Rank discriminants for predicting phenotypes from RNA expression

Statistical methods for analyzing large-scale biomolecular data are commonplace in computational biology. A notable example is phenotype prediction from gene expression data, for instance, detecting human cancers, differentiating subtypes and predicting clinical outcomes. Still, clinical applications remain scarce. One reason is that the complexity of the decision rules that emerge from standard statistical learning impedes biological understanding, in particular, any mechanistic interpretation. Here we explore decision rules for binary classification utilizing only the ordering of expression among several genes; the basic building blocks are then two-gene expression comparisons. The simplest example, just one comparison, is the TSP classifier, which has appeared in a variety of cancer-related discovery studies. Decision rules based on multiple comparisons can better accommodate class heterogeneity, and thereby increase accuracy, and might provide a link with biological mechanism. We consider a general framework ("rank-in-context") for designing discriminant functions, including a data-driven selection of the number and identity of the genes in the support ("context"). We then specialize to two examples: voting among several pairs and comparing the median expression in two groups of genes. Comprehensive experiments assess accuracy relative to other, more complex, methods, and reinforce earlier observations that simple classifiers are competitive.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS738 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

OPTIMIZATION OF RAILWAY TRANSPORTATION HAZMATS AND REGULAR COMMODITIES

Transportation of dangerous goods has been receiving more attention in the realm of academic and scientific research during the last few decades as countries have been increasingly becoming industrialized throughout the world, thereby making Hazmats an integral part of our life style. However, the number of scholarly articles in this field is not as many as those of other areas in SCM. Considering the low-probability-and-high-consequence (LPHC) essence of transportation of Hazmats, on the one hand, and immense volume of shipments accounting for more than hundred tons in North America and Europe, on the other, we can safely state that the number of scholarly articles and dissertations have not been proportional to the significance of the subject of interest. On this ground, we conducted our research to contribute towards further developing the domain of Hazmats transportation, and sustainable supply chain management (SSCM), in general terms. Transportation of Hazmats, from logistical standpoint, may include all modes of transport via air, marine, road and rail, as well as intermodal transportation systems. Although road shipment is predominant in most of the literature, railway transportation of Hazmats has proven to be a potentially significant means of transporting dangerous goods with respect to both economies of scale and risk of transportation; these factors, have not just given rise to more thoroughly investigation of intermodal transportation of Hazmats using road and rail networks, but has encouraged the competition between rail and road companies which may indeed have some inherent advantages compared to the other medium due to their infrastructural and technological backgrounds. Truck shipment has ostensibly proven to be providing more flexibility; trains, per contra, provide more reliability in terms of transport risk for conveying Hazmats in bulks. In this thesis, in consonance with the aforementioned motivation, we provide an introduction into the hazardous commodities shipment through rail network in the first chapter of the thesis. Providing relevant statistics on the volume of Hazmat goods, number of accidents, rate of incidents, and rate of fatalities and injuries due to the incidents involving Hazmats, will shed light onto the significance of the topic under study. As well, we review the most pertinent articles while putting more emphasis on the state-of-the-art papers, in chapter two. Following the discussion in chapter 3 and looking at the problem from carrier company’s perspective, a mixed integer quadratically constraint problem (MIQCP) is developed which seeks for the minimization of transportation cost under a set of constraints including those associating with Hazmats. Due to the complexity of the problem, the risk function has been piecewise linearized using a set of auxiliary variables, thereby resulting in an MIP problem. Further, considering the interests of both carrier companies and regulatory agencies, which are minimization of cost and risk, respectively, a multiobjective MINLP model is developed, which has been reduced to an MILP through piecewise linearization of the risk term in the objective function. For both single-objective and multiobjective formulations, model variants with bifurcated and nonbifurcated flows have been presented. Then, in chapter 4, we carry out experiments considering two main cases where the first case presents smaller instances of the problem and the second case focuses on a larger instance of the problem. Eventually, in chapter five, we conclude the dissertation with a summary of the overall discussion as well as presenting some comments on avenues of future work

The minimum rank of universal adjacency matrices

In this paper we introduce a new parameter for a graph called the {\it minimum universal rank}. This parameter is similar to the minimum rank of a graph. For a graph $G$ the minimum universal rank of $G$ is the minimum rank over all matrices of the form $$U(\alpha, \beta, \gamma, \delta) = \alpha A + \beta I + \gamma J + \delta D$$ where $A$ is the adjacency matrix of $G$, $J$ is the all ones matrix and $D$ is the matrix with the degrees of the vertices in the main diagonal, and $\alpha\neq 0, \beta, \gamma, \delta$ are scalars. Bounds for general graphs based on known graph parameters are given, as is a formula for the minimum universal rank for regular graphs based on the multiplicity of the eigenvalues of $A$. The exact value of the minimum universal rank of some families of graphs are determined, including complete graphs, complete bipartite graph, paths and cycles. Bounds on the minimum universal rank of a graph obtained by deleting a single vertex are established. It is shown that the minimum universal rank is not monotone on induced subgraphs, but bounds based on certain induced subgraphs, including bounds on the union of two graphs, are given. Finally we characterize all graphs with minimum universal rank equal to 0 and to 1

Analysis and Extraction of Tempo-Spatial Events in an Efficient Archival CDN with Emphasis on Telegram

This paper presents an efficient archival framework for exploring and tracking cyberspace large-scale data called Tempo-Spatial Content Delivery Network (TS-CDN). Social media data streams are renewing in time and spatial dimensions. Various types of websites and social networks (i.e., channels, groups, pages, etc.) are considered spatial in cyberspace. Accurate analysis entails encompassing the bulk of data. In TS-CDN by applying the hash function on big data an efficient content delivery network is created. Using hash function rebuffs data redundancy and leads to conclude unique data archive in large-scale. This framework based on entered query allows for apparent monitoring and exploring data in tempo-spatial dimension based on TF-IDF score. Also by conformance from i18n standard, the Unicode problem has been dissolved. For evaluation of TS-CDN framework, a dataset from Telegram news channels from March 23, 2020 (1399-01-01), to September 21, 2020 (1399-06-31) on topics including Coronavirus (COVID-19), vaccine, school reopening, flood, earthquake, justice shares, petroleum, and quarantine exploited. By applying hash on Telegram dataset in the mentioned time interval, a significant reduction in media files such as 39.8% for videos (from 79.5 GB to 47.8 GB), and 10% for images (from 4 GB to 3.6 GB) occurred. TS-CDN infrastructure in a web-based approach has been presented as a service-oriented system. Experiments conducted on enormous time series data, including different spatial dimensions (i.e., Khabare Fouri, Khabarhaye Fouri, Akhbare Rouze Iran, and Akhbare Rasmi Telegram news channels), demonstrate the efficiency and applicability of the implemented TS-CDN framework

Development and Validation of a Mechanistic Vapor-Compression Cycle Model

Detailed models are crucial tools for engineers in designing and optimizing systems. In particular, mechanistic modeling of vapor compression systems for accurate performance predictions at both full- and part-load conditions have been improved significantly in the past decades. Yet, fully deterministic models present still challenges in estimating charge inventory in order to optimize the performance. In this work, a generalized framework for simulating vapor compression cycles (VCC) has been develvoped with emphasis on a charge-sensitive model. In order to illustrate the capabilities of the tool, a direct–expansion (DX) cycle has been considered. In the cycle model, the compressor was mapped by employing the ANSI/AHRI 540 10-coefficient correlation, the evaporator and the condenser were constructed based on the ACHP models (Bell, 2010). Furthermore, a TXV model was implemented based on Li and Braun (2008) formulation. With respect to the charge inventory estimation, the two-point regression model proposed by Shen et al. (2009) was used to account for inaccurate estimation of refrigerant volumes, ambiguous flow patterns for two-phase flow, and amount of refrigerant dissolved in the oil. The solution scheme required manufacturer input data for each component as well as the amount of refrigerant charge. Hence, the degree of superheating at the evaporator outlet, the subcooling at the condenser outlet and the perfromance parameters of the VCC system can be predicted. The model was validated with available experimental and numerical data available in literature. The simulation results demonstrated that the proposed model is more accurate and more generic than other methods presented in the literature