An Independent-Connection Model for Traffic Matrices

A common assumption made in traffic matrix (TM) modeling and estimation is independence of a packet's network ingress and egress. We argue that in real IP networks, this assumption should not and does not hold. The fact that most traffic consists of two-way exchanges of packets means that traffic streams flowing in opposite directions at any point in the network are not independent. In this paper we propose a model for traffic matrices based on independence of connections rather than packets. We argue that the independent connection (IC) model is more intuitive, and has a more direct connection to underlying network phenomena than the gravity model. To validate the IC model, we show that it fits real data better than the gravity model and that it works well as a prior in the TM estimation problem. We study the model's parameters empirically and identify useful stability properties. This justifies the use of the simpler versions of the model for TM applications. To illustrate the utility of the model we focus on two such applications: synthetic TM generation and TM estimation. To the best of our knowledge this is the first traffic matrix model that incorporates properties of bidirectional traffic.

Sugar matrices in stabilization of bioactives by dehydration

Development of functional foods with bioactive components requires component stability in foods and ingredients. Stabilization of sensitive bioactive components can be achieved by entrapment or encapsulation of these components in solid food matrices. Lactose or trehalose was used as the structure-forming material for the entrapment of hydrophilic ascorbic acid and thiamine hydrochloride or the encapsulation of oil particles containing hydrophobic α-tocopherol. In the delivery of hydrophobic components, milk protein isolate, soy protein isolate, or whey protein isolate were used as emulsifiers and, in some cases, applied in excess amount to form matrices together with sugars. Dehydrated amorphous structures with bioactives were produced by freezing and freeze-drying. Experimental results indicated that: (i) lactose and trehalose showed similar water sorption and glass transition but very different crystallization behavior as pure sugars; (ii) the glass transition of sugar-based systems was slightly affected by the presence of other components in anhydrous systems but followed closely that of sugar after water plasticization; (iii) sugar crystallization in mixture systems was composition-dependent; (iv) the stability of bioactives was better retained in the amorphous matrices, although small losses of stability were observed for hydrophilic components above glass transition and for hydrophobic components as a function of water activity; (v) sugar crystallization caused significant loss of hydrophilic bioactives as a result of the exclusion from the continuous crystalline phase; (vi) loss of hydrophobic bioactives upon sugar crystallization was a result of dramatic change of emulsion properties and the exclusion of oil particles from the protecting structure; (vii) the double layers at the hydrophilic-hydrophobic interfaces improved the stability of hydrophobic bioactives in dehydrated systems. The present study provides information on the physical and chemical stability of sugar-based dehydrated delivery systems, which could be helpful in designing foods and ingredients containing bioactive components with improved storage stability.

Boosting high-intensity focused ultrasound-induced anti-tumor immunity using a sparse-scan strategy that can more effectively promote dendritic cell maturation.

BACKGROUND: The conventional treatment protocol in high-intensity focused ultrasound (HIFU) therapy utilizes a dense-scan strategy to produce closely packed thermal lesions aiming at eradicating as much tumor mass as possible. However, this strategy is not most effective in terms of inducing a systemic anti-tumor immunity so that it cannot provide efficient micro-metastatic control and long-term tumor resistance. We have previously provided evidence that HIFU may enhance systemic anti-tumor immunity by in situ activation of dendritic cells (DCs) inside HIFU-treated tumor tissue. The present study was conducted to test the feasibility of a sparse-scan strategy to boost HIFU-induced anti-tumor immune response by more effectively promoting DC maturation. METHODS: An experimental HIFU system was set up to perform tumor ablation experiments in subcutaneous implanted MC-38 and B16 tumor with dense- or sparse-scan strategy to produce closely-packed or separated thermal lesions. DCs infiltration into HIFU-treated tumor tissues was detected by immunohistochemistry and flow cytometry. DCs maturation was evaluated by IL-12/IL-10 production and CD80/CD86 expression after co-culture with tumor cells treated with different HIFU. HIFU-induced anti-tumor immune response was evaluated by detecting growth-retarding effects on distant re-challenged tumor and tumor-specific IFN-gamma-secreting cells in HIFU-treated mice. RESULTS: HIFU exposure raised temperature up to 80 degrees centigrade at beam focus within 4 s in experimental tumors and led to formation of a well-defined thermal lesion. The infiltrated DCs were recruited to the periphery of lesion, where the peak temperature was only 55 degrees centigrade during HIFU exposure. Tumor cells heated to 55 degrees centigrade in 4-s HIFU exposure were more effective to stimulate co-cultured DCs to mature. Sparse-scan HIFU, which can reserve 55 degrees-heated tumor cells surrounding the separated lesions, elicited an enhanced anti-tumor immune response than dense-scan HIFU, while their suppressive effects on the treated primary tumor were maintained at the same level. Flow cytometry analysis showed that sparse-scan HIFU was more effective than dense-scan HIFU in enhancing DC infiltration into tumor tissues and promoting their maturation in situ. CONCLUSION: Optimizing scan strategy is a feasible way to boost HIFU-induced anti-tumor immunity by more effectively promoting DC maturation.

Cross-Domain Multitask Learning with Latent Probit Models

Learning multiple tasks across heterogeneous domains is a challenging problem since the feature space may not be the same for different tasks. We assume the data in multiple tasks are generated from a latent common domain via sparse domain transforms and propose a latent probit model (LPM) to jointly learn the domain transforms, and the shared probit classifier in the common domain. To learn meaningful task relatedness and avoid over-fitting in classification, we introduce sparsity in the domain transforms matrices, as well as in the common classifier. We derive theoretical bounds for the estimation error of the classifier in terms of the sparsity of domain transforms. An expectation-maximization algorithm is derived for learning the LPM. The effectiveness of the approach is demonstrated on several real datasets.

Matrices de sentido para las nociones de velocidad y tiempo

Las distancias entre saberes de la vida diaria, los escolares y los eruditos, afincan sus raíces en matrices de sentido de epistemes propias. Tal ocurre para las nociones de velocidad y tiempo de la matemática del cambio. Una didáctica crítica es desafiada a deconstruirlos, desentrañando su presencia en el sentido común del estudiantado y en los saberes escolares de los que debe apropiarse éste, de modo de proporcionar antecedentes para diseñar y validar puentes de diálogo entre estos cuerpos de saberes. Para colaborar en esta línea, se presentan matrices de sentido para las nociones de velocidad y de tiempo obtenidas en investigaciones de la Matemática del Cambio.

Códigos secretos: otra forma de aplicar las matrices en bachillerato (16-18)

Tras una breve introducción para hacer referencia a distintos tipos de códigos secretos, el articulo estudia con detalle, esquemáticamente y mediante ejemplos, los códigos matriciales. Se expone, además, una forma de automatizar dichos códigos en el aula, mediante un programa escrito en dBASE III Plus. La parte final consta de unas preguntas sobre sus posibilidades didácticas.

An application of quasi-Newton methods for the numerical solution of interface problems

Quasi-Newton methods are applied to solve interface problems which arise from domain decomposition methods. These interface problems are usually sparse systems of linear or nonlinear equations. We are interested in applying these methods to systems of linear equations where we are not able or willing to calculate the Jacobian matrices as well as to systems of nonlinear equations resulting from nonlinear elliptic problems in the context of domain decomposition. Suitability for parallel implementation of these algorithms on coarse-grained parallel computers is discussed.

How should sparse marine in situ measurements be compared to a continuous model: an example

This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.

Quadratic Forms on Complex Random Matrices and Multiple-Antenna Systems

This research published in the foremost international journal in information theory and shows interplay between complex random matrix and multiantenna information theory. Dr T. Ratnarajah is leader in this area of research and his work has been contributed in the development of graduate curricula (course reader) in Massachusetts Institute of Technology (MIT), USA, By Professor Alan Edelman. The course name is "The Mathematics and Applications of Random Matrices", see http://web.mit.edu/18.338/www/projects.html

The conjugacy problem for two-by-two matrices over polynomial rings

We give an effective solution of the conjugacy problem for two-by-two matrices over the polynomial ring in one variable over a finite field.

2-D R-matrix propagation: A large scale electron scattering simulation dominated by the multiplication of dynamically changing matrices

We examine the computational aspects of propagating a global R-matrix, R, across sub-regions in a 2-D plane. This problem originates in the large scale simulation of electron collisions with atoms and ions at intermediate energies. The propagation is dominated by matrix multiplications which are complicated because of the dynamic nature of R, which changes the designations of its rows and columns and grows in size as the propagation proceeds. The use of PBLAS to solve this problem on distributed memory HPC machines is the main focus of the paper.