Autonomous Wildfire Detection System

According to the National Fire Protection Association Journal, federal wildfire suppression costs in the United States have risen from an annual average of about $425 million from 1985 to 1999 up to$1.6 billion from 2000 to 2019. On average, more than 200,000 acres in the United States are burned per year due to wildfires, with more than 700,000 acres burned in 2020 alone. With the risk of wildfire ever rising, there is a need for better early detection of remote wildfires, as existing methods often include long delays like satellites or rely on human lookout towers. The objective is to develop an early, remote wildfire detection device that covers a wide range and quickly transmits warnings to appropriate personnel. The device will be wireless and self-powered as to facilitate deployment in remote areas. In practice there would be a network of these detection units communicating back to a gateway in order to cover a wide area of land in order to help catch wildfires early

Fresh air in the 21st century?

Ozone is an air quality problem today for much of the world's population. Regions can exceed the ozone air quality standards (AQS) through a combination of local emissions, meteorology favoring pollution episodes, and the clean-air baseline levels of ozone upon which pollution builds. The IPCC 2001 assessment studied a range of global emission scenarios and found that all but one projects increases in global tropospheric ozone during the 21st century. By 2030, near-surface increases over much of the northern hemisphere are estimated to be about 5 ppb (+2 to +7 ppb over the range of scenarios). By 2100 the two more extreme scenarios project baseline ozone increases of >20 ppb, while the other four scenarios give changes of -4 to +10 ppb. Even modest increases in the background abundance of tropospheric ozone might defeat current AQS strategies. The larger increases, however, would gravely threaten both urban and rural air quality over most of the northern hemisphere

The Talking Texts: What Pop Culture Really Has to Say

This newsletter is built upon work done in a Fall 2017 honors writing course based around the rhetorical analysis of pop culture. Students wrote several initial analyses before choosing one to research and write about further. They then chose a short excerpt from their researched projects to include in the newsletter

Gut Microbial Stability is Associated with Greater Endurance Performance in Athletes Undertaking Dietary Periodization

Dietary manipulation with high-protein or high-carbohydrate content are frequently employed during elite athletic training, aiming to enhance athletic performance. Such interventions are likely to impact upon gut microbial content. This study explored the impact of acute high-protein or high-carbohydrate diets on measured endurance performance and associated gut microbial community changes. In a cohort of well-matched, highly trained endurance runners, we measured performance outcomes, as well as gut bacterial, viral (FVP), and bacteriophage (IV) communities in a double-blind, repeated-measures design randomized control trial (RCT) to explore the impact of dietary intervention with either high-protein or high-carbohydrate content. High-dietary carbohydrate improved time-trial performance by +6.5% (P < 0.03) and was associated with expansion of Ruminococcus and Collinsella bacterial spp. Conversely, high dietary protein led to a reduction in performance by −23.3% (P = 0.001). This impact was accompanied by significantly reduced diversity (IV: P = 0.04) and altered composition (IV and FVP: P = 0.02) of the gut phageome as well as enrichment of both free and inducible Sk1virus and Leuconostoc bacterial populations. Greatest performance during dietary modification was observed in participants with less substantial shifts in community composition. Gut microbial stability during acute dietary periodization was associated with greater athletic performance in this highly trained, well-matched cohort. Athletes, and those supporting them, should be mindful of the potential consequences of dietary manipulation on gut flora and implications for performance, and periodize appropriately

THE COMMUNITY LEVERAGED UNIFIED ENSEMBLE (CLUE) IN THE 2016 NOAA/HAZARDOUS WEATHER TESTBED SPRING FORECASTING EXPERIMENT

One primary goal of annual Spring Forecasting Experiments (SFEs), which are coorganized by NOAA’s National Severe Storms Laboratory and Storm Prediction Center and conducted in the National Oceanic and Atmospheric Administration’s (NOAA) Hazardous Weather Testbed, is documenting performance characteristics of experimental, convection-allowing modeling systems (CAMs). Since 2007, the number of CAMs (including CAM ensembles) examined in the SFEs has increased dramatically, peaking at six different CAM ensembles in 2015. Meanwhile, major advances have been made in creating, importing, processing, verifying, and developing tools for analyzing and visualizing these large and complex datasets. However, progress toward identifying optimal CAM ensemble configurations has been inhibited because the different CAM systems have been independently designed, making it difficult to attribute differences in performance characteristics. Thus, for the 2016 SFE, a much more coordinated effort among many collaborators was made by agreeing on a set of model specifications (e.g., model version, grid spacing, domain size, and physics) so that the simulations contributed by each collaborator could be combined to form one large, carefully designed ensemble known as the Community Leveraged Unified Ensemble (CLUE). The 2016 CLUE was composed of 65 members contributed by five research institutions and represents an unprecedented effort to enable an evidence-driven decision process to help guide NOAA’s operational modeling efforts. Eight unique experiments were designed within the CLUE framework to examine issues directly relevant to the design of NOAA’s future operational CAM-based ensembles. This article will highlight the CLUE design and present results from one of the experiments examining the impact of single versus multicore CAM ensemble configurations

THE COMMUNITY LEVERAGED UNIFIED ENSEMBLE (CLUE) IN THE 2016 NOAA/HAZARDOUS WEATHER TESTBED SPRING FORECASTING EXPERIMENT

One primary goal of annual Spring Forecasting Experiments (SFEs), which are coorganized by NOAA’s National Severe Storms Laboratory and Storm Prediction Center and conducted in the National Oceanic and Atmospheric Administration’s (NOAA) Hazardous Weather Testbed, is documenting performance characteristics of experimental, convection-allowing modeling systems (CAMs). Since 2007, the number of CAMs (including CAM ensembles) examined in the SFEs has increased dramatically, peaking at six different CAM ensembles in 2015. Meanwhile, major advances have been made in creating, importing, processing, verifying, and developing tools for analyzing and visualizing these large and complex datasets. However, progress toward identifying optimal CAM ensemble configurations has been inhibited because the different CAM systems have been independently designed, making it difficult to attribute differences in performance characteristics. Thus, for the 2016 SFE, a much more coordinated effort among many collaborators was made by agreeing on a set of model specifications (e.g., model version, grid spacing, domain size, and physics) so that the simulations contributed by each collaborator could be combined to form one large, carefully designed ensemble known as the Community Leveraged Unified Ensemble (CLUE). The 2016 CLUE was composed of 65 members contributed by five research institutions and represents an unprecedented effort to enable an evidence-driven decision process to help guide NOAA’s operational modeling efforts. Eight unique experiments were designed within the CLUE framework to examine issues directly relevant to the design of NOAA’s future operational CAM-based ensembles. This article will highlight the CLUE design and present results from one of the experiments examining the impact of single versus multicore CAM ensemble configurations

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference

Antipsychotic medication versus psychological intervention versus a combination of both in adolescents with first-episode psychosis (MAPS): a multicentre, three-arm, randomised controlled pilot and feasibility study

Background Evidence for the effectiveness of treatments in early-onset psychosis is sparse. Current guidance for the treatment of early-onset psychosis is mostly extrapolated from trials in adult populations. The UK National Institute for Health and Care Excellence has recommended evaluation of the clinical effectiveness and cost-effectiveness of antipsychotic drugs versus psychological intervention (cognitive behavioural therapy [CBT] and family intervention) versus the combination of these treatments for early-onset psychosis. The aim of this study was to establish the feasibility of a randomised controlled trial of antipsychotic monotherapy, psychological intervention monotherapy, and antipsychotics plus psychological intervention in adolescents with first-episode psychosis. Methods We did a multicentre pilot and feasibility trial according to a randomised, single-blind, three-arm, controlled design. We recruited participants from seven UK National Health Service Trust sites. Participants were aged 14–18 years; help-seeking; had presented with first-episode psychosis in the past year; were under the care of a psychiatrist; were showing current psychotic symptoms; and met ICD-10 criteria for schizophrenia, schizoaffective disorder, or delusional disorder, or met the entry criteria for an early intervention for psychosis service. Participants were assigned (1:1:1) to antipsychotics, psychological intervention (CBT with optional family intervention), or antipsychotics plus psychological intervention. Randomisation was via a web-based randomisation system, with permuted blocks of random size, stratified by centre and family contact. CBT incorporated up to 26 sessions over 6 months plus up to four booster sessions, and family intervention incorporated up to six sessions over 6 months. Choice and dose of antipsychotic were at the discretion of the treating consultant psychiatrist. Participants were followed up for a maximum of 12 months. The primary outcome was feasibility (ie, data on trial referral and recruitment, session attendance or medication adherence, retention, and treatment acceptability) and the proposed primary efficacy outcome was total score on the Positive and Negative Syndrome Scale (PANSS) at 6 months. Primary outcomes were analysed by intention to treat. Safety outcomes were reported according to as-treated status, for all patients who had received at least one session of CBT or family intervention, or at least one dose of antipsychotics. The study was prospectively registered with ISRCTN, ISRCTN80567433. Findings Of 101 patients referred to the study, 61 patients (mean age 16·3 years [SD 1·3]) were recruited from April 10, 2017, to Oct 31, 2018, 18 of whom were randomly assigned to psychological intervention, 22 to antipsychotics, and 21 to antipsychotics plus psychological intervention. The trial recruitment rate was 68% of our target sample size of 90 participants. The study had a low referral to recruitment ratio (around 2:1), a high rate of retention (51 [84%] participants retained at the 6-month primary endpoint), a high rate of adherence to psychological intervention (defined as six or more sessions of CBT; in 32 [82%] of 39 participants in the monotherapy and combined groups), and a moderate rate of adherence to antipsychotic medication (defined as at least 6 consecutive weeks of exposure to antipsychotics; in 28 [65%] of 43 participants in the monotherapy and combined groups). Mean scores for PANSS total at the 6-month primary endpoint were 68·6 (SD 17·3) for antipsychotic monotherapy (6·2 points lower than at randomisation), 59·8 (13·7) for psychological intervention (13·1 points lower than at randomisation), and 62·0 (15·9) for antipsychotics plus psychological intervention (13·9 points lower than at randomisation). A good clinical response at 6 months (defined as ≥50% improvement in PANSS total score) was achieved in four (22%) of 18 patients receiving antipsychotic monotherapy, five (31%) of 16 receiving psychological intervention, and five (29%) of 17 receiving antipsychotics plus psychological intervention. In as-treated groups, serious adverse events occurred in eight [35%] of 23 patients in the combined group, two [13%] of 15 in the antipsychotics group, four [24%] of 17 in the psychological intervention group, and four [80%] of five who did not receive any treatment. No serious adverse events were considered to be related to participation in the trial. Interpretation This trial is the first to show that a head-to-head clinical trial comparing psychological intervention, antipsychotics, and their combination is safe in young people with first-episode psychosis. However, the feasibility of a larger trial is unclear because of site-specific recruitment challenges, and amendments to trial design would be needed for an adequately powered clinical and cost-effectiveness trial that provides robust evidence

Dark sectors 2016 Workshop: community report

This report, based on the Dark Sectors workshop at SLAC in April 2016, summarizes the scientific importance of searches for dark sector dark matter and forces at masses beneath the weak-scale, the status of this broad international field, the important milestones motivating future exploration, and promising experimental opportunities to reach these milestones over the next 5-10 years