Miracle-dz/UniFAR-FTUs huggingface dataset:
How Instagram Influencers Affect the Value Perception of Thai Millennial Followers and Purchasing Intention of Luxury Fashion for Sustainable Marketing

Social media influencers play a significant role in marketing by introducing products to their followers. We investigate how Instagram influencers impact consumer parasocial interaction (PSI) in the relationship between value perception and purchase intention. Whereas customers influence the attractiveness (social and physical) PSI of social media influencers, studies of the effects of luxury purchasing PSI in Thailand are limited. We examine the relationship between PSI and followers of luxury fashion’s value (social, personal, and conspicuous) on social media. We use structural equation modeling to evaluate hypotheses by conducting an online survey with 400 Thai millennial respondents who had experience following influencers on Instagram. The findings indicate that Thai millennials accept Instagram influencers’ PSIs in terms of value perception and motivation to purchase luxury fashion. The attractiveness of influencers initiates the formation of PSI; followers receive value perception and react to purchasing intention from influencers. The concepts were investigated to prove that influencers’ power can encourage followers to mitigate negative consequences by delivering value perceptions on PSI. These findings provided managerial implications for comprehending consumers in the field of digitalization.
Analysis On Radar Image Classification Using Deep Learning

The progress of the last 10 years of deep learning technology has inspired many fields of research, such as the processing of radar signal, speech and audio recognition, etc. Data representation acquired with Lidar or camera sensors are used for most prominent deep learning models, leaving automotive radars seldom used. Despite their vital potential in adverse weather conditions and their ability to seamlessly measure the range of an object and radial speed. Since radar signals have still not been used, the available benchmarking data is lacking. In the recent past, however, the application of radar data to various profound learning algorithms has been very interesting, since more datasets are being provided. This article aims to describe a new method of grading applied for the synthetic aperture radar (SAR), followed by fine tuning in such a grading scheme; Pre-trained architectures in the ImageNet database were used; the VGG 16 had actually been used as a feature extractor and the new classifier was trained based on the extracted features. The Dataset used is the data acquisition and recognition (MSTAR) of the Moving and Stationary Traget; for ten (10) different classes we have achieved a final accuracy of 97.91 percent.
Satin Bowerbird optimization algorithm for the Application of Optimal power flow of power system with FACTS devices

The following research paper, addresses the issue of the optimal power flow ( OPF) of power system dealt by the proposal of adapting flexible ac transmission FACTS devices with Satin Bowerbird optimization (SBBOA) algorithm. The SBBOA is bio-inspired algorithm; it is carried out based totally on the principle of ‘female-attracted-by-male’ for breeding. The algorithm that is proposed is tested by usingIEEE-30 bus and IEEE-57 bus test systems with FACT devices of two different types. The following are the two types of FACT devices that are kept at fixed locations: FACT devices that are kept at fixed locations: Thyristor controlled series capacitor and Thyristor controlled phase shifter The objective of the present study aims at four different functions. They are: (a) Minimizing the cost of fuel (b) Minimizing active power loss during transmission (c) Reduction of emission and (d) Minimizing the combination of economic and environmental cost. The SBBOA give the finest simulation outcomes than lately proposed optimization algorithms given in the literature.
Investigating the Impact of Different Religions on Corporate Social Responsibility Practices: A Cross-National Evidence

The growing interest in the impact that organizations have on society has made Corporate Social Responsibility (CSR) a matter of extraordinary relevance. Religions are among the factors that may drive the adoption of more CSR practices and, as such, may play a significant role in their promotion. The aim here is to discover whether religions contribute to the development of a broader range of CSR initiatives on the basis of Stakeholder, and Legitimacy theories. We studied the impact of different religions on an index made up of 122 CSR practices that include social and environmental issues. We tested the hypothesis proposed through panel data models for a sample composed of 13,884 firm-year observations from 30 countries. Our findings suggest that certain religions, such as Christianity, Judaism, and Buddhism, have a positive influence on the adoption of CSR practices. Companies operating in countries with a high percentage of adherents to these religions are more prone to undertake CSR activities. However, Islam, Hinduism, and Folk religions record an inverse trend that evidences a negative link. JEL codes: M14, M16
Experimental Study Comparing Structural Changes Induced by Biologic Versus Synthetic Mesh Implants in Nephropexy

BACKGROUND: Long-term chronic inflammatory response when using meshes for nephropexy may lead to kidney fibrosis, renal failure, and chronic pain syndrome. Research on biological properties of various materials used for nephropexy, as well as the search for new implant materials is a pressing problem, as it greatly affects patients’ quality of life. The present study suggests that the use of the extracellular bovine-derived peritoneum matrix as a new biological implant opens up new prospects for nephropexy. AIM: This study aims to evaluate the structural changes at the interface of the renal tissues and paranephron with the extracellular bovine-derived peritoneum matrix and the UltraPro mesh after nephropexy in an experimental animal. MATERIALS AND METHODS: Experimental nephropexy was performed in 64 white shorthaired adult rats, divided into two groups: Extracellular bovine-derived peritoneum matrix and UltraPro mesh. Implants were 1.5 × 1.5 cm per one animal. Observation periods were 7, 21, 30, and 180 days. The tissue was stained with hematoxylin and eosin, Van Gieson’s with Pikro-Fuchsin. Cellular infiltrate was evaluated by counting granulocytes, mononuclear cells, and foreign body giant cells on five high-magnification images for each stained section (×400). RESULTS: The use of the extracellular bovine-derived peritoneum matrix induced less intense and less prolonged chronic inflammatory response, as well as intense production of new collagen fibers more similar to the native connective tissue in terms of their histologic structure. The UltraPro mesh induced moderately persistent chronic inflammatory response throughout the 6-month study period. By this period, the level of multinucleated foreign body giant cells in the UltraPro group was 1.0 ± 0.2, it was statistically significantly higher than in the group with extracellular bovine-derived peritoneum matrix – 0.6 ± 0.1 (p < 0.05). CONCLUSION: Histologic evaluation demonstrates high biocompatibility of both the extracellular bovine-derived peritoneum matrix and the UltraPro mesh implants. The results of using new biological material are not worse than synthetic mesh. Edited by: Ksenija Bogoeva-Kostovska Citation: Abatova AN, Tussupbekova MM, Abatov NT, Badyrov RM, Kamyshanskiy YK. Experimental Study Comparing Structural Changes Induced by Biologic Versus Synthetic Mesh Implants in Nephropexy. Open Access Maced J Med Sci. 2021 May 14; 9A:284-290. https://doi.org/10.3889/oamjms.2021.5944
A Method to Create Hybrid Models Using a Morphological Matrix

Prescriptive management models are falling short to deal with the current and increasingly uncertain and dynamic business environment. The search for so-called hybrid models has increased among different organizations and industrial sectors. Despite the interest, there is a lack of systematic procedures to effectively adapt hybrid models to specific projects. In order to bridge this gap, we propose a method to support the creation of hybrid models, based on a morphological matrix that allows the combination of practices to the specific needs of each project. The method was developed through a systematic literature review, a theoretical proposition phase and its evaluation in a single case study involving an information technology company. The results indicate that a customization by project is feasible, allowing professionals to be more assertive in creating customized management solutions. Finally, the study highlights the possibility of creating systematic procedures to assist organizations and professionals in choosing management practices for their projects and the consequent creation of hybrid models .
Brain tumor segmentation and overall survival period prediction in glioblastoma multiforme using radiomic features

Glioblastoma multiforme (GBM or glioblastoma) is a fast‐growing glioma that are the most invasive type of glial tumors, rapidly growing and commonly spreading into nearby brain tissue. Due to its aggressive and fast growing nature, patients suffer from high grade glioma (GBM) survive very less time as compare to other tumors. Prediction of patient survival (OS) time helps the radiologist for better systematic treatment planning and clinical decision making. The OS rate depends on the tumor size, shape, and different imaging features of brain. In this study, the OS period prediction was performed using Random Forest, SVM, XgBoost, and LGBM taking radiomic features which represents fused deep features and hand crafted features of the tumor. Efficiency of the prediction depends on the tumor volume that is segmented from the different MRI modalities. Hence the whole tumor and its sub tumor are extracted from multi‐modal MR images using U‐Net++ deep model and stacked together for deep features extraction using convolutional neural networks. To increase the accuracy, the features are reduced using PCA and then this radiomic feature set was used for OS period prediction. Prediction performance was evaluated for both 2‐class and 3‐class survival groups. The experiment was performed on well‐known dataset BraTS 2017 and achieved a classification AUC value as 63% for 3‐class classification and 2‐class group using different classifier. Segmentation DOR is computed as 1269.29, 2033.99, and 648.00 for complete tumor, enhancing tumor, and necrotic tumor extraction, respectively. To achieve even more accuracy, bio inspired optimization methods GA and PSO are used on fused feature set. Finally, the method achieves the AUC score of 0.66 using fused feature+SVM+GA (3‐class group) and 0.70 using fused feature+SVM+PSO (2‐class group) which outperforms the state‐of‐the‐art.
TURKISH SENTIMENT ANALYSIS FOR OPEN AND DISTANCE EDUCATION SYSTEMS

Students’ opinions are the most essential source to enhance the quality of education and educational services in Open and Distance education (ODE) Systems. How to access and analyze students’ real opinions is a problem for ODE institutions. The purpose of the present study is to conduct a sentiment analysis (SA) on the collected Turkish tweets about an ODE system to monitor students’ opinions and sentiments about the system. Firstly, the related 63699 tweets about the ODE system are gathered and analyzed. Later, pre-processing is applied to the dataset. Sentence-based SA is performed with the data provided. The dataset is vectorized using two vector space models to test four classifiers which are Support Vector Machines, K-Nearest Neighbor, Logistic Regression (LR), and Artificial Neural Networks. F-score values obtained with these classifiers are evaluated, and the results are discussed. LR classifier gives the best F-score values with %75 for each vector space model. Through the SA results, students’ dissatisfaction, appreciation, and concerns will be learned quickly by the university administration to develop strategies that will increase the quality of education and educational services.
Transformative outcomes: assessing and reorienting experimentation with transformative innovation policy

The impending climate emergency, the Paris agreement and Sustainable Development Goals demand significant transformations in economies and societies. Science funders, innovation agencies, and scholars have explored new rationales and processes for policymaking, such as transformative innovation policy (TIP). Here, we address the question of how to orient the efforts of science, technology, and innovation policy actors to enable transformations. We build on sustainability transitions research and a 4-year co-creation journey of the TIP Consortium to present twelve transformative outcomes that can guide public policy agencies in evaluating and reformulating their projects, programmes, and policies. We illustrate the transformative outcomes in two empirical cases: transitions towards mobility-as-a-service in the Finnish transport system and the emergence of speciality coffee in Colombia. We argue that the twelve transformative outcomes can guide public policy agents to fundamentally transform their ways of thinking and operation in advancing transformative change.
Why not talk about repression? Radical Activism and its Responses to Repression

By exploring silence as a response to repression, this study contributes to the literature on the dynamic rela-tionship between protest and repression; it examines the ways in which certain radical activists responded with silence to the escalating repression they were experiencing. Analysis explains how and why they remained si-lent, and the consequences of that silence for individual activists and collective mobilization. Based on a case study of the Stop Huntingdon Animal Cruelty (SHAC) campaign in the UK, this article includes the reflections of activists who experienced repression first-hand. By analysing in-depth interviews and other qualitative data, the study identifies four different forms of silence among the activists facing repression: silence as a strategy, si-lence as a cultural trait, silence due to over-confidence and silence resulting from the normalization of repres-sion. The results show how cultural and strategic dynamics play out in protestors' experiences of and responses to repression. The study demonstrates the importance of the neglected research area of the response to re-pression for advancing our understanding of the conditions under which repression leads either to demobiliza-tion or to mobilization.
Options for Modernization of Heat Supply to Consumers of Condensing Power Plant

High competition and strict requirements of the wholesale electricity and capacity market make optimization of heat supply schemes an urgent issue for generating companies. Replacement of life-expired generation equipment with new capacities based on advanced technologies is a priority goal for the energy industry development. This work focuses on condensing power plant (CPP), which is the only source in the city that supplies heat to all consumer categories. The plant carries out quantitative and qualitative heat supply regulation according to the temperature profile of 135/70°C with a cutoff of 110/70°C. The study examines the possibility of CPP modernization based on three options: building a pressure-reducing cooling unit 140/12, commissioning an auxiliary boiler house, and building a 110 MW combined-cycle gas plant. This paper presents technical solutions for the considered options and preliminary technical and economic calculations of their efficiency.
CFD Simulation of the Safety of Unmanned Ship Berthing under the Influence of Various Factors

The safety of unmanned ship berthing is of paramount importance. In order to explore the influence of wind and wave coupling, a berthing computational fluid dynamics (CFD) model was established, and the characteristics of speed field, pressure field, and vortex have been obtained under different speed, wind direction, and the quay wall distances. The results show that the total resistance of the hull against the current can be about 1.60 times higher compared to the downstream resistance, water flow resistance is the dominant factor, accounting for more than 80% of the total resistance. When changing the distance between ship and shore at fixed speed, the results found that the torque is small, but the growth rate is very large when driving below 2 m/s, and the torque growth rate is stable above 2 m/s. Based on the established coupling model, a multi-factor berthing safety study is carried out on an actual unmanned ship. The results show that when the speed increases from 4 m/s to 12 m/s, the curve slope is small, the resistance increases from 3666 N to 18,056 N, and the rear slope increases. The pressure increases with the speed, and when the speed is 24 m/s, the maximum pressure is up to 238,869 Pa. When the wind speed is fixed, the vertical force of the unmanned ship increases first and then decreases to zero and then reverses the same law change, and the maximum resistance is about 425 N at the wind angle of about 45 degrees; At 90 degrees, the maximum lateral force on an unmanned boat is about 638 N. The above results can provide control strategy for unmanned ship berthing safety, and provide theoretical basis for unmanned ship route planning and obstacle avoidance, safety design, etc.
Who moved with you? The companionship of significant others reduces movers’ motivation to make new friends

This research investigated how residential moves with versus without the companionship of signiﬁcant others would affect people’s motivation to make new friends. Studies 1a and 1b showed that the companionship of signiﬁcant others predicted fewer new friends among university students who moved within the same country (Study 1a) and to a different country (Study 1b), suggesting that the companionship of signiﬁcant others was associated with a lower level of motivation to make new friends. In Study 2, the results of an experiment demonstrated that the companionship of a signiﬁcant other reduced movers’ motivation to make new friends, and this was explained by positive affect but not negative affect. Speciﬁcally, the companionship of a signiﬁcant other, compared with the companionship of an acquaintance or no companionship, led to stronger positive affect, which, in turn, reduced motivation to make new friends. Taken together, these ﬁndings call for more nuanced theory on the inﬂuence of residential mobility on well-being and social networks.
An Introduction to Montmorillonite Purification

Purification of montmorillonite is a process to remove non clay minerals (gangue) such as calcite, feldspar, quartz, opal (C-T), and mica from montmorillonite ore. This is performed to make montmorillonite suitable for use in sensitive applications such as pharmaceutical, cosmetic, food, and advanced materials for nanotechnology. Gangue minerals in raw montmorillonite ores can cause serious health problems when used in pharmaceutics, cosmetic, and food industries and reduce material quality in advanced materials production. Montmorillonite purification can be divided into two main classes as physical and chemical purification. Physical purification processes are based on particle size difference between the gangue and montmorillonite minerals. Purification processes based on gravity separation are ineffective since the specific weights of gangue and montmorillonite minerals are very close to each other. Physical purification process includes sedimentation, centrifugal separation, aero separation, and sieving techniques. Chemical purification of montmorillonite is based on dissolution and so extraction of carbonates, metal hydroxides, organic materials, and silica, respectively, using different leaching techniques.
Application of Pont’s index to a Pakistani population: a digital stereomicroscopic study

Abstract Objective To investigate the applicability of Pont’s index for predicting maxillary and mandibular dental arch widths in a Pakistani population. Materials and methods A Hirox digital stereomicroscope (SM) (HIROX KH7700 Japan) was used to construct digital models of fabricated plaster casts. Gender differences in the measured totals of the incisor widths, arch widths and expansion indices were evaluated. Pont’s correlations were computed between measured and predicted arch widths. An analysis of variance (ANOVA) was applied to determine the differences between arch length and arch perimeter groups. Results Males had significantly larger mean values for the sums of the incisors, arch widths and expansion indices compared with females (p ≤ 0.05). There were significant differences observed between the large and small, average and small and the average and large arch length groups (p ≤ 0.05) in the maxilla, while a significant difference was observed only between the large and small arch length groups in the mandibular arch. Pont’s index predictions were consistently less than the actual interpremolar and intermolar arch widths for both genders. The dissimilarity in the predictions for interpremolar width averaged -4.33 mm for males and -4.21 mm for females while the intermolar width averages were -4.93 mm for males and -4.92 mm for females. Conclusion The results indicated that Pont’s index should not be applied to the Pakistani population. Maxillary and mandibular arch length groups and arch perimeters should be carefully investigated before applying any prediction formulae.
The Mediating Effect of Financial Distress on Audit Tenure and Auditor Switching Towards Audit Delay

The aim of this study is to investigate the impact of audit tenure and auditor switching as an intervening variable on audit delay and financial distress. Manufacturing companies listed on the Indonesian Stock Exchange for the period 2016 to 2018 are the population of this analysis. This research uses purposeful sampling to obtain 14 businesses as an item. The hypothesis test is conducted using a partial least square. This study found that there is no effect of audit tenure and audit switching on audit delay. Audit tenure does not affect financial distress, but auditor switching affects financial distress. Indirectly, both audit tenure and auditor switching don't affect audit delay through financial distress. Keywords—audit tenure, auditor switch, financial distress, audit delay
Identity and access management using distributed ledger technology: A survey

As the basic building block of any information security system, identity and access management (IAM) solutions play vital role in enterprise's security programmes. Providing centric solutions for IAM is inefficient in terms of having single point of failure, high cost, duplication and complexity to the users. Recently, emerging the distributed ledger technology (DLT) has attracted significant scientific interests in research areas like identity management, authentication and access control processes. In these contexts, Blockchain can offer greater data and rule confidentiality and integrity, as well as increasing the availability of the system by removing the single point of failure in the procedure. In this paper, we provide a comprehensive overview of the IAM solutions based on their basic components including identity management, authentication and access control. In the identity concept, we discuss about self‐sovereign identity which enhances privacy and security of distributed digital identities by providing individual's consolidated digital identity and verified attributes for enabling them to utilize their ownership. To offer a clearer understanding of the state of the art, we propose taxonomy to categorize them based on their features. For the conclusion of the paper, we compare the existing methods based on proposed taxonomy. Also, considering the advantages and disadvantages of existing methods, we discussed about the possible future directions.