate the mounting procedure of wind protection screens, nor do they contain the analysis of wind effects on structures with different angles of attack of an incident wind flow. The codes prescribe aeroelastic model testing in special civil engineering wind tunnels during the design of such structures. The purpose of this research project is to analyze wind effects on the force and torque specification of a canceled structure at different wind effect angles accounting for the mounting sequence of wind protection screens. The subject of the article is an experimental aeroelastic study of wind effects on a canceled structure accounting for sequential mounting of wind protection screens on the structure’s facade. The obtained data will allow for the analysis of effects of the wind flow angle on internal forces of the structure, given that a change in its permeability is taken into account. At the initial design stage, experimental modeling of wind effects in a wind tunnel is thereby considered a structure model validation step. The relevance of the paper lies in the need to identify optimum operating conditions of canceled structures, subjected to a wind effect, to ensure safe and comfortable work of people and reliable operation of process equipment installed inside the facility.
Highlighting In Vitro the Role of Brain-like Endothelial Cells on the Maturation and Metabolism of Brain Pericytes by SWATH Proteomics
Authors: Menaceur Camille , Hachani Johan , Dib Shiraz , Duban-Deweer Sophie , Karamanos Yannis , Shimizu Fumitaka , Kanda Takashi , Gosselet Fabien , Fenart Laurence , Saint-Pol Julien
Published: March 2023

Within the neurovascular unit, brain pericytes (BPs) are of major importance for the induction and maintenance of the properties of the blood-brain barrier (BBB) carried by the brain microvessel endothelial cells (ECs). Throughout barriergenesis, ECs take advantage of soluble elements or contact with BPs to maintain BBB integrity and the regulation of their cellular homeostasis. However, very few studies have focused on the role of ECs in the maturation of BPs. The aim of this study is to shed light on the proteome of BPs solocultured (hBP-solo) or cocultured with ECs (hBP-coc) to model the human BBB in a non-contact manner. We first generated protein libraries for each condition and identified 2233 proteins in hBP-solo versus 2492 in hBP-coc and 2035 common proteins. We performed a quantification of the enriched proteins in each condition by sequential window acquisition of all theoretical mass spectra (SWATH) analysis. We found 51 proteins enriched in hBP-solo related to cell proliferation, contractility, adhesion and extracellular matrix element production, a protein pattern related to an immature cell. In contrast, 90 proteins are enriched in hBP-coc associated with a reduction in contractile activities as observed in vivo in ‘mature’ BPs, and a significant gain in different metabolic functions, particularly related to mitochondrial activities and sterol metabolism. This study highlights that BPs take advantage of ECs during barriergenesis to make a metabolic switch in favor of BBB homeostasis in vitro.
Molecular Modeling and Potential Ca2+ Channel Blocker Activity of Diphenylmethoxypiperidine Derivatives
Authors: Pulgar Victor M. , Harp Jill , Reeves Tony E.
Published: March 2023

Molecular interactions of 4-diphenylmethoxy-1-methylpiperidine derivatives with the calcium channel CaV1.1 (pdb:6JP5) are described. All the compounds tested, previously shown to inhibit adrenergic vascular contractions, display similar binding energetics and interactions with the trans-membrane domain of 6JP5 on the opposite side relative to the channel pore, where nifedipine, a known dihydropyridine Ca2+ channel blocker binds. Additionally, the compounds tested inhibit Ca2+-dependent contractions in isolated mouse mesenteric arteries. Thus, diphenylpyraline analogs may exert their anticontractile effects, at least partially, by blocking vascular Ca2+ channels.
A Facile Synthetic Approach toward Obtaining N-Doped Carbon Quantum Dots from Citric Acid and Amino Acids, and Their Application in Selective Detection of Fe(III) Ions
Authors: Šafranko Silvija , Janđel Kristina , Kovačević Monika , Stanković Anamarija , Dutour Sikirić Maja , Mandić Šimun , Széchenyi Aleksandar , Glavaš Obrovac Ljubica , Leventić Marijana , Strelec Ivica , Aladić Krunoslav , Jokić Stela
Published: March 2023

This work reports the preparation of amino acid-functionalized CQDs from citric acid by facile hydrothermal synthesis. The prepared N-doped CQDs exhibited excellent optical, physical, and chemical properties, and the differences were observed among the six different amino acids used as nitrogen dopants (Leu, Trp, Lys, Arg, Ala, His). Compared to the blank sample (without the addition of amino acids), N-doped CQDs have shown significantly higher quantum yield, also demonstrating the potential in metal ion sensing. The highest quantum yield of 36.45%, with a peak excitation/emission of 340/406 nm, was achieved using citric acid and amino acid Leu (CQD@Leu), treated at temperature of 180 °C during 9 h. The prepared samples were investigated toward metal ion selectivity (Ca2+, Cu2+, Fe3+, K+, Hg2+, Mg2+, Al3+, Mn2+, and Na+), and the CQD@Leu showed a selective and sensitive response upon the addition of Fe3+ ions. Therefore, CQD@Leu was selected for further investigation in Fe3+ detection in the model system and real well water samples. A developed model was described by a logistic function with a good coefficient of determination of R2 = 0.9982, while the linear range was determined in the concentration range from 0.3 mol dm−3 to 30 mol dm−3, with a determined limit of detection of LOD = 1.77 ± 0.01 mol dm−3 and limit of quantification of LOQ = 5.89 ± 0.04 mol dm−3. Furthermore, the results of the in vitro cytotoxicity test (MTT) with normal and tumor cell lines (MRC-5, HeLa, NCI-H358, and CaCo-2) clearly demonstrate the excellent biocompatibility of CQD@Leu.
Systematic Literature Review (SLR) and Network Meta-Analysis (NMA) of First-Line Therapies (1L) for Locally Advanced/Metastatic Urothelial Carcinoma (la/mUC)
Authors: Bloudek Lisa , Wright Phoebe , McKay Caroline , Derleth Christina Louise , Lill Jennifer Susan , Lenero Enrique , Hepp Zsolt , Ramsey Scott David , Sullivan Sean D. , Devine Beth
Published: March 2023

To compare efficacy outcomes for all approved and investigational first-line (1L) treatment regimens for locally advanced or metastatic urothelial carcinoma (la/mUC) with standard of care (SOC), a network meta-analysis (NMA) was conducted. A systematic literature review (SLR) identified phase 2 and 3 randomized trials investigating 1L treatment regimens in la/mUC published January 2001–September 2021. Three networks were formed based on cisplatin (cis) eligibility: cis-eligible/mixed (cis-eligible patients and mixed populations of cis-eligible/ineligible patients), cis-ineligible (strict; exclusively cis-ineligible patients), and cis-ineligible (wide; including studies with investigator’s choice of carbo). Analyses examined comparative efficacy by hazard ratio (HR) for overall survival (OS), and progression-free survival (PFS), and odds ratio (OR) for overall response rate (ORR), with 1L regimens vs. SOC. SOC was gemcitabine + cis (GemCis) or carboplatin (GemCarbo), cis-eligible/mixed network, and GemCarbo cis-ineligible networks. Of 1906 SLR identified citations, 55 trials were selected for data extraction. The NMA comprised 11, 6, and 8 studies in the cis-eligible/mixed, cis-ineligible (strict), cis-ineligible (wide) networks, respectively. In a meta-analysis of SOC control arms, median (95% CI) overall survival (OS) in months varied by network: 13.19 (12.43, 13.95) cis-eligible/mixed, 11.96 (10.43, 13.48) cis-ineligible (wide), and 9.74 (6.71, 12.76) cis-ineligible (strict). Most differences in OS, PFS, and ORR with treatment regimens across treatment networks were not statistically significant compared with SOC. Outcomes with current 1L regimens remain poor, and few significant improvements over SOC have been made, despite inclusion of recent clinical trial data, highlighting an unmet need in the la/mUC patient population.
Distributed Offloading for Multi-UAV Swarms in MEC-Assisted 5G Heterogeneous Networks
Authors: Ma Mingfang , Wang Zhengming
Published: March 2023

Mobile edge computing (MEC) is a novel paradigm that offers numerous possibilities for Internet of Things (IoT) applications. In typical use cases, unmanned aerial vehicles (UAVs) that can be applied to monitoring and logistics have received wide attention. However, subject to their own flexible maneuverability, limited computational capability, and battery energy, UAVs need to offload computation-intensive tasks to ensure the quality of service. In this paper, we solve this problem for UAV systems in a 5G heterogeneous network environment by proposing an innovative distributed framework that jointly considers transmission assessment and task offloading. Specifically, we devised a fuzzy logic-based offloading assessment mechanism at the UAV side, which can adaptively avoid risky wireless links based on the motion state of an UAV and performance transmission metrics. We introduce a multi-agent advantage actor–critic deep reinforcement learning (DRL) framework to enable the UAVs to optimize the system utility by learning the best policies from the environment. This requires decisions on computing modes as well as the choices of radio access technologies (RATs) and MEC servers in the case of offloading. The results validate the convergence and applicability of our scheme. Compared with the benchmarks, the proposed scheme is superior in many aspects, such as reducing task completion delay and energy consumption.
Entropy and Fractal Techniques for Monitoring Fish Behaviour and Welfare in Aquacultural Precision Fish Farming—A Review
Authors: Eguiraun Harkaitz , Martinez Iciar
Published: March 2023

In a non-linear system, such as a biological system, the change of the output (e.g., behaviour) is not proportional to the change of the input (e.g., exposure to stressors). In addition, biological systems also change over time, i.e., they are dynamic. Non-linear dynamical analyses of biological systems have revealed hidden structures and patterns of behaviour that are not discernible by classical methods. Entropy analyses can quantify their degree of predictability and the directionality of individual interactions, while fractal dimension (FD) analyses can expose patterns of behaviour within apparently random ones. The incorporation of these techniques into the architecture of precision fish farming (PFF) and intelligent aquaculture (IA) is becoming increasingly necessary to understand and predict the evolution of the status of farmed fish. This review summarizes recent works on the application of entropy and FD techniques to selected individual and collective fish behaviours influenced by the number of fish, tagging, pain, preying/feed search, fear/anxiety (and its modulation) and positive emotional contagion (the social contagion of positive emotions). Furthermore, it presents an investigation of collective and individual interactions in shoals, an exposure of the dynamics of inter-individual relationships and hierarchies, and the identification of individuals in groups. While most of the works have been carried out using model species, we believe that they have clear applications in PFF. The review ends by describing some of the major challenges in the field, two of which are, unsurprisingly, the acquisition of high-quality, reliable raw data and the construction of large, reliable databases of non-linear behavioural data for different species and farming conditions.
Forecasting Commodity Market Synchronization with Commodity Currencies: A Network-Based Approach
Authors: Magner Nicolas S. , Hardy Nicolás , Lavin Jaime , Ferreira Tiago
Published: March 2023

This paper shows that some commodity currencies (from Chile, Iceland, Norway, South Africa, Australia, Canada, and New Zealand) predict the synchronization of metals and energy commodities. This relationship links the present-value theory for exchange rates and its connection with commodity export economies’ fundamentals, where prospective commodity price fluctuations affect exchange rates. Predicting commodity market return synchronization is critical for dealing with systemic risk, market efficiency, and financial stability since synchronization reduces the benefits of diversification and increases the probability of contagion in financial markets during economic and financial crises. Using network methods coupled with in-sample and out-of-sample econometrics models, we find evidence that a fall in the return of commodity-currencies (dollar appreciation) predicts an increase in commodity market synchronization and, consequently, in commodity market systemic risk. This discovery is consistent with a transitive capacity phenomenon, suggesting that commodity currencies have a predictive ability over commodities that extend beyond the commodity bundle that a country produces. The latter behavior would be exacerbated by the high financialization of commodities and strong co-movement of commodity markets. Our paper is part of a vigorously growing literature that has recently measured and predicted systemic risk caused by synchronization, combining a complex systems perspective and financial network analysis.
Multi-Source Partial Discharge Fault Location with Comprehensive Arrival Time Difference Extraction Method and Multi-Data Dynamic Weighting Algorithm
Authors: Wang Disheng , Du Lin , Wang Tao , Zhao Xiuna
Published: March 2023

The location of the partial discharge source is an important part of fault diagnosis inside power equipment. As a key step of the ultra-high frequency location method, the extraction of the time difference of arrival can generate large errors due to interference. To achieve accurate time difference extraction and further multi-source partial discharge location, a location method with comprehensive time difference extraction and a multi-data dynamic weighting algorithm is proposed. For time difference extraction, the optimized energy accumulation curve method applies wavelet transform and mode maximization calculations such that it overcomes the effect of interference signals before the wave peak. The secondary correlation method improves the interference capability by performing two rounds of correlation calculations. Both extraction methods are combined to reduce the error in time difference extraction. Then, the dynamic weighting algorithm effectively utilizes multiple data and improves the location accuracy. Experimental results on multi-source partial discharge locations performed in a transformer tank validate the accuracy of the proposed method.
Gender Differences in University Students’ Levels of Physical Activity and Motivations to Engage in Physical Activity
Authors: Espada María , Romero-Parra Nuria , Bores-García Daniel , Delfa-De La Morena José Manuel
Published: March 2023

The transition of students to the university stage is a critical period in which there are numerous changes that could influence their lifestyles. The aim of this research was to analyse the levels of physical activity and the types of motivation for physical activity among university students according to gender. A quantitative, descriptive, and cross-sectional survey methodology was used. A total sample of 3060 university students, 47.8% women and 52.2% men, with a mean age of 20.88 ± 2.01 years was recruited. The sampling margin of error was ±1.85%. The short form of the International Physical Activity Questionnaire and the third version of the Behavioural Regulation in Exercise Questionnaire were used to evaluate MVPA and motivations to exercise, respectively. Two-way ANCOVA and a mediation analysis were performed. The most relevant results show that less than half of the university men and women are considered physically active. Furthermore, when analysing the interaction between motivation and gender, a large effect in identified motivation (F = 65.03; p≤ 0.001) and integrated motivation (F = 324.58; p ≤.0.001) and a medium one intrinsic motivation (F = 169.39; p ≤ 0.001) was found. Therefore, women university students have lower levels of physical activity practice than men students and show higher external motivation and demotivation.
The Impact of a Challenge-Based Learning Experience in Physical Education on Students’ Motivation and Engagement
Authors: Simón-Chico Luis , González-Peño Alba , Hernández-Cuadrado Ernesto , Franco Evelia
Published: March 2023

The present study investigated how challenge-based learning (CBL) in physical education (PE) may affect students’ basic psychological needs (BPNs), motivational regulations, engagement, and learning in comparison with a traditional teaching (TT) methodology. A quasiexperimental study with experimental and control groups was carried out. In total, 50 participants (16 boys and 34 girls) between 13 and 15 years old (Mage = 13.35, SD = 0.62) were involved in the experience for 6 weeks (ncontrol = 24; nexperimental = 26). Validated questionnaires were administered both before and after the intervention in both groups. Furthermore, theoretical knowledge and badminton-specific motor skill tests were carried out in both groups after the intervention. An analysis showed that after the intervention, students in the CBL condition improved their autonomy (Mbefore = 3.15 vs. Mafter = 3.39; ES = 0.26 *), competence (Mbefore = 4.01 vs. Mafter = 4.18; ES = 0.33 *), and relatedness satisfaction (Mbefore = 3.86 vs. Mafter = 4.06; ES = 0.32 *). As for behavioural engagement measures, students in the CBL condition exhibited higher scores after than those from before (Mbefore = 4.12 vs. Mafter = 4.36; ES = 0.35 *). No significant changes were observed for motivational regulations or agentic engagement. On learning outcomes, students in the experimental group achieved higher scores in both theoretical knowledge (Mcontol = 6.48 vs. Mexperimental = 6.79) and badminton-specific motor skills (Mcontol = 6.85 vs. Mexperimental = 7.65) than the control group did. The present study findings highlight that CBL might be a valid and effective methodological approach for students in PE to achieve adaptive motivational, behavioural, and learning outcomes.
Hybrid Encrypted Watermarking Algorithm for Medical Images Based on DCT and Improved DarkNet53
Authors: Li Dekai , Li Jingbing , Bhatti Uzair Aslam , Nawaz Saqib Ali , Liu Jing , Chen Yen-Wei , Cao Lei
Published: March 2023

To solve the problem of robustness of encrypted medical image watermarking algorithms, a zero watermarking algorithm based on the discrete cosine transform (DCT) and an improved DarkNet53 convolutional neural network is proposed. The algorithm targets medical images in the encrypted domain. In this algorithm, DCT is performed on the encrypted medical image to extract 32-bit features as feature 1. DarkNet53, a pre-trained network, was chosen for migration learning for the network model. The network uses a fully connected layer and a regression layer instead of the original Softmax layer and classification layer, changing the original classification network into a regression network with an output of 128. With these transformations, 128-bit features can be extracted from encrypted medical images by this network, and then DCT is performed to extract 32-bit features as feature 2. The fusion of features 1 and 2 can effectively improve the robustness of the algorithm. The experimental results show that the algorithm can accurately distinguish different encrypted medical images and can effectively restore the original information from the encrypted watermarked information under traditional and geometric attacks. Compared with other algorithms, the proposed method demonstrates better robustness and invisibility.
Deep Deformable Artistic Font Style Transfer
Authors: Zhu Xuanying , Lin Mugang , Wen Kunhui , Zhao Huihuang , Sun Xianfang
Published: March 2023

The essence of font style transfer is to move the style features of an image into a font while maintaining the font’s glyph structure. At present, generative adversarial networks based on convolutional neural networks play an important role in font style generation. However, traditional convolutional neural networks that recognize font images suffer from poor adaptability to unknown image changes, weak generalization abilities, and poor texture feature extractions. When the glyph structure is very complex, stylized font images cannot be effectively recognized. In this paper, a deep deformable style transfer network is proposed for artistic font style transfer, which can adjust the degree of font deformation according to the style and realize the multiscale artistic style transfer of text. The new model consists of a sketch module for learning glyph mapping, a glyph module for learning style features, and a transfer module for a fusion of style textures. In the glyph module, the Deform-Resblock encoder is designed to extract glyph features, in which a deformable convolution is introduced and the size of the residual module is changed to achieve a fusion of feature information at different scales, preserve the font structure better, and enhance the controllability of text deformation. Therefore, our network has greater control over text, processes image feature information better, and can produce more exquisite artistic fonts.
Transportation of Service Enhancement Based on Virtualization Cloud Desktop
Authors: Li Fan , Guo Tengda , Li Xiaohui , Wang Junfeng , Xia Yunni , Ma Yong
Published: March 2023

Cloud desktop represents an outstanding product in the domain of cloud computing, which refers to the desktop cloud, desktop virtualization and virtual desktop. Cloud desktop explores the virtualization technology to concentrate computing resources, which delivers traditional computer desktops (operating system interfaces) or applications deployed in the pooled computing resources to polymorphic terminals through the Internet. As a distinctive product of cloud computing, cloud desktop has been a hot topic since its inception. Today, the virtualized resource pool of cloud computing achieves the elastic and dynamic expansion of resources, which brings the desktop system from an independent personal computer to a centralized physical server. Consequently, the great improvement in basic network conditions makes it possible to transmit high-quality desktops over the network. There are two key factors for cloud desktops, one of which is the virtualization technology on the server side and the other one, which is the transmission protocol of cloud desktops. The cloud desktop transmission protocol mainly completes the transmission of graphics, images and audio from the server to the user terminal. The transmission of input information from the user terminal, called DaaS (Desktop-as-a-Service), includes the input information of peripherals such as a mouse, keyboard, printer and so on. The efficiency of the transmission protocol determines the basic delivery capability of the cloud desktop, while the bearer protocol and graphics and image processing methods in the transmission protocol determine the interactive experience of the cloud desktop. Different protocols have their characteristics and applicable space. This paper spies on application and transport layer communication protocols to meet DaaS communication requirements. This paper describes the internal mechanism of various transport protocols applicable to a cloud desktop from the principle level and points out the pros and cons and the current application environment. It can be seen that these methods solve the transmission efficiency of burst traffic, improve user experience and reduce bandwidth consumption, which are the development direction of transmission protocols.
Improve Model Testing by Integrating Bounded Model Checking and Coverage Guided Fuzzing
Authors: Yang Yixiao
Published: March 2023

Eectromechanical systems built by Simulink or Ptolemy have been widely used in industry fields, such as autonomous systems and robotics. It is an urgent need to ensure the safety and security of those systems. Test case generation technologies are widely used to ensure the safety and security. State-of-the-art testing tools employ model-checking techniques or search-based methods to generate test cases. Traditional search-based techniques based on Simulink simulation are plagued by problems such as low speed and high overhead. Traditional model-checking techniques such as symbolic execution have limited performance when dealing with nonlinear elements and complex loops. Recently, coverage guided fuzzing technologies are known to be effective for test case generation, due to their high efficiency and impressive effects over complex branches of loops. In this paper, we apply fuzzing methods to improve model testing and demonstrate the effectiveness. The fuzzing methods aim to cover more program branches by mutating valuable seeds. Inspired by this feature, we propose a novel integration technology SPsCGF, which leverages bounded model checking for symbolic execution to generate test cases as initial seeds and then conduct fuzzing based upon these worthy seeds. Over the evaluated benchmarks which consist of industrial cases, SPsCGF could achieve 8% to 38% higher model coverage and 3x-10x time efficiency compared with the state-of-the-art works.
Investigation of Oscillation and Resonance in the Renewable Integrated DC-Microgrid
Authors: Habibullah Mohammad , Mithulananthan Nadarajah , Shah Rakibuzzaman , Islam Md Rabiul , Muyeen S. M.
Published: March 2023

This paper assessed the small-signal stability performance of a multi-converter-based direct current microgrid (DCMG). The oscillation and potential interactions between critical modes are evaluated. First, the complete analytical model of the DCMG is developed with the converter and associated controllers. Three methodologies, impedance scanning, eigenvalue analysis, and time-domain simulation, along with the fast Fourier transform (FFT) analysis, have been used to comprehensively investigate the oscillations and interactions. The simulation results show inherent weak modes, with a wide range of oscillations in the studied DCMG, which may destabilize the system under disturbances. Based on the sensitivity analysis, controller gains and DC-link capacitance are identified as the most critical parameters and substantially influence the weak modes leading to oscillations, interactions, and resonance. Finally, the performance of the various control synthesis methods is compared. This examination would help the researchers, planning, and design engineers to design and stably operate a multi converter-based DC microgrid.
A New Method for Determining Outdoor Humidity Ratio of Natatorium in Transition Season
Authors: Lei Jiaxiang , Li Honglian , Li Chengwang , Xu Minrui
Published: March 2023

The natatorium’s ventilation problem receives much concern because of its large wet load. The outdoor humidity ratio in transition season is the basic design parameter of the ventilation calculation, directly affecting the rationality of architectural design. At present, the ventilation-curve (V-C) method is the most widely used method to determine the outdoor humidity ratio in the transition season in China. However, due to failing to reflect non-guaranteed hours, the rationality of this value is difficult to assess by employing this approach. This paper presents a new method, the typical transition season method (TTS), for determining the outdoor humidity ratio in the transition season of a natatorium. The TTS method selects the transition season based on the typical meteorological year (TMY) data and calculates the outdoor humidity ratio with multiple non-guaranteed hours. This can well-represent the local perennial climate characteristics and clearly reflect the non-guaranteed hours. In this study, through selecting six typical representative cities in China, the evaluation of the outdoor humidity ratio is achieved through calculating ventilation volume and air change rate, verifying the rationality of this method. The results show that the humidity ratio obtained by the V-C method is lower than that obtained by the TTS method at about 2 g/kg without guarantee of 200 h humidity ratio, and even that the maximum difference is 6.64 g/kg. Meanwhile, the validation results of the ventilation calculation show that the humidity ratio determined by the V-C method cannot meet the minimum design requirements in five cities, while the humidity ratio obtained by the TTS method cannot meet the requirements in only one city.
Control Methods for Levitation System of EMS-Type Maglev Vehicles: An Overview
Authors: Li Fengxing , Sun Yougang , Xu Junqi , He Zhenyu , Lin Guobin
Published: March 2023

As new advanced vehicles, electromagnetic suspension (EMS)-type maglev trains have received wide attention because of their advantages such as high speed, no mechanical friction, low noise, low cost and energy consumption, strong climbing ability, and green environmental protection. The open-loop instability is one of the key points and difficulties for the levitation control systems of maglev trains. The closed-loop feedback control method must be applied to realize stable levitation. However, there are currently many levitation control methods just in theory. Considering their advantages and disadvantages, it is a major demand for maglev trains to select efficient, stable, applicable, and cost-saving methods to improve their dynamic performance and safety, which motivated this review. First, the current status of research on maglev trains is introduced in this paper, including types, system components, and research modes in various countries, followed by an analysis of the levitation control methods for EMS-type maglev trains. Then, the technical characteristics of the levitation control systems are described according to the basic principles of levitation systems, model building, mathematical derivation, and control objectives. Next, three kinds of typical levitation control methods are reviewed, namely, linear state feedback methods, nonlinear control methods, and intelligent control methods, according to their improvements and applications. Lastly, we summarize and evaluate the advantages and disadvantages of the three methods, and future developments of levitation control are suggested.
Multi-Time-Scale Coordinated Optimum Scheduling Technique for a Multi-Source Complementary Power-Generating System with Uncertainty in the Source-Load
Authors: Huang Zhengwei , Liu Lu , Liu Jiachang
Published: March 2023

An optimal dispatching strategy for a multi-source complementary power generation system taking source–load uncertainty into account is proposed, in order to address the effects of large-scale intermittent renewable energy consumption and power load instability on power grid dispatching. The uncertainty problem is first converted into common situations for study, such as load power forecasting and solar and wind power. The backward scenario reduction and Latin hypercube sampling techniques are used to create these common situations. Based on this, a multi-timescale coordinated optimum scheduling control method for a multi-source complementary power generation system taking the demand response into account is presented, and the optimal operation of a wind–PV–thermal-pumped storage hybrid system is examined. The time-of-use power price optimizes the electrical load in the day-ahead pricing mode, and the two types of demand response loads are selected in the day-ahead scheduling. Second, the lowest system operating cost and the minimal day-ahead and intra-day adjustment of each source are established as the optimization targets in the day-ahead and intra-day phases of the multi-timescale coordinated scheduling model of the multi-source complementary system. The example study demonstrates that the scheduling strategy may increase the amount of renewable energy consumed, minimize load fluctuations, increase system stability, and further reduce operating expenses, proving the viability and efficiency of the suggested strategy.
New Approach to Evaluate the Transformation Accuracy of Inductive CTs for Distorted Current
Authors: Kaczmarek Michal , Stano Ernest
Published: March 2023

This paper presents a newly developed method to determine the values of current error and phase displacement for the transformation of distorted current harmonics by the inductive current transformers. This approach eliminates the necessity for the utilization of an expensive, high-current supply system for the measuring setup. In this method, the secondary winding is fed by the distorted voltage with RMS values of harmonics calculated in order to reproduce the operation point of the inductive current transformer on the magnetization characteristic of its magnetic core, as in primary winding excitation conditions. This proposed approach is successfully verified with the typically used primary current excitation method, where the secondary currents of the reference and tested current transformers are compared in the differential measuring setup. It was confirmed that the inductive CT with current error and phase displacement for transformation of distorted current harmonics determined in the rated ampere-turns conditions may be effectively used in the measuring setup as the reference source of the primary current.
Islanding Detection with Reduced Non-Detection Zones and Restoration by Reconfiguration
Authors: Ramachandradurai Sowmya , Krishnan Narayanan , Sharma Gulshan , Bokoro Pitshou N.
Published: March 2023

The development and use of PV (Photovoltaic), Wind, and Hydro-based Distributed Generation (DG) is presently on the rise worldwide for improving stability and reliability, and reducing the power loss in the distribution system with reduced emission of harmful gases. A crucial issue addressed in this article, due to the increased penetration of DGs, is islanding operations. The detection of islanding is performed by a proposed v&f (voltage and frequency) index method. The reliability indices of the IEEE-33 and 118 radial bus distribution system after the detection of islanding by the proposed method is evaluated by considering the islanding issue as customer interruption. To mitigate the islanding, a reconfiguration strategy using Particle Swarm Optimization (PSO) is also performed and the proposed strategy is also evaluated with the conventional reconfiguration strategy of the distribution system.
Aspen Plus® Process Simulation Model of the Biomass Ash-Based Treatment of Anaerobic Digestate for Production of Fertilizer and Upgradation of Biogas
Authors: Moure Abelenda Alejandro , Ali Abdikhani , Semple Kirk T. , Aiouache Farid
Published: March 2023

The use of the commercial simulator Aspen Plus® could bring an amelioration in the accuracy of the predictions of the chemical species composition in the output streams of the anaerobic digestion process. Compared to the traditionally employed lumped models, which are elaborated from scratch, the models implemented in Aspen Plus® have access to a broad library of thermodynamic and phenomena transport properties. In the present investigation, a process simulation model for anaerobic digestion has been prepared by including a stoichiometric-equilibria reactor to calculate the extent of the ionization of the molecules present in the anaerobic digestate. The model characterizes the technical feasibility of anaerobic digestate stabilization, by means of biomass ash-based treatment, for the production of an organic fertilizer and potential biogas upgradation with the synthesis of ammonium carbonate. First of all, the titration of the manure digestate with the hydrochloric acid showed that a dose of 3.18 mEq/g would be required to attain the targeted pH of zero-point charge, upon addition of the sewage sludge ash in a ratio to the manure digestate of 0.6 ± 0.2%. Secondly, the profiles of ammonia, carbon dioxide, and methane found in the biogas agree with the pH of the treated digestate and enable the upgrading of the biogas with the production of NH4HCO3. The model needs to be further developed to ensure the standards are attained in all output streams of stabilized anaerobic digestate, biomethane, and isolated added-value chemical fertilizers.