Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature-Selection Overfitting with Small-Sample Classifier Design

High-throughput technologies facilitate the measurement of vast numbers of biological variables, thereby providing enormous amounts of multivariate data with which to model biological processes.1 In translational genomics, phenotype classification via gene expression promises highly discriminatory molecular-based diagnosis, and regulatory-network modeling offers the potential to develop therapeutic strategies based on genomic decision making using classical engineering disciplines such as control theory.2Yet one must recognize the obstacles inherent in dealing with extremely large numbers of interacting variables in a nonlinear, stochastic, and redundant system that reacts aggressively to any attempt to probe it—a living system. In particular, large data sets may have the perverse effect of limiting the amount of scientific information that can be extracted, because the ability to build models with scientific validity is negatively impacted by an increasing ratio between the number of variables and the sample size. Our specific interest is in how this dimensionality problem creates the need for feature selection while making feature-selection algorithms less reliable with small samples. Two well-appreciated issues tend to confound feature selection: redundancy and multivariate prediction. Both of these can be illustrated by taking a naïve approach to feature selection by considering all features in isolation, ranking them on the basis of their individual predictive capabilities, selecting some features with the highest individual performances, and then applying a standard classification rule to these features, the reasoning being that these are the best predictors of the class. Redundancy arises because the top-performing features might be strongly related—say, by the fact that they share a similar regulatory pathway—and using more than one or two of them may provide little added benefit. The issue of multivariate prediction arises because top-performing single features may not be significantly more beneficial when used in combination with other features, whereas features that perform poorly when used alone may provide outstanding classifiEvolving Feature Selection
GENERALIZED SYMMETRIC ALTERNATING DIRECTION METHOD FOR SEPARABLE CONVEX PROGRAMMING

The Alternating Direction Method of Multipliers (ADMM) has been proved to be effective for solving separable convex optimization subject to linear constraints. In this paper, we propose a Generalized Symmetric ADMM (GS-ADMM), which updates the Lagrange multiplier twice with suitable stepsizes, to solve the multi-block separable convex programming. This GS-ADMM partitions the data into two group variables so that one group consists of p block variables while the other has q block variables, where p ≥ 1 and q ≥ 1 are two integers. The two grouped variables are updated in a Gauss-Seidel fashion, while the variables within each group are updated in a Jacobi scheme, which would make it very attractive for a big data setting. By adding proper proximal terms to the subproblems, we specify the domain of the stepsizes to guarantee that the GS-ADMM is globally convergent with a worst-case O(1/t) ergodic convergence rate. It turns out that our convergence domain of the stepsizes is significantly larger than other convergence domains in the literature. Hence, the GS-ADMM is more flexible on choosing and using larger stepsizes of the dual variable. Besides, two special cases of the GS-ADMM, which allows using zero penalty terms, are also discussed and analyzed. Compared with several state-of-the-art methods, preliminary numerical experiments on solving the sparse matrix minimization problem in statistical learning show that our proposed method is effective and promising.
EyeQ: Practical Network Performance Isolation at the Edge

The datacenter network is shared among untrusted tenants in a public cloud, and hundreds of services in a private cloud. Today we lack fine-grained control over network bandwidth partitioning across tenants. In this paper we present EyeQ, a simple and practical system that provides tenants with bandwidth guarantees as if their endpoints were connected to a dedicated switch. To realize this goal, EyeQ leverages the high bisection bandwidth in a datacenter fabric and enforces admission control on traffic, regardless of the tenant transport protocol. We show that this pushes bandwidth contention to the network's edge, enabling EyeQ to support end-to-end minimum bandwidth guarantees to tenant end-points in a simple and scalable manner at the servers. EyeQ requires no changes to applications and is deployable with support from the network available today. We evaluate EyeQ with an efficient software implementation at 10Gb/s speeds using unmodified applications and adversarial traffic patterns. Our evaluation demonstrates EyeQ's promise of predictable network performance isolation. For instance, even with an adversarial tenant with bursty UDP traffic, EyeQ is able to maintain the 99.9th percentile latency for a collocated memcached application close to that of a dedicated deployment.
The dream and the cross: Bringing 3D content in a digital edition

The Dream of the Rood is one of the earliest Christian poems in the corpus of Old English literature, and an example of the genre of dream poetry. While its complete text can be found in the 10th Century ”Vercelli Book”, the poem is considerably older, and its oldest occurrence is carved (in runes) on the 7-8th Century Ruthwell Stone Cross. In this paper, we present the prototype of a web-based digital edition of the Dream of the Rood, as it appears on the Ruthwell Cross. The multimedia framework presents the highly detailed 3D model acquired with 3D Scanning technology, together with the transcription and translation of the runes that can be found on its surface. The textual and spatial information are linked through a system of bi-directional links called spots, that give the possibility to the user to have a free navigation over the multimedia content, keeping the 3D and textual data synchronized. The proposed work provides discussion and solution on two main issues related to digital editions: the integration of three dimensional content in the context of the presentation on the web platform of heterogeneous multimedia data, and the creation of an XML encoding that could account for the necessities of 3D data disposition, but keeping the encoding rules in the context of the standards of the community.
Verocytotoxin-producing Escherichia coli 0157:H7 in the Swedish pig population

Verocytotoxin-producing Escherichia coli 0157:H7 (VTEC 0157:H7) was detected in two of 2446 individual faecal samples collected from pigs slaughtered at five Swedish slaughterhouses, indicating a prevalence of 0-08 per cent, with a 95 per cent confidence interval from 0 to 0.16 per cent. Four Swedish VTEC 0157:H7-pOsitiVe farms which kept ruminants and pigs were studied by repeated faecal sampling; VTEC 0157:H7 was isolated from the ruminants and pigs on all the farms and the same strains were present in the pigs and the ruminants. On one of the farms, the organism persisted in the pig population for 11 months. On all four farms, management practices which might have influenced the isolation rate in pigs were identified. A group of young VTEC 0157:H7-positive pigs was moved from one of the VTEC 0157:H7-positiVe farms to a fattening herd where there were no ruminants. The number of VTEC 0157:H7-positive faecal samples decreased gradually and after nine weeks the pigs were all negative; at slaughter none of the pigs was VTEC 0157:H7-positive.
BMS-345541 targets inhibitor of kappaB kinase and induces apoptosis in melanoma: involvement of nuclear factor kappaB and mitochondria pathways.

PURPOSE Constitutive activation of inhibitor of kappaB kinase (IKK) confers melanoma resistance to apoptosis and chemotherapy. Whether IKK is able to serve as a therapeutic target in melanoma is unknown. We explored the possibility of exploiting IKK as a therapeutic target in melanoma by using BMS-345541, a novel compound with a highly selective IKKbeta inhibitory activity, to trigger melanoma cell apoptosis. EXPERIMENTAL DESIGN Three human melanoma cell lines (SK-MEL-5, Hs 294T, and A375), all of which have high constitutive IKK activities, served as in vitro and in vivo melanoma models for treatment with BMS-345541. Two known antitumor drugs (temozolomide and bortezomib) were used as parallel controls for evaluation of the therapeutic efficiency and toxicity of BMS-345541. The effects of BMS-345541 on nuclear factor kappaB (NF-kappaB) signaling and on the apoptosis machinery were investigated. RESULTS Inhibition of constitutive IKK activity by BMS-345541 resulted in the reduction of NF-kappaB activity, CXCL1 chemokine secretion by cultured melanoma cells and melanoma cell survival in vitro and in vivo. The effect of BMS-345541 on tumor cell growth was through mitochondria-mediated apoptosis, based on the release of apoptosis-inducing factor, dissipation of mitochondrial membrane potential, and reduced ratio of B cell lymphoma gene-2 (Bcl-2)/Bcl-associated X protein (Bax) in mitochondria. The BMS-345541 execution of apoptosis was apoptosis-inducing factor-dependent, but largely caspase-independent. CONCLUSION BMS-345541 down-regulation of IKK activity results in mitochondria-mediated apoptosis of tumor cells because the programmed cell death machinery in melanoma cells is highly regulated by NF-kappaB signaling. Therefore, IKK may serve as a potential target for melanoma therapy.
Age as a factor in sensory integration function in Taiwanese children

Objective Sensory integration progresses along a normal developmental sequence. However, few studies have explored how age difference affects the way sensory integration functions in Taiwanese children as they develop. Therefore, this study aims to pinpoint the role of age in sensory integration. Method A purposive sampling plan was employed. The study population comprised 1,000 Chinese children aged 36 to 131 months (mean = 74.48 months, standard deviation = 25.69 months). Subjects were scored on seven subsets of the Test of Sensory Integration Function (TSIF). An analysis of variance (ANOVA) was used to identify differences between four age groups (ages 3–4, 5–6, 7–8, and 9–10 years), in the categories of the TSIF. Results ANOVA revealed that age is a significant factor in each of the seven tasks of sensory integration associated with various stages of development. The effect of age was significant in all four groups for the subscale of Bilateral Integration Sequences. The function of sensory integration for the children aged 5–8 years did not produce statistically significant results for the subscale of Postural Movement, Sensory Discrimination, Sensory Seeking, or Attention and Activity. For the subscale of Sensory Modulation and Emotional Behavior, the effect of age was significant in only group 1 (children aged 3–4 years) and group 2 (children aged 5–6 years). Conclusion There was significant difference between group 1 and group 2 for seven categories. Significant differences were contributed by the differences from group 1 (3–4 years) and group 4 (9–10 years) in five subscales (Postural Movement, Bilateral Integration Sequences, Sensory Discrimination, Sensory Seeking, and Attention and Activity). There were three developmental trends in the seven categories of the TSIF.
Neuroplastin Isoform Np55 Is Expressed in the Stereocilia of Outer Hair Cells and Required for Normal Outer Hair Cell Function

Neuroplastin (Nptn) is a member of the Ig superfamily and is expressed in two isoforms, Np55 and Np65. Np65 regulates synaptic transmission but the function of Np55 is unknown. In an N-ethyl-N-nitrosaurea mutagenesis screen, we have now generated a mouse line with an Nptn mutation that causes deafness. We show that Np55 is expressed in stereocilia of outer hair cells (OHCs) but not inner hair cells and affects interactions of stereocilia with the tectorial membrane. In vivo vibrometry demonstrates that cochlear amplification is absent in Nptn mutant mice, which is consistent with the failure of OHC stereocilia to maintain stable interactions with the tectorial membrane. Hair bundles show morphological defects as the mutant mice age and while mechanotransduction currents can be evoked in early postnatal hair cells, cochlea microphonics recordings indicate that mechanontransduction is affected as the mutant mice age. We thus conclude that differential splicing leads to functional diversification of Nptn, where Np55 is essential for OHC function, while Np65 is implicated in the regulation of synaptic function. SIGNIFICANCE STATEMENT Amplification of input sound signals, which is needed for the auditory sense organ to detect sounds over a wide intensity range, depends on mechanical coupling of outer hair cells to the tectorial membrane. The current study shows that neuroplastin, a member of the Ig superfamily, which has previously been linked to the regulation of synaptic plasticity, is critical to maintain a stable mechanical link of outer hair cells with the tectorial membrane. In vivo recordings demonstrate that neuroplastin is essential for sound amplification and that mutation in neuroplastin leads to auditory impairment in mice.
The Organization Of Curve Detection: Coarse Tangent Fields And Fine Spline Coverings

We propose a new paradigm for curve detection in which an autonomous and atomic description is computed between measurements on the image and global curves. The description takes the form of a discrete tangent field, i.e. an estimated representation of quantized tangents and curvatures at each possible trace point. We then present a new algorithm for inferring global curves through this tangent field. by inferring a covering of the global curve. The elements of the covering are short splines, each of which moves according to a potential distribution computed from the tangent field. Both stages of the algorithm are parallel and both bear some analogy to biological mechanisms for curve detection
Ursa: Scalable Load and Power Management in Cloud Storage Systems

Enterprise and cloud data centers are comprised of tens of thousands of servers providing petabytes of storage to a large number of users and applications. At such a scale, these storage systems face two key challenges: (1) hot-spots due to the dynamic popularity of stored objects; and (2) high operational costs due to power and cooling. Existing storage solutions, however, are unsuitable to address these challenges because of the large number of servers and data objects. This article describes the design, implementation, and evaluation of Ursa, a system that scales to a large number of storage nodes and objects, and aims to minimize latency and bandwidth costs during system reconfiguration. Toward this goal, Ursa formulates an optimization problem that selects a subset of objects from hot-spot servers and performs topology-aware migration to minimize reconfiguration costs. As exact optimization is computationally expensive, we devise scalable approximation techniques for node selection and efficient divide-and-conquer computation. We also show that the same dynamic reconfiguration techniques can be leveraged to reduce power costs by dynamically migrating data off under-utilized nodes, and powering up servers neighboring existing hot-spots to reduce reconfiguration costs. Our evaluation shows that Ursa achieves cost-effective load management, is time-responsive in computing placement decisions (e.g., about two minutes for 10K nodes and 10M objects), and provides power savings of 15%--37%.
Auditory-Based Spectral Amplitude Estimators for Speech Enhancement

We propose a new family of Bayesian estimators for speech enhancement where the cost function includes both a power law and a weighting factor. The parameters of the cost function, and therefore of the corresponding estimator gain, are chosen based on characteristics of the human auditory system, namely, the compressive nonlinearities of the cochlea, the perceived loudness and the ear's masking properties. It is found that choosing the parameters in this way results in a decrease of the estimator gain at high frequencies. This frequency dependence of the gain improves the noise reduction while limiting the speech distortion. Experimental results show that the new estimators achieve better enhancement performance than existing Bayesian estimators such as those based on the minimum mean-square error (MMSE) of the short-time spectral amplitude (STSA), the MMSE of the logarithm of the STSA (LSA) or the weighted euclidien (WE) error, both in terms of objective and subjective measures.
Detection performance of Roy's largest root test when the noise covariance matrix is arbitrary

Detecting the presence of a signal embedded in noise from a multi-sensor system is a fundamental problem in signal and array processing. In this paper we consider the case where the noise covariance matrix is arbitrary and unknown but we are given both signal bearing and noise-only samples. Using a matrix perturbation approach, combined with known results on the eigenvalues of inverse Wishart matrices, we study the behavior of the largest eigenvalue of the relevant covariance matrix, and derive an approximate expression for the detection probability of Roy's largest root test. The accuracy of our expressions is confirmed by simulations.
Performance Analysis of Shortest Path Bridging Control Protocols

Ethernet networks are evolving from the enterprise to the carrier thus facing new demands and requirements. Therefore, a set of new control approaches are being defined for Ethernet. Amongst these, IEEE 802.1aq Shortest Path Bridging (SPB) aims to assure the transmission of unicast and multicast frames on the shortest path in a bridged network. Three protocols have been proposed for the control of SPB. This paper provides an extensive analysis of these proposals based on simulations focusing on protocol convergence time, which is a key attribute of carrier grade networks. The simulation model was created based on recent measurements. Furthermore, the analysis presented in the paper provides reference for further development of Ethernet control protocols.
Work engagement, burnout and related constructs as predictors of turnover intentions : original research

Orientation: The focus of the study was to investigate the predictive relationship between the work engagement-burnout continuum and turnover intentions. Research purpose: The main purpose of the study was to determine whether work engagement, burnout, organisational citizenship behaviour (OCB) and work alienation are predictors of turnover intentions. Motivation for the study: Organisations operating within the 21st century face significant challenges in the management of talent and human capital. One in particular is voluntary employee turnover and the lack of appropriate business models to track this process. Research design, approach and method: A secondary data analysis (SDA) was performed in a quantitative research tradition on the cross-sectional survey data collected from a large South African Information and Communication Technologies (ICT) sector company (n = 2429). Main findings: The results of the study confirmed the predictive model (work engagement, burnout, OCB and work alienation) of turnover intention. Specifically, work engagement and OCBs were significantly negatively related to turnover intention; whilst burnout and work alienation were significantly positively related to turnover intention. Several third-variable relationships, such as biographic and demographic variables, indicated statistical significance. Practical/managerial implications: Practical implications of the study could impact on human resource (HR) value-chain activities in the form of evidence-based and improved recruitment and selection procedures, employee retention strategies and training and development interventions. Issues concerning talent management could also be addressed. Contribution/value-add: The study described in this article took Industrial/Organisational (I/O) psychological concepts and linked them in unique combinations to establish better predictive validity of a new turnover intentions model.
First-class open and closed code framgents

Staged languages that allow “evaluation under lambdas” are excellent implementation languages for programs that manipulate, specialize, and execute code at runtime. In statically typed staged languages, the existence of staging primitives demands a sound distinction between open code (that may be manipulated under lambdas) and closed code (that may be executed). We present λ [ ], a monomorphic type-safe staged language for manipulating code with free identifiers. It differs from most existing staged languages (such as, for example, derivatives of MetaML) in that its dynamic fragment is not hygienic; in other words, dynamic identifiers are not renamed during substitution. λ[ ] contains a first-class run operation, supports mutable cells (and other computational effects), and has decidable type inference. As such, it is a promising first step towards a practical multi-stage programming language.
Antitumor activity of ZD6474, a vascular endothelial growth factor-2 and epidermal growth factor receptor small molecule tyrosine kinase inhibitor, in combination with SC-236, a cyclooxygenase-2 inhibitor.

PURPOSE The epidermal growth factor receptor (EGFR) autocrine pathway plays an important role in cancer cell growth. Vascular endothelial growth factor (VEGF) is a key regulator of tumor-induced endothelial cell proliferation and vascular permeability. Enhanced cyclooxygenase-2 (COX-2) expression has been linked to cancer cell proliferation, EGFR activation, VEGF secretion, and tumor-induced angiogenesis. ZD6474 is an orally available, small molecule, dual VEGF receptor-2 (VEGFR-2) and EGFR tyrosine kinase inhibitor. We investigated the activity of ZD6474 in combination with SC-236, a selective COX-2 inhibitor, to determine the antitumor activity of the simultaneous blockade of EGFR, COX-2, and VEGF functions. EXPERIMENTAL DESIGN The antitumor activity in vitro and in vivo of ZD6474 and/or SC-236 was tested in human cancer cell lines with a functional EGFR autocrine pathway. RESULTS The combination of ZD6474 and SC-236 determined supra-additive growth inhibition in all cancer cell lines tested. In nude mice bearing established human colon (GEO) or lung adenocarcinoma (A549) cancer xenografts and treated with ZD6474 and/or SC-236 for 3 weeks, a reversible tumor growth inhibition was seen with each agent, whereas a more prolonged growth inhibition that lasted for 3 to 5 weeks following the end of treatment resulted from the combination of the two agents. A long-term, 10-week treatment with ZD6474 plus SC-236 resulted in sustained tumor growth inhibition in all mice with tumor eradication in 3 of 10 GEO tumor-bearing mice and in 4 of 10 A549 tumor-bearing mice. CONCLUSIONS This study provides a rationale for evaluating the simultaneous blockade of EGFR, COX-2, and VEGF signaling as cancer therapy in a clinical setting.
A Hybrid Oriya Named Entity Recognition System: Integrating HMM with MaxEnt

This paper describes a hybrid system that applies maximum entropy (MaxEnt) model with Hidden Markov model (HMM) and some linguistic rules to recognize name entities in Oriya language. The main advantage of our system is, we are using both HMM and MaxEnt model successively with some manually developed linguistic rules. First we are using MaxEnt to identify name entities in Oria corpus, then tagging them temporary as reference. The tagged corpus of MaxEnt now regarded as a training process for HMM. Now we use HMM for final tagging. Our approach can achieve higher precision and recall, when providing enough training data and appropriate error correction mechanism.