Miracle-dz/UniFAR-FTUs huggingface dataset:
Initial evaluation of virtual un-enhanced imaging derived from fast kVp-switching dual energy contrast enhanced CT for the abdomen

The feasibility and utility of creating virtual un-enhanced images from contrast enhanced data acquired using a fast switching dual energy CT acquisition, is explored. Utilizing projection based material decomposition data, monochromatic images are generated and a Multi-material decomposition technique is applied. Quantitative and qualitative evaluation is performed to assess the equivalence of Virtual Un-Enhanced (VUE) and True Un-enhanced (TUE) for multiple tissue types and different organs in the abdomen. Ten patient cases were analyzed where a TUE and a subsequent Contrast Enhanced (CE) acquisition were obtained using fast kVp-switching dual energy CT utilizing Gemstone Spectral Imaging. Quantitative measurements were made by placing multiple Regions of Interest on the different tissues and organs in both the TUE and the VUE images. The absolute Hounsfield Unit (HU) differences in the mean values between TUE & VUE were calculated as well as the differences of the standard deviations. Qualitative analysis was done by two radiologists for overall image quality, presence of residual contrast, appearance of pathology, appearance and contrast of normal tissues and organs in comparison to the TUE. There is a very strong correlation between the TUE and VUE images.
Scalable Secure Computation of Statistical Functions with Applications to k-Nearest Neighbors

Given a set $S$ of $n$ $d$-dimensional points, the $k$-nearest neighbors (KNN) is the problem of quickly finding $k$ points in $S$ that are nearest to a query point $q$. The $k$-nearest neighbors problem has applications in machine learning for classification and regression and also in searching. The secure version of KNN where either $q$ or $S$ are encrypted, has applications such as providing services over sensitive (such as medical or localization) data. In this work we present the first scalable and efficient algorithm for solving KNN with Fully Homomorphic Encryption (FHE) that is realized by a polynomial whose degree is independent of $n$, the number of points. We implemented our algorithm in an open source library based on HELib implementation for the Brakerski-Gentry-Vakuntanthan's FHE scheme, and ran experiments on MIT's OpenStack cloud. Our experiments show that given a query point $q$, we can find the set of 20 nearest points out of more than 1000 points in less than an hour. Our result introduces a statistical coreset, which is a data summarization technique that allows statistical functions, such as moments, to be efficiently and scalably computed. As a central tool, we design a new coin toss technique which we use to build the coreset. This coin toss technique and computation of statistical functions may be of independent interest.
OntDR: An Ontology-based Augmented Method for Document Retrieval

document retrieval is one of the fast growing and complex research area in the field of information retrieval. An effective Information retrieval can be obtained only under strong document retrieval algorithm. As compared to the information retrieval, document retrieval is also a tedious process. The accurate retrieval of a document needs highly precise and mathematically vibrant methods. A number of researches have been targeted for the document retrieval, which yielded expected result within their boundaries. In this paper, we proposed an ontology-based augmented method for document retrieval. The ontology defined in our proposed approach gives extra freedom to choose between the documents and thus give an accurate retrieval of the documents. The mutual association (MA) value specifies the interrelated documents in the problem space. The array index values, which we provide, give accurate distinction between each document. The results and analysis of our proposed method showed expected results and a comparative analysis was subjected for analyzing the proposed method with an existing algorithm. The F-measure comparison showed the performance improvement of the proposed method with respect to the existing method.
AQM stability in multiple bottleneck networks

In this paper, we highlight that multiple bottlenecks can affect the performance of active queue management controllers, which are usually configured on a single bottleneck basis, as if each controller were the only element regulating the TCP traffic along its path. To see this, we consider a network scenario where RED is configured at each router, according to previously developed control theoretic techniques. These configuration rules assure stability in a single bottleneck scenario. Yet, we show that instability may arise when two link become congested. We justify this result through a multiple bottleneck model and give guidelines for new cooperative AQM controllers.
Stabilization of a helicopter using optical flow

Estimating position and orientation (pose) of an object in real time constitutes an important issue for vision-based control of robots. In this paper, we present a nonlinear controller design based on vision and its application in a quadrotor. Experiment results show good performance of the proposed controller using “real-time” optical flow and image processing.
Stem Cell Selection In Vivo Using Foamy Vectors Cures Canine Pyruvate Kinase Deficiency

Background Hematopoietic stem cell (HSC) gene therapy has cured immunodeficiencies including X-linked severe combined immunodeficiency (SCID-X1) and adenine deaminase deficiency (ADA). For these immunodeficiencies corrected cells have a selective advantage in vivo, and low numbers of gene-modified cells are sufficient to provide therapeutic benefit. Strategies to efficiently transduce and/or expand long-term repopulating cells in vivo are needed for treatment of diseases that require higher levels of corrected cells, such as hemoglobinopathies. Here we expanded corrected stem cells in vivo in a canine model of a severe erythroid disease, pyruvate kinase deficiency. Methodology/Principal Findings We used a foamy virus (FV) vector expressing the P140K mutant of methylguanine methyltransferase (MGMTP140K) for in vivo expansion of corrected hematopoietic repopulating cells. FV vectors are attractive gene transfer vectors for hematopoietic stem cell gene therapy since they efficiently transduce repopulating cells and may be safer than more commonly used gammaretroviral vectors. Following transplantation with HSCs transduced ex vivo using a tri-cistronic FV vector that expressed EGFP, R-type pyruvate kinase, and MGMTP140K, we were able to increase marking from approximately 3.5% to 33% in myeloid long-term repopulating cells resulting in a functional cure. Conclusions/Significance Here we describe in one affected dog a functional cure for a severe erythroid disease using stem cell selection in vivo. In addition to providing a potential cure for patients with pyruvate kinase deficiency, in vivo selection using foamy vectors with MGMTP140K has broad potential for several hematopoietic diseases including hemoglobinopathies.
An autoradiographic study of the mouse olfactory epithelium: Evidence for long‐lived receptors

In order to try to determine whether differentiated olfactory receptors turn over (die and are replaced by newly differentiated cells) during adult life, mice were injected with a single dose of 3H‐thymidine at either 2 or 4 months of age and allowed to survive for up to 12 months; they were caged in a laminar flow unit to prevent rhinitis. Counts of labeled receptor cells detected autoradiographically after injection at 2 months of age revealed that, following an initial decrease from 1 to 3 months of survival, numbers of labeled cells remained approximately constant, at least up to 12 months of survival. Cells still labeled at 12 months of survival were confirmed as receptor cells by electron microscopic examination of reembedded sections. The hypothesis is suggested that in the absence of disease‐related destruction of the olfactory epithelium, most or all receptor cell turnover represents newly formed cells that fail to establish synapses with the olfactory bulb; fully differentiated receptor cells may be quite long‐lived.
A framework for specific term recommendation systems

In this paper we present the IRSA framework that enables the automatic creation of search term suggestion or recommendation systems (TS). Such TS are used to operationalize interactive query expansion and help users in refining their information need in the query formulation phase. Our recent research has shown TS to be more effective when specific to a certain domain. The presented technical framework allows owners of Digital Libraries to create their own specific TS constructed via OAI-harvested metadata with very little effort.
Technical Note: Description and Use of the New Jump Mass Spectrum Mode of Operation for the Aerodyne Quadrupole Aerosol Mass Spectrometers (Q-AMS)

A new mode of operation for the Aerodyne Quadrupole Aerosol Mass Spectrometer (Q-AMS) has been developed and used to improve the detection limits and time resolution of the instrument. The Jump Mass Spectrum (JMS) mode works by stepping through a small number of specific user defined positions within the mass spectrum, increasing the time spent scanning specific m/z's . The JMS mode is conceptually similar to the “Selected Ion Monitoring” mode of some commercial quadrupole-based instrumentation and can be used for direct quantification when the fragmentation pattern is known. The JMS mode can also be used to augment the standard Q-AMS operation in Mass Spectrum mode when the fragmentation pattern is not known, improving the effective signal-to-noise ratio (SNR) and in turn the detection limits and time resolution. A decrease in detection limits for the Q-AMS by factors of 4.6, 3.9, 1.3, and 3.5 for nitrate, sulphate, total organics, and m/z 43 mass loadings respectively was achieved for 1 minute sampling (20 s in each of the three Q-AMS modes, monitoring 10 m/z in JMS mode). Although the benefit to the SNR of the total organic mass concentration measured by the Q-AMS is smaller, sensitivity to organic fragments which can act as markers for various sources and processes (such as fresh primary anthropogenic emissions, aged secondary organics, and biomass burning aerosol), is greatly increased by the JMS mode. Example data from applications that benefit from this technique are presented, including an aircraft platform and in smog chamber experiments, alongside high time-resolution, ground-based data.
WHAT MAGNETAR SEISMOLOGY CAN TEACH US ABOUT MAGNETIC FIELDS

The effect of magnetic fields on the frequencies of toroidal oscillations of neutron stars is derived to lowest order. We suggest that the fine structure in the quasiperiodic oscillation power spectrum of magnetars following giant flares reported by Strohmayer & Watts is magnetic splitting of degenerate toroidal modes, and we estimate a corresponding crustal magnetic field on the order of 1015 Gauss or more. We suggest that residual m, −m symmetry following such splitting, together with nonaxisymmetric or rotational splitting of the residual symmetry, might allow beating of individual frequency components that is slow enough to be observed.
The bone marrow microenvironment contributes to type I diabetes induced osteoblast death

Type I diabetes increases an individual's risk for bone loss and fracture, predominantly through suppression of osteoblast activity (bone formation). During diabetes onset, levels of blood glucose and pro‐inflammatory cytokines (including tumor necrosis factor α (TNFα)) increased. At the same time, levels of osteoblast markers are rapidly decreased and stay decreased chronically (i.e., 40 days later) at which point bone loss is clearly evident. We hypothesized that early bone marrow inflammation can promote osteoblast death and hence reduced osteoblast markers. Indeed, examination of type I diabetic mouse bones demonstrates a greater than twofold increase in osteoblast TUNEL staining and increased expression of pro‐apoptotic factors. Osteoblast death was amplified in both pharmacologic and spontaneous diabetic mouse models. Given the known signaling and inter‐relationships between marrow cells and osteoblasts, we examined the role of diabetic marrow in causing the osteoblast death. Co‐culture studies demonstrate that compared to control marrow cells, diabetic bone marrow cells increase osteoblast (MC3T3 and bone marrow derived) caspase 3 activity and the ratio of Bax/Bcl‐2 expression. Mouse blood glucose levels positively correlated with bone marrow induced osteoblast death and negatively correlated with osteocalcin expression in bone, suggesting a relationship between type I diabetes, bone marrow and osteoblast death. TNF expression was elevated in diabetic marrow (but not co‐cultured osteoblasts); therefore, we treated co‐cultures with TNFα neutralizing antibodies. The antibody protected osteoblasts from bone marrow induced death. Taken together, our findings implicate the bone marrow microenvironment and TNFα in mediating osteoblast death and contributing to type I diabetic bone loss. J. Cell. Physiol. 226: 477–483, 2011. © 2010 Wiley‐Liss, Inc.
Attribute associated image retrieval and similarity reranking

Existence of countless digital images has given rise to image retrieval in many applications. Conventional image databases being text-annotated pose two major problems of keywords for images and complexity. Hence, retrieval systems based on image's visual content are more desirable [1]. The content based image retrieval (CBIR) technique, employed here uses visual cues to retrieve images. This technique is query based, extracts the most vital attributes like color, shape and texture. Automatic extraction of spatial based color feature and invariant Fourier descriptors makes it more flexible. The extent of each attribute is obtained from the user, compared with attributes of images in database and most similar images are retrieved based on the degree of similarity.
A Soft Decision-Based Speech Enhancement Using Acoustic Noise Classification

In this letter, we present a speech enhancement technique based on the ambient noise classification incorporating the Gaussian mixture model (GMM). The principal parameters of the statistical model-based speech enhancement algorithm such as the weighting parameter in the decision-directed (DD) method and the long-term smoothing parameter of the noise estimation, are chosen as different values according to the classified contexts to ensure best performance for each noise. For the real-time environment awareness, the noise classification is performed on a frame-by-frame basis using the GMM with the soft decision framework. Thespeechabsenceprobability(SAP)isusedindetecting the speech absence periods and updating the likelihood of the GMM. Index Terms: Speech Enhancement, Noise Classification, Soft Decision, Gaussian Mixture Model
What is Data Sketching , and Why Should I Care ?

Do you ever feel overwhelmed by a constant stream of information? It can seem like there is a barrage of new email and text messages arriving, phone calls, articles to read, and knocks on the door. Putting these pieces together to keep track of what’s important can be a real challenge. The same information overload is of concern in many computational settings. For example, telecommunications companies want to keep track of the activity on their network, to identify the overall network health, and spot anomalies or changes in behavior. Yet, the scale of events occurring is huge: many millions of network events per hour, per network element. And while new technologies allow the scale and granularity of events being monitored to increase by orders of magnitude, the capacity of computing elements to make sense of these (processors, memory and disks) is barely increasing. Even on a small scale, the amount of information may be too large to store in an impoverished setting (say, an embedded device), or be too big to conveniently keep in fast storage. In response to this challenge, the model of streaming data processing has grown in popularity. In this setting, the aim is no longer to capture, store and index every minute event, but rather to quickly process each observation to create some summary of the current state. Following its processing, an event is dropped, and is no longer accessible. The summary that is retained is often referred to as sketch of the data. Coping with the vast scale of information means making a number of compromises: the description of the world is approximate, rather than exact; the nature of queries to be answered must be decided in advance, rather than after the fact; and some questions are now insoluble. However, the ability to process vast quantities of data at blinding speeds with modest resources can more than make up for these limitations. As a consequence, streaming methods have been adopted in a number of domains, starting with telecommunications, but spreading to search engines, social networks, finance, and time-series analysis. These ideas are also finding application in areas where traditional approaches are applicable, but the rough and ready sketching approach is more cost-effective. Successful applications of sketching involve a mixture of algorithmic tricks, systems know-how, and mathematical insight, and have led to new research contributions in each of these areas. In this article, we introduce the ideas behind, and applications, of sketching, with a focus on the algorithmic innovations. That is, we describe some algorithmic developments in the abstract, and then indicate the subsequent steps needed to put them into practice, with examples. We will see four novel algorithmic ideas, and discuss some emerging areas.
Image restoration of arbitrarily warped documents

We present a framework for acquiring and restoring images of warped documents. The purpose of our restoration is to create a planar representation of a once planar document that has undergone an arbitrary and unknown rigid deformation. To accomplish this restoration, our framework acquires and flattens the 3D shape of a warped document to determine a nonlinear image transform that can correct for image distortion caused by the document's shape. Our framework is designed for use in library and museum digitization efforts where very old and badly damaged manuscripts are imaged.
On-demand dynamic summary-based points-to analysis

Static analyses can be typically accelerated by reducing redundancies. Modern demand-driven points-to or alias analysis techniques rest on the foundation of Context-Free Language (CFL) reachability. These techniques achieve high precision efficiently for a small number of queries raised in small programs but may still be too slow in answering many queries for large programs in a context-sensitive manner. We present an approach, called DynSum, to perform context-sensitive demand-driven points-to analysis fully on-demand by means of computing CFL-reachability summaries without any precision loss. The novelty lies in initially performing a Partial Points-To Analysis (PPTA) within a method, which is field-sensitive but context-independent, to summarize its local points-to relations encountered during a query and reusing this information later in the same or different calling contexts. We have compared DynSum with RefinePTS, a refinement-based analysis, using three clients (safe casting, null dereferencing and factory methods) for a suite of nine Java programs. DynSum's average speedups are 1.95x, 2.28x and 1.37x, respectively. We have also compared DynSum with a static approach, which is referred to StaSum here, to show its improved scalability for the same three clients.
Fighting Coordinated Attackers with Cross-Organizational Information Sharing

In this paper we propose an architecture for using crossorganization information sharing to identify members of a group of hosts enslaved for malicious purposes on the Internet. We root our system in so-called “detectives”— savvy network monitors like sophisticated intrusion detection systems or honeyfarms that have a deep understanding of malicious behavior. We augment information from these detectives with observations from a large array of “witnesses” that are already in-place at many locations in the network. These witnesses are not savvy enough to understand that a particular behavior is malicious, but their simple factual observations can be shared with a detective in order to form a broad picture of a group of bad actors. A key aspect of the system is the design of a lightweight mechanism to reliably share enough information between detectives and witnesses to form an understanding of a group of bad actors without sharing more information than necessary, in order to address privacy and competitive concerns.
Recent developments in deposition techniques for optical thin films and coatings

Abstract: The most significant processes for optical coating manufacture are variants of vacuum deposition. Thermal evaporation is the traditional process and still of great importance but in the last two decades there has been a major shift to the energetic processes, primarily ion and plasmaassisted deposition and various forms of sputtering. Vacuum processes are very flexible and so dominate short-run production but various forms of pulsed chemical vapor deposition are just starting to appear in long runs of very specialized components. There is also a wide range of other viable and occasionally used techniques, with various degrees of promise, ranging from arc evaporation to liquid deposition.
A Practical Model of Convective Dynamics for Stellar Evolution Calculations

Turbulent motions in the interior of a star play an important role in its evolution, since they transport chemical species, thermal energy and angular momentum. Our overall goal is to construct a practical turbulent closure model for convective transport that can be used in a multi‐dimensional stellar evolution calculation including the effects of rotation, shear and magnetic fields. Here, we focus on the first step of this task: capturing the well‐known transition from radiative heat transport to turbulent convection with and without rotation, as well as the asymptotic relationship between turbulent and radiative transport in the limit of large Rayleigh number. We extend the closure model developed by Ogilvie (2003) and Garaud and Ogilvie (2005) to include heat transport and compare it with experimental results of Rayleigh‐Benard convection.
p53 suppresses type II endometrial carcinomas in mice and governs endometrial tumour aggressiveness in humans

Type II endometrial carcinomas are a highly aggressive group of tumour subtypes that are frequently associated with inactivation of the TP53 tumour suppressor gene. We show that mice with endometrium‐specific deletion of Trp53 initially exhibited histological changes that are identical to known precursor lesions of type II endometrial carcinomas in humans and later developed carcinomas representing all type II subtypes. The mTORC1 signalling pathway was frequently activated in these precursor lesions and tumours, suggesting a genetic cooperation between this pathway and Trp53 deficiency in tumour initiation. Consistent with this idea, analyses of 521 human endometrial carcinomas identified frequent mTORC1 pathway activation in type I as well as type II endometrial carcinoma subtypes. mTORC1 pathway activation and p53 expression or mutation status each independently predicted poor patient survival. We suggest that molecular alterations in p53 and the mTORC1 pathway play different roles in the initiation of the different endometrial cancer subtypes, but that combined p53 inactivation and mTORC1 pathway activation are unifying pathogenic features among histologically diverse subtypes of late stage aggressive endometrial tumours.