Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytoplasmic Expression of Pontin in Renal Cell Carcinoma Correlates with Tumor Invasion, Metastasis and Patients’ Survival

Renal cell carcinoma (RCC) is the most lethal of all genitourinary malignancies. Distant metastasis represents the major cause of death in patients with RCC. Recent studies have implicated the AAA+ ATPase pontin in many cellular activities that are highly relevant to carcinogenesis. In this study, we demonstrate for the first time that pontin was up-regulated in RCC, and plays a previously unknown pro-invasive role in the metastatic progression of RCC through epithelial-to-mesenchymal transition (EMT) pathway. 28 pairs of freshly frozen clear cell RCC samples and the matched normal renal tissues analyzed by quantitative RT-PCR and western blotting demonstrated that pontin was up-regulated in clear cell RCC tissues than in normal renal tissues. In addition, immunohistochemistry was used to evaluate subcellular pontin expression in 95 RCC patients, and found that overexpression of pontin in cytoplasm positively correlated with the metastatic features, predicting unfavorable outcomes of RCC patients. Furthermore, in vitro experiments show pontin was predominantly expressed in cytoplasm of RCC cell lines, and a significant suppression of cell migration and invasion in pontin siRNA treated RCC cell lines was observed. Mechanistic studies show that pontin depletion up-regulated the E-cadherin protein and down-regulated vimentin protein, and decreased nuclear β-catenin expression, suggesting the involvement of EMT in pontin induced metastatic progression. Together, our data suggest pontin as a potential prognostic biomarker in RCC, and provide new promising therapeutic targets for clinical intervention of kidney cancers.
Adding run‐time checking to the portable C compiler

Run‐time checking of array subscripts and pointer bounds was added to the Portable C Compiler (PCC). Memory overwrite bugs are then caught as they happen instead of when the overwritten memory is used later in the program execution. The run‐time checking compiler is used both to find the true cause of a core dump and to eliminate run‐time errors as the cause of unexpected program behavior. On average, it takes about 40 percent longer to compile, the generated code is about three times larger, and it runs about ten times slower. This performance may seem slow, but it typically reduces days of debugging to less than an hour. The implementation described herein can be adapted to any C compiler as it describes how to generate run‐time checking code in a machine/compiler independent way by changing the intermediate expression trees. In four years of use it has found latent bugs and the cause of intermittent core dumps in programs used for many years by thousands of people.
On Agreement and Learning

We consider a group of Bayesian agents who each possess an independent private signal about an unknown state of the world. We study the question of efficient learning: in which games is private information efficiently disseminated among the agents? In particular, we explore the notion of asymptotic learning, which is said to occur when agents learn the state of the world with probability that approaches one as the number of agents tends to infinity. We show that under general conditions asymptotic learning follows from agreement on posterior actions or posterior beliefs, regardless of the information exchange dynamics.
Pulsar wind nebulae in supernova remnants Spherically symmetric hydrodynamical simulations

A spherically symmetric model is presented for the interaction of a pulsar wind with the associated supernova remnant. This results in a pulsar wind nebula whose evolution is coupled to the evolution of the surrounding supernova remnant. This evolution can be divided in three stages. The rst stage is characterised by a supersonic expansion of the pulsar wind nebula into the freely expanding ejecta of the progenitor star. In the next stage the pulsar wind nebula is not steady; the pulsar wind nebula oscillates between contraction and expansion due to interaction with the reverse shock of the supernova remnant: reverberations which propagate forward and backward in the remnant. After the reverberations of the reverse shock have almost completely vanished and the supernova remnant has relaxed to a Sedov solution, the expansion of the pulsar wind nebula proceeds subsonically. In this paper we present results from hydrodynamical simulations of a pulsar wind nebula through all these stages in its evolution. The simulations were carried out with the Versatile Advection Code.
Neural Computing and Applications Robust Classification with Reject Option Using the Self-Organizing Map

Reject option is a technique used to improve classifier’s reliability in decision support systems. It consists in withholding the automatic classification of an item, if the decision is considered not sufficiently reliable. The rejected item is then handled by a different classifier or by a human expert. The vast majority of the works on this issue has been concerned with the developement of reject option mechanisms to be used by supervised learning architectures (e.g., MLP, LVQ or SVM). In this paper, however, we aim at proposing alternatives to this view which are based on the Self-Organizing Map (SOM), originally an unsupervised learning scheme, but that has also been successfully used in the design of prototype-based classifiers. The basic hypothesis we defend is that it is possible to design SOM-based classifiers endowed with reject option mechanisms whose performances are comparable to or better than those achieved by standard supervised classifiers. For this purpose, we carried out a comprehensively evaluation of the proposed SOM-based classifiers on two synthetic and three real-world data sets. The obtained results suggest that the proposed SOM-based classifiers consistently outperform standard supervised classifiers. Ricardo Sousa? INEB – Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal, E-mail: contact@rsousa.org Ajalmar R. da Rocha Neto? Programa de Pós-Graduação em Engenharia de Telecomunicações, Instituto Federal do Ceará (IFCE), Fortaleza, Ceará, Brasil, E-mail: ajalmar@ifce.edu. br ? First two authors contributed equally to this manuscript. Jaime S. Cardoso INESC Porto, Faculdade de Engenharia da Universidade do Porto, Porto, Portugal, E-mail: jaime.cardoso@inescporto.pt Guilherme A. Barreto Departamento de Engenharia de Teleinformática, Universidade Federal do Ceará (UFC), Fortaleza, Ceará, Brasil, E-mail: gbarreto@ufc.br Manuscript Click here to download Manuscript: article.tex Click here to view linked References 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 2 Ricardo Sousa? et al.
ReHub

Quite recently, the algorithmic community has focused on solving multiple shortest-path query problems beyond simple vertex-to-vertex queries, especially in the context of road networks. Unfortunately, those advanced query-processing techniques cannot be applied to large-scale graphs, such as social or collaboration networks, or to efficiently answer reverse k-nearest neighbor (RkNN) queries, which are of practical relevance to a wide range of applications. To remedy this, we propose ReHub, a novel main-memory algorithm that extends the hub labeling technique to efficiently answer RkNN queries on large-scale networks. Our experimentation will show that ReHub is the best overall solution for this type of queries, requiring only minimal additional preprocessing and providing very fast query times in all cases.
Rapid analytical and preparative isolation of functional endosomes by free flow electrophoresis

Endosomes are prelysosomal organelles that serve as an intracellular site for the sorting, distribution, and processing of receptors, ligands, fluid phase components, and membrane proteins internalized by endocytosis. Whereas the overall functions of endosomes are increasingly understood, little is known about endosome structure, composition, or biogenesis. In this paper, we describe a rapid procedure that permits analytical and preparative isolation of endosomes from a variety of tissue culture cells. The procedure relies on a combination of density gradient centrifugation and free flow electrophoresis. It yields a fraction of highly purified, functionally intact organelles. As markers for endosomes in Chinese hamster ovary cells, we used endocytosed horseradish peroxidase, FITC-conjugated dextran, and [35S]methionine-labeled Semliki Forest virus. Total postnuclear supernatants, crude microsomal pellets, or partially purified Golgi fractions were subjected to free flow electrophoresis. Endosomes and lysosomes migrated together as a single anodally deflected peak separated from most other organelles (plasma membrane, mitochondria, endoplasmic reticulum, and Golgi). The endosomes and lysosomes were then resolved by centrifugation in Percoll density gradients. Endosomes prepared in this way were enriched up to 70-fold relative to the initial homogenate and were still capable of ATP- dependent acidification. By electron microscopy, the isolated organelles were found to consist of electron lucent vacuoles and tubules, many of which could be shown to contain an endocytic tracer (e.g., horseradish peroxidase). SDS PAGE analysis of integral and peripheral membrane proteins (separated from each other by condensation in Triton X-114) revealed a unique and restricted subset of proteins when compared with lysosomes, the unshifted free flow electrophoresis peak, and total cell protein. Altogether, the purification procedure takes 5-6 h and yields amounts of endosomes (150-200 micrograms protein) sufficient for biochemical, immunological, and functional analysis.
Heterogeneous associative cache for multimedia applications

The off-chip memory communication is often a critical part of a video processing system. Traditional cache usually behaves poor since some video algorithms such as H.264 motion compensation tend to access memory in an inefficient way. Based on the analysis of cache line fetch efficiency, we find out that more than 10% fetches are inefficient. In this paper, we propose a Heterogeneous Associative Cache (HA Cache) architecture, in which there is an additional special way with a smaller cache line size, special mapping strategy and replacement policy. This scheme can effectively reduce power, cache space, and bandwidth wasted on useless data. By adding a special way to the traditional 2-way set-associative cache (with 1/8 cache size increase), the HA Cache can save up to 10% memory access. In most cases, it is even better than doubling the traditional cache size.
AGE DISTRIBUTIONS AND RETURNS OF FINANCIAL ASSETS February 1994

This paper explores the relationship between age distribution and asset returns impled by an overlapping-generations asset pricing model. The model predicts that as more individuals reach the age when the increment to their wealth reaches its maximum, asset returns fall. Cross-sectional evidence from the Survey of Financial Characteristics of Consumers and the Surveys of Consumer Finances indicates that individuals aged 45 to 54 have the largest increment to wealth of all age group. Time series estimates confirm that a close link exists between aggregate household wealth and the size of this age group. In accordance with the model presented in this paper, time series estimates of the relationship between asset returns and age distribution suggests a large, statistically significant, negative correlation between the fraction of the population aged 45 to 54 and the returns of several types of assets.
Causality Assignment and Model Approximation for Hybrid Bond Graph: Fault Diagnosis Perspectives

Bond graph (BG) is an effective tool for modeling complex systems and it has been proven useful for fault detection and isolation (FDI) for continuous systems. BG provides the causal relations between system's variables which allow FDI algorithms to be developed systematically from the graph. In the same spirit, Hybrid bond graph (HBG) is a BG-based modeling approach which provides an avenue to model complex hybrid systems. However, due to mode-varying causality properties of HBG, HBG has not been efficiently-exploited for fault diagnosis. In this work, a comprehensive study on the HBG from FDI viewpoints is presented. Some properties pertaining to the HBG are gained in the study. Based on these findings, a causality assignment procedure and a model approximation technique are developed to achieve a HBG with a desirable causality assignment that leads a unified description of system's behavior. These results lay a foundation for quantitative FDI design for complex hybrid systems.
Dual functionality of O-GlcNAc transferase is required for Drosophila development

Post-translational modification of intracellular proteins with O-linked N-acetylglucosamine (O-GlcNAc) catalysed by O-GlcNAc transferase (OGT) has been linked to regulation of diverse cellular functions. OGT possesses a C-terminal glycosyltransferase catalytic domain and N-terminal tetratricopeptide repeats that are implicated in protein–protein interactions. Drosophila OGT (DmOGT) is encoded by super sex combs (sxc), mutants of which are pupal lethal. However, it is not clear if this phenotype is caused by reduction of O-GlcNAcylation. Here we use a genetic approach to demonstrate that post-pupal Drosophila development can proceed with negligible OGT catalysis, while early embryonic development is OGT activity-dependent. Structural and enzymatic comparison between human OGT (hOGT) and DmOGT informed the rational design of DmOGT point mutants with a range of reduced catalytic activities. Strikingly, a severely hypomorphic OGT mutant complements sxc pupal lethality. However, the hypomorphic OGT mutant-rescued progeny do not produce F2 adults, because a set of Hox genes is de-repressed in F2 embryos, resulting in homeotic phenotypes. Thus, OGT catalytic activity is required up to late pupal stages, while further development proceeds with severely reduced OGT activity.
Criminal Responsibility in Canada: Mental Disorder Stigma Education and the Insanity Defense

ABSTRACT These online studies tested whether combining education about the Not Criminally Responsible on account of Mental Disorder (NCRMD) defense with education about mental disorders might encourage jurors to use it in a suitable case. In Study 1, Canadian jury eligible community members (N = 370) were provided with mental disorder (vs. irrelevant) education, and NCRMD (vs. irrelevant) education, then read a fabricated NCRMD trial stimulus in which the defendant's mental disorder varied (schizophrenia, substance use disorder, depression). Results showed that in the trial involving depression, for the group who received mental disorder education, NCRMD education increased the likelihood of a guilty verdict. In Study 2 (N = 407)—which featured a different case—again, NCRMD education combined with mental disorder education increased likelihood of a guilty verdict in the depression condition. These studies show that mental disorder education is a potentially useful tool, but can backfire in some contexts.
Semi-automated location identification of catheters in digital chest radiographs

Localization of catheter tips is the most common task in intensive care unit imaging. In this work, catheters appearing in digital chest radiographs acquired by portable chest x-rays were tracked using a semi-automatic method. Due to the fact that catheters are synthetic objects, its profile does not vary drastically over its length. Therefore, we use forward looking registration with normalized cross-correlation in order to take advantage of a priori information of the catheter profile. The registration is accomplished with a two-dimensional template representative of the catheter to be tracked generated using two seed points given by the user. To validate catheter tracking with this method, we look at two metrics: accuracy and precision. The algorithms results are compared to a ground truth established by catheter midlines marked by expert radiologists. Using 12 objects of interest comprised of naso-gastric, endo-tracheal tubes, and chest tubes, and PICC and central venous catheters, we find that our algorithm can fully track 75% of the objects of interest, with a average tracking accuracy and precision of 85.0%, 93.6% respectively using the above metrics. Such a technique would be useful for physicians wishing to verify the positioning of catheter tips using chest radiographs.
Parallelization of star alignment

Pair-wise sequence alignment is a technique of comparing the similarity of two organisms. It is the basic technique in DNA sequence alignment. There is an extraordinary number of data sequences when they are compared. Problems when comparing the huge data sequences are accuracy and efficiency. These parameters are contradiction which means reaching faster speed will decrease accuracy, and vice versa. Older method such as Needleman-Wunchs has extremely high computational complexity of O(n2). Similarly, multiple sequence alignment that processes the sequences one by one, called Star Alignment, takes time until O(k2n2). Therefore, they have a timing issue problem while processing the data. However, the computation result still has high accuracy. Consequently, it is very important to get a better way to improve the performance. One of the methods for increasing the speed is parallel computation by using multiple computers work together as a system. This research focuses on finding a faster method to process multiple sequence alignment using the Star method with a parallel computer. Our proposed method is implemented using Message Passing Interface (MPI). The results show that the paralellization of the Star Alignment increased speed up 4-6 times compared to that of using single CPU.
DMOSS: Open source software documentation assessment

Besides source code, the fundamental source of information about open source software lies in documentation, and other non source code files, like README, INSTALL, or How-To files, commonly available in the software ecosystem. These documents, written in natural language, provide valuable information during the software development stage, but also in future maintenance and evolution tasks. DMOSS3 is a toolkit designed to systematically assess the quality of non source code content found in software packages. The toolkit handles a package as an attribute tree, and performs several tree traverse algorithms through a set of plugins, specialized in retrieving specific metrics from text, gathering information about the software. These metrics are later used to infer knowledge about the software, and composed together to build reports that assess the quality of specific features. This paper discusses the motivations for this work, continues with a description of the toolkit implementation and design goals. This is followed by an example of its usage to process a software package, and the produced report.
Server Based Dora in Vanets and Its Applications

Consider the drive-thru scenario, where vehicles pass by several APs located along a highway and obtain Internet access for only a limited amount of time. We assume that a vehicle wants to upload a ﬁle when it is within the coverage ranges of the APs, and needs to pay for the attempts to access the channel. As both the channel contention level and achievable data rate vary over time, the vehicle needs to decide when to transmit by taking into account the required payment, the application’s QoS requirement, and the level of contention in current and future time slots. Because of the dynamic nature of the problem, we formulate it as a ﬁnite horizon sequential decision problem and solve it using the dynamic programming (DP).
Mathematical morphology aided enhancement and segmentation of T2-weighted brain MRI images

Segmentation of the brain MRI into its constituent White Matter (WM), Gray Matter (GM) and Cerebrospinal Fluid (CSF) is a vital task for the diagnosis of various neurological diseases. In this work, mathematical morphology has been employed for contrast enhancement of the brain T2-wighted MRI, followed by segmentation with the help of Fuzzy C-means (FCM) clustering algorithm. The proposed method has resulted in better results, both qualitatively and quantitatively in comparison to the conventional method where FCM is directly applied to the raw MR images.
Short-circuit faults in distributed and concentrated windings of PM synchronous motors

For investigation of coil currents, torque and speed pulsation at coil short-circuit faults, an "independent coil" model is set up and presented. The model is based on the calculation of the self and mutual inductances and is implemented in MATLAB/SIMULINK (Matrix operation). Both distributed and concentrated windings are simulated at short circuit faults of different coils. For an x-by-wire application different pole numbers and winding configurations are investigated for the lowest torque pulsation at fault-condition. Moreover, a possible solution for avoiding a disturbing pulsating torque at short-circuit fault is discussed. This method comprises the short-circuit of the coils (or a multiple) constituting the "basic winding scheme".
Nearest-Neighbor Artist Identification

We propose and investigate the performance of a simple artist identification system. Our approach learns a set of signatures for songs by known artists and then given an new song chooses the nearest neighbor from amongst these to identify the artist. The song signatures consist of clusters of MFCC frames hence artist similarity is based on timbral properties. On a 75 artist task, our algorithm has 17.0% accuracy. On the MIREX task our overall performance is 26.0%. This is substantially less than the best performance for this task of 72.5%. We thus conclude that while our approach is better than random, it does not compare well with other more complex systems. The extra modeling in such systems is thus justified.
Improved Isomap Algorithm for Motion Analysis

Euclidean distance, Hausdorff distance and SSP distance are discussed, and SSP distance is used to improve Isomap algorithm. Two methods are put forward for improving Isomap algorithm. One is aligning input data of original Isomap algorithm, the other is modifying Isomap algorithm itself. SSP distance is used to search neighbors and compose neighborhood graph, and the plot for each dimension of Isomap representation is used for visualization of Isomap representation. Motion analysis experiments results show that improved Isomap algorithm is better than original Isomap algorithm for translated data and has better visualization results of Isomap representation.