Økt bærekraft ved Måling og Verifikasjon av energitiltak i dagligvaresektoren

The IPCC Sixth Assessment Report leaves little doubt that we urgently need to respond to be able to reduce human-induced climate change. The report clearly states that human activities is causing alarming and widespread disruption in nature and is affecting billions of people. Floods, heatwaves, and droughts are seen more often than ever, and unfortunately, people who are least able to struggle through are most affected. To avoid ascending loss of life, infrastructure, and biodiversity we have to quickly make major cuts in greenhouse gas emissions (GHG) Buildings worldwide consume some 40% of all produced energy and are significant contributors to GHG emissions. Hence, energy efficiency retrofitting is a fundamental step in reducing energy consumption. However, one important barrier that hinders renovation projects is uncertainty regarding the expected savings. The main objective of this thesis is to contribute to lower that barrier and to deliver reliable methods to be used to document and monitor energy savings in retrofitting projects.FNs klimapanels siste rapport (AR6)2 er forstemmende lesning, men også, til forskningsrapport å være, usedvanlig tydelig. I rapporten har 700 eksperter fra 90 forskjellige land bidratt og blitt enige. Kort oppsummert - om vi ønsker å begrense den globale oppvarmingen til 1,5 grad trenger vi kraftige utslippskutt i alle sektorer - umiddelbart. FNs generalsekretær, António Guterres, kaller den siste klimarapporten en «skammens rapport». For å sitere Generalsekretærens relativt umilde beskrivelse av dagens situasjon Det er på tide å slutte å brenne planeten, og starte å investere i den rikelige fornybare energien rundt oss Og om dagens regjeringers og selskapers innsats… …en katalog av tomme løfter som setter oss på sporet av en verden der det ikke går an å leve På global basis forbruker bygninger omtrent 40% av all produsert energi, og er dermed en vesentlig bidragsyter til utslipp av klimagasser. Denne avhandlingen viser at i norsk dagligvare er det mulig å oppnå en energireduksjon på mellom 30 til 55% gitt at det installeres ny teknisk infrastruktur i byggene. I all hovedsak handler denne avhandlingen om hvordan det på en pålitelig måte er mulig å dokumentere og monitorere energireduserende tiltak. Tidligere forskning har vist at usikkerhet rundt oppnådd energibesparelse er en barriere for iverksetting av nye energitiltak. Alle de 5 artiklene i denne avhandlingen omhandler ulike metoder som kan brukes for å redusere denne barrieren og bidra positivt til økt insentiv for mer energieffektive bygg innen norsk dagligvare.publishedVersio

ShinyRBase: Near real-time energy saving models using reactive programming

To document energy savings from retrofitting a building, a reliable baseline model is needed. The development and implementation of the baseline model is an important step in the measurement and verification (M&V) process. Usually, an energy analyst enters the stage, collects data, do the estimation and delivers the baseline model. The modeling work of the energy analyst is done on either a proprietary or open-source statistical software, often using a coding script. If stakeholders want an updated report on energy savings, the analyst must re-do the whole process, for example on a monthly basis. This workflow is based on an imperative programming paradigm. The analyst holds on to the code that performs the analysis and re-run the code when agreed upon. The consequence of this workflow is that stakeholders are dependent on the energy analyst and that updated energy savings results must be planned and scheduled. However, emerging M&V 2.0 technologies enables automation of the energy saving reports. This paper demonstrates how energy savings from retrofitting’s in the Norwegian food retail sector is continuously monitored and documented in a web application. The application is built using open-source tools where the baseline model is delivered through a reactive programming framework. As an energy savings baseline model, the Tao Vanilla benchmarking model (TVB) was set into production in the web application. The TVB is a linear regression model with well specified features, easy to interpret and has a history of excellent prediction performance. The proposed web application framework allows for a fast development cycle without any need-to-know web programming languages like HTML, CSS or JavaScript. The reactive framework delivers several advantages. First, the stakeholders will always have a current and real-time report on the savings. Second, complex methodologies are dynamically used by the end-user. Third, increased involvement by stakeholders and interaction with the analyst related to the methods used in the energy savings analysis leads to collaborative benefits such as faster disseminating of knowledge. These synergy effect leads to a better technical understanding from the end user perspective and enhanced practical understanding for the analyst. Finally, the paper presents an integrated look at the energy kWh savings versus the cost of the retrofitting’s

Development of a Precision Medicine Workflow in Hematological Cancers, Aalborg University Hospital, Denmark

Within recent years, many precision cancer medicine initiatives have been developed. Most of these have focused on solid cancers, while the potential of precision medicine for patients with hematological malignancies, especially in the relapse situation, are less elucidated. Here, we present a demographic unbiased and observational prospective study at Aalborg University Hospital Denmark, referral site for 10% of the Danish population. We developed a hematological precision medicine workflow based on sequencing analysis of whole exome tumor DNA and RNA. All steps involved are outlined in detail, illustrating how the developed workflow can provide relevant molecular information to multidisciplinary teams. A group of 174 hematological patients with progressive disease or relapse was included in a non-interventional and population-based study, of which 92 patient samples were sequenced. Based on analysis of small nucleotide variants, copy number variants, and fusion transcripts, we found variants with potential and strong clinical relevance in 62% and 9.5% of the patients, respectively. The most frequently mutated genes in individual disease entities were in concordance with previous studies. We did not find tumor mutational burden or micro satellite instability to be informative in our hematologic patient cohort

Statistical learning to estimate energy savings from retrofitting in the Norwegian food retail market

Accepted manuscript version, licensed CC BY-NC-ND 4.0. Buildings worldwide consume about 40% of all produced energy and are major contributors to GHG emissions. Hence, to reach the 2030 European energy efficiency target it is vital to reduce the energy consumption in buildings. An important barrier that hinders renovation projects is uncertainty regarding the expected savings. The main objective of this paper is to present two different statistical methods to estimate energy savings. The two methods are easy to implement for practitioners within the energy retrofitting industry, and at the same time has acceptable precision and reliability. The two methods are applied at 5 different food retail stores that undertook renovation in 2019. The models are trained on data from 2018 (one whole year before any of the retrofitting's took place) and are further applied to estimate the energy savings in 2021. The first method is the Tao Vanilla benchmarking method (TVB). The TVB model predict energy consumption in buildings on an hourly level. The model has received a lot of attention within the load forecasting literature and has previously proved its performance in machine learning competitions. The TVB has a straightforward specification, and the model parameters are easily understood. This is the first study that apply the TVB to estimate energy savings in a large retrofitting project within the energy and building sector. The second method relies on a more common industrial approach, which is to use weekly data and energy temperature curves to document energy savings. In addition, we demonstrate a novel approach of using broken line (BL) models to estimate energy savings. The suggested BL approach can simultaneously estimate all the model parameters and yield a full covariance matrix within a standard linear regression framework. The results from the retrofitting projects demonstrates considerable energy savings between 25% and 55%. Furthermore, both the TVB and the BL models deliver reliable precision. The estimated energy savings from both models are coinciding. This indicates that they could jointly be used to gain insight that may lead to more informed decisions for energy saving projects. The TVB model proves to be a proficient benchmarking model that can give detailed hourly information about the savings. The BL model is used to gain intrinsic details about the buildings varying cooling and heating needs depending on the outside temperature during the year

Molecular classification of tissue from a transformed non-Hogkin's lymphoma case with unexpected long-time remission

BACKGROUND: The concept of precision medicine in cancer includes individual molecular studies to predict clinical outcomes. In the present N = 1 case we retrospectively have analysed lymphoma tissue by exome sequencing and global gene expression in a patient with unexpected long-term remission following relaps. The goals were to phenotype the diagnostic and relapsed lymphoma tissue and evaluate its pattern. Furthermore, to identify mutations available for targeted therapy and expression of genes to predict specific drug effects by resistance gene signatures (REGS) for R-CHOP as described at http://www.hemaclass.org. We expected that such a study could generate therapeutic information and a frame for future individual evaluation of molecular resistance detected at clinical relapse. CASE PRESENTATION: The patient was diagnosed with a transformed high-grade non-Hodgkin lymphoma stage III and treated with conventional R-CHOP [rituximab (R), cyclophosphamide (C), doxorubicin (H), vincristine (O) and prednisone (P)]. Unfortunately, she suffered from severe toxicity but recovered during the following 6 months’ remission until biopsy-verified relapse. The patient refused second-line combination chemotherapy, but accepted 3 months’ palliation with R and chlorambucil. Unexpectedly, she obtained continuous complete remission and is at present >9 years after primary diagnosis. Molecular studies and data evaluation by principal component analysis, mutation screening and copy number variations of the primary and relapsed tumor, identified a pattern of branched lymphoma evolution, most likely diverging from an in situ follicular lymphoma. Accordingly, the primary diagnosed transformed lymphoma was classified as a diffuse large B cell lymphoma (DLBCL) of the GCB/centrocytic subtype by “cell of origin BAGS” assignment and R sensitive and C, H, O and P resistant by “drug specific REGS” assignment. The relapsed DLBCL was classified as NC/memory subtype and R, C, H sensitive but O and P resistant. CONCLUSIONS: Thorough analysis of the tumor DNA and RNA documented a branched evolution of the two clinical diagnosed tFL, most likely transformed from an unknown in situ lymphoma. Classification of the malignant tissue for drug-specific resistance did not explain the unexpected long-term remission and potential cure. However, it is tempting to consider the anti-CD20 immunotherapy as the curative intervention in the two independent tumors of this case. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40164-016-0063-0) contains supplementary material, which is available to authorized users