Transient liquid phase sintering of high density Transient liquid phase sintering of high density Fe₃Al using Fe and Fe₂Al₅/FeAl₂ powders Part 1: Experimentation and results

High density Fe[sub 3]Al was produced through transient liquid phase sintering, using rapid heating rates of greater than 150 K min[sup -1] and a mixture of prealloyed and elemental powders. Prealloyed Fe[sub 2]Al[sub 5]/FeAl[sub 2] (50Fe/50Al, wt-%) powder was added to elemental iron powder in a ratio appropriate for producing an overall Fe[sub 3]Al (13•87 wt-%) ratio. The heating rate, sintering time, sintering temperature, green density and powder particle size were controlled during the study. Heating rate, sintering time and powder particle size had the most significant influence upon the sintered density of the compacts. The highest sintered density of 6•12 Mg m[sup -3] (92% of the theoretical density for Fe3Al) was achieved after 15 minutes of sintering at 1350°C, using a 250 K min[sup - 1] heating rate, 1-6 μm Fe powders and 5•66 μm alloy powders. SEM microscopy suggests that agglomerated Fe[sub 2]Al[sub 5]/ FeAl[sub 2] particles, which form a liquid during sintering, are responsible for a significant portion of the remaining porosity in high sintered density compacts, creating stable pores, larger than 100 μm diameter, after melting. High density was achieved by minimising the Kirkendall porosity formed during heating by unbalanced diffusion and solubility between the iron and Fe[sub 2]Al[sub 5]/FeAl[sub 2] components. The lower diffusion rate of aluminium in the prealloyed powder into the iron compared with elemental aluminium in iron, coupled with a fast heating rate, is expected to permit minimal iron-aluminium interdiffusion during heating so that when a liquid forms the aluminium dissolves in the iron to promote solidification at a lower aluminium content. This leads to a further reduction in porosity

A logical deduction based clause learning algorithm for Boolean satisfiability problems

Clause learning is the key component of modern SAT solvers, while conflict analysis based on the implication graph is the mainstream technology to generate the learnt clauses. Whenever a clause in the clause database is falsified by the current variable assignments, the SAT solver will try to analyze the reason by using different cuts (i.e., the Unique Implication Points) on the implication graph. Those schemes reflect only the conflict on the current search subspace, does not reflect the inherent conflict directly involved in the rest space. In this paper, we propose a new advanced clause learning algorithm based on the conflict analysis and the logical deduction, which reconstructs a linear logical deduction by analyzing the relationship of different decision variables between the backjumping level and the current decision level. The logical deduction result is then added into the clause database as a newly learnt clause. The resulting implementation in Minisat improves the state-of-the-art performance in SAT solving

Attribution of climate change, vegetation restoration, and engineering measures to the reduction of suspended sediment in the Kejie catchment, southwest China

10.5194/hess-18-1979-2014Hydrology and Earth System Sciences1851979-199

Multi-neutron transfer coupling in sub-barrier 32S+90,96Zr fusion reactions

The role of neutron transfers is investigated in the fusion process below the Coulomb barrier by analyzing 32S+90Zr and 32S+96Zr as benchmark reactions. A full coupled-channel calculation of the fusion excitation functions has been performed for both systems by using multi-neutron transfer coupling for the more neutron-rich reaction. The enhancement of fusion cross sections for 32S+96Zr is well reproduced at sub-barrier energies by NTFus code calculations including the coupling of the neutron-transfer channels following the Zagrebaev semiclassical model. We found similar effects for 40Ca+90Zr and 40Ca+96Zr fusion excitation functions.Comment: Minor corrections, 11 pages, 4 figures, Fusion11 Conference, Saint Malo, France, 2-6 mai 201

A meta-analysis on the nutritional value of insects in aquafeeds

A major challenge for development of sustainable aquafeeds is its dependence on fish meal and fish oil. Similarly, it is unwanted to include more plant ingredients which adds more pressure on resources like arable land, freshwater and fertilisers. New ingredients that do not require these resources but rather refine and valorise organic side streams, like insects, are being developed. Increasing evidence indicates that using insect ingredients in aquafeeds are a sustainable alternative and considerable progress has been made on this topic in the past years. The aim of this chapter is to present a comprehensive and systematic analysis of the data available on the impact of insects in aquafeeds. Systematic search, collection and selection of relevant literature from databases such as Web of Science and NCBI was performed. The literature search enabled 91 scientific papers from peer-reviewed journals, comprising a dataset of 415 experimental diets, including 35 different aquatic species and 14 insect species to be included in this meta-analysis, covering what we consider a close to complete representation of credible publications on this topic. Information on aquatic species, insect species, dietary composition (amino acids, fatty acids, proximate composition) and performance outputs (growth performance indicators and nutrient digestibility) were included in the construction of the dataset. Regression models and principal component analyses were performed on the meta-data. The results from the meta-analysis revealed a great degree of variation in the maximum threshold for insect inclusion in aquafeeds (from 4 to 37%) based on subgroups of trophic level of aquatic species, insect species used, statistical method and the output parameter. Overall, a maximum threshold of 25-30% inclusion of insects in aquafeeds for uncompromised performance is suggested. Reduction in protein digestibility, imbalanced amino acid profile and increasing levels of saturated fatty acid were identified as major factors limiting higher inclusion of insects in aquafeeds.publishedVersio

A self-consistent method to analyze the effects of the positive Q-value neutron transfers on fusion

AbstractConsidering the present limitation of the need for external parameters to describe the nucleus–nucleus potential and the couplings in the coupled-channels calculations, this work introduces an improved method without adjustable parameter to overcome the limitation and then sort out the positive Q-value neutron transfers (PQNT) effects based on the CCFULL calculations. The corresponding analysis for Ca+Ca, S,Ca+Sn, and S,Ca+Zr provides a reliable proof and a quantitative evaluation for the residual enhancement (RE) related to PQNT. In addition, the RE for S32,Ca40+Zr94 shows an unexpected larger enhancement than S32,Ca40+Zr96 despite the similar multi-neutron transfer Q-values. This method should rather strictly test the fusion models and be helpful for excavating the underlying physics

Identifying mantle carbonatite metasomatism through Os–Sr–Mg isotopes in Tibetan ultrapotassic rocks

Mantle-derived magmas at convergent plate boundaries provide unique insights into the nature of materials subducted to and recycled from depths. Here we present a study of Os–Sr–Mg isotopes on the Oligocene–Miocene ultrapotassic rocks aimed at better understanding sediment subduction and recycling beneath southern Tibet. New isotopic data confirm that ultrapotassic rocks in southern Tibet are of mantle origin, but underwent crustal contamination as evidenced by the variably high 187Os/188Os that obviously deviates from normal mantle reservoir. Still some samples with mantle-like 187Os/188Os exhibit δ26Mg significantly lower than mantle and crustal lithologies, suggesting that the isotopically light Mg may not result from crustal contamination but retain specific fingerprint of carbonate-related metasomatism in mantle sources. Mantle carbonatite metasomatism is manifested by the inverse δ26Mg–87Sr/86Sr correlations, as well as the depletion of high field strength elements relative to rare earth elements and the enrichment of CaO in ultrapotassic rocks. The positive co-variations between δ26Mg and Hf/Sm defined by those low-187Os/188Os ultrapotassic rocks provide evidence for the potential of recycled dolomites to modify mantle Mg isotopic composition. The correlated spatial variations of δ26Mg and Hf/Sm are interpreted to reflect carbonatitic metasomatism associated with the northward subduction of the Neo-Tethyan oceanic slab and its profound influence on postcollisional ultrapotassic magmatism

Predicted robustness as QoS for Deep Neural Network Models

The adoption of deep neural network (DNN) model as the integral part of real-world software systems necessitates explicit consideration of their quality-of-service (QoS). It is well-known that DNN models are prone to adversarial attacks, and thus it is vitally important to be aware of how robust a model’s prediction is for a given input instance. A fragile prediction, even with high confidence, is not trustworthy in light of the possibility of adversarial attacks. We propose that DNN models should produce a robustness value as an additional QoS indicator, along with the confidence value, for each prediction they make. Existing approaches for robustness computation are based on adversarial searching, which are usually too expensive to be excised in real time. In this paper, we propose to predict, rather than to compute, the robustness measure for each input instance. Specifically, our approach inspects the output of the neurons of the target model and trains another DNN model to predict the robustness. We focus on convolutional neural network (CNN) models in the current research. Experiments show that our approach is accurate, with only 10%–34% additional errors compared with the offline heavy-weight robustness analysis. It also significantly outperforms some alternative methods. We further validate the effectiveness of the approach when it is applied to detect adversarial attacks and out-of-distribution input. Our approach demonstrates a better performance than, or at least is comparable to, the state-of-the-art techniques

N-glycosylation of LRP6 by B3GnT2 promotes Wnt/βcatenin signalling

Reception of Wnt signals by cells is predominantly mediated by Frizzled receptors in conjunction with a co-receptor, the latter being LRP6 or LRP5 for the Wnt/β-catenin signalling pathway. It is important that cells maintain precise control of receptor activation events in order to properly regulate Wnt/β-catenin signalling as aberrant signalling can result in disease in humans. Phosphorylation of the intracellular domain (ICD) of LRP6 is well known to regulate Wntβ-catenin signalling; however, less is known for regulatory post-translational modification events within the extracellular domain (ECD). Using a cell culture-based expression screen for functional regulators of LRP6, we identified a glycosyltransferase, B3GnT2-like, from a teleost fish (medaka) cDNA library, that modifies LRP6 and regulates Wnt/β-catenin signalling. We provide both gain-of-function and loss-of-function evidence that the single human homolog, B3GnT2, promotes extension of polylactosamine chains at multiple N-glycans on LRP6, thereby enhancing trafficking of LRP6 to the plasma membrane and promoting Wnt/β-catenin signalling. Our findings further highlight the importance of LRP6 as a regulatory hub in Wnt signalling and provide one of the few examples of how a specific glycosyltransferase appears to selectively target a signalling pathway component to alter cellular signalling events.Proteomic

Colletotrichum species associated with anthracnose of Pyrus spp. in China

Colletotrichum species are plant pathogens, saprobes, and endophytes on a range of economically important hosts. However, the species occurring on pear remain largely unresolved. To determine the morphology, phylogeny and biology of Colletotrichum species associated with Pyrus plants, a total of 295 samples were collected from cultivated pear species (including P. pyrifolia, P. bretschneideri, and P. communis) from seven major pear-cultivation provinces in China. The pear leaves and fruits affected by anthracnose were sampled and subjected to fungus isolation, resulting in a total of 488 Colletotrichum isolates. Phylogenetic analyses based on six loci (ACT, TUB2, CAL, CHS-1, GAPDH, and ITS) coupled with morphology of 90 representative isolates revealed that they belong to 10 known Colletotrichum species, including C. aenigma, C. citricola, C. conoides, C. fioriniae, C. fructicola, C. gloeosporioides, C. karstii, C. plurivorum, C. siamense, C. wuxiense, and two novel species, described here as C. jinshuiense and C. pyrifoliae. Of these, C. fructicola was the most dominant, occurring on P. pyrifolia and P. bretschneideri in all surveyed provinces except in Shandong, where C. siamense was dominant. In contrast, only C. siamense and C. fioriniae were isolated from P. communis, with the former being dominant. In order to prove Koch's postulates, pathogenicity tests on pear leaves and fruits revealed a broad diversity in pathogenicity and aggressiveness among the species and isolates, of which C. citricola, C. jinshuiense, C. pyrifoliae, and C. conoides appeared to be organ-specific on either leaves or fruits. This study also represents the first reports of C. citricola, C. conoides, C. karstii, C. plurivorum, C. siamense, and C. wuxiense causing anthracnose on pear.Earmarked Fundhttps://www.ingentaconnect.com/content/nhn/pimjhj2020BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant Patholog