Conceptual Model. 5.1 Point source waste discharges
5.2 Non-point sources of pollution
5.3 Parameters of concern 5.3.1 Environmental fate and pathway analysis
Conceptual Model. 5.1 Point source waste discharges
5.2 Non-point sources of pollution
5.3 Parameters of concern
5.3.1 Environmental fate and pathways analysis for parameters of concern
5.3.2 Bioaccumulation/biomagnification risk for parameters of concern 5.4 Receptors
5.4.1 Analysis and rationale for human receptors
5.4.2 Analysis and rationale for biological receptors
5.4.3 Analysis and rationale for ecological receptors
Conceptual Model. The AIXM Conceptual Model is the component of the AIXM data standard that provides a conceptual model of aeronautical data. It models the important features, properties (attributes and associations) and business rules that make up aeronautical information. As such, it can be used as the basis for the design of an AIM database. The model is designed using the Unified Modelling Language (UML).
Conceptual Model. ESAP, in and of itself, provides no compute or analysis capabilities (beyond a simple ability to view tabular data and preview images). Rather, it acts as a broker between users and the various query and analysis services which are available to them. These might include, for example: • bulk data query systems, which can help the user locate and access data files (images, visibility data, etc) in archives, data lakes, or similar bulk storage systems; • tabular data query systems, which can help the user find relevant entries in source catalogues and similar relational systems; • Interactive Data Analysis (XXX) systems, which provide the user compute and visualization tools in a convenient environment with access to relevant datasets (for example, a Jupyter [7] notebook, or con‐ tainerized analysis application); • bulk data processing systems, which provide batch (non‐interactive) processing of data at‐scale in HPC or HTC environments; • scientific software repositories, which provide access to specialist analysis tools and workflows; A given instance of ESAP is configured with information about available services1. When a user connects, the ESAP instance should: • help the user select services which are relevant to them (for example, by clearly presenting the available services; by making clear what science cases those services support, by taking account of the user’s access privileges, etc); • facilitate authentication and authorization with the various services, as necessary; • provide a consistent and convenient way for the user to access services (for example, by providing the user with a single way to enter a particular query, and then automatically translating that to the requirements of each individual service); • mediate data flow between services (for example, by enabling the user to locate data with an archive query, dispatch the data to the processing facility, and schedule processing of the data on a bulk data processing system). This relationship is illustrated schematically in Fig. 1: this shows the end user communicating directly with ESAP, which mediates their interactions with a range of other services, deployed across a variety of different infrastructures. Note that the user communicates with a single ESAP instance, while that instance mediates interactions with a range of different services from a variety of infrastructure providers.
Conceptual Model. A model (Figure 1) is tested that derived from a review of the literature by integrating theory and research relating to the organizational justice, commitment and their relationship to opportunistic behaviour by creating psychological contract between employer and employee. INDEPENDENT VARIABLES DEPENDENT VARIABLES AFFECTIVE NORMATIVE REDUCING OPPORTUNISTIC BEHAVIOUR CONINUOUS EMPLOYER EMPLOYEE
Conceptual Model. HRM policies and business performance
Hypothesis 1: The calculative HRM policy is positively related to firm performance.
Hypothesis 2: The collective sharing HRM policy is positively related to firm performance. Xxxx Xxxxxxx, Xxxx X.X Xxxxxxxx and Xxxx Xxxxx 83
Hypothesis 3: The collaborative HRM policy is positively related to firm performance.
Hypothesis 4: The positive relationship of a calculative HRM policy with firm performance is stronger for organizations that have a high collaborative HRM policy than for organizations that have a low collaborative HRM policy.
Conceptual Model. When transmitting Data to the Data Receiver, the following means/methods/tools shall be applied:
Conceptual Model. Description of the effects that stressors have on the ecological components in the environment and the relationship with assessment endpoints.
Conceptual Model. The conceptual model simulates general aspects of Port Valdez that can interact and pose a risk to the environment. These aspects covered by the model include: • Sub-Areas - designated subdivisions of the marine environment created for the purpose of comparison • Sources - anthropogenic operations or activities that release stressors • Habitats - environments supporting specific groups of receptor; • Impacts - changes to individuals, populations, or communities related to the assessment endpoints • Exposure and Effects-Links - connections between sources, habitats, and impacts that establish a risk. The first part of the conceptual model defines the sub-areas used for comparison within the Port (Section 5.1). The second part describes components of the model that were compared between the different sub-areas (Section 5.2 to 5.4). In this assessment, these components included sources, habitats, and impacts to assessment endpoints. Anthropogenic stressors originate from a source. Identifying the sources provides information on what types of stressors might be present in the environment. We have identified possible sources of anthropogenic stressors by reviewing scientific and monitoring reports, public comments, use patterns, and regulatory permits. The sources are described in Section
Conceptual Model. The present analysis was based on the CAM Healthcare Model20 which is a modification of Xxxxxxxx’x Behavioral Model for Health Services Use21, 22. According to the CAM Healthcare Model, CAM use is dictated by both “push” and “pull” related factors. Factors that may “push” an individual away from conventional care include dissatisfaction with conventional care and financial issues (e.g., cost of care, low income, lack of health insurance); factors that may “pull” an individual towards CAM may include personal values that prioritize self-care and positive beliefs about CAM being “natural.” These individual-level determinants of CAM use can be classified into three main categories: predisposing factors, enabling factors and need-based factors. According to the model, predisposing factors are those that influence whether an individual will use CAM. These factors are divided into demographic characteristics (e.g., gender, age and marital status), social structure (e.g., education), beliefs and values (e.g., satisfaction with conventional healthcare) and personal factors (e.g., perceived self- efficacy and perceived control over health/healthcare). Enabling factors (resources) are those that either facilitate or impede an individual’s use of CAM. For example, individuals must have the financial means (e.g., income and employment) and the “know- how” to access CAM (e.g., health literacy). Finally, need-based factors refer to an individual’s health status or illness state and are divided into perceived need factors and evaluated need factors. Perceived need factors are subjective assessments of health status (e.g., perceived symptom severity, self-reported quality of life, etc.); evaluated need factors include those that are based on objective assessments of disease status (e.g., date of diagnosis, number of doctor’s office visits, etc.). Using these categories, the model aims to identify factors associated with CAM use and enhance understanding of factors that predict CAM use20. Though the present study examined whether these individual-level determinants predicted CAM use, it is important to note that the model also accounts for the potential impact of social and system-based factors on CAM use such as changes in the availability of CAM therapies in conventional healthcare settings, availability of CAM-related training in schools of medicine, nursing, pharmacy and public health and health insurance reimbursement policies for CAM therapy utilization.
