Miracle-dz/UniFAR-FTUs huggingface dataset:
New intravascular contrast agent applied to dynamic contrast enhanced MR imaging of human breast cancer.

PURPOSE To evaluate the feasibility of using dynamic contrast-enhanced MR imaging with a new intravascular contrast agent in grading human breast cancer. MATERIAL AND METHODS 23 patients with 27 breast tumors (21 carcinomas and 6 fibroadenomas) were examined with dynamic MR imaging after administration of Clariscan, an iron oxide nanoparticle with large T1 relaxivity and a long plasma half life. A 3D T1-weighted gradient echo sequence with an acquisition time of 60 s was repeated at regular intervals of 3-5 min before and up to 1 h after injection of 2 mg/kg b.w. of Clariscan. The endothelial transfer constant, Kps, which reflects overall vascular permeability, and the fractional plasma volume, fPV, were estimated from time-intensity curves acquired from three separate regions of interest (ROIs): whole tumor, a permeability hot spot, and a blood volume hot spot. Kps and fPV were compared to the results of histologic tumor grading (Scarff-Bloom-Richardson, SBR) and microvascular density, MVD. RESULTS A statistically significant correlation between the MR-derived Kps parameters and the SBR score was obtained for the whole tumor ROI (R = 0.70), and for the permeability hot spot ROIs (R = 0.67). A correlation between fPV and SBR was detected for the blood volume hot spot ROIs (R = 0.48). There was no statistically significant correlation between Kps or fPV with MVD. CONCLUSION The results support the hypothesis that dynamic MR with the intravascular contrast agent Clariscan may be used for non-invasive tumor grading.
Search strategies for peg-in-hole assemblies with position uncertainty

This paper presents search strategies for peg-in-hole assemblies with position uncertainty. The assembly of parts whose position uncertainty far exceeds assembly clearance has to rely on either, visual assistance or blind searching to achieve part mating. In the absence of visual assistance we look at blind search strategies to cover the search area in an efficient manner. The paper also describes a tilt strategy using special cues to guide the assembly and enhance blind search. Results from assemblies on an actual robot are presented.
Specific functional properties of 3D woven glass nanocomposites

An exploratory work has been carried out in the field of three-phase composites in which fly ash nanoparticles were incorporated in addition with 2D and 3D glass woven fabrics while preparing composites. These fly ash nanoparticles were prepared by high-energy ball milling technique and its effect on functional properties of composites were observed. In thermo-mechanical analysis, the composites with the 3D woven fabrics as reinforcement showed higher storage modulus. Further improvement in the storage modulus due to addition of fly ash can be explained as the nanoscale dimension of fly ash nanoparticles have got very large surface area which leads to interaction sites and hence efficient load transfer between reinforcing agent and matrix. Though the addition of fly ash nanoparticles improved the mechanical properties of composites marginally, a significant improvement was observed in functional properties of composites.
Energy-Aware Fair Routing in Wireless Sensor Networks with Maximum Data Collection

This paper considers the problem of routing in sensor networks from the point of view od data collection. That is, given the initial amount of battery energy in each node, the aim is to determine how much data can each source transmit until the network is partitioned (i. e., until the nodes cannot find end-to-end routes to their respective sinks). In addition, to respond to some specific applications' requirements, when determining such nodal data volume distribution, fairness among nodes is taken into account. The problem is formulated as a concave utility maximization and a sub-gradient algorithm is proposed to solve it distributively. Some numerical results are given and the convergence of the algorithm is discussed.
Aortic elastic properties predict occult coronary artery disease: a multidetector row computed tomography study.

BACKGROUND Multidetector row computed tomography (MDCT) is an attractive noninvasive imaging modality to detect coronary atherosclerotic plaques which may be underestimated by conventional angiography. However, its routine clinical use is limited due to contrast-associated problems, high cost, inapplicability at bedside and exposure to radiation. Thus, exploring safer and more practical measurements to predict occult coronary artery disease (CAD) is required. AIM To demonstrate the predictive value of aortic elastic properties for occult CAD diagnosed by MDCT. METHODS Forty subjects with angiographically normal coronary arteries were consecutively included in our study. They underwent MDCT including indications and were divided into a no CAD group (23 subjects, 11 males, 46 ± 8 years) and an occult CAD group (17 subjects, 12 males, 48 ± 10 years), with respect to the presence of coronary plaque. As a control group, 19 consecutive patients with angiographically proven CAD (16 males, 52 ± 6 years) were included. Aortic stiffness index (ASI), aortic distensibility and aortic strain were calculated from the aortic diameters measured by echocardiography and blood pressure obtained by sphygmomanometry. RESULTS It was found that ASI, aortic distensibility and aortic strain were significantly different in the occult CAD group compared to the no CAD group (p = 0.008, p = 0.01, p = 0.03, respectively) and to the evident CAD group (p = 0.01, p = 0.02, p = 0.02). They also differed significantly between the no CAD and the evident CAD groups. Receiver operating characteristics analysis for ASI, to distinguish between the occult CAD group and the no CAD group, revealed an area under the curve of 0.80 (confidence interval 0.68-0.94, p = 0.004) and that the cut-off value of 3.42 could significantly predict patients with occult CAD (sensitivity: 78%; specificity: 63%). CONCLUSIONS Measurement of ASI is an easily applicable and safe method with its non-radiographic ability for the assessment of aortic stiffness, and it may be useful to predict subclinical atherosclerosis in clinical practice. A cut-off value of 3.42 for ASI may guide to refer individuals to preventive strategies to reduce atherosclerosis progression.
Interactive Editing of GigaSample Terrain Fields

Previous terrain rendering approaches have addressed the aspect of data compression and fast decoding for rendering, but applications where the terrain is repeatedly modified and needs to be buffered on disk have not been considered so far. Such applications require both decoding and encoding to be faster than disk transfer. We present a novel approach for editing gigasample terrain fields at interactive rates and high quality. To achieve high decoding and encoding throughput, we employ a compression scheme for height and pixel maps based on a sparse wavelet representation. On recent GPUs it can encode and decode up to 270 and 730 MPix/s of color data, respectively, at compression rates and quality superior to JPEG, and it achieves more than twice these rates for lossless height field compression. The construction and rendering of a height field triangulation is avoided by using GPU ray‐casting directly on the regular grid underlying the compression scheme. We show the efficiency of our method for interactive editing and continuous level‐of‐detail rendering of terrain fields comprised of several hundreds of gigasamples.
Efficient Similarity Search over Future Stream Time Series

With the advance of hardware and communication technologies, stream time series is gaining ever-increasing attention due to its importance in many applications such as financial data processing, network monitoring, Web click-stream analysis, sensor data mining, and anomaly detection. For all of these applications, an efficient and effective similarity search over stream data is essential. Because of the unique characteristics of the stream, for example, data are frequently updated and real-time response is required, the previous approaches proposed for searching through archived data may not work in the stream scenarios. Especially, in the cases where data often arrive periodically for various reasons (for example, the communication congestion or batch processing), queries on such incomplete time series or even future time series may result in inaccuracy using traditional approaches. Therefore, in this paper, we propose three approaches, polynomial, Discrete Fourier Transform (DFT), and probabilistic, to predict the unknown values that have not arrived at the system and answer similarity queries based on the predicted data. We also apply efficient indexes, that is, a multidimensional hash index and a B+-tree, to facilitate the prediction and similarity search on future time series, respectively. Extensive experiments demonstrate the efficiency and effectiveness of our methods for prediction and answering queries.
A graph-based profile similarity calculation method for collaborative information retrieval

Collaborative Information Retrieval (CIR) is one of the popular social-based IR approaches. A CIR system registers the previous user interactions to response to the subsequent user queries more efficiently. But CIR suffers from the personalization problem because the goals and the characteristics of two users may be different; so when they send the same query to a CIR system, they may be interested in two different lists of documents. We have developed a personalized CIR system, called PERCIRS, to solve this problem. Selecting an efficient method to calculate the similarity between user profiles is a key factor for enhancing PERCIRS's efficiency. In this paper, we propose a new graph-based method for user profile similarity calculation. Finally, by introducing an evaluation method, we will show that this new method is more efficient than the previous methods.
Authorship Attribution with Latent Dirichlet Allocation

The problem of authorship attribution -- attributing texts to their original authors -- has been an active research area since the end of the 19th century, attracting increased interest in the last decade. Most of the work on authorship attribution focuses on scenarios with only a few candidate authors, but recently considered cases with tens to thousands of candidate authors were found to be much more challenging. In this paper, we propose ways of employing Latent Dirichlet Allocation in authorship attribution. We show that our approach yields state-of-the-art performance for both a few and many candidate authors, in cases where these authors wrote enough texts to be modelled effectively.
On subtyping and matching

A relation between recursive object types, called matching, has been proposed as a generalization of subtyping. Unlike subtyping, matching does not support subsumption, but it does support inheritance of binary methods. We argue that matching is a good idea, but that it should not be regarded as a form of F-bounded subtyping (as was originally intended). We show that a new interpretation of matching as higher-order subtyping has better properties. Matching turns out to be a third-order construction, possibly the only one to have been proposed for general use in programming.
Duality-Based Robust Transceiver Design for Cognitive Downlink Systems

This paper studies robust transceiver optimization for cognitive downlink systems in the presence of imperfect channel state information (CSI). We aim at minimizing the sum mean square error (MSE) of the secondary downlink transmission subject to the interference constraint imposed on the primary users. The MSE duality is developed to describe the uplink-downlink relation, in which imperfect CSI and multiple power constraints are taken into account. Based on the duality result, we propose an efficient robust approach which can effectively avoid the violation of the interference constraint. We also discuss the performance in terms of optimality as well as complexity issue. Compared to the downlink-based approach, the proposed one features faster convergence speed and lower complexity.
Unique somato-dendritic distribution pattern of Kv4.2 channels on hippocampal CA1 pyramidal cells

A‐type K+ current (IA) plays a critical role in controlling the excitability of pyramidal cell (PC) dendrites. In vitro dendritic patch‐pipette recordings have demonstrated a prominent, sixfold increase in IA density along the main apical dendrites of rat hippocampal CA1 PCs. In these cells, IA is mediated by Kv4.2 subunits, whose precise subcellular distribution and densities in small‐diameter oblique dendrites and dendritic spines are still unknown. Here we examined the densities of the Kv4.2 subunit in 13 axo‐somato‐dendritic compartments of CA1 PCs using a highly sensitive, high‐resolution quantitative immunogold localization method (sodium dodecyl sulphate‐digested freeze‐fracture replica‐labelling). Only an approximately 70% increase in Kv4.2 immunogold density was observed along the proximo‐distal axis of main apical dendrites in the stratum radiatum with a slight decrease in density in stratum lacunosum‐moleculare. A similar pattern was detected for all dendritic compartments, including main apical dendrites, small‐diameter oblique dendrites and dendritic spines. The specificity of the somato‐dendritic labelling was confirmed in Kv4.2−/− tissue. No specific immunolabelling for the Kv4.2 subunit was found in SNAP‐25‐containing presynaptic axons. Our results demonstrate a novel distribution pattern of a voltage‐gated ion channel along the somato‐dendritic surface of CA1 PCs, and suggest that the increase in the IA along the proximo‐distal axis of PC dendrites cannot be solely explained by a corresponding increase in Kv4.2 channel number.
Optimizing Joint Data and Power Transfer in Energy Harvesting Multiuser Wireless Networks

Energy harvesting emerges as a potential solution for prolonging the lifetime of the energy-constrained mobile wireless devices. In this paper, we focus on radio frequency (RF) energy harvesting for multiuser multicarrier mobile wireless networks. Specifically, we propose joint data and energy transfer optimization frameworks for powering mobile wireless devices through RF energy harvesting. We introduce a power utility that captures the power consumption cost at the base station (BS) and the used power from the users’ batteries, and determine optimal power resource allocations that meet data rate requirements of downlink and uplink communications. Two types of harvesting capabilities are considered at each user: harvesting only from dedicated RF signals and hybrid harvesting from both dedicated and ambient RF signals. The developed frameworks increase the end users’ battery lifetime at the cost of a slight increase in the BS power consumption. Several evaluation studies are conducted in order to validate our proposed frameworks.
Supply chain multi-objective simulation optimization

A critical decision companies are faced with on a regular basis is the ordering of products and/or raw materials. Poor decisions can lead to excess inventories that are costly or to insufficient inventory that cannot meet its customer demands. These decisions may be as simple as "how much to order" or "how often to order" to more complex decision forecasting models. This paper addresses optimizing these sourcing decisions within a supply chain to determine robust solutions. Utilizing an existing supply chain simulator, an optimization methodology that employs genetic algorithms is developed to optimize system parameters. The performance measure that is optimized plays a very important role in the quality of the results. The deficiencies in using traditionally used performance measures in optimization are discussed and a new multi-objective GA methodology is developed to overcome these limitations.
3d reconstruction of a female lung using the Visible Human Data Set to predict cigarette smoke particle deposition

A detailed comparison ofparticle deposition of a female smoker lung compared to a nonsmoker is vital when trying to gain a further understanding of lung cancer. To make this comparison, two airway models were created that consisted ofthe oral cavity, oropharynx, laryngopharynx, larynx, trachea, and generations up to the 3rd, 4th or 5th generation. The difference between the two models is in the shape ofthe oral cavity. The smoker model has an oral cavity that represents the mouth during the inhalation ofa cigarette and the nonsmoker model represents normal oral breathing. The oral cavity models were created by scanning a cast. The model ofthe oropharynx, laryngopharynx, and larynx was created by a medical illustrator based on dimensions from medical photographs and a cast of this region. The trachea through the 5th generation was created by segmenting the 2D cryosectioned images from the Visible Female Dataset and reconstructing them to create a 3D model. It was determined that the error ofthe segmentation process was 0.33 mm based on the pixel size of the images. The model was then smoothed, decimated and trimmed, which incurred no error beyond the
Blind Detection in IDMA Systems

Interleaved Division Multiple Access (IDMA) is a new access scheme that has been proposed in the literature to increase the capacity of wireless channels. The performance of such systems depends on the accuracy of the channel state information (CSI) at the receiver. In this paper, a Noisy-Independent Component Analysis (NICA) based IDMA receiver for multiple access communication channels is proposed and compared to classical receivers. The N-ICA component is applied as a post processor. The estimation of CSI will often have some measurement errors, which degrade the accuracy of symbol detection. Using blind methods, this overhead can be eliminated. Simulation results demonstrate that N-ICA post processor provides an improvement in performance in terms of bit error rate (BER) in loaded systems and it offers an efficient alternative to systems with block channel estimation. When the system is not loaded, the proposed post processor presents the same performance as conventional IDMA receiver with less iterations leading to a complexity reduction.
An Empirical Study of Collusion Behavior in the Maze P2P File-Sharing System

Peer-to-peer networks often use incentive policies to encourage cooperation between nodes. Such systems are generally susceptible to collusion by groups of users in order to gain unfair advantages over others. While techniques have been proposed to combat Web spam collusion, there are few measurements of real collusion in deployed systems. In this paper, we report analysis and measurement results of user collusion in Maze, a large-scale peer-to-peer file sharing system with a non-net-zero point-based incentive policy. We search for colluding behavior by examining complete user logs, and incrementally refine a set of collusion detectors to identify common collusion patterns. We find collusion patterns similar to those found in Web spamming. We evaluate how proposed reputation systems would perform on the Maze system. Our results can help guide the design of more robust incentive schemes.
Titanium: A Technical Guide

Designed to support the need of engineering, management, and other professionals for information on titanium by providing an overview of the major topics, this book provides a concise summary of the most useful information required to understand titanium and its alloys. The author provides a review of the significant features of the metallurgy and application of titanium and its alloys. All technical aspects of the use of titanium are covered, with sufficient metals property data for most users. Because of its unique density, corrosion resistance, and relative strength advantages over competing materials such as aluminum, steels, and superalloys, titanium has found a niche in many industries. Much of this use has occurred through military research, and subsequent applications in aircraft, of gas turbine engines, although more recent use features replacement joints, golf clubs, and bicycles. Contents include: A primer on titanium and its alloys, Introduction to selection of titanium alloys, Understanding titanium's metallurgy and mill products, Forging and forming, Castings, Powder metallurgy, Heat treating, Joining technology and practice, Machining, Cleaning and finishing, Structure/processing/property relationships, Corrosion resistance, Advanced alloys and future directions, Appendices: Summary table of titanium alloys, Titanium alloy datasheets, Cross-reference to titanium alloys, Listing of selected specification and standardization organizations, Selected manufacturers, suppliers, services, Corrosion data, Machining data.
Cinemicrographic observations on the trophoblast and zona pellucida of the mouse blastocyst.

The mammalian ovum is surrounded by a secondary membrane, the zona pellucida, which is produced by the follicle cells round the ovarian oocyte. The major constituents of this membrane are neutral or weakly acidic mucoproteins, and it is sensitive to dissolution by a variety of proteases, depending on species (Gwatkin, 1964), especially the bacterial protease “Pronase” (Mintz, 1962). In the rabbit and rat the zona is impermeable to compounds with a molecular weight above 1200 (Austin & Lovelock, 1958). Since in all mammals, an intact zona surrounds the cleavage stages and early blastocyst, this membrane must be removed, or penetrated by the trophoblast cells before implantation can take place. This could result from the interaction of chemical or mechanical factors produced either by the conceptus or by the uterus, or from a combination of some or all of these.
Bootstrapping Coreference Classifiers with Multiple Machine Learning Algorithms

Successful application of multi-view co-training algorithms relies on the ability to factor the available features into views that are compatible and uncorrelated. This can potentially preclude their use on problems such as coreference resolution that lack an obvious feature split. To bootstrap coreference classifiers, we propose and evaluate a single-view weakly supervised algorithm that relies on two different learning algorithms in lieu of the two different views required by co-training. In addition, we investigate a method for ranking unlabeled instances to be fed back into the bootstrapping loop as labeled data, aiming to alleviate the problem of performance deterioration that is commonly observed in the course of bootstrapping.