For randomized controlled trials to be conclusive, it is important to set the target sample size accurately at the design stage. Comparing two normal populations, the sample size calculation requires specification of the variance other than the treatment effect and misspecification can lead to underpowered studies. Blinded sample size re-estimation is an approach to minimize the risk of inconclusive studies. Existing methods proposed to use the total (one-sample) variance that is estimable from blinded data without knowledge of the treatment allocation. We demonstrate that, since the expectation of this estimator is greater than or equal to the true variance, the one-sample variance approach can be regarded as providing an upper bound of the variance in blind reviews. This worst-case evaluation can likely reduce a risk of underpowered studies. However, blinded reviews of small sample size may still lead to underpowered studies. We propose a refined method accounting for estimation error in blind reviews using an upper confidence limit of the variance. A similar idea had been proposed in the setting of external pilot studies. Furthermore, we developed a method to select an appropriate confidence level so that the re-estimated sample size attains the target power. Numerical studies showed that our method works well and outperforms existing methods. The proposed procedure is motivated and illustrated by recent randomized clinical trials.
Shared-account usage is common on streaming and e-commerce platforms, where multiple users share one account. Existing shared-account sequential recommendation (SSR) methods often assume a fixed number of latent users per account, limiting their ability to adapt to diverse sharing patterns and reducing recommendation accuracy. Recent latent reasoning technique applied in sequential recommendation (SR) generate intermediate embeddings from the user embedding (e.g, last item embedding) to uncover users' potential interests, which inspires us to treat the problem of inferring the number of latent users as generating a series of intermediate embeddings, shifting from inferring preferences behind user to inferring the users behind account. However, the last item cannot be directly used for reasoning in SSR, as it can only represent the behavior of the most recent latent user, rather than the collective behavior of the entire account. To address this, we propose DisenReason, a two-stage reasoning method tailored to SSR. DisenReason combines behavior disentanglement stage from frequency-domain perspective to create a collective and unified account behavior representation, which serves as a pivot for latent user reasoning stage to infer the number of users behind the account. Experiments on four benchmark datasets show that DisenReason consistently outperforms all state-of-the-art baselines across four benchmark datasets, achieving relative improvements of up to 12.56\% in MRR@5 and 6.06\% in Recall@20.
En un contexto marcado por la globalización, la digitalización y el aumento de escándalos financieros, el rol del contador público ha adquirido una relevancia crítica. El objetivo del artículo fue analizar los desafíos éticos que debe enfrentar en el entorno contemporáneo. Con un método de investigación hermenéutico, un estudio documental con un enfoque cualitativo y desde un paradigma interpretativo, se consultó el material publicado entre enero del 2020 hasta septiembre 2025 en las bases de datos electrónicas Google Académico, Scopus, Redalyc, Dialnet, Scielo y Jstore; aplicándose la técnica de la observación sobre una muestra de cincuenta (50) artículos científicos. La revisión bibliografía mostró que el principal reto es mantener una postura ética ante los intereses empresariales que pueden entrar en conflicto con la transparencia y responsabilidad social. Se concluyó que debe fortalecer sus principios donde estos valores sean una herramienta clave para generar la confianza que su profesión demanda.
Este artigo analisa a importância da Escrituração Contábil Digital (ECD), no âmbito do Sistema Público de Escrituração Digital (SPED), para a efetividade da fiscalização tributária no Brasil. Utiliza-se abordagem qualitativa, com base em revisão bibliográfica e documental, abordando os efeitos da padronização, automação e impactos organizacionais. Os resultados demonstram que a ECD se consolida como instrumento essencial de inteligência fiscal e conformidade tributária, embora desafios de natureza distributiva ainda limitem sua aplicação plena. Destaca-se também sua relevância frente à nova legislação tributária.
State-of-the-art blockchain sharding solutions such as Monoxide, can cause severely imbalanced distribution of transaction (TX) workloads across all blockchain shards due to the deployment policy of their accounts. Imbalanced TX distributions then produce hot shards, in which the cross-shard TXs may experience an unlimited confirmation latency. Thus, how to address the hot-shard issue and how to reduce crossshard TXs become significant challenges of blockchain sharding. Through reviewing the related studies, we find that a crossshard TX protocol that can achieve workload balance among all shards and simultaneously reduce the quantity of crossshard TXs is still absent from the literature. To this end, we propose BrokerChain, which is a cross-shard blockchain protocol dedicated to account-based state sharding. Essentially, BrokerChain exploits fine-grained state partition and account segmentation. We also elaborate on how BrokerChain handles cross-shard TXs through broker accounts. The security issues and other properties of BrokerChain are analyzed rigorously. Finally, we conduct comprehensive evaluations using an opensource blockchain sharding prototype named BlockEmulator. The evaluation results show that BrokerChain outperforms other baselines in terms of transaction throughput, transaction confirmation latency, the queue size of the transaction pool, and workload balance.
To enable effective human-AI collaboration, merely optimizing AI performance without considering human factors is insufficient. Recent research has shown that designing AI agents that take human behavior into account leads to improved performance in human-AI collaboration. However, a limitation of most existing approaches is their assumption that human behavior remains static, regardless of the AI agent's actions. In reality, humans may adjust their actions based on their beliefs about the AI's intentions, specifically, the subtasks they perceive the AI to be attempting to complete based on its behavior. In this paper, we address this limitation by enabling a collaborative AI agent to consider its human partner's beliefs about its intentions, i.e., what the human partner thinks the AI agent is trying to accomplish, and to design its action plan accordingly to facilitate more effective human-AI collaboration. Specifically, we developed a model of human beliefs that captures how humans interpret and reason about their AI partner's intentions. Using this belief model, we created an AI agent that incorporates both human behavior and human beliefs when devising its strategy for interacting with humans. Through extensive real-world human-subject experiments, we demonstrate that our belief model more accurately captures human perceptions of AI intentions. Furthermore, we show that our AI agent, designed to account for human beliefs over its intentions, significantly enhances performance in human-AI collaboration.
Yağmurlu gün fonu (bütçe istikrar fonu) ekonomik dalgalanmalar ve bütçe
açıkları karşısında mali esneklik sağlamak amacıyla oluşturulmuş tasarruf fonlarıdır. Bu
fonlar ekonomik krizler, beklenmeyen gelir kayıpları veya yüksek giderler gibi durumlarla
karşılaşıldığında devreye girmekte ve hükümetlerin temel hizmetlerini sürdürmesi için
gerekli finansmanı sağlamaktadır. Dolayısıyla yağmurlu gün fonları ekonomik istikrarı
sağlamak ve bütçe dengesini korumak amacıyla başvurulan önemli bir finansman
aracıdır. Bu çalışma Amerika Birleşik Devletleri’ndeki yağmurlu gün fonu uygulamalarının
teorik bir incelemesidir. Literatürdeki ampirik çalışmalardan elde edilen bulgular ışığında,
yağmurlu gün fonlarının varlığı durumunda eyaletlerin mali stres dönemlerini vergi
ve harcama değişikliklerine başvurmadan daha rahat atlattıkları, kamu tasarruflarını
artırdıkları ve mali istikrarın sürdürülmesinde yağmurlu gün fonlarının önemli bir araç
olduğu sonucuna ulaşılmıştır.
This study aims to analyze the role of corporate governance mechanisms consisting of audit committee and managerial ownership and also macroeconomic indicators consisting of inflation and interest rates on financial distribution in infrastructure, transport and logistics companies listed on the Indonesian Stock Exchange for the period 2019-2021. This study used a quantitative approach with secondary data sources in the form of financial statements and corporate annual reports. The samples used in this study were 68 companies with a total of 204 firm year with purposive sampling methods. Data analysis techniques used include regression model selection tests, classical assumption tests, multiple regression analysis tests, and hypothesis tests with the STATA 16 program. The results showed that managerial ownership had a significant and negative impact on financial distress, and interest rate had a significant and positive impact on financial distress. Meanwhile, the other variables include: audit committee and inflation do not have significant impact on financial distress. This study will provide information that can assist to anticipating financial distress by improving the corporate governance mechanisms and understanding of macroeconomics studies.
This community service activity aims to provide education about the urgency of bookkeeping in business for prospective young entrepreneurs at MAN Lumajang. This community service activity is carried out using three methods, namely direct observation, implementation of activities, and evaluation of activities. This community service activity was carried out with good results in that students at MAN Lumajang were able to receive and digest an understanding of the science of bookkeeping in business for prospective young entrepreneurs. This is because bookkeeping is important for a business and is part of accounting records in order to build a new business and become a young entrepreneur in the future.
Writing this article aims to find out the use of technology, especially in the field of accounting, to know the role of accounting information systems in SME, and the application of digital bookkeeping to SME. The method used is a case study method using related journals. The results that have been obtained indicate that the current use of technology in SME has implemented digitalization in their activities. For example on sales and payments. However, many SME bookkeepers still use bookkeeping manually using paper. Counseling is carried out, it is hoped that with the rapid advancement of technology, currently SME actors can carry out bookkeeping in their businesses effectively and efficiently so that they can create technologically literate SME.
This research evaluates the role of accounting information systems in harnessing technology for digital bookkeeping in MSMEs in Kampung Kue. These MSMEs still use manual bookkeeping, with the risk of missing records and potential fraud. The results suggest the adoption of digital bookkeeping applications as a solution, providing efficiency, transparency, and preventing recording errors. The application of this technology can help Kampung Kue MSMEs improve their financial management. Training and counseling are needed to ensure better understanding and acceptance from MSMEs of digital bookkeeping.
Nyata Nugraha, Iwan Budiyono, Ida Nurhayati
et al.
This study aims to analyze the implementation and use of accounting information systems in Micro, Small and Medium Enterprises (SMEs) in the service and trade sector in Semarang City. The population of this research is SMEs in the service and trade sector in the city of Semarang. The sampling technique in this study used the stratified random sampling method. The number of samples in this study were 104 SMEs. This study uses descriptive analysis to analyze the results of the survey questionnaire. It was found that the problem with the Accounting Information System (AIS) in SMEs starts from limited capital for SMEs so that they are unable to pay employees in the accounting department, or for reasons of efficiency. So that the bookkeeping or accounting records of the company are the owners themselves. Meanwhile, SMEs owners do not have sufficient knowledge of accounting. Limited capital and lack of knowledge about accounting, causes SMEs not to use the Accounting Information System (AIS) in recording their business transactions. This is what causes SMEs not to compile financial reports, both in the form of Income Statements and Statements of Financial Position. This problem is the basis for the preparation of accounting applications for SMEs.
A self-consistent radiation-hydrodynamics model of an accretion channel of subcritical X-ray pulsars is constructed. The influence of the presence of resonance in the scattering cross-section on the accretion process and radiation transfer is taken into account. It is shown that the efficiency of plasma deceleration by radiation depends on the magnitude of the magnetic field $B$. For $B=1.7\times 10^{12}$ G, the spectra and the degree of linear polarization of the radiation of the accretion channel are constructed. In the obtained spectra, the shape of the cyclotron line depends on the direction of the outgoing radiation. The calculated linear polarization degree of the outgoing radiation is $30 -40\%$ near the cyclotron resonance, whereas it can be small ($\lesssim 5 - 10\%$) at energies significantly lower than the resonant one.
Umme Ayman Koana, Francis Chew, Chris Carlson
et al.
The COVID-19 pandemic has accelerated the adoption of digital health solutions. This has presented significant challenges for software development teams to swiftly adjust to the market need and demand. To address these challenges, product management teams have had to adapt their approach to software development, reshaping their processes to meet the demands of the pandemic. Brighsquid implemented a new task assignment process aimed at enhancing developer accountability toward the customer. To assess the impact of this change on code ownership, we conducted a code change analysis. Additionally, we surveyed 67 developers to investigate the relationship between accountability and ownership more broadly. The findings of our case study indicate that the revised assignment model not only increased the perceived sense of accountability within the production team but also improved code resilience against ownership changes. Moreover, the survey results revealed that a majority of the participating developers (67.5%) associated perceived accountability with artifact ownership.
This research aims to provide an example or illustration of how to apply a simple accounting system, namely Microsoft Excel in a fashion business that has just been started and has not used an application or system to do the recording. This research used a literature study method. The results of this study are expected for business beginners, especially fashion businesses, to understand how recording and bookkeeping in accounting are created using a simple accounting application. By displaying steps on how to make general journals, ledgers, adjustment entries, profit, and loss in Microsoft Excel. Therefore, it can be concluded that how important it is to make recording and bookkeeping using a simple application system method so that it can be easily applied by fashion business people who have just entered the business field.
Alexander C. Nwala, Alessandro Flammini, Filippo Menczer
Malicious actors exploit social media to inflate stock prices, sway elections, spread misinformation, and sow discord. To these ends, they employ tactics that include the use of inauthentic accounts and campaigns. Methods to detect these abuses currently rely on features specifically designed to target suspicious behaviors. However, the effectiveness of these methods decays as malicious behaviors evolve. To address this challenge, we propose a general language for modeling social media account behavior. Words in this language, called BLOC, consist of symbols drawn from distinct alphabets representing user actions and content. The language is highly flexible and can be applied to model a broad spectrum of legitimate and suspicious online behaviors without extensive fine-tuning. Using BLOC to represent the behaviors of Twitter accounts, we achieve performance comparable to or better than state-of-the-art methods in the detection of social bots and coordinated inauthentic behavior.
The issue of quantifying and characterizing various forms of social media manipulation and abuse has been at the forefront of the computational social science research community for over a decade. In this paper, I provide a (non-comprehensive) survey of research efforts aimed at estimating the prevalence of spam and false accounts on Twitter, as well as characterizing their use, activity, and behavior. I propose a taxonomy of spam and false accounts, enumerating known techniques used to create and detect them. Then, I summarize studies estimating the prevalence of spam and false accounts on Twitter. Finally, I report on research that illustrates how spam and false accounts are used for scams and frauds, stock market manipulation, political disinformation and deception, conspiracy amplification, coordinated influence, public health misinformation campaigns, radical propaganda and recruitment, and more. I will conclude with a set of recommendations aimed at charting the path forward to combat these problems.
Daniel Dalthorp, Manuela Huso, Mark Dalthorp
et al.
In estimating bird and bat mortality at wind turbines, it is essential to account for carcasses that lie outside the searched area. In this manuscript we explore some of the difficulties and nuances involved in the spatial prediction of the number of carcasses that lie outside the searched area and provide extensive guidance and documentation for a new R package (dwp) for modeling carcass density as a function of distance from a turbine and estimation of the fraction of carcasses lying within the searched area, which is a critical parameter in fatality estimation software such as GenEst, eoa, acmeR, and carcass.
Reproducibility is a key requirement for scientific progress. It allows the reproduction of the works of others, and, as a consequence, to fully trust the reported claims and results. In this work, we argue that, by facilitating reproducibility of recommender systems experimentation, we indirectly address the issues of accountability and transparency in recommender systems research from the perspectives of practitioners, designers, and engineers aiming to assess the capabilities of published research works. These issues have become increasingly prevalent in recent literature. Reasons for this include societal movements around intelligent systems and artificial intelligence striving towards fair and objective use of human behavioral data (as in Machine Learning, Information Retrieval, or Human-Computer Interaction). Society has grown to expect explanations and transparency standards regarding the underlying algorithms making automated decisions for and around us. This work surveys existing definitions of these concepts, and proposes a coherent terminology for recommender systems research, with the goal to connect reproducibility to accountability. We achieve this by introducing several guidelines and steps that lead to reproducible and, hence, accountable experimental workflows and research. We additionally analyze several instantiations of recommender system implementations available in the literature, and discuss the extent to which they fit in the introduced framework. With this work, we aim to shed light on this important problem, and facilitate progress in the field by increasing the accountability of research.
As the IoT becomes increasingly ubiquitous, concerns are being raised about how IoT systems are being built and deployed. Connected devices will generate vast quantities of data, which drive algorithmic systems and result in real-world consequences. Things will go wrong, and when they do, how do we identify what happened, why they happened, and who is responsible? Given the complexity of such systems, where do we even begin? This chapter outlines aspects of accountability as they relate to IoT, in the context of the increasingly interconnected and data-driven nature of such systems. Specifically, we argue the urgent need for mechanisms - legal, technical, and organisational - that facilitate the review of IoT systems. Such mechanisms work to support accountability, by enabling the relevant stakeholders to better understand, assess, interrogate and challenge the connected environments that increasingly pervade our world.