Miracle-dz/UniFAR-FTUs huggingface dataset:
Locating the magnetic center of the SSC CDM using a temporary quadrupole field

For the Superconducting Super Collider (SSC) to meet its physics requirements, the magnetic center of each collider dipole magnet (CDM) must be accurately aligned. A technique has been developed to determine the magnetic center of the SSC dipole magnet under ambient test conditions. This technique involves flowing current in the upper half of the coils in the direction opposite to the current in the lower half. This is done using a temporary lead connected to the splice joining the two coil halves and two matched power supplies. The resulting field is primarily skew quadrupole and has high field gradients which allow the center to be accurately located. The viability of this method has been verified by analysis using a Taylor series expansion of the resulting magnetic field. The analysis has also verified that off-the-shelf power supplies have low enough mismatch to be used in this technique. The analytical results have been verified through the test of a short dipole magnet at the Brookhaven National Laboratory. <<ETX>>
Back to the future: Forecasting program behavior in automated homes

Networked devices such as locks and thermostats are now cheaply available, which is accelerating the adoption of home automation. But unintended behaviors of programs that control automated homes can pose severe problems, including security risks (e.g., accidental disarming of alarms). We facilitate predictable control of automated homes by letting users “fast forward” their program and observe its possible future behaviors under different sequences of inputs and environmental conditions. A key challenge that we face, which is not addressed by existing program exploration techniques, is to systematically handle time because home automation programs depend intimately on absolute and relative timing of inputs. We develop an approach that models programs as timed automata and incorporates novel mechanisms to enable scalable and comprehensive exploration of their behavior. We implement our approach in a tool called DeLorean and apply it to 10 real home automation programs. We find that it can fast forward these programs 3.6 times to 36K times faster than real time and uncover unintended behaviors in them.
Current smoking among young adolescents: assessing school based contextual norms

Objective: To extend research on the relation of school based contextual norms to current smoking among adolescents by using three analytic techniques to test for contextual effects. It was hypothesised that significant contextual effects would be found in all three models, but that the strength of these effects would vary by the statistical rigor of the model. Design: Three separate analytic approaches were conducted on baseline self report student survey data from a larger study to test the relation between school level perceived peer tobacco use and individual current smoking status. Participants: A representative sample of 5399 sixth through eighth grade students in 14 midwestern middle schools completed the survey. All enrolled sixth through eighth grade students were eligible to participate in the survey. The student participation rate was 91.4% for the entire sample, and did not differ significantly between the schools (range 82–100%). Main outcome measure: Thirty day cigarette smoking prevalence. Results: A level 2 only model based on aggregated individual responses indicated that students in schools with higher average reported peer tobacco use were more likely to be current smokers than students in schools with lower average peer tobacco use. Using a level 1 only model based on individual responses indicated that the effect of school level perceived peer tobacco use on current smoking was significant when individual perceived peer tobacco use was excluded from the model but was non-significant when individual perceived peer tobacco use was added to the model. A multilevel model also indicated that the effect of school level perceived peer tobacco use on current smoking was not significant when individual perceived peer tobacco use was added to the model. Conclusion: The analytic approach used to examine contextual effects using individuals’ reports of peer tobacco use norms that were aggregated to obtain a context measure of the school norms may produce statistical artefacts that distort the association of the school context in general, and peer tobacco use norms in particular, with increased risk for current smoking beyond the risk associated with individual factors.
Routed inter-ALU networks for ILP scalability and performance

Modern processors rely heavily on broadcast networks to bypass instruction results to dependent instructions in the pipeline. However, as clock rates increase, architectures get wider, and pipelines get deeper, broadcasting becomes more complex, slower, and more difficult to implement. This complexity is compounded by shrinking feature size, as the communication speed decreases relative to transistor switching speeds. We examine the fundamental needs of bypassing networks and propose a method for classifying these inter-ALU networks based on how operands are routed from producers to consumers. We then propose and evaluate at both the circuit and architectural level a fine grain point-to-point routed inter-ALU network (RIAN) that delivers the same or higher instruction throughput as a full bypass network but at higher speeds while using fewer wires.
Twenty–Four Month Coronal Caries Incidence: The Role of Dental Care and Race

Objectives: To describe for a diverse sample of dentate middle–aged and older adults: (1) the 24–month incidence of coronal caries, and (2) its association with a broad range of clinical, behavioral, financial, attitudinal, and sociodemographic factors. Methods: The Florida Dental Care Study is a prospective observational longitudinal cohort study of 873 persons who at baseline had at least 1 tooth and were 45 years or older. In–person interviews and clinical examinations were conducted at baseline and 24 months, with 6–monthly telephone interviews between those times. A multinomial logistic regression was done to predict whether a participant was in one of four mutually exclusive groups at the 24–month examination (new decay only [NDO]; new filling(s) only [NFO]; both new decay and filling(s) [BOTH]; or neither [NONE]). Results: Only 33% of the 24–month participants were in the NONE group. There was no significant difference in caries incidence between regular attenders and problem–oriented attenders, regardless of whether teeth crowned at baseline, incident crowns, or incident root fragments were excluded. However, once differences in incident tooth loss and baseline clinical, behavioral, financial, and attitudinal differences were taken into account, regular attenders did appear to benefit by developing fewer coronal lesions and fewer dental symptoms than problem–oriented attenders. Baseline carious surfaces, filled surfaces, number of teeth, and bulk restoration fractures predicted caries incidence, but baseline cusp fractures did not. Persons with negative dental attitudes were more likely to be in the NDO and BOTH groups, and negative attitude toward brushing and flossing (but not their frequency) also predicted caries incidence. Conclusion: Certain baseline clinical conditions, approach to dental care, ability to pay for dental care, dental attitudes, race, and age group were predictive of coronal caries incidence, and regular attenders appeared to benefit from regular attendance.
Efficient and Robust Schemes for Sensor Data Aggregation Based on Linear Counting

Sensor networks have received considerable attention in recent years, and are often employed in the applications where data are difficult or expensive to collect. In these applications, in addition to individual sensor readings, statistical aggregates such as Min and Count over the readings of a group of sensor nodes are often needed. To conserve resources for sensor nodes, in-network strategies are adopted to process the aggregates. One primitive in-network aggregation strategy is the tree-based aggregation, where the aggregates are computed from leaves to the root of a spanning tree over a sensor network. However, a shortcoming with the tree-based aggregation is that it is not robust against communication failures, which are common in sensor networks. One of the solutions to overcome this shortcoming is to enable multipath routing, by which each node broadcasts its reading or a partial aggregate to multiple neighbors. However, multipath routing-based aggregation typically suffers from the problem of overcounting sensor readings. In this study, we propose two schemes based on the linear counting technique to deal with the overcounting problem. These two schemes process aggregates by statically and dynamically, respectively, allocating space for the use of the linear counting technique. Both schemes provide the same accuracy guarantee but involve different communication costs. Through extensive experiments with real-world and synthetic data, we demonstrate the efficiency and effectiveness of using these two schemes as solutions for processing aggregates in a sensor network. The experiments also show that the scheme that dynamically allocates the space often outperforms the other one in terms of energy conservation since it requires less space to satisfy an accuracy constraint.
GPU-Acceleration of Sequence Homology Searches with Database Subsequence Clustering

Sequence homology searches are used in various fields and require large amounts of computation time, especially for metagenomic analysis, owing to the large number of queries and the database size. To accelerate computing analyses, graphics processing units (GPUs) are widely used as a low-cost, high-performance computing platform. Therefore, we mapped the time-consuming steps involved in GHOSTZ, which is a state-of-the-art homology search algorithm for protein sequences, onto a GPU and implemented it as GHOSTZ-GPU. In addition, we optimized memory access for GPU calculations and for communication between the CPU and GPU. As per results of the evaluation test involving metagenomic data, GHOSTZ-GPU with 12 CPU threads and 1 GPU was approximately 3.0- to 4.1-fold faster than GHOSTZ with 12 CPU threads. Moreover, GHOSTZ-GPU with 12 CPU threads and 3 GPUs was approximately 5.8- to 7.7-fold faster than GHOSTZ with 12 CPU threads.
An Input Switching Interface Using Carbon Copy Metaphor

This paper proposes a novel input technique that aims to switch between relative and absolute coordinates input methods seamlessly based on the "carbon copy" metaphor. We display a small workspace (``carbon copy area'') on a computer screen that corresponds one-to-one with the handy trackpad. The user can input hand-written characters or images using absolute coordinates input on this virtual carbon copy paper and move it anywhere using relative coordinates. Our technique allows a user to call both absolute and relative coordinates input methods and use them appropriately with arbitrary timing. Several advantages can be obtained by combining these methods. We developed a desktop application software to utilize this technique in a real GUI environment based on a user's evaluation.
Motifs in biological networks

Current progress in molecular biology, particularly in genome sequencing and highthroughput technologies, have led to an unprecedented growth in data. The availability of detailed molecular data allows the reconstruction of the structure and dynamic of biological processes and systems. This transition from the molecular level to the systems level is necessary for an understanding of the function and regulation of these complex biological systems [20; 17]. In this regard the application of mathematical and computational techniques for the analysis of biological data on the systems level is of great importance due to the complexity of the systems and the wealth of data. A mathematical branch used in modelling complex biological systems is graph theory. The elements of a system are represented as vertices of a graph and the interaction between them are represented as edges. Graph algorithms can then be used to analyse, simulate and visualise the system. Graphs have been used to represent for example, metabolic, protein-protein interaction and gene regulatory networks. In these networks entities such as metabolites, proteins or genes are represented by vertices and relationships between entities such as reactions or protein interactions are represented by edges. Processes of life are highly regulated. A cell as the smallest entity of life has the ability to respond to various signals, can adapt to changing conditions of their
Fast image dehazing algorithm based on multiple filters

This paper proposes a new fast dehazing method based on multiple filtering methods. We firstly estimate an initial airlight map through its characteristics, then refine it by bilateral filter and guided filter to generate a new one which removes the abundant texture information and recovers the depth edge information. And, the correct atmosphere light is generated by a hierarchical searching method based on the quad-tree subdivision. Finally, the scene radiance is produced by the atmosphere attenuation model. Comparing experiments show that the proposed algorithm can get a good dehazing effect and is sufficiently fast for realtime applications.
Correlation based phase noise compensation in 60 GHz wireless systems

The necessity of phase noise (PN) compensation in future 60GHz communication systems is shown in this paper. Based on a reference hardware testbed we evaluate the impact of PN on the transmission performance. We show that long data transmissions can only be obtained with PN compensation even for low modulation orders. A low-complexity algorithm for phase noise estimation and compensation based on auto-correlation of pilot words is described. An efficient all-digital architecture for the proposed algorithm is presented.
Interrater Reliability in Content Analysis of Healthcare Service Quality Using Montreal’s Conceptual Framework

Abstract: This study examines the usefulness of the Montreal Service Concept framework of service quality measurement, when it was used as a predefined set of codes in content analysis of patients’ responses. As well, the study quantifies the interrater agreement of coded data. Two raters independently reviewed each of the responses from a mail survey of ambulatory patients about the quality of care and recorded whether or not a patient expressed each concern. Interrater agreement was measured in three ways: the percent crude agreement, Cohen’s kappa, and the coefficient of the generalizability theory. We found all levels of interrater code-specific agreement to be over 96%. All kappa values were above 0.80, except four codes associated with rarely observed characteristics. A coefficient of generalizability equal to 0.93 was obtained. All indices consistently revealed substantial agreement. We empirically showed that the content categories of the Montreal Service Concept were exhaustive and reliable in a well-defined content-analysis procedure.
Relation-Based File Management for Portable Device

As storage capacity in CE devices has been increased, the number and type of files has been increased accordingly. But traditional file systems generally use hierarchical directory/file structure to organize files. When we want to store and retrieve a file, we should know the name and location of the file exactly. And only one access path can be allowed to users. These file systems are not adequate to manage files of portable storage. We present WebFS to effectively manage files stored in mobile storage and to provide users with a convenient way to retrieve files. WebFS represents complicated information of files by using extended file metadata and provides various and effective way to access files by using inter-file relationships among files.
Assessment of Radiation doses to Paediatric Patients in Computed Tomography Procedures

Summary Background The use of pediatric CT that had recently emerged as a valuable imaging tool has increased rapidly with an annual growth estimated at about 10% per year. Worldwide, there is a remarkable increase in the number of CT examinations performed. The purposes of this study are to: (i) to measure the radiation dose and estimate the effective doses to pediatric patients during CT for chest, abdomen and brain. Material/Methods A total of 182 patients were investigated. CT scanners that participated in this study are helical CT scanners (64 slices, 16 slices and dual slices). Organ and surface dose to specific radiosensitive organs were estimated by using software from National Radiological Protection Board (NRPB). Results For all patients, the age was ranged between 1.12 month–10.0 years while the weight was ranged between 5.0 kg to 29.0 kg. The DLP was 320.58 mGy·cm, 79.93 mGy·cm, 66.63 mGy·cm for brain, abdomen and chest respectively. The effective dose was, 2.05, 1.8, 1.08 mSv for brain, abdomen and chest respectively. Conclusions The patient dose is independent of CT modality and depends on operator experience and CT protocol. The study has shown a great need for referring criteria, continuous training of staff in radiation protection concepts. Further studies are required in order to establish a reference level in Sudan.
Novel species of Mycosphaerellaceae and Teratosphaeriaceae

Recent phylogenetic studies based on multi-gene data have provided compelling evidence that the Mycosphaerellaceae and Teratosphaeriaceae represent numerous genera, many of which can be distinguished based on their anamorph morphology. The present study represents the second contribution in a series describing several novel species in different capnodealean genera defined in a previous study. Novelties on Eucalyptus from Australia include: Penidiella pseudotasmaniensis, P. tenuiramis, Phaeothecoidea intermedia, P. minutispora, Pseudocercospora tereticornis, Readeriella angustia, R. eucalyptigena, R. menaiensis, R. pseudocallista, R. tasmanica, Teratosphaeria alboconidia, T. complicata, T. majorizuluensis, T. miniata, T. profusa, Zasmidium aerohyalinosporum and Z. nabiacense, while Teratosphaeria xenocryptica is described on Eucalyptus from Chile. Novelties on other hosts include Phaeophleospora eugeniicola on Eugenia from Brazil, and Zasmidium nocoxi on twig litter from the USA.
LAP: Loop-Block Aware Inclusion Properties for Energy-Efficient Asymmetric Last Level Caches

Emerging non-volatile memory (NVM) technologies, such as spin-transfer torque RAM (STT-RAM), are attractive options for replacing or augmenting SRAM in implementing last-level caches (LLCs). However, the asymmetric read/write energy and latency associated with NVM introduces new challenges in designing caches where, in contrast to SRAM, dynamic energy from write operations can be responsible for a larger fraction of total cache energy than leakage. These properties lead to the fact that no single traditional inclusion policy being dominant in terms of LLC energy consumption for asymmetric LLCs. We propose a novel selective inclusion policy, Loop-block-Aware Policy (LAP), to reduce energy consumption in LLCs with asymmetric read/write properties. In order to eliminate redundant writes to the LLC, LAP incorporates advantages from both non-inclusive and exclusive designs to selectively cache only part of upper-level data in the LLC. Results show that LAP outperforms other variants of selective inclusion policies and consumes 20% and 12% less energy than non-inclusive and exclusive STT-RAM-based LLCs, respectively. We extend LAP to a system with SRAM/STT-RAM hybrid LLCs to achieve energy-efficient data placement, reducing the energy consumption by 22% and 15% over non-inclusion and exclusion on average, with average-case performance improvements, small worst-case performance loss, and minimal hardware overheads.
Positive feelings facilitate working memory and complex decision making among older adults

The impact of induced mild positive feelings on working memory and complex decision making among older adults (aged 63–85) was examined. Participants completed a computer administered card task in which participants could win money if they chose from “gain” decks and lose money if they chose from “loss” decks. Individuals in the positive-feeling condition chose better than neutral-feeling participants and earned more money overall. Participants in the positive-feeling condition also demonstrated improved working-memory capacity. These effects of positive-feeling induction have implications for affect theory, as well as, potentially, practical implications for people of all ages dealing with complex decisions.
A presentation theorem for continuous logic and metric abstract elementary classes

In recent years, model theory has widened its scope to include metric structures by considering real‐valued models whose underlying set is a complete metric space. We show that it is possible to carry out this work by giving presentation theorems that translate the two main frameworks (continuous first order logic and Metric Abstract Elementary Classes) into discrete settings (a nice fragment of Lω1,ω and Abstract Elementary Classes, respectively). We also translate various notions of classification theory.
Using lateral length measurements in GMTI convoy tracking

This contribution deals with tracking of convoys moving on ground by airborne GMTI radar. A technique based on generalized power estimators using multiple beams is used to estimate the lateral length component of an unresolved convoy. In combination with the conventional range measurement, the full length information can be obtained in case of a linear convoy. The main focus of this paper is the exploitation of this attribute information in order to improve the tracking process. The Bayes algorithm based on our earlier work is improved and incorporated into a JPDAF framework to deal with multiple targets. The processing of Doppler measurements is also included. Numerical results are presented based on a simulation scenario.
Visualisation of Left Ventricular Dysfunction in the Virtual Pathological Heart

While there has been significant progress in the treatment of ischemic heart failure, it remains a significant health and economic problem worldwide. In this paper, we present the challenges of modelling ischemic heart failure and introduce a user-friendly software system that will be a sub-set of the Virtual Pathological Heart environment which is currently being developed under the FP7 VPH2 project. This will provide patient-specific computational modelling and simulation of the human heart to assist the cardiologist and the cardiac surgeon in defining the severity and extent of disease in patients with post-ischemic Left Ventricular Dysfunction. The proposed system will provide visualisation tools for surgical assessment and planning: the registration and display of necrotic and hypo-kinetic regions; simulated surgical restoration (cutting and patching); and finally post-operative functional prediction (volume, shape and mitral valve regurgitation).