The construction industry is one of the most fatal industries, so it is important to pay more attention to safety solutions. Even though work-related accidents are known as major waste in construction projects, little attention has been paid so far to incorporating safety into the lean construction framework. In this research, lean construction theory is reviewed through the lens of safety. That being so, the identified challenges in previous research on improving safety in construction projects are categorized and those related to the concept of lean project delivery are introduced. Then, the principles of the lean construction framework are explained and the relevant changes for incorporating safety into the framework are introduced and discussed. It is expected that this hybrid model would further enrich the lean construction framework. The careful attention of project executives to this model may improve the safety situation in construction projects.

As a service business models have been ranked by management consultants the management innovation of 2020, and yet are scarcely theorized. Therein, value stipulations in customer contracts lead to the shift from product to service. However, there is no available research about the nature, formula and decisional process about these value stipulations. The motive for this research is to fill in this gap. The goal is to provide first insight about value stipulations in as a service business models: their formula and decisional methodology. The article is a multiple theory building case study on leading platform as a service providers, which aims to contruct the paradigm of the value decision methodology to invest in this technology by purchasing it from dedicated vendors. The methodology works to identify the management instruments involved in the decisional activities to invest in digital technology, where each management instrument is assumed to match an activity at seller and buyer; the sequence of the activities using the Critical Path Method gives the decisional process. Dependent variables are the elements of the as a service business contracts: the customer offering (product-service solution) and the value created, captured and delivered by the solution. Independent variables are given by empirical data analysis. Findings show a relationship between dependent variable value in the as a service business model contracts and independent variables governance objective, strategy, as a service business model type, activity management techniques (roadmap, program, project, operations, lean start-up), capital allocation techniques (equity, debt, options, venture capital typology). If innovation is exploitative, then the customer offering is known and value is determinable via roadmap – project management techniques (program, project, an operations) and capital allocation techniques for precictable environment, If innovation is radical, then the customer offering is not known and value is a target used to architect the solution via lean start-up innovation techniques funded by venture capital. The contribution is a new theoretical construct and deep insight into the practice of digital transformation considering all inherent issues.

This study empirically analyzes how R&D expenditures affect firm value using a regression model for listed firms in Shandong Province, China. The dependent variable is measured by To-bin Q, which measures firm value, and the experimental variable among the independent varia-bles is R&D expenditure. In addition, financial leverage and firm size, which have been found to have a significant impact on firm value in previous studies, were selected as control variables. The study sample consisted of 554 data points analyzed over a nine-year period from 2010 to 2018. Without controlling for variables that affect firm value, the correlation analysis shows that R&D expenditures of listed firms in Shandong Province, China have a significant positive impact on firm value at the 1% level. For a more precise analysis, we ran a multivariate regression analysis controlling for other variables that affect firm value and found that R&D expenditure has a significant positive impact on firm value at the 1% level. These findings suggest that man-agers of listed companies in Shandong Province, China, need to actively engage in R&D activi-ties to increase firm value. Companies in Shandong Province, China, are currently experiencing very strong growth, and this study, which shows that R&D is the key to increasing the value of these companies, can help companies in Shandong formulate their business strategies.

This work is concerned with the existence and uniqueness of boundary value problems defined on semi-infinite intervals. These kinds of problems seldom admit exactly known solutions and, therefore, the theoretical information on their well-posedness is essential before attempting to derive an approximate solution by analytical or numerical means. Our utmost contribution in this context is the definition of a numerical test for investigating the existence and uniqueness of solutions of boundary problems defined on semi-infinite intervals. The main result is given by a theorem relating the existence and uniqueness question to the number of real zeros of a function implicitly defined within the formulation of the iterative transformation method. As a consequence, we can investigate the existence and uniqueness of solutions by studying the behaviour of that function. Within such a context the numerical test is illustrated by two examples where we find meaningful numerical results.

We examine how external triggers, including the digital imperative and the need for more sustainable resource and stakeholder employment, spark the development of transformative sustainable business models. Drawing on the resource-based view and the shared value approach we conceptualize a multifaceted framework that helps to identify key determinants and coherent layers of transformative sustainable businesses models. Our theoretical arguments integrate recent research findings on external dynamics, such as digital technological advances and rising global competitive dynamics, with internal capabilities on both the organizational and the individual level, allowing for a more complete understanding of transformative potentials on the firm level. We propose that key determinants of sustainable transformative business models adhere to both, innovative value-creating reconstructionist and sustainable shared-value logic, and include elements such as co-creation with customers, usage-based pricing, agile and adaptive behavior, closed-loop resource employment, asset-sharing, and collaborative business ecosystems. At the same time, organizational, economic, and environmental layers encompassing sustainable business models need to be both horizontally and vertically coherent to unfold their full potential.

Recently dairying becomes an important farming activity in the districts. Even if these districts are potential in milk production and marketing activities, little was known about determinates of participation and level of participation in milk value addition. This study was analyzing determinates of participation and level of participation in milk value addition in the study areas. Both primary and secondary data were used. Primary data were collected from 244 producers, 50 traders and 20 consumers by using semi-structured questionnaires. Data were analyzed by using descriptive statistics and econometrics model. Results from Heckman selection model first step revealed that milk producers’ participation decision on milk value addition was significantly affected by religion, distance the market, cooperative membership, volume of milk produced per day and market access. Whereas milk producers’ participation decision on the volume of milk value addition was significantly affected by religion, level of education, number of children less than six years, membership for milk cooperatives, volume of milk produced per day, access to market information, access to credit and access to livestock extension. Therefore, dairy sector development programs should take in to account determinants of participation decision on milk value addition as well as on volume of milk production.

1) Background: In service business areas, design enhances the customer experience through the elements which anticipate specific emotional responses of customers. Many service companies are keen to develop and examine design elements from the customer perspective. Furthermore, recently, having considered the significance of customers’ emotional responses by design elements, categorising design elements into manageable dimensions can facilitate the evaluation of design elements. However, design elements and dimensions of design value are not defined in the current service marketing literature, and companies need a measurement tool and managerial guideline to their innovative value creation and compelling service delivery. For these reasons, this research aims to categorise the design value dimensions and propose the managerial implication for the innovative use of design; 2) Methods: This study used the mixed methodology; two stages of interviews and SEM (Structural Equation Modelling); 3) Results: Interview analyses facilitate the identification of design elements in the service delivery process. SEM results underpin the relevance of the categorised design elements and their impact on customer loyalty by comparing different groups (country and time elapsed from experience); and 4) Conclusions: Findings are the fundamentals of developing measuring tool for design and trigger future studies for conceptualising intangible assets.

Deep fat frying is not novel, but a classical antiquity culinary technique preferred chiefly for its swiftness, amenity, conferment of a crisp texture, attractive sensorial and organoleptic qualities and thus delectableness of the fries. Regrettably, repeated use of oils for deep frying impacts the storage life and nutritional suitability of fries. This concerted study investigated the effects of continuous deep fat frying on the physicochemical properties of ten brands of edible cooking oils: Fortune Butto, Roki, Tamu, Best Fry, Golden Fry, Mukwano, Sunny, Sunvita, Sunlite and Sunseed used in deep frying of potato chips in Kampala, Uganda. Three oil samples from local Irish chip fryers were also collected. The color value (CV) and the acidification of the oils as free fatty acid (FFA), peroxide value (POV), paraanisidine value (AnV) and iodine adsorption value (IV) before and between ten successive deep-fryings using potato chips were determined. The possible reuse of the oils was estimated from the frying round when a quality criterion surpassed national or CODEX specifications for the respective edible cooking oils. For fresh oils, the statistical parameter ranges were: CV (0.4R 3.4Y-7.7R 70Y), % FFA (0.0430-0.1508), POV (0.5951-6.6134 meqO₂/Kg), AnV (0.90-4.30) and IV (57.62-128.35gI₂/100g). By the tenth fry, the values were respectively 3.0R 23Y-20.4R 70Y, 0.2286-0.4817, 11.1138-15.7525 meqO₂/Kg, 10.31-22.16 and 53.66-126.03 gI₂/100g. Reuse of the oils for continuous frying of potatoes on the same day can be done only up to 7 times on average for hard oils and 6 times for soft oils.

Metaverse has become an emerging trend for both academia and industry, and it seems to concern the next generation of the Internet. Although it is still in its grassroots, metaverse is estimated to bring disruption to people’s lives. One of the effects concerns the generation of new value oppor-tunities that don't exist in real life. These new types of value as well as their impact on people's lives must be explored. In this respect, this paper utilizes literature evidence to define the value types of metaverse, which are circulated with experts from the focus group on metaverse of the Interna-tional Telecommunications Union. Results uncover economic, public, and social values that metaverse generates, which can ensure its financial viability and the community's social sustaina-bility. The economic value sources come from both the industrial and the commercial sectors, while the public values concern citizen empowerment and government efficiency. The social values of metaverse concern employment growth, and the provision of immersive experiences in enter-tainment and education environments. Finally, this paper critically reviews their role for envi-ronmental, economic, and social sustainability. The literature review indicated that metaverse can on the one hand, enhance sustainability but on the other hand, it can cause environmental impact.

Phialemonium inflatum is a useful fungus known for its ability to mineralise lignin during primary metabolism and decompose polycyclic aromatic hydrocarbons (PAHs). However, no functional genetic analysis techniques have been developed yet for this fungus, specifically in terms of transformation. In this study, we applied an Agrobacterium tumefaciens-mediated transformation (ATMT) system to P. inflatum for functional gene analysis. We generated 3,689 transformants using the binary vector pSK1044, which carried either the hygromycin B phosphotransferase (hph) gene or the enhanced green fluorescent protein (eGFP) gene to label the transformants. Southern blot analysis showed that the probability of a single copy of T-DNA insertion was approximately 50% when the co-cultivation time of fungal spores and Agrobacterium tumefaciens cells was performed at 24–36 h, whereas at 48 h, it was approximately 35.5%. Therefore, when performing gene knockout using ATMT, co-cultivation was reduced to ≤ 36 h. The resulting transformants were mitotically stable, and PCR analysis confirmed gene integration into the transformant genome. Additionally, hph and eGFP gene expressions were confirmed by PCR amplification and fluorescence microscopy. This optimised transformation system will enable functional gene analysis to study genes of interest in P. inflatum.

The realization of value in eco-products represents a rapidly advancing research theme. However, the clarity of relevant concepts, types and operational mechanisms remains elusive. A comprehensive review of current-stage research outcomes in eco-product value realization not only provides a novel approach to rejuvenating regional economies but also proactively contributes to the enhancement of local ecological environments. This article conducts a systematic literature review on the fundamental concepts, research scope and pathways for realizing the value of eco-products. The conclusions are as follows: (1) To clarify the basic concepts of ecosystem services and eco-products, the interrelationship between the two and the research scope of eco-products. (2) To elaborate the method for accounting the value of eco-products. (3) To demonstrate governmental path, market path and collaborative path for realizing the value of eco-products. (4)To review cases pertaining to the realization of value in public eco-products, quasi-public eco-products and operational eco-products both domestically and internationally. Building on this research foundation, the article identifies shortcomings in past research results and proposes key directions for future research progress.

This research aims to analyse the sustainability of retirement system and relevant optimal path to achieve sustainable post-retirement livings in Malaysia context. Focus of this study is put on Employees Provident Fund (EPF) which is mainly constituted by employees from private sector. EPF is a fully funded defined-contribution by both employees and employers. In this research, main variables used are contribution rate and retirement age based on relevant indexation of pension. For a sustainable retirement living, retirement benefits are expected to be in a maximisation function. Attempts to find sustainable retirement fund are via step-by-step mathematical calculation using formulas in Microsoft Excel and verification of the result with Excel Solver via Generalised Reduced Gradient (GRG) algorithm. Eventually, two-third retirement decision model is used to justify the sustainability of retirement fund other than justification using monthly household expenditure.

It is universally accepted that Maxwell equations do not remain invariant under the Galilean transformation. This conflicts the principle of relativity which states that the physical law must remain invariant in the mathematical form in all inertial frames of reference. For this reason, the Lorentz transformation is invented, and the Galilean transformation is nowadays superseded by the Lorentz transformation. However, this paper challenges this widely held belief that the Maxwell equations are not invariant under the Galilean transformation. By applying the Galilean transformation to Lienard-Wiechert electromagnetic fields it is mathematically proven that the Maxwell equations indeed remain invariant under the Galilean transformation. In addition, the critical error in Lorentz's proof of Galilean non-invariance of Maxwell equations is pointed out, and it turns out that Lorentz's conclusion that Maxwell equations are not invariant under the Galilean transformation is the result of a mathematical error.

In this study, we demonstrate how the incorporation of appropriate feature engineering together with the selection of a Machine Learning (ML) algorithm that best suits the available dataset, leads to the development of a predictive model for transformation temperatures that can be applied to a wide range of shape memory alloys. We develop a gradient boosting ML surrogate model capable of predicting Martensite Start, Martensite Finish, Austenite Start, and Austenite Finish transformation temperatures with an average accuracy of more than 95% by explicitly taking care of potential distribution changes when modeling different alloy systems. We included heat treatment, rolling, extrusion processing parameters, and alloy system categorical features in the model input features to achieve more accurate and realistic results. In addition, using Shapley values, which are calculated based on the average marginal contribution of features to all possible coalitions, this study was able to gain insights into the governing features and their effect on predicted transformation temperatures, providing a unique opportunity to examine the critical parameters and features in martensite transformation temperatures.

This paper presents the results of an experimental study of the patterns of steel and lead shot transformation under the impact of environmental factors (two types of shot exposed alone and in combination with each other). The analyzed environmental factors include atmospheric precipitation of various acidity and soil solutions with a higher content of organic acids. This research demonstrated that steel shot is characterized by a high transformation rate that is an order of magnitude higher on average than the transformation rate of lead under the same conditions. The prevalence of the suspended iron form (excluding the interaction with organic acids) presents risks for such environmental components as soils and sediments and may be hazardous to the ambient air and natural waters in case of wind erosion and surface runoff from the catchment area. Furthermore, the joint presence of steel and lead shot mutually accelerates the corrosion of both metals, thus increasing the environmental risks.

The value of an NBA basketball player varies at each crucial point in time, depending on the player’s career and performance. This study constructs a player’s value assessment model. The model comprises two parts. First, from an objective perspective, entropy is employed to measure each player’s achievement in five categories—rebounds, assists, steals, blocked shots, and scores. The total entropy assessment value is calculated and then combined with the players’ scores to develop a player's value matrix to assess the relative value model among players of the same type.

The aim of the research results presented in the article is to strengthen a better understanding of the processes related to the transformation of hard coal mining in Poland, in particular the preparation of employees and their representatives, as well as employers from transformed areas for the upcoming changes. In this perspective, anticipating future skills against the internal potential of entrepreneurs becomes more and more important. It is a key element that enables entrepreneurs to adapt to changes, create innovative solutions and remain competitive on the market.

The insurance sector has undergone a transformative shift with the emergence of Insurtech, integrating technological innovations into the industry. This review aims to provide a comprehensive overview of the impact of Insurtech on the insurance sector, focusing on the case study of Lemonade. By placing the study in the context of the broader insurance landscape, the review explores the significance and relevance of this transformation. The article analyzes Lemonade's unique business model and its departure from traditional insurance practices. Furthermore, it examines the implications of Lemonade's approach on the industry and the challenges it faces. Through this analysis, the review sheds light on how Insurtech and the transformation of the insurance sector are redefining insurance services and consumer experiences. The future implications of these trends for insurance companies, consumers, and the industry as a whole are also explored. In summary, this review provides valuable insights into the transformative power of Insurtech, emphasizing the importance of technological advancements and innovative approaches in shaping the future of the insurance sector.

Este artigo apresenta o processo de implementação da Hiperautomação no setor público brasileiro, especialmente no âmbito da Procuradoria Geral do Estado de Pernambuco. Devido à atual economia competitiva, a demanda por soluções inteligentes e confiáveis está aumentando. Para atender a essa necessidade, tecnologias inovadoras que abordem a complexidade inerente à transformação digital são desejáveis. Assim, as organizações públicas têm buscado aplicar a automação de processos para atender às necessidades dos cidadãos por um serviço mais eficiente e eficaz. No entanto, podemos observar que a automação pura e direta é apenas parte do processo de transformação. Algumas das razões que explicam a necessidade de ir além da automação de processos e alcançar a hiperautomação é a abundância de dados de várias fontes e tipos. Tudo deve estar dentro dos padrões legais, ressaltando que toda tecnologia deve estar alinhada com transparência e auditabilidade para ser incorporada com segurança. Para a experimentação, foi utilizado o método de pesquisa-ação com a aplicação da Hiperautomação, visando aumentar a arrecadação e a economia do Estado na Procuradoria Geral do Estado de Pernambuco.

Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature, but of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.

Proposed study aims to investigate the digital transformation of Greek small and medium enterprises (SMEs), with a particular focus on their digital maturity and the strategic and organizational factors contributing to digital transformation. The research issue of digital transformation is attracting considerable interest among academics and business practicians since COVID-19 accelerated the procedure of implementing Industry’s 4.0 principles all over global economies. Quantitative research on 147 Greek SMEs revealed most important issues on how these businesses implement digital transformation, factors accelerating or decelerating the process, barriers and expected outcomes. Research enlights how SMEs face the transition to digital business and reveals the factors that can facilitate the whole process. Results can be valuable for stakeholders enabled to digital transformation process from both business and academic point of view, while there exist aspects that can contribute to policy makers / motivation developers in state’s level as well.

The research was carried out in southern Ethiopia to determine farmers' preferences for indigenous legume, fodder trees and shrubs (ILFTS), as well as the relationship between local feed valuation and scientific parameters. A focus group discussion (FGD) was conducted with ten farmers in each agro-ecological zone to determine the benchmarks for the preference ratings. The respondent farmers used the preference score sheet to rate all ILFTS on an individual basis. Twenty farmers with extensive experience in ILFTS took part in the preference score rating of each plant species in each agroecosystems. Dry matter (DM), organic matter (OM), Ash, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and metabolizable energy (ME) content of the samples were determined. The standard two-stage in vitro approach was used to measure the in vitro dry matter digestibility (IVDMD) of samples. ANOVA was used to analyze the variation among the species in agroecosystems. Farmers evaluated the ILFTS using a variety of parameters, according to the study (feed value, growth rate, biomass output, compatibility, and multifunctionality). The farmers ILFTS preference score on the evaluation criteria differed considerably (P<0.05) with species in agroecosystems. The nutritive value of ILFTS was in the acceptable range for feeding ruminants although exhibited a wide variation among the species in agroecosystems. The CP content was above the minimum requirement (8%) to support the normal function of rumen microorganisms. Moreover, CP exhibited positive significant correlation with IVDMD, IVOMD, and DOMD unlike CT and ADL which exhibited negative significant correlation. Thus, ADL and CT were identified as feed fractions that inhibit IVDMD either by depressing the activity of rumen microorganisms or restricting enzyme access to cell wall components. Conversely, the DM, OM, CP, IVDMD, IVOMD, DOMD, and ME were shown a positive significant correlation with farmers feed preference score, unlike the ADL and CT which exhibited a negative significant correlation. In conclusion, Farmers' indigenous knowledge of feed value is therefore relevant to some extent for judging the nutritive value of the ILFTS and could complement the scientific indicators.

Manufacturing organizations shall recognize sustainability as a business occasion to capitalize on, rather than an undesirable pressing situation. Still, empirical evidence shows that this opportunity is hard to capture and communicate in global strategic decisions, through planning by tactical management, to daily operational activities. This paper systematically reviews the modeling challenges at the crossroad of value and sustainability decisions making, spotlighting methods and tools proposed in literature to link sustainability to customer value creation at strategic, tactical and operational level. While statistical results show that the topic of sustainability and value modeling is trending in literature, findings from content analysis reveal that recent attempts to promote a value-based view in the sustainability discussion remain at a strategic level, with most of the proposed indicators being suited for managerial decision-making. The lack of support at operational level points to the opportunity of cross-pollinating sustainability research with value-centered methodologies originating from the aerospace sector. The Value Driven Design framework is proposed as main hub from which to derive models supporting engineers and technology developers in the identification of win-win-win situations, where sustainable improvements are aligned with business advantages.

Using a theorem of Ulam and Hyers, we will prove the Hyers-Ulam stability of two-dimensional Lagrange's mean value points $(\eta, \xi)$ which satisfy the equation, $f(u, v) - f(p, q) = (u-p) f_x(\eta, \xi) + (v-q) f_y(\eta, \xi)$, where $(p, q)$ and $(u, v)$ are distinct points in the plane. Moreover, we introduce an efficient algorithm for applying our main result in practical use.

Economic development and advancements in information technology contributed to the shift on accounting objective from commission responsibility view to decision-making useful view. The decision-making useful view claims that the accounting measurement methods should be changed to improve the usefulness of accounting information, to enable information users to make correct decisions. In addition, the development of financial instruments leads to the birth of fair value accounting. In recent years, fair value has been one of the most important measurement methods in the International Accounting Standard and US Generally Accepted Accounting Principles. However, China has been quite cautious when it comes to applying fair value full time, especially after the global financial crisis happened in 2008, wherein fair value accounting was exposed to strong suspicion. Hence, studying the value relevance of fair value is of great significance to exploring the accounting profession and reforming accounting standards. This paper attempts to investigate the value-relevance of fair value based on the data of listed financial companies and manufacturing companies in China. The results indicate that the fair value information in the financial industry has a strong explanatory influence to corporate share price. In contrast, the fair value information shows limited relevance in the manufacturing industry. Finally, consulting with the results of normative analysis and empirical study, this paper suggests several rational advices for the application of fair value in China.

Pressure drop and flow pattern of oil-water flows were investigated in a 19 mm ID clear polyvinyl chloride pipe consisting of U-bend with radius of curvature of 100 mm. The range for oil and water superficial velocities tested were and respectively. Measurements were carried out under different flow conditions in a test section that consisted of four different parts: upstream of the bend, at the bend and at two redeveloping flow locations after the bend. The result indicated that the bend had limited influence on downstream flow patterns. However, the shear forces imposed by the bend caused some shift flow pattern transition and bubble characteristics in the redeveloping flow section after the bend relative to develop flow before the bend. Generally, pressure gradient at all the test sections increased with both oil fraction and water superficial velocity and there was a sharp change of pressure gradient profile during phase inversion. The transition point where phase inversion occurred was always within the range of . Pressure losses differed at the various test sections and the difference was strongly linked to the superficial velocity of the phases and the flow pattern. At high mixture velocity, pressure losses at the redeveloping section after the bend were higher than that at the bend and that for fully developed flows. At low mixture velocity, pressure losses at the bend are higher than in the straight sections. Pressure drop generally decreased with level of flow development downstream of the bend.

This paper examines the transformation of the Ukrainian stock market by analyzing daily returns from the PFTS stock index spanning 1995-2022. Segmented into sub-periods, it tests the hypothesis that the market's efficiency has grown over time. Various data properties, including persistence, volatility, normality, and resistance to anomalies, are explored using different statistical techniques and methods. Volatility, indicated by standard deviation, exhibits a general decreasing trend, suggesting a shift towards a more efficient market. Returns show no significant differences across sub-periods, except for 2005-2007. R/S analysis indicates the decrease of persistence in the market: a trend towards increased efficiency. Normality tests support a normal distribution of daily returns throughout sub-periods. An analysis of anomalies reveals the market's resilience to day-of-the-week effects, with no specific trends observed. The results suggest the absence of serious changes in data properties in the Ukrainian stock market over the time, means evolutionary processes over 25 years can’t be clearly observed. Reforms and changes have had limited impact, justifying continued reform for the market's evolution.

In an era of rapid technological advancement, Egypt stands at the crossroads of digital transformation. Our research delves into the intersection of economy and 5G technology, exploring how these forces can reshape the nation’s economic landscape. By examining the impact on GDP, we aim to guide policymakers, telecom operators, and citizens toward a more connected and prosperous future. Join us on this journey as we unravel the potential of 5G and pave the way for inclusive growth.

The present-day financial system is being influenced by the rapid development of Fintech (financial technologies), which are technologies created to improve and automate traditional forms of finance for businesses and consumers. The topic of Fintech as a financial disruptor is gaining popularity in line with the swift spread of digitalization across the banking industry, whereby this paper contributes to the field by presenting a novel bibliometric analysis of academic literature related to Fintech as a financial disruptor. The analysis is based on metadata extracted from the Scopus database through the VOSviewer and Biblioshiny software. The bibliometric analysis of 363 documents identified the most impactful sources of publication, keywords, authors, and most cited documents on the topic of Fintech as a financial disruptor. As our analysis demonstrates the number of publications on the given topic increases, defining both the interest among academia and potential for future research.

The flow properties of pellets or granules are crucial for further processing the drug dosage forms. Optimal compression or filling the multiparticulate dosage forms into capsules is influenced by forces between discrete particles, which could be partially characterized by flow properties. Several techniques were developed for the examination of flowability, including static and dynamic methods applying empirical studies and the up-to-date chaos theory; however newest methods seem only to be powerful with the supplement of empirical principles. Our experiments try to refine both the technique of analysis and the methods by finding new, alternative ways. Our approach to the flowability measurements was to set up a dynamic time-dependent model which combines empirical observations and the chaos theory on a geometrical basis, thus find new aspects regarding flow properties of pellets and granules that could be relevant for drug developers.

This study seeks to interrogate the degree to which lecturers and students of higher institutions in Nigeria perceive the role of lecturers doubling as parents under the term lecturenting, i.e., a coinage used to refer to a person who performs the dual roles of lecturing and parenting students of higher institutions. The study is based on Professor Obiora Ike’s ideology of communication of values, normally applicable to traditionally homes only. The research used a quantitative survey of 266 undergraduates and 109 lecturers, totaling 375 respondents from two purposively selected higher institutions in Nigeria, namely: Edo state University Uzairue and Federal Polytechnic Auchi, both in Etsako West Local Government Area of Edo state, Nigeria. A questionnaire with a set of nine semi-structured questions was used to obtain data from the students during the school semesters between July 15 and August 31, 2022. The study was based on the value theory. Findings indicate that lecturers frequently engage in lecturenting which helped improve the academic performance of students but shows that students do not want lecturenting on their behavioral change. The study concludes that the more lecturers engage in Lecturenting, the more positive impact it will have on their students. It is recommended that lecturers should engage in the practice of lecturenting as it helps to improve student academic performance and that students should perceive lecturenting as positive as well as be favorably disposed to it and approach their lecturers for counselling frequently.

This study will present a comprehensive review of the two-phase flow boiling heat transfer coefficient of hydrocarbons such propane (R-290), butane (R-600) and iso-butane (R-600a) and ethanol at various experimental conditions. Studying the multiphase flow heat transfer coefficient has a crucial importance for many heat transfer equipment to achieve higher efficiency for more compact design and cost reduction. One reason behind choosing hydrocarbons as refrigerants in this study is because hydrocarbons have zero ozone depletion potential (ODP=0) and insignificant direct global warming potential (GWP = 3). Moreover, thermodynamic and thermophysical characteristics of hydrocarbons qualify them to be a strong candidate for more heat transfer applications. Initially, by constructing a database for the working fluids from various experimental work available in the literature. The current data that this study has collected for the flow boiling of spans wide ranges of parameters, such as: mass flux, heat flux, operating pressure, and saturation temperature, etc. Furthermore, by comparing the experimental multiphase heat transfer coefficient database with the anticipated values of each correlation, the prediction performance of 26 correlations found in the literature was assessed. This study leads to the selection of the best prediction method based on the minimum deviation of predicted results from the experimental database provided by calculated mean absolute error (MAE) from the assessed correlations. The findings of this study can also be useful in the development of more accurate correlation methods for these fluids and improve the prediction of their flow boiling characteristics.

In this study, it was aimed to analyze the multi-cultural characteristics of the pre-service teachers and the values they have in terms of various variables, to determine the relationship between these values. Descriptive survey model, one of the quantitative research methods, was used in the study. The population of the study consisted of the pre-service teachers studying in different departments in the Faculty of Education, İbrahim Çeçen University of Ağrı in 2017-2018 academic years. The sample of the study consisted of 341 pre-service teachers selected with random sampling method. According to the results obtained from the study, it was determined that the value preferences of the pre-service teachers and their multicultural personality characteristics showed a significant difference in terms of gender, undergraduate program, educational background of the mother, having social media account and daily internet use variables; however, there was not a significant difference in terms of family structure, the place s/he grew up, educational background of the father and monthly income variables. The abstract does not include information about which groups are favored for the difference in the variables and in which sub-dimensions, but detailed information is given in the following sections of the study.

Heritage conservation area designation is often resisted by communities due to concerns with overly strict regulations for property alterations and negative impacts on property values. This paper addresses these concerns by examining Freemans Bay and Onehunga – two Special Character Areas (SCAs) in Auckland, New Zealand. A property value analysis was used to assess the impact of SCA designation on property values and an online questionnaire survey gathered information on homeowners’ experiences and levels of satisfaction with living in an SCA. The results indicate that designated SCA properties have higher average values than non-designated properties and homeowners are overwhelmingly satisfied with living in a SCA. The main benefits are a sense of community and having certainty around the look and feel of their neighbourhood into the future. The main issue identified by respondents is the requirement for Resource Consent. The majority of people who had gone through the process found it to be a negative experience because of the high cost in terms of time and money. A historic urban landscape approach to the development of management plans and design guidelines is recommended to improve the implementation of the Special Character Areas in Auckland and beyond.

In 2020, the early Covid-19 lockdown and social distancing induced the abrupt migration of traditionally presential learning activities to online domains. This “new normal” environment affected management not only of training courses, but also educational events whose main added value consisted in providing students with an interactive experience onsite, as it is the case of inter-institutional summer schools. The following research corresponds to a case study in which our organization, a French university, had to reformulate, in less than three months, one of its traditional summer schools while trying to keep the original goals. We aimed at identifying the impact of four managerial decisions by analyzing, through qualitative and quantitative surveys, students’ perception of gained or lost value regarding four topics: a) online teaching, b) pre-recorded busines cases providers, c) online social events, and d) technical solutions. With an emphasis in both didactics (i.e., knowledge) and pedagogics (i.e., learning experience), the analysis of perceived value allowed as to learn about students’ assessment position, which revealed two main issues at stake: belonging, in relation to students’ identity and academic background, and performing, related to students’ expectations.

Optical micro-angiography (OMAG) is a new method of detecting flow rate and widely used for in vivo imaging. Although OMAG can distinguish between flowing and stationary parts, it cannot obtain accurate flow rate information. This study proposed a range formula for OMAG and the ultrahigh-sensitivity OMAG (UHS-OMAG) method to quantify the measurement range of an entire system. The parameters of the angle between beam scanning and flow directions, the angular velocity of the galvanometer, and the offset of incident light were introduced, and a formula for calculating the range was derived. Experiments were conducted to measure fine and ultra-fine flow rates by using OMAG and UHS-OMAG methods. The minimum measured flow rate was approximately 30 μm/s, and the maximum measured flow rate was approximately 8 mm/s. Experimental results are in good agreement with the preset results.

The changing of banking customer preferences after Covid-19 pandemic encourages banking transformation. Neobanks emerges as innovation in banking that enter the market to compete with the incumbent banks by offering new digital experience for customer. This paper analyzes the neobanks which transformed from traditional bank, specifically its efficiency after they implement digital transformation. Efficiency is measured by using Stochastic Frontier Analysis (SFA). This study also uses Pooled Mean Group (PMG) of Panel ARDL (Autoregressive Distributed Lagged) to investigate digital transformation as one of determinants neobank’s efficiency, as well as to examine the existence of short-term and long-term relationship between digital transformation and efficiency. The SFA results show that the efficiency of the neobanks increase after they carry out digital transformation. Furthermore, from PMG Panel ARDL, it can be concluded that digital transformation is one of determinant of efficiency and there is longevity relationship between digital transformation and efficiency. In the short run, digital transformation has a significant and negative correlation with efficiency and in the long run, it has a significant positive relationship because initially digital transformation cost for operational and risk management innovation decreases the profit efficiency, but afterwards it increases the profit efficiency.

The Randić index of a graph G is the sum of (dG(u)dG(v))−1/2 over all edges uv of G, where dG(u) denotes the degree of vertex u in G. In this paper, we investigate a few graph transformations that decrease Randić index of graph. By applying those transformations, we determine the minimum Randić index on tricyclic graphs, and characterize the corresponding extremal graphs.

the process of rapidly digitalizing and transforming businesses, known as Industry 4.0, was already underway before COVID-19. However, the imposed restrictions during the pandemic significantly amplified the need and motivation for both businesses and consumers to utilize digital tools across all sectors including the sectors of bioeconomy. The agricultural and food production sectors have a predominant role in the bioeconomy of the European Union (EU), followed by wood production. These sectors make significant contributions not only to national economies but also to rural areas. Consequently, the digitalization of businesses within the bioeconomy sector not only transforms the enterprises and value chains themselves but also benefits the rural communities in which these enterprises are situated. This study aims to assess the barriers of the bioeconomy sector and ways to support digital transformation within this sector. The paper analyses bioeconomy in EU and the state of digitalisation in the EU. The empiric analysis is based on the cluster analysis of the digitalisation and R&D indicators of the EU and the AHP analysis that allows determining the digitalisation scenarios in Latvia, Lithuania and Poland carried out by four stake-holder groups - national government; advisory and extension; research and entrepreneurship. The results of the AHP indicate that experts from Lithuania and Poland preferred the scenario that suggested the self-initiative from the entrepreneurs of the sector, but experts from Latvia – prioritization of support for digital transformation using national and EU funding. The AHP results also indicate that the opinions of the national government, consulting, and research experts are more aligned throughout all three countries, but the opinion of entrepreneurs differs from these groups.

Abstract Most Asian countries like South Korea have transformed themselves from poor agrarian nations into one of the fastest-growing industrialized economies in the world. Rural transformation poses great challenges to rural people and areas, but also it also provides great opportunities for sustainable rural development. The evolution of South Korea's rural policies is embedded through the different national institutions with different sectors. Diversification of rural economic opportunities may further extend to the industries for economic development in rural regions alongside efforts to improve living. Examining the rural transformation in South Korea, mainly the rural development with land, agriculture, truism, politic,s and strategy they used that shaped the structure of the rural transformation and its activities over time and Ethiopia takes lessons is the objective of the study. Document analysis is a tool for achieving information. Ethiopia takes lessons from South Korea from the general sector of rural development to the particular agricultural development sector, rural truism development, land reform which is the core asset for the world people, health care reform, and market and trade transformation (indicates that the base for developed country development was trade reform from import to export), rural job employment transformation (which have the multidimensional impact to the development of nation) and rural political transformation are the basic areas of rural transformation in which Ethiopia focused to do. The country can grow with the integrated/ collaborative work of the stakeholders. The government of Ethiopia applying a functional regional strategy to shape the socio-economic and cultural changes of the rural people and working with civil societies and other non-governmental stakeholders must be the primary tasks

Oral squamous cell carcinoma often arises from an oral potentially malignant disorder called oral leukoplakia (OL). With this work we aimed to develop a novel data-driven predictive model based on gene expression profiles to distinguish OL patients who underwent malignant transformation from those who did not. We used the Tree Augmented Naïve (TAN) Bayes classifier to predict the posterior probability of having oral cancer given the data. 86 patients were included with a median follow-up of 7.11 years. Fifty-one patients (51/86; 59%) underwent malignant transformation. We found that 16 genes were predictors of oral cancer in patients with OL and these included SLC7A11, SPINK6, SERPINA12, VIT, ATP1B3, CST6, FLRT2, ELMOD1, AZGP1, RNASE13, DIO2, ECM1, CYP4F11, SYTL4, AKR1C1, and AKR1C3. In conclusion, we showed that Bayesian gene networks are a data-driven approach which could be used also in other predictor models in oncology.

The morphological transformation of an arched ribbon driven by torsion is a scientific problem that is connected with daily life and requires thorough analysis. An arched ribbon can achieve an instantaneous high speed through energy transformation and then return to the original shape of the structure. In this paper, based on the characteristics of the ribbon structure, the dynamic mathematical model of the arched ribbon driven by torsion is established from the Kirchhoff rod equation. The variations of the Euler angle of each point on the center line of the ribbon with the arc coordinate s and the rotation angle of the supports $\phi$ was examined. The relationship between the internal force distribution of each point in the direction of $\hat{d}_{a}$ and the material, cross-sectional properties, and rotation angle of the supports was obtained. We used ABAQUS, a nonlinear finite element analysis tool, to simulate the morphological transformations of the ribbons, verified our theory with simulation results, and reproduced the experimental results of Sano. Furthermore, we redefined the concept of the ``critical flipping point'' of Sano. In this paper, the dimensional analysis method was used to fit the simulation data. The following relationship between the critical width $ w ^{*} $, thickness h, and the radius R of the ribbon with different cross sections was obtained: $w^{*}=A\cdot R\left(h/R\right)^{0.6}$, where A is 3.19 for rectangular cross sections and 3.06 for elliptical cross sections. By analyzing the simulation data, we determined the variation behavior of the out-of-plane deflection of the center point of the ribbon with the radius R, width w, and thickness h. Our research has guiding significance for understanding and designing arched ribbons driven by torsion, and the results can be applied to problems of different scales.

Africanization of education was a major policy option in most countries in Africa upon the attainment of independence. This is because of the perceived negative effects of colonial education. The paper is an empirical sources study which discusses Africanization as an epistemicide and analyses efforts by some African states to Africanize their educational systems. It concludes that while some countries embraced the idea and actually initiated policies to Africanize their educational systems, the general picture indicates that Africanization has not succeeded in most countries due to various challenges. Such challenges are identified and recommendations made which could be significant for the revamping of the policy.

Hierarchical tungsten oxide assemblies such as spindle-like, flowers with sharp petals, nanowires and regular hexagonal structures are successfully synthesized via a solvothermal reduction method by simply adjusting the reaction conditions. On the basis of the experimental results, it is determined that the reaction time significantly influences the phase transition, microstructure and photocatalytic activity of the prepared samples. The possible mechanisms for the phase transition and morphology evolution process have been systematically proposed. Moreover, the as-prepared products exhibit significant morphology-depended photocatalytic activity. The flower-like W18O49 prepared at 6 h possesses large specific surface area (150.1 m²g^-1), improved separation efficiency of electron-hole pairs and decreased electron-transfer resistance by the photoelectrochemical measurements. As a result, the flower-like W₁₈O₄₉ prepared at 6 h exhibits the highest photocatalytic activity for the degradation of Methyl orange aqueous solution. The radical trap experiments showed that the degradation of MO was driven mainly by the participation of h⁺ and •O²⁻ radicals.

Mechanical ventilation systems, which are used for breathing support when a person is not able to do it by their own, requires a device for measuring the air flow to the patient in order to monitoring and a assure the magnitude establish by a medical staff. Flow sensors are the conventional devices used for the air flow measuring; however, there were not available in Peru, because of the international demand during COVID-19 pandemic. In this sense, a novel air flow sensor based on orifice plate and an intelligent transducer stage were developed as an integrated design. Advanced methodologies in simulations and experiments using specially designed equipment for this application were carried out. The obtained data was used for a mathematical characterization and dimensions validation of the integrated design. The device was tested in its real working conditions, it was implemented in a breathing circuit connected to a low-cost mechanical ventilation system based on cams. Results indicate that the designed air flow sensor/transducer is a low-cost complete medical device for mechanical ventilators able to provide satisfactorily all the ventilation parameters air flow, pressure and volume over time by measuring the air flow and calculating the others. Furthermore, this device provides directly a filtered equivalent electrical signal for a display or a computer.

Imaging flow cytometry (ImFC) represents a significant technological advancement in the field of cytometry, effectively merging the high-throughput capabilities of flow analysis with the image-based features of microscopy. In this comprehensive review article, we take a historical perspective and delve into the evolution of this methodology, presenting its past, exploring current state-of-the-art and forecasting potential future advancements. The inception of ImFC arose from the innovative combination of a flow cytometer's hydraulics with the technology of an advanced camera. This synergistic coupling facilitated the morphological analysis of cell populations at a high-throughput scale, effectively evolving the landscape of cytometry. However, the application of ImFC faced several challenges. Among the most prominent ones, is the development and implementation of software systems that can reliably and efficiently handle the robust data acquisition and analysis inherent in ImFC. The scale and complexity of the data generated by ImFC necessitates the creation of novel analytical tools that can effectively manage and interpret this data, thus allowing us to unlock the full potential of ImFC. Interestingly, artificial intelligence (AI) algorithms have begun to be implemented on ImFC, offering a promise for enhancing analytical capabilities. The adaptability and learning capacity of AI may prove to be essential in knowledge mining from high-dimensional data produced by ImFC, potentially enabling more accurate analyses. Looking forward, we project that ImFC may become an indispensable tool, not only in research laboratories but also in clinical settings. Given the unique combination of high-throughput cytometry and detailed imaging offered by ImFC, we foresee a critical role for this technology in the next generation of scientific research and diagnostics. As such, we encourage both current and future scientists to consider the integration of ImFC as an addition to their research toolkit and clinical diagnostic routine.

Objectives: The purposes of this study were to 1) analyze the disruption of intracardiac flow by flow components and kinetic energy (KE) parameters in single ventricle physiology patients and compare with controls; 2) investigate left ventricular diastolic dysfunction in terms of 4D flow parameters in repaired Fontan (rFontan) group; 3) compare intracardiac flow parameters in morphologic LV and RV rFontan patient groups. Methods: Twenty-five rFontan patients (age: 10±3, M/F: 15/10) and fourteen controls (age: 10±2, M/F: 8/6) were prospectively recruited. All underwent cine and 4D flow cardiovascular magnetic resonance (CMR) on 3.0T scanner. Cardiac function and inter-ventricular mechanical dyssynchrony were analyzed using cine images. From 4D flow CMR, ventricular flow components were assessed: direct flow, retained inflow, delayed ejection flow and residual volume. Global and regional blood flow KE parameters, normalized to end-diastolic volume (EDV) were analyzed for functional single ventricle (FSV). Left ventricular (LV) diastolic dysfunction was assessed on echocardiography guidelines. Results: In comparison of rFontan vs. controls, median FSV residual volume (28% vs. 23%, P= 0.034) were higher in rFontan; median FSV direct flow (32% vs. 40%, P=0.005) and delayed ejection flow (17% vs. 24%, P=0.024) were lower in rFontan. FSV KEiEDV parameters were all lower in rFontan (all P<0.05). No significant differences were observed for flow components and KE parameters between patients with and without inter-ventricular dyssynchrony. FSV direct flow (AUC=0.76, Sensitivity=86%, Specificity=70%) was an independent predictor of LV diastolic dysfunction. Residual volume and E-wave KEiEDV were significantly different between morphologic RV and morphologic LV patient group. Conclusions: The changed flow pattern and decreased KE may be hemodynamic disturbances and impaired ventricular filling in rFontan patients. Reduced direct flow is associated with LV diastolic dysfunction. Morphologic right ventricular subgroup is worse than morphologic left ventricular group in terms of the intracardiac hemodynamics.

This study focuses on traffic condition analysis, especially in under developing country India and makes more visible of traffic flow by using traffic flow theory in order to understand real traffic condition. India is one of rapid economic growing countries and large market with second largest population 1.3 billion in 2018. On the other hand, there are social issues such as environment air pollution and global warming by traffic CO2 emission of transportation. This kind of condition is not only in India, but in other South East Asia and Africa in future. From recent more than one-month traffic observation in a typical major city Ahmedabad in Gujarat state, which has about 8 million population and industrialized city. In terms of traffic data collection, 14 CCTV cameras are used in the city. Based on multiple traffic cameras monitoring, author found the unique traffic flow characteristics and compares traffic flow theory. In this study, it is described what is key parameters to show real traffic congestion condition and how these congestion occurs.

The aim of this study is to model hydrodynamic processes of the Istanbul Strait with its stratified flow characteristic and calibrate the most important parameters using local and global search algorithms. For that two open boundary conditions are defined, which are in the North and South part of the Strait. Observed bathymetric, hydrographic, meteorological and water level data are used to set up the Delft3D-FLOW model. First, the sensitivities of model parameters on the numerical model outputs are assessed using PEST toolbox. Then, the model is calibrated based on the objective functions focusing on the flowrates of upper and lower layers. The salinity and temperature profiles of the Strait are only used for model validation. The results show that the calibrated model outputs of Istanbul Strait are reliable and consistent with the in-situ measurements. The sensitivity analysis reveals that the Spatial Low-Pass Filter Coefficient, Horizontal Eddy Viscosity, Prandtl-Schmidt Number, Slope in log-log Spectrum and Manning Roughness Coefficient are most sensitive parameters affecting flowrate performance of the model. The agreement between observed salinity profiles and simulated model outputs is promising whereas the match between observed and simulated temperature profiles is weak showing that the model can be improved particularly for simulating the mixing layer.

In today’s world face detection is the most important task. Due to the chromosomes disorder sometimes a human face suffers from different abnormalities. For example, one eye is bigger than the other, cliff face, different chin-length, variation of nose length, length or width of lips are different, etc. For computer vision currently this is a challenging task to detect normal and abnormal face and facial parts from an input image. In this research paper a method is proposed that can detect normal or abnormal faces from a frontal input image. This method used Fast Fourier Transformation (FFT) and Discrete Cosine Transformation of frequency domain and spatial domain analysis to detect those faces.

Kim-Kim ([9]) studied some properties of the degenerate gamma and degenerate Laplace transformation and obtained their properties. In this paper, we define modified degenerate gamma and modified degenerate Laplace Transformation and investigate some properties and formulas related to them.

The development of the chicken value chain in The Gambia has immense potentials to lead to the modernisation of agriculture and creating employment for young people and women. Chicken can be raised throughout the year in most parts of The Gambia. With increasing populations, environmental degradation and loss of rangelands, chicken is easier to producer than other livestock, such as cattle and small ruminants. The development of the chicken value chain in The Gambia is also mainly constrained at commercialisation. Commercial farmers in The Gambia are not able to compete with cheap import. Critical inputs such as day-old chicks and feed are imported. Most farms are operating below 40% capacity and only less than 4% utilisation of the available processing capacity. At full capacity and with some needed investments along the value chain, The Gambia has the capacity to meet the demand for chicken and eggs. 88% of the value chain actors believe that the imposition of tariffs on chicken imports will lead to the upward transformation of the chicken value chain being able to employ at least 10% of the Gambian population.

Backyard production systems (BPS) are highly distributed in central Chile. Poultry BPS have been previously characterized; however, swine BPS have not yet been deeply characterized in central Chile. In addition, there is evidence that zoonotic pathogens, such as influenza A virus and Salmonella spp., are circulating in both poultry and pigs kept these production systems. A total of 358 BPS located in central Chile were evaluated between 2013 and 2015 by interviewing farm owners. Severe deficiencies in biosecurity measures were observed. The value chain of swine backyard production identified feeding, products and veterinary visits, and replacement or breeding animals as the main inputs to the backyard. The most common origin of swine replacements was from outside the BPS (63%). Meat and live animals (piglets and breeding animals) were identified as the main outputs of the system. In 16% of BPS, breeding animals were lent to other BPS, indicating the existence of animal and animal products movement in and out of backyard farms. Results from this study suggest that swine BPS in central Chile represent an animal-human interphase that need special attention to direct preventive measures aimed at avoiding the introduction and dissemination of animal pathogens and the emergence of zoonotic pathogens.

The aim of the article is to present a snapshot in time, of the current state in cryptocurrencies, the values and risks associated to blockchains. With emergence of over 20,000 crypto projects, the first objective of this article is to present the stage as it is in 2023, with historical overview since Satoshi presented the first paper on decentralised blockchains, until today. Second objective of the article is to review the values and risks associated to cryptocurrencies, and to clarify the differences between cryptocurrencies from blockchain technologies. The research questions that drive this article are related determining if the blockchain technology an innovation or its already obsolete technology? Are there any significant risks from cryptocurrencies? And are the potential values to society and economy worth pursuing? Would developed or developing countries benefit more from these technologies? And which blockchain projects will survive in the long run? In other words, where is the money and is there money or just hype. The review discusses the high probability that some crypto projects will fail, and given the vast number of cryptos, the article acknowledges that many of these projects are nothing more than ponzies. These are discussed and acknowledged, then the focus is shifted to the real-world use cases of blockchain projects.

Climate adaptation is a major challenge. Chasing the sufficient amount of hay is getting in higher priority. Distant mass hay producers give favourable offers despite long distances. Quality is also gaining position and indicators like RFQ (Relative Forage Quality) is highlighting the marketing language. Hay market as we knew no longer exists in Hungary. Most farmers produce their own hay and do not spend extra cents to buy bales. Climate change however, force them to adapt and store more bales for the future. Horse owners and dairy farmers are the main driver to convince hay producers to provide high quality forage. We gathered Hungarian regional hay-price information and evaluated the trends in this sector. The demand-driven hay-price is in contradiction with premium quality timothy grass hay.

Qualitative and quantitative values estimation is a crucial aspect of social data science and plays a vital role in social and psychological research. Numerous methods of personal values measurement such as Schwartz Value Survey (SVS) and its re-modified versions have been proposed and invented, but many are challenged with one or more limitations. In this article, an alternative approach in a new paradigm of values measurement called Kabiru’s Value Survey (KVS) was proposed to measure the relative degree of importance or significance attached to particular value-actions of an individual(s) in a given population over a period. The methodological innovations in KVS unlike other existing methods of human value measurement include the use of habitually reported practices associated with a particular value-action in place of judging the series of Schwartz hypothetical statements, the use of multiple dependent variables rather than a single coded hypothetical statement. In terms of data analysis, a new approach of multivariate compression is introduced which merges the chain of multiple dependent variables into one coded scale. Psychometric result interpretation is also another innovative aspect of KVS methodology. Finally, the proposed methodology however solved some of the criticized limitations of the other methods of human value measurement.

It is increasingly common for experiments in biology and medicine to involve large numbers of hypothesis tests. A natural graphical method for visualizing these tests is to construct a histogram from the p-values of these tests. In this article, we examine the shapes, both normal and abnormal, that these histograms can take on, as well as present simple inferential procedures that help to interpret the shapes in terms of diagnosing potential problems with the experiment. We examine potential causes of these problems in detail, and discuss potential remedies. Throughout, examples of abnormal-looking p-value histograms are provided and based on case studies involving real biological experiments.

Revealing the multidimensional value of cultivated land resources, improving calculation methods, and exploring their spatial distribution characteristics and influencing factors are crucial for the enhancement of natural resource accounting system and the protection of cultivated land resources. This study take Guangxi, China as an example and construct a comprehensive multidimensional value evaluation system for cultivated land resources at the county scale. The income capitalization method, substitution market method, and value equivalent correction method were applied to calculate the economic, social, and ecological values of cultivated land resources in 111 counties. Furthermore, spatial autocorrelation analysis was employed to study their distribution characteristics and influencing factors. The results show that: (1) The total value of cultivated land resources in Guangxi reach 19,729.2 billion yuan, and the average cultivated land value is 5.3511 million yuan/hm2, of which the ratio of economic, social and ecological values is about 6:1:2; (2) The value of cultivated land has a certain distribution pattern in the global space, and the average economic and social value show the spatial distribution patterns of "low in the west and high in the east" and "low in the northwest and high in the southeast" respectively."(3) There is a significant spatial clustering effect of all values of cultivated land resources in local space, with "high-high" and "low-low" clustering. (4) Economic development level is significantly negatively correlated with the ecological value of cultivated land, while has a significant positive correlation with social value; (5) Natural conditions, economic development and agricultural development approaches are the key factors affecting the value of cultivated land resources.

Hospital bed shortage is a worldwide concern. Beds unavailability has caused elective surgery cancellations, at our hospital peaking in spring 2016 at over 50%. This is often due to difficult patient step-down from intensive care (ICU) and high-dependency units (HDU). In our general/digestive surgery service admitting approximately 1000 patients yearly, ward rounds were run on a consultant firm basis. We report a quality improvement (ISRCTN13976096) introducing in our service a structured daily multi-disciplinary board round framework (SAFER Surgery R2G) adapted from the “SAFER patient flow bundle” and the "Red to Green days” approaches to enhance flow, comparing the previous year to 2017, when our framework was applied for 12 months.We used a Plan-Do-Study-Act (PDSA) methodology. Our intervention consisted in 1) systematic communication of the key care plan after the afternoon ward rounds to the nurse in charge; 2) 30’ 10AM Monday-to-Friday multidisciplinary board rounds, attended daily by the senior-team and weekly by hospital and site managers, revising the key care plan aiming at safe, early discharges, assessing the appropriateness of each inpatient day and tackling any cause of delay. We measured patient flow by average length of stay (LOS), ICU/HDU step-downs and operation cancellations count, monitoring safety through early 30-day readmissions. Compliance was assessed by board round attendance and staff satisfaction rate surveys.After 12 months (PDSA 2, N=1032), LOS significantly decreased from 7.2(±8.9) to 6.3(±7.4) days (p=0.003); ICU/HDU bed step-down flow increased by 9.3% from 345 to 375 (p=0.197), surgery cancellations dropped from 38 to 15 (p=0.100). 30-day re-admissions increased from 0.9% (N=9) to 1.3% (N=14)(p=0.390). Average cross-specialty attendance was 80%. Satisfaction rates were >75%, regarding enhanced teamwork and faster decisions.The SAFER Surgery R2G framework has shown an increase in patient flow in the context of an enhanced multidisciplinary approach, requiring senior staff commitment to remain sustainable.

Blockchain technology (BCT) has the potential for sustainable development, enhancing business efficiency, reducing costs, and strengthening data security. Despite its potential, adoption among small and medium-sized enterprises (SMEs) is low due to the need for significant changes in technology infrastructure and the challenge of interoperability. A cross-sectional survey was done with 226 Hong Kong SMEs. The PLS-SEM results highlighted favorable transformation conditions as the most critical factor for SMEs considering the adoption of BCT. These conditions address both internal and external readiness for adopting the disruptive strategy. Other contributing factors to BCT adoption include trust in BCT developers, perceived usefulness and ease of use, government support, and perceived security. The research results contributed to the literature on disruptive technology acceptance, adoption, transformation conditions, technology readiness, and SMEs’ technology adoption. Government-supported policies and initiatives can promote BCT adoption, including educational programs, case studies, and resources for readiness. Financial support and regulatory frameworks can further encourage adoption. BCT developers can demonstrate the value of their systems, effectively communicate potential ROI and cost savings, and provide user-friendly interfaces to increase SMEs’ intention to adopt BCT.

Reactions of Co(OAc)24H2O, N‚N'-bis(3-pyridylmethyl)oxalamide (L) and 4,4’-sulfonyldibenzoic acid (H2SDA) afforded four coordination polymers with the same mixed ligands, {[Co(L)(SDA)(H2O)2]·H2O·CH3OH}n, 1, {[Co(L)0.5(SDA)]·2H2O·0.5L}n, 2, {[Co(L)1.5(SDA)(H2O)]·H2O}n, 3, and {[Co2(L)1.5(SDA)2(H2O)2]·4H2O}n, 4, which have been structurally characterized by using single crystal X-ray crystallography. Complexes 1 – 4 are 2D layers, revealing the topologies of sql, 2,6L1, (4,4)Ia and 6L12, respectively, and demonstrating that the metal to ligand ratio, solvent system and reaction temperature are important in determining the structural diversity. Immersion of these complexes into various solvents show that the structural types govern the chemical stabilities of 1 – 4. Reversible structural transformation can be shown for complexes 1 and 2 upon solvent removal and adsorption, while those of 3 and 4 are irreversible.

Various implementations of the Move with Interleaving transform are discussed in this paper, with the transformation itself explained briefly at first. The transform has an expected time complexity of O(n), where n represents the length of the sequence being transformed. The importance of implementation also grows as the sequences become longer. The paper explains three different implementations: the first uses the standard vector, the second employs a lookup table, and the third utilises a dynamic linked list with a pool of released records. The experiments were conducted on 32 greyscale raster images of various contexts and sizes. All three solutions were implemented in both C++ and Java, and then executed on three different platforms: a personal computer running MS Windows and Linux, and a Raspberry Pi 2 with Linux. The implementation based on the dynamic linked list was the fastest, and outperformed the vector-based implementation by more than 1800%. While direct comparisons between results on the Raspberry Pi and those on the modern personal computer may not be straightforward, a consistent pattern prevails: the dynamic linked list implementation outperformed the other two consistently, and the C++ code was faster than the code written in Java. The difference was most evident on the Raspberry Pi.

Mesenchymal stromal cells (MSCs) are a subset of heterogeneous non-hematopoietic fibro-blast-like cells which play important roles in tissue repair, inflammation, and immune modula-tion. MSCs residing in the bone marrow microenvironment (BMME) functionally interact with hematopoietic stem progenitor cells regulating hematopoiesis. However, MSCs have also emerged in the last years as key regulator of tumor microenvironment. Indeed, they are now con-sidered as active players in the pathophysiology of hematologic malignancies rather than passive by-standers in hematopoietic microenvironment. Once the malignant event occurs, the BMME acquires cellular, molecular, and epigenetic abnormalities affecting tumor growth and progres-sion. In this context, MSC behavior is affected by signals coming from cancer cells. Furthermore, it has been showed that stromal cells themselves play a major role in several hematological malig-nancies’ pathogenesis. This bidirectional crosstalk creates a functional tumor niche unit wherein tumor cells acquire a selective advantage over their normal counterpart and are protected from drug treatment. It is therefore of critical importance to unveil the underlying mechanisms which activate a protumor phenotype of MSCs for defining unmasked vulnerabilities of hematological cancer cells which could be pharmacologically exploited to disrupt the tumor/MSCs coupling. The present review will focus on the current knowledge about MSC dysfunction mechanisms in the BMME of hematological cancers, sustaining tumor growth, immune escape, and cancer pro-gression.

The cubic B2 to monoclinic B19’ martensitic transformation in NiTi shape memory alloys proceeds by the nucleation and propagation of habit plane interfaces that remain undistorted and unrotated by the transformation. Due to incompatibility of austenite and martensite lattices in NiTi, the interfaces form between austenite and twinned martensite as described by Phenomenological Theory of Martensite Crystallography (PTMC). This have been assumed also for stress-induced martensitic transformation where, however, interfaces with single martensite variant have been frequently reported. On this account, we propose a different solution of strain compatibile habit planes by considering the effect of elastic deformation of both lattices due to external stress. Using modified PTMC theory, we evaluate the magnitudes and orientations of the critical uniaxial stress in tension and compression for which strain compatible habit plane interfaces with a single variant of martensite can form. The calculated stress is too high, but considering the pre-transformation softening of the C’ elastic constant for the {110}A⟨110⟩A austenite shear mode, the critical stress decreases down to 500 MPa. For such situation, we analyse orientation dependence and tension-compression asymmetry of required C’ softening, and the orientations of strain compatible habit planes that are compared with available experimental results. All calculations, including source code and interactive graphs, are available for download.

Non-rigid registration presents a significant challenge in the domain of point cloud processing. The general objective is to model complex non-rigid deformations between two or more overlapping point clouds. Applications are diverse and span multiple research fields, including registration of topographic data, scene flow estimation, and dynamic shape reconstruction. To provide context, we begin with a general introduction to the topic of point cloud registration, including a categorization of methods. Next, we introduce a general mathematical formulation for point cloud registration and extend it to address non-rigid registration. A detailed discussion and categorization of existing approaches to non-rigid registration follows. We then introduce our own method where the usage of piece-wise tricubic polynomials for modeling non-rigid deformations is proposed. Our method offers several advantages over existing methods. These advantages include easy control of flexibility through a small number of intuitive tuning parameters, a closed-form optimization solution, and an efficient transformation of huge point clouds. We demonstrate our method through multiple examples that cover a broad range of applications, with a focus on remote sensing applications - namely, the registration of Airborne Laser Scanning (ALS), Mobile Laser Scanning (MLS), and Terrestrial Laser Scanning (TLS) point clouds. The implementation of our algorithms is open source and can be found on GitHub.

ABSTRACT Education is the most important instrument in human life because education can increase human dignity. In addition, education can also be a benchmark for human quality and an example of the progress of a nation. The history of education in Indonesia has evolved from the colonial era to the digital era. These developments have influenced government policies in every era. In the 21st century, the development of education in Indonesia is starting to show progress. This is because it is supported by the rapid growth of information and technology. This research article aims to analyze the educational policies carried out by the government from the colonial era to the digital era to be used as evaluation material at this time so that in the future education in Indonesia is even better. To achieve this goal, this research focuses on the question of how is the transformation of education in Indonesia from the colonial era to the digital era? and what is the paradigm of education in Indonesia when viewed from a historical perspective?. The research method used is the Literature Review method from 27 sources in journal articles, websites, and data reports for 2019-2021. The results of this study found that changes in the Indonesian education system from time to time have a positive influence on the progress of the Indonesian nation. The development of education in Indonesia also has an impact on increasing the Human Development Index (HDI). This shows that the quality of Indonesian society is increasing. Based on the results obtained, it is hoped that it can provide information about the transformation of education in Indonesia from the colonial era to the digital era from a historical perspective. This article is suitable as a reference source for education observers in Indonesia to know the history of education and its policies from the colonial era to the digital era and useful for academics to know the history of education in Indonesia. This research has limitations, namely this research is only limited to the development of education in Indonesia from the colonial era to the digital era and the paradigm of education development in Indonesia from a historical perspective.

We consider mixture experiments in which the proportions of the components must be non-negative and their sum must equal one. Thus, the experimental region for a mixture of components is a simplex. Li and Zhang (2017) made the conjecture that the pseudo component transformation of the lattice points in the simplex has a special property. In this paper, we show that this conjecture is not true in general. Furthermore, we refine this conjecture and prove the refined conjecture.

In this study, we discuss the theoretical studies on the creation of artificial magnetic monopole, and new electromagnetic equations. Employing Lorentz transformation, radial electrostatic fields, and a stationary wave derived from a superconducting loop, we demonstrate the existence of a magnetic monopole whereby the divergence of the magnetic field is not zero. We develop a device wherein a condenser provides electrostatic fields along the radial direction to the superconducting loop and discuss the nodes of the resulting stationary wave along the superconducting loop. We employ the Lorentz transformation with respect to the vector and electrostatic potentials. Then, because the nodes have no three-dimensional vector potential and have zero magnetic field rotation, the conserved energy is converted into new form that is associated with the magnetic field potential to yield the Lorentz transformation. As a result, we derived the relationship between the electric and the magnetic fields. This dependent relationship involves the exchange of the distribution characteristics of the static electric and static magnetic fields, and new electromagnetic equations of both electric and magnetic fields are obtained. We also analyzed the magnetic field from the magnetic monopole whose result assists the theory.

Jakarta belongs to the cities with the highest flood risk in the world. Its flood hazard is driven by land subsidence, soil sealing, changes in river discharge and increasingly sea level rise. As all of these trends are set to continue, Jakarta’s flood hazard is expected to intensify in the future. Designing and implementing risk reduction and adaption measures is therefore of utmost importance. Against the background, the paper draws on a discourse analysis and original empirical household survey data to review and evaluate current adaptation measures and to analyze in how far they describe a path that is transformative from previous risk reduction approaches. The results show that the focus is clearly on engineering solutions, foremost in the Giant Sea Wall project. The project is likely to transform the city’s flood hydrology. However, it cements rather than transforms the current risk management paradigm which gravitates around the goal of controlling flood symptoms, rather than addressing their anthropogenic root causes. The results also show that the planned measures are heavily contested due to concerns about ecological impacts, social costs, distributional justice, public participation and long-term effectiveness. On the outlook, the results therefore suggest that the more the flood hazard will intensify in the future, the deeper a societal debate will be needed about the desired pathway in flood risk reduction and overall development planning – particularly with regards to the accepted level of transformation, such as partial retreat from the most flood-affected areas.

This study aimed to enhance a micro hydroelectric generator system driven by free-flow vortex and to compare efficiency of Propeller and Crossflow turbines. Series of turbines in each type were designed and tested at water-flowrate of 0.02 m3/s. The turbine housing has 1 meter in diameter and 0.5-meter height with 2 meters outlet drain at the bottom. The best efficiency extracted from Crossflow turbines with the same height (0.3 meter) but different in diameter (0.4, 0.5, 0.6, and 0.7 meter) and numbers of blade (12, 18, 24, 30, and 23) was from an 18 blades turbine at 23.01% of efficiency. The best efficiency extracted from Propeller turbines with 5 blades was from a 0.4-meter-high turbine with a diameter of 0.7 meter at 13.92% of efficiency. There were 12 Propeller turbines designed in this study. They were different in height (0.2, 0.3, and 0.4 meter) and, in each height, 0.4, 0.5, 0.6, and 0.7 of diameter was applied. The result revealed that Cross Flow turbine had more efficiency to the system than Propeller turbine (9.09%) at the water-flowrate of 0.02 m3/s

Design criteria for coastal defenses exposed to wave overtopping are usually assessed by mean overtopping discharges and maximum individual overtopping volumes. However, it is often difficult to give clear and precise limits of tolerable overtopping for all kind of layouts. A few studies analyzed the relationship between wave overtopping flows and hazard levels for people on sea dikes, confirming that one single value of admissible mean discharge or individual overtopping volume is not a sufficient indicator of the hazard, but detailed characterization of flow velocities and depths is required. This work presents the results of an experimental campaign aiming at characterizing the flow characteristics associated to maximum individual overtopping volumes for an urbanized stretch of a town along the Catalan coast, where a walking and bike path and a railway run along the coastline are exposed to significant overtopping events every stormy season. The work compares different safety criteria for pedestrian. Results prove that safety of pedestrian on a sea dike can be still guaranteed even for overtopping volumes larger than 1000 l/m. Pedestrian hazard is rather proved to be linked to the combination of overtopping flow velocity and flow depth.

We present a normative methodology, for value-pricing B2B services, using a Nash Equilibrium mechanism. Value is fundamental to any service, yet it has defied a definition. The literature is conspicuously silent on how to define value, but abounds in richly descriptive characterizations. To overcome this deficit, we focus on the financial economics of service-value. We formulate an axiomatic definition and a differential equation that embodies the idea of service-value. We specify a set of value axioms and multidisciplinary postulates that coherently form our service-value constructs. Value-pricing is challenging. It is natural that providers desire a high price and customers want a low price. Realistically, both will agree on a win-win price. To uncover this price, we specify an algorithm to reveal the Nash Equilibrium. Once agreed, it validates providers’ and customers’ commitments, and payment obligations. Service value is cocreated by both provider and customer. For a reciprocal process, its treatment is remarkably asymmetric favoring the customer. We argue that one-sided descriptions of value-in-use and value-proposition are limiting mental models. We propose the additional ideas of value-from-use and value-supposition to strengthen the conceptual symmetry of cocreation. Our work reveals a critical gap in service science, metrology. Metrology, the science of measurements, is absent from service-science. Service-value is silent on the questions of quantities, units, scales, measurement principles and instruments. We argue for a call to action for Service Metrology. We sketch a roadmap of actionable suggestions to get started.

The paper presents a modeling framework to analyze the effect of episodic rainfall supply on groundwater dynamics in the Ionian coastal plain multilayered aquifer. The focus is essentially on the short-term behavior of the shallowest layer, with a specific analysis on episodic rainfall events. In the studied aquifer, groundwater level responds sensitively to rainfall events, highlighting the presence of preferential recharge zones. The hydraulic head peak is a function of groundwater level antecedent to the rainfall event. A kinematic dispersion wave model was used to model infiltration processes via preferential pathways. A one-dimensional and non-linear particle based numerical model was developed. Particles with constant water volume travel according to celerity and hydraulic dispersion to simulate the infiltration rate wave through the vadose zone. The flow rate that reaches the water table represents the input function to determine groundwater level fluctuations along groundwater flow direction and according to the lithological features of the surficial levels of the multilayered aquifer, its storage capacity changes passing from unconfined to confined conditions. The model was validated with high time resolution time series of precipitation and groundwater level coming from Terra Montonata meteo-climatic and groundwater level monitoring station. The developed model represents a basis for evaluating and predicting groundwater discharge of the shallowest layers of the Ionian coastal multilayered aquifer under natural conditions including episodic rainfall.

The theory of special relativity has reexamined and reconstructed the concepts of space and time, which are indispensable for describing physical laws, consequently instigating a major revolution in physics in general. Although the correctness of the special theory of relativity has been con-firmed by many observations and experiments, it is unclear why the "principle of relativity" and the "principle of the constant speed of light," which form the basis of the idea, are valid. Moreo-ver, although special relativity has advanced our understanding of time, our understanding of the fundamental question, "What is time?" is still limited. The theory of special relativity regards space as a four-dimensional construct consisting of one-dimensional time and three-dimensional space. This paper proposes an alternative framework, wherein real space is uniform and isotropic four-dimensional space, and elementary particles are waves that propagate through this four-dimensional space at a constant speed. This new perspective provides evidence to support two of Einstein’s key principles—the "principle of relativity" and the "principle of the constant speed of light." Furthermore, this model clarifies what time is and why time flows at a constant rate from the past to the future.

Heart attacks and strokes are one of the leading causes of death in the world today, and heart attacks caused by clogged arteries that carry blood to the heart muscle are a significant part of these strokes. These are caused by the accumulation of fat particles in the walls of the arteries and the reduction of blood flow through it over a long process. The process of fat penetration in the underlying layers of the Artery wall has been the focus of many researchers, and various researches and Simulations have been done on it, in each of them, the effect of specific parameters has been considered. In the present study, the effect of blood flow rate on the flow pattern in a bifurcate artery with two ducts has been investigated using FLUENT software with Computation fluid dynamic Method. The effect of the angle between the two ducts of the Artery on the flow pattern has been investigated.

In this paper, an analytical form of Rump Function is presented. This seminal function constitutes a fundamental concept of digital signal processing theory and is also involved in many other areas of applied mathematics. In particular, Rump Function is performed in a simple manner as the limit of a sequence of real functions letting ? tend to infinity. This limit is zero for strictly negative values of the real variable ? whereas it coincides with the independent variable ? for strictly positive values of the variable ?. The novelty of this work compared to other research studies concerning analytical expressions of the Ramp Function, is that the proposed formula is not exhibited in terms of miscellaneous special functions, e.g. Gamma Function, Biexponential Function or any other special functions such as Error Function, Hyperbolic Function, Orthogonal polynomials etc. Hence, this formula may be much more practical, flexible and useful in the computational procedures which are inserted into digital signal processing techniques and other engineering practices.

In the bioprinting process, controlling the motion of bioprinters involves a computer-aided design (CAD) model, converting that model into g-code, and transmitting the motion commands to the bioprinters. The g-code file contains information about the motion of the axes and can be generated using various software. However, a challenge arises when using g-code between different bioprinters. Therefore, the objective of this study was to propose a reliable method for analyzing the differences in 3D bioprinting devices by parameterizing a crucial variable for extrusion bioprinting: the E-value. Four bioprinters from three different manufacturers were used to investigate the extrusion behavior when subjected to the same E-value.

The present study took into account the influence of local cuisine in the restaurants awarded Michelin stars in Phuket Old Town, influenced by Chinese cultural diffusion to other cultures contributing to a unique culture in the Malay Peninsula. It sought to investigate components of local gastronomic tourism and perceived value towards the Michelin Guide’s assessment criteria of local cuisine in Phuket Old Town, delving into the relationship between these two factors. In particular, a structural equation model (SEM) was adopted to explore such a relationship, with an exploratory factor analysis (EFA) and a confirmatory factory analysis (CFA) to assess a measurement model of latent variables and accuracy and reliability of the structure. The study was conducted in the context of Phuket Old Town, Phuket Province, Thailand, renowned as a City of Gastronomy. The results demonstrated that the phenomenon of local cuisine in Phuket Old Town embodied the perceived value of local cuisine, origins, history, traditions, rituals, and unique lifestyles; particularly, the components of local gastronomic tourism reflected the significance of food products in the food industry, together with the organization of local cuisine activities and festivals. This finding contributed to an understanding of the reasons behind the perceived value among consumers traveling to this town to gain experiences of local cuisine in the restaurants awarded with Michelin stars. It could serve as a policy for improving food establishments’ quality and standards based on the specified criteria to foster sustainable gastronomic tourism in Thailand.

With the branding development of the international exhibition industry and the increase in the number of mergers and acquisitions of exhibitions, the assessment of the brand value of exhibitions has gradually come into the view of governments, investment and financing institutions and researchers. Compared with the brand value assessment of consumer goods and industrial sectors, the brand value assessment of exhibitions, especially B2B exhibitions, has special characteristics. A model for brand value assessment of B2B exhibitions is proposed, which can not only provide a reference for decision-making on M&A behaviour of exhibitions, but also provide a decision-making tool for government exhibition brand promotion. The aim of this paper is to explore the feasibility of constructing an AHP-based conceptual model for brand value assessment of exhibitions in Shanghai through a hybrid study. The applicability of the conceptual model for exhibition brand value assessment is empirically demonstrated by analysing six steps, including establishing pairwise comparison matrices, calculating the maximum eigenvalues and normalised eigenvectors of each comparison matrix, conducting consistency checks, group decision matrix synthesis and weight allocation of exhibition brand value assessment indicators. On this basis, the three values of the model in practice and theory are explored separately. The research results can provide better brand value assessment and development support for exhibition stakeholders and improve the sustainability of exhibition brands.

Kenyan coffee is ranked among the best in the world and 99% is exported mainly to Germany, Sweden and Belgium, the USA and Saudi Arabia. Kenya produces quality Arabica beans which are generally recognized and upgraded with other relatively lower brands. In 1937, the Kenya Planters Cooperative Union (KPCU) was formed to represent small farmers' interests. In 1944, in the Coffee Board of Kenya (CBA) the law required smallholders to join local growing cooperatives run by government to reduce the power of large estates to control the board. Many reforms in the coffee industry have been initiated. This review explores evolution and existing coffee varieties in Kenya, the coffee value chain and the regions that grow coffee in Kenya. Additionally, the variety agronomics and appearance that encompass; quality potential at different altitudes, yield potential and nematodes susceptibility.

Cervical cancer is a common malignancy in women and has a poor prognosis.More and more studies have shown that autophagy disorder is closely related to the occurrence of tumors. However, the prognostic role of autophagy gene in cervical cancer is still unclear. In this study, we constructed the risk signatures of autophagy related genes to predict the prognosis of cervical cancer. The expression profiles and clinical information of autophagy gene sets were downloaded from the TCGA and GES52903 queues as training sets and validation sets. The cervical normal tissue expression profile data from UCSC XENA website is GTEx data as a supplement to TCGA normal cervical tissue. Univariate COX regression analysis of 17 different autophagy genes with the Consensus approach tumor samples from the TCGA is divided into six subtypes, and the clinical traits in the six subtypes have different distribution, with further then absolute shrinkage and selection operator (LASSO) and multiariable COX regression method finally got seven autophagy genetic risk model is constructed, in the training set, the survival rate of high risk group is lower than the low risk group (p < 0.0001), the validation set,The AUC area of the receiver operating characteristic (ROC) curve, the training set is 0.894, and the verification set is 0.736. We find that the high and low risk score is closely related to the TMN stage (All P is less than 0.05).The nomogram shows that the risk score combined with other indicators such as age, G,T,M, and N better predicts 1-year, 2-year, 3-year survival, and the DCA curve shows that the risk model combined with other indicators produces better clinical efficacy.Then immune cells in 28 in the enrichment score, there were statistically significant differences, high and low risk most GSEA enrichment analysis, the main enrichment in G2 / M checkpoint high-risk score, Genes defining epithelial and mesenchymal transition, raised in response to the low oxygen levels (hypoxia) gene, gene is important to the mitotic spindle assembly, these are closely related with the occurrence of tumor . In conclusion, our constructed autophagy risk signature may be a prognostic tool for cervical cancer.

The article suggests a Value Proposition (VP) framework that enables the analysis of the beneficial impact of Artificial Intelligence (AI) resources and capabilities on specific VP development activities. To develop such a framework, we examined existing management research publications to identify and extract assertions that could be used as a source of actionable insights for new growth-oriented companies. The extracted assertions were assembled into a corpus of texts that were subjected to topic modelling analysis – a machine learning approach to natural language processing that is used to identify latent themes in large corpora of text documents. The topic modeling resulted in the identification of seven topics. Each topic is defined by a set of most frequent words co-occurring in a distinctive subset of texts that could be interpreted in terms of activities constituting the core elements of the VP framework. We then examined each activity in terms of its potential to be enhanced by employing AI resources and capabilities. The interpretation of the topic modeling results led to the identification of seven topics: 1) Value created; 2) Stakeholder value propositions; 3) Foreign market entry; 4) Customer base; 5) Continuous improvement; 6) cross-border operations; and 7) Company image. The uniqueness of the adopted topic modeling approach consists in the quality of the assertions and the interpretation of the seven topics as an activity framework, i.e. in its capacity to generate actionable insights for practitioners. The additional analysis suggests that there is a potential for AI to enhance emerging the four core elements of the VP framework: Value created, Stakeholder value propositions, Foreign market entry, and Customer base. More importantly, we found that the greatest number of assertions related to activities that could be enhanced by AI are part of the Customer base topic, i.e., the topic that is most directly related to the growth potential of the companies. In addition, the VP framework suggests that a company’s customer base growth is continuously enhanced through a positive loop enabled by activities focused on the Continuous improvement of the activities and the amount of Value created, the alignment of Stakeholder value propositions, and companies’ Foreign market entry. Thus, Foreign market entry appears as a factor that helps in understanding the beneficial impact of AI on the VP development of new growth-oriented companies.

(1) Background: AI technology has been deeply applied to online shopping platform to provide more accurate and personalized services for consumers. It is of great significance to study the different functional experience of AI for consumers to improve the current application status of AI technology.(2)Method: Based on the "S-O-R" model, this study divided the AI technology expe-rienced by the consumers of online shopping platform into accuracy, insight and interaction experience. Takes the perceived value as the mediating variable from the prospect of perceived utility value and perceived hedonic value. This article use empirical research method to analyze the effect of three dimensions of online shopping AI experience to research the internal influence mechanism of consumers purchase intention. (3) Results:① The accuracy, insight and interaction experience of AI marketing technology have a significant positive impact on consumers' per-ceived utility value and hedonic value respectively; ②Both of the perceived utility value and perceived hedonic value obtained by AI technology experience can promote the formation of consumers' purchase intention; ③ The perceived hedonic value was better than perceived utility value to promote the consumers' purchase intention; ④The results of multi group analysis show that some younger and less experiences consumers groups prefer the pleasure experience such as shopping desire stimulation, shopping process relaxation and pleasure that AI marketing brought. However, utilitarian value cannot promote this kind of consumers' purchase intention. (4) Con-clusions: Perceived utility value and perceived hedonic value can be the intermediary between AI technology and consumers' purchase intention.

Many of engineering’s problems are about to optimise equations, functions and process models equations which appear on common or even complex science’s cases. Most applied optimisation methods nowadays can only be used on particular cases, so the main objective of this article is to define a computational method that can optimise or even find target values for specified objective functions and variables, by just using computer effort. Chemical plants involve many differential equations and they can be optimised with more facility now. On this paper, there are shown as example, an optimisation for a chemical reactor, which is found the optimal temperature and volumetric flow rate of feed, for the given objective function being the composition of the desired product. Named Domain’s Sweep, it is an algorithm that evaluate given(s) mathematical function(s) and/or equation(s) by varying your(s) independent variable(s) through loops with a given step size and solving it after closing the degrees of freedom, and finally, with some condition statements, store all the optimum values of given or created objective functions with its respective independent variables. In another words, the user create an objective function and this method find the function’s maximum, minimum or a certain chosen target value, even if it does not have an inflection point in the given search interval of the independent variables.

High-resolution wave measurements at intermediate water depth are required to improve coastal impact modeling. Specifically, such data sets are desired to calibrate and validate models, and broaden the insight on the boundary conditions that force models. Here, we present a wave data set collected in the North Sea at three stations in intermediate water depth (6-14~m) during the 2021/2022 storm season as part of the RealDune/REFLEX experiments. Continuous measurements of synchronized surface elevation, velocity and pressure were recorded at 2-4~Hz by Acoustic Doppler Profilers and an Acoustic Doppler Velocimeter for a 5~month duration. Time series were quality-controlled, directional-frequency energy spectra were calculated, and common bulk parameters were derived. Measured wave conditions vary from calm to energetic with 0.1-5.0~m sea-swell wave height, 5-16~s mean wave period and W-NNW direction. Nine storms, i.e. wave height beyond 2.5~m for at least six hours, were recorded including the triple storms Dudley, Eunice and Franklin. This unique data set can be used to investigate wave transformation, wave nonlinearity and wave directionality for higher and lower frequencies (e.g. sea-swell and infragravity waves) to compare with theoretical and empirical descriptions. Furthermore, the data can serve to force, calibrate and validate models during storm conditions.

A rapid synthesis of chiral sulfoxide-functionalized meta-terphenyl derivatives by a 2,5-[C4+C2] ring transformation reaction of pyrylium salts with in-situ generated enantio-merically pure .alpha.-sulfinylacetaldehydes is described. This synthetic method demonstrates for the first time the use of .alpha.-sulfinylacetaldehydes in a reaction sequence initiated by nu-cleophilic attack of pyrylium salts by .alpha.-sulfinylcarbanions to generate chiral aromatic systems. The method presented shows broad applicability starting with various methyl sulfoxides and a number of functionalized pyrylium salts, furnishing meta-terphenyls with complex substitution patterns from readily accessible starting compounds.

The integration of automation and process optimization within the context of AI-powered digital transformation has emerged as a pivotal strategy for organizations aiming to enhance efficiency, foster innovation, and competitiveness. This paper is devoted to present innovative contribution by providing a comprehensive structured roadmap that outlines the foundational principles necessary for the successful integration of automation and optimizing processes within the con-text of emerging AI technologies. The paper introduce a cohesive framework consisting of es-sential key pillars: Data-Driven Insights, Seamless Automation, Adaptive Learning and Contin-uous Improvement, Human-Centric Collaboration, Ethical and Responsible AI, Strategic Align-ment, Scalability, and Innovation. These pillars function as guiding principles to navigate the in-tricate landscape of automation-driven initiatives within AI-powered digital transformation. By embracing these pillars, organizations can embark on a transformative journey that maximizes the potential of automation, fosters innovation, and positions them as leaders in the ever-evolving landscape of AI-driven business operations.

Image encryption based on chaotic maps is an important way to ensure the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed by employing a compound chaotic map and random cyclic shift. Firstly, an improved Hybrid chaotic system is designed by coupling Logistic, ICMIC, Tent, and Chebyshev maps (HLITC). Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and Kolmogorov entropy illustrate the new hybrid chaotic map has better chaotic performance. Then the proposed HLITC chaotic system is used to develop a new chaotic image encryption scheme with the double cyclic shift. The improved HLITC chaotic system is performed to generate key sequences used in the image scrambling and diffusion stage. The spiral transformation controlled by chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments of statistical analysis, key sensitivity, and keyspace analysis are conducted. Experimental results show the proposed encryption scheme has good robustness against brute force attacks, statistical attacks, and differential attacks, and is more effective than many existing chaotic image encryption algorithms.

At present, countries around the world adopt digital strategy, so that enterprises apply digital technology, digital supply chain, blockchain, and a series of digital measures to enhance their competitiveness. By analyzing the relationship between digital transformation of manufacturing export enterprises, and their business performance and export performance, this paper focused on the current situation and existing problems of digital transformation of manufacturing export enterprises in China. Based on the Resource Based View theory and Trade theory, the impact of digital transformation of enterprises performance, proposing hypotheses, and building regression models were explored. With the samples of 1007 listed companies in Shanghai and Shenzhen Stock markets from 2012 to 2019, the regression analysis, intermediate effect test, robustness test, stage lag, and heterogeneity analysis were conducted. The results shew that: (1) Listed manufacturing export enterprises carried out digital transformation, which had a significantly positive effect on enterprise performance; (2) It was found that digital transformation could improve enterprise performance by reducing costs, improving R&amp;D intensity and improving human resources etc. (3) According to the fractal analysis, non-state-owned enterprises had more positive effects on enterprise performance, and digital transformation of manufacturing export enterprises in developed areas had a more significant impact on enterprise performance. Finally, according to the empirical results, relevant suggestions for digital transformation were provided.

This study investigates the multifaceted aspects of 21st century teaching and identifies gaps in current educational practices. The researcher employed a qualitative approach, utilizing interviews, observations, and document analysis. Grounded in a theoretical framework emphasizing student-centered pedagogy, technology integration, and innovative instructional strategies, the study involved a diverse sample of 30 participants, including teachers, students, and administrators. Rigorous measures were implemented to ensure validity and reliability, such as researcher triangulation and member checking. The findings revealed significant gaps in areas such as student engagement, digital literacy, and pedagogical innovation. These findings are discussed in relation to existing literature, highlighting the implications for educational practice and the urgent need for educational transformation. The study's limitations include the small sample size and its focus on a specific educational context. Future research should explore the identified gaps using different methodologies and extend the investigation to other educational settings. The study contributes to the growing body of knowledge on 21st century teaching, providing valuable insights for educators, policymakers, and researchers aiming to promote effective and transformative teaching practices in the modern era.

The search for growth and sustainability in any organization largely depends on its ability to carry out digital transformation and agility processes. These processes are essential to adapt to an increasingly changing and competitive business environment, allowing companies to be more efficient and effective in creating an unbreakable bond with their customers. This manuscript addresses the importance of detecting and eliminating anti-patterns in organizational culture for a successful digital and agile transformation. During the early stages of the transformation process, prejudices and paradigms rooted in the organization can become an obstacle to change. The goal of this writing is to offer a practical guide for leaders and teams in organizations seeking successful cultural transformation. Effective strategies are proposed to overcome the challenges faced by organizations during this early stage. In summary, the key steps to be followed in the initial stages of digital transformation with agility are described, including the importance of establishing strong leadership, defining a clear vision and scope of the transformational process, among others. A set of recommendations will be provided to overcome recurring anti-patterns, such as lack of stakeholder participation and commitment, lack of proper planning, and confusion of roles and responsibilities.

First came the digital banks without offices, and then the “fintech” companies that combined technology and finance to achieve greater efficiency and new business models. Later was the turn of transport and logistics, understood as the sector whose economic activities derived from the transport of people and goods, while on the one hand, it has had a new spring thanks to factors such as online sales. Then, perhaps catalyzed by the pandemic scenario, the turn has reached education, where years ago was only a complement of traditional education, now is a central part with multiple modern methodologies. Numerous studies exist about using or implementing these e-learning procedures, but technical analysis is barely found in references. This work aims to analyze the digital transformation of the main sectors of our society, including finances, transport, and education, together with several examples of how technology was helping to fight the pandemic scenario.

Digital transformation of companies is often referred to as a future track and a strategic path towards ensuring the survival and sustainability of companies. In this paper, we aim to outline this transformation process in Tunisian companies and identify its driving factors and finally explain its key success factors. To this end, we examine a sample of 70 companies operating in all economic sectors. The results indicate that such a digital strategy has a significant and a positive effect on the success of digital transformation of companies. Leadership has an effect at a low level of digital maturity. On the other hand, corporate culture does not have a significant effect on digital transformation. These results contribute to explaining this emerging phenomenon by focusing on the driving factors as well as the factors that contribute to its success.

Brain tumors are abnormal cells growth in the brain tissues that can be cancerous, or not. In any case, they could be a very aggressive disease that should be detected as early as possible. Usually, magnetic resonance imaging (MRI) is the main tool commonly adopted by neurologists and radiologists to identify and classify any possible anomalies present in the brain anatomy. In the present work, an automatic unsupervised method called Z2-$\gamma$, based on the use of adaptive finite-elements and suitable pre-processing and post-processing techniques, is introduced. In particular, the proposed methodology is able to automatically classify whether a given MR image represents a healthy or a diseased brain and in this latter case, is able to locate the tumor area.

The new SARS-CoV-2 coronavirus has brought with it an increase in the use of digital platforms and an exponential increase in the number of scientific papers worldwide. The purpose of this study is to show a global overview of the digital transformation from 1975 to the present (2021). The main collection of the Web of Science database was used to retrieve global scientific production on digital transformation. Bibliometric indicators of production, visibility, impact, and collaboration were analyzed to assess research progress on the topic. The results show that digital transformation is a construct of recent development, increasingly relevant and transdisciplinary, with a clear growth after the declaration of the global COVID-19 pandemic.

Seismic imaging is the main technology used for subsurface hydrocarbon prospection. It~provides an image of the subsurface using the same principles as ultrasound medical imaging. As for any data acquired through hydrophones (pressure sensors) and/or geophones (velocity/acceleration sensors), the raw seismic data are heavily contaminated with noise and unwanted reflections that need to be removed before further processing. Therefore, the noise attenuation is done at an early stage and often while acquiring the data. Quality control (QC) is mandatory to give confidence in the denoising process and to ensure that a costly data re-acquisition is not needed. QC is done manually by humans and comprises a major portion of the cost of a typical seismic processing project. It is therefore advantageous to automate this process to improve cost and efficiency. Here, we propose a supervised learning approach to build an automatic QC system. The~QC system is an attribute-based classifier that is trained to classify three types of filtering (mild = under filtering, noise remaining in the data; optimal = good filtering; harsh = over filtering, the signal is distorted). The attributes are computed from the data and represent geophysical and statistical measures of the quality of the filtering. The system is tested on a full-scale survey (9000 km²) to QC the results of the swell noise attenuation process in marine seismic data.

Seismic imaging is the main technology used for subsurface hydrocarbon prospection. It provides an image of the subsurface using the same principles as ultrasound medical imaging. It is based on emitting a sound (pressure) wave through the subsurface and recording the reflected echoes using hydrophones (pressure sensors) and/or geophones (velocity/acceleration sensors). Contrary to medical imaging, which is done in real time, subsurface seismic imaging is an offline process that involves a huge volume of data and needs considerable computing power. The raw seismic data are heavily contaminated with noise and unwanted reflections that need to be removed before further processing. Therefore, the noise attenuation is done at an early stage and often while acquiring the data. Quality control (QC) is mandatory to give confidence in the denoising process and to ensure that a costly data re-acquisition is not needed. QC is done manually by humans and comprises a major portion of the cost of a typical seismic processing project. It is therefore advantageous to automate this process to improve cost and efficiency. Here, we propose a supervised learning approach to build an automatic QC system. The QC system is an attribute-based classifier that is trained to classify three types of filtering (mild = underfiltering, noise remaining in the data; optimal = good filtering; harsh = overfiltering, the signal is distorted). The attributes are computed from the data and represent geophysical and statistical measures of the quality of the filtering. The system is tested on a full-scale survey (9000 km2) to QC the results of the swell noise attenuation process in marine seismic data. The results are encouraging and helped identify localized issues that were difficult for a human to spot.

In personalized healthcare, an ecosystem for the manipulation of reliable and safe private data should be orchestrated. This paper describes a first approach for the generation of fake electrocardiograms (ECGs) based on Generative Adversarial Networks (GANs) with the objective of anonymizing users’ information for privacy issues. This is intended to create valuable data that can be used both, in educational and research areas, while avoiding the risk of a sensitive data leakage. As GANs are mainly exploited on images and video frames, we are proposing general raw data processing after transformation into an image, so it can be managed through a GAN, then decoded back to the original data domain. The feasibility of our transformation and processing hypothesis is primarily demonstrated. Next, from the proposed procedure, main drawbacks for each step in the procedure are addressed for the particular case of ECGs. Hence, a novel research pathway on health data anonymization using GANs is opened and further straightforward developments are expected.

The study sought to gauge the impact of COVID-19 pandemic in unleashing digital transformation in the education sector in South Africa. In order to gauge the impact, the study tracked the rate at which the 4IR tools were used by various institutions during the COVID-19 lockdown. Data were obtained from secondary sources, mainly newspaper articles, magazines and peer-reviewed journals. The findings are that, in South Africa, during the lockdown, a variety of 4IR tools were unleashed from primary education to higher and tertiary education where educational activities switched to remote learning (online learning). These observations point to the fact that South Africa generally has, some pockets of excellence to drive the education sector into the 4IR, which has the potential to increase access. Access to education, particularly at a higher education level, has always been a challenge due to a limited number of spaces available. Much as this pandemic has brought with it massive human suffering across the globe, there is an opportunity to assess successes and failures of deployed technologies, costs associated with them, and scaling these technologies to improve access.

In this research, atomistic molecular dynamics simulations are combined with mesoscopic phase-field computational methods in order to investigate phase-transformation in polycrystalline Aluminum microstructure. In fact, microstructural computational modeling of engineering materials could help to optimize their mechanical properties for industrial applications (e.g. directional solidification for turbine blades). As a result, a multiscale modeling approach is developed to find a relation between manufacturing variables (e.g. temperature) and microstructural properties of crystalline materials (e.g. grain size), which could be used to develop an advanced manufacturing process for sensitive applications. The results show that atomistic modeling of grain growth could be used as a first-principle approach in order to study phase transformation's kinetics, which could capture morphology of polycrystalline materials more accurately. On the other hand, phase-field mesoscopic approach needs less computational efforts, but still it relies on semi-empirical data to capture accurate phase transformation regimes, which makes this approach suitable for rapid examining of new manufacturing conditions as well as its effects on microstructural properties of polycrystalline materials.