Miracle-dz/UniFAR-FTUs huggingface dataset:
Enabling green content distribution network by cloud orchestration

Cloud providers seek to maximize their market share. Traditionally, they deploy datacenters with sufficient capacity to accommodate their entire compute demand while maintaining geographical affinity to its customers. Achieving these goals by a single cloud provider is increasingly unrealistic from a cost of ownership perspective. Moreover, the carbon emissions from underutilized datacenters place an increasing demand on electricity, and is an increasing factor in the cost of cloud provider datacenters. However, the recognition that on-demand video streaming now constitutes the bulk portion of traffic to Internet consumers provides a path to mitigate rising energy demand. On-demand video is usually served through Content Delivery Networks (CDN), often scheduled in backend and edge datacenters. This publication describes a CDN deployment solution that utilizes green energy to supply on-demand streaming workload. A cross-cloud provider collaboration will allow cloud providers to both operate near their customers and reduce operational costs, primarily by lowering the datacenter deployments per provider ratio. Our approach optimizes cross-datacenters deployment. Specifically, we model an optimized CDN-edge instance allocation system that maximizes, under a set of realistic constraints, green energy utilization. The architecture of this cross-cloud coordinator service is based on Ubernetes, an open source container cluster manager that is a federation of Kubernetes clusters. It is shown how, under reasonable constraints, it can reduce the projected datacenters carbon emissions growth by 22% from the currently reported consumption.
Next-Generation Sequencing for Rodent Barcoding: Species Identification from Fresh, Degraded and Environmental Samples

Rodentia is the most diverse order among mammals, with more than 2,000 species currently described. Most of the time, species assignation is so difficult based on morphological data solely that identifying rodents at the specific level corresponds to a real challenge. In this study, we compared the applicability of 100 bp mini-barcodes from cytochrome b and cytochrome c oxidase 1 genes to enable rodent species identification. Based on GenBank sequence datasets of 115 rodent species, a 136 bp fragment of cytochrome b was selected as the most discriminatory mini-barcode, and rodent universal primers surrounding this fragment were designed. The efficacy of this new molecular tool was assessed on 946 samples including rodent tissues, feces, museum samples and feces/pellets from predators known to ingest rodents. Utilizing next-generation sequencing technologies able to sequence mixes of DNA, 1,140 amplicons were tagged, multiplexed and sequenced together in one single 454 GS-FLX run. Our method was initially validated on a reference sample set including 265 clearly identified rodent tissues, corresponding to 103 different species. Following validation, 85.6% of 555 rodent samples from Europe, Asia and Africa whose species identity was unknown were able to be identified using the BLASTN program and GenBank reference sequences. In addition, our method proved effective even on degraded rodent DNA samples: 91.8% and 75.9% of samples from feces and museum specimens respectively were correctly identified. Finally, we succeeded in determining the diet of 66.7% of the investigated carnivores from their feces and 81.8% of owls from their pellets. Non-rodent species were also identified, suggesting that our method is sensitive enough to investigate complete predator diets. This study demonstrates how this molecular identification method combined with high-throughput sequencing can open new realms of possibilities in achieving fast, accurate and inexpensive species identification.
Temperature, Viral Genetics, and the Transmission of West Nile Virus by Culex pipiens Mosquitoes

The distribution and intensity of transmission of vector-borne pathogens can be strongly influenced by the competence of vectors. Vector competence, in turn, can be influenced by temperature and viral genetics. West Nile virus (WNV) was introduced into the United States of America in 1999 and subsequently spread throughout much of the Americas. Previously, we have shown that a novel genotype of WNV, WN02, first detected in 2001, spread across the US and was more efficient than the introduced genotype, NY99, at infecting, disseminating, and being transmitted by Culex mosquitoes. In the current study, we determined the relationship between temperature and time since feeding on the probability of transmitting each genotype of WNV. We found that the advantage of the WN02 genotype increases with the product of time and temperature. Thus, warmer temperatures would have facilitated the invasion of the WN02 genotype. In addition, we found that transmission of WNV accelerated sharply with increasing temperature, T, (best fit by a function of T4) showing that traditional degree-day models underestimate the impact of temperature on WNV transmission. This laboratory study suggests that both viral evolution and temperature help shape the distribution and intensity of transmission of WNV, and provides a model for predicting the impact of temperature and global warming on WNV transmission.
SPEED-RANGE DILEMMAS FOR VISION-BASED NAVIGATION IN UNSTRUCTURED TERRAIN

Abstract The performance of vision-based navigation systems for off-road mobile robots depends crucially on the resolution of the camera, the sophistication of the visual processing, the latency between image and sensor capture to actuator control, and the period of the control loop. One particularly important design question is whether one should increase the resolution of the camera images, and the range of the obstacle detection algorithms, at the expense of latency and control loop period. We first report experimental results on the resolution-period trade-off with a stereo vision-based navigation system implemented on the LAGR mobile robot platform. We propose a multi-agent perception and control architecture that combines a sophisticated long-range path detection method operating at high resolution and low frame rate, with a simple stereo-based obstacle detection method operating at low resolution, high frame rate, and low latency. The system combines the advantages of the long-range module for strategic path planning, with the advantages of the short-range module for tactical driving.
Introduction: Metric Culture and the Over-examined Life

Abstract Metrics, data, algorithms and numbers play an unmistakably powerful role in today’s society. Over the years, their use and function have expanded to cover almost every sphere of everyday life so much so that it can be argued that we are now living in a ‘metric culture’, a term indicating at once the growing cultural interest in numbers and a culture that is increasingly shaped by numbers, as Beer (2016) also argues. At the same time, metric culture is not only about numbers and numbers alone, but also links to issues of power and control, to questions of value and agency and to expressions of self and identity. Self-tracking practices are indeed a manifestation of this metric culture and a testimony to how measurement, quantification, documentation and datafication have all become important tropes for managing life and the living in contemporary society. In this introductory chapter, I provide a general contextualisation of the topic of this edited collection along with an overview of the different chapters and their key arguments.
Analysis of genomic sequences of 95 papillomavirus types: uniting typing, phylogeny, and taxonomy

Our aim was to study the phylogenetic relationships of all known papillomaviruses (PVs) and the possibility of establishing a supratype taxonomic classification based on this information. Of the many detectably homologous segments present in PV genomes, a 291-bp segment of the L1 gene is notable because it is flanked by the MY09 and MY11 consensus primers and contains highly conserved amino acid residues which simplify sequence alignment. We determined the MY09-MY11 sequences of human PV type 20 (HPV-20), HPV-21, HPV-22, HPV-23, HPV-24, HPV-36, HPV-37, HPV-38, HPV-48, HPV-50, HPV-60, HPV-70, HPV-72, HPV-73, ovine (sheep) PV, bovine PV type 3 (BPV-3), BPV-5, and BPV-6 and created a database which now encompasses HPV-1 to HPV-70, HPV-72, HPV-73, seven yet untyped HPV genomes, and 15 animal PV types. Three additional animal PVs were analyzed on the basis of other sequence data. We constructed phylogenies based on partial L1 and E6 gene sequences and distinguished five major clades that we call supergroups. One of them unites 54 genital PV types, which can be further divided into eleven groups. The second supergroup has 24 types and unites most PVs that are typically found in epidermodysplasia verruciformis patients but also includes several types typical of other cutaneous lesions, like HPV-4. The third supergroup unites the six known ungulate fibropapillomaviruses, the fourth includes the cutaneous ungulate PVs BPV-3, BPV-4, and BPV-6, and the fifth includes HPV-1, HPV-41, HPV-63, the canine oral PV, and the cottontail rabbit PV. The chaffinch PV and two rodent PVs, Micromys minutus PV and Mastomys natalensis PV, are left ungrouped because of the relative isolation of each of their lineages. Within most supergroups, groups formed on the basis of cladistic principles unite phenotypically similar PV types. We discuss the basis of our classification, the concept of the PV type, speciation, PV-host evolution, and estimates of their rates of evolution.
Automatic Music Transcription: Breaking the Glass Ceiling

Automatic music transcription is considered by many to be the Holy Grail in the field of music signal analysis. However, the performance of transcription systems is still significantly below that of a human expert, and accuracies reported in recent years seem to have reached a limit, although the field is still very active. In this paper we analyse limitations of current methods and identify promising directions for future research. Current transcription methods use general purpose models which are unable to capture the rich diversity found in music signals. In order to overcome the limited performance of transcription systems, algorithms have to be tailored to specific use-cases. Semi-automatic approaches are another way of achieving a more reliable transcription. Also, the wealth of musical scores and corresponding audio data now available are a rich potential source of training data, via forced alignment of audio to scores, but large scale utilisation of such data has yet to be attempted. Other promising approaches include the integration of information across different methods and musical aspects.
Adaptation of precision matrix models on large vocabulary continuous speech recognition

Recently, structured precision matrix models were found to outperform the conventional diagonal covariance matrix models. Minimum phone error discriminative training of these models gave very good unadapted performance on large vocabulary continuous speech recognition systems. To obtain state-of-the-art performance, it is important to apply adaptation techniques efficiently to these models. In this paper, simple row-by-row iterative formulae are described for both MLLR mean and constrained MLLR transform estimations of these models. These update formulae are derived within the standard expectation maximisation framework and are guaranteed to increase the likelihood of the adaptation data. Efficient approximate schemes for these adaptation methods are also investigated to further reduce the computation. Experimental results are presented based on the MPE trained subspace for precision and mean models, evaluated on both broadcast news and conversational telephone speech English tasks.
Community respiratory virus infections in patients with hematologic malignancies.

BACKGROUND AND OBJECTIVE The main difficulty of PCR-based clonality studies for B-cell lymphoproliferative disorders (B-LPD) is discrimination between monoclonal and polyclonal PCR products, especially when there is a high background of polyclonal B cells in the tumor sample. Actually, PCR-based methods for clonality assessment require additional analysis of the PCR products in order to discern between monoclonal and polyclonal samples. Heteroduplex analysis represents an attractive approach since it is easy to perform and avoids the use of radioactive substrates or expensive equipment. DESIGN AND METHODS We studied the sensitivity and specificity of heteroduplex PCR analysis for monoclonal detection in samples from 90 B-cell non Hodgkin's lymphoma (B-NHL) patients and in 28 individuals without neoplastic B-cell disorders (negative controls). Furthermore, in 42 B-NHL and in the same 28 negative controls, we compared heteroduplex analysis vs the classical PCR technique. We also compared ethidium bromide (EtBr) vs. silver nitrate (AgNO(3)) staining as well as agarose vs. polyacrylamide gel electrophoresis (PAGE). RESULTS Using two pair consensus primers sited at VH (FR3 and FR2) and at JH, 91% of B-NHL samples displayed monoclonal products after heteroduplex PCR analysis using PAGE and AgNO(3) staining. Moreover, no polyclonal sample showed a monoclonal PCR product. By contrast, false positive results were obtained when using agarose (5/28) and PAGE without heteroduplex analysis: 2/28 and 8/28 with EtBr and AgNO(3) staining, respectively. In addition, false negative results only appeared with EtBr staining: 13/42 in agarose, 4/42 in PAGE without heteroduplex analysis and 7/42 in PAGE after heteroduplex analysis. INTERPRETATION AND CONCLUSIONS We conclude that AgNO(3) stained PAGE after heteroduplex analysis is the most suitable strategy for detecting monoclonal rearrangements in B-NHL samples because it does not produce false-positive results and the risk of false-negative results is very low.
Personal hygiene among visually challenged adolescent girls at selected blind schools, Coimbatore

A study was conducted to find out the effect of audio drama to promote personal hygiene among visually challenged adolescent girls in selected Blind schools, Coimbatore. The research design adopted for this study was Quasiexperimental one group pre-test post test design. Purposive sample of 21 samples were selected for this study. Initially, the knowledge and practice of personal hygiene of the visually challenged adolescent girls was assessed using an interview schedule and checklist respectively. Audio drama on techniques and importance of hygienic practices was played 20 minutes daily once for a period of 26 days. Post test was done using the same tool. Appropriate statistical techniques were used to test the hypotheses. The finding reveals that there was a significant improvement in knowledge and practice of personal hygiene. Thus, audio drama promotes knowledge and practice of personal hygiene among visually challenged adolescent girls.
Should nephrologists use beta-blockers? A perspective.

Given the high prevalence of cardiovascular disease in people with chronic kidney disease (CKD) and the clear benefits of mortality reduction observed for most β−blockers in clinical trials, they are relatively underused in CKD patients [1,2]. The rationale for use of β-blockers in patients with CKD is reviewed in detail elsewhere [2,3] but is summarized in this editorial. Alterations in β- and α-receptor responsiveness are associated with sympathetic over-activity in CKD. This increased sympathetic activity is involved in the genesis of hypertension, and contributes to cardiac complications seen in CKD [2,3]. The contribution of the sympathetic nervous system to nephropathy progression is documented in sub-totally nephrectomized rats where non-hypotensive doses of β-blockers ameliorate development of glomerulosclerosis and cardiac injury [4]. In men, sympathetic over-activity, as assessed by sural nerve microneurography, was present in patients on haemodialysis [5], stage 4 nephropathy [6] and in early stage 2 nephropathy among patients with polycystic kidney disease [7]. The role of the damaged kidney in causing sympathetic over-activity is illustrated by normalization of sympathetic over-activity in haemodialysis patients following bilateral nephrectomy [5] and in renal allograft recipients when their shrunken native kidneys are removed [8]. The most common cause of death in stage 3 and higher CKD results from complications of cardiovascular disease. This may be due, in part, to inadequate treatment of blood pressure, where blood pressure goals were not attained and agents known to reduce mortality secondary to cardiovascular causes, i.e. aspirin, ACE inhibitors and β-blockers were not used [9]. In a separate study, β-blockers were used in fewer than 30% of haemodialysis patients [10]. This is surprising, since β-blockers are well-established, evidence-based therapy for reducing cardiovascular risk in hypertension associated with diabetes and after myocardial infarction [11,12]. Observational studies support definite survival benefits derived from β-blocker use in patients with advanced CKD [13,14]. Furthermore, a prospective,
Bayesian hierarchical modeling of simply connected 2D shapes

Models for distributions of shapes contained within images can be widely used in biomedical applications ranging from tumor tracking for targeted radiation therapy to classifying cells in a blood sample. Our focus is on hierarchical probability models for the shape and size of simply connected 2D closed curves, avoiding the need to specify landmarks through modeling the entire curve while borrowing information across curves for related objects. Prevalent approaches follow a fundamentally dierent strategy in providing an initial
Research on integration of port cluster in Pearl River Delta

Ports in Pearl River Delta have a very dense distribution, overlapped economic hinterland and fierce competition, so the efficiency of port resources is low. By analyzing the status of development of each port, it's necessary and feasible to carry out the integration strategy among Pearl River Delta ports. The core of the integration is the integration of the operations management, including the establishment of the integration cooperating agency, the differentiation port positioning and the unified management system, etc. The support of the integration is the integration of public infrastructure, which mainly includes the unified planning, anchorage ground, shorelines, transportation, etc. At last, the paper proposes the safeguards of the integration from four respects: policy, technology, capital and talents. Unlike the traditional approach, this paper makes integration plan of port cluster in Pearl River Delta from the view of port operations management.
Information extraction procedure to support the constitution of Virtual Organizations

Within the framework of co-operating firms in virtual organizations (VO), starting with their Web sites an automatic control approach for business sectors and the savoir faire of the enterprises involved is proposed. Information extraction mechanisms as well as how to identify activities mainly via the treatment of code NAF (Nomenclature of the French Activities) are presented. Moreover promising test results will be illustrated and discussed.
INLO-PUB-05 / 02 Multi-Caloron solutions

We discuss the construction of multi-caloron solutions with non-trivial holonomy, both as approximate superpositions and exact self-dual solutions. The charge k SU(n) moduli space can be described by kn constituent monopoles. Exact solutions help us to understand how these constituents can be seen as independent objects, which seems not possible with the approximate superposition. An “impurity scattering” calculation provides relatively simple expressions. Like at zero temperature an explicit parametrization requires solving a quadratic ADHM constraint, achieved here for a class of axially symmetric solutions. We will discuss the properties of these exact solutions in detail, but also demonstrate that interesting results can be obtained without explicitly solving for the constraint.
Follow the mob: An innovative approach for roaming characters in MMO games

In modern Massively Multiplayer Online Games, Non Playing Characters (NPCs) moving on the battlefield play a key role in term of user experience: many time players are required - alone or in groups - to fight or avoid them in order to progress in experience. Unfortunately, standard NPCs behavior, i.e., patrolling between rally points, does not put a significant challenge to players once its deterministic movement pattern is discovered. This paper addresses the problem of defining a smart, more challenging, and natural movement model for NPCs.
CHARACTERISTIC VARIETIES OF ARRANGEMENTSDANIEL

The k th Fitting ideal of the Alexander invariant B of an arrangement A of n complex hyperplanes deenes a characteristic subvariety, V k (A), of the algebraic torus (C) n. In the combinatorially determined case where B decomposes as a direct sum of local Alexander invariants, we obtain a complete description of V k (A). For any arrangement A, we show that the tangent cone at the identity of this variety coincides with R 1 k (A), one of the cohomol-ogy support loci of the Orlik-Solomon algebra. Using work of Arapura 1], we conclude that all irreducible components of V k (A) which pass through the identity element of (C) n are combinatorially determined, and that R 1 k (A) is the union of a subspace arrangement in C n , thereby resolving a conjecture of Falk 11]. We use these results to study the reeection arrangements associated to monomial groups.
Wideband DOA estimation by joint sparse representation under Bayesian learning framework

Wideband direction of arrival (DOA) estimation is a practical problem frequently occurring in sonar application. Compared to the entire angular domain, targets only occupy a few directions and the received signals are considered to be sparse in the angular domain. It is further noted that signals in different spectrum bands show a strong joint sparsity due to the fact that targets from different directions share the spectrum. This paper exploits the joint sparsity of the signals and reformulates the DOA estimation problem under the Bayesian learning framework. The resulted method is a data-driven learning process and does not need the tedious parameter tuning. Comparing to the conventional delay-sum beamformer, the proposed method has the advantages of reduced number of sensors, reduced spatial aliasing and increased resolution. The improved performance is validated by real sonar data experiments.
Volatility, Correlation and Tails for Systemic Risk Measurement

This paper proposes an empirical methodology to measure systemic risk. We associate the systemic risk of a financial institution with its contribution to the deterioration of the system capitalization that would be experienced in a crisis. In order to measure this empirically we introduce the SRISK index, the expected capital shortage of a firm conditional on a substantial market decline. The index is a function of the degree of Leverage, Size and Marginal Expected Shortfall (MES) of a firm. MES is the expected loss an equity investor in a financial firm would experience if the market declined substantially. To estimate MES, we introduce a dynamic model for the market and firm returns. The specification is characterized by time varying volatility and correlation as well a nonlinear tail dependence. The empirical application to a set of top U.S. financial firms between 2000 and 2010 is used to illustrate the usefulness of the methodology. Results show that SRISK provides useful ranking of systemically risky firms at various stages of the financial crisis: one year and a half before the Lehman bankruptcy, nine companies out of the SRISK top ten turned out to be troubled institutions. The aggregate SRISK of the financial system provides early warning signals of distress in the real economy: a one standard deviation shock in aggregate SRISK predicts a twentyfive basis points drop in Industrial Production over the next month.