Search results for: thermal models

Authors: Nikoloz Jalabadze, Roin Chedia, Lili Nadaraia, Levan Khundadze

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Nanocrystalline materials in powder condition can be manufactured by a number of different methods, however manufacture of composite materials product in the same nanocrystalline state is still a problem because the processes of compaction and synthesis of nanocrystalline powders go with intensive growth of particles – the process which promotes formation of pieces in an ordinary crystalline state instead of being crystallized in the desirable nanocrystalline state. To date spark plasma sintering (SPS) has been considered as the most promising and energy efficient method for producing dense bodies of composite materials. An advantage of the SPS method in comparison with other methods is mainly low temperature and short time of the sintering procedure. That finally gives an opportunity to obtain dense material with nanocrystalline structure. Graphene has recently garnered significant interest as a reinforcing phase in composite materials because of its excellent electrical, thermal and mechanical properties. Graphene nanoplatelets (GNPs) in particular have attracted much interest as reinforcements for ceramic matrix composites (mostly in Al2O3, Si3N4, TiO2, ZrB2 a. c.). SPS has been shown to fully densify a variety of ceramic systems effectively including Al2O3 and often with improvements in mechanical and functional behavior. Alumina consolidated by SPS has been shown to have superior hardness, fracture toughness, plasticity and optical translucency compared to conventionally processed alumina. Knowledge of how GNPs influence sintering behavior is important to effectively process and manufacture process. In this study, the effects of GNPs on the SPS processing of Al2O3 are investigated by systematically varying sintering temperature, holding time and pressure. Our experiments showed that SPS process is also appropriate for the synthesis of nanocrystalline powders of alumina-graphene composites. Depending on the size of the molds, it is possible to obtain different amount of nanopowders. Investigation of the structure, physical-chemical, mechanical and performance properties of the elaborated composite materials was performed. The results of this study provide a fundamental understanding of the effects of GNP on sintering behavior, thereby providing a foundation for future optimization of the processing of these promising nanocomposite systems.

Keywords: alumina oxide, ceramic matrix composites, graphene nanoplatelets, spark-plasma sintering

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Authors: Gangadhara Siva Naga Venkata Krishna Satya Narayana Swamy Undi

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Particulate matter (PM) pollution in ambient air is a major environmental health risk factor contributing to disease and mortality worldwide. Current air pollution control methods have limitations in reducing real-world ambient PM levels. This study demonstrates the efficacy of using pulsed radio wave technology as a distinct approach to lower outdoor particulate pollution. Experimental data were compared with computational models to evaluate the efficiency of pulsed waves in coagulating and settling PM. Results showed 50%+ reductions in PM2.5 and PM10 concentrations at the city scale, with particle removal rates exceeding gravity settling by over 3X. Historical air quality data further validated the significant PM reductions achieved in test cases. Computational analyses revealed the underlying coagulation mechanisms induced by the pulsed waves, supporting the feasibility of this strategy for ambient particulate control. The pulsed electromagnetic technology displayed robustness in sustainably managing PM levels across diverse urban and industrial environments. Findings highlight the promise of this advanced approach as a next-generation solution to mitigate particulate air pollution and associated health burdens globally. The technology's scalability and energy efficiency can help address a key gap in current efforts to improve ambient air quality.

Keywords: particulate matter, mitigation technologies, clean air, ambient air pollution

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Authors: Julien Deborde, Thomas Milcent, Stéphane Glockner, Pierre Lubin

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A fully Eulerian method is developed to solve the problem of fluid-elastic structure interactions based on a 1-fluid method. The interface between the fluid and the elastic structure is captured by a level set function, advected by the fluid velocity and solved with a WENO 5 scheme. The elastic deformations are computed in an Eulerian framework thanks to the backward characteristics. We use the Neo Hookean or Mooney Rivlin hyperelastic models and the elastic forces are incorporated as a source term in the incompressible Navier-Stokes equations. The velocity/pressure coupling is solved with a pressure-correction method and the equations are discretized by finite volume schemes on a Cartesian grid. The main difficulty resides in that large deformations in the fluid cause numerical instabilities. In order to avoid these problems, we use a re-initialization process for the level set and linear extrapolation of the backward characteristics. First, we verify and validate our approach on several test cases, including the benchmark of FSI proposed by Turek. Next, we apply this method to study the wave damping phenomenon which is a mean to reduce the waves impact on the coastline. So far, to our knowledge, only simulations with rigid or one dimensional elastic structure has been studied in the literature. We propose to place elastic structures on the seabed and we present results where 50 % of waves energy is absorbed.

Keywords: damping wave, Eulerian formulation, finite volume, fluid structure interaction, hyperelastic material

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Authors: Patricia Heredia, Isabel Saz, Marta Fernández

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This article proposes that the decision regarding exporting and the choice of export channel are nested and non-independent decisions. We assume that firms make two sequential decisions before arriving at their final choice: the decision to access foreign markets and the decision about the type of channel. This hierarchical perspective of the choices involved in the process is appealing for two reasons. First, it supports the idea that people have a limited analytical capacity. Managers often break down a complex decision into a hierarchical process because this makes it more manageable. Secondly, it recognizes that important differences exist between entry modes. In light of the above, the objective of this study is to test different entry mode choice processes: independent decisions and nested and non-independent decisions. To do this, the methodology estimates and compares the following two models: (i) a simultaneous single-stage model with three entry mode choices (using a multinomial logit model); ii) a two-stage model with the export decision preceding the channel decision using a sequential logit model. The study uses resource-based factors in determining these decision processes concerning internationalization and the study carries out empirical analysis using a DOC Rioja sample of 177 firms.Using the Akaike and Schwarz Information Criteria, the empirical evidence supports the existence of a nested structure, where the decision about exporting precedes the export mode decision. The implications and contributions of the findings are discussed.

Keywords: sequential logit model, two-stage choice process, export mode, wine industry

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Authors: Tahmina Sultana, Yasser Hassan

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Vehicle technologies rapidly evolving due to their multifaceted advantages. Adapted different vehicle technologies like connectivity and automation on the same roads with conventional vehicles controlled by human drivers may increase speed disparity in mixed vehicle technologies. Identifying relationships between speed distribution measures of different vehicles and road geometry can be an indicator of speed disparity in mixed technologies. Previous studies proved that speed disparity measures and traffic accidents are inextricably related. Horizontal curves from three geographic areas were selected based on relevant criteria, and speed data were collected at the midpoint of the preceding tangent and starting, ending, and middle point of the curve. Multiple linear mixed effect models (LME) were developed using the instantaneous speed measures representing the speed of vehicles at different points of horizontal curves to recognize relationships between speed variance (standard deviation) and road geometry. A simulation-based framework (Monte Carlo) was introduced to check the speed disparity on horizontal curves in mixed vehicle technologies when consideration is given to the interactions among connected vehicles (CVs), autonomous vehicles (AVs), and non-connected vehicles (NCVs) on horizontal curves. The Monte Carlo method was used in the simulation to randomly sample values for the various parameters from their respective distributions. Theresults show that NCVs had higher speed variation than CVs and AVs. In addition, AVs and CVs contributed to reduce speed disparity in the mixed vehicle technologies in any penetration rates.

Keywords: autonomous vehicles, connected vehicles, non-connected vehicles, speed variance

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Authors: Chia-Chen Chen, Mu-Yen Chen

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In recent years, with the vigorous growth of hardware and software technologies of smart mobile devices coupling with the rapid increase of social network influence, mobile commerce also presents the commercial operation mode of the future mainstream. For the time being, SoLoMo has become one of the very popular commercial models, its full name and meaning mainly refer to that users can obtain three key service types through smart mobile devices (Mobile) and omnipresent network services, and then link to the social (Social) web site platform to obtain the information exchange, again collocating with position and situational awareness technology to get the service suitable for the location (Local), through anytime, anywhere and any personal use of different mobile devices to provide the service concept of seamless integration style, and more deriving infinite opportunities of the future. The study tries to explore the use intention of users with SoLoMo mobile application formula, proposing research model to integrate TAM, ISSM, IDT and network externality, and with questionnaires to collect data and analyze results to verify the hypothesis, results show that perceived ease-of-use (PEOU), perceived usefulness (PU), and network externality have significant impact on the use intention with SoLoMo mobile application formula, and the information quality, relative advantages and observability have impacts on the perceived usefulness, and further affecting the use intention.

Keywords: SoLoMo (social, local, and mobile), technology acceptance model, innovation diffusion theory, network externality

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Authors: Abdul Rahman Chamseddine

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The Companions of the Prophet Muhammad, the Sahaba, are regarded as the first link between him and later believers who did not know him or learn from him directly. This makes the Sahaba a link in the chain between God and the ummah (community). Apart from their role in spreading the Prophet’s teachings, they came to be regarded as role models, representing the Islamic ideal of life as prescribed by the Prophet himself. According to Hadith, the Prophet had promised some Sahaba unqualified admission to paradise. It is commonly agreed that the Sahaba have the following attributes in common: God is well pleased with them; they will surely go to paradise; they are perfectly trustworthy; and they are the authorities from whom Muslims can learn all matters related to their religion. No other generation of Muslims has received the attention received by the Companions of the Prophet. In spite of the importance of the Sahaba in Islam, we still know comparatively little about them. There are at least two reasons for this. First, there is the overall scarcity of information surviving from the early period. At the death of the Prophet, it is said, there were more than 100,000 Companions. As we shall see, this is a complex issue, involving the definition of the term Sahaba. However, only few Companions of the Prophet are known to us. Ibn Hajar al-‘Asqalani, who wrote in the fifteenth century A.D., was only able to collect facts about 11,000 of them (including those whose status as Sahaba was disputed). Ibn Sa‘d, Ibn ‘Abd al-Barr and Ibn al-Athir, all of whom lived earlier than Ibn Hajar, included in their respective works fewer lives of Sahaba than he did. If we consider Ibn Hajar’s Isaba as the most complete biographical account of the Sahaba that remains available, we have information, presumably, on approximately one tenth of them. The remaining nine tenths are apparently lost from the historical record. Second, discussion of the Sahaba tends to focus on those considered the most important among them such as ‘Uthman, ‘Ali and Mu‘awiya, while others, who together number in the thousands, are less well-known. This paper will try to study the origins of the term Sahaba that became exclusive to the Companions of the Prophet and not a synonym of the word companions in general.

Keywords: companions, Hadith, Islamic history, Muhammad, Sahaba, transmission

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Authors: Yuchao Yao

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As two of the main characteristics of Chinese demographic trends, increasing divorce rates and decreasing fertility rates both shaped the population structure in the recent decade. Figuring out to what extent can be having a child make a difference in the divorce rate of a couple will not only draw a picture of Chinese families but also bring about a new perspective to evaluate the Chinese child-breeding policies. Based on China Family Panel Studies (CFPS) Data 2010-2018, this paper provides a systematic evaluation of how children influence a couple’s marital stability through a series of empirical models. Using survival analysis and propensity score matching (PSM) model, this paper finds that the number and age of children that a couple has mattered in consolidating marital relationship, and these effects vary little over time; during the last decade, newly having children can in fact decrease the possibility of divorce for Chinese couples; the such decreasing effect is largely due to the birth of a second child. As this is an inclusive attempt to study and compare not only the effects but also the causality of children on divorce risk in the last decade, the results of this research will do a good summary of the status quo of divorce in China. Furthermore, this paper provides implications for further reforming the current marriage and child-breeding policies.

Keywords: divorce risk, fertility, China, survival analysis, propensity score matching

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Authors: Saman Mostafazadeh-Fard, Zohrab Samani, Kenneth Suazo

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Agricultural ditch liners are used to prevent soil erosion and reduce seepage losses. This paper introduced an approach to validate a computational fluid dynamics (CFD) platform FLOW-3D code and its use to design a flow-regulating corrugated agricultural ditch liner system (Smart Ditch (SM)). Hydrodynamic and sediment transport analyses were performed on the proposed liner flow using the CFD platform FLOW-3D code. The code's hydrodynamic and scour and sediment transport models were calibrated and validated using lab data with an accuracy of 94 % and 95%, respectively. The code was then used to measure hydrodynamic parameters of sublayer turbulent intensity, kinetic energy, dissipation, and packed sediment mass normalized with respect to sublayer flow velocity. Sublayer turbulent intensity, kinetic energy, and dissipation in the SM flow were significantly higher than CR flow. An alternative corrugated liner was also designed, and sediment transport was measured and compared to SM and CR flows. Normalized packed sediment mass with respect to average sublayer flow velocity was 27.8 % lower in alternative flow compared to SM flow. CFD platform FLOW-3D code could effectively be used to design corrugated ditch liner systems and perform hydrodynamic and sediment transport analysis under various corrugation designs.

Keywords: CFD, hydrodynamic, sediment transport, ditch, liner design

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Authors: Collence Takaingenhamo Chisita, Munyaradzi Shoko

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Library and Information Science Schools play significant roles in socio–economic transformation but in most cases they are downplayed or overshadowed by other institutions, and professions. Currently Zimbabwe boasts of high literacy rate in Africa and this success would have been impossible without the contributions of library schools and related institutions. Libraries and librarians are at the epicentre of socio-economic development and their role cannot be downplayed. It is out of this context that the writer will explore the extent to which library schools are contributing towards socio-economic transformation, for example, human capital development and facilitating access to information. The writer will seek to explain and clarify how LIS schools are engaged in socio-economic transformation through supporting education and culture through community engagement. The paper will examine the LIS education models, for example, general education and Technical Vocational Education and Training (TVET) or Competency Based Education and Training (CBET). It will also seek to find out how LIS Schools are contributing to the information/knowledge economy through education, training and research. The writer will also seek to find out how LIS Education is responding to socio-economic and political dynamics in Zimbabwe amidst forces of globalisation and cultural identities. Furthermore, the writer will explore the extent to which LIS education can help to reposition Zimbabwe in the global knowledge economy. The author will examine how LIS schools integrate culture and technology.

Keywords: development, information/knowledge economy, culture, empowerment, collaboration, globalisation

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Authors: B. Cheknane, F. Zermane

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The main objective of the present study is the valorization of natural raw materials of plant origin for the treatment of textile industry wastewater. Selected bark was: maritime (MP), pinyon (PP) and Aleppo pine (AP) bark. The efficiency of these barks were tested for the removal of three dye; rhodamine B (RhB), Green Malachite (GM) and X Methyl Orange (MO). At the first time we focus to study the different parameters which can influence the adsorption processes such as: nature of the adsorbents, nature of the pollutants (dyes) and the effect of pH. Obtained results reveals that the speed adsorption is strongly influencing by the pH medium and the comparative study show that adsorption is favorable in the acidic medium with amount adsorbed of (Q=40mg/g) for rhodamine B and (Q=46mg/g) for orange methyl. Results of adsorption kinetics reveals that the molecules of GM are adsorbed better (Q=48mg/g) than the molecules of RhB (Q=46mg/g) and methyl orange (Q=18mg/g), with equilibrium time of 6 hours. The results of adsorption isotherms show clearly that the maritime pine bark is the most effective adsorbents with adsorbed amount of (QRhB=200mg/g) and (QMO=88mg/g) followed by pinyon pine (PP) with (QRhB=184mg/g) and (QMO=56mg/g) and finally Aleppo pine (AP) bark with (QRhB=131mg/g) and (QMO= 46mg/g). The different obtained isotherms were modeled using the Langmuir and Freundlich models and according to the adjustment coefficient values R2, the obtained isotherms are well represented by Freundlich model.

Keywords: maritime pine bark (MP), pinyon pine bark (PP), Aleppo pine (AP) bark, adsorption, dyes

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Authors: Vladimir Hovhannisyan, Chen Yuan Dong

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Recently nanoparticles (NPs) have been introduced in biomedicine as effective agents for cancer-targeted drug delivery and noninvasive tissue imaging. The most important requirements to these agents are their non-toxicity, biocompatibility and stability. In view of these criteria, the zeolite (ZL) nanoparticles (NPs) may be considered as perfect candidates for biomedical applications. ZLs are crystalline aluminosilicates consisting of oxygen-sharing SiO4 and AlO4 tetrahedral groups united by common vertices in three-dimensional framework and containing pores with diameters from 0.3 to 1.2 nm. Generally, the behavior and physical properties of ZLs are studied by SEM, X-ray spectroscopy, and AFM, whereas optical spectroscopic and microscopic approaches are not effective enough, because of strong scattering in common ZL bulk materials and powders. The light scattering can be reduced by using of ZL NPs. ZL NPs have large external surface area, high dispersibility in both aqueous and organic solutions, high photo- and thermal stability, and exceptional ability to adsorb various molecules and atoms in their nanopores. In this report, using multiphoton microscopy and nonlinear spectroscopy, we investigate nonlinear optical properties of clinoptilolite type of ZL micro- and nanoparticles with average diameters of 2200 nm and 240 nm, correspondingly. Multiphoton imaging is achieved using a laser scanning microscope system (LSM 510 META, Zeiss, Germany) coupled to a femtosecond titanium:sapphire laser (repetition rate- 80 MHz, pulse duration-120 fs, radiation wavelength- 720-820 nm) (Tsunami, Spectra-Physics, CA). Two Zeiss, Plan-Neofluar objectives (air immersion 20×∕NA 0.5 and water immersion 40×∕NA 1.2) are used for imaging. For the detection of the nonlinear response, we use two detection channels with 380-400 nm and 435-700 nm spectral bandwidths. We demonstrate that ZL micro- and nanoparticles can produce nonlinear optical response under the near-infrared femtosecond laser excitation. The interaction of hypericine, chlorin e6 and other dyes with ZL NPs and their photodynamic activity is investigated. Particularly, multiphoton imaging shows that individual ZL NPs particles adsorb Zn-tetraporphyrin molecules, but do not adsorb fluorescein molecules. In addition, nonlinear spectral properties of ZL NPs in native biotissues are studied. Nonlinear microscopy and spectroscopy may open new perspectives in the research and application of ZL NP in biomedicine, and the results may help to introduce novel approaches into the clinical environment.

Keywords: multiphoton microscopy, nanoparticles, nonlinear optics, zeolite

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Authors: Sun-Ki Choi

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The U.S. student loan policy was initiated to improve the equality of educational opportunity and help low-income families to provide higher education opportunities for their children. However, with the increase in the average student loan amount, college graduates with student loans experience problems and restrictions in their early-career choices. This study examines the early career labor market choices of college graduates who obtained student loans to finance their higher education. In this study, National Survey of College Graduates (NSCG) data for 2017 and 2019 was used to estimate the effects of student loans on the employment status and current job wages of graduates with student loans. In the analysis, two groups of workers, those with student loans and those without loans, were compared. Using basic models and Mahalanobis distance matching, it was found that graduates who rely on student loans to finance their education are more likely to participate in the labor market than those who do not. Moreover, in entry-level jobs, graduates with student loans receive lower salaries than those without student loans. College graduates make job-related decisions based on their current and future wages and fringe benefits. Graduates with student loans tend to demonstrate risk-averse behaviors due to their financial restrictions. Thus, student loan debt creates inequity in the early-career labor market for college graduates. Furthermore, this study has implications for policymakers and researchers in terms of the student loan policy.

Keywords: student loan, wage differential, unintended consequences, mahalanobis distance matching

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Authors: Adel Ali Elshaibani

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Risk management indicators augment the reporting infrastructure, particularly for the board and senior management, to identify, monitor, and manage risks. This enhancement facilitates improved decision-making throughout the banking organization. Decision tree analysis is a tool that visually outlines potential outcomes, costs, and consequences of complex decisions. It is particularly beneficial for analyzing quantitative data and making decisions based on numerical values. By calculating the expected value of each outcome, decision tree analysis can help assess the best course of action. In the context of banking, decision tree analysis can assist lenders in evaluating a customer’s creditworthiness, thereby preventing losses. However, applying these tools in developing countries may face several limitations, such as data availability, lack of technological infrastructure and resources, lack of skilled professionals, cultural factors, and cost. Moreover, decision trees can create overly complex models that do not generalize well to new data, known as overfitting. They can also be sensitive to small changes in the data, which can result in different tree structures and can become computationally expensive when dealing with large datasets. In conclusion, while risk management indicators and decision tree analysis are beneficial for decision-making in banks, their effectiveness is contingent upon how they are implemented and utilized by the board of directors, especially in the context of developing countries. It’s important to consider these limitations when planning to implement these tools in developing countries.

Keywords: risk management indicators, decision tree analysis, developing countries, board of directors, bank performance, risk management strategy, banking institutions

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Authors: Imali T. Jayamanne, K. P. Asoka Ramanayake

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Transition from tertiary level education to employment is one of the challenges that many fresh university graduates face after graduation. The transition period or the waiting time to obtain the first employment varies with the socio-economic factors and the general characteristics of a graduate. Compared to other fields of study, Arts graduates in Sri Lanka, have to wait a long time to find their first employment. The objective of this study is to identify the determinants of the transition from higher education to employment of these graduates using survival models. The study is based on a survey that was conducted in the year 2016 on a stratified random sample of Arts graduates from Sri Lankan universities who had graduated in 2012. Among the 469 responses, 36 (8%) waiting times were interval censored and 13 (3%) were right censored. Waiting time for the first employment varied between zero to 51 months. Initially, the log-rank and the Gehan-Wilcoxon tests were performed to identify the significant factors. Gender, ethnicity, GCE Advanced level English grade, civil status, university, class received, degree type, sector of first employment, type of first employment and the educational qualifications required for the first employment were significant at 10%. The Cox proportional hazards model was fitted to model the waiting time for first employment with these significant factors. All factors, except ethnicity and type of employment were significant at 5%. However, since the proportional hazard assumption was violated, the lognormal Accelerated failure time (AFT) model was fitted to model the waiting time for the first employment. The same factors were significant in the AFT model as in Cox proportional model.

Keywords: AFT model, first employment, proportional hazard, survey design, waiting time

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Authors: Jia-Yu Wu, Chih-Han Chang, Shu-Fen Chuang, Rong-Yang Lai

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Objective: This study was to examine the stress distribution of tooth with different class V restorations under different loading situations and geometry by 3D finite element (FE) analysis. `Methods: A series of FE models of mandibular premolars containing class V cavities were constructed using micro-CT. The class V cavities were assigned as the combinations of different cavity depths x occlusal -gingival heights: 1x2, 1x4, 2x2, and 2x4 mm. Three alveolar bone loss conditions were examined: 0, 1, and 2 mm. 200 N force was exerted on the buccal cusp tip under various directions (vertical, V; obliquely 30° angled, O; oblique and parallel the individual occlusal cavity wall, P). A 3-D FE analysis was performed and the von-Mises stress was used to summarize the data of stress distribution and maximum stress. Results: The maximal stress did not vary in different alveolar bone heights. For each geometry, the maximal stress was found at bilateral corners of the cavity. The peak stress of restorations was significantly higher under load P compared to those under loads V and O while the latter two were similar. 2x2mm cavity exhibited significantly increased (2.88 fold) stress under load P compared to that under load V, followed by 1x2mm (2.11 fold), 2x4mm (1.98 fold) and 1x4mm (1.1fold). Conclusion: Load direction causes the greatest impact on the results of stress, while the effect of alveolar bone loss is minor. Load direction parallel to the cavity wall may enhance the stress concentration especially in deep and narrow class cavities.

Keywords: class v restoration, finite element analysis, loading situation, stress

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Authors: Oludare Isaac Abiodun, Esther Omolara Abiodun

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The purpose of this paper is to demonstrate that cyberterrorism is existing and poses a threat to computer security and national security. Nowadays, people have become excitedly dependent upon computers, phones, the Internet, and the Internet of things systems to share information, communicate, conduct a search, etc. However, these network systems are at risk from a different source that is known and unknown. These network systems risk being caused by some malicious individuals, groups, organizations, or governments, they take advantage of vulnerabilities in the computer system to hawk sensitive information from people, organizations, or governments. In doing so, they are engaging themselves in computer threats, crime, and terrorism, thereby making the use of computers insecure for others. The threat of cyberterrorism is of various forms and ranges from one country to another country. These threats include disrupting communications and information, stealing data, destroying data, leaking, and breaching data, interfering with messages and networks, and in some cases, demanding financial rewards for stolen data. Hence, this study identifies many ways that cyberterrorists utilize the Internet as a tool to advance their malicious mission, which negatively affects computer security and safety. One could identify causes for disparate anomaly behaviors and the theoretical, ideological, and current forms of the likelihood of cyberterrorism. Therefore, for a countermeasure, this paper proposes the use of previous and current computer security models as found in the literature to help in countering cyberterrorism

Keywords: cyberterrorism, computer security, information, internet, terrorism, threat, digital forensic solution

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Authors: R. Hellmuth, F. Wehner

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Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Short-term rescheduling can no longer be handled by on-site inspections and manual measurements. The tight time schedules require up-to-date planning models. Due to the high adaptation rate of factories described above, a methodology for rescheduling factories on the basis of a modern digital factory twin is conceived and designed for practical application in factory restructuring projects. The focus is on rebuild processes. The aim is to keep the planning basis (digital factory model) for conversions within a factory up to date. This requires the application of a methodology that reduces the deficits of existing approaches. The aim is to show how a digital factory model can be kept up to date during ongoing factory operation. A method based on photogrammetry technology is presented. The focus is on developing a simple and cost-effective solution to track the many changes that occur in a factory building during operation. The method is preceded by a hardware and software comparison to identify the most economical and fastest variant. 

Keywords: digital factory model, photogrammetry, factory planning, restructuring

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Authors: Y. J. Wang, C. Q. Ru

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A key issue of cohesive zone models is how to determine the cohesive zone model (CZM) parameters based on real material test data. In this paper, uniaxial nominal stress-strain curve (SS curve) is used to determine two key parameters of a cohesive zone model: the maximum traction and the area under the curve of traction-separation law (TSL). To this end, the true SS curve is obtained based on the nominal SS curve, and the relationship between the nominal SS curve and TSL is derived based on an assumption that the stress for cracking should be the same in both CZM and the real material. In particular, the true SS curve after necking is derived from the nominal SS curve by taking the average of the power law extrapolation and the linear extrapolation, and a damage factor is introduced to offset the true stress reduction caused by the voids generated at the necking zone. The maximum traction of the TSL is equal to the maximum true stress calculated based on the damage factor at the end of hardening. In addition, a simple specimen is simulated by Abaqus/Standard to calculate the critical J-integral, and the fracture energy calculated by the critical J-integral represents the stored strain energy in the necking zone calculated by the true SS curve. Finally, the CZM parameters obtained by the present method are compared to those used in a previous related work for a simulation of the drop-weight tear test.

Keywords: dynamic fracture, cohesive zone model, traction-separation law, stress-strain curve, J-integral

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Authors: Asif Husain, Shah Alam Khan

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Coumarins and flavones are oxygen containing heterocyclic compounds which are present in various biologically active compounds. Both the heterocyclic rings are associated with diverse biological actions, therefore considered as an important scaffold for the design of molecules of pharmaceutical interest. Aim: To synthesize and evaluate the in vivo anti-inflammatory activity of few coumrain and flavone derivatives containing 1,4 dioxane ring system. Materials and methods: Coumarin derivatives (3a-d) were synthesized by reacting 7,8 dihydroxy coumarin (2a) and its 4-methyl derivative (2b) with epichlorohydrin/ethylene dibromide. The flavone derivatives (10a-d) were prepared by using quercetin and 3,4 dihydroxy flavones. Compounds of both the series were also evaluated for their anti-inflammatory, analgesic activity and ulcerogenicity in animal models by reported methods. Results and Discussion: The structures of all newly synthesized compounds were confirmed with the help of IR, 1H NMR, 13C NMR and Mass spectral studies. Elemental analyses data for each element analyzed (C, H, N) was found to be within acceptable range of ±0.4 %. Flavone derivatives, but in particular quercetin containing 1,4 dioxane ring system (10d) showed better anti-inflammatory and analgesic activity along with reduced gastrointestinal toxicity as compared to other synthesized compounds. The results of anti-inflammatory and analgesic activities of both the series are comparable with the positive control, diclofenac. Conclusion: Compound 10d, a quercetin derivative, emerged as a lead molecule which exhibited potent anti-inflammatory and analgesic activity with significant reduced gastric toxicity.

Keywords: analgesic, anti-inflammatory, 1, 4 dioxane, coumarin, flavone

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Authors: Junior Nomani

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This paper presents a novel approach to modelling the metal cutting of duplex stainless steels, a two-phase alloy regarded as a difficult-to-machine material. Calculation and control of shear strain and stresses during cutting are essential to achievement of ideal cutting conditions. Too low or too high leads to higher required cutting force or excessive heat generation causing premature tool wear failure. A 2D finite element cutting model was created based on electron backscatter diffraction (EBSD) data imagery of duplex microstructure. A mesh was generated using ‘object-oriented’ software OOF2 version V2.1.11, converting microstructural images to quadrilateral elements. A virtual workpiece was created on ABAQUS modelling software where a rigid body toolpiece advanced towards workpiece simulating chip formation, generating serrated edge chip formation cutting. Model results found calculated stress strain contour plots correlated well with similar finite element models tied with austenite stainless steel alloys. Virtual chip form profile is also similar compared experimental frozen machining chip samples. The output model data provides new insight description of strain behavior of two phase material on how it transitions from workpiece into the chip.

Keywords: Duplex stainless steel, ABAQUS, OOF2, Chip formation

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Authors: Pasquali Frederique, Manfreda Chiara, Crippa Cecilia, Indio Valentina, Ianieri Adriana, De Cesare Alessandra

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Microbiological hazards can be transmitted to humans through milk. In this study, we compared the microbiome composition and presence of foodborne pathogens in organic milk (n=6), organic hay milk (n=6), standard milk (n=6) and high-quality milk (n=6). The milk samples were collected during six samplings between December 2022 to January 2023 and between April and May 2024 to take into account seasonal variations. The 24 milk samples were submitted to DNA extraction and library preparation before shotgun sequencing on the Illumina HiScan™ SQ System platform. The total sequencing output was 600 GB. In all the milk samples, the phyla with the highest relative abundances were Pseudomonadota, Bacillota, Ascomycota, Actinomycetota and Apicomplexa, while the most represented genera were Pseudomonas, Streptococcus, Geotrichum, Acinetobacter and Babesia. The alpha and beta diversity indexes showed a clear separation between the microbiome of high-quality milk and those of the other milk types. Moreover, in the high-quality milk, the relative abundance of Staphylococcus (4.4%), Campylobacter (4.5%), Bacillus (2.5%), Enterococcus (2.4%), Klebsiella (1.3%) and Escherichia (0 .7%) was significantly higher in comparison to other types of milk. On the contrary, the relative abundance of Geotrichum (0.5%) was significantly lower. The microbiome results collected in this study showed significant differences in terms of the relative abundance of bacteria genera, including foodborne pathogen species. These results should be incorporated into risk assessment models tailored to different types of milk.

Keywords: raw milk, foodborne pathogens, microbiome, risk assessment

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Authors: Salma Krafessi

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The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

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Authors: Lynda K. Eneh, Okal N. Mike, Anna-Karin Borg-Karlson, Ulrike Fillinger, Jenny M. Lindh

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The responses of individual gravid Anopheles gambiae sensu stricto (s.s.) to hay infusion volatiles were evaluated under laboratory conditions. Such infusions have long been known to be effective baits for monitoring mosquitoes that vector arboviral and filarial diseases but have previously not been tested for malaria vectors. Hay infusions were prepared by adding sun-dried Bermuda grass to lake water and leaving the mixture in a covered bucket for three days. The proportions of eggs laid by gravid An. gambiae s.s. in diluted (10%) and concentrated infusions ( ≥ 25%) was compared to that laid in lake water in two-choice egg-count bioassays. Furthermore, with the aim to develop a method that can be used to collect volatiles that influence the egg-laying behavior of malaria mosquitoes, different volatile trapping methods were investigated. Two different polymer-traps eluted using two different desorption methods and three parameters were investigated. Porapak®-Q traps and solvent desorption was compared to Tenax®-TA traps and thermal desorption. The parameters investigated were: collection time (1h vs. 20h), addition of salt (0.15 g/ml sodium chloride (NaCl) vs. no NaCl), and stirring the infusion (0 vs. 300 rpm). Sample analysis was with gas chromatography-mass spectrometry (GC-MS). An. gambiae s.s was ten times less likely to lay eggs in concentrated hay infusion than in lake water. The volatiles were best characterized by thermally desorbed Tenax traps, collected for 20 hours from infusion aliquots with sodium chloride added. Ten volatiles identified from headspace and previously indicated as putative oviposition semiochemicals for An. gambiae s.s. or confirmed semiochemicals for other mosquito species were tested in egg-count bioassays. Six of these (3-methylbutanol, phenol, 4-methylphenol, nonanal, indole and 3-methylindole), when added to lake water, were avoided for egg-laying when lake water was offered as the alternative in dual-choice egg count bioassays. These compounds likely contribute to the unfavorable oviposition responses towards hay infusions. This difference in oviposition response of different mosquito species should be considered when designing control measures.

Keywords: Anopheles gambiae, oviposition behaviour, egg-count cage bioassays, hay infusions, volatile detection, semiochemicals

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Yongsheng Guo, Shuchao Li

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This study explores Chinese foreign direct investment (FDI) in Europe and the cross-cultural cooperation between Chinese and European managers. The aim of this research is to shed light on the phenomenon of investments in developed countries from an emerging market and to gain insights into the cooperation process. A grounded theory approach is adopted, and 46 semi-structured interviews were conducted with 10 case companies in Germany and 13 case companies in the UK. Grounded theory models are developed from primary data and interview quotes are used to support the themes. The interviewees perceived differences between the two parties in cultural traits, management concepts, knowledge structure and resource endowment between the two parties. Chinese and European partners can take advantage of different resources and cooperate in innovative ways to improve corporate performance. Moreover, both parties appreciate different ethical and cultural characteristics and complement each other to develop a combined organizational culture. This study proposes an ethical and cultural diversity theory in international management arguing that a team with diversified values and behaviors may be more excited and motivated. This study suggests that “resource complement” and “cross-cultural cooperation” might be an advantage for international investment. Firms are encouraged to open their minds and cooperate with partners with different resources and cultures. The authorities may review the FDI policies to reduce social and political barriers.

Keywords: cross-culture, FDI, cooperation, innovation, China, Europe

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Authors: Jennifer K. Bowerman, Rhonda L. Reich

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The purpose of this paper is to explore the concepts ACDC (Amore, Consciousness, Discipline, and Commitment) which the authors first discovered as a philosophy and framework for recruitment and organizational development in a successful start-up tech company in Brazil. This paper represents an exploration of these concepts as a potential pedagogical foundation for undergraduate business education in the classroom. It explores whether their application has potential to build emotional and practical resilience in the face of constant organizational and societal change. Derived from Holonomy this paper explains the concepts and develops a narrative around how change influences the operation of organizations. Using examples from leading edge organizational theorists, it explains why a different educational approach grounded in ACDC concepts may not only have relevance for the working world, but also for undergraduates about to enter that world. The authors propose that in the global context of constant change, it makes sense to develop an approach to education, particularly business education, beyond cognitive knowledge, models and tools, in such a way that emotional and practical resilience and creative thinking may be developed. Using the classroom as an opportunity to explore these concepts, and aligning personal passion with the necessary discipline and commitment, may provide students with a greater sense of their own worth and potential as they venture into their ever-changing futures.

Keywords: ACDC, holonomic thinking, organizational learning, organizational change, business pedagogy

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Authors: Suzanne Giasson, Alberto Guerron

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Stimuli-responsive polymer coatings can be used as functional elements in nanotechnologies, such as valves in microfluidic devices, as membranes in biomedical engineering, as substrates for the culture of biological tissues or in developing nanomaterials for targeted therapies in different diseases. However, such coatings usually suffer from major shortcomings, such as a lack of selectivity and poor environmental stability. The study will present multi-responsive hierarchical and hybrid polymer-based coatings aiming to overcome some of these limitations. Hierarchical polymer coatings, consisting of two-dimensional arrays of thermo-responsive cationic PNIPAM-based microgels and surface-functionalized with non-responsive or pH-responsive polymers, were covalently grafted to substrates to tune the surface chemistry and the elasticity of the surface independently using different stimuli. The characteristic dimensions (i.e., layer thickness) and surface properties (i.e., adhesion, friction) of the microgel coatings were assessed using the Surface Forces Apparatus. The ability to independently control the swelling and surface properties using temperature and pH as triggers were investigated for microgels in aqueous suspension and microgels immobilized on substrates. Polymer chain grafting did not impede the ability of cationic PNIPAM microgels to undergo a volume phase transition above the VPTT, either in suspension or immobilized on a substrate. Due to the presence of amino groups throughout the entirety of the microgel polymer network, the swelling behavior was also pH dependent. However, the thermo-responsive swelling was more significant than the pH-triggered one. The microgels functionalized with PEG exhibited the most promising behavior. Indeed, the thermo-triggered swelling of microgel-co-PEG did not give rise to changes in the microgel surface properties (i.e., surface potential and adhesion) within a wide range of pH values. It was possible for the immobilized microgel-co-PEG to undergo a volume transition (swelling/shrinking) with no change in adhesion, suggesting that the surface of the thermal-responsive microgels remains rather hydrophilic above the VPTT. This work confirms the possibility of tuning the swelling behavior of microgels without changing the adhesive properties. Responsive surfaces whose swelling properties can be reversibly and externally altered over space and time regardless of the surface chemistry are very innovative and will enable revolutionary advances in technologies, particularly in biomedical surface engineering and microfluidics, where advanced assembly of functional components is increasingly required.

Keywords: responsive materials, polymers, surfaces, cell culture

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: Pavana Basavakumar, Devadas Bhat

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Diabetes is a disease which often goes undiagnosed until its secondary effects are noticed. Early detection of the disease is necessary to avoid serious consequences which could lead to the death of the patient. Conventional invasive tests for screening of diabetes are mostly painful, time consuming and expensive. There’s also a risk of infection involved, therefore it is very essential to develop non-invasive methods to screen and estimate the level of blood glucose. Extensive research is going on with this perspective, involving various techniques that explore optical, electrical, chemical and thermal properties of the human body that directly or indirectly depend on the blood glucose concentration. Thus, non-invasive blood glucose monitoring has grown into a vast field of research. In this project, an attempt was made to device a prototype for screening of diabetes by measuring electrical impedance of the skin and building a model to predict a patient’s condition based on the measured impedance. The prototype developed, passes a negligible amount of constant current (0.5mA) across a subject’s index finger through tetra polar silver electrodes and measures output voltage across a wide range of frequencies (10 KHz – 4 MHz). The measured voltage is proportional to the impedance of the skin. The impedance was acquired in real-time for further analysis. Study was conducted on over 75 subjects with permission from the institutional ethics committee, along with impedance, subject’s blood glucose values were also noted, using conventional method. Nonlinear regression analysis was performed on the features extracted from the impedance data to obtain a model that predicts blood glucose values for a given set of features. When the predicted data was depicted on Clarke’s Error Grid, only 58% of the values predicted were clinically acceptable. Since the objective of the project was to screen diabetes and not actual estimation of blood glucose, the data was classified into three classes ‘NORMAL FASTING’,’NORMAL POSTPRANDIAL’ and ‘HIGH’ using linear Support Vector Machine (SVM). Classification accuracy obtained was 91.4%. The developed prototype was economical, fast and pain free. Thus, it can be used for mass screening of diabetes.

Keywords: Clarke’s error grid, electrical impedance of skin, linear SVM, nonlinear regression, non-invasive blood glucose monitoring, screening device for diabetes

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