Moderator role in green product purchases.

Abstract: Opinion polls consistently show large majorities of Americans supporting efforts to protect and improve the planet’s ability to sustain life. However, when it comes to environmentally preferable products, firms attract relatively small shares compared with conventional products. The present study examined the effect intentions (Verbal Commitment – VC) , emotions (Affect – Aff) and two moderators (Perceived Consumer Effectiveness – a PCE and Faith in Others – FIO) have on purchase (Actual Commitment – AC) of environmentally preferable products. Support was found for a direct influence of intentions aided by emotions – affect (Aff) – on AC, purchasing of environmentally preferable products. PCE was also found to be a favorable moderator on actual commitment (AC), buying environmentally preferable purchases and FIO positively influenced Aff and PCE, as in a cheerleader effect. The former finding regarding PCE is consistent with other studies, while the latter finding with respect to FIO represents a possible new dimension for FIO, which previously was thought to have a negative “free-rider” or “let-others-do-it” effect on actual commitment to purchase environmentally preferable products

Heterostructures for High Performance Devices

Contains table of contents for Part I, table of contents for Section 1, an introduction, reports on eighteen research projects and a list of publications.Charles S. Draper Laboratories Contract DL-H-418483DARPA/NCIPTJoint Services Electronics Program Contract DAAL03-89-C-0001Joint Services Electronics Program Contract DAAL03-92-C-0001IBM Corporation FellowshipNational Science Foundation FellowshipVitesse SemiconductorGTE LaboratoriesCharles S. Draper LaboratoriesElectronics and Telecommunications Research Institute (ETRI) FellowshipNational Science Foundation/Northeastern UniversityTRW SystemsU.S. Army Research OfficeNational Science FoundationAT&T Bell Laboratories FellowshipNational Science Foundation Grant ECS 90-0774

JAK1/2 inhibition with baricitinib in the treatment of autoinflammatory interferonopathies

BACKGROUND. Monogenic IFN-mediated autoinflammatory diseases present in infancy with systemic inflammation, an IFN response gene signature, inflammatory organ damage, and high mortality. We used the JAK inhibitor baricitinib, with IFN-blocking activity in vitro, to ameliorate disease. METHODS. Between October 2011 and February 2017, 10 patients with CANDLE (chronic atypical neutrophilic dermatosis with lipodystrophy and elevated temperatures), 4 patients with SAVI (stimulator of IFN genes-associated [STING-associated] vasculopathy with onset in infancy), and 4 patients with other interferonopathies were enrolled in an expanded access program. The patients underwent dose escalation, and the benefit was assessed by reductions in daily disease symptoms and corticosteroid requirement. Quality of life, organ inflammation, changes in IFN-induced biomarkers, and safety were longitudinally assessed. RESULTS. Eighteen patients were treated for a mean duration of 3.0 years (1.5-4.9 years). The median daily symptom score decreased from 1.3 (interquartile range [IQR], 0.93-1.78) to 0.25 (IQR, 0.1-0.63) (P < 0.0001). In 14 patients receiving corticosteroids at baseline, daily prednisone doses decreased from 0.44 mg/kg/day (IQR, 0.31-1.09) to 0.11 mg/kg/day (IQR, 0.02-0.24) (P < 0.01), and 5 of 10 patients with CANDLE achieved lasting clinical remission. The patients' quality of life and height and bone mineral density Z-scores significantly improved, and their IFN biomarkers decreased. Three patients, two of whom had genetically undefined conditions, discontinued treatment because of lack of efficacy, and one CANDLE patient discontinued treatment because of BK viremia and azotemia. The most common adverse events were upper respiratory infections, gastroenteritis, and BK viruria and viremia. CONCLUSION. Upon baricitinib treatment, clinical manifestations and inflammatory and IFN biomarkers improved in patients with the monogenic interferonopathies CANDLE, SAVI, and other interferonopathies. Monitoring safety and efficacy is important in benefit-risk assessment

Predicting solar cell performance from terahertz and microwave spectroscopy

Mobilities and lifetimes of photogenerated charge carriers are core properties of photovoltaic materials and can both be characterized by contactless terahertz or microwave measurements. Here, the expertise from fifteen laboratories is combined to quantitatively model the current-voltage characteristics of a solar cell from such measurements. To this end, the impact of measurement conditions, alternate interpretations, and experimental inter-laboratory variations are discussed using a (Cs,FA,MA)Pb(I,Br)3 halide perovskite thin-film as a case study. At 1 sun equivalent excitation, neither transport nor recombination is significantly affected by exciton formation or trapping. Terahertz, microwave, and photoluminescence transients for the neat material yield consistent effective lifetimes implying a resistance-free JV-curve with a potential power conversion efficiency of 24.6 %. For grainsizes above ≈20 nm, intra-grain charge transport is characterized by terahertz sum mobilities of ≈32 cm2 V−1 s−1. Drift-diffusion simulations indicate that these intra-grain mobilities can slightly reduce the fill factor of perovskite solar cells to 0.82, in accordance with the best-realized devices in the literature. Beyond perovskites, this work can guide a highly predictive characterization of any emerging semiconductor for photovoltaic or photoelectrochemical energy conversion. A best practice for the interpretation of terahertz and microwave measurements on photovoltaic materials is presented

Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE