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Emotional eating (EE) is defined as eating in response to negative emotions (e.g., sadness and boredom). Child temperament and parental feeding practices are predictive of child EE and may interact to shape child EE. Previous research has demonstrated that children eat more when they are experiencing sadness, however, boredom-EE (despite how common boredom is in children) has yet to be explored experimentally using remote methodologies. The current study explores whether feeding practices and child temperament interact with mood to predict children's snack selection in an online hypothetical food choice task. Using online experimental methods, children aged 6-9-years (N = 347) were randomised to watch a mood-inducing video clip (control, sadness, or boredom). Children completed a hypothetical food choice task from images of four snacks in varying portion sizes. The kilocalories in children's online snack choices were measured. Parents reported their feeding practices and child's temperament. Results indicated that the online paradigm successfully induced feelings of boredom and sadness, but these induced feelings of boredom and sadness did not significantly shape children's online food selection. Parental reports of use of restriction for health reasons (F = 8.64, p = .004, n = 0.25) and children's negative emotionality (F = 6.81, p = .009, n = 0.020) were significantly related to greater total kilocalorie selection by children. Three-way ANCOVAs found no evidence of any three-way interactions between temperament, feeding practices, and mood in predicting children's online snack food selection. These findings suggest that children's hypothetical snack food selection may be shaped by non-responsive feeding practices and child temperament. This study's findings also highlight different methods that can be successfully used to stimulate emotional experiences in children by using novel online paradigms, and also discusses the challenges around using online methods to me

BACKGROUND: Preventing progression to moderate or severe opioid use disorder (OUD) among people who exhibit risky opioid use behavior that does not meet criteria for treatment with opioid agonists or antagonists (subthreshold OUD) is poorly understood. The Subthreshold Opioid Use Disorder Prevention (STOP) Trial is designed to study the efficacy of a collaborative care intervention to reduce risky opioid use and to prevent progression to moderate or severe OUD in adult primary care patients with subthreshold OUD. METHODS: The STOP trial is a cluster randomized controlled trial, randomized at the PCP level, conducted in 5 distinct geographic sites. STOP tests the efficacy of the STOP intervention in comparison to enhanced usual care (EUC) in adult primary care patients with risky opioid use that does not meet criteria for moderate-severe OUD. The STOP intervention consists of (1) a practice-embedded nurse care manager (NCM) who provides patient participant education and supports primary care providers (PCPs) in engaging and monitoring patient-participants; (2) brief advice, delivered to patient participants by their PCP and/or prerecorded video message, about health risks of opioid misuse; and (3) up to 6 sessions of telephone health coaching to motivate and support behavior change. EUC consists of primary care treatment as usual, plus printed overdose prevention educational materials and an educational video on cancer screening. The primary outcome measure is self-reported number of days of risky (illicit or nonmedical) opioid use over 180 days, assessed monthly via text message using items from the Addiction Severity Index and the Current Opioid Misuse Measure. Secondary outcomes assess other substance use, mental health, quality of life, and healthcare utilization as well as PCP prescribing and monitoring behaviors. A mixed effects negative binomial model with a log link will be fit to estimate the difference in means between treatment and control groups usin

Children who emotionally eat (EE) tend to consume palatable foods that are high in sugar and fat. How EE develops remains unclear, but children’s temperament and parental feeding practices may interact to shape child EE. To date, no research has explored these interaction effects on EE experimentally. Furthermore, most research has explored EE in response to generic ‘negative’ mood rather than specific negative emotions, such as boredom, which has never been explored in this context. This study aimed to explore interactions between induced mood condition (sadness, boredom, control), parent-reported non-responsive feeding practices and parent-reported child temperament (negative affect, surgency, effortful control) in predicting kilocalories consumed by children aged 4–5-years in a laboratory setting. Using three-way ANOVA, the interactions between mood state, parental feeding practice and child temperament were assessed. Results indicated that children who experienced boredom consumed significantly more total kilocalories than children in the control condition. Additionally, children with high negative affect who also had parents who reported high use of food for emotion regulation consumed significantly more kilocalories from sweet food when experiencing boredom compared to control condition, and children with high negative affect who also had parents who reported low use of food as a reward consumed significantly more kilocalories from sweet food when experiencing boredom compared to control condition. These findings suggest that feelings of boredom differentially predict children’s snack food intake, and that child negative affect and non-responsive feeding practices play an important role in the expression of this relationship.

The fairness of a deep neural network is strongly affected by dataset bias and spurious correlations, both of which are usually present in modern feature-rich and complex visual datasets. Due to the difficulty and variability of the task, no single de-biasing method has been universally successful. In particular, implicit methods not requiring explicit knowledge of bias variables are especially relevant for real-world applications. We propose a novel implicit mitigation method using a Bayesian neural network, allowing us to leverage the relationship between epistemic uncertainties and the presence of bias or spurious correlations in a sample. Our proposed posterior estimate sharpening procedure encourages the network to focus on core features that do not contribute to high uncertainties. Experimental results on three benchmark datasets demonstrate that Bayesian networks with sharpened posterior estimates perform comparably to prior existing methods and show potential worthy of further exploration., Comment: We are revising this paper with significant changes

While several previous studies have devised methods for segmentation of polyps, most of these methods are not rigorously assessed on multi-center datasets. Variability due to appearance of polyps from one center to another, difference in endoscopic instrument grades, and acquisition quality result in methods with good performance on in-distribution test data, and poor performance on out-of-distribution or underrepresented samples. Unfair models have serious implications and pose a critical challenge to clinical applications. We adapt an implicit bias mitigation method which leverages Bayesian epistemic uncertainties during training to encourage the model to focus on underrepresented sample regions. We demonstrate the potential of this approach to improve generalisability without sacrificing state-of-the-art performance on a challenging multi-center polyp segmentation dataset (PolypGen) with different centers and image modalities., Comment: To be presented at the Fairness of AI in Medical Imaging (FAIMI) MICCAI 2023 Workshop and published in volumes of the Springer Lecture Notes Computer Science (LNCS) series

Background: Synchronous hybrid instruction offers flexible learning opportunities by allowing a portion of students to attend class sessions on campus while simultaneously allowing the remaining students to attend remotely. Although such flexibility may offer a number of advantages for pharmacy students, one area of concern is whether online participation options within synchronous hybrid courses can promote similar levels of engagement as courses that are designed entirely for face-to-face (FTF) participation. Objectives: The objective of this study was to evaluate the impact of synchronous hybrid instruction on pharmacy students’ engagement in a pharmacotherapy course. An evaluation was completed to determine if students were more likely to actively engage in class when they were participating remotely via teleconferencing technology or when FTF. Additionally, students’ perspectives were evaluated to determine their views of the benefits and challenges of the hybrid model for engagement in learning. Methods: The course utilizes team-based learning to apply critical thinking skills and develop a comprehensive care plan. A mixed methods approach was used to examine students’ engagement in the hybrid learning environment by quantitatively analyzing students’ responses to likert-scale survey items and qualitatively analyzing their responses to open-ended survey questions. Results: Students reported they were more likely to actively listen (p=0.004), avoid distractions (p=0.008), and react emotionally to a topic or instruction (p=0.045) when FTF. There were no significant differences found in student reported note taking, asking questions, responding to questions, or engaging in group work between the two modes of participation. Content analysis identified other benefits that supported student engagement, including perceived flexibility and enhanced ability to interact during class via the teleconferencing technology. For some students, challenges that negatively impac

https://revistas.uned.ac.cr/index.php/espiga/article/view/4139#:~:text=La%20educaci%C3%B3n%20durante,de%20este%20trabajo.

BACKGROUND: Children's tendency to eat while they are emotional, irrespective of satiety, is termed emotional eating (EE). EE develops early in childhood and has been associated with maternal modelling of EE and food parenting practices. In addition, individual differences in a child's appetitive traits (ie, food approach behaviors) are related to the development of EE. OBJECTIVE: The objective of this study was to examine whether or not the previously identified mediating relationship between maternal EE and child EE via maternal use of food as a reward, food for emotion regulation, or restriction of food for health reasons varies as a function of child food approach. DESIGN: A cross-sectional online questionnaire study was conducted. PARTICIPANTS/SETTING: One hundred eighty-five mothers of children aged between 3 and 5 years were recruited between January 2020 and March 2020 from advertisements placed on social media in the United Kingdom. MAIN OUTCOME MEASURE: Questionnaires assessed child EE, child food approach tendencies, maternal EE, and food parenting practices. STATISTICAL ANALYSES PERFORMED: Using PROCESS version 3.4, model 14, moderated mediations were employed to assess whether or not child food approach tendencies moderated the mediating effect of controlling food parenting practices between maternal EE and child EE. RESULTS: This study found the relationship between maternal reports of maternal EE and child EE was mediated by maternal use of food as a reward, but only for children with high food approach tendencies (B = .05, 95% CI 0.010 to 0.101; R 2 = 48%). This study also found the relationship between maternal EE and child EE was mediated by maternal use of restriction for health reasons, but only when children showed medium (B = .02, 95% CI 0.004 to 0.072) to high (B = .06, 95% CI 0.016 to 0.110; R 2 = 51%) food approach tendencies. CONCLUSIONS: The potential for the intergenerational transmission of EE via the use of food as a reward and food res

Emotional eating (EE; defined as overeating irrespective of satiety and in response to emotional states) develops within childhood, persists into adulthood, and is linked with obesity. The origins of EE remain unclear, but parental behaviours (e.g., controlling feeding practices and modelling) and child characteristics (e.g., temperament) are often implicated. To date, the interaction between these influences has not been well investigated. This study explores whether the relationship between parent and child EE is shaped by parental feeding practices, and if the magnitude of this relationship varies as a function of child temperament. Mothers (N = 244) of 3–5‐year‐olds completed questionnaires about their EE, feeding practices, their children's EE and temperament. Results showed that parental use of food to regulate children's emotions fully mediated the relationship between parent and child EE, and using food as a reward and restricting food for health reasons partially mediated this relationship. Analyses demonstrated that the mediated relationship between parent and child EE via use of food as a reward and restriction of food for health reasons varied as a function of child negative affect, where high child negative affect moderated these mediations. These findings suggest child EE may result from interrelationships between greater parent EE, use of food as a reward, restriction of food for health reasons and negative affective temperaments, but that greater use of food for emotion regulation may predict greater child EE irrespective of child temperament.

Emotional eating (EE) in children; the tendency to consume food in response to negative emotions; is associated with the development of childhood obesity. The Biopsychosocial Model suggests child EE arises from interactions between the parent, the child, and the environment. However, no research has yet examined how parent EE, parental feeding practices, and child individual differences interact to predict child EE, particularly in the context of different negative emotions. The overarching aim of this thesis was to explore these relationships during early childhood. In study 1 (N = 244) and study 2 (N = 185) parents completed an online questionnaire. Findings highlighted that the positive relationship between parent EE and child EE was fully mediated by parental emotional feeding and partially mediated by parental use of food as a reward and restriction of food. Further, medium-high child negative affect (study 1) and high child food approach (study 2) moderated these partial mediations. In study 3, 347 parent-child dyads participated in an online experiment study. There were no significant interactions between parent-reported child temperament, parental feeding practices, and child mood state in predicting the number of kilocalories children selected after a mood induction task. In study 4, using a laboratory experimental study with 119 children, children with high parentally reported negative affect, who also had parents who reported high emotional feeding, consumed significantly more kilocalories from sweet foods when experiencing boredom compared to a control group. Finally, in study 5 more objective measures of child temperament were used and children with lower motor impulsivity consumed significantly more kilocalories when experiencing boredom, compared to when experiencing sadness or a neutral mood. This thesis demonstrates that children’s individual differences are key to shaping how much children eat in response to different mood states, alongside influen

Deep neural networks are highly susceptible to learning biases in visual data. While various methods have been proposed to mitigate such bias, the majority require explicit knowledge of the biases present in the training data in order to mitigate. We argue the relevance of exploring methods which are completely ignorant of the presence of any bias, but are capable of identifying and mitigating them. Furthermore, we propose using Bayesian neural networks with a predictive uncertainty-weighted loss function to dynamically identify potential bias in individual training samples and to weight them during training. We find a positive correlation between samples subject to bias and higher epistemic uncertainties. Finally, we show the method has potential to mitigate visual bias on a bias benchmark dataset and on a real-world face detection problem, and we consider the merits and weaknesses of our approach., Comment: Published in 2022 IEEE CVPR Workshop on Fair, Data Efficient and Trusted Computer Vision

Infertility is a significant public health concern in the United States. As such, utilization of infertility services, including pharmacotherapeutic treatments, is prevalent, and the role of the pharmacist as part of the health care team is essential. Pharmacists can assist patients by providing education on infertility causes, risk factor mitigation, referrals, nonpharmacologic and pharmacologic management options, navigation of the prescription process, and resource availability for the significant financial burden accompanying infertility treatment. In-depth pharmacotherapeutic information may not be readily available to pharmacists dispensing and counseling on these medications, and infertility management regimens are often varied and complicated requiring more in-depth counseling on use and administration. Given the complexity of infertility management, pharmacists are a valuable patient support and education resource. This article provides an in-depth review of infertility management strategies, both nonpharmacologic and pharmacologic.

Objective: To provide guidance for clinicians on risk assessment of medication use during pregnancy and lactation. Data Sources: Authors completed PubMed searches to identify articles focused on the use of medications in pregnancy, including fetal development, drug transfer across the placenta, trimester exposure, chronic conditions in pregnancy, medications in lactation, and lactation and chronic disease. Study Selection and Data Extraction: Articles were reviewed to provide overall guidance to medication selection during pregnancy. The following information was reviewed: medication use in pregnancy, including fetal development, drug transfer across the placenta, trimester exposure, chronic conditions in pregnancy, medications in lactation, and lactation and chronic disease. Data Synthesis: This article will provide an overview of medication safety considerations during pregnancy and lactation. Information was interpreted to help clinicians predict the potential risk and benefit in each patient to make an evidence-based decision. The article concludes with guidance on risk assessment and how pharmacists may support fellow health care providers and their patients when considering medication use. Conclusions: Information about the effects of medication use during reproductive periods is limited. With the removal of the Food and Drug Administration pregnancy categories, clinicians will be relying on pharmacists to aid in the appropriate selection of therapies for patients. It is critical that pharmacists keep abreast of resources available and be able to assess data to help prescribers and their patients.

Virtual reality is becoming mainstream in areas such as entertainment, medicine and training. However, the affect on a user’s perceived states are still to be fully understood. This study aims to add to the existing body of research by examining changes in user interfaces and the affect on perceived responses. Subjects in the study were exposed to two virtual environments, while undertaking a physical exercise task. Their perceived responses were captured through a combination of interviews, observations, and surveys. This differs from previous studies in that it is capturing the perceived differences between the environments themselves. The results highlighted that the content of the environments resulted in a variety of interesting, and unexpected, perceived responses.

Oral contraceptive pills (OCPs) containing estrogen and progestin or progestin only were introduced as a contraceptive option for women in 1960. Since their introduction to the market, there have been significant changes in the drug content and formulations of these products, in part to decrease the risk of adverse effects. The OCP products available today, particularly combined oral estrogen and progestin products (COCs), continue to be widely used. The major adverse effect associated with COCs is an increased risk of a cardiovascular event. COCs are contraindicated for women with increased cardiovascular risk, increased thromboembolic risk, significant liver disease, systemic lupus erythematosus, or migraine with aura. In addition, both COCs and progestin-only pills (POPs) are contraindicated in patients with a personal history of breast cancer. Commonly reported minor adverse effects may include menstrual bleeding pattern changes, breast tenderness, headache, mood changes, and nausea. Frequently these minor adverse effects subside following the initial 3 months of appropriately administered therapy, and otherwise may be managed by changing the hormone strength or product formulation and confirming patient adherence. It is imperative that providers are familiar with the potential adverse effects associated with OCP use, so they may in turn educate and counsel patients. Since adverse effects are the primary reason for OCP discontinuation, it is critical that patients are made aware of and expect these in advance and are counseled how to minimize or manage adverse effects. It is important to note that many women also use OCPs for noncontraceptive benefits, such as regulating menstrual irregularities, treatment of premenstrual syndrome, prevention of menstrual migraine, treatment of acne, and others.

A bulk turbulence-closure mixed layer model is generalized to allow prediction of very deep polar sea mixing. The model includes unsteady three- component turbulent kinetic energy budgets. In addition to terms for shear production, pressure redistribution, and dissipation, special attention is devoted to realistic treatment of thermobaric enhancement of buoyancy flux and to Coriolis effect on turbulence. The model is initialized and verified with CTD data taken by R/V Valdivia in the Greenland Sea during winter 1993-1994. Model simulations show (1) mixed layer deepening is significantly enhanced when the thermal expansion coefficient's increase with pressure is included; (2) entrainment rate is sensitive to the direction of wind stress because of Coriolis; and (3) the predicted mixed layer depth evolution agrees qualitatively with the observations. Results demonstrate the importance of water column initial conditions, accurate representation of strong surface cooling events, and inclusion of the thermobaric effect on buoyancy, to determine the depth of mixing and ultimately the heat and salt flux into the deep ocean. Since coupling of the ocean to the atmosphere through deep mixed layers in polar regions is fundamental to our climate system, it is important that regional and global models be developed that incorporate realistic representation of this coupling, http://archive.org/details/deepmixedlayeren00ston, Lieutenant Commander, United States Navy, Approved for public release; distribution is unlimited.

Skillful long-range forecasts of acoustic variables have the potential to be very useful in planning Navy undersea warfare operations. Our study assessed the potential to predict sonic layer depth (SLD) in the western north Pacific at lead times of one to several months. We conducted correlations between SLD and remote climate system variables, and identified a high potential for skillful long-range forecasts of SLD in the western north Pacific using sea surface temperature in equatorial and south Pacific as predictors. We used tercile matching and composite analysis forecast (CAF) methods to develop hindcasts and forecasts of SLD based on SST predictors at lead times of one to four months. Our forecast verification metrics show that the resulting long lead probabilistic forecasts are a clear improvement over presently available long term mean climatology products. We also used conditional compositing techniques to create mean and environmental threshold probability products based on the long lead forecasts. Our results indicate that the support of USW operations by the Navy meteorology and oceanography community could be improved by the use of advanced climate data sets, climate analysis, and long-range forecasting methods., http://archive.org/details/longrangetmosphe109454516, US Navy (USN) author., Approved for public release; distribution is unlimited.

The sensitivity of operational decision making to atmospheric forecasts is a key component of the Decision Tier, or Tier 3, of Battlespace on Demand, Naval Oceanography's operational concept. To that end, effects of different wind forecast inputs were analyzed within a modeled decision context for an aircraft carrier ammunition offload. Development of the decision context using expected distance as the utility measurement was followed by an examination of the climatology of wind events that could adversely affect an offload evolution. Two high-wind event cases from 2009 were chosen for analysis within the decision model. Ensembles from numerical weather prediction models were formed into probabilistic wind forecasts and applied to several decision scenarios. Slight changes to both the forecast inputs and the decision context itself produced different decision outcomes, which emphasized the interdependency between forecasts and optimum decisions in the modeled scenario., http://archive.org/details/aprocessforpplyi109455240, US Navy (USN) author, Approved for public release; distribution is unlimited.

The rapid Arctic sea ice decline since the 1970s has propelled the United States into a state of urgency for updating its defense plan as Arctic and non-Arctic nations alike are taking an interest in the newfound natural resources of an ice-declining Arctic. In line with the National Security Presidential Directive-66, we quantify the amount of anomalous sea ice variability (aSIV) that anomalous atmospheric forcing parameters explain using partial covariance analysis. A one-system approach where the NPS Model sea ice parameters are the direct output of the atmospheric forcing parameters input is employed. Atmospheric forcing fields of 2-m temperature, downward shortwave and longwave fluxes, 10-m zonal and meridional winds and stresses, are from the European Centre for Medium-Range Weather Forecasts Reanalysis-15 and Operational Products. Locations of interest are the Central Arctic seas, and locations along the Northwest Passage (NWP) and the Northern Sea Route (NSR). Results show that the atmospheric parameter having the largest influence on aSIV is anomalous surface air temperature. This occurs during the cooling months and averages 4-39% of aSAT contribution to aSIV in the Central Arctic, 9-16% along the NWP, and 11-25% along the NSR. Results also suggest that atmospheric forcing alone does not explain all of aSIV., http://archive.org/details/towardquantifyin109455416, US Air Force (USAF) author, Approved for public release; distribution is unlimited.

Skillful long range forecasts of dust storms have the potential to be very useful in planning operations by the Department of Defense (DoD) and other organizations. Our study assessed the potential to predict Iraq dust storms at long lead times (e.g., several weeks to several months). We examined two variables that associated with dust storms: precipitation rate and surface winds. To characterize conditions during dust storms, we generated averages (conditional means) of Iraq precipitation prior to, and winds during, dust storms, as well as the anomalies in those variables compared them to their long term means. We then identified statistically significant correlations between those Iraq variables and remote climate system variables. Those correlations were used to develop two long range predictors of dust favorable precipitation and winds in Iraq: (a) sea surface temperature in the Indian Ocean; and (b) an index of the difference between sea level pressure near Tunisia and Kazakhstan (an indicator of surface winds). We used these predictors in an adaptation of the composite analysis forecast (CAF) method to hindcast and forecast dust favorable conditions in Iraq at lead times of one and two months. Verification of our results indicates that our method has a high potential for producing skillful long range forecasts of the potential for dust storms in Iraq., http://archive.org/details/climatenalysisnd109454753, US Navy (USN) author., Approved for public release; distribution is unlimited.

"For acoustic frequencies of interest in the development of undersea wireless wide-area networks, wind noise is the dominant contribution to channel noise. The large dynamic range of wind noise forces the network designer to consider wide variations in link margin and effective node-to-node range. Previous reported correlations of acoustic communication performance and wind speed led to multiple hypotheses explaining degradation, including noise variability as well as wind-driven sea-surface effects such as roughness, entrained bubbles, mixing, and stratification. This theses examines operations of a 40-node wide-area acoustic network in varying noise conditions. This data set is unique in that the environment is strongly downward refracting. Based on theoretical models, wind noise is assumed to dominate all other noise sources. Considerations include dependence of link margin and range on wind speed. Although the experiment was not designed to examine the correlation between transmission range and wind speed, a weak correlation was observed in the limited data set available." p. i., http://archive.org/details/effectofwindnois109451936, Approved for public release; distribution is unlimited.

Undersea warfare operations, especially sound navigation and ranging (SONAR), are sensitive to small changes in the ocean environment. Variations in both atmospheric and oceanic conditions on monthly to decadal scales can have significant impacts on U.S. Navy operations in the undersea environment. Climate databases presently used in U.S. Navy tactical decision aids (TDAs) are based on less than optimal data sets and long term mean (LTM) climatologies that are unable to represent climatic trends or variations. Thus, existing Navy climatologies are likely to provide inadequate representations of the actual dynamic ocean environment. We have used the Naval Postgraduate School smart climatology process, including state-of-the-science atmospheric and oceanic re-analysis data sets, to create smart ocean climatologies. Comparisons of these climatologies with existing Navy climatologies based on the Generalized Digital Environmental Model (GDEM) reveal differences in sonic layer depth (SLD) and sound speed. These differences lead, in turn, to tactically significant differences in the results from Navy TDAs that support undersea warfare., http://archive.org/details/smartclimatology109453919, US Navy (USN) author., Approved for public release; distribution is unlimited.

In this thesis, the performance and accuracy of explicit, semiimplicit, and Hybrid EulerianLagrangian SemiImplicit (HELSI) timeintegration methods used in atmospheric modeling are examined. Four test cases are analyzed: A density current, an inertial gravity wave, a rising thermal bubble, and a hydrostatic mountain wave. Strict attention is paid to computational time, stability criteria, and accuracy. The project aims to show increased efficiency using the HELSI method over fully semiimplicit methods, which, in turn, should be better than the splitexplicit methods currently used in mesoscale models such as WRF, COAMPS, and the German LM model. This increase in efficiency allows for valuable computational resources to be used for other purposes, such as improved data assimilation, increased spatial resolution, or more detailed physics., http://archive.org/details/performanceofhyb109453309, US Air Force (USAF) author

Stochastic (probabilistic) forecasting techniques give forecasters a means to transmit information about certainty and a range of forecast possibilities to operational decision makers. Previous studies have shown value in probabilistic forecasting through series of independent hypothetical events, or through comparative period forecasts. This thesis demonstrates the value of stochastic forecasting through a series of operational events, in the context of a Strike Warfare campaign in the Weather Impact Assessment Tool (WIAT), a campaign simulator. Simulated ensemble members and probability files were created to study six weather parameters and their impacts on various Strike Warfare missions. Tests were run comparing deterministic and stochastic forecasts, incorporating varying levels of forecast error and sampled probability thresholds. Metrics within and external to WIAT were employed to analyze the results of the forecasting strategies. Constraints in WIAT's structure and campaign modeling yielded results that suggest, but do not definitively prove, enhanced campaign performance as a result of incorporating probabilistic forecasting. Programming adjustments to WIAT are recommended in order to provide a higher-quality test bed for future studies of both deterministic and stochastic forecasting techniques., http://archive.org/details/incorporatingens109455256, US Navy (USN) author, Approved for public release; distribution is unlimited.

We have developed metrics of the performance and operational impacts of METOC support to strike operations conducted on operational aircraft carriers (CVs). Our goal was to assess that support and make recommendations on improving it. We adapted an existing automated real time METOC metrics system, which was developed for land based training missions, for use on CVs by developing a new data collection form, new metrics, and new collection, analysis, and reporting architecture for the remote entering of sensitive mission data without compromise. The weather support element of a CV, the OA division, does not provide strike mission planning support, but does provide situational awareness to pilots. Our system allows that situational awareness to be measured and assessed using metrics that quantify the performance of the forecasts, the relationship of the forecasts to the mitigating actions taken by pilots due to adverse weather conditions, and the effects of individual weather phenomena on the execution of strike missions. A key element of the data collection, analysis, and reporting system developed in this study is the collection of METOC related data from pilots during their intelligence debriefings. This system is readily adaptable for the assessment of METOC support to other warfare areas., http://archive.org/details/metricsofmetocfo109452677, Approved for public release; distribution is unlimited.

A novel synthetic method was developed for the controlled functionalization of Fluorinated Polyhedral Oligomeric SilSesquioxanes (F-POSS), which are useful as low surface energy materials for superhydrophobic and oleophobic materials. Utilizing triflic acid, open-cage compounds were created and then reacted with a variety of dichlorosilanes to produce functional F-POSS structures possessing alkyl, aryl, and acrylate based moieties. The crystal structure for an endo,endo disilanol F-POSS compound was determined by single crystal X-ray diffraction. The chemical structures were confirmed using multinuclear NMR spectroscopy (1H, 13C, 19F, and 29Si), FT-IR, and combustion analysis. Dynamic contact angle measurements of these compounds were taken with water and hexadecane. These novel structures were found to possess excellent wettingresistant behavior, similar to that of the parent F-POSS compound. They are the first well-defined fluorinated nanobuilding blocks with a controlled level of reactive functionality for the development of new superhydrophobic and oleophobic materials., For publication in the Journal of the American Chemical Society.

To be super-resistant to wetting, surfaces generally require both nano- and micro-scale roughness, as well as low surface energy. Based on calculations, to have a smooth superoleophobic surface would require a surface energy lower than any known material. Increasing the length of the fluorinated chains may lead to molecules with even lower solid surface energies and therefore even better hydrophobic and oleophobic properties. We present the synthesis of the longest chain fluorinated POSS molecules reported: fluorododecylPOSS (FDD). The synthesis is performed via the base-catalyzed, one-step condensation of the corresponding trialkoxysilane., Presented at the American Chemical Society Spring, 2011 National Conference, held in Anaheim, CA, on 31 Mar 2011.

The sensitivity of operational decision making to atmospheric forecasts is a key component of the Decision Tier, or Tier 3, of Battlespace on Demand, Naval Oceanography's operational concept. To that end, effects of different wind forecast inputs were analyzed within a modeled decision context for an aircraft carrier ammunition offload. Development of the decision context using expected distance as the utility measurement was followed by an examination of the climatology of wind events that could adversely affect an offload evolution. Two high-wind event cases from 2009 were chosen for analysis within the decision model. Ensembles from numerical weather prediction models were formed into probabilistic wind forecasts and applied to several decision scenarios. Slight changes to both the forecast inputs and the decision context itself produced different decision outcomes, which emphasized the interdependency between forecasts and optimum decisions in the modeled scenario.

The rapid Arctic sea ice decline since the 1970s has propelled the United States into a state of urgency for updating its defense plan as Arctic and non-Arctic nations alike are taking an interest in the newfound natural resources of an ice-declining Arctic. In line with the National Security Presidential Directive-66, we quantify the amount of anomalous sea ice variability (aSIV) that anomalous atmospheric forcing parameters explain using partial covariance analysis. A one-system approach where the NPS Model sea ice parameters are the direct output of the atmospheric forcing parameters input is employed. Atmospheric forcing fields of 2-m temperature, downward shortwave and longwave fluxes, 10-m zonal and meridional winds and stresses, are from the European Centre for Medium-Range Weather Forecasts Reanalysis-15 and Operational Products. Locations of interest are the Central Arctic seas, and locations along the Northwest Passage (NWP) and the Northern Sea Route (NSR). Results show that the atmospheric parameter having the largest influence on aSIV is anomalous surface air temperature. This occurs during the cooling months and averages 4-39% of aSAT contribution to aSIV in the Central Arctic, 9-16% along the NWP, and 11-25% along the NSR. Results also suggest that atmospheric forcing alone does not explain all of aSIV.

Stochastic (probabilistic) forecasting techniques give forecasters a means to transmit information about certainty and a range of forecast possibilities to operational decision makers. Previous studies have shown value in probabilistic forecasting through series of independent hypothetical events, or through comparative period forecasts. This thesis demonstrates the value of stochastic forecasting through a series of operational events, in the context of a Strike Warfare campaign in the Weather Impact Assessment Tool (WIAT), a campaign simulator. Simulated ensemble members and probability files were created to study six weather parameters and their impacts on various Strike Warfare missions. Tests were run comparing deterministic and stochastic forecasts, incorporating varying levels of forecast error and sampled probability thresholds. Metrics within and external to WIAT were employed to analyze the results of the forecasting strategies. Constraints in WIAT's structure and campaign modeling yielded results that suggest, but do not definitively prove, enhanced campaign performance as a result of incorporating probabilistic forecasting. Programming adjustments to WIAT are recommended in order to provide a higher-quality test bed for future studies of both deterministic and stochastic forecasting techniques.

Skillful long-range forecasts of acoustic variables have the potential to be very useful in planning Navy undersea warfare operations. Our study assessed the potential to predict sonic layer depth (SLD) in the western north Pacific at lead times of one to several months. We conducted correlations between SLD and remote climate system variables, and identified a high potential for skillful long-range forecasts of SLD in the western north Pacific using sea surface temperature in equatorial and south Pacific as predictors. We used tercile matching and composite analysis forecast (CAF) methods to develop hindcasts and forecasts of SLD based on SST predictors at lead times of one to four months. Our forecast verification metrics show that the resulting long lead probabilistic forecasts are a clear improvement over presently available long term mean climatology products. We also used conditional compositing techniques to create mean and environmental threshold probability products based on the long lead forecasts. Our results indicate that the support of USW operations by the Navy meteorology and oceanography community could be improved by the use of advanced climate data sets, climate analysis, and long-range forecasting methods.

Skillful long range forecasts of dust storms have the potential to be very useful in planning operations by the Department of Defense (DoD) and other organizations. Our study assessed the potential to predict Iraq dust storms at long lead times (e.g., several weeks to several months). We examined two variables that associated with dust storms: precipitation rate and surface winds. To characterize conditions during dust storms, we generated averages (conditional means) of Iraq precipitation prior to, and winds during, dust storms, as well as the anomalies in those variables compared them to their long term means. We then identified statistically significant correlations between those Iraq variables and remote climate system variables. Those correlations were used to develop two long range predictors of dust favorable precipitation and winds in Iraq: (a) sea surface temperature in the Indian Ocean; and (b) an index of the difference between sea level pressure near Tunisia and Kazakhstan (an indicator of surface winds). We used these predictors in an adaptation of the composite analysis forecast (CAF) method to hindcast and forecast dust favorable conditions in Iraq at lead times of one and two months. Verification of our results indicates that our method has a high potential for producing skillful long range forecasts of the potential for dust storms in Iraq.

Undersea warfare operations, especially sound navigation and ranging (SONAR), are sensitive to small changes in the ocean environment. Variations in both atmospheric and oceanic conditions on monthly to decadal scales can have significant impacts on U.S. Navy operations in the undersea environment. Climate databases presently used in U.S. Navy tactical decision aids (TDAs) are based on less than optimal data sets and long term mean (LTM) climatologies that are unable to represent climatic trends or variations. Thus, existing Navy climatologies are likely to provide inadequate representations of the actual dynamic ocean environment. We have used the Naval Postgraduate School smart climatology process, including state-of-the-science atmospheric and oceanic re-analysis data sets, to create smart ocean climatologies. Comparisons of these climatologies with existing Navy climatologies based on the Generalized Digital Environmental Model (GDEM) reveal differences in sonic layer depth (SLD) and sound speed. These differences lead, in turn, to tactically significant differences in the results from Navy TDAs that support undersea warfare.

In this thesis, the performance and accuracy of explicit, semiimplicit, and Hybrid EulerianLagrangian SemiImplicit (HELSI) timeintegration methods used in atmospheric modeling are examined. Four test cases are analyzed: A density current, an inertial gravity wave, a rising thermal bubble, and a hydrostatic mountain wave. Strict attention is paid to computational time, stability criteria, and accuracy. The project aims to show increased efficiency using the HELSI method over fully semiimplicit methods, which, in turn, should be better than the splitexplicit methods currently used in mesoscale models such as WRF, COAMPS, and the German LM model. This increase in efficiency allows for valuable computational resources to be used for other purposes, such as improved data assimilation, increased spatial resolution, or more detailed physics.

We have developed metrics of the performance and operational impacts of METOC support to strike operations conducted on operational aircraft carriers (CVs). Our goal was to assess that support and make recommendations on improving it. We adapted an existing automated real time METOC metrics system, which was developed for land based training missions, for use on CVs by developing a new data collection form, new metrics, and new collection, analysis, and reporting architecture for the remote entering of sensitive mission data without compromise. The weather support element of a CV, the OA division, does not provide strike mission planning support, but does provide situational awareness to pilots. Our system allows that situational awareness to be measured and assessed using metrics that quantify the performance of the forecasts, the relationship of the forecasts to the mitigating actions taken by pilots due to adverse weather conditions, and the effects of individual weather phenomena on the execution of strike missions. A key element of the data collection, analysis, and reporting system developed in this study is the collection of METOC related data from pilots during their intelligence debriefings. This system is readily adaptable for the assessment of METOC support to other warfare areas.

"For acoustic frequencies of interest in the development of undersea wireless wide-area networks, wind noise is the dominant contribution to channel noise. The large dynamic range of wind noise forces the network designer to consider wide variations in link margin and effective node-to-node range. Previous reported correlations of acoustic communication performance and wind speed led to multiple hypotheses explaining degradation, including noise variability as well as wind-driven sea-surface effects such as roughness, entrained bubbles, mixing, and stratification. This theses examines operations of a 40-node wide-area acoustic network in varying noise conditions. This data set is unique in that the environment is strongly downward refracting. Based on theoretical models, wind noise is assumed to dominate all other noise sources. Considerations include dependence of link margin and range on wind speed. Although the experiment was not designed to examine the correlation between transmission range and wind speed, a weak correlation was observed in the limited data set available." p. i.

Performance of high resolution mesoscale models has been in a continuous state of refinement since their inception. Mesoscale models have become quite skillful in forecasting synoptic scale events such as mid-latitude cyclones. However, atmospheric forcing becomes a much more complicated process when faced with the challenge of forecasting near topography along the coastline. Phenomena such as gap flows, blocked flow winds and low level stratification become important to predictability at these scales. The problem is further complicated by the dynamics of a frontal passage event. The skill of mesoscale models in predicting these winds is not as well developed. This study examines several forecasts by the Coupled Ocean Atmospheric Mesoscale Prediction System (COAMPS) during frontal passage events for the Winter of 2003-2004. An attempt is made to characterize the predictability of the wind speed and direction both before and after frontal passage along the California coast. Synoptic forcing during this time is strong due to the effects of the mid-latitude cyclones propagate across the Pacific. The study's results indicate that the wind field predictability is subject to several consistent errors associated with the passage of fronts over topography. These errors arise due to difficulty in the model capturing weak thermal advection events and topographic wind funneling. The deficiencies in model representation of topography contributes to these errors.

The theory of oceanic convection and entrainment has been developed mainly in horizontally homogeneous regimes, yet large-scale spatial variability is known to control the sites and intensity of deep convection. Wintertime Greenland Sea conditions were selected to simulate convection and quantify the interplay between local forcing and large-scale gradients. Here circulation and preconditioning produce horizontal gradients in the stratification; some of the resulting stratification conducive to the formation of thermobaric convective instabilities. A large eddy simulation (LES) model modified to include large-scale horizontal density gradients was used to study the effects of the gradients on turbulence. Horizontal turbulent kinetic energy (IKE) and scalar variances increased compared to simulations with no large-scale gradient. The additional horizontal IKE is created at scales larger than the convective plume scale. A mean horizontal circulation develops in response to the large-scale overturning. The balance between convection and overturning increases stratification in the lower region of the mixed layer, and plumes may undergo slantwise convection.

The theory of oceanic convection and entrainment has been developed mainly in horizontally homogeneous regimes, yet large-scale spatial variability is known to control the sites and intensity of deep convection. Wintertime Greenland Sea conditions were selected to simulate convection and quantify the interplay between local forcing and large-scale gradients. Here circulation and preconditioning produce horizontal gradients in the stratification; some of the resulting stratification conducive to the formation of thermobaric convective instabilities. A large eddy simulation (LES) model modified to include large- scale horizontal density gradients was used to study the effects of the gradients on turbulence. Horizontal turbulent kinetic energy (IKE) and scalar variances increased compared to simulations with no large-scale gradient. The additional horizontal IKE is created at scales larger than the convective plume scale. A mean horizontal circulation develops in response to the large-scale overturning. The balance between convection and overturning increases stratification in the lower region of the mixed layer, and plumes may undergo slantwise convection.

For MUC-7, BBN has for the first time fielded a fully-trained system for NE, TE, and TR; results are all the output of statistical language models trained on annotated data, rather than programs executing handwritten rules. Such trained systems have some significant advantages: 1. They can be easily ported to new domains by simply annotating data with semantic answers. 2. The complex interactions that make rule-based systems difficult to develop and maintain can here be learned automatically from the training data. We believe that the results in this evaluation are evidence that such trained systems, even at their current level of development, can perform roughly on a par with rules hand-tailored by experts. Since MUC-3, BBN has been steadily increasing the proportion of the information extraction process that is statistically trained. Already in MET-1, our name-finding results were the output of a fully statistical, HMM-based model, and that statistical Identifinder(trademark) model was also used for the NE task in MUC-7. For the MUC-7 TE and TR tasks, BBN developed SIFT, a new model that represents a significant further step along this path, replacing PLUM, a system requiring handwritten patterns, with SIFT, a single integrated trained model., Presented at the Message Understanding Conference (7th), MUC-7, held in Fairfax, VA on 29 Apr-1 May 1998 and published in proceedings of the same. The original document contains color images.

A bulk turbulence-closure mixed layer model is generalized to allow prediction of very deep polar sea mixing. The model includes unsteady three-component turbulent kinetic energy budgets. In addition to terms for shear production, pressure redistribution, and dissipation, special attention is devoted to realistic treatment of thermobaric enhancement of buoyancy flux and to Coriolis effect on turbulence. The model is initialized and verified with CTD data taken by R/V Valdivia in the Greenland Sea during winter 1993-1994. Model simulations show (1) mixed layer deepening is significantly enhanced when the thermal expansion coefficient's increase with pressure is included; (2) entrainment rate is sensitive to the direction of wind stress because of Coriolis; and (3) the predicted mixed layer depth evolution agrees qualitatively with the observations. Results demonstrate the importance of water column initial conditions, accurate representation of strong surface cooling events, and inclusion of the thermobaric effect on buoyancy, to determine the depth of mixing and ultimately the heat and salt flux into the deep ocean. Since coupling of the ocean to the atmosphere through deep mixed layers in polar regions is fundamental to our climate system, it is important that regional and global models be developed that incorporate realistic representation of this coupling.

A bulk turbulence-closure mixed layer model is generalized to allow prediction of very deep polar sea mixing. The model includes unsteady three- component turbulent kinetic energy budgets. In addition to terms for shear production, pressure redistribution, and dissipation, special attention is devoted to realistic treatment of thermobaric enhancement of buoyancy flux and to Coriolis effect on turbulence. The model is initialized and verified with CTD data taken by R/V Valdivia in the Greenland Sea during winter 1993-1994. Model simulations show (1) mixed layer deepening is significantly enhanced when the thermal expansion coefficient's increase with pressure is included; (2) entrainment rate is sensitive to the direction of wind stress because of Coriolis; and (3) the predicted mixed layer depth evolution agrees qualitatively with the observations. Results demonstrate the importance of water column initial conditions, accurate representation of strong surface cooling events, and inclusion of the thermobaric effect on buoyancy, to determine the depth of mixing and ultimately the heat and salt flux into the deep ocean. Since coupling of the ocean to the atmosphere through deep mixed layers in polar regions is fundamental to our climate system, it is important that regional and global models be developed that incorporate realistic representation of this coupling

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The theory of oceanic convection and entrainment has been developed mainly in horizontally homogeneous regimes, yet large-scale spatial variability is known to control the sites and intensity of deep convection. Wintertime Greenland Sea conditions were selected to simulate convection and quantify the interplay between local forcing and large-scale gradients. Here circulation and preconditioning produce horizontal gradients in the stratification; some of the resulting stratification conducive to the formation of thermobaric convective instabilities. A large eddy simulation (LES) model modified to include large- scale horizontal density gradients was used to study the effects of the gradients on turbulence. Horizontal turbulent kinetic energy (IKE) and scalar variances increased compared to simulations with no large-scale gradient. The additional horizontal IKE is created at scales larger than the convective plume scale. A mean horizontal circulation develops in response to the large-scale overturning. The balance between convection and overturning increases stratification in the lower region of the mixed layer, and plumes may undergo slantwise convection., http://archive.org/details/entrainmentdetra1094539421, US Navy (USN) author

Performance of high resolution mesoscale models has been in a continuous state of refinement since their inception. Mesoscale models have become quite skillful in forecasting synoptic scale events such as mid-latitude cyclones. However, atmospheric forcing becomes a much more complicated process when faced with the challenge of forecasting near topography along the coastline. Phenomena such as gap flows, blocked flow winds and low level stratification become important to predictability at these scales. The problem is further complicated by the dynamics of a frontal passage event. The skill of mesoscale models in predicting these winds is not as well developed. This study examines several forecasts by the Coupled Ocean Atmospheric Mesoscale Prediction System (COAMPS) during frontal passage events for the Winter of 2003-2004. An attempt is made to characterize the predictability of the wind speed and direction both before and after frontal passage along the California coast. Synoptic forcing during this time is strong due to the effects of the mid-latitude cyclones propagate across the Pacific. The study's results indicate that the wind field predictability is subject to several consistent errors associated with the passage of fronts over topography. These errors arise due to difficulty in the model capturing weak thermal advection events and topographic wind funneling. The deficiencies in model representation of topography contributes to these errors., http://archive.org/details/evaluationofcoam109452281, Lieutenant, United States Navy, Approved for public release; distribution is unlimited.