Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-varying fair queueing scheduling for multicode CDMA based on dynamic programming

Fair queueing (FQ) algorithms, which have been proposed for quality of service (QoS) wireline/wireless networking, rely on the fundamental idea that the service rate allocated to each user is proportional to a positive weight. Targeting wireless data networks with a multicode CDMA-based physical layer, we develop FQ with time-varying weight assignment in order to minimize the queueing delays of mobile users. Applying dynamic programming, we design a computationally efficient algorithm which produces the optimal service rates while obeying 1) constraints imposed by the underlying physical layer and 2) QoS requirements. Furthermore, we study how information about the underlying channel quality can be incorporated into the scheduler to improve network performance. Simulations illustrate the merits of our designs.
Instructor Rating Markets

We describe the design of Instructor Rating Markets (IRMs) where human participants interact through intelligent automated market-makers in order to provide dynamic collective feedback to instructors on the progress of their classes. The markets are among the first to enable the empirical study of prediction markets where traders can affect the very outcomes they are trading on. More than 200 students across the Rensselaer campus participated in markets for ten classes in the Fall 2010 semester. In this paper, we describe how we designed these markets in order to elicit useful information, and analyze data from the deployment. We show that market prices convey useful information on future instructor ratings and contain significantly more information than do past ratings. The bulk of useful information contained in the price of a particular class is provided by students who are in that class, showing that the markets are serving to disseminate insider information. At the same time, we find little evidence of attempted manipulation by raters. The markets are also a laboratory for comparing different market designs and the resulting price dynamics, and we show how they can be used to compare market making algorithms.
Isolation of Highly Pathogenic Avian Influenza H5N1 from Table Eggs After Vaccinal Break in Commercial Layer Flock

Abstract In May 2009, during routine monitoring of a commercial layer flock of about 87,000 birds kept in cages in 4 different houses that had been vaccinated 3 times with an inactivated H5N1 vaccine at weeks 1, 7, and 16, highly pathogenic avian influenza (HPAI) virus of subtype H5N1 was isolated and detected by real-time reverse transcriptase–polymerase chain reaction (RT-PCR) in tracheal and cloacal swabs collected from houses 3 and 4; 7 days after onset of clinical signs, there was an increase in mortality accompanied by a decrease in egg production and egg quality. In addition, using RT-PCR, the viral RNA could be detected from albumin and eggshell as well. Seven days after the onset of the clinical signs, the hemagglutination inhibition (HI) titers in the affected houses were 3.2 and 1.9 log2. In the other two houses, there were no clinical signs, and all tested samples were negative using virus isolation and real-time RT-PCR. The HI titers were 6.6 and 7.0 log2 in nonaffected houses. The isolated virus from egg albumin showed high nucleotides and amino-acid identities and clustered with viruses from recently H5N1-confirmed human infections and poultry from different places in Egypt. Moreover, several amino-acid substitutions of viral H5 protein were observed. The vaccinal break seems to be associated with immune escape mutants and/or improper vaccination. The role of contaminated eggs as a source of infection and as a vehicle for spread of the virus should be considered in area with avian influenza outbreaks.
Buprenorphine/naloxone and methadone maintenance treatment outcomes for opioid analgesic, heroin, and combined users: findings from starting treatment with agonist replacement therapies (START).

OBJECTIVE The objective of this secondary analysis was to explore differences in baseline clinical characteristics and opioid replacement therapy treatment outcomes by type (heroin, opioid analgesic [OA], or combined [heroin and OA]) and route (injector or non-injector) of opioid use. METHOD A total of 1,269 participants (32.2% female) were randomized to receive one of two study medications (methadone or buprenorphine/naloxone [BUP]). Of these, 731 participants completed the 24-week active medication phase. Treatment outcomes were opioid use during the final 30 days of treatment (among treatment completers) and treatment attrition. RESULTS Non-opioid substance dependence diagnoses and injecting differentiated heroin and combined users from OA users. Non-opioid substance dependence diagnoses and greater heroin use differentiated injectors from non-injectors. Further, injectors were more likely to be using at end of treatment compared with non-injectors. OA users were more likely to complete treatment compared with heroin users and combined users. Non-injectors were more likely than injectors to complete treatment. There were no interactions between type of opioid used or injection status and treatment assignment (methadone or BUP) on either opioid use or treatment attrition. CONCLUSIONS Findings indicate that substance use severity differentiates heroin users from OA users and injectors from non-injectors. Irrespective of medication, heroin use and injecting are associated with treatment attrition and opioid misuse during treatment. These results have particular clinical interest, as there is no evidence of superiority of BUP over methadone for treating OA users versus heroin users.
A quality / cost-based improvement approach for conceptual process planning

This paper proposes an approach to develop a quality/cost-based conceptual process planning (QCCPP). This approach aims to determine key process resources with estimation of manufacturing cost taking into account the risk cost associated to process plan. Quality Function Deployment (QFD) method is used to select process alternatives. The results of QFD method have been taken as input to complete process Failure Mode and Effects Analysis (FMEA). To estimate manufacturing cost, the proposed approach deploys Activity-Based Costing (ABC) method. Then cost-based FMEA method is employed to estimate the cost of all risks associated to studied process plan. The output data gathered in this approach could be used as the guidelines for detailed process planning in order to improve product quality/cost ratio.
Characterising a Socio-Technical approach to Knowledge Management - Cases in Small to Medium Sized Software Enterprises (SMEs)

With promises of reinventing the organisation, practitioners, consultants and academics alike jumped on the Knowledge Management (KM) bandwagon in the late 1990s. It has typically been larger organisations that have possessed the economies of scale i.e. the financial resources to pursue this strategy, where they perceive they will lose their market share if they do not follow the trend while smaller organisations have not had the same luxury. Ironically, it is these small businesses that have successfully managed knowledge for centuries. However, the success of the KM approach is too tightly linked to the implementation of Knowledge Management Systems (KMS). Although information systems are integral to a KM approach, from an organisational perspective, it is essential that alternative mechanisms which support a formalised KM approach are better understood in order to make a suitable match between the organization's knowledge needs with the most fitting modes available to support the activity. Consequently, using multiple case studies, this study presents a well rounded view of the KM approach, identifying both routine and non-routine modes of knowledge processing for small software organisations, addressing the balance of usage associated with supporting knowledge requirements, in order to improve the organisation's ability to be more flexible in the face of change.
Expanding MISR LAI Products to High Temporal Resolution With MODIS Observations

The Multi-Angle Imaging Spectroradiometer (MISR) is a powerful sensor for leaf area index (LAI) mapping with its simultaneous multi-angle observations. However, the LAI product derived from MISR observations has low temporal resolution, which is unsatisfactory for many applications. This paper presents an algorithm that expands the MISR LAI product to high temporal resolution with the aid of Moderate Resolution Imaging Spectroradiometer (MODIS) data. The algorithm establishes relationships between the MISR LAI and the MODIS red/near-infrared band ratio (simple ratio (SR)) pixel by pixel using coincident data of these two sensors for the past nine years. Using these pixel-based SR-LAI relationships, a new LAI product with the merits of the original MISR product and high temporal resolution is obtained from MODIS surface reflectance. The expanded LAI series was compared with the original MISR and MODIS LAI products, as well as field LAI measurements made at the Baohe and Maoershan forest sites and the Hulunbeier grassland site, to assess the algorithm's performance. The results show that the temporal coverage of the MISR LAI improved from 15.5% to 65.2% in an 8-day composite, and the mean root-mean-square error is 0.74 for the vegetated pixels. This LAI product has similar temporal consistency and seasonal dynamics to the existing MODIS LAI product generated from the main algorithm, but is more robust against the low quality of reflectance inputs. The expanded LAI product differs with field measurements by about 11.5%, with agreement to field observations at all three sites within an accuracy of 0.8 LAI.
A guide to systematic review and meta-analysis of prediction model performance

Validation of prediction models is highly recommended and increasingly common in the literature. A systematic review of validation studies is therefore helpful, with meta-analysis needed to summarise the predictive performance of the model being validated across different settings and populations. This article provides guidance for researchers systematically reviewing and meta-analysing the existing evidence on a specific prediction model, discusses good practice when quantitatively summarising the predictive performance of the model across studies, and provides recommendations for interpreting meta-analysis estimates of model performance. We present key steps of the meta-analysis and illustrate each step in an example review, by summarising the discrimination and calibration performance of the EuroSCORE for predicting operative mortality in patients undergoing coronary artery bypass grafting.
The Measurement of Monopoly Power in Dynamic Markets

importance in the design and application of antitrust policy. Much of the recent literature has focused on the structural and behavioral determinants of monopoly and monopsony power, including the characteristics of costs and demand and the ways in which firms in the market interact with each other. There has been less concern, however, with the development of a measure of monopoly (or monopsony) power. Instead, the Lerner index, first introduced in 1934, has for years been accepted as the standard measure of monopoly power and is often used as a summary statistic in antitrust applications.1 The Lerner index is just the margin between price and marginal cost, L = (P MC)/P. In a static market, D = I1/, where rfis the elasticity of demand facing the firm, so that the firm's elasticity of demand completely determines its monopoly power.2 However, this need not be the case in a
BIODEGRADATION OF PHENOL AND EMULSIFICATION PROPERTIES OF NATIVE MICROORGANISMS FROM COAL CARBONIZATION PLANT

Phenols (aromatic organic compounds) are commonly occurring organic pollutants in the environment. Some of the toxic effects of phenol in humans are corrosive to eyes, skin and respiratory track, in addition also causes lethal effects in animal and plant community when discharged even in low concentrations. The problem associated with phenol in the environment, is in need to removal such hazardous compound. Considering the importance, the present investigation attempts for degradation of phenol by native bacterial strains isolated from coal carbonization plant wastewater. About 36 bacterial isolates were found to exhibit phenol degrading activity. Among them, higher phenol degrading strains were identified tentatively as CA1 - Rhodococcus sp. , CA2 - Bacillus sp. , CA3 - Pseudomonas sp. and CA4 -Citrobacter sp. Phenol degrading ability of Rhodococcus sp. was found to be 60% with maximum cell dry weight. Surface active compounds were observed to be 1.31G for Rhodococcus sp, 0.85 G for Bacillus sp, 1.26 G for Pseudomonas sp. and 1.02 G for Citrobacter sp. In case of mixed cultures, 1.62 G maximum rate among the tested was observed. The Emulsification Index (E24) for CA1, CA2, CA3, CA4 and mixed culture was observed as 78%, 65%, 59%, 22% and 80% respectively. The plasmid profile was additionally studied for the isolates. Significantly, the study reveals the potentials of native strain, Rhodococcus sp. (CA1), in degradation of phenols.
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation

We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to learn the grammatical rules and context dependent changes using a phrase reordering classification framework. We consider a variety of machine learning techniques, including state-of-the-art structured prediction methods. Techniques are compared and evaluated on a Chinese-English corpus, a language pair known for the high reordering characteristics which cannot be adequately captured with current models. In the reordering classification task, the method significantly outperforms the baseline against which it was tested, and further, when integrated as a component of the state-of-the-art machine translation system, MOSES, it achieves improvement in translation results.
Prefetch-aware shared-resource management for multi-core systems

Chip multiprocessors (CMPs) share a large portion of the memory subsystem among multiple cores. Recent proposals have addressed high-performance and fair management of these shared resources; however, none of them take into account prefetch requests. Without prefetching, significant performance is lost, which is why existing systems prefetch. By not taking into account prefetch requests, recent shared-resource management proposals often significantly degrade both performance and fairness, rather than improve them in the presence of prefetching. This paper is the first to propose mechanisms that both manage the shared resources of a multi-core chip to obtain high-performance and fairness, and also exploit prefetching. We apply our proposed mechanisms to two resource-based management techniques for memory scheduling and one source-throttling-based management technique for the entire shared memory system. We show that our mechanisms improve the performance of a 4-core system that uses network fair queuing, parallelism-aware batch scheduling, and fairness via source throttling by 11.0%, 10.9%, and 11.3% respectively, while also significantly improving fairness.
Concept-Based Document Similarity Based on Suffix Tree Document

Document clustering has been studied as a post retrieval document visualization technique to provide an intuitive navigation and browsing mechanism by organizing documents into groups and each group represents a different topic. The clustering techniques are based on four concepts: Data representation model, Similarity measure, Clustering model, and Clustering algorithm. In the previous work, phrase has been considered as an informative feature term for improving the effectiveness of document clustering. In this paper, we propose a Concept-based document similarity to compute the similarities of documents based on the Suffix Tree Document (STD) model. By mapping each node in the suffix tree of STD model into a unique feature term in the Vector Space Document (VSD) model, the concept-based document similarity inherits the term ctf (conceptual term frequency), tf (term frequency), df (document frequency) weighting scheme in computing the document similarity with concept. In this paper the concept-based document similarity is applied to the Hierarchical Agglomerative Clustering (HAC) algorithm to develop a new document clustering approach. The new concept-based model analyzes the terms on the sentence, document, and in corpus levels. The similarity between documents is calculated based on a new concept-based similarity measure (Euclidean distance Measure.). The proposed similarity measure takes full advantage of using the concept analysis measures. Key words—Concept-based model, Suffix tree document Model, Suffix tree, Similarity measure, Document clustering.
Teachers Nurturing Math-Talented Young Children.

Talent in mathematical reasoning is highly valued in this society and yet very little is known about its early course. This book is an outgrowth of a two-year study of children discovered during preschool or kindergarten to be advanced in their thinking about math. In addition to psychometric and cognitive testing conducted at the beginning, middle, and end of the study, half of the children were randomly assigned to biweekly intervention (Saturday Club) for a total of 28 weeks over the two years. Among other findings, the study revealed that, as a group, the children remained advanced in math over the two-year period, that their spatial reasoning related more closely to their math reasoning than did their verbal reasoning (although they were ahead in all three domains), and that the math scores of the boys started and remained somewhat higher than those of the girls. The Saturday Club intervention proved effective in enhancing mathematical reasoning. This book discusses ways of identifying very young math-advanced children as well as a variety of educational strategies to meet their needs. Its primary emphasis is on creating an open-ended approach to teaching mathematics that provides an opportunity for children at different levels of advancement and different personal styles to engage with mathematical challenges in a playful way, to conceptualize math broadly, to pose problems, and to make sense of the mathematical system. Also emphasized are the importance of representing and communicating mathematical ideas in multiple ways in order to deepen children's understanding. A variety of engaging activities such as the Fibonacci series, the Vedic square, and chip-trading are described. Most of these activities emanate from "big ideas" such as the nature of numerals and the number system, equivalence, visualizing and graphing numbers, measurement, estimation, and so on. Job cards for various mathematical tasks are included, as well as ways to integrate mathematics into other aspects of the curriculum. The approach to mathematics portrayed in this book is one that creative teachers can flexibly adapt to meet the needs of math-advanced children in a regular or specialized classroom.
An Improved CAMSHIFT Tracking Algorithm Applying on Surveillance Videos

In this paper, we present an improved version of CAMSHIFT algorithm applying on surveillance videos. A 2D, hue and brightness, histogram is used to describe the color feature of the target. In this way, videos with poor quality or achromatic points can be characterized better. The flooding process and contribution evaluation are executed to obtain a precise target histogram which reflects true color information and enhances discrimination ability. The proposed method is compared with existing methods and shows steady and satisfactory results.
Descriptive epidemiology of collegiate women's lacrosse injuries: National Collegiate Athletic Association Injury Surveillance System, 1988-1989 through 2003-2004.

OBJECTIVE To review 16 years of National Collegiate Athletic Association injury surveillance data for women's lacrosse and identify potential areas for injury prevention initiatives. BACKGROUND Women's lacrosse is a fast-paced, primarily noncontact sport. Participation in collegiate women's lacrosse almost doubled between the 1988-1989 and 2003-2004 seasons. Lacrosse equipment consists of sticks made of wood or a synthetic material and a hard rubber ball. Until recently, mouth guards were the only required protective equipment. MAIN RESULTS Collegiate women's lacrosse game injury rates increased over the 16-year study period. More than 60% of all severe game injuries were lower extremity sprains and strains and knee internal derangements, most frequently the result of noncontact incidents. The most common injury scenarios by injury mechanism and player activity were no contact while ball handling (16.4%) and contact from a stick while ball handling (10.5%). Contact from a stick or a ball accounted for 5.6% and 5.2% of injuries sustained during shooting activities, respectively. Approximately 22% of all game and 12% of all practice injuries involved the head and neck. Contact from a stick accounted for the majority (56.0%) of above-the-neck injuries in games; contact from the ball accounted for 20.0% of these injuries. Participants had 5 times the risk of sustaining a concussion in a game as in a practice (0.70 versus 0.15 injuries per 1000 athletic-exposures, rate ratio = 4.7, 95% confidence interval = 3.8, 6.5). RECOMMENDATIONS To reduce the lower extremity injuries that comprise the greatest injury burden in women's lacrosse, future researchers should evaluate proprioceptive, plyometric, and balance training interventions designed specifically for female players. Other research areas of great interest involve determining whether protective eyewear (mandated in 2004) reduces injuries to the eye, orbit, and nasal area and identifying any unintended consequences of the mandate, such as increased risk of injuries to other areas of the face or more aggressive play.
A study to understand lead-lag performance of subject vs rehabilitation system

Robotic assistance in stroke rehabilitation is rapidly advancing based on the recent developments in robotics, haptic interfaces and virtual reality. GENTLE/S is a rehabilitation system that utilized haptic and virtual reality technologies to deliver challenging and meaningful therapies to upper limb impaired stroke subjects. The current research is working towards designing GENTLE/A system with a better adaptive human-robot interface, which allows for automatic tuning of the assistance and resistance based on provided input. This paper presents the results from a preliminary study conducted with three healthy subjects as part of this research. The aim of the investigation is to explore whether it is possible to identify if a robot or a person is leading the interaction by comparing the results from the actual performance of the subject with the minimum jerk model used to drive the robot. The final goal is to use these observations to probe various ways in which the contribution of robot can be established and the adaptability of the robot during the therapy can be enhanced.