International Collaboration Framework for the Calculation of Performance Loss Rates: Data Quality, Benchmarks, and Trends (Towards a Uniform Methodology)

The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance loss rates of a large number of commercial and research photovoltaic (PV) power plants and their related weather data coming across various climatic zones. The general steps to calculate the performance loss rate are (i) input data cleaning and grading; (ii) data filtering; (iii) performance metric selection, corrections, and aggregation; and finally, (iv) application of a statistical modeling method to determine the performance loss rate value. In this study, several high-quality power and irradiance datasets have been shared, and the participants of the study were asked to calculate the performance loss rate of each individual system using their preferred methodologies. The data are used for benchmarking activities and to define capabilities and uncertainties of all the various methods. The combination of data filtering, metrics (performance ratio or power based), and statistical modeling methods are benchmarked in terms of (i) their deviation from the average value and (ii) their uncertainty, standard error, and confidence intervals. It was observed that careful data filtering is an essential foundation for reliable performance loss rate calculations. Furthermore, the selection of the calculation steps filter/metric/statistical method is highly dependent on one another, and the steps should not be assessed individually

Key aerodynamic technologies for aircraft engine nacelles

Customer requirements and vision in aerospace dictate that the next generation of civil transport aircraft should have a strong emphasis on increased safety, reduced environmental impact and reduced cost without sacrificing performance. In this context, the School of Mechanical and Aerospace Engineering at the Queen's University of Belfast and Bombardier have, in recent years, been conducting research into some of the key aerodynamic technologies for the next generation of aircraft engine nacelles. Investigations have been performed into anti-icing technology, efficient thrust reversal, engine fire zone safety, life cycle cost and integration of the foregoing with other considerations in engine and aircraft design. A unique correlation for heat transfer in an anti-icing system has been developed. The effect of normal vibration on heat transfer in such systems has been found to be negligible. It has been shown that carefully designed natural blockage thrust reversers without a cascade can reduce aircraft weight with only a small sacrifice in the reversed thrust. A good understanding of the pressure relief doors and techniques to improve the performance of such doors have been developed. Trade off studies between aerodynamics, manufacturing and assembly of engine nacelles have shown the potential for a significant reduction in life cycle cost

Silica-Supported Oligomeric Benzyl Phosphate (Si-OBP) and Triazole Phosphate (Si-OTP) Alkylating Reagents

The syntheses of silica-supported oligomeric benzyl phosphates (Si-OBPn) and triazole phosphates (Si-OTPn) using ring-opening metathesis polymerization (ROMP) for use as efficient alkylating reagents is reported. Ease of synthesis and grafting onto the surface of norbornenyl-tagged (Nb-tagged) silica particles has been demonstrated for benzyl phosphate and triazole phosphate monomers. It is shown that these silica polymer hybrid reagents, Si-OBPn and Si-OTPn, can be used to carry out alkylation reactions with an array of different nucleophiles to afford the corresponding benzylated and (triazolyl)methylated products in good yield and high purity

A multicriteria decision analysis comparing pharmacotherapy for chronic neuropathic pain, including cannabinoids and cannabis-based medical products

Background: Pharmacological management of chronic neuropathic pain (CNP) still represents a major clinical challenge. Collective harnessing of both the scientific evidence base and clinical experience (of clinicians and patients) can play a key role in informing treatment pathways and contribute to the debate on specific treatments (e.g., cannabinoids). A group of expert clinicians (pain specialists and psychiatrists), scientists, and patient representatives convened to assess the relative benefit–safety balance of 12 pharmacological treatments, including orally administered cannabinoids/cannabis-based medicinal products, for the treatment of CNP in adults. Methods: A decision conference provided the process of creating a multicriteria decision analysis (MCDA) model, in which the group collectively scored the drugs on 17 effect criteria relevant to benefits and safety and then weighted the criteria for their clinical relevance. Findings: Cannabis-based medicinal products consisting of tetrahydrocannabinol/cannabidiol (THC/CBD), in a 1:1 ratio, achieved the highest overall score, 79 (out of 100), followed by CBD dominant at 75, then THC dominant at 72. Duloxetine and the gabapentinoids scored in the 60s, amitriptyline, tramadol, and ibuprofen in the 50s, methadone and oxycodone in the 40s, and morphine and fentanyl in the 30s. Sensitivity analyses showed that even if the pain reduction and quality-of-life scores for THC/CBD and THC are halved, their benefit–safety balances remain better than those of the noncannabinoid drugs. Interpretation: The benefit–safety profiles for cannabinoids were higher than for other commonly used medications for CNP largely because they contribute more to quality of life and have a more favorable side effect profile. The results also reflect the shortcomings of alternative pharmacological treatments with respect to safety and mitigation of neuropathic pain symptoms. Further high-quality clinical trials and systematic comprehensive capture of clinical experience with cannabinoids is warranted. These results demonstrate once again the complexity and multimodal mechanisms underlying the clinical experience and impact of chronic pain

Individual variation in 3-methylbutanal: A putative link between human leukocyte antigen and skin microflora

The human derma emits volatile compounds whose interaction with a receiver's olfactory sensory system may affect individual recognition and mating preferences. Studies suggest that both genes and environmental factors determine characteristic odor of an individual. Here, we use solid phase micro-extraction and GC-MS to identify 3-methylbutanal (3-MB) in human axillary odor, show that the abundance of this volatile compound varies significantly between individuals and demonstrate in vitro that its formation may be influenced by interaction between human leukocyte antigen peptide and dermal microflora

Direct nanoscale mapping of open circuit voltages at local back surface fields for PERC solar cells

The open circuit voltage (VOC) is a critical and common indicator of solar cell performance as well as degradation, for panel down to lab-scale photovoltaics. Detecting VOC at the nanoscale is much more challenging, however, due to experimental limitations on spatial resolution, voltage resolution, and/or measurement times. Accordingly, an approach based on Conductive Atomic Force Microscopy is implemented to directly detect the local VOC, notably for monocrystalline Passivated Emitter Rear Contact (PERC) cells which are the most common industrial-scale solar panel technology in production worldwide. This is demonstrated with cross-sectioned monocrystalline PERC cells around the entire circumference of a poly-aluminum-silicide via through the rear emitter. The VOC maps reveal a local back surface field extending * 2 lm into the underlying p-type Si absorber due to Al in-diffusion as designed. Such high spatial resolution methods for photovoltaic performance mapping are especially promising for directly visualizing the effects of processing parameters, as well as identifying signatures of degradation for silicon and other solar cell technologies

Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data

Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a

Early Last Interglacial ocean warming drove substantial ice mass loss from Antarctica

The future response of the Antarctic ice sheet to rising temperatures remains highly uncertain. A useful period for assessing the sensitivity of Antarctica to warming is the Last Interglacial (LIG) (129 to 116 ky), which experienced warmer polar temperatures and higher global mean sea level (GMSL) (+6 to 9 m) relative to present day. LIG sea level cannot be fully explained by Greenland Ice Sheet melt (∼2 m), ocean thermal expansion, and melting mountain glaciers (∼1 m), suggesting substantial Antarctic mass loss was initiated by warming of Southern Ocean waters, resulting from a weakening Atlantic meridional overturning circulation in response to North Atlantic surface freshening. Here, we report a blue-ice record of ice sheet and environmental change from the Weddell Sea Embayment at the periphery of the marine-based West Antarctic Ice Sheet (WAIS), which is underlain by major methane hydrate reserves. Constrained by a widespread volcanic horizon and supported by ancient microbial DNA analyses, we provide evidence for substantial mass loss across the Weddell Sea embayment during the LIG, most likely driven by ocean warming and associated with destabilization of subglacial hydrates. Ice sheet modeling supports this interpretation and suggests that millennial-scale warming of the Southern Ocean could have triggered a multimeter rise in global sea levels. Our data indicate that Antarctica is highly vulnerable to projected increases in ocean temperatures and may drive ice–climate feedbacks that further amplify warming

Genetically-Based Olfactory Signatures Persist Despite Dietary Variation

Individual mice have a unique odor, or odortype, that facilitates individual recognition. Odortypes, like other phenotypes, can be influenced by genetic and environmental variation. The genetic influence derives in part from genes of the major histocompatibility complex (MHC). A major environmental influence is diet, which could obscure the genetic contribution to odortype. Because odortype stability is a prerequisite for individual recognition under normal behavioral conditions, we investigated whether MHC-determined urinary odortypes of inbred mice can be identified in the face of large diet-induced variation. Mice trained to discriminate urines from panels of mice that differed both in diet and MHC type found the diet odor more salient in generalization trials. Nevertheless, when mice were trained to discriminate mice with only MHC differences (but on the same diet), they recognized the MHC difference when tested with urines from mice on a different diet. This indicates that MHC odor profiles remain despite large dietary variation. Chemical analyses of urinary volatile organic compounds (VOCs) extracted by solid phase microextraction (SPME) and analyzed by gas chromatography/mass spectrometry (GC/MS) are consistent with this inference. Although diet influenced VOC variation more than MHC, with algorithmic training (supervised classification) MHC types could be accurately discriminated across different diets. Thus, although there are clear diet effects on urinary volatile profiles, they do not obscure MHC effects

Large Scale Comparative Codon-Pair Context Analysis Unveils General Rules that Fine-Tune Evolution of mRNA Primary Structure

BACKGROUND: Codon usage and codon-pair context are important gene primary structure features that influence mRNA decoding fidelity. In order to identify general rules that shape codon-pair context and minimize mRNA decoding error, we have carried out a large scale comparative codon-pair context analysis of 119 fully sequenced genomes. METHODOLOGIES/PRINCIPAL FINDINGS: We have developed mathematical and software tools for large scale comparative codon-pair context analysis. These methodologies unveiled general and species specific codon-pair context rules that govern evolution of mRNAs in the 3 domains of life. We show that evolution of bacterial and archeal mRNA primary structure is mainly dependent on constraints imposed by the translational machinery, while in eukaryotes DNA methylation and tri-nucleotide repeats impose strong biases on codon-pair context. CONCLUSIONS: The data highlight fundamental differences between prokaryotic and eukaryotic mRNA decoding rules, which are partially independent of codon usage