Miracle-dz/UniFAR-FTUs huggingface dataset:
EpoDB: a prototype database for the analysis of genes expressed during vertebrate erythropoiesis

EpoDB is a database of genes expressed in vertebrate red blood cells. It is also a prototype for the creation of cell and tissue-specific databases from multiple external sources. The information in EpoDB obtained from GenBank, SWISS-PROT, Transfac, TRRD and GERD is curated to provide high quality data for sequence analysis aimed at understanding gene regulation during erythropoiesis. New protocols have been developed for data integration and updating entries. Using a BLAST-based algorithm, we have grouped GenBank entries representing the same gene together. This sequence similarity protocol was also used to identify new entries to be included in EpoDB. We have recently implemented our database in Sybase (relational tables) in addition to SICStus Prolog to provide us with greater flexibility in asking complex queries that utilize information from multiple sources. New additions to the public web site (http://www.cbil.upenn.edu/epodb) for accessing EpoDB are the ability to retrieve groups of entries representing different variants of the same gene and to retrieve gene expression data. The BLAST query has been enhanced by incorporating BLASTView, an interactive and graphical display of BLAST results. We have also enhanced the queries for retrieving sequence from specified genes by the addition of MEME, a motif discovery tool, to the integrated analysis tools which include CLUSTALW and TESS.
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—We study online cloud resource auctions where users can arrive anytime and bid for heterogeneous types of virtual machines (VMs) assembled and provisioned on the ﬂy. The proposed auction mechanism RSMOA, to the authors’ knowledge, represents the ﬁrst truthful online mechanism that timely responds to incoming users’ demands and makes dynamic resource provisioning and allocation decisions, while guaranteeing efﬁciency in both the provider’s revenue and system social welfare. RSMOA consists of two components: (1) an online mechanism that computes resource allocation and users’ payments based on a global, non-decreasing pricing curve, and guarantees truthfulness; (2) a judiciously designed pricing curve, which is derived from a threat-based strategy and guarantees a competitive ratio O (ln( p )) in both system social welfare and the provider’s revenue, as compared to the celebrated ofﬂine Vickrey-Clarke-Groves (VCG) auction. Here p is the ratio between the upper and lower bounds of users’ marginal valuation of a type of resource. The efﬁcacy of RSMOA is validated through extensive theoretical analysis and trace-driven simulation studies.
Comprehensive Analysis of Affymetrix Exon Arrays Using BioConductor

Why BioConductor? BioConductor [1] is a collection of open source software packages designed to support the analysis of biological data. BioConductor is written using the programming language R, which itself provides access to a wide range of tools for statistical analysis, data presentation, and visualization. BioConductor has more than 200 packages representing not only analytical tools but also data and annotation. It has a highly active international developers' community. For those unfamiliar with R and BioConductor, numerous books and tutorials exist (see, for example, [2–4]), and there are also very active e-mail mailing lists for both.
Fast approximate dynamic warping kernels

The dynamic time warping (DTW) distance is a popular similarity measure for comparing time series data. It has been successfully applied in many fields like speech recognition, data mining and information retrieval to automatically cope with time deformations and variations in the length of the time dependent data. There have been attempts in the past to define kernels on DTW distance. These kernels try to approximate the DTW distance. However, these have quadratic complexity and these are computationally expensive for large time series. In this paper, we introduce FastDTW kernel, which is a linear approximation of the DTW kernel and can be used with linear SVM. To compute the DTW distance for any given sequences, we need to find the optimal warping path from all the possible alignments, which is a computationally expensive operation. Instead of finding the optimal warping path for every pair of sequences, we learn a small set of global alignments from a given dataset and use these alignments for comparing the given sequences. In this work, we learn the principal global alignments for the given data by using the hidden structure of the alignments from the training data. Since we use only a small number of global alignments for comparing the given test sequences, our proposed approximation kernel is computationally efficient compared to previous kernels on DTW distance. Further, we also propose a approximate explicit featuremap for our proposed kernel. Our results show the efficiency of the proposed approximation kernel.
SIP

A feature model specifies the sets of features that define valid products in a software product line. Recent work has considered the problem of choosing optimal products from a feature model based on a set of user preferences, with this being represented as a many-objective optimization problem. This problem has been found to be difficult for a purely search-based approach, leading to classical many-objective optimization algorithms being enhanced either by adding in a valid product as a seed or by introducing additional mutation and replacement operators that use an SAT solver. In this article, we instead enhance the search in two ways: by providing a novel representation and by optimizing first on the number of constraints that hold and only then on the other objectives. In the evaluation, we also used feature models with realistic attributes, in contrast to previous work that used randomly generated attribute values. The results of experiments were promising, with the proposed (SIP) method returning valid products with six published feature models and a randomly generated feature model with 10,000 features. For the model with 10,000 features, the search took only a few minutes.
Expression pattern and functional characteristics of two novel splice variants of the two‐pore‐domain potassium channel TREK‐2

Two novel alternatively spliced isoforms of the human two‐pore‐domain potassium channel TREK‐2 were isolated from cDNA libraries of human kidney and fetal brain. The cDNAs of 2438 base pairs (bp) (TREK‐2b) and 2559 bp (TREK‐2c) encode proteins of 508 amino acids each. RT‐PCR showed that TREK‐2b is strongly expressed in kidney (primarily in the proximal tubule) and pancreas, whereas TREK‐2c is abundantly expressed in brain. In situ hybridization revealed a very distinct expression pattern of TREK‐2c in rat brain which partially overlapped with that of TREK‐1. Expression of TREK‐2b and TREK‐2c in human embryonic kidney (HEK) 293 cells showed that their single‐channel characteristics were similar. The slope conductance at negative potentials was 163 ± 5 pS for TREK‐2b and 179 ± 17 pS for TREK‐2c. The mean open and closed times of TREK‐2b at −84 mV were 133 ± 16 and 109 ± 11 μs, respectively. Application of forskolin decreased the whole‐cell current carried by TREK‐2b and TREK‐2c. The sensitivity to forskolin was abolished by mutating a protein kinase A phosphorylation site at position 364 of TREK‐2c (construct S364A). Activation of protein kinase C (PKC) by application of phorbol‐12‐myristate‐13‐acetate (PMA) also reduced whole‐cell current. However, removal of the putative TREK‐2b‐specific PKC phosphorylation site (construct T7A) did not affect inhibition by PMA. Our results suggest that alternative splicing of TREK‐2 contributes to the diversity of two‐pore‐domain K+ channels.
Tutorial: open source enterprise application integration - introducing the event processing capabilities of apache camel

"Interesting applications rarely live in isolation. " ([1], xxix) With this sentence G. Hohpe and B. Woolf start the introduction to their book Enterprise Integration Pattern: Designing, Building, and Deploying Messaging Solutions. While the statement is valid now for more than ten years, Gartner estimates today the cost increase targeting integration aspects for midsize to large companies at about 33% within the next three years (cf. [2]). The expected increase will be mainly driven by the integration of cloud services and mobile devices. Since event processing addresses clearly problems arising with the growth of computational distribution, particularly with the increasing number of mobile devices or cloud services, integration is a topic that needs to be addressed by event processing functionalities. One of the frameworks within the integration domain is Apache Camel. Since it's initial release in 2007, the framework has gained quite some attention - not only within the open-source arena. Apache Camel has a strong focus on enterprise application integration since it implements well known Enterprise Integration Patterns (EIP's) (cf. [1]). This work reveals the event processing capabilities of Apache Camel alongside a logistics parcel delivery process. The delivery process facilitates the scenario descriptions to exemplify the event processing functionalities within a real-world context. All coding examples, supporting the functionality demonstration, are setup around the shipment of parcels.
Demo: using mobile devices to personalize pervasive displays

Personalising content on public displays can be achieved through many methods; recent work has often used the Bluetooth capabilities of mobile devices [4, 1]. However, power and privacy concerns may lead users to switch off the Bluetooth on their mobile devices, making them less useful for display personalisation. In this demonstration we show applications built using Tacita, an alternative method for allowing mobile users to make display personalisation requests.
THE ONLINE SET COVER PROBLEM∗

Let X = { 1 , 2 ,. ,n } be a ground set of n elements, and let S be a family of subsets of X , |S| = m , with a positive cost c S associated with each S ∈ S . Consider the following online version of the set cover problem, described as a game between an algorithm and an adversary. An adversary gives elements to the algorithm from X one by one. Once a new element is given, the algorithm has to cover it by some set of S containing it. We assume that the elements of X and the members of S are known in advance to the algorithm; however, the set X (cid:2) ⊆ X of elements given by the adversary is not known in advance to the algorithm. (In general, X (cid:2) may be a strict subset of X . ) The objective is to minimize the total cost of the sets chosen by the algorithm. Let C denote the family of sets in S that the algorithm chooses. At the end of the game the adversary also produces (oﬄine) a family of sets C OPT that covers X (cid:2) . The performance of the algorithm is the ratio between the cost of C and the cost of C OPT . The maximum ratio, taken over all input sequences, is the competitive ratio of the algorithm. We present an O (log m log n ) competitive deterministic algorithm for the problem and establish a nearly matching Ω (cid:2) log n log m loglog m +loglog n (cid:3) lower bound for all interesting values of m and n . The techniques used are motivated by similar techniques developed in computational learning theory for online prediction (e.g., the WINNOW algorithm) together with a novel way of converting a fractional solution into a deterministic online algorithm.
Closing a Million-Landmarks Loop

We present an improved version of the treemap SLAM algorithm which uses Cholesky factors for representing Gaussians and a hierarchical tree partitioning algorithm derived from the established Kernighan-Lin heuristic for graph bisection. We demonstrate the algorithm's efficiency by mapping a simulated building with 1032271 landmarks. In the end, we close a million-landmarks loop in 21 ms, providing an estimate for ap10000 selected landmarks close to the robot, or in 442 ms for computing a full estimate
Molecular alterations in metaplastic breast carcinoma

Metaplastic carcinoma of the breast is a rare and heterogeneous subtype of breast carcinoma with a generally poor outcome, and few therapeutic options once disease recurs or progresses. Metaplastic carcinomas of the breast are usually of a larger size at diagnosis, with less frequent nodal metastasis compared with invasive ductal carcinoma no special type, and lack hormone and HER2 receptor expression. Recent research has revealed some potentially actionable genetic changes in a subset of these rare tumours. However, ongoing efforts to further characterise the genetic basis and the molecular alterations underlying the distinctive morphological and clinical characteristics of these tumours are needed in order to identify new targets for treatment. This review will describe the theories of pathogenesis of metaplastic breast carcinoma, and highlight genetic changes and potential therapeutic targets in this generally poor prognosis malignancy.
The PISAB Question Answering System

The PISAB Question Answering system is based on a combination of Information Extraction and Information Retrieval techniques. Knowledge extracted from documents is modeled as a set of entities extracted from text and by relations between them. During the learning phase we index documents using the entities they contain. In the answering phase we exploit the index previously built in order to focus the search for the answer to just the most relevant documents. As answers to a question we select from these documents the paragraphs containing entities most similar to those in the question. PISAB has been submitted to the TREC-9 Conference, achieving encouraging results despite it current prototypical development stage. Introduction The problem of finding answers to questions on a large document collection, could in principle be solved by creating a knowledge base with the information extracted from documents and then querying such knowledge base. Unfortunately this approach is not yet feasible, since it requires advanced techniques of natural language processing, knowledge extraction, knowledge representation and reasoning, which are beyond the current state of the art. On the other hand, Information Retrieval techniques are quite effective in retrieving documents relevant to a certain subject, so in particular those which might contain the answer to a question. Information Extraction techniques help identifying certain kinds of information, but their capabilities are quite domain dependent and limited to entities with predefined patterns. Neither of these techniques is sufficient to address the Question Answering problem, but we have explored a way of combining them to build a complete question answering system. The approach The meaning of a document might be expressed in terms of entities and relations between them. Entities are the semantic equivalent of nouns present in the document, while relations correspond to verbs. For example, the information contained in the following phrase: “John reads a book” can be represented by means of the entities “John” and “book”, and by the relation “reads” that links subject and object. Relations need not be binary: prepositional phrases and various kinds of syntactic adjuncts allow expressing n-ary relations.
Organic Waste in Composting: A brief review

This work studied on the composting process of organic waste. Organic waste is the easily biodegradable waste. Organic wastes are produced from many sources Such as agricultural waste, market waste, kitchen waste, urban solid waste and municipal solid waste. Without proper management, this waste could create several environments problem. Therefore, composting is the best low-cost alternative solution to overcome this problem. The composting method can degrade all types of organic waste such as fruits, vegetables, plants, yard waste and others. The organic waste composition can be used as nutrients for crops, soil additives and for environmental management. However, many factors can contribute to the quality of compost products since different types of organic waste have different concentrations of nutrients, Nitrogen, Phosphorus and Potassium (N, P, K) that are the common macro energetics present in fertilizers. The presence of heavy metals shows how Composts can be applied to soils without contributing any negative effects. In terms of the factor affecting the composting process, temperature, pH, moisture content and carbon nitrogen ratio (C: N) are the main parameters that contribute to the efficiency of the composting process.
Towards Motivation-based Plan Evaluation

AI planning systems tend to be disembodied and are not situated within the environment for which plans are generated, thus losing information concerning the interaction between the system and its environment. This paper argues that such information may potentially be valuable in constraining plan formulation, and presents both an agent- and domainindependent architecture that extends the classical AI planning framework to take into account context ,o rthe interaction between an autonomous situated planning agent and its environment. The paper describes how context constrains the goals an agent might generate, enables those goals to be prioritised, and constrains plan selection.
The Combined Effects of Obesity, Abdominal Obesity and Major Depression/Anxiety on Health-Related Quality of Life: the LifeLines Cohort Study

Background Obesity and major depressive disorder (MDD)/anxiety disorders often co-occur and aggravate each other resulting in adverse health-related outcomes. As little is known about the potential effects of interaction between obesity and MDD and/or anxiety disorders on health-related quality of life (HR-QoL), this study was aimed at examining these combined effects. Methods We collected data among N = 89,332 participants from the LifeLines cohort study. We categorized body weight using body mass index (kg/m2) as normal weight (18.5–24.99), overweight (25–29.9), mild obesity (30–34.9) and moderate/severe obesity (≥ 35); we measured abdominal obesity using a waist circumference of ≥102 and ≥ 88 cm for males and females, respectively. MDD and anxiety disorders were diagnosed with the Mini-International Neuropsychiatric Interview. HR-QoL was assessed using the RAND-36 questionnaire to compute physical and mental quality of life scores. We used binary logistic and linear regression analyses. Results The combined effect of obesity and MDD and/or anxiety disorders on physical QoL was larger than the sum of their separate effects; regression coefficients, B (95%-confidence interval, 95%-CI) were: - 1.32 (-1.75; -0.90). However, the combined effect of obesity and major depression alone on mental QoL was less than the additive effect. With increasing body weight participants report poorer physical QoL; when they also have MDD and/or anxiety disorders participants report even poorer physical QoL. In persons without MDD and/or anxiety disorders, obesity was associated with a better mental QoL. Conclusions Obesity and MDD and/or anxiety disorders act synergistically on physical and mental QoL. The management of MDD and/or anxiety disorders and weight loss may be important routes to improve HR-QoL.
Visual Attention for Stereoscopic Image Quality Assessment

Depth perception is one of the most important characteristic in three-dimensional (3D) images different from traditional two-dimensional (2D) images. Therefore, 3D visual attention will be advantageous to improve 3D visual experience and particularly depth perception. In this paper, we propose a 3D visual attention model for stereoscopic image quality assessment task. The proposed model is constructed based on 2D saliency model, center bias, depth cue (foreground cue and background). Different combination and modulation means of the 3D visual attention model for quality assessment are investigated. The experimental results show that compared with other schemes, the proposed 3D visual attention-based pooling scheme can achieve higher consistency with the subjective assessment of stereoscopic images.
Reduced Basis Approximation for Nonlinear Parametrized Evolution Equations based on Empirical Operator Interpolation

We present a new approach to treating nonlinear operators in reduced basis approximations of parametrized evolution equations. Our approach is based on empirical interpolation of nonlinear differential operators and their Frechet derivatives. Efficient offline/online decomposition is obtained for discrete operators that allow an efficient evaluation for a certain set of interpolation functionals. An a posteriori error estimate for the resulting reduced basis method is derived and analyzed numerically. We introduce a new algorithm, the PODEI-greedy algorithm, which constructs the reduced basis spaces for the empirical interpolation and for the numerical scheme in a synchronized way. The approach is applied to nonlinear parabolic and hyperbolic equations based on explicit or implicit finite volume discretizations. We show that the resulting reduced scheme is able to capture the evolution of both smooth and discontinuous solutions. In case of symmetries of the problem, the approach realizes an automatic and intuitive space-compression or even space-dimensionality reduction. We perform empirical investigations of the error convergence and run-times. In all cases we obtain a good run-time acceleration.
Non-blocking deterministic replacement of functionality, timing, and data-flow for hard real-time systems at runtime

Embedded systems are usually an integral component of a larger system and are used to control and/or directly monitor this system by using special hardware devices. The complexity of the whole system, which the embedded control system monitors, increases steadily. Consequently, the initial version of the control software that is used at the time of deployment may be inadequate and may need to be updated. Often this requires the whole system to be shut down to have the software replaced. This is not a desirable solution. In this work, we propose a non-blocking mechanism embedded into an infrastructure for RTLinuxPro for deterministic replacement of system functionality, task timing, and data-flow for hard real-time systems. We explain the mechanism, discuss its implementation using RTLinuxPro, and present a case study of a stop watch in which we replace single functionality and timing behavior at runtime without compromising the timeliness of tasks or the correctness of the output values. The contribution is to show how such a mechanism can work, how it can be implemented, and what problems arise in multi-mode real-time applications.
Study of Punching-Teeth Test Platform Based on Image Processing Technology

Facing the problem of punching-teeth process accuracy is not high in hardware manufacturing field,this paper discusses image signal collection, pre-processing, object orientation system structure and working thesis of juicer cutter plate in punching-teeth process, based on image real time processing technology. Through CCD collection image information,image mode matching,using maximum intra-class variance heredity method and Roberts edge detection operator, this experiment realizes image threshold segmentation and edge detection. Finally, with analysis, calculating and processing,the object location of punching-teeth is true and accurate.