The application of scientific management to the Watertown arsenal

Thesis (M.B.A.)--Boston Universit

The social psychology of seismic hazard adjustment: re-evaluating the international literature

The majority of people at risk from earthquakes do little or nothing to reduce their vulnerability. Over the past 40 years social scientists have tried to predict and explain levels of seismic hazard adjustment using models from behavioural sciences such as psychology. The present paper is the first to synthesise the major findings from the international literature on psychological correlates and causes of seismic adjustment at the level of the individual and the household. It starts by reviewing research on seismic risk perception. Next, it looks at norms and normative beliefs, focusing particularly on issues of earthquake protection responsibility and trust between risk stakeholders. It then considers research on attitudes towards seismic adjustment attributes, specifically beliefs about efficacy, control and fate. It concludes that an updated model of seismic adjustment must give the issues of norms, trust, power and identity a more prominent role. These have been only sparsely represented in the social psychological literature to date

Port waiting time for oil tankers : Leveraging AIS data to predict port waiting time using machine learning

This master's thesis investigates the predictability of waiting times at crude oil ports using Automatic Identification System (AIS) data and machine learning. Focusing on the wet bulk market, specifically four congested Middle Eastern Gulf ports, we aimed to answer: 11Can the waiting times in crude oil ports be predicted based on AIS data? 11. In this thesis clustering algorithms with novel modifications are utilized to establish berth and anchorage polygons. These polygons form the basis for a spatial matching of AIS data that is used to generate event logs. A cross-sectional data set is derived from the event logs which in turn is the basis for extracting features used in five different machine learning models. The findings show that AIS-derived features have predictive power on waiting times, with vessel composition within ports and port dynamics being significant factors. These insights hold practical implications for ship owners and academics alike, enhancing vessel economics through speed adjustments and facilitating further research within the maritime domain. The thesis also proposes further research areas, including methodology refinement within polygon generation, event log generation and waiting time prediction.nhhma

Silicon-based three-dimensional microstructures for radiation dosimetry in hadrontherapy

In this work, we propose a solid-state-detector for use in radiation microdosimetry. This device improves the performance of existing dosimeters using customized 3D-cylindrical microstructures etched inside silicon. The microdosimeter consists of an array of micro-sensors that have 3D-cylindrical electrodes of 15 μm diameter and a depth of 5 μm within a silicon membrane, resulting in a well-defined micrometric radiation sensitive volume. These microdetectors have been characterized using an 241Am source to assess their performance as radiation detectors in a high-LET environment. This letter demonstrates the capability of this microdetector to be used to measure dose and LET in hadrontherapy centers for treatment plan verification as part of their patient-specific quality control program

Nociceptin attenuates the escalation of oxycodone self-administration by normalizing CeA-GABA transmission in highly addicted rats.

Approximately 25% of patients who are prescribed opioids for chronic pain misuse them, and 5 to 10% develop an opioid use disorder. Although the neurobiological target of opioids is well known, the molecular mechanisms that are responsible for the development of addiction-like behaviors in some but not all individuals are poorly known. To address this issue, we used a unique outbred rat population (heterogeneous stock) that better models the behavioral and genetic diversity that is found in humans. We characterized individual differences in addiction-like behaviors using an addiction index that incorporates the key criteria of opioid use disorder: escalated intake, highly motivated responding, and hyperalgesia. Using in vitro electrophysiological recordings in the central nucleus of the amygdala (CeA), we found that rats with high addiction-like behaviors (HA) exhibited a significant increase in γ-aminobutyric acid (GABA) transmission compared with rats with low addiction-like behaviors (LA) and naive rats. The superfusion of CeA slices with nociceptin/orphanin FQ peptide (N/OFQ; 500 nM), an endogenous opioid-like peptide, normalized GABA transmission in HA rats. Intra-CeA levels of N/OFQ were lower in HA rats than in LA rats. Intra-CeA infusions of N/OFQ (1 μg per site) reversed the escalation of oxycodone self-administration in HA rats but not in LA rats. These results demonstrate that the downregulation of N/OFQ levels in the CeA may be responsible for hyper-GABAergic tone in the CeA that is observed in individuals who develop addiction-like behaviors. Based on these results, we hypothesize that small molecules that target the N/OFQ system might be useful for the treatment of opioid use disorder

Norwegian fathers’ experiences with a home visiting program

Objective - To explore fathers’ experiences with a Norwegian home visiting program during the prenatal period and the first-year postpartum. Design - Qualitative design with interpretive description (ID) as the methodological approach. Sample - Individual interviews with fathers (n = 13) who received home visits by a public health nurse (PHN) within the New Families home visiting program. Measures - Interviews were guided by a semi-structured interview-guide, which contained open-ended questions encouraging informants to reflect on their experiences with home visits. The analysis of the data was informed by content analysis. Results - Two main themes that reflect the fathers’ experiences emerged: (1) The importance of being on their home ground captures the fathers’ experience of receiving home visits and building a trusting relationship with the PHN. (2) Including fathers in the home visit represents their thoughts about the content and focus of the home visits. Conclusions - Fathers experienced the universal New Families home visiting program as an important contribution towards a more available and tailored service, with the home environment as a suitable arena for developing a trusting relationship with the PHN. However, the fathers often felt insufficiently included in the home visits, with only scant attention towards them as independent caregivers, their emotional reactions, roles, and family relationships. Pre-birth home visits might contribute to strengthening preparations for fatherhood and increase fathers’ engagement in the Child Health Service

Expert-Augmented Machine Learning

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications