Miracle-dz/UniFAR-FTUs huggingface dataset:
Drawdown and Stream Depletion Produced by Pumping in the Vicinity of a Partially Penetrating Stream

Commonly used analytical approaches for estimation of pumping‐induced drawdown and stream depletion are based on a series of idealistic assumptions about the stream‐aquifer system. A new solution has been developed for estimation of drawdown and stream depletion under conditions that are more representative of those in natural systems (finite width stream of shallow penetration adjoining an aquifer of limited lateral extent). This solution shows that the conventional assumption of a fully penetrating stream will lead to a significant overestimation of stream depletion (> 100%) in many practical applications. The degree of overestimation will depend on the value of the stream leakance parameter and the distance from the pumping well to the stream. Although leakance will increase with stream width, a very wide stream will not necessarily be well represented by a model of a fully penetrating stream. The impact of lateral boundaries depends upon the distance from the pumping well to the stream and the stream leakance parameter. In most cases, aquifer width must be on the order of hundreds of stream widths before the assumption of a laterally infinite aquifer is appropriate for stream‐depletion calculations. An important assumption underlying this solution is that stream‐channel penetration is negligible relative to aquifer thickness. However, an approximate extension to the case of nonnegligible penetration provides reasonable results for the range of relative penetrations found in most natural systems (up to 85%). Since this solution allows consideration of a much wider range of conditions than existing analytical approaches, it could prove to be a valuable new tool for water management design and water rights adjudication purposes.
The New York High-Risk Project.

Background— We herein present lifetime prevalence rates of psychoses and DSM-III-R cluster A personality disorders in sample A of the New York High-Risk Project, a prospective study following offspring of parents with schizophrenia (HRSz subjects) and affective illness (HRAff subjects) and of psychiatrically normal parents (NC subjects) from midchildhood to adulthood. Methods— We interviewed the offspring in adulthood with the Schedule for Affective Disorders and Schizophrenia, Lifetime Version, for Axis I disorders and the Personality Disorder Examination for Axis II disorders. Results— Lifetime prevalence rates (±SE) of schizophrenia and unspecified psychosis were 11.1%±4.3% and 5.6%±3.1%, respectively, in the HRSz group and 0% in the HRAff and NC groups. Rates of schizoaffective disorder subclassified as mainly schizophrenic, however, were highest in the HRAff group. Rates of psychotic
Trans-kingdom Cross-Talk: Small RNAs on the Move

This review focuses on the mobility of small RNA (sRNA) molecules from the perspective of trans-kingdom gene silencing. Mobility of sRNA molecules within organisms is a well-known phenomenon, facilitating gene silencing between cells and tissues. sRNA signals are also transmitted between organisms of the same species and of different species. Remarkably, in recent years many examples of RNA-signal exchange have been described to occur between organisms of different kingdoms. These examples are predominantly found in interactions between hosts and their pathogens, parasites, and symbionts. However, they may only represent the tip of the iceberg, since the emerging picture suggests that organisms in biological niches commonly exchange RNA-silencing signals. In this case, we need to take this into account fully to understand how a given biological equilibrium is obtained. Despite many observations of trans-kingdom RNA signal transfer, several mechanistic aspects of these signals remain unknown. Such RNA signal transfer is already being exploited for practical purposes, though. Pathogen genes can be silenced by plant-produced sRNAs designed to affect these genes. This is also known as Host-Induced Genes Silencing (HIGS), and it has the potential to become an important disease-control method in the future.
Iterative LS Channel Estimation for OFDM Systems Based on Transform-Domain Processing

Channel estimation is crucial for the performance of OFDM systems. In this paper, at first we describe the LS channel estimator based on transform domain processing and an iterative algorithm to improve the performance of channel estimator. Both of them could remove the additive Gaussian noise in the LS channel estimate effectively. Then we initially apply this iterative algorithm to the introduced transform-domain based LS channel estimator. We also introduce a decision-directed process to the channel estimator to further improve the estimation accuracy. Simulation results show that the new estimator performs better than the former ones.
Network management in heterogeneous wireless sensor network applications

There is an increasing demand in designing heterogeneous networks, where various low-power wireless radios such as ZigBee and Bluetooth devices coexist, while sensing devices may generate traffic with different intervals. In this work, we devise an architecture of a cross layer controller, encompassing a software defined radio at the data plane to manage radio access, and a software defined networking at the control plane to manage data flow, while considering the application requirements. The overall architecture aims at simplifying system management and network re-configuration, while providing better network performance.
Magnetic Materials and Design Trade-Offs for High Inductance Density, High-Q and Low-Cost Power and EMI Filter Inductors

This paper investigates the trade-offs in inductance density and quality factor of inductors with and without magnetic-cores through modeling, design, fabrication and model validation through characterization. Two type of inductors, one for power-supply and the other for EMI filters, are investigated. Parametric analysis was performed to study the enhancement in inductance density without compromising the current handling and efficiency. For EMI filter inductors, the inductance and quality factor (Q) were improved by 13X and 4X respectively with and without magnetic cores. For power inductors, the inductance and quality factor were improved by 5X and 1.6X respectively. The fabricated magnetic core inductors achieved 5X reduction in thickness, compared to the stage-of-the art air-core inductors which use multilayered and thick solenoid.
The Effect of PEG Molecular Weights on Dissolution Behavior of Simvastatin in Solid Dispersions

The purpose of the present study was to investigate the effect of polyethylene glycol (PEG) molecular weights (6000, 12000 and 20000) as solid dispersion (SD) carriers on the dissolution behavior of simvastatin. SDs with various drug : carrier ratios were prepared by solvent method and evaluated for dissolution rate. Differential scanning calorimetry (DSC), X-ray diffraction (XRD), infrared spectroscopy and solubility studies were also performed on the optimum SD formulation. Samples prepared with all three types of PEG showed improved drug dissolution compared to intact drug and corresponding physical mixtures. Meanwhile, the best result was obtained by PEG 12000 with drug : carrier ratio of 1:7 which showed a 3-fold increase in dissolution rate compared to the intact drug. Based on DSC and XRD, no crystalline change occurred during the sample preparation. Solubility studies revealed that increasing the PEG molecular weight resulted in higher phase solubility of drug. In addition, saturated solubility of the optimum SD was significantly higher than that of intact drug and the related physical mixture (24.83, 8.74 and 8.88 μg/mL, respectively) that could be due to the decreased particle size and aggregation. The results confirmed the influence of PEG molecular weight on drug dissolution rate from solid dispersion systems.
Visual and skill effects on soccer passing performance, kinematics, and outcome estimations

The role of visual information and action representations in executing a motor task was examined from a mental representations approach. High-skill (n = 20) and low-skill (n = 20) soccer players performed a passing task to two targets at distances of 9.14 and 18.29 m, under three visual conditions: normal, occluded, and distorted vision (i.e., +4.0 corrective lenses, a visual acuity of approximately 6/75) without knowledge of results. Following each pass, participants estimated the relative horizontal distance from the target as the ball crossed the target plane. Kinematic data during each pass were also recorded for the shorter distance. Results revealed that performance on the motor task decreased as a function of visual information and task complexity (i.e., distance from target) regardless of skill level. High-skill players performed significantly better than low-skill players on both the actual passing and estimation tasks, at each target distance and visual condition. In addition, kinematic data indicated that high-skill participants were more consistent and had different kinematic movement patterns than low-skill participants. Findings contribute to the understanding of the underlying mechanisms required for successful performance in a self-paced, discrete and closed motor task.
Simulated Action in an Embodied Construction Grammar

Various lines of research on language have converged on the premise that linguistic knowledge has as its basic unit pairings of form and meaning. The precise nature of the meanings involved, however, remains subject to the longstanding debate between proponents of arbitrary, abstract representations and those who argue for more detailed perceptuo-motor representations. We propose a model, Embodied Construction Grammar (ECG), which integrates these two positions by casting meanings as schematic representations embodied in human perceptual and motor systems. On this view, understanding everyday language entails running mental simulations of its perceptual and motor content. Linguistic meanings are parameterizations of aspects of such simulations; they thus serve as an interface between the relatively discrete properties of language and the detailed and encyclopedic knowledge needed for simulation. This paper assembles evidence from neural imaging and psycholinguistic experiments supporting this general approach to language understanding. It also introduces ECG as a model that fulfills the requisite constraints, and presents two kinds of support for the model. First, we describe two verbal matching studies that test predictions the model makes about the degree of motor detail available in lexical representations. Second, we demonstrate the viability and utility of ECG as a grammar formalism through its capacity to support computational models of language understanding and acquisition.
A Comparative Study of Two Techniques for Analyzing Software Measurement Data

Careful analysis of Software Engineering measurement data is essential in deriving the right conclusions from performed experiments. Different data analysis techniques may provide data analysts with different and complementary insights into the studied phenomena. In this paper, two data analysis techniques Rough Sets and Logistic Regression are compared, from both the theoretical and the experimental points of view. In particular, the empirical study was performed as part of the ESPRIT/ESSI project CEMP on a real-life maintenance project, the DATATRIEVE project carried out at Digital Engineering Italy. The two data analysis techniques are different in nature: Logistic Regression uses a statistical approach, while the Rough Sets analysis technique does not. We have applied both techniques to the same data set. The goal of the experimental study was to determine the major factors affecting reliability and reusability in the application context. Results obtained with either analysis technique are discussed and compared, to identify commonalities and differences between the two techniques. Finally, both analysis techniques are evaluated with respect to their weaknesses and strengths.
High‐level synthesis by dynamic ant

In this article, a new algorithm called dynamic ant is introduced. It was a combination of ant colony optimization (ACO) techniques and the dynamic niche sharing scheme. The interesting point of this algorithm is that it is implemented easily and could be well matched with existing design algorithms by adding the heuristic weights to speed up the algorithm. The algorithm uses the problem state structure as in the reinforcement‐learning algorithm, but the storage explosion is prevented by means of the pheromone trail. This algorithm was investigated for the data path design problem of high‐level synthesis of which has a large number of design steps and design techniques. © 2004 Wiley Periodicals, Inc.
Executing Multiple Pipelined Data Analysis Operations in the Grid

Processing of data in many data analysis applications can be represented as an acyclic, coarse grain data flow, from data sources to the client. This paper is concerned with scheduling of multiple data analysis operations, each of which is represented as a pipelined chain of processing on data. We define the scheduling problem for effectively placing components onto Grid resources, and propose two scheduling algorithms. Experimental results are presented using a visualization application.
Distribution and Expression of Soluble Epoxide Hydrolase in Human Brain

Epoxyeicosatrienoic acids (EETs) are cytochrome P450 metabolites of arachidonic acid, which function in the brain to regulate cerebral blood flow and protect against ischemic brain injury. EETs are converted by soluble epoxide hydrolase (sEH) to the corresponding inactive diol metabolites. Previous animal studies have indicated that sEH gene deletion or treatment with sEH inhibitors results in increased levels of EETs and protection against stroke-induced brain damage. To begin elucidating the underlying mechanism for these effects, we sought to determine the distribution, expression, and activity of sEH in human brain samples obtained from patients with no neurological changes/pathologies. Immunohistochemical analyses showed the distribution of sEH mainly in the neuronal cell bodies, oligodendrocytes, and scattered astrocytes. Surprisingly, in the choroid plexus, sEH was found to be highly expressed in ependymal cells. Vascular localization of sEH was evident in several regions, where it was highly expressed in the smooth muscles of the arterioles. Western blot analysis and enzyme assays confirmed the presence of sEH in the normal brain. Our results indicate differential localization of sEH in the human brain, thus suggestive of an essential role for this enzyme in the central nervous system. This manuscript contains online supplemental material at http://www.jhc. org. Please visit this article online to view these materials.
Structural Risk Minimization for Character Recognition

The method of Structural Risk Minimization refers to tuning the capacity of the classifier to the available amount of training data. This capacity is influenced by several factors, including: (1) properties of the input space, (2) nature and structure of the classifier, and (3) learning algorithm. Actions based on these three factors are combined here to control the capacity of linear classifiers and improve generalization on the problem of handwritten digit recognition.
Mining frequent itemsets: a perspective from operations research

Mining frequent itemsets is a flourishing research area. Many papers on this topic have been published and even some contests have been held. Most papers focus on speed and introduce ad hoc algorithms and data structures. In this paper we put most of the algorithms in one framework, using classical Operations Research paradigms such as backtracking, depth‐first and breadth‐first search and branch‐and‐bound. Moreover, we present experimental results where the different algorithms are implemented under similar designs.
Real-Time Automatic Segmentation of Optical Coherence Tomography Volume Data of the Macular Region

Optical coherence tomography (OCT) is a high speed, high resolution and non-invasive imaging modality that enables the capturing of the 3D structure of the retina. The fast and automatic analysis of 3D volume OCT data is crucial taking into account the increased amount of patient-specific 3D imaging data. In this work, we have developed an automatic algorithm, OCTRIMA 3D (OCT Retinal IMage Analysis 3D), that could segment OCT volume data in the macular region fast and accurately. The proposed method is implemented using the shortest-path based graph search, which detects the retinal boundaries by searching the shortest-path between two end nodes using Dijkstra’s algorithm. Additional techniques, such as inter-frame flattening, inter-frame search region refinement, masking and biasing were introduced to exploit the spatial dependency between adjacent frames for the reduction of the processing time. Our segmentation algorithm was evaluated by comparing with the manual labelings and three state of the art graph-based segmentation methods. The processing time for the whole OCT volume of 496×644×51 voxels (captured by Spectralis SD-OCT) was 26.15 seconds which is at least a 2-8-fold increase in speed compared to other, similar reference algorithms used in the comparisons. The average unsigned error was about 1 pixel (∼ 4 microns), which was also lower compared to the reference algorithms. We believe that OCTRIMA 3D is a leap forward towards achieving reliable, real-time analysis of 3D OCT retinal data.
25-Hydroxyvitamin D levels and survival in advanced pancreatic cancer: findings from CALGB 80303 (Alliance).

BACKGROUND Data from animal and cell-line models suggest that vitamin D metabolism plays an important role in pancreatic tumor behavior. Although vitamin D deficiency has been implicated in numerous cancers, the vitamin D status of patients with advanced pancreatic cancer and the effect of baseline vitamin D levels on survival are unknown. METHODS Participants in this correlative study (CALGB 151006) were enrolled in CALGB 80303, which was a randomized trial of patients with advanced pancreatic cancer that demonstrated no difference in overall survival (OS) among patients treated with gemcitabine plus placebo vs gemcitabine plus bevacizumab. We measured baseline serum 25-hydroxyvitamin D (25[OH]D) levels and examined associations between baseline 25(OH)D levels and progression-free survival and OS using the Cox rank score test. All statistical tests were two-sided. RESULTS Of 256 patients with available serum, the median 25(OH)D level was 21.7ng/mL (range 4 to 77). 44.5% of patients were vitamin D deficient (25[OH]D <20ng/mL), and 32.4% were insufficient (25[OH]D ≥20 and <30ng/mL). 25(OH)D levels were lower in black patients compared with white patients, and patients of other/undisclosed race (10.7 vs 22.4 vs 20.9ng/mL, P < .001). Baseline 25(OH)D levels were not associated with PFS (HR = 1.00, 95% CI = 0.99 to 1.01, P = .60) or OS (HR = 1.00, 95% CI = 0.99 to 1.01, P = .95). CONCLUSION Vitamin D deficiency was highly prevalent among patients with a new diagnosis of advanced pancreatic cancer. Black patients had statistically significantly lower 25(OH)D levels than white patients. In this cohort of patients with advanced pancreatic cancer receiving gemcitabine-based chemotherapy, baseline 25(OH)D levels were not associated with PFS or OS.
Recent improvements in tensor scale computation and new applications to medical image registration and interpolation

Recommended Citation Xu, Ziyue. "Recent improvements in tensor scale computation and new applications to medical image registration and interpolation. " other faculties, staffs and students at the Iowa Institute for Biomedical Imaging for their help and lectures. iii ABSTRACT Tensor scale (t-scale) is a parametric representation of local structure morphology that simultaneously describes its orientation, shape and isotropic scale. At any image location, t-scale is the parametric representation of the largest ellipse (an ellipsoid in 3D) centered at that location and contained in the same homogeneous region. Recently, we have improved the t-scale computation algorithm by: (1) optimizing digital representations for LoG and DoG kernels for edge detection and (2) ellipse fitting by using minimization of both algebraic and geometric distance errors. Also, t-scale has been applied to computing the deformation vector field with applications to medical image registration. Currently, the method is implemented in two-dimension (2D) and the deformation vector field is directly computed from t-scale-derived normal vectors at matching locations in two images to be registered. Also, the method has been used to develop a simple algorithm for computing 2D warping from one shape onto another. Meanwhile, t-scale has been applied to generating interpolation lines with applications to medical image interpolation using normal vector. Normal vector yields local structure orientation pointing to the closest edge. However, this information is less reliable along the medial axis of a shape as it may be associated with either of the two opposite edges of the local shape. This problem is overcome using a shape-linearity measure estimating relative changes in scale along the orthogonal direction. Preliminary results demonstrate the method's potential in estimating deformation between two images and interpolating between neighboring slices in a grey scale image. Table 1 Mean absolute errors (gray value range 0~255) and standard deviation of the absolute errors between 20 pairs of successive image slices before and after applying different registration methods. Figure 16 Performance of different methods for data at different noise level measured by (a) MAD and (b) square root of MSD. Figure 17 Performance of different methods for data at different level of intensity non-uniformity measured by (a) MAD and (b) square root of MSD. Figure 18 Performance of different methods on 12 images measured by (a) MAD and (b) square root of MSD.