The role of microstructural evolution during spark plasma sintering on the soft magnetic and electronic properties of a CoFe–Al2O3 soft magnetic composite

Journal of Materials Science - For transformers and inductors to meet the world’s growing demand for electrical power, more efficient soft magnetic materials with high saturation magnetic...     

Bayesian Inference for ARFIMA Models

This article develops practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of observations. These methods utilize sequentially adaptive Bayesian learning, a sequential Monte Carlo algorithm that can exploit massively parallel desktop computing with graphics processing units (GPUs). The article identifies and solves several problems in the computation of the likelihood function that apparently have not been addressed in the literature. Four applications illustrate the utility of the approach. The most ambitious is an ARFIMA(2,d,2) model for the Campito tree ring time series (length 5405), for which the methods developed in the article provide an essentially uncorrelated sample of size 16,384 from the exact posterior distribution in under four hours. Less ambitious applications take as little as 4 minutes without exploiting GPUs.     

Photomontage in the Present Perfect Continuous

In its first instance as art practice among the historical avant-garde, photomontage was considered indispensable for its claim to intervene in perceptual processes, stimulating a critical mode of apprehension that would redirect the viewer away from conventions of aesthetic experience and towards a lived reception of art with pronounced relevance to the sociopolitical landscape. The effect was understood as structural, that is, activated not so much by direct political content, but by the stark and shocking effects of juxtaposition. By this measure, one challenge to contemporary photomontage is clear: in a postindustrial and postdigital visual landscape dominated by the structural fragmentation of the attention economy, the ‘simultaneity of the radically disparate’ (as Peter Bürger put it) might no longer present as heterodoxy but rather threaten to sink into invisibility. Yet with the migration off-screen of the effects of electronic media, a new urgency around moving photomontage structures into physical, public space is rising in contemporary practices. Shannon Ebner’s multi-part project A Hudson Yard (2014–15) is emblematic of the new ways in which artists are manipulating photomontage as a form of fully sensory experience that gives the medium room to play critically in both virtual and material space. By constructing subtle interruptions of naturalised commercial space, A Hudson Yard activates a détournement of instrumentalised language, using structures of juxtaposition to divert the discursive surfaces of public space away from consumption and towards what could be called a public poesis.     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

GC-TOF-MS定性和定量评估5 种木本油料种籽油的脂肪酸

采用气相色谱-飞行时间串联质谱和超临界二氧化碳提取技术，分析评价5 种木本油料种籽油的脂肪酸组成及相对含量。油茶和榛子种籽油中富含油酸，亚油酸是沙棘和文冠果种籽油中的主要脂肪酸，牡丹种籽油中的亚麻酸含量最高。沙棘种籽油的单不饱和脂肪酸与饱和脂肪酸比值为1.57：1，亚油酸与亚麻酸的比值为1.56：1，符合功能性健康食用油的标准；牡丹种籽油是补充人体ω-3脂肪酸的优质食用油；油茶和榛子种籽富含单不饱和脂肪酸，适合食品加工；文冠果种籽油含有3 种长链单不饱和脂肪酸（如神经酸等）。本实验评价了5 种木本油料油脂脂肪酸的组分，对指导企业生产生物活性油和人们的健康消费具有重要意义。     

Poly(cyclodextrin)‐Polydrug Nanocomplexes as Synthetic Oncolytic Virus for Locoregional Melanoma Chemoimmunotherapy

Despite the approval of oncolytic virus (OV) therapy for advanced melanoma, its intrinsic limitations that include the risk of persistent viral infection and cost‐intensive manufacturing motivate the development of analogous approaches that are free from the disadvantages of virus‐based therapies. Herein, reported is a nanoassembly comprised of multivalent host–guest interactions between polymerized paclitaxel (pPTX) and nitric oxide‐incorporated polymerized β‐cyclodextrin (pCD‐pSNO) that through its bioactive components and when used locoregionally recapitulates the therapeutic effects of OV. The resultant pPTX/pCD‐pSNO exhibits significantly enhanced cytotoxicity, immunogenic cell death, dendritic cell (DC) activation, and T cell expansion in vitro compared to free agents alone or in combination. In vivo, intratumoral administration of pPTX/pCD‐pSNO results in activation and expansion of DCs systemically, but with a corresponding expansion of myeloid‐derived suppressor cells and suppression of CD8⁺ T cell expansion. When combined with antibody targeting cytotoxic T lymphocyte antigen‐4 that blunts this molecule's signaling effects on T cells, intratumoral pPTX/pCD‐pSNO treatment elicits potent anticancer effects that significantly prolong animal survival. This formulation thus leverages the chemo‐ and immunotherapeutic synergies of PTX and nitric oxide and suggests the potential for virus‐free nanoformulations to mimic the therapeutic action and benefits of OVs.