| 1. |
- Capo, Eric, et al.
(författare)
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Lake sedimentary dna research on past terrestrial and aquatic biodiversity: Overview and recommendations
- 2021
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Ingår i: Quaternary. - : MDPI. - 2571-550X. ; 4:1
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Forskningsöversikt (refereegranskat)abstract
- The use of lake sedimentary DNA to track the long-term changes in both terrestrial and aquatic biota is a rapidly advancing field in paleoecological research. Although largely applied nowadays, knowledge gaps remain in this field and there is therefore still research to be conducted to ensure the reliability of the sedimentary DNA signal. Building on the most recent literature and seven original case studies, we synthesize the state-of-the-art analytical procedures for effective sampling, extraction, amplification, quantification and/or generation of DNA inventories from sedimentary ancient DNA (sedaDNA) via high-throughput sequencing technologies. We provide recommendations based on current knowledge and best practises.
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| 2. |
- de Rubeis, Tullio, et al.
(författare)
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Learning lighting models for optimal control of lighting system via experimental and numerical approach
- 2021
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Ingår i: Science and Technology for the Built Environment. - : Informa UK Limited. - 2374-4731 .- 2374-474X. ; 27:8, s. 1018-1030
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Tidskriftsartikel (refereegranskat)abstract
- Lighting control systems have been traditionally employed to reduce energy use for lighting by, for example, maximizing daylight harvesting. When highly efficient light sources are installed and for tasks where maintaining target illuminance is particularly important, designers may decide to prioritize the latter together with energy use. In this context, the use of data-driven algorithms is emerging. In this paper different data-driven approaches are proposed as lighting control systems, to maximize daylight harvestingand to optimize energy consumption. The approaches employ experimental data of occupancy and lighting switch on/off events of a private side-lit office in an academic building. The office is later modeled in DIVA4Rhino to provide yearly illuminances and electric lighting dimming profiles. These data are used to implement data-driven optimal controls. Three different approaches have beenemployed: Regression Trees; Random Forests; Least Squares. Different lighting control strategies have been hypothesized based on installed Lighting Power Densities (LPD). Results show that Regression Trees outperforms both Least Squares and Random Forests, in terms of model accuracy and control performance.
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| 3. |
- Vergaro, Giuseppe, et al.
(författare)
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NT-proBNP for Risk Prediction in Heart Failure : Identification of Optimal Cutoffs Across Body Mass Index Categories
- 2021
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Ingår i: JACC. Heart failure. - : American College of Cardiology. - 2213-1779 .- 2213-1787. ; 9:9, s. 653-663
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesThe goal of this study was to assess the predictive power of N-terminal pro–B-type natriuretic peptide (NT-proBNP) and the decision cutoffs in heart failure (HF) across body mass index (BMI) categories.BackgroundConcentrations of NT-proBNP predict outcome in HF. Although the influence of BMI to reduce levels of NT-proBNP is known, the impact of obesity on prognostic value remains uncertain.MethodsIndividual data from the BIOS (Biomarkers In Heart Failure Outpatient Study) consortium were analyzed. Patients with stable HF were classified as underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25-29.9 kg/m2), and mildly (BMI 30-34.9 kg/m2), moderately (BMI 35-39.9 kg/m2), or severely (BMI ≥40 kg/m2) obese. The prognostic role of NT-proBNP was tested for the endpoints of all-cause and cardiac death.ResultsThe study population included 12,763 patients (mean age 66 ± 12 years; 25% women; mean left ventricular ejection fraction 33% ± 13%). Most patients were overweight (n = 5,176), followed by normal weight (n = 4,299), mildly obese (n = 2,157), moderately obese (n = 612), severely obese (n = 314), and underweight (n = 205). NT-proBNP inversely correlated with BMI (β = –0.174 for 1 kg/m2; P < 0.001). Adding NT-proBNP to clinical models improved risk prediction across BMI categories, with the exception of severely obese patients. The best cutoffs of NT-proBNP for 5-year all-cause death prediction were lower as BMI increased (3,785 ng/L, 2,193 ng/L, 1,554 ng/L, 1,045 ng/L, 755 ng/L, and 879 ng/L, for underweight, normal weight, overweight, and mildly, moderately, and severely obese patients, respectively) and were higher in women than in men.ConclusionsNT-proBNP maintains its independent prognostic value up to 40 kg/m2 BMI, and lower optimal risk-prediction cutoffs are observed in overweight and obese patients.
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