Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of the ELAV-Like Protein HuR Is Associated with Higher Tumor Grade and Increased Cyclooxygenase-2 Expression in Human Breast Carcinoma

Purpose: The human ELAV (embryonic lethal abnormal vision)-like protein HuR stabilizes a certain group of cellular mRNAs that contain AU-rich elements in their 3′-untranslated region. Cell culture studies have shown that the mRNA of cyclooxygenase (COX)-2 can be stabilized by HuR. Experimental Design: To investigate a possible contribution of dysregulation of mRNA stability to the progression of cancer and to overexpression of COX-2, we studied expression of HuR in 208 primary breast carcinomas by immunohistochemistry. Results: There were two different staining patterns of HuR in tumor tissue of breast carcinomas: nuclear expression was seen in 61% of cases; and an additional cytoplasmic expression was seen in 30% of cases. Expression of HuR was significantly associated with increased COX-2 expression; this association was particularly significant for cytoplasmic HuR expression (P < 0.0005). We further observed a significant association of cytoplasmic (P = 0.002) or nuclear HuR (P = 0.027) expression with increased tumor grade. Only 13% of the grade 1 carcinomas showed cytoplasmic expression of HuR, compared with 46% of the grade 3 carcinomas. There was no significant correlation between HuR expression and other clinicopathological parameters such as histological type, tumor size, or nodal status as well as patient survival. Conclusions: Our results suggest that overexpression of HuR in tumor tissue may be part of a regulatory pathway that controls the mRNA stability of several important targets in tumor biology, such as COX-2. Based on our results, additional studies are necessary to investigate whether HuR might be a potential target for molecular tumor therapy.
Clustering time series from ARMA models with clipped data

Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering data derived from Autoregressive Moving Average (ARMA) models using k-means and k-medoids algorithms with the Euclidean distance between estimated model parameters. We justify our choice of clustering technique and distance metric by reproducing results obtained in related research. Our research aim is to assess the affects of discretising data into binary sequences of above and below the median, a process known as clipping, on the clustering of time series. It is known that the fitted AR parameters of clipped data tend asymptotically to the parameters for unclipped data. We exploit this result to demonstrate that for long series the clustering accuracy when using clipped data from the class of ARMA models is not significantly different to that achieved with unclipped data. Next we show that if the data contains outliers then using clipped data produces significantly better clusterings. We then demonstrate that using clipped series requires much less memory and operations such as distance calculations can be much faster. Finally, we demonstrate these advantages on three real world data sets.
REGULATION OF THE IMMUNE SYSTEM BY SYNTHETIC POLYNUCLEOTIDES

Polyadenylic-polyuridylic acid complexes, a potent adjuvant to the immune response, were tested for action on thymic-influenced and bone marrow-derived lymphocytes in model systems deficient in one or the other of these cells. Adult mice, thymectomized at birth or mice treated with heterologous antithymocyte serum produced 90–95% fewer splenic rosette-forming cells than normal mice in response to an injection of sheep erythrocytes. Intravenous injection of complexes of homoribopolynucleotides, polyadenylic and polyuridylic acids, poly A:U with SRBC restored immunologic competence to NTx- or ATS-treated mice such that they produced normal or near normal levels of splenic RFC. In addition, injection of poly A:U enabled NTx mice to reject allogeneic skin grafts at the same rate as control mice with an intact thymus. Further reduction in residual thymocytes by combining neonatal thymectomy with ATS treatment reduced the number of anti-SRBC RFC induced by poly A:U. Lethally irradiated mice which received SRBC, excess bone marrow cells, and as few as 40,000 thymic lymphocytes were stimulated by poly A:U to produce RFC. No adjuvant effect was observed when irradiated mice received excess thymic lymphocytes and low doses of bone marrow cells with poly A:U. The results suggested that the adjuvant action of poly A:U was exerted on the thymic-influenced, antigen-reactive cell and that restoration of immunocompetence to NTx- or ATS-treated mice was caused by amplification of a small number of residual antigen-reactive cells which were influenced by the thymus in utero before thymectomy, or which survived treatment with ATS.
A Novel Role for Extracellular Signal-Regulated Kinase in Maintaining Long-Term Memory-Relevant Excitability Changes

Pyramidal neurons in the piriform cortex from olfactory-discrimination-trained rats show enhanced intrinsic neuronal excitability that lasts for several days after learning. Such enhanced intrinsic excitability is mediated by long-term reduction in the postburst afterhyperpolarization (AHP), which is generated by repetitive spike firing. AHP reduction is attributable to decreased conductance of a calcium-dependent potassium current, the sIAHP. We have previously shown that such learning-induced AHP reduction is maintained by PKC activation. However, the molecular machinery underlying such long-lasting modulation of intrinsic excitability is yet to be fully described. Here we examine whether the extracellular signal-regulated kinase I/II (ERKI/II) pathway, which is known to be crucial in learning, memory, and synaptic plasticity processes, is instrumental for the long-term maintenance of learning-induced AHP reduction. PD98059 or UO126, which selectively block MEK, the upstream kinase of ERK, increased the AHP in neurons from trained rats but not in neurons from naive and pseudo-trained rats. Consequently, the differences in AHP amplitude and neuronal adaptation between neurons from trained rats and controls were abolished. This effect was not mediated by modulation of basic membrane properties. In accordance with its effect on neuronal excitability, the level of activated ERK in the membranal fraction was significantly higher in piriform cortex samples taken from trained rats. In addition, the PKC activator OAG (1-oleoyl-20acety-sn-glycerol), which was shown to reduce the AHP in neurons from control rats, had no effect on these neurons in the presence of PD98059. Our data show that ERK has a key role in maintaining long-lasting learning-induced enhancement of neuronal excitability.
The Presentation of Self in Electronic Life: Goffman on the Internet

Electronic communication (EC) has established a new range of frames of interaction with a developing etiquette. Although apparently more limited and less rich than interactions in which the participants are physically present, it also provides new problems and new opportunities in the presentation of self. There have been exciting discussions about the possible nature of 'electronic selves' (for instance Stone, 1991). This paper is a basic exploration of how the presentation of self is actually taking place in a technically limited, but rapidly spreading, aspect of EC: personal homepages on the World Wide Web. Between the 50s and the early 80s, Erving Goffman worked to describe the structure of face-to-face interaction and to account for how that structure was involved in the interactive tasks of everyday life. He developed a series of concepts which are useful in describing and understanding interaction, and also showed how the physical nature of interaction settings is involved in people's interactions. One of things people need to do in their interactions with others is present themselves as an acceptable person: one who is entitled to certain kinds of consideration, who has certain kinds of expertise, who is morally relatively unblemished, and so on. (Goffman has a whole book (1964) in which he considers cases where there are particular problems in making these claims. ) People have techniques and resources available to allow them to do this. 'Backstage' preparation can help in presenting an effective 'front', 'expressive resources' can be mobilised, and cooperation from others present in the interaction can often be relied upon to smooth over jagged places and provide opportunities for redeeming gaffes. Goffman sees embarrassment as an important indicator of where people fail to present an acceptable self, and an important motivator. A person wishes to present themself effectively to minimise the embarrassment of a failing presentation, but other participants are also motivated to help the performance by their wish to avoid the embarrassment they feel at its failure. So, most of the time, we interact in a cosy conspiracy in which it appears as if everyone knows what they are talking about, can
Area optimization of delay-optimized structures using intrinsic constraint graphs

In this paper, we present a new methodology for structure optimization of block-based design. Instead of merging area and delay criteria, we segregate them into two independent steps. Solutions optimized for delay in the first step are optimized for area with a block-sizing algorithm in the second step. The fully optimized solutions eventually return to the first optimization step, if the user constraints are not met, using a structure-extraction module. A condition to this approach is that the area optimization phase does not alter the quality reached during delay optimization. We propose a framework for area optimization of delay-optimized structures based on structure similarities. We present a new model to represent block placements that share the same qualities for global routing. Using this model, we formally define the relation of similarity and exhibit several properties and theorems to validate our approach. The modules composing the area optimization phase are presented and experimental results confirm the validity of our methodology.
Relationship among emotions, mood, personality and clothing: an exploratory study

A B ST R A C T This study tends to investigate the application of psychological research methods in the fashion endeavor. The prospect of this challenge is to quantify, formalize and investigate the causal relationships connecting clothing style, preference, personality factors, emotions and mood with an observation to an improved understanding of the psychological profile of the fashion consumer. The result specifies strong relationships between mood and important relationships among three out of five personality factors and clothing style preference; mood was an important predictor of preference, at the same time as personality was restrained. Personality, emotion and mood were exposed to be managed and reflected through clothing with propositions for assistance in consumer clothing service training, resolution, and strategies for personal shoppers, market segmentation and design. The methodology derivative from a combination of research methods coupled with definite wearing experience, previously not studied collectively. This is a vital demonstration of how important this combination is in order to fully be pleased about the psychological profile of the fashion consumer.
A Systematic ANSI S1.11 Filter Bank Specification Relaxation and Its Efficient Multirate Architecture for Hearing-Aid Systems

Recently, emerging mobile computing requires the high integration of hearing aids into a single system-on-chip. Modern hearing aid systems include a frequency decomposer, noise reduction, feedback cancellation, auditory compensation, and intelligent adaptation. The majority of existing works concentrated on improving the performance and efficiency on a single-signal processing block or one-sided effect. These works lacked comprehensive discussions on system-wide aspects regarding the overall impacts. To design an optimal hearing aid system, frequency decomposers, or the filter banks that dominate in hearing aid systems, are the first priority. We propose a systematic relaxation of the ANSI S1.11 specification and its design procedure for filter banks. The proposed design procedure overcomes the drawbacks of previous works and changes the five performance indices of the filter bank: delay, complexity, sub-band rate reduction, ripples of synthesized output, and prescription matching errors. These performance indices help system or algorithm designers in selecting a beneficial system-relaxed filter bank to achieve optimal hearing aids. The proposed multirate filter bank using the resampling method provides an efficient, low complexity, and delay-constrained computing architecture. Finally, seven design cases are used to demonstrate the proposed method, and comprehensive discussions of the five performance indices are presented.
Towards the optimization of a parallel streaming engine for telco applications

Parallel and distributed computing is becoming essential to process in real time the increasingly massive volume of data collected by telecommunications companies. Existing computational paradigms such as MapReduce (and its popular open-source implementation Hadoop) provide a scalable, fault tolerant mechanism for large scale batch computations. However, many applications in the telco ecosystem require a real time, incremental streaming approach to process data in real time and enable proactive care. Storm is a scalable, fault tolerant framework for the analysis of real time streaming data. In this paper we provide a motivation for the use of real time streaming analytics in the telco ecosystem. We perform an experimental investigation into the performance of Storm, focusing in particular on the impact of parameter configuration. This investigation reveals that optimal parameter choice is highly non-trivial and we use this as motivation to create a parameter configuration engine. As first steps towards the creation of this engine we provide a deep analysis of the inner workings of Storm and provide a set of models describing data flow cost, central processing unit (CPU) cost, and system management cost.
Sequencing of peptide-derived Amadori products by the electron capture dissociation method.

The electron capture dissociation (ECD) of peptide-derived Amadori products has been successfully applied for their sequencing. In contrast to the collision induced dissociation (CID), based on the vibrational excitation of peptides, the ECD method does not produce ions formed by fragmentation of the hexose moiety, that facilitates interpretation of the obtained spectra. The fragmentation spectrum is dominated by c(n) and z. (n) ions, providing the sufficient information for sequencing of peptides and establishing the location of glycated Lys residues in the peptide chain. The ECD experiments were conducted on a series of synthetic peptides and unseparated digests of glycated ubiquitin.
Increased Coagulation With Aging: Importance of Homocysteine and Vitamin B12.

2. Poli D, Antonucci E, Cecchi E, Marcucci R, Liotta AA, Cellai AP, et al. Culprit factors for the failure of well-conducted warfarin therapy to prevent ischemic events in patients with atrial fibrillation: The role of homocysteine. Stroke 2005; 36: 2159 – 2163. 3. Spence JD. Metabolic vitamin B12 deficiency: A missed opportunity to prevent dementia and stroke. Nutr Res 2016; 36: 109 – 116. 4. Spence JD. Nutrition and stroke prevention. Stroke 2006; 37: 2430 – 2435. 5. Spence JD. Homocysteine lowering for stroke prevention: Unravelling the complexity of the evidence. Int J Stroke 2016; 11: 744 – 747. 6. Spence JD, Urquhart BL, Bang H. Effect of renal impairment on atherosclerosis: Only partially mediated by homocysteine. Nephrol Dial Transplant 2016; 31: 937 – 944. 7. Spence D. Mechanisms of thrombogenesis in atrial fibrillation. Lancet 2009; 373: 1006.
New primal-dual proximal algorithm for distributed optimization

We consider a network of agents, each with its own private cost consisting of the sum of two possibly nonsmooth convex functions, one of which is composed with a linear operator. At every iteration each agent performs local calculations and can only communicate with its neighbors. The goal is to minimize the aggregate of the private cost functions and reach a consensus over a graph. We propose a primal-dual algorithm based on Asymmetric Forward-Backward-Adjoint (AFBA), a new operator splitting technique introduced recently by two of the authors. Our algorithm includes the method of Chambolle and Pock as a special case and has linear convergence rate when the cost functions are piecewise linear-quadratic. We show that our distributed algorithm is easy to implement without the need to perform matrix inversions or inner loops. We demonstrate through computational experiments how selecting the parameter of our algorithm can lead to larger step sizes and yield better performance.
Gender Stereotype Susceptibility

Gender affects performance on a variety of cognitive tasks, and this impact may stem from socio-cultural factors such as gender stereotyping. Here we systematically manipulated gender stereotype messages on a social cognition task on which no initial gender gap has been documented. The outcome reveals: (i) Stereotyping affects both females and males, with a more pronounced impact on females. Yet an explicit negative message for males elicits a striking paradoxical deterioration in performance of females. (ii) Irrespective of gender and directness of message, valence of stereotype message affects performance: negative messages have stronger influence than positive ones. (iii) Directness of stereotype message differentially impacts performance of females and males: females tend to be stronger affected by implicit than explicit negative messages, whereas in males this relationship is opposite. The data are discussed in the light of neural networks underlying gender stereotyping. The findings provide novel insights into the sources of gender related fluctuations in cognition and behavior.
Intentions are Plural: Towards a Multidimensional View of Intentions in Consumer Research

Intentions are often included in consumer behavior research, but researchers have paid little attention to a discussion in psychology and philosophy indicating that different intention constructs may exist. The findings in this study suggest that researchers should indeed pay close attention to how intentions are conceptualized and operationalized. More specifically, our analysis shows that three proposed intentions constructs (intentions-as-expectations, intentions-as-plans, and intentions-as-wants) produce a good fit with a three-factor conceptualization. Our analysis also shows that global evaluation variables (satisfaction, attitude, and delight) are not associated with the three intentions constructs with the same strength.
Introduction to Social Network Analysis

as a quantitative sociologist, she uses demographic and social network analytic techniques to examine the processes which lead to and perpetuate social inequalities in health. She has experience analyzing large, population-level datasets and administrative data, and collecting and analyzing both whole and ego-centred social network data. She is a popular undergraduate teacher and an award-winning graduate supervisor. Dr. Godley is also the Chair of the Conjoint Faculties Research Ethics Board at the University of Calgary and has a particular interest in the ethical issues which arise when collecting social network data. More information about her work can be found
Software Project Team Characteristics and Team Performance: Team Motivation as a Moderator

This study examines the relationship between software project team characteristics and team performance by focusing on two questions: whether or not different team characteristics in software project team affect project performance, and whether or not different types of team motivation lead to different level of influence to the relationship between team characteristics and performance? In this study, we argue that team motivation should be considered as a moderate between the relationship of team characteristics and performance. Different kind and level of team motivation can result in different project performance outcome. We examine the interaction effects between team characteristics and team motivation before their final impact to the performance. The results show that the relationship between project team characteristics and performance can be interfered with team motivation. Management should pay more attention to team motivation within project teams so that a better project performance could be achieved.
Texture Image Retrieval Based on Rotated Complex Wavelet Signatures

In this paper, we propose a new approach of extracting texture features for texture image retrieval. A set of rotated wavelet filters (RCWF) is used jointly with dual-tree complex wavelet transform (DT-CWT) for texture analysis in twelve different directions. Wavelet signatures are generated from the decomposition coefficients. Graph-based spectral clustering method is applied on the distance of the signatures. Because the wavelet signature represents the image texture well and the spectral based method exploits the local relationship significantly, experimental results show that the proposed method outperforms other existing methods remarkably.
Bringing evidence-based education to CS

The Communications Web site, http://cacm.acm. org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of Communications, we'll publish selected posts or excerpts. twitter Follow us on Twitter at http://twitter.com/blogCACM http://cacm.acm. org/blogs/blog-cacm Mark Guzdial says computer science teachers should use more evidence, less intuition.
A Survey of Transfer and Multitask Learning in Bioinformatics

Machine learning and data mining have found many applications in biological domains, where we look to build predictive models based on labeled training data. However, in practice, high quality labeled data is scarce, and to label new data incurs high costs. Transfer and multitask learning offer an attractive alternative, by allowing useful knowledge to be extracted and transferred from data in auxiliary domains helps counter the lack of data problem in the target domain. In this article, we survey recent advances in transfer and multitask learning for bioinformatics applications. In particular, we survey several key bioinformatics application areas, including sequence classification, gene expression data analysis, biological network reconstruction and biomedical applications. Category: Convergence computing
Quantization-based complexity reduction for range-dependent modified Gilbert model

In this contribution we propose an algorithm for dimension reduction of the previously introduced range-dependent modified Gilbert model. For reduction of the model dimension we suggest to jointly quantize model parameters estimated based on very narrow measurement intervals. We analyze the influence of the number of quantization levels on the model performance and based on this analysis find the optimal model dimension. Furthermore, we show that selected environmental and propagation effects, influencing the error pattern, can be identified by means of quantizing model parameters. Finally we demonstrate that these effects can be accurately reproduced by our model.