Henri Fayol, accounting and control: An environmental reflection

Henry Fayol (1841-1925) was a leading administrator in the French mining and metallurgy industry. After studying at the Lycee at Lyons and the Ecole Nationale Des Mines de Saint Etienne, he was appointed engineer of the Commentry pits of the S.A. Commentry-Fourchambault combine in 1860. By 1888 he had risen to the managing directorship of that company, retiring as chief executive in 1918 but remaining as a director. During his lifetime he was awarded a number of prizes and honors.1 In 1916 he published his now famous Administration Industrielle et Generale-Prevoyance, Organisation, Commandement, Coordination, Controle, in the Bulletin de la Societe de l\u27Industrie Minerale.2 Fayol attempted to develop a teachable theory of general management via a comprehensive set of principles. This theory was intended to demonstrate the benefits of adopting a scientific approach to the management of large organizations and represented the first attempt to outline a general theory of administration

Accounting History Research Methodology Committee: Committee report

I have pleasure in presenting this report on the committee\u27s activities for the year ended August 1986. The development of a comprehensive bibliography of historical research methodology sources continues on schedule

Explorations in Historical Method

In 1985 The Academy of Accounting Historians established a new committee named The Accounting History Research Methodology (AHRM) Committee. The Academy specified the objectives of the Committee as identifying the range of historical research methods and facilitating accounting historians\u27 access to literature on historical methodology in general. More broadly, its role was envisaged as one of encouraging a greater awareness and use of historical method in accounting history research

Heme metabolism genes Downregulated in COPD Cachexia.

IntroductionCachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers.MethodsWe analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss > 5% in the past 12 months or low body mass index (BMI) (< 20 kg/m2) and 1/3 criteria: decreased muscle strength (six-minute walk distance < 350 m), anemia (hemoglobin < 12 g/dl), and low fat-free mass index (FFMI) (< 15 kg/m2 among women and < 17 kg/m2 among men) in COPDGene. In ECLIPSE, cachexia was defined as weight-loss > 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (> 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB.ResultsThe prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR < 0.05) and ECLIPSE (FDR < 0.05).DiscussionSeveral replicated genes regulating heme metabolism were downregulated among participants with COPD cachexia. Impaired heme biosynthesis may contribute to cachexia development through free-iron buildup and oxidative tissue damage

Large carnivore science: non-experimental studies are useful, but experiments are better

1. Response to Bruskotter and colleagues We recently described the following six interrelated issues that justify questioning some of the discourse about the reliability of the literature on the ecological roles of large carnivores (Allen et al., in press): 1. The overall paucity of available data, 2. The reliability of carnivore population sampling techniques, 3. The general disregard for alternative hypotheses to top-down forcing, 4. The lack of applied science studies, 5. The frequent use of logical fallacies, 6. The generalisation of results from relatively pristine systems to those substantially altered by humans. We thank Bruskotter et al. (2017) for responding to our concerns and engaging with this important issue. We agree completely that nonexperimental studies can and do often have great value, and we recognize that in many (most) cases these types of studies may provide the only data that are available. We acknowledge the many challenges of working on large, cryptic, dangerous, and highly-mobile animals in the wild. However, the absence of more robust data and the reality of these challenges do not excuse weak inference or overstating conclusions – a practice apparent in many studies (and communication of those studies) adopting only observational or correlative methods to infer the roles of large carnivores (reviewed in Allen et al., in press)

A comparative analysis of algorithms for somatic SNV detection in cancer

Motivation: With the advent of relatively affordable high-throughput technologies, DNA sequencing of cancers is now common practice in cancer research projects and will be increasingly used in clinical practice to inform diagnosis and treatment. Somatic (cancer-only) single nucleotide variants (SNVs) are the simplest class of mutation, yet their identification in DNA sequencing data is confounded by germline polymorphisms, tumour heterogeneity and sequencing and analysis errors. Four recently published algorithms for the detection of somatic SNV sites in matched cancer–normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer–normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterized and compared to investigate the strengths and weaknesses of each SNV calling algorithm. Results: Comparing the candidate SNV sets returned by VarScan, SomaticSniper, JointSNVMix2 and Strelka revealed substantial differences with respect to the number and character of sites returned; the somatic probability scores assigned to the same sites; their susceptibility to various sources of noise; and their sensitivities to low-allelic-fraction candidates.Nicola D. Roberts, R. Daniel Kortschak, Wendy T. Parker, Andreas W. Schreiber, Susan Branford, Hamish S. Scott, Garique Glonek and David L. Adelso