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The research describes the procedure for accounting for the items of the consolidated cash flow statement as a consolidated financial statement. The authors also discuss the operating, investing, and financing activities of the consolidated cash flow statement and various aspects of the items included in it. Moreover, the authors consider the direct and indirect methods and exchange rate differences in foreign exchange funds (i.e., spot rate, reporting rate, various aspects of average rates, and money). The accounting and compilation of unrelated transactions in the financial statement are given. The authors also consider the purpose of the consolidated cash flow statement, the requirements for presenting the statement of cash flows, the distinction between cash equivalents and other financial assets, and the purpose of the consolidated cash flow statement, which is reliable for foreign investors and prospective investors and approximates the financial statements of large companies. Foreign currency funds, interest and dividend cash flows, profit tax cash flows, and noncash transactions are considered when drawing up a statement of operations using direct and indirect methods.

This study explores the concept of hydraulic flushing gate with an automated control system as a flow control structure of the urban storm water system. The research team has implemented a flush gate with the automated control system to the flow of the water in a drainage channel. The flow control structure was used to determine the effectiveness of such design by applying the concept of virtually on a real-world drainage system at Jalan Astana, Kuching. Computer representations of the existing drainage system and flow control structure were built using EPA SWMM 5.0 model. The series of flow control structure was proven to hold the runoff from 10-year storm. The modelling result shows that there is 25.9% of flow reduction at outlet node. As a modification of the existing drainage system in the urban area involves high construction cost, by installing a flow control structure in the drainage system is an innovative way to control the flow of the water.

The scientific and professional accounting and auditing community has been widely discussing the transformation of the information environment for presenting the results of business conduct by commercial entities in the field of sustainable development in three vectors: environmental impact assessment, impact assessment for compliance with human rights and solving socially important tasks, and assessment of corporate governance efficiency. Cash flows are an important object of financial accounting in companies. Cash flows combine indicators used to make key decisions and reflect the effectiveness of compliance with corporate policies and implementation of sustainable development programs. Today's external environment is predetermined by the need to make financial decisions in real time. Thus, it is necessary to understand what cash flow the company has and what type of activity will generate cash flows in the future. Therefore, companies need to be guided by national and international accounting and financial reporting standards in terms of analytical disclosure of cash flow information in the sustainable development context. The presented research considers the conceptual apparatus, historical aspects of the accounting category “cash flows,” and contemporary approaches to forming cash flow reporting in accordance with certain provisions of international standards. The authors provide recommendations on developing cash flow accounting and reporting in the context of new requirements of international standards. The presented research discloses practice-oriented recommendations on forming the company's cash flow statements, as well as methodological aspects of analyzing financial statements on cash flows as an additional information environment for making decisions on the main and additional financing of various business areas.

This study proposes a framework that demonstrates how the perceived value of augmented reality (AR) shopping influences the formation of psychological ownership of product and technology. The mediating role of flow experience and the moderating role of perceived control are identified.

An online survey study recruiting 480 participants who experienced AR shopping was conducted to test the hypotheses.

Functional value is negatively related to psychological ownership of product and technology whereas emotional value shows opposite effects. Flow experience mediates the relationships between functional/emotional value and psychological ownership of product and technology. Perceived control moderates the relationship between emotional value and flow experience, as well as the relationship between functional/emotional value and psychological ownership of product and technology.

The findings suggest the importance of AR’s functional and emotional values in developing psychological ownership of product and technology. To mitigate the negative effect of functional value, AR designers should focus on creating emotionally engaging apps that induce a flow experience, thereby enhancing psychological ownership. Furthermore, AR apps should be designed to empower users with a sense of control in the AR experience.

This research contributes to the AR and psychological ownership literature. It introduces a model that can explain both the formation of psychological ownership of product and psychological ownership of technology, thereby expanding the current understanding. By adding perceived values as antecedents of psychological ownership, it enriches the psychological ownership literature. Moreover, it enhances the flow experience literature by demonstrating the role of flow experience in the formation of psychological ownership of product and technology.

This study aims to explore entropy evaluation in the bi-directional flow of Casson hybrid nanofluids within a stagnated domain, a topic of significant importance for optimizing thermal systems. The aim is to investigate the behavior of unsteady, magnetized and laminar flow using a parametric model based on the thermo-physical properties of alumina and copper nanoparticles.

The research uses boundary layer approximations and the Keller-box method to solve the derived ordinary differential equations, ensuring numerical accuracy through convergence and stability analysis. A comparison benchmark has been used to authenticate the accuracy of the numerical outcomes.

Results indicate that increasing the Casson fluid parameter (ranging from 0.1 to 1.0) reduces velocity, the Bejan number decreases with higher bidirectional flow parameter (ranging from 0.1 to 0.9) and the Nusselt number increases with higher nanoparticle concentrations (ranging from 1% to 4%).

This study has limitations, including the assumption of laminar flow and the neglect of possible turbulent effects, which could be significant in practical applications.

The findings offer insights for optimizing thermal management systems, particularly in industries where precise control of heat transfer is crucial. The Keller-box simulation method proves to be effective in accurately predicting the behavior of such complex systems, and the entropy evaluation aids in assessing thermodynamic irreversibilities, which can enhance the efficiency of engineering designs.

These findings provide valuable insights into the thermal management of hybrid nanofluid systems, marking a novel contribution to the field.

This study aims to focuse on the flow behavior of a specific nanofluid composed of blood-based iron oxide nanoparticles, combined with motile gyrotactic microorganisms, in a ciliated channel with electroosmosis.

This study applies a powerful mathematical model to examine the combined impacts of bio convection and electrokinetic forces on nanofluid flow. The presence of cilia, which are described as wave-like motions on the channel walls, promotes fluid propulsion, which improves mixing and mass transport. The velocity and dispersion of nanoparticles and microbes are modified by the inclusion of electroosmosis, which is stimulated by an applied electric field. This adds a significant level of complexity.

To ascertain their impact on flow characteristics, important factors such as bio convection Rayleigh number, Grashoff number, Peclet number and Lewis number are varied. The results demonstrate that while the gyrotactic activity of microorganisms contributes to the stability and homogeneity of the nanofluid distribution, electroosmotic forces significantly enhance fluid mixing and nanoparticle dispersion. This thorough study clarifies how to take advantage of electroosmosis and bio convection in ciliated micro channels to optimize nanofluid-based biomedical applications, such as targeted drug administration and improved diagnostic processes.

First paper discussed “Numerical Computation of Cilia Transport of Prandtl Nanofluid (Blood-Fe₃O₄) Enhancing Convective Heat Transfer along Micro Organisms under Electroosmotic effects in Wavy Capillaries”.

The purpose of this study was to leverage agency theory to examine the impact of board attributes on cash flow management in Ghana’s financial institutions.

Data for the study was collected from the annual published financial statements of selected financial institutions, which were obtained from their respective websites. The sampling technique used was purposive, resulting in the selection of 15 financial institutions in Ghana, of which 10 were listed on the Ghana Stock Exchange and 5 were non-listed. The study covered a period of 10 years, ranging from 2011 to 2020. The two-step generalized method of moments estimation was used to determine the relationship between the board attributes and cash flow management.

The study found that board size had a positive and significant influence on net cash flow from operating, investing and financing activities. The study also discovered that the proportion of nonexecutive directors had a positive and significant influence on net cash flow from operating, investing and financing activities. In addition, it was revealed that the proportion of female directors on the board exhibited a positive and significant influence on net cash flow from operating activities but a negative and significant influence on net cash flow from investing and financing activities.

The study recommends increasing female representation on corporate boards to 25%, as women bring valuable skills, knowledge and experience that positively impact the financial institutions’ cash flows.

This study focused on the impact of board attributes on cash flow management within Ghana. It explored how corporate governance affects strategic decisions related to cash flow management, contributing original insights to this field of research.

The purpose of this study is to optimize and improve conventional welding using EMF assisted technology. Current industrial production has put forward higher requirements for welding technology, so the optimization and improvement of traditional welding methods become urgent needs.

External magnetic field assisted welding is an emerging technology in recent years, acting in a non-contact manner on the welding. The action of electromagnetic forces on the arc plasma leads to significant changes in the arc behavior, which affects the droplet transfer and molten pool formation and ultimately improve the weld seam formation and joint quality.

In this paper, different types of external magnetic fields are analyzed and summarized, which mainly include external transverse magnetic field, external longitudinal magnetic field and external cusp magnetic field. The research progress of welding behavior under the effect of external magnetic field is described, including the effect of external magnetic field on arc morphology, droplet transfer and weld seam formation law.

However, due to the extremely complex physical processes under the action of the external magnetic field, the mechanism of physical fields such as heat, force and electromagnetism in the welding has not been thoroughly analyzed, in-depth theoretical and numerical studies become urgent.

Wall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall region. However, its use is limited in flows that have high non-equilibrium effects like separation or transition. This study aims to present a novel methodology of using high-fidelity data and machine learning (ML) techniques to capture these non-equilibrium effects.

A precursor to this methodology has already been tested in Radhakrishnan et al. (2021) for equilibrium flows using LES of channel flow data. In the current methodology, the high-fidelity data chosen for training includes direct numerical simulation of a double diffuser that has strong non-equilibrium flow regions, and LES of a channel flow. The ultimate purpose of the model is to distinguish between equilibrium and non-equilibrium regions, and to provide the appropriate wall shear stress. The ML system used for this study is gradient-boosted regression trees.

The authors show that the model can be trained to make accurate predictions for both equilibrium and non-equilibrium boundary layers. In example, the authors find that the model is very effective for corner flows and flows that involve relaminarization, while performing rather ineffectively at recirculation regions.

Data from relaminarization regions help the model to better understand such phenomenon and to provide an appropriate boundary condition based on that. This motivates the authors to continue the research in this direction by adding more non-equilibrium phenomena to the training data to capture recirculation as well.

This study aims to introduce a novel machine learning feature vector (MLFV) method to bring machine learning to overcome the time-consuming computational fluid dynamics (CFD) simulations for rapidly predicting turbulent flow characteristics with acceptable accuracy.

In this method, CFD snapshots are encoded in a tensor as the input training data. Then, the MLFV learns the relationship between data with a rod filter, which is named feature vector, to learn features by defining functions on it. To demonstrate the accuracy of the MLFV, this method is used to predict the velocity, temperature and turbulent kinetic energy fields of turbulent flow passing over an innovative nature-inspired Dolphin turbulator based on only ten CFD data.

The results indicate that MLFV and CFD contours alongside scatter plots have a good agreement between predicted and solved data with R² ≃ 1. Also, the error percentage contours and histograms reveal the high precisions of predictions with MAPE = 7.90E-02, 1.45E-02, 7.32E-02 and NRMSE = 1.30E-04, 1.61E-03, 4.54E-05 for prediction velocity, temperature, turbulent kinetic energy fields at Re = 20,000, respectively.

The method can have state-of-the-art applications in a wide range of CFD simulations with the ability to train based on small data, which is practical and logical regarding the number of required tests.

The paper introduces a novel, innovative and super-fast method named MLFV to address the time-consuming challenges associated with the traditional CFD approach to predict the physics of turbulent heat and fluid flow in real time with the superiority of training based on small data with acceptable accuracy.