Miracle-dz/UniFAR-FTUs huggingface dataset:
Scripting graphical applications by demonstration

Writing scripts (often called “macros”) can be helpful for automating repetitive tasks. Scripting facilities for text editors like Emacs and Microsoft Word have been widely used and available. However, for graphical applications, scripting has been tried many times but has never been successful. This is mainly due to the data description problem of determining how to generalize the particular objects selected at demonstration time. Previous systems have mostly tried to solve this using inferencing, but this has a number of problems, including guessing wrong and providing appropriate feedback and control to users. Therefore, the Topaz framework does not use inferencing and instead allows the user to specify how the appropriate objects should be found. This is achieved by recording changes to which objects are selected and searches for objects, so that scripts can be written with respect to the selected object, in the same way as Emacs keyboard macros. Furthermore, all values can be explicitly generalized in a number of ways, and scripts can be invoked as a result of other commands. By leveraging off of Amulet’s command object architecture, programmers get these capabilities for free in their applications. The result is that much more sophisticated scripting capabilities available in applications with no extra work for programmers.
The fragment structure of a putative HsdR subunit of a type I restriction enzyme from Vibrio vulnificus YJ016: implications for DNA restriction and translocation activity

Among four types of bacterial restriction enzymes that cleave a foreign DNA depending on its methylation status, type I enzymes composed of three subunits are interesting because of their unique DNA cleavage and translocation mechanisms performed by the restriction subunit (HsdR). The elucidated N-terminal fragment structure of a putative HsdR subunit from Vibrio vulnificus YJ016 reveals three globular domains. The nucleolytic core within an N-terminal nuclease domain (NTD) is composed of one basic and three acidic residues, which include a metal-binding site. An ATP hydrolase (ATPase) site at the interface of two RecA-like domains (RDs) is located close to the probable DNA-binding site for translocation, which is far from the NTD nucleolytic core. Comparison of relative domain arrangements with other functionally related ATP and/or DNA complex structures suggests a possible translocation and restriction mechanism of the HsdR subunit. Furthermore, careful analysis of its sequence and structure implies that a linker helix connecting two RDs and an extended region within the nuclease domain may play a central role in switching the DNA translocation into the restriction activity.
A Kernel-Based Two-Class Classifier for Imbalanced Data Sets

Many kernel classifier construction algorithms adopt classification accuracy as performance metrics in model evaluation. Moreover, equal weighting is often applied to each data sample in parameter estimation. These modeling practices often become problematic if the data sets are imbalanced. We present a kernel classifier construction algorithm using orthogonal forward selection (OFS) in order to optimize the model generalization for imbalanced two-class data sets. This kernel classifier identification algorithm is based on a new regularized orthogonal weighted least squares (ROWLS) estimator and the model selection criterion of maximal leave-one-out area under curve (LOO-AUC) of the receiver operating characteristics (ROCs). It is shown that, owing to the orthogonalization procedure, the LOO-AUC can be calculated via an analytic formula based on the new regularized orthogonal weighted least squares parameter estimator, without actually splitting the estimation data set. The proposed algorithm can achieve minimal computational expense via a set of forward recursive updating formula in searching model terms with maximal incremental LOO-AUC value. Numerical examples are used to demonstrate the efficacy of the algorithm
STABILITY OF TWO TIME-INTEGRATORS FOR THE ALIEV-PANFILOV SYSTEM

We propose a second-order accurate method for computing the solutions to the Aliev-Panfilov model of cardiac excitation. This two-variable reaction-diffusion system is due to its simplicity a popular choice for model- ing important problems in electrocardiology; e.g. cardiac arrhythmias. The solutions might be very complicated in structure, and hence highly resolved numerical simulations are called for to capture the fine details. Usually the for- ward Euler time-integrator is applied in these computations; it is very simple to implement and can be effective for coarse grids. For fine-scale simulations, however, the forward Euler method suffers from a severe time-step restriction, rendering it less efficient for simulations where high resolution and accuracy are important. We analyze the stability of the proposed second-order method and the forward Euler scheme when applied to the Aliev-Panfilov model. Compared to the Eu- ler method the suggested scheme has a much weaker time-step restriction, and promises to be more efficient for computations on finer meshes.
Real-Time Impulse Noise Removal from MR Images for Radiosurgery Applications

In the recent years image processing techniques are used as a tool to improve detection and diagnostic capabilities in the medical applications. Medical applications have been so much affected by these techniques which some of them are embedded in medical instruments such as MRI, CT and other medical devices. Among these techniques, medical image enhancement algorithms play an essential role in removal of the noise which can be produced by medical instruments and during image transfer. It has been proved that impulse noise is a major type of noise, which is produced during medical operations, such as MRI, CT, and angiography, by their image capturing devices. An embeddable hardware module which is able to denoise medical images before and during surgical operations could be very helpful. In this paper an accurate algorithm is proposed for real-time removal of impulse noise in medical images. All image blocks are divided into three categories of edge, smooth, and disordered areas. A different reconstruction method is applied to each category of blocks for the purpose of noise removal. The proposed method is tested on MR images. Simulation results show acceptable denoising accuracy for various levels of noise. Also an FPAG implementation of our denoising algorithm shows acceptable hardware resource utilization. Hence, the algorithm is suitable for embedding in medical hardware instruments such as radiosurgery devices.
A Classic Near-Infrared Probe Indocyanine Green for Detecting Singlet Oxygen

The revelation of mechanisms of photodynamic therapy (PDT) at the cellular level as well as singlet oxygen (1O2) as a second messengers requires the quantification of intracellular 1O2. To detect singlet oxygen, directly measuring the phosphorescence emitted from 1O2 at 1270 nm is simple but limited for the low quantum yield and intrinsic efficiency of 1O2 emission. Another method is chemically trapping 1O2 and measuring fluorescence, absorption and Electron Spin Resonance (ESR). In this paper, we used indocyanine green (ICG), the only near-infrared (NIR) probe approved by the Food and Drug Administration (FDA), to detect 1O2 in vitro. Once it reacts with 1O2, ICG is decomposed and its UV absorption at 780 nm decreases with the laser irradiation. Our data demonstrated that ICG could be more sensitive and accurate than Singlet Oxygen Sensor Green reagent® (SOSG, a commercialized fluorescence probe) in vitro, moreover, ICG functioned with Eosin Y while SOSG failed. Thus, ICG would reasonably provide the possibility to sense 1O2 in vitro, with high sensitivity, selectivity and suitability to most photosensitizers.
Increasing Class-Component Testability

Testability has many effects on software. In general, increasing testability makes detecting faults easier. However, increasing testability of third party software components is difficult because the source is usually not available. This paper introduces a method to increase component testability. This method helps a user test when the component is reused during integration. First, we analyze a component to gather definition and use information about method and class variables. Then, this information is used to increase component testability to support component testing. Increased testability helps to detect errors, and helps testers observe state variables and generate inputs for testing. This paper uses an example to report the effort (in terms of test cases) and effectiveness (in terms of killed mutants).
Phosphoribosyl transferase activity in normal subjects, gout patients, and children with mental retardation

Activity of hypoxanthine-guanine and adenine phosphoribosyl transferase enzymes has been assayed in erythrocytes from 10 normal adults, 37 subjects with gout, and 21 mentally retarded children with high and normal urinary uric acid:creatinine ratios. These were compared with one case of known HGPRTase deficiency. Apart from the last subject, no cases of HGPRTase deficiency were found.
The Construction of BOPPPS Teaching Model in The Course of Inorganic Chemistry Course

Through the teaching reform of BOPPPS model in inorganic chemistry teaching, the status of students as the main body is fully embodied, the role of the teacher's guidance is well realized, and the students' cognition, emotion and motivation are stimulated. A climate of teaching atmosphere full of democracy, harmony, joy and intelligence is created to promote students' active participation and create a good premise for students' initiative development.
Amplified Distributed Denial of Service Attack in Software Defined Networking

Software Defined Networking (SDN) is an alternative networking paradigm that provides flexible network management through the separation between data plane and control plane functionalities. This separation results in extensive communication between control and data plane, which can result in a severe bottleneck for the whole network, under high traffic conditions. Moreover, researchers shown that an adversary can exploit this bottleneck to mount a powerful Denial of Service attack on the control plane, known as Control Plane Saturation Attack (CPSA). In this paper, we provide a thorough analysis of the CPSA, and in particular we show how it can be amplified by long forwarding paths in an SDN network. We prove the effectiveness of the attack through extensive testing using OpenFlow, the most widely adopted control-data plane communication protocol for SDN. Our evaluation shows that, when the forwarding path length in increased by 5 times, the attacker can leverage a 55% decrease in the attack rate required to incapacitate the network.
Age effects on diffusion tensor magnetic resonance imaging tractography measures of frontal cortex connections in schizophrenia

Diffusion tensor magnetic resonance imaging (DT‐MRI) has previously been used to investigate white matter tracts in schizophrenia, with inconsistent results. The aim of the study was to use a novel method for tract‐specific measurements of fronto‐temporal fasciculi in early‐onset schizophrenia. We hypothesized that by making tract‐specific measurements, clear diffusion abnormalities would be revealed in specific fasciculi in schizophrenia. Measurements of diffusion anisotropy and mean diffusivity were localized within fronto‐temporal fasciculi by forming 3‐D reconstructions of the cingulum, uncinate, superior longitudinal, and inferior fronto‐occipital fasciculi using diffusion tensor tractography. We were limited in our ability to test our hypothesis by the important and surprising finding that age affected DT‐MRI‐based measures in schizophrenia patients in a different way from comparison subjects, most notably in the left superior longitudinal fasciculus. The youngest schizophrenia patients that we studied had lower diffusion anisotropy than age‐matched comparison subjects, but this difference diminished with increasing age. The main conclusion of this study was that direct comparisons of absolute DT‐MRI‐based measures between individuals with schizophrenia and comparison subjects may be problematic and misleading because of underlying age‐related differences in brain maturation between groups. Hum Brain Mapp, 2005. © 2005 Wiley‐Liss, Inc.
Lift-off dynamics in a simple jumping robot

We study vertical jumping in a simple robot comprising an actuated mass-spring arrangement. The actuator frequency and phase are systematically varied to find optimal performance. Optimal jumps occur above and below (but not at) the robot's resonant frequency f(0). Two distinct jumping modes emerge: a simple jump, which is optimal above ff(0), is achievable with a squat maneuver, and a peculiar stutter jump, which is optimal below f(0), is generated with a countermovement. A simple dynamical model reveals how optimal lift-off results from nonresonant transient dynamics.
Learning Active Learning from Data

In this paper, we suggest a novel data-driven approach to active learning (AL). The key idea is to train a regressor that predicts the expected error reduction for a candidate sample in a particular learning state. By formulating the query selection procedure as a regression problem we are not restricted to working with existing AL heuristics; instead, we learn strategies based on experience from previous AL outcomes. We show that a strategy can be learnt either from simple synthetic 2D datasets or from a subset of domain-specific data. Our method yields strategies that work well on real data from a wide range of domains.
Protein fluxes along the filopodium as a framework for understanding the growth-retraction dynamics

We present a picture of filopodial growth and retraction from physics perspective, where we emphasize the significance of the role played by protein fluxes due to spatially extended nature of the filopodium. We review a series of works, which used stochastic simulations and mean field analytical modeling to find the concentration profile of G-actin inside a filopodium, which, in turn, determines the stationary filopodial length. In addition to extensively reviewing the prior works, we also report some new results on the role of active transport in regulating the length of filopodia. We model a filopodium where delivery of actin monomers towards the tip can occur both through passive diffusion and active transport by myosin motors. We found that the concentration profile of G-actin along the filopodium is rather non-trivial, containing a narrow minimum near the base followed by a broad maximum. For efficient enough actin transport, this non-monotonous shape is expected to occur under a broad set of conditions. We also raise the issue of slow approach to the stationary length and the possibility of multiple steady state solutions.
New Unification Matching Scheme for efficient information retrieval using Genetic Algorithm

This article presents a new Unification Matching Scheme (UMS) for information retrieval using the genetic algorithm. The selection of appropriate matching functions contributes to the performance of the information retrieval system. The proposed UMS executes the Unification function on three classical matching functions for different threshold values. The main objective is to utilize all the base functions to increase the relevancy of a users query with the data objects. The best results from each matching function define the new generation on, which the other matching functions are applied. The results from each generation are optimized using the Genetic Algorithm. The working of UMS is compared with individual classical matching functions. A significant improvement is seen in the experimental results in terms of precision and recall. The performance increased/increases gradually, in each generation thereby, producing the relevant results.
Comparative Ecology, Resource Utilization and Niche Segregation among Gekkonid Lizards in the Southern Kalahari

Research was supported by American Philosophical Society grant 7113, by the Research Foundation of the State University of New York grant 20-7331-A and by funds from the Shenandoah Natural History Association. I am very grateful to Linda Jaeger and William Gergits for help in the field studies and to L. Jaeger for the computer programming involved. Douglas Fraser, W. Gergits and Patricia Nanartowich kindly criticized the manuscript. I thank E. Raymond Schaffner and Dennis Carter, of the National Park Service, for permission to work in Shenandoah National Park.
Obesity, metabolic syndrome, and coronary atherosclerosis.

The relationship between obesity and coronary atherosclerosis (and coronary heart disease [CHD]) has been a subject of some dispute for many years. Data from early investigations suggested that obesity is not an important contributing cause of coronary atherosclerosis and CHD. For example, results of the Seven Countries Study1 revealed little correlation between body weight and incidence of CHD. Moreover, in the massive autopsy study called “The Geographic Pathology of Atherosclerosis,” edited by Henry C. McGill, Jr,2 the relationship between body weight and atherosclerosis was weak at best. This study included a detailed examination of arteries from a large number of autopsies carried out in New Orleans, Sao Paulo, Puerto Rico, Lima, and Santiago; by and large, the results uncovered no association between extent of arterial fatty streaks or raised atherosclerotic lesions in either the coronary arteries or the aorta for any measure of body weight, height, or obesity.3 It was noted that this study had the advantage of including several groups that differed greatly in geographic origin, ethnicity, CHD morbidity, and severity of atherosclerosis. Although the authors3 conceded that obesity is a factor contributing to risk factors for CHD such as hypertension, they surmised that the relationship between obesity and other risk factors is too weak for obesity to have a detectable effect on the severity of atherosclerosis. See p 2712 In spite of these earlier negative findings, the Framingham Heart Study in the United States has consistently shown that increasing degrees of obesity are accompanied by greater rates of CHD.4,5⇓ Even so, multivariate analysis of Framingham data strongly suggests that most of the relationship between body weight and CHD risk is mediated through the standard, major risk factors, ie, blood pressure, total cholesterol, HDL cholesterol, and diabetes.6 Their own data led Framingham …
Solutions for 3D self-reconfiguration in a modular robotic system: implementation and motion planning

In this manuscript, we discuss new solutions for mechanical design and motion planning for a class of 3D modular self- reconfigurable robotic system, namely I-Cubes. This system is a bipartite collection of active links that provide motions for self-reconfiguration, and cubes acting as connection points. The links are three degree of freedom manipulators that can attach to and detach from the cube faces. The cubes can be positioned and oriented using the links. These capabilities enable the system to change its shape and perform locomotion tasks over difficult terrain. This paper describes the scaled down version of the system previously described in and details the new design and manufacturing approaches. Initially designed algorithms for motion planning of I-Cubes are improved to provide better results. Results of our tests are given and issues related to motion planning are discussed. The user interfaces designed for the control of the system and algorithm evaluation is also described.
A Possibility-Based Robust Optimal Design Algorithm in Preliminary Design Stage of Electromagnetic Devices

In the early design stage of an electromagnetic device, sufficient information on uncertainties of design variables is not available. Therefore, a reliable optimal design cannot be achieved by the conventional reliability analysis, in which the probabilistic method is applied. This paper, considering the insufficient uncertainty data, proposes a possibility-based optimal design algorithm to get a robust and reliable optimal design of electromagnetic devices. The suggested algorithm adopts a possibility analysis utilizing the fuzzy set theory. In addition, to mitigate the expensive performance analysis during possibility analysis, the design sensitivity analysis is employed to construct a surrogate model. Finally, the developed algorithm is validated through applications to several examples.
Predictors of Adherence to Copaxone Therapy in Individuals with Relapsing‐Remitting Multiple Sclerosis*

&NA; The purpose of this study was to evaluate psychological, biophysical, and sociodemographic variables as predictors of adherence to glatiramer acetate (Copaxone®) therapy in individuals with relapsing‐remitting multiple sclerosis (MS). Because Copaxone is a daily subcutaneous injection, individuals with MS are challenged by the daily routine of preparation and administration of this medication. Despite the challenges, some individuals with MS adhere to treatment with injectable medications with little or no difficulty, while others struggle to adhere to, and soon abandon, the daily task. It is important to identify predictors of adherence to Copaxone therapy so those at risk can be identified early and provided with individualized support at the onset of therapy. Potential participants were identified from the Consortium of Multiple Sclerosis Centers North American Research Committee on Multiple Sclerosis Patient Registry database (n = 600) and from the Shared SolutionsTM MS patient support database (n = 600). Individuals who had taken or stopped taking Copaxone were specifically selected. Those taking multiple immunomodulating drugs or not able to complete the data collection instruments were excluded. Booklets containing four instruments (MS Self‐Efficacy Control and Function Subscales, Rosenberg Self‐Esteem Scale, Herth Hope Index [HHI], and Performance Scale) and sociodemographic data sheets were mailed to 1,200 individuals. Of the 594 who completed and returned booklets, 341 individuals had relapsing‐remitting MS and met the inclusion criteria. There were 225 individuals in the adherent group and 116 in the nonadherent group. Logistic regression analysis revealed four significant predictors of adherence: self‐efficacy (control), hope, perception that the doctor was the most supportive of the individual taking Copaxone, and no previous use of other immunomodulators. The higher the score on the MS Self‐Efficacy Control Subscale and HHI, the more likely the individual will adhere to Copaxone therapy. The MS Self‐Efficacy Control Subscale and HHI show promise of being useful predictors of adherence. Further testing is recommended. Physician support should be conveyed to all individuals starting and maintaining Copaxone therapy for MS. Creator support needs to be provided to those who have previously taken immunomodulating drugs.
Distributed Data Location in a Dynamic Network

Modern networking applications replicate data and services widely, leading to a need for location-independent routing -- the ability to route queries directly to objects using names that are independent of the objects'' physical locations. Two important properties of a routing infrastructure are routing locality and rapid adaptation to arriving and departing nodes. We show how these two properties can be achieved with an efficient solution to the nearest-neighbor problem. We present a new distributed algorithm that can solve the nearest-neighbor problem for a restricted metric space. We describe our solution in the context of Tapestry, an overlay network infrastructure that employs techniques proposed by Plaxton, Rajaraman, and Richa.