Exploring polymer/nanoparticle hybrid solar cells in tandem architecture

Tandem solar cells offer the possibility to significantly enhance solar cell performance through harvesting a broader part of the solar spectrum by using complementary absorbing materials. We report on tandem solar cells, with at least one polymer/nanoparticle hybrid layer as absorber material, in which the nanoparticles are prepared in situ by thermal decomposition of metal xanthates directly in the polymer matrix. In a first series, we investigated a hybrid-organic tandem solar cell, with a hybrid solar cell consisting of the silafluorene containing low band gap polymer PSiF-DBT and copper indium sulphide (CIS) nanoparticles as the bottom cell, and a low band gap polymer (PTB7)/fullerene derivative (PC61BM) organic solar cell as the top cell in order to study different recombination layers. Tandem devices with open circuit voltages nearly reaching the sum of the individual cells have been realised. The short circuit current is equal to the value of the hybrid single cell and a fill factor above 50% is obtained, leading to power conversion efficiencies of about 4.1%. Furthermore, the first results on hybrid-hybrid tandem solar cells consisting of two PSiF-DBT/CIS solar cells are presented. Although the preparation of these double hybrid devices is challenging because of the necessity of two thermal annealing steps, the resulting multilayer stack reveals smooth and homogeneous layers with sharp interfaces. The first working hybrid-hybrid tandem solar cells still exhibited 81% of the sum of the open circuit voltages of the single junction solar cells. © 2013 The Royal Society of Chemistry

Expert-augmented machine learning.

Machine learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption is limited by the level of trust afforded by given models. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of humans and machines. Here, we present expert-augmented machine learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We used a large dataset of intensive-care patient data to derive 126 decision rules that predict hospital mortality. Using an online platform, we asked 15 clinicians to assess the relative risk of the subpopulation defined by each rule compared to the total sample. We compared the clinician-assessed risk to the empirical risk and found that, while clinicians agreed with the data in most cases, there were notable exceptions where they overestimated or underestimated the true risk. Studying the rules with greatest disagreement, we identified problems with the training data, including one miscoded variable and one hidden confounder. Filtering the rules based on the extent of disagreement between clinician-assessed risk and empirical risk, we improved performance on out-of-sample data and were able to train with less data. EAML provides a platform for automated creation of problem-specific priors, which help build robust and dependable machine-learning models in critical applications

quasiharmonic equations of state for dynamically-stabilized soft-mode materials

We introduce a method for treating soft modes within the analytical framework of the quasiharmonic equation of state. The corresponding double-well energy-displacement relation is fitted to a functional form that is harmonic in both the low- and high-energy limits. Using density-functional calculations and statistical physics, we apply the quasiharmonic methodology to solid periclase. We predict the existence of a B1--B2 phase transition at high pressures and temperatures

Bright Points and Subflares in UV Lines and in X-Rays

We have analysed an active region which was observed in Halpha (MSDP), UV lines (SMM/UVSP), and in X rays (SMM/HXIS). In this active region there were only a few subflares and many small bright points visible in UV and in X rays. Using an extrapolation based on the Fourier transform we have computed magnetic field lines connecting different photospheric magnetic polarities from ground-based magnetograms. Along the magnetic inversion lines we find 2 different zones: 1. a high shear region (less than 70 degrees) where subflares occur 2. a low shear region along the magnetic inversion line where UV bright points are observed

Evidence of a high incidence of subclinically affected calves in a herd of cattle with fatal cases of Bovine Neonatal Pancytopenia (BNP).

BACKGROUND: Bovine Neonatal Pancytopenia (BNP) is a disease of calves characterised by bone marrow trilineage hypoplasia, mediated by ingestion of alloantibodies in colostrum. Suspected subclinical forms of BNP have been reported, suggesting that observed clinical cases may not represent the full extent of the disease. However to date there are no objective data available on the incidence of subclinical disease or its temporal distribution. This study aimed to 1) ascertain whether subclinical BNP occurs and, if so, to determine the incidence on an affected farm and 2) determine whether there is evidence of temporal clustering of BNP cases on this farm. To achieve these aims, haematological screening of calves born on the farm during one calving season was carried out, utilising blood samples collected at defined ages. These data were then analysed in comparison to data from both known BNP-free control animals and histopathologically confirmed BNP cases. An ordinal logistic regression model was used to create a composite haematology score to predict the probabilities of calves being normal, based on their haematology measurements at 10–14 days old. RESULTS: This study revealed that 15% (21 of 139) of the clinically normal calves on this farm had profoundly abnormal haematology (<5% chance of being normal) and could be defined as affected by subclinical BNP. Together with clinical BNP cases, this gave the study farm a BNP incidence of 18%. Calves with BNP were found to be distributed throughout the calving period, with no clustering, and no significant differences in the date of birth of cases or subclinical cases were found compared to the rest of the calves. This study did not find any evidence of increased mortality or increased time from birth to sale in subclinical BNP calves but, as the study only involved a single farm and adverse effects may be determined by other inter-current diseases it remains possible that subclinical BNP has a detrimental impact on the health and productivity of calves under certain circumstances. CONCLUSIONS: Subclinical BNP was found to occur at a high incidence in a herd of cattle with fatal cases of BNP

Multiple constraints cause positive and negative feedbacks limiting grassland soil CO2efflux under CO2enrichment

Terrestrial ecosystems are increasingly enriched with resources such as atmospheric CO2that limit ecosystem processes. The consequences for ecosystem carbon cycling depend on the feedbacks from other limiting resources and plant community change, which remain poorly understood for soil CO2efflux, JCO2, a primary carbon flux from the biosphere to the atmosphere. We applied a unique CO2enrichment gradient (250 to 500 μL L-1) for eight years to grassland plant communities on soils from different landscape positions. We identified the trajectory of JCO2responses and feedbacks from other resources, plant diversity [effective species richness, exp(H)], and community change (plant species turnover). We found linear increases in JCO2on an alluvial sandy loam and a lowland clay soil, and an asymptotic increase on an upland silty clay soil. Structural equation modeling identified CO2as the dominant limitation on JCO2on the clay soil. In contrast with theory predicting limitation from a single limiting factor, the linear JCO2response on the sandy loam was reinforced by positive feedbacks from aboveground net primary productivity and exp(H), while the asymptotic JCO2response on the silty clay arose from a net negative feedback among exp(H), species turnover, and soil water potential. These findings support a multiple resource limitation view of the effects of global change drivers on grassland ecosystem carbon cycling and highlight a crucial role for positive or negative feedbacks between limiting resources and plant community structure. Incorporating these feedbacks will improve models of terrestrial carbon sequestration and ecosystem services

Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes.

Background: MicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study, we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients and in combination with bioinformatics analysis to evaluate the utility of selected differentially expressed miRNAs in the serum as potential OA biomarkers. Methods: Serum samples were collected from 12 primary OA patients, and 12 healthy individuals were screened using the Agilent Human miRNA Microarray platform interrogating 2549 miRNAs. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative real-time PCR (qRT-PCR) in all serum and in articular cartilage samples from OA patients (n = 12) and healthy individuals (n = 7). Bioinformatics analysis was used to investigate the involved pathways and target genes for the above miRNAs. Results: We identified 279 differentially expressed miRNAs in the serum of OA patients compared to controls. Two hundred and five miRNAs (73.5%) were upregulated and 74 (26.5%) downregulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC) > 0.8 and p < 0.05. Bioinformatics analysis in the 77 miRNAs revealed that their target genes were involved in multiple signaling pathways associated with OA, among which FoxO, mTOR, Wnt, pI3K/akt, TGF-β signaling pathways, ECM-receptor interaction, and fatty acid biosynthesis. qRT-PCR validation in seven selected out of the 77 miRNAs revealed 3 significantly downregulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p, and hsa-miR-140-3p) in the serum of OA patients, which were in silico predicted to be enriched in pathways involved in metabolic processes. Target-gene analysis of hsa-miR-140-3p, hsa-miR-33b-3p, and hsa-miR-671-3p revealed that InsR and IGFR1 were common targets of all three miRNAs, highlighting their involvement in regulation of metabolic processes that contribute to OA pathology. Hsa-miR-140-3p and hsa-miR-671-3p expression levels were consistently downregulated in articular cartilage of OA patients compared to healthy individuals. Conclusions: A serum miRNA signature was established for the first time using high density resolution miR-arrays in OA patients. We identified a three-miRNA signature, hsa-miR-140-3p, hsa-miR-671-3p, and hsa-miR-33b-3p, in the serum of OA patients, predicted to regulate metabolic processes, which could serve as a potential biomarker for the evaluation of OA risk and progression.Peer reviewedFinal Published versio

Multiple constraints cause positive and negative feedbacks limiting grassland soil CO2efflux under CO2enrichment

Terrestrial ecosystems are increasingly enriched with resources such as atmospheric CO2that limit ecosystem processes. The consequences for ecosystem carbon cycling depend on the feedbacks from other limiting resources and plant community change, which remain poorly understood for soil CO2efflux, JCO2, a primary carbon flux from the biosphere to the atmosphere. We applied a unique CO2enrichment gradient (250 to 500 μL L-1) for eight years to grassland plant communities on soils from different landscape positions. We identified the trajectory of JCO2responses and feedbacks from other resources, plant diversity [effective species richness, exp(H)], and community change (plant species turnover). We found linear increases in JCO2on an alluvial sandy loam and a lowland clay soil, and an asymptotic increase on an upland silty clay soil. Structural equation modeling identified CO2as the dominant limitation on JCO2on the clay soil. In contrast with theory predicting limitation from a single limiting factor, the linear JCO2response on the sandy loam was reinforced by positive feedbacks from aboveground net primary productivity and exp(H), while the asymptotic JCO2response on the silty clay arose from a net negative feedback among exp(H), species turnover, and soil water potential. These findings support a multiple resource limitation view of the effects of global change drivers on grassland ecosystem carbon cycling and highlight a crucial role for positive or negative feedbacks between limiting resources and plant community structure. Incorporating these feedbacks will improve models of terrestrial carbon sequestration and ecosystem services

CO2 enrichment and soil type additively regulate grassland productivity

The development of a predictive understanding of how atmospheric CO2 enrichment is affecting the primary productivity of the terrestrial biosphere is among the most pressing of ecological challenges. The terrestrial biosphere absorbs c. 25% of anthropogenic carbon (C) emissions (Le Quere et al., 2018). Uncertainty in CO2 effects on ecosystem C uptake is a major constraint in the prediction of C cycling and the provisioning of productivity- related ecosystem services. Grasslands cover c. 25% of the terrestrial area and are an important contributor to the global C balance (Sala et al., 1996). CO2 enrichment stimulates the aboveground net primary productivity (ANPP) of most water-limited grasslands by increasing plant water use efficiency (WUE; productivity per unit of transpiration; Morgan et al., 2004; Nowak et al., 2004; Fatichi et al., 2016), but grassland ANPP, as other ecosystem functions, is determined by drivers in addition to water availability which act simultaneously and often interactively with CO2 (Polley et al., 2011). CO2 enrichment usually shows greater stimulation of plant productivity when nitrogen (N) availability is relatively high (Owensby et al., 1994; Reich & Hobbie, 2013; Mueller et al., 2016), for example. Other drivers include precipitation timing (Hovenden et al., 2014), disturbance regimes (Newton et al., 2014), plant species composition (Langley & Megonigal, 2010; Fay et al., 2012; Polley et al., 2012) and soil properties (Epstein et al., 1997, 1998), including soil texture, which influences water availability to plants (Tor-Ngern et al., 2017)

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Abstract Thirty-four patients with acute hemispheric ischemic strokes underwent both CT angiography and contrastenhanced transcranial color-coded duplexsonography (TCCD) to study the effectiveness of the combined noninvasive techniques for evaluation of the circle of Willis. In 3/34 patients, CT angiography and contrast-enhanced TCCD demonstrated middle cerebral artery (MCA) occlusion, in 5 others MCA stenosis. A severe posterior cerebral artery stenosis was missed by CT angiography. In 8 patients, contrast-enhanced TCCD failed because of poor bone windows. In these patients, CT angiography was normal. CT angiography and contrast-enhanced TCCD are complementary noninvasive diagnostic tools. Disagreements between the diagnostic findings of these methods still need further evaluation by digital subtraction angiography