bluuebunny/crossref_metadata_2025 huggingface dataset:
EFFECTIVENESS OF STRATEGIC ENVIRONMENTAL ASSESSMENT (SEA) IN SOUTH AFRICA
Authors: RETIEF FRANCOIS
Published: April 2007

South Africa is regarded as a leading developing country in terms of SEA practice. However, the lack of empirical research to evaluate and learn from this wealth of practical experience can be considered a major lost opportunity not only for South Africa but also for the development of our understanding of SEA in the developing world. This paper provides the research results of an effectiveness review of six high profile SEA case studies within the South African context. Measured against four key performance areas (KPAs) and nine key performance indicators (KPIs) the research results show a high degree of ineffectiveness across all six cases in terms of 'direct outputs'. The main areas of weakness were the inability to influence the contents of plans and programmes as well as decision making in general. It can thus be concluded that based on the 'poor' direct effectiveness results SEA is not achieving its objectives within the South African context. However, certain 'indirect outputs' also emerged such as highlighting deficiencies and gaps in existing policy as well as examples where SEA facilitated capacity building and raised awareness of sustainability issues. Moreover, SEAs also contributed significantly to information generation and sharing. The research results suggest that practitioners need to either redefine the purpose of SEA, or fundamentally rethink the way in which SEA is being applied within the South African context. The paper concludes by making proposals for future international research.
SUPPORT VECTOR MACHINE BASED AUTOMATIC CLASSIFICATION OF HUMAN BRAIN USING MR IMAGE FEATURES
Authors: SELVARAJ HENRY , THAMARAI SELVI S. , SELVATHI D. , RAMKUMAR R.
Published: April 2007

This paper proposes an intelligent classification technique to identify two categories of MRI volume data as normal and abnormal. The manual interpretation of MRI slices based on visual examination by radiologist/physician may lead to incorrect diagnosis when a large number of MRIs are analyzed. In this work, the textural features are extracted from the MR data of patients and these features are used to classify a patient as belonging to normal (healthy brain) or abnormal (tumor brain). The categorization is obtained using various classifiers such as support vector machine (SVM), radial basis function, multilayer perceptron and k-nearest neighbor. The performance of these classifiers are analyzed and a quantitative indication of how better the SVM performance is when compared with other classifiers is presented. In intelligent computer aided health care system, the proposed classification system using SVM classifier can be used to assist the physician for accurate diagnosis.
TWO-DIMENSIONAL IIR FILTER DESIGN WITH MODERN SEARCH HEURISTICS: A COMPARATIVE STUDY
Authors: DAS SWAGATAM , KONAR AMIT
Published: April 2007

In the past few years, there has been a massive growth in the field of biologically inspired global search heuristics. Computational cost having been reduced almost dramatically, researchers from all corners are taking more interset in following the underlying principles of nature to solve nearly intractable search problems. In this paper, we attempt to solve one very important optimization problem arising in the field of two-dimensional IIR (infinite impulse response) filter design, with three naturally inspired global search algorithms. We have used a state-of-the-art real coded genetic algorithm (GA), one very recent and modified version of the particle swarm opimization (PSO) and finally an improved version of the differential evolution (DE) algorithm. The DE algorithm has been modified by us to prevent its premature convergence to some suboptimal region of the search space. The design task is formulated as a constrained minimization problem and solved by the three metaheuristics. Numerical results are presented over three difficult instances of the design problem. The study also compares the results with two recently published filter design methods. Our experiments reveal that the DE family of algorithms should receive primary attention in solving the constrained multidimensional filter design tasks.
MULTIOBJECTIVE OPTIMIZATION OF PROCESS PLANT USING GENETIC ALGORITHM
Authors: GOVINDARAJAN L. , KARUNANITHI T.
Published: April 2007

The optimal design of large-scale process plant is difficult due to the presence of Pareto sets or nondominated solutions. Many conventional and advanced mathematical techniques had been adopted which have their own limitations in solving the complex design problem. In this paper, nondominant-sorted genetic algorithms NSGA and NSGA-II have been adopted for the optimal design of complex Williams–Otto model process plant. The plant consists of a reactor, separation system consisting of heat exchanger, decanter and distillation column. Multiobjective optimization is used to maximize the profit, i.e. the return on investment, to maintain lesser use of costlier raw material and lesser disposal of the waste byproducts. So NSGA-II is employed in this study as an effective replacement for NSGA, classical genetic algorithm, conventional and traditional methods of optimization in solving multiobjective process design problems and to achieve fine-tuning of variables in determining Pareto optimal design parameters. NSGA-II method finding global optimal front has a significant effect on the design of control system for the real time and continuous robust control of complex process plant as each target vector provides proper direction and drives the process to multiobjective optimum conditions.
DIRECT ADAPTIVE TYPE-2 FUZZY CONTROL FOR NONLINEAR SYSTEMS
Authors: CHAFAA KHEIREDDINE , SAIDI LAMIR , GHANAI MOUNA , BENMAHAMMED KHIER
Published: April 2007

A new direct adaptive type-2 fuzzy controller for a nonlinear dynamical system is developed in this paper. The parameters of the membership functions characterizing the linguistic terms in the type-2 fuzzy IF–THEN rules change according to some adaptive law for the purpose of controlling a plant to track a reference trajectory. A supervisory controller is appended to the type-2 fuzzy controller to force the state to be within the constraint set. Stability of this adaptive scheme is established using Lyapunov stability tools, where we guarantee the global stability of the resulting closed-loop system, in the sense that all signals involved are uniformly bounded. The simulation results for a Duffing forced-oscillation system show better performances, i.e. tracking error and control effort can be made smaller.
FUZZY STATE AGGREGATION AND POLICY HILL CLIMBING FOR STOCHASTIC ENVIRONMENTS
Authors: WARDELL DEAN C. , PETERSON GILBERT L.
Published: April 2007

Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the operating environment changes. Additionally, by applying reinforcement learning to multiple cooperative software agents (a multi-agent system) not only allows each individual agent to learn from its own experience, but also opens up the opportunity for the individual agents to learn from the other agents in the system, thus accelerating the rate of learning. This research presents the novel use of fuzzy state aggregation, as the means of function approximation, combined with the fastest policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF). The combination of fast policy hill climbing and fuzzy state aggregation function approximation is tested in two stochastic environments: Tileworld and the simulated robot soccer domain, RoboCup. The Tileworld results demonstrate that a single agent using the combination of FSA and PHC learns quicker and performs better than combined fuzzy state aggregation and Q-learning reinforcement learning alone. Results from the multi-agent RoboCup domain again illustrate that the policy hill climbing algorithms perform better than Q-learning alone in a multi-agent environment. The learning is further enhanced by allowing the agents to share their experience through a weighted strategy sharing.
A CEREBELLAR MODEL CLASSIFIER FOR DATA MINING WITH LINEAR TIME COMPLEXITY
Authors: CORNFORTH DAVID
Published: April 2007

Techniques for automated classification need to be efficient when applied to large datasets. Machine learning techniques such as neural networks have been successfully applied to this class of problem, but training times can blow out as the size of the database increases. Some of the desirable features of classification algorithms for large databases are linear time complexity, training with only a single pass of the data, and accountability for class assignment decisions. A new training algorithm for classifiers based on the Cerebellar Model Articulation Controller (CMAC) possesses these features. An empirical investigation of this algorithm has found it to be superior to the traditional CMAC training algorithm, both in accuracy and time required to learn mappings between input vectors and class labels.
IMAGE-BASED PAINTERLY RENDERING BY EVOLUTIONARY ALGORITHM
Authors: CHAKRABORTY UDAY K. , KANG HYUNG W. , WANG PAUL P.
Published: April 2007

This paper presents an effective method based on genetic algorithm for optimizing the rendering quality in image-based painterly rendering. Based on a multi-level evolutionary approach, the proposed method produces, for a variety of input images, results that are better in a statistically significant way than previous methods.
GEO-RBAC
Authors: Damiani Maria Luisa , Bertino Elisa , Catania Barbara , Perlasca Paolo
Published: April 2007

Securing access to data in location-based services and mobile applications requires the definition of spatially aware access-control systems. Even if some approaches have already been proposed either in the context of geographic database systems or context-aware applications, a comprehensive framework, general and flexible enough to deal with spatial aspects in real mobile applications, is still missing. In this paper, we make one step toward this direction and present GEO-RBAC, an extension of the RBAC model enhanced with spatial-and location-based information. In GEORBAC, spatial entities are used to model objects, user positions, and geographically bounded roles. Roles are activated based on the position of the user. Besides a physical position, obtained from a given mobile terminal or a cellular phone, users are also assigned a logical and device-independent position, representing the feature (the road, the town, the region) in which they are located. To enhance flexibility and reusability, we also introduce the concept of role schema, specifying the name of the role, as well as the type of the role spatial boundary and the granularity of the logical position. We then extend GEO-RBAC to support hierarchies, modeling permission, user, and activation inheritance, and separation of duty constraints. The proposed classes of constraints extend the conventional ones to deal with different granularities (schema/instance level) and spatial information. We conclude the paper with an analysis of several properties concerning the resulting model.
A survey on peer-to-peer key management for mobile ad hoc networks
Authors: Merwe Johann Van Der , Dawoud Dawoud , McDonald Stephen
Published: April 2007

The article reviews the most popular peer-to-peer key management protocols for mobile ad hoc networks (MANETs). The protocols are subdivided into groups based on their design strategy or main characteristic. The article discusses and provides comments on the strategy of each group separately. The discussions give insight into open research problems in the area of pairwise key management.
Survey of network-based defense mechanisms countering the DoS and DDoS problems
Authors: Peng Tao , Leckie Christopher , Ramamohanarao Kotagiri
Published: April 2007

This article presents a survey of denial of service attacks and the methods that have been proposed for defense against these attacks. In this survey, we analyze the design decisions in the Internet that have created the potential for denial of service attacks. We review the state-of-art mechanisms for defending against denial of service attacks, compare the strengths and weaknesses of each proposal, and discuss potential countermeasures against each defense mechanism. We conclude by highlighting opportunities for an integrated solution to solve the problem of distributed denial of service attacks.
Introduction to special issue on reasoning in natural language information processing
Authors: Song Dawei , Nie Jian-Yun
Published: April 2007

For any applications related to Natural Language Processing (NLP), reasoning has been recognized as a necessary underlying aspect. Many of the existing work in NLP deals with specific NLP problems in a highly heuristic manner, yet not from an explicit reasoning perspective. Recently, there have been developments on models that allow reasoning in NLP such as language models, logical models, and so on. The goal of this special issue is to present high-quality contributions that integrate reasoning involved in different areas of natural language processing both at theoretical and/or practical levels. In this article, we give a brief overview on some major aspects of explicating reasoning in NLP and summarize the articles included in this special issue.
Inferential language models for information retrieval
Authors: Nie Jian-Yun , Cao Guihong , Bai Jing
Published: April 2007

Language modeling (LM) has been widely used in IR in recent years. An important operation in LM is smoothing of the document language model. However, the current smoothing techniques merely redistribute a portion of term probability according to their frequency of occurrences only in the whole document collection. No relationships between terms are considered and no inference is involved. In this article, we propose several inferential language models capable of inference using term relationships. The inference operation is carried out through a semantic smoothing either on the document model or query model, resulting in document or query expansion. The proposed models implement some of the logical inference capabilities proposed in the previous studies on logical models, but with necessary simplifications in order to make them tractable. They are a good compromise between inference power and efficiency. The models have been tested on several TREC collections, both in English and Chinese. It is shown that the integration of term relationships into the language modeling framework can consistently improve the retrieval effectiveness compared with the traditional language models. This study shows that language modeling is a suitable framework to implement basic inference operations in IR effectively.
Statistical query translation models for cross-language information retrieval
Authors: Gao Jianfeng , Nie Jian-Yun , Zhou Ming
Published: April 2007

Query translation is an important task in cross-language information retrieval (CLIR), which aims to determine the best translation words and weights for a query. This article presents three statistical query translation models that focus on the resolution of query translation ambiguities. All the models assume that the selection of the translation of a query term depends on the translations of other terms in the query. They differ in the way linguistic structures are detected and exploited. The co-occurrence model treats a query as a bag of words and uses all the other terms in the query as the context for translation disambiguation. The other two models exploit linguistic dependencies among terms. The noun phrase (NP) translation model detects NPs in a query, and translates each NP as a unit by assuming that the translation of a term only depends on other terms within the same NP. Similarly, the dependency translation model detects and translates dependency triples, such as verb-object, as units. The evaluations show that linguistic structures always lead to more precise translations. The experiments of CLIR on TREC Chinese collections show that all three models have a positive impact on query translation and lead to significant improvements of CLIR performance over the simple dictionary-based translation method. The best results are obtained by combining the three models.
A statistical framework for query translation disambiguation
Authors: Liu Yi , Jin Rong , Chai Joyce Y.
Published: April 2007

Resolving ambiguity in the process of query translation is crucial to cross-language information retrieval (CLIR), given the short length of queries. This problem is even more challenging when only a bilingual dictionary is available, which is the focus of our work described here. In this paper, we will present a statistical framework for dictionary-based CLIR that estimates the translation probabilities of query words based on the monolingual word co-occurrence statistics. In addition, we will present two realizations of the proposed framework, i.e., the “maximum coherence model” and the “spectral query-translation model,” that exploit different metrics for the coherence measurement between a translation of a query word and the theme of the entire query. Compared to previous work on dictionary-based CLIR, the proposed framework is advantageous in three aspects: (1) Translation probabilities are calculated explicitly to capture the uncertainty in translating queries; (2) translations of all query words are estimated simultaneously rather than independently; and (3) the formulated problem can be solved efficiently with a unique optimal solution. Empirical studies with Chinese--English cross-language information retrieval using TREC datasets have shown that the proposed models achieve a relative 10%--50% improvement, compared to other approaches that also exploit word co-occurrence statistics for query translation disambiguation.
Improving discriminative sequential learning by discovering important association of statistics
Authors: Phan Xuan-Hieu , Nguyen Le-Minh , Inoguchi Yasushi , Ho Tu-Bao , Horiguchi Susumu
Published: April 2007

Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing or information extraction. Their key advantage is the ability to capture various nonindependent and overlapping features of inputs. However, several unexpected pitfalls have a negative influence on the model's performance; these mainly come from a high imbalance among classes, irregular phenomena, and potential ambiguity in the training data. This article presents a data-driven approach that can deal with such difficult data instances by discovering and emphasizing important conjunctions or associations of statistics hidden in the training data. Discovered associations are then incorporated into these models to deal with difficult data instances. Experimental results of phrase-chunking and named entity recognition using CRFs show a significant improvement in accuracy. In addition to the technical perspective, our approach also highlights a potential connection between association mining and statistical learning by offering an alternative strategy to enhance learning performance with interesting and useful patterns discovered from large datasets.
LYDIAN
Authors: Koldehofe Boris , Papatriantafilou Marina , Tsigas Philippas
Published: April 2007

LYDIAN is an environment to support the teaching and learning of distributed algorithms. It provides a collection of distributed algorithms as well as continuous animations. Users can combine algorithms and animations with arbitrary network structures defining the interconnection and behavior of the distributed algorithm. Further, it facilitates the creation of algorithm descriptions as well as the creation of network structures. This makes LYDIAN a flexible tool to be used with students with different skills and backgrounds. This article gives an overview about various ideas and concepts behind LYDIAN by describing in detail the framework for an educational visualization and simulation environment for learning/teaching distributed algorithms as well as discussing possible extensions, which may improve possibilities for user interaction. Moreover, in our effort to understand better what visualization and simulation environments, such as LYDIAN, need to provide, we show results taken from a case study integrating LYDIAN in an undergraduate distributed-systems course.
A word from the editor
Authors: Lee Newton
Published: April 2007

Welcome to
ACM Computers in Entertainment
, a premier online magazine featuring video interviews with leading professionals and interesting articles on entertainment technology and its applications.
An implementation of real-time 3D interactive drama
Authors: Szilas Nicolas , Barles Jason , Kavakli Manolya
Published: April 2007

Interactive fiction and adventure video games are narrative genres which provide the player with the option of acting as the main character of the story. However these genres do not fully match the expectations of their authors and readers because the player cannot deeply affect the storyline.

This article describes a system integrating highly interactive narrative structures in a real-time 3D environment.

Based on a theoretical foundation of narrative and drama, an interactive drama engine (IDE) has been implemented. It comprises an action calculus system, a text-generation system, a behavior engine, an animation engine as well as an innovative adaptive user interface. The IDE is demonstrated with two scenarios.
Combining gameplay and narrative techniques to enhance the user experience of viewing galleries
Authors: Wolff Annika , Mulholland Paul , Zdrahal Zdenek , Joiner Richard
Published: April 2007

Owing to high production costs, the reuse of film and television broadcast content in spin-off merchandise is often necessary. Games and DVDs are popular spin-off products, and when aimed at children in particular, they often include viewing galleries in which a user can browse scenes from the original broadcast. This is a highly economic form of literal content reuse, since it minimizes authoring additional resources. There is also the potential to improve the experience of users as they interact with content in viewing galleries. Ways to do so become apparent by examining the principles of both narrative and gameplay which underpin the original broadcasts and their spin-offs. Scene-Driver is a narrative-driven game architecture that enables the user, via a domino-like interface, to select and order content. This mechanism creates an engaging means for a user to interact with existing broadcast content. Three versions of the Scene-Driver approach to content reuse have been developed, each using content from a children's animated television series called Tiny Planets. Four studies to evaluate the Scene-Driver game have been done, all with positive results.
A report on the crossmedia game epidemic menace
Authors: LINDT IRMA , OHLENBURG JAN , PANKOKE-BABATZ UTA , GHELLAL SABIHA
Published: April 2007

Crossmedia games employ a wide variety of gaming interfaces based on stationary and mobile devices to facilitate different game experiences within a single game. This article presents the crossmedia game Epidemic Menace, introduces the game concept, and describes experiences from two Epidemic Menace game events. We also explain the technical realization of Epidemic Menace, the evaluation methodologies we used, and some evaluation results.
Gene Therapy in the Treatment of Heart Failure
Authors: Ly Hung , Kawase Yoshiaki , Yoneyama Ryuichi , Hajjar Roger J.
Published: April 2007

Heart failure is a major cause of morbidity and mortality in contemporary societies. Although progress in conventional treatment modalities is making steady and incremental gains to reduce this disease burden, there remains a need to explore new and potentially therapeutic approaches. Gene therapy, for example, was initially envisioned as a treatment strategy for inherited monogenic disorders. It is now apparent that gene therapy has broader potential that also includes acquired polygenic diseases, such as heart failure. Advances in the understanding of the molecular basis of conditions such as these, together with the evolution of increasingly efficient gene transfer technology, has placed congestive heart failure within reach of gene-based therapy.
A Dominant Role of Cardiac Molecular Motors in the Intrinsic Regulation of Ventricular Ejection and Relaxation
Authors: Hinken Aaron C. , Solaro R. John
Published: April 2007

Molecular motors housed in myosins of the thick filament react with thin-filament actins and promote force and shortening in the sarcomeres. However, other actions of these motors sustain sarcomeric activation by cooperative feedback mechanisms in which the actin-myosin interaction promotes thin-filament activation. Mechanical feedback also affects the actin-myosin interaction. We discuss current concepts of how these relatively under-appreciated actions of molecular motors are responsible for modulation of the ejection time and isovolumic relaxation in the beating heart.
Direct and Indirect Cortico-Motoneuronal Pathways and Control of Hand/Arm Movements
Authors: Isa Tadashi , Ohki Yukari , Alstermark Bror , Pettersson Lars-Gunnar , Sasaki Shigeto
Published: April 2007

Recent studies from our group have demonstrated the existence of a disynaptic excitatory cortico-motoneuronal (CM) pathway in macaque monkeys via propriospinal neurons in the midcervical segments. Results from behavioral studies with lesion of the direct pathway suggest that the indirect CM pathway can mediate the command for dexterous finger movements.
Integrative Genomic Analysis of Small-Cell Lung Carcinoma Reveals Correlates of Sensitivity to Bcl-2 Antagonists and Uncovers Novel Chromosomal Gains
Authors: Olejniczak Edward T. , Van Sant Charles , Anderson Mark G. , Wang Gang , Tahir Stephen K. , Sauter Guido , Lesniewski Rick , Semizarov Dimitri
Published: April 2007

Cancer is a highly heterogeneous disease in terms of the genetic profile and the response to therapeutics. An early identification of a genomic marker in drug discovery may help select patients that would respond to treatment in clinical trials. Here we suggest coupling compound screening with comparative genomic hybridization analysis of the model systems for early discovery of genomic biomarkers. A Bcl-2 antagonist, ABT-737, has recently been discovered and shown to induce regression of solid tumors, but its activity is limited to a fraction of small-cell lung carcinoma (SCLC) models tested. We used comparative genomic hybridization on high-density single-nucleotide polymorphism genotyping arrays to carry out a genome-wide analysis of 23 SCLC cell lines sensitive and resistant to ABT-737. The screen revealed a number of novel recurrent gene copy number abnormalities, which were also found in an independent data set of 19 SCLC tumors and confirmed by real-time quantitative PCR. A previously unknown amplification was identified on 18q and associated with the sensitivity of SCLC cell lines to ABT-737 and another Bcl-2 antagonist. The region of gain contains Bcl-2 and NOXA, two apoptosis-related genes. Expression microarray profiling showed that the genes residing in the amplified region of 18q are also overexpressed in the sensitive lines relative to the resistant lines. Fluorescence in situ hybridization analysis of tumors revealed that Bcl-2 gain is a frequent event in SCLC. Our findings suggest that 18q21-23 copy number will be a clinically relevant predictor for sensitivity of SCLC to Bcl-2 family inhibitors. The 18q21-23 genomic marker may have a broader application in cancer because Bcl-2 is associated with apoptosis evasion and chemoresistance. (Mol Cancer Res 2007;5(4):331–39)
Overexpression of Myofibrillogenesis Regulator-1 Aggravates Cardiac Hypertrophy Induced by Angiotensin II in Mice
Authors: Li Hong-Liang , She Zhi-Gang , Li Tian-Bo , Wang Ai-Bing , Yang Qinglin , Wei Yu-Sheng , Wang Yi-Guang , Liu De-Pei
Published: April 2007

Myofibrillogenesis regulator-1 (MR-1) augments cardiomyocytes hypertrophy induced by angiotensin II (Ang II) in vitro. However, its roles in cardiac hypertrophy in vivo remain unknown. Here, we investigate whether MR-1 can promote cardiac hypertrophy induced by Ang II in vivo and elucidate the molecular mechanisms of MR-1 on cardiac hypertrophy. We used a model of Ang II–induced cardiac hypertrophy by infusion of Ang II in female mice. In wild-type mice subjected to the Ang II infusion, cardiac hypertrophy developed after 2 weeks. In mice overexpressing human MR-1 (transgenic), however, cardiac hypertrophy was significantly greater than in wild-type mice as estimated by heart weight:body weight ratio, cardiomyocyte area, and echocardiographic measurements, as well as cardiac atrial natriuretic peptide and B-type natriuretic peptide mRNA and protein levels. Our further results showed that cardiac inflammation and fibrosis observed in wild-type Ang II mice were augmented in transgenic Ang II mice. Importantly, increased nuclear factor κB activation was significantly increased higher in transgenic mice compared with wild-type mice after 2 weeks of Ang II infusion. In vitro experiments also revealed that overexpression of MR-1 enhanced Ang II–induced nuclear factor κB activation, whereas downregulation of MR-1 blocked it in cardiac myocytes. In conclusion, our results suggest that MR-1 plays an aggravative role in the development of cardiac hypertrophy via activation of the nuclear factor κB signaling pathway.
Neuronal Responsiveness to Central Na
+
in 2 Congenic Strains of Dahl Salt-Sensitive Rats
Authors: Huang Bing S. , Ahmad Monir , Deng Alan Y. , Leenen Frans H.H.
Published: April 2007

Dahl salt-sensitive rats show increased Na
+
entry into the brain on high salt intake and increased sympathetic and pressor responses to central Na
+
. We examined C10QTL2 and C17QTL to test whether they contribute to these phenotypes. In Dahl salt-sensitive, Lewis, and C10S.L16, and C17S.L2 congenic rats on a high salt diet for 8 to 10 days, blood pressure and heart rate were higher in Dahl salt-sensitive versus others and in C10S.L16 and C17S.L2 versus Lewis rats. Cerebrospinal fluid [Na
+
] increased by ∼5 mmol/L in Dahl salt-sensitive, C10S.L16, and C17S.L2 compared with Lewis rats. In rats on a regular salt diet, 8-minute intracerebroventricular infusions of artificial cerebrospinal fluid with increasing [Na
+
] caused increases in blood pressure, heart rate, and renal sympathetic nerve activity, which were ≈90% larger in Dahl salt-sensitive and C17S.L2 versus Lewis rats and only 35% to 45% larger in C10S.L16 versus Lewis rats. In another set of rats on regular salt, blood pressure and heart rate were recorded by telemetry before and during intracerebroventricular infusion of Na
+
-rich cerebrospinal fluid for 14 days. Na
+
-rich cerebrospinal fluid caused significantly larger increases in blood pressure and heart rate, larger responses to air stress and more impairment of baroreflex in Dahl salt-sensitive and C17S.L2 rats versus Lewis rats. In contrast, responses in C10S.L16 rats were similar to those in Lewis rats. These data suggest that, in Dahl salt-sensitive rats, genetic variants in C10QTL2 but not C17QTL contribute to increased neuronal responsiveness to cerebrospinal fluid [Na
+
]. However, neither of them contributes to the increase in cerebrospinal fluid [Na
+
] induced by high salt.
The Global Trend in Sea Surface Temperature from 20 Years of Advanced Very High Resolution Radiometer Data
Authors: Good S. A. , Corlett G. K. , Remedios J. J. , Noyes E. J. , Llewellyn-Jones D. T.
Published: April 2007

The trend in sea surface temperature has been determined from 20 yr of Advanced Very High Resolution Radiometer Pathfinder data (version 5). The data span the period from January 1985 to December 2004, inclusive. The linear trends were calculated to be 0.18° ± 0.04° and 0.17° ± 0.05°C decade−1 from daytime and nighttime data, respectively. However, the measured trends were found to be somewhat smaller if version 4.1 of the Pathfinder data was used, or if the time series of data ended earlier. The influence of El Niño on global temperatures can be seen clearly in the data. However, it was not found to affect the trend measurements significantly. Evidence of cool temperatures after the eruption of Mount Pinatubo in 1991 was also observed.
The Effect of the Threat of Legal Sanction on Program Retention and Completion: Is That Why They Stay in Drug Court?
Authors: Hepburn John R. , Harvey Angela N.
Published: April 2007

Drug courts routinely rely on the threat of legal sanction to motivate drug-using criminal offenders to enter and complete community-based treatment programs. In light of the high failure rates among drug court participants, what is the effect of the threat of legal sanction on program retention and completion? A quasiexperimental research design was used to study program retention and completion within two adult drug courts that employed the same staff to administer identical treatment and supervision programs in the same jurisdiction. One court relied on a 120-day suspended sentence to coerce program participation, whereas the other court was prohibited by law from imposing a jail sentence on its participants. Using alternative measures of program retention, a single measure of program completion, and controls for salient sociodemographic and criminal history factors, the analysis found no differences in program retention or completion between the two courts.
Inmate-on-Inmate Victimization Among Older Male Prisoners
Authors: Kerbs John J. , Jolley Jennifer M.
Published: April 2007

Research on the safety and victimization of older prisoners has been limited. This study examines quantitative and qualitative victimization data gathered from face-to-face interviews with 65 male prisoners (ages 50 and above) confined in a state-level prison system. Both victimization rates and narrative descriptions of psychological, property, physical, and sexual inmate-on-inmate episodes are presented. Content analyses suggest that younger prisoners victimize older prisoners and that a majority of older prisoners support the use of age-segregated living arrangements to prevent victimization. Future research is needed to address methodological limitations of this study and others.
A Meta-Analysis of Interventions for Informal Stroke Caregivers
Authors: Lee JuHee , Soeken Karen , Picot Sandra J.
Published: April 2007

The purpose of this study is to examine the effectiveness of the interventions for improving mental health of caregivers of people with stroke by synthesizing individual studies. A meta-analysis was performed to summarize findings of intervention studies of caregivers of elderly stroke patients. Additionally, a sensitivity analysis and a publication bias were tested. The overall mean weighted effect size (MWES) for the four studies is 0.277 ( Z = 3.432, p = .001) with a 95% CI .118 to .435 ( N = 718) indicating that the intervention was effective in improving the mental health of informal stroke caregivers. The MWES for the education program was 0.354 ( Z= 2.613, p < .01) and for the support program was .234 ( Z = 2.335, p= .02). The MWES for the Europe study was .219 ( Z= 2.613, p < .01) and for the United States was .922 ( Z = 3.287, p = .001). The results show that overall interventions improved mental health of informal stroke caregivers. The small number of studies included in the meta-analysis limits the generalizability of results while supporting the need for more research in this area.
Combined Path-following and Obstacle Avoidance Control of a Wheeled Robot
Authors: Lapierre Lionel , Zapata Rene , Lepinay Pascal
Published: April 2007

This paper proposes an algorithm that drives a unicycle type robot to a desired path, including obstacle avoidance capabilities. The path-following control design relies on Lyapunov theory, backstepping techniques and deals explicitly with vehicle dynamics. Furthermore, it overcomes the initial condition constraints present in a number of path-following control strategies described in the literature. This is done by controlling explicitly the rate of progression of a “virtual target” to be tracked along the path; thus bypassing the problems that arise when the position of the path target point is simply defined as the closest point on the path. The obstacle avoidance part uses the Deformable Virtual Zone (DVZ) principle. This principle defines a safety zone around the vehicle in which the presence of an obstacle induces an “intrusion of information” that drives the vehicle reaction. The overall algorithm is combined with a guidance solution that embeds the path-following requirements in a desired intrusion information function, which steers the vehicle to the desired path while the DVZ ensures minimal contact with the obstacle, implicitly bypassing it. Simulation and experimental results illustrate the performance of the control system proposed.
Instrumentation and Algorithms for Posture Estimation in Compliant Framed Modular Mobile Robots
Authors: Minor Mark A. , Merrell Roy
Published: April 2007

Posture sensing techniques for Compliant Framed Modular Mobile Robots (CFMMR) are presented in this paper using a new Relative Posture Sensor (RPS) combined with standard sensors in a tiered fusion algorithm. The RPS consists of a compliant frame member instrumented with strain gauges and associated algorithms such that the RPS can predict relative posture. The first tier of the fusion algorithm uses traditional Kalman filters and rigid axle kinematic models to predict the global posture of each axle. In the second tier, a Relative Measurement Stochastic Posture Error Correction (RMSPEC) algorithm is introduced to fuse disparate axle data using the RPS. Experimental results are derived from over 60 trials operating the robot on high traction carpet, low traction sand, and sand with rugged rocky terrain. Results comparing the proposed sensory system with standard sensory systems demonstrate that the proposed techniques yield accurate relative posture estimates and posture regulation even on rugged terrain, which is a vast improvement over previous results.
Arthroscopic Management of Femoroacetabular Impingement
Authors: Philippon Marc J. , Stubbs Allston J. , Schenker Mara L. , Maxwell R. Brian , Ganz Reinhold , Leunig Michael
Published: April 2007

Morphological and spatial abnormalities of the proximal femur and acetabulum have been recently recognized as causes of femoroacetabular impingement. During joint motion in hips with femoroacetabular impingement, abnormal bony contact occurs, and soft tissue structures (chondral and labral) often fail. Femoroacetabular impingement has been reported to be a contributor to early-onset joint degeneration. Ganz et al have described good midterm success with an open surgical dislocation approach to reconstruct normal joint clearance. The purpose of this report is to discuss relevant literature and describe an arthroscopic approach to treat femoroacetabular impingement. This approach has particular relevance in high-demand patients, particularly in athletes seeking to return to high-level sport.
Team Leadership
Authors: O'Connor Dennis , Yballe Leodones
Published: April 2007

In response to the challenge of assigning and conducting group projects, this article lays out a brief context for team projects and puts forth a positive vision of teams and leadership. The authors provide some guiding values, tools, and goals and propose a model that expands the usual conceptualization of the student-team leadership challenge. The authors also share a number of project worksheets that they have developed over the years that have helped increase the learning that occurs through group projects.
Case Method Teaching as Science and Art
Authors: Greenhalgh Anne M.
Published: April 2007

The following article takes a metaphoric approach to case method teaching to shed light on one of our most important practices. The article hinges on the dual comparison of case method as science and as art. The dominant, scientific view of cases is that they are neutral descriptions of real-life business problems, subject to rigorous analysis. The dormant literary perspective enables us to see cases as incomplete natural narratives, open to multiple and diverse interpretations. By taking a stereoscopic view of case method—as a scientific and literary enterprise—we hone our students' managerial, problem-solving skills and heighten their leadership potential by developing their abilities as critical and creative thinkers. This article describes The Language of Leadership, an upper-level elective course that illustrates the implications of treating case method as science and art.
Personal Leadership Conundrum
Authors: Eriksen Matthew
Published: April 2007

The Personal Leadership Conundrum leadership development project is a semester-long, personal leadership inquiry that provides students with a self-directed learning opportunity. The guiding framework for this leadership inquiry is a personal leadership conundrum developed by students based on their experience. Students engage in problem-based learning and reflect on their experience to develop a clear understanding of their conundrum and how they might resolve it in practice. The exercise provides a structure through which students can become lifelong learners. In addition to the students' personal development, through interviews conducted by the students with leaders, the project creates a community of inquiry into leadership within the institution and/or field that it is employed.
Growing Leaders in Emergent Markets
Authors: April Kurt A. , April Amanda R.
Published: April 2007

South Africa has unique challenges. Thirteen years since becoming democratic, it is still going through its own unprecedented change in joining the global economic network and moving from Apartheid to democracy and from a closed to an open community. These political and sociological changes have also infiltrated business and therefore management education in South Africa, bringing demand for new approaches. At the Graduate School of Business, University of Cape Town, the authors adapted their traditional MBA teaching approaches to become more creative. This article summarizes the main themes within a core MBA course that have been guided by their new learning design, growth-stages methodology, a multipronged plan for moving management and leadership students through the growth stages by using ideas from systems thinking, scenario planning, coaching and mentoring, and organizational learning. These Western constructs are being complemented by African knowledge, which the authors are slowly developing and integrating into the traditional business school curricula.
Barriers to Working With Sexual Assault Survivors
Authors: Ullman Sarah E. , Townsend Stephanie M.
Published: April 2007

To better understand barriers service providers may face when advocating for survivors, a study using grounded theory and qualitative, semistructured interviews was conducted of rape victim advocates ( N= 25) working in rape crisis centers in a large metropolitan area. Broader societal attitudes framed and were reflected in institutional responses to victims and in barriers faced by advocates working with survivors. Organizational barriers noted by advocates related to resources, environmental factors, professionalization, and racism. Staff burnout was a major barrier affecting advocates' ability to help survivors. Finally, the most salient direct service barrier was secondary victimization by criminal justice and medical or mental health systems.
The Reporting of Nonresponse Analyses in Survey Research
Authors: Werner Steve , Praxedes Moira , Kim Hyun-Gyu
Published: April 2007

Because survey respondents may not be representative of the population being studied, the external validity of many research conclusions may be of concern. Nonresponse analyses helps address this concern. The purpose of this article is to identify how frequently nonresponse analyses are reported and what variables are related to these rates. The authors find that less than one third of the survey studies include nonresponse analyses. A number of journal and article quality measures and sample characteristics were found to be related to the reporting of nonresponse analyses.
An Attachment Theory Approach to the Short-Term Treatment of a Woman With Borderline Personality Disorder and Comorbid Diagnoses
Authors: Sherry Alissa
Published: April 2007

The current case study highlights the treatment of “Thelma,” a 48-year-old woman of African American and Hispanic descent who was diagnosed with borderline personality disorder (BPD), major depressive disorder, post-traumatic stress disorder, and bulimia. An attachment theory approach was used to elicit core structure change in Thelma's BPD symptoms after traditional modern cognitive approaches proved ineffective. It was hypothesized that treating her Axis II disorder would actually serve to reduce her Axis I symptoms. The attachment approach entailed a shift toward second-order change processes, a shift away from problem-solving approaches, a focus on the quality and intensity of the relationship, and a more relaxed approach to boundary setting in the context of treatment. The approach did appear to reduce many Axis I symptoms including self-mutilation, suicidal ideation, and binging and purging behaviors and appeared to improve her interpersonal functioning.
Girls' Juvenile Justice Uniforms
Authors: Ulasewicz Connie
Published: April 2007

The purpose of this study was to examine how juvenile justice uniforms subjectively and objectively create meaning for the girls who wear them and the staff who observe them. Forty-one incarcerated female youth and 14 teachers and staff members were personally interviewed regarding their definitions of what pieces and parts constituted the prescribed uniform. Their impressions concerning what signs and symbols embody and communicate the cultural reality of the juvenile justice system were recorded. Although for both groups there is an ambiguity regarding the meaning of the uniform and what it communicates, the findings from this research will further the identification and understanding of the special needs of the female incarcerated youth.
Identification of heat shock protein 32 (Hsp32) as a novel survival factor and therapeutic target in neoplastic mast cells
Authors: Kondo Rudin , Gleixner Karoline V. , Mayerhofer Matthias , Vales Anja , Gruze Alexander , Samorapoompichit Puchit , Greish Khaled , Krauth Maria-Theresa , Aichberger Karl J. , Pickl Winfried F. , Esterbauer Harald , Sillaber Christian , Maeda Hiroshi , Valent Peter
Published: April 2007

Systemic mastocytosis (SM) is a myeloid neoplasm characterized by increased survival and accumulation of neoplastic mast cells (MCs). In most patients, the D816V-mutated variant of KIT is detectable. We report here that heat shock protein 32 (Hsp32), also known as heme oxygenase-1 (HO-1), is a novel KIT-inducible survival factor in neoplastic MCs. As assessed by reverse transcription-polymerase chain reaction (RT-PCR), immunocytochemistry, and Western blotting, the KIT D816V+ MC line HMC-1.2 as well as highly enriched primary neoplastic MCs were found to express Hsp32 mRNA and the Hsp32 protein. Moreover, KIT D816V and stem cell factor (SCF)–activated wild-type KIT were found to induce Hsp32 promoter activity, expression of Hsp32 mRNA, and expression of the Hsp32 protein in Ba/F3 cells. Correspondingly, the KIT D816V-targeting drug PKC412 decreased the expression of Hsp32 as well as proliferation/survival in neoplastic MCs. The inhibitory effects of PKC412 on the survival of HMC-1.2 cells were counteracted by the HO-1 inductor hemin or lentiviral-transduced HO-1. Moreover, 2 Hsp32-targeting drugs, pegylated zinc protoporphyrin (PEG-ZnPP) and styrene maleic acid copolymer micelle-encapsulated ZnPP (SMA-ZnPP), were found to inhibit proliferation and to induce apoptosis in neoplastic MCs. Furthermore, both drugs were found to cooperate with PKC412 in producing growth inhibition. Together, these data show that Hsp32 is an important survival factor and interesting new therapeutic target in neoplastic MCs.