Miracle-dz/UniFAR-FTUs huggingface dataset:
A FRGSNN Hybrid Feature Selection Combining FRGS filter and GSNN wrapper

How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes. Widely used methods typically rank genes according to their differential expressions among phenotypes and pick the top-ranked genes. While microarrays can measure the levels of thousands of genes per sample, case-control microarray studies usually involve no more than several dozen samples. Standard classifiers do not work well in these situations where the number of features (gene expression levels measured in these microarrays) far exceeds the number of samples. Selecting only the features that are most relevant for discriminating between the two categories can help construct better classifiers, in terms of both accuracy and efficiency. We observe that feature sets so obtained have certain redundancy and study methods to minimize it. We propose the minimum redundancy and maximum relevance feature selection framework. In this paper we have applied two general approaches of feature subset selection, more specifically, wrapper and filter approaches and then created a new model called hybrid model by combining the characteristics of the two specified models for gene selection. We have also compared the gene selection performance of the filter model, wrapper model and hybrid model. This lead to significantly improved class predictions in extensive experiments on 4 gene expression data sets: CNS, Leukemia, Lung and Brain Tumor. Improvements are observed consistently among 3 neural network algorithms classification methods such as Linear Vector Quantization (LVQ), Self-Organization Map (SOM) and Back Propagation (BP). The selection of efficient feature extraction techniques and predictive models provide high classification accuracy for microarray dataset. As such, the investigations show that a small number of gene expression data has strong correlation with certain phenotypes compared to the total number of genes available. Consequently, selections of differentially expressed relevant predictor genes correctly analyse gene expression profiles and also play a crucial role in classification process. The subset of potential genes identified by feature selection technique correctly distinguish the sample classes. Therefore, a good selection method for genes, relevant for sample classification- based on the number of genes investigated-is needed to increase the predictive accuracy and to avoid incomprehensibility. An application of the gene expression data analysis is cancer classification. Usually, expression levels of the
A hybrid joint ML technique for CFO, timing offset, and channel estimations in an OFDMA uplink

In this paper, we propose a novel hybrid joint maximum‐likelihood estimator for carrier frequency offset (CFO), timing offset, and channel response of all users in the uplink of an orthogonal frequency division multiple access (OFDMA) system. The proposed estimation method significantly reduces complexity of this multiparameter, multidimensional optimization problem, using the concept of separation of the different user signals by means of newly defined projection operators. This projection technique is combined with the alternating projection method available in the literature to arrive at a new hybrid algorithm that offers significant performance advantages in terms of computational complexity and estimator performance. The joint estimation of the CFOs, timing offsets, and channel coefficients for all active users together at the base station of the OFDMA uplink is a rarely addressed task. The proposed method also offers the flexibility of application to any subcarrier assignment scheme used in OFDMA systems. Extensive simulation studies corroborate the advantages of the new hybrid method for all three estimation requirements in the multiuser OFDMA uplink. Copyright © 2012 John Wiley & Sons, Ltd.
Channel Material Dependence of Wave Function Deformation Scattering in Ultrascaled FinFETs

We investigate the channel material dependence of wave function deformation scattering (WDS), a phenomenon that occurs when the shape of the carrier wave function is forced to change as the channel is traversed. Line-edge roughness (LER) is one nonideality that can induce WDS in confined device geometries. We perform nonequilibrium Green’s function simulations of ensembles of ultrascaled Fin Field Effect Transistors that exhibit correlated LER to determine the resulting on-current distributions. By considering various channel materials, we demonstrate two trends. First, WDS has a greater impact when the transport effective mass of the channel material is low, due to stronger coupling between conducting subbands. Second, WDS has a greater impact when the confinement effective mass of the channel material is high, due to the presence of more conducting subbands, which further enhances coupling.
The Eukaryotic Promoter Database: expansion of EPDnew and new promoter analysis tools

We present an update of EPDNew (http://epd.vital-it.ch), a recently introduced new part of the Eukaryotic Promoter Database (EPD) which has been described in more detail in a previous NAR Database Issue. EPD is an old database of experimentally characterized eukaryotic POL II promoters, which are conceptually defined as transcription initiation sites or regions. EPDnew is a collection of automatically compiled, organism-specific promoter lists complementing the old corpus of manually compiled promoter entries of EPD. This new part is exclusively derived from next generation sequencing data from high-throughput promoter mapping experiments. We report on the recent growth of EPDnew, its extension to additional model organisms and its improved integration with other bioinformatics resources developed by our group, in particular the Signal Search Analysis and ChIP-Seq web servers.
Study of Proper Hierarchical Graphs on a Grid

Hierarchical planar graph embedding (sometimes called level planar graphs) is widely recognized as a very important task in diverse fields of research and development. Given a proper hierarchical planar graph, we want to find a geometric position of every vertex (layout) in a straight-line grid drawing without any edge-intersection. An additional objective is to minimize the area of the rectangular grid in which G is drawn with more aesthetic embedding. In this paper we propose several ideas to find an embedding of G in a rectangular grid with area, ( -1) × (k-1), where is the number of vertices in the longest level and k is the number of levels in G. )
Dead Letters to Alice - Reachability of E-Mail Addresses in the PGP Web of Trust

Over the last 25 years four million e-mail addresses have accumulated in the PGP web of trust. In a study each of them was tested for vitality with the result of 40% being unreachable. Of the mailboxes proven to be reachable, 46.77% turn out to be operated by one of three organizations. In this article, the authors share their results and challenges during the study.
Developing trust in large-scale peer-to-peer systems

In peer-to-peer (P2P) systems, peers often must interact with unknown or unfamiliar peers without the benefit of trusted third parties or authorities to mediate the interactions. A peer needs reputation mechanisms to incorporate the knowledge of others to decide whether to trust another party in P2P systems. This paper discusses the design of reputation mechanisms and proposes a distributed reputation mechanism to detect malicious or unreliable peers in P2P systems. It illustrates the process for rating gathering and aggregation and presents some experimental results to evaluate the proposed approach. Moreover, it considers how to effectively aggregate noisy (dishonest or inaccurate) ratings from independent or collusive peers using weighted majority techniques. Furthermore, it analyzes some possible attacks on reputation mechanisms and shows how to defend against such attacks.
Leaders' fairness and followers' conflict handling style: The moderating role of need for cognitive closure

Purpose – The present paper aims to identify an important moderator of the effect of leader's fairness on the conflict handling style adopted by followers. Based on the uncertainty management model the authors hypothesize that the motivation to reduce uncertainty, reflected by individual differences in need for cognitive closure, moderates the use of constructive conflict handling style as a response to variation in leader's perceived procedural fairness.Design/methodology/approach – A correlational study was conducted on a sample of 175 Italian public employees. Each participant filled out a questionnaire. Data analysis was carried out performing a series of multiple regression analyses.Findings – Consistent with previous research, regression analysis showed that perceived leader's fairness promoted a more constructive approach to manage conflict with leaders. More importantly this relationship was stronger under high rather than low need for cognitive closure.Practical implications – Present results sug.
Poor Man's Virtual Camera: Real-Time Simultaneous Matting and Camera Pose Estimation

Today's film and advertisement production heavily uses computer graphics combined with living actors by chroma keying. The matchmoving process typically takes a considerable manual effort. Semiautomatic matchmoving tools exist as well, but they still work offline and require manual check-up and correction. In this paper, we propose an instant matchmoving solution for green screen. It uses a recent technique of planar uniform marker fields. Our technique can be used in indie and professional filmmaking as a cheap and ultramobile virtual camera, and for shot prototyping and storyboard creation. The matchmoving technique based on marker fields of shades of green is very computationally efficient: we developed and present in this paper a mobile application running at 33 FPS. Our technique is thus available to anyone with a smartphone at low cost and with an easy setup, opening space for new levels of filmmakers’ creative expression.
High-Level HOOK3 Expression Is an Independent Predictor of Poor Prognosis Associated with Genomic Instability in Prostate Cancer

Hook microtubule-tethering protein 3 (HOOK3) is an adaptor protein for microtubule-dependent intracellular vesicle and protein trafficking. In order to assess the role of HOOK3 in prostate cancer we analyzed HOOK3 expression by immunohistochemistry on a TMA containing more than 12,400 prostate cancers. Results were compared to tumor phenotype and PSA recurrence as well as aberrations possibly defining relevant molecular subtypes such as ERG status and deletions of 3p13, 5q21, 6q15 and PTEN. HOOK3 immunostaining was negative in normal luminal cells of prostate epithelium, whereas 53.3% of 10,572 interpretable cancers showed HOOK3 expression, which was considered low in 36.4% and high in 16.9% of cases. High-level HOOK3 expression was linked to advanced tumor stage, high Gleason score, high proliferation index, positive lymph node stage, and PSA recurrence (p<0.0001 each). The prognostic role of HOOK3 expression was independent of established clinico-pathological parameters both in preoperative and postoperative settings. Comparisons with molecular features were performed to draw conclusions on the potential function of HOOK3 in the prostate. A strong association with all examined deletions is consistent with a role of HOOK3 for maintaining genomic integrity by contributing to proper centrosome assembly. Finding HOOK3 expression in 74% of ERG positive but in only 38% of ERG negative cancers (p<0.0001) further suggests functional interactions between these genes. In conclusion, the results of our study identify HOOK3 as a strong candidate prognostic marker with a possible role in maintaining genomic integrity in prostate cancer, which may have potential for inclusion into clinical routine assays.
Efficient Structured Prediction with Latent Variables for General Graphical Models

In this paper we propose a unified framework for structured prediction with latent variables which includes hidden conditional random fields and latent structured support vector machines as special cases. We describe a local entropy approximation for this general formulation using duality, and derive an efficient message passing algorithm that is guaranteed to converge. We demonstrate its effectiveness in the tasks of image segmentation as well as 3D indoor scene understanding from single images, showing that our approach is superior to latent structured support vector machines and hidden conditional random fields.
Exploiting sequential dependencies for expert finding

We propose an expert finding method based on assumption of sequential dependence between a candidate expert and the query terms in the scope of a document. We assume that the strength of relation of a candidate to the document's content depends on its position in this document with respect to the positions of the query terms. The experiments on the official Enterprise TREC data demonstrate the advantage of our method over the method based on independence of query terms and persons in a document.
Fast Semi-Automatic Reconstruction of Heart Pathology from MRI Data with Soft Objects

Heart diseases cause considerable morbidity and the prognosis after heart failure is poor. Modelling the heart pathology is useful for diagnosis, analysis, and treatment planning of cardiac diseases. This is in particular the case for congenital abnormalities where surgery is often necessary directly after birth. Over the past decade, a variety of tools for ventricular modelling have been suggested. However, most of them require either substantial user interaction or make use of the default topology of a healthy heart. In this paper we present a modelling tool based on soft objects which allows a fast semi-automatic approximation of the heart pathology. The tool requires little user interaction, works well for normal and abnormal heart topologies, and makes it easy to model cardiac arteries and veins.
Comparison of Levels of Satisfaction with Distance Education and On-campus Programs

Introduction The study compared the level of satisfaction of 101 graduates with a distance education versus an on-campus program. Methods A self-administered anonymous survey was used to gather information about satisfaction from the recent graduates of a university personnel preparation program in visual impairments (response rate = 57.7%). The survey measured graduates’ satisfaction with their programs in six subareas: (1) faculty-student interaction, (2) student-student interaction, (3) fairness of evaluations, (4) organization of courses, (5) adequacy of the difficulty of courses, and (6) practicum or internship experience. Results The program modality was not a significant predictor of overall satisfaction with a program once we controlled for the confounding variables, including age, program area, and presence of visual impairments (—.277 – .226, 95% CI). However, it was a significant independent predictor of faculty-student interaction (—.616 – —.012, 95% CI) and student-student interaction (—.875 – —.073, 95% CI). Discussion There was no significant difference in the two groups of graduates’ overall satisfaction with the program, but although the findings are preliminary in nature, the graduates from the on-campus program indicated a higher level of faculty-student and student-student interactions. Implications for practitioners Given the findings of this study, prospective students who are interested in university personnel preparation programs in visual impairments may consider distance education programs an option that may satisfy them. Similarly, these programs may consider continuing their distance education programs as a satisfactory option for many students. However, the lower level of faculty-student and student-student interactions perceived by the distance education graduates may suggest a need to ensure a mechanism that facilitates such interactions more effectively.
Science objectives of the ozone monitoring instrument

The Ozone Monitoring Instrument (OMI) flies on NASA's Earth Observing System AURA satellite, launched in July 2004. OMI is an ultraviolet/visible (UV/VIS) nadir solar backscatter spectrometer, which provides nearly global coverage in one day, with a spatial resolution of 13 km/spl times/24 km. Trace gases measured include O/sub 3/, NO/sub 2/, SO/sub 2/, HCHO, BrO, and OClO. In addition OMI measures aerosol characteristics, cloud top heights and cloud coverage, and UV irradiance at the surface. OMI's unique capabilities for measuring important trace gases with daily global coverage and a small footprint will make a major contribution to our understanding of stratospheric and tropospheric chemistry and climate change along with Aura's other three instruments. OMI's high spatial resolution enables detection of air pollution at urban scales. Total Ozone Mapping Spectrometer and differential optical absorption spectroscopy heritage algorithms, as well as new ones developed by the international (Dutch, Finnish, and U.S.) OMI science team, are used to derive OMI's advanced backscatter data products. In addition to providing data for Aura's prime objectives, OMI will provide near-real-time data for operational agencies in Europe and the U.S. Examples of OMI's unique capabilities are presented in this paper.
What the Frog's Eye Tells the Frog's Brain

In this paper, we analyze the activity of single fibers in the optic nerve of a frog. Our method is to find what sort of stimulus causes the largest activity in one nerve fiber and then what is the exciting aspect of that stimulus such that variations in everything else cause little change in the response. It has been known for the past 20 years that each fiber is connected not to a few rods and cones in the retina but to very many over a fair area. Our results show that for the most part within that area, it is not the light intensity itself but rather the pattern of local variation of intensity that is the exciting factor. There are four types of fibers, each type concerned with a different sort of pattern. Each type is uniformly distributed over the whole retina of the frog. Thus, there are four distinct parallel distributed channels whereby the frog's eye informs his brain about the visual image in terms of local pattern independent of average illumination. We describe the patterns and show the functional and anatomical separation of the channels. This work has been done on the frog, and our interpretation applies only to the frog.
A game-theoretic framework with reinforcement learning for multinode cooperation in wireless networks

In this paper, a game-theoretic framework based on the iterated prisoner's dilemma (IPD) is proposed to model the repeated dynamic interactions of multiple source nodes when communicating with multiple destinations in ad-hoc wireless networks. In such networks where nodes are autonomous, selfish, and not familiar with other nodes' strategies, fully cooperative behaviors cannot be assumed. Thus, a Q-learning algorithm is proposed to allow network nodes to adapt to and play the IPD game against opponents with a variety of known and unknown strategies. Simulation results illustrate that the proposed Q-learning algorithm allows network nodes to play optimally and achieve their maximum expected return values.
Dimensions of trust as predictors of willingness to share and use tacit knowledge among health workers in Nigeria

While there is a growing body of empirical studies on the predictors of tacit knowledge sharing behaviour among employees in service and non-service industries, little is known about health workers willingness to share and use tacit knowledge in Nigeria. This study examined how the dimensions of trust (affect-based trust and cognition-based trust) predict willingness to share and use tacit knowledge among health workers in Nigeria. The study adopted a cross-sectional survey design. Using a simple random sampling technique, a sample of 410 health workers were randomly selected from a Federal Medical Centre and a State hospital in Ondo State, South-Western Nigeria. Participants’ ages ranged from 22 to 53 years with a mean of 29.61 years (SD = 8.48). Hierarchical multiple regression analysis was used to test the study hypotheses. Results indicated that both affect-based trust and cognition-based trust significantly contributed to healthcare workers willingness to share and use tacit knowledge. However, affect-based trust contributed more than cognition-based trust to willingness to share tacit knowledge while cognition-based trust exerted more influence than affect-based trust on willingness to use tacit knowledge. Hence, we suggest that in order to facilitate tacit knowledge sharing and use among health workers, managements of healthcare sector in Nigeria should establish psychological strategies that can foster affect-based trust and cognition-based trust among health workers.
Metacognitive Therapy for Comorbid Anxiety Disorders: A Case Study

We aimed to systematically evaluate a generic model of metacognitive therapy (MCT) with a highly comorbid anxiety disorder patient, that had been treated with diagnosis-specific cognitive-behavioral therapy (CBT) without significant effect. Traditionally, CBT has progressed within a disorder-specific approach, however, it has been suggested that this could be less optimal with highly comorbid patients. To address comorbidity, transdiagnostic treatment models have been emerging. This case study used an AB-design with repeated assessments during each therapy session and a 1-year follow-up assessment to evaluate the effectiveness of MCT. Following 8 sessions of MCT, significant decrease in anxiety and depression symptoms, as well as loss of diagnostic status was observed. Outcomes were preserved at 12 months follow up. The generic model of MCT seems promising as an approach to highly comorbid mixed anxiety depression patients. Further testing using more powered methodologies are needed.
Enhanced Progression of Urinary Albumin Excretion in IDDM During Puberty

OBJECTIVE To determine whether the progression of urinary albumin excretion rate (AER) is higher during puberty than before or after this period. RESEARCH DESIGN AND METHODS A prospective study was conducted in which normoalbuminuric prepubertal (n = 20), pubertal (n = 28), and postpubertal (n = 26) IDDM groups matched for diabetes duration and long-term metabolic control were followed for 3 years. At 6-month intervals, 24-h urine collection was used to determine AER. RESULTS AER increased significantly over a period of 3 years in the pubertal (P = 0.001) and postpubertal (P = 0.003) subjects but not in prepubertal subjects. The annual progression of AER was significantly higher in the pubertal group than in the prepubertal (P = 0.001) or postpubertal (P = 0.001) groups. Six pubertal, two postpubertal, and none of the prepubertal subjects developed microalbuminuria (AER ≥ 20 μg/min on two consecutive occasions) over a 3-year period (P = 0.047). Multiple logistic regression analysis showed that the risk of development of microalbuminuria was increased in pubertal subjects compared with the prepubertal and postpubertal subjects (adjusted relative risk [95% CI]: 4.3 [1.5–9.3], P = 0.012, and 2.1 [1.1–5.0], P = 0.023, respectively). CONCLUSIONS Puberty represents an independent risk of the development of microalbuminuria in diabetes. This findings suggests that the endocrine changes of puberty lead to an accelerated process of early kidney damage in diabetes. In pediatric diabetes care, screening for microalbuminuria is needed soon after the onset of puberty.