This research examined the suitability of the biotic ligand model (BLM) approach for assessing environmental risk in surface waters consisting substantially of treated sewage effluent, and the implications of its use within a compliance-based regulatory framework aimed at controlling discharges of metals into the aquatic environment. The results from a series of Daphnia magna acute copper toxicity assays conducted in an undiluted sewage effluent medium demonstrated that BLMs could predict an acute copper toxicity endpoint with suitable accuracy. This finding contributes further support for the use of BLMs for assessing risk and compliance, even in effluent impacted waters. Additional studies, however, also demonstrated that effluent derived organic matter contained a greater concentration of metal complexing ligands per milligram of dissolved organic carbon than organic matter derived from natural sources. This indicates that effluent derived organic matter offers greater protection against the potentially adverse effects from metals than the protection offered by organic matter derived from natural sources. These studies also demonstrated that improvements in the accuracy of BLM forecasts were achievable by taking these differences into account which, from a regulatory perspective, is also desirable since this enhances the environmental relevance of compliance criteria. These findings therefore justify that consideration for the influence of site-specific metal complexation characteristics should included as part of the regulatory framework within which BLMs will be applied. The implication of the BLM approach for Severn Trent Water Limited is that, as currently proposed, the approach will require a reduction in the concentration of copper in the effluent discharges for a small number of wastewater treatment works (9), whereas for zinc, concentration reductions may be required for numerous treatment works (126).

This research evaluates how contextual variables such as knowledge of the rules, the perception about punishment and formal enforcement levels, perception of social control, fishers’ attitudes about legitimacy of rules, and social/economic factors, affect compliance with fisheries regulations. The analysis is carried out in Old Providence Island [OPI]. A survey of 100 fishermen was completed and data from that survey is used to econometrically estimate a model of compliance choices. Results suggest that reports on compliance change depending whether the interviewed is asked about compliance or about violation. I argue that this seemingly inconsistency, reveals an implication on methodological approach. Contrary to the main literature on compliance behavior, in this research deterrence variables were not statistically significant in the econometric estimations. This result may be because sanctions and fines are not clearly established, reflecting the existence of structural problems in enforcement activities in the island. The results indicate that fishers adjust their violation with respect to other fishers’ behavior, and the knowledge about regulations. The probability of being a violator is higher for divers, and this fact is recognized by the fishers themselves.

<p>FDA has long served as the front safeguard to the U.S. citizen public health, is also perceived as one of the world-leading drug regulators. Despite the tremendous efforts and progress have been made to promote the public health, FDA was criticized for putting the agency’s trust icon at stake and was questioned of its ability to serve the agency’s ultimate mission to protect the public. In the wake of the arousing concerns, FDA sought the transformation the oversight model of the medicinal products. One of the actions is to launch quality metrics program. However, this program has been unanimously opposed by the industry. Instead of the current conventional approach, which is constrained by the high dependence on industry cooperation, we try to explore</p><p>the measurement of company and product quality risk with public domain data, try to help in visualizing quality and risk. To that end, we develop conceptual frameworks for both company and product quality, examine some of the factors (education, local authority intensity, historical inspection results, physiochemical, physiological, formulation factors, etc.), further developed a warning letter and product recall prediction model with machine learning method referenced to the data analysis outcome.</p>

[pt] Um grande desafio na pesquisa de sistemas multiagentes (SMA) é a concepção e implementação de SMA abertos em que normas podem ser eficazmente aplicadas aos seus agentes e facilmente gerenciadas. Estas tarefas são árduas porque normas são usualmente escritas para propósitos gerais, dificultando uma regulação mais precisa. A motivação para esta pesquisa surgiu diante da necessidade de resolver este desafio, proporcionando uma abordagem aplicável em sistemas abertos. Nesses sistemas, heterogeneidade e autonomia excluem qualquer hipótese relativa à forma com que entidades de terceiros são implementadas e como se comportam. Assim, uma solução viável para regulação em SMA abertos não deve ser rigidamente codificada dentro das implementações originais de agentes e deve permitir, a um certo grau de precisão e flexibilidade, atualizar dados (e.g., normas) durante a execução do sistema. Nesta tese, nossa abordagem DynaCROM para lidar com normas em SMA abertos é apresentada. Da perspectiva individual de agentes, DynaCROM é um mecanismo informativo que torna agentes da aplicação cientes das normas as quais eles estão vinculados em um determinado momento. Da perspectiva de desenvolvedores do sistema, DynaCROM é uma metodologia para aplicação e gerenciamento de normas em SMA abertos de tal modo que desenvolvedores sejam capazes de incorporar em normas abstratas valores de domínio. Portanto, normas são contextualizadas no domínio de aplicação onde elas são válidas, facilitando regulação. Considerando que um SMA regulado deve ter suas normas respeitadas, apresentamos também a integração de DynaCROM com dois mecanismos distintos de cumprimento de normas. Em resumo, o resultado dessa tese é nossa abordagem DynaCROM que operacionaliza normas regulativas em SMA. / [en] A major challenge in the research of multiagent systems (MAS) is the design and implementation of open MAS in which norms can be effectively applied to their agents and easily managed. These tasks are arduous because norms are usually written for general purposes, hindering a more precise regulation. The motivation for this research came forth from the need to resolve this challenge, providing an approach applicable in open systems. In such systems, heterogeneity and autonomy rule out any assumption concerning the way third-party entities are implemented and behaved. A viable solution for regulation in open MAS should not be hard coded inside agents` original implementations and must allow, for some degree of precision and flexibility, to update data (e.g., norms) during the system execution. In this thesis, our DynaCROM approach for dealing with norms in open MAS is presented. From the individual agents perspective, Dyna- CROM is an information mechanism that makes application agents aware of the norms they are bound to at a given moment. From the system developers perspective, DynaCROM is a methodology for the application and management of norms in open MAS so developers are able to embody abstract norms with domain values. Therefore, norms are contextualized in the application domain wherein they hold, facilitating regulation. Considering that a regulated MAS should have its norms enforced, the integration of DynaCROM with two distinct enforcement mechanisms is also presented. In summary, the result of this thesis is our DynaCROM approach, which operationalizes regulative norms in MAS.

This dissertation examined recently issued regulatory standards using cheese and produce as model systems. FDA's 2015 Domestic and Imported Cheese and Cheese Products Compliance Program Guidelines (CPG) E. coli standards on cheese safety, and the extent to which these standards affect domestic and imported cheese commerce, was assessed. Results from FDA's Domestic and Imported Cheese Compliance Program for samples collected between January 1, 2004 and December 31, 2006 were analyzed. Of 3,007 cheese samples tested for non-toxigenic E. coli, 76% (2,300) of samples exceeded 10/g, FDA's target for regulatory activity. In cheese samples containing E. coli levels of 10/g and 100/g, there was no statistically significant association with presence of Listeria monocytogenes. However, associations between Staphylococcus aureus levels of 10,000 CFU/g and presence of Salmonella and L. monocytogenes were statistically significant, indicating that EU regulations targeting S. aureus as the pathogen of concern may be more appropriate than E. coli for cheese safety assessment. Compost amended soils in the Northeastern U.S. were assessed for the presence and survival of E. coli and Listeria spp. against FDA Food Safety Modernization Act (FSMA) requirements. Manure and poultry litter-based biological soil amendments of animal origin (BSAAO) must achieve pathogen reduction to reduce risk of pathogen contamination on the harvested produce. Two trials of replicated field plots of loamy (L) or sandy (S) soils were tilled and un-amended (NC) or amended with dairy compost (DC), poultry litter compost (PL), or poultry pellets (PP). Colony count and most probable number (MPN) methods were used to determine persistence of E. coli in these plots over 104 days post-inoculation. Detection of indigenous Listeria spp. were also examined in all plots. Higher E. coli populations were observed in PL and PP amended soils when compared to DC and NC plots. E. coli was detected at low levels on radish crops, where PL treatments encouraged greater levels of survival and growth than DC or NC. Study results verify that a 120 day interval following BSAAO application should be sufficient to ensure food safety of edible crops subsequently planted on these soils. The sensitivity of environmental monitoring methods and collection formats were evaluated to identify optimal procedures for detection of Listeria spp. on product contact surfaces within artisan cheese production environments. Four environmental surfaces (dairy brick, stainless steel, plastic, and wood; n=405/surface type) were inoculated with L. innocua, L.m. ATTC® 19115 and L.m. 1042, at high (106-107/cm2) and low (0.1-1/cm2) target concentrations. Inoculated surfaces were swabbed with World Bioproducts© EZ ReachTM and 3MTM environmental swabs (3MTM). Five enrichment and enumeration methods were used to compare sensitivity of recovery between environmental swabs. All swab formats performed equally on all environmental surfaces at high target concentrations. At low concentrations, PetrifilmTM and WBEZ swabs recovered Listeria spp. from 87.5% of plastic, stainless steel, and dairy brick surfaces, but only 62.7% of wooden surfaces; recovering 14.8%, 77%, and 96.3% of cells from initial inoculations of 0.01, 0.1, and 1/cm2, respectively . Our data demonstrate that results may be discrepant due to variation in the porosity of environmental surfaces and should be taken into consideration when implementing environmental sampling plans. Results from this thesis can be used to inform regulatory policy and help to achieve improved food safety.

<p><strong>Background</strong></p><p>International transfer pricing has been a highlighted issue during the last decades as country after country has revised and introduced new transfer pricing laws as a respond to the expanded globalization. Several countries are adopting similar approaches and the prime guiding principles are provided by the Organization for Economic Co-Operation (OECD). The international law as well as the laws of all 30 member countries is based on the OECD Guidelines.</p><p><strong>Purpose</strong></p><p>The purpose of this master’s thesis is to describe differences and similarities regarding the transfer pricing regulations in China and Sweden and to explain how a Swedish multinational enterprise (MNE) have to utilize and adjust their transfer pricing strategy when trading with group companies in China. The results then conclude into a step model for strategic transfer pricing.</p><p><strong>Result</strong></p><p>The differences between the regulations are mainly uncovered in the definition of associated parties and associated interest. The differences in the regulations are thus of minor importance and does not affect a Swedish MNE to any major extent. The challenging area is instead the conflict between the tax authority and the customs service. To enable this study, three Swedish MNEs are used as a case study. We discovered that all had very different transfer pricing strategies even though they are within the same industry and two of them even within same range of products. Out of this we made the conclusion that the strategy chosen is not just depending on what product or service you trade with but also the aim and purpose, the range of products and the structure of the company. International transfer pricing is a very complex issue that goes into nearly all business operations. The concept of transfer pricing can thus be broken down and simplified if the demands from the company is minor.</p>

Background International transfer pricing has been a highlighted issue during the last decades as country after country has revised and introduced new transfer pricing laws as a respond to the expanded globalization. Several countries are adopting similar approaches and the prime guiding principles are provided by the Organization for Economic Co-Operation (OECD). The international law as well as the laws of all 30 member countries is based on the OECD Guidelines. Purpose The purpose of this master’s thesis is to describe differences and similarities regarding the transfer pricing regulations in China and Sweden and to explain how a Swedish multinational enterprise (MNE) have to utilize and adjust their transfer pricing strategy when trading with group companies in China. The results then conclude into a step model for strategic transfer pricing. Result The differences between the regulations are mainly uncovered in the definition of associated parties and associated interest. The differences in the regulations are thus of minor importance and does not affect a Swedish MNE to any major extent. The challenging area is instead the conflict between the tax authority and the customs service. To enable this study, three Swedish MNEs are used as a case study. We discovered that all had very different transfer pricing strategies even though they are within the same industry and two of them even within same range of products. Out of this we made the conclusion that the strategy chosen is not just depending on what product or service you trade with but also the aim and purpose, the range of products and the structure of the company. International transfer pricing is a very complex issue that goes into nearly all business operations. The concept of transfer pricing can thus be broken down and simplified if the demands from the company is minor.

Unlike hardware, software does not degrade over time or frequency use. This is good for software. Also unlike hardware, software can be easily changed. This unique characteristic gives software much of its power, but is also responsible for possible failures in software applications. When software is used within medical devices, software failures may result in bodily injury or death. As a result, regulations have been imposed on the makers of medical devices to ensure their safety, which includes the safety of the devices’ software. The U.S. Food and Drug Administration requires establishment of systems and control processes to ensure quality devices. A principal part of the quality assurance effort is testing. This paper explores the unique role of software testing in the design, development, and release of software used for medical devices and applications. It also provides practical, industry-driven guidance on medical device software testing techniques and strategies. / text

The purpose of this research is to support the California Department of Food & Agriculture (CDFA) with education and outreach about recent changes regarding antimicrobial use in livestock, and to enhance their emergency communications network. This was done by characterizing a population of small-scale livestock owners underserved with regards to educational outreach about animal health issues, such as antimicrobial use rules. The project also seeks to enhance public understanding of the importance of responsible antimicrobial use in animal and human health. To accomplish this, the study used a survey administered in person at local farm supply stores and online to investigate the level of understanding of antimicrobial rules among livestock owners in San Luis Obispo county. The survey gathered information about the livestock owners’ practices, connection to livestock groups, and access to information pertaining to animal health among other things. The results of the survey showed that respondents were largely unaware of new rules pertaining to use of antimicrobials in livestock. Familiarity with California rules of this kind was used as an indicator of access to information about animal health and was found to correlate positively with knowledge about antimicrobial resistance and familiarity with federal rules concerning antimicrobial use in livestock. As predicted, respondents with a connection to 4-H and FFA had greater familiarity with both federal and state rules concerning antimicrobial use in livestock.

The presented study investigates the role of Machine Learning in Regulatory Compliance software systems by conducting a case study in the maritime industry. There is a need to obtain a clear understanding of Machine Learning approaches for automating regulatory compliance.  Background: Organizations and software developers face different regulations in different domains that need to be satisfied by the requirements of systems. Trading across borders brings challenges in managing each country's regulatory requirements. Even though a large amount of effort from international and local organizations, an efficient AI-based system is not yet fully deployed for offering decision support in handling such complex issues as a viable solution. The increasing enforcement of sanctions and anti-money laundering by various institutions and countries poses a significant threat to many industries worldwide if they are not educated or aware of the legal and financial risks. therefore, Regulatory Compliance plays a critical role in this area. Regulatory Compliance is a guideline for laws or regulations related to the business that the stakeholders must abide by to promote a safer business environment and benefit society. Developing a Digital Compliance(DigiComp) system as a software service is a solution that involves both technical and organizational challenges which need a large amount of research. As a case study, an AI-based DigiComp system has been implemented in the port of Vordingborg for the EU-financed project "Connect2SmallPorts". A major Corporate challenge was the choice of appropriate and efficient approaches and tools for designing the automated regulatory compliance system. This study investigates the role of Machine Learning in regulatory compliance systems and its possible opportunities and limitations.  Objectives: The significant role of compliance management made it an interesting research topic since some highly regulated systems need to follow specific laws and guidelines. As the objectives of this study, the role of machine learning on regulatory compliance systems has been investigated by extracting the most popular ML approaches and their benefits and challenges from previous studies and then analyzing the related benefits and limitations in a real-world case. Methods: We have done a systematic literature review as the qualitative research method with database search and snowballing to collect the applied Machine Learning approaches and their benefits and challenges for Regulatory Compliance software systems. Then a case study was conducted for implementing a regulatory compliance system in the maritime industry and investigating the benefits and challenges in a real-world project. Also, Focus groups and interviews with the stakeholder and domain experts were held as data collection methods during the case study.  Results: After investigating the existing challenges in regulatory compliance and identifying the risk assessment framework based on Machine Learning as the most popular AI approach in this area, we implemented a risk assessment framework based on neural networks. It provides high accuracy and a low error rate in predicting the future state to prevent the non-compliance risk. Conclusions: Examining the proposed digital compliance system explores its similarity to the benefits and limitations extracted from SLR. This study has provided the development of a new AI-Based system that can inspire software companies to build more efficient regulatory compliance systems for different domains in the industry.