Search results for: impact models

Authors: Huda Al-Shuaily, E. M. Lacap

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Higher Education is one of the most essential fundamentals for the advancement and progress of a country. It demands to be as accessible as possible and as comprehensive as it can be reached. In this paper, we succeeded to expand the accessibility and delivery of higher education using an Open Educational Resources (OER), a freely accessible, openly licensed documents, and media for teaching and learning. This study creates a comparative design of student’s academic performance on the course Introduction to Database and student engagement to the virtual learning environment (VLE). The study was done in two successive semesters - one without using the OER and the other is using OER. In the study, we established that there is a significant increase in student’s engagement in VLE in the latter semester compared to the former. By using the latter semester’s data, we manage to show that the student’s engagement has a positive impact on students’ academic performance. Moreso, after clustering their academic performance, the impact is seen higher for students who are low performing. The results show that these engagements can be used to potentially predict the learning styles of the student with a high degree of precision.

Keywords: EDM, learning analytics, moodle, OER, student-engagement

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Authors: E. O. E. Nnadi

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Transportation is a critical factor in the economic growth and development of any nation, region or state. Good transportation network supports every sector of the economy like the manufacturing, transportation and encourages investors thereby affect the overall economic prosperity. The paper evaluates the impact of transportation on the economic growth of Nigeria using south eastern states as a case study. The choice of the case study is its importance as the commercial and industrial nerve of the country. About 200 respondents who are of different professions such as dealers in goods, transporters, contractors, consultants, bankers were selected and a set of questionnaire were administered to using the systematic sampling technique in the five states of the region. Descriptive statistics and relative importance index (RII) technique was employed for the analysis of the data gathered. The findings of the analysis reveal that Nigeria has the least effective ratio per population in Africa of 949.91 km/Person. Conclusion was drawn to improve road network in the area and the country as a whole to enhance the economic activities of the people.

Keywords: economic growth, south-east, transportation, transportation cost, Nigeria

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Authors: Daniel Martinez, Tim de Leeuw, Stefan Haefliger

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The challenges of managing a large and geographically dispersed R&D organization have been further increasing during the past years, concentrating on the leverage of a geo-graphically dispersed body of knowledge in an efficient and effective manner. In order to reduce complexity and improve performance, firms introduce product modularity as one key element for global R&D network teams to develop their products and projects in collaboration. However, empirical studies on the effects of product modularity on innovation performance are really scant. Furthermore, some researchers have suggested that product modularity promotes innovation performance, while others argue that it inhibits innovation performance. This research fills this gap by investigating the impact of product modularity on various dimensions of innovation performance, i.e. effectiveness and efficiency. By constructing the theoretical framework, this study suggests that that there is an inverted U-shaped relationship between product modularity and innovation performance. Moreover, this research work suggests that the optimum of innovation performance efficiency will be at a higher level than innovation performance effectiveness at a given product modularity level.

Keywords: modularity, innovation performance, networks, R&D, collaboration

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Authors: Lidiia Nazarenko, Henryk Stolarski, Holm Altenbach

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In the paper, a (hierarchical) approach to analysis of thermo-elastic properties of random composites with interphases is outlined and illustrated. It is based on the statistical homogenization method – the method of conditional moments – combined with recently introduced notion of the energy-equivalent inhomogeneity which, in this paper, is extended to include thermal effects. After exposition of the general principles, the approach is applied in the investigation of the effective thermo-elastic properties of a material with randomly distributed nanoparticles. The basic idea of equivalent inhomogeneity is to replace the inhomogeneity and the surrounding it interphase by a single equivalent inhomogeneity of constant stiffness tensor and coefficient of thermal expansion, combining thermal and elastic properties of both. The equivalent inhomogeneity is then perfectly bonded to the matrix which allows to analyze composites with interphases using techniques devised for problems without interphases. From the mechanical viewpoint, definition of the equivalent inhomogeneity is based on Hill’s energy equivalence principle, applied to the problem consisting only of the original inhomogeneity and its interphase. It is more general than the definitions proposed in the past in that, conceptually and practically, it allows to consider inhomogeneities of various shapes and various models of interphases. This is illustrated considering spherical particles with two models of interphases, Gurtin-Murdoch material surface model and spring layer model. The resulting equivalent inhomogeneities are subsequently used to determine effective thermo-elastic properties of randomly distributed particulate composites. The effective stiffness tensor and coefficient of thermal extension of the material with so defined equivalent inhomogeneities are determined by the method of conditional moments. Closed-form expressions for the effective thermo-elastic parameters of a composite consisting of a matrix and randomly distributed spherical inhomogeneities are derived for the bulk and the shear moduli as well as for the coefficient of thermal expansion. Dependence of the effective parameters on the interphase properties is included in the resulting expressions, exhibiting analytically the nature of the size-effects in nanomaterials. As a numerical example, the epoxy matrix with randomly distributed spherical glass particles is investigated. The dependence of the effective bulk and shear moduli, as well as of the effective thermal expansion coefficient on the particle volume fraction (for different radii of nanoparticles) and on the radius of nanoparticle (for fixed volume fraction of nanoparticles) for different interphase models are compared to and discussed in the context of other theoretical predictions. Possible applications of the proposed approach to short-fiber composites with various types of interphases are discussed.

Keywords: effective properties, energy equivalence, Gurtin-Murdoch surface model, interphase, random composites, spherical equivalent inhomogeneity, spring layer model

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Authors: Nadia Fatima Zahra Malki

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Quality is one of the most important modern management patterns that organizations seek to achieve in all areas and sectors in order to meet the needs and desires of customers and to remain and continuity, as they constitute a competitive advantage for the organization. and among the most prominent organizations that must be available on the quality factor are health organizations as they relate to the most valuable component of production. It is a person, and his health, and any error in it threatens his life and may lead to death, so she must provide health services of high quality to achieve the highest degree of satisfaction for the patient. This research aims to study the quality of health services and the extent of their impact on patient satisfaction, and this is through an applied study that relied on measuring the level of quality of health services in the university hospital center of Algeria and the extent of their impact on patient satisfaction according to the dimensions of the quality of health services, and we reached a conclusion that the determinants of the quality of health services It affects patient satisfaction, which necessitates developing health services according to patients' requirements and improving their quality to obtain patient satisfaction.

Keywords: health service, health quality, quality determinants, patient satisfaction

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Authors: Aderet Pantierer, Shmuel Pantierer, Atif Saeed, Amir Elzawawy

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In recent years, air travel has seen volatile growth. Due to this growth, the maximization of efficiency and space utilization has been a major issue for aircraft manufacturers. Elongation of the wingspan of aircraft has resulted in increased lift; and, thereby, efficiency. However, increasing the wingspan of aircraft has been detrimental to the manufacturing process and has led to airport congestion and required airport reconfiguration to accommodate the extended wingspans of aircraft. This project outlines differing wing configurations of a commercial aircraft and the effects on the aerodynamic loads produced. Multiple wing configurations are analyzed using Finite Element Models. These models are then validated by testing one wing configuration in a wind tunnel under laminar flow and turbulent flow conditions. The wing configurations to be tested include high and low wing aircraft, as well as various combinations of the two, including a unique model hereon referred to as an infinity wing. The infinity wing configuration consists of both a high and low wing, with the two wings connected by a vertical airfoil. This project seeks to determine if a wing configuration consisting of multiple airfoils produces more lift than the standard wing configurations and is able to provide a solution to manufacturing limitations as well as airport congestion. If the analysis confirms the hypothesis, a trade study will be performed to determine if and when an arrangement of multiple wings would be cost-effective.

Keywords: aerodynamics, aircraft design, aircraft efficiency, wing configuration, wing design

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

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Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: Zbigniew Czyż, Adam Majczak, Lukasz Grabowski

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The paper presents a description of geometric models, computational algorithms, and results of numerical analyses of charge exchange in a two-stroke opposed-piston engine. The research engine was a newly designed internal Diesel engine. The unit is characterized by three cylinders in which three pairs of opposed-pistons operate. The engine will generate a power output equal to 100 kW at a crankshaft rotation speed of 3800-4000 rpm. The numerical investigations were carried out using ANSYS FLUENT solver. Numerical research, in contrast to experimental research, allows us to validate project assumptions and avoid costly prototype preparation for experimental tests. This makes it possible to optimize the geometrical model in countless variants with no production costs. The geometrical model includes an intake manifold, a cylinder, and an outlet manifold. The study was conducted for a series of modifications of manifolds and intake and exhaust ports to optimize the charge exchange process in the engine. The calculations specified a swirl coefficient obtained under stationary conditions for a full opening of intake and exhaust ports as well as a CA value of 280° for all cylinders. In addition, mass flow rates were identified separately in all of the intake and exhaust ports to achieve the best possible uniformity of flow in the individual cylinders. For the models under consideration, velocity, pressure and streamline contours were generated in important cross sections. The developed models are designed primarily to minimize the flow drag through the intake and exhaust ports while the mass flow rate increases. Firstly, in order to calculate the swirl ratio [-], tangential velocity v [m/s] and then angular velocity ω [rad / s] with respect to the charge as the mean of each element were calculated. The paper contains comparative analyses of all the intake and exhaust manifolds of the designed engine. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: computational fluid dynamics, engine swirl, fluid mechanics, mass flow rates, numerical analysis, opposed-piston engine

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Authors: Balwinder Singh, Veerpaul Kaur Mann

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The COVID-19 had a dramatic impact on several countries across the world. National governments have imposed widespread restrictions to prevent the growth of this pandemic. The new health competitive scenario induced by the COVID-19 crisis raised many issues on how business activities should be reorganized due to the difficulties of physical interactions with distributors, suppliers and customers. The pandemic has particularly affected the whole marketing processes because of the relevant issues emerged in managing physical sale channels and interactions with one another, both in the Business-to-Consumer and in the Business-to-Business markets. Recent research about the appropriate actions and strategies that could help firms overcome the crisis has highlighted the key role of digital technologies that may ensure connections and, thus, help business activities to run smoothly. This could be true, especially with the emergence of strong limitations on physical interactions during the COVID-19 pandemic. In such a scenario, the online channel becomes the most important conducive for online customers to get in contact with the firm and carry out online purchasing activities.

Keywords: COVID-19, business, digital marketing, online customers

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Authors: Jehad Al Dallal

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Software engineers apply different measures to quantify the quality of software design. These measures consider artifacts developed at low or high level software design phases. The results are used to point to design weaknesses and to indicate design points that have to be restructured. Understanding the relationship among the quality measures and among the design quality aspects considered by these measures is important to interpreting the impact of a measure for a quality aspect on other potentially related aspects. In addition, exploring the relationship between quality measures helps to explain the impact of different quality measures on external quality aspects, such as reliability and maintainability. In this paper, we report a replication study that empirically explores the correlation between six well known and commonly applied design quality measures. These measures consider several quality aspects, including complexity, cohesion, coupling, and inheritance. The results indicate that inheritance measures are weakly correlated to other measures, whereas complexity, coupling, and cohesion measures are mostly strongly correlated.  

Keywords: quality attribute, quality measure, software design quality, Spearman correlation

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Authors: C. E. Sutton, A. Varvani-Farahani

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Fatigue damage and life prediction of particle metal matrix composites (PMMCs) under uniaxial and multiaxial loading conditions were investigated. Three PMM composite materials of Al6061/Al2O3/20p-T6, Al6061/Al2O3/22p-T6 and Al6061/SiC/17w-T6 tested under tensile, torsion, and combined tension-torsion fatigue cycling were evaluated with various fatigue damage models. The fatigue damage models of Smith-Watson-Topper (S. W. T.), Ellyin, Brown-Miller, Fatemi-Socie, and Varvani were compared for their capability to assess the fatigue damage of materials undergoing various loading conditions. Fatigue life predication results were then evaluated by implementing material-dependent coefficients that factored in the effects of the particle reinforcement in the earlier developed Varvani model. The critical plane-energy approach incorporated the critical plane as the plane of crack initiation and early stage of crack growth. The strain energy density was calculated on the critical plane incorporating stress and strain components acting on the plane. This approach successfully evaluated fatigue damage values versus fatigue lives within a narrower band for both uniaxial and multiaxial loading conditions as compared with other damage approaches studied in this paper.

Keywords: fatigue damage, life prediction, critical plane approach, energy approach, PMM composites

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Authors: Syed Toqueer Akhter, Rabia Zulfiqar

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This paper attempts to trace the determining factor- as far as individual preferences and expectations are concerned- of what causes the direction of international migration to drift in certain ways owing to factors such as Religiosity and Cultural Assimilation. The narrative on migration has graduated from the age long ‘push/pull’ debate to that of complex factors that may vary across each individual. We explore the longstanding factor of religiosity widely acknowledged in mentioned literature as a key variable in the assessment of migration, wherein the impact of religiosity in the form of a drift into the intent of migration has been analyzed. A more conventional factor cultural assimilation is used in a contemporary way to estimate how it plays a role in affecting the drift in direction. In particular what our research aims at achieving is to isolate the effect our key variables: Cultural Assimilation and Religiosity have on direction of migration, and to explore how they interplay as a composite unit- and how we may be able to justify the change in behavior displayed by these key variables. In order to establish a true sense of what drives individual choices we employ the method of survey research and use a questionnaire to conduct primary research. The questionnaire was divided into six sections covering subjects including household characteristics, perceptions and inclinations of the respondents relevant to our study. Religiosity was quantified using a proxy of Migration Network that utilized secondary data to estimate religious hubs in recipient countries. To estimate the relationship between Intent of Migration and its variants three competing econometric models namely: the Ordered Probit Model, the Ordered Logit Model and the Tobit Model were employed. For every model that included our key variables, a highly significant relationship with the intent of migration was estimated.

Keywords: international migration, drift in direction, cultural assimilation, religiosity, ordered probit model

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Authors: Mai M. Farid, Ximeng Yang, Tomoharu Kuboyama, Yuna Inada, Chihiro Tohda

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Intro: Trigonella foenum-graecum (Fenugreek), from Fabaceae family is a well-known plant traditionally used as food and medicine. Many pharmacological effects of Trigonella foenum- graecum seeds extract (TF extract) were evaluated such as anti-diabetic, anti-tumor and anti-dementia effects using in vivo models. Regarding the anti-dementia effects of TF extract, diabetic rats, aluminum chloride-induced amnesia rats and scopolamine-injected mice were used previously for evaluation, which are not well established as Alzheimer’s disease models. In addition, those previous studies, active constituents in TF extract for memory function were not identified. Method: This study aimed to clarify the effect of TF extract on Alzheimer’s disease model, 5XFAD mouse that overexpresses mutated APP and PS1 genes and determine the major active constituent in the brain after oral intake of TF extract. Results: Trigonelline was detected in the cerebral cortex of 5XFAD mice after 24 hours of oral administration of TF extract by LC-MS/MS. Oral administration of TF extract for 17 days improved object location memory in 5XFAD mice. Conclusion: These results suggest that TF extract and its active constituents could be an expected therapeutic candidate for Alzheimer’s disease.

Keywords: Alzheimer's disease, LC-MS/MS, memory recovery, Trigonella foenum-graecum Seeds, 5XFAD mice

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Authors: Kent Salomonsson, Xuefang Zhao, Sara Kallin

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Human soft tissue is loaded and deformed by any activity, an effect known as a stress-strain relationship, and is often described by a load and tissue elongation curve. Several advances have been made in the fields of biology and mechanics of soft human tissue. However, there is limited information available on in vivo tissue mechanical characteristics and behavior. Confident mechanical properties of human soft tissue cannot be extrapolated from e.g. animal testing. Thus, there is need for non invasive methods to analyze mechanical characteristics of soft human tissue. In the present study, the internal mechanical conditions of the lower limb, which is subject to an external load, is studied by use of the finite element method. A detailed finite element model of the lower limb is made possible by use of MRI scans. Skin, fat, bones, fascia and muscles are represented separately and the material properties for them are obtained from literature. Previous studies have been shown to address macroscopic deformation features, e.g. indentation depth, to a large extent. However, the detail in which the internal anatomical features have been modeled does not reveal the critical internal strains that may induce hypoxia and/or eventual tissue damage. The results of the present study reveals that lumped material models, i.e. averaging of the material properties for the different constituents, does not capture regions of critical strains in contrast to more detailed models.

Keywords: FEM, tissue, indentation, properties

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Authors: Tafadzwa Shumba, Rose C. Nyatondo, Regret Sunge

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This research analyses the impact of budget deficits on the economic performance of Zimbabwe. The study employs the autoregressive distributed lag (ARDL) confines testing method to co-integration and long-run estimation using time series data from 1980-2018. The Augmented Dick Fuller (ADF) and the Granger approach were used to testing for stationarity and causality among the factors. Co-integration test results affirm a long term association between GDP development rate and descriptive factors. Causality test results show a unidirectional connection between budget shortfall to GDP development and bi-directional causality amid debt and budget deficit. This study also found unidirectional causality from debt to GDP growth rate. ARDL estimates indicate a significantly positive long term and significantly negative short term impact of budget shortfall on GDP. This suggests that budget deficits have a short-run growth retarding effect and a long-run growth-inducing effect. The long-run results follow the Keynesian theory that posits that fiscal deficits result in an increase in GDP growth. Short-run outcomes follow the neoclassical theory. In light of these findings, the government is recommended to minimize financing of recurrent expenditure using a budget deficit. To achieve sustainable growth and development, the government needs to spend an absorbable budget deficit focusing on capital projects such as the development of human capital and infrastructure.

Keywords: ARDL, budget deficit, economic performance, long run

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Authors: Kavish Kejriwal, Richa Grover

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Consumer awareness and pending legislation have pushed environmental issues into the spotlight, making it imperative for organizations to have a plan of action for “going green.” This is the reason why Green Supply Chain Management has become the integral part of many organization with a goal to reduce cost, increase efficiency and be environmental friendly. Implementation of GSCM involves many factors which act as barriers, making it a tedious task. These barriers have different relationship among themselves creating different impact on implementation Green Supply Chain Management. This work focuses on determining those barriers which have essentially to be removed in the initial stages of GSCM adoption. In this work, the author has taken the case of a petroleum industry in order to come up with a solution. A DEMATEL approach is used to reach the solution.

Keywords: barriers, environment, green supply chain management, impact, interpretive structural modeling

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Authors: Manal M. Kame, Zeinab A. Demerdash, Hanan G. El-Baz, Salwa M. Hassan, Faten M. Salah, Wafaa Mansour, Olfat Hammam

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Cord blood (CB) derived Unrestricted Somatic Stem Cells (USSCs) with their multipotentiality hold great promise in liver regeneration. This work aims at evaluation of the therapeutic potentiality of USSCs in two experimental models of chronic liver injury induced either by S. mansoni infection in balb/c mice or CCL4 injection in hamsters. Isolation, propagation, and characterization of USSCs from CB samples were performed. USSCs were induced to differentiate into osteoblasts, adipocytes and hepatocyte-like cells. Cells of the third passage were transplanted in two models of liver fibrosis: (1) Twenty hamsters were induced to liver fibrosis by repeated i. p. injection of 100 μl CCl4 /hamster for 8 weeks. This model was designed as; 10 hamsters with liver fibrosis and treated with i.h. injection of 3x106 USSCs (USSCs transplanted group), 10 hamsters with liver fibrosis (pathological control group), and 10 hamsters with healthy livers (normal control group). (2) Murine chronics S.mansoni model: twenty mice were induced to liver fibrosis with S. mansoni ceracariae (60 cercariae/ mouse) using the tail immersion method and left for 12 weeks. This model was designed as; 10 mice with liver fibrosis were transplanted with i. v. injection of 1×106 USCCs (USSCs transplanted group). Other 2 groups were designed as in hamsters model. Animals were sacrificed 12 weeks after USSCs transplantation, and their liver sections were examined for detection of human hepatocyte-like cells by immunohistochemistry staining. Moreover, liver sections were examined for fibrosis level, and fibrotic indices were calculated. Sera of sacrificed animals were tested for liver functions. CB USSCs, with fibroblast-like morphology, expressed high levels of CD44, CD90, CD73 and CD105 and were negative for CD34, CD45, and HLA-DR. USSCs showed high expression of transcripts for Oct4 and Sox2 and were in vitro differentiated into osteoblasts, adipocytes. In both animal models, in vitro induced hepatocyte-like cells were confirmed by cytoplasmic expression of glycogen, alpha-fetoprotein, and cytokeratin18. Livers of USSCs transplanted group showed engraftment with human hepatocyte-like cells as proved by cytoplasmic expression of human alpha-fetoprotein, cytokeratin18, and OV6. In addition, livers of this group showed less fibrosis than the pathological control group. Liver functions in the form of serum AST & ALT level and serum total bilirubin level were significantly lowered in USSCs transplanted group than pathological control group (p < 0.001). Moreover, the fibrotic index was significantly lower (p< 0.001) in USSCs transplanted group than pathological control group. In addition liver sections, of i. v. injection of 1×106 USCCs of mice, stained with either H&E or sirius red showed diminished granuloma size and a relative decrease in hepatic fibrosis. Our experimental liver fibrosis models transplanted with CB-USSCs showed liver engraftment with human hepatocyte-like cells as well as signs of liver regeneration in the form of improvement in liver function assays and fibrosis level. These data provide hope that human CB- derived USSCs are introduced as multipotent stem cells with great potentiality in regenerative medicine & strengthens the concept of cellular therapy for the treatment of liver fibrosis.

Keywords: cord blood, liver fibrosis, stem cells, transplantation

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Authors: Ali Karrech, Alberto Puccini, Ben Galvin, Davide Galli

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This paper summarises the laboratory tests, numerical models and statistical approach developed to investigate the behaviour of concrete blocks loaded in shear through metallic anchors. This research is proposed to bridge a gap in the state of the art and practice related to anchors loaded against partially confined concrete surfaces. Eight concrete blocks (420 mm x 500 mm x 1000 mm) with 150 and/or 250 deep anchors were tested. The stainless-steel anchors of diameter 16 mm were bonded with HIT-RE 500 V4 injection epoxy resin and were subjected to shear loading against partially supported edges. In addition, finite element models were constructed to validate the laboratory tests and explore the influence of key parameters such as anchor depth, anchor distance from the edge, and compressive strength on the stability of the block. Upon their validation experimentally, the numerical results were used to populate, develop and interpret a systematic parametric study based on the Design of Experiment approach through the Box-Behnken design and Response Surface Methodology. An empirical model has been derived based on this approach, which predicts the load capacity with the desirable intervals of confidence.

Keywords: finite element modelling, design of experiment, response surface methodology, Box-Behnken design, empirical model, interval of confidence, load capacity

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Authors: Souad Hassene Daouadji, Larbi Hammadi, Abdelkrim Hazzab

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The slips intended for the manufacture of ceramics must have rheological properties well-defined in order to bring together the qualities required for the casting step (good fluidity for feeding the molds easily settles while generating a regular settling of the dough and for the dehydration phase of the dough in the mold a setting time relatively short is required to have a sufficient refinement which allows demolding both easy and fast). Many additives haveadded in slip of ceramic in order to improve their rheological properties. In this study, we investigated the impact of xanthan gumon rheological properties of ceramic Slip. The modified Cross model is used to fit the stationary flow curves of ceramic slip at different concentration of xanthan added. The thixotropic behavior studied of mixture ceramic slip-xanthan gumat constant temperature is analyzed by using a structural kinetic model (SKM) in order to account for time dependent effect.

Keywords: ceramic slip, xanthan gum, modified cross model, thixotropy, viscosity

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Authors: Evgeni Baratashvili, Giorgi Sulashvili, Malkhaz Sulashvili, Bela Khotenashvili, Irma Makharashvili

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The most investment decision-making principle of regional travel firm's management and its partner is the formulation of the aims of investment programs. The investments can be targeted in order to reduce the firm's production costs and to purchase good transport equipment. In attractive region, in order to develop firm’s activities, the investment program can be targeted for increasing of provided services. That is the case where the sales already have been used in the market. The investment can be directed to establish the affiliate firms, branches, to construct new hotels, to create food and trade enterprises, to develop entertainment enterprises, etc. Economic development is of great importance to regional development. International experience shows that inclusive economic growth largely depends on not only the national, but also regional development planning and implementation of a strong and competitive regions. Regional development is considered as the key factor in achieving national success. Establishing a modern institute separate entities if the pilot centers will constitute a promotion, international best practice-based public-private partnership to encourage the use of models. Regional policy directions and strategies adopted in accordance with the successful implementation of major importance in the near future specific action plans for inclusive development and implementation, which will be provided in accordance with the effective monitoring and evaluation tools and measurable indicators combined. All of these above-mentioned investments are characterized by different levels, which are related to the following fact: How successful tourism marketing service is, whether it is able to determine the proper market's reaction according to the particular firm's actions. In the sphere of regional tourism industry and in the investment decision possible variants it can be developed the some specter of models. Each of the models can be modified and specified according to the situation, and characteristic skills of the existing problem that must be solved. Besides, while choosing the proper model, the process is affected by the regulation system of economic processes. Also, it is influenced by liberalization quality and by the level of state participation.

Keywords: net income of travel firm, economic growth, Investment profitability, regional development, tourist product, tourism development

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Authors: Wesley Teskey, Vedran Glavas, Julian Wegener

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Generating battery cathode microstructures is an important area of research, given the proliferation of the use of automotive batteries. Currently, finite element analysis (FEA) is often used for simulations of battery cathode microstructures before physical batteries can be manufactured and tested to verify the simulation results. Unfortunately, a key drawback of using FEA is that this method of simulation is very slow in terms of computational runtime. Generative AI offers the key advantage of speed when compared to FEA, and because of this, generative AI is capable of evaluating very large numbers of candidate microstructures. Given AI generated candidate microstructures, a subset of the promising microstructures can be selected for further validation using FEA. Leveraging the speed advantage of AI allows for a better final microstructural selection because high speed allows for the evaluation of many more candidate microstructures. For the approach presented, battery cathode 3D candidate microstructures are generated using Gaussian Mixture Models (GMMs) and pix2pix. This approach first uses GMMs to generate a population of spheres (representing the “active material” of the cathode). Once spheres have been sampled from the GMM, they are placed within a microstructure. Subsequently, the pix2pix sweeps over the 3D microstructure (iteratively) slice by slice and adds details to the microstructure to determine what portions of the microstructure will become electrolyte and what part of the microstructure will become binder. In this manner, each subsequent slice of the microstructure is evaluated using pix2pix, where the inputs into pix2pix are the previously processed layers of the microstructure. By feeding into pix2pix previously fully processed layers of the microstructure, pix2pix can be used to ensure candidate microstructures represent a realistic physical reality. More specifically, in order for the microstructure to represent a realistic physical reality, the locations of electrolyte and binder in each layer of the microstructure must reasonably match the locations of electrolyte and binder in previous layers to ensure geometric continuity. Using the above outlined approach, a 10x to 100x speed increase was possible when generating candidate microstructures using AI when compared to using a FEA only approach for this task. A key metric for evaluating microstructures was the battery specific power value that the microstructures would be able to produce. The best generative AI result obtained was a 12% increase in specific power for a candidate microstructure when compared to what a FEA only approach was capable of producing. This 12% increase in specific power was verified by FEA simulation.

Keywords: finite element analysis, gaussian mixture models, generative design, Pix2Pix, structural design

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Authors: Melika Masjedi

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Post-Traumatic Stress Disorder (PTSD) has a significant impact on the mental health and relationship dynamics of couples, leading to decreased marital satisfaction. This study examines the mediating role of sexual and romantic relationship dynamics in relation to PTSD and marital satisfaction among Iranian couples. Using a sample of 107 participants, quantitative methods were utilized to assess variables such as relationship functioning, PTSD symptom severity, and the influence of sexual and romantic interactions. The findings demonstrate a strong correlation between heightened PTSD symptoms and reduced marital satisfaction, particularly in the domains of intimacy and emotional connection. The study highlights the importance of addressing relational dynamics to improve marital outcomes in PTSD-affected couples.

Keywords: intimacy, marital satisfaction, PTSD, relationship dynamics, trauma

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Authors: Rabiatu Bonku, Faisal Alkaabneh

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Inspired by a food banks distribution operation for non-profit organization, we study a variant synchronized vehicle routing problem for equitable resource allocation. This research paper introduces a Mixed Integer Programming (MIP) model aimed at addressing the complex challenge of efficiently distributing vital resources, particularly for food banks serving vulnerable populations in urban areas. Our optimization approach places a strong emphasis on social equity, ensuring a fair allocation of food to partner agencies while minimizing wastage. The primary objective is to enhance operational efficiency while guaranteeing fair distribution and timely deliveries to prevent food spoilage. Furthermore, we assess four distinct models that consider various aspects of sustainability, including social and economic factors. We conduct a comprehensive numerical analysis using real-world data to gain insights into the trade-offs that arise, while also demonstrating the models’ performance in terms of fairness, effectiveness, and the percentage of food waste. This provides valuable managerial insights for food bank managers. We show that our proposed approach makes a significant contribution to the field of logistics optimization and social responsibility, offering valuable insights for improving the operations of food banks.

Keywords: food banks, humanitarian logistics, equitable resource allocation, synchronized vehicle routing

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Authors: Dai-Ling Li, Jung-Fa Cheng, Min-Lang Huang, Yun-Yao Chi

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The hedonic pricing model has been popularly applied to describe the economic value of environmental amenities in urban housing, but the results for cultural heritage variables remain relatively ambiguous. In this paper, integrated variables extending by GIS-based data and an existing typology of communities used to examine how cultural heritage and environmental amenities and disamenities affect housing prices across urban communities in Tainan, Taiwan. The developed models suggest that, although a sophisticated variable for central services is selected, the centrality of location is not fully controlled in the price models and thus picked up by correlated peripheral and central amenities such as cultural heritage, open space or parks. Analysis of these correlations permits us to qualify results and present a revised set of relatively reliable estimates. Positive effects on housing prices are identified for views, various types of recreational infrastructure and vicinity of nationally cultural sites and significant landscapes. Negative effects are found for several disamenities including wasteyards, refuse incinerators, petrol stations and industries. The results suggest that systematic hypothesis testing and reporting of correlations may contribute to consistent explanatory patterns in hedonic pricing estimates for cultural heritage and landscape amenities in urban.

Keywords: hedonic pricing model, cultural heritage, landscape amenities, housing

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Authors: Ayman Abd-Elhamed, Sayed Mahmoud

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The present research work investigates the seismic response of reinforced concrete (RC) frame building considering the effect of modeling masonry infill (MI) walls. The seismic behavior of a residential 6-storey RC frame building, considering and ignoring the effect of masonry, is numerically investigated using response spectrum (RS) analysis. The considered herein building is designed as a moment resisting frame (MRF) system following the Egyptian code (EC) requirements. Two developed models in terms of bare frame and infill walls frame are used in the study. Equivalent diagonal strut methodology is used to represent the behavior of infill walls, whilst the well-known software package ETABS is used for implementing all frame models and performing the analysis. The results of the numerical simulations such as base shear, displacements, and internal forces for the bare frame as well as the infill wall frame are presented in a comparative way. The results of the study indicate that the interaction between infill walls and frames significantly change the responses of buildings during earthquakes compared to the results of bare frame building model. Specifically, the seismic analysis of RC bare frame structure leads to underestimation of base shear and consequently damage or even collapse of buildings may occur under strong shaking. On the other hand, considering infill walls significantly decrease the peak floor displacements and drifts in both X and Y-directions.

Keywords: masonry infill, bare frame, response spectrum, seismic response

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Authors: Bayonle Abiola Omoniyi

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In turbidite reservoirs with volumetrically significant thin-bedded turbidites (TBTs), thin-pay intervals may be underestimated during calculation of reserve volume due to poor vertical resolution of conventional well logs. This paper demonstrates the strong control of bed-scale sedimentary heterogeneity on oil recovery using six facies distribution scenarios that were generated from outcrop data from the Eocene Itzurun Formation, Basque Basin (northern Spain). The variable net sand volume in these scenarios serves as a primary source of sedimentary heterogeneity impacting sandstone-mudstone ratio, sand and shale geometry and dimensions, lateral and vertical variations in bed thickness, and attribute indices. The attributes provided input parameters for modeling the scenarios. The models are 20-m (65.6 ft) thick. Simulation of the scenarios reveals that oil production is markedly enhanced where degree of sedimentary heterogeneity and resultant permeability contrast are low, as exemplified by Scenarios 1, 2, and 3. In these scenarios, bed architecture encourages better apparent vertical connectivity across intervals of laterally continuous beds. By contrast, low net-to-gross Scenarios 4, 5, and 6, have rapidly declining oil production rates and higher water cut with more oil effectively trapped in low-permeability layers. These scenarios may possess enough lateral connectivity to enable injected water to sweep oil to production well; such sweep is achieved at a cost of high-water production. It is therefore imperative to consider not only net-to-gross threshold but also facies stack pattern and related attribute indices to better understand how to effectively manage water production for optimum oil recovery from basin-plain reservoirs.

Keywords: architecture, connectivity, modeling, turbidites

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: R. R. Govind

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In the digital age, artificial intelligence (AI) is having a significant impact on the rapid changes that cities are experiencing. This study explores the profound impact of AI on urban morphology, especially with regard to promoting friendly design choices. It addresses a significant research gap by examining the real-world effects of integrating AI into urban design and management. The main objective is to outline a framework for integrating AI to transform urban settings. The study employs an urban design framework to effectively navigate complicated urban environments, emphasize the need for urban management, and provide efficient planning and design strategies. Taking Gangtok's informal settlements as a focal point, the study employs AI methodologies such as machine learning, predictive analytics, and generative AI to tackle issues of 'urban informality'. The insights garnered not only offer valuable perspectives but also unveil AI's transformative potential in addressing contemporary urban challenges.

Keywords: urban design, artificial intelligence, urban challenges, machine learning, urban informality

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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