Miracle-dz/UniFAR-FTUs huggingface dataset:
On the detection of network traffic anomalies in content delivery network services

Today's Internet traffic is largely dominated by major content providers and highly distributed Content Delivery Networks (CDNs). Internet-scale applications like Facebook and YouTube are served by large CDNs like Akamai and Google CDN, which push content as close to end-users as possible to improve the overall performance of the applications, minimize the effects of peering point congestion and enhance the user experience. The load is balanced among multiple servers or caches according to non-disclosed CDN internal policies. As such, adopting space and time variant policies, users' requests are served from different physical locations at different time. Cache selection and load balancing policies can have a relevant impact on the traffic routed by the underlying transport network, as well as on the end-user experience. In this paper, we analyze the provisioning of two major Internet applications, namely Facebook and YouTube, in two datasets collected at major European Internet Service Providers (ISPs). First, we show how the cache selection performed by Akamai might result in higher transport costs for the ISP. Second, we present evidence on large-scale outages occurring in the Facebook traffic distribution. Finally, we characterize the variation of YouTube cache selection strategies and their impact on the users' quality of experience. We argue that it is important for the ISP to rapidly and automatically detect such events. Therefore, we present an Anomaly Detection (AD) system for detecting unexpected cache-selection events and changes in the traffic delivered by CDNs. The proposed algorithm improves over traditional AD approaches by analyzing the complete probability distribution of the monitored features, providing higher visibility and better detection capabilities.
Blueberry juice: preliminary evaluation as an oral contrast agent in gastrointestinal MR imaging.

PURPOSE To evaluate the use of blueberry juice as an oral contrast agent in magnetic resonance (MR) imaging. MATERIALS AND METHODS MR imaging of phantoms of blueberry juice and of manganese chloride solutions with different manganese concentrations were conducted. Patient trials were conducted to evaluate manganese blood levels and signal intensity changes on MR images of the abdomen. T1- and T2-weighted conventional spin-echo MR imaging was performed at various field strengths. Six radiologists graded image contrast; signal intensities were calculated. RESULTS T1 and T2 relaxation curves for blueberry juice and manganese chloride showed similar signal intensity profiles as a function of manganese concentration. Blood concentrations of manganese were unchanged before and after an oral dose of blueberry juice that contained 18 mg of manganese. The results of patient studies indicated that the optimal oral dose of manganese in blueberry juice was 3-4 mg/dL. T1 and T2 shortening were apparent at field strengths of 0.2-1.5 T. CONCLUSION At appropriate concentrations, blueberry juice has the potential to be an effective oral contrast agent for MR imaging.
Depth estimation for hand-held light field cameras under low light conditions

Depth estimation is one of the new functions provided by hand-held light field cameras. However, the quality of depth estimation is very sensitive to noise, which is especially a problem for scenes under low light conditions. In this paper, we propose a depth estimation flow for light field data, which can be fully-automated and no noise characteristics are required a priori. The results of Root Mean Square Error (RMSE) and Percentage of Bad Matching Pixels (PBM) show the effectiveness of this iterative correlation-based depth estimation flow even with basic filtering functions.
A Comparison of Elastic Tubing and Isotonic Resistance Exercises

The aim of this study was to assess effects of a short-term resistance program on strength in fit young women using weight machines/free weights or elastic tubing. 42 physically fit women (21.79±0.7 years) were randomly assigned to the following groups: (i) the Thera-Band (®) Exercise Station Group (TBG); (ii) the weight machines/free weights group (MFWG); or (iii) the control group (CG). Each experimental group performed the same periodised training program that lasted for 8 weeks, with 2-4 sessions per week and 3-4 sets of 8-15 submaximal reps. A load cell (Isocontrol; ATEmicro, Madrid, Spain) was used to test the evolution of the Maximum Isometric Voluntary Contraction (MIVC) in 3 different exercises: Vertical Rowing (VR), Squat (S) and Back Extension (BE). A mixed model MANOVA [group (CG, TBG, MFWG) x testing time (pre-test, post-test)] was applied to determine the effect of the different resistance training devices on strength. The only groups to improve their MIVC (p<0.005) were TBG and MFWG, respectively: VR 19.87% and 19.76%; S 14.07 and 28.88; BE 14.41% and 14.00%. These results indicate that resistance training using elastic tubing or weight machines/free weights have equivalent improvements in isometric force in short-term programs applied in fit young women.
Genome of Emerging Norovirus GII.17, United States, 2014

To determine whether the norovirus strain GII.17 recently detected in Maryland, USA, (Hu/GII.17/Gaithersburg/2014/US) is spreading globally, we characterized the genome. High similarity with the norovirus GII.17 that caused recent outbreaks in Asia indicates that the same strain was present in the United States during the 2014–15 norovirus season (winter).
A useful feature-engineering approach for a LVCSR system based on CD-DNN-HMM algorithm

In this paper, we propose a useful feature-engineering approach for Context-Dependent Deep-Neural-Network Hidden-Markov-Model (CD-DNN-HMM) based Large-Vocabulary-Continuous-Speech-Recognition (LVCSR) systems. The speech recognition performance of a LVCSR system is improved from two feature-engineering perspectives. The first performance improvement is achieved by adopting the intra/inter-frame feature subsets when the Gaussian-Mixture-Model (GMM) HMMs for the HMM state-level alignment are built. And the second performance gain is then followed with the additional features augmenting the front-end of the DNN. We evaluate the effectiveness of our feature-engineering approach under a series of Korean speech recognition tasks (isolated single-syllable recognition with a medium-sized speech corpus and conversational speech recognition with a large-sized database) using the Kaldi speech recognition toolkit. The results show that the proposed feature-engineering approach outperforms the traditional Mel Frequency Cepstral Coefficient (MFCCs) GMM + Mel-frequency filter-bank output DNN method.
Iterative learning control for nonlinear systems with input constraints and discontinuously changing dynamics

This paper discusses the implementation and application of an iterative learning control (ILC) algorithm for nonlinear systems with input constraints and discontinuously changing dynamics. The ILC approach consists of two steps: in the first step the nominal model of the plant is corrected based on the previous iteration's output, and in the second step the corrected model is inverted to track the reference. Both steps are formulated as nonlinear least squares problems with a sparse, banded structure, and solved using an efficient implementation of an interior point method called IPOPT. Due to this implementation high order systems and long data sets can be efficiently processed. The considered application is a trajectory tracking problem of a one degree-of-freedom robot arm carrying an object that is suddenly released during motion. Both the case where the exact time instant of release is known and unknown are considered.
Examining the safety of amiodarone

Introduction: Amiodarone is the most widely used antiarrhythmic agent, with demonstrated effectiveness against all the spectrum of cardiac tachyarrhythmias. The risk of adverse effects acts as a limiting factor to its utilization especially in the long term. This article systematically reviews the published evidence on amiodarone versus placebo to examine its safety as an antiarrhythmic drug. Areas covered: Authors collected data on adverse effects reported in 49 randomized placebo-controlled trials with amiodarone. Adverse effects were classified according to the organ/system involved. Pooled estimates of the number needed to treat (NNT) and to harm (NNH) versus placebo were calculated. Expert opinion: Amiodarone is effective for both the acute conversion of atrial fibrillation (AF) (11 trials, NNT = 4 at 24 h; p = 0.003) and the prevention of postoperative AF (18 trials, NNT = 8; p < 0.001), although with an increased risk of bradycardia, hypotension, nausea or phlebitis (pooled NNH = 4; p < 0.001). Amiodarone administration for the maintenance of sinus rhythm has a favorable net clinical benefit (pooled NNT = 3; p < 0.001 versus pooled NNH for either thyroid toxicity, gastrointestinal discomfort, skin toxicity or eye toxicity = 11; p < 0.001). Treatment with amiodarone for the prophylaxis of sudden cardiac death has less favorable net clinical benefit (15 trials, NNT = 38; p < 0.001 versus NNH for either thyroid toxicity, hepatic toxicity, pulmonary toxicity or bradycardia = 14; p < 0.001). Amiodarone treatment in this setting should be used in only selected cases.
Functional validation of GWAS gene candidates for abnormal liver function during zebrafish liver development

SUMMARY Genome-wide association studies (GWAS) have revealed numerous associations between many phenotypes and gene candidates. Frequently, however, further elucidation of gene function has not been achieved. A recent GWAS identified 69 candidate genes associated with elevated liver enzyme concentrations, which are clinical markers of liver disease. To investigate the role of these genes in liver homeostasis, we narrowed down this list to 12 genes based on zebrafish orthology, zebrafish liver expression and disease correlation. To assess the function of gene candidates during liver development, we assayed hepatic progenitors at 48 hours post fertilization (hpf) and hepatocytes at 72 hpf using in situ hybridization following morpholino knockdown in zebrafish embryos. Knockdown of three genes (pnpla3, pklr and mapk10) decreased expression of hepatic progenitor cells, whereas knockdown of eight genes (pnpla3, cpn1, trib1, fads2, slc2a2, pklr, mapk10 and samm50) decreased cell-specific hepatocyte expression. We then induced liver injury in zebrafish embryos using acetaminophen exposure and observed changes in liver toxicity incidence in morphants. Prioritization of GWAS candidates and morpholino knockdown expedites the study of newly identified genes impacting liver development and represents a feasible method for initial assessment of candidate genes to instruct further mechanistic analyses. Our analysis can be extended to GWAS for additional disease-associated phenotypes.
On Stopwords, Filtering and Data Sparsity for Sentiment Analysis of Twitter

Sentiment classification over Twitter is usually affected by the noisy nature (abbreviations, irregular forms) of tweets data. A popular procedure to reduce the noise of textual data is to remove stopwords by using pre-compiled stopword lists or more sophisticated methods for dynamic stopword identification. However, the effectiveness of removing stopwords in the context of Twitter sentiment classification has been debated in the last few years. In this paper we investigate whether removing stopwords helps or hampers the effectiveness of Twitter sentiment classification methods. To this end, we apply six different stopword identification methods to Twitter data from six different datasets and observe how removing stopwords affects two well-known supervised sentiment classification methods. We assess the impact of removing stopwords by observing fluctuations on the level of data sparsity, the size of the classifier’s feature space and its classification performance. Our results show that using pre-compiled lists of stopwords negatively impacts the performance of Twitter sentiment classification approaches. On the other hand, the dynamic generation of stopword lists, by removing those infrequent terms appearing only once in the corpus, appears to be the optimal method to maintaining a high classification performance while reducing the data sparsity and shrinking the feature space.
Cholesterol Biosynthesis Supports Myelin Gene Expression and Axon Ensheathment through Modulation of P13K/Akt/mTor Signaling

Myelin, which ensheaths and insulates axons, is a specialized membrane highly enriched with cholesterol. During myelin formation, cholesterol influences membrane fluidity, associates with myelin proteins such as myelin proteolipid protein, and assembles lipid-rich microdomains within membranes. Surprisingly, cholesterol also is required by oligodendrocytes, glial cells that make myelin, to express myelin genes and wrap axons. How cholesterol mediates these distinct features of oligodendrocyte development is not known. One possibility is that cholesterol promotes myelination by facilitating signal transduction within the cell, because lipid-rich microdomains function as assembly points for signaling molecules. Signaling cascades that localize to cholesterol-rich regions of the plasma membrane include the PI3K/Akt pathway, which acts upstream of mechanistic target of rapamycin (mTOR), a major driver of myelination. Through manipulation of cholesterol levels and PI3K/Akt/mTOR signaling in zebrafish, we discovered that mTOR kinase activity in oligodendrocytes requires cholesterol. Drawing on a combination of pharmacological and rescue experiments, we provide evidence that mTOR kinase activity is required for cholesterol-mediated myelin gene expression. On the other hand, cholesterol-dependent axon ensheathment is mediated by Akt signaling, independent of mTOR kinase activity. Our data reveal that cholesterol-dependent myelin gene expression and axon ensheathment are facilitated by distinct signaling cascades downstream of Akt. Because mTOR promotes cholesterol synthesis, our data raise the possibility that cholesterol synthesis and mTOR signaling engage in positive feedback to promote the formation of myelin membrane. SIGNIFICANCE STATEMENT The speed of electrical impulse movement through axons is increased by myelin, a specialized, cholesterol-rich glial cell membrane that tightly wraps axons. During development, myelin membrane grows dramatically, suggesting a significant demand on mechanisms that produce and assemble myelin components, while it spirally wraps axons. Our studies indicate that cholesterol is necessary for both myelin growth and axon wrapping. Specifically, we found that cholesterol facilitates signaling mediated by the PI3K/Akt/mTOR pathway, a powerful driver of myelination. Because mTOR promotes the expression of genes necessary for cholesterol synthesis, cholesterol formation and PI3K/Akt/mTOR signaling might function as a feedforward mechanism to produce the large amounts of myelin membrane necessary for axon ensheathment.
A Hamster-Derived West Nile Virus Isolate Induces Persistent Renal Infection in Mice

Background West Nile virus (WNV) can persist long term in the brain and kidney tissues of humans, non-human primates, and hamsters. In this study, mice were infected with WNV strain H8912, previously cultured from the urine of a persistently infected hamster, to determine its pathogenesis in a murine host. Methodology/Principal Findings We found that WNV H8912 was highly attenuated for neuroinvasiveness in mice. Following a systemic infection, viral RNA could be detected quickly in blood and spleen and much later in kidneys. WNV H8912 induced constitutive IL-10 production, upregulation of IFN-β and IL-1β expression, and a specific IgM response on day 10 post-infection. WNV H8912 persisted preferentially in kidneys with mild renal inflammation, and less frequently in spleen for up to 2.5 months post infection. This was concurrent with detectable serum WNV-specific IgM and IgG production. There were also significantly fewer WNV- specific T cells and lower inflammatory responses in kidneys than in spleen. Previous studies have shown that systemic wild-type WNV NY99 infection induced virus persistence preferentially in spleen than in mouse kidneys. Here, we noted that splenocytes of WNV H8912-infected mice produced significantly less IL-10 than those of WNV NY99-infected mice. Finally, WNV H8912 was also attenuated in neurovirulence. Following intracranial inoculation, WNV persisted in the brain at a low frequency, concurrent with neither inflammatory responses nor neuronal damage in the brain. Conclusions WNV H8912 is highly attenuated in both neuroinvasiveness and neurovirulence in mice. It induces a low and delayed anti-viral response in mice and preferentially persists in the kidneys.
ClusPro: an automated docking and discrimination method for the prediction of protein complexes

MOTIVATION Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. RESULTS We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. AVAILABILITY The fully automated docking and discrimination server ClusPro can be found at http://structure.bu. edu
Feedback in Conversation as Incremental Semantic Update

In conversation, interlocutors routinely indicate whether something said or done has been processed and integrated. Such feedback includes backchannels such as ‘okay’ or ‘mhm’, the production of a next relevant turn, and repair initiation via clarification requests. Importantly, such feedback can be produced not only at sentence/turn boundaries, but also sub-sententially. In this paper, we extend an existing model of incremental semantic processing in dialogue, based around the Dynamic Syntax (DS) grammar framework, to provide a low-level, integrated account of backchannels, clarification requests and their responses; demonstrating that they can be accounted for as part of the core semantic structure-building mechanisms of the grammar, rather than via higher level pragmatic phenomena such as intention recognition, or treatment as an “uno cial” part of the conversation. The end result is an incremental model in which words, not turns, are seen as procedures for contextual update and backchannels serve to align participant semantic processing contexts and thus ease the production and interpretation of subsequent conversational actions. We also show how clarification requests and their following responses and repair can be modelled within the same DS framework, wherein the divergence and re-alignment e ort in participants’ semantic processing drives conversations forward.
Crystal plasticity theory during the 1950s and 1960s

In the field of crystal plasticity, the two decades 1950–1969 were a time of great activity, in which the foundations were laid for our present understanding of the work-hardening of face-centred cubic metals in terms of dislocation mechanisms. Decisive developments were the ‘invention’ of the Frank–Read source, the recognition of the importance of the specific energy of stacking faults, and the (at least partial) resolution of the controversy between macroscopic stress–strain measurements, X-ray results, ferromagnetism and the study of slip lines and slip bands on the one hand, and the observation of dislocations by transmission electron microscopy of thin foils prepared from plastically deformed macroscopic specimens on the other hand. The understanding of the dislocation mechanisms dominant at very large plastic strains was and still is limited, however. It is argued that here a holistic approach based on concepts such as energy dissipation and self-organization is more promising than the mechanistic approach based on concepts successfully developed in the two decades covered in the paper.
NAD+-Dependent 15-Hydroxyprostaglandin Dehydrogenase Regulates Levels of Bioactive Lipids in Non–Small Cell Lung Cancer

Elevated levels of procarcinogenic prostaglandins (PG) are found in a variety of human malignancies including non–small cell lung cancer (NSCLC). Overexpression of cyclooxygenase-2 and microsomal prostaglandin synthase 1 occurs in tumors and contributes to increased PG synthesis. NAD+-dependent 15-hydroxyprostaglandin dehydrogenase (15-PGDH), the key enzyme responsible for metabolic inactivation of PGs, is down-regulated in various malignancies. The main objective of this study was to elucidate the effect of loss of 15-PGDH on levels of bioactive lipids in NSCLC. We found that levels of cyclooxygenase-2 and microsomal prostaglandin synthase 1 were commonly increased whereas the amount of 15-PGDH was frequently decreased in NSCLC compared with adjacent normal lung. Reduced expression of 15-PGDH occurred in tumor cells and was paralleled by decreased 15-PGDH activity in tumors. Amounts of PGE1, PGE2, and PGF2α, known substrates of 15-PGDH, were markedly increased whereas levels of 13,14-dihydro-15-keto-PGE2, a catabolic product of PGE2, were markedly reduced in NSCLC compared with normal lung. Complementary in vitro and in vivo experiments were done to determine whether these changes in PG levels were a consequence of down-regulation of 15-PGDH in NSCLC. Similar to NSCLC, amounts of PGE1, PGE2, and PGF2α were markedly increased whereas levels of 13,14-dihydro-15-keto-PGE2 were decreased in the lungs of 15-PGDH knockout mice compared with wild-type mice or when 15-PGDH was silenced in A549 lung cancer cells. Collectively, these data indicate that 15-PGDH is commonly down-regulated in NSCLC, an effect that contributes to the accumulation of multiple bioactive lipids in NSCLC.
Non-negative Matrix Factorization based on γ-divergence

Non-negative Matrix Factorization (NMF) is a method of multivariate analysis which factorizes a non-negative matrix into two non-negative matrices. While conventional NMF algorithms use the Euclidian distance or the Kullback-Leibler divergence as cost functions, those methods fail to extract latent structure or interpretable information from the matrix when the target matrix is contaminated by noise. In this paper, we propose novel NMF algorithms based on the γ-divergence which is known to be robust, and investigate robustness of proposed methods with numerical experiments.
On the Feasibility of Completely Wirelesss Datacenters

Conventional datacenters, based on wired networks, entail high wiring costs, suffer from performance bottlenecks, and have low resilience to network failures. In this paper, we investigate a radically new methodology for building wire-free datacenters based on emerging 60-GHz radio frequency (RF) technology. We propose a novel rack design and a resulting network topology inspired by Cayley graphs that provide a dense interconnect. Our exploration of the resulting design space shows that wireless datacenters built with this methodology can potentially attain higher aggregate bandwidth, lower latency, and substantially higher fault tolerance than a conventional wired datacenter while improving ease of construction and maintenance.