Miracle-dz/UniFAR-FTUs huggingface dataset:
Handbook of Fiber Optic Data Communication: A Practical Guide to Optical Networking

The 4th edition of this popular Handbook continues to provide an easy-to-use guide to the many exciting new developments in the field of optical fiber data communications. With 90 per cent new content, this edition contains all new material describing the transformation of the modern data communications network, both within the data center and over extended distances between data centers, along with best practices for the design of highly virtualized, converged, energy efficient, secure, and flattened network infrastructures. Key topics include networks for cloud computing, software defined networking, integrated and embedded networking appliances, and low latency networks for financial trading or other time-sensitive applications. Network architectures from the leading vendors are outlined (including Smart Analytic Solutions, Qfabric, FabricPath, and Exadata) as well as the latest revisions to industry standards for interoperable networks, including lossless Ethernet, 16G Fiber Channel, RoCE, FCoE, TRILL, IEEE 802.1Qbg, and more. It is written by experts from IBM, HP, Dell, Cisco, Ciena, and Sun/ Oracle. It features case studies and 'How to. ' demonstrations on a wide range of topics, including Optical Ethernet, next generation Internet, RDMA and Fiber Channel over Ethernet. It covers quick reference tables of all the key optical network parameters for protocols like ESCON, FICON, and SONET/ATM and a glossary of technical terms and acronyms.
Predicting the risk of mortality and rehospitalization in heart failure patients: A retrospective cohort study by machine learning approach

Abstract Background Heart failure (HF) is a global problem, affecting more than 26 million people worldwide. This study evaluated the performance of 10 machine learning (ML) algorithms and chose the best algorithm to predict mortality and readmission of HF patients by using The Fasa Registry on Systolic HF (FaRSH) database. Hypothesis ML algorithms may better identify patients at increased risk of HF readmission or death with demographic and clinical data. Methods Through comprehensive evaluation, the best‐performing model was used for prediction. Finally, all the trained models were applied to the test data, which included 20% of the total data. For the final evaluation and comparison of the models, five metrics were used: accuracy, F1‐score, sensitivity, specificity and Area Under Curve (AUC). Results Ten ML algorithms were evaluated. The CatBoost (CAT) algorithm uses a series of decision tree models to create a nonlinear model, and this CAT algorithm performed the best of the 10 models studied. According to the three final outcomes from this study, which involved 2488 participants, 366 (14.7%) of the patients were readmitted to the hospital, 97 (3.9%) of the patients died within 1 month of the follow‐up, and 342 (13.7%) of the patients died within 1 year of the follow‐up. The most significant variables to predict the events were length of stay in the hospital, hemoglobin level, and family history of MI. Conclusions The ML‐based risk stratification tool was able to assess the risk of 5‐year all‐cause mortality and readmission in patients with HF. ML could provide an explicit explanation of individualized risk prediction and give physicians an intuitive understanding of the influence of critical features in the model.
Rapid and Repeated Climate Adaptation Involving Chromosome Inversions following Invasion of an Insect

Abstract Following invasion, insects can become adapted to conditions experienced in their invasive range, but there are few studies on the speed of adaptation and its genomic basis. Here, we examine a small insect pest, Thrips palmi, following its contemporary range expansion across a sharp climate gradient from the subtropics to temperate areas. We first found a geographically associated population genetic structure and inferred a stepping-stone dispersal pattern in this pest from the open fields of southern China to greenhouse environments of northern regions, with limited gene flow after colonization. In common garden experiments, both the field and greenhouse groups exhibited clinal patterns in thermal tolerance as measured by critical thermal maximum (CTmax) closely linked with latitude and temperature variables. A selection experiment reinforced the evolutionary potential of CTmax with an estimated h2 of 6.8% for the trait. We identified 3 inversions in the genome that were closely associated with CTmax, accounting for 49.9%, 19.6%, and 8.6% of the variance in CTmax among populations. Other genomic variations in CTmax outside the inversion region were specific to certain populations but functionally conserved. These findings highlight rapid adaptation to CTmax in both open field and greenhouse populations and reiterate the importance of inversions behaving as large-effect alleles in climate adaptation.
Cattle are more motivated for a high-concentrate diet than Sudan grass hay, despite low reticulorumen pH

Abstract Subacute ruminal acidosis (SARA) is characterized by chronic low ruminal pH, and occurs for feedlot cattle fed high-concentrate diets. Forages slow digestion and reduce acid production. We aimed to assess how motivated finishing cattle are to access forage (Sudan grass hay, SG) via their willingness to interact with an electrified barrier. Reticulorumen pH was measured to relate the results to digestive health. Twenty-eight animals fed a high-concentrate ration ad libitum had access to 4 L of one of two treatments (n = 14/treatment) fed 1×/d behind a barrier: 1) SG or 2) an additional offering of the normal ration (total mixed ration [TMR]). To access their treatment, the steer voluntarily pushed his muzzle against an electrified barrier. The electrical current was increased exponentially every 24 h (0, 156, 312, 625, 1,250, 2,500, 5,000 µA) until the animal ceased accessing it. Visits to the treatment were recorded continuously 24 h/d and reticulorumen pH was measured every 10 min. Time with a reticulorumen pH below 5.8 was 348 ± 101 and 280 ± 76 min/24 h for SG and TMR animals, respectively; these durations meet the criterion for SARA. However, animals with access to SG were less likely to advance to the next current than TMR animals (P < 0.01) and were approximately 3× less willing to interact with higher currents than TMR (mean maximum current touched: 469 ± 169 and 1,380 ± 254 μA, respectively, mean ± SE, P = 0.01). Lower motivation to access SG was further demonstrated through fewer visits to the SG (2.4 ± 0.4 vs. 5.3 ± 0.6 #/d, P < 0.01), and less SG consumed than TMR (32.0 ± 0.1 vs. 74.0 ± 0.0 %/d, P < 0.01, measured as % due to weight differences of SG and TMR). Overall, finishing cattle valued the TMR more than SG, likely because of differences in the quantity offered, palatability, and familiarity. When rumen health was considered, SG animals visited more often (r = 0.5, P = 0.09) and showed fewer failed attempts (r = −0.5, P = 0.06) to access forage as the severity and duration of pH depression below 5.6, for example, increased. No measures of treatment use were related to pH depression for TMR animals (P ≥ 0.31). These findings provide evidence that cattle are motivated for Sudan grass hay when experiencing chronic low reticulorumen pH. However, they also contribute to the mixed evidence about the motivation for forage in this life stage, because, overall TMR was valued more highly than SG. Despite widespread pH depression, TMR cattle contrafreeloaded for additional concentration, demonstrating unexpectedly high motivation for this resource.
Decadal Delays in Groundwater Recovery from Nitrate Contamination Caused by Low O2 Reduction Rates

Nitrate (NO 3− ) is one of the main pollutants in agriculturally impacted groundwater systems. The availability and reactivity of electron donors control the prevalent redox conditions in aquifers and past nitrate contamination of groundwater can be ameliorated if denitrification occurs. Using aqueous geochemistry data and the stable isotope composition of dissolved nitrate (δ15N and δ18O), we found that nitrate concentrations above the World Health Organization drinking water guideline were caused predominantly by manure and to a lesser extent by synthetic fertilizer applications and that denitrification was not a significant nitrate removal process in an aquifer in southern Germany underlying agricultural land with intensive hog farming. We also applied environmental isotopes (δ2H and δ18O, 3H/3He, and 14C) linked with a lumped parameter approach to determine apparent mean transit times (MTT) of groundwater that ranged from <5 years to >100 years. Furthermore, we determined low reduction rates of dissolved oxygen (O2) of 0.015 1/year for first‐order kinetics. By extrapolating the O2 reduction rates beyond the apparent MTT ranges of sampled groundwater, denitrification lag times (time prior to commencement of denitrification) of approximately 114 years were determined. This suggests that it will take many decades to significantly reduce nitrate concentrations in the porous aquifer via denitrification, even if future nitrate inputs were significantly reduced.
Modeling of karst aquifer genesis: Influence of exchange flow

This paper presents a numerical model study simulating the early karstification of a single conduit embedded in a fissured system. A hybrid continuum‐discrete pipe flow model (CAVE) is used for the modeling. The effects of coupling of the two flow systems on type and duration of early karstification are studied for different boundary conditions. Assuming fixed head boundaries at both ends of the conduit, coupling of the two flow systems via exchange flow between the conduit and the fissured system leads to an enhanced evolution of the conduit. This effect is valid over a wide range of initial conduit diameters, and karstification is accelerated by a factor of about 100 as compared to the case of no exchange flow. Parameter studies reveal the influence of the exchange coefficient and of the hydraulic conductivity of the fissured system on the development time for the conduit. In a second scenario the upstream fixed head boundary is switched to a fixed flow boundary at a specified flow rate during the evolution, limiting the amount of water draining toward the evolving conduit. Depending on the flow rate specified, conduit evolution may be slowed down or greatly impaired if exchange flow is considered.
Aesthetic Computing

The paper describes recent developments in Video Constructs, the basic versions of which are generative abstract computer animations. In video constructs, the logic in the computer provides the underlying structure that leads to the form of the work. The most exciting element of the constructive video is, perhaps, the careful and very terse way in which a specification of what occurs in time is possible. The brevity of the specification is extremely important in the development of ideas. The inevitable exploration is so strongly supported by this aspect of the use of the computer that new ways of thinking about work emerge in their very construction. This has led to developments both in interaction and in changing behaviors as the result of experience. The time-based video constructs have developed into interactive video constructs. It is not hard to understand how the structures in time can be so constructed as to react to events detected by sensor systems. A real time image analysis system is incorporated into the generative program. The behaviour of the piece, i.e. the generative path that it takes, is then reactive to what participants are doing or what music is being played.
Randomness-efficient Low Degree Tests and Short PCPs via Epsilon-Biased Sets

We present the first explicit construction of Probabilistically Checkable Proofs (PCPs) and Locally Testable Codes (LTCs) of fixed constant query complexity which have almostlinear (= n · 2 √ ) size. Such objects were recently shown to exist (nonconstructively) by Goldreich and Sudan [17]. Previous explicit constructions required size n ) with 1/ queries. The key to these constructions is a nearly optimal randomnessefficient version of the low degree test [32]. In a similar way we give a randomness-efficient version of the BLR linearity test [13] (which is used, for instance, in locally testing the Hadamard code). The derandomizations are obtained through ε-biased sets for vector spaces over finite fields. The analysis of the derandomized tests rely on alternative views of ε-biased sets — as generating sets of Cayley expander graphs for the low degree test, and as defining linear error-correcting codes for the linearity test. ∗Supported by NSF grants CCR-0133096, CCR-9877049, CCR 0205390, and NTT Award MIT 2001-04. †Supported in part by NSF Awards CCR 0205390, and NTT Award MIT 2001-04. ‡URL: http://www.eecs. harvard.edu/~salil. Supported by NSF grant CCR-0133096 and a Sloan Research Fellowship. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. STOC’03, June 9–11, 2003, San Diego, California, USA. Copyright 2003 ACM 1-58113-674-9/03/0006 . $10.00. General Terms
Towards predictable datacenter networks

The shared nature of the network in today's multi-tenant datacenters implies that network performance for tenants can vary significantly. This applies to both production datacenters and cloud environments. Network performance variability hurts application performance which makes tenant costs unpredictable and causes provider revenue loss. Motivated by these factors, this paper makes the case for extending the tenant-provider interface to explicitly account for the network. We argue this can be achieved by providing tenants with a virtual network connecting their compute instances. To this effect, the key contribution of this paper is the design of virtual network abstractions that capture the trade-off between the performance guarantees offered to tenants, their costs and the provider revenue. To illustrate the feasibility of virtual networks, we develop Oktopus, a system that implements the proposed abstractions. Using realistic, large-scale simulations and an Oktopus deployment on a 25-node two-tier testbed, we demonstrate that the use of virtual networks yields significantly better and more predictable tenant performance. Further, using a simple pricing model, we find that the our abstractions can reduce tenant costs by up to 74% while maintaining provider revenue neutrality.
A New Approach for Detecting Shifts in Forecast Accuracy

Forecasts play a critical role at inflation-targeting central banks, such as the Bank of England. Breaks in the forecast performance of a model can potentially incur important policy costs. Commonly used statistical procedures, however, implicitly put a lot of weight on type I errors (or false positives), which result in a relatively low power of tests to identify forecast breakdowns in small samples. We develop a procedure which aims at capturing the policy cost of missing a break. We use data-based rules to find the test size that optimally trades off the costs associated with false positives with those that can result from a break going undetected for too long. In so doing, we also explicitly study forecast errors as a multivariate system. The covariance between forecast errors for different series, though often overlooked in the forecasting literature, not only enables us to consider testing in a multivariate setting but also increases the test power. As a result, we can tailor the choice of the critical values for each series not only to the in-sample properties of each series but also to how the series for forecast errors covary.
Enhancing the Structure of the WRF-Hydro Hydrologic Model for Semiarid Environments

In August 2016, the National Weather Service Office of Water Prediction (NWS/OWP) of the National Oceanic and Atmospheric Administration (NOAA) implemented the operational National Water Model (NWM) to simulate and forecast streamflow, soil moisture, and other model states throughout the contiguous United States. Based on the architecture of the WRF-Hydro hydrologic model, the NWM does not currently resolve channel infiltration, an important component of the water balance of the semiarid western United States. Here, we demonstrate the benefit of implementing a conceptual channel infiltration function (from the KINEROS2 semidistributed hydrologic model) into the WRF-Hydro model architecture, configured as NWM v1.1. After calibration, the updated WRF-Hydro model exhibits reduced streamflow errors for the Walnut Gulch Experimental Watershed (WGEW) and the Babocomari River in southeast Arizona. Model calibration was performed using NLDAS-2 atmospheric forcing, available from the NOAA National Centers for Environmental Prediction (NCEP), paired with precipitation forcing from NLDAS-2, NCEP Stage IV, or local gauge precipitation. Including channel infiltration within WRF-Hydro results in a physically realistic hydrologic response in the WGEW, when the model is forced with high-resolution, gauge-based precipitation in lieu of a national product. The value of accounting for channel loss is also demonstrated in the Babocomari basin, where the drainage area is greater and the cumulative effect of channel infiltration is more important. Accounting for channel infiltration loss thus improves the streamflow behavior simulated by the calibrated model and reduces evapotranspiration bias when gauge precipitation is used as forcing. However, calibration also results in increased high soil moisture bias, which is likely due to underlying limitations of the NWM structure and calibration methodology.
Heterogeneous Strong Computation Migration

The continuous increase in performance requirements, for both scientific computation and industry, motivates the need of a powerful computing infrastructure. The Grid appeared as a solution for inexpensive execution of heavy applications in a parallel and distributed manner. It allows combining resources independently of their physical location and architecture to form a global resource pool available to all grid users. However, grid environments are highly unstable and unpredictable. Adaptability is a crucial issue in this context, in order to guarantee an appropriate quality of service to users. Migration is a technique frequently used for achieving adaptation. The objective of this report is to survey the problem of strong migration in heterogeneous environments like the grids’, the related implementation issues and the current solutions.
Oblivious RAM with O ( ( log N ) 3 ) Worst-Case Cost

Oblivious RAM (O-RAM) is a useful primitive that allows a client to hide its data access patterns from an untrusted server in storage outsourcing applications. This paper proposes novel O-RAM constructions that achieves poly-logarithmic worst-case cost, while consuming constant client-side storage. Our techniques for constructing Oblivious RAM are fundamentally different from previous approaches. Specifically, we organize the O-RAM storage into a binary tree over data buckets, while moving data blocks obliviously along tree edges. Our construction (instantiated the trivial bucket O-RAM) has remarkable conceptual simplicity, and eliminates the need to perform expensive oblivious sorting operations. As a result, to the best of our knowledge, our construction is by far the most practical scheme with constant client-side memory, under realistic parameterizations.
Speech Perception Test of Zero-Error Consonant-Vowel Syllables in Presbycusis

Speech Perception Test of Zero-Error Consonant-Vowel Syllables in Presbycusis Woojae Han and Jont B. Allen Div. of Speech Pathology and Audiology, College of Natural Science, Hallym University, Chuncheon, Korea Research Institute of Audiology and Speech Pathology, Hallym University, Chuncheon, Korea Dept. of Electrical and Computer Engineering, Univ. of Illinois at Urbana-Champaign, IL, USA The purpose of this study is to measure speech perception ability in presbycusis, using zero-error consonant-vowel (CV) syllables as a function of signal-to-noise ratio (SNR). Seventeen elder people with symmetric mild-to-moderate sensorineural hearing loss were tested with 14 syllables spoken by two different speakers at four different SNRs. Error rate and entropy calculation were used to analyze data. The results show that both error rate and entropy significantly increased as noise increased. In particular, /ba, va, ga, na/ were affected by noise level in both error rate and entropy, yet /za, Ʒa/ were only in entropy. We conclude that evaluating speech perception ability using zero-error CV syllables might scrutinize the unique characteristics of presbycusis. We also find that entropy analysis is very useful in even including response’s uncertainty which is not found in the typical error rate analysis.
NRC Publications Archive Archives des publications du CNRC

We describe a mixture-model approach to adapting a Statistical Machine Translation System for new domains, using weights that depend on text distances to mixture components. We investigate a number of variants on this approach, including cross-domain versus dynamic adaptation; linear versus loglinear mixtures; language and translation model adaptation; different methods of assigning weights; and granularity of the source unit being adapted to. The best methods achieve gains of approximately one BLEU percentage point over a state-of-the art non-adapted baseline system.
A Survey on Sentiment Classification for Product Aspect Ranking

A large number of reviews for the product are available on the internet . To classify these reviews is very difficult task. The Sentiment classification is one of the ongoing research areas in text mining field which is used for classifying the polarity of the reviews. In this paper, we study the survey of different techniques for sentiment classification. General Terms Aspects, online customer reviews, sentiment analysis
Blocking-Effect Reduction in a Reversed-Complexity Video Codec Based on a Mixed-Quality Framework

This paper presents a blocking-effect reduction in a method for reversed-complexity video codec. We used intra predicted frames encoded at different quality (distortion) targets. We propose a technique to improve the enhancement layer of a mixed-quality encoded sequence, using information from the high-quality (key) frames to enhance the low-quality (nonkey) ones at the decoder. The results show that it is possible to subjectively reduce the blocking effect by using overlapped motion compensation at the enhancement layer. It is shown that the subjective quality is improved and the objective quality is incremented at the non-key frames.
Rural entrepreneurial space and identity

The tourism industry is a capitalist activity concerned with the production, accumulation and distribution of wealth. Power is an important arena for research in this respect as diverse outcomes for the local economy in general, and its players specifically, provide important aspects to study when considering the lives of rural entrepreneurs. However, it may be argued that while Marxist theorists using critical approaches on power have tended to focus on issues around the equality of power relations between actors or stakeholders, the inherently spatial nature of power has received less emphasis. This article focuses on an exploration of the spatiality of power which surrounds entrepreneurship and tourism industry development.