Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic Resonance Imaging and Magnetic Resonance Cholangiopancreatography Findings Compared With Fecal Elastase 1 Measurement for the Diagnosis of Chronic Pancreatitis

Objectives: To correlate magnetic resonance cholangiopancreatography (MRCP) and magnetic resonance imaging (MRI) findings of the pancreas with the pancreatic exocrine function determined by fecal elastase 1 concentration. Methods: Magnetic resonance imaging and MRCP findings of 81 consecutive patients with clinically suspected chronic pancreatitis and 21 healthy volunteers were evaluated. All subjects underwent MRI/MRCP and fecal elastase 1 testing within 1 to 4 weeks' interval. Magnetic resonance cholangiopancreatography images were evaluated according to Cambridge classification. Magnetic resonance imaging of the pancreas was assessed for pancreatic size, signal, and arterial enhancement. Results: All volunteers had normal fecal elastase 1 levels (>200 &mgr;g/g) and normal MRI/MRCP findings. Thirty-one of 56 patients revealed MRI and/or MRCP findings despite normal fecal elastase 1 concentration. Four of 25 patients revealed normal MRI and MRCP findings despite low fecal elastase 1 concentration (<200 &mgr;g/g). Magnetic resonance imaging findings of size (P = 0.00001), arterial enhancement (P = 0.00001), and parenchymal signal (P = 0.001) were significantly different among the control group, patients with normal fecal elastase 1 levels, and patients with low fecal elastase 1 levels. Magnetic resonance cholangiopancreatography findings (P = 0.00001), pancreatic size (P = 0.00001), arterial enhancement (P = 0.014), and parenchymal signal (P = 0.004) on MRI correlated with the fecal elastase 1 concentration. Conclusions: Magnetic resonance imaging/MRCP findings correlate with fecal elastase 1 concentration and may precede pancreatic exocrine insufficiency in the early stages of chronic pancreatitis.
Group-based Security in a Federated File System

The SILENUS federated file system was developed by the SORCER research group at Texas Tech University. The distributed file system with its dynamic nature does not require any configuration by the end users and system administrators. Managing security in a metacomputing system is a new challenge. It must be ensured that every user has a valid authentication and authorization to view, modify, and create files in the system spread across many heterogeneous computers that to individual requestor, it looks and acts like a single computer. User management is a must be on a metacomputing system and scale well. Existing user credential databases must be incorporated as secure data services if present. In this paper a new scalable authentication model for federated file systems is described. In this model users authenticate to an authentication service for their identity and a group manager service for their collaborative groups membership. The group manager service provides an authorization token that can be used to invoke service-oriented functionality of the federated file system. The group manager service uses existing user credential databases as its back-end. There may be any number of group manager services on the network with different user administration domains to provide desirable scalability. Multiple replicated group manager services for the same user base can provide for increased reliability. A scaled-down replica called nomadic group manager service provides support for disconnected operations. It contains the necessary credentials for a single user to use the system while being disconnected from the main network.
Mesh Geometry Compression for Mobile Graphics

This paper presents a compression scheme for mesh geometry, which is suitable for mobile graphics. The main focus is to enable real-time decoding of compressed vertex positions while providing reasonable compression ratios. Our scheme is based on local quantization of vertex positions with mesh partitioning. To prevent visual seams along the partitioning boundaries, we constrain the locally quantized cells of all mesh partitions to have the same size and aligned local axes. We propose a mesh partitioning algorithm to minimize the size of locally quantized cells, which relates to the distortion of a restored mesh. Vertex coordinates are stored in main memory and transmitted to graphics hardware for rendering in the quantized form, saving memory space and system bus bandwidth. Decoding operation is combined with model geometry transformation, and the only overhead to restore vertex positions is one matrix multiplication for each mesh partition.
Online Tissue Conductivity Estimation in Deep Brain Stimulation

Deep brain stimulation (DBS) is an established therapy that consists of sending electrical pulses to specific brain areas via chronically implanted electrodes. DBS is used to alleviate symptoms of neurological conditions such as Parkinson’s disease and essential tremor. However, the stimulation effect is patient-specific and hard to predict. In addition, electrical properties of the brain tissue around the lead change over time thus influencing the therapeutical effect. This paper proposes an approach to online conductivity estimation by applying a specially designed electrical probing signal to one contact of the DBS electrode and measuring the response on another one. A conductivity estimate is then obtained from the estimated parameters of a linear time-invariant model. Both voltage-controlled and current-controlled DBS systems are treated. Continuous least squares and the Laguerre domain identification are employed to estimate the model parameters. Results suggest that a smooth Gaussian-shaped signal is sufficient to identify the model in a noise-free situation, but the resulting excitation might be not enough for accurate estimation in the face of disturbances, e.g., local field potential deviations due to neuron firings. Better excitation is produced by input signals with designed Laguerre spectra. Due to the infeasibility of assigning electrical properties to the surroundings of the lead in vivo, synthetic data from an individualized high-fidelity mathematical model of DBS are used instead. The latter model is validated against clinically measured impedance values.
Dosing Considerations for Capecitabine-Irinotecan Regimens in the Treatment of Metastatic and/or Locally Advanced Colorectal Cancer

Capecitabine (Xeloda®, Roche Laboratories Inc., Nutley, NJ) is an orally administered fluoropyrimidine carbamate that serves as a prodrug of 5-fluorouracil (5-FU), an integral component of chemotherapy (CT) regimens for metastatic colorectal cancer (mCRC). As the drug is orally administered, capecitabine permits greater convenience and flexibility in dosing by eliminating the need for continuous infusion and its potential complications. In phase 3 trials, capecitabine has been used as an alternative to 5-FU, both as a monotherapy and in combination with agents such as oxaliplatin (as XELOX), with good efficacy and tolerability. Combination therapy with capecitabine and irinotecan (XELIRI), however, has produced more variable results, with some dose combinations and schedules resulting in excessive and/or unexplained treatment-related toxicity. Recent initiatives using lower doses of capecitabine and irinotecan, as well as alternative dosing schedules, have resulted in more favorable outcomes (efficacy and tolerability), even in combination with targeted-agents such as bevacizumab. Dose reduction in elderly populations and in those with moderate renal impairment also appears to be important for minimizing toxicity with XELIRI regimens. Although additional phase 3 studies are needed, XELIRI may be an effective base CT regimen, allowing a greater number of treatment options for tumor control in patients with mCRC.
The descent of ant: field-measured performance of gliding ants

ABSTRACT Gliding ants avoid predatory attacks and potentially mortal consequences of dislodgement from rainforest canopy substrates by directing their aerial descent towards nearby tree trunks. The ecologically relevant measure of performance for gliding ants is the ratio of net horizontal to vertical distance traveled over the course of a gliding trajectory, or glide index. To study variation in glide index, we measured three-dimensional trajectories of Cephalotes atratus ants gliding in natural rainforest habitats. We determined that righting phase duration, glide angle, and path directness all significantly influence variation in glide index. Unsuccessful landing attempts result in the ant bouncing off its target and being forced to make a second landing attempt. Our results indicate that ants are not passive gliders and that they exert active control over the aerodynamic forces they experience during their descent, despite their apparent lack of specialized control surfaces. Summary: Gliding ants exhibit variation in aerial righting phase duration, glide angle and trajectory directness, which are the principal determinants of ecologically relevant performance.
Designing new XML based multidimensional messaging interface for the new XWarehouse architecture

OLAP (Online Analysis Processing) applications have very special requirements to the underlying multidimensional data that differs significantly from other areas of application (e.g. the existence of highly structured dimensions). In addition, providing access and search among multiple, heterogeneous, distributed and autonomous data warehouses, especially web warehouses, has become one of the leading issues in data warehouse research and industry. This paper proposes a new message interface for a new platform independent data warehouse architecture that can deliver location, platform, and schema transparency for clients that access autonomous data warehouses. The new message interface uses XML in order to provide interoperable way to query and administrate federated data warehouses in addition to compose the multidimensional query result sets.
Detecting Information Leakage Based on Subtracting Matrix

This paper proposes an approach of detecting information leakage based on subtracting matrix to determine files when and where were leaked from file system. Due to the low efficiency of detecting leak operation and the rapid growth of the size of storage device make it difficult to locate the place where the leakage occurred. We build a time matrix model by file system access timestamps in a suspicious information system. Then three kinds of two-value (0-1) matrices are generated based on the similarity of access timestamps in the time matrix. The behavior of information leakage can be finally determined by comparing the degree of the similarity in these matrices. The experimental results show the method can detect information leakage more quickly and accurately.
Scalable distributed collaborative tracking and mapping with Micro Aerial Vehicles

This paper describes work on a distributed framework for collaborative multi-robot localisation and mapping with large teams of Micro Aerial Vehicles (MAVs). We demonstrate the benefits of running both image capture and frame-to-frame tracking on the same device while offloading the more computationally intensive aspects of map creation and optimization to an off-board computer. We show no impact on the accuracy of pose estimates of this distributed approach and indeed demonstrate a robustness to delay that improves localisation performance. The bandwidth requirements of our system are much lower than similar systems which enables us to accommodate larger teams of MAVs. In the results section we demonstrate the performance of our system in both simulated and real-world environments.
Real-Time Estimation of FLE Statistics for 3-D Tracking With Point-Based Registration

Target registration error (TRE) has become a widely accepted error metric in point-based registration since the error metric was introduced in the 1990s. It is particularly prominent in image-guided surgery (IGS) applications where point-based registration is used in both image registration and optical tracking. In point-based registration, the TRE is a function of the fiducial marker geometry, location of the target and the fiducial localizer error (FLE). While the first two items are easily obtained, the FLE is usually estimated using an a priori technique and applied without any knowledge of real-time information. However, if the FLE can be estimated in real-time, particularly as it pertains to optical tracking, then the TRE can be estimated more robustly. In this paper, a method is presented where the FLE statistics are estimated from the latest measurement of the fiducial registration error (FRE) statistics. The solution is obtained by solving a linear system of equations of the form Ax=b for each marker at each time frame where x are the six independent FLE covariance parameters and b are the six independent estimated FRE covariance parameters. The A matrix is only a function of the tool geometry and hence the inverse of the matrix can be computed a priori and used at each instant in which the FLE estimation is required, hence minimizing the level of computation at each frame. When using a good estimate of the FRE statistics, Monte Carlo simulations demonstrate that the root mean square of the FLE can be computed within a range of 70-90 mum. Robust estimation of the TRE for an optically tracked tool, using a good estimate of the FLE, will provide two enhancements in IGS. First, better patient to image registration will be obtained by using the TRE of the optical tool as a weighting factor of point-based registration used to map the patient to image space. Second, the directionality of the TRE can be relayed back to the surgeon giving the surgeon the option of changing their strategy in order to improve the overall system accuracy and, in turn, the quality of procedure.
Liquid xenon scintillation calorimetry and Xe optical properties

The optical properties of liquid xenon (LXe) in the vacuum ultra violet (VUV), determining the performance of a scintillation calorimeter, are discussed in detail. The available data, measured in a wider spectral region from visible to UV light, and in a large range of Xe densities, from gas to liquid, are examined. It is shown that this information can be used for deriving the LXe optical properties in the VUV. A comparison is made with the few direct measurements in LXe for VUV light resulting from the LXe excitation by ionizing particles. A useful relation is obtained which connects the Rayleigh scattering length to the refractive index in LXe
Provenance for nested subqueries

Data provenance is essential in applications such as scientific computing, curated databases, and data warehouses. Several systems have been developed that provide provenance functionality for the relational data model. These systems support only a subset of SQL, a severe limitation in practice since most of the application domains that benefit from provenance information use complex queries. Such queries typically involve nested subqueries, aggregation and/or user defined functions. Without support for these constructs, a provenance management system is of limited use. In this paper we address this limitation by exploring the problem of provenance derivation when complex queries are involved. More precisely, we demonstrate that the widely used definition of Why-provenance fails in the presence of nested subqueries, and show how the definition can be modified to produce meaningful results for nested subqueries. We further present query rewrite rules to transform an SQL query into a query propagating provenance. The solution introduced in this paper allows us to track provenance information for a far wider subset of SQL than any of the existing approaches. We have incorporated these ideas into the Perm provenance management system engine and used it to evaluate the feasibility and performance of our approach.
The Role of Peer Influence in Churn in Wireless Networks

Subscriber churn remains a top challenge for wireless carriers. In this paper, we look at the effect of peer influence on churn and we try to disentangle it from other effects that drive simultaneous churn across friends but that do not relate to peer influence. We analyze a random sample of roughly 10 thousand subscribers from large dataset from a major wireless carrier over a period of 10 months. We apply Generalized Propensity Scores to identify the role of peer influence. We show that the propensity to churn increases when friends do and that it increases more when many strong friends churn. Therefore, our results suggest that churn managers should consider strategies aimed at preventing group churn.
Isolation and characterization of krp, a dibasic endopeptidase required for cell viability in the fission yeast Schizosaccharomyces pombe.

The activation of pro‐hormones and many precursor proteins involves cleavage by endopeptidases belonging to the subtilisin‐like family of enzymes. Here we describe the isolation and characterization of the first member of this family from the fission yeast Schizosaccharomyces pombe. The enzyme, which has been named krp for KEX2‐related protease, is a type I membrane‐bound endopeptidase that cleaves substrates after pairs of dibasic residues. It appears to be synthesized as a pre‐pro‐protein that is likely to undergo processing following translocation into the endoplasmic reticulum. Processing has been characterized in a cell‐free translation/translocation system prepared from Xenopus eggs. Krp is N‐glycosylated on all five of its potential sites and both the pre‐sequence and the pro‐sequence are quickly removed following translocation, the latter probably by autocatalytic cleavage. The inhibitor profile of krp broadly reflects the known properties of the eukaryotic subtilisin proteases, while its pH and Ca2+ dependence are consistent with it being active within the secretory pathway. One of its physiological substrates is likely to be the pheromone precursor pro‐P‐factor, which it is shown to process in an in vitro system, but identification of other substrates is complicated because, unlike other members of this family, krp is essential for cell viability.
A SURVEY ON ARTIFICIAL INTELLIGENCE BASED BRAIN PATHOLOGY IDENTIFICATION TECHNIQUES IN MAGNETIC RESONANCE IMAGES ( Survey Paper )

Brain tumor pathologies are the most common fatality in the current scenario of health care society. Hence, accurate detection of the type of the brain abnormality is highly essential for treatment planning which can minimize the fatal results. Accurate results can be obtained only through computer aided automated systems. Besides being accurate, these techniques must converge quickly in order to apply them for real time applications. Even though several automated methods are available with these desirable performance measures, there is no clear differentiation between these techniques about the suitability for various applications. Many reports claim its work to be superior but a complete comparative analysis is lacking in these works. In this survey paper, an extensive comparative analysis is performed to illustrate the merits and demerits of various available techniques. This work also explores the applicability of the techniques in brain disorder diagnosis in MR images. The main objective of this work is to highlight the position of various automated techniques which can indirectly aid in developing novel techniques for solving the health care problem of the current society.
Ultrasensitive Microwave Near-Field Sensors For Detection, Imaging, and Material Characterization

Affordable, sensitive, selective, fast-responding, label-free sensors are currently in high demand for many of today’s applications and technologies, particularly in the food industry, bio-sensing applications, and quality control. In addition, modern technologies such as a lab-on-a-chip involve microfluidic analysis, which requires highly accurate and miniaturized sensing systems. These systems can be implemented in biomedical applications such as point-of-care diagnostics, as well as in environmental monitoring, agriculture, biotechnology, and public health and safety. A need, therefore, exists for highly accurate and reliable sensing systems that can meet the requirements of these applications. This dissertation presents electrically-small planar microwave resonators for the design of near-field sensors that can satisfy the needs of the aforementioned applications. This thesis proposes a number of novel concepts related to miniaturization and the enhancement of the sensitivity of electrically-small sensors. In the first part of the thesis, an analysis of the sensitivity of complementary split-ring resonators (CSRRs) with respect to changes in resonator topology is presented. Eigenmode solvers, circuit models, numerical simulations, and laboratory measurements were all employed for the analysis. The results show that the resonance frequency is adjustable and scalable. The second part of the thesis proposed an ultrasensitive near-field sensor for detecting submillimeter cracks in metallic materials. Experimental measurements revealed that a surface crack of 200 μm wide and 2 mm deep results in a 1.5 GHz shift in the resonance frequency. The results led to the idea of utilizing CSRRs for designing near-field sensors for crack detection in dielectric materials. The work was further extended to increase the sensitivity of planar CSRRs to detect the presence of dielectric materials. This concept is based on increasing the sensing areas per unit length and on the utilization of multiple, identical, and coupled resonators. Although the electromagnetic energy stored in electrically-small planar resonators is concentrated primarily in an electrically-small volume, most of that energy is located in the host substrate, thus limiting the sensitivity required for detecting changes in the material under test (MUT), which differs from the host substrate. For this reason, a sensor designed for enhancing the EM energy stored in the sensing volume that is exposed to the
Searching for Collective Behavior in a Large Network of Sensory Neurons

Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such “K-pairwise” models—being systematic extensions of the previously used pairwise Ising models—provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the population's capacity to represent visual information; 2) classifying activity patterns into a small set of metastable collective modes; 3) showing that the neural codeword ensembles are extremely inhomogenous; 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction.