In-fiber photoelectric device based on graphene-coated tilted fiber grating

Graphene and related two-dimensional materials have attracted great research interests due to prominently optical and electrical properties and flexibility in integration with versatile photonic structures.Here,we report an in-fiber photoelec-tric device by wrapping a few-layer graphene and bonding a pair of electrodes onto a tilted fiber Bragg grating(TFBG)for photoelectric and electric-induced thermo-optic conversions.The transmitted spectrum from this device consists of a dense comb of narrowband resonances that provides an observable window to sense the photocurrent and the electrical injection in the graphene layer.The device has a wavelength-sensitive photoresponse with responsivity up to 11.4 A/W,allowing the spectrum analysis by real-time monitoring of photocurrent evolution.Based on the thermal-optic effect of electrical injection,the graphene layer is energized to produce a global red-shift of the transmission spectrum of the TF-BG,with a high sensitivity approaching 2.167×10^(4)nm/A^(2).The in-fiber photoelectric device,therefore as a powerful tool,could be widely available as off-the-shelf product for photodetection,spectrometer and current sensor.

Broadband and continuous wave pumped second-harmonic generation from microfiber coated with layered GaSe crystal

The conversion-efficiency for second-harmonic(SH)in optical fibers is significantly limited by extremely weak second-order nonlinearity of fused silica,and pulse pump lasers with high peak power are widely employed.Here,we propose a simple strategy to efficiently realize the broadband and continuous wave(CW)pumped SH,by transferring a crystalline GaSe coating onto a microfiber with phase-matching diameter.In the experiment,high efficiency up to 0.08%W-1mm-1 is reached for a C-band pump laser.The high enough efficiency not only guarantees SH at a single frequency pumped by a CW laser,but also multi-frequencies mixing supported by three CW light sources.Moreover,broadband SH spectrum is also achieved under the pump of a superluminescent light-emitting diode source with a 79.3 nm bandwidth.The proposed scheme provides a beneficial method to the enhancement of various nonlinear parameter processes,development of quasi-monochromatic or broadband CW light sources at new wavelength regions.

高分子交替多层结构的隔声特性仿真

使用有限元仿真方法对高分子交替多层结构的隔声特性进行了研究,构建了阻抗管测试的平面波声场和高分子多层复合材料模型,使用LMS Virtual. Lab进行了声振耦合计算,得到的隔声量曲线与实验测试结果规律一致。针对聚丙烯(PP)与乙烯-辛烯共聚物(POE)的交替层状样品,探究了在100~5000 Hz的计算范围内,层数、层厚比及两组分材料参数对整体隔声性能规律的影响,结果显示16层结构的隔声性能更优。同时,计算了板与多孔材料交替结构的隔声性能,结果表明,在给定的条件下4层结构有更高的隔声量。

T cells promote the regeneration of neural precursor cells in the hippocampus of Alzheimer's disease mice

Alzheimer＇s disease is closely associated with disorders of neurogenesis in the brain, and growing evidence supports the involvement of immunological mechanisms in the development of the disease. However, at present, the role of T cells in neuronal regeneration in the brain is unknown. We injected amyloid-beta 1-42 peptide into the hippocampus of six BALB/c wild-type mice and six BALB/c-nude mice with T-cell immunodeficiency to establish an animal model of Alzhei- mer＇s disease. A further six mice of each genotype were injected with same volume of normal saline. Immunohistochemistry revealed that the number of regenerated neural progenitor cells in the hippocampus of BALB/c wild-type mice was significantly higher than that in BALB/c-nude mice. Quantitative fluorescence PCR assay showed that the expression levels of peripheral T cell-associated cytokines （interleukin-2, interferon-y） and hippocampal microglia-related cyto- kines （interleukin-113, tumor necrosis factor-a） correlated with the number of regenerated neural progenitor cells in the hippocampus. These results indicate that T cells promote hippocampal neurogenesis in Alzheimer＇s disease and T-cell immunodeficiency restricts neuronal regeneration in the hippocampus. The mechanism underlying the promotion of neuronal regeneration by T cells is mediated by an increased expression of peripheral T cells and central microglial cytokines in Alzheimer＇s disease mice. Our findings provide an experimental basis for understanding the role of T cells in Alzheimer＇s disease.

Change of Tillage Layer Thickness of Farmland in Anhui Province of Eastern China

Tillage layer thickness (TLT) of farmland could be regarded as one of physical indexes in assessing soil productivity and quality. In recent years, tillage layer shallowing was found in China in various regions, mainly due to the adoption of non-tillage or rotary tillage practices, but only little rough and non-quantitative information is available so far on the issue. This research took Anhui, a typical agricultural province in Eastern China as an example and compared the TLTs of 87 typical profiles on provincial scale and 210 on county scale from 1980s to 2010s. The results showed that TLTs of 3.7% and 17.2% of samples in 1980s and 2010s respectively were larger than 20 cm. From 1980s to 2010s the mean TLT increased from 16.3 to 17.4 cm on the provincial scale and from 15.0 to 15.5 cm on the county scale respectively. In the middle and southern regions the mean TLTs increased by 0.4-0.7 cm on the provincial scale and 0.3-3.2 cm on the county scale respectively, but decreased by 2.0 cm in northern region on the county scale. The mean TLT increased by 0.8 cm for paddy-field and 1.4 cm for dry-land on the provincial scale. TLT was influenced comprehensively by the factors of soil texture, the depth of rotary tillage and the farming positivity of the farmers. Generally, TLT of farmland with coarse soil texture was higher than that of farmland with fine soil texture, in 1980s TLT in region of poor-economic condition usually was deeper than in region of good-economic condition, and the adoption of rotary tillage led widely TLTs of farmlands to about 15 cm in 2010s.

Explainable data transformation recommendation for automatic visualization

Automatic visualization generates meaningful visualizations to support data analysis and pattern finding for novice or casual users who are not familiar with visualization design.Current automatic visualization approaches adopt mainly aggregation and filtering to extract patterns from the original data.However,these limited data transformations fail to capture complex patterns such as clusters and correlations.Although recent advances in feature engineering provide the potential for more kinds of automatic data transformations,the auto-generated transformations lack explainability concerning how patterns are connected with the original features.To tackle these challenges,we propose a novel explainable recommendation approach for extended kinds of data transformations in automatic visualization.We summarize the space of feasible data transformations and measures on explainability of transformation operations with a literature review and a pilot study,respectively.A recommendation algorithm is designed to compute optimal transformations,which can reveal specified types of patterns and maintain explainability.We demonstrate the effectiveness of our approach through two cases and a user study.

EasySVM: A visual analysis approach for open-box support vector machines

Support vector machines(SVMs) are supervised learning models traditionally employed for classification and regression analysis. In classification analysis, a set of training data is chosen, and each instance in the training data is assigned a categorical class. An SVM then constructs a model based on a separating plane that maximizes the margin between different classes. Despite being one of the most popular classification models because of its strong performance empirically, understanding the knowledge captured in an SVM remains difficult. SVMs are typically applied in a black-box manner where the details of parameter tuning, training, and even the final constructed model are hidden from the users. This is natural since these details are often complex and difficult to understand without proper visualization tools. However, such an approach often brings about various problems including trial-and-error tuning and suspicious users who are forced to trust these models blindly.The contribution of this paper is a visual analysis approach for building SVMs in an open-box manner.Our goal is to improve an analyst's understanding of the SVM modeling process through a suite of visualization techniques that allow users to have full interactive visual control over the entire SVM training process.Our visual exploration tools have been developed to enable intuitive parameter tuning, training datamanipulation, and rule extraction as part of the SVM training process. To demonstrate the efficacy of our approach, we conduct a case study using a real-world robot control dataset.

VisComposer: A Visual Programmable Composition Environment for Information Visualization

As the amount of data being collected has increased,the need for tools that can enable the visual exploration of data has also grown.This has led to the development of a variety of widely used programming frameworks for information visualization.Unfortunately,such frameworks demand comprehensive visualization and coding skills and require users to develop visualization from scratch.An alternative is to create interactive visualization design environments that require lttle to no programming.However,these tools only supports a small portion of visual formns.We present a programmable integrated development environment(IDE),VisComposer,that supports the development of expressive visualization using a drag and-drop visual interface.Vis-Composer exposes the programmability by customizing desired components within a modular-ized visualization composition pipeline,effectively balancing the capability gap between expert coders and visualization artists.The implemented system empowers users to compose compre-bensive visualizations with real-time preview and optimization features,and supports prototyp-ing,sharing and reuse of the effects by means of an intuitive visual composer.Visual program-ming and textual programming integrated in our system allow users to compose more complex visual effects while retaining the simplicity of use.We demonstrate the performance of VisCom-poser with a variety of examples and an informal user evaluation.

Polycyclic aromatic hydrocarbons in benthos of the northern Bering Sea Shelf and Chukchi Sea Shelf

Eighteen polycyclic aromatic hydrocarbons(PAHs)were detected in benthos collected onboard the‘Snow Dragon’in the Northern Bering Sea Shelf and Chukchi Sea Shelf during the 6 th Chinese National Arctic Research Expedition(CHINARE 2014).18 PAHs for all biota samples ranged from 34.2 to 128.1 ng/g dry weight(dw),with the highest concentration observed in fish muscle(Boreogadus saida)samples close to St.Lawrence Island.The PAH composition pattern was dominated by the presence of lighter 3 ring(57%)and 2 ring(28%)PAHs,indicating oil-related or petrogenic sources as important origins of PAH contamination.Concentrations of alkyl-PAHs(1-methylnaphthalene and 2-methylnaphthalene)were lower than their parent PAH(naphthalene)in all biological tissue,and their percentage also decreased significantly(p<0.05)compared with those in the corresponding sediment.There were no significant relationships between PAH concentrations and trophic levels,which is possibly due to the combined results of the complex benthic foodweb in the subarctic/Arctic shelf region,as well as a low assimilation/effective metabolism for PAHs.According to toxic potency evaluation results from TCDD toxic equivalents(TEQs)and Ba P-equivalent(Ba PE)values,whelk(Neptunea heros)and starfish(Ctenodiscus crispatus)are two macroinvertebrate species showing relatively higher dioxin-like toxicity and carcinogenic risk.

A new emerging target in cancer immunotherapy: Galectin-9 (LGALS9)

Over the past few decades, advances in immunological knowledge have led to the identification of novel immune checkpoints, reinvigorating cancer immunotherapy. Immunotherapy, represented by immune checkpoint inhibitors, has become the leader in the precision treatment of cancer, bringing a new dawn to the treatment of most cancer patients. Galectin-9 (LGALS9), a member of the galectin family, is a widely expressed protein involved in immune regulation and tumor pathogenesis, and affects the prognosis of various types of cancer. Galectin-9 regulates immune homeostasis and tumor cell survival through its interaction with its receptor Tim-3. In the review, based on a brief description of the signaling mechanisms and immunomodulatory activities of galectin-9 and Tim-3, we summarize the targeted expression patterns of galectin-9 in a variety of malignancies and the promising mechanisms of anti-galectin-9 therapy in stimulating anti-tumor immune responses.

Recent progress and trends in predictive visual analytics

A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future predictions are output with no insight into what goes on during the process. Unfortunately, such a closed system approach often leaves little room for injecting domain expertise and can result in frustration from analysts when results seem snurious or confusing. In order to allow for more human-centric approaches, the visualization community has begun developing methods to enable users to incorporate expert knowledge into the pre- diction process at all stages, including data cleaning, feature selection, model building and model validation. This paper surveys current progress and trends in predictive visual ana- lytics, identifies the common framework in which predictive visual analytics systems operate, and develops a summariza- tion of the predictive analytics workfiow.

Mobile CRISPR-Cas9 based anti-phage system in E. coli

Escherichia coli is one of the most important microbial cell factories,but infection by bacteriophages in the environment may have a huge impact on its application in industrial production.Here,we developed a mobile CRISPR-Cas9 based anti-phage system for bacteriophages defense in E.coli.Two conjugative plasmids pGM1(phosphoglucomutase 1)and pGM2 carrying one and two guide RNAs,respectively,were designed to defend against a filamentous phage.The results showed that the pGM1 and pGM2 could decrease the phage infection rate to 1.6%and 0.2%respectively in infected cells.For preventing phage infection in E.coli,the pGM2 decreased the phage infection rate to 0.1%,while pGM1 failed to block phage infection.Sequence verification revealed that point mutations in protospacer or protospacer adjacent motif sequences of the phage genome caused loss of the defense function.These results support the potential application of MCBAS in E.coli cell factories to defend against phage infections.

The Visual Analytics and Data Exploration Research Lab at Arizona State University

This article describes the research agenda for the Visual Analytics and Data Exploration Research(VADER)Lab at Arizona State University.Over the past decade,the VADER Lab has focused on creating novel algorithms,tools and visualizations for spatiotemporal data.This article will highlight past success in spatiotemporal analysis,explainable AI,graph mining,and mathematical topology.While,at first,these topics seem largely disjoint,we will describe how the underpinnings of spatiotemporal analysis has informed the various research directions in the VADER Lab,and how this research agenda has served to form a network of strong international collaborations.Finally,we will outline a vision for the Lab’s future research.