A maximum-likelihood algorithm for reduction of Langmuir probe data

The reduction of Langmuir triple and quadruple probe data, i.e., the determination of the electron temperature T(e) from the measured voltages and currents, requires the solution of an implicit transcendental equation in T(e), at every point in time. Random errors and noise in the measurements occasionally precludes solution of the equation, resulting in an indeterminate temperature at those times. We present a method for overcoming this problem that uses the method of maximum likelihood. The experimental uncertainties, assumed to be normally distributed, are used in solving the implicit equation in T(e). At every point in time, a likelihood function is calculated, and the temperature which maximizes this function is taken to be the solution T(e). The uncertainty in the resulting measurement is taken to be the width of the likelihood function. Examples of this technique are shown.     

Simulated train driving: fatigue, self-awareness and cognitive disengagement

Fatigue is a serious issue for the rail industry, increasing inefficiency and accident risk. The performance of 20 train drivers in a rail simulator was investigated at low, moderate and high fatigue levels. Psychomotor vigilance (PVT), self-rated performance and subjective alertness were also assessed. Alertness, PVT reaction times, extreme speed violations (>25% above the limit) and penalty brake applications increased with increasing fatigue level. In contrast, fuel use, draft (stretch) forces and braking errors were highest at moderate fatigue levels. Thus, at high fatigue levels, errors involving a failure to act (errors of omission) increased, whereas incorrect responses (errors of commission) decreased. The differential effect of fatigue on error types can be explained through a cognitive disengagement with the virtual train at high fatigue levels. Interaction with the train reduced dramatically, and accident risk increased. Awareness of fatigue-related performance changes was moderate at best. These findings are of operational concern.     

Unconditional lower bounds for learning intersections of halfspaces

We prove new lower bounds for learning intersections of halfspaces, one of the most important concept classes in computational learning theory. Our main result is that any statistical-query algorithm for learning the intersection of $\sqrt{n}$ halfspaces in n dimensions must make $2^{\varOmega (\sqrt{n})}$ queries. This is the first non-trivial lower bound on the statistical query dimension for this concept class (the previous best lower bound was n ^Ω(log?n)). Our lower bound holds even for intersections of low-weight halfspaces. In the latter case, it is nearly tight. We also show that the intersection of two majorities (low-weight halfspaces) cannot be computed by a polynomial threshold function (PTF) with fewer than n ^{Ω(log?n/log?log?n)} monomials. This is the first super-polynomial lower bound on the PTF length of this concept class, and is nearly optimal. For intersections of k=ω(log?n) low-weight halfspaces, we improve our lower bound to $\min\{2^{\varOmega (\sqrt{n})},n^{\varOmega (k/\log k)}\},$ which too is nearly optimal. As a consequence, intersections of even two halfspaces are not computable by polynomial-weight PTFs, the most expressive class of functions known to be efficiently learnable via Jackson’s Harmonic Sieve algorithm. Finally, we report our progress on the weak learnability of intersections of halfspaces under the uniform distribution.     

Screening of serum samples from Wegener's granulomatosis patients using antibody microarrays

Wegener's Granulomatosis (WG) is an idiopathic granulomatosis autoimmune vasculitis that primarily affects small vessels and is associated with glomerulonephritis and pulmonary granulomatous vasculitis. Anti‐neutrophil cytoplasmic auto‐antibodies (cANCA) against proteinase‐3 are used to identify WG, but ANCA titers are not present in some patients with the localized disease. The objective of this study was to develop an antibody array to help identify protein expression patterns in serum from patients with WG as compared to normals. The arrays were tested for limits of detection, background, and cross reactivity using standard proteins. The arrays were hybridized with either normal patient serum (n = 30) or with serum samples from a population of WG patients (n = 26) that were age and sex matched. Data analysis and curve fitting of the standard dilution series calculated r² values and determined a sensitivity of <50 pg/mL for the majority of proteins. A total of 24 proteins were assessed. Several statistically significant increases (p<0.05) were seen in the expression of: angiotensin converting enzyme‐I, IFN‐γ, IL‐8, s‐ICAM‐1 and s‐VCAM in WG patients as compared to controls. Utilizing the antibody microarray technology has led to the identification of potential biomarkers of vascular injury in the serum of WG patients.     

Balancing systematic and flexible exploration of social networks

Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks. However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. This results in exploration that is largely opportunistic. Our contributions are techniques to help structural analysts understand social networks more effectively. We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures. Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview. For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks     

The confused world of sulfate attack on concrete

External sulfate attack is not completely understood. Part I identifies the issues involved, pointing out disagreements, and distinguishes between the mere occurrence of chemical reactions of sulfates with hydrated cement paste and the damage or deterioration of concrete; only the latter are taken to represent sulfate attack. Furthermore, sulfate attack is defined as deleterious action involving sulfate ions; if the reaction is physical, then, it is physical sulfate attack that takes place. The discussion of the two forms of sulfate attack leads to a recommendation for distinct nomenclature. Sulfate attack on concrete structures in service is not widespread, and the amount of laboratory-based research seems to be disproportionately large. The mechanisms of attack by different sulfates—sodium, calcium, and magnesium—are discussed, including the issue of topochemical and through-solution reactions. The specific aspects of the action of magnesium sulfate are discussed, and the differences between laboratory conditions and field exposure are pointed out.Part II discusses the progress of sulfate attack and its manifestations. This is followed by a discussion of making sulfate-resisting concrete. One of the measures is to use Type V cement, and this topic is extensively discussed. Likewise, the influence of w/c on sulfate resistance is considered. The two parameters are not independent of one another. Moreover, the cation in the sulfate salt has a strong bearing on the efficiency of the Type V cement. Recent interpretations of the Bureau of Reclamation tests, both long term and accelerated, are evaluated, and it appears that they need reworking.Part III reviews the standards and guides for the classification of the severity of exposure of structures to sulfates and points out the lack of calibration of the various classes of exposure. A particular problem is the classification of soils because much depends on the extraction ratio of sulfate in the soil: there is a need for a standardized approach. Taking soil samples is discussed, with particular reference to interpreting highly variable contents of sulfates. The consequences of disturbed drainage of the soil adjacent to foundations and of excessive irrigation, coupled with the use of fertilizer, are described. Whether concrete has undergone sulfate attack can be established by determining the change in the compressive strength since the time of placing the concrete. The rejection of this method and the reliance on determining the tensile strength of concrete because of “layered damage” are erroneous. Scanning electron microscopy (SEM) should not be the primary, and certainly not the first, method of determining whether sulfate attack has occurred. Mathematical modeling will be of help in the future but, at present, cannot provide guidance on the sulfate resistance of concrete in structures.Part IV presents conclusions and an overview of the situation, with consideration of future improvements. Appendix A contains the classification of exposure to sulfate given by various codes and guides.     

Light on! Real world evaluation of a P300-based brain-computer interface (BCI) for environment control in a smart home

Brain-computer interface (BCI) systems aim to enable interaction with other people and the environment without muscular activation by the exploitation of changes in brain signals due to the execution of cognitive tasks. In this context, the visual P300 potential appears suited to control smart homes through BCI spellers. The aim of this work is to evaluate whether the widely used character-speller is more sustainable than an icon-based one, designed to operate smart home environment or to communicate moods and needs. Nine subjects with neurodegenerative diseases and no BCI experience used both speller types in a real smart home environment. User experience during BCI tasks was evaluated recording concurrent physiological signals. Usability was assessed for each speller type immediately after use. Classification accuracy was lower for the icon-speller, which was also more attention demanding. However, in subjective evaluations, the effect of a real feedback partially counterbalanced the difficulty in BCI use. PRACTITIONER SUMMARY: Since inclusive BCIs require to consider interface sustainability, we evaluated different ergonomic aspects of the interaction of disabled users with a character-speller (goal: word spelling) and an icon-speller (goal: operating a real smart home). We found the first one as more sustainable in terms of accuracy and cognitive effort.     

Decentralized fault detection and diagnosis via sparse PCA based decomposition and Maximum Entropy decision fusion

This paper proposes an approach for decentralized fault detection and diagnosis in process monitoring sensor networks. The sensor network is decomposed into multiple, potentially overlapping, blocks using the Sparse Principal Component Analysis algorithm. Local predictions are generated at each block using Support Vector Machine classifiers. The local predictions are then fused via a Maximum Entropy algorithm. Empirical studies on the benchmark Tennessee Eastman Process data demonstrated that the proposed decentralized approach achieves accuracy comparable to that of the fully centralized approach, while offering benefits in terms of fault tolerance, reusability, and scalability.     

Instrumental Learning Within the Rat Spinal Cord: Localization of the Essential Neural Circuit.

Following spinal transection of the upper thoracic spinal cord, male Sprague-Dawley rats given legshock whenever a hindlimb is extended learn to maintain the leg in a flexed position. The region of the cord that mediates this instrumental learning was isolated using neuroanatomical tracing, localized infusion of lidocaine, and surgical transections. DiI and Fluoro-Gold microinjection at the site of shock application labeled motor neuron bodies of lamina IX in the lower lumbar region. Local application of the Na++ channel blocker lidocaine disrupted learning when it was applied over a region extending from the lower lumbar (L3) to upper sacral (S2) cord. The drug had no effect rostral or caudal to this region. Surgical transections as low as L4 had no effect on learning. Learning also survived a dual transection at L4 and S3, but not L4 and S2. The results suggest that the essential neural circuit lies between L4 and S3. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On the cultural guises of cognitive dissonance: The case of Easterners and Westerners.

Cognitive dissonance and effects of self-affirmation on dissonance arousal were examined cross-culturally. In Studies 1 and 2, European Canadians justified their choices more when they made them for themselves, whereas Asian Canadians (Study 1) or Japanese (Study 2) justified their choices more when they made them for a friend. In Study 3, an interdependent self-affirmation reduced dissonance for Asian Canadians but not for European Canadians. In Study 4, when Asian Canadians made choices for a friend, an independent self-affirmation reduced dissonance for bicultural Asian Canadians but not for monocultural Asian Canadians. These studies demonstrate that both Easterners and Westerners can experience dissonance, but culture shapes the situations in which dissonance is aroused and reduced. Implications of these cultural differences for theories of cognitive dissonance and self-affirmation are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)