Target detection against narrow band noise backgrounds

AbstractWe studied the detectability of narrow band random noise targets embedded in narrow band random noise backgrounds as a function of differences in center frequency, spatial frequency bandwidth and orientation bandwidth between target and the immediately adjacent background. Unlike most target detection experiments the targets were not added to the background; they replaced the underlying background texture. Simulations showed that target detection probabilities could be accounted for by a simple transformation on the summed outputs of a two layer filter model similar to the complex channels model proposed by Graham, Beck and Sutter (Graham, N., Beck, J., & Sutter, A. (1992). Vision Research, 32, 719–743). Subsequently, the model was tested on the detection of camouflaged vehicle targets with encouraging results

Effects of thyroid status and thyrostatic drugs on hepatic glucuronidation of lodothyronines and other substrates in rats - Induction of phenol UDP-glucuronyltransferase by methimazole

Glucuronidation of iodothyronines in rat liver is catalyzed by at least three UDP-glucuronyltransferases (UGTs): bilirubin UGT, phenol UGT, and androsterone UGT. Bilirubin and phenol UGT activities are regulated by thyroid hormone, but the effect of thyroid status on hepatic glucuronidation of iodothyronines is unknown. We examined the effects of hypothyroidism induced by treatment of rats with propylthiouracil (PTU) or methimazole (MMI) or by thyroidectomy as well as the effects of T4-induced hyperthyroidism on the hepatic UGT activities for T4, T3, bilirubin, p-nitrophenol (PNP), and androsterone. Bilirubin UGT activity was increased in MMI- or PTU-induced hypothyroid and thyroidectomized rats, and decreased in hyperthyroid animals. T4 and, to a lesser extent, T3 UGT activities were increased in MMI- or PTU-induced hypothyroid rats, and T4 but not T3 glucuronidation also showed a significant increase in thyroidectomized rats. T4 but not T3 UGT activity was slightly decreased in hyperthyroid rats. While PNP UGT activity was decreased in thyroidectomized rats and increased in hyperthyroid animals, it was also markedly increased by MMI and slightly increased by PTU-induced hypothyroidism. In T4-substituted rats, MMI did not affect T4, T3, bilirubin and androsterone UGT activities but again strongly induced PNP UGT activity, indicating that this represented a direct induction of PNP UGT by the drug independent of its thyrostatic action. Androsterone UGT activity was hardly affected by thyroid status. Our results suggest a modest, negative control of the hepatic glucuronidation of thyroid hormone by thyroid status, which may be mediated by changes in bilirubin UGT activity. To our knowledge, this is the first report of the marked induction of a hepatic enzyme by MMI, which is not mediated by its thyroid hormone-lowering effect

Integrating Machine Learning and Multiscale Modeling: Perspectives, Challenges, and Opportunities in the Biological, Biomedical, and Behavioral Sciences

Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunity in this regard. However, classical machine learning techniques often ignore the fundamental laws of physics and result in ill-posed problems or non-physical solutions. Multiscale modeling is a successful strategy to integrate multiscale, multiphysics data and uncover mechanisms that explain the emergence of function. However, multiscale modeling alone often fails to efficiently combine large data sets from different sources and different levels of resolution. We show how machine learning and multiscale modeling can complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces. We critically review the current literature, highlight applications and opportunities, address open questions, and discuss potential challenges and limitations in four overarching topical areas: ordinary differential equations, partial differential equations, data-driven approaches, and theory-driven approaches. Towards these goals, we leverage expertise in applied mathematics, computer science, computational biology, biophysics, biomechanics, engineering mechanics, experimentation, and medicine. Our multidisciplinary perspective suggests that integrating machine learning and multiscale modeling can provide new insights into disease mechanisms, help identify new targets and treatment strategies, and inform decision making for the benefit of human health

Standardization of Epidemiological Surveillance of Group A Streptococcal Impetigo

Impetigo is a highly contagious bacterial infection of the superficial layer of skin. Impetigo is caused by group A Streptococcus (Strep A) and Staphylococcus aureus, alone or in combination, with the former predominating in many tropical climates. Strep A impetigo occurs mainly in early childhood, and the burden varies worldwide. It is an acute, self-limited disease, but many children experience frequent recurrences that make it a chronic illness in some endemic settings. We present a standardized surveillance protocol including case definitions for impetigo including both active (purulent, crusted) and resolving (flat, dry) phases and discuss the current tests used to detect Strep A among persons with impetigo. Case classifications that can be applied are detailed, including differentiating between incident (new) and prevalent (existing) cases of Strep A impetigo. The type of surveillance methodology depends on the burden of impetigo in the community. Active surveillance and laboratory confirmation is the preferred method for case detection, particularly in endemic settings. Participant eligibility, surveillance population and additional considerations for surveillance of impetigo, including examination of lesions, use of photographs to document lesions, and staff training requirements (including cultural awareness), are addressed. Finally, the core elements of case report forms for impetigo are presented and guidance for recording the course and severity of impetigo provided

Cardiovascular and renal outcomes with canagliflozin according to baseline diuretic use:a post hoc analysis from the CANVAS Program

Aims The CANVAS Program identified the effect of canagliflozin on major adverse cardiovascular events (MACE) differed according to whether participants were using diuretics at study commencement. We sought to further evaluate this finding related to baseline differences, treatment effects, safety, and risk factor changes.Methods and results The CANVAS Program enrolled 10 142 participants with type 2 diabetes mellitus and high cardiovascular risk. Participants were randomized to canagliflozin or placebo and followed for a mean of 188 weeks. The primary outcome was major cardiovascular events, a composite of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke. Secondary outcomes included multiple cardiovascular, renal, and safety events. In this post hoc subgroup analysis, participants were categorized according to baseline use of any diuretic. The effect on outcomes was compared using Cox proportional hazards models, while risk factor changes were compared using mixed-effect models. At baseline, 4490 (44.3%) participants were using a diuretic. Compared with those not using a diuretic, participants using a diuretic were more likely to be older (mean age +/- standard deviation, 64.3 +/- 8.0 vs. 62.5 +/- 8.3), be female (38.9% vs. 33.4%), and have heart failure (19.6% vs. 10.3%) (all P-difference &lt; 0.0001). The effect of canagliflozin on major cardiovascular events was greater for those using diuretic at baseline than for those who were not [adjusted hazard ratio 0.65 (95% confidence interval 0.54-0.78) vs. adjusted hazard ratio 1.13 (95% confidence interval 0.93-1.36), P-heterogeneity &lt; 0.0001]. Changes in most risk factors, including blood pressure, body weight, and urine albumin-to-creatinine ratio, were similar between groups (all P-difference &gt; 0.11), although the effect of canagliflozin on haemoglobin A1c reduction was slightly weaker in participants using compared with not using diuretics at baseline (-0.52% vs. -0.64%, P-heterogeneity = 0.0007). Overall serious adverse events and key safety outcomes, including adverse renal events, were also similar (all P-heterogeneity &gt; 0.07).Conclusions Participants on baseline diuretics derived a greater benefit for major cardiovascular events from canagliflozin, which was not fully explained by differences in participant characteristics nor risk factor changes.</p

Development of the Resource Prospector Planetary Rover

The Resource Prospector (RP) is an In-Situ Resource Utilization (ISRU) lunar rover mission under study by NASA. RP is planned to launch in 2020 to prospect for subsurface volatiles and to extract oxygen from lunar regolith. The mission will address several of NASA's "Strategic Knowledge Gaps" for lunar exploration. The mission will also address the Global Exploration Roadmap's strategic goal of using local resources for human exploration. The distribution of lunar subsurface volatiles drives the mission requirement for mobility. The spatial distribution is hypothesized to be governed by impact cratering with the top 0.5 m being patchy at scales of 100 m. The mixing time scale increases with depth (less frequent larger impacts). Consequently, increased mobility reduces the depth requirement for sampling. The target RP traverse will extend 1 km radially from the landing site to sample craters of varying sizes. Sampling craters with different ages will reveal possible volatile emplacement history. In 1 Ga, approximately 60-70 craters of 10 m diameter form per km2. Thus, the rover will need to sample at least ten of these craters, which may require a total traverse path length of 2-3 km. During 2014-2015, we developed an initial prototype rover for RP. The current design is a solar powered, four-wheeled vehicle, with hub motor drive, offset four wheel steering, and active suspension. Active suspension provides capabilities including changing vehicle ride height, traversing comparatively large obstacles, and controlling load on the wheels. All-wheel steering enables the vehicle to point arbitrarily while roving, e.g., to keep the solar array pointed at the sun while in motion. The offset steering combined with active suspension improves driving in soft soil. The rover's on-board software utilizes NASA's Core Flight Software, which is a reusable flight software environment. During 2015, we completed the initial rover software build, which provides low-level hardware interfaces, basic mobility control, waypoint driving, odometry, basic error checking, and camera services. Development of the prototype rover has enabled maturation of many of the subsystems to TRL 5. During the next year, we will conduct integrated testing of concepts of operation, navigation, and remote driving tools. In addition, we will perform environmental tests including radiation (avionics), thermal and thermal/vacuum (mechanisms), and gravity offload (mobility)

Goal disruption theory, military personnel, and the creation of merged profiles: A mixed method investigation

The present study provides an example of the integrated data analysis technique of creating and interpreting merged profiles. By using this approach to merging data sources, we gained unique insight into goal disruption theory (GDT). Qualitative data suggest that military personnel harbor a wide range of desired end-states. Quantitative data support a component of GDT, suggesting that participants who have a strong need for desired end-state displayed greater purposive harm endurance. Interpretation of merged profiles revealed caveats to this relationship, in particular that not all end-states are equally motivating. Results illustrate the benefits of the integrated data analysis technique of creating and interpreting merged profiles. Utilization of the merged profiles illuminated relationships that would not have been exposed otherwise

The effects of canagliflozin on heart failure and cardiovascular death by baseline participant characteristics:Analysis of the CREDENCE trial

Heart failure is prevalent in those with type 2 diabetes and chronic kidney disease, and is associated with significant mortality and morbidity. In the CREDENCE trial, canagliflozin reduced the risk of hospitalization for heart failure (HHF) or cardiovascular (CV) death by 31%. In the current analysis we sought to determine whether the effect of canagliflozin on HHF/CV death differed in subgroups defined by key baseline participant characteristics. Cox regression models were used to estimate hazard ratios and 95% confidence intervals. Canagliflozin was associated with a reduction in the relative risk of HHF/CV death regardless of age, sex, history of heart failure or CV disease, and the use of loop diuretics or glucagon-like peptide-1 receptor agonists (all p(interaction) > .114). The absolute benefit of canagliflozin was greater in those at highest baseline risk, such as those with CV disease (50 fewer events/1000 patients treated over 2.5 years vs. 20 fewer events in those without CV disease) or advanced kidney disease (estimated glomerular filtration rate [eGFR] 30-45 mL/min/1.73m(2): 61 events prevented/1000 patients treated over 2.5 years vs. 23 events in eGFR 60-90 mL/min/1.73m(2)). Canagliflozin consistently reduces the proportional risk of HHF/CV death across a broad range of subgroups with greater absolute benefits in those at highest baseline risk