Electoral systems and ideological voting

Electoral systems affect vote choice. While a vast literature studies this relationship by examining aggregate-level patterns and focussing on the interparty dimension of electoral rules, the convenience of analyzing this phenomenon by emphasizing the role played by the incentives to cultivate a personal vote generated by the system and matching voters with the party they vote for has been traditionally overlooked. In this article, we offer new evidence that documents the impact of the intraparty dimension of electoral systems on the levels of ideological voting registered in a democracy. Using spatial models of politics and employing data from the five waves of the Comparative Study of Electoral Systems, we find that ideological voting in proportional representation systems is higher when lists are either closed or flexible. Moreover, the results suggest that this effect is slightly amplified in the case of high numbers of district-level candidates

Proof Planning for Automating Hardware Verification

Centre for Intelligent Systems and their ApplicationsIn this thesis we investigate the applicability of proof planning to automate the verification of hardware systems. Proof planning is a meta-level reasoning technique which captures patterns of proof common to a family of theorems. It contributes to the automation of proof by incorporating and extending heuristics found in the Nqthm theorem prover and using them to guide a tactic-based theorem prover in the search for a proof. We have addressed the automation of proof for hardware verification from a proof planning perspective, and have applied the strategies and search control mechanisms of proof planning to generate automatically customised tactics which prove conjectures about the correctness of many types of circuits. The contributions of this research can be summarised as follows: (1) we show by experimentation the applicability of the proof planning ideas to verify automatically hardware designs;(2)we develop and use a methodology based on the concept of proof engineering using proof planning to verify various combinational and sequential circuits which include: arithmetic circuits (adders, subtracters, multipliers, dividers, factorials), data-path components arithmetic logic units shifters, processing units) and a simple microprocessor system; and (3) we contribute to the profiling of the Clam proof planning system by improving its robustness and efficiency in handling large terms and proofs. In verifying hardware, the user formalises a problem by writing the specification, the implementation and the conjecture, using a logic language, and asks Clam to compose a tactic to prove the conjecture. This tactic is then executed by the Oyster prover. To compose a tactic, Clam uses a set of methods which implement the heuristics that specify general-purpose tactics, and AI planning mechanisms. Search is controlled by a type of annotated rewriting called rippling, which controls the selective application of rewrite scaled wave rules. We have extended some of the Clam's methods to verify circuits.The size of the proofs were orders of magnitude larger than the proofs that had been attempted before with proof planning, and are comparable with similar verification proofs obtained by other systems but using fewer lemmas and less interaction. Proof engineering refers to the application of formal proof for system design and verification. We propose a proof engineering methodology which consists of partitioning the automation of formal proof into three different kind of tasks: user, proof and systems tasks.User tasks have to do with formalising a particular verification problem and using a formal tool to obtain a proof. Proof tasks refer to the tuning of proof techniques (e.g. methods and tactics)to help obtain a proof. Systems tasks have to do with the modification of a formal tool system. By making this distinction explicit, proof development is more manageable. We conjecture that our approach is widely applicable and can be integrated into formal verification environments to improve automation facilities, and be utilised to verify commercial and safety-critical hardware systems in industrial settings

A Bayesian Reasoning Framework for On-Line Business Information Systems

We describe a Bayesian Reasoning Framework (BRF) that supports business rule operations for on-line information systems. BRF comprises a three-layer environment with business information systems at the top, a middle-ware Bayesian reasoning server, and a Bayesian reasoning engine at the bottom. The top and middle-ware layers communicate via SOAP/XML protocol, while the middle-ware and bottom layers communicate via a Tag-value protocol that fetches business rules from a central repository. BRF is built as a Bayesian Reasoning Agent and tested in a helpdesk system for assigning advisors to users for trouble-shooting in the operation of business information systems. BRF is modeled following a use-case methodology as well as an inference modeling that uses an assignation template from Common- KADS. The concept, design and implementation of BRF for real-world, on-line business information systems are the main contribution of this research project

Inferencia de parámetros en una red de regulación génica

En el presente trabajo se abordan diferentes tipos de metodologías para la inferencia de parámetros en redes de interacción génetica. Se presentan resutados en base al estudio realizado en una red artificial específica conocida como el Represilador. Primeramente de métodos de muestreo de datos empleados. Posteriormente se presentan diversos tipos de suavizado y su desempeño en base al funcionamiento de la red estudiada. El problema es motivado por un caso de estudio real en líneas celulares de cáncer al cuál se pretende extender el presente análisis

A Knowledge-Based Entrepreneurial Approach for Business Intelligence in Strategic Technologies: Bio-Mems

We propose a knowledge-based entrepreneurial (KBE) approach for business intelligence in strategic technologies at industrial sectors. The KBE approach is at the convergence of business intelligence and knowledge management and is used for advising users in business decisions and potential risks. Our approach comprises both a technology roadmap model as well as a knowledge-based entrepreneurial portal for various technologies. We use the Biological-Micro-Electrical-and- Mechanical-Systems industry (Bio-MEMS) to illustrate the approach. The technology roadmap model identifies the main actors, defines their roles and specifies the issues to be addressed. It handles information about main products, market trends, companies, research centers, application domains, products, standardization, and intellectual properties issues. The portal provides knowledge about the main actors through automation facilities based on digital libraries, searching and knowledge extraction from databases, data-ware houses and the Web. We explain how the KBE is helping Bio-MEMS users in business analysis

TRACKING LEAD (Pb) IN THE ENVIRONMENT OF JAKARA, KANO STATE, NIGERIA

Lead is considered a toxic substance that is already available in environment and has health impacts. The objective of the present study is to track the availability of lead in the environment of Jakara, Kano State, Nigeria. Lead was tracked in water, soil, and vegetables including lettuce, spinach, and onion. Study methodology involved taking random samples from water, soil, and vegetables at Jakara. Samples were prepared and assayed by atomic absorption spectrometry. Study findings showed that the mean concentration of lead in water was 0.115±0.023 mg/l, while it was in soil 2.46 ±0.95 μg/g. The mean concentration of lead in both lettuce and spinach was the same (22.95+ 3.28 mg/kg), and in onion was 19.67 ±3.28 mg/kg . Conclusions: the present study showed that there is a lead contamination of Jakara region by heavy metal (lead). This contamination is evident in water, soil, and vegetables

High Smac/DIABLO expression is associated with early local recurrence of cervical cancer

<p>Abstract</p> <p>Background</p> <p>In a recent pilot report, we showed that Smac/DIABLO mRNA is expressed <it>de novo </it>in a subset of cervical cancer patients. We have now expanded this study and analyzed Smac/DIABLO expression in the primary lesions in 109 cervical cancer patients.</p> <p>Methods</p> <p>We used immunohistochemistry of formalin-fixed, paraffin-embedded tissue sections to analyze Smac/DIABLO expression in the 109 primary lesions. Seventy-eight samples corresponded to epidermoid cervical cancer and 31 to cervical adenocarcinoma. The median follow up was 46.86 months (range 10–186).</p> <p>Results</p> <p>Smac/DIABLO was expressed in more adenocarcinoma samples than squamous tumours (71% vs 50%; p = 0.037). Among the pathological variables, a positive correlation was found between Smac/DIABLO immunoreactivity and microvascular density, a marker for angiogenesis (p = 0.04). Most importantly, Smac/DIABLO immunoreactivity was associated with a higher rate of local recurrence in squamous cell carcinoma (p = 0.002, log rank test). No association was found between Smac/DIABLO and survival rates.</p> <p>Conclusion</p> <p>Smac/DIABLO expression is a potential marker for local recurrence in cervical squamous cell carcinoma patients.</p

Transcriptome Remodeling Contributes to Epidemic Disease Caused by the Human Pathogen Streptococcus pyogenes

For over a century, a fundamental objective in infection biology research has been to understand the molecular processes contributing to the origin and perpetuation of epidemics. Divergent hypotheses have emerged concerning the extent to which environmental events or pathogen evolution dominates in these processes. Remarkably few studies bear on this important issue. Based on population pathogenomic analysis of 1,200 Streptococcus pyogenes type emm89 infection isolates, we report that a series of horizontal gene transfer events produced a new pathogenic genotype with increased ability to cause infection, leading to an epidemic wave of disease on at least two continents. In the aggregate, these and other genetic changes substantially remodeled the transcriptomes of the evolved progeny, causing extensive differential expression of virulence genes and altered pathogen-host interaction, including enhanced immune evasion. Our findings delineate the precise molecular genetic changes that occurred and enhance our understanding of the evolutionary processes that contribute to the emergence and persistence of epidemically successful pathogen clones. The data have significant implications for understanding bacterial epidemics and for translational research efforts to blunt their detrimental effects. IMPORTANCE The confluence of studies of molecular events underlying pathogen strain emergence, evolutionary genetic processes mediating altered virulence, and epidemics is in its infancy. Although understanding these events is necessary to develop new or improved strategies to protect health, surprisingly few studies have addressed this issue, in particular, at the comprehensive population genomic level. Herein we establish that substantial remodeling of the transcriptome of the human-specific pathogen Streptococcus pyogenes by horizontal gene flow and other evolutionary genetic changes is a central factor in precipitating and perpetuating epidemic disease. The data unambiguously show that the key outcome of these molecular events is evolution of a new, more virulent pathogenic genotype. Our findings provide new understanding of epidemic disease.Peer reviewe