Miracle-dz/UniFAR-FTUs huggingface dataset:
PIssGA: An ultra fast meta-heuristic approach to solve protein inference problem

The protein inference problem represents a major challenge in proteomics research. In this paper, we propose a novel meta-heuristic approach i.e. PIssGA to infer proteins from a given peptide sequence identified from tandem mass spectrometry in shotgun proteomics. Although most of the works available in the literature mainly adopts parsimonious pressure i.e. prefer least number of inferred proteins, our model is neither strictly parsimonious nor strictly optimistic, rather a tunable model that provides the flexibility to infer proteins either parsimoniously or optimistically or somewhere in between. Another important feature of PIssGA is its efficiency in search that makes the approach ultra first. We used Sigma49 dataset to test our method and found the proposed algorithm extremely fast and moderately accurate.
Two-Channel Perfect Reconstruction FIR Filter Banks over Commutative Rings

Abstract The relation between ladder and lattice implementations of two-channel filter banks is discussed and it is shown that these two concepts differ in general. An elementary proof is given for the fact that over any integral domain which is not a field there exist causal realizable perfect reconstructing filter banks that cannot be implemented with causal lifting filters. A complete parametrization of filter banks with coefficients in local rings and semiperfect rings is given.
Estimation Methods for Microarray Data with Missing Values : A Review Ms

DNA microarrays have gained widespread uses in biological studies such as cancer classification, cancer prognosis and identifications of cell cycle-regulated genes of yeast because of their large number of genes and small size. But they often produce missing expression values due to various reasons which significantly affect the performance of any data analysis. One primary concern of classifier learning is prediction accuracy.Presence of incomplete information significantly effect the performance and accuracy of a classifier.Hence prior to the classification a complete matrix is needed for which in the pre processing step the missing value should be estimated(imputed). This survey paper proposes different existing estimation methods including KNNimpute, SVDimpute, LSimpute, LLSimpute, IFRAA, Principal curve etc for missing values with the description of the basic principles behind the different imputation approaches, also the review tries to provide the performance of each method on the basis of different datasets used and future direction for the research. Keywords-Missing value imputation, gene classification, gene expression data
THE EVOLUTION OF THERMOTOLERANCE A CHARACTERIZATION OF A DIRECTIONALLY EVOLVED CYANOBACTERIUM

iv ACKNOWLEDGEMENTS I would like to acknowledge and thank Dr. Elizabeth Vierling for the tremendous amount of opportunity she has provided me with. I would also like to thank my lab members for being some of the best people I have known. Sandler for your suggestions and assistance with my work. My family who has supported me throughout my seemingly endless amount of time at Umass. Chaperone proteins are essential components in the maintenance and turnover of the proteome. Many chaperones play integral functions in the folding and unfolding of cellular substrates under many conditions, including heat stress. Most chaperones can be characterized into two categories; the typical ATP dependent chaperones and the ATP independent chaperones. One ATP independent chaperone class it the Small Heat Shock Proteins (sHSPs), which as molecular life vests and are thought to protect misfolding proteins from irreversible aggregation. SHSPs have a conserved basic domain structure, containing an N-terminal arm of variable length, a conserved α-crystalline domain, and a short C-terminal extension. sHSPs are found in virtually all forms of life and are essential in some organisms for acquired thermotolerance to elevated temperatures. One such organism, the cyanobacterium Synechocystis sp. PCC. 6803, is an excellent model for the study and understanding of these proteins and their functions in vivo. The genome of Synechocystis encodes only one sHSP, Hsp16.6, and it has be shown to be essential for acquired thermotolerance. Two mutant derivatives of Hsp16.6 with single amino acid substitutions in the N-terminal arm (L9P and E25K) have loss-of-function phenotypes similar to knock out strains, but each has very different biochemical properties. The mutant L9P has an inability to interact with putative substrates during heat stress in vivo, while the mutant E25K vi appears unable to release substrates. Using a directed evolution approach, suppressors have been isolated that recover the lost thermotolerance of their respective parent strains, either L9P (16 suppressors) or E25K (10 suppressors). These suppressors show thermotolerance equivalent to wild type under acute heat stress, while displaying superior chronic heat stress tolerance. This suggests that the response to acute and chronic heat stress may have different components. Additionally, deleting the L9P or E25K Hsp16.6 allele in each of the suppressor strains or replacing it with wild type Hsp16.6 revealed that 16 of the suppressors tested so far (9 L9P and 7 E25K) no longer require Hsp16.6 for acute heat tolerance. Illumina sequencing and comparative genomics …
Grasp planning of 3D objects using genetic algorithm

In this paper, we apply genetic algorithm (GA) to the optimization problem in grasp planning. This method can be used to find “pregrasps” for 3D objects in arbitrary shape and different dexterous hands, which serve as the first step of a complete grasping action. Each component of the GA planner is discussed in detail. The proposed algorithm is implemented in GraspIt! simulator [1]. It is tested on different hand-object combinations and the result shows that genetic algorithm is effective in finding high-quality pregrasps.
Predicting homologous signaling pathways using machine learning

MOTIVATION In general, each cell signaling pathway involves many proteins, each with one or more specific roles. As they are essential components of cell activity, it is important to understand how these proteins work-and in particular, to determine which of the species' proteins participate in each role. Experimentally determining this mapping of proteins to roles is difficult and time consuming. Fortunately, many pathways are similar across species, so we may be able to use known pathway information of one species to understand the corresponding pathway of another. RESULTS We present an automatic approach, Predict Signaling Pathway (PSP), which uses the signaling pathways in well-studied species to predict the roles of proteins in less-studied species. We use a machine learning approach to create a predictor that achieves a generalization F-measure of 78.2% when applied to 11 different pathways across 14 different species. We also show our approach is very effective in predicting the pathways that have not yet been experimentally studied completely. AVAILABILITY The list of predicted proteins for all pathways over all considered species is available at http://www.cs. ualberta.ca/~bioinfo/signaling.
A Retrieve Model of WESU for Encrypted XML Database

To resolve the problems of poor security and low retrieve efficiency for XML DAS, a new retrieve model of WESU foe encrypted XML database is presented in this paper. It establishes the value index and structure index in the encrypted XML database, and executes the barrel management algorithm to record the entrance addresses in the value index and structure index. Through this model, the security of XML database and the retrieve efficiency are both improved.
transcriptome Detection and evaluation of intron retention events in the human

Alternative splicing is a very frequent phenomenon in the human transcriptome. There are four major types of alternative splicing: exon skipping, alternative 3 splice site, alternative 5 splice site, and intron retention. Here we present a large-scale analysis of intron retention in a set of 21,106 known human genes. We observed that 14.8% of these genes showed evidence of at least one intron retention event. Most of the events are located within the untranslated regions (UTRs) of human transcripts. For those retained introns interrupting the coding region, the GC content, codon usage, and the frequency of stop codons suggest that these sequences are under selection for coding potential. Furthermore, 26% of the introns within the coding region participate in the coding of a protein domain. A comparison with mouse shows that at least 22% of all informative examples of retained introns in human are also present in the mouse transcriptome. We discuss that the data we present suggest that a significant fraction of the observed events is not spurious and might reflect biological significance. The analyses also allowed us to generate a reliable set of intron retention events that can be used for the identification of splicing regulatory elements.
Design and Simulation of Permanent Magnet Synchronous Motor Drive by Using Fuzzy Logic Controller

To improve the dynamic performances of the permanent magnet synchronous motor (PMSM) drive, a novel implementation of speed controller based on adaptive fuzzy logic is presented in this paper. Using the output of the fuzzy speed controller (FC), the quadrature axis current reference value can be obtained. At the same time, the outputs of the current controller can be corrected by the disturbance voltage observer's outputs. Results of simulation are provided to demonstrate the effectiveness of the proposed scheme under the occurrence of parameter variations and external disturbance.
Emerging techniques for printed reconfigurable antenna: A review

This paper presents a review of emerging techniques for printed reconfigurable antennas. The need of change in radiation parameters of an antenna like frequency, polarization, radiation pattern or combination of these parameters, on board had given rise to design reconfigurable antennas. This reconfiguration on antenna is achieved by switching feed location of an antenna or switching ground or switching the radiating path of an antenna which brings change in the effective resonating length. The switching can be done by using PIN diodes, varactor diodes, optical switches and MEMS to connect/disconnect different parts on an antenna. Due to this the total antenna volume of printed reconfigurable antenna can be reused to achieve different antenna modes. Thus, printed reconfigurable antenna integrates functional diversities to accommodate the increasing demands of modern wireless applications like software defined radio, cognitive radio, fading, noise interference, MIMO with a small form factor.
Performance Modeling of P2P File Sharing Applications

Peer-to-Peer (P2P) based file sharing applications have become highly popular in today’s Internet due to the spread of platforms such as Napster, Gnutella, KaZaa, eDonkey, BitTorrent, and others. There are several interesting issues in P2P-based file sharing applications that affect their performance. As their diffusion grew, the scientific community started to analyze these applications using analytical and mathematical techniques, measurements and simulations. In this paper we make a first step towards a comprehensive survey of the existing literature on the performance analysis of P2P-based file sharing applications. In particular, we first provide a classification structure of performance issues in P2P-based file sharing that exploits different viewpoints that could be chosen to analyze the behavior of such applications. Furthermore, we discuss and summarize a subset of the proposals that are based on analytical and mathematical models of P2P-based file sharing applications. The discussion of measurement and simulation based experiments is left for later development.
Algorithmic Cross-Complexity and Relative Complexity

Information content and compression are tightly related concepts that can be addressed by classical and algorithmic information theory. Several entities in the latter have been defined relying upon notions of the former, such as entropy and mutual information, since the basic concepts of these two approaches present many common tracts. In this work we further expand this parallelism by defining the algorithmic versions of cross-entropy and relative entropy (or Kullback-Leiblerdivergence), two well-known concepts in classical information theory. We define the cross-complexity of an object x with respect to another object y as the amount of computational resources needed to specify x in terms of y, and the complexity of x related to y as the compression power which is lost when using such a description for x, with respect to its shortest representation. Since the main drawback of these concepts is their uncomputability, a suitable approximation based on data compression is derived for both and applied to real data. This allows us to improve the results obtained by similar previous methods which were intuitively defined.
The genetic basis of energy conservation in the sulfate-reducing bacterium Desulfovibrio alaskensis G20

Sulfate-reducing bacteria play major roles in the global carbon and sulfur cycles, but it remains unclear how reducing sulfate yields energy. To determine the genetic basis of energy conservation, we measured the fitness of thousands of pooled mutants of Desulfovibrio alaskensis G20 during growth in 12 different combinations of electron donors and acceptors. We show that ion pumping by the ferredoxin:NADH oxidoreductase Rnf is required whenever substrate-level phosphorylation is not possible. The uncharacterized complex Hdr/flox-1 (Dde_1207:13) is sometimes important alongside Rnf and may perform an electron bifurcation to generate more reduced ferredoxin from NADH to allow further ion pumping. Similarly, during the oxidation of malate or fumarate, the electron-bifurcating transhydrogenase NfnAB-2 (Dde_1250:1) is important and may generate reduced ferredoxin to allow additional ion pumping by Rnf. During formate oxidation, the periplasmic [NiFeSe] hydrogenase HysAB is required, which suggests that hydrogen forms in the periplasm, diffuses to the cytoplasm, and is used to reduce ferredoxin, thus providing a substrate for Rnf. During hydrogen utilization, the transmembrane electron transport complex Tmc is important and may move electrons from the periplasm into the cytoplasmic sulfite reduction pathway. Finally, mutants of many other putative electron carriers have no clear phenotype, which suggests that they are not important under our growth conditions.
From stable to chaotic juggling: theory, simulation, and experiments

Recent results of dynamical systems theory are used to derive strong predictions concerning the global properties of a simplified model of a planar juggling robot. In particular, it is found that certain lower-order local (linearized) stability properties determine the essential global (nonlinear) stability properties, and that successive increments in the controller gain settings give rise to a cascade of stable period-doubling bifurcations that comprise a universal route to chaos. The theoretical predictions are verified by simulation and corroborated by experimental data from the juggling robot. <<ETX>>
An Exploration of Acquisition and Mean Functions in Variational Bayesian Monte Carlo

Variational Bayesian Monte Carlo (VBMC) is a novel framework for tackling approximate posterior and model inference in models with black-box, expensive likelihoods by means of a sample-efficient approach (Acerbi, 2018). VBMC combines variational inference with Gaussian-process (GP) based, active-sampling Bayesian quadrature, using the latter to efficiently approximate the intractable integral in the variational objective. VBMC has been shown to outperform state-of-the-art inference methods for expensive likelihoods on a benchmark consisting of meaningful synthetic densities and a real model-fitting problem from computational neuroscience. In this paper, we study the performance of VBMC under variations of two key components of the framework. First, we propose and evaluate a new general family of acquisition functions for active sampling, which includes as special cases the acquisition functions used in the original work. Second, we test different mean functions for the GP surrogate, including a novel squared-exponential GP mean function. From our empirical study, we derive insights about the stability of the current VBMC algorithm, which may help inform future theoretical and applied developments of the method.
Offensive Language Detection with Neural Networks for Germeval Task 2018

In this paper we describe our submissions to task I of the GermEval 2018 Shared Task with the goal of identifying offensive language in a set of German tweets. We ex-periment with two neural architectures and different features. Our submission consists of 3 runs using ensembles of different neural network architectures, each achieving approximately 78 % macro-F1 measure on the last 500 tweets from the training set. The source code for our experiments is publicly available on Github. 1
A Conceptual Framework For Structuring An IT Organization

Organizational efficiency and effectiveness result from aligning organizational needs and IT. Consequently, the structure of an IT Organization is crucial for obtaining good results, particularly in product and service delivery. However, in spite of the importance that IT Organization might have, no relevant documentation about its structure is found. As a result, using the Portuguese Navy as a case study to the design research, this paper aims at reviewing the main related research work and proposes a conceptual framework for structuring an IT organization. Through the proposed framework, it is possible to rationally structure an IT organization and, thus, contribute to the research in this area.
Dialog Act Classification Using N-Gram Algorithms

Speech act classification remains one of the challenges in natural language processing. This paper evaluates a classification system that assigns one of twelve dialog acts to an utterance from the Map Task Corpus. The dialog act classification system chooses a dialog act based on n-grams from a training set. The system’s performance is comparable to other classification systems, like those using support vector machines. Performance is high given the fact that the system only considers an utterance out of context and from written input only. Moreover, the system’s performance is on par with human performance.
Using computed tomography colonography in patients at high risk of colorectal cancer – a prospective study in a university hospital in South America

OBJECTIVES: The purpose of our study was to report the results of the implementation of computed tomography colonography in a university hospital setting serving a Brazilian population at high risk of colorectal cancer. METHODS: After creating a computed tomography colonography service in our institution, 85 patients at high risk of colorectal cancer underwent computed tomography colonography followed by a same-day optical colonoscopy from September 2010 to May 2012. The overall accuracy of computed tomography colonography in the detection of lesions ≥6 mm was compared to that of optical colonoscopy (direct comparison). All colonic segments were evaluated using quality imaging (amount of liquid and solid residual feces and luminal distension). To assess patient acceptance and preference, a questionnaire was completed before and after the computed tomography colonography and optical colonoscopy. Fisher's exact test was used to measure the correlations between colonic distension, discomfort during the exam, exam preference and interpretation confidence. RESULTS: Thirteen carcinomas and twenty-two lesions ≥6 mm were characterized. The sensitivity, specificity and accuracy of computed tomography colonography were 100%, 98.2% and 98.6%, respectively. Computed tomography colonography was the preferred method of investigation for 85% of patients. The preparation was reported to cause only mild discomfort for 97.6% of patients. According to the questionnaires, there was no significant relationship between colonic distension and discomfort (p>0.05). Most patients (89%) achieved excellent bowel preparation. There was a statistically significant correlation between the confidence perceived in reading the computed tomography colonography and the quality of the preparation in each colonic segment (p≤0.001). The average effective radiation dose per exam was 7.8 mSv. CONCLUSION: It was possible to institute an efficient computed tomography colonography service at a university hospital that primarily assists patients from the public health system, with high accuracy, good acceptance and effective radiation doses. Our results seem to be comparable to other centers of excellence and fall within acceptable published guidelines, showing that a successful computed tomography colonography program can be reproduced in a South American population screened in a university hospital.
Early Warning System for DDoS Attacking Based on Multilayer Deployment of Time Delay Neural Network

Distributed denial of service (DDoS) is one of the most persecution network attack techniques to be confronted in recent years. From the definition of DDoS, thousands of network attacks must initiate simultaneously and continuously to achieve a successful DDoS attacking. Therefore, almost all of the information system cannot survive as they confront the DDoS attacks. Although there are a lot of intrusion detection system (IDS) developed, preventing DDoS attack is still difficult and perplexing. In this paper, an early warning system for detecting DDoS attacking has been mounted to a traditional IDS to form a completely system. This early warning system is developed based on the rationale of time delay neural network. In the networking topology, each node is monitored with the deployment of detectors to establish a multilayer architecture. In addition, the activities of each node will be monitored by their neighboring nodes to check whether it is still survival or not mutually. After then, all of the attacking information will be collected and transferred to the expert module for integrating analysis. As those nodes dispatched on the DMZ or between the first and second layer of firewall face some attacking similar as the pattern of DDoS, the kernel expert module which dispatched behind the second firewall will take some feasible actions and initiate the defense strategies to protect the kernel information system. In the meanwhile, those failed nodes will be restarted and act as the role of vanguard to assure the networking under normal operation.
Immunocytochemical studies of endothelial cells in vivo. I. The presence of desmin only, or of desmin plus vimentin, or vimentin only, in the endothelial cells of different capillaries of the adult chicken

It is currently believed that the intermediate filaments of endothelial cells contain vimentin subunits exclusively. This inference, however, is derived from studies of only a few types of endothelial cells. By double indirect immunofluorescence and immunoelectron microscopy, we have now examined the endothelial cells of the micro- and macrovasculature of a variety of tissues and organs of adult chicken in vivo for their content of desmin and vimentin. Endothelial cells of the peritubular capillary in the renal cortex, the hepatic sinusoid, and the splenic sinusoid were found to contain only desmin; those of the exocrine pancreas capillary contained both desmin and vimentin; and the endothelial cells of the macrovasculatures and of all the other microvasculatures examined, including the vasa recta of the renal medulla, contained only vimentin. Such heterogeneity suggests that different types of adult chicken endothelial cells may have different embryological origins. To the extent that desmin and vimentin intermediate filaments may be functionally distinct, these results also suggest that different capillary endothelial cells may have different functional properties.