Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-organized stochastic tipping in slow-fast dynamical systems

Polyhomeostatic adaption occurs when evolving systems try to achieve a target distribution function for certain dynamical parameters, a generalization of the notion of homeostasis. Here we consider a single rate encoding leaky integrator neuron model driven by white noise, adapting slowly its internal parameters, the threshold and the gain, in order to achieve a given target distribution for its time-average firing rate. For the case of sparse encoding, when the target firing-rated distribution is bimodal, we observe the occurrence of spontaneous quasi-periodic adaptive oscillations resulting from fast transition between two quasi-stationary attractors. We interpret this behavior as self-organized stochastic tipping, with noise driving the escape from the quasi-stationary attractors.
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming

Sparse additive models are families of d-variate functions with the additive decomposition f* = Σj∈S fj*, where S is an unknown subset of cardinality s < d. In this paper, we consider the case where each univariate component function fj* lies in a reproducing kernel Hilbert space (RKHS), and analyze a method for estimating the unknown function f* based on kernels combined with l1-type convex regularization. Working within a high-dimensional framework that allows both the dimension d and sparsity s to increase with n, we derive convergence rates in the L2(P) and L2(Pn) norms over the class Fd,s,H of sparse additive models with each univariate function fj* in the unit ball of a univariate RKHS with bounded kernel function. We complement our upper bounds by deriving minimax lower bounds on the L2(P) error, thereby showing the optimality of our method. Thus, we obtain optimal minimax rates for many interesting classes of sparse additive models, including polynomials, splines, and Sobolev classes. We also show that if, in contrast to our univariate conditions, the d-variate function class is assumed to be globally bounded, then much faster estimation rates are possible for any sparsity s = Ω(√n), showing that global boundedness is a significant restriction in the high-dimensional setting.
The miR‐137 schizophrenia susceptibility variant rs1625579 does not predict variability in brain volume in a sample of schizophrenic patients and healthy individuals

The micro RNA 137 (miR‐137) variant rs1625579 has been identified as a genome‐wide significant risk variant for schizophrenia. miR‐137 has an established role in neurodevelopment and may mediate cognitive dysfunction in schizophrenia. This role of miR‐137 may be related to changes in brain morphology for risk‐related genotypes; however this has not yet been delineated. Here we considered whether rs1625579 genotype was predictive of indices of brain structure in patients with schizophrenia and healthy controls. Structural magnetic resonance imaging (sMRI) data (i.e. 3T T1‐TFE or 1.5T T1‐MPRAGE) were acquired from 150 healthy controls and 163 schizophrenic patients. Two volumetric analyses that considered the impact of miR‐137/rs1625579 genotype were carried out on sMRI data. In the first analysis, voxel based morphometry was employed to consider genotype‐related variability in local grey and white matter across the entire brain volume. Our secondary analysis utilized the FIRST protocol in FSL to consider the volume of subcortical structures (i.e. bilateral accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus). Several brain regions in both analyses demonstrated the expected main effect of participant group (i.e. schizophrenics < controls), yet there were no regions where we observed an impact of rs1635579 genotype on brain volume. Our analyses suggest that the mechanism by which miR‐137 confers risk for schizophrenia and impacts upon cognitive function may not be mediated by changes in local brain volume. However, it remains to be determined whether or not alternative measures of brain structure are related to these functions of miR‐137. © 2014 Wiley Periodicals, Inc.
Implementation of buffy coat platelet component production: comparison to platelet‐rich plasma platelet production

BACKGROUND: Buffy coat (BC) production of platelets (PLTs) has been successfully used in Europe for more than two decades. Currently, Canadian Blood Services is implementing the BC method. This article summarizes results of the validation testing performed to qualify the process of PLT production from whole blood and compares the quality of PLTs produced in routine production by either the PLT‐rich plasma method (PRP‐PCs) or the BC method (BC‐PCs).
The Organizational Adoption of Open Source Server Software: A Quantitative Study

Despite the attention that open source software (OSS) has received, relatively little is known about the factors which influence the decision of an organization on whether to adopt OSS or not. Although much anecdotal evidence has been published on this topic in practitioner literature, these claims have been insufficiently validated. Although some qualitative studies on the organizational adoption of OSS have been conducted, empirical support based on a large sample is missing. In this paper, we propose a conceptual model describing the factors that influence the organizational adoption of open source server software (OSSS). This model is based upon the results of a prior qualitative study that we have conducted in Belgian organizations. We present the results of a partial least squares analysis of survey data collected from 270 Belgian organizations. The main factors that influence the adoption of OSSS are its reliability, the presence of boundary spanners in the organization, and the switching costs involved in the migration. The latter are influenced by the availability of external support, the perception that OSSS is less expensive and the presence of boundary spanners. These results largely confirm the findings of our qualitative study. Theoretical and practical implications are discussed.
Distributed Maximum Likelihood Sensor Network Localization

We propose a class of convex relaxations to solve the sensor network localization problem, based on a maximum likelihood (ML) formulation. This class, as well as the tightness of the relaxations, depends on the noise probability density function (PDF) of the collected measurements. We derive a computational efficient edge-based version of this ML convex relaxation class and we design a distributed algorithm that enables the sensor nodes to solve these edge-based convex programs locally by communicating only with their close neighbors. This algorithm relies on the alternating direction method of multipliers (ADMM), it converges to the centralized solution, it can run asynchronously, and it is computation error-resilient. Finally, we compare our proposed distributed scheme with other available methods, both analytically and numerically, and we argue the added value of ADMM, especially for large-scale networks.
Automatic trust calculation for service-oriented systems

Among various service providers providing identical or similar services with varying quality of service, trust is essential for service consumers to find the right one. Manually assigning feedback costs much time and suffers from several drawbacks. Only automatic trust calculation is feasible for large-scale service-oriented applications. Therefore an automatic method of trust calculation is proposed. To make the calculation accurate, the Kalman filter is adopted to filter out malicious non-trust quality criterion (NTQC) values instead of malicious trust values. To offer higher detection accuracy, it is further improved by considering the relationship between NTQC values and variances. Since dishonest or inaccurate values can still influence trust values, the similarity between consumers is used to weight data from other consumers. As existing models only used the Euclidean function and ignored others, a collection of distance functions is modified to calculate the similarity. Finally, experiments are carried out to access the robustness of the proposed model. The results show that the improved algorithm can offer higher detection accuracy, and it was discovered that another equation outperformed the Euclidean function.
Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems

It has been suggested that neural systems across several scales of organization show optimal component placement, in which any spatial rearrangement of the components would lead to an increase of total wiring. Using extensive connectivity datasets for diverse neural networks combined with spatial coordinates for network nodes, we applied an optimization algorithm to the network layouts, in order to search for wire-saving component rearrangements. We found that optimized component rearrangements could substantially reduce total wiring length in all tested neural networks. Specifically, total wiring among 95 primate (Macaque) cortical areas could be decreased by 32%, and wiring of neuronal networks in the nematode Caenorhabditis elegans could be reduced by 48% on the global level, and by 49% for neurons within frontal ganglia. Wiring length reductions were possible due to the existence of long-distance projections in neural networks. We explored the role of these projections by comparing the original networks with minimally rewired networks of the same size, which possessed only the shortest possible connections. In the minimally rewired networks, the number of processing steps along the shortest paths between components was significantly increased compared to the original networks. Additional benchmark comparisons also indicated that neural networks are more similar to network layouts that minimize the length of processing paths, rather than wiring length. These findings suggest that neural systems are not exclusively optimized for minimal global wiring, but for a variety of factors including the minimization of processing steps.
Modulation of the Partition Coefficient between Octanol and Buffer at pH 7.4 and pKa to Achieve the Optimum Balance of Blood Clearance and Volume of Distribution for a Series of Tetrahydropyran Histamine Type 3 Receptor Antagonists

The relationship between rat pharmacokinetics and physicochemical parameters [the partition coefficient between octanol and buffer at pH 7.4 (log D(7.4)) and pKa] was studied for a series of tetrahydropyran compounds. Sixteen compounds ranging in log D(7.4) 0.1 to 1.8 were administered intravenously to rats, and the pharmacokinetic parameters were determined from blood concentration time curves. Across the series, a weak correlation was observed between log D(7.4) and blood clearance, suggesting that log D(7.4) values less than 0.5 were required to prevent clearance at hepatic blood flow. In terms of the volume of distribution (Vd), the compounds fell into three distinct subseries characterized by the number of basic centers and differences in ionization of each basic center at physiological pH. These were referred to as the monobasic, weak second base, and strong second base subseries. All the compounds exhibited Vd greater than body water, as would be expected from their lipophilic and basic nature. For a given clog P, the strong second base subseries showed higher Vd than the weak second base subseries, which in turn exhibited higher values than the monobasic subseries. In addition, for the weak second base subseries, Vd could be tuned by modulating the pKa of the second basic center. This relationship was rationalized in respect to the interactions of the ionizable centers with phospholipid heads in the cell membrane and/or lysosomal trapping. Compounds in the weak second base subseries showed optimal Vd, and when combined with a log D(7.4) of 0.1, driving to moderate blood clearance, one compound showed the optimal pharmacokinetic profile.
Threshold estimation in self-destructing scheme using regression analysis

As technologies and services that leverage cloud computing evolve, more and more businesses or individuals are using them. However, as users increasingly use and store personal information in cloud storage, research on privacy protection models in the cloud environment is becoming more important. A self-destructing scheme has been proposed to prevent the decryption of encrypted user data after a certain period of time using a DHT network. However, the existing privacy protection model does not mention the method of setting the threshold value considering the availability and security of the data. Therefore, in this paper, we propose an optimal threshold finding method considering both data availability and security of privacy protection model by applying regression analysis.
Hierarchical mesh deformation with shape preservation

It is very difficult to deform flexible objects in computer animation. This paper presents a novel approach to address this problem. A detail‐sensitive and deformation‐sensitive simplification is first conducted on the original mesh. The simplified mesh is then deformed, and this deformation is transferred to the original mesh to produce an initial result. Because of the discontinuity between some vertices, an as‐rigid‐as‐possible optimization is employed to prevent the shape distortion and control the surface stiffness. Various experimental data demonstrate that our algorithm is intuitive, efficient, and effective in deforming large meshes. Copyright © 2014 John Wiley & Sons, Ltd.
Chronic Hepatitis C Virus Infection in Haemophilic Patients: Clinical Significance of Viral Genotype

Summary We have undertaken a comprehensive study of hepatitis C virus (HCV) genotype and its clinical significance in haemophilic patients. 189 HCV RNA positive patients were typed, using the Simmonds classification scheme, by restriction fragment length polymorphism (RFLP) in an amplified segment of the 5 non-coding region of the HCV genome. Type 1 was found in 121 (64.0%), type 2 in 23 (12.2%), type 3 in 36 (19.0%), type 4 in 3 (1.6%), type 5 in 2 (1.1%) and mixed infection in 3 (1.6%). There were no type 6 infections and one patient (0.5%) could not be typed. Genotype was not associated with diagnosis, age, or with HIV infection. Type I was associated with higher serum HCV RNA levels, and with a poor response to interferon. Progression to hepatic decompensation has been seen less frequently in those with type 3 compared to type 1 infection (p = 0.07). Three out of eleven patients studied over a longer time course showed a change in genotype, the remainder were persistently infected with HCV type 1. In conclusion, HCV genotype has clinical relevance in the management of haemophilic patients. Those with type 1 are probably more likely to develop serious liver disease and since they respond poorly to inter- feron-α, should be considered for new treatment strategies aimed at sustained clearance of HCV RNA.
Strong Inhibition of Beta‐Amyloid Peptide Aggregation Realized by Two‐Steps Evolved Peptides

Several decades of cumulated research evidence have proven that aggregation of beta‐amyloid 42 (Aβ42) is the main cause of neuronal death in the brains of patients with Alzheimer's disease. Therefore, inhibition of Aβ42 aggregation holds great promise for the prevention and treatment of Alzheimer's disease. To this end, we used a systematic in vitro evolution including a paired peptide library method. We identified two peptides with high binding affinity (with Kd in the nm range) for Aβ42. Functionally, these peptides strongly inhibited the aggregation of Aβ42 as shown by the thioflavin T assay and atomic force microscopy. Moreover, these peptides rescued PC12 cells from the cytotoxic effect of aggregated Aβ42 in vitro. Our results suggest that these novel peptides may be potential therapeutic seeds for the treatment of Alzheimer's disease.
Alteration of Cell–Cell and Cell–Matrix Adhesion in Urothelial Cells: An Oncogenic Mechanism for Mutant FGFR3

Activating mutations of FGFR3 are a common and early event in bladder cancer. Ectopic expression of mutant FGFR3 in normal urothelial cells has both pro-proliferative and antiapoptotic effects at confluence, suggesting that mutant cells are insensitive to cell–cell contact inhibition. Herein, detailed analysis revealed that these cells have reduced cell–cell adhesion, with large intercellular spaces observable at confluence, and diminished cell–substrate adhesion to collagen IV, collagen I, and fibronectin. These phenotypic alterations are accompanied by changes in the expression of genes involved in cell adhesion and extracellular matrix remodeling. Silencing of endogenous mutant FGFR3 in bladder cancer cells induced converse changes in transcript levels of CDH16, PLAU, MMP10, EPCAM, TNC, and HAS3, confirming them as downstream gene targets of mutant FGFR3. Overexpression of EPCAM, HAS3, and MMP10 transcripts was found in a large fraction of primary bladder tumors analyzed, supporting their key role in bladder tumorigenesis in vivo. However, no correlation was found between their protein and/or mRNA expression and FGFR3 mutation status in tumor specimens, indicating that these genes may be targeted by several converging oncogenic pathways. Overall, these results indicate that mutant FGFR3 favors the development and progression of premalignant bladder lesions by altering key genes regulating the cell–cell and cell–matrix adhesive properties of urothelial cells. Implications: The ability of mutant FGFR3 to drive transcriptional expression profiles involved in tumor cell adhesion suggests a mechanism for expansion of premalignant urothelial lesions. Mol Cancer Res; 13(1); 138–48. ©2014 AACR.
The Genus of Embedded Surfaces in the Projective Plane

1. Statement of the result The genus of a smooth algebraic curve of degree d in CP is given by the formula g = (d − 1)(d − 2)/2. A conjecture sometimes attributed to Thom states that the genus of the algebraic curve is a lower bound for the genus of any smooth 2-manifold representing the same homology class. The conjecture has previously been proved for d ≤ 4 and for d = 6, and less sharp lower bounds for the genus are known for all degrees [5,6,7,10,14]. In this note we confirm the conjecture. Theorem 1. Let Σ be an oriented 2-manifold smoothly embedded in CP so as to represent the same homology class as an algebraic curve of degree d. Then the genus g of Σ satisfies g ≥ (d − 1)(d − 2)/2.
Molecular Epidemiology of Feline and Human Bartonella henselae Isolates

Multiple locus variable number tandem repeat analysis was performed on 178 Bartonella henselae isolates from 9 countries; 99 profiles were distributed into 2 groups. Human isolates/strains were placed into the second group. Genotype I and II isolates shared no common profile. All genotype I isolates clustered within group B. The evolutive implications are discussed.
CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.
The Impact of Privatization on the Economic Returns to R & D Activities . Empirical Evidence from a Sample of European Firms

Privatization and liberalization processes have been two of the defining economic changes worldwide over the last two decades. In this paper we address the issue of evaluating if and how privatization impacts on the economic returns to firms' innovative activities. We use data from a sample of 40 firms, including 20 privatized firms that were matched at the country and industry level with 20 publicly held firms. The first group refers to a set of companies which were privatized through public share offering in different countries of Western Europe over the period 1982-1997. Using the market value of firms to measure the private returns to innovation (Hall, 1999), we show that stock markets under-evaluate R&D expenditures of newly privatized companies in comparison to our benchmark of industry-matched private companies, coherently with our expectations of path dependenc ies negatively affecting the economic performance of R&D activities after privatization. Furthermore, we find that the gap tends to disappear over time, as privatized companies progressively gain higher returns from their investments in research.
Sleep spindles in midday naps enhance learning in preschool children

Significance Lacking scientific understanding of the function of naps in early childhood, policy makers may curtail preschool classroom nap opportunities due to increasing curriculum demands. Here we show evidence that classroom naps support learning in preschool children by enhancing memories acquired earlier in the day as compared with equivalent intervals spent awake. Despite the fact that midday naps are characteristic of early childhood, very little is understood about the structure and function of these sleep bouts. Given that sleep benefits memory in young adults, it is possible that naps serve a similar function for young children. However, children transition from biphasic to monophasic sleep patterns in early childhood, eliminating the nap from their daily sleep schedule. As such, naps may contain mostly light sleep stages and serve little function for learning and memory during this transitional age. Lacking scientific understanding of the function of naps in early childhood, policy makers may eliminate preschool classroom nap opportunities due to increasing curriculum demands. Here we show evidence that classroom naps support learning in preschool children by enhancing memories acquired earlier in the day compared with equivalent intervals spent awake. This nap benefit is greatest for children who nap habitually, regardless of age. Performance losses when nap-deprived are not recovered during subsequent overnight sleep. Physiological recordings of naps support a role of sleep spindles in memory performance. These results suggest that distributed sleep is critical in early learning; when short-term memory stores are limited, memory consolidation must take place frequently.