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To explore and validate the clinical value of ultrasound (US) viscosity imaging in differentiating breast lesions by combining with BI-RADS, and then comparing the diagnostic performances with BI-RADS alone. This multicenter, prospective study enrolled participants with breast lesions from June 2021 to November 2022. A development cohort (DC) and validation cohort (VC) were established. Using histological results as reference standard, the viscosity-related parameter with the highest area under the receiver operating curve (AUC) was selected as the optimal one. Then the original BI-RADS would upgrade or not based on the value of this parameter. Finally, the results were validated in the VC and total cohorts. In the DC, VC and total cohorts, all breast lesions were divided into the large lesion, small lesion and overall groups respectively. A total of 639 participants (mean age, 46 years ± 14) with 639 breast lesions (372 benign and 267 malignant lesions) were finally enrolled in this study including 392 participants in the DC and 247 in the VC. In the DC, the optimal viscosity-related parameter in differentiating breast lesions was calculated to be A′-S2-Vmax, with the AUC of 0.88 (95% CI: 0.84, 0.91). Using > 9.97 Pa.s as the cutoff value, the BI-RADS was then modified. The AUC of modified BI-RADS significantly increased from 0.85 (95% CI: 0.81, 0.88) to 0.91 (95% CI: 0.87, 0.93), 0.85 (95% CI: 0.80, 0.89) to 0.90 (95% CI: 0.85, 0.93) and 0.85 (95% CI: 0.82, 0.87) to 0.90 (95% CI: 0.88, 0.92) in the DC, VC and total cohorts respectively (P <.05 for all). The quantitative viscous parameters evaluated by US viscosity imaging contribute to breast cancer diagnosis when combined with BI-RADS. [ABSTRACT FROM AUTHOR]

: To determine whether pretreatment moxibustion prevents asthma by down-regulating the lung RhoA/ROCK pathway in rats with bronchial asthma and benignly mediating the lung inflammatory response. : Twenty Sprague Dawley (SD) rats were randomly divided into normal control group (C), asthma model group (M), suspended moxibustion 40 min +asthma group (SM40), and suspended moxibustion 10 min +asthma group (SM10). Ovalbumin was used as a sensitizer. The two moxibustion groups completed moxibustion treatment lasted 40 min or 10 min respectively 30 min before modeling onset, and was repeated five times in each modeling cycle, for a total of 15 times. Samples were harvested on day 30. : Lung impairment was significant in the M group, whereas pretreatment with SM10 and SM40 dramatically attenuated the injury. After modeling, mRNA expression of RhoA and ROCK2 in the lung tissue was significantly higher than that in C group (both P < 0.001), resulting in significant increase in protein levels of IL-17A (P < 0.001). Significant decrease in RhoA and ROCK2 mRNA expression was seen in the SM10 (P <0.001, P <0.01) and SM40 (both P <0.001) groups compared to that with M rats. The differential trend in the SM40 group was more evident than that in the SM10 group. Regarding IL-10 or IL-17A protein concentration, an upregulation or down-regulation was observed in both SM10 (P <0.05, P < 0.01) and SM40 groups (both P < 0.001) compared to that with the M group. : Moxibustion pretreatment significantly prevented pulmonary inflammation in asthmatic rats, potentially via inhibition of the RhoA/ROCK pathway. The efficacty of moxibustion appeared to be significantly associated with the duration of intervention with moxibustion. [ABSTRACT FROM AUTHOR]

Abstract Amphioxus has been widely used as a model for the comparative immunology of vertebrates. Studies have reported that gene expression changes in the amphioxus gill in response to biotic stress, such as microbial and their mimic challenge, but little is known about how gene expression is affected by abiotic stress in the marine environment, such as nitrite. A lack of information regarding gene expression response to abiotic stress hinders a comprehensive understanding of gill defense response in amphioxus. Here, RNA sequencing was used to carry out gene expression profiling analyses of Branchiostoma belcheri gills under nitrite stress. Six libraries were created for the control and treatment groups, including three biological replicates. In total, 2416 differently expressed genes (DEGs) were detected in response to nitrite stress, of which 1522 DEGs were up-regulated in the treatment group in comparison to the control, while the remaining 894 DEGs were down-regulated genes. Functional enrichment revealed that these DEGs are primarily involved in disease, innate immunity, xenobiotic biodegradation and metabolism, and biomolecular processes and apoptosis. We screened 11 key nitrite-responsive DEGs to detect their expression responses to nitrite stress at different time points, and validate the sequencing data using real time quantitative PCR. The results indicated that the expression of gene encoding CYP3A, POD, CASPR1, GST, MAO, DDH, and XDH/XO were induced, while those encoding MRC, GT, DNASE1L, and RIPK5 were reduced, to participate in the anti-nitrite response. This study provides a useful resource for research of molecular toxicology in amphioxus under environmental stress. Highlights • Gene expression profiling was analyzed in Branchiostoma belcheri gills between control and nitrite-treated groups. • 2,416 genes presented expression response to nitrite stress. • The analysis of qRT-PCR confirmed the accuracy of expression profiling results. • We screened 11 key nitrite-responsive DEGs. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) often leads to long-term neurocognitive dysfunctions. Adult neurogenesis in the hippocampal dentate gyrus (DG) serves critical functions in cognition but can be disrupted by brain injury and insult in serval forms. In the present study, we explore the cellular and molecular targets of DPP-4 inhibitors (or gliptins) as related to hippocampal function and TBI cognitive sequelae. Two structurally different gliptins, sitagliptin and vildagliptin, were examined using a controlled cortical impact (CCI) model of moderate TBI in mice. Sensorimotor CCI, although distal from the hippocampus, impaired hippocampal-dependent cognition without obvious hippocampal tissue destruction. Neurogenic cell proliferation in the DG was increased accompanied by large numbers of reactive astrocyte. Increased numbers of immature granule cells with abnormal dendritic outgrowth were ectopically localized in the outer granule cell layer (GCL) and hilus. Long-term potentiation of dentate immature granule cells was also impaired. Both sitagliptin and vildagliptin attenuated the CCI-induced ectopic migration of doublecortin-positive immature neurons into the outer GCL and hilus, restored the normal dendritic branching pattern of the immature neurons and prevented astrocyte reactivation. Both gliptins prevented loss of normal synaptic integration in the DG after sensorimotor CCI and improved cognitive behavior. Sensorimotor cortical injury thus results in an abnormal neurogenesis pattern and astrocyte reactivation in the distal hippocampus which appears to contribute to the development of cognitive dysfunction after TBI. DPP-4 inhibitors prevent astrocyte reactivation, normalize the posttraumatic hippocampal neurogenesis and help to maintain normal electrophysiology in the DG with positive behavioral effect in a mouse model. • Sensorimotor cortical injury distally impairs hippocampal-dependent cognition. • TBI-increased neurogenesis adversely affects long-term cognition. • TBI induces abnormal localization and complex dendritic pattern of immature neurons. • TBI induces hypertrophic astrocyte processes which facilitate aberrant neurogenesis. • Gliptins normalize post-TBI hippocampal neurogenesis, restore hippocampal function. [ABSTRACT FROM AUTHOR]

Paeonol is a major constituent of the Chinese herb Moutan cortex radices. Recent studies report that paeonol has neuroprotective effects and improves impaired learning and memory. However, its underlying mechanisms by which paeonol contributes to synaptic transmission remain unclear. In this study, we found that paeonol increased the frequency of miniature excitatory postsynaptic currents (mEPSCs) and spontaneous excitatory postsynaptic currents (sEPSCs), but had no effect on the amplitude in rat hippocampal CA1 neurons. Similarly, the acetylcholinesterase (AChE) inhibitor rivastigmine increased the frequency of mEPSCs, but had no effect upon amplitude in rat hippocampal neurons. Rivastigmine also inhibited the delayed outward K + currents in rat hippocampal CA1 neurons, but had no effect in nucleus ambiguus (NA) neurons. The Kv2 blocker guangxitoxin-1E increased the frequency of both mEPSCs and sEPSCs of rat hippocampal CA1 neurons, without affecting their amplitude. Our results suggest that paeonol and rivastigmine enhance spontaneous presynaptic transmitter release, which may be associated with the inhibition of the hippocampal Kv2 current and with therapeutic potential in neurotransmitter deficits found in Alzheimer's disease (AD). Moreover, our data also show that paeonol protects against Aβ 25–35 -induced impairment of long-term potentiation (LTP) in mouse hippocampal neurons. However, guangxitoxin-1E failed to potentiate the evoked field excitatory postsynaptic potentials (fEPSPs), LTP and Aβ 25–35 -induced impairment of LTP. These results indicate that paeonol may has the potential to improve learning and memory in AD. Interestingly, this effect is not involved in the inhibition of the hippocampal Kv2 current. [ABSTRACT FROM AUTHOR]

The aim of the present study is to evaluate the ability and mechanism by which grape seed procyanidin extract (GSPE) relieves arsenic trioxide (As 2 O 3 )-induced renal inflammatory injury. Therefore, male Kunming mice were treated with As 2 O 3 and/or GSPE by gavage for 5 weeks. Mice were then sacrificed and inflammatory cytokines of kidneys were examined by ELISA, whereas the expression levels of molecules involved in the nuclear factor (NF)-κB signaling pathway were evaluated by both qRT-PCR and Western blot. Our results indicate that GSPE prevents As 2 O 3 -mediated renal inflammatory injury by inhibiting activation of the NF-κB signaling pathway and inflammatory cytokine production, while promoting expression of anti-inflammatory cytokines. [ABSTRACT FROM AUTHOR]

The orexin system consists of two peptides, orexin A and B and two receptors, OX 1 R and OX 2 R. It is implicated in learning and memory regulation while controversy remains on its role in modulating hippocampal synaptic plasticity in vivo and in vitro . Here, we investigated effects of orexin A on two forms of synaptic plasticity, long-term potentiation (LTP) and depotentiation of field excitatory postsynaptic potentials (fEPSPs), at the Schaffer Collateral-CA1 synapse of mouse hippocampal slices. Orexin A (≧30 nM) attenuated LTP induced by theta burst stimulation (TBS) in a manner antagonized by an OX 1 R (SB-334867), but not OX 2 R (EMPA), antagonist. Conversely, at 1 pM, co-application of orexin A prevented the induction of depotentiation induced by low frequency stimulation (LFS), i.e. restoring LTP. This re-potentiation effect of sub-nanomolar orexin A occurred at LFS of 1 Hz, but not 2 Hz, and with LTP induced by either TBS or tetanic stimulation. It was significantly antagonized by SB-334867, EMPA and TCS-1102, selective OX 1 R, OX 2 R and dual OXR antagonists, respectively, and prevented by D609, SQ22536 and H89, inhibitors of phospholipase C (PLC), adenylyl cyclase (AC) and protein kinase A (PKA), respectively. LFS-induced depotentiation was antagonized by blockers of NMDA, A 1 -adenosine and type 1/5 metabotropic glutamate (mGlu1/5) receptors, respectively. However, orexin A (1 pM) did not affect chemical-induced depotentiation by agonists of these receptors. These results suggest that orexin A bidirectionally modulates hippocampal CA1 synaptic plasticity, inhibiting LTP via OX 1 Rs at moderate concentrations while inducing re-potentiation via OX 1 Rs and OX 2 Rs, possibly through PLC and AC-PKA signaling at sub-nanomolar concentrations. [ABSTRACT FROM AUTHOR]

Summary Tuberculosis remains one of the world's deadliest communicable diseases. Limitations in the current diagnosis tools have heavily slowed down the step to eliminate TB. The objective of this study was to identify potential circulating miRNA associated with tuberculosis (TB) infection and disease development. Agilent human miRNA microarray was used to estimate the circulating levels of 1887 miRNAs among 34 study participants (10 patients with pulmonary TB, 13 controls with latent TB infection and 11 non-infected healthy controls). The identified miRNAs were subsequently verified by real-time qPCR. Target gene prediction and miRNA-gene network construction were further explored. A total of 119 miRNAs were identified to be in different levels between any two groups of the study population by microarray (Fold Change>2, p < 0.01). 11 most promising miRNAs were then selected for verification by real-time qPCR. The levels of hsa-let-7b-5p and hsa-miR-30b-5p were confirmed to be significantly up-regulated in pulmonary TB patients as compared to both control groups (p < 0.01). Caspase 3 was predicted to be one common target gene for these two miRNAs. None of the selected miRNA was confirmed to be related with the infection status. This pilot study suggested circulating hsa-let-7b and hsa-miR-30b might be associated with TB development by regulating the target genes involved in TLR-NF-kB mediated signal pathway. [ABSTRACT FROM AUTHOR]

Abstract: In order to extend light response of TiO2 into the visible region and enhance its photocatalytic activity, W and S codoped TiO2–SiO2–ZnO composite film was successfully prepared. The Brunauer–Emmett–Teller (BET) results showed that the surface area of the modified TiO2 was 424.5m2 g−1, while that of the pure TiO2 was 103.4m2 g−1. The high-resolution field emission scanning electron microscopy (FE-SEM) results revealed that the surface of the modified TiO2 film was more uniform and smooth with smaller particles compared to pure TiO2 film. The diffuse reflectance measurements exhibited that the modified TiO2 film had obvious red-shift. The photoluminescence (PL) analysis indicated that the electron–hole recombination rate was effectively inhibited in the modified TiO2 systems. The photocatalytic activities of the TiO2 films were evaluated by the photocatalytic decomposition of organic dyes in aqueous solution. Compared with pure TiO2 film, the modified TiO2 film exhibited excellent photocatalytic activity. [Copyright &y& Elsevier]

Abstract: To enhance the photocatalytic activity of TiO2, V and Zn co-doped TiO2 films were synthesized by the sol–gel method. The experimental results indicated that the films were composed of round-like nano-particles or aggregates. V and Zn codoping could not only obviously increase the specific surface area of TiO2 but also result in the narrowed band gap of TiO2 sample. The photocatalytic activities of the TiO2 films were evaluated by the photocatalytic decomposition of organic dyes in aqueous solution. Compared with un-doped TiO2 film or single doped TiO2 film, V and Zn co-doped TiO2 film exhibited excellent photocatalytic activities under both UV light and visible light. The improvement mechanism by V and Zn codoping was also discussed. [Copyright &y& Elsevier]

Abstract: Emotional state recognition is an important component for efficient human–computer interaction. Most existing works address this problem using 2D features, which are usually sensitive to head pose, clutter, and variations in lighting conditions. The existing 3D based methods only consider geometric information for visual feature extraction. In this paper, we introduce a method based on real 3D visual features for human emotion recognition. The 3D geometric information plus color/density information of the facial expressions are extracted by 3D Gabor library to construct visual feature vectors. The filter’s scale, orientation and shape of the library are specified according to the appearance patterns of the 3D facial expressions. An improved kernel canonical correlation analysis (IKCCA) algorithm is adopted for final decision. From training samples, the semantic ratings that describe the different facial expressions are computed by IKCCA to generate a seven dimensional semantic expression vector. It is then applied for learning the correlation with different testing samples. According to this correlation, we estimate the associated expression vector and perform expression classification. From experimental results, our proposed method demonstrates impressive performance. [Copyright &y& Elsevier]

Abstract: Automatic human face detection from video sequences is an important component of intelligent human computer interaction systems for video surveillance, face recognition, emotion recognition and face database management. This paper proposes an automatic and robust method to detect human faces from video sequences that combines feature extraction and face detection based on local normalization, Gabor wavelets transform and Adaboost algorithm. The key step and the main contribution of this work is the incorporation of a normalization technique based on local histograms with optimal adaptive correlation (OAC) technique to alleviate a common problem in conventional face detection methods: inconsistent performance due to sensitivity to variation illuminations such as local shadowing, noise and occlusion. The approach uses a cascade of classifiers to adopt a coarse-to-fine strategy for achieving higher detection rates with lower false positives. The experimental results demonstrate a significant performance improvement gains and achieved by local normalization over methods without normalizations in real video sequences with a wide range of facial variations in color, position, scale, and varying lighting conditions. [Copyright &y& Elsevier]

Background/Purpose: The electropharmacological effect of arsenic trioxide (As2O3) is unknown. The present study investigated the effects of As2O3 on spontaneous neuronal impulse activity. Methods: Intracellular recordings and the two-electrode voltage clamp method were used to study the effect of As2O3 on the RP4 neuron, the number 4 neuron in the right partial ganglion of the giant African snail (Achatina fulica Ferussac). Results: The RP4 neuron generated spontaneous action potentials, which were affected by As2O3 in a concentration-dependent manner. Extracellular application of 1 or 3 mM As2O3 decreased the frequency of spontaneously generated action potentials. At 10 mM, As2O3 first depolarized and then elicited irreversible bursts of potential (BoPs) at 60 minutes after administration. At 30 mM, As2O3 depolarized the resting membrane potential and abolished the spontaneous action potentials. The BoPs elicited by 10 mM As2O3 were blocked when neurons were pretreated with phospholipase C (PLC) inhibitors (10 mM U73122 or 3 mM neomycin). The BoPs elicited by As2O3 remained unchanged in the presence of KT5720, verapamil, or calcium replacement solution. Voltage-clamp studies revealed that 10 mM As2O3 decreased the fast inward current and had no effect on the steady-state outward current of the neuron. Conclusion: As2O3 at 10 mM elicits BoPs in central snail neurons and this effect may relate to the PLC activity of the neuron, rather than protein kinase A activity, or calcium influxes of the neuron. As2O3 at higher concentration irreversibly abolishes the spontaneous action potentials of the neuron. [Copyright &y& Elsevier]

Abstract: The Self Organising Tree Map (SOTM) neural network is investigated as a means of segmenting micro-organisms from confocal microscope image data. Features describing pixel and regional intensities, phase congruency and spatial proximity are explored in terms of their impact on the segmentation of bacteria and other micro-organisms. The significance of individual features is investigated, and it is proposed that, within the context of micro-biological image segmentation, better object delineation can be achieved if certain features are more dominant in the initial stages of learning. In this way, other features are allowed to become more/less significant as learning progresses: as more knowledge is acquired about the data being segmented. We argue that the efficiency and flexibility of the SOTM in adapting to, and preserving the topology of input space, makes it an appropriate candidate for implementing this idea. We propose a refinement to the competitive search strategy that allows for a more appropriate fusion of signal and proximal features, thereby promoting a segmentation that is more sensitive to the regional associations of different microbial matter. A refined stop criterion is also suggested such that the dynamically generated number of classes becomes more data dependant. Preliminary experiments are presented and it is found that favouring intensity characteristics in the early phases of learning, whilst relaxing proximity constraints in later phases of learning, offers a general mechanism through which we can improve the segmentation of microbial constituents. 1 [1] An abbreviated version of some portions of this article appeared in [Kyan, M., Guan, L., & Liss, S. (2005). Dynamic feature fusion in the self organising Tree map—applied to the segmentation of biofilm images. Proceedings of the International Joint Conference on Neural Networks. July 31–August 4, 2005, Montreal, Canada.], published under the IEEE copyright. [Copyright &y& Elsevier]

Angiotensin-converting enzyme (ACE), consisting of N-domain and C-domain, is a key regulator of blood pressure. The use of cACE-specific inhibitors helps minimize side effects in clinical applications. Legumes are a good source of proteins containing ACE inhibitory peptides; however, no studies have reported the identification of cACE-specific inhibitory peptides from Fabaceae. In this study, thermal hydrolysates from seeds, sprouts, pods, seedlings, and flowers of legumes were analyzed. Flowers of legumes exhibited a C-domain-preference ACE inhibition and anti-hypertensive effect in rats. Screening the legume peptide library identified a novel cACE inhibitory peptide, SJ-1. This study reported the first identification of cACE inhibitory peptide from Fabaceae foods. SJ-1, identified from the legume flowers, interacted with active site residues of cACE, leading to the inhibition of ACE activity, downregulation of bradykinin levels, and reduction of blood pressure. These findings also suggested the potential of legume proteins as a source of cACE inhibitory peptides. [Display omitted] • The first identification of cACE inhibitory peptides from Fabaceae foods was reported. • cACE inhibitory activity was observed in the thermal hydrolysate of legume flowers. • A novel cACE inhibitory peptide, SJ-1, was identified from the legume peptide library. • SJ-1 interacted with the active site residues of cACE and reduced blood pressure in rats. • SJ-1 inhibited ACE cleavage of angiotensin I but not bradykinin. [ABSTRACT FROM AUTHOR]

In current deep learning architectures, each of the deeper layers in networks tends to contain hundreds of unorganized neurons which makes it hard for humans to understand how they interact with each other. By organizing the neurons using correlation as the criteria, humans can observe how clusters of neighbouring neurons interact with each other. Research in Explainable Artificial Intelligence (XAI) aims to all alleviate the black-box nature of current AI methods and make them understandable by humans. In this paper, we extend our previous algorithm for XAI in deep learning, called Locality Guided Neural Network (LGNN). LGNN preserves locality between neighbouring neurons within each layer of a deep network during training. Motivated by Self-Organizing Maps (SOMs), the goal is to enforce a local topology on each layer of a deep network such that neighbouring neurons are highly correlated with each other. Our algorithm can be easily plugged into current state of the art Convolutional Neural Network (CNN) models to make the neighbouring neurons more correlated. A cluster of neighbouring neurons activating for a class makes the network both quantitatively and qualitatively more interpretable when visualized, as we show through our experiments. This paper focuses on image processing with CNNs, but can theoretically be applied to any type of deep learning architecture. In our experiments, we train VGG and WRN networks for image classification on CIFAR100 and Imagenette. Our experiments analyse different perceptible clusters of activations in response to different input classes. [ABSTRACT FROM AUTHOR]

The visible light active Ce/F codoped TiO 2 –ZnO composite films with a bad gap of 1.82 eV were successfully prepared though a simple sol–gel method. Experimental results indicated that the composite films showed excellent photocatalytic performance towards photocatalytic oxidation of organic pollutants including formaldehyde, acid naphthol red (ANR) and methyl green (MG). The catalysts were characterized by photoluminescence (PL) spectra, UV–vis diffraction reflectance absorption spectra (DRS), X-ray diffraction (XRD), differential thermal analysis-thermogravimetry (DTA-TG), field emission scanning electron microscopy (FE-SEM) equipped with energy-dispersive spectroscopy (EDS), and N 2 adsorption/desorption isotherms. The DRS and PL spectra results showed that multi-modification not only induced strong visible light absorption but also reduced the recombination rate of electron–hole pairs. The DTA-TG and XRD results indicated that the crystal type of the TiO 2 -based catalyst was mostly stabilized in anatase. The FE-SEM and BET surface area results revealed that the nanocrystalline Ce/F codoped TiO 2 –ZnO composite samples with the larger specific surface area were composed of smaller nanoparticles compared to pure TiO 2 . The mechanism of the enhanced photocatalytic activity was discussed in this study. [ABSTRACT FROM AUTHOR]

Highlights: [•] We synthesize nanocrystalline Co2+/F− codoped TiO2–SiO2 composite film. [•] The film shows strong visible light adsorption and diminished e−/h+ recombination. [•] The film is effective in oxidizing organic dyes and emerging contaminants. [•] The mechanism of enhanced photocatalytic activity is explained. [ABSTRACT FROM AUTHOR]

Accurate determination of similarity between samples is fundamental and critical for graph network based few-shot learning tasks. Previous approaches typically employ convolutional neural networks to obtain relations between nodes. However, these networks are not adept at handling node features in vector form. To overcome this limitation, we proposed a modified gated graph network (MGGN) that uniquely integrates graph networks and modified gated recurrent units (M-GRU) for few-shot classification. The introduced M-GRU mitigates the loss of label information from the initial graph and reduces computational complexity. The MGGN contains two modules that alternately update node and edge features. The node update module leverages a gating mechanism to integrate edge features into node update weights, fostering a learnable node aggregation process. The edge update component perceives the trend in edge feature changes and establishes long-term dependencies. Experimental results on two benchmark datasets demonstrate that our MGGN achieves comparable performance to state-of-the-art methods. The code is available at https://github.com/zpx16900/MGGN. • Introducing the M-GRU to measure the similarity of node features in graph networks. • The extraction of edge features relies on the current layer as well as past layers. • Weighted gating edge features are utilized for node aggregation. [ABSTRACT FROM AUTHOR]

Abstract: A hybrid method for personalized recommendation of news on the Web is presented, which provides Web users with an autonomous tool that is able to minimize repetitive and tedious Web surfing. The proposed approach classifies Web pages by calculating the respective weights of terms. A user’s interest and preference models are generated by analyzing the user’s navigational history. Based on the content of the Web pages and on a user’s interest and preference models, the recommender system suggests news Web pages to the user who is likely interested in the related topics. Moreover, the technique of collaborative filtering, which aims to choose the trusted users, is employed to improve the performance of the recommender system. Experiments are carried out in order to demonstrate the effectiveness of the proposed method. In the experiments, Web news items are classified and recommended to Web users by matching the users’ interests with the contents of the news. [Copyright &y& Elsevier]

The effect of Si content on the growth of σ phase in SUS 309L was investigated. It was proven that δ-ferrite decomposes rapidly at 800 °C and more σ phases are formed with an increase in the Si content. All δ-ferrite in SUS 309L containing 0.76 wt% Si decomposes after 50 h aging at 800 °C. The Si content acts as a catalyst to accelerate σ phase formation. [Copyright &y& Elsevier]

• In this paper, nano-sheet self-assembled spherical Ni-MoS 2 material was prepared by a simple hydrothermal method, and then Ni-MoS 2 and Bi 2 WO 6 were composed of heterojunction composite material by hydrothermal method. • First principles calculations show that impurity levels appear after Ni is incorporated into MoS 2 , and the heterostructure forms a built-in electric field between the interfaces. Both methods can promote the effective separation of photo-generated carrier. • Bi 2 WO 6 /Ni-MoS 2 heterojunction materials showed excellent photocatalytic degradation of Rhodamine B dye with high concentration, which was unprecedented in previous reports. In this study, the Ni-doped MoS 2 photocatalyst was first prepared by hydrothermal method, and then combined with Bi 2 WO 6 to form Bi 2 WO 6 /Ni-MoS 2 heterogeneous composite material. Bi 2 WO 6 /Ni-MoS 2 composites have higher optical absorption intensity and photogenic carrier mobility. The 4% Bi 2 WO 6 /Ni-MoS 2 composite had the best photocatalytic degradation efficiency in the photocatalytic degradation experiment of rhodamine B at high concentration. The first - principles analysis shows that the heterogeneous structure can promote charge transfer. The experimental results showed that ·OH, O 2 −· and h+ all acted in the reaction, and h+ played the main role. On the basis of systematic study, the mechanism of Ni-doped MoS 2 and the construction of heterojunction structure to enhance the photocatalytic activity is elucidated, which provides a new reference for the design of novel efficient photocatalysts. [Display omitted] [ABSTRACT FROM AUTHOR]

Canonical correlation analysis(CCA) and its variants have been playing an important role in dimension reduction and information fusion. Most of the existing CCA-related algorithms can only handle fully-paired scenarios, where all the samples from different views require to be rigorously paired. However, majority of the samples only provide partial pairwise correspondences in most cases. In such semi-paired scenarios, traditional methods often perform poorly due to overfitting. Furthermore, most CCA-related algorithms only focus on the correlation between different views but ignore preserving the within-view similarity which is helpful to make samples in the same class mapped more compactly onto canonical correlation space. In addition, since CCA is unable to exploit discriminative information effectively, improved performance is limited in many tasks. To solve these challenging problems, we propose a novel method named joint Intermodal and Intramodal Semi-paired Canonical Correlation Analysis (I 2 SCCA), which properly handle the semi-paired scenarios. At the same time, the method preserves the within-view similarity information by making two neighbor samples in the same view closer in the projected space. Different from traditional similarity matrix construction, we incorporate a rank constraint of Laplacian matrix into the graph-based clustering algorithms. With fewer parameters, a graph that has exactly c (the number of clusters) connected components is learned without requiring any post graph-cut processing. Based on the obtained graph, we estimate the cross-view correlation through similarity measure of the single view. Specially, taking advantage of clustering assumption, discriminative information is derived although there is no label available. Finally, we extend I 2 SCCA to multi-view and non-linear cases. Extensive experiments on several datasets demonstrate the effectiveness of I 2 SCCA. [ABSTRACT FROM AUTHOR]

Background: The management of latent Mycobacterium tuberculosis infection is a new priority action for the WHO End Tuberculosis (TB) Strategy. However, national guidelines on latent tuberculosis infection testing and treatment have not yet been developed in China. Here, we present the results from the 2-year follow-up of a study that aimed to track the development of active disease in individuals with latent tuberculosis infection, identify priority populations for latent infection management, and explore the most suitable latent infection diagnostic approach.Methods: A population-based multicentre prospective study was done in four sites in rural China, between 2013 and 2015. The baseline survey in 2013 measured the prevalence of latent tuberculosis infection using QuantiFERON-TB Gold In-Tube (QFT) and tuberculin skin test (TST) in eligible participants. During the follow-up phase between 2014-15, we assessed individuals who had tuberculosis infection at baseline (QFT-positivity or TST tuberculin reaction size [induration] of ≥10 mm) for the development of active disease through active case finding. Eligible participants included in follow-up survey had a birth date before June 1, 2008 (5 years or older in 2013), and continuous residence at the study site for 6 months or longer in the past year. Participants with current active tuberculosis at baseline survey were excluded.Findings: Between Sept 1, 2013, and Aug 31, 2015, 7505 eligible participants (aged 5 years or older) were included in tuberculosis infection test positive cohorts (4455 were QFT positive, 6404 had TST induration ≥10 mm, and 3354 were positive for both tests) after baseline examination. During the 2-year follow-up period, 84 incident cases of active tuberculosis were diagnosed. Of participants who developed active tuberculosis, 75 were diagnosed with latent infection by QFT, 62 were diagnosed by TST, and 53 were diagnosed by both tests. An incidence rate of 0·87 (95% CI 0·68-1·07) per 100 person-years was observed for individuals who tested positive with QFT, 0·50 (0·38-0·63) per 100 person-years for those who tested positive with TST (p<0·0001), and 0·82 (0·60-1·04) per 100 person-years for those who tested positive with both tests. Male sex and a history of tuberculosis were significantly associated with increased risk of disease development with adjusted hazard ratios of 2·36 (95% CI 1·30-4·30) for male sex and 5·40 (3·34-8·71) for a history of tuberculosis.Interpretation: Our results suggest that high-risk populations in communities in rural China, such as individuals at a high risk of disease reactivation from previous tuberculosis, should be targeted for latent infection screening and treatment with an interferon-γ releasing assay rather than a TST.Funding: National Science and Technology Major Project of China, Program for Changjiang Scholars and Innovative Research Team in University of China, CAMS Innovation Fund for Medical Sciences, and Sanming Project of Medicine in Shenzhen. [ABSTRACT FROM AUTHOR]

Abstract: In one-class classification, the low variance directions in the training data carry crucial information to build a good model of the target class. Boundary-based methods like One-Class Support Vector Machine (OSVM) preferentially separates the data from outliers along the large variance directions. On the other hand, retaining only the low variance directions can result in sacrificing some initial properties of the original data and is not desirable, specially in case of limited training samples. This paper introduces a Covariance-guided One-Class Support Vector Machine (COSVM) classification method which emphasizes the low variance projectional directions of the training data without compromising any important characteristics. COSVM improves upon the OSVM method by controlling the direction of the separating hyperplane through incorporation of the estimated covariance matrix from the training data. Our proposed method is a convex optimization problem resulting in one global optimum solution which can be solved efficiently with the help of existing numerical methods. The method also keeps the principal structure of the OSVM method intact, and can be implemented easily with the existing OSVM libraries. Comparative experimental results with contemporary one-class classifiers on numerous artificial and benchmark datasets demonstrate that our method results in significantly better classification performance. [Copyright &y& Elsevier]