Contribution of lubricating oil to particulate matter emissions from light-duty gasoline vehicles in Kansas City

The contribution of lubricating oil to particulate matter (PM) emissions representative of the in-use 2004 light-duty gasoline vehicles fleet is estimated from the Kansas City Light-Duty Vehicle Emissions Study (KCVES). PM emissions are apportioned to lubricating oil and gasoline using aerosol-phase chemical markers measured in PM samples obtained from 99 vehicles tested on the California Unified Driving Cycle. The oil contribution to fleet-weighted PM emission rates is estimated to be 25% of PM emission rates. Oil contributes primarily to the organic fraction of PM, with no detectable contribution to elemental carbon emissions. Vehicles are analyzed according to pre-1991 and 1991-2004 groups due to differences in properties of the fitting species between newer and older vehicles, and to account for the sampling design of the study. Pre-1991 vehicles contribute 13.5% of the KC vehicle population, 70% of oil-derived PM for the entire fleet, and 33% of the fuel-derived PM. The uncertainty of the contributions is calculated from a survey analysis resampling method, with 95% confidence intervals for the oil-derived PM fraction ranging from 13% to 37%. The PM is not completely apportioned to the gasoline and oil due to several contributing factors, including varied chemical composition of PM among vehicles, metal emissions, and PM measurement artifacts. Additional uncertainties include potential sorption of polycyclic aromatic hydrocarbons into the oil, contributions of semivolatile organic compounds from the oil to the PM measurements, and representing the in-use fleet with a limited number of vehicles.     

Conversion of Extracted Oil Cake Fibers into Bioethanol Including DDGS,Canola, Sunflower,Sesame, Soy,and Peanut for Integrated Biodiesel Processing

We have come up with a novel, integrated approach for making biodiesel by in-house producion of ethanol after fermentation of hexane extracted edible oil cake fiber. In addition, we have demonstrated how ethanol could be manufactured from commonly available oil cakes (such as canola, sunflower, sesame, soy, peanut) and dried distiller’s grains with solubles (DDGS). The edible oil cakes and DDGS were hexane extracted, ammonia fiber expansion pretreated, enzymatically hydrolysed and fermented to produce ethanol. From all the oil cakes tested in this work, DDGS and peanut oil cake showed the most promising results giving more than 180 g of glucose/kg of oil cake. These two feedstock’s were hydrolyzed at 15% solids loading and fermented by a native strain of Pichia stipitis. Most sugars were consumed during the first 24 h, with no pronounced inhibition of P. stipitis by the degradation products in the hydrolysate. Xylose consumption was more effective for peanut cake hydrolyzate compared to DDGS.     

Self-esteem stability and depressive symptoms in acute stroke rehabilitation: Methodological and conceptual expansion.

Objectives: Explore the relationship of self-esteem level, self-esteem stability, and other moderating variables with depressive symptoms in acute stroke rehabilitation. Measures: One hundred twenty participants completed measures of state self-esteem, perceived recovery, hospitalization-based hassles, impairment-related distress, and tendency to overgeneralize negative self-connotations of bad events. Self-report of depressive symptoms was collected at admission and on discharge. Four regression analyses explored the relationship of self-esteem level and stability and each of 4 moderating variables (perceived recovery, hassles, impairment-related distress, and overgeneralization) with depressive symptoms at discharge. Results: Analyses indicated significant 3-way interactions in the 4 regression models. In general, individuals with unstable high self-esteem endorsed greater depressive symptoms under conditions of vulnerability (e.g., lower perceived recovery) than did individuals with stable high self-esteem. Under conditions of vulnerability, participants with stable low self-esteem indicated the highest levels of depressive symptoms. Implications: Self-esteem level and stability interact with psychological, environmental, and stroke-specific variables to predict depressive symptoms at discharge from stroke rehabilitation. This suggests the viability of self-esteem stability in exploring depressive symptoms in this setting and the complexity of emotional adjustment early after stroke. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Are working memory deficits in bipolar disorder markers for psychosis?

Working memory deficits have been identified in bipolar disorder, but there is evidence suggesting that these deficits may be markers for psychosis rather than affective disorder. The current study examined this issue by comparing two groups of individuals with bipolar disorder, one with psychotic features and one without psychotic features, with a group of normal controls. Working memory was conceptualized as a multicomponent system that includes auditory and visuospatial short-term stores, executive control processes, and an episodic buffer that allows for communication between short- and long-term memory stores (Baddeley & Logie, 1999). Results indicated that only executive control processes significantly differentiated the psychotic and nonpsychotic bipolar groups, although visuospatial working memory differentiated both bipolar groups from controls. The results support the idea that some aspects of working memory performance are markers for psychosis, while others may be more general markers for bipolar disorders. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Group psychotherapy focusing on self-concept change following acquired brain injury: A pilot investigation.

Objective: The current study explored the effectiveness of a group therapy intervention that was focused specifically on self-concept changes following acquired brain injury (ABI). Method: Eighteen individuals in the postacute phase of recovery underwent a 6-week group therapy intervention and were administered a self-concept measure before and after the intervention. Results: Group members showed a significant increase (improvement) in self-concept ratings at the end of the group intervention. Conclusions: Although the results of this study suggest that this intervention may be helpful in improving self-concept following ABI, further exploration is clearly warranted. Future research is needed to investigate the impact of self-concept on emotional adjustment, participation in rehabilitation activities, and functional outcome. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Monitoring of ethylene by a pulsed quantum cascade laser

We report on the development and performance of a gas sensor based on a quantum cascade laser operating at a wavelength of approximately 10 microns to measure ethylene (C2H4) concentrations by use of a rotational component of the fundamental nu 7 band. The laser is thermoelectrically cooled and operates in a pulsed mode. The influence of pulse-to-pulse fluctuations is minimized by use of a reference beam and a single detector with time discriminating electronics. Gas absorption is recorded in a 100-m optical path-length astigmatic Herriott cell. With a 10-kHz pulse repetition rate and an 80-s total acquisition time, a noise equivalent sensitivity of 30 parts per billion has been demonstrated. The sensor has been applied to monitor C2H4 in vehicle exhaust as well as in air collected in a high-traffic urban tunnel.     

Geometric Approach to Digital Quantum Information

We present geometric methods for uniformly discretizing the continuous N-qubit Hilbert space H_N. When considered as the vertices of a geometrical figure, the resulting states form the equivalent of a Platonic solid. The discretization technique inherently describes a class of /2 rotations that connect neighboring states in the set, i.e., that leave the geometrical figures invariant. These rotations are shown to generate the Clifford group, a general group of discrete transformations on N qubits. Discretizing H_N allows us to define its digital quantum information content, and we show that this information content grows as N². While we believe the discrete sets are interesting because they allow extra-classical behavior—such as quantum entanglement and quantum parallelism—to be explored while circumventing the continuity of Hilbert space, we also show how they may be a useful tool for problems in traditional quantum computation. We describe in detail the discrete sets for one and two qubits.PACS: 03.67.Lx; 03.67.pp; 03.67.-a; 03.67.Mn.PACS: 03.67.Lx; 03.67.pp; 03.67.-a; 03.67.Mn.     

Membrane current from transmembrane potentials in complex core-conductor models

Core-conductor models, used to integrate the behavior of the longitudinal currents with the distributed voltages of electrically active tissue, have evolved for over a century. A critical step in the use of such models is the computation of membrane current from the set of distributed transmembrane potential values that exist at a given moment, where the potentials are obtained either experimentally or computationally. Over time, interest has developed in a number of substantial extensions of the original model to include such features as nonuniform spatial resistances, loop instead of linear structure, and multiple sites of extracellular stimulation. This paper concisely restates and extends the equations for calculation of transmembrane currents with the systematic inclusion of alternative cases, noting how they reduce to the standard forms. An important issue is how complex the calculation of membrane current has to be. Thus, the paper goes on to show criteria (based on the uniformity of resistance and the presence of stimulation) for deciding when membrane currents can be obtained with a relatively simple calculation with a single equation involving local variables versus with a more complex calculation involving the simultaneous solution of a (possibly large) set of equations.     

A multi-level cache model for run-time optimization of remote visualization

Remote visualization is an enabling technology aiming to resolve the barrier of physical distance. While many researchers have developed innovative algorithms for remote visualization, previous work has focused little on systematically investigating optimal configurations of remote visualization architectures. In this paper, we study caching and prefetching, an important aspect of such architecture design, in order to optimize the fetch time in a remote visualization system. Unlike a processor cache or web cache, caching for remote visualization is unique and complex. Through actual experimentation and numerical simulation, we have discovered ways to systematically evaluate and search for optimal configurations of remote visualization caches under various scenarios, such as different network speeds, sizes of data for user requests, prefetch schemes, cache depletion schemes, etc. We have also designed a practical infrastructure software to adaptively optimize the caching architecture of general remote visualization systems, when a different application is started or the network condition varies. The lower bound of achievable latency discovered with our approach can aid the design of remote visualization algorithms and the selection of suitable network layouts for a remote visualization system.