When laws and ethics collide: What should psychologists do?

At times the laws under which psychologists function may appear to contradict generally recognized ethical values and/or good clinical care. When these circumstances arise, psychologists must determine if a conflict really exists and, if so, seek solutions that reconcile respect for the law with their ethical values. At times, psychologists may decide to follow the law despite their ethical concerns. At other times, they may determine that a conscientious objection is warranted. The authors recommend options to consider when these situations arise and offer a decision-making process. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Synthesis and Characterisation of Some New Ferrocenyl- and Ferrocenylalkynyl-[60]Fullerene Compounds

We report the synthesis and characterisation of a series of ferrocenylfullerene compounds, and some new ferrocene derivatives required as intermediates. The new fullerene species are Fc-[60]fullerene, (8); Fc-C=C-[60]fullerene, (10); Fc-C=C-C=C-[60]fullerene, (12); and (η-C₅H₄SiBu₃)Fe(η-C₅H₄)-[60]fullerene, (14).     

Rainbow smelt population responses to species invasions and change in environmental condition

Invasive species can cause major disruptions in native food webs, yet the impact of species introductions and whether they will become invasive appears to be context-dependent. Rainbow smelt and alewife co-exist as invasive species in the Laurentian Great Lakes and as native species on the Atlantic coast of North America, but in Lake Champlain rainbow smelt is the dominant native forage fish and alewife are invasive. Alewife became abundant by 2007, providing an opportunity to explore the dynamics of these two species in a system where only one is invasive. We used data from a 28-year forage fish survey to compare demographics of rainbow smelt populations in three basins of Lake Champlain with different volumes, nutrient levels, and predator abundances. Rainbow smelt catch-per-unit-effort (CPUE) remained constant in the large, deep Main Lake before and after alewife invaded, but decreased in the two smaller basins. Declines were primarily a result of increased age-0 and age-1 mortality. Predation by top piscivores, system productivity, and competition for resources alone could not explain the patterns in CPUE across the basins. The mechanisms that allow alewife and rainbow smelt to co-exist could be related to system volume and oxythermal habitat availability, and may explain why the two species do not negatively affect each other in the Great Lakes. Summer hypoxia in the smaller basins could force individuals into smaller habitat volumes with higher densities of competitors and cannibalistic adult rainbow smelt. Habitat availability may mediate the impact of invasive alewife on native rainbow smelt.     

Register allocation for write activity minimization on non-volatile main memory for embedded systems

Non-volatile memories are good candidates for DRAM replacement as main memory in embedded systems and they have many desirable characteristics. Nevertheless, the disadvantages of non-volatile memory co-exist with its advantages. First, the lifetime of some of the non-volatile memories is limited by the number of erase operations. Second, read and write operations have asymmetric speed or power consumption in non-volatile memory. This paper focuses on the embedded systems using non-volatile memory as main memory. We propose register allocation technique with re-computation to reduce the number of store instructions. When non-volatile memory is applied as the main memory, reducing store instructions will reduce write activities on non-volatile memory. To re-compute the spills effectively during register allocation, a novel potential spill selection strategy is proposed. During this process, live range splitting is utilized to split certain long live ranges such that they are more likely to be assigned into registers. In addition, techniques for re-computation overhead reduction is proposed on systems with multiple functional units. With the proposed approach, the lifetime of non-volatile memory is extended accordingly. The experimental results demonstrate that the proposed technique can efficiently reduce the number of store instructions on systems with non-volatile memory by 33% on average.     

Ensuring reliability in B2B services: Fault tolerant inter-organizational workflows

In the age of Business-to-Business (B2B) collaboration, ensuring reliability of workflows underlying inter-organizational business processes is of significant importance. There are, however, quite a few challenges towards achieving seamless operation. Such challenges arise from heterogeneity in infrastructure and coordination mechanism at participant organizations, as well as time and cost associated with recovery from failure. Our research presents foundations for a reliable scheme for recovery from failure of workflow processes spanning through multiple business entities. First, a system model is adapted from the mobile computing literature that serves to establish the requirements to be enforced by each participating organization. In our model, we adopt the Maximal Sequence Path (MSP) approach from Yoo et al. (Lecture Notes in Artificial Intelligence 2132:222–236, 2001), as a means of decomposing workflows into mobile agent-driven processes that communicate via web services at each organization. This decomposition ensures defining logical points within the dynamics of a workflow instance for locating accurate and consistent states of the system for recovery in case of a failure. Then, a set of algorithms for various business scenarios are developed and presented as practical solutions. These algorithms are shown to create checkpoints such that the system is always in a globally consistent state. As such, these algorithms constitute a set of standards that can be incorporated in business process management suites that support reliable inter-organizational collaboration.     

A secure cookie scheme

Cookies are the primary means for web applications to authenticate HTTP requests and to maintain client states. Many web applications (such as those for electronic commerce) demand a secure cookie scheme. Such a scheme needs to provide the following four services: authentication, confidentiality, integrity, and anti-replay. Several secure cookie schemes have been proposed in previous literature; however, none of them are completely satisfactory. In this paper, we propose a secure cookie scheme that is effective, efficient, and easy to deploy. In terms of effectiveness, our scheme provides all of the above four security services. In terms of efficiency, our scheme does not involve any database lookup or public key cryptography. In terms of deployability, our scheme can be easily deployed on existing web services, and it does not require any change to the Internet cookie specification. We implemented our secure cookie scheme using PHP and conducted experiments. The experimental results show that our scheme is very efficient on both the client side and the server side.A notable adoption of our scheme in industry is that our cookie scheme has been used by Wordpress since version 2.4. Wordpress is a widely used open source content management system.     

Decentralized observers with consensus filters for distributed discrete-time linear systems

This paper presents a decentralized observer with a consensus filter for the state observation of discrete-time linear distributed systems. Each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors’ estimates. It is proven that the state estimates of the proposed observer exponentially converge to the actual plant states under arbitrarily changing, but connected, communication and pseudo-connected sensing graph topologies. Except these connectivity properties, full knowledge of the sensing and communication graphs is not needed at the design time. As a byproduct, we obtained a result on the location of eigenvalues, i.e., the spectrum, of the Laplacian for a family of graphs with self-loops.     

Exploring album structure for face recognition in online social networks

In this paper, we propose an album-oriented face-recognition model that exploits the album structure for face recognition in online social networks. Albums, usually associated with pictures of a small group of people at a certain event or occasion, provide vital information that can be used to effectively reduce the possible list of candidate labels. We show how this intuition can be formalized into a model that expresses a prior on how albums tend to have many pictures of a small number of people. We also show how it can be extended to include other information available in a social network. Using two real-world datasets independently drawn from Facebook, we show that this model is broadly applicable and can significantly improve recognition rates.     

Development of high‐definition aqueous polyvinylpyrrolidone photoresists for cathode ray tubes

Aqueous photoresists that are capable of higher resolutions than are currently employed by the cathode ray tube (CRT) industry were developed by combining photoactivators, which activate at shorter UV wavelengths with polyvinylpyrrolidone (PVP). Two photoactivators were synthesized: 4,4′‐diazido‐2,2′‐biphenyl disodium disulfonate (DABP), which has a maximum absorbance at 264 nm, and 4,4′‐diazido‐2,2′‐biphenylethane disodium disulfonate (DABPE), which has a maximum absorbance at 258 nm. The PVP/DABP and PVP/DABPE photoresists successfully imaged a pattern with resolution as small as 4.4 μm with photoactivator concentrations greater than 20% of the PVP concentration. Addition of silane and emulgen greatly improved the performance of the photoresists with more uniform coatings of thicknesses of up to 1.4 μm. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 1637–1644, 2006     

Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A shapelet is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselves.