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Existing circular RNA (circRNA) databases have become essential for transcriptomics. However, most are unsuitable for mining in-depth information for candidate circRNA prioritization. To address this, we integrate circular transcript collections to develop the circAtlas database based on 1070 RNA-seq samples collected from 19 normal tissues across six vertebrate species. This database contains 1,007,087 highly reliable circRNAs, of which over 81.3% have been assembled into full-length sequences. We profile their expression pattern, conservation, and functional annotation. We describe a novel multiple conservation score, co-expression, and regulatory networks for circRNA annotation and prioritization. CircAtlas can be accessed at http://circatlas.biols.ac.cn/ .

Marine Spatial Planning (MSP) provides a process that uses spatial data and models to evaluate environmental, social, economic, cultural, and management trade-offs when siting (i.e., strategically locating) ocean industries. Aquaculture is the fastest-growing food sector in the world. The United States (U.S.) has substantial opportunity for offshore aquaculture development given the size of its exclusive economic zone, habitat diversity, and variety of candidate species for cultivation. However, promising aquaculture areas overlap many protected species habitats. Aquaculture siting surveys, construction, operations, and decommissioning can alter protected species habitat and behavior. Additionally, aquaculture-associated vessel activity, underwater noise, and physical interactions between protected species and farms can increase the risk of injury and mortality. In 2020, the U.S. Gulf of Mexico was identified as one of the first regions to be evaluated for offshore aquaculture opportunities as directed by a Presidential Executive Order. We developed a transparent and repeatable method to identify aquaculture opportunity areas (AOAs) with the least conflict with protected species. First, we developed a generalized scoring approach for protected species that captures their vulnerability to adverse effects from anthropogenic activities using conservation status and demographic information. Next, we applied this approach to data layers for eight species listed under the Endangered Species Act, including five species of sea turtles, Rice’s whale, smalltooth sawfish, and giant manta ray. Next, we evaluated four methods for mathematically combining scores (i.e., Arithmetic mean, Geometric mean, Product, Lowest Scoring layer) to generate a combined protected species data layer. The Product approach provided the most logical ordering of, and the greatest contrast in, site suitability scores. Finally, we integrated the combined protected species data layer into a multi-criteria decision-making modeling framework for MSP. This process identified AOAs with reduced potential for protected species conflict. These modeling methods are transferable to other regions, to other sensitive or protected species, and for spatial planning for other ocean-uses.

In the USA and the European Union, buildings account for more than 40% of total energy use and a large proportion of buildings are energy inefficient. Countries address these inefficiency challenges with various initiatives and strategies. One of them relies on rating buildings with energy performance certificates, with the goal that awareness on energy consumption would lead to an efficient retrofit. In this article, we analyze the different methods chosen by the USA and France to rate multifamily buildings, i.e., the Energy Star score and the Diagnostic de Performance Energétique. We conduct a case study of a multifamily housing using a Design of Experiments to determine what inputs are the most influent on the output. In the French certificate, the results show that the climate, ventilation system, and building envelope are the most influent inputs on the energy consumption. In the USA certificate, the actual energy consumption and the climate are the most influent factors on the building score. We then discuss the significant differences in the two approaches, and the consequences in terms of accuracy, as well as how the DPE and ES scores are used as a tool in public energy policy to propose energy conservation measures and reduce energy consumption.

Increasingly, private landowners are participating in conservation easement programs, but their effects on land management remain to be addressed. Data from the USDA Forest Service National Woodland Owner Survey for the US Northern Region were used to investigate how conservation easement participation is associated with selected past and future forest management practices. Multiple data imputation was used to correct for missing data bias, and propensity score matching was applied to correct for selection bias. Results show that only the adoption of forest management plans, among 17 forest management practices, was significantly and positively correlated with easement participation. Conservation easements legally bind participants to maintain land forested, but there was no evidence of greater association between easement participation and active forest management practices, including timber harvesting. These findings suggest that adoption of conservation easements is a policy tool that can preserve forestland from changing to other uses but may not necessarily be conducive to wider implementation of land practices necessary for long-term protection of forests.

Sustainable construction practices rely on carefully selecting building materials and balancing environmental and economic considerations. This study examines the complex link between local climate, market dynamics, and building material selection. Market data analysis, parametric modeling, and brute‐force optimization are used to provide insights into construction decision‐making. Across 5540 simulations, a thorough assessment of the financial and energy performance of various materials for walls, roofs, windows, and floors is conducted. Incorporating Pareto ranking, parallel simulation, and sensitivity analysis, the comprehensive evaluation reveals the intricate tradeoffs between cost, thermal properties, and energy savings. The findings highlight the potential for optimal external wall solutions to reduce U ‐values by up to 30% and achieve source energy savings of up to 25% source energy savings across diverse climates. By emphasizing the importance of local context in material selection, this study highlights how energy consumption patterns and transmission losses influence financial and energy performance, thus advancing sustainable construction practices.

Evaluation of selective decontamination of the digestive tract (SDD) on late mortality in ventilated trauma patients in an intensive care unit (ICU). A multicenter, randomized controlled trial was undertaken in 401 trauma patients with Hospital Trauma Index-Injury Severity Score of 16 or higher. Patients were randomized to control (n=200) or SDD (n=201), using polymyxin E, tobramycin, and amphotericin B in throat and gut throughout ICU treatment combined with cefotaxime for 4 days. Primary endpoint was late mortality excluding early death from hemorrhage or craniocerebral injury. Secondary endpoints were infection and organ dysfunction. Mortality was 20.9% with SDD and 22.0% in controls. Overall late mortality was 15.3% (57/372) as 29 patients died from cerebral injury, 16 SDD and 13 control. The odds ratio (95% confidence intervals) of late mortality for SDD relative to control was 0.75 (0.40-1.37), corresponding to estimates of 13.4% SDD and 17.2% control. The overall infection rate was reduced in the test group (48.8% vs. 61.0%). SDD reduced lower airway infections (30.9% vs. 50.0%) and bloodstream infections due to aerobic Gram-negative bacilli (2.5% vs. 7.5%). No difference in organ dysfunction was found. This study demonstrates that SDD significantly reduces infection in multiple trauma, although this RCT in 401 patients was underpowered to detect a mortality benefit.

An integrative negotiation model is proposed so that watershed committees (WSC) can deal better with conflicts over alternatives for protecting water resources from pollution and overcoming water shortages by, for example, making conscious use of water and soil, introducing best agricultural practices, and recovering riparian forest. All of these have an impact on the hydrological cycle and the health of the basin. The proposed model consists of three phases: pre-negotiation, negotiation, and post-negotiation. In the pre-negotiation phase, an approach that extends value focused thinking to situations that involve a group is applied to provide WSC members (representatives from different segments of society) with the opportunity to think creatively about their values, objectives, attributes, and also to generate alternatives that integrate their perspectives and encourage collaboration for the efficient and sustainable use of water. In the negotiation phase, multi-objective optimization models and the global criterion method (GCM) are used so as to select sets of alternatives and to allocate them among the representatives of the WSC. Also, GCM is proposed as a new way of scoring proposals in the bargaining process. Finally, in the post-negotiation phase, the agreement on implementing alternatives is formalized. A realistic case study based on the WSC of the Pajeú River in northeastern Brazil is presented to illustrate the use of the proposed model and the results show the compromise solution between the segments. This study advances the understanding of negotiating alternatives for preserving water resources from a proactive perspective and also enhances users’ ability to use this model to resolve conflicts in other hydrographic basins worldwide.

The aim of this study was to assess the ability of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) II scoring system, and Trauma and Injury Severity Score (TRISS) method to predict group mortality for intensive care unit (ICU) trauma patients. The medical records of 706 consecutive major trauma patients admitted to the ICU of Samsung Changwon Hospital from May 2006 to April 2010 were retrospectively examined. The SOFA and the APACHE II scores were calculated based on data from the first 24 hours of ICU admission, and the TRISS was calculated using initial laboratory data from the emergency department and operative data. The probability of death was calculated for each patient based on the SOFA score, APACHE II score, and TRISS equations. The ability to predict group mortality for the SOFA score, APACHE II score, and TRISS method was assessed by using 2-by-2 decision matrices and receiver operating characteristic curve analysis and calibration analysis. In 2-by-2 decision matrices with a decision criterion of 0.5, the sensitivities, specificities, and accuracies were 74.1%, 97.1%, and 92.4%, respectively, for the SOFA score; 58.5%, 99.6%, and 91.1%, respectively, for the APACHE II scoring system; and 52.4%, 94.8%, and 86.0%, respectively, for the TRISS method. In the receiver operating characteristic curve analysis, the areas under the curve for the SOFA score, APACHE II scoring system, and TRISS method were 0.953, 0.950, and 0.922, respectively. The results from the present study showed that the SOFA score was not different from APACHE II scoring system and TRISS in predicting the outcomes for ICU trauma patients. However, the method for calculating SOFA scores is easier and simpler than APACHE II and TRISS.

To determine whether severity and organ failure scores over the first 3 days in an ICU predict in-hospital mortality in onco-hematological malignancy patients. Retrospective study in a 22-bed medical ICU. 92 consecutive patients with onco-hematological malignancies including 20 hematopoietic stem cell transplantation (HSCT) patients (11 with allogenic HSCT). Simplified Acute Physiology Score (SAPS) II, Organ Dysfunction and/or Infection (ODIN) score, Logistic Organ Dysfunction System (LODS), and Sequential Organ Failure Assessment (SOFA) score were recorded on admission. The change in each score (Delta score) during the first 3 days in the ICU was calculated as follows: severity or organ failure score on day 3 minus severity or organ failure score on day 1, divided by severity or organ failure score on day 1. In-hospital mortality was 58%. Using multivariate analysis in-hospital mortality was predicted by all scores on day 1 and all Delta scores. Areas under the receiver operating characteristics curves were similar for SAPS II (0.78), ODIN (0.78), LODS (0.83), and SOFA (0.78) scores at day 1. They were also similar for DeltaSAPS II, DeltaODIN, DeltaLODS, and DeltaSOFA. Similar results were observed when excluding patients with allogenic HSCT. Severity and three organ failure scores on day 1 and Delta scores perform similarly in predicting in-hospital mortality in ICU onco-hematological malignancy patients but do not predict individual outcome. Decision to admit such patients to the ICU or to forgo life-sustaining therapies should not be based on these scores.

Our research investigates the effects of residential energy efficiency audit programs on subsequent household electricity consumption. Here there is a one-time interaction between households, which participate voluntarily, and the surveyors. Our research objective is to determine whether and to what extent the surveys lead to behavioral changes. We then examine how persistent the intervention is over time and whether the effects decay or intensify. The main evaluation problem here is survey participants’ self-selection, which we address econometrically via several non-parametric estimators involving kernel-based propensity-score matching. In the first method we use difference-in-differences (DID) estimation. Our second estimator is quantile DID, which produces estimates on distributions. The comparison group consists of households who were not yet participating in the survey but participated later. Our evidence is that the customers who participated in the survey reduced their electricity consumption by about 7%, on average compared to customers who had not yet participated in the survey. Considering the total number of high-usage households participating in the survey in 2009, we estimate that electricity consumption was reduced by an aggregate of 2 million kWh per year, which is approximately equal to the monthly consumption of 3500 typical households in California with an estimated 1527 metric tons less of carbon dioxide emissions. Because the energy audit program is inexpensive ( $10–$ 20 per household) a key issue is that while the program is cost-effective, is it regressive? We find that as the quantiles of the outcome distribution increase, high-use households save proportionally less electricity than do low-use customers. Overall, our results imply that program designers can better target low-use and low-income households, because they are more likely to benefit from the programs through energy savings.