Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Survival Outcomes in Cancer Patients with Hereditary Hemorrhagic Telangiectasia

Background: Hereditary hemorrhagic telangiectasia (HHT) is a genetic disorder characterized by deficiency in endoglin, an angiogenic protein. The net effect of endoglin expression on cancer outcomes from animal studies has proven controversial. We evaluated whether reduced systemic endoglin levels, expected in patients diagnosed with HHT, impacted clinical outcomes for cancer. Methods: A retrospective cohort analysis using Surveillance, Epidemiology, and End Results–Medicare was conducted to evaluate the effect of HHT on survival among patients diagnosed with breast, colorectal, lung, or prostate cancer between 2000 and 2007 (n = 540,520). We generated Kaplan–Meier survival curves and Cox models to compare the effect of HHT on all-cause survival for a composite of the four cancers, and separate models by cancer, adjusting for demographic variables, cancer type, cancer stage, and comorbidities. Results: All-cause survival analysis for a composite of the four cancers showed an adjusted HR of 0.69 [95% confidence interval (CI) of 0.51–0.91; P = 0.009] for HHT, indicating significantly improved survival outcome. When stratified by cancer type, HHT diagnosis showed a significant protective effect among breast cancer patients with an adjusted HR of 0.31 (95% CI, 0.13–0.75; P = 0.009). Conclusions: There was a significant association between HHT and improved survival outcome for a composite of patients with breast, prostate, colorectal, and lung cancer, and in analysis stratified by cancer, the association was significant for HHT patients with breast cancer. Impact: This study supports the hypothesis that systemically educed endoglin expression is associated with improved survival outcome in multiple cancers, and suggests that anti-endoglin antibody therapy may have broad-based application. Cancer Epidemiol Biomarkers Prev; 23(1); 117–25. ©2013 AACR.
SpeedTracer: A Web Usage Mining and Analysis Tool

SpeedTracer, a World Wide Web usage mining and analysis tool, was developed to understand user surfing behavior by exploring the Web server log files with data mining techniques. As the popularity of the Web has exploded, there is a strong desire to understand user surfing behavior. However, it is difficult to perform user-oriented data mining and analysis directly on the server log files because they tend to be ambiguous and incomplete. With innovative algorithms, SpeedTracer first identifies user sessions by reconstructing user traversal paths. It does not require “cookies” or user registration for session identification. User privacy is protected. Once user sessions are identified, data mining algorithms are then applied to discover the most common traversal paths and groups of pages frequently visited together. Important user browsing patterns are manifested through the frequent traversal paths and page groups, helping the understanding of user surfing behavior. Three types of reports are prepared: user-based reports, path-based reports and group-based reports. In this paper, we describe the design of SpeedTracer and demonstrate some of its features with a few sample reports.
Common Variation in SIM1 Is Reproducibly Associated With BMI in Pi ma Indians

OBJECTIVE Haploinsufficiency of SIM1 is a cause of rare monogenic obesity. To assess the role of SIM1 in polygenic obesity, this gene was analyzed in the Pima Indian population, which has a high prevalence of obesity. RESEARCH DESIGN AND METHODS SIM1 was sequenced in 96 individuals. Variants (n = 46) were genotyped in a population-based sample of 3,250 full-heritage Pima Indians and in a separate replication sample of 2,944 predominately non–full-heritage subjects from the same community. RESULTS Variants spanning the upstream region of SIM1 through intron 8 were associated with BMI in the full-heritage Pima Indians, where the strongest associations (P ∼ 10−4 to 10−6) were with common variants (risk allele frequency 0.61–0.67). The difference in mean BMI between individuals homozygous for the major allele compared with homozygotes for the minor allele was ∼2.2 kg/m2 (P = 2 × 10−5 for rs3213541). These associations replicated in the separate sample of subjects from the same community (P = 5 × 10−3 for rs3213541). The strongest associations (P = 4 × 10−7, controlled for age, sex, birth year, and heritage) were seen in the combined sample (n = 6,194). The risk allele for obesity was more common in full-heritage Pimas than in the mixed-heritage subjects. Two variants (rs3734353 and rs3213541) were also genotyped in 1,275 severely obese and 1,395 lean control subjects of French European ancestry. The Pima risk alleles were the minor alleles in the European samples, and these variants did not display any significant association (P > 0.05). CONCLUSIONS Common variation in SIM1 is associated with BMI on a population level in Pima Indians where the risk allele is the major allele.
NANOPARTICLE DEPOSITION AND DOSIMETRY FOR IN VITRO TOXICOLOGY

This thesis addresses several issues in the field of in vitro toxicology involving particle exposure. First, controlling and assessing particle dosimetry in in vitro models is addressed. Traditional in vitro models expose cells grown at the bottom of a dish to nanoparticles under static conditions, regardless of the exposure route of interest (e.g. inhalation, ingestion, systemic translocation). We demonstrated the use of flowing media to reduce sedimentation and simplify dosimetry. The shear stress introduced at the cell layer was found to be much lower than physiological conditions, avoiding potential damage to the cells, and allowing this model to serve as a straightforward approach for dosimetry that can be easily adopted using standard cell culture tools for a broad range of cell types. For the second and third studies, aerosol methods were used to represent inhalation exposure. In the second study, the deposition of ultrafine (<100 nm) and fine (100–2500 nm) aerosol particles onto cells at an air–liquid interface (ALI) was investigated. We studied the effect of chamber design and electrostatics on aerosol deposition using both theoretical and empirical techniques to provide guidelines for controlling the dose of submicron aerosols, which has been a significant challenge to date. Third, we designed and validated a scaled–up portable multi–well aerosol exposure chamber (PM–AEC). The device contains eight wells for cell culture inserts arranged
An artificial neural network architecture for skeletal age assessment

Skeletal age assessment is a common and time-consuming task in pediatric radiology. In this work we describe a system which implements the TW2 method, using a neural network architecture. Each bone complex is localized on the image, and preprocessed using either a Gabor transform or a multiscale difference of Gaussian filtering. The output of the preprocessing stage is fed to a set of neural networks trained to classify each bone accordingly to the TW2 method. Afterward, the skeletal age is estimated and compared with the classification of an expert radiologist.
Exploration and Adaptation in Multiagent Systems: A Model-based Approach

Agents that operate in a multi-agent system can benefit significantly from adapting to other agents while interacting with them. This work presents a general architecture for a modelbased learning strategy combined with an exploration strategy. This combination enables adaptive agents to learn models of their rivals and to explore their behavior for exploitation in future encounters. We report experimental results in the Iterated Prisoner’s Dilemma domain, demonstrating the superiority of the model-based learning agent over non-adaptive agents and over reinforcement-learning agents. The Experimental results also show that exploration can improve the performance of a modelbased agent significantly.
Core-Loss Prediction for Non-Oriented Electrical Steels Based on the Steinmetz Equation Using Fixed Coefficients With a Wide Frequency Range of Validity

An accurate prediction of the core losses is crucial for the optimal design and selection of the electrical steels used in electrical devices. The measured specific core losses are divided into three main parts, i.e., the eddy-current loss, the hysteresis loss, and the excess loss. In this paper, a simplified, predictive model for the core loss in a non-oriented electrical steel using fixed coefficients is proposed. The coefficients for a wide frequency spectrum up to 10 000 Hz of validity for the prediction of the eddy current, the hysteresis, and the excess components were calculated with respect to a sinusoidal voltage using the modified Steinmetz equation and a polynomial regression analysis.
Gaia Data Release 1. Summary of the astrometric, photometric, and survey properties

At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. We summarize Gaia DR1 and provide illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Gaia DR1 consists of: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set,consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ~3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas/yr for the proper motions. A systematic component of ~0.3 mas should be added to the parallax uncertainties. For the subset of ~94000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas/yr. For the secondary astrometric data set, the typical uncertainty of the positions is ~10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ~0.03 mag over the magnitude range 5 to 20.7. Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.
An experimental multilingual speech translation system

In this paper, we describe an experimental speech translation system utilizing small, PC-based hardware with multi-modal user interface. Two major problems for people using an automatic speech translation device are speech recognition errors and language translation errors. In this paper we focus on developing techniques to overcome these problems. The techniques include a new language translation approach based on example sentences, simplified expression rules, and a multi-modal user interface which shows possible speech recognition candidates retrieved from the example sentences. Combination of the proposed techniques can provide accurate language translation performance even if the speech recognition result contains some errors. We propose to use keyword classes by looking at the dependency between keywords to detect the misrecognized keywords and to search the example expressions. Then, the suitable example expression is chosen using a touch panel or by pushing buttons. The language translation picks up the expression in the other language, which should always be grammatically correct. Simplified translated expressions are realized by speech-act based simplifying rules so that the system can avoid various redundant expressions. A simple comparison study showed that the proposed method outputs almost 2 to 10 times faster than a conventional translation device.
Selective encryption techniques of JPEG2000 codestream for medical images transmission

In this paper, novel selective encryption image schemes based on JPEG2000 are proposed. The first one encrypts only the code-blocks corresponding to some sensitive precincts. In order to improve the security level we introduce the permutation of codeblocks contributing in the selected precincts. The idea of combining permutation and selective encryption is used in order to minimize the amount of processed data encryption while ensuring the best possible degradation through the permutation. Many of proposals format compliant encryption schemes for JPEG2000 that have been made encrypt packet body data, but leave header packet in plaintext. The second approach, combines code-blocks data encryption to a cyclic permutation of all packets headers in the bitstream. Actually, in the JPEG2000 codestream, packet header information is specific to the visual content, and it is can be used as a fingerprint of the codestream. Symmetric encryption AES with CFB mode is used to encrypt in the two schemes. The proposed schemes don't introduce superfluous JPEG2000 markers in the protected codestream, i.e, its format is compliant to JPEG2000 codestream one. It keeps file format and compression ratio unchanged and doesn't degrade the original error robustness. The proposed scheme works with any standard ciphers and introduces negligible computational cost.
Abstraction and Assume-Guarantee Reasoning for Automated Software Verification

Compositional verification and abstraction are the key techniques to address the state explosion problem associated with model checking of concurrent software. A promising compositional approach is to prove properties of a system by checking properties of its components in an assume-guarantee style. This article proposes a framework for performing abstraction and assume-guarantee reasoning of concurrent C code in an incremental and fully automated fashion. The framework uses predicate abstraction to extract and refine finite state models of software and it uses an automata learning algorithm to incrementally construct assumptions for the compositional verification of the abstract models. The framework can be instantiated with different assume-guarantee rules. We have implemented our approach in the COMFORT reasoning framework and we show how COMFORT out-performs several previous software model checking approaches when checking safety properties of non-trivial concurrent programs.
A Nested-Lumen Nerve Graft Design for Neuroengineering

A biomimetic nerve graft design was developed for use in peripheral nerve regeneration. Nerve endings are difficult to suture or enjoin without support and autograft techniques also lead to added morbidity. Most clinically available synthetic nerve grafts are only capable of facilitating neuroregeneration across small lesions ( 5 mm). Nested single-lumen and multilumen configurations with an insulating outer-portion were developed to mimic the fascicular architecture observed in peripheral nerves. Polymer solutions and composite suspensions were electrospun into microfiber membranes under the influence of 5 kV electric field. 80mm length conduit graft specimens were fabricated. Specimens were tension tested and found to have a Young’s Modulus of 15.7 ± 2.9 MPa and a tensile strength of 1.17 ± 0.16 MPa and 1.37 ± 0.08 MPa for the single and multi-channel grafts respectively. Graft specimens were verified for spinal cord (kangaroo tail) attachment by suturing and did not result in tearing under 1.2 N tensile load. A preliminary neurotoxicity study using N2A cell-line confirmed cell-scaffold adhesion and viability.
Sensor technology for ice hockey and skating

Sensor technology that is unobtrusively integrated into the clothing and equipment of an athlete can support the training of sport activities and monitor the athlete's progress. In this paper, we propose two wearable systems that support ice hockey players in the training of skating and shooting. These assistants measure the motions of players and compare them with reference executions of the same activities by professional players. A third system that we introduce monitors the player;s activities during a hockey game and creates a match report for objective performance measurement. For each of the three proposed applications, we present a prototype setup that we evaluate with amateur and professional players. The main findings are i) that with a skate-worn motion sensor and user-dependent training, eight skating motions can be spotted with an accuracy above 90%, ii) that stick-integrated sensors enable the measurement of relevant shot features, which differentiate professional from amateur athletes, and iii) that it is possible to spot important ice hockey activities in the signals of body-worn motion sensors worn during a game.
Photoreceptor cells in the vitiligo mouse die by apoptosis. TRPM-2/clusterin expression is increased in the neural retina and in the retinal pigment epithelium.

PURPOSE To determine the mechanism of photoreceptor cell death in the vitiligo mouse, a model of retinal degeneration in which the genetic defect is not retina specific but is instead caused by single point mutation in the microphthalmia (mi) gene that codes for a basic helix-loop-helix DNA transcription factor. METHODS Detection of apoptotic cells was performed in fixed retinal tissue using the TUNEL assay in animals 1, 2, 4, 6, 8, 16, 32, 40, and 52 weeks. Electron microscopic analysis was used to confirm the morphologic hallmarks of apoptosis, and Southern blot analysis was used to detect internucleosomal DNA fragmentation. Additionally, the expression of a gene associated with apoptosis, TRPM-2/clusterin, was examined. RESULTS At ages beyond the time of normal retinal programmed cell death, vitiligo retinas had significantly more TUNEL-positive photoreceptor cells and more photoreceptor cells with condensed chromatin than controls. DNA internucleosomal fragmentation ladders were present in vitiligo retinas even as late as 15 weeks, a time well beyond developmental apoptosis in controls. TRPM-2/clusterin mRNA levels in vitiligo neural retinas were similar to controls initially but were two times greater than controls by 12 weeks. Surprisingly, TRPM-2/clusterin mRNA levels were elevated in the retinal pigment epithelium in the mutant; the expression at one week was two times greater than normals and remained elevated for many months, even though retinal pigment epithelial cells showed no morphologic evidence of apoptosis. CONCLUSIONS The morphologic and biochemical data suggest that photoreceptor cells die by apoptosis in vitiligo mice. The increased retinal TRPM-2/clusterin mRNA levels may be a direct response to these events. The increased expression of this gene in the retinal pigment epithelium, however, may reflect its role in tissue regression and membrane remodeling. Mechanisms by which the mi gene defect might result in the vitiligo retinopathy are proposed.
Joint layer resource allocation for multimedia packet CDMA systems

A joint layer resource allocation algorithm is proposed for CDMA networks carrying integrated services. The link quality requirements of heterogeneous services, which measured in fading channel environments, as well as other physical layer resources are mapped into the equivalent spectral bandwidth which can be allocated to calls in different layers with the cross- layer optimization. The QoS in terms of BER and latency time for different services can be guaranteed by the scheme. The numerical results show that the performance of the proposed system in terms of spectral efficiency is better than that of the existing systems.
A Persistent Stress Response to Impeded Axonal Transport Leads to Accumulation of Amyloid-β in the Endoplasmic Reticulum, and Is a Probable Cause of Sporadic Alzheimer’s Disease

Background and Objective: Could a normal – but persistent – stress response to impeded axonal transport lead to late-onset Alzheimer’s disease (AD)? Our results offer an affirmative answer, suggesting a mechanism for the abnormal production of amyloid-β (Aβ), triggered by the slowed axonal transport at old age. We hypothesize that Aβ precursor protein (APP) is a sensor at the endoplasmic reticulum (ER) that detects, and signals to the nucleus, abnormalities in axonal transport. When persistently activated, due to chronically slowed-down transport, this signaling pathway leads to accumulation of Aβ within the ER. Methods and Results: We tested this hypothesis with the neuronal cell line CAD. We show that, normally, a fraction of APP is transported into neurites by recruiting kinesin-1 via the adaptor protein, Fe65. Under conditions that block kinesin-1-dependent transport, APP, Fe65 and kinesin-1 accumulate in the soma, and form a complex at the ER. This complex recruits active c-Jun N-terminal kinase (JNK), which phosphorylates APP at Thr668. This phosphorylation increases the cleavage of APP by the amyloidogenic pathway, which generates Aβ within the ER lumen, and releases Fe65 into the cytoplasm. Part of the released Fe65 translocates into the nucleus, likely to initiate a gene transcription response to arrested transport. Prolonged arrest of kinesin-1-dependent transport could thus lead to accumulation and oligomerization of Aβ in the ER. Conclusion: These results support a model where the APP:Fe65 complex is a sensor at the ER for detecting the increased level of kinesin-1 caused by halted transport, which signals to the nucleus, while concomitantly generating an oligomerization-prone pool of Aβ in the ER. Our hypothesis could thus explain a pathogenic mechanism in AD.
Maximum Margin/Volume Outlier Detection

Due to the absence or scarcity of outliers, designing a robust outlier detector is very challenging. In this paper, we first propose to use the maximum margin criterion to sift unknown outliers from a given data set, which demonstrates superior performance in outlier detection. However, the resultant learning task is formulated as a Mixed Integer Programming (MIP) problem, which is computationally hard. To this end, we alter the recently developed label generating technique, which efficiently solves a convex relaxation of the MIP problem of outlier detection. Specifically, we propose an effective procedure to find a largely violated labeling vector for identifying rare outliers from abundant normal patterns, and its convergence is also presented. Then, a set of largely violated labeling vectors are combined by multiple kernel learning methods to robustly detect outliers. Besides these, to further enhance the efficacy of our outlier detector, we also explore the use of maximum volume criterion to measure the quality of separation between outliers and normal patterns. This criterion can be easily incorporated into our proposed framework by introducing an additional regularization. Comprehensive experiments on real-world data sets verify that the outlier detectors using the two proposed criteria outperform existing outlier detection methods.