Simple Toroidal Vertex Algebras and Their Irreducible Modules

In this paper, we continue the study on toroidal vertex algebras initiated in \cite{LTW}, to study concrete toroidal vertex algebras associated to toroidal Lie algebra $L_{r}(\hat{\frak{g}})=\hat{\frak{g}}\otimes L_r$, where $\hat{\frak{g}}$ is an untwisted affine Lie algebra and $L_r=$\mathbb{C}[t_{1}^{\pm 1},\ldots,t_{r}^{\pm 1}]$. We first construct an$(r+1)$-toroidal vertex algebra$V(T,0)$and show that the category of restricted$L_{r}(\hat{\frak{g}})$-modules is canonically isomorphic to that of$V(T,0)$-modules.Let$c$denote the standard central element of$\hat{\frak{g}}$and set$S_c=U(L_r(\mathbb{C}c))$. We furthermore study a distinguished subalgebra of$V(T,0)$, denoted by$V(S_c,0)$. We show that (graded) simple quotient toroidal vertex algebras of$V(S_c,0)$are parametrized by a$\mathbb{Z}^r$-graded ring homomorphism$\psi:S_c\rightarrow L_r$such that Im$\psi$is a$\mathbb{Z}^r$-graded simple$S_c$-module. Denote by$L(\psi,0}$the simple$(r+1)$-toroidal vertex algebra of$V(S_c,0)$associated to$\psi$. We determine for which$\psi$,$L(\psi,0)$is an integrable$L_{r}(\hat{\frak{g}})$-module and we then classify irreducible$L(\psi,0)$-modules for such a$\psi$. For our need, we also obtain various general results.Comment: 50 page

Predictive Resource Allocation in mmWave Systems with Rotation Detection

Millimeter wave (MmWave) has been regarded as a promising technology to support high-capacity communications in 5G era. However, its high-layer performance such as latency and packet drop rate in the long term highly depends on resource allocation because mmWave channel suffers significant fluctuation with rotating users due to mmWave sparse channel property and limited field-of-view (FoV) of antenna arrays. In this paper, downlink transmission scheduling considering rotation of user equipments (UE) and limited antenna FoV in an mmWave system is optimized via a novel approximate Markov decision process (MDP) method. Specifically, we consider the joint downlink UE selection and power allocation in a number of frames where future orientations of rotating UEs can be predicted via embedded motion sensors. The problem is formulated as a finite-horizon MDP with non-stationary state transition probabilities. A novel low-complexity solution framework is proposed via one iteration step over a base policy whose average future cost can be predicted with analytical expressions. It is demonstrated by simulations that compared with existing benchmarks, the proposed scheme can schedule the downlink transmission and suppress the packet drop rate efficiently in non-stationary mmWave links.Comment: 7 pages, 5 figures. Paper accepted for publication in IEEE International Conference on Communications, 202

The EADGENE Microarray Data Analysis Workshop (Open Access publication)

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses

Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies

Hollow mesoporous silica nanoparticles for intracellular delivery of fluorescent dye

In this study, hollow mesoporous silica nanoparticles (HMSNs) were synthesized using the sol-gel/emulsion approach and its potential application in drug delivery was assessed. The HMSNs were characterized, by transmission electron microscopy (TEM), Scanning Electron Microscopy (SEM), nitrogen adsorption/desorption and Brunauer-Emmett-Teller (BET), to have a mesoporous layer on its surface, with an average pore diameter of about 2 nm and a surface area of 880 m2/g. Fluorescein isothiocyanate (FITC) loaded into these HMSNs was used as a model platform to assess its efficacy as a drug delivery tool. Its release kinetic study revealed a sequential release of FITC from the HMSNs for over a period of one week when soaked in inorganic solution, while a burst release kinetic of the dye was observed just within a few hours of soaking in organic solution. These FITC-loaded HMSNs was also found capable to be internalized by live human cervical cancer cells (HeLa), wherein it was quickly released into the cytoplasm within a short period of time after intracellular uptake. We envision that these HMSNs, with large pores and high efficacy to adsorb chemicals such as the fluorescent dye FITC, could serve as a delivery vehicle for controlled release of chemicals administered into live cells, opening potential to a diverse range of applications including drug storage and release as well as metabolic manipulation of cells

Entropy analysis on convective film flow of power-law fluid with nanoparticles along an inclined plate

Entropy generation in a two-dimensional steady laminar thin film convection flow of a non-Newtonian nanofluid (Ostwald-de-Waele-type power-law fluid with embedded nanoparticles) along an inclined plate is examined theoretically. A revised Buongiorno model is adopted for nanoscale effects, which includes the effects of the Brownian motion and thermophoresis. The nanofluid particle fraction on the boundary is passively rather than actively controlled. A convective boundary condition is employed. The local nonsimilarity method is used to solve the dimensionless nonlinear system of governing equations. Validation with earlier published results is included. A decrease in entropy generation is induced due to fluid friction associated with an increasing value of the rheological power-law index. The Brownian motion of nanoparticles enhances thermal convection via the enhanced transport of heat in microconvection surrounding individual nanoparticles. A higher convective parameter implies more intense convective heating of the plate, which increases the temperature gradient. An increase in the thermophoresis parameter decreases the nanoparticle volume fraction near the wall and increases it further from the wall. Entropy generation is also reduced with enhancement of the thermophoresis effect throughout the boundary layer