bluuebunny/crossref_metadata_2025 huggingface dataset:
TRANSPOSITION IN THE UKRAINIAN-LANGUAGE REPRODUCTION OF ENGLISH TEXTS (BASED ON THE MATERIAL OF INTERNATIONAL LAW DOCUMENTS
Authors: Kuzmina Valeriia , Baklazhenko Yuliia
Published: December 2023

The article is devoted to consideration of the issue of transposition in the Ukrainian-language reproduction of texts in the international legal sphere. The research is conducted in two stages. During the first stage, the importance of translating international legal documents into Ukrainian is defined. The main requirement for the translation of texts in the international legal sphere is also defined, namely: to accurately convey the content of legal documents in the target language. It is found that the translation of international legal documents is an integral component of the development and improvement of the Ukrainian terminological system in the international legal sphere. It is established that Ukrainian linguists deeply study the English-language terminology of the legal sphere because of the development of the legal system in English-speaking countries. Definitions of the concepts “international law” and “international legal documents” and their categories and types are also characterized. It is clarified that international legal documents have legal force, therefore the definition of the concept of “legal documents” and their features are also defined: the definitions of legal terms are not always fixed in lexicographic sources, for the terms of the legal sphere, the division into inter-branch and intra-branch terms is unacceptable, legal terms can be used not only in a professional context, but also in everyday communication. During the second stage, the concepts of affixation and conversion are analyzed. The main components of affixation are also found out. Additionally, the definition of the concept of “transposition”, its levels (complete or morphological and incomplete or syntactic), as well as its classification, are presented. It is also found that transposition has three components: the transposed, the transpositor, and the transpose. 10 types of transposition are presented: substantivation, verbalization, adjectivization, pronominalization, prepositionalization, numeralization, adverbialization, conjunctionalization, particulation, and internalization. 10 sentences of the English-language text from the European Convention on Human Rights and their Ukrainian translation are analyzed and classified according to 7 types of transposition: substantivation, verbalization, adjectiveization, pronominalization, prepositionalization, adverbialization, and particulation. During the analysis of examples of translation by means of numeralization, conjunctionalization and internalization in the texts of the European Convention on Human Rights, no examples are found. The research material is the European Convention on Human Rights [7], [8] and the scientific work of E. Koval, 2020 [9].
ТHE STRUCTURAL AND SEMANTIC FEATURES OF NATO OFFICIAL DOCUMENTS TERMINOLOGY FROM THE TRANSLATION PERSPECTIVE
Authors: Borbenchuk Iryna , Severyna Halyna , Maevska Margarita
Published: December 2023

The article focuses on the study of the English terminology used in the official documentation of NATO and seeks to investigate the specific nature of its translation into the Ukrainian language. It is determined that the NATO Standardization Agency administrates the dissemination of statutes, standards, and doctrines to facilitate effective interaction and cooperation among allies. A notable characteristic of official documents resides in their connection to international law, thereby necessitating imperative precision in translation, standardized recording, and legal implementation. The NATO terminology system comprises terms and abbreviations, along with data (comments, examples, cross-references), and metadata (acceptability rating, source, approval date). It is established that the successful use of such documentation in Ukraine is contingent upon the adaptation of military terminology to align with the linguistic and cultural nuances of the Ukrainian context. The structural-semantic analysis provided in the research reveals the main translation models for terms as well as the parts of speech forming the structural models. The conducted research demonstrates that multi-component military terms from NATO official documents tend to be translated with equivalent prepositional attributive phrases by rearranging components and employing functional substitution, namely through loan translation. The investigation uncovers that the translation of military terminology predominantly employs descriptive methods, word-for-word translation, transliteration, transcription, and semantic translation, aimed at conveying the content of English-language terms. It is worth noting that military-related texts comprise abbreviations and acronyms necessitating precise explication and even decryption, given their informational significance, which cannot be replicated verbatim in the translated language. The results confirm that the translation of military terminology in NATO official documents necessitates the utilization of specialized military terms and calls for advancements in the standardization and unification of the termbase for adequate translation.
Investigation of the Difference Between Ordinary and FSI Numerical Solution for Flutter of Tandem Compressor
Authors: Benis Alireza Sekhavat , Togh Reza Aghaei
Published: December 2023

This research aims to analyze and compare the flutter of turbine compressor blades from experimental, numerical, and fluid structure interaction (FSI) derived data. The results proved that the FSI solution results are closer to the experimental results. A reduced velocity parameter of 5 can be regarded as the flutter boundary in the bending flutter. Additionally, the incidence angle parameter equal to 1.5 can be characterized as the torsional flutter boundary. Tandem leads to strengthening the load applied on the compressor blades, reducing the number of compressor stages, and ultimately reducing the weight of the engine. Adding tandem to the rotor increases the vibration bending frequency by a factor of 2. Increasing the compressor velocity caused the FSI vibration frequency to be close to the experimental results. It was found that the vibration range of the main rotor is greater than that of the tandem. The vibration of the rotor and the tandem is damped for approximately 0.1 s to reach a constant frequency.
Structure Research of Resistance Shunt Type Piezoelectric Composite and Underwater Sound Absorption Performance Analysis
Authors: Sun Yang , Hua Bo
Published: December 2023

The high-efficiency sound absorption of underwater sound-absorbing materials under "low frequency" and "wide frequency" conditions has become a hot topic in current research. Underwater semi-active sound absorption can help to improve low frequency sound absorption performance by designing the structure of the piezoelectric composite and the shunt circuits, and it is also advantageous due to its simplicity, compactness, ease of installation, low cost, and high stability. In this paper, a kind of resistance shunt type piezoelectric composite is designed, and its underwater sound absorption performance is analyzed. Theoretical analytical formulas and finite element numerical calculation are used to calculate the electro-elastic constants of the piezoelectric composite. The theoretical model based on the Mason equivalent circuit and transfer matrix theory is used to calculate the sound absorption coefficient. Through the study of 0-3 and 1-3 composites used in the existing research work, it was found that the piezoelectric composite which is suitable for resistance shunt type underwater semi-active sound absorption should have a low longitudinal wave velocity and high electromechanical conversion coefficient. According to this design objective, the structure of the piezoelectric composite has been gradually modified, and finally it is determined that the sparse oblique 2-1-3 composite is an appropriate type of piezoelectric composite. Theoretical calculations and simulation experimental measurement verifies that when the inclination angle is 21 deg and the shunt resistance is 10 kOhm or the inclination angle is 24 deg and the shunt resistance is 10 kOhm, the sound absorption coefficient within the low frequency band 1--3~kHz can be significantly improved.
A TEOLOGIA FEMINISTA LATINO-AMERICANA: NOVOS SUJEITOS E NOVAS POSTURAS EPISTEMOLÓGICAS
Authors: Serrato Andreia Cristina , Candiotto Jaci de Fátima Souza
Published: December 2023

A produção teológica feminista latino-americana foi inicialmente desenvolvida a partir das vivências das mulheres, sobretudo, de suas experiências de invisibilidade, exploração, exclusão e empobrecimento e situada no horizonte da teologia da libertação. Os objetivos foram ampliados, à medida em que a sensibilidade e atenção ao cotidiano confrontam-se com o sexismo, o racismo, o fundamentalismo e o conservadorismo. O objetivo deste artigo é destacar deslocamentos epistemológicos que caracterizam a produção teológica realizada por mulheres nesse contexto, além de identificar as características dessa produção e sua contribuição para o protagonismo das mulheres no campo teológico. A participação delas na teologia tem contribuído para evidenciar a necessidade de justiça social de gênero e fortalecer a luta contra formas de discriminação e opressão presentes nas práticas religiosas e na sociedade em geral. A mulher como sujeito de produção teológica, no contexto da América Latina, tem ampliado seu método diante dos desafios que os novos contornos vivenciais tecem.
PALAVRAS-CHAVE: Teologia. Gênero. Mulheres.
Reseña del texto: Branko Milanovic (2018). Global inequality
Authors: Franco Martínez J. Agustin
Published: December 2023

Texto: Branko Milanovic (2018). Global inequality. A new approach for the age of globalization. Harvard University Press, 320 pp., ISBN: 978-06-749-8403-5
Reseña realizada por Dr. J. Agustín Franco Martínez, Universidad de Extremadura.
Dirección de contacto: franco@unex.es
FORMATION OF EMOTIONAL INTELLIGENCE IN THE PROCESS OF PREPARATION OF FUTURE SOCIAL PROFESSIONALS IN HIGHER EDUCATION INSTITUTIONS
Authors: Грень Лариса , Kirsanov Ivan
Published: December 2023

Abstract: the article emphasizes the importance of the role of education as one of the main components of supporting the transition period of Ukraine on the way to the EU and NATO; it has been proven that the formation of a new philosophy of higher education is simultaneously connected with emotional intelligence, which is of great importance in the training of future specialists in the social sphere in institutions of higher education. It was determined that the state and development of the modern Ukrainian economy depends on the quality of personnel training provided by universities. It was found that the lack of management culture, the insufficient level of moral and ethical training of specialists in the social sphere and qualified specialists in the field of professional ethics is an obstacle to the creation of an emotional and ethical infrastructure in Ukraine. The opinion is substantiated that the wide application of active learning methods with the analysis of real and educational business situations and the regular professional practice of future specialists in the social sphere at enterprises, firms, state authorities and local governments will ensure the effectiveness of the training of specialists in the social sphere, will contribute to the formation and development of ethical norms and emotional intelligence.
RESOURCES FOR ADAPTATION TO LEARNING STUDENTS – FUTURE BACHELORS OF MECHANICAL ENGINEERING IN THE CURRENT EDUCATIONAL CONDITIONS
Authors: Kravtsova Nataliia
Published: December 2023

Abstract: the article explores the impact of martial law on the self-educational activities of students – future bachelors of mechanical engineering specialities in higher education institutions. The necessity of increasing the internal resources of students for their effective adaptation to the crisis and unpredictable changes in the educational environment and related stress factors is substantiated. The arguments for determining the psychological well-being of students by means of effective stress management and effective learning in stressful situations and uncertainty are validated. The article presents the results of a pedagogical experiment aimed at determining the relationship between the psychological well-being of future bachelors of mechanical engineering specialities and their self-educational activities in the current educational environment. The importance of independent cognitive activity of mechanical engineering students is emphasised, which focusses on the ability to withstand challenges both in the educational environment and in the extracurricular life of students, which positively affects the level of their psychological well-being.
İslam Aile Hukukunda Boşama Yetkisinin Mahkemeye Devri Meselesinin Tarihi, Siyasi/Fikri ve Sosyolojik Arka Planı
Authors: KÜÇÜKTİRYAKİ Ahmet Yasin
Published: December 2023

İslam aile hukukunda evlilik birliği farklı şekillerde sonlandırılabilmektedir. Kadının da istemediği evliliği sona erdirebilmesi için bir takım yollar mevcut olsa da en yaygın şekilde karşılaşılan bir yöntem olan talak ile nikâh bağını çözebilme yetkisi İslam aile hukukunda yerleşik bir kural olarak kocaya aittir. Kocaya ait olan bu yetkinin usulsüz kullanımıyla ortaya çıkan ve özellikle kadının mağduriyeti ile sonuçlanabilen bir takım problemler sebebiyle talak yetkisinin kocadan tamamen alınarak aile mahkemelerine devredilip devredilmeyeceği konusu gündeme gelmiş ve İslam hukukçular arasında değerlendirilmeye başlanmıştır. Bu çalışmada bahse konu meselenin fıkhi değerlendirmesinden sarf-ı nazarla sadece hangi siyasi ve sosyolojik sebeplerle ne zaman ve nasıl ortaya çıktığını tespit etmeye çalışacağız.
"Kur'ân'ın Anlamı ve Tefsiri" Adlı Eserin Yöntem ve Muhteva Açısından İncelenmesi
Authors: ŞAHİN AYNUR Hatice , KARA Mustafa
Published: December 2023

Bu makalede Prof. Dr. İsmail Karagöz tarafından kaleme alınan “Kur’ân’ın Anlamı ve Tefsiri” isimli eser ele alınmaktadır. Çalışmanın amacı, bu eseri yöntem ve muhteva açısından -ana hatlarıyla- incelemektir. Çalışma, “Kur’ân’ın Anlamı ve Tefsiri” adlı eserle sınırlı tutulmuştur. Bugüne dek söz konusu tefsirle ilgili herhangi bir bilimsel çalışma yapılmamış olması, makale-nin hem önemini hem de özgünlüğünü ortaya koymaktadır. Makale literatür taramasına dayanmaktadır. Sekiz ciltten oluşan bu eser, Kur’ân’ın baştan sona tefsirini içermektedir. Eserde Kur’ân’ın Kur’ân’la, sünnetle ve sahabe kavliyle tefsirine önem verilmiştir. Rivayet tefsirinden ziyade dirayet yönü ağır basan bu eserde yöntem ve muhteva açısından en dikkat geçen özellik, Kur’ân’ın Kur’ân’la tefsiridir. Bu doğrultuda müellif, her bir ayeti açıklamak için diğer ayetlere ve sünnete atıfta bulunmaktadır. Ayrıca lafızların izahında lügat, sarf ve nahiv çerçevesinde tahliller yapmakta ve yeri geldikçe fıkhî hükümlere de değinmektedir.
ASPECT EXTRACTION IN E-COMMERCE USING LATENT DIRICHLET ALLOCATION (LDA) WITH TERM FREQUENCY-INVERSE DOCUMENT FREQUENCY (TF-IDF)
Authors: Nugroho Satyawan Agung , Bachtiar Fitra A , Wihandika Randy Cahya
Published: December 2023

Social media is a common thing that people use. Posts or comments found on social media describe someoneâ€™s feelings and opinions so there have to be important topics that can be extracted from social media. In the e-commerce field, topic is an interesting thing to know because it can describes peopleâ€™s opinion towards a product. However, the large number of social media users is currently making the process of finding topics from social media difficult, so computer assistance is needed. One method that can be used is Latent Dirichlet Allocation (LDA). LDA is a good method for extracting topics, but the drawback is that sometimes the topics are incomprehensible. To cover up the drawback, TF-IDF feature selection method is used so that less important words can be skipped so LDA can generate a better topic. The best hyperparameter values â€‹â€‹obtained were 10 iterations, 10 topics, Î± and Î² values consecutively 0,1 and 0,01. The best feature selection percentile value is 90. This value is used to find the threshold that can be used as the lower limit of the TF-IDF value of each word so that the word with greater TF-IDF value can be used as feature.
APPLICATION OF COST-SENSITIVE CONVOLUTIONAL NEURAL NETWORK FOR PNEUMONIA DETECTION
Authors: Anantama Rizki
Published: December 2023

Pneumonia is a disease caused by a viral, bacterial, or fungal infection. In the diagnostic process of pneumonia, one approach is to use X-ray images. One of the existing problems is the lack of qualified and experienced medical personnel to recognize the X-ray images that have been taken. For this reason, an alternative is needed to detect pneumonia. Existing research shows that the use of convolutional neural networks can effectively detect pneumonia X-ray images. However, one of the problems is that this approach focuses a lot on accuracy without considering performance criteria such as sensitivity and specificity. To solve this problem, a cost-sensitive based approach has been proposed. In this study, a convolutional neural network-based model was created and trained using a cost-sensitive and non-cost sensitive approach. From the results obtained, it is seen that the model made still has a comparatively low level of accuracy. However, it is found that training with a cost-sensitive approach is able to improve performance on the specificity side, although at the expense of performance on the sensitivity side.
SLEEP DISORDER IDENTIFICATION FROM SINGLE LEAD ECG BY IMPROVING HYPERPARAMETERS OF 1D-CNN
Authors: Fahruzi Iman
Published: December 2023

Disruption of the flow of breathing during sleep will result in significant heart problems if

not treated seriously. An electrocardiogram (ECG) recording is one of the most used

methods for detecting sleep disorders early on. An ECG is a representation of electrical

activity in the heart while it is beating. The irregularities of the morphology and the

complexity of the recordings have clinical significance that can be used as a tool for

diagnosing sleep disorders. This study uses engineering to obtain features from ECG

recordings that are carried out automatically using deep learning machine learning with

a Convolutional Neural Network (CNN) model approach. The ECG recordings were

processed to remove noise before being used in the CNN model. Tests are carried out on

the most optimal model to get good accuracy by applying two scenarios. The test results of

the two scenarios show that scenario one has an accuracy of 83.03% compared to scenario

two with an accuracy of 76.88%. Meanwhile, the precision, sensitivity, cohens kappa and

ROC UAC levels were 81.78%, 87.78%, 65.73% and 82.68% in scenario one testing on the

CNN model with the most optimal parameter settings, respectively
DESIGN AND DEVELOPMENT OF BACKEND APPLICATION FOR THESIS MANAGEMENT SYSTEM USING MICROSERVICE ARCHITECTURE AND RESTFUL API
Authors: Khozaimi Ach. , Pramudita Yoga Dwitya , Solihin Firdaus
Published: December 2023

A thesis is a scientific work completed by students with the aim of developing the knowledge gained during the lecture period. Students at Universitas Trunojoyo Madura (UTM), Faculty of Engineering, particularly Informatics Engineering, carry out their theses manually and on paper. Thesis Management System (TMS) is software designed to help with the thesis execution process by reducing paper usage and increasing time efficiency. Monolithic system development can disrupt the service process if improvements are being made to the system. Therefore, in this research, a Thesis Management System (TMS) will be built using a microservice approach to make it easier to maintain and develop the system, for example, system scalability. As a means of communication between services, TMS is designed and developed using the REST API. TMS has undergone system performance testing to verify that it performs well under certain conditions. The results show that the number of requests increases the performance response time, CPU usage, and memory consumption, with an average resource usage of each service based on a response time of 61.64 ms, CPU usage of 8.64%, and memory usage of 89.47 Mb. As the number of requests on the service increases, so does resource usage in each service, but this has no effect on device performance because the increase is so low.
OPTIMIZATION OF K-MEANS CLUSTERING USING PARTICLE SWARM OPTIMIZATION ALGORITHM FOR GROUPING TRAVELER REVIEWS DATA ON TRIPADVISOR SITES
Authors: Bimantara I Made Satria , Widiartha I Made
Published: December 2023

K-Means Algorithm can be used to group tourists based on reviews on tourist destination objects. This algorithm has a weakness that is sensitive to the determination of the initial centroid. The initial centroid that is determined at random will decreasing the level accuracy, often gets stuck at the local optimum, and gets a random solution. Optimization algorithms such as PSO can overcome this by determining the optimal initial centroid. The optimal number of clusters (K) will be determined using the Elbow method by calculating the SSE value of the resulting cluster. The average Silhouette Coefficient (SC) is used to measure the quality of the clusters produced by the K-Means Algorithm with and without the PSO Algorithm. This study uses secondary data obtained from the UCI Machine Learning Repository with the name Travel Reviews Data Set which consists of 980 records and 10 attributes. The test results show that K=2 is the optimal number of clusters. The K-Means and PSO Algorithm gives an average SC value of 0.300358 which is better than without the PSO Algorithm of 0.300076. The optimal PSO hyperparameter generated is the number of particles=30, \varphi_1=2.2, and {\ \varphi}_2=3 at maximum iteration of 100.
Ensembled Surrogate Assisted Material Extrusion Based 3D Printing Process Parameter Optimization for Enhanced Mechanical Properties of PEEK
Authors: Padhy Chinmaya , Simhambhatla Suryakumar , Bhattacharjee Debraj
Published: December 2023

In the material extrusion based 3D printing-fused deposition modelling (FDM), each material may require its own unique set of processing parameters and these parameters can be difficult to optimise and control. This can lead to variability in the final product and can make it challenging to produce parts with consistent quality. Indeed, it is difficult to consider specific FDM parameters to obtain optimum mechanical properties mainly in case of high grade polymers (HGPs) e.g. PEEK, PEK, PPS etc. With the high thermal gradient and heat distribution during their printing, possibilities of residual stresses and deformations are unavoidable, which directly affects its quality and mechanical properties. In this article, an ensembled Surrogate Assisted Evolutionary Algorithm (SAEA) based method is used to optimise the process parameters (layer height, print speed, print direction and nozzle temperature) to enhance the mechanical properties, considered as print quality, of PEEK considering print time into account. The solution obtained through the SAEA approach is further compared with the solution computed through Gray Relational Analysis (GRA) Taguchi, which is used as the benchmark method, to establish the superiority of the proposed one. The comparison indicates the SAEA based solution has 28.86% of higher Ultimate stress value, 66.95% of lower percentage of elongation and 7.14% of lower print time in comparison to the benchmark result. It has also been found that print direction has a greater role in deciding the optimum value of mechanical properties for FDM 3d-printed PEEK material.
Process Improvement Through Six-Sigma DMAIC: A Case Study in Label Printing Firm
Authors: Shameem Huda , Mittal Rubina
Published: December 2023

.This article offers a thorough method for reducing defects in a Micro, Small, and Medium-sized Enterprise (MSME) that specialises in label printing using the Six Sigma DMAIC (Define, Measure, Analyse, Improve, and Control) framework. Delivering high-quality goods while preserving productivity and efficiency becomes crucial in emerging economies where global industry leaders pose substantial challenges to local MSMEs.
This study makes use of a variety of cutting-edge tools, such as Pareto analysis, cause and effect diagrams, affinity diagrams, and interrelationship diagrams, among others, to accomplish these goals. The analysis determines misregistration, irregular ink application, and cutting errors as the most serious flaws, accounting for an astounding 84% of all rejection cases, by applying the classic 80-20 rule.The fishbone diagram, affinity diagram, and interrelationship diagram, among other tools, enable a more thorough analysis of these faults, revealing that the main root causes are changes in printing parameters, maintenance problems, and human errors.
The company's quality control initiatives have reached a critical turning point with the adoption of the suggested corrective measures. It is interesting that the sigma level, which is a crucial gauge of process quality, significantly increased. For example, in the printing and die-cutting step of the flexographic label printing process, the sigma level increased from the starting baseline of 3.6 to an astonishing 4.5, further increasing to 4.8 in the slitting stage
MXene-supported MIL-88A(Fe) as persulfate activator for removal of tetracycline
Authors: Chen Junxia , Yang Zhenzhen , Li Weigang , Yang Yuying , Zhu Feng , Huo Zongli , Zhou Qing
Published: December 2023

The poor conductivity, poor stability and agglomeration of MIL-88A(Fe) limit its application as persulfate (PS) activator in water purification. Herein, MXene-supported MIL-88A (Fe) composites (M88A/MX) were synthesized to enhance its adsorption and catalytic capability for tetracycline (TC) removal. M88A/MX-0.2 composites exhibits optimal degradation efficiency，reaching 98% under conditions of 0.2 g/L M88A/MX-0.2, 1.0 mM PS, 20 ppm TC, and pH 5. The degradation rate constants of M88A/MX-0.2 was 0.03217 min-1, which was much higher than that of MIL-88A(Fe) (0.00159 min-1) and MXene (0.00626 min-1). The removal effects of reaction parameters, such as dosage of M88A/MX-0.2 and PS, initial solution pH and the presence of the common co-existing constituents (humic acid and the inorganic anions) were investigated in detail. Additionally, the reuse of M88A/MX-0.2 showed that the composites had good cycling stability. The results of electron paramagnetic resonance (EPR) and quenching experiments indicated that ·OH, ·SO4- and ·O2- were involved in the M88A/MX-0.2/PS system. This study offered a new avenue for sulfate-based degradation of Fe-based metal organic framework.
Case report: anti-synthase syndrome associated with SARS-Cov-2 infection
Authors: Chen Xing-yue , Chen Jun , Zhi Li-jia , Long Kun-lan , Gao Pei-yang
Published: December 2023

Background: Anti-synthetase syndrome (AS) is a rare autoimmune idiopathic inflammatory myopathy (IIM) with diverse manifestations, including arthritis, interstitial lung disease (ILD), Maynard's phenomenon, unexplained persistent fever, and mechanic's hands.
Case presentation: We present the case of a 72-year-old woman, previously healthy, who was admitted to our hospital for treatment of cough and rapid breathing. The patient had elevated white blood cells and C-reactive protein, and tested negative for severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). She was initially diagnosed with community-acquired pneumonia and received tamoxifen for anti-infection treatment, but her dystonia worsened. She eventually required non-invasive ventilator support, tested positive for SARS-Cov-2 again, and started antiviral therapy, corticosteroids to reduce alveolar effusion, anticoagulation, and other treatments. However, her condition continued to deteriorate, with the lowest oxygenation index reaching only 80mmHg. Ultimately, she underwent tracheal intubation and mechanical ventilation. Chest CT revealed rapid progressive interstitial changes in her lungs, and her hands showed noticeable fraternization changes. At this point, we suspected that the novel coronavirus infection might be associated with autoimmune diseases. The patient's autoimmune antibody spectrum showed positive results for anti-recombinant RO-52 antibody and myositis-specific antibody anti-alanyl tRNA synthetase (anti-PL-12). The patient was treated with dexamethasone sodium phosphate for anti-inflammatory and anti-fibrotic effects. After successful extubation, the patient was discharged with only oral prednisone tablets at a dose of 30mg.
Conclusions: This case emphasizes the significance of a thorough physical examination. Additionally, the swift advancement of interstitial lung lesions during SARS-Cov-2 infection can be challenging to differentiate on imaging. It is important to consider screening for autoimmune diseases early if the treatment for SARS-Cov-2 infection proves to be ineffective. Consequently, the successful treatment of this case serves as a valuable reference for future clinical studies on anti-synthase syndrome.
Flood Detection System: Text-Driven Flood Alert Systems with IoT Arduino
Authors: Singh Chetan , Dey Tarun Danti , Pandey Digvijay
Published: December 2023

Flood detection is a critical aspect of disaster management, aiming to provide timely alerts and mitigate potential damage. This research presents a novel approach to flood detection by integrating IoT Arduino technology with text-driven flood alert systems. The primary objective of this study is to design and develop a cost-effective and efficient flood detection system that leverages Internet of Things (IoT) capabilities to deliver real-time flood alerts through text messages. The methodology employed in this research involves the deployment of Arduino-based sensors in flood-prone areas to monitor water levels. These sensors continuously collect data and transmit it to a central processing unit, which analyses the data for flood patterns. When a potential flood is detected, the system sends instant text messages to local authorities and residents, enabling rapid response and evacuation if necessary. Additionally, the system allows users to customize alert thresholds and receive alerts based on their preferences, enhancing its user-friendliness. The contributions of this research are two-fold. Firstly, it introduces an innovative flood detection system that is not only affordable but also highly accessible to communities in flood-prone regions. By utilizing text messages, it ensures that alerts reach a wide audience, including those without access to smartphones or the internet. Secondly, the system's flexibility and customization options empower users to tailor alerts to their specific needs, promoting community engagement and preparedness. In conclusion, this research offers a robust flood detection solution that combines IoT technology with user-friendly text-driven alerts, ultimately enhancing disaster resilience in vulnerable regions.
Static and fatigue performance of GNP coated bi-directional carbon fibre- epoxy composites under bending loads
Authors: Srivas Alok K. , Yerramalli Chandra S. , Singh Aparna
Published: December 2023

The addition of graphene nanoplatelets as a nanofiller on the surface of pristine and oxidized carbon fiber for making reinforced polymer composites has shown improvement in monotonic flexural properties. However, the fatigue response of these laminates under bending loads has not been investigated so far. The current study aims to examine the monotonic and fatigue behaviour of the graphene nanoplatelets (GNPs) coated bi-directional pristine and oxidized carbon fiber epoxy composites under bending loads. Eight layers of fabrics were used to manufacture the laminates through vacuum-assisted resin transfer molding technique (VARTM). An optimum amount of GNP addition on oxidized fiber leads to ~830-fold enhanced fatigue life at higher stresses as compared to pristine laminates. However, excessive GNP addition on pristine as well as oxidized fiber leads to a deterioration in fatigue life. In-situ optical microscopic examination was done to observe the crack initiation and propagation of all the specimens with respect to the number of cycles coupled with postmarterm SEM images of the fracture surfaces.
Towards designing a social interaction model based eXplainable Autism Spectrum Disorder (ASD) care agent
Authors: Gupta Prashant K. , Mazumdar Bireshwar Dass , Bhurani Kashish , Chadha Rubina
Published: December 2023

Autism Spectrum Disorder (ASD) is a neurological disorder that impacts a subject’s ability to be involved in a social interaction. A large body of work exists on the detection of ASD using machine learning (ML) and deep learning (DL) algorithms. Further the use of eXplainable artificial intelligence (XAI) algorithms is being advocated in the healthcare domain (on account of the ‘black-box’ nature of DL algorithms), to the best of our knowledge, no social interaction model based eXplainable Autism Spectrum Disorder (ASD) care agent exists for social interaction training of an ASD subject. Therefore, we make a beginning in this direction through this work. We present the interaction protocol and the social interaction training model for the design of an ASD care agent and elucidate its working through six representative social interaction scenarios. Further, we also put forward interesting discussions that emanate from the behavior of the ASD care agent in these scenarios and some practical considerations that need to be accounted for when the agent is put in practice with the ASD subject. We hope that the interested researchers can develop further on the work in future.
Increased Efficiency by Changing the Slot Topology of a Light Electric Vehicle Three-Phase Induction Motor.
Authors: Roberto Igor , Caetano Ricardo
Published: December 2023

Electric vehicles have become more widely used in the market given their numerous benefits. Electric motors should be optimized for optimal development and application. High-performance slot topologies, including rounded, rectangular, or mixed configurations, have already become established in the market, showing excellent results in terms of final induction motor performance. Consequently, new slot topologies, be they for the stator or for the rotor, can offer several advantages. These new topologies may facilitate greater magnetic flux or reduce magnetic flux dispersions. These enhancements result in increased efficiency for electric vehicle induction motor applications. This study examines the performance of a three-phase induction motor intended for use in a light electric vehicle propulsion system. The focus is on altering the stator slot plate topology to gauge its impact. The analyses compared the magnetic flux dispersion for three different slot topologies. The original stator slot design featured a flared shape, which was compared with a rectangular slot design. The COMSOL software program allowed us to visually represent the generated magnetic field lines within the induction motor. This included the magnetic flux dispersion lines, categorized as either gap dispersion, slot dispersion, coil head dispersion, slot tooth dispersion, and slope dispersion. With the MATLAB software program, we performed a quantitative analysis of the magnetic flux dispersion for the three stator slot topologies. The induction motor equipped with the rectangular slot showed a 0.13 \% efficiency gain compared to the motor with the original slot design.
Effect of Precursor Solution Temperature on the Morphology and Electrochemical Performance of Electrodeposited MnO 2 Nanofilms for Lithium-Ion Batteries
Authors: Zhao Haodong , Zhao Junshan , Zhang Ming , Chen Die , Yang Dingyu
Published: December 2023

This study investigated the impact of precursor solution temperature on the electrodeposition of MnO 2 material, which were prepared on a nickel substrate using the electrodeposition method under varying precursor solution temperatures of 25℃, 40℃, 50℃, and 60℃, respectively. The morphology and structure of the MnO 2 nanomaterials were characterized using SEM and TEM. These materials were subsequently employed as anodes in Lithium-Ion Batteries to study their electrochemical performance. The results indicate that an increase in temperature induces preferential aggregation and growth of MnO 2 nanosheets towards specific orientations, which is advantageous for enhancing the electrochemical performance of MnO 2 electrode materials. Notably, the electrode material prepared at a solution temperature of 50℃ exhibited optimal performance. At 50℃, the initial discharge specific capacity reached a remarkable 1476.7 mAh g-1 , and the rate capability even exceeded twice that at 25℃. Additionally, the charge transfer impedance was lower, which could be attributed to the growth of the highly conductive β-MnO 2 main phase under 50℃. However, excessively high temperatures impede this growth process, leading to a reduction in electrochemical performance. This study presents a novel approach for effectively improving electrodeposited nanomaterials, offering insights into the optimization of electrochemical performance.
Medical Image Fusion with Deep Neural Networks
Authors: Liang Nannan
Published: December 2023

Medical image fusion aims to fuse multiple images from a single or multiple imaging modes to enhance their corresponding clinical applications in diagnosing and evaluating medical problems, a trend that has attracted increasing attention. However, most recent medical image fusion methods require prior knowledge, making it difficult to select image features. In this paper, we propose a novel deep medical image fusion method based on a deep convolutional neural network (DCNN) for directly learning image features from original images. Specifically, source images are first decomposed by low rank representation to obtain the principal and salient components, respectively. Following that, the deep features are extracted from the decomposed principal components via DCNN and fused by a weighted-average rule. Then, considering the complementary between the salient components obtained by the low rank representation, a simple yet effective sum rule is designed to fuse the salient components. Finally, the fused result is obtained by reconstructing the principal and salient components. The experimental results demonstrate that the proposed method outperforms several state-of-the-art medical image fusion approaches in terms of both objective indices and visual quality.
Color Image Encryption System based Fractionalhyperchaotic, Fibonacci matrix and Quaternion algebra
Authors: Chaker Rachid , ogri Omar El , BOUA Abdelkarim
Published: December 2023

In this study, we use quaternion algebra, quaternion discrete fractional Charlier transform(QDFCTs), Fibonacci matrix and fractional 7D hyperchaotic Lorenz-Like system to encryptioncolor images. Also, we present a new color image encryption and decryption scheme based anew algorithm consisting of two basic steps: first step, the 7D hyperchaotic Lorenz-like systemwith fractional order generates random numbers that we use to change pixel positions. In thesecond step, we split the permitted image into blocks of dimensions 8 x 8, then we diffusedeach of them a first time with the Fibonacci matrix and to increase the effectiveness of thismethod we enhance it by using the fractional discrete Charlier transform (FrDCTs). Theefficiency of our proposed algorithm is evaluated using obfuscation and data segmentationattacks, correlation coefficient and graphing, differential attacks, keyspace, entropy and highsensitivity. The obtained results show a high level of security performance and excellent colorimage encryption efficiency.
Aspects of public attention on popular nonindigenous species, as determined by a comprehensive assessment of Japanese social media
Authors: Tomojiri Daiki , Takaya Kosuke
Published: December 2023

Invasion culturomics is an emerging field of study that utilizes digital data existing on the Internet to reveal the human dimension of nonindigenous species (NIS) invasions. Although hypothetical approaches have been used to examine explanatory variables that predict the amount of public attention by using proxies, it has been difficult to observe direct associations between these variables. Here, we aimed to deepen our understanding of the relationship between people and NIS by analyzing the content of texts about NIS on social media, and by clarifying the context and aspects to which public attention is directed. Specifically, we quantified tweets about NIS to identify popular NIS that attract a lot of public attention on Twitter. We also identified hidden topics in which NIS names occurred by applying topic modeling to tweets, and we investigated the topic distribution over popular NIS. A relatively small number of species were selected as popular NIS for further analysis, and 25 hidden topics were identified from all the tweets used in the analysis. The topic distribution over popular NIS had three patterns across taxonomic groups: (1) biased among topics but consistent within taxonomic groups; (2) relatively even among topics and consistent within taxonomic groups; and (3) not consistent within taxonomic groups and with biases differing among species. These findings can provide important insights into the formulation of a better strategy for NIS management by approaching the social and human dimensions of NIS invasion; such a strategy would include information dissemination, environmental education, and management campaigns.
Machine Learning-Based Credit Risk Assessment for Predicting Loan Defaulters in Ethiopian Banking industry
Authors: Asresa Tsega , Dargaso Tekle , Bayih Melaku
Published: December 2023

Machine Learning is an AI technique, empowers organizations globally to gain insights from their data and achieve success. This study focuses on improving risk management of banking in Ethiopia by employing machine learning techniques to detect and predict loan defaulters, ultimately mitigating bad loans. The research aims to distinguish borrowers who repay loans promptly from those who don't, forecast potential defaults, and assess the creditworthiness of prospective customers without overhauling existing systems and data. To showcase the study's results, classification models are constructed to reveal significant patterns among customer attributes. The primary objective is to apply cutting-edge machine learning algorithms to classify bank loan defaulters. Several machine learning algorithms, including Random Forest, Decision Tree, Gradient Boosting (GB), XGBoost, and Multi-Layer Perceptron (MLP), are employed in the process. Various data split ratios, such as 70/30, 60/40, and 90/10, are explored, alongside the 80/20 data split, to build classification models for each classifier algorithm. Based on the experiment's outcomes, the 70/30 split is selected for its superior accuracy. The study evaluates the performance of these algorithms using metrics like accuracy, precision, recall, and F1-score. The results indicate that the Gradient Boosting classification technique surpasses other algorithms, achieving a training accuracy of 98.7% and a testing accuracy of 97.8%.
A complete overview of Packaging discoloration & delamination of Salt packs (Iodized) at market places under conditions relevant to product packaging, ageing & stabilization of filled polymers and product storage.
Authors: Haque Azizul
Published: December 2023

Polymeric packaging protects food during storage and transportation and withstands mechanical & thermal stresses from high temperature. Packaged salt containing potassium iodate was produced at Bangladeshi commercial facility. The outer pack became discolored, turning yellow following layer separation, delamination to a degree that would impact consumer acceptance at market places. Therefore, there was a need for an investigation to find out the actual root cause and possible remedy for this discoloration and delamination. The components of the packaged salt product, storage conditions, and processing characteristics along with packaging structures as well as packaging design were taken into consideration. Salt samples were prepared with iodine and stored at 25˚C and 45˚C in glass & polyethylene or commercial polymer film. Salt samples containing iodine when heated before storage, packaging material turned yellow in color. From this study, it was found that due to heat and the presence of a sacrificial antioxidant component in the packaging film, potassium iodate was reduced to elemental Iodine (I2) turning packaged salt samples to a yellow/orange color and simultaneously outer packaging also turning yellowish. Hence it is recommended that in the manufacture of foods containing potassium iodate, the packaging material selected should be free from readily accessible antioxidants. Again, Salt is a translucent mineral that appears white. For NaCl, with heat or other environmental conditions, the concentration of the metal Sodium (Na) could increase in the compound and changes the salt and outer packaging yellowish simultaneously. Again, iron is present in the NaCl crystals, which can impact the yellow color of the crystals. If it contains impurities, it may take on other colors, integrating additives or cleaners into the salt pellets to improve the whiteness and can change the salt color as well. Salt itself has no expiration date but salt products that contain iodine or seasonings can deteriorate over time.
Management of Innovations in the Environmental, Social, and Governance Scores and Sustainability Performance Through ESG Disclosure: Evidence from Emerging Markets
Authors: Ahmed Essia Ries , Alabdullah Tariq Tawfeeq Yousif , Akyurek Mustafa
Published: December 2023

Based on managerial accounting, Ratings for the environment, society, and governance (ESG) are now crucial measures for assessing how corporations behave with respect to sustainability. This study aims to present research in the managerial accounting and innovation field to determine how industrial firms’ sustainability performance and associated ESG scores relate to one another. This study especially evaluates the management of innovations in the manufacturing industry in terms of Turkey’s ESG performance ratings based on Refinitiv Eikon’s listing. To examine the association between the management of innovations in industrial firms’ overall sustainability performance and ESG scores, hypotheses were developed and tested. Cutting-edge Smart-PLS 4.0 software wasused to carry out a rigorous partial least squares (PLS) analysis together with conventional bootstrapping to accomplish these goals. The results show that the management of innovations in Turkey’s manufacturing sector’s sustainability performance is stronglyimpacted by all ESG issues (social, governance, and environmental scores), which makes it a vital issue from the perspective of the managerial accounting field. The present research emphasizes the management of innovations as a crucial part of determining the sustainability of the industrial sector’s environment. The assignment of goals when conducting planning and policy making should appropriately take into account ESG-related factors, according to the key findings of this study. Industrial firms can improve their overall sustainability performance and make good contributions to the well-being of innovations, the environment and society while upholding sound governance standards by incorporating ESG concepts into decision-making processes. For the purpose of developing strategies that balance economic growth with sustainable development objectives, this research offers insightful information to industrial executives and legislators.