Data Valuation from Data-Driven Optimization

With the ongoing investment in data collection and communication technology in power systems, data-driven optimization has been established as a powerful tool for system operators to handle stochastic system states caused by weather- and behavior-dependent resources. However, most methods are ignorant to data quality, which may differ based on measurement and underlying privacy-protection mechanisms. This paper addresses this shortcoming by (i) proposing a practical data quality metric based on Wasserstein distance, (ii) leveraging a novel modification of distributionally robust optimization using information from multiple data sets with heterogeneous quality to valuate data, (iii) applying the proposed optimization framework to an optimal power flow problem, and (iv) showing a direct method to valuate data from the optimal solution. We conduct numerical experiments to analyze and illustrate the proposed model and publish the implementation open-source

Characterization of Anisotropic Properties of Hot Compacted Self-Reinforced Composites (SRCs) via Thermal Diffusivity Measurement

Originally published at https://doi.org/10.3139/217.381

Nothing Lasts Forever: Environmental Discourses on the Collapse of Past Societies

The study of the collapse of past societies raises many questions for the theory and practice of archaeology. Interest in collapse extends as well into the natural sciences and environmental and sustainability policy. Despite a range of approaches to collapse, the predominant paradigm is environmental collapse, which I argue obscures recognition of the dynamic role of social processes that lie at the heart of human communities. These environmental discourses, together with confusion over terminology and the concepts of collapse, have created widespread aporia about collapse and resulted in the creation of mixed messages about complex historical and social processes

Registered Replication Report: Dijksterhuis and van Knippenberg (1998)

Dijksterhuis and van Knippenberg (1998) reported that participants primed with a category associated with intelligence ("professor") subsequently performed 13% better on a trivia test than participants primed with a category associated with a lack of intelligence ("soccer hooligans"). In two unpublished replications of this study designed to verify the appropriate testing procedures, Dijksterhuis, van Knippenberg, and Holland observed a smaller difference between conditions (2%-3%) as well as a gender difference: Men showed the effect (9.3% and 7.6%), but women did not (0.3% and -0.3%). The procedure used in those replications served as the basis for this multilab Registered Replication Report. A total of 40 laboratories collected data for this project, and 23 of these laboratories met all inclusion criteria. Here we report the meta-analytic results for those 23 direct replications (total N = 4,493), which tested whether performance on a 30-item general-knowledge trivia task differed between these two priming conditions (results of supplementary analyses of the data from all 40 labs, N = 6,454, are also reported). We observed no overall difference in trivia performance between participants primed with the "professor" category and those primed with the "hooligan" category (0.14%) and no moderation by gender

Producing mixed linked xylooligosaccharides from red algae biomass through single-step enzymatic hydrolysis

BackgroundThe red alga Palmaria palmata is a rich source of sugar compounds, particularly mixed-linkage xylans present in the cell walls of the algae. In contrast to their terrestrial lignocellulosic counterparts, these xylans are more easily accessible. They can be hydrolyzed enzymatically into valuable xylooligosaccharides (XOS), known for their prebiotic, antioxidant, and immunomodulatory properties.ResultsThis study introduces a simplified, one-step enzymatic process utilizing the endo-1,4-beta-xylanase FO15_GH10 that directly hydrolyzes P. palmata biomass to produce XOS, eliminating the need for prior xylan extraction and improving efficiency. The exact structure of the resulting XOS was determined using NMR and MS/MS techniques. In addition, the xylosidase FO17_GH43 can be added to break down all residual 1,4-linked XOS. As a result, only 1,3- and mixed-linkage XOS (degree of polymerization (DP) 2-4) remains under simultaneous increase of the xylose obtained. Using FO15_GH10 alone, it was possible to produce approximately 17.6 (+/- 0.16) % (176 mg) XOS from 1 g of powdered biomass while combining both enzymes resulted in 22.6 (+/- 0.51) % (226 mg) XOS. Further optimization upon upscaling offers the possibility of achieving even greater improvements.ConclusionIn summary, our one-step enzymatic approach offers an efficient and sustainable method for producing XOS directly from P. palmata biomass. This streamlined process overcomes the need for resource-consuming extraction processes. The further characterization of the obtained XOS and the potential to gain solely 1,3- and mixed-linkage XOS is paving the way for future studies on their functional properties

Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data.

Funder: Technische Universität Berlin (TU Berlin); doi: https://doi.org/10.13039/501100006764Funder: - German Federal Ministry for Education and Research through the Berlin Big Data Centre (01IS14013A), the Berlin Center for Machine Learning (01IS18037I) and the TraMeExCo project (01IS18056A). Partial funding by DFG is acknowledged (EXC 2046/1, project-ID: 390685689) - Institute for Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2017-0-01779)Funder: GlaxoSmithKline (GlaxoSmithKline plc.); doi: https://doi.org/10.13039/100004330Funder: Pfizer (Pfizer Inc.); doi: https://doi.org/10.13039/100004319In many research areas scientists are interested in clustering objects within small datasets while making use of prior knowledge from large reference datasets. We propose a method to apply the machine learning concept of transfer learning to unsupervised clustering problems and show its effectiveness in the field of single-cell RNA sequencing (scRNA-Seq). The goal of scRNA-Seq experiments is often the definition and cataloguing of cell types from the transcriptional output of individual cells. To improve the clustering of small disease- or tissue-specific datasets, for which the identification of rare cell types is often problematic, we propose a transfer learning method to utilize large and well-annotated reference datasets, such as those produced by the Human Cell Atlas. Our approach modifies the dataset of interest while incorporating key information from the larger reference dataset via Non-negative Matrix Factorization (NMF). The modified dataset is subsequently provided to a clustering algorithm. We empirically evaluate the benefits of our approach on simulated scRNA-Seq data as well as on publicly available datasets. Finally, we present results for the analysis of a recently published small dataset and find improved clustering when transferring knowledge from a large reference dataset. Implementations of the method are available at https://github.com/nicococo/scRNA

New aspects on efficient anticoagulation and antiplatelet strategies in sheep

Background After addressing fundamental questions in preclinical models in vitro or in small animals in vivo, the translation into large animal models has become a prerequisite before transferring new findings to human medicine. Especially in cardiovascular, orthopaedic and reconstructive surgery, the sheep is an important in vivo model for testing innovative therapies or medical devices prior to clinical application. For a wide variety of sheep model based research projects, an optimal anticoagulation and antiplatelet therapy is mandatory. However, no standardised scheme for this model has been developed so far. Thus the efficacy of antiplatelet (acetylsalicylic acid, clopidogrel, ticagrelor) and anticoagulant (sodium enoxaparin, dabigatran etexilate) strategies was evaluated through aggregometry, anti-factor Xa activity and plasma thrombin inhibitor levels in sheep of different ages. Results Responses to antiplatelet and anticoagulant drugs in different concentrations were studied in the sheep. First, a baseline for the measurement of platelet aggregation was assessed in 20 sheep. The effectiveness of 225 mg clopidogrel twice daily (bid) in 2/5 sheep and 150 mg bid in 3/5 lambs could be demonstrated, while clopidogrel and its metabolite carboxylic acid were detected in every plasma sample. High dose ticagrelor (375 mg bid) resulted in sufficient inhibition of platelet aggregation in 1/5 sheep, while acetylsalicylic acid did not show any antiplatelet effect. Therapeutic anti-factor Xa levels were achieved with age-dependent dosages of sodium enoxaparin (sheep 3 mg/kg bid, lambs 5 mg/kg bid). Administration of dabigatran etexilate resulted in plasma concentrations similar to human ranges in 2/5 sheep, despite receiving quadruple dosages (600 mg bid). Conclusion High dosages of clopidogrel inhibited platelet aggregation merely in a low number of sheep despite sufficient absorption. Ticagrelor and acetylsalicylic acid cannot be recommended for platelet inhibition in sheep. Efficient anticoagulation can be ensured using sodium enoxaparin rather than dabigatran etexilate in age-dependent dosages. The findings of this study significantly contribute to the improvement of a safe and reliable prophylaxis for thromboembolic events in sheep. Applying these results in future translational experimental studies may help to avoid early dropouts due to thromboembolic events and associated unnecessary high animal numbers

PORTAL: Pilot study on the safety and tolerance of preoperative melatonin application in patients undergoing major liver resection: a double-blind randomized placebo-controlled trial

<p>Abstract</p> <p>Background</p> <p>Major surgical procedures facilitate systemic endotoxinemia and formation of free radicals with subsequent inflammatory changes that can influence the postoperative course. Experimental data suggest that preoperative supraphysiological doses of melatonin, a potent immuno-modulator and antioxidant, would decrease postoperative infectious and non-infectious complications induced by major abdominal surgery.</p> <p>Methods/Design</p> <p>A randomized controlled double blind single center clinical trial with two study arms comprising a total of 40 patients has been designed to assess the effects of a single preoperative dose of melatonin before major liver resection. Primary endpoints include the determination of safety and tolerance of the regimen as well as clinical parameters reflecting pathophysiological functions of the liver. Furthermore, data on clinical outcome (infectious and non-infectious complications) will be collected as secondary endpoints to allow a power calculation for a randomized clinical trial aiming at clinical efficacy.</p> <p>Discussion</p> <p>Based on experimental data, this ongoing clinical trial represents an advanced element of the research chain from bench to bedside in order to reach the highest level of evidence-based clinical facts to determine if melatonin can improve the general outcome after liver resection.</p> <p>Trial Registration</p> <p>EudraCT200600530815</p

State-of-the-art analytical methods of viral infections in human lung organoids

Human-based organ models can provide strong predictive value to investigate the tropism, virulence, and replication kinetics of viral pathogens. Currently, such models have received widespread attention in the study of SARS-CoV-2 causing the COVID-19 pandemic. Applicable to a large set of organoid models and viruses, we provide a step-by-step work instruction for the infection of human alveolar-like organoids with SARS-CoV-2 in this protocol collection. We also prepared a detailed description on state-of-the-art methodologies to assess the infection impact and the analysis of relevant host factors in organoids. This protocol collection consists of five different sets of protocols. Set 1 describes the protein extraction from human alveolar-like organoids and the determination of protein expression of angiotensin-converting enzyme 2 (ACE2), transmembrane serine protease 2 (TMPRSS2) and FURIN as exemplary host factors of SARS-CoV-2. Set 2 provides detailed guidance on the extraction of RNA from human alveolar-like organoids and the subsequent qPCR to quantify the expression level of ACE2, TMPRSS2, and FURIN as host factors of SARS-CoV-2 on the mRNA level. Protocol set 3 contains an in-depth explanation on how to infect human alveolar-like organoids with SARS-CoV-2 and how to quantify the viral replication by plaque assay and viral E gene-based RT-qPCR. Set 4 provides a step-by-step protocol for the isolation of single cells from infected human alveolar-like organoids for further processing in single-cell RNA sequencing or flow cytometry. Set 5 presents a detailed protocol on how to perform the fixation of human alveolar-like organoids and guides through all steps of immunohistochemistry and in situ hybridization to visualize SARS-CoV-2 and its host factors. The infection and all subsequent analytical methods have been successfully validated by biological replications with human alveolar-like organoids based on material from different donors