Mining data from intensive care patients

In this paper we describe the application of data mining methods for predicting the evolution of patients in an intensive care unit. We discuss the importance of such methods for health care and other application domains of engineering. We argue that this problem is an important but challenging one for the current state of the art data mining methods and explain what improvements on current methods would be useful. We present a promising study on a preliminary data set that demonstrates some of the possibilities in this area.     

增强战斗力的有效途径:虚拟战争

在军事领域中,随着军事斗争的复杂性的不断增加,人们一直在寻求一种能在实验条件下“预先实践战争”的方法,来深入地研究未来战争的规律。现代科学技术的飞速发展,使得人们这一愿望得以实现。在虚拟现实技术基础上发展起来的“虚拟战争”方法,正是研究增强军队战斗力的有效途径。本文对这一课题作了概要的阐述。     

Generalized ordering-search for learning directed probabilistic logical models

Recently, there has been an increasing interest in directed probabilistic logical models and a variety of formalisms for describing such models has been proposed. Although many authors provide high-level arguments to show that in principle models in their formalism can be learned from data, most of the proposed learning algorithms have not yet been studied in detail. We introduce an algorithm, generalized ordering-search, to learn both structure and conditional probability distributions (CPDs) of directed probabilistic logical models. The algorithm is based on the ordering-search algorithm for Bayesian networks. We use relational probability trees as a representation for the CPDs. We present experiments on a genetics domain, blocks world domains and the Cora dataset. Editors: Stephen Muggleton, Ramon Otero, Simon Colton.     

Could SGLT2 Inhibitors Improve Exercise Intolerance in Chronic Heart Failure?

Despite the constant improvement of therapeutical options, heart failure (HF) remains associated with high mortality and morbidity. While new developments in guideline-recommended therapies can prolong survival and postpone HF hospitalizations, impaired exercise capacity remains one of the most debilitating symptoms of HF. Exercise intolerance in HF is multifactorial in origin, as the underlying cardiovascular pathology and reactive changes in skeletal muscle composition and metabolism both contribute. Recently, sodium-related glucose transporter 2 (SGLT2) inhibitors were found to improve cardiovascular outcomes significantly. Whilst much effort has been devoted to untangling the mechanisms responsible for these cardiovascular benefits of SGLT2 inhibitors, little is known about the effect of SGLT2 inhibitors on exercise performance in HF. This review provides an overview of the pathophysiological mechanisms that are responsible for exercise intolerance in HF, elaborates on the potential SGLT2-inhibitor-mediated effects on these phenomena, and provides an up-to-date overview of existing studies on the effect of SGLT2 inhibitors on clinical outcome parameters that are relevant to the assessment of exercise capacity. Finally, current gaps in the evidence and potential future perspectives on the effects of SGLT2 inhibitors on exercise intolerance in chronic HF are discussed.     

Effects of testing configurations and cell geometries on the performance of a SOFC: A modeling approach

A two-dimensional electrochemical model including mass and charge transfer has been developed to illustrate the effects of testing configurations and cell geometries on SOFC’s performance. The model is favorably validated by the well agreeable experimental results. It is shown that the separation of anode and cathode overpotential by three-electrode method is essentially impractical for anode-supported SOFCs. It is also found that testing configuration has little effect on cell performance due to the high electrical conductivity in anode. Furthermore, because the effective resistance of electrolyte is lower for asymmetric cells than for symmetric cells, cell performance of a symmetric cell is smaller than that of an asymmetric cell. Discrepancy in cell performance is shown to increase with increasing the thickness of electrolyte or decreasing the cathode radii.     

Optimal attacks on qubit-based Quantum Key Recycling

Quantum Key Recycling (QKR) is a quantum cryptographic primitive that allows one to reuse keys in an unconditionally secure way. By removing the need to repeatedly generate new keys, it improves communication efficiency. ?kori? and de Vries recently proposed a QKR scheme based on 8-state encoding (four bases). It does not require quantum computers for encryption/decryption but only single-qubit operations. We provide a missing ingredient in the security analysis of this scheme in the case of noisy channels: accurate upper bounds on the required amount of privacy amplification. We determine optimal attacks against the message and against the key, for 8-state encoding as well as 4-state and 6-state conjugate coding. We provide results in terms of min-entropy loss as well as accessible (Shannon) information. We show that the Shannon entropy analysis for 8-state encoding reduces to the analysis of quantum key distribution, whereas 4-state and 6-state suffer from additional leaks that make them less effective. From the optimal attacks we compute the required amount of privacy amplification and hence the achievable communication rate (useful information per qubit) of qubit-based QKR. Overall, 8-state encoding yields the highest communication rates.     

Population balances for particulate processes—a volume approach

Population balance models have been used in chemical engineering since the 1960s and have evolved to become the most important tools for design and control of particulate processes. In this paper we show that the intrinsic particle parameter that determines changes in the process and should thus be included in the population balance is the particle volume. The basic population that is modeled should be the mass distribution, or the volume distribution if the density is constant. The population balance thus describes the change of the volume distribution of volume with time. Furthermore, we suggest that the “birth” and “death” terms that are often used to describe discrete events in particulate processes can almost always be replaced by a rate of change term.To design and control existing and future processes, a multi-dimensional population balance model is required. We propose a volume-based model in which the particle properties that are modeled are the volumes of solid, liquid, and air, respectively. In the most general case the model will consist of a properties vector and a distribution tensor. Depending on the complexity of the process, one or more of the properties may be omitted from the model. This is shown in three examples of increasing complexity: comminution, sintering, and granulation.     

Inhibitors against Fungal Cell Wall Remodeling Enzymes

Fungal β‐1,3‐glucan glucanosyltransferases are glucan‐remodeling enzymes that play important roles in cell wall integrity, and are essential for the viability of pathogenic fungi and yeasts. As such, they are considered possible drug targets, although inhibitors of this class of enzymes have not yet been reported. Herein we report a multidisciplinary approach based on a structure‐guided design using a highly conserved transglycosylase from Sacharomyces cerevisiae, that leads to carbohydrate derivatives with high affinity for Aspergillus fumigatus Gel4. We demonstrate by X‐ray crystallography that the compounds bind in the active site of Gas2/Gel4 and interact with the catalytic machinery. The topological analysis of noncovalent interactions demonstrates that the combination of a triazole with positively charged aromatic moieties are important for optimal interactions with Gas2/Gel4 through unusual pyridinium cation–π and face‐to‐face π–π interactions. The lead compound is capable of inhibiting AfGel4 with an IC₅₀ value of 42 μm .     

Renewable linear alpha olefins by selective ethenolysis of decarboxylated unsaturated fatty acids

A two‐step concept for the production of linear alpha olefins from biomass is reported. As a starting material an internally unsaturated C17 alkene was used, which was obtained by the decarboxylation of oleic acid. Here, we report on the ethenolysis of this bio‐based product, using commercially available metathesis catalysts. The desired alpha olefin products, 1‐nonene and 1‐decene, were obtained in excellent yield (96%) and selectivity (96%). Practical applications: The two‐step conversion described in this contribution, starting from unsaturated fatty acids, provides a method for the production of industrially important linear alpha olefins. These valuable products are widely used as starting materials for the production of surfactants and polymers such as linear low density polyethylene (LLDPE).