Miracle-dz/UniFAR-FTUs huggingface dataset:
The Topological Effects of Smoothing

Scientific data sets generated by numerical simulations or experimental measurements often contain a substantial amount of noise. Smoothing the data removes noise but can have potentially drastic effects on the qualitative nature of the data, thereby influencing its characterization and visualization via topological analysis, for example. We propose a method to track topological changes throughout the smoothing process. As a preprocessing step, we oversmooth the data and collect a list of topological events, specifically the creation and destruction of extremal points. During rendering, it is possible to select the number of topological events by interactively manipulating a merging parameter. The result that a specific amount of smoothing has on the topology of the data is illustrated using a topology-derived transfer function that relates region connectivity of the smoothed data to the original regions of the unsmoothed data. This approach enables visual as well as quantitative analysis of the topological effects of smoothing.
On handling cutting planes in interior-point methods for solving semi-definite relaxations of binary quadratic optimization problems

We describe an improved technique for handling large numbers of cutting planes when using an interior-point method for the solution of linear and semi-definite programming relaxations of combinatorial optimization problems. The approach combines an infeasible primal-dual interior-point algorithm with a cutting-plane scheme that does not solve successive relaxations to optimality, but adds and removes cuts at intermediate iterates based on indicators for cut violation and feasibility of the associated slacks. The slack variables of added cuts are initialized using a recently proposed interior-point warm-start technique that relaxes the interiority condition on the original primal-dual variables and enables a restart from the current iterate without additional centring or correction steps. Our computational tests on relaxations of the maximum-cut and single-row facility-layout problem demonstrate that this new scheme is robust for both unconstrained and constrained binary quadratic problems and that its performance is superior to solving only the final relaxation with all relevant cuts known in advance.
A frequency domain deterministic approach to channel identification

This letter studies the problem of identifying a single-input single-output channel by linearly precoding the input. Although it is known that filterbanks induce cyclostationarity if the input is stationary, this work demonstrates that filterbanks induce a special form of spectral redundancy even if the input is deterministic. This frequency domain interpretation of filterbanks nicely characterizes all linear precoders. It not only helps to identify the strengths and aid in the design of linear precoders, it leads to frequency domain subspace methods for the identification of AR, MA and ARMA channels.
A Novel Approach for Segmenting and Classifying Shadow Image

The disadvantages of domestic and oversea shadow image edge detection algorithms are analyzed. A novel shadow detection algorithm based on edge growing and rough set theory and subsequent solution is proposed. We describe how to detect image edge using condition attribution of rough set in this paper. Also, the method of thinning and connection for shadow edge using edge growing from the edge nodes is proposed. As can be seen from the experimental analysis, the method we proposed has better performance in edge detection and image segmentation.
Fitness Costs Limit Viral Escape from Cytotoxic T Lymphocytes at a Structurally Constrained Epitope

ABSTRACT The intense selection pressure exerted by virus-specific cytotoxic T lymphocytes (CTL) on replicating human immunodeficiency virus and simian immunodeficiency virus results in the accumulation of CTL epitope mutations. It has been assumed that fitness costs can limit the evolution of CTL epitope mutations. However, only a limited number of studies have carefully examined this possibility. To explore the fitness costs associated with viral escape from p11C, C-M-specific CTL, we constructed a panel of viruses encoding point mutations at each position of the entire p11C, C-M epitope. Amino acid substitutions at positions 3, 4, 5, 6, 7, and 9 of the epitope significantly impaired virus replication by altering virus production and Gag protein expression as well as by destabilizing mature cores. Amino acid substitutions at position 2 of the epitope were tolerated but required reversion or additional compensatory mutations to generate replication-competent viruses. Finally, while amino acid substitutions at positions 1 and 8 of the p11C, C-M epitope were functionally tolerated, these substitutions were recognized by p11C, C-M-specific CTL and therefore provided no selection advantage for the virus. Together, these data suggest that limited sequence variation is tolerated by the region of the capsid encoding the p11C, C-M epitope and therefore that only a very limited number of mutations can allow successful viral escape from the p11C, C-M-specific CTL response.
A perspective on software agents research

This paper sets out, ambitiously, to present a brief reappraisal of software agents research. Evidently, software agent technology has promised much. However, some five years after the word ‘agent’ came into vogue in the popular computing press, it is perhaps time the efforts in this fledgling area are thoroughly evaluated with a view to refocusing future efforts. We do not pretend to have done this in this paper—but we hope we have sown the first seeds towards a thorough first five-year report on the software agents area. The paper contains some strong views not necessarily widely accepted by the agent community.The views expressed in this paper are those of the authors only, and do not necessarily reflect the views of our organisation.
A SOCS 1 antagonist enhances antigen-presenting capacity and tumor 1 cell antigen-specific cytotoxic T lymphocyte responses by human 2 monocyte-derived dendritic cells

18 Suppressors of cytokine signaling (SOCS) has emerged as a critical inhibitory molecule for 19 controlling the cytokine response and antigen presentation by dendritic cells (DCs), thereby 20 regulating the magnitude of both innate and adaptive immunity. The aim of this study was to 21 investigate whether the SOCS1 antagonist pJAK2(1001–1013) peptide can weaken or block the 22 inhibition function of SOCS1 in DCs by evaluating the phenotype, cytokine production, 23 antigen-presenting and specific T-cell-activating capacity of DCs electroporated with human gastric 24 cancer cell total RNA. Furthermore, the STAT1 activation of JAK/STAT signal pathway mediated 25 by SOCS1 was analyzed by Western blot. Results demonstrated that the SOCS1 antagonist 26 pJAK2(1001–1013) peptide up-regulated the expression of the maturation marker (CD83) and 27 co-stimulatory molecule (CD86) of RNA-electroporated human monocyte-derived mature DCs 28 (mDCs), potentiated the capacity of mDCs to induce T-cell proliferation, stimulated the secretion of 29 pro-inflammatory cytokines, and enhanced the cytotoxicity of tumor cell antigen-specific CTLs 30 activated by human gastric cancer cell total RNA-electroporated mDCs. Data from Western blot 31 analysis indicated that STAT1 was further activated in pJAK2(1001–1013) peptide-loaded mDCs. 32 These results imply that the SOCS1 antagonist pJAK2(1001–1013) peptide is an effective reagent 33 to enhance antigen-specific antitumor immunity by DCs. 34
The association between therapists' attachment security and mentalizing capacity

Aims: The review examines the evidence that parents’ mentalizing predicts infant attachment security. Method: Studies were included if they examined primary care-givers’ mentalizing, defined as the capacity to understand mental states underlying behaviour, and infants’ attachment status. Results: Nine studies met criteria for review. Mentalizing was conceptualised and measured in different ways, including: reflective function (n = 1), maternal reflective function (n = 2), mind-mindedness (n = 5) and insightfulness (n = 1). Conclusion: The studies suggest that care-givers’ attachment contributes to infants’ attachment security. The evidence is limited however by the small number of studies, small sample sizes and methodological and conceptual differences between studies. Moreover mentalizing alone appears unlikely to account fully for the intergenerational transmission of attachment.
A Simple Passive Attitude Stabilizer for Palm-Size Aerial Vehicles

This paper presents a simple passive attitude stabilizer (PAS) for vision-based stabilization of palm-size aerial vehicles. First, a mathematical dynamic model of a palm-size aerial vehicle with the proposed PAS is constructed. Stability analysis for the dynamics is carried out in terms of Lyapunov stability theory. The analysis results show that the proposed stabilizer guarantees passive stabilizing behavior, i.e., passive attitude recovering, of the aerial vehicle for small perturbations from a stability theory point of view. Experimental results demonstrate the utility of the proposed PAS for the aerial vehicle.
Effect of Reference Genome Selection on the Performance of Computational Methods for Genome-Wide Protein-Protein Interaction Prediction

Background Recent progress in computational methods for predicting physical and functional protein-protein interactions has provided new insights into the complexity of biological processes. Most of these methods assume that functionally interacting proteins are likely to have a shared evolutionary history. This history can be traced out for the protein pairs of a query genome by correlating different evolutionary aspects of their homologs in multiple genomes known as the reference genomes. These methods include phylogenetic profiling, gene neighborhood and co-occurrence of the orthologous protein coding genes in the same cluster or operon. These are collectively known as genomic context methods. On the other hand a method called mirrortree is based on the similarity of phylogenetic trees between two interacting proteins. Comprehensive performance analyses of these methods have been frequently reported in literature. However, very few studies provide insight into the effect of reference genome selection on detection of meaningful protein interactions. Methods We analyzed the performance of four methods and their variants to understand the effect of reference genome selection on prediction efficacy. We used six sets of reference genomes, sampled in accordance with phylogenetic diversity and relationship between organisms from 565 bacteria. We used Escherichia coli as a model organism and the gold standard datasets of interacting proteins reported in DIP, EcoCyc and KEGG databases to compare the performance of the prediction methods. Conclusions Higher performance for predicting protein-protein interactions was achievable even with 100–150 bacterial genomes out of 565 genomes. Inclusion of archaeal genomes in the reference genome set improves performance. We find that in order to obtain a good performance, it is better to sample few genomes of related genera of prokaryotes from the large number of available genomes. Moreover, such a sampling allows for selecting 50–100 genomes for comparable accuracy of predictions when computational resources are limited.
Model based noisy speech recognition with environment parameters estimated by noise adaptive speech recognition with prior

We have proposed earlier a noise adaptive speech recognition approach for recognizing speech corrupted by nonstationary noise and channel distortion. In this paper, we extend this approach. Instead of maximum likelihood estimation of environment parameters (as done in our previous work), the present method estimates environment parameters within the Bayesian framework that is capable of incorporating prior knowledge of the environment. Experiments are conducted on a database that contains digit utterances contaminated by channel distortion and nonstationary noise. Results show that this method performs better than the previous methods.
lnterleukin-8 gene polymorphism and susceptibility to gastric cancer in a Brazilian population.

BACKGROUND Studies have demonstrated that some polymorphisms in different interleukin genes may increase the risk of cancer. The aim of this study was to investigate the association between the IL-8 (rs4073) -251A/T gene polymorphism and the risk of gastric cancer (GC). PATIENTS AND METHODS A case-control study was conducted on patients with noncardia gastric cancer. DNA was extracted from leukocytes and the IL-8 (rs4073) -251A/T polymorphism was analyzed by PCR-RFLP. Infection with Helicobacter pylori was investigated in the serum by ELISA. RESULTS The sample consisted of 104 patients with GC and 196 controls. Cigarette smoking (P=0.007) and high fat intake (P=0.01) were more frequent in patients with GC. The proportion of patients infected with H. pylori was similar in the two groups (P=0.101). The frequency of the genotype A/T was higher in the cancer group (P=0.008). An increased risk of GC was found in subjects carrying the genotype A/T (OR=2.50, CI: 1.27-4.90), subjects with high fat intake (OR=1.92, CI: 1.17-3.15), and smokers (OR=2.00, CI: 1.203.31). CONCLUSIONS Subjects with the heterozygous A/T genotype, high fat intake and smokers or ex-smokers presented an increased risk of GC. Individuals with A/A genotype may have protective effect for GC.
The efficacy of home security measures

Crime prevention through environmental design(CPTED) assumes that criminal acts are influenced by their inherent costs and benefits. Policy implications drawn from CPTED suggest that home security measures increase these costs and reduce the likelihood of burglary. This paper tests the efficacy of home security measures. A telephone survey of 566 residents in Mobile County, Alabama, inquired about security measures that burglary victims and nonvictims employed. A logistic regression solution found some, but not all, of these security measures to be quite effective.
On Grief and Grieving: Finding the Meaning of Grief Through the Five Stages of Loss

Elisabeth Kubler-Ross' On Death and Dying changed the way we talk about the end of life. Before her own death in 2004, she and David Kessler completed On Grief and Grieving, which looks at the way we experience the process of grief. Just as On Death and Dying taught us the five stages of death -- denial, anger, bargaining, depression, and acceptance -- On Grief and Grieving applies these stages to the grieving process and weaves together theory, inspiration, and practical advice, including sections on sadness, hauntings, dreams, isolation, and healing.
Unravelling transmission trees of infectious diseases by combining genetic and epidemiological data

Knowledge on the transmission tree of an epidemic can provide valuable insights into disease dynamics. The transmission tree can be reconstructed by analysing either detailed epidemiological data (e.g. contact tracing) or, if sufficient genetic diversity accumulates over the course of the epidemic, genetic data of the pathogen. We present a likelihood-based framework to integrate these two data types, estimating probabilities of infection by taking weighted averages over the set of possible transmission trees. We test the approach by applying it to temporal, geographical and genetic data on the 241 poultry farms infected in an epidemic of avian influenza A (H7N7) in The Netherlands in 2003. We show that the combined approach estimates the transmission tree with higher correctness and resolution than analyses based on genetic or epidemiological data alone. Furthermore, the estimated tree reveals the relative infectiousness of farms of different types and sizes.
Activation of rapid signaling pathways does not contribute to 1α,25‐dihydroxyvitamin D3‐induced growth inhibition of mouse prostate epithelial progenitor cells

The active form of vitamin D, 1α,25‐dihydroxyvitamin D3 (1,25(OH)2D) inhibits the growth of prostate epithelial cells, however the underlying mechanisms have not been clearly delineated. In the current study, the impact of 1,25(OH)2D on the rapid activation of extracellular‐regulated kinase (ERK) 1/2 and protein kinase C α (PKCα), and the role of these pathways in growth inhibition was examined in immortalized mouse prostate epithelial cells, MPEC3, that exhibit stem/progenitor cell characteristics. 1,25(OH)2D treatment suppressed the growth of MPEC3 in a dose and time dependent manner (e.g., 21% reduction at three days with 100 nM 1,25(OH)2D treatment). However, ERK1/2 activity was not altered by 100 nM 1,25(OH)2D treatment for time points from 1 min to 1 h in either serum‐containing or serum‐free medium. Similarly, PKCα activation (translocation onto the plasma membrane) was not regulated by short‐term treatment of 100 nM 1,25(OH)2D. In conclusion, 1,25(OH)2D did not mediate rapid activation of ERK1/2 or PKCα in MPEC3 and therefore the growth inhibitory effect of 1,25(OH)2D is independent of rapid activation of these signaling pathways in this cell type. J. Cell. Biochem. 107: 1031–1036, 2009. © 2009 Wiley‐Liss, Inc.
Adaptive large scale artifact reduction in edge-based image super-resolution

The goal of multi-frame image super-resolution is to use information from low-resolution images to construct highresolution images. Existing construction techniques are highly sensitive to prominent large scale artifacts in the low-resolution images. This paper presents a novel, adaptive approach to large scale artifact reduction in multiframe image super-resolution. The proposed method adaptively selects information from the low-resolution images such that prominent large scale artifacts are rejected during the construction of high-resolution images. An efficient super-resolution algorithm that utilizes the proposed technique with an edge-adaptive constraint relaxation is introduced. Experimental results demonstrate that the proposed algorithm improves the visual quality of the constructed high-resolution images when prominent large scale artifacts exist.
SiMEA: A framework for simulating neurons on multi-electrode array

A Multi-Electrode Array (MEA) is a practical device for recording the extracellular activity of in-vitro biological culture. Such culture - for instance neurons - is prone to mistakes leading to irrelevant recordings or no recording at all. Additionally, with the expenses generated by in-vitro culture, minimizing risks is a must. This paper proposes a framework designed and implemented for simulating the spatial positioning of neuronal cultures on a MEA. The framework serves as a sandbox for researchers to simulate the model of their MEA experiments before its eventual in-vitro implementation. The framework enables simulating the density of the plated culture, the death of cells over time, choosing diverse reconstructed morphologies of cells, and simulating their spiking activity in interaction with Brian2 simulator.
A novel dual neuro-fuzzy system approach for large-scale knowledge consolidation

Fuzzy and neuro-fuzzy systems are increasingly among the key technologies employed in many real-world applications. However, traditional neuro-fuzzy systems are generally still lacking the scalability traits required in the face of large-scale data and the capability to incorporate new information without catastrophically disrupting the existing knowledge base. This work aims at addressing these issues by proposing a novel neuro-fuzzy system termed dual consolidation network (DCN) that models the complementary interactions between hippocampus and neocortex regions in the human brain to consolidate and exploit knowledge effectively. This approach allows the DCN to handle data sets with high-dimensional features and/or a very large number of samples efficiently, as well as to minimize interference when acquiring new information. Preliminary experiments employing DCN on large-scale biomedical data have shown encouraging results.
Discriminative frequent subgraph mining with optimality guarantees

The goal of frequent subgraph mining is to detect subgraphs that frequently occur in a dataset of graphs. In classification settings, one is often interested in discovering discriminative frequent subgraphs, whose presence or absence is indicative of the class membership of a graph. In this article, we propose an approach to feature selection on frequent subgraphs, called CORK, that combines two central advantages. First, it optimizes a submodular quality criterion, which means that we can yield a near‐optimal solution using greedy feature selection. Second, our submodular quality function criterion can be integrated into gSpan, the state‐of‐the‐art tool for frequent subgraph mining, and help to prune the search space for discriminative frequent subgraphs even during frequent subgraph mining. Copyright © 2010 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 3: 302‐318, 2010
Experiential ecommerce: A summary of research investigating the impact of virtual experience on consumer learning

Contents: C.P. Haugtvedt, K.A. Machleit, R.F. Yalch, Introduction. Part I: Community. A. Toder-Alon, F.F. Brunel, W.L. S. Siegal, Ritual Behavior and Community Change: Exploring the Social-Psychological Roles of Net Rituals in the Developmental Processes of Online Consumption Communities. R.M. Schindler, B. Bickart, Published Word of Mouth: Referable, Consumer-Generated Information on the Internet. R. Lewis, L. Mobilio, J.E. Phelps, N. Raman, Understanding Pass-Along Emails: Motivations and Behaviors of Viral Consumers. D.M. Boush, L. Kahle, What, and How, We Can Learn From Online Consumer Discussion Groups. Part II: Advertising. A. Mitchell, A. Valenzuela, How Banner Ads Affect Brand Choice Without Click-Through. J-L. Chandon, M.S. Chtourou, Factors Affecting Click-Through Rate. M.R. Nelson, Exploring Consumer Response to "Advergaming. " R.J. Kent, P.D. Lynch, S.S. Srinivasan, Going Mobile: Marketing and Advertising on Wireless Networks Around the World. Part III: Customization. J.J. Crow, J. Shanteau, Online Product Customization: Factors Investigating the Product and Process. J. Godek, J.F. Yates, Marketing to Individual Consumers Online: The Influence of Perceived Control. D. Luna, L.A. Perrachio, M.D. de Juan Vigaray, Smoother Surfing Across Cultures: Bilinguals on the Web. K.B. Murray, G. Haubl, Processes of Preference Construction in Agent-Assisted Online Shopping. Part IV: Site Design. R.C. Omanson, J.A. Cline, C.L. Nordhielm, Effects of Visual Consistency on the Site Identity and Product Attitude. E. Purinton, D.E. Rosen, Gendered Information Processing: Implication for Web Site Design. B. Fasolo, G.H. McClelland, K.A. Lange, The Effect of Site Design and Interattribute Correlations on Interactive Web-Based Decisions. Part V: Decision Making. P. Henry, Is the Internet Empowering Consumers to Make Better Decisions, or Strengthening Marketers' Potential to Persuade? S. Mishra, R.W. Olshavsky, Rationality Unbounded: The Internet and Its Effect on Consumer Decision Making. J.W. Park, H-J. Lee, H-I. Lee, Consumer Relationships With an e-Brand: Implications for e-Brand Extensions. A.M. Levin, I.P. Levin, C.E. Heath, Finding the Best Ways to Combine Online and Offline Shopping Features. E. Sivadas, B. Stern, R. Mehta, M. Jones, Consumer Behavior in Online Auctions: An Exploratory Study. N.T. Brewer, The Impact of Internet Use on Health Cognitions and Health Behavior. Part VI: Research Tools and Approaches. T. Daugherty, H. Li, F. Biocca, Experiential Ecommerce: A Summary of Research Investigating the Impact of Virtual Experience on Consumer Learning. B.G. Englis, M.R. Solomon, P. Danskin, Web-Based Consumer Research.