9,921 research outputs found

    Testing the nomological network for the Personal Engagement Model

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    The study of employee engagement has been a key focus of management for over three decades. The academic literature on engagement has generated multiple definitions but there are two primary models of engagement: the Personal Engagement Model of Kahn (1990), and the Work Engagement Model (WEM) of Schaufeli et al., (2002). While the former is cited by most authors as the seminal work on engagement, research has tended to focus on elements of the model and most theoretical work on engagement has predominantly used the WEM to consider the topic. The purpose of this study was to test all the elements of the nomological network of the PEM to determine whether the complete model of personal engagement is viable. This was done using data from a large, complex public sector workforce. Survey questions were designed to test each element of the PEM and administered to a sample of the workforce (n = 3,103). The scales were tested and refined using confirmatory factor analysis and then the model was tested determine the structure of the nomological network. This was validated and the generalisability of the final model was tested across different work and organisational types. The results showed that the PEM is viable but there were differences from what was originally proposed by Kahn (1990). Specifically, of the three psychological conditions deemed necessary for engagement to occur, meaningfulness, safety, and availability, only meaningfulness was found to contribute to employee engagement. The model demonstrated that employees experience meaningfulness through both the nature of the work that they do and the organisation within which they do their work. Finally, the findings were replicated across employees in different work types and different organisational types. This thesis makes five contributions to the engagement paradigm. It advances engagement theory by testing the PEM and showing that it is an adequate representation of engagement. A model for testing the causal mechanism for engagement has been articulated, demonstrating that meaningfulness in work is a primary mechanism for engagement. The research has shown the key aspects of the workplace in which employees experience meaningfulness, the nature of the work that they do and the organisation within which they do it. It has demonstrated that this is consistent across organisations and the type of work. Finally, it has developed a reliable measure of the different elements of the PEM which will support future research in this area

    A hybrid model using data mining and multi-criteria decision-making methods for landslide risk mapping at Golestan Province, Iran

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    The accurate modeling of landslide risk is essential pre-requisite for the development of reliable landslide control and mitigation strategies. However, landslide risk depends on the poorly known environmental and socio-economic factors for regional patterns of landslide occurrence probability and vulnerability, which constitute still a matter of research. Here, a hybrid model is described that couples data mining and multi-criteria decision-making methods for hazard and vulnerability mapping and presents its application to landslide risk assessment in Golestan Province, Northeastern Iran. To this end, landslide probability is mapped using three state-of-the-art machine learning (ML) algorithms—Maximum Entropy, Support Vector Machine and Genetic Algorithm for Rule Set Production—and combine the results with Fuzzy Analytical Hierarchy Process computations of vulnerability to obtain the landslide risk map. Based on obtained results, a discussion is presented on landslide probability as a function of the main relevant human-environmental conditioning factors in Golestan Province. In particular, from the response curves of the machine learning algorithms, it can be found that the probability p of landslide occurrence decreases nearly exponentially with the distance x to the next road, fault, or river. Specifically, the results indicated that p≈exp(−λx) where the length scale λ is about 0.0797 km−1 for road, 0.108 km−1 for fault, and 0.734 km−1 0.734 km−1 for river. Furthermore, according to the results, p follows, approximately, a lognormal function of elevation, while the equation p=p0−K(θ−θ0)2 fits well the dependence of landslide modeling on the slope-angle θ, with p0≈0.64,θ0≈25.6∘and|K|≈6.6×10−4. However, the highest predicted landslide risk levels in Golestan Province are located in the south and southwest areas surrounding Gorgan City, owing to the combined effect of dense local human occupation and strongly landslide-prone environmental conditions. Obtained results provide insights for quantitative modeling of landslide risk, as well as for priority planning in landslide risk management

    Targeting Fusion Proteins of HIV-1 and SARS-CoV-2

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    Viruses are disease-causing pathogenic agents that require host cells to replicate. Fusion of host and viral membranes is critical for the lifecycle of enveloped viruses. Studying viral fusion proteins can allow us to better understand how they shape immune responses and inform the design of therapeutics such as drugs, monoclonal antibodies, and vaccines. This thesis discusses two approaches to targeting two fusion proteins: Env from HIV-1 and S from SARS-CoV-2. The first chapter of this thesis is an introduction to viruses with a specific focus on HIV-1 CD4 mimetic drugs and antibodies against SARS-CoV-2. It discusses the architecture of these viruses and fusion proteins and how small molecules, peptides, and antibodies can target these proteins successfully to treat and prevent disease. In addition, a brief overview is included of the techniques involved in structural biology and how it has informed the study of viruses. For the interested reader, chapter 2 contains a review article that serves as a more in-depth introduction for both viruses as well as how the use of structural biology has informed the study of viral surface proteins and neutralizing antibody responses to them. The subsequent chapters provide a body of work divided into two parts. The first part in chapter 3 involves a study on conformational changes induced in the HIV-1 Env protein by CD4-mimemtic drugs using single particle cryo-EM. The second part encompassing chapters 4 and 5 includes two studies on antibodies isolated from convalescent COVID-19 donors. The former involves classification of antibody responses to the SARS-CoV-2 S receptor-binding domain (RBD). The latter discusses an anti-RBD antibody class that binds to a conserved epitope on the RBD and shows cross-binding and cross-neutralization to other coronaviruses in the sarbecovirus subgenus.</p

    How to Be a God

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    When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers. Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong. Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice. That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer. The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves? How should we be gods

    The extent and impact of intellectual capital research:a two decade analysis

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    Purpose: This paper examines the leading publication trends including the extent and impact of intellectual capital research in the Journal of Intellectual Capital (JIC) over a two-decade period (2000–2020). The bibliometric analysis offers the description of publications trends such as key authors, articles, cited references, institutions and countries— in other words the extent and impact in the field. This paper also presents the knowledge structure (including conceptual, intellectual and social structures) of JIC, that is prominent themes, co-citation and bibliographic networks. Design/methodology/approach: In order to achieve research objectives, we collected the bibliographic information of the articles published in JIC for the period 2000 to 2020 from the Scopus database on 11.04.2020. The bibliographic information of 737 documents were analysed using to open source analysis tool, that is bibliometrics package in r software and VOSviewer. These tools were used to create the graphical visualization of bibliographic data on basis of co-occurrence, co-citation and bibliographic coupling. Findings: The results show that the journal is progressing in terms of publication quantity and reputation in the field. To date, 737 documents have been published in JIC, which includes 659 research articles, eight editorials, seven notes and 63 review papers. This paper also portrays the author impact list in terms of most impactful articles published in JIC. Country-wise Italy, Australia, and USA exert maximum influence on JIC scholarship. Originality/value: Bibliographic analysis offers a comprehensive understanding of past trends and presents the future direction of a journal

    AIUCD 2022 - Proceedings

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    L’undicesima edizione del Convegno Nazionale dell’AIUCD-Associazione di Informatica Umanistica ha per titolo Culture digitali. Intersezioni: filosofia, arti, media. Nel titolo è presente, in maniera esplicita, la richiesta di una riflessione, metodologica e teorica, sull’interrelazione tra tecnologie digitali, scienze dell’informazione, discipline filosofiche, mondo delle arti e cultural studies

    SYSTEMS METHODS FOR ANALYSIS OF HETEROGENEOUS GLIOBLASTOMA DATASETS TOWARDS ELUCIDATION OF INTER-TUMOURAL RESISTANCE PATHWAYS AND NEW THERAPEUTIC TARGETS

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    In this PhD thesis is described an endeavour to compile litterature about Glioblastoma key molecular mechanisms into a directed network followin Disease Maps standards, analyse its topology and compare results with quantitative analysis of multi-omics datasets in order to investigate Glioblastoma resistance mechanisms. The work also integrated implementation of Data Management good practices and procedures

    Hunting Wildlife in the Tropics and Subtropics

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    The hunting of wild animals for their meat has been a crucial activity in the evolution of humans. It continues to be an essential source of food and a generator of income for millions of Indigenous and rural communities worldwide. Conservationists rightly fear that excessive hunting of many animal species will cause their demise, as has already happened throughout the Anthropocene. Many species of large mammals and birds have been decimated or annihilated due to overhunting by humans. If such pressures continue, many other species will meet the same fate. Equally, if the use of wildlife resources is to continue by those who depend on it, sustainable practices must be implemented. These communities need to remain or become custodians of the wildlife resources within their lands, for their own well-being as well as for biodiversity in general. This title is also available via Open Access on Cambridge Core

    Graphical scaffolding for the learning of data wrangling APIs

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    In order for students across the sciences to avail themselves of modern data streams, they must first know how to wrangle data: how to reshape ill-organised, tabular data into another format, and how to do this programmatically, in languages such as Python and R. Despite the cross-departmental demand and the ubiquity of data wrangling in analytical workflows, the research on how to optimise the instruction of it has been minimal. Although data wrangling as a programming domain presents distinctive challenges - characterised by on-the-fly syntax lookup and code example integration - it also presents opportunities. One such opportunity is how tabular data structures are easily visualised. To leverage the inherent visualisability of data wrangling, this dissertation evaluates three types of graphics that could be employed as scaffolding for novices: subgoal graphics, thumbnail graphics, and parameter graphics. Using a specially built e-learning platform, this dissertation documents a multi-institutional, randomised, and controlled experiment that investigates the pedagogical effects of these. Our results indicate that the graphics are well-received, that subgoal graphics boost the completion rate, and that thumbnail graphics improve navigability within a command menu. We also obtained several non-significant results, and indications that parameter graphics are counter-productive. We will discuss these findings in the context of general scaffolding dilemmas, and how they fit into a wider research programme on data wrangling instruction
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