Vitamin e analytical procedure for cottonseed and its products

Conclusions A procedure for the analysis of cottonseed and its products for Vitamin E has been developed and improved. The present procedure generally gives good checks on duplicate analyses. The Vitamin E content of whole cottonseed is somewhat more a function of variety than of locality. The 1952 crop of cottonseed contained more Vitamin E than the 1951 crop. The two crops averaged 84 g. per ton and 68.5 g. per ton, respectively. Most recent results show that there is no loss of Vitamin E in the storage of cottonseed or during the processing of the seed for its oil and other products. The hexane-soluble portion of a methanol extract of rolled or cooked cottonseed meats contains Vitamin E in concentrations that have exceeded the values reported for wheat germ oil, the present commercial source. A sample of commercial solvent extracted cottonseed meal was found to contain considerably less Vitamin E than hydraulic- or screw-pressed meals. The Vitamin E research described in this writing was conducted as a cooperative project of the Texas Engineering Experiment Station and the Cotton Research Committee of Texas.     

MET𝔸P: revisiting Privacy-Preserving Data Publishing using secure devices

The goal of Privacy-Preserving Data Publishing (PPDP) is to generate a sanitized (i.e. harmless) view of sensitive personal data (e.g. a health survey), to be released to some agencies or simply the public. However, traditional PPDP practices all make the assumption that the process is run on a trusted central server. In this article, we argue that the trust assumption on the central server is far too strong. We propose Met _??P, a generic fully distributed protocol, to execute various forms of PPDP algorithms on an asymmetric architecture composed of low power secure devices and a powerful but untrusted infrastructure. We show that this protocol is both correct and secure against honest-but-curious or malicious adversaries. Finally, we provide an experimental validation showing that this protocol can support PPDP processes scaling up to nation-wide surveys.     

A conformance test suite for TTCN-3 tools

With more than 10 years of maturing through industrial use and standardization, the Testing and Test Control Notation (TTCN-3) has become a widely used technology that many businesses depend upon for ensuring their product quality. With the rising number of supporters and tools, the demand for a means to assess the standards compliance of TTCN-3 tools has increased. In this article, we describe the motivation, approach, methodology, and results of the still ongoing project to develop a standardized conformance test suite for TTCN-3 tools. We discuss the challenges involved in creating such a test suite, the way to deal with imposed resource limitations of the project, and where we think the effort is heading.     

On detecting co-resident cloud instances using network flow watermarking techniques

Virtualization is the cornerstone of the developing third-party compute industry, allowing cloud providers to instantiate multiple virtual machines (VMs) on a single set of physical resources. Customers utilize cloud resources alongside unknown and untrusted parties, creating the co-resident threat—unless perfect isolation is provided by the virtual hypervisor, there exists the possibility for unauthorized access to sensitive customer information through the exploitation of covert side channels. This paper presents co-resident watermarking, a traffic analysis attack that allows a malicious co-resident VM to inject a watermark signature into the network flow of a target instance. This watermark can be used to exfiltrate and broadcast co-residency data from the physical machine, compromising isolation without reliance on internal side channels. As a result, our approach is difficult to defend against without costly underutilization of the physical machine. We evaluate co-resident watermarkingunder a large variety of conditions, system loads and hardware configurations, from a local laboratory environment to production cloud environments (Futuregrid and the University of Oregon’s ACISS). We demonstrate the ability to initiate a covert channel of 4 bits per second, and we can confirm co-residency with a target VM instance in $<$ 10 s. We also show that passive load measurement of the target and subsequent behavior profiling is possible with this attack. We go on to consider the detectability of co-resident watermarking, extending our scheme to create a subtler watermarking attack by imitating legitimate cloud customer behavior. Our investigation demonstrates the need for the careful design of hardware to be used in the cloud.     

Vapor-liquid equilibria in the argon-methane system

Vapor-liquid equilibrium compositions have been measured for the argon-methane system at 115.2°, 123.4° and 137.1°K, by means of a forced-recirculation apparatus. A modified Redlich-Kwong equation of state with the incorporation of a binary interaction constant has been successfully employed to represent the data. Liquid activity coefficients have been evaluated and correlated.     

The chemical feeding ecology ofNeodiprion dubiosus schedl,N. rugifrons midd., andN. lecontei (Fitch) on jack pine (Pinus banksiana lamb.)

Two monophagous sawflies,Neodiprion dubiosus andN. rugifrons, actively avoid feeding on the current season's needles of jack pine,Pinus banksiana, while the polyphagousN. lecontei feeds indiscriminately on foliage of all age classes. Bioassay studies with needle extracts indicate thatN. dubiosus andN. rugifrons larval feeding preference is governed by a group of tricyclic diterpene resin acids. Resin acids commonly occur in needles of all ages; however, levopimaric, palustric, dehydroabietic, and neoabietic acids were at higher concentrations in the new needles.N. dubiosus was significantly deterred from feeding on 1-year-old foliage when treated with the pure resin acids, palustric and levopimaric, at 0.5 and 1.0 mg/ml MeOH.N. rugifrons larvae were deterred from feeding by pure dehydroabietic, neoabietic, and palustric acids at 1.0 mg/ml MeOH.     

An embedding approach for the design of state‐feedback tracking controllers for references with jumps

We study the problem of designing state‐feedback controllers to track time‐varying state trajectories that may exhibit jumps. Both plants and controllers considered are modeled as hybrid dynamical systems, which are systems with both continuous and discrete dynamics, given in terms of a flow set, a flow map, a jump set, and a jump map. Using recently developed tools for the study of stability in hybrid systems, we recast the tracking problem as the task of asymptotically stabilizing a set, the tracking set, and derive conditions for the design of state‐feedback tracking controllers with the property that the jump times of the plant coincide with those of the given reference trajectories. The resulting tracking controllers guarantee that solutions of the plant starting close to the reference trajectory stay close to it and that the difference between each solution of the controlled plant and the reference trajectory converges to zero asymptotically. Constructive conditions for tracking control design in terms of LMIs are proposed for a class of hybrid systems with linear maps and input‐triggered jumps. The results are illustrated by various examples. Copyright © 2013 John Wiley & Sons, Ltd.     

Breaking Bad in Cyberspace: Understanding why and how Black Hat Hackers Manage their Nerves to Commit their Virtual Crimes

Information Systems Frontiers - What is happening in hacker’s minds when they are committing criminal activities? How black hat hackers manage nerves, which is about managing fear and...     

Popular News Are Relevant News! How Investor Attention Affects Algorithmic Decision-Making and Decision Support in Financial Markets

Algorithmic decision-making plays an important role in financial markets. Current tools in trading focus on popular companies which are discussed in thousands of news items. However, it remains unclear whether methodologies from the field of data analytics relying on large samples can also be applied to small datasets of less popular companies or whether these methodologies lead to the discovery of meaningless patterns resulting in economic losses. We analyze whether the impact of media sentiment on financial markets is influenced by two levels of investor attention and whether this impacts algorithmic decision-making. We find that the influence differs substantially between news and companies with high and low investor attention. We apply a trading simulation to outline the practical consequences of these interrelations for decision support systems. Our results are of high importance for financial market participants, especially for algorithmic traders that consider sentiment for investment decision support.