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• Accounting methods of agricultural methane are summarized. • Influencing factors of emission sources from agricultural sources were analyzed. • Mitigation strategies based on accounting and actual situation are proposed. Methane is one of the major greenhouse gases (GHGs) and agriculture is recognized as its primary emitter. Methane accounting is a prerequisite for developing effective agriculture mitigation strategies. In this review, methane accounting methods and research status for various agricultural emission source including rice fields, animal enteric fermentation and livestock and poultry manure management were overview, and the influencing factors of each emission source were analyzed and discussed. At the same time, it analyzes the different research efforts involving agricultural methane accounting and makes recommendations based on the actual situation. Finally, mitigation strategies based on accounting results and actual situation are proposed. This review aims to provide basic data and reference for agriculture-oriented countries and regions to actively participate in climate action and carry out effective methane emission mitigation. [Display omitted] [ABSTRACT FROM AUTHOR]

We use recently developed difference-in-differences methodologies and a panel of US states over the period 1960–2015 to examine how bank branching deregulation impacted state-level income inequality. Existing research relying on traditional two-way fixed effects estimates and event studies provide mixed results. However, these results potentially suffer from biases due to treatment effect heterogeneity and the failure to account for multiple related treatments. Using bias-corrected difference-in-differences procedures and properly accounting for the timing of treatment, we find evidence that the combined effect of intrastate and interstate banking deregulation increased the income share of the top 10%, 5%, and 1% of income earners, respectively. Conversely, we find no evidence that intrastate branching deregulation in isolation impacted income inequality. [ABSTRACT FROM AUTHOR]

Grey rhino risks are high-impact but seemingly low-probability risks that get shuttled to the sidelines, often due to a misguided hope that the risk will not materialise in the near term, so mitigation planning can be delayed or dismissed. As the author has argued previously in this journal, it is time to change the way we look at risks in order to reassess and re-prioritise our grey rhino risks. We must stop shrugging our shoulders and treating grey rhinos as 'unforeseeable' and therefore absolving ourselves from doing anything about them. The author's previous paper, "Rhinos and risk assessments: Adjusting risk assessment methodologies to account for "unforeseeable' events"'1 provided a methodology for pulling grey rhinos into the spotlight, so that we can see them more easily and recognise that their high-impact status requires both acknowledging and planning for. The present paper takes the methodology a step further — demonstrating how to plan for grey rhino risks that have been identified. Rather than continuing to tag grey rhinos as 'unforeseeable', we can and must prepare our organisations for them. [ABSTRACT FROM AUTHOR]

Cable force estimation of the suspenders is of tremendous significance for the safety and condition evaluation of arch bridges. The modern suspender cable structure widely used nowadays calls for an efficient and robust estimation method accounting for the cable bending stiffness, complex boundary conditions, intermediate dampers, and variable suspender segments. To estimate the tension force in arch bridge suspenders, this paper proposes an exact analytical method that can simultaneously consider the aforementioned factors for the first time. Based on a generalized suspender cable model including all these factors, the transcendental equation for cable force calculation was obtained from the determinant of a 4 × 4 matrix derived using the transfer matrix method. Due to the low dimensionality of the matrix, the transcendental equation size is largely reduced. This allows rapid cable force calculation without requiring complicated numerical iteration algorithms. A dimensionless parametric analysis was conducted to investigate the impact of various factors on the frequency parameter of the suspenders. Subsequently, the efficacy of the proposed method was verified, and an extensive estimation error analysis was performed using finite elements. Moreover, the method was applied to four real-world bridges with measured vibration frequency available. The results showed that the method can accurately estimate the tension force in suspenders with flexural rigidity, arbitrary boundary conditions, and any number of intermediate dampers and nonuniform segments. The proposed method can also be used for suspender cable force estimation of other cable-supported bridges, such as suspension bridges. [ABSTRACT FROM AUTHOR]

Accurate and continuous estimation of surface albedo is vital for assessing and understanding land–surface–atmosphere interactions. We developed a method for estimating instantaneous all-sky at-surface shortwave upwelling radiance and albedo over the Tibetan Plateau. The method accounts for the complex interplay of topography and atmospheric interactions and aims to mitigate the occurrence of data gaps. Employing an RTLSR-kernel-driven model, we retrieved surface shortwave albedo with a 1 km resolution, incorporating direct, isotropic diffuse; circumsolar diffuse; and surrounding terrain irradiance into the all-sky solar surface irradiance. The at-surface upwelling radiance and surface shortwave albedo estimates were in satisfactory agreement with ground observations at four stations in the Tibetan Plateau, with RMSE values of 56.5 W/m2 and 0.0422, 67.6 W/m2 and 0.0545, 98.6 W/m2 and 0.0992, and 78.0 98.6 W/m2 and 0.639. This comparison indicated an improved accuracy of at-surface upwelling radiance and surface albedo and significantly reduced data gaps. Valid observations increased substantially in comparison to the MCD43A2 data product, with the new method achieving an increase ranging from 40% to 200% at the four stations. Our study demonstrates that by integrating terrain, cloud properties, and radiative transfer modeling, the accuracy and completeness of retrieved surface albedo and radiance in complex terrains can be effectively improved. [ABSTRACT FROM AUTHOR]

One of the most effective and extensively used recommendation technique is collaborative filtering. Based on related users or items, collaborative filtering creates recommendations for the users. Similarity measures play a crucial role in Collaborative Filtering Recommender System. One useful similarity measure for a cold-start situation is the Proximity-Impact-Popularity (PIP) measure. The PIP measure is, nevertheless, subject to several limitations as it penalises users' multiple times throughout similarity computation in addition to ignoring their global rating behaviour. When a user rates the items, their overall rating behavior—whether they are lenient or strict—is referred to as global rating behaviour. In this study, we introduce an improved similarity metric to calculate similarity more accurately and generate high-quality recommendations. Our method takes into account both the user's rating behaviour and the percentage of co-rated items among users. Additionally, we have considered the computation complexity of the suggested work. In addition, to exhibit the performance of the proposed measure, empirical analysis has been done on real datasets. The results of the experiments performed on the dataset show that the suggested work takes precedence over the current similarity metrics. In comparison to state-of-the-art measurements, the suggested work exhibits improvements in MAE of 1.73%, RMSE of 4.01%, and F measure of 1.47% on an average. [ABSTRACT FROM AUTHOR]

Assessment practices are, among other things, concerned with issues of fairness and appropriate score interpretation, in particular when making claims about subgroup differences in performance are of interest. In order to make such claims, a psychometric concept of measurement invariance or differential item functioning (DIF) ought to be considered and met. Over the last decades, researchers have proposed and developed a plethora of methods aimed at detecting DIF. However, DIF detection methods that allow multilevel data structures to be modeled are limited and understudied. In the current study, we evaluated the performance of four methods, including the model-based multilevel Wald and the score-based multilevel Mantel-Haenszel (MH), and two well-established single-level methods, the model-based single-level Lord and the score-based single-level MH. We conducted a simulation study that mimics real-world scenarios. Our results suggested that when data were generated as multilevel, mixed results regarding performances were observed, and not one method consistently outperformed the others. Single-level Lord and multilevel Wald yielded best control of the Type I error rates, in particular in conditions when latent means were generated as equal for the two groups. Power rates were low across all four methods in conditions with small number of between- and within-level units and when small DIF was modeled. However, in those conditions, single-level MH and multilevel MH yielded higher power rates than either single-level Lord or multilevel Wald. This suggests that current practices in detecting DIF should strongly consider adopting one of the more recent methods only in certain contexts as the tradeoff between power and complexity of the method may not warrant a blanket recommendation in favor of a single method. Limitations and future research directions are also discussed. [ABSTRACT FROM AUTHOR]

Typical public institutions such as government offices, hospitals, and schools play important leading and exemplary roles in the green and low-carbon development of the whole society. This paper analyzes the business and energy consumption characteristics of public institutions, as well as the characteristics of personnel travel, and constructs a carbon accounting model for public institutions. It innovatively proposes a methodology for carbon accounting of personnel travel related to public institutions and validates and analyzes it using a comprehensive hospital as an example. The paper analyzes the carbon emission characteristics of various energy types, systems, and types of travelers in hospitals, provides schemes for the transformation of main energy systems, and corresponding emission reduction effects, thereby providing technical support for the full-chain carbon accounting of public institutions. Additionally, this paper explores the carbon reduction pathways for hospitals to support the peak carbon and carbon neutrality goals of public institutions, and promote the high-quality development of public institutions in China. [ABSTRACT FROM AUTHOR]

In the context of China's freshwater crisis high-resolution data are critical for sustainable water management and economic growth. Yet there is a dearth of data on water withdrawal and scarcity regardless of whether total or subsector amount, for prefectural cities. In administrative and territorial scope, we accounted for water withdrawal of all 63 economic-socio-environmental sectors for all 343 prefectural cities in China, based on a general framework and 2015 data. Spatial and economic-sector resolution is improved compared with previous studies by partitioning general sectors into industrial and agricultural sub-sectors. Construction of these datasets was based on selection of 16 driving forces. We connected a size indicator with corresponding water-withdrawal efficiency. We further accounted for total blue-water withdrawal and quantitative water scarcity status. Then we compared different scopes and methods of official accounts and statistics from various water datasets. These disaggregated and complete data could be used in input-output models for municipal design and governmental planning to help gain in-depth insights into subsector water-saving priorities from local economic activities. [ABSTRACT FROM AUTHOR]

China's sewage treatment standards have been gradually improving, yet there is a widening gap between sewage treatment fees and actual costs. This discrepancy, where the fees for sewage treatment are lower than the actual operational expenses, poses a significant bottleneck to the sustainable development of China's sewage treatment industry. As a core aspect of environmental economic policies, sewage treatment fees are pivotal in regulating water pollution emissions and addressing water resource shortages. Currently, there are major issues with sewage treatment fees, including an incomplete pricing system, insufficient fees, unclear fee distribution, and a heavy reliance on local finances. These problems impede systematic planning, diminish management efficiency, and hinder the sustainable development of the sewage treatment industry. Thus, future research efforts should prioritize the establishment of a pricing mechanism that comprehensively covers the full cost of sewage treatment. This article presents a concise summary and review of the current situation, types of fee collection, cost accounting methodologies, challenges, and proposed countermeasures for sewage treatment fees, and could serve as a relevant reference for future research on sewage treatment fees. By comprehensively addressing these issues, the sewage treatment industry would progress towards healthier and more sustainable development, ultimately achieving the goal of green growth. [ABSTRACT FROM AUTHOR]

Limitations in statistical data and differences in accounting methods have hindered the accuracy of tourism carbon emissions accounting. In this research, based on the Tourism Satellite Account (TSA) and underpinned by the logic of "accounting basis–key coefficient–accounting objective," a comprehensive decomposition accounting method is built from a consumption stripping perspective. First, it classifies the tourism industry by the "sector–industry–product" structure into seven sectors, 13 industries, and 22 characteristic products/services. Next, it strips the actual tourism consumption from the tourism industry by constructing two key coefficients. Finally, it transforms tourism consumption data into carbon emissions data by introducing tourism ecological efficiency. Taking Guangdong province of China as an example, its tourism carbon emissions are calculated from 2010 to 2020 using the proposed method. The results reveal the distribution structure of tourism carbon emissions and confirm the scientific and accurate nature of this accounting method. [ABSTRACT FROM AUTHOR]

COALESCE, a collaborative network studying the impacts of carbonaceous aerosols, measured PM2.5 mass and its constituents at several regionally representative sites in India. This study reconciles the reconstructed mass (RCM) from PM2.5 chemical constituents with gravimetric PM2.5 mass measured during 2019 at three COALESCE sites (Bhopal, Mesra, and Mysuru). To evaluate the extent of mass closure, the spatiotemporal variability of organic matter/organic carbon (OM/OC), filter sampling artifacts of OC, nitrate, and aerosol liquid water (ALW) were assessed. The annual loss of total particulate OC from Teflon filters varied across Bhopal (0.46–1.35 μg m−3), Mesra (0.30–0.92 μg m−3), and Mysuru (0.16–0.68 μg m−3). Likewise, the range of nitrate volatilization was 0.7–2.7 μg m−3 at Bhopal, 0.5–2 μg m−3 at Mesra, and 1.3–2.2 μg m−3 at Mysuru. Also, the range of ALW mass was 2.6–6.8 μg m−3 at Bhopal, 3.2–9.5 μg m−3 at Mesra, and 0.8–3.8 μg m−3 at Mysuru. Seasonality was observed in the value of OM/OC with an increase during the pre‐monsoon season at all sites viz., Bhopal (2.20), Mesra (1.61), and Mysuru (2.02) compared to their annual averages, suggesting enhanced contribution of secondary organics to OC. The method developed for estimating RCM in this study resulted in better mass closure compared to using conventional RCM algorithms. Overall, this study provides a robust data validation strategy and India‐specific species coefficients for use in the RCM algorithm. The outcomes of this study can guide regional aerosol sampling, chemical analyses, and model–measurement reconciliation efforts. Plain Language Summary: This work investigates the relationships between surface PM2.5 and its chemical constituents across three locations in India through a mass closure investigation. The study enhances traditional mass reconstruction methodology by accounting for residual aerosol liquid water and volatilization losses of nitrates and organics, as well by using seasonal coefficients in the reconstruction algorithm. The seasonality of the volatilization losses and value of OM/OC provide insights on primary and secondary organic carbon across the sites. The application of seasonal coefficients improved the agreement between the RCM (reconstructed PM mass from chemical species) and PM2.5. Overall, this study provides a better understanding of the relationship between surface PM2.5 and its chemical constituents in India and will help guide sampling and chemical speciation efforts for aerosol mass apportionment. [ABSTRACT FROM AUTHOR]

Unpaired image-to-image translation (I2IT) involves establishing an effective mapping between the source and target domains to enable cross-domain image transformation. Previous contrastive learning methods inadequately accounted for the variations in features between two domains and the interrelatedness of elements within the features. Consequently, this can result in challenges encompassing model instability and the blurring of image edge features. To this end, we propose a multi-attention bidirectional contrastive learning method for unpaired I2IT, referred to as MabCUT. We design separate embedding blocks for each domain based on depthwise separable convolutions and train them simultaneously from both the source and target domains. Then we utilize a pixel-level multi-attention extractor to query images from embedding blocks in order to select feature blocks with crucial information, thus preserving essential features from the source domain. To enhance the feature representation capability of the model, we incorporate depthwise separable convolutions for the generator. We conducted comprehensive evaluations using three datasets, demonstrating that our approach enhances the quality of unpaired I2IT while avoiding the issue of mode collapse-related image blurring. [ABSTRACT FROM AUTHOR]

Cryptocurrency, as one of the most successful applications of blockchain technology, has played a vital role in promoting the development of the digital economy. However, its anonymity, large scale of cryptographic transactions, and decentralization have also brought new challenges in identifying abnormal accounts and preventing abnormal transaction behaviors, such as money laundering, extortion, and market manipulation. Recently, some researchers have proposed efficient and accurate abnormal transaction detection based on machine learning. However, in reality, abnormal accounts and transactions are far less common than normal accounts and transactions, so it is difficult for the previous methods to detect abnormal accounts by training with such an imbalance in abnormal/normal accounts. To address the issues, in this paper, we propose a method for identifying abnormal accounts using topology analysis of cryptographic transactions. We consider the accounts and transactions in the blockchain as graph nodes and edges. Since the abnormal accounts may have special topology features, we extract topology features from the transaction graph. By analyzing the topology features of transactions, we discover that the high-dimensional sparse topology features can be compressed by using the singular value decomposition method for feature dimension reduction. Subsequently, we use the generative adversarial network to generate samples like abnormal accounts, which will be sent to the training dataset to produce an equilibrium of abnormal/normal accounts. Finally, we utilize several machine learning techniques to detect abnormal accounts in the blockchain. Our experimental results demonstrate that our method significantly improves the accuracy and recall rate for detecting abnormal accounts in blockchain compared with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

A new technique for assessing functional diversity is proposed, which is essentially a way to calculate Rao's quadratic entropy. In contrast to the original method of calculating entropy, the new method takes into account intraspecific variability and allows us to evaluate other useful aspects of functional diversity, such as functional richness, functional evenness, the uniqueness of each species, and the contributions to functional diversity of intraspecific variability of each species and each trait separately. However, due to the peculiarities of the calculation, the proposed technique can only be applicable for an absolute count of all organisms within the "island" community or when collecting material based on a fixed sampling effort. The article provides an example of the application of the proposed technique to real rodent trapping data. [ABSTRACT FROM AUTHOR]

This study examines the impact of firm characteristics on earnings management (EM) using a sample of listed non-financial firms in India. First, we take a comprehensive perspective to estimate EM focusing on total accruals, current accruals and specific accruals. Second, we examine firm characteristics such as size, leverage, performance, growth opportunities and industry membership that are potentially related to accruals EM. We find that: 1) Large firms and firms with high performance have higher accruals quality. 2) Firms with higher growth opportunities have lower accruals quality. 3) Firms with high leverage use accruals EM to avoid violation of debt covenants. These findings indicate that investors and regulators should take into account both: the abnormal accruals over a period of time and the variability of abnormal accruals to analyse the quality of financial reporting of large firms, firms with high performance and highly levered firms. [ABSTRACT FROM AUTHOR]

The Mexican economy experienced two large crises: in 1995 and in 2008. The dynamics and origins of the episodes are very different; nevertheless, is there a common underlying mechanism? First, by applying the Business Cycle Accounting method, we find that the efficiency wedge is the main driver of output during both episodes. We present an equivalence between the neoclassical growth model with distortions and a small open economy with imported intermediate goods inputs, in which relative price changes manifest themselves as changes on the efficiency wedge. This result proposes a solution for the theoretical puzzle regarding the relationship between terms of trade shocks and productivity. Finally, the model is able to reproduce both the intensities and velocities of the crises in Mexico. [ABSTRACT FROM AUTHOR]

In the world of human–robot coexistence, ensuring safe interactions is crucial. Traditional logic-based methods often lack the intuition required for robots, particularly in complex environments where these methods fail to account for all possible scenarios. Reinforcement learning has shown promise in robotics due to its superior adaptability over traditional logic. However, the exploratory nature of reinforcement learning can jeopardize safety. This paper addresses the challenges in planning trajectories for robotic arm manipulators in dynamic environments. In addition, this paper highlights the pitfalls of multiple reward compositions that are susceptible to reward hacking. A novel method with a simplified reward and constraint formulation is proposed. This enables the robot arm to avoid a nonstationary obstacle that never resets, enhancing operational safety. The proposed approach combines scalarized expected returns with a constrained Markov decision process through a Lagrange multiplier, resulting in better performance. The scalarization component uses the indicator cost function value, directly sampled from the replay buffer, as an additional scaling factor. This method is particularly effective in dynamic environments where conditions change continually, as opposed to approaches relying solely on the expected cost scaled by a Lagrange multiplier. [ABSTRACT FROM AUTHOR]

Satellite observations of tropospheric trace gases and aerosols are evolving rapidly. Recently launched instruments provide increasingly higher spatial resolutions with footprint diameters in the range of 2–8 km, with daily global coverage for polar orbiting satellites or hourly observations from geostationary orbit. Often the modelling system has a lower spatial resolution than the satellites used, with a model grid size in the range of 10–100 km. When the resolution mismatch is not properly bridged, the final analysis based on the satellite data may be degraded. Superobservations are averages of individual observations matching the resolution of the model and are functional to reduce the data load on the assimilation system. In this paper, we discuss the construction of superobservations, their kernels and uncertainty estimates. The methodology is applied to nitrogen dioxide tropospheric column measurements of the TROPOMI instrument on the Sentinel-5P satellite. In particular, the construction of realistic uncertainties for the superobservations is non-trivial and crucial to obtaining close to optimal data assimilation results. We present a detailed methodology to account for the representativity error when satellite observations are missing due to e.g. cloudiness. Furthermore, we account for systematic errors in the retrievals leading to error correlations between nearby individual observations contributing to one superobservation. Correlation information is typically missing in the retrieval products where an error estimate is provided for individual observations. The various contributions to the uncertainty are analysed: from the spectral fitting, the estimate of the stratospheric contribution to the column and the air-mass factor. The method is applied to TROPOMI data but can be generalised to other trace gases such as HCHO, CO, SO2 and other instruments such as OMI, GEMS and TEMPO. The superobservations and uncertainties are tested in the ensemble Kalman filter chemical data assimilation system developed by JAMSTEC. These are shown to improve forecasts compared to thinning or compared to assuming fully correlated or uncorrelated uncertainties within the superobservation. The use of realistic superobservations within model comparisons and data assimilation in this way aids the quantification of air pollution distributions, emissions and their impact on climate. [ABSTRACT FROM AUTHOR]

Copyright of FinanzRundschau is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article explores the regulation of municipally owned water plants in the United States, with a focus on providing adequate service and fair rates to the public. It acknowledges the difficulties faced by small utilities in meeting regulatory requirements and maintaining accurate records. The article concludes by discussing the role of state commissions in monitoring compliance and improving service quality. It argues for the necessity of a central regulatory body to assist municipalities in maintaining proper accounting practices and determining equitable rates, highlighting the benefits of state regulation in ensuring high standards of service and fair rates for consumers. [Extracted from the article]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study examines the effect of measurement error on binary Randomized Response Technique models. We discuss a method for estimating and accounting for measurement error and untruthfulness in two basic models and one comprehensive model. Both theoretical and empirical results show that not accounting for measurement error leads to inaccurate estimates. We introduce estimators that account for the effect of measurement error. Furthermore, we introduce a new measure of model privacy using an odds ratio statistic, which offers better interpretability than traditional methods. [ABSTRACT FROM AUTHOR]

We study how foreign financial developments influence the conditional distribution of domestic GDP growth. We propose a method to account for foreign vulnerabilities using bilateral-exposure weights when assessing downside macroeconomic risks within quantile regressions. For an advanced-economy panel, we show that tighter foreign financial conditions and faster foreign credit-to-GDP growth are associated with a more severe left-tail of domestic GDP growth, even controlling for domestic indicators. Incorporating foreign variables improves estimates of domestic GDP-at-Risk, both in and out of sample. Decomposing GDP-at-Risk into domestic and foreign origins, we show that foreign shocks are a key driver of domestic macroeconomic tail risks. [ABSTRACT FROM AUTHOR]

The article examines the activity of the municipality from the point of view of the education management system in modern realities, namely in the conditions of digital transformation of society and its life, in particular, digitalization of educational activities. The main advantages and disadvantages of the digitalization of education are analyzed and presented. In the context of the research, the theoretical, normative and legal aspects of the current educational activity are presented, as a key link in solving problems of any nature for the benefit of the local population, in particular at the municipal level. In conclusion, the priority directions of the development of education management in the conditions of digitalization are given, which should effectively influence the optimization of organizational and management processes in the field of digital transformation, as well as the active penetration of digital technologies into the educational process of various educational organizations. The article reveals the effectiveness of information and communication technologies in municipal educational institutions training future specialists. In the context of the implementation of the research goal, the role of digitization as a factor in the implementation of educational activities in the process of training specialists in the economic field is studied. In the modern conditions of the development of the information society, there is a need for fast and high-quality calculation of economic indicators. It is this need that prompts the widespread use of software accounting methods. Digitalization has absorbed various fields of human activity. [ABSTRACT FROM AUTHOR]

The implementation of European funds is a critical pillar in Romania's economic and social development, yet it often faces significant accounting challenges, particularly during the pre-financing and accounting reconciliation phases. This study addresses the difficulties encountered in the process of adjustment and accounting reconciliation within projects funded by European funds, through a simulation. By examining the scenario of incomplete recording of amounts received as pre-financing, the paper explores the accounting adjustment methods necessary to ensure compliance and financial transparency. The results emphasize the importance of careful planning and the implementation of rigorous verification and accounting adjustment procedures, essential for the successful management of European funds. The adopted perspective encourages a proactive and integrated approach, suggesting that adaptability and accounting precision are keys in overcoming financial obstacles and achieving the objectives of projects with European funding. [ABSTRACT FROM AUTHOR]

This paper empirically investigates corruption-related disclosure in the banking industry, aiming to shed light on the reasons why financial institutions disclose corruption-related information in their annual financial reports. Using a total sample of 88 banks from the GIPSI countries during the period 2011-2019, our results reveal that, on average, banks involved in corruption issues disclose less on corruption-related matters than banks not involved in any corruption scandal. Moreover, banks not involved in corruption cases disclose even more information after other banks' corruption events become public. These basic relationships, however, are shaped by the characteristics of each particular country in terms of control of corruption and the specific regulation on non-traditional banking activities. Our results are robust to different specifications of econometric models, to alternative empirical methods accounting for potential reverse causality and sample selection concerns and to the inclusion of internal corporate governance mechanisms. [ABSTRACT FROM AUTHOR]

With the continuous development of the global economy, carbon dioxide and other greenhouse gas emissions are persistently increasing, making global warming an indisputable fact. As a high-energy consuming industry, the building industry has gradually emerged as the primary source of greenhouse gas emissions during urban expansion. Consequently, countries are exploring sustainable development pathways for low-carbon buildings to minimize the detrimental impact caused by the construction industry. This paper summarizes the current status of low-carbon building development and, through literature analysis concerning carbon standard systems and carbon emission accountings, discusses the challenges and possible improvements for the future. Establishing a quantitative evaluation tool for carbon emissions and elucidating accounting methods in the construction field is fundamental and a prerequisite for comprehensively studying low-carbon buildings throughout their life cycle. The challenges of low-carbon building development are as follows: (1) lack of a set of carbon emission measurement standards that can be commonly used internationally, (2) lack of a deep and systematic study of the theory of carbon emission accountings and (3) difficulty in recognizing carbon emission boundaries and related data for existing carbon emission accounting methods. This paper provides a comprehensive analysis of the current progress in low-carbon building development, along with an examination and optimization of the application of carbon emission accounting methodologies within construction to address the challenges. [ABSTRACT FROM AUTHOR]

Wetlands are among the most productive ecosystems on Earth, providing various key ecosystem services to humans and other organisms. However, an insufficient understanding of the economic value and importance of wetland resources has seriously weakened the ecosystem service value of wetlands. Thus, a more comprehensive understanding of wetland ecosystem services must be revealed in order to propose appropriate conservation policies. Therefore, to achieve the abovementioned goals, we used the emergy value accounting method to account for the ecosystem service value of the Maqu alpine wetlands, and the Logarithmic Mean Divisia Index was used to analyze the driving forces affecting changes in ecosystem services. The results indicate that the ecosystem service value of the Maqu alpine wetlands showed a trend of decline and then rebound during 1990–2020; its unit area emergy value decreased from 3.85 × 1010 sej/m2/y to 3.04 × 1010 sej/m2/y during 1990–2000, and after 2010, it began to gradually rebound. Moreover, the monetary ecosystem service value of the Maqu alpine wetlands continued to rise during the study period, reaching 41.45 USD/m2/y in 2020, thus reflecting the great potential value of wetland ecosystems. Based on our analysis, the key drivers affecting the changes in ecosystem services include economic scale and emergy benefit. Rapid and intensive human activities have boosted local economic development, but these developments have come at the cost of environmental degradation. Finally, some suggestions are proposed. This study suggests that the alpine wetlands in Maqu occupy an important ecological position within the whole Yellow River basin. Therefore, it is worthwhile to invest a significant amount of funding in their restoration and protection. [ABSTRACT FROM AUTHOR]

This paper aims at investigating the triaxial behavior of Autoclaved Aerated Concrete (AAC) under extremely high pressures, and experimentally determine Equation of State (EOS) for several different AAC densities. Oedometric tests were carried out using a home-made high-pressure triaxial apparatus, and pressures up to ~500 MPa were applied. The complete pressure-bulk strain relationships were measured, and new findings and insights were obtained. The paper presents the testing set-up and the measurement system. The data processing method accounting for the AAC pronounced shortening during the ongoing test is described using a weighted functions procedure for the circumferential strains' calculation, with which the confining pressure was determined. The boundary conditions effects on the test results were investigated, and a new technique for specimen insulation was suggested to ensure loading without friction and the prevention of local shear failure. The experimental EOS for different AAC densities were obtained. EOS curves for different specimens with the same density demonstrated good to very good repeatability of the EOS curves over the entire pressure range. Based on the tests results and the density's span, three classes of AAC are proposed. A preliminary attempt to apply the newly obtained EOS curves has been carried out to examine the energy dissipation for three different dynamic load levels. Although this is a preliminary stage that is beyond the objective of this paper, early interesting results were observed where an optimal AAC density, for which the highest energy has been absorbed, was identified. This finding encourages inclusion of that preliminary study as a closure section. Numerical simulations of wave propagation through ACC layers of different densities, laid on rigid supporting slabs, was carried out. The minimum total impulse imparted to the rigid slab was found for the optimal AAC density that has been determined above. [ABSTRACT FROM AUTHOR]

We have framed a detailed account of the synthetic methods and the bioactivity and pharmacological aspects available for aminopyrazolecarbonitriles as they have substantial role as a building block and starting materials for producing enormous biologically active heterocyclic skeletons. Hydrazine derivatives are important precursors in the synthesis of aminopyrazolecarbonitriles where, the nucleophilic addition of hyrazines to monocyano, dicyano, tricyano and tetracyanoethylenes led to the formation of the target compounds via the formation of two C–N bonds. Multicomponent reactions (MCRs) of hydrazines, aromatic aldehydes, and malononitrile is considered an efficient one pot protocol for the synthesis of aminopyrazolecarbonitriles. Intramolecular cyclization involves one bond formation and functional group transformations are used to prepare aminopyrazolecarbonitriles. [ABSTRACT FROM AUTHOR]

Ecosystem products and services are fundamental to human survival and development. The gross ecosystem product can be defined as the total value of products and services provided by ecosystems for human wellbeing and sustainable socioeconomic development. This includes the value of production system products, ecosystem regulation services, and ecosystem cultural services. The valuation of gross ecosystem product offers crucial technical support for constructing mechanisms by which to realize them, and it holds significant importance in promoting the comprehensive green transformation of economic and social development. In this study, we introduce the definition and accounting methods of the gross ecosystem product and explore the application of the gross ecosystem product and ecosystem asset accounting in ecological benefit assessment, using Tonglu County in Hangzhou City, Zhejiang Province, as an example. Finally, we provide recommendations by which to strengthen gross ecosystem product accounting and explore mechanisms for realizing ecological values based on this foundation. The results indicate that in 2021, the total gross ecosystem product value of Tonglu County reached CNY 55.129 billion, equivalent to 1.33 times the gross domestic product of that year. Among the various services, regulatory services contributed the most to the total ecological products, with climate regulation being the largest contributor at CNY 27.199 billion, accounting for 49.34%. Tonglu County boasts abundant natural resources, which hold significant value. By conducting an audit of the total ecological products, we can precisely determine the value of the ecosystem. This aids relevant departments in estimating the value of ecological products in Tonglu County's ecosystem. Such information can support the formulation of ecological protection and sustainable development policies in Tonglu County, while also serving as a reference for estimating the total ecological products and enhancing the ecological value in other counties. [ABSTRACT FROM AUTHOR]

This paper presents the results of a listening experiment designed to assess annoyance and perceived loudness (PL) for several unmanned aircraft system (UAS) operations, with the listener simulated in indoor and outdoor positions. This research investigated (i) how participant responses change depending on UAS operation, (ii) which broadband metrics are most suitable for representing annoyance and PL, (iii) differences in noise level required to result in equal participant responses to different operations, and (iv) which sound quality metrics (SQMs) are significant for UAS noise perception. Results indicate annoyance and PL responses were greatest for landing operations with flyovers being the least annoying or loud. LAeq, LASmax, and loudness (N5) were the strongest predictors in representing annoyance. Offset analysis predicted small differences in annoyance responses between flyovers and other operations, but also indicated that flyovers would require an increase to LASmax of 3.3 to 6.3 dB compared to other operations to achieve equal PL. Loudness was the most significant SQM, with minor contributions from impulsivity for annoyance and PL when outside, and tonality for PL when indoors. These findings contribute to the understanding of UAS noise perception for the development of metrics and assessment methods accounting for the characteristics of UAS operations. [ABSTRACT FROM AUTHOR]

As digital technologies continue to reshape economic landscapes, the comprehensive evaluation of digital economy (DE) development in provincial regions becomes a critical endeavor. This article proposes a novel approach, integrating the linear programming method, fuzzy logic, and the alternative ranking order method accounting for two-step normalization (AROMAN), to assess the multifaceted facets of DE growth. The primary contribution of the AROMAN is the coupling of vector and linear normalization techniques in order to produce accurate data structures that are subsequently utilized in calculations. The proposed methodology accommodates the inherent uncertainties and complexities associated with the evaluation process, offering a robust framework for decision-makers. The linear programming aspect optimizes the weightings assigned to different evaluation criteria, ensuring a dynamic and context-specific assessment. By incorporating fuzzy logic, the model captures the vagueness and imprecision inherent in qualitative assessments, providing a more realistic representation of the DE's multifaceted nature. The AROMAN further refines the ranking process, considering the interdependencies among the criteria and enhancing the accuracy of the evaluation. In order to ascertain the efficacy of the suggested methodology, a case study is undertaken pertaining to provincial areas, showcasing its implementation in the evaluation and a comparison of DE progress in various geographical settings. The outcomes illustrate the capacity of the model to produce perceptive and implementable insights for policymakers, thereby enabling them to make well-informed decisions and implement focused interventions that promote the expansion of the DE. Moreover, managerial implications, theoretical limitations, and a comparative analysis are also given of the proposed method. [ABSTRACT FROM AUTHOR]

Objective: Iverson (2001) expanded on reliable change methodology by accounting for the variability in scores at Time 2 in the calculation of change scores. However, due to limitations in available data, an incomplete picture of variables affecting change was presented. The current paper sought to address some of these limitations and clarify the methodology for assessing reliable change. Method: Using one-year test-retest data on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in older adults who were cognitively intact or had mild Alzheimer's disease (AD), change scores were calculated, and various models, consistent with or divergent from Iverson, were presented. Results: Across the RBANS, individuals with intact cognition tended to show less variable scores, especially at Time 2, which resulted in larger change scores than those with AD. When applied to an independent sample, different patterns of change were observed, with: (1) models that used intact data showed more cognitive change than those using AD data; (2) the model that corrected for practice effects and used intact data showed the most decline; and (3) the model that corrected for practice effects and used AD data showed the most improvement. The models that showed the strongest association in classifying independent cases as decline/stable/improve were those that used intact data and were discordant on the use of practice effects. Conclusions: Overall, findings highlight the complexity of calculating reliable change, and they lend additional caution to Iverson's original limitations. However, the use of data from individuals classified as cognitively intact and a correction for practice effects seems warranted. [ABSTRACT FROM AUTHOR]

The standard of accurate accounting method for carbon emissions of sewage treatment plants is studied. Based on the existing carbon accounting methods of wastewater treatment plants(WWTP) in China, combined with the research of carbon accounting standards and guidelines at home and abroad, we put forward some suggestions for revising carbon emission accounting methods of WWTP from the aspects of accounting boundary, greenhouse gas type, emission source and emission process. It is suggested to extend the accounting boundary both WWTP and its upstream/downstream, including upstream and downstream sewage pipe networks and downstream discharge water bodies on the basis of not causing double counting. It is also suggested that the fossil CO2 originated from both sewage and the applied chemicals should be included in the accounting. Additionally, supplementary identification of fuel combustion, transportation equipment and fugitive emission sources within the plant boundary, and additional consideration of discharge sources such as outsourced transportation and sludge disposal are proposed. It is recommended to conclude the carbon emissions of energy(electricity and other forms of energy) and substances(chemicals, etc.) from the manufacturing and transportation links. And the fluctuation effect of wastewater treatment operating conditions on carbon emissions is considered. It is suggested that the optimal operation and management of WWTP and multiple forms of resource and energy recovery should be included in carbon offset. On this basis, the carbon emission process and carbon emission source of WWTP are summarized. In addition, how to optimize the carbon emission calculation of WWTP is prospected from the aspects of carbon accounting boundary, emission factor, model application and fossil CO2. [ABSTRACT FROM AUTHOR]

In this paper, we propose an Iterative Greedy-Universal Adversarial Perturbations (IGUAP) approach based on an iterative greedy algorithm to create universal adversarial perturbations for acoustic prints. A thorough, objective account of the IG-UAP method is provided, outlining its framework and approach. The method leverages a greedy iteration approach to formulate an optimization problem for solving acoustic universal adversarial perturbations, with a new objective function designed to ensure that the attack has higher accuracy in terms of minimizing the perceptibility of adversarial perturbations and increasing the accuracy of successful attacks. The perturbation generation process is described in detail, and the resulting acoustic universal adversarial perturbation is evaluated in both target-attack and no-target-attack scenarios. Experimental analysis and testing were carried out using comparable techniques and dissimilar target models. The findings reveal that the acoustic generality adversarial perturbation produced by the IG-UAP method can obtain effective attack results even when the audio training data sample size is minimal, i.e., one for each category. Moreover, the human ear finds it difficult to detect the loss of original data information and the addition of adversarial perturbation (for the case of a target attack, the ASR values range from 82.4% to 90.2% for the small sample data set). The success rates for untargeted and targeted attacks average 85.8% and 84.9%, respectively. [ABSTRACT FROM AUTHOR]

Many studies have developed methods for assessing attractiveness, but the question is which one should be used to evaluate geopark designated areas? Therefore, the aim of this study is to find suitable criteria for assessing the attractiveness of a natural area such as a geopark in order to find the best quantifiable method as a methodological guide to evaluate attractiveness. The principle of the methodology takes into account three facts: the use of available attractiveness methods elaborated over time, the UNESCO Global Geoparks (UGGp) geopark requirements, and a certified geopark (Haţeg UNESCO Global Geopark was chosen as etalon—benchmark), then matching these together. To this end, the following specific objectives have been set: (i) an inventory of factors used to estimate attractiveness; (ii) through analysis, identifying the appropriate evaluation criteria for the field (a set for criteria's SMART parameter, which can be clearly expressed, quantitatively measurable, and achievable); and (iii) developing a methodological guideline for geopark attractiveness assessment. The methodology is based on an analytical thinking approach, builds on the experience of existing methods, and stands out by the attributes matched to the UGGp's evaluation criteria using the certified geopark as a benchmark. The result itself presents a method for assessing the attractiveness of geoparks. The outcome offers the attractiveness suitability for new geopark-designated areas as well as for existing geoparks aspiring to UNESCO certification. [ABSTRACT FROM AUTHOR]

Road safety is a central issue in the management and development of a road network. Road agencies must try to identify the most dangerous sections of their network and act on them to improve safety. The most used procedure for this purpose is about considering the indicators based on crashes. However, a mature road safety management system must be able to assess the safety of a road section before accidents occur. The European community is moving in this direction with the update of Directive 2008/96/EC (Directive 1936/2019). This paper proposes a new methodology for carrying out a network-wide road safety assessment on rural single-carriageways and two-lane two-way roads. This procedure accounts for the influence of road characteristics on drivers' perceptions. The methodology has been developed based on the human factors concepts from PIARC, and it includes a series of checklists that guide an inspector in carrying out a visual inspection of single-carriageway roads. The results from the checklist are then processed into an algorithm, and the level of risk in the analyzed section is provided. The objectives of the procedure are (a) to account for the perceptive aspects that are one of the major causes of road accidents, (b) to provide a proactive procedure in line with the requirements of the European Directive, and (c) to provide a useful instrument that can be easily implemented by road agencies and integrated with other analysis procedures. The procedure has been applied and tested on a case study of six different stretches of two-lane, two-way rural highways in Italy, Germany, and Slovenia (about 65 km). The results show a high degree of concordance with a risk classification based on the accident rate, mainly considering high-risk sections. Therefore, the procedure demonstrated its potential to be a useful instrument to be included in network safety assessments. Road agencies should consider the use of this procedure in their network safety analysis and ranking. [ABSTRACT FROM AUTHOR]

Purpose: American Indian/Alaska Native (AI/AN) populations experience significantly higher incidence and mortality rates of cervical cancer. The objective of this systematic scoping review is to characterize the volume and nature of research being conducted specific to the AI/AN population regarding cervical cancer and related clinical themes. Methods: This scoping review was conducted in collaboration with the Pacific Northwest Evidence-based Practice Center. Search strategies identified eligible publications from 1990 through 4 February 2022. Two reviewers independently abstracted study data, including clinical area, number of participants and percent inclusion of AI/AN, intervention or risk factor, outcomes reported, Indian Health Service (IHS) Region, and funding source. We used published algorithms to assess study design. Results: Database searches identified 300 unique citations. After full-text evaluation of 129 articles, 78 studies and 9 secondary publications were included (total of 87). Approximately 74% of studies were observational in design, with cross-sectional methodology accounting for 42.7% of all included studies. The most common clinical theme was cervical cancer screening. The most common intervention/exposure was risk factor, typically race (AI/AN compared with other groups) (69%). For studies with documented funding sources, 67% were funded by the US Government. Conclusion: Of the small number of publications identified, the majority are funded through government agencies, are descriptive and/or cross-sectional studies that are hypothesis generating in nature, and fail to represent the diversity of the AI/AN populations in the US. This systematic scoping review highlights the paucity of rigorous research being conducted in a population suffering from a greater burden of disease. [ABSTRACT FROM AUTHOR]

Background: As interest in the voluntary soil carbon market surges, carbon registries have been developing new soil carbon measurement, reporting, and verification (MRV) protocols. These protocols are inconsistent in their approaches to measuring soil organic carbon (SOC). Two areas of concern include the type of SOC stock accounting method (fixed-depth (FD) vs. equivalent soil mass (ESM)) and sampling depth requirement. Despite evidence that fixed-depth measurements can result in error because of changes in soil bulk density and that sampling to 30 cm neglects a significant portion of the soil profile's SOC stock, most MRV protocols do not specify which sampling method to use and only require sampling to 30 cm. Using data from UC Davis's Century Experiment ("Century") and UW Madison's Wisconsin Integrated Cropping Systems Trial (WICST), we quantify differences in SOC stock changes estimated by FD and ESM over 20 years, investigate how sampling at-depth (> 30 cm) affects SOC stock change estimates, and estimate how crediting outcomes taking an empirical sampling-only crediting approach differ when stocks are calculated using ESM or FD at different depths. Results: We find that FD and ESM estimates of stock change can differ by over 100 percent and that, as expected, much of this difference is associated with changes in bulk density in surface soils (e.g., r = 0.90 for Century maize treatments). This led to substantial differences in crediting outcomes between ESM and FD-based stocks, although many treatments did not receive credits due to declines in SOC stocks over time. While increased variability of soils at depth makes it challenging to accurately quantify stocks across the profile, sampling to 60 cm can capture changes in bulk density, potential SOC redistribution, and a larger proportion of the overall SOC stock. Conclusions: ESM accounting and sampling to 60 cm (using multiple depth increments) should be considered best practice when quantifying change in SOC stocks in annual, row crop agroecosystems. For carbon markets, the cost of achieving an accurate estimate of SOC stocks that reflect management impacts on soils at-depth should be reflected in the price of carbon credits. [ABSTRACT FROM AUTHOR]

Weakly supervised semantic segmentation with only image-level labels is an essential application since it reduces the considerable human effort to fully annotate image. Most state-of-the-art methods take into account discriminative regions or prior knowledge (called seeds) by applying the recent Classification Activation Maps (CAM) methods. As seeds used in the CAM methods could be considered as segmentation knowledge, increasing seeds will naturally improve the performance of the CAM methods. We treat such task as a seed exploration with clustering learning, which is different from the current methods in which region mining or seeds learning are performed in an end-to-end learning manner. In this paper, we propose a progressive framework containing autoencoders to explore numerous and accurate seeds to further improve the performance of CAM methods. Our explored seeds can replace the initial seeds, and thus, they can be integrated with current weakly supervised semantic segmentation methods for performance improvement. We show experimentally that our provided seeds lead to better model training. As a result, we obtain performance improvement from corresponding counterparts to reach 68.1 and 69.2% mIoU on PASCAL VOC 2012 validation and test dataset, respectively. [ABSTRACT FROM AUTHOR]

With the widespread adoption of virtual reality and 360-degree video, there is a pressing need for objective metrics to assess quality in this immersive panoramic format reliably. However, existing image quality assessment models developed for traditional fixed-viewpoint content do not fully consider the specific perceptual issues involved in 360-degree viewing. This paper proposes a 360-degree image full-reference quality assessment (FR-IQA) methodology based on a multi-channel architecture. The proposed 360-degree FR-IQA method further optimizes and identifies the distorted image quality using two easily obtained useful saliency and depth-aware image features. The convolutional neural network (CNN) is designed for training. Furthermore, the proposed method accounts for predicting user viewing behaviors within 360-degree images, which will further benefit the multi-channel CNN architecture and enable the weighted average pooling of the predicted FR-IQA scores. The performance is evaluated on publicly available databases to demonstrate the advantages brought by the proposed multi-channel model in performance evaluation and cross-database evaluation experiments, where it outperforms other state-of-the-art ones. Moreover, an ablation study exhibits good generalization ability and robustness. [ABSTRACT FROM AUTHOR]

The knowledge of the positions of the corotation resonance in spiral arms is a key way to estimate their pattern speed, which is a fundamental parameter determining the galaxy dynamics. Various methods for its estimation have been developed, but they all demonstrate certain limitations and a lack of agreement with each other. Here, we present a new method for estimating the corotation radius. This method takes into account the shape of the profile across the arm and its width and, thus, only photometric data is needed. The significance of the method is that it can potentially be used for the farthest galaxies with measurable spiral arms. We apply it to a sample of local galaxies from Savchenko et al.(2020) and compare the obtained corotation radii with those previously measured in the literature by other methods. Our results are in good agreement with the literature. We also apply the new method to distant galaxies from the COSMOS field. For the first time, corotation locations for galaxies with photometric redshifts up to z ∼ 0.9 are measured. [ABSTRACT FROM AUTHOR]

Axial forces can be artificially adjusted in deep excavations braced with servo struts to reduce excavation-induced deformations. The interactions among the servo strut, retaining wall, and retained soil must be considered to predict the excavation-induced deformations and axial force adjustment. According to the beam–spring model, this study advances a simplified method to calculate the wall deflections generated by excavation with adjustable axial forces in struts. The proposed method incorporates the coupling relationship between the alterations in the earth pressure and wall displacement to consider soil–wall interactions. A mixed boundary, including force boundary and spring boundary, is introduced in the equilibrium equation to simulate the adjustable forces in the servo struts. The recommended method accounts for the soil–wall–strut interactions. Two real excavation cases supported by traditional and servo steel struts, respectively, validate this study's findings. Comparisons between the predictions and measurements demonstrate the effectiveness of the proposed method. Projections and measurements indicate that the servo struts reduce the maximum wall deflection, which decreases significantly with the increased axial force. Importantly, the retaining wall moves outside the excavation if excessive axial forces are applied in the servo struts. [ABSTRACT FROM AUTHOR]

The article presents the criteria applied in the sociolinguistic annotation in the Corpus of old Polish dramatic texts (1772-1939) (KorTeDa). This level of annotation was about assigning the three basic sociolinguistic variables: age, sex and social status to all the utterances of drama characters (except for collective statements). Six values were selected for determining age (underage, young adult, middle-aged adult, older adult (senior), indeterminate adult, indeterminate); three for sex (female, male, indeterminate); and four for social status (low, medium, high, indeterminate). The article shows the interdependence between those factors and the historical, social and cultural context. Additionally, the authors illustrated substantial and technical problems they faced during the process of this type of annotation. KorTeDa may become an important tool for analysing the history of the Polish language taking into account the methods of corpus linguistics and sociopragmatics. [ABSTRACT FROM AUTHOR]

Objectives The study examined the impact of creative and aggressive accounting on the quality of financial reporting in the hospitality industry in Zimbabwe., Prior Work The study also identified the motives behind creative accounting and established the areas that are mainly affected by creative accounting in financial reporting. Approach This study adopted a mixed-methods research design, integrating both qualitative and quantitative approaches. Twenty-six semi-structured interviews were conducted, and financial statements were analyzed from five hotels which were randomly sampled. Results The study found that management uses creative accounting for their personal gain, to improve share market prices, to avoid paying taxation, to ensure that they do not fail in debt covenants, and to acquire loans from financial service providers. The study found that hotels in Zimbabwe use creative accounting methods such as altering accounting principles, asset valuation, intra-company transactions, undervaluing liabilities, and early revenue recognition. The findings further revealed that there is a significant relationship between creative accounting practices and the quality of financial reporting in the hospitality industry in Zimbabwe. Implications This suggests that those entities that practice creative accounting practices in manipulating their financial statements, jeopardize the quality of the reports, and misleading various stakeholders, hence, they should be sanctioned or forced to pay penalties. Value This study provides research-based knowledge as it is the first studies to be conducted in Zimbabwe on creative accounting in the hospitality industry in Zimbabwe. [ABSTRACT FROM AUTHOR]

In quantitative measurement of the T2 value of tissues, the diffusion of water molecules has been recognized as a confounder. This is most notably so for transient‐state quantitative mapping techniques, which allow simultaneous estimation of T1 and T2. In prior work, apparently conflicting conclusions are presented on the level of diffusion‐induced bias on the T2 estimate. So far there is a lack of studies on the effect of the RF pulse angle sequence on the level of diffusion‐induced bias. In this work, we show that the specific transient‐state RF pulse sequence has a large effect on this level of bias. In particular, the bias level is strongly influenced by the mean value of the RF pulse angles. Also, for realistic values of the spoiling gradient area, we infer that the diffusion‐induced bias is negligible for non‐liquid human tissues; yet, for phantoms, the effect can be substantial (15% of the true T2 value) for some RF pulse sequences. This should be taken into account in validation procedures. [ABSTRACT FROM AUTHOR]