Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Food and Environmental Exposures Relating to the Epidemiology of Campylobacter coli in Humans in Northwest England

ABSTRACT This study uses multilocus sequence typing (MLST) to investigate the epidemiology of Campylobacter coli in a continuous study of a population in Northwest England. All cases of Campylobacter identified in four Local Authorities (government administrative boundaries) between 2003 and 2006 were identified to species level and then typed, using MLST. Epidemiological information was collected for each of these cases, including food and recreational exposure variables, and the epidemiologies of C. jejuni and C. coli were compared using case-case methodology. Samples of surface water thought to represent possible points of exposure to the populations under study were also sampled, and campylobacters were typed with multilocus sequence typing. Patients with C. coli were more likely to be older and female than patients with C. jejuni. In logistic regression, C. coli infection was positively associated with patients eating undercooked eggs, eating out, and reporting problems with their water supply prior to illness. C. coli was less associated with consuming pork products. Most of the cases of C. coli yielded sequence types described elsewhere in both livestock and poultry, but several new sequence types were also identified in human cases and water samples. There was no overlap between types identified in humans and surface waters, and genetic analysis suggested three distinct clades but with several “intermediate” types from water that were convergent with the human clade. There is little evidence to suggest that epidemiological differences between human cases of C. coli and C. jejuni are a result of different food or behavioral exposures alone.
YOURPRIVACYPROTECTOR, A recommender system for privacy settings in social networks

Ensuring privacy of users of social networks is probably an unsolvable conundrum. At the same time, an informed use of the existing privacy options by the social network participants may alleviate - or even prevent - some of the more drastic privacy-averse incidents. Unfortunately, recent surveys show that an average user is either not aware of these options or does not use them, probably due to their perceived complexity. It is therefore reasonable to believe that tools assisting users with two tasks: 1) understanding their social net behavior in terms of their privacy settings and broad privacy categories, and 2)recommending reasonable privacy options, will be a valuable tool for everyday privacy practice in a social network context. This paper presents YourPrivacyProtector, a recommender system that shows how simple machine learning techniques may provide useful assistance in these two tasks to Facebook users. We support our claim with empirical results of application of YourPrivacyProtector to two groups of Facebook users.
Towards Multi-Purpose Spectral Rhythm Features: An Application to Dance Style, Meter and Tempo Estimation

This paper addresses the extraction of multipurpose spectral rhythm features that simultaneously tackle a variety of rhythm analysis tasks, namely, dance style classification, meter estimation, and tempo estimation. The term spectral rhythm features emanates from the origin of the extracted features, which is the periodicity function (PF), a spectral representation that encapsulates the salience of the rhythm frequencies. Two dimensionality reduction techniques applied on the PF to extract expressive and compact features are compared, namely, a linear transformation resulting from Principal Component Analysis and a nonlinear mapping derived from a Restricted Boltzmann Machine. Subsequently, the derived features were used as input to an SVM classifier for each task. Moreover, an additional method is proposed that reformulates the well-studied tempo estimation task as a combination of multiple binary classification sub-problems. Evaluation was performed on a large number of datasets demonstrating that the same set of features learned from the PF provide a robust rhythmic representation that achieved comparable results to the current state-of-the-art methods for the aforementioned tasks.
Absorption sensing enhancement in a microresonator coupled to a non-adiabatic tapered fiber

Whispering-gallery microresonators are well suited for use as sensors. For example, fluid analytes can be sensed through their effect on the refractive index or by their optical absorption. The former results in a frequency shift of a whispering-gallery mode (WGM); the latter changes the WGM’s intensity profile, and can be even more sensitive than the former. WGMs are typically excited by coupling of light from a tapered fiber. It has recently been demonstrated that using a non-adiabatic tapered fiber can produce a Fano resonance whose asymmetric shape can enhance the sensitivity of refractive-index sensing. The non-adiabatic taper allows the incoming light to be distributed between two fiber modes that interfere when exciting a single WGM, thereby producing the asymmetric resonance. However, just as absorption sensing can be more sensitive than index sensing, its enhancement by using a non-adiabatic taper can be greater as well. This enhancement is demonstrated theoretically here, and experiments for confirmation are underway.
Abstracting for Dimensionality Reduction in Text Classification

There is a growing interest in efficient models of text mining and an emergent need for new data structures that address word relationships. Detailed knowledge about the taxonomic environment of keywords that are used in text documents can provide valuable insight into the nature of the subject matter contained therein. Such insight may be used to enhance the data structures used in the text data mining task as relationships become usefully apparent. A popular scalable technique used to infer these relationships, while reducing dimensionality, has been Latent Semantic Analysis. We present a new approach, which uses an ontology of lexical abstractions to create abstraction profiles of documents and uses these profiles to perform text organization based on a process that we call frequent abstraction analysis. We introduce TATOO, the Text Abstraction TOOlkit, which is a full implementation of this new approach. We present our data model via an example of how taxonomically derived abstractions can be used to supplement semantic data structures for the text classification task.
A VLIW architecture for a trace scheduling compiler

Very Long Instruction Word (VLIW) architectures were promised to deliver far more than the factor of two or three that current architectures achieve from overlapped execution. Using a new type of compiler which compacts ordinary sequential code into long instruction words, a VLIW machine was expected to provide from ten to thirty times the performance of a more conventional machine built of the same implementation technology.Multiflow Computer, Inc., has now built a VLIW called the TRACETM along with its companion Trace SchedulingTM compacting compiler. This new machine has fulfilled the performance promises that were made. Using many fast functional units in parallel, this machine extends some of the basic Reduced-Instruction-Set precepts: the architecture is load/store, the microarchitecture is exposed to the compiler, there is no microcode, and there is almost no hardware devoted to synchronization, arbitration, or interlocking of any kind (the compiler has sole responsibility for runtime resource usage). This paper discusses the design of this machine and presents some initial performance results.
Isolation and Partial Purification of Macrophage- and Dendritic Cell-Activating Components from Mycoplasma arthritidis: Association with Organism Virulence and Involvement with Toll-Like Receptor 2

ABSTRACT Mycoplasma arthritidis induces toxicity, arthritis, and dermal necrosis in mice. Virulence factors include a superantigen and membrane adhesins and possibly also a bacteriophage component. Here we compare the biological properties of Triton X-114 extracts derived from avirulent and virulent M. arthritidis strains. Macrophage cell lines and resident peritoneal macrophages were used to assess inflammatory potential as indicated by production of tumor necrosis factor alpha, interleukin-6, and/or nitric oxide. The activity resided exclusively within the hydrophobic detergent phase, was unaffected by heat treatment at 100°C for 30 min, and was resistant to proteinase K digestion, suggesting involvement of a lipopeptide. Contamination of extracts with endotoxin or superantigen was excluded. Extracts of the more virulent strain had higher activity than did those of the avirulent strain. Using CHO cells expressing Toll-like receptor 2 (TLR2) or TLR4, both with transfected CD14, we showed that extracts activated these cells via TLR2 but not by TLR4. Also, macrophages from C57BL/6 TLR2−/− mice failed to respond to the extracts, whereas those from TLR2+/+ cells did respond. The preparations from the virulent strain of M. arthritidis were also more potent in activating dendritic cells, as evidenced by up-regulation of major histocompatibility complex class II, CD40, B7-1, and B7-2. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis and subsequent elution of gel slices revealed the presence of three active moieties which corresponded to molecular masses of approximately 24, 28, and 40 kDa. Three active components were also found by reverse-phase chromatography. We suggest that macrophage activation by M. arthritidis could play a significant role in the inflammatory response induced in the host by this organism.
Circulating Tumor DNA Reveals Clinically Actionable Somatic Genome of Metastatic Bladder Cancer

Purpose: Targeted agents and immunotherapies promise to transform the treatment of metastatic bladder cancer, but therapy selection will depend on practical tumor molecular stratification. Circulating tumor DNA (ctDNA) is established in several solid malignancies as a minimally invasive tool to profile the tumor genome in real-time, but is critically underexplored in bladder cancer. Experimental Design: We applied a combination of whole-exome sequencing and targeted sequencing across 50 bladder cancer driver genes to plasma cell-free DNA (cfDNA) from 51 patients with aggressive bladder cancer, including 37 with metastatic disease. Results: The majority of patients with metastasis, but only 14% of patients with localized disease, had ctDNA proportions above 2% of total cfDNA (median 16.5%, range 3.9%–72.6%). Twelve percent of estimable samples had evidence of genome hypermutation. We reveal an aggressive mutational landscape in metastatic bladder cancer with 95% of patients harboring deleterious alterations to TP53, RB1, or MDM2, and 70% harboring a mutation or disrupting rearrangement affecting chromatin modifiers such as ARID1A. Targetable alterations in MAPK/ERK or PI3K/AKT/mTOR pathways were robustly detected, including amplification of ERBB2 (20% of patients) and activating hotspot mutations in PIK3CA (20%), with the latter mutually exclusive to truncating mutations in TSC1. A novel FGFR3 gene fusion was identified in consecutive samples from one patient. Conclusions: Our study demonstrates that ctDNA provides a practical and cost-effective snapshot of driver gene status in metastatic bladder cancer. The identification of a wide spectrum of clinically informative somatic alterations nominates ctDNA as a tool to dissect disease pathogenesis and guide therapy selection in patients with metastatic bladder cancer. Clin Cancer Res; 23(21); 6487–97. ©2017 AACR.
The Internet Motion Sensor - A Distributed Blackhole Monitoring System

As national infrastructure becomes intertwined with emerging global data networks, the stability and integrity of the two have become synonymous. This connection, while necessary, leaves network assets vulnerable to the rapidly moving threats of today’s Internet, including fast moving worms, distributed denial of service attacks, and routing exploits. This paper introduces the Internet Motion Sensor (IMS), a globally scoped Internet monitoring system whose goal is to measure, characterize, and track threats. The IMS architecture is based on three novel components. First, a Distributed Monitoring Infrastructure increases visibility into global threats. Second, a Lightweight Active Responder provides enough interactivity that traffic on the same service can be differentiated independent of application semantics. Third, a Payload Signatures and Caching mechanism avoids recording duplicated payloads, reducing overhead and assisting in identifying new and unique payloads. We explore the architectural tradeoffs of this system in the context of a 3 year deployment across multiple dark address blocks ranging in size from /24s to a /8. These sensors represent a range of organizations and a diverse sample of the routable IPv4 space including nine of all routable /8 address ranges. Data gathered from these deployments is used to demonstrate the ability of the IMS to capture and characterize several important Internet threats: the Blaster worm (August 2003), the Bagle backdoor scanning efforts (March 2004), and the SCO Denial of Service attacks (December 2003).
The ISMIR Cloud: A Decade of ISMIR Conferences at Your Fingertips

In this paper, we analyze the proceedings of the past International Symposia on Music Information Retrieval (ISMIR). We extract meaningful term sets from the accepted submissions and apply term weighting and Web-based filtering techniques to distill information about the topics covered by the papers. This enables us to visualize and interpret the change of hot ISMIR topics in the course of time. Furthermore, the performed analysis allows for assessing the cumulative ISMIR proceedings by semantic content (rather than by literal text search). To illustrate this, we introduce two prototype applications that are publicly accessible online 1 . The first allows the user to search for ISMIR publications by selecting subsets of ISMIR topics. The second provides interactive visual access to the joint content of ISMIR publications in the form of a tag cloud ‐ the ISMIR Cloud.
Endovascular treatment of acute ischemic stroke

Early recanalization of the occluded artery leads to better clinical outcomes in patients with acute ischemic stroke (AIS) through protection of the time-sensitive penumbra. Intravenous administration of pharmacologic thrombolytic agents has been a standard treatment for AIS. To get better rates of recanalization, enhance the time window, and diminish the possibility of intracranial hemorrhage, endovascular thrombectomy was launched, with first authorization of the Merci clot retriever, a corkscrew-like apparatus, followed by approval of the Penumbra thromboaspiration system. Both devices lead to a high rate of recanalization. On the other hand, time to recanalization was on an average of 45 minutes, with most of the patients attaining only partial recanalization. More lately, retrievable stents have shown promise in decreasing the time to recanalization, and attaining a superior rate of complete clot resolution. The retrievable stent can be released within the clot to engage it within the struts of the stent, and afterwards it is taken back by pulling it under flow arrest. Neurointerventional techniques have a persistently ever-increasing and stimulating role in the management of AIS, as indicated by the advent of several important techniques. Stent retrievers have the capability to be ascertained as the most important approach to endovascular stroke treatment.
From Catch the Flag to Shock and Awe: how World of Warcraft Negotiates Battle

Within the MMORPG World of Warcraft, attitudes towards warfare are expressed in conflicting ways. This is partly a result of the difficult relationship modern Western society has with warfare, and the various political agendas that surround this. Within World of Warcraft, this is expressed specifically in the minigames known as 'Battlegrounds', which allow players to fight against each other in teams. The way in which these popular areas have been developed in the game is symptomatic of increasingly accepting attitudes towards warfare. © 2007 Authors & Digital Games Research Association (DiGRA).
Adipose-Derived Stem Cells Seeded on Acellular Dermal Matrix Grafts Enhance Wound Healing in a Murine Model of a Full-Thickness Defect

IntroductionThe promotion of wound healing using dermal substitutes has become increasingly widespread, but the outcomes of substitute-assisted healing remain functionally deficient. Adipose-derived stem cells (ASCs) have been investigated widely in regenerative medicine and tissue engineering, and they have the potential to enhance wound healing. In this study, we focused on investigating the effects and mechanism of ASCs combined with an acellular dermal matrix (ADM) to treat full-thickness cutaneous wounds in a murine model. MethodsThe ADM was prepared from the dorsal skin of nude mice by decellularization by treatment with trypsin followed by Triton X-100. The human ASCs were isolated and cultured from abdominal lipoaspirate. We created a rounded, 8-mm, full-thickness cutaneous wound in nude mice and divided the mice into the following 4 groups: silicon sheet cover only, silicon sheet with spreading ASCs, ADM only, and ASCs seeded on ADM. The granulation thickness was evaluated by histology after 7 days. Further comparisons between the ADM only and ASC-seeded ADM groups were undertaken by assessing the reepithelialization ratio and blood vessel density at postoperative days 9 and 14. Statistical analyses were conducted using Student 2-tailed t test. Immunofluorescent histology and ASC labeling were also performed to identify possible mechanisms. ResultsThe ADM was successfully prepared, and the cytometry analysis and differentiation assay provided the characterization of the human ASCs. A marked improvement in granulation thickness was detected in the ADM-ASC group in comparison with other 3 groups. A significantly increased rate of reepithelialization in the ADM-ASC group (80 ± 6%) compared to the ADM only group (60 ± 7%) was noted on postoperative day 9. The blood vessel density was evidently increased in the ADM-ASC group (7.79 ± 0.40 vessels per field) compared to the ADM only group (5.66 ± 0.23 vessels) on day 14. Cell tracking experiments demonstrated that labeled ASCs were colocalized with staining for VEGF or endothelial cell maker vWF after the transplantation of ADM-ASCs on postoperative day 14. ConclusionsAdipose-derived stem cells seeded on an ADM can enhance wound healing, promote angiogenesis, and contribute to newly formed vasculature, and VEGF-expressing ASCs can be detected after transplantation. This model could be used to improve the other clinical applications of ASCs and to decipher the detailed mechanism by which ASCs interact with wound tissue.
MIC-TJU in MediaEval 2015 Affective Impact of Movies Task

The MediaEval 2015 Affective Impact of Movies task challenged participants to automatically detect video content that depicts violence, or predict the affective impact that video content will have on viewers. In this paper, we describe our system and discuss the performance results obtained in this task. We adopt our recently proposed Trajectory Based Covariance (TBC) descriptor to depict the motion information. Besides that, other features including audio, scene, color and appearance are also utilized in our system. To combine these features, a late fusion strategy is employed. Our results show that the trajectory based motion feature can achieve very competitive performances, furthermore the combination with audio, scene, color and appearance features can improve the overall performance.
A Lexicon-based Investigation of Research Issues in Japanese Factuality Analysis

Event factuality is information about whether events mentioned in natural language correspond to either actual events that have occurred in the real world or events that are of uncertain interpretation. Factuality analysis is useful for information extraction and textual entailment recognition, among others, but sufficient performance has not yet been achieved by the machine learning-based approach. It is now important to take a closer look at the linguistics phenomena involved in factuality analysis and identify the technical research issues more precisely. In this paper, we discuss issues regarding lexical knowledge through error analysis of a Japanese factuality analyzer based on lexical knowledge and compositionality.
Femtosecond x-ray pulses of synchrotron radiation.

A method capable of producing femtosecond pulses of synchrotron radiation is proposed. It is based on the interaction of femtosecond light pulses with electrons in a storage ring. The application of the method to the generation of ultrashort x-ray pulses at the Advanced Light Source of Lawrence Berkeley National Laboratory has been considered. The same method can also be used for extraction of electrons from a storage ring in ultrashort series of microbunches spaced by the periodicity of light wavelength. {copyright} {ital 1996 The American Physical Society. }
A virtual light field approach to global illumination

This paper describes an algorithm that provides real-time walkthrough for globally illuminated scenes that contain mixtures of ideal diffuse and specular surfaces. A type of light field data structure is used for propagating radiance outward from light emitters through the scene, accounting for any kind of L(S\D)* light path. The light field employed is constructed by choosing a regular point subdivision over a hemisphere, to give a set of directions, and then corresponding to each direction there is a rectangular grid of parallel rays. Each rectangular grid of rays is further subdivided into rectangular tiles, such that each tile references a sequence of 2D images containing colour values corresponding to the outgoing radiances of surfaces intersected by the rays in that tile. This structure is then used for final image rendering. Propagation times can be very long and the memory requirements very high. This algorithm, however, offers a global illumination solution for real-time walkthrough even on a single processor
Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow

This paper puts forth a novel algorithm, termed \emph{truncated generalized gradient flow} (TGGF), to solve for $\bm{x}\in\mathbb{R}^n/\mathbb{C}^n$ a system of $m$ quadratic equations $y_i=|\langle\bm{a}_i,\bm{x}\rangle|^2$, $i=1,2,\ldots,m$, which even for $\left\{\bm{a}_i\in\mathbb{R}^n/\mathbb{C}^n\right\}_{i=1}^m$ random is known to be \emph{NP-hard} in general. We prove that as soon as the number of equations $m$ is on the order of the number of unknowns $n$, TGGF recovers the solution exactly (up to a global unimodular constant) with high probability and complexity growing linearly with the time required to read the data $\left\{\left(\bm{a}_i;\,y_i\right)\right\}_{i=1}^m$. Specifically, TGGF proceeds in two stages: s1) A novel \emph{orthogonality-promoting} initialization that is obtained with simple power iterations; and, s2) a refinement of the initial estimate by successive updates of scalable \emph{truncated generalized gradient iterations}. The former is in sharp contrast to the existing spectral initializations, while the latter handles the rather challenging nonconvex and nonsmooth \emph{amplitude-based} cost function. Numerical tests demonstrate that: i) The novel orthogonality-promoting initialization method returns more accurate and robust estimates relative to its spectral counterparts; and ii) even with the same initialization, our refinement/truncation outperforms Wirtinger-based alternatives, all corroborating the superior performance of TGGF over state-of-the-art algorithms.