Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteome coverage prediction with infinite Markov models

Motivation: Liquid chromatography tandem mass spectrometry (LC-MS/MS) is the predominant method to comprehensively characterize complex protein mixtures such as samples from prefractionated or complete proteomes. In order to maximize proteome coverage for the studied sample, i.e. identify as many traceable proteins as possible, LC-MS/MS experiments are typically repeated extensively and the results combined. Proteome coverage prediction is the task of estimating the number of peptide discoveries of future LC-MS/MS experiments. Proteome coverage prediction is important to enhance the design of efficient proteomics studies. To date, there does not exist any method to reliably estimate the increase of proteome coverage at an early stage. Results: We propose an extended infinite Markov model DiriSim to extrapolate the progression of proteome coverage based on a small number of already performed LC-MS/MS experiments. The method explicitly accounts for the uncertainty of peptide identifications. We tested DiriSim on a set of 37 LC-MS/MS experiments of a complete proteome sample and demonstrated that DiriSim correctly predicts the coverage progression already from a small subset of experiments. The predicted progression enabled us to specify maximal coverage for the test sample. We demonstrated that quality requirements on the final proteome map impose an upper bound on the number of useful experiment repetitions and limit the achievable proteome coverage. Contact: manfredc@inf.ethz. ch; jbuhmann@inf.ethz. ch
Trust Evolution: Modeling and Its Applications

Trust plays a crucial role in helping online users collect reliable information and it has gained increasing attention from the computer science community in recent years. Traditionally, research about online trust assumes static trust relations between users. However, trust, as a social concept, evolves as people interact. Most existing studies about trust evolution are from sociologists in the physical world while little work exists in an online world. Studying online trust evolution faces unique challenges because more often than not, available data is from passive observation. In this work, we leverage social science theories to develop a methodology that enables the study of online trust evolution. In particular, we identify the differences of trust evolution study in physical and online worlds and propose a framework, eTrust, to study trust evolution using online data from passive observation in the context of product review sites by exploiting the dynamics of user preferences. We present technical details about modeling trust evolution, and perform experiments to show how the exploitation of trust evolution can help improve the performance of online applications such as trust prediction, rating prediction and ranking evolution.
Cyclooxygenase-2 Is an Independent Prognostic Factor in Gastric Cancer and Its Expression Is Regulated by the Messenger RNA Stability Factor HuR

Purpose: Cyclooxygenase-2 (COX-2) promotes carcinogenesis and its expression associates with clinicopathologic characteristics in gastric cancer. HuR is an mRNA binding protein that controls the stability of certain transcripts including COX-2. We evaluated the prognostic significance of COX-2 and HuR expressions in gastric cancer and whether there exists a link between HuR and COX-2 expressions. Experimental Design: The study included 342 consecutive patients with histologically confirmed gastric adenocarcinoma, of whom 321 patients had tissue specimens available for COX-2 and 316 for HuR immunohistochemistry. Specimens were stained by COX-2– and HuR-specific monoclonal antibodies and scored by two independent observers. Correlation to clinical data and survival was assessed. TMK-1 gastric adenocarcinoma cells were treated with small interfering RNA against HuR and expressions of HuR and COX-2 were detected by immunofluorescence and Western blot analysis. Results: Patients with low COX-2 expression had a cumulative 5-year survival of 53% and those with high COX-2 expression had 16% (P < 0.0001). In multivariate analysis, COX-2 was an independent prognostic factor (P = 0.003). Cytoplasmic HuR expression was associated with high COX-2 expression (P < 0.0001) and with reduced survival (P = 0.004) whereas nuclear positivity for HuR was not. When TMK-1 cells were treated with HuR small interfering RNA, expressions of HuR and COX-2 were reduced. Conclusions: High COX-2 is an independent prognostic factor in gastric cancer. Cytoplasmic expression of HuR associates with high COX-2 expression and with reduced survival, and tissue culture experiments show that HuR can regulate expression of COX-2 in gastric cancer cells.
Intensifying the Dominant Response

Two studies examined the effects of initial nonconscious affective responses on subsequent evaluations made by conversational participants and observers. Participants either first engaged in a subliminal priming task to induce a positive or negative affective response toward a confederate or were in a control (no priming) condition. After the priming task, participants either engaged in an interaction with the confederate or watched the interaction on videotape and then evaluated the confederate. The confederate used an uninvolved interaction style in Study 1 (N = 240) and a more involved style in Study 2 (N = 180). Results for conversational participants suggest that the nonconscious negative prime made the involved interaction seem more positive and the uninvolved interaction seem more negative. As predicted, results were stronger for participants than for observers and were stronger for negative rather than positive nonconscious affect.
Host-Selected Amino Acid Changes at the Sialic Acid Binding Pocket of the Parvovirus Capsid Modulate Cell Binding Affinity and Determine Virulence

ABSTRACT The role of receptor recognition in the emergence of virulent viruses was investigated in the infection of severe combined immunodeficient (SCID) mice by the apathogenic prototype strain of the parvovirus minute virus of mice (MVMp). Genetic analysis of isolated MVMp viral clones (n = 48) emerging in mice, including lethal variants, showed only one of three single changes (V325M, I362S, or K368R) in the common sequence of the two capsid proteins. As was found for the parental isolates, the constructed recombinant viruses harboring the I362S or the K368R single substitutions in the capsid sequence, or mutations at both sites, showed a large-plaque phenotype and lower avidity than the wild type for cells in the cytotoxic interaction with two permissive fibroblast cell lines in vitro and caused a lethal disease in SCID mice when inoculated by the natural oronasal route. Significantly, the productive adsorption of MVMp variants carrying any of the three mutations selected through parallel evolution in mice showed higher sensitivity to the treatment of cells by neuraminidase than that of the wild type, indicating a lower affinity of the viral particle for the sialic acid component of the receptor. Consistent with this, the X-ray crystal structure of the MVMp capsids soaked with sialic acid (N-acetyl neuraminic acid) showed the sugar allocated in the depression at the twofold axis of symmetry (termed the dimple), immediately adjacent to residues I362 and K368, which are located on the wall of the dimple, and approximately 22 Å away from V325 in a threefold-related monomer. This is the first reported crystal structure identifying an infectious receptor attachment site on a parvovirus capsid. We conclude that the affinity of the interactions of sialic-acid-containing receptors with residues at or surrounding the dimple can evolutionarily regulate parvovirus pathogenicity and adaptation to new hosts.
From Early Requirements Modeled by the i* Technique to Later Requirements Modeled in Precise UML

Requirements capture has been acknowledged as a critical phase of software development, precisely because it is the phase which deals not only with technical knowledge, but also with organizational, managerial, economic and social issues. The emerging consensus is that a requirement specification should include not only software specifications but also business models and other kinds of information describing the context in which the intended system will function. Unfortunately, the current dominant object oriented modeling technique, i.e. Unified Modeling Technique, is ill equipped for capturing early requirements which are typically informal and often focus on organisational objectives. UML is more suitable for later phases of requirements capture, which usually focus on completeness, consistency, and automated verification of functional requirements for the new system. In this paper, we present some guidelines for the integration of early and late requirements specifications. For the organizational modeling we use the i* technique, which focuses on the de- scription of organizational relationships among various organizational actors, as well as an understanding of the rationale for the alternatives chosen. For the functional requirements specification, we rely on the precise Unified Mod- eling Language (pUML), annotated with constraints described in OCL. A small CD store example is used to illustrate how the requirements process it- erates between the early and late requirements specification.
Immunohistochemical localization of Ih channel subunits, HCN1–4, in the rat brain

Hyperpolarization‐activated cation currents (Ih) contribute to various physiological properties and functions in the brain, including neuronal pacemaker activity, setting of resting membrane potential, and dendritic integration of synaptic input. Four subunits of the Hyperpolarization‐activated and Cyclic‐Nucleotide‐gated nonselective cation channels (HCN1–4), which generate Ih, have been cloned recently. To better understand the functional diversity of Ih in the brain, we examined precise immunohistochemical localization of four HCNs in the rat brain. Immunoreactivity for HCN1 showed predominantly cortical distribution, being intense in the neocortex, hippocampus, superior colliculus, and cerebellum, whereas those for HCN3 and HCN4 exhibited subcortical distribution mainly concentrated in the hypothalamus and thalamus, respectively. Immunoreactivity for HCN2 had a widespread distribution throughout the brain. Double immunofluorescence revealed colocalization of immunoreactivity for HCN1 and HCN2 in distal dendrites of pyramidal cells in the hippocampus and neocortex. At the electron microscopic level, immunogold particles for HCN1 and HCN2 had similar distribution patterns along plasma membrane of dendritic shafts in layer I of the neocortex and stratum lacunosum moleculare of the hippocampal CA1 area, suggesting that these subunits could form heteromeric channels. Our results further indicate that HCNs are localized not only in somato‐dendritic compartments but also in axonal compartments of neurons. Immunoreactivity for HCNs often occurred in preterminal rather than terminal portions of axons and in specific populations of myelinated axons. We also found HCN2‐immunopositive oligodendrocytes including perineuronal oligodendrocytes throughout the brain. These results support previous electrophysiological findings and further suggest unexpected roles of Ih channels in the brain. J. Comp. Neurol. 471:241–276, 2004. © 2004 Wiley‐Liss, Inc.
A recursive SVD-based self-constructing rule generation for neuro-fuzzy system modeling

We propose a recursive SVD-based self-constructing rule generation (RSVD-SCRG) approach for structure identification in neuro-fuzzy system modeling. Fuzzy clusters are generated incrementally, with none at the beginning, by presenting the training data one by one. For each presented data, we evaluate its input similarities and output similarities to existing clusters. If the data is not similar enough to any of existing clusters, a new fuzzy cluster is created and its corresponding Gaussian input membership functions and TSK-type linear output function are initialized. Otherwise, we combine the data into the most similar existing cluster and update the corresponding membership functions and output function with statistical calculations and a recursive SVD-based least squares estimator. Therefore, our approach solves the parameter estimation problem encountered in processes of cluster generation and updating. Besides, experimental results have shown that our approach generates more precise initial fuzzy rules and produces lower approximation errors than other approaches.
GPUrdma: GPU-side library for high performance networking from GPU kernels

We present GPUrdma, a GPU-side library for performing Remote Direct Memory Accesses (RDMA) across the network directly from GPU kernels. The library executes no code on CPU, directly accessing the Host Channel Adapter (HCA) Infiniband hardware for both control and data. Slow single-thread GPU performance and the intricacies of the GPU-to-network adapter interaction pose a significant challenge. We describe several design options and analyze their performance implications in detail. We achieve 5μsec one-way communication latency and up to 50Gbit/sec transfer bandwidth for messages from 16KB and larger between K40c NVIDIA GPUs across the network. Moreover, GPUrdma outperforms the CPU RDMA for smaller packets ranging from 2 to 1024 bytes by factor of 4.5x thanks to greater parallelism of transfer requests enabled by highly parallel GPU hardware. We use GPUrdma to implement a subset of the global address space programming interface (GPI) for point-to-point asynchronous RDMA messaging. We demonstrate our preliminary results using two simple applications -- ping-pong and a multi-matrix-vector product with constant matrix and multiple vectors -- each running on two different machines connected by Infiniband. Our basic ping-pong implementation achieves 5%higher performance than the baseline using GPI-2. The improved ping-pong implementation with per-threadblock communication overlap enables further 20% improvement. The multi-matrix-vector product is up to 4.5x faster thanks to higher throughput for small messages and the ability to keep the matrix in fast GPU shared memory while receiving new inputs. GPUrdma prototype is not yet suitable for production systems due to hardware constraints in the current generation of NVIDIA GPUs which we discuss in detail. However, our results highlight the great potential of GPU-side native networking, and encourage further research toward scalable, high-performance, heterogeneous networking infrastructure.
Comprehensive Reputation-Based Security Mechanism against Dynamic SSDF Attack in Cognitive Radio Networks

Collaborative spectrum sensing (CSS) was envisioned to improve the reliability of spectrum sensing in centralized cognitive radio networks (CRNs). However, secondary users (SUs)’ changeable environment and ease of compromise make CSS vulnerable to security threats, which further mislead the global decision making and degrade the overall performance. A popular attack in CSS is the called spectrum sensing data falsification (SSDF) attack. In the SSDF attack, malicious cognitive users (MUs) send false sensing results to the fusion center, which significantly degrades detection accuracy. In this paper, a comprehensive reputation-based security mechanism against dynamic SSDF attack for CRNs is proposed. In the mechanism, the reliability of SUs in collaborative sensing is measured with comprehensive reputation values in accordance with the SUs’ current and historical sensing behaviors. Meanwhile a punishment strategy is presented to revise the reputation, in which a reward factor and a penalty factor are introduced to encourage SUs to engage in positive and honest sensing activities. The whole mechanism focuses on ensuring the correctness of the global decision continuously. Specifically, the proposed security scheme can effectively alleviate the effect of users’ malicious behaviors on network decision making, which contributes greatly to enhancing the fairness and robustness of CRNs. Considering that the attack strategy adopted by MUs has been gradually transforming from simplicity, fixedness and singleness into complexity, dynamic and crypticity, we introduce two dynamic behavior patterns (true to false and then to true (TFT) and false to true and then to false (FTF)) to further validate the effectiveness of our proposed defense mechanism. Abundant simulation results verify the rationality and validity of our proposed mechanism.
Regulation of hub mRNA stability and translation by miR430 and the dead end protein promotes preferential expression in zebrafish primordial germ cells

The Hu proteins are RNA‐binding proteins known to be involved in various aspects of RNA metabolism, such as nucleo‐cytoplasmic shuttling, translation, and stability. These proteins are predominantly expressed in neuronal tissues and are important for neuronal differentiation and plasticity. Here, we report on the regulation over hub mRNA stability and function in zebrafish embryos. Using reporters encoding for fluorescent proteins, we show that hub RNA is a target of global miRNA‐mediated repression, while the RNA‐binding protein Dead end (Dnd) contributes to maintenance of the expression in the primordial germ cells (PGCs). Developmental Dynamics 240:695–703, 2011. © 2011 Wiley‐Liss, Inc.
Demotivation: Understanding Resistance to English Language Learning - The Case of Vietnamese Students

Demotivation in English language learning was investigated, using Vietnam as a case study, with three main foci: (i) the reasons (i.e., the demotives) underlying demotivation; (ii) the degree of influence of different demotives; and (iii) students’ experiences in overcoming demotivation. Using stimulated recall essays from 100 university students of their foreign language learning experiences, the findings indicated that demotivation was a significant issue for EFL learning, and a framework for discussing the different sources of demotives was developed. While some categories of demotives occurred more frequent than others, no category appeared to be more or less difficult to overcome. Rather, students’ awareness of the role of English language and their determination to succeed were critical factors in overcoming demotivation.
Learning deformation model for expression-robust 3D face recognition

Expression change is the major cause of local plastic deformation of the facial surface. The intra-class differences with large expression change somehow are larger than the inter-class differences as it's difficult to distinguish the same individual with facial expression change. In this paper, an expression-robust 3D face recognition method is proposed by learning expression deformation model. The expression of the individuals on the training set is modeled by principal component analysis, the main components are retained to construct the facial deformation model. For the test 3D face, the shape difference between the test and the neutral face in training set is used for reconstructing the expression change by the constructed deformation model. The reconstruction residual error is used for face recognition. The average recognition rate on GavabDB and self-built database reaches 85.1% and 83%, respectively, which shows strong robustness for expression changes.
BlobSeer: Bringing high throughput under heavy concurrency to Hadoop Map-Reduce applications

Hadoop is a software framework supporting the Map-Reduce programming model. It relies on the Hadoop Distributed File System (HDFS) as its primary storage system. The efficiency of HDFS is crucial for the performance of Map-Reduce applications. We substitute the original HDFS layer of Hadoop with a new, concurrency-optimized data storage layer based on the BlobSeer data management service. Thereby, the efficiency of Hadoop is significantly improved for data-intensive Map-Reduce applications, which naturally exhibit a high degree of data access concurrency. Moreover, BlobSeer's features (built-in versioning, its support for concurrent append operations) open the possibility for Hadoop to further extend its functionalities. We report on extensive experiments conducted on the Grid'5000 testbed. The results illustrate the benefits of our approach over the original HDFS-based implementation of Hadoop.
Applanation tonometry and correction according to corneal thickness.

PURPOSE In previous studies, it has been shown that the central corneal thickness influences the measurement values of applanation tonometry. The aim of this study is to answer the question as to which values and with what frequency the tonometer readings as based on corneal thickness have to be corrected in the patients attending an ophthalmic practice. SUBJECTS AND METHODS The corneal thickness was measured in 579 patients using ultrasound pachymetry under the conditions prevailing in a medical practice; from the thickness obtained, the correction values for intraocular pressure were calculated. RESULTS Correction values of +/-2 mm Hg and above were found in half of the patients examined, and correction values of +/-3 mm Hg and above in a good quarter of the patients. The correction value was +/-4 mm Hg and more in every fifth patient. CONCLUSIONS Corneal thickness does, in fact, influence the results of applanation tonometry to a clinically relevant degree.
Reconceptualising advocacy: creating inclusive education in US universal pre-kindergarten

This narrative inquiry concerns preschool education in the USA. It describes and analyses the barriers and possibilities for inclusion/exclusion that educators and parents of young children in a West Virginian community believe that it poses. The researchers present a case study designed to examine the context of inclusive education as revealed in 15 educators’ and parents’ narratives and observations of universal pre-kindergarten (UPK) practice. Due to semi-market-based orientations, new UPK structures, and perceptions of acceptable roles for parents and educators, possibilities for advocacy, and inclusive education often went unrealised. Based on these data, the researchers offer suggestions for how teacher education might be further developed to reconceptualise advocacy as inclusive education created in part through a praxis orientation and deliberative relationships between homes and schools.
Modeling of Threshold-Voltage Drift in Phase-Change Memory (PCM) Devices

The amorphous phase of the chalcogenide material in phase-change memory (PCM) devices is sensitive to temperature-activated crystallization and structural relaxation (SR). The latter leads to a change of device/material properties, such as the mobility band gap, the resistance, and the threshold voltage VT for threshold switching. In this paper, we present a VT drift model based on physical descriptions of the electrical transport, the threshold switching, and the SR. We introduce an analytical formula describing the relation between the drift slopes of resistance and VT via the subthreshold slope STS of the I-V curve. A numerical model predicting the time evolution of VT for different programmed states in the PCM multilevel cell is finally presented and compared with experiments.