Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous-time filter featuring Q and frequency on-chip automatic tuning

In this paper we report the on-chip automatic tuning of digitally programmable continuous-time Gm-C filters with a wide operation range employing a hybrid analog/fine-digital/coarse master-slave scheme. The tuning method, for both Q-factor and the characteristic frequency, is based on a digital phase comparator included in the phase-locked loop and achieves high-precision tunability. The digital frequency tuning is obtained with an error of plusmn4% and the maximum settling time when changing between two consecutive digital words is 0.3 mus. Once the digital word is fixed, the fine tuning finely adjusts the value of the characteristic frequency to the reference and corrects for possible temperature variations with an error of plusmn5% and a settling time of 0.2 mus.
Urinary neutrophil gelatinase-associated lipocalin as a marker for disease activity in lupus nephritis

Abstract The neutrophil gelatinase-associated lipocalin (NGAL) has been emerging as a novel biomarker of acute kidney injury while its value in lupus nephritis is uncertain. The aim of this study was to assess urinary NGAL levels as a marker for disease activity in patients with lupus nephritis.This study included 70 systemic lupus erythematosus (SLE) patients; 50 with active lupus nephritis (LN) and 20 without as well as 20 matched controls. The neutrophil gelatinase-associated lipocalin (NGAL) in both serum and urine samples was measured by enzyme-linked immunosorbent assay (ELISA). Patients with active LN received standard treatment then assessed for response as well as the value of urinary NGAL (uNGAL). Our results revealed that, The SLE patients with or without LN had an elevated urinary NGAL as compared to controls (p < 0.000) and the mean of uNGAL was (20.67 ± 5.34),(10.63 ± 3.53),(5.65 ± 2.49) respectively. Furthermore,Urinary NGAL levels in LN patients were significantly higher than those in non-LN patients (P < 0.0001). In the ROC curve analysis , the diagnostic performance of uNGAL for discriminating patients with nephritis from those without nephritis showed that the best cutoff value was 13.66 ng/ml ,sensitivity 92%,specificity 75%,area undercurve (0.959) and (P < 0.0001). Measurement of urinary NGAL levels showed an excellent diagnostic performance for discriminating patients with LN from SLE without nephritis.
A trusted computing environment model in cloud architecture

The main difference between cloud computing and traditional enterprise internal IT services is that the owner and the user of cloud IT infrastructures are separated in cloud. This change requires a security duty separation in cloud computing. Cloud service providers (CSP) should secure the services they offer and cannot exceed the customers' authorities. Currently, no traditional information security products can meet this requirement. A multi-tenancy trusted computing environment model (MTCEM) is designed for IaaS delivery model, and its purpose is to assure a trusted cloud infrastructure to customers. MTCEM presents a dual level transitive trust mechanism and supports a security duty separation function simultaneously. With MTCEM, CSP and customers can cooperate to build and maintain a trusted cloud computing environment. MTCEM can be used to improve customers' confidence on cloud computing. The prototype of MTCEM shows that it has low impact on system performance and it is technically and practically feasible.
Reduction of Inter-Cell interference in close proximity cell using dynamic fractional frequency reuse method

Close Proximity is emerging as a cost effective solution for satisfying the huge demands of mobile data. It can be deployed at any place where mobile traffic is required without the need for cell planning. However, coexistence of many uncontrolled small-cells using the same licensed frequency band can result in serious interference problems. In order to utilize small-cell efficiently, it is highly desirable that the small-cell can self-organize the network and mitigate interference automatically. This paper is proposing a dynamic fractional frequency reuse (DFFR) method for reducing the inter-cell interference (ICI) automatically. With reference to dynamic fractional frequency reuse (DFFR), each cell is separated into two regions identified as super region and regular region. For regular region, it is separated into three parts equivalent to the three sectors. The proposed method has evidently provided a comparable performance with Fractional Frequency Reuse (FFR) through simulation. Simulation results have verified the effectiveness of the proposed method.
Biochemical, Structural and Molecular Dynamics Analyses of the Potential Virulence Factor RipA from Yersinia pestis

Human diseases are attributed in part to the ability of pathogens to evade the eukaryotic immune systems. A subset of these pathogens has developed mechanisms to survive in human macrophages. Yersinia pestis, the causative agent of the bubonic plague, is a predominately extracellular pathogen with the ability to survive and replicate intracellularly. A previous study has shown that a novel rip (required for intracellular proliferation) operon (ripA, ripB and ripC) is essential for replication and survival of Y. pestis in postactivated macrophages, by playing a role in lowering macrophage-produced nitric oxide (NO) levels. A bioinformatics analysis indicates that the rip operon is conserved among a distally related subset of macrophage-residing pathogens, including Burkholderia and Salmonella species, and suggests that this previously uncharacterized pathway is also required for intracellular survival of these pathogens. The focus of this study is ripA, which encodes for a protein highly homologous to 4-hydroxybutyrate-CoA transferase; however, biochemical analysis suggests that RipA functions as a butyryl-CoA transferase. The 1.9 Å X-ray crystal structure reveals that RipA belongs to the class of Family I CoA transferases and exhibits a unique tetrameric state. Molecular dynamics simulations are consistent with RipA tetramer formation and suggest a possible gating mechanism for CoA binding mediated by Val227. Together, our structural characterization and molecular dynamic simulations offer insights into acyl-CoA specificity within the active site binding pocket, and support biochemical results that RipA is a butyryl-CoA transferase. We hypothesize that the end product of the rip operon is butyrate, a known anti-inflammatory, which has been shown to lower NO levels in macrophages. Thus, the results of this molecular study of Y. pestis RipA provide a structural platform for rational inhibitor design, which may lead to a greater understanding of the role of RipA in this unique virulence pathway.
Engineering topology aware adaptive security: Preventing requirements violations at runtime

Adaptive security systems aim to protect critical assets in the face of changes in their operational environment. We have argued that incorporating an explicit representation of the environment's topology enables reasoning on the location of assets being protected and the proximity of potentially harmful agents. This paper proposes to engineer topology aware adaptive security systems by identifying violations of security requirements that may be caused by topological changes, and selecting a set of security controls that prevent such violations. Our approach focuses on physical topologies; it maintains at runtime a live representation of the topology which is updated when assets or agents move, or when the structure of the physical space is altered. When the topology changes, we look ahead at a subset of the future system states. These states are reachable when the agents move within the physical space. If security requirements can be violated in future system states, a configuration of security controls is proactively applied to prevent the system from reaching those states. Thus, the system continuously adapts to topological stimuli, while maintaining requirements satisfaction. Security requirements are formally expressed using a propositional temporal logic, encoding spatial properties in Computation Tree Logic (CTL). The Ambient Calculus is used to represent the topology of the operational environment - including location of assets and agents - as well as to identify future system states that are reachable from the current one. The approach is demonstrated and evaluated using a substantive example concerned with physical access control.
Symmetric Interior Penalty Discontinuous Galerkin Discretizations and Block Preconditioning for Heterogeneous Stokes Flow

Provable stable arbitrary order symmetric interior penalty (SIP) discontinuous Galerkin discretizations of heterogeneous, incompressible Stokes flow utilizing $Q^2_k$--$Q_{k-1}$ elements and hierarchical Legendre basis polynomials are developed and investigated. For solving the resulting linear system, a block preconditioned iterative method is proposed. The nested viscous problem is solved by a $hp$-multilevel preconditioned Krylov subspace method. For the $p$-coarsening, a two-level method utilizing element-block Jacobi preconditioned iterations as a smoother is employed. Piecewise bilinear ($Q^2_1$) and piecewise constant ($Q^2_0$) $p$-coarse spaces are considered. Finally, Galerkin $h$-coarsening is proposed and investigated for the two $p$-coarse spaces considered. Through a number of numerical experiments, we demonstrate that utilizing the $Q^2_1$ coarse space results in the most robust $hp$-multigrid method for heterogeneous Stokes flow. Using this $Q^2_1$ coarse space we observe that the convergen.
A Survey of Multimedia Streaming in LTE Cellular Networks

With the growing of Long Term Evolution (LTE) cellular networks and the increase in the demand of the video services, it is vital to consider the challenges in the streaming services from a different perspective. A perspective that focuses on the streaming services in light of cellular networks challenges, both per layer basis and across multiple layers as well. In this tutorial, we highlight the main challenges that faces the industry of video streaming in the context of cellular networks with a focus on LTE. We also discuss proposed solutions for these challenges while highlighting the limitations of these solutions and the conditions/assumptions required for these solution to deliver high performance. In addition, we show different work in cross layer optimization for video streaming and how it leads towards a more optimized end to end LTE networking for video streaming. Finally, we suggest different open research areas in the domain of video delivery over LTE networks that can significantly enhance the quality of streaming experience to the end user.
Advancing the management of obstructive airways diseases through translational research

Obstructive airways diseases (OAD) represent a huge burden of illness world‐wide, and in spite of the development of effective therapies, significant morbidity and mortality related to asthma and COPD still remains. Over the past decade, our understanding of OAD has improved vastly, and novel treatments have evolved. This evolution is the result of successful translational research, which has connected clinical presentations of OAD and underlying disease mechanisms, thereby enabling the development of targeted treatments. The next challenge of translational research will be to position these novel treatments for OAD for optimal clinical use. At the same time, there is great potential in these treatments providing even better insights into disease mechanisms in OAD by studying the effects of blocking individual immunological pathways. To optimize this potential, there is a need to ensure that translational aspects are added to randomized clinical trials, as well as real‐world studies, but also to use other trial designs such as platform studies, which allow for simultaneous assessment of different interventions. Furthermore, demonstrating clinical impact, that is research translation, is an increasingly important component of successful translational research. This review outlines concepts of translational research, exemplifying how translational research has moved management of obstructive airways diseases into the next century, with the introduction of targeted, individualized therapy. Furthermore, the review describes how these therapies may be used as research tools to further our understanding of disease mechanisms in OAD, through translational, mechanistic studies. We underline the current need for implementing basic immunological concepts into clinical care in order to optimize the use of novel targeted treatments and to further the clinical understanding of disease mechanisms. Finally, potential barriers to adoption of novel targeted therapies into routine practice and how these may be overcome are described.
Detecting Botclouds at Large Scale: A Decentralized and Robust Detection Method for Multi-Tenant Virtualized Environments

Cloud computing has gained an important role in providing high quality and cost-effective IT services by outsourcing part of their operations to dedicated cloud providers. If intrinsic security issues of this architecture have been extensively studied, it has recently been considered as a ready-to-use platform able to perform malicious activities, thus offering new targets for indirect threats. However, its large scale, the heterogeneous and dynamic nature of the activities it executes, as well as multi-tenancy and privacy-related issues, make the security operation complex. Consequently, cloud providers can hardly detect and mitigate malicious activities they unknowingly host. Leveraging the autonomic paradigm represents a promising solution to face such a complexity, but it requires efficient grounded monitoring and analysis functions to efficiently detect malicious activities hidden within the large number of legitimate ones. In this effort, this paper presents a robust and cost-effective solution to detect malicious activities in a public virtualized environment. Its contribution is twofold: 1) a scalable and robust workload estimation of the virtual host activities in a cloud and 2) a detection algorithm able to discriminate infected hosts with low malicious activities hidden within their legitimate workload and potentially scattered across several tenants. For both of these contributions, we establish their theoretical performance, which demonstrates their optimality, and we evaluate their efficiency on a dataset made of real data collected on PlanetLab. Finally, we study the scalability on a large dataset that consists of simulated data resulting from the real dataset modeling. This demonstrates to what extent the proposal exhibits an excellent sharpness and a reasonable cost, even at a very large scale.
Identification of Circulating MicroRNA Signatures in Crohn's Disease Using the Nanostring nCounter Technology

Background:Current clinical indices, such as Harvey–Bradshaw index, are often inadequate for the assessment of disease activity in Crohn's disease (CD). Alternative methods including imaging modalities and laboratory markers, such as C-reactive protein (CRP), are routinely applied to assess disease activity. However, laboratory markers poorly reflect the actual disease activity. Consequently, novel biomarkers represent a clinical necessity for CD patient management. We hypothesized that circulating serum-derived microRNAs may be used as diagnosis and disease activity monitoring tools of CD patients. Methods:To test this hypothesis, we performed microRNA expression profiling through Nanostring nCounter technology in blood serum samples of CD patients and healthy control subjects. Harvey–Bradshaw index score was used to capture clinical disease activity; CRP was measured as part of standard clinical practice. The expression profile of circulating microRNAs and the levels of CRP correlated with Harvey–Bradshaw index. Results:We identified a signature of 10 circulating microRNAs that are differentially expressed in CD patients compared with healthy control subjects. Two of these microRNAs (hsa-miR-1286 and hsa-miR-1273d) correlated with CD disease activity and exhibited higher correlation values compared with CRP. Further analysis revealed distinct microRNA signatures between CD patients with ileal and colonic involvement. Conclusions:Circulating microRNAs show superior value as diagnostic and disease activity markers in comparison to traditional methods. Circulating microRNAs could improve CD patient management, if applied in combination with current state-of-the-art diagnostic and disease activity assessment modalities.
The complete chloroplast genome sequence of Cynanchum auriculatum Royle ex Wight (Apocynaceae)

Abstract Cynanchum auriculatum is a climbing vine belonging to the Apocynaceae family and shows very similar morphology to Cynanchum wilfordii, a medicinal plant. The complete chloroplast genome of C. auriculatum was generated by de novo assembly using the small amount of whole genome sequencing data. The chloroplast genome of C. auriculatum was 160 840 bp in length and consisted of four distinct regions, such as large single copy region (91 973 bp), small single copy region (19 667 bp), and a pair of inverted repeat regions (24 600 bp). The overall GC contents of the chloroplast genome were 37.8%. A total of 114 genes were predicted and included 80 protein-coding genes, 30 tRNA genes, and four rRNA genes. Phylogenetic analysis with the reported chloroplast genomes revealed that C. auriculatum is most closely related to Cynanchum wilfordii, a medicinal plant.
A new strategy for improved secondary screening and lead optimization using high‐resolution SPR characterization of compound–target interactions

Biophysical label‐free assays such as those based on SPR are essential tools in generating high‐quality data on affinity, kinetic, mechanistic and thermodynamic aspects of interactions between target proteins and potential drug candidates. Here we show examples of the integration of SPR with bioinformatic approaches and mutation studies in the early drug discovery process. We call this combination ‘structure‐based biophysical analysis’. Binding sites are identified on target proteins using information that is either extracted from three‐dimensional structural analysis (X‐ray crystallography or NMR), or derived from a pharmacore model based on known binders. The binding site information is used for in silico screening of a large substance library (e.g. available chemical directory), providing virtual hits. The three‐dimensional structure is also used for the design of mutants where the binding site has been impaired. The wild‐type target and the impaired mutant are then immobilized on different spots of the sensor chip and the interactions of compounds with the wild‐type and mutant are compared in order to identify selective binders for the binding site of the target protein. This method can be used as a cost‐effective alternative to high‐throughput screening methods in cases when detailed binding site information is available. Here, we present three examples of how this technique can be applied to provide invaluable data during different phases of the drug discovery process. Copyright © 2005 John Wiley & Sons, Ltd.
Vitamin D Reduces Colitis- and Inflammation-Associated Colorectal Cancer in Mice Independent of NOD2

ABSTRACT Inflammatory bowel disease (IBD) patients are at increased risk of developing colorectal cancer (CRC). Vitamin D (vD) induces NOD2 gene expression, enhancing immunity, while deficiency impairs intestinal epithelial integrity, increasing inflammation. This study investigated the effect of vD on CRC in colitis, and if preventive benefits are mediated via NOD2. Inflammation-associated CRC was induced by treating C57BL/6J and Nod2−/− mice with azoxymethane (AOM) and dextran sodium sulfate (DSS) cycles (×3). vD-deficient mice displayed more severe colitis compared to vD-supplemented mice, with greater weight loss, higher colitis activity index, increased colonic weight/length ratios, and lower survival rates. Increased histological inflammation score and increased IL-6 were observed in the mucosa of vD-deficient mice. Overall incidence of colonic tumors was not significantly different between vD-deficient and vD-supplemented mice. Higher tumor multiplicity was observed in vD-deficient vs vD-supplemented groups (both mouse strains). After AOM/DSS treatment, decreased plasma 25(OH)D3 levels and downregulation of vD target genes Cyp24 and Vdr were observed in both mice strains (vD-deficient or vD-supplemented diet), compared to saline-treated controls on the vD-deficient diet. In conclusion, vD supplementation reduced colitis severity and decreased the number of inflammation-associated colorectal tumors in both C57BL/6J and Nod2−/− mice, independent of NOD2.
Classical Chinese Sentence Segmentation

Sentence segmentation is a fundamental issue in Classical Chinese language processing. To facilitate reading and processing of the raw Classical Chinese data, we propose a statistical method to split unstructured Classical Chinese text into smaller pieces such as sentences and clauses. The segmenter based on the conditional random field (CRF) model is tested under different tagging schemes and various features including n-gram, jump, word class, and phonetic information. We evaluated our method on four datasets from several eras (i.e., from the 5th century BCE to the 19th century). Our CRF segmenter achieves an F-score of 83.34% and can be applied on a variety of data from different eras.
Ambient Particulate Matter Air Pollution Exposure and Mortality in the NIH-AARP Diet and Health Cohort

Background: Outdoor fine particulate matter (≤ 2.5 μm; PM2.5) has been identified as a global health threat, but the number of large U.S. prospective cohort studies with individual participant data remains limited, especially at lower recent exposures. Objectives: We aimed to test the relationship between long-term exposure PM2.5 and death risk from all nonaccidental causes, cardiovascular (CVD), and respiratory diseases in 517,041 men and women enrolled in the National Institutes of Health-AARP cohort. Methods: Individual participant data were linked with residence PM2.5 exposure estimates across the continental United States for a 2000–2009 follow-up period when matching census tract–level PM2.5 exposure data were available. Participants enrolled ranged from 50 to 71 years of age, residing in six U.S. states and two cities. Cox proportional hazard models yielded hazard ratio (HR) estimates per 10 μg/m3 of PM2.5 exposure. Results: PM2.5 exposure was significantly associated with total mortality (HR = 1.03; 95% CI: 1.00, 1.05) and CVD mortality (HR = 1.10; 95% CI: 1.05, 1.15), but the association with respiratory mortality was not statistically significant (HR = 1.05; 95% CI: 0.98, 1.13). A significant association was found with respiratory mortality only among never smokers (HR = 1.27; 95% CI: 1.03, 1.56). Associations with 10-μg/m3 PM2.5 exposures in yearly participant residential annual mean, or in metropolitan area-wide mean, were consistent with baseline exposure model results. Associations with PM2.5 were similar when adjusted for ozone exposures. Analyses of California residents alone also yielded statistically significant PM2.5 mortality HRs for total and CVD mortality. Conclusions: Long-term exposure to PM2.5 air pollution was associated with an increased risk of total and CVD mortality, providing an independent test of the PM2.5–mortality relationship in a new large U.S. prospective cohort experiencing lower post-2000 PM2.5 exposure levels. Citation: Thurston GD, Ahn J, Cromar KR, Shao Y, Reynolds HR, Jerrett M, Lim CC, Shanley R, Park Y, Hayes RB. 2016. Ambient particulate matter air pollution exposure and mortality in the NIH-AARP Diet and Health cohort. Environ Health Perspect 124:484–490; http://dx.doi. org/10.1289/ehp.1509676