A note on octonionic support vector regression

This note presents an analysis of the octonionic form of the division algebraic support vector regressor (SVR) first introduced by Shilton A detailed derivation of the dual form is given, and three conditions under which it is analogous to the quaternionic case are exhibited. It is shown that, in the general case of an octonionic-valued feature map, the usual "kernel trick" breaks down. The cause of this (and its interpretation) is discussed in some detail, along with potential ways of extending kernel methods to take advantage of the distinct features present in the general case. Finally, the octonionic SVR is applied to an example gait analysis problem, and its performance is compared to that of the least squares SVR, the Clifford SVR, and the multidimensional SVR.     

Leveraging 802.11n frame aggregation to enhance QoS and power consumption in Wi-Fi networks

The Wi-Fi technology, driven by its tremendous success, is expanding into a wide variety of devices and applications. However, many of these new devices, like handheld devices, pose new challenges in terms of QoS and energy efficiency. In order to address these challenges, in this paper we study how the novel MAC aggregation mechanisms developed in the 802.11n standard can be used to enhance the current 802.11 QoS and power saving protocols. Our contribution is twofold. First, we present a simulation study that illustrates the interactions between 802.11n and the current 802.11 QoS and power saving protocols. This study reveals that the 802.11n MAC aggregation mechanisms perform better when combined with the power save mode included in the original 802.11 standard than with the 802.11e U-APSD protocol. Second, we design CA-DFA, an algorithm that, using only information available at layer two, adapts the amount of 802.11n aggregation used by a Wi-Fi station according to the level of congestion in the network. A detailed performance evaluation demonstrates the benefits of CA-DFA in terms of QoS, energy efficiency and network capacity with respect to state of the art alternatives.     

Design optimization of supersonic jet pumps using high fidelity flow analysis

Supersonic jet pumps are simple devices with no moving parts, where a high velocity (primary) flow is used to pump a second fluid. In this paper, Computational Fluid Dynamics (CFD) is combined with an optimization framework in order to develop a tool for the rapid generation of jet pump designs. A key feature of the problem formulation is the transformation of the jet pump design parameters in terms of geometric ratios. This approach dramatically reduces the number of unrealistic designs covered by the Design of Experiments. Optimal Latin Hypercubes for surrogate model building and model validation points are constructed using a permutation genetic algorithm and design points are evaluated using CFD. Surrogate models of primary and entrained flow rates are built using a Moving Least Squares approach. A series of optimizations for various pump sizes are performed using a genetic algorithm and Sequential Quadratic Programming, with responses calculated from the surrogates. This approach results in a set of optimized designs, from which pumps for a wide range of flow rates can be interpolated.     

Probability densities for conditional statistics in the cubic sensor problem

This paper applies the techniques of Malliavin’s stochastic calculus of variations to Zakai’s equation for the one-dimensional cubic sensor problem in order to study the existence of densities of conditional statistics. Let {X _t} be a Brownian motion observed by a cubic sensor corrupted by white noise, and let denote the unnormalized conditional estimate of φ(X _i ). If φ₁,...,φ _n are linearly independent, and if , it is shown that the probability distribution of admits a density with respect to Lebesgue measure for anyn. This implies that, at any fixed time, the unnormalized conditional density cannot be characterized by a finite set of sufficient statistics. Research supported in part by NSF Grant No. MCS-8301880 and by the Institute for Mathematics and It Applications, Minneapolis, Minnesota.     

A parallel Monte Carlo search algorithm for the conformational analysis of polypeptides

In recent years several approaches have been proposed to overcome the multiple-minima problem associated with nonlinear optimization techniques used in the analysis of molecular conformations. One such technique based on a parallel Monte Carlo search algorithm is analyzed. Experiments on the Intel iPSC/2 confirm that the attainable parallelism is limited by the underlying acceptance rate in the Monte Carlo search. It is proposed that optimal performance can be achieved in combination with vector processing. Tests on both the IBM 3090 and Intel iPSC/2-VX indicate that vector performance is related to molecule size and vector pipeline latency.     

A Universal Method of Scientific Inquiry

A paradigm of scientific discovery is defined within a first-order logical framework. Within this paradigm, the concept of successful scientific inquiry is formalized and investigated. Among other results, it is shown that a simple method of scientific inquiry is universal in the sense that it leads to success on every problem for which success is in principle possible.     

Multi-Omics Revealed Molecular Mechanisms Underlying Guard Cell Systemic Acquired Resistance

Systemic Acquired Resistance (SAR) improves immunity of plant systemic tissue after local exposure to a pathogen. Guard cells that form stomatal pores on leaf surfaces recognize bacterial pathogens via pattern recognition receptors, such as Flagellin Sensitive 2 (FLS2). However, how SAR affects stomatal immunity is not known. In this study, we aim to reveal molecular mechanisms underlying the guard cell response to SAR using multi-omics of proteins, metabolites and lipids. Arabidopsis plants previously exposed to pathogenic bacteria Pseudomonas syringae pv. tomato DC3000 (Pst) exhibit an altered stomatal response compared to control plants when they are later exposed to the bacteria. Reduced stomatal apertures of SAR primed plants lead to decreased number of bacteria in leaves. Multi-omics has revealed molecular components of SAR response specific to guard cells functions, including potential roles of reactive oxygen species (ROS) and fatty acid signaling. Our results show an increase in palmitic acid and its derivative in the primed guard cells. Palmitic acid may play a role as an activator of FLS2, which initiates stomatal immune response. Improved understanding of how SAR signals affect stomatal immunity can aid biotechnology and marker-based breeding of crops for enhanced disease resistance.     

Mushroom-Derived Medicine? Preclinical Studies Suggest Potential Benefits of Ergothioneine for Cardiometabolic Health

Medicinal use of mushrooms has been documented since ancient times, and in the modern world, mushrooms have a longstanding history of use in Eastern medicine. Recent interest in plant-based diets in Westernized countries has brought increasing attention to the use of mushrooms and mushroom-derived compounds in the prevention and treatment of chronic diseases. Edible mushrooms are the most abundant food sources of the modified amino acid, ergothioneine. This compound has been shown to accumulate in almost all cells and tissues, but preferentially in those exposed to oxidative stress and injury. The demonstrated cytoprotectant effect of ergothioneine has led many to suggest a potential therapeutic role for this compound in chronic conditions that involve ongoing oxidative stress and inflammation, including cardiovascular and metabolic diseases. However, the in vivo effects of ergothioneine and its underlying therapeutic mechanisms in the whole organism are not as clear. Moreover, there are no well-defined, clinical prevention and intervention trials of ergothioneine in chronic disease. This review highlights the cellular and molecular mechanisms of action of ergothioneine and its potential as a Traditional, Complementary and Alternative Medicine for the promotion of cardiometabolic health and the management of the most common manifestations of cardiometabolic disease.     

Recovery and Recycling Silica Flux in Submerged Arc Welding – Acceptable Properties and Economical Correlation

Silicon - This research aims at optimum utilization of waste recycled submerged arc welding slag along with virgin flux in place of pure virgin flux without compromising the quality of welding and...     

Differential Subcellular Distribution of Cytokinins: How Does Membrane Transport Fit into the Big Picture?

Cytokinins are a class of phytohormones, signalling molecules specific to plants. They act as regulators of diverse physiological processes in complex signalling pathways. It is necessary for plants to continuously regulate cytokinin distribution among different organs, tissues, cells, and compartments. Such regulatory mechanisms include cytokinin biosynthesis, metabolic conversions and degradation, as well as cytokinin membrane transport. In our review, we aim to provide a thorough picture of the latter. We begin by summarizing cytokinin structures and physicochemical properties. Then, we revise the elementary thermodynamic and kinetic aspects of cytokinin membrane transport. Next, we review which membrane-bound carrier proteins and protein families recognize cytokinins as their substrates. Namely, we discuss the families of “equilibrative nucleoside transporters” and “purine permeases”, which translocate diverse purine-related compounds, and proteins AtPUP14, AtABCG14, AtAZG1, and AtAZG2, which are specific to cytokinins. We also address long-distance cytokinin transport. Putting all these pieces together, we finally discuss cytokinin distribution as a net result of these processes, diverse in their physicochemical nature but acting together to promote plant fitness.