Machine Learning and Survey-based Predictors of InfoSec Non-Compliance

Survey items developed in behavioral Information Security (InfoSec) research should be practically useful in identifying individuals who are likely to create risk by failing to comply with InfoSec guidance. The literature shows that attitudes, beliefs, and perceptions drive compliance behavior and has influenced the creation of a multitude of training programs focused on improving ones’ InfoSec behaviors. While automated controls and directly observable technical indicators are generally preferred by InfoSec practitioners, difficult-to-monitor user actions can still compromise the effectiveness of automatic controls. For example, despite prohibition, doubtful or skeptical employees often increase organizational risk by using the same password to authenticate corporate and external services. Analysis of network traffic or device configurations is unlikely to provide evidence of these vulnerabilities but responses to well-designed surveys might. Guided by the relatively new IPAM model, this study administered 96 survey items from the Behavioral InfoSec literature, across three separate points in time, to 217 respondents. Using systematic feature selection techniques, manageable subsets of 29, 20, and 15 items were identified and tested as predictors of non-compliance with security policy. The feature selection process validates IPAM's innovation in using nuanced self-efficacy and planning items across multiple time frames. Prediction models were trained using several ML algorithms. Practically useful levels of prediction accuracy were achieved with, for example, ensemble tree models identifying 69% of the riskiest individuals within the top 25% of the sample. The findings indicate the usefulness of psychometric items from the behavioral InfoSec in guiding training programs and other cybersecurity control activities and demonstrate that they are promising as additional inputs to AI models that monitor networks for security events.

Identifying Non-Technical Skill Gaps in Software Engineering Education: What Experts Expect But Students Don’t Learn

As the importance of non-technical skills in the software engineering industry increases, the skill sets of graduates match less and less with industry expectations. A growing body of research exists that attempts to identify this skill gap. However, only few so far explicitly compare opinions of the industry with what is currently being taught in academia. By aggregating data from three previous works, we identify the three biggest non-technical skill gaps between industry and academia for the field of software engineering: devoting oneself to continuous learning , being creative by approaching a problem from different angles , and thinking in a solution-oriented way by favoring outcome over ego . Eight follow-up interviews were conducted to further explore how the industry perceives these skill gaps, yielding 26 sub-themes grouped into six bigger themes: stimulating continuous learning , stimulating creativity , creative techniques , addressing the gap in education , skill requirements in industry , and the industry selection process . With this work, we hope to inspire educators to give the necessary attention to the uncovered skills, further mitigating the gap between the industry and the academic world.

Essential oils of Cordia species, compounds and applications: a systematic review

The purpose of this systematic review was to identify the available literature on the essential oil from species of genus Cordia. This study followed the Preferred Reporting Items for Systematic Reviews. The search was conducted on four databases: LILACS, PubMed, Science Direct, and Scopus until June 5th, 2020, with no time or language restrictions. Sixty out of the 1,333 initially gathered studies fit the inclusion criteria after the selection process. Nine species of Cordiawere reported in the selected studies, out of which 79% of the evaluated studies reported essential oil from Cordia curassavica. The essential oil extraction methods identified were hydrodistillation and steam distillation. As for biological application, antimicrobial, anti-inflammatory, larvicidal and antioxidant activities were the most reported. The main compounds reported for essential oil were β-caryophyllene, α-humulene, α-pinene, bicyclogermacrene, and sabinene. The information reported in this systematic review can contribute scientifically to the recognition of the importance of the genus Cordia.

RECRUITMENT APP – A CUSTOM APPLICATION ON SALESFORCE.COM

Cloud Computing is one of the upcoming Internet based technology. It is been considered as the next generation computing model for its advantages. It is the latest computational model after distributed computing, parallel processing and grid computing. To be effective they need to tap all available sources of supply, both internal and external. The system has facilities where prospective candidates can upload their CV’s and other academic achievements. Earlier recruitment was done manually and it was all at a time-consuming work. Now it is all possible in a fraction of second. Better recruitment and selection strategies result in improved organizational outcomes. With reference to this context, the research paper entitled Recruitment and Selection has been prepared to put a light on Recruitment and Selection process.

A Descriptive Analysis on Effect of Corporate Governance on Investor’s Decision

Purpose: The article studies the impact of internal factors and external factors influencing an investor’s investment decision. Design/Methodology: The information for the study was obtained from secondary sources like journal papers, magazines and books. Findings: Human psychology has an internal role in investing choice, whereas corporate governance is an external influence. Corporate governance plays a major role in the investment decision-making process by revealing all elements of business information, but investors understand the information according to their own assessments and assumptions based on their psychology. As a result, a firm’s transparency hardly impacts in investment decisions, and it only works to a limited extent; the rest of the investment selection process is dominated by human behaviour. However, the firm is transparent, there is no guarantee that the investor will always act rationally when making a choice for investment. Originality/Value: Every investor should make rational decisions about their investments. Therefore, it is an investor’s responsibility to follow the information provided by the firm, although some investors fail to do so. As a result of investor psychology, investors’ investment decisions are beyond the reach of business transparency. The study implies that a behavioural survey will be useful in determining the factor influencing investors’ investing decisions. Type of Paper: Conceptual Paper

Can I show my skills? Affective responses to artificial intelligence in the recruitment process

Companies increasingly use artificial intelligence (AI) and algorithmic decision-making (ADM) for their recruitment and selection process for cost and efficiency reasons. However, there are concerns about the applicant’s affective response to AI systems in recruitment, and knowledge about the affective responses to the selection process is still limited, especially when AI supports different selection process stages (i.e., preselection, telephone interview, and video interview). Drawing on the affective response model, we propose that affective responses (i.e., opportunity to perform, emotional creepiness) mediate the relationships between an increasing AI-based selection process and organizational attractiveness. In particular, by using a scenario-based between-subject design with German employees (N = 160), we investigate whether and how AI-support during a complete recruitment process diminishes the opportunity to perform and increases emotional creepiness during the process. Moreover, we examine the influence of opportunity to perform and emotional creepiness on organizational attractiveness. We found that AI-support at later stages of the selection process (i.e., telephone and video interview) decreased the opportunity to perform and increased emotional creepiness. In turn, the opportunity to perform and emotional creepiness mediated the association of AI-support in telephone/video interviews on organizational attractiveness. However, we did not find negative affective responses to AI-support earlier stage of the selection process (i.e., during preselection). As we offer evidence for possible adverse reactions to the usage of AI in selection processes, this study provides important practical and theoretical implications.

Single-cell analysis reveals selection of TP53-mutated clones after MDM2 inhibition

The mechanisms of transformation of chronic myeloproliferative neoplasms (MPN) to leukemia are largely unknown but TP53mutations acquisition is considered a key event in this process. P53 is a main tumor suppressor but mutations in this protein per se do not confer a proliferative advantage to the cells and a selection process is needed for the expansion of mutant clones. MDM2 inhibitors may rescue normal p53 from degradation and have been evaluated in a variety of cancers with promising results. However the impact of these drugs on TP53 mutated cells is underexplored. We report herein evidence of a direct effect of MDM2 inhibition on the selection of MPN patients' cells harboring TP53 mutations. To decipher whether these mutations can arise in a specific molecular context we used a DNA single cell approach to determine the clonal architecture of TP53 mutated cells. We observed that TP53 mutations are late events in MPN mainly occurring in the driver clone while clonal evolution frequently consists of sequential branching instead of linear consecutive acquisition of mutations in the same clone. At the single cell level the presence of additional mutations does not influence the selection of TP53 mutant cells by MDM2 inhibitor treatment. Also, we describe an in vitro test allowing to predict the emergence of TP53 mutated clones. Altogether, this is the first demonstration that a drug treatment can directly favor the emergence of TP53-mutated subclones in MPN.

A Scoping Review of Indicators for Sustainable Healthy Diets

Introduction: Diets are currently unsustainable in many countries as evidenced by the growing burden of malnutrition, degradation of natural resources, contributions to climate change, and unaffordability of healthy diets. Agreement on what constitutes a healthy and sustainable diet has been debated. In 2019, FAO and WHO published the Sustainable Healthy Diets Guiding Principles, defining what qualifies as a sustainable healthy diet. While valuable, these principles require measurable indicators to support their operationalization. Our scoping review aims to describe how sustainable healthy diets have been assessed in the literature since 2010.Methods: A search for English-language articles published in peer-reviewed journals was conducted from January 2010 through February 2020 across three databases. Out of the 504 articles initially identified, 103 articles were included. Metadata were extracted from each article on: publication year, country of study, study aims, methods, main data sources, indicators used to assess sustainable healthy diets, reported indicator strengths or limitations, and main study findings. A qualitative content analysis identified major conceptual themes across indicators and their frequency of use.Findings: From the 103 empirical articles included in our review, 57.3% were published after 2017. Most studies were carried out in high-income countries (74%). Approximately 42% of the articles assessed the sustainability of diets using solely health and environmental indicators; <25% assessed the sustainability of diets across health, environmental, and sociocultural aspects of sustainability. We found a substantial number of unique indicators used for assessing health (n = 82), environmental (n = 117), and sociocultural (n = 43) aspects of diets. These indicators covered concepts related to health outcomes, aspects of diet quality, natural resources, climate change, cultural acceptability, and cost of diets. The preponderance of indicators currently used in research likely poses challenges for stakeholders to identify the most appropriate measures.Conclusion: Robust indicators for sustainable healthy diets are critical for understanding trends, setting targets, and monitoring progress across national and sub-national levels. Our review highlights the geographical imbalance, the narrow focus on health and environmental aspects, and the lack of common measures used in research. Measures registries could provide the decision-support needed by stakeholders to aid in the indicator selection process.