Miracle-dz/UniFAR-FTUs huggingface dataset:
Neutral Fragment Filtering for Rapid Identification of New Diester-Diterpenoid Alkaloids in Roots of Aconitum carmichaeli by Ultra-High-Pressure Liquid Chromatography Coupled with Linear Ion Trap-Orbitrap Mass Spectrometry

A rapid and effective method was developed for separation and identification of diester-diterpenoid alkaloids (DDA) in the roots of Aconitum carmichaeli by ultra-high-pressure liquid chromatography coupled with high resolution LTQ-Orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap-MSn). According to accurate mass measurement and the characteristic neutral loss filtering strategy, a total of 42 diester-diterpenoid alkaloids (DDA) were rapidly detected and characterized or tentatively identified. Meanwhile, the proposed fragmentation pathways and the major diagnostic fragment ions of aconitine, mesaconitine and hypaconitine were investigated to trace DDA derivatives in crude plant extracts. 23 potential new compounds were successfully screened and characterized in Aconitum carmichaeli, including 16 short chain fatty acyls DDA, 4 N-dealkyl DDA and several isomers of aconitine, mesaconitine and hypaconitine.
A Multi-Level Accumulation-Based Rectification Method and Its Circuit Implementation

Rectification is an essential procedure for simplifying the disparity extraction of stereo matching algorithms by removing vertical mismatches between left and right images. To support real-time stereo matching, studies have introduced several look-up table (LUT)- and computational logic (CL)-based rectification approaches. However, to support high-resolution images, the LUT-based approach requires considerable memory resources, and the CL-based approach requires numerous hardware resources for its circuit implementation. Thus, this paper proposes a multi-level accumulation-based rectification method as a simple CL-based method and its circuit implementation. The proposed method, which includes distortion correction, reduces addition operations by 29%, and removes multiplication operations by replacing the complex matrix computations and high-degree polynomial calculations of the conventional rectification with simple multi-level accumulations. The proposed rectification circuit can rectify 1,280 × 720 stereo images at a frame rate of 135 fps at a clock frequency of 125 MHz. Because the circuit is fully pipelined, it continuously generates a pair of left and right rectified pixels every cycle after 13-cycle latency plus initial image buffering time. Experimental results show that the proposed method requires significantly fewer hardware resources than the conventional method while the differences between the results of the proposed and conventional full rectifications are negligible.
An Effective Approach to Controller Placement in Software Defined Wide Area Networks

One grand challenge in software defined networking is to select appropriate locations for controllers to shorten the latency between controllers and switches in wide area networks. In the literature, the majority of approaches are focused on the reduction of packet propagation latency, but propagation latency is only one of the contributors of the overall latency between controllers and their associated switches. In this paper, we explore and investigate more possible contributors of the latency, including the end-to-end latency and the queuing latency of controllers. In order to decrease the end-to-end latency, the concept of network partition is introduced and a clustering-based network partition algorithm (CNPA) is then proposed to partition the network. The CNPA can guarantee that each partition is able to shorten the maximum end-to-end latency between controllers and switches. To further decrease the queuing latency of controllers, appropriate multiple controllers are then placed in the subnetworks. Extensive simulations are conducted under two real network topologies from the Internet Topology Zoo. The results verify that the proposed algorithm can remarkably reduce the maximum latency between controllers and their associated switches.
A Western dietary pattern is associated with elevated level of high sensitive C‐reactive protein among adolescent girls

Serum high sensitive C‐reactive protein (hs‐CRP), is an indicator of low‐grade inflammation, and is associated with several non‐communicable diseases. The effects of diet on inflammation have not been extensively investigated, particularly among adolescents. We aimed to examine the association between major dietary patterns and elevated serum level of hs‐CRP among Iranian adolescent girls.
Joint beamforming and cooperative jamming for secure transmission in multi-antenna decode-and-forward relaying sensor networks: A greedy switching strategy

In wireless sensor networks, sensor nodes are deployed to collect data and deliver the sensed information to a base station in a wireless manner. Due to the broadcast nature of wireless sensor communications, relay-sensor-based secure transmission remains a challenging issue. This article proposes a joint cooperative beamforming and jamming scheme in the relay wireless sensor networks, where the switching strategy from cooperative beamforming to cooperative jamming is applied to weaken the signal-to-interference-plus-noise ratio of the eavesdropper when the decoding threshold is not triggered. In particular, based on Charnes–Cooper transformation and S-procedure, semi-definite programming is constructed to solve the robust cooperative beamforming and jamming with a low implementation complexity, respectively. Additionally, we adopt the global power constraints in semi-definite programming to take full exploitation of the power at relay sensor. Finally, simulation results demonstrate the superiority of the proposed scheme in comparison with the traditional decode-and-forward robust scheme and the non-robust scheme.
A RST-Resilient Watermarking Scheme Based on Invariant Features

A RST-resilient watermarking scheme based on invariant features are proposed in this paper. The scale-invariant points of wavelet low-frequency sub-image are used to realize resynchronization after RST (Rotation Scale Translation) attacks. An improved HVS model is adopted to embed multiplicative spread spectrum watermark in DWT (Discrete Wavelet Transform) domain, and optimal water- marking detection algorithm is employed to enhance robustness of watermarking. Experiments demonstrate that the proposed scheme can resist both RST and general image processing attacks.
Maternal alcohol use during pregnancy and offspring attention-deficit hyperactivity disorder (ADHD): a prospective sibling control study.

Background Maternal alcohol use during pregnancy has repeatedly been associated with development of attention-deficit hyperactivity disorder (ADHD) in the offspring. It is, however not known whether this reflects a direct casual intra-uterine effect or a non-causal relationship due to confounding. We used three different approaches to control for measured and unmeasured confounding: statistical adjustment for covariates, negative control comparison against maternal pre-pregnancy alcohol use, and comparison among differentially exposed siblings. Methods The sample comprised 114 247 children (34 283 siblings) from 94 907 mothers, recruited to the Norwegian Mother and Child Birth Cohort Study between 1999 and 2008. Self-reported measurements of alcohol use were obtained in week 30 during the pregnancy. Mothers rated offspring ADHD symptoms at 5 years on two measures. Clinical ADHD diagnoses were obtained from the Norwegian Patient Registry. Results We found an overall positive association between maternal alcohol use during pregnancy and offspring ADHD symptoms, which was only marginally attenuated after inclusion of measured covariates. Both the negative control and the sibling comparison analysis further attenuated the estimated association, but it remained greater than zero [β = 0.017, 95% confidence interval (CI) = 0.005-0.030). No association was found between maternal alcohol use during pregnancy and offspring ADHD diagnosis. Conclusions For offspring ADHD symptoms we found a weak, but possibly causal association with maternal alcohol use during pregnancy, but no such effect was observed for clinical ADHD diagnosis.
Noisy Euclidean Distance Realization: Robust Facial Reduction and the Pareto Frontier

We present two algorithms for large-scale noisy low-rank Euclidean distance matrix completion problems, based on semidefinite optimization. Our first method works by relating cliques in the graph of the known distances to faces of the positive semidefinite cone, yielding a combinatorial procedure that is provably robust and partly parallelizable. Our second algorithm is a first-order method for maximizing the trace---a popular low-rank inducing regularizer---in the formulation of the problem with a constrained misfit. Both of the methods output a point configuration that can serve as a high-quality initialization for local optimization techniques. Numerical experiments on large-scale sensor localization problems illustrate the two approaches.
Illuminating an Ecosystem of Partisan Websites

This paper aims to shed light on alternative news media ecosystems that are believed to have influenced opinions and beliefs by false and/or biased news reporting during the 2016 US Presidential Elections. We examine a large, professionally curated list of 668 hyper-partisan websites and their corresponding Facebook pages, and identify key characteristics that mediate the traffic flow within this ecosystem. We uncover a pattern of new websites being established in the run up to the elections, and abandoned after. Such websites form an ecosystem, creating links from one website to another, and by 'liking' each others' Facebook pages. These practices are highly effective in directing user traffic internally within the ecosystem in a highly partisan manner, with right-leaning sites linking to and liking other right-leaning sites and similarly left-leaning sites linking to other sites on the left, thus forming a filter bubble amongst news producers similar to the filter bubble which has been widely observed among consumers of partisan news. Whereas there is activity along both left- and right-leaning sites, right-leaning sites are more evolved, accounting for a disproportionate number of abandoned websites and partisan internal links. We also examine demographic characteristics of consumers of hyper partisan news and find that some of the more populous demographic groups in the US tend to be consumers of more right-leaning sites.
Integrated Metagenomics/Metaproteomics Reveals Human Host-Microbiota Signatures of Crohn's Disease

Crohn's disease (CD) is an inflammatory bowel disease of complex etiology, although dysbiosis of the gut microbiota has been implicated in chronic immune-mediated inflammation associated with CD. Here we combined shotgun metagenomic and metaproteomic approaches to identify potential functional signatures of CD in stool samples from six twin pairs that were either healthy, or that had CD in the ileum (ICD) or colon (CCD). Integration of these omics approaches revealed several genes, proteins, and pathways that primarily differentiated ICD from healthy subjects, including depletion of many proteins in ICD. In addition, the ICD phenotype was associated with alterations in bacterial carbohydrate metabolism, bacterial-host interactions, as well as human host-secreted enzymes. This eco-systems biology approach underscores the link between the gut microbiota and functional alterations in the pathophysiology of Crohn's disease and aids in identification of novel diagnostic targets and disease specific biomarkers.
The Risks and Opportunities of the University of Science and Technology: The Concept and Application of School Effectiveness

In recent years, subject to changes in the industrial structure, outward manufacturers, the unemployment rate has increased steadily, and the birth rate leads to domestic human structural imbalance, so that universities faced unprecedented challenges. Among the private university of science and technology is the most serious. The crisis probably be divided into the internal factors about school operations and the external factors about social environment. In this study, we will use Customer Relationship Management (CRM) to investigate the relationship between schools, students and alumni. And try to use VIdegree cloud management system as a classroom and alumni database that combines CRM concepts. This article will explore its benefits for school development. Through the database, it could create personalized service and provide scheduled messages by the computer screening. It also could provide the latest information and services instantly. School could establish a Joint Service Center by the databases, computer and telephone to enhance connectivity between the school administration and alumni or students to help improve the school service satisfaction. It will also enhance students and alumni's loyalty to the school, And it will establish the school's reputation to enhance competitiveness.
Whole-genome association and genome partitioning revealed variants and explained heritability for total number of teats in a Yorkshire pig population

Objective The study was designed to perform a genome-wide association (GWA) and partitioning of genome using Illumina’s PorcineSNP60 Beadchip in order to identify variants and determine the explained heritability for the total number of teats in Yorkshire pig. Methods After screening with the following criteria: minor allele frequency, MAF≤0.01; Hardy-Weinberg equilibrium, HWE≤0.000001, a pair-wise genomic relationship matrix was produced using 42,953 single nucleotide polymorphisms (SNPs). A genome-wide mixed linear model-based association analysis (MLMA) was conducted. And for estimating the explained heritability with genome- or chromosome-wide SNPs the genetic relatedness estimation through maximum likelihood approach was used in our study. Results The MLMA analysis and false discovery rate p-values identified three significant SNPs on two different chromosomes (rs81476910 and rs81405825 on SSC8; rs81332615 on SSC13) for total number of teats. Besides, we estimated that 30% of variance could be explained by all of the common SNPs on the autosomal chromosomes for the trait. The maximum amount of heritability obtained by partitioning the genome were 0.22±0.05, 0.16±0.05, 0.10±0.03 and 0.08±0.03 on SSC7, SSC13, SSC1, and SSC8, respectively. Of them, SSC7 explained the amount of estimated heritability along with a SNP (rs80805264) identified by genome-wide association studies at the empirical p value significance level of 2.35E-05 in our study. Interestingly, rs80805264 was found in a nearby quantitative trait loci (QTL) on SSC7 for the teat number trait as identified in a recent study. Moreover, all other significant SNPs were found within and/or close to some QTLs related to ovary weight, total number of born alive and age at puberty in pigs. Conclusion The SNPs we identified unquestionably represent some of the important QTL regions as well as genes of interest in the genome for various physiological functions responsible for reproduction in pigs.
Linear-Time Sequence Classification using Restricted Boltzmann Machines

Classification of sequence data is the topic of interest for dynamic Bayesian models and Recurrent Neural Networks (RNNs). While the former can explicitly model the temporal dependencies between class variables, the latter have a capability of learning representations. Several attempts have been made to improve performance by combining these two approaches or increasing the processing capability of the hidden units in RNNs. This often results in complex models with a large number of learning parameters. In this paper, a compact model is proposed which offers both representation learning and temporal inference of class variables by rolling Restricted Boltzmann Machines (RBMs) and class variables over time. We address the key issue of intractability in this variant of RBMs by optimising a conditional distribution, instead of a joint distribution. Experiments reported in the paper on melody modelling and optical character recognition show that the proposed model can outperform the state-of-the-art. Also, the experimental results on optical character recognition, part-of-speech tagging and text chunking demonstrate that our model is comparable to recurrent neural networks with complex memory gates while requiring far fewer parameters.
A Bayesian Approach for Fast and Accurate Gene Tree Reconstruction

Recent sequencing and computing advances have enabled phylogenetic analyses to expand to both entire genomes and large clades, thus requiring more efficient and accurate methods designed specifically for the phylogenomic context. Here, we present SPIMAP, an efficient Bayesian method for reconstructing gene trees in the presence of a known species tree. We observe many improvements in reconstruction accuracy, achieved by modeling multiple aspects of evolution, including gene duplication and loss (DL) rates, speciation times, and correlated substitution rate variation across both species and loci. We have implemented and applied this method on two clades of fully sequenced species, 12 Drosophila and 16 fungal genomes as well as simulated phylogenies and find dramatic improvements in reconstruction accuracy as compared with the most popular existing methods, including those that take the species tree into account. We find that reconstruction inaccuracies of traditional phylogenetic methods overestimate the number of DL events by as much as 2–3-fold, whereas our method achieves significantly higher accuracy. We feel that the results and methods presented here will have many important implications for future investigations of gene evolution.
Urokinase-derived peptide UP-7 suppresses tumor angiogenesis and metastasis through inhibition of FAK activation

The recombinant kringle domain of urokinase (UK1) has been shown to inhibit angiogenesis and brain tumor growth in vivo. To avoid limitations in application due to mass production of recombinant protein, we attempted to develop a novel peptide inhibitor from UK1 sequence consisting of 83 amino acids that contains α-helices, loops and β-sheets. We dissected UK1 sequence to seven peptides based on structure and amino acid characteristics, and examined the anti-angiogenic activities for the constructed peptides. Among the tested peptides, UP-7 most potently inhibited the proliferation and migration of endothelial cells (ECs) in vitro, and also potently inhibited in vivo angiogenesis in the mouse matrigel plug assay. Such anti-angiogenic activities were not exerted by the scrambled peptide. At molecular level, UP-7 inhibited growth factor-induced phosphorylation of FAK and ERK1/2. It also suppressed formation of stress fibers and focal adhesions and also inhibited the attachment and spreading of ECs onto immobilized fibronectin. In a lung cancer animal model xenografted with non-UP-7-sensitive NCI-H460 cells, systemic treatment of UP-7 effectively suppressed tumor growth through inhibition of angiogenesis. Interestingly, breast cancer cells such as LM-MDA-MB-231 cells were moderately sensitive to UP-7 in proliferation differently from other cancer cells. UP-7 also inhibited migration, invasion and FAK phosphorylation of LM-MDA-MB-231 cells. Accordingly, UP-7 potently inhibited lung metastatic growth of LM-MDA-MB-231 cells in an experimental metastasis model. Taken together, these results suggest that novel peptide UP-7 can be effectively used for treatment of breast cancer metastatic growth through inhibition of angiogenesis and invasion.
Report of the 14th International Conference on Malignant Lymphoma (ICML) Closed Workshop on Future Design of Clinical Trials in Lymphomas

The 14th ICML held in Lugano in June 2017 was preceded by a closed workshop (organized in collaboration with the American Association for Cancer Research and the European School of Oncology) where experts in preclinical and clinical research in lymphomas met to discuss the current drug development landscape focusing on critical open questions that need to be addressed in the future to permit a more efficient drug development paradigm in lymphoma. Topics discussed included both preclinical models that can be used to test new drugs and drug combinations, as well as the optimal design of clinical trials and the endpoints that should be used to facilitate accelerated progress. This report represents a summary of the workshop. Clin Cancer Res; 24(13); 2993–8. ©2018 AACR.
Environmental Applications of Semiconductor Photocatalysis

The civilian, commercial, and defense sectors of most advanced industrialized nations are faced with a tremendous set of environmental problems related to the remediation of hazardous wastes, contaminated groundwaters, and the control of toxic air contaminants. For example, the slow pace of hazardous waste remediation at military installations around the world is causing a serious delay in conversion of many of these facilities to civilian uses. Over the last 10 years problems related to hazardous waste remediation have emerged as a high national and international priority.
On the statistical analysis of practical SPARQL queries

In this paper, we analyze some basic features of SPARQL queries from practical world in a statistical way. In particular, we focus on three statistic features including the occurrence frequency of triple patterns, fragments, and well-designed patterns and four semantic features including monotonicity, non-monotonicity, weak monotonicity and satisfiability. All the features contribute to characterize SPARQL queries in different dimensions. We hope that this statistical analysis would provide some useful observations for researchers and engineers who are interested in what real-word SPARQL queries look like, so that they could develop some practical heuristics for processing SPARQL queries, as well as build SPARQL query processing engines and benchmarks. In addition, our research facilitates to reduce scope of the problems by avoiding some cases that may not occur in practice.