Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated detection of local normalization areas for ictal-interictal subtraction brain SPECT.

UNLABELLED Whole-brain activity is often chosen to quantitatively normalize peri-ictal and interictal SPECT scans before their subtraction. This use is not justified, because significant and extended modification of the cerebral blood flow can occur during a seizure. We validated and compared 2 automatic methods able to determine the optimal reference region, using simulation and clinical data. METHODS In the first method, the selected reference region is the intersection of peri-ictal-interictal areas with no significantly different z values. The other method relies on a 3-dimensional iterative voxel aggregation. The increase of the selected volume is stopped by using 2 different variance tests (Levene and SE). These algorithms were tested on 39 epileptic patients and were validated using 1 interictal and 10 peri-ictal scans simulated from the mean image of 22 healthy subjects. RESULTS In the patient studies, the mean relative activity of the selected regions, compared with whole-brain activity (classic normalization), was 122.6%. Their average relative size (compared with the size of the whole brain) was 33.2% for the z map method, 22.8% for the SE test, and 11.8% for the Levene test. After application of our automatic processes, subtraction of the simulated images revealed a recovery of abnormal regions up to 45% larger than the region obtained with classic normalization. CONCLUSION These results illustrate the role of normalization on the subtracted peri-ictal and interictal images. Our methods are automatic and objective and give good results on various simulated images. The z map construction is worth considering because it is simple, selects large parts of the brain, and requires little computation time.
The Effect of NeuroMuscular Electrical Stimulation on Quadriceps Strength and Knee Function in Professional Soccer Players: Return to Sport after ACL Reconstruction

The aim of this study was to assess the clinical efficacy and safety of NMES program applied in male soccer players (after ACL reconstruction) on the quadriceps muscle. The 80 participants (NMES = 40, control = 40) received an exercise program, including three sessions weekly. The individuals in NMES group additionally received neuromuscular electrical stimulation procedures on both right and left quadriceps (biphasic symmetric rectangular pulses, frequency of impulses: 2500 Hz, and train of pulses frequency: 50 Hz) three times daily (3 hours of break between treatments), 3 days a week, for one month. The tensometry, muscle circumference, and goniometry pendulum test (follow-up after 1 and 3 months) were applied. The results of this study show that NMES (in presented parameters in experiment) is useful for strengthening the quadriceps muscle in soccer athletes. There is an evidence of the benefit of the NMES in restoring quadriceps muscle mass and strength of soccer players. In our study the neuromuscular electrical stimulation appeared to be safe for biomechanics of knee joint. The pathological changes in knee function were not observed. This trial is registered with Australian and New Zealand Clinical Trials Registry ACTRN12613001168741.
Isolation of adipose and bone marrow mesenchymal stem cells using CD29 and CD90 modifies their capacity for osteogenic and adipogenic differentiation

Mesenchymal stem cells isolated from rats are frequently used for tissue engineering research. However, considerable differences have been identified between rat mesenchymal stem cells and those derived from humans, and no defined panel of markers currently exists for the isolation of these cells. The aim of this study was to examine the effects of cell sorting for CD29+/CD90+ cells from rat adipose and bone marrow tissues on their differentiation and expression of stem cell–associated genes. Flow cytometry showed 66% and 78% CD29+/CD90+ positivity within passage 1 of adipose and bone marrow cultures, respectively. CD29+/CD90+ cells showed a reduction in both osteogenic and adipogenic differentiation when compared with unsorted cells, as determined by alizarin red and Oil Red-O staining, respectively. These findings could not entirely be explained by fluorescence-activated cell sorting–induced cell injury as sort recovery was only modestly affected in adipose-derived cells. Maintaining cells in fluorescence-activated cell sorting buffer did not affect adipose-derived cell viability, but a significant (p < 0.05) reduction was found in bone marrow–derived cell viability. Additionally, CD29+/CD90+ selection was associated with a significant decrease in the expression of Lin28, Sox2, Nanog and CD73 in adipose-derived cell cultures, whereas differences in stem cell–associated gene expression were not observed in sorted bone marrow–derived cell cultures. In summary, this study demonstrated that fluorescence-activated cell sorting had differential effects on adipose-derived cells and bone marrow–derived cells, and both CD29+/CD90+ cells displayed a significantly reduced capacity for osteogenic/adipogenic differentiation. In conclusion, we identify that maintaining heterogeneity within the mesenchymal stem cell population may be important for optimal differentiation.
4P: fast computing of population genetics statistics from large DNA polymorphism panels

Massive DNA sequencing has significantly increased the amount of data available for population genetics and molecular ecology studies. However, the parallel computation of simple statistics within and between populations from large panels of polymorphic sites is not yet available, making the exploratory analyses of a set or subset of data a very laborious task. Here, we present 4P (parallel processing of polymorphism panels), a stand-alone software program for the rapid computation of genetic variation statistics (including the joint frequency spectrum) from millions of DNA variants in multiple individuals and multiple populations. It handles a standard input file format commonly used to store DNA variation from empirical or simulation experiments. The computational performance of 4P was evaluated using large SNP (single nucleotide polymorphism) datasets from human genomes or obtained by simulations. 4P was faster or much faster than other comparable programs, and the impact of parallel computing using multicore computers or servers was evident. 4P is a useful tool for biologists who need a simple and rapid computer program to run exploratory population genetics analyses in large panels of genomic data. It is also particularly suitable to analyze multiple data sets produced in simulation studies. Unix, Windows, and MacOs versions are provided, as well as the source code for easier pipeline implementations.
Thermal transport in the Falicov-Kimball model

We prove the Jonson-Mahan theorem for the thermopower of the Falicov-Kimball model by solving explicitly for the correlation functions in the large dimensional limit. We prove a similar result for the thermal conductivity. We separate the results for thermal transport into the pieces of the heat current that arise from the kinetic energy and those that arise from the potential energy. Our method of proof is specific to the Falicov-Kimball model, but illustrates the near cancellations between the kinetic-energy and potential-energy pieces of the heat current implied by the Jonson-Mahan theorem. Primary: 72.15. Jf; 72.20. Pa, 71.20. +h, 71.10. Fd I. INTRODUCTION The Jonson-Mahan 1,2 theorem shows that there is a simple relation between the transport coefficient for the electrical conductivity and that needed for the thermopower. The relation is that the integral for the L12 coefficient has an extra power of frequency in the integrand than the L11 coefficient. This result has been known for many years 3 for a noninteracting system— the Jonson-Mahan theorem generalizes this result for a wide class of many-body systems (including the FalicovKimball model, the static Holstein model, and the periodic Anderson model, but not including the Hubbard model or quantum Holstein model). We use the exact solution of the Falicov-Kimball model in the large-dimensional limit to provide an alternate derivation of the Jonson-Mahan theorem by explicitly evaluating all relevant correlation functions needed for the thermal transport. Our exact analysis also allows us to separate the contributions to thermal transport that arise from the kinetic energy and the potential energy pieces of the heat current. These results provide an interesting interpretation of thermal transport in correlated systems. In Section II we develop the formalism for deriving the dc conductivity, the thermopower and the thermal conductivity. We derive exact results for the relevant correlation functions and use them to prove the Jonson-Mahan theorem and its generalization to the thermal conductivity. In Section III we provide numerical results for the thermal transport illustrating the different contributions to the thermal coefficients for a number of illustrative cases. Conclusions are presented in Section IV.
A new generation of ergonomic exoskeletons - The high-performance X-Arm-2 for space robotics telepresence

This paper introduces the mechatronic design and a first performance analysis of a new haptic exoskeleton, the X-Arm-2. The X-Arm-2 is a fully actuated force-reflecting human arm exoskeleton that is based on our previously proposed approach to ergonomic and human-centered exoskeleton design [1] [2]. The X-Arm-2 is a highly power-dense impedance-type haptic device that (1) can interact with natural human arm movement of varying operators without requiring adjustments and creating constraint forces, (2) provides crisp force-feedback through high actuator bandwidth, low residual friction and good joint torque sensor resolution, (3) has a low total mass of only 6.2 kg and (4) low inertia through a human-oriented mixed implementation of Bowden-cable relocated and directly-integrated DC actuators.
Neurite outgrowth of PC12 cells on diX (parylene) family materials

We investigated neuronal cell differentiation, particularly neurite outgrowth, on the surface of diX H and diX AM using an in vitro examination of a neuron‐like rat pheochromocytoma cell line, PC12. diX H and diX AM are in the parylene family of diX C (or Parylene‐C), which is widely used as a novel coating material to insulate neural electrodes, and they have been recently commercialized; diX H and diX AM offer different features of biocompatibility. Previously, we found that these new parylene materials have high cell adhesiveness to neuronal cells whereas the adhesiveness of diX C is extremely low. However, their cell differentiation remains unknown although neuronal cell differentiation plays a crucial role in their development and regeneration. This study showed that almost all PC12 cells adhering to the surface of diX AM and diX H were differentiated, but the neurite outgrowth was significantly larger on diX H than that on diX AM and a conventional polystyrene culture dish. The result suggests that diX H may be advantageous as a biocompatible coating material for a scaffold, which can be used on virtually any substrate to get various configurations in neural devices. © 2011 American Institute of Chemical Engineers Biotechnol. Prog. , 2012
A Distributed Algorithm for Maximizing Linear Tree Density for One to Many Wireless Communication

Reliable and efficient broadcast functions are essential in large, dense, multi-hop low power wireless systems managed by a gateway. Previous approaches addressing this issue rely on centralized and/or solutions requiring complex implementations. This paper describes the {\em Deal} algorithm for minimizing transmissions and hop count while maintaining reliability in a distributed fashion. The algorithm is compatible with and easily integrated into current low power, lossy network protocols. We first present Deal as a centralized algorithm and evaluate using numerical simulations. We then derive a distributed algorithm appropriate for low power, lossy networks. We evaluate the distributed algorithm using a testbed with over 300 nodes. Our results demonstrate that Deal is reliable and energy efficient. The experiments show that Deal significantly reduces the required number of transmissions for network broadcast in large low power, lossy networks.
The Effect of Asset and Credit Constraint on the Labor Migration Efficiency in Less Developed Countries

Migration decision-making in developing economies is addressed from the perspective of status in the labor force (unemployed or unemployed) and traditional concerns with utility maximization are expanded to include the role of assets and access to capital markets. A dynamic model is formulated and the results reveal that the migration mechanism is efficient when workers have access to borrowing from financial institutions; without this access, migration is shown to be inefficient, a fact exacerbated when consideration is directed to unemployed/poor workers in less prosperous regions. JEL Classification: J41, J61, O12, O15, R23 and R58
Delay-dependent stability criterion of a class of neural networks with time-varying delay

A new Lyapunov-Krasovskii functional is constructed for a class of neural networks with time-varying delay, and some free-weighting matrices and S-procedure are employed to derive the delay-dependent stability criterion. The derived criterion is formulated in terms of linear matrix inequalities (LMIs). A numerical example is given to demonstrate the effectiveness and applicability of the criterion
Document page classification and nonlinear diffusion filtering for image segmentation and noise removal

Dong, Xiaogang Ph.D., Purdue University, May, 2007. Docume nt Page Classification and Nonlinear Diffusion Filtering for Image Segmentation and N oise Removal. Major Professor: Ilya Pollak. We develop a real-time, strip-based, low-complexity docum ent page classification algorithm, which can be used as a copy mode selector in the copy p ipeline. It analyzes the scan images and classifies them into one of eight modes. Modes are the combinations of mono/color and text/mix/picture/photo settings. Mode c lassification is 29accurate with misclassifications tending towards benign modes. The benefi ts of such a copy mode selector include improving copy quality, simplifying user in teraction, and increasing copy rate. We propose a novel family of nonlinear diffusions and apply i t to the problem of segmentation of multivalued images defined on arbitrary graphs . These equations generalize previously proposed scalar-valued diffusion equations wh ich ave been used for segmenting grayscale images. We demonstrate the effectiveness of o ur new methods on a large number of color, texture and natural image segmentation tas ks. We in addition introduce another extension of our diffusion equations which can proc ess orientation images, i.e., images whose every pixel takes values on a circle. We analyze a specific scalar-valued diffusion equation and s how that it can be used as an approximate method for solving the constrained total var iation minimization problem posed by Osher, Rudin, and Fatemi.
Predicting psychological attributions from face photographs with a deep neural network

Judgements about personality based on facial appearance are strong effectors in social decision making and are known to impact on areas from presidential elections to jury decisions. Recent work has shown that it is possible to predict perception of memorability, trustworthiness, intelligence and other attributes in human face images. The most successful of these approaches requires face images expertly annotated with key facial landmarks. We demonstrate a Convolutional Neural Network (CNN) model that is able perform the same task without the need for landmark features thereby greatly increasing efficiency. The model has high accuracy, surpassing human level performance in some cases. Furthermore, we use a deconvolutional approach to visualize important features for perception of 22 attributes and show that these can be described as a composites of their positive and negative components by separately visualizing both.
Semantic Knowledge Management to Support Sustainable Product Design

Building upon the perspective of integrating knowledge management, ontology engineering and sustainable product technologies, the paper argues that formalization of sustainable design knowledge in ontology and semantic knowledge markup would allow efficient and effective semantic knowledge sharing in sustainable product design. Towards this end, two mechanisms are proposed: for ontology modeling to formalize design knowledge and for ontology implementation in sustainable design systems to facilitate semantic knowledge sharing across multidisciplinary teams and applications. A use scenario is demonstrated in the paper to validate these mechanisms.
The Psychophysics and Modelling of Double-Vowel IdentiÞcation : A Comparative Review First Year

Human listeners appear to have little difÞculty in following one voice amongst a mixture of voices. This has been referred to as the Ôcocktail partyÕ phenomenon. Various factors have been shown to contribute to this ability, and one particularly important factor is the pitch of competing voices. A difference in pitch has been shown to increase the intelligibility of simultaneous speech. A widely used paradigm for investigating this effect is the so-called Ôdouble-vowelÕ experiment. Simultaneous, steady-state, synthetic vowel-pairs are played to listeners, who are generally required to identify both vowels. IdentiÞcation scores increase with an increasing difference in fundamental frequency between the vowels. Increasing rapidly at Þrst, and asymptoting at around one to two semitones. This Þnding has prompted much investigation into the mechanisms underlying this effect, and a number of computational models of the possible processing involved have been developed. Many of these models succeed in predicting the crucial aspects of human performance on this task, and so the actual mechanisms employed by the auditory system is still in question. This report presents an overview of the psychoacoustic data which has been obtained on this task, and a comparative review of the various models in light of this data. The various aspects of the data which have not been used as tests of the models are outlined, and a more discriminative measure of the performance of the models is proposed. This involves assessing the degree to which the various models can reproduce the particular pattern of confusions made by listeners. A pilot study is described which assesses the ability of one of the more successful models to reproduce some human confusion data. SigniÞcant discrepancies between the model and human data are identiÞed and a possible source of these differences is discussed, along with possible tests of the hypothesis. Further work necessary to conclude the pilot study is then outlined. Finally, future directions of research are discussed. Firstly involving introducing dynamic aspects into the stimuli, since a major problem with the double-vowel paradigm has been identiÞed as being due to the steady-state nature of the stimuli. Secondly, moving on to study the effects of a difference in fundamental frequency on the identiÞcation of continuous speech material, since there appear to be discrepancies between the data on continuous speech stimuli and that obtained from double-vowel experiments.
A common intrusion detection framework

As intrusions and other attacks become more widespread and more sophisticated, it becomes beyond the scope of any one intrusion detection and response (ID&R) system to deal with them. The need thus arises for systems to cooperate with one another, to manage diverse attacks across networks and time. Heretofore, eeorts toward \cooperation" have focused primarily on homogeneous components, with little if any attention toward standardization. In this paper, we discuss the eeorts of the Common Intrusion Detection Framework (CIDF) working group in designing a framework in which ID&R systems may cooperate with one another. We consider the issues involved in standardizing formats, protocols, and architectures to co-manage intrusion detection and response systems, and compare the strengths and weaknesses of previous approaches. We examine various ways that these systems and their components may be connected and related. We conclude with an overview of CIDF's current approach to providing a common intrusion speciication language. The work presented in this paper is currently funded by a lot of nice people. Abstract As intrusions and other attacks become more widespread and more sophisticated, it becomes beyond the scope of any one intrusion detection and response (ID&R) system to deal with them. The need thus arises for systems to cooperate with one another, to manage diverse attacks across networks and time. Heretofore, eeorts toward \cooperation" have focused primarily on homogeneous components, with little if any attention toward standardization. In this paper, we discuss the eeorts of the Common Intrusion Detection Framework (CIDF) working group in designing a framework in which ID&R systems may cooperate with one another. We consider the issues involved in standardizing formats, protocols, and architectures to co-manage intrusion detection and response systems, and compare the strengths and weaknesses of previous approaches. We examine various ways that these systems and their components may be connected and related. We conclude with an overview of CIDF's current approach to providing a common intrusion speciication language.
Foundations of Computational Mathematics, Hong Kong 2008: Linear and Nonlinear Subdivision Schemes in Geometric Modeling

Subdivision schemes are efficient computational methods for the design, representation and approximation of 2D and 3D curves, and of surfaces of arbitrary topology in 3D. Subdivision schemes generate curves/surfaces from discrete data by repeated refinements. While these methods are simple to implement, their analysis is rather complicated. The first part of the paper presents the ”classical” case of linear, stationary subdivision schemes refining control points. It reviews univariate schemes generating curves and their analysis. Several well known schemes are discussed. The second part of the paper presents three types of nonlinear subdivision schemes, which depend on the geometry of the data, and which are extensions of univariate linear schemes. The first two types are schemes refining control points and generating curves. The last is a scheme refining curves in a geometry-dependent way, and generating surfaces.