Auditor Performance Within Moderasi Compliance and the Influence of Audit Structure, Good Governance, and Organizational Culture

The purpose of this study is to investigate the role of audit structure, Good Governance, and organizational culture in influencing the performance of auditors on the Audit Board of the Republic of Indonesia (BPK RI). This quantitative research employs a survey conducted on auditors of government agencies in six regions of Indonesia, and the survey tool employs questionnaires, which are delivered to 320 persons and returned by all of them. Partial Lease Square Analysis Using the Structural Equation Model (SEM) (PLS). According to the findings, the Audit Structure, excellent governance, and corporate culture all have a favorable impact on auditor performance. Compliance moderation in the relationship Audit structure, good governance does not strengthen or weaken the relationship Audit structure, good governance to auditor performance in the variable of compliance moderation. Meanwhile, compliance moderation appears to be capable of strengthening the link between organizational culture and auditor performance. The study's findings are valuable for auditors and researchers in understanding the elements that affect auditor performance as well as the effect of compliance moderation on auditor performance within the Auditor of the Audit Board of the Republic of Indonesia (BPK RI)

Biogeographic survey of soil bacterial communities across Antarctica

Background: Antarctica and its unique biodiversity are increasingly at risk from the effects of global climate change and other human influences. A significant recent element underpinning strategies for Antarctic conservation has been the development of a system of Antarctic Conservation Biogeographic Regions (ACBRs). The datasets supporting this classification are, however, dominated by eukaryotic taxa, with contributions from the bacterial domain restricted to Actinomycetota and Cyanobacteriota. Nevertheless, the ice-free areas of the Antarctic continent and the sub-Antarctic islands are dominated in terms of diversity by bacteria. Our study aims to generate a comprehensive phylogenetic dataset of Antarctic bacteria with wide geographical coverage on the continent and sub-Antarctic islands, to investigate whether bacterial diversity and distribution is reflected in the current ACBRs. Results: Soil bacterial diversity and community composition did not fully conform with the ACBR classification. Although 19% of the variability was explained by this classification, the largest differences in bacterial community composition were between the broader continental and maritime Antarctic regions, where a degree of structural overlapping within continental and maritime bacterial communities was apparent, not fully reflecting the division into separate ACBRs. Strong divergence in soil bacterial community composition was also apparent between the Antarctic/sub-Antarctic islands and the Antarctic mainland. Bacterial communities were partially shaped by bioclimatic conditions, with 28% of dominant genera showing habitat preferences connected to at least one of the bioclimatic variables included in our analyses. These genera were also reported as indicator taxa for the ACBRs. Conclusions: Overall, our data indicate that the current ACBR subdivision of the Antarctic continent does not fully reflect bacterial distribution and diversity in Antarctica. We observed considerable overlap in the structure of soil bacterial communities within the maritime Antarctic region and within the continental Antarctic region. Our results also suggest that bacterial communities might be impacted by regional climatic and other environmental changes. The dataset developed in this study provides a comprehensive baseline that will provide a valuable tool for biodiversity conservation efforts on the continent. Further studies are clearly required, and we emphasize the need for more extensive campaigns to systematically sample and characterize Antarctic and sub-Antarctic soil microbial communities. APsmQ8MphSAgg4BzZyqdNTVideo Abstrac

Bootstrap confidence intervals for three-way component methods

The two most common component methods for the analysis of three-way data, CANDECOMP/PARAFAC (CP) and Tucker3 analysis, are used to summarize a three-mode three-way data set by means of a number of component matrices, and, in case of Tucker3, a core array, Until recently, no procedures for computing confidence intervals for the results from such analyses were available. Recently, such procedures have come available by Riu and Bro (2003) for CP using the jack-knife procedure, and by Kiers (2004) for CP and Tucker3 analysis using the bootstrap procedure. The present paper reviews the latter procedures, discusses their performance as reported by Kiers (2004), and illustrates them on an example data set