On repairable earthquake resisting archetypes with a view to resiliency objectives and assisted self‐centering

Performance‐based seismic design, as an alternative to conventional methods of approach, has served engineers and the public rather well during the last two decades. Neither approach guaranties catastrophic collapse prevention nor post‐earthquake realignment and repairs (PERR) due to major seismic events. As a result, most code‐compliant buildings can be regarded as relatively safe but practically disposable. The paper presents a new philosophy that leads to sustainable design of new structures and the upgrading of existing earthquake resisting moment frames. Repairability‐based design (RBD) relies on softening and control rather than strength and resistance to elevate seismic performance to economically viable, physical collapse prevention, damage control, and post‐earthquake realignment and repairs. The new approach was inspired by design led analysis (DLA), performance control (PC), and recent developments in rocking core‐moment frame design. DLA is a displacement based method of analysis with built‐in results. PC is the ability to design a structure in such a way as to expect predetermined modes of response at certain stages of loading, extents of damage, and drift ratios. This paper advocates higher performance objectives than current codes of practice do. Several demonstrative examples have been provided.     

Loss of control, self-blame, and depression: An investigation of spouse caregivers of Alzheimer's disease patients.

Tested several predictions derived from the reformulated learned helplessness (RLH) depression model developed by L. Y. Abramson et al (see record 1979-00305-001) and from recent critiques of that model, in a longitudinal study of spouses caring for a husband or wife with Alzheimer's disease. During initial interviews, 68 caregivers (aged 37–85 yrs) rated the uncontrollability of important upsetting events related to their spouse's disease and were scored on an index of internal–external causal attribution (CATN) for those events. In addition, at both the initial and follow-up interviews (n?=?38) about 10 mo later, caregivers were rated for depression, anxiety, and hostility. Results indicate that the indices of loss of control and CATN were more consistently related to depression than to anxiety or hostility, although hostility was related to CATNs. Correlations of the loss of control and CATN variables with depression remained significant after controlling for a measure of the spouse's objective disability. In hierarchical regression analyses, perceived loss of control and its interaction with CATN significantly predicted follow-up depression after controlling for initial depression. The interaction showed that loss of control combined with an internal attribution predicted higher depression than did either one alone. The importance of including specific uncontrollable events when studying the RLH model is emphasized. (36 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A temporal cross section specification of the demand for gasoline using a random coefficient regression model

This paper uses a random coefficient regression approach to estimate the demand for gasoline by pooling cross-sectional (state level) and time series data. The analysis proceeds by estimating two alternative models, namely a stock adjustment model and a flow adjustment model. The two models are estimated using state level data on gasoline consumption, gasoline price, income and the stock of automobiles. The random coefficient specification of each demand model is estimated assuming heteroskedastic disturbances across states, autocorrelated disturbances over time and variable intercept and slope coefficients across states. The resultant price and income elasticities are compared and inferences concerning the ability of the flow adjustment model to approximate the underlying demand function are made.     

Nonlocal quantum information in bipartite quantum error correction

We show how to convert an arbitrary stabilizer code into a bipartite quantum code. A bipartite quantum code is one that involves two senders and one receiver. The two senders exploit both nonlocal and local quantum resources to encode quantum information with local encoding circuits. They transmit their encoded quantum data to a single receiver who then decodes the transmitted quantum information. The nonlocal resources in a bipartite code are ebits and nonlocal information qubits, and the local resources are ancillas and local information qubits. The technique of bipartite quantum error correction is useful in both the quantum communication scenario described above and in fault-tolerant quantum computation. It has application in fault-tolerant quantum computation because we can prepare nonlocal resources offline and exploit local encoding circuits. In particular, we derive an encoding circuit for a bipartite version of the Steane code that is local and additionally requires only nearest-neighbor interactions. We have simulated this encoding in the CNOT extended rectangle with a publicly available fault-tolerant simulation software. The result is that there is an improvement in the “pseudothreshold” with respect to the baseline Steane code, under the assumption that quantum memory errors occur less frequently than quantum gate errors.     

Implementing enterprise resource planning systems: organizational performance and the duration of the implementation

This paper examines the impact of the duration of ERP implementation on firm performance both during and after implementation. Organizations choose either an accelerated implementation approach or a traditional (longer) implementation approach. The former approach gives the organization the advantage of speed, but the disadvantage of fitting its processes to that of a packaged (thus, undifferentiated from competitors) ERP. The latter approach allows the organization to redesign strategy and processes, and thus, search for ways to be unique from its competition. The study uses a regression model to capture the changes in various performance measures during and after implementation between firms that implemented the ERP, using the performance measure of a matched group of firms that did not implement an ERP as a benchmark/control sample, on the basis of the duration of the implementation. Financial data from Compustat, and data on start date and end date of ERP implementation between 1990 and 2005 for firms in the Oil and Gas industry was collected from an ERP vendor. Results show that measures such as return on sales improved after implementation. However, measures such as inventory turnover, which reflect operational benefits, improve during implementation. We find that accelerated implementation confers both operational and strategic benefits. This study highlights the strategic consequences of the different choices of implementation.     

A formal framework for scenario development in support of environmental decision-making

Scenarios are possible future states of the world that represent alternative plausible conditions under different assumptions. Often, scenarios are developed in a context relevant to stakeholders involved in their applications since the evaluation of scenario outcomes and implications can enhance decision-making activities. This paper reviews the state-of-the-art of scenario development and proposes a formal approach to scenario development in environmental decision-making. The discussion of current issues in scenario studies includes advantages and obstacles in utilizing a formal scenario development framework, and the different forms of uncertainty inherent in scenario development, as well as how they should be treated. An appendix for common scenario terminology has been attached for clarity. Major recommendations for future research in this area include proper consideration of uncertainty in scenario studies in particular in relation to stakeholder relevant information, construction of scenarios that are more diverse in nature, and sharing of information and resources among the scenario development research community.     

Growth of Escherichia coli O157:H7 in raw ground beef stored at 10 degrees C and the influence of competitive bacterial flora,strain variation,and fat level

Pure-culture broth-based models of the growth of Escherichia coli O157:H7 have been used to estimate its behavior in ground beef, even though these models have not been adequately validated for this food product. This situation limits accurate estimates of the behavior of E. coli O157:H7 in ground beef and introduces uncertainties in risk assessments. In the present study, the growth of single and multiple strains of E. coli O157:H7 were measured in retail ground beef stored at 10 degrees C for up to 12 days, and the results were compared with estimates generated by the U.S. Department of Agriculture's Pathogen Modeling Program (PMP; version 5.1). At pH 5.9, the PMP predicted a maximum population density (MPD) of 9.13 log10 CFU/g, an exponential growth rate (EGR) of 0.052 log10 CFU/h, and a lag time of 56.3 h. Similar parameter values were observed for sterilized ground beef; however, no lag phase was observed. In contrast, the mean MPD and EGR for retail ground beef were 5.09 log10 CFU/g and 0.019 log10 CFU/h, respectively, and no lag phase was observed. Both the EGR and the MPD increased with decreasing fat levels. There was low variation in the MPD and EGR parameters for the nine E. coli O157:H7 ground beef isolates. Two isolates of competitive native flora were separately added to sterilized ground beef, and the EGR and MPD decreased as the ratio of competitive flora to E. coli O157:H7 increased. For one strain, at ratios of 1:1, 10:1, and 100:1, the EGRs were 0.033, 0.025, and 0.018 log10 CFU/h, respectively, and the MPDs were 6.14, 5.08, and 4.84 log10 CFU/g, respectively. These results demonstrate that existing broth-based models for E coli O157:H7 must be validated for food and that models should consider the effects of the food matrix, the competitive microflora, and potential pathogen strain variation.     

Identifying Candidate Protein Markers of Acute Kidney Injury in Acute Decompensated Heart Failure

One-quarter of patients with acute decompensated heart failure (ADHF) experience acute kidney injury (AKI)—an abrupt reduction or loss of kidney function associated with increased long-term mortality. There is a critical need to identify early and real-time markers of AKI in ADHF; however, to date, no protein biomarkers have exhibited sufficient diagnostic or prognostic performance for widespread clinical uptake. We aimed to identify novel protein biomarkers of AKI associated with ADHF by quantifying changes in protein abundance in the kidneys that occur during ADHF development and recovery in an ovine model. Relative quantitative protein profiling was performed using sequential window acquisition of all theoretical fragment ion spectra–mass spectrometry (SWATH–MS) in kidney cortices from control sheep (n = 5), sheep with established rapid-pacing-induced ADHF (n = 8), and sheep after ~4 weeks recovery from ADHF (n = 7). Of the 790 proteins quantified, we identified 17 candidate kidney injury markers in ADHF, 1 potential kidney marker of ADHF recovery, and 2 potential markers of long-term renal impairment (differential abundance between groups of 1.2–2.6-fold, adjusted p < 0.05). Among these 20 candidate protein markers of kidney injury were 6 candidates supported by existing evidence and 14 novel candidates not previously implicated in AKI. Proteins of differential abundance were enriched in pro-inflammatory signalling pathways: glycoprotein VI (activated during ADHF development; adjusted p < 0.01) and acute phase response (repressed during recovery from ADHF; adjusted p < 0.01). New biomarkers for the early detection of AKI in ADHF may help us to evaluate effective treatment strategies to prevent mortality and improve outcomes for patients.     

Enhanced π-π interactions between a C60 fullerene and a buckle bend on a double-walled carbon nanotube

In situ low-voltage aberration corrected transmission electron microscopy (TEM) observations of the dynamic entrapment of a C₆₀ molecule in the saddle of a bent double-walled carbon nanotube is presented. The fullerene interaction is non-covalent, suggesting that enhanced π-π interactions (van der Waals forces) are responsible. Classical molecular dynamics calculations confirm that the increased interaction area associated with a buckle is sufficient to trap a fullerene. Moreover, they show hopping behavior in agreement with our experimental observations. Our findings further our understanding of carbon nanostructure interactions, which are important in the rapidly developing field of low-voltage aberration corrected TEM and nano-carbon device fabrication.