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We propose a new type of magnetocaloric composite that excludes the conventional use of non-magnetocaloric materials as the binder. Spark plasma sintering was adopted to make a fully dense La(Fe, Co, Si)13/Gd composite at low temperatures (450–600 °C), which shows relatively high thermal conductivity and compressive strength compared with the counterparts of other bonded magnetic refrigeration composites. The mechanism of high thermal conductivity and compressive strength were discussed. The diffusion processes between La(Fe, Co, Si)13and Gd were also analyzed, though it has a limited influence on the magnetocaloric effect of the composite. The results suggest that using Gd as the metal binder is promising for improving the performance of present magnetic refrigeration composites. It also provides an important approach for the design of new magnetocaloric materials.

We prove a universality theorem for learning with random features. Our result shows that, in terms of training and generalization errors, a random feature model with a nonlinear activation function is asymptotically equivalent to a surrogate linear Gaussian model with a matching covariance matrix. This settles a so-called Gaussian equivalence conjecture based on which several recent papers develop their results. Our method for proving the universality theorem builds on the classical Lindeberg approach. Major ingredients of the proof include a leave-one-out analysis for the optimization problem associated with the training process and a central limit theorem, obtained via Stein’s method, for weakly correlated random variables.

Abstract

Thermal barrier coating is a high-temperature protective technology widely used in industrial gas turbines. However, the failure of coating peeling because of the generation of thermally grown oxide (TGO) at the interface during service hinders its further application. In this study, Raman spectroscopy and wedge indentation are used to determine the TGO residual stress and the interface energy release rate, respectively. The effect of TGO on the interfacial fracture toughness during the growth process was discussed. Raman spectroscopy test results show that the residual stress of TGO is about 0.5 GPa. Wedge indentation test results illustrate that high-temperature heat treatment could accelerate the interface degradation of thermal barrier coatings. Stress analysis and test research demonstrate that the microcracks induced by compressive stress of TGO will propagate with increasing heating time, ending with failure of barrier coatings.

ABSTRACTBackgroundThe Fas cell surface death receptor (FAS) and Fas ligand (FASL) can participate in the apoptosis of immune cells and target cells infected with a virus through the FAS-FASL signalling pathway. The decoy receptor 3 (DCR3) can competitively inhibit the binding of FAS to FASL. Our aim is to investigate the effect of single nucleotide polymorphisms (SNPs) in FAS, FASLand DCR3on hepatitis C virus (HCV) infection.MethodsFour SNPs (rs763110 in FASL, rs1324551 and rs2234767 in FASand rs2257440 in DCR3) were genotyped in 1495 controls free of HCV, 522 individuals with spontaneous HCV clearance and 732 patients with hepatitis C virus infection. The RegulomeDB database and RNAfold web servers were used to explore potential biological functions of SNPs.ResultsFASLrs763110 was associated with susceptibility to HCV infection, and not to CHC. The odds ratio (95% confidence interval) of HCV infection in high-risk populations carrying FASLrs763110-TT was 1.82 (1.36–2.51, P< 0.001) compared to that of CC genotypes and 1.93 (1.43–2.60, P< 0.001) higher than that of CC + CT genotypes. Based on computer simulation, FASLrs763110-T may affect the transcription of mRNA by affecting the binding of a transcription factor, leading to structural changes in mRNA.ConclusionThe genetic variant in FASLis linked with HCV infection, but not to spontaneous HCV clearance.

Substantial gaps exist between weed management researchers and practitioners with respect to prompt exchange of knowledge between the two groups, hindering the implementation of effective management to solve weed problems. We conducted a survey between 2016 and 2018 among weed management practitioners (n = 259) across diverse ecoregions on California rangelands and collected essential information from practitioners for bridging the research-implementation gap. The information included management costs, high-priority weeds, and spatial scales and temporal changes in weed management. The management cost had a mean of $5.12 ha−1yr−1with a large variance implying the uncertainty of this information. The percentage of annual budget dedicated to weed management explained about 30% of the variation in this cost. Moreover, this annual per-unit area cost decreased with increasing management area. The average size of rangeland managed by survey respondents was 1 256 ha. The top three high-priority weeds statewide were yellow starthistle (Centaurea solstitialis),medusahead (Taeniatherum caput-medusae),and all thistles combined. Medusahead and some thistle species remained on the top list in each ecoregion. Respondents overwhelmingly (80.9%) noted changes in weed problems in the past 5−10 yr, specifically citing greater weed pressure and changes in weed species. A significantly higher proportion of respondents from agencies and private businesses reported changes in weed problems than those from universities and nongovernmental organizations (NGOs), further underscoring the gap between practitioners and researchers. A majority of the respondents (75.3%) indicated the record-setting California drought had a negative effect on weed management, reducing treatment efficacy and favoring weeds over desirable species. Overall, our findings illustrate increasing challenges in weed management on California rangeland. These challenges call for adaptive management-research programs to increase cost-effectiveness of weed management and to swiftly and effectively respond to dynamic weed problems on large spatial and long temporal scales.

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