A Search for Light Fermionic Dark Matter Absorption on Electrons in PandaX-4T

We report a search on a sub-MeV fermionic dark matter absorbed by electrons with an outgoing active neutrino using the 0.63 tonne-year exposure collected by PandaX-4T liquid xenon experiment. No significant signals are observed over the expected background. The data are interpreted into limits to the effective couplings between such dark matter and electrons. For axial-vector or vector interactions, our sensitivity is competitive in comparison to existing astrophysical bounds on the decay of such dark matter into photon final states. In particular, we present the first direct detection limits for an axial-vector (vector) interaction which are the strongest in the mass range from 25 to 45 (35 to 50) keV/c$^2$

A novel general kernel-based non-negative matrix factorisation approach for face recognition

Kernel-based non-negative matrix factorisation (KNMF) is a promising nonlinear approach for image data representation using non-negative features. However, most of the KNMF algorithms are developed via a specific kernel function and thus fail to adopt other kinds of kernels. Also, they have to learn pre-image inaccurately that may influence the reliability of the method. To address these problems of KNMF, this paper proposes a novel general kernel-based non-negative matrix factorisation (GKBNNMF) method. It not only avoids pre-image learning but also is suitable for any kernel functions as well. We assume that the mapped basis images fall within the cone spanned by the mapped training data, allowing us to use arbitrary kernel function in the algorithm. The symmetric NMF strategy is exploited on kernel matrix to establish our general kernel NMF model. The proposed algorithm is proven to be convergent. The facial image datasets are selected to evaluate the performance of our method. Compared with some state-of-the-art approaches, the experimental results demonstrate that our proposed is both effective and robust

Approximated Slack Scaling for Structural Support Vector Machines in Scene Depth Analysis

Based upon the framework of the structural support vector machines, this paper proposes two approaches to the depth restoration towards different scenes, that is, margin rescaling and the slack rescaling. The results show that both approaches achieve high convergence, while the slack approach yields better performance in prediction accuracy. However, due to its nondecomposability nature, the application of the slack approach is limited. This paper therefore introduces a novel approximation slack method to solve this problem, in which we propose a modified way of defining the loss functions to ensure the decomposability of the object function. During the training process, a bundle method is used to improve the computing efficiency. The results on Middlebury datasets show that proposed depth inference method solves the nondecomposability of slack scaling method and achieves relative acceptable accuracy. Our approximation approach can be an alternative for the slack scaling method to ensure efficient computation

Incremental Nonnegative Matrix Factorization for Face Recognition

Nonnegative matrix factorization (NMF) is a promising approach for local feature extraction in face recognition tasks. However, there are two major drawbacks in almost all existing NMF-based methods. One shortcoming is that the computational cost is expensive for large matrix decomposition. The other is that it must conduct repetitive learning, when the training samples or classes are updated. To overcome these two limitations, this paper proposes a novel incremental nonnegative matrix factorization (INMF) for face representation and recognition. The proposed INMF approach is based on a novel constraint criterion and our previous block strategy. It thus has some good properties, such as low computational complexity, sparse coefficient matrix. Also, the coefficient column vectors between different classes are orthogonal. In particular, it can be applied to incremental learning. Two face databases, namely FERET and CMU PIE face databases, are selected for evaluation. Compared with PCA and some state-of-the-art NMF-based methods, our INMF approach gives the best performance

De Novo Biosynthesis of <i>p</i>-Coumaric Acid in <i>E. coli</i> with a <i>trans</i>-Cinnamic Acid 4-Hydroxylase from the Amaryllidaceae Plant <i>Lycoris aurea</i>

p-Coumaric acid is a commercially available phenolcarboxylic acid with a great number of important applications in the nutraceutical, pharmaceutical, material and chemical industries. p-Coumaric acid has been biosynthesized in some engineered microbes, but the potential of the plant CYP450-involved biosynthetic route has not investigated in Escherichia coli. In the present study, a novel trans-cinnamic acid 4-hydroxylase (C4H) encoding the LauC4H gene was isolated from Lycoris aurea (L&#8217; H&#233;r.) Herb via rapid amplification of cDNA ends. Then, N-terminal 28 amino acids of LauC4H were characterized, for the subcellular localization, at the endoplasmic reticulum membrane in protoplasts of Arabidopsis thaliana. In E. coli, LauC4H without the N-terminal membrane anchor region was functionally expressed when fused with the redox partner of A. thaliana cytochrome P450 enzyme (CYP450), and was verified to catalyze the trans-cinnamic acid to p-coumaric acid transformation by whole-cell bioconversion, HPLC detection and LC-MS analysis as well. Further, with phenylalanine ammonia-lyase 1 of A. thaliana, p-coumaric acid was de novo biosynthesized from glucose as the sole carbon source via the phenylalanine route in the recombinant E. coli cells. By regulating the level of intracellular NADPH, the production of p-coumaric acid was dramatically improved by 9.18-fold, and achieved with a titer of 156.09 &#956;M in shake flasks. The recombinant cells harboring functional LauC4H afforded a promising chassis for biological production of p-coumaric acid, even other derivatives, via a plant CYP450-involved pathway

Magnetic Properties and Biocompatibility of Different Thickness (Pd/Fe)_n Coatings Deposited on Pure Ti Surface via Multi Arc Ion Plating

The different thickness (Fe/Pd)n coatings were prepared by vacuum ion plating technology on a pure Ti substrate. The (Fe/Pd)n coatings were magnetized using an MC-4000 high-pressure magnetizing machine. Then, the effect of the (Fe/Pd)n coating thickness on the magnetic properties was studied. The surface and section morphology, composition, phase structure, magnetic properties, and biocompatibility of the (Fe/Pd)n coatings were studied by scanning electron microscopy, X-ray diffraction, energy-dispersive X-ray spectroscopy, and CCTC-1 digital flux field measurement. The results showed that the (Fe/Pd)n coatings were granular, smooth, and compact, without cracks. In addition the (Fe/Pd)n coatings formed an L10 phase with a magnetic face-centered tetragonal-ordered structure after heat treatment. With the increase in the thickness of (FePd)n coatings, the content of L10 FePd phase increased and the remanence increased. The remanence values of the Fe/Pd, (Fe/Pd)5, (Fe/Pd)10, and (Fe/Pd)15 magnetic coatings were 0.83 Gs, 5.52 Gs, 7.14 Gs, and 7.94 Gs, respectively. Additionally, the (Fe/Pd)n magnetic coatings showed good blood compatibility and histocompatibility

Seasonal habitat use and activity patterns of blood pheasant Ithaginis cruentusbe in the presence of free-ranging livestock

Livestock grazing has become the most prevalent human disturbance in protected areas across the range of giant panda (Ailuropoda melanoleuca). Previous studies have documented the impacts of livestock grazing on habitat and food resources of giant panda, however, little is known about how free-ranging livestock influences other sympatric species. In this study, we investigated the presence of livestock on the habitat use and activity patterns of blood pheasant (Ithaginis cruentusbe), a representative species of phasianids in China, of which more than 50% are under threats due to habitat loss and fragmentation, illegal harvest and human disturbance. We combined camera-trap and sign survey data collected within Wanglang National Nature Reserve, where the livestock population has increased by nine-fold in the past decade, and used both an occupancy modeling framework and kernel density estimation to understand blood pheasant's recent distribution, changes in occurrences, and diel activity patterns in the presence of free ranging livestock in different seasons (i.e., breeding [April to July], non-breeding [August to October] and winter [November to March]). For diel activity, blood pheasant overlapped highly with livestock regardless of the season, as both are primarily diurnal species. With regards to distribution, we detected a significant positive correlation between the presence of blood pheasants and livestock (P = 0.02) in breeding season which was against our expectation; no significant relationship in non-breeding season; and a significant negative correlation in winter. Besides, livestock had a significant negative correlation with blood pheasant extinction probability, and no significant impact on colonization probability. Aided by results from two-season occupancy modeling, we argued that the spatial co occurrence in breeding season wasn't due to causality, but similar habitat preferences between them. Our study confirms that free-ranging livestock do have the potential to impact blood pheasant due to temporal and spatial overlap, but the consequences of this overlap were unclear. (c) 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Tiny Grains Give Huge Gains: Nanocrystal-Based Signal Amplification for Biomolecule Detection

Nanocrystals, despite their tiny sizes, contain thousands to millions of atoms. Here we show that the large number of atoms packed in each metallic nanocrystal can provide a huge gain in signal amplification for biomolecule detection. We have devised a highly sensitive, linear amplification scheme by integrating the dissolution of bound nanocrystals and metal-induced stoichiometric chromogenesis, and demonstrated that signal amplification is fully defined by the size and atom density of nanocrystals, which can be optimized through well-controlled nanocrystal synthesis. Further, the rich library of chromogenic reactions allows implementation of this scheme in various assay formats, as demonstrated by the iron oxide nanoparticle linked immunosorbent assay (ILISA) and blotting assay developed in this study. Our results indicate that, owing to the inherent simplicity, high sensitivity and repeatability, the nanocrystal based amplification scheme can significantly improve biomolecule quantification in both laboratory research and clinical diagnostics. This novel method adds a new dimension to current nanoparticle-based bioassays

Modified Frailty Index Combined with a Prognostic Nutritional Index for Predicting Postoperative Complications of Hip Fracture Surgery in Elderly

Aim: There is currently no consensus on the best risk assessment technique for predicting complications after hip surgery in the elderly, which is hindering the accuracy of surgical risk assessment. The goal of this study was to build a risk assessment model and evaluate its predictive value using the modified frailty index (5-mFI) and the prognostic nutritional index (PNI). Methods: A retrospective investigation was undertaken on 150 patients (aged ≥60 years) who had hip fracture surgery. Using univariate and multivariate logistic regression models, the relationship between combined 5-mFI and PNI and the evaluation of postoperative unfavorable outcomes such as infection and unscheduled intensive care unit (ICU) admission was investigated. Finally, utilizing receiver operating characteristic (ROC) curve analysis, the model’s predictive value for adverse outcomes following hip fracture surgery in elderly patients was assessed. Results: Univariate and multivariate logistic analyses revealed that preoperative PNI, 5-mFI, ASA, and gender acted as independent predictors of adverse outcomes after hip fracture surgery in the elderly. According to the ROC curve analysis, the predictive model demonstrated a high predictive value for total postoperative complications (AUC: 0.788; 95%CI: 0.715–0.860; p<0.01), infectious complications (AUC: 0.798; 95% CI: 0.727–0.868; P<0.001), and unplanned ICU admission (AUC: 0.783; 95% CI: 0.705–0.861; P<0.001). Conclusions: The multivariable evaluation model, which included 5-mFI and PNI, showed a high predictive value and can hence be applied to predict the adverse outcomes in elderly patients undergoing hip fracture surgery