4,665 research outputs found

    Learning Mechanisms to Predispose Risky Alcohol Drinking Behaviors During Young Adulthood

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    Alcohol use disorder (AUD) is a mental disorder that negatively affects personal health and burdens the global health system. Alcohol-attributed harms can also extend beyond the drinkers to other people in the society through increased road traffic accidents and more interpersonal violent behaviors. The effects of this disorder make it crucial to investigate predisposing mechanisms in order to identify at-risk individuals and further develop novel interventions. Although aberrant learning and dysfunctions in decision-making have been observed in individuals with AUD, it is not yet clear whether they predispose the development of risky drinking behaviors or result from repetitive alcohol use. To disentangle this, we studied the drinking behaviors of a community sample comprising participants who were 18–24, which is when the prevalence of alcohol use typically peaks. This thesis investigates whether two types of learning mechanisms—the balance between goal-directed and habitual control and the susceptibility to interference between Pavlovian cues and instrumental behaviors—are associated with the development of risky alcohol drinking behaviors. For Study 1, we assessed how goal-directed and habitual controls at 18 predispose alcohol use development over the course of 3 years. Goal-directed and habitual control, which are informed by model-based (MB) and model-free (MF) learning, were assessed with a two-step sequential decision-making task during functional magnetic resonance imaging. Three-year drinking trajectories were constructed based on the Alcohol Use Disorders Identification Test (AUDIT-C; assessed every 6 months) and a gram/drinking occasion measure (binge drinking score; assessed yearly). Latent growth curve models were applied to examine how the MB and MF controls were associated with the drinking trajectories. We found that MB control was negatively associated with the development of the binge drinking score trajectory. In contrast, MF reward prediction signals in the ventromedial prefrontal cortex and the ventral striatum (VS) were associated with a higher starting point and a steeper increase/less decrease in AUDIT-C, respectively. For Study 2, we investigated the cross-sectional association between the susceptibility to interference between Pavlovian cues and instrumental behaviors and risky (binge) drinking behaviors at age 18. During a Pavlovian-to-instrumental transfer (PIT) task, the participants were instructed to “collect good shells” and “leave bad shells” while the appetitive (monetary gain) or aversive (monetary loss) Pavlovian cues were presented in the background. The behavioral interference PIT effect was characterized by an increased error rate (ER) during incongruent trials (“collecting good shells” in the presence of an aversive Pavlovian cue or “leaving bad shells” during the presentation of an appetitive Pavlovian cue) in comparison to congruent ones. Overall, the individuals demonstrated a substantial behavioral PIT effect. Neural PIT correlates were found in the VS, dorsomedial, and lateral prefrontal cortices (dmPFC and lPFC, respectively). High-risk drinkers, in comparison to low-risk drinkers, exhibited a stronger behavioral PIT effect, decreased lPFC responses, and increased trend-level VS responses. Moreover, the effective connectivity from the VS to the lPFC during the incongruent trials was weaker for the high-risk drinkers, which indicates that the altered interplay between bottom-up and top-down neural responses may contribute to the poor interference control performance of this group. During Study 3, we further examined whether the susceptibility to Pavlovian cues during conflict trials was associated with the development of drinking behaviors over 6 years from ages 18 to 24. The drinking behaviors were again constructed based on the AUDIT-C and the binge drinking score. The PIT task was assessed at ages 18 and 21. Following Study 2, the increased ER in the incongruent condition compared with the congruent condition (along with the neural responses in the VS, lPFC, and dmPFC during the incongruent trials) were included in the latent growth curve models as predictors. A stronger VS response during a conflict at age 18 was associated with a higher starting point in both drinking trajectories but was negatively associated with the development of the binge drinking score trajectory. At age 21, high ER and enhanced neural responses in the dmPFC were associated with a risky AUDIT-C trajectory that started to emerge and develop until age 24. Through exploratory cluster analyses of the drinking trajectories, we identified two subgroups: the drinking behavior in the 'late riser' group escalated after age 21, whereas the drinking of 'early peakers' culminated at this age and then declined. The late risers displayed enhanced dmPFC responses and higher ER during conflict at age 21. Interestingly, this group also exhibited an increased ER from ages 18 to 21. Taken altogether, the unbalanced goal-directed to habitual control, informed by less MB and more MF control, appears to be a strong predisposing candidate mechanism that underlies the development of risky drinking behaviors during young adulthood. At age 18, the susceptibility to interference between Pavlovian cues and instrumental behaviors was associated with risky drinking behavior. The development of risky drinking behaviors over the 6 years was associated with the behavioral interference PIT effect at age 21 and its change from ages 18 to 21. Researchers could further explore the dynamics in PIT to predict risky drinking behaviors in the future

    Comparison between unipolar and bipolar single phase grid-connected inverters for PV applications

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    An inverter is essential for the interfacing of photovoltaic panels with the AC network. There are many possible inverter topologies and inverter switching schemes and each one will have its own relative advantages and disadvantages. Efficiency and output current distortion are two important factors governing the choice of inverter system. In this paper, it is argued that current controlled inverters offer significant advantages from the point of view of minimisation of current distortion. Two inverter switching strategies are explored in detail. These are the unipolar current controlled inverter and the bipolar current controlled inverter. With respect to low frequency distortion, previously published works provide theoretical arguments in favour of bipolar switching. On the other hand it has also been argued that the unipolar switched inverter offers reduced switching losses and generates less EMI. On efficiency grounds, it appears that the unipolar switched inverter has an advantage. However, experimental results presented in this paper show that the level of low frequency current distortion in the unipolar switched inverter is such that it can only comply with Australian Standard 4777.2 above a minimum output current. On the other hand it is shown that at the same current levels bipolar switching results in reduced low frequency harmonics

    Comparison between unipolar and bipolar single phase grid-connected inverters for PV applications

    Get PDF
    An inverter is essential for the interfacing of photovoltaic panels with the AC network. There are many possible inverter topologies and inverter switching schemes and each one will have its own relative advantages and disadvantages. Efficiency and output current distortion are two important factors governing the choice of inverter system. In this paper, it is argued that current controlled inverters offer significant advantages from the point of view of minimisation of current distortion. Two inverter switching strategies are explored in detail. These are the unipolar current controlled inverter and the bipolar current controlled inverter. With respect to low frequency distortion, previously published works provide theoretical arguments in favour of bipolar switching. On the other hand it has also been argued that the unipolar switched inverter offers reduced switching losses and generates less EMI. On efficiency grounds, it appears that the unipolar switched inverter has an advantage. However, experimental results presented in this paper show that the level of low frequency current distortion in the unipolar switched inverter is such that it can only comply with Australian Standard 4777.2 above a minimum output current. On the other hand it is shown that at the same current levels bipolar switching results in reduced low frequency harmonics

    The Challenges in SDN/ML Based Network Security : A Survey

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    Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge. Sitting at the application layer and communicating with the control layer, machine learning based SDN security models exercise a huge influence on the routing/switching of the entire SDN. Compromising the models is consequently a very desirable goal. Previous surveys have been done on either adversarial machine learning or the general vulnerabilities of SDNs but not both. Through examination of the latest ML-based SDN security applications and a good look at ML/SDN specific vulnerabilities accompanied by common attack methods on ML, this paper serves as a unique survey, making a case for more secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with arXiv:1705.0056

    Preserving the Quality of Architectural Tactics in Source Code

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    In any complex software system, strong interdependencies exist between requirements and software architecture. Requirements drive architectural choices while also being constrained by the existing architecture and by what is economically feasible. This makes it advisable to concurrently specify the requirements, to devise and compare alternative architectural design solutions, and ultimately to make a series of design decisions in order to satisfy each of the quality concerns. Unfortunately, anecdotal evidence has shown that architectural knowledge tends to be tacit in nature, stored in the heads of people, and lost over time. Therefore, developers often lack comprehensive knowledge of underlying architectural design decisions and inadvertently degrade the quality of the architecture while performing maintenance activities. In practice, this problem can be addressed through preserving the relationships between the requirements, architectural design decisions and their implementations in the source code, and then using this information to keep developers aware of critical architectural aspects of the code. This dissertation presents a novel approach that utilizes machine learning techniques to recover and preserve the relationships between architecturally significant requirements, architectural decisions and their realizations in the implemented code. Our approach for recovering architectural decisions includes the two primary stages of training and classification. In the first stage, the classifier is trained using code snippets of different architectural decisions collected from various software systems. During this phase, the classifier learns the terms that developers typically use to implement each architectural decision. These ``indicator terms\u27\u27 represent method names, variable names, comments, or the development APIs that developers inevitably use to implement various architectural decisions. A probabilistic weight is then computed for each potential indicator term with respect to each type of architectural decision. The weight estimates how strongly an indicator term represents a specific architectural tactics/decisions. For example, a term such as \emph{pulse} is highly representative of the heartbeat tactic but occurs infrequently in the authentication. After learning the indicator terms, the classifier can compute the likelihood that any given source file implements a specific architectural decision. The classifier was evaluated through several different experiments including classical cross-validation over code snippets of 50 open source projects and on the entire source code of a large scale software system. Results showed that classifier can reliably recognize a wide range of architectural decisions. The technique introduced in this dissertation is used to develop the Archie tool suite. Archie is a plug-in for Eclipse and is designed to detect wide range of architectural design decisions in the code and to protect them from potential degradation during maintenance activities. It has several features for performing change impact analysis of architectural concerns at both the code and design level and proactively keep developers informed of underlying architectural decisions during maintenance activities. Archie is at the stage of technology transfer at the US Department of Homeland Security where it is purely used to detect and monitor security choices. Furthermore, this outcome is integrated into the Department of Homeland Security\u27s Software Assurance Market Place (SWAMP) to advance research and development of secure software systems

    Auditing Symposium IX: Proceedings of the 1988 Touche Ross/University of Kansas Symposium on Auditing Problems

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    Auditor evidential planning judgments / Arnold Wright, Theodore J. Mock; Discussant\u27s response to Auditor evidential planning judgments / Robert H. Temkin; Relative importance of auditing to the accounting profession: Is auditing a profit center? / Norman R. Walker, Michael D. Doll; Using and evaluating audit decision aids / Robert H. Ashton, John J. Willingham; Discussant\u27s response to The relative importance of auditing to the accounting profession: Is auditing a profit center? / Zoe-Vonna Palmrose; Accounting standards and professional ethics / Arthur R. Wyatt; Discussant\u27s response to Using and evaluating audit decision aids / Stephen J. Aldersley; Audit theory paradigms / Jack C. Robertson; Discussant\u27s response to Audit theory paradigms / Donald L. Neebes; Why the auditing standards on evaluating internal control needed to be replaced / Jerry D. Sullivan; Discussant\u27s response to Why the auditing standards on evaluating internal control needed to be replaced / William R. Kinney; AUDITOR\u27S ASSISTANT: A knowledge engineering tool for audit decisions / Glenn Shafer, Prakash P. Shenoy, Rajendra P. Srivastava; Discussant\u27s response to AUDITOR\u27S ASSISTANT: A knowledge engineering tool for audit decisions / John B. Sullivan; Reports on the application of accounting Principles -- A Review of SAS 50 / James A. Johnson; Discussant\u27s response to Reports on the application of accounting Principles -- A Review of SAS 50 / Gary L. Holstrumhttps://egrove.olemiss.edu/dl_proceedings/1008/thumbnail.jp
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