bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of an Extruded Austenitic Stainless Steel for Advanced Fossil Power Plant Applications
Authors: Purdy D. , Gandy D. , Shingledecker J.
Published: March 2024

Ultrasupercritical (USC) steam boiler and heat recovery steam generator (HRSG) technology is constantly evolving to improve efficiency and reduce emissions. Currently, temperatures are pushing beyond the capabilities of even the most advanced ferritic steels with some applications requiring nickel-based superalloys. Cost-effective design of these systems requires the application of a variety of alloys representing a range of cost/property trade-offs. CF8C-Plus is a cast austenitic stainless steel recently developed for application in high temperatures similar to those in power plants (600 - 900 °C) with creep strength comparable to several superalloys. This makes it an attractive alternative for those expensive alloys. EPRI, with assistance from PCC subsidiaries Special Metals and Wyman Gordon Pipes and Fittings, has produced and characterized two pipe extrusions nominally 5.25 inch OD x 0.5 inch wall thickness and 6 inch OD x 0.75 inch wall (13.3 x 1.3 cm and 15.2 x 1.9 cm), each about 1000 lbs, to continue to assess the feasibility of using a wrought version of the alloy in power piping and tubing applications. The mechanical properties from these extrusions show performance in the same population as earlier forging trials demonstrating capability exceeding several austenitic stainless steels common to the industry. Creep-rupture performance in these extrusions continues to be competitive with nickel-based superalloys.
Development of High Chromium Ferritic Steels Strengthened by Intermetallic Phases
Authors: Kuhn B. , Talik M. , Zurek J. , Beck T. , Quadakkers W.J. , Singheiser L.S. , Hattendorf H.
Published: March 2024

Constricted steam oxidation resistance and finite microstructural stability limits the use of 9 - 12 wt.-% chromium ferritic-martensitic steels to steam temperatures of about 620 °C. Newly developed 12 wt.-% Cr steels are prone to Z-phase precipitation, which occurs at the expense of the strengthening precipitates, and therefore suffer an accelerated decline in strength during longterm operation. While the concept of ferritic-martensitic chromium steels thus seems to hit technological limitations, further improvement in steam power plant efficiency necessitates a further increase of steam pressure and temperature. Furthermore increasing integration of intermitting renewable energy technologies in electrical power generation poses a great challenge for supply security, which has to be ensured on the basis of conventional power plant processes. Besides improved efficiency for resource preservation, load flexibility, thermal cycling capability and downtime corrosion resistance will play key roles in the design of tailored materials for future energy technology. Under these preconditions a paradigm shift in alloy development towards improvement of cyclic steam oxidation and downtime corrosion resistance in combination with adequate creep and thermomechanical fatigue strength seems to be mandatory. The steam oxidation, mechanical and thermomechanical properties of fully ferritic 18 - 24 wt.-% chromium model alloys, strengthened by the precipitation of intermetallic (Fe,Cr,Si)2(Nb,W) Laves phase particles, indicate the potential of this type of alloys as candidate materials for application in highly efficient and highly flexible future supercritical steam power plants.
Microstructure and Properties of 12Cr2MoWVTiB Steel for Membrane Walls
Authors: Cieszyński Krzysztof , Osuch Władysław , Kaczorowski Maciej , Fudali Stanisław , Czyrska-Filemonowicz Aleksandra
Published: March 2024

Research on low-alloyed, heat-resistant 12Cr2MoWVTiB steel, implemented in China to power plants in 50’s last century, was performed to investigate a possibility of its application for pressure elements of boilers, in particular for membrane walls. The microstructure of the as-received 12Cr2MoWVTiB tube, investigated by light microscopy, scanning- and transmission electron microscopy, consists of ferritic grains with some bainite areas between them as well as primary carbides (MC) and secondary carbides (VC, M23C6, M6C) formed during tempering of the steel. Results of mechanical tests of 12Cr2MoWVTiB welded joints (butt- and fillet welded joints) as well as microstructure analyses of are satisfactory.
Corrosion Characteristics of Alloy622 Weld Overlay for Waterwall Tubes in Coal Fired Boilers
Authors: Matsui Masakazu , Matsumoto Hirotoshi , Miyazawa Takeshi
Published: March 2024

Recently, boiler waterwall tube damage such as fireside corrosion and circumferential cracking in low NOx environments has become a serious issue in Japan, despite the typical use of relatively lower sulfur content coal is typically being used than in US. Thermal spray coating has been the most popular method for tube protection in Japan, and thermal spray coated tubes have been used for this purpose. However, extensive damage to thermal spray coating tubes from cracking and exfoliation has been recently experienced. It has been reported that the thermal fluctuations occurring due to operational changes create alternating stress, leading to cracking and exfoliation of the thermal sprayed thin coating. Corrosion-resistant weld overlays, such as Type 309 stainless steel (in sub-critical boilers) and Alloy 622 (in sub-critical and super-critical boilers), are commonly used to protect boiler tubes from corrosion in low NOx coal fired boilers in U.S. In order to develop a fundamental understanding of the high temperature corrosive behavior of Alloy 622 weld overlay, gaseous corrosion testing and certain mechanical tests for consideration of long-term aging were undertaken. After four years of service in the low NOx combustion environment of a coal fired supercritical boiler, field tests on Alloy 622 weld overlay panels are in continuation. This paper describes the field test behavior of Alloy 622 weld overlay panels installed in a Japanese supercritical boiler, the laboratory results of weight loss corrosion testing, and the results of cyclic bend tests with overlay welded tubes related to aging.
A Computational Design Study of Novel Creep Resistant Steels for Fossil Fuel Power
Authors: Lu Qi , Xu Wei , van der Zwaag Sybrand
Published: March 2024

This work concerns a study into the design of creep resistant precipitation hardened austenitic steels for fossil fuel power plants using an integrated thermodynamics based model in combination with a genetic algorithm optimization routine. The key optimization parameter is the secondary stage creep strain at the intended service temperature and time, taking into account the coarsening rate of MX carbonitrides and its effect on the threshold stress for secondary creep. The creep stress to reach a maximal allowed creep strain (taken as 1%) at a given combination of service temperature and time is formulated and maximized. The model was found to predict the behavior of commercial austenitic creep resistant steels rather accurately. Using the alloy optimization scheme three new steel compositions are presented yielding optimal creep strength for various intended service times up to 105 hours. According to the evaluation parameter employed, the newly defined compositions will outperform existing precipitate strengthened austenitic creep resistant steels.
Cenab Şehabeddin’in Hikâyeleri Üzerine Bir Değerlendirme
Authors: ÖZTÜRK Yakup
Published: March 2024

Cenab Şehabeddin (1871-1934), Türk edebiyatında Servet-i Fünûn Dönemi olarak isimlendirilen edebiyat hareketliliğinin özellikle şiir cephesinden en önemli şairi kabul edilir. Bunda, tıp tahsili için Paris’e gönderilmesinden sonra ortaya koyduğu sanat anlayışının ve Avrupa’dan getirdiği yeniliklerin de payı büyüktür. Dönemin batılı sanatçılarını yakından takip etmiş, özellikle Natüralistlerin edebiyata bakışını kabullenmiş, yeni nazım biçimlerini denemiş, görülmemiş imaj ve imgelerle yeni Türk şiirinin yolunu açmıştır. Kendi kuşağının da ötesine geçerek sonraki şairlere tesir etmiştir. Cenab Şehabeddin edebiyat türleri arasında en çok mesaiyi şiire harcasa da o, deneme, fıkra, gezi yazısı, mizah, piyes gibi birden fazla türde kendisini ispatlamış çok yönlü bir sanatçıdır. Bu türler arasında onun hikâyeler yazdığı edebiyat araştırmacılarının pek ilgisini çekmemiştir. Bugün, tespit edilen dokuz hikâyesi, büyük külliyatı karşısında pek kayda değer görülmemiş olmalıdır. Bu makalede Cenab Şehabeddin’in hikâyelerindeki temalar tespit edilmeye çalışılmış, baskın olan temanın aşk olması dolayısıyla sanatçının şiiri ve hikâyesi arasında aşk temasının nasıl işlendiğine dair bir mukayese yapılmıştır. Aşk, aile, evlilik gibi kadın-erkek ilişkilerine dayalı hikâyelerinin yanında hastalık ve vatan duygusunu işlediği hikâyeleri de vardır. Cenab Şehabeddin, dil ve estetik tutum açısından Servet-i Fünûn dönemi Türk hikâyeciliğinin doğrudan temsilcisi olmayı hak eder. Bu dönem dil ve edebiyat anlayışını hikâyesine taşıyan isim odur.
Psychological aspects of veterans' professional integration: challenges and strategies
Authors: Novokhatskyi Volodymyr
Published: March 2024

The full-scale war in Ukraine has led to the emergence of new challenges that were previously unknown to our society. One of these challenges is the professional integration of war veterans. Promoting the employment of war veterans should be a key part of the strategy of transition from military career to civilian life. Professional integration in the future will, on the one hand, contribute to the ability of war veterans to meet their needs and self-realise in various spheres of public life, and on the other hand, contribute to the restoration and development of Ukraine as a whole and a particular community in particular. The protracted nature of Russia's armed aggression is leading to an increase in the number of Ukrainian defenders who will soon have the status of "war veterans". Military operations are worsening demographic indicators, and the number of disabled people of working age is growing. These realities in Ukraine make it inevitable that there will be significant losses of labour force and a deterioration in its quality. The article explores the complex psychological aspects that arise in the process of professional integration of war veterans. It examines the key challenges that veterans face when returning to civilian life and the labour market, and suggests strategies and approaches to overcome these obstacles. The authors analyse the psychological consequences of military service and the impact of stressful situations on veterans' mental health. They consider the issue of adaptation to new living conditions, including changes in work, social interactions and family relationships. In addition, the article highlights the importance of psychological support and psychotherapeutic methods for veterans during the transition to civilian life. It suggests various strategies that contribute to successful integration, such as vocational training, psychological counselling and social support. The article aims to raise awareness and understanding of the psychological challenges faced by war veterans during professional integration and provide specific recommendations for their successful overcoming.
Dobro wspólne w nauczaniu papieży Jana Pawła II i Franciszka a wybrane aspekty teorii ekonomii
Authors: Horodecka Anna , Żuk Andrzej Jakub
Published: March 2024

Głównym celem artykułu jest przedstawienie, porównanie i ocena współczesnych koncepcji dobra wspólnego sformułowanych przez ekonomistów w odniesieniu do rozumienia dobra wspólnego przez papieży Jana Pawła II i Franciszka. Intencją autorów niniejszego opracowania jest zatem wniesienie wkładu w toczącą się dyskusję na temat dobra wspólnego poprzez przedstawienie interdyscyplinarnej perspektywy integrującej tradycje katolickiej nauki społecznej ze współczesnymi koncepcjami ekonomicznymi, wzbogacając tym samym rozumienie kategorii dobra wspólnego w teorii ekonomii.Artykuł podkreśla tendencję teorii ekonomii w kierunku jednowymiarowych i relatywistycznych koncepcji dobra wspólnego oraz sugeruje poszukiwanie jednocześnie dwuwymiarowych i uniwersalistycznych ekonomicznych idei dobra wspólnego. Uznaje osiągnięcia papieży Jana Pawła II i Franciszka w pogłębianiu zrozumienia kategorii dobra wspólnego i zakłada, że nauczanie to może służyć jako inspiracja badawcza dla ekonomistów. Praca ukazuje także, w jaki sposób kategoria dobra wspólnego skłania do przewartościowania i umożliwia modyfikację podstawowych założeń teorii ekonomii, takich jak homo oeconomicus czy rozumienie racjonalności.
Performance Analysis of Random Forest on Quartile Classification Journal
Authors: Sucahyo Cornaldo Beliarding , Rizqini Fajriwati Qoyyum , Naufal Ayyub , Yandratama Hengky , Shiddiqy Jabar Ash , Utama Agung Bella Putra , Putri Nastiti Susetyo Fanany , Wibawa Aji Prasetya
Published: March 2024

Journals play a pivotal role in disseminating scientific knowledge, housing a multitude of valuable research articles. In this digital age, the evaluation of journals and their quality is essential. The SCImago Journal Rank (SJR) stands as one of the prominent platforms for ranking journals, categorizing them into five index classes: Q1, Q2, Q3, Q4, and NQ. Determining these index classes often relies on classification methodologies. This research, drawing inspiration from the Cross-Industry Standard Process for Data Mining (CRISP-DM), seeks to employ the Random Forest method to classify journals, thus contributing to the refinement of journal ranking processes. Random Forest stands out as a robust choice due to its remarkable ability to mitigate overfitting, a common challenge in machine learning classification tasks. In the context of approximating SJR index classes, Random Forest, when utilizing the Gini index, exhibits promise, albeit with an initial accuracy rate of 62.12%. The Gini index, an impurity measure, enables Random Forest to make informed decisions while classifying journals into their respective SJR index classes. However, it is worth noting that this accuracy rate represents a starting point, and further refinement and feature engineering may enhance the model's performance. This research underscores the significance of machine learning techniques in the domain of journal classification and journal-ranking systems. By harnessing the power of Random Forest, this study aims to facilitate more accurate and efficient categorization of journals, thereby aiding researchers, academics, and institutions in identifying and accessing high-quality scientific literature.
Privacy-aware quantum convolutional neural network for blockchain-based IoT health care data
Authors: Jagdale Balaso , Sugave Shounak Rushikesh , Kulkarni Yogesh R. , Gutte Vitthal
Published: March 2024

Nowadays, the Internet of Things (IoT) is widely used in many applications, including healthcare to monitor the health condition of patients. However, it faces privacy and security issues due to the massive growth of hacking systems that provide illegal access to confidential health information. Blockchain (BC) is applied in IoT healthcare systems to manage healthcare data securely by using transparency features. In this research, a novel CAViaR Jellyfish Swarm Optimization enabled Quantum Convolutional Neural Network (CJSO-QCNN) is developed for the removal of noise in a privacy-aware BC-based IoT healthcare system. The CJSO is the combination of Conditional Autoregressive Value at Risk (CAViaR) and Jellyfish Search Optimizer (JSO). The data privacy is ensured according to the user preference by the service provider. The data is classified initially for identifying the sensitive data and is allowed for the treatment of noise, which is then stored in BC. Later, the user accesses the data by removing the noise using the CJSO-QCNN model. The valid data credentials are stored at the service provider according to user preferences. In addition, the superiority of the designed model is computed by comparing the performance with other prevailing approaches. The experimental results revealed that the CJSO-QCNN attained a maximum accuracy of 88.79%, a True Positive Rate (TPR) of 88.20%, and a True Negative Rate (TNR) of 88.61%.
Brain Age Is Associated with Cognitive Outcomes of Cholinesterase Inhibitor Treatment in Patients with Mild Cognitive Impairment
Authors: Tseng Wen-Yih Isaac , Hsu Yung-Chin , Huang Li-Kai , Hong Chien-Tai , Lu Yueh-Hsun , Chen Jia-Hung , Fu Chin-Kun , Chan Lung
Published: March 2024

Background:

The effect of cholinesterase inhibitor (ChEI) on mild cognitive impairment (MCI) is controversial. Brain age has been shown to predict Alzheimer’s disease conversion from MCI.

Objective:

The study aimed to show that brain age is related to cognitive outcomes of ChEI treatment in MCI.

Methods:

Brain MRI, the Clinical Dementia Rating (CDR) and Mini-Mental State Exam (MMSE) scores were retrospectively retrieved from a ChEI treatment database. Patients who presented baseline CDR of 0.5 and received ChEI treatment for at least 2 years were selected. Patients with stationary or improved cognition as verified by the CDR and MMSE were categorized to the ChEI-responsive group, and those with worsened cognition were assigned to the ChEI-unresponsive group. A gray matter brain age model was built with a machine learning algorithm by training T1-weighted MRI data of 362 healthy participants. The model was applied to each patient to compute predicted age difference (PAD), i.e. the difference between brain age and chronological age. The PADs were compared between the two groups.

Results:

58 patients were found to fit the ChEI-responsive criteria in the patient data, and 58 matched patients that fit the ChEI-unresponsive criteria were compared. ChEI-unresponsive patients showed significantly larger PAD than ChEI-responsive patients (8.44±8.78 years versus 3.87±9.02 years, p = 0.0067).

Conclusions:

Gray matter brain age is associated with cognitive outcomes after 2 years of ChEI treatment in patients with the CDR of 0.5. It might facilitate the clinical trials of novel therapeutics for MCI.
2024 United States Elections: Air Pollution, Neurodegeneration, Neuropsychiatric, and Neurodevelopmental Disorders. Who Cares?
Authors: Calderón-Garcidueñas Lilian , Ayala Alberto , Mukherjee Partha S.
Published: March 2024

Air pollution exposures ought to be of significant interest for the United States (US) public as health issues will play a role in the 2024 elections. Citizens are not aware of the harmful brain impact of exposures to ubiquitous anthropogenic combustion emissions and friction-derived nanoparticles, industrial nanoplastics, the growing risk of wildfires, and the smoke plumes of soot. Ample consideration of pediatric and early adulthood hallmarks of Alzheimer’s disease, Parkinson’s disease, frontotemporal lobar degeneration, and amyotrophic lateral sclerosis and associations with neuropsychiatric and neurodevelopmental disorders in the process of setting, reviewing, and implementing standards for particulate matter (PM)2.5, ultrafine PM, and industrial nanoparticles must be of interest to US citizens.
Utilizing deep learning models for the identification of enhancers and super-enhancers based on genomic and epigenomic features
Authors: Ahani Zahra , Shahiki Tash Moein , Ledo Mezquita Yoel , Angel Jason
Published: March 2024

Super-enhancers are a category of active super-enhancers densely occupied by transcription factors and chromatin regulators, controlling the expression of disease-related genes and cellular identity. Recent studies have demonstrated the formation of complex structures by various factors and super-enhancers, particularly in various cancers. However, our current knowledge of super-enhancers, such as their genomic locations, interaction with factors, functions, and distinction from other super-enhancers regions, remains limited. This research aims to employ deep learning techniques to detect and differentiate between super-enhancers and enhancers based on genomic and epigenomic features and compare the accuracy of the results with other machine learning methods In this study, in addition to evaluating algorithms, we trained a set of genomic and epigenomic features using a deep learning algorithm and the Python-based cross-platform software to detect super-enhancers in DNA sequences. We successfully predicted the presence of super-enhancers in the sequences with higher accuracy and precision.
On the explanation of COVID-19 blood test variables using fuzzy models
Authors: Téllez-Velázquez Arturo , Delice Pierre A. , Salgado-Leyva Rafael , Cruz-Barbosa Raúl
Published: March 2024

This paper performs an analysis comparing two evolutionary explainable fuzzy models that make inferences in a pipeline with a blood test data set for COVID-19 classification. Firstly, data is preprocessed by the following stages: cleaning, imputation and ranking feature selection. Later, we perform a comparative analysis between several clustering methods used in an Evolutionary Clustering-Structured Fuzzy Classifier (ECSFC) to solve this classification problem using the Differential Evolution (DE) algorithm. Complementarily, we find that the Fuzzy Decision Tree model produces similar performance when is tuned with the DE algorithm (EFDT). The obtained results show that, simpler models are easier to explain qualitatively, i.e., increasing the number of clusters in ECSFC model or the maximum depth of the tree in EFDT model, does not necessarily help to obtain simplified and accurate models. In addition, although the EFDT model is by itself an intuitively explainable model, the ECSFC, with the help of the proposed Weighted Stacked Features Plot, generates more intuitive models that allow not only highlighting the features and the linguistic terms that defines a patient with COVID-19, but also allows users to visualize in a single graph and in specific colors the analyzed classes.
CycleGAN generated pneumonia chest x-ray images: Evaluation with vision transformer
Authors: Lugo-Torres Gerardo , Valdez-Rodríguez José E. , Peralta-Rodríguez Diego A.
Published: March 2024

The use of generative models in image synthesis has become increasingly prevalent. Synthetic medical imaging data is of paramount importance, primarily because medical imaging data is scarce, costly, and encumbered by legal considerations pertaining to patient confidentiality. Synthetic medical images offer a potential answer to these issues. The predominant approaches primarily assess the quality of images and the degree of resemblance between these images and the original ones employed for their generation.The central idea of the work can be summarized in the question: Do the performance metrics of Frechet Inception Distance(FID) and Inception Score(IS) in the Cycle-consistent Generative Adversarial Networks (CycleGAN) model are adequate to determine how real a generated chest x-ray pneumonia image is? In this study, a CycleGAN model was employed to produce artificial images depicting 3 classes of chest x-ray pneumonia images: general(any type), bacterial, and viral pneumonia. The quality of the images were evaluated assessing and contrasting 3 criteria: performance metric of CycleGAN model, clinical assessment of respiratory experts and the results of classification of a visual transformer(ViT). The overall results showed that the evaluation metrics of the CycleGAN are insufficient to establish realism in generated medical images.
A novel multi-task TSK fuzzy system modeling method based on multi-task fuzzy clustering
Authors: Yao Ziyang
Published: March 2024

The traditional multi-task Takagi-Sugeno-Kang (TSK) fuzzy system modeling methods pay more attention to utilizing the inter-task correlation to learn the consequent parameters but ignore the importance of the antecedent parameters of the model. To this end, we propose a novel multi-task TSK fuzzy system modeling method based on multi-task fuzzy clustering. This method first proposes a novel multi-task fuzzy c-means clustering method that learns multiple specific clustering centers for each task and some common clustering centers for all tasks. Secondly, for the consequent parameters of the fuzzy system, the novel low-rank and row-sparse constraints are proposed to better implement multi-task learning. The experimental results demonstrate that the proposed model shows better performance compared with other existing methods.
Application of fuzzy prediction control model based on neural network in teaching resource recommendation and matching
Authors: Shao Shuai , Li Dongwei
Published: March 2024

As technology evolves, the allocation and use of educational resources becomes increasingly complex. Due to the many factors involved in recommending and matching English education resources, traditional predictive control models are no longer adequate. Therefore, fuzzy predictive control models based on neural networks have emerged. To increase the effectiveness and efficiency of using English educational resources (EER), this research aims to create a neural network-based fuzzy predictive control model (T-S-BPNN) for resource suggestion and matching. The results of the study show that the T-S-BPNN model α proposed in the study starts from 0 and increases sequentially by 0.1 up to 1, observing the change in MAE values. The experiment’s findings demonstrate that the value of MAE is lowest at values around 0.5. The T-S-BPNN model, on the other hand, gradually plateaued in its adaptation rate up to 7 runs, reaching about 9.8%. The accuracy rate peaked at 0.843 when the number of recommendations reached 7. The recall rate also peaked at 0.647 when the number of recommended English courses reached 7. The R-value for each set hovered around 0.97, which is a good fit. And the R-value of the training set is 0.97024, which can indicate that the T-S-BPNN model model proposed in the study fits well. It indicates that the algorithm proposed in the study is highly practical.
Advancing electric demand forecasting through the temporal fusion transformer model
Authors: Karthikeyan M. , Colak Ilhami , Sagar Imambi S. , Joselin Jeya Sheela J. , Nair Sruthi , Umarani B. , Alagusabai Andril , Suriyakrishnaan K. , Rajaram A.
Published: March 2024

This research paper introduces a cutting-edge approach to electric demand forecasting by incorporating the Temporal Fusion Transformer (TFT). As the landscape of demand forecasting becomes increasingly intricate, precise predictions are vital for effective energy management. To tackle this challenge, we leverage the sequential and temporal patterns in an extensive electric demand dataset spanning from 2003 to 2014. Our proposed Temporal Fusion Transformer model combines attention mechanisms with the transformer architecture, enabling it to adeptly capture intricate temporal dependencies. Thorough data preprocessing, including temporal embedding and external features, enhances prediction accuracy. Through rigorous evaluation, the TFT model surpasses existing forecasting techniques, showcasing its capacity for accurate, resilient, and adaptive predictions. This research contributes to the advancement of electric demand forecasting, harnessing the TFT’s capabilities to excel in capturing diverse temporal patterns. The findings hold the potential to enhance energy management and support decision-making in the energy sector, bridging the gap between innovation and practical utility.
Dynamic task scheduling in edge cloud systems using deep recurrent neural networks and environment learning approaches
Authors: Ammavasai S.K.
Published: March 2024

The rapid growth of the cloud computing landscape has created significant challenges in managing the escalating volume of data and diverse resources within the cloud environment, catering to a broad spectrum of users ranging from individuals to large corporations. Ineffectual resource allocation in cloud systems poses a threat to overall performance, necessitating the equitable distribution of resources among stakeholders to ensure profitability and customer satisfaction. This paper addresses the critical issue of resource management in cloud computing through the introduction of a Dynamic Task Scheduling with Virtual Machine allocation (DTS-VM) strategy, incorporating Edge-Cloud computing for the Internet of Things (IoT). The proposed approach begins by employing a Recurrent Neural Network (RNN) algorithm to classify user tasks into Low Priority, Mid Priority, and High Priority categories. Tasks are then assigned to Edge nodes based on their priority, optimizing efficiency through the application of the Spotted Hyena Optimization (SHO) algorithm for selecting the most suitable edge node. To address potential overloads on the edge, a Fuzzy approach evaluates offloading decisions using multiple metrics. Finally, optimal Virtual Machine allocation is achieved through the application of the Stable Matching algorithm. The seamless integration of these components ensures a dynamic and efficient allocation of resources, preventing the prolonged withholding of customer requests due to the absence of essential resources. The proposed system aims to enhance overall cloud system performance and user satisfaction while maintaining organizational profitability. The effectiveness of the DTS-VM strategy is validated through comprehensive testing and evaluation, showcasing its potential to address the challenges posed by the diverse and expanding cloud computing landscape.
RETRACTED: Optimizing deep learning-based intrusion detection in cloud computing environment with chaotic tunicate swarm algorithm
Authors: Jansi Sophia Mary C. , Mahalakshmi K.
Published: March 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Treatment Approaches for Altered Facial Expression: A Systematic Review in Facioscapulohumeral Muscular Dystrophy and Other Neurological Diseases
Authors: Rasing Nathaniël B. , van de Geest-Buit Willianne A. , Chan On Ying A. , Mul Karlien , Lanser Anke , van Engelen Baziel G.M. , Erasmus Corrie E. , Fischer Agneta H. , Ingels Koen J.A.O. , Post Bart , Siemann Ietske , Groothuis Jan T. , Voermans Nicol C.
Published: March 2024

Background:

Facial weakness is a key feature of facioscapulohumeral muscular dystrophy (FSHD) and may lead to altered facial expression and subsequent psychosocial impairment. There is no cure and supportive treatments focus on optimizing physical fitness and compensation of functional disabilities.

Objective:

We hypothesize that symptomatic treatment options and psychosocial interventions for other neurological diseases with altered facial expression could be applicable to FSHD. Therefore, the aim of this review is to collect symptomatic treatment approaches that target facial muscle function and psychosocial interventions in various neurological diseases with altered facial expression in order to discuss the applicability to FSHD.

Methods:

A systematic search was performed. Selected studies had to include FSHD, Bell’s palsy, Moebius syndrome, myotonic dystrophy type 1, or Parkinson’s disease and treatment options which target altered facial expression. Data was extracted for study and patients’ characteristics, outcome assessment tools, treatment, outcome of facial expression and or psychosocial functioning.

Results:

Forty studies met the inclusion criteria, of which only three studies included FSHD patients exclusively. Most, twenty-one, studies were performed in patients with Bell’s palsy. Studies included twelve different therapy categories and results were assessed with different outcomes measures.

Conclusions:

Five therapy categories were considered applicable to FSHD: training of (non-verbal) communication compensation strategies, speech training, physical therapy, conference attendance, and smile restoration surgery. Further research is needed to establish the effect of these therapies in FSHD. We recommend to include outcome measures in these studies that cover at least cosmetic, functional, communication, and quality of life domains.
Reduced Thickness of the Retina in de novo Parkinson’s Disease Shows A Distinct Pattern, Different from Glaucoma
Authors: Chrysou Asterios , Heikka Tuomas , van der Zee Sygrid , Boertien Jeffrey M. , Jansonius Nomdo M. , van Laar Teus
Published: March 2024

Background:

Parkinson’s disease (PD) patients experience visual symptoms and retinal degeneration. Studies using optical coherence tomography (OCT) have shown reduced thickness of the retina in PD, also a key characteristic of glaucoma.

Objective:

To identify the presence and pattern of retinal changes in de novo, treatment-naive PD patients compared to healthy controls (HC) and early primary open angle glaucoma (POAG) patients.

Methods:

Macular OCT data (10×10 mm) were collected from HC, PD, and early POAG patients, at the University Medical Center Groningen. Bayesian informative hypotheses statistical analyses were carried out comparing HC, PD-, and POAG patients, within each retinal cell layer.

Results:

In total 100 HC, 121 PD, and 78 POAG patients were included. We showed significant reduced thickness of the inner plexiform layer and retinal pigment epithelium in PD compared to HC. POAG patients presented with a significantly thinner retinal nerve fiber layer, ganglion cell layer, inner plexiform layer, outer plexiform layer, and outer photoreceptor and subretinal virtual space compared to PD. Only the outer segment layer and retinal pigment epithelium were significantly thinner in PD compared to POAG.

Conclusions:

De novo PD patients show reduced thickness of the retina compared to HC, especially of the inner plexiform layer, which differs significantly from POAG, showing a more extensive and widespread pattern of reduced thickness across layers. OCT is a useful tool to detect retinal changes in de novo PD, but its specificity versus other neurodegenerative disorders has to be established.
Opportunities and Pitfalls of REM Sleep Behavior Disorder and Olfactory Dysfunction as Early Markers in Parkinson’s Disease
Authors: Orso Beatrice , Brosse Sarah , Frasnelli Johannes , Arnaldi Dario
Published: March 2024

During its pre-motor stage, Parkinson’s disease (PD) presents itself with a multitude of non-motor symptoms with different degrees of specificity and sensitivity. The most important among them are REM sleep behavior disorder (RBD) and olfactory dysfunction. RBD is a parasomnia characterized by the loss of REM sleep muscle atonia and dream-enacting behaviors. Olfactory dysfunction in individuals with prodromal PD is usually described as hyposmia (reduced sense of smell) or anosmia (complete loss of olfactory function). These symptoms can precede the full expression of motor symptoms by decades. A close comprehension of these symptoms and the underlying mechanisms may enable early screening as well as interventions to improve patients’ quality of life. Therefore, these symptoms have unmatched potential for identifying PD patients in prodromal stages, not only allowing early diagnosis but potentially opening a window for early, possibly disease-modifying intervention. However, they come with certain challenges. This review addresses some of the key opportunities and pitfalls of both RBD and olfactory dysfunction as early markers of PD.
Research on neural networks in computer network security evaluation and prediction methods
Authors: Wei Hanyu , Zhao Xu , Shi Baolan
Published: March 2024

Anomaly detection in networks to identify intrusions is a common and successful security measure used in many different types of network infrastructure. Network data traffic has increased due to the proliferation of viruses and other forms of cyber-attacks as network technology and applications have developed quickly. The limitations of classical intrusion detection, such as poor detection accuracy, high false negatives, and dependence on dimensionality reduction methods, become more apparent in the face of massive traffic volumes and characteristic information. That’s why IoT infrastructures often use Software-Defined Networking (SDN), allowing for better network adaptability and control. Hence, this paper’s convolutional neural network-based Security Evaluation Model (CNN-SEM) is proposed to secure the source SDN controller from traffic degradation and protect the source network from DDoS assaults. The proposed CNN-SEM system might defend against DDoS assaults once discovered by applying and testing a Convolutional Neural Network (CNN). The model can automatically extract the useful aspects of incursion samples, allowing for precise classification of such data. The detection and mitigation modules evaluate the proposed SDN security system’s performance, and the findings showed promise against next-generation DDoS assaults. The experimental results show the CNN-SEM achieves a high accuracy ratio of 96.6%, a detection ratio of 97.1%, precision ratio of 97.2%, a performance ratio of 95.1% and an enhanced security rate of 98.1% compared to other methods.
Determinantes de los datos abiertos a nivel países: un modelo de panel de datos
Authors: Alderete María Verónica
Published: March 2024

Este trabajo se enmarca en el paradigma de gobierno abierto cuyo objetivo consiste en empoderar a la ciudadanía a partir de la apertura de datos de carácter público y promover su participación en la toma de decisiones. Por ese motivo, este estudio analiza los factores que contribuyen a explicar la apertura de datos a nivel países desde una metodología cuantitativa. Con este fin, se emplea un modelo de panel de datos para 27 países del mundo correspondiente al período 2014-2017. Los resultados obtenidos sugieren que a mayor PBI per cápita, mayor desarrollo en Tecnologías de la Información y Comunicación, y mayor nivel de empleo, mayor es la apertura de datos de un país.
Student Perspectives of Global Citizenship within a Virtual Exchange
Authors: Weaver Gregory
Published: March 2024

Higher education internationalization has become an increasingly challenging endeavor. The outbreak of the COVID-19 virus and the ever-changing landscape of immigration policies have called for a need to reexamine how universities internationalize. Transnational virtual classrooms or virtual exchanges have been shown to provide students with a more equal opportunity to develop their global competencies and cultural skills than study abroad. Traditional internationalization methods may no longer be as effective as they have been in the past, creating a need to reconceptualize how we educate college students for global competencies. This research in-progress summarizes a portion of a dissertation. The aim of this qualitative study is to investigate global citizenship student awareness in a virtual exchange. This study presents preliminary findings of their experiences; applied global citizenship and virtual exchange as a channel.
Lord Krishna as a Deconstructionist Teacher in the Bhagavadgita
Authors: Kamali Hari
Published: March 2024

The Gita, a classic of Hinduism, has been studied over different periods and perspectives. In this study, the Gita was studied as a pedagogical text and analyzed founded on the theory of deconstruction vis-à-vis postmethod pedagogy. It was discovered that, as a teacher, Lord Krishna used deconstruction in his pedagogy, so he was identified as a deconstructionist teacher. Then, this role of a teacher was further discussed with reference to the role of a teacher in postmethod pedagogy and concluded that deconstructionist is the most significant role of a teacher in postmethod pedagogy. Thus, this study claims that if teachers play the role of a deconstructionist teacher in pedagogy, quality in education can be ascertained.
Movilidad Estudiantil Después del Covid-19: La Percepción de las Personas a Cargo de la Internacionalización en Seis Instituciones de Educación Superior Mexicanas
Authors: Cortes-Velasco Christian , Maldonado-Maldonado Alma
Published: March 2024

Como hecho social disruptivo, la pandemia por covid-19 obligó a adaptar las principales actividades de las instituciones de educación superior (IES), entre ellas se destaca la movilidad estudiantil como una de las estrategias más visibles de internacionalización. Los cambios que buscaron responder al encierro por la pandemia plantearon escenarios que, con el retorno a lo presencial, es posible valorar en cuanto a su influencia a largo plazo en las IES. Este artículo responde a la necesidad de documentar las modificaciones que se hicieron durante la pandemia y que persisten en el retorno a los planteles educativos en materia de movilidad estudiantil, particularmente sobre la función de las experiencias educativas internacionales virtuales y de la forma en que coexisten con la movilidad estudiantil física. Se condujeron entrevistas semiestructuradas a funcionarios con una participación clave en la gestión de la movilidad estudiantil (y la internacionalización) durante la pandemia. Los funcionarios pertenecen a seis IES—tres públicas y tres privadas—que se caracterizan por tener un volumen considerable de movilidad estudiantil. Se analiza lo que se llamó “movilidad virtual” y su pertinencia para describir los cambios experimentados. Además, se discute sobre los procesos de adaptación y la forma en que las IES integran la virtualidad como un medio más de internacionalización que complementa, pero no sustituye, la movilidad estudiantil física.
ФОРМИ ТА МЕТОДИ ДІЯЛЬНОСТІ ОРГАНІВ МІСЦЕВОГО САМОВРЯДУВАННЯ В УКРАЇНІ
Authors: БАСКО Андрій
Published: March 2024

У статті застосовано науково-методологічний підхід до аналізу форм та методів діяльності органів місцевого самоврядування. Визначено, що в сучасній Україні впровадження та розвиток форм та методів діяльності органів місцевого самоврядування має здійснюватись з урахуванням найкращих практик децентралізації в країнах ЄС, які проходили схожий з Україною шлях до євроінтеграції. Метою статті є комплексний аналіз форм та методів діяльності органів місцевого самоврядування з огляду на процеси децентралізації; виокремлення проблемних напрямків їх реалізації та обґрунтування дієвих способів їх удосконалення. Методологічну основу дослідження складає діалектичний метод, застосування якого дозволило всебічно розкрити природу форм та методів діяльності органів місцевого самоврядування. Наукова новизна. Доведено, що слід виокремлювати такі форми управлінської діяльності органів місцевого самоврядування: правотворча діяльність, пов’язана з виданням нормативно-правових актів; правозастосовна діяльність, пов’язана з виданням ненормативних (індивідуально-розпорядчих) правових актів; укладення адміністративних договорів; здійснення публічних закупівель; надання адміністративних послуг; організаційна та матеріально-технічна діяльність; здійснення внутрішнього адміністративного контролю за діяльністю органів та посадових осіб місцевого самоврядування. Висновки. Доведено, що найбільш ефективним способом забезпечення законності управлінської діяльності органів місцевого самоврядування має стати надання головам місцевих державних адміністрацій права зупиняти дію правових актів органів місцевого самоврядування з одночасним зверненням до адміністративних судів з позовами про визнання їх незаконними, крім того, з метою забезпечення відкритості діяльності органів місцевого самоврядування запропоновано запровадити обов’язкову повідомну державну реєстрацію нормативно-правових актів органів місцевого самоврядування.
ПРАВОВЕ РЕГУЛЮВАННЯ КРИПТОВАЛЮТИ
Authors: КРИШТАЛЬ Галина , ВАСИЛЬКОНОВА Еліна , БРЮХОВЕЦЬКА Ірина
Published: March 2024

У статті розглянуто правове регулювання операцій з криптовалютою, яка функціонує за допомогою блокчейн-технології. Визначено, що технологія блокчейн не лише революціонізує фінансові сфери, але і має потенціал змінити підходи до управління даними, кібербезпеки, логістики, медицини та інших галузей. Заснована на принципах децентралізації та безпеки, вона відкриває нові можливості для оптимізації бізнес-процесів та забезпечення прозорості в інших секторах суспільства. Мета роботи. Полягає в глибокому вивченні сутності криптовалют за допомогою аналізу міжнародного досвіду щодо їхнього правового регулювання. Окрім того, робота націлена на розробку конкретних пропозицій та перспектив для подальшого розвитку правового регулювання криптовалют в Україні. Наукова новизна. Зазначено, що розвиток та розширення застосування блокчейн-технології в Україні свідчать про стрімкий процес адаптації до цифрового віку та визначають країну як перспективного учасника глобального інноваційного руху. Доведено, що поза фінансовим сектором технологія блокчейну може служити як ефективний інструмент для платформ голосування та управління документами та титулами, що може сприяти вдосконаленню процесів демократії та адміністрування. Зазначено, що Україна, будучи підтримувачем цифрових інновацій, вже впроваджує блокчейн у державних сферах, таких як СЕТАМ та державний земельний кадастр. Однак, головним застосуванням блокчейну в Україні в громадській сфері наразі є криптовалютний ринок, який регулюється Законом України «Про віртуальні активи». Методи та методологія. У ході дослідження були використані такі методи, як аналіз та синтез, методи історичного та логічного моделювання. Також були застосовані теоретичні підходи, зокрема метод формалізації та метод «від абстрактного до конкретного». Результати. У запропонованій статті особливу увагу приділено аналізу аспектів практичного застосування правового механізму ринку криптовалют. Висновки. Національне законодавство щодо регулювання криптовалютного ринку в Україні потребує удосконалення. Це може включати в себе впровадження системи оподаткування для криптовалюти та визначення чіткого правового статусу для цього виду цифрових активів. Важливо також визначити алгоритм дій для здійснення операцій з криптовалютами та встановити прозорі правила для їх регулювання. Створення спеціальних регуляторних органів, які спеціалізуються у справах цифрових валют, може сприяти більш ефективному нагляду за галуззю. Ці органи можуть відповідати за консультування користувачів, видачу ліцензій та контроль за процесами, пов'язаними з використанням криптовалют, включаючи попередження відмивання грошей.