bluuebunny/crossref_metadata_2025 huggingface dataset:
Stress Martensite Nucleation in a State of Premartensitic Lattice Instability
Authors: Dolgachev Y. V. , Pustovoit V. N. , Vernigorov Y. M.
Published: March 2024

Introduction. The combined effect on the phase transformation process, involving a combination of heat treatment and external action, is a major technology solution for obtaining the required properties of steel products. When hardening steel in a constant magnetic field with a strength of 1–2 MA/m, martensite formation is observed at higher temperatures. In addition, when compared to conventional hardening, there are changes in structure and properties. Such effects cannot be explained only in terms of thermodynamics, since the expected shift in the equilibrium temperature between austenite and martensite in a magnetic field of such strength does not exceed 4–8°C. To explain the effects that occur during hardening in a magnetic field, it is proposed to consider the features of martensitic transformation in highspeed steel when exposed to an external magnetic field in the temperature range of austenite superplasticity. This research was aimed at identifying the features of martensitic transformation in the presence of a constant magnetic field in steel with account for the phenomena occurring in the premartensitic state.

Materials and Methods. Samples made of steel R6M5 were used. Characteristics of the martensitic transformation were studied using the potentiometric method of electrical resistance. The data were recorded using an L-CARD E14-440 analog-to-digital converter with the LGraph2 software package. The sample was heated by passing current. The sample was placed in the interpolar space of an open-type laboratory electromagnet FL-1, which provided the creation of a magnetic field with a strength of 1.2 MA/m.

Results. The obtained differentiated dependences were characterized by electrical resistance anomalies (low-temperature peaks) at a temperature corresponding to the appearance of a ferromagnetic phase as a result of martensitic transformation. In a magnetic field, the development of martensitic transformation began at a higher temperature, which could not be explained in terms of thermodynamics. Thus, the formation of stress martensite was observed in microvolumes of austenite with ferromagnetic ordering, which perceived the energy of the external field through magnetostrictive stresses. Under conditions of superplastic austenite, such stresses were sufficient to initiate shear transformation. The minimum possible size of lattice instability fluctuations (1.372 nm) was determined.

Discussion and Conclusion. Exposure to a magnetic field under hardening intensified the processes of some magnetic decomposition of austenite. At temperatures close to the beginning of the martensitic transformation, the existing areas of magnetic inhomogeneity were superimposed on the effects of the phenomenon of instability of the crystal lattice. In the temperature range Md-Mn, when austenite exhibited superplasticity, the formation of stress martensite in microvolumes of austenite with ferromagnetic ordering was significantly facilitated
Helminth Fauna of Bats of the Rostov Region: Review. 2. Trematoda
Authors: Evsyukov A. P. , Tsygankova M. G.
Published: March 2024

Introduction. The class of Trematoda includes two subclasses — Aspidogastrea and Digenea. Representatives of the former do not parasitize in bats. The definitive hosts for digenetic trematodes (Digenea) are vertebrates, including bats, in which the sexual generation (maritae) parasitizes. Gastropods or bivalves are the intermediate hosts. Supplementary hosts for the trematodes of bats are larvae and imagos of flying insects. Since in most cases the development of parthenites and cercariae of trematodes is related to water environment, the supplementary hosts are the groups of insects whose larvae live in the water. The list of bat species living in the Rostov region has been compiled in the previous research. In the present article the authors investigate the trematode fauna parasitizing in bats of the region under study. The aim of this review is to analyse the current state of knowledge on the species composition of the helminth parasitizing in chiropterans of the Rostov region.

Materials and Methods. The research materials have been obtained from the libraries and open access resources: PubMed (pubmed.ncbi.nlm.nih.gov), CyberLeninka (cyberleninka.ru), Google Scholar (scholar.google.com), BHL (www.biodiversitylibrary.org), JSTOR (www.jstor.org). Some data has been provided by the colleagues.

Results. 42 trematode species from 10 genera, 5 families and 1 order can parasitize in 15 bat species living in the Rostov region. The Lecithodendriidae family (24 species) and the genus Paralecithodendrium (9 species) are represented by a large number of species. Of the listed trematodes, 33 species used to be recorded on the territory of Russia.

Discussion and Conclusion. The results of the conducted systematic review have revealed that the largest number of trematode species parasitizes in two bat species living in the Rostov region: the common noctule (27 species) and the serotine bat (24 species). The smallest number of species (4 per each) is found in the giant noctule and the soprano pipistrelle bat. Two species (Plagiorchis elegans and Plagiorchis vespertilionis) have been found in the companion cats and dogs includingly, wheras a case of the latter parazitising in humans has also been recorded. The presence of bats in the urban environment enables the full life cycle of these trematodes. There exists possibility of the companion animals and people to get infected through incidental ingestion of the infested insects.
Globalization’s Impact on Culture: An Exploration of McDonaldization vs. Clash of Civilizations
Authors: Karras Ioannis
Published: March 2024

This theoretical article sets out to conceptualize the notions of McDonaldization and the clash of civilizations in a globalized context and propose a middle-of-the-road solution in this dichotomy, i.e., hybridization. As cultures and cultural values constantly evolve and reshape and new forms of culture emerge, cultural hybridization is the preferred viewpoint adopted herein. In essence, cultural expressions (such as values, beliefs, and ideas) interact and engage with one another, promoting and broadening cultural offerings.
Ketencik Proteinlerinin Bazı Tekno-Fonksiyonel Özellikleri Üzerine Ultrasonikasyon Uygulamasının Etkisi
Authors: Korkmaz Fatma , Mutlu Ceren
Published: March 2024

Bu araştırmada, farklı güçlerdeki ultrasonikasyon uygulamasının ketencik (Camelina sativa (L.) Crantz) proteinlerinin tekno-fonksiyonel özelliklerine etkisinin belirlenmesi amaçlanmıştır. Alkali ekstraksiyon (pH 12) ve izoelektrik noktada çöktürme (pH 4.5) yöntemi kullanılarak elde edilen ketencik proteinlerine beş farklı ultrasonikasyon (20 kHz) gücünde (0, 50, 100, 150 ve 200 W) işlem uygulanmış ve proteinlerin su bağlama, yağ bağlama, köpürme ve emülsiyon özelliklerindeki değişimler incelenmiştir. Uygulanan ultrasonikasyon işlemlerinin ketencik proteinlerinin su bağlama kapasitelerinde %251.07-500.03 aralığında gerçekleşen bir azalışa, yağ bağlama kapasitelerinde ise %14.10-21.21 aralığında gerçekleşen bir artışa neden olduğu belirlenmiştir. Ayrıca en yüksek köpürme kapasitesi (%53.59) ve köpürme stabilitesi değerleri (15. ve 30. dakikalar için sırasıyla %42.20 ve %40.71) 200 W gücünde ultrasonikasyon işlemi ile üretilen protein örneğinde tespit edilmiştir. Elde edilen sonuçlara göre ketencik proteinlerinin bazı tekno-fonksiyonel özelliklerinin geliştirilmesinde ultrasonikasyon işleminin kullanım potansiyeli ortaya koyulmuştur.
Katık Keşinin Fizikokimyasal, Biyokimyasal, Mikrobiyolojik ve Duyusal Özellikleri Üzerine Üretim Yöntemi ile Depolama Sıcaklığının Etkisi
Authors: Aydoğan Hamiyet , Coşkun Hayri , Sarıca Ercan
Published: March 2024

Bu çalışmada, yoğurdun süzülmesi (S yöntemi) ve ısıtılıp süzülmesi (I yöntemi) yöntemleri ile üretilen Katık Keşi peynir örnekleri iki gruba ayrılarak; birinci grup 4C’de, ikinci grup ise 24C’de 90 gün boyunca depolanmıştır. Depolama süresince örneklerin bazı fizikokimyasal, biyokimyasal ve mikrobiyolojik özelliklerinde meydana gelen değişimler belirlenmiştir. Örneklerin duyusal testleri ise sadece depolama sonunda gerçekleştirilmiştir. Elde edilen sonuçlara göre yöntem farklılığı Katık Keşi örneklerinin kuru madde, yağ, protein, tuz ve pH değerlerini etkilemiştir (p0.05), tuz, asitlik ve pH değerleri üzerinde etkili olmuştur (p
An applied study of a technique incorporating machine learning algorithms to optimize water demand prediction
Authors: Wang Ruiyi , Zou Xiangling , Song Haojing
Published: March 2024

In water resource management, accurate water demand prediction is essential for developing effective water supply strategies and optimizing resource allocation. This study aims to investigate machine learning algorithms, particularly echo state network (ESN) models, to improve the accuracy and efficiency of water demand prediction. ESN models are selected for their excellent nonlinear time series processing capabilities, which address the challenges of traditional prediction methods when dealing with complex water resource systems. By optimizing the parameters of the ESN model, the study hopes to provide a more scientific and efficient method for residential domestic and agricultural water demand forecasting, thus supporting more refined water resources planning and management decisions. Residential water demand prediction and crop water demand prediction are the two parts of this study. In the prediction of residential water demand, based on the actual data of City Z, the optimized ESN model predicts the water demand in 2025, and the total water demand in the baseline scenario is 790.9 million m3, and the expected values of water demand in different scenarios combined with the economic growth rate and the change of water price range from 659.4708 million m3 to 730.448 million m3. The article’s accuracy analysis of crop water demand prediction indicates that the model’s relative errors in predicting the water demand of the three major crops are limited to 10%. The ESN model optimized using the machine learning algorithm in this paper has good potential for water demand prediction and is an efficient and accurate prediction tool for managing water resources.
Optimization of Enterprise Economic Management Model and Risk Control Based on Marginal Analysis Approach
Authors: Wu Xiaoyun
Published: March 2024

As an effective economic decision-making tool in enterprise economic management, Marginal Analysis is crucial to reflect the small change relationship between costs and benefits. This paper aims to develop a multi-objective marginal analysis optimization algorithm (MMAOA) that utilizes marginal analysis to optimize the enterprise economic management model and risk control. This algorithm's improvement of the population initialization method and constraint handling enhances the quality of understanding and search efficiency. In this study, an improved population initialization method is designed to ensure that the population is within the upper and lower limits of the output power. Then the constraints are reasonably handled by the penalty function method and the correction method to enhance the feasibility and robustness of the algorithm. Guided by the concept of Pareto optimality, MMAOA is successfully applied to multi-objective optimization problems, and the algorithm can efficiently generate a set of Pareto optimal solutions under the consideration of equilibrium constraints and inequality constraints, in which the objective function values of certain optimization instances are improved by more than 10%. Following marginal analysis, this study presents the disparity in ROI between the East and West and the three stages of agricultural economic efficiency. This article provides a new optimization tool for enterprise financial management and a quantitative analysis method for risk assessment.
A Study on Mobile Phone Interface Interaction Design for the Elderly Based on Digital Technology
Authors: Yuan Lei
Published: March 2024

The rapid development of digital technology significantly impacts the use of cell phone interfaces by the elderly. This paper aims to analyze the interaction design of cell phone interfaces for the elderly to enhance their user experience and ease of use. This paper investigates the evaluation system for evaluating cell phone interface interaction for the elderly, including interface size, Layout, and functionality. A group of elderly people aged 65-75 are invited to evaluate the effects of different design options by observing their performance under different interface sizes (large size 6.0 inches, medium size 5.5 inches, small size 4.5 inches) and layouts (nine-cell grid and combination type). The evaluation metrics are task completion time, number of operation errors, and eye movement data. The 6.0-inch interface experienced an average task completion time of 6.97 seconds, a decrease of approximately 6 seconds and 1 second from the 4.5-inch and 5.5-inch interfaces, respectively. The large-size interface had an average error rate of 1.11 per task, significantly less than the average error rate in the 4.5-inch and 5.5-inch interfaces. The more extensive interface significantly decreased user gaze points and gaze time, indicating more efficient information acquisition. More extensive cell phone interfaces and combined layouts can significantly improve interaction efficiency and reduce operation errors for elderly users, enhancing user experience. The findings of this study offer practical guidance for designing cell phone interfaces for the elderly and aid in promoting cell phone interface design for the elderly.
Implementation Strategy of Guangxi Urban Resilient Grid Based on Integrated Utilization of Distributed Renewable Energy and Buildings in the Internet Era
Authors: Zhang Juncheng , Li Min , Tan Jing , Tan Xiaohong , Tao Yigang
Published: March 2024

Facing global climate change and energy crises, urban power grids, particularly in Guangxi, need resilience enhancements to cope with these unprecedented challenges. This study proposes a resilience improvement strategy by integrating distributed renewable energy with building systems, tailored to Guangxi’s unique conditions. We demonstrate that optimizing the network structure and protection settings significantly enhances fault recovery capabilities through system analysis, model development, and simulation. Implementing a distributed multi-microgrid system increased the resilience power supply rate by an average of 15% across eight cities in Guangxi, with a 20% improvement in the system’s resilience emergence rate. This was achieved by optimizing power interactions using a dynamic consistency algorithm, showcasing a viable pathway to bolster urban grid resilience through renewable integration and offering insights applicable to similar urban settings.
Research on Key Technologies of Smart Breeding Platform Based on 5G
Authors: Yang Wen
Published: March 2024

In modern animal husbandry, the application of 5G technology opens a new era of farming management, especially in intelligent farming. The high-speed and low-latency communication characteristics make remote monitoring, data transmission, and thoughtful decision-making possible, significantly improving breeding efficiency and management. It has great potential for monitoring animal health, preventing and controlling diseases, and improving production efficiency. This paper explores the application of 5G technology in an intelligent farming management platform and its key technologies. By analyzing the needs of smart farming, we clarify the key application areas of 5G technology. To identify sick pigs, measure their weight accurately using binocular vision technology, and combine with machine learning algorithms, the YOLO v3 algorithm is utilized. The accuracy of sick pig identification based on YOLO v3 reaches 98%, the error of pig weight measurement is controlled within ±2%, and the real-time data transmission and processing realized by 5G technology significantly improves the efficiency of disease prevention and control.5G technology can effectively support the efficient operation of the intelligent farming platform, which is of great significance to enhance the level of farming management and promote the sustainable development of the animal husbandry industry.
Research on Online Course Design and Application of SPOC-based Moral Education Course
Authors: Zhang Yingshuai , Zhang Tongshuai , Jing Junmiao
Published: March 2024

Small Private Online Courses (SPOC) represent a significant stride in online education, merging personalization with flexibility to revolutionize moral education. Our research investigates the efficacy of SPOC for ethical education, leveraging advanced analytics like Pearson correlation and cosine similarity, alongside 3D convolutional neural network-based student behavior analysis, to develop a tailored teaching recommendation system. In a comparative 20-week trial involving traditional and SPOC methodologies, students engaged with SPOC demonstrated superior cognitive, emotional, and behavioral performance, outscoring their peers by 4.011 points in moral education. These findings underscore the transformative potential of SPOC in enhancing the quality and effectiveness of moral education online.
The Chinese Integration and Application of Marxism in the Context of Digital Intelligence
Authors: Xuan Lu
Published: March 2024

This paper aims to explore the integration of Marxism and Chinese-style modernization and its practical application in the context of the digital intelligence era. Through theoretical Analysis and empirical research, a system for assessing development of Marxist Chinese-style modernization has been established. The study finds that Marxism’s multiple characteristics, such as political, scientific, people’s, practical, developmental, and revolutionary, provide theoretical support for Chinese-style modernization. This paper uses grey correlation analysis and multiple linear regression models to evaluate the modernization development of 31 provinces, municipalities, and autonomous regions in China during 2010-2019. The study results show that the Marxist Chinese-style modernization index has grown from 0.164 in 2010 to 0.731 in 2020, with an average annual growth rate of 34.57%. The index significantly impacts the quality of the regional economy, cultural industry, and ecological environment. The study shows that the application of Marxism in China accelerates economic development and promotes the governance of cultural industry and ecological environment, which provides impetus for the construction of socialist modernization with Chinese characteristics.
Regression analysis of factors affecting college students’ employment motivation: college students’ willingness to receive career guidance
Authors: Zhang Rui , Jen Tsao Hsueh
Published: March 2024

This study analyzes the factors affecting college students’ employment motivation, especially the influence of college students’ acceptance of employment guidance, to propose effective strategies to improve employment motivation. This paper discusses the factors that affect college students’ employment motivation, with particular attention to their willingness to accept employment guidance. The research methodology included regression analyses of student data, significant data, and career guidance data for undergraduate students at University A between 2018 and 2022. The results showed that factors such as career guidance acceptance, professional knowledge, and interpersonal communication ability significantly affected students’ motivation to find employment. Specifically, students who received career guidance increased their motivation by an average of 15 per cent, while those with professional solid knowledge increased their motivation by 20 per cent. In addition, we found that gender, type of specialization and place of origin significantly affected motivation, and that comprehensive career guidance and targeted educational strategies are essential for improving college students’ motivation.
Research on Piano Curriculum Education and Its Performance Ecosystem Based on Network Flow Optimization
Authors: Wang Huang
Published: March 2024

This paper investigates music education, where an efficient and accurate performance evaluation system in the piano teaching and performance ecosystem is increasingly becoming an essential tool for improving teaching quality and performance level. The objective evaluation of students’ performance skills can be achieved by carefully analyzing piano performances using the network flow optimization technique. This technique optimizes the performance evaluation system’s audio recognition ability by analyzing the piano audio signal and solving the multi-constraint nonlinear optimization problem in a limited time domain. This paper establishes a network flow optimization model, applies the multi-constraint nonlinear optimization technique, and combines the non-negative matrix decomposition and dynamic time regularization algorithm to analyze the piano performance for experiments. After optimization processing, hundreds of piano audio samples were collected, and the audio recognition accuracy was improved by 20%. By optimizing and processing the audio signals from the network stream, the evaluation system could detect polyphony more accurately and track the musical score effectively, improving accuracy and efficiency. Using the non-negative matrix decomposition algorithm, the accuracy of detecting polyphony can reach 85%, while the dynamic temporal regularization algorithm can match the position of the musical score with 95% accuracy. The accuracy of piano performance evaluation is optimized by this network flow optimization method, providing new technical means for music education, and promoting the quality of teaching and performance.
Analysis of Construction Quality Control Measures of Building Decoration Engineering Based on Big Data Technology
Authors: Hong Ying , Xie Minjing
Published: March 2024

In the field of architectural decoration engineering, construction quality control is the main issue, which has a significant impact on project safety, cost and schedule. Under the background of the increasing maturity of big data technology, its application in the quality control of architectural decoration engineering has become a new trend in the industry, which is expected to improve quality management through technological innovation. This study analyzes the construction quality control measures of architectural decoration projects using big data technology to improve the efficiency and effectiveness of project quality management. The study utilizes PDCA and SDCA quality control theories, BIM technology, and extensive data analysis to fully monitor and assess the construction process of building decoration projects. The construction quality control mode using big data technology performs significantly better in improving project quality than traditional mode. The project’s second phase adopts the new model, and its construction quality score is higher than that of the first phase by more than 5 points on average, and the frequency of quality problems is reduced by 23%. A multi-layer fuzzy comprehensive evaluation model evaluates the quality control effect, and the construction quality control effect is rated as “excellent” with an affiliation value of 62.1%. The introduction of data technology significantly improves the efficiency and effectiveness of construction quality control in architectural decoration projects, and provides an effective management model for the industry.
Research on Long-term Mechanism of School-Enterprise Cooperation for Civic and Political Education Professional Talent Cultivation in Colleges and Universities under Big Data Technology
Authors: Shi Yaping
Published: March 2024

In the era of big data, establishing a sustainable school-enterprise collaboration framework for cultivating Civic and Political Education talents in higher education is crucial. This study employs the DEMATEL model and Structural Equation Modeling (SEM) to dissect this collaboration’s dynamics. Through DEMATEL, we unravel the complex interrelations among these factors, constructing a direct influence matrix and quantifying the centrality and causality indices. SEM further elucidates the causal interplays, underscoring the profound impact of university infrastructure, corporate culture, and governmental roles on the collaboration’s efficacy. Notably, the engagement of enterprise entities, academic institutions, and equitable benefit mechanisms emerge as pivotal, with path regression coefficients of 0.961, 0.943, and 0.925, respectively. The study highlights the indispensability of balanced benefit distribution, resource sharing, and strategic improvements in organizational management, pedagogical innovation, dual-expertise faculty development, and fostering industry-academia-research synergies. Offering theoretical insights and actionable strategies, this research advances the optimization of school-enterprise partnerships, ensuring the adept nurturing of Civic and Political Education professionals.
Exploration of Innovative Development and Talent Digital Cultivation Path of Computer Specialties in Colleges and Universities
Authors: Zou Hailin , Wu Qinlan
Published: March 2024

In the face of globalization and the rapid evolution of information technology, higher education, particularly in computer science, encounters both challenges and opportunities. This paper investigates strategies for fostering innovation and digital competency among university computer science students. Through an analysis of teaching methodologies across various institutions, student development, and industry collaborations, we propose a comprehensive educational framework. We evaluate and refine our student innovation ability assessment system by employing both quantitative and qualitative approaches, including the entropy weight method and gray correlation analysis. By updating curriculum content, prioritizing hands-on learning, and enhancing industry partnerships, we demonstrate a marked improvement in students’ programming and practical skills—showing 20% and 25% increases, respectively. Our findings advocate for a holistic revamp of teaching approaches, course material, and university-enterprise collaborations, aligning computer science education with the demands of the digital age.
Practice and Analysis of Rural Planning and Design for the Integration of Agriculture, Culture and Tourism in the Context of Big Data
Authors: Zhang Chao
Published: March 2024

In the contemporary society of globalization and rapid information technology development, rural areas face unprecedented challenges and opportunities. Rural planning and design are essential for regional economic development, cultural heritage, and ecological protection. As an innovative development model, integrating agriculture, culture, and tourism provides new ideas for rural revitalization. Big data technology can help analyze the countryside’s development potential more accurately and allocate resources more efficiently to promote the science and refinement of rural planning and design. This study establishes a GIS management system supported by geographic information data, uses Oracle database to manage spatial information and attribute information, and utilizes vector slicing technology and WebGL graphic rendering to achieve rapid rendering and diverse expression of maps. In creating an agricultural, cultural, and tourism integration index system, the entropy index method is used to assign weights to each index, and the coupling coordination degree model is set up. The coupling degree of Tibet’s agricultural, cultural, and tourism industry from 2011-2021 has increased from 0.219 to 0.769, and the coupling coordination degree has increased from 0.158 to 0.778, which shows an excellent upward trend. The study shows that big data technology can effectively improve the quality and efficiency of rural planning and design, and promote the development of agricultural, cultural, and tourism integration.
Factors Predicting Singers’ Work Efficiency and Singers’ Singing Peak
Authors: Huang Xuejie , Ang Mei Foong
Published: March 2024

The research focusses on understanding the controls and predicting singers’ work efficiency, which is measured by rework times (RwT) in the recording studios. We conducted a comprehensive literature synthesis to identify a set of nine critical factors combining advancements in both acoustic field and recording practice. We measured each of these potential variables while 10 individual singers performed the same original song independently. The pieces of music sentences (n = 380) were analyzed by the multiple linear regression method. We found that:

In the recording process, the RwT of a singer are predicted mainly by intensity, singing duration (SinD) and rhythm consistency.

SinD mediates the connection between intensity and RwT.

A singing peak exists in the performance.
A comparative study on characteristics of retracted publications across different open access levels
Authors: Zheng Er-Te , Fu Hui-Zhen
Published: March 2024

Purpose

Recently, global science has shown an increasing open trend, however, the characteristics of research integrity of open access (OA) publications have rarely been studied. The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.

Design/methodology/approach

The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases. These publications were categorized based on their OA levels, including Gold OA, Green OA, and non-OA. The study explored retraction rates, time lags and reasons within these categories.

Findings

The findings of this research revealed distinct patterns in retraction rates among different OA levels. Publications with Gold OA demonstrated the highest retraction rate, followed by Green OA and non-OA. A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions, while Green OA exhibited a higher proportion due to falsification and manipulation issues, along with a lower occurrence of plagiarism and authorship issues. The retraction time lag was shortest for Gold OA, followed by non-OA, and longest for Green OA. The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.

Research limitations

There is no exploration of a wider range of OA levels, such as Hybrid OA and Bronze OA.

Practical implications

The outcomes of this study suggest the need for increased attention to research integrity within the OA publications. The occurrences of falsification, manipulation, and ethical concerns within Green OA publications warrant attention from the scientific community.

Originality/value

This study contributes to the understanding of research integrity in the realm of OA publications, shedding light on retraction patterns and reasons across different OA levels.
Challenges of Academic Ethos: The Scientific Community’s Response to the Ostracism of Russian Scientists Following the Invasion of Ukraine
Authors: Dziedzic Justyna , Sułkowski Łukasz
Published: March 2024

Objective

The primary aim of this article is to understand how contemporary scientists from the Polish academic community perceive the scientific ethos in the context of ostracism within the scientific community, which emerged following Russia’s invasion of Ukraine. The article focuses on analyzing the epistemological and ethical implications of this ostracism in the academic context, considering Russia’s invasion of Ukraine.

Methodology

For this purpose, in-depth interviews were conducted within the Polish scientific community (11 participants), with respondents with degrees (full professors, Ph. D’s, associate professors, assistant professors, and professor emeritus), and literature review was carried out.

Findings

Based on the discussion, the research findings illuminate diverse approaches within the Polish academic community regarding the ostracism of Russian scientists following Ukraine’s invasion, shedding light on the intricate interplay between personal beliefs, scientific ethos, and educational values while also highlighting the multifaceted ethical challenges faced by scientific research, especially within military and political contexts.

Value Added

The study suggests the necessity for academic institutions to establish clear protocols for knowledge dissemination and crisis management that respect the ethos of scientific work while being adaptable to the shifting geopolitical landscape. It is also recommended that there should be a concerted effort to create forums for international scholarly dialogue to ensure that ostracism does not stifle academic collaboration and knowledge advancement.

Recommendations

This article contributes to the existing literature by providing empirical insights into how the academic community navigates the ethical dilemmas posed by geopolitical conflicts. Moreover, it underscores the importance of maintaining the integrity of the scientific discourse amidst external pressures, offering a nuanced understanding of the interplay between political events and academic practices.
Analytical and Experimental Investigation of Asymmetric Floating Phenomena of Uniform Bodies
Authors: Gu Jian , Fernandes Antonio Carlos , Chai Wei , Bu Shu Xia , Han Xiangxi
Published: March 2024

Uniform symmetric bodies can be observed floating asymmetrically under certain circumstances. Previous explanations of this are mostly abstract and lack experimental verification, making their understanding and application difficult. This article presents in detail alternative insights into the floating equilibria of uniform prisms and parabolic cylinders. The intrinsic characteristics of the equilibrium curves are investigated, and several equilibria different from those in the literature are found. The inflection points in the equilibrium curves are analyzed quantitatively due to their significance for floating states. Furthermore, experiments have been conducted for the square prism which validate the derived equilibrium curve, and provide a practical impression of the asymmetric floating phenomenon of symmetric bodies. These results have the potential to be applied in naval and ocean engineering, such as in the design of vessels and floating offshore structures.
Analysis and Experimental Verification of Improving the EEDI of a Ship using a Thruster Supplied by a Hybrid Power System
Authors: Mindykowski Janusz , Wierzbicki Łukasz , Górniak Mariusz , Piłat Andrzej
Published: March 2024

In this study, the authors present a theoretical analysis and experimentally verified methods to improve the Energy Efficiency Design Index (EEDI) of ships. The improvements were studied via the application of an innovative solution of a thruster supplied by a hybrid power system on board a passenger-car ferry. The authors performed sea trials of a ship’s electrical power system supplied by battery packs with diesel generating set power units. The experimental study focused on energy balance and management, which were considered together with related power quality issues. The authors found that the application of an energy storage system to the ferry, such as batteries, with the simultaneous adaption of the operation modes of the electrical power system for current exploitation, significantly improved energy efficiency. Fuel consumption and CO2 emission were reduced, while adequate parameters of electrical power quality were maintained to meet classification standards.
Re-Identifying Naval Vessels Using Novel Convolutional Dynamic Alignment Networks Algorithm
Authors: Roy Sudipta , Jana Dipak Kumar , Long Nguyen
Published: March 2024

Technological innovation for re-identifying maritime vessels plays a crucial role in both smart shipping technologies and the pictorial observation tasks necessary for marine recon- naissance. Vessels are vulnerable to varying gradations of engaging in the marine environment, which is complicated and dynamic compared to the conditions on land. Fewer picture samples along with considerable similarity are characteristics of warships as a class of ship, making it more challenging to recover the identities of warships at sea. Consequently, a convolutional dynamic alignment network (CoDA-Net) re-identification framework is proposed in this research. To help the network understand the warships within the desired domain and increase its ability to identify warships, a variety of ships are employed as origin information. Simulating and testing the winning of war vessels at sea helps to increase the network’s ability to recognize complexity so that users can better handle the effects of challenging maritime environments. The impact of various types of ships as transfer items is also highlighted. The research results demonstrate that the enhanced algorithm increases the overall first hit rate (Rank1) by approximately 5.9%; it also increases the mean average accuracy (mAP) by approximately 10.7% and the correlation coefficient by 0.997%.
Automatic Classification of Unexploded Ordnance (UXO) Based on Deep Learning Neural Networks (DLNNS)
Authors: Sigiel Norbert , Chodnicki Marcin , Socik Paweł , Kot Rafał
Published: March 2024

This article discusses the use of a deep learning neural network (DLNN) as a tool to improve maritime safety by classifying the potential threat to shipping posed by unexploded ordnance (UXO) objects. Unexploded ordnance poses a huge threat to maritime users, which is why navies and non-governmental organisations (NGOs) around the world are using dedicated advanced technologies to counter this threat. The measures taken by navies include mine countermeasure units (MCMVs) and mine-hunting technology, which relies on the use of sonar imagery to detect and classify dangerous objects. The modern mine-hunting technique is generally divided into three stages: detection and classification, identification, and neutralisation/disposal. The detection and classification stage is usually carried out using sonar mounted on the hull of a ship or on an underwater vehicle. There is now a strong trend to intensify the use of more advanced technologies, such as synthetic aperture sonar (SAS) for high-resolution data collection. Once the sonar data has been collected, military personnel examine the images of the seabed to detect targets and classify them as mine-like objects (MILCO) or non mine-like objects (NON-MILCO). Computer-aided detection (CAD), computer-aided classification (CAC) and automatic target recognition (ATR) algorithms have been introduced to reduce the burden on the technical operator and reduce post-mission analysis time. This article describes a target classification solution using a DLNN-based approach that can significantly reduce the time required for post-mission data analysis during underwater reconnaissance operations.
Environmental Marine Degradation of PLA/Wood Composite as an Alternative Sustainable Boat Building Material
Authors: Çamlı Selin Barış , Neşer Gökdeniz , Sözen Ayberk
Published: March 2024

IIn this study, which can be considered a contribution to the global effort to produce sustainable materials and to search new manufacturing methods for the boat building industry, the performance of a 3D printable polylactic acid and recycled wood (PLAW) composite was investigated under the simulated operational conditions of a boat. The wood used in the composite was yellow pine (Pinus sylvestris), a local wood widely used in boat building and 8% by weight in the composite. For the study, tensile and compressive strength tests were performed in both atmospheric and post-aging conditions, using composite samples produced by the additive manufacturing method. The durations of the accelerated aging before the experiments were one, two and four weeks. During these aging periods, water spraying, a salty fog environment and a drying cycle were applied at elevated temperatures and at equal time intervals, daily. The effect of wood additive on the composite and the joining efficiency of the components were also examined with scanning and optical microscopes. The performance of the obtained composite and the effects of aging on performance were measured using two different thermal analyses: differential scanning calorimetry and thermogravimetric analysis. From the results obtained, it can be seen that PLAW composite can be used in the manufacture of structural elements subjected to relatively low loads in boats. It is an option that will provide integrity in the future interior design of wooden boats.
Determination of copper and other trace elements in serum samples from patients with biliary tract cancers: prospective noninterventional nonrandomized clinical study protocol
Authors: Rebersek Martina , Hribernik Nezka , Markovic Katarina , Markovic Stefan , Valentinuzzi Katja Ursic , Cemazar Maja , Zuliani Tea , Milacic Radmila , Scancar Janez
Published: March 2024

Background

Biliary tract cancers (BTCs) are usually diagnosed at an advanced stage, when the disease is incurable. Currently used tumor biomarkers have limited diagnostic value for BTCs, so there is an urgent need for sensitive and specific biomarkers for their earlier diagnosis. Deregulation of the homeostasis of trace elements is involved in the carcinogenesis of different cancers, including BTCs. The objective of the study is to determine/compare the total concentrations of copper (Cu), zinc (Zn) and iron (Fe) and the proportions of free Cu and Cu bound to ceruloplasmin (Cp) and the isotopic ratio of 65Cu/63Cu in serum samples from healthy volunteers and cancer patients using inductively coupled plasma-mass spectrometry-based methods (ICP-MS).

Patients and methods

In this prospective, noninterventional, nonrandomized study 20 patients and 20 healthy volunteers will be enrolled to identify serum Cu, Zn and Fe levels, Cu isotopic fractionation as a predictive biomarker of response to systemic therapy of BTCs, which will be evaluated by computed tomography. Newly developed analytical methods based on ICP-MS will be applied to metal-based biomarker research in oncology.

Conclusions

In the study the comparison of the total concentration of selected trace elements, the proportion of free Cu and Cu bound to Cp and the isotopic ratio of 65Cu/63Cu in serum samples from healthy volunteers and cancer patients will be conducted to provide the foundation for the development of a BTC cancer screening methodology and the data on their usability as a potential predictive biomarker for BTCs of response to systemic therapy.
Seismic Structure-Soil-Structure Interaction (SSSI) between piled neighboring bridges: Influence of height ratio
Authors: Alfach Mohanad Talal
Published: March 2024

This paper explores the impact of height ratios on the seismic Structure-Soil-Structure Interaction (SSSI) for three adjacent bridges with varying superstructure masses (Mst = 350, 1050, 350 t) through 3D numerical simulations. A comprehensive series of numerical analyses has been conducted across different height ratios (R = 1, 1.1, 1.15, 1.2, 1.25, 1.5, 2, and 3) to assess their influence on superstructure acceleration and the internal forces within the foundation piles. The bridges under investigation are supported by groups of piles embedded in nonlinear clay. The numerical simulations were executed using fast Lagrangian analysis of continua in three dimensions (FLAC 3D), a three-dimensional finite differences modeling software. The findings revealed that variations in mass ratios significantly impact the SSSI effects on superstructure acceleration and pile internal forces. Notably, adverse effects were more pronounced for mass ratios of R = 1.1 and 1.2, leading to an increase in bending moment, shear force, and superstructure acceleration by up to 237.8%, 291.4%, and 70.33%, respectively. In contrast, a mass ratio of R = 3 resulted in a decrease in bending moment, shear force, and superstructure acceleration by up to 72%, 82.14%, and 81.13%, respectively. This implies that a careful arrangement of adjacent structures with different masses can be employed effectively to manage the (SSSI) effects.
Comparing fracture openings in mortar using different imaging techniques
Authors: Marliot Jonathan , Hedan Stephen , Siitari-Kauppi Marja , Sammaljärvi Juuso , Landesman Catherine , Henocq Pierre , Sardini Paul
Published: March 2024

This paper presents a quantitative characterisation of the fracture openings obtained in triaxial shear tests on several cement mortar samples. The comparison was carried out on three samples with various apertures using different methods of semi-destructive and non-destructive characterisation: optical microscopy, scanning electron microscopy, X-ray computed tomography, digital volume correlation and the 14C-polymethylmethacrylate method. The fracture aperture distribution results are in good agreement between the different methods. Although the opening results obtained are comparable, the most advantageous method was considered to be XRCT profile analysis based on the size of the target area studied and the specific characteristics of each technique.
Road Infrastructure, Supply Chain Costs Reduction, and Road Safety in Economic Geography Perspective
Authors: Adu James Peprah , Dorasamy Nirmala
Published: March 2024

Purpose: While it is expected that road transport infrastructure may enhance supply chain cost reduction, the mechanisms and conditions under which road transport infrastructure may enhance supply chain cost reduction are less understood.
 
Theoretical framework: Drawing insights from the economic geography perspective, and survey data from 359 senior managers of manufacturing firms in Ghana, we found support for the argument that road transport infrastructure is important in the quest to improve supply chain cost reduction.
 
Methods: The hypothesized model was tested with survey data from beverage manufacturing firms in Ghana. The survey method is usually appropriate for strategic management studies.
 
Results and Conclusion: Our findings also suggest that road safety does not just support supply chain cost reduction but serves as a transformative mechanism to reap superior supply chain cost reduction in a resource-constrained environment. Our findings make a contemporary contribution to the economic geography theory as well as important managerial guidance for managers in the supply chain management space in resource-constrained regions like SSA.
 
Research implications: The outcome of this study offers an important extension to the frontiers of innovative literature in supply chain management.
 
Originality/value:  It also provides practical insight to practitioners in the manufacturing setting by emphasizing the need to pay crucial attention to road safety as well as invest in road infrastructure development in the quest to reduce supply chain costs.