Miracle-dz/UniFAR-FTUs huggingface dataset:
Water quality in the River Clyde: a case study of additive and interaction models

Additive models are widely used to provide very flexible and effective descriptions of regression data where assumptions of linear relationships are too restrictive. However, these models usually assume independent errors and there are many applications where the data are correlated. This is often true in environmental settings and an application to water quality modelling in the River Clyde is described. Methods of fitting and analysing an additive model in this setting are discussed. An approach which fits an additive model in the usual way but incorporates the correlated error structure into the assessment of components is described. The methods are applied to the Clyde data to identify the factors which affect water quality, as well as spatial and temporal trends. Interaction terms, which allow the effects of explanatory variables to change smoothly with position down the river, are also explored. Particular emphasis is placed on approximate F tests to identify the most suitable models and the presence and nature of particular covariate effects. Copyright © 2007 John Wiley & Sons, Ltd.
Iron loss evaluation of AC filter inductor core in a PWM inverter

Iron loss of an AC filter inductor used in a PWM inverter is discussed based on a dynamic minor loop method developed by the authors. A distinctive feature of the dynamic minor loop method is that the instantaneous iron loss of the AC filter inductor can be measured during every switching period of the inverter, and the instantaneous iron loss distribution during one cycle of the output frequency can be produced using this data. The shape of the distribution changes with both the modulation method of the inverter and the load conditions, so that this method is suitable for characterization of the iron loss. Iron loss of the AC filter inductor can be categorized as two types; one type is high frequency loss, which is caused by the switching ripple current, and the other is low frequency loss caused by the low frequency output current. High frequency loss is usually much higher than low frequency loss; therefore, mainly the high frequency loss was evaluated in this study. The instantaneous iron loss of an AC filter inductor and the total loss under various conditions of the PWM inverter are measured, and the relationships between the output current and the iron loss, the DC-bus voltage and the iron loss, and the power factor and the iron loss are discussed.
How much information do software metrics contain?

Software metrics computation and presentation are considered an important feature of many software design and development tools. The System Grokking Technology developed by IBM research enables investigation, validation and evolution of complex software systems at the level of abstraction suitable for human comprehension. As part of our ongoing effort to improve the tool and offer more useful abstractions we considered adorning the presented information with software metrics. The difficulty in doing that is in selecting among the legions of metrics competing for both scarce screen space and for the architect's attention. In this paper, we describe a new criterion for evaluating the competing metrics based on a normalized version of Shannon's information theoretical content. We also give values of these in a large software corpus and for a large set of metrics. Based on our measurements and this criterion, we can recommend the presentation of two metrics: module centrality, as measured by a variant of Google's classical page ranking algorithm, and module size, as measured by Chidamber and Kemerer's WMC metric.
- 29 December 2012 , Dhaka , Bangladesh Performance Evaluation of 8-Transistor and 9-Transistor , 32-nm CNT-OPAMPs in Designing and Comparing Non-Inverting Amplifiers

In this paper, we have presented the design and characteristic performance evaluation of two different Carbon Nanotubebased Operational Amplifiers (CNT-OPAMPs) using a benchmark eight-transistor and a ninetransistor OPAMP model with single-walled Carbon Nanotube Field-Effect Transistors (SW-CNTFETs) as primary building-blocks for 32nm technology. Our simulation-based assessment of a non-inverting amplifier has shown that for 8T configuration, excepting the CNT-FET with n=1, the devices with n=3 and n=5 showed considerable improved performance in all parameters except the input resistance. For a 9T configuration, all the CNTFET based devices (n=1, n=3, and n=5) showed considerable improved performance than Sibased device in terms of Bandwidth,Output Resistance, Power Dissipation, and Gain-Bandwidth Product. The CNT-FET based device fell short just in terms of input resistance and phase margin. The DC Gain of both the Sibased as well as the CNT-FET based device was almost same. The results obtained suggest that the CNT-OPAMP has a promising potential for lowpower, high-speed applications in both analog and mixed-signal nanoelectronic circuits.
Leading Edge Review Interactome Networks and Human Disease

Marc Vidal,1,2,* Michael E. Cusick,1,2 and Albert-László Barabási1,3,4,* 1Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA 2Department of Genetics, Harvard Medical School, Boston, MA 02115, USA 3Center for Complex Network Research (CCNR) and Departments of Physics, Biology and Computer Science, Northeastern University, Boston, MA 02115, USA 4Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA *Correspondence: marc_vidal@dfci.harvard. edu (M.V.), alb@neu.edu (A.-L.B.) DOI 10.1016/j.cell. 2011.02. 016
MT Evaluation: Human-Like vs. Human Acceptable

We present a comparative study on Machine Translation Evaluation according to two different criteria: Human Likeness and Human Acceptability. We provide empirical evidence that there is a relationship between these two kinds of evaluation: Human Likeness implies Human Acceptability but the reverse is not true. From the point of view of automatic evaluation this implies that metrics based on Human Likeness are more reliable for system tuning. Our results also show that current evaluation metrics are not always able to distinguish between automatic and human translations. In order to improve the descriptive power of current metrics we propose the use of additional syntax-based metrics, and metric combinations inside the QARLA Framework.
WHAT IS COMPOUND STRESS ?

This paper investigates the implementation of stress in English noun-noun compounds. First, a perception experiment examines how listeners perceive prominence in compounds. After that, significant acoustic correlates of prominence are established. Finally, a cluster analysis is described that classifies compounds on the basis of their phonetic features and which is capable of separating different stress categories. The results demonstrate how gradient acoustic measurements and discrete phonological contrasts can be mapped onto each other.
PRELIMINARY AND INCOMPLETE : Please do not cite without permission Draft : 11 / 09 / 04 School Accountability and the Distribution of Student Achievement

This paper examines whether minimum competency school accountability systems, such as those created under No Child Left Behind, influence the distribution of student achievement. Because school ratings in these systems only incorporate students’ test scores via pass rates, this type of system increases incentives for schools to improve the performance of students who are on the margin of passing but does not increase short-run incentives for schools to improve other students’ performance. Using student-level, panel data from Texas during the 1990’s, I explicitly calculate schools’ short-run incentives to improve various students’ expected performance, and I find that schools do respond to these incentives. Students perform slightly better than expected when their test score is particularly important for their schools’ accountability rating. Also, students perform substantially better than expected when many of their classmates’ scores are important for the schools’ rating, and this is especially true for the lowest achieving students. This suggests that the distributional effects are more closely related to broad changes in instruction or resources than related to narrowly tailored attempts to improve the performance of specific students. If one of the primary goals is to create a sort of educational triage, in which students moderately below minimum grade-level skills are pushed up, then the No Child Left Behind type of rating system appears to be fairly effective. However, if accountability systems are not intended to induce schools to shift resources disproportionately towards certain types of students, then these systems should use test results to formulate school ratings that do not simply reflect the fraction of students achieving minimum competency. “Under the [No Child Left Behind] law, schools must test students annually in reading and math from third grade to eighth grade, and once in high school. Schools receiving federal antipoverty money must show that more students each year are passing standardized tests or face expensive and progressively more severe consequences. As long as students pass the exams, the federal law offers no rewards for raising the scores of high achievers, or punishment if their progress lags. ” (Schemo, New York Times, A1, March 2, 2004).
KPCA Spatio-temporal trajectory point cloud classifier for recognizing human actions in a CBVR system

We describe a content based video retrieval (CBVR) software system for identifying specific locations of a human action within a full length film, and retrieving similar video shots from a query. For this, we introduce the concept of a trajectory point cloud for classifying unique actions, encoded in a spatio-temporal covariant eigenspace, where each point is characterized by its spatial location, local Frenet-Serret vector basis, time averaged curvature and torsion and the mean osculating hyperplane. Since each action can be distinguished by their unique trajectories within this space, the trajectory point cloud is used to define an adaptive distance metric for classifying queries against stored actions. Depending upon the distance to other trajectories, the distance metric uses either large scale structure of the trajectory point cloud, such as the mean distance between cloud centroids or the difference in hyperplane orientation, or small structure such as the time averaged curvature and torsion, to classify individual points in a fuzzy-KNN. Our system can function in real-time and has an accuracy greater than 93% for multiple action recognition within video repositories. We demonstrate the use of our CBVR system in two situations: by locating specific frame positions of trained actions in two full featured films, and video shot retrieval from a database with a web search application.
Review on Fractal Image Compression based on Fast DCT Algorithm

Fractal image compressions is a lossy compression technique for digital images. It is based on the assumptions that the image redundancies can be efficiently exploited by means of block self-affine transformations . Unlike other compression techniques it considers the interrelations between local (range blocks) and global (domain blocks) data. Use of contractive transform on the space of images encompasses a wide variety of coding scheme. However, the high computational complexity of fractal image encoding greatly restricts its application. This review gives a study of different speed ups using DCT to reduce the searching time . Index terms Iterated function system, Discrete cosine transform, Self similarity, contractive mapping,
Universal Potential Model in Tied and Separated Double-Gate MOSFETs With Consideration of Symmetric and Asymmetric Structure

A universal compact potential model for all types of double-gate MOSFETs is presented. An analytical closed-form solution to a 2D Poisson's equation is obtained with the approximation that a vertical channel potential distribution is a cubic function of position. As a result, an analytical equation for the threshold voltage is derived from the proposed potential model. Different gate work functions and independent gate biases for front and back gates are considered, and the proposed model is found to be valid for an arbitrary double-gate structure: a symmetric versus asymmetric double gate and a tied versus separated double-gate structure. The threshold voltage behaviors for double-gate MOSFETs are investigated for various device dimensions. The back-gate effects of the separated double gate are also investigated for various silicon channel thicknesses and gate oxide thicknesses. Last, a process-induced threshold voltage fluctuation is estimated for symmetric and asymmetric separated double-gate MOSFETs. The analytical solution of the threshold voltages is verified by a comparison with simulation results in terms of the gate length, the silicon thickness, and the gate oxide thickness. A good agreement between two sets of results is obtained.
Abstract only: power and energy-aware processor scheduling

Power consumption is a critical consideration in high computing systems. We propose a novel job scheduler that optimizes power and energy consumed by clusters when running parallel benchmarks with minimal impact on performance. We construct accurate models for estimating power consumption. These models are based on measurements of power consumption on benchmarks with different characteristics and on systems with processors using different micro-architectures. We show the power estimation models achieve less than 2% error versus actual measurements. We show a job scheduler can be enhanced to make it 'power-aware' and to optimize power consumption of jobs with similar performance characteristics. The enhanced scheduler can estimate the power consumed by a particular job using the power estimation model, configure the nodes in the cluster via suitably adjusting processor frequency on each of the nodes to maximize performance, minimize power, or minimize energy with a predictable impact on power, energy and performance.
Assessing ground-water vulnerability to contamination: Providing scientifically defensible information for decision makers

Throughout the United States increasing demands for safe drinking water and requirements to maintain healthy ecosystems are leading policy makers to ask complex social and scientific questions about how to assess and manage our water resources. This challenge becomes particularly difficult as policy and management objectives require scientific assessments of the potential for ground-water resources to become contaminated from anthropogenic, as well as natural sources of contamination. Assessments of the vulnerability of ground water to contamination range in scope and complexity from simple, qualitative, and relatively inexpensive approaches to rigorous, quantitative, and costly assessments. Tradeoffs must be carefully considered among the competing influences of the cost of an assessment, the scientific defensibility, and the amount of acceptable uncertainty in meeting the objectives of the water-resource decision maker.
Real-Time Shear Wave versus Transient Elastography for Predicting Fibrosis: Applicability, and Impact of Inflammation and Steatosis. A Non-Invasive Comparison

Background and Aims Real-time shear wave elastography (2D-SWE) is a two-dimensional transient elastography and a competitor as a biomarker of liver fibrosis in comparison with the standard reference transient elastography by M probe (TE-M). The aims were to compare several criteria of applicability, and to assess inflammation and steatosis impact on elasticity values, two unmet needs. Methods We took FibroTest as the fibrosis reference and ActiTest and SteatoTest as quantitative estimates of inflammation and steatosis. After standardization of estimates, analyses used curve fitting, quantitative Lin concordance coefficient [LCC], and multivariate logistic regression. Results A total of 2,251 consecutive patients were included. We validated the predetermined 0.2 kPa cut-off as a too low minimal elasticity value identifying not-reliable 2D-SWE results (LCC with FibroTest = 0.0281[-0.119;0.175]. Other criteria, elasticity CV, body mass index and depth of measures were not sufficiently discriminant. The applicability of 2D-SWE (95%CI) 89.6%(88.2–90.8), was significantly higher than that of TE, 85.6%(84.0–87.0; P<0.0001). In patients with non-advanced fibrosis (METAVIR F0F1F2), elasticity values estimated by 2D-SWE was less impacted by inflammation and steatosis than elasticity value estimated by TE-M: LCC (95%CI) 0.039 (0.021;0.058) vs 0.090 (0.068;0.112;P<0.01) and 0.105 (0.068;0.141) vs 0.192 (0.153;0.230; P<0.01) respectively. The three analyses methods gave similar results. Conclusions Elasticity results including very low minimal signal in the region of interest should be considered not reliable. 2D-SWE had a higher applicability than TE, the reference elastography, with less impact of inflammation and steatosis especially in patients with non-advanced fibrosis, as presumed by blood tests. Trial Registration ClinicalTrials.gov NCT01927133
Diversity-and-Multiplexing Tradeoff of Superposition Coding Relaying Strategy without Channel State Feedback

Superposition coding relaying (SC-relaying) has the merit of high throughput. At the same time, the investigation of the diversity-multiplexing tradeoff (DMT) is also particularly useful for the design and analysis of cooperative relaying strategy. In this work, we consider a two-level rate SC-relaying strategy without the channel state feedback under short term power constraint. For the SC-relaying strategy, the optimizing DMT is investigated as well as its optimizing close-form explicit solution.
Matrix quadratic convex combination for stability of linear systems with time-varying delay via new augmented Lyapunov functional

The paper addresses the delay-dependent stability problem for linear systems with time-varying delay. Novel delay-dependent stability criteria in terms of linear matrix inequalities for systems with state time-varying delay are derived by the newly proposed augmented Lyapunov-Krasovski (L-K) functional. A matrix-type quadratic convex combination approach is introduced to prove the negative definiteness of the derivative of the L-K functional along with the trajectory of the delayed system. Different from previous results by using the first order convex combination, our derivation applies the idea of second order convex combination, and the property of quadratic convex function without resorting to the Jensen's inequality.
Acetylcholine Encodes Long-Lasting Presynaptic Plasticity at Glutamatergic Synapses in the Dorsal Striatum after Repeated Amphetamine Exposure

Locomotion and cue-dependent behaviors are modified through corticostriatal signaling whereby short-term increases in dopamine availability can provoke persistent changes in glutamate release that contribute to neuropsychiatric disorders, including Parkinson's disease and drug dependence. We found that withdrawal of mice from repeated amphetamine treatment caused a chronic presynaptic depression (CPD) in glutamate release that was most pronounced in corticostriatal terminals with a low probability of release and lasted >50 d in treated mice. An amphetamine challenge reversed CPD via a dopamine D1-receptor-dependent paradoxical presynaptic potentiation (PPP) that increased corticostriatal activity in direct pathway medium spiny neurons. This PPP was correlated with locomotor responses after a drug challenge, suggesting that it may underlie the sensitization process. Experiments in brain slices and in vivo indicated that dopamine regulation of acetylcholine release from tonically active interneurons contributes to CPD, PPP, locomotor sensitization, and cognitive ability. Therefore, a chronic decrease in corticostriatal activity during withdrawal is regulated around a new physiological range by tonically active interneurons and returns to normal upon reexposure to amphetamine, suggesting that this paradoxical return of striatal activity to a more stable, normalized state may represent an additional source of drug motivation during abstinence.
On Low-Complexity Network Coding for Data Collection in Wireless Sensor Networks

— In this paper, we investigate the possibilities of developing and applying reduced complexity network coding schemes. The proposed schemes are motivated by recent developments in the field of sparse-graph erasure codes and the iterative decoding algorithms. Performances of low-complexity network coding schemes deployed for the purpose of data collection in wireless sensor networks are analyzed by means of the simulation experiments.
Structure Based In Silico Analysis of Quinolone Resistance in Clinical Isolates of Salmonella Typhi from India

Enteric fever is a major cause of morbidity in several parts of the Indian subcontinent. The treatment for typhoid fever majorly includes the fluoroquinolone group of antibiotics. Excessive and indiscriminate use of these antibiotics has led to development of acquired resistance in the causative organism Salmonella Typhi. The resistance towards fluoroquinolones is associated with mutations in the target gene of DNA Gyrase. We have estimated the Minimum Inhibitory Concentration (MIC) of commonly used fluoroquinolone representatives from three generations, ciprofloxacin, ofloxacin, levofloxacin and moxifloxacin, for 100 clinical isolates of Salmonella Typhi from patients in the Indian subcontinent. The MICs have been found to be in the range of 0.032 to 8 μg/ml. The gene encoding DNA Gyrase was subsequently sequenced and point mutations were observed in DNA Gyrase in the quinolone resistance determining region comprising Ser83Phe/Tyr and Asp87Tyr/Gly. The binding ability of these four fluoroquinolones in the quinolone binding pocket of wild type as well as mutant DNA Gyrase was computationally analyzed by molecular docking to assess their differential binding behaviour. This study has revealed that mutations in DNA Gyrase alter the characteristics of the binding pocket resulting in the loss of crucial molecular interactions and consequently decrease the binding affinity of fluoroquinolones with the target protein. The present study assists in understanding the underlying molecular and structural mechanism for decreased fluoroquinolone susceptibility in clinical isolates as a consequence of mutations in DNA Gyrase.
The Strategic Role of Information Systems in Supporting Sustainability

As sustainability becomes more mainstream, companies face increasing demands to address environmental and social factors as part of their daily operations. The result is that companies need to attend to an ever increasing set of regulations that vary by jurisdiction and often overlap along with demands for more transparency and reporting on how they are meeting these requirements. Delivering on these commitments, which is a first step towards embedding sustainability into the fabric of the company, comes with a high cognitive load. It is natural under these circumstances to turn to information systems (IS) to help manage the task. Our study examines how one large integrated energy company is attempting to use IS to support these foundational sustainability efforts and asks to what extent IS can successfully meet the challenge.