Advantages of a modified gastroscope for video-assisted internal mammary artery harvesting.

Instead of standard rigid thoracoscopes, we used a modified gastroscope for video assistance during 12 minimally invasive left internal mammary harvesting. Flexibility and remote control of its last centimeters give to the gastroscope a total freedom of movements, and perfect positioning in every direction. The scope is equipped with cold light, a suction canal and an irrigation canal, which allow for in situ washing without needing to remove it from the thoracic cavity. Thanks to these advantages, vision and lighting are always perfect.

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

On the Segregation of Genetically Modified, Conventional, and Organic Products in European Agriculture: A Multi-market Equilibrium Analysis, October 2005

Evaluating the possible benefits of the introduction of genetically modified (GM) crops must address the issue of consumer resistance as well as the complex regulation that has ensued. In the European Union (EU) this regulation envisions the “co-existence” of GM food with conventional and quality-enhanced products, mandates the labelling and traceability of GM products, and allows only a stringent adventitious presence of GM content in other products. All these elements are brought together within a partial equilibrium model of the EU agricultural food sector. The model comprises conventional, GM and organic food. Demand is modelled in a novel fashion, whereby organic and conventional products are treated as horizontally differentiated but GM products are vertically differentiated (weakly inferior) relative to conventional ones. Supply accounts explicitly for the land constraint at the sector level and for the need for additional resources to produce organic food. Model calibration and simulation allow insights into the qualitative and quantitative effects of the large-scale introduction of GM products in the EU market. We find that the introduction of GM food reduces overall EU welfare, mostly because of the associated need for costly segregation of non-GM products, but the producers of quality-enhanced products actually benefit.

Traducción comentada de “Genetically Modified Organisms (GMOs): Transgenic Crops and Recombinant DNA Technology”

The purpose of this paper is to provide a translation into Spanish of a review articleabout genetically modified organisms (GMOs) entitled “Genetically ModifiedOrganisms (GMOs): Transgenic Crops and Recombinant DNA Technology” publishedby the well-known scientific journal Nature. In a world where English has become thelingua franca when it comes to transferring scientific knowledge and information, itmust be taken into account that not everyone—from scientist to the general public—hasa good enough command of English so that they can feel comfortable enough reading inthis language. Translators are consequently needed resulting from a great demand oftranslation activity into, for example, Spanish. This is the reason why the proposedSpanish translation is followed by a detailed analysis emphasizing the difficulties andproblems that characterize scientific—and also general—translation (i.e. terminology,syntax, semantics, pragmatics, and ideology), for which different approaches as how tosolve them are provided. On the basis of the analysis, it can be concluded thatexperience will be of much help to scientific translators, given that specificterminological knowledge and style requirements must always be born in mind whentranslating in this field. Moreover, this paper is intended to serve as a guide forTranslation students specializing in the field of science and the expectation is to helpthem make the right decisions when it comes to translating. However, it is clear that itcan only be thought of as an introduction that should be completed with further researchand documentation tasks in order to offer a complete reference tool: the ultimatehandbook of scientific translation.

ILS-ESP An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem

From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

Dual-wavelength digital holographic microscopy with sub-nanometer axial accuracy

We present dual-wavelength Digital Holographic Microscopy (DHM) measurements on a certified 8.9 nm high Chromium thin step sample and demonstrate sub-nanometer axial accuracy. We introduce a modified DHM Reference Calibrated Hologram (RCH) reconstruction algorithm taking into account amplitude contributions. By combining this with a temporal averaging procedure and a specific dual-wavelength DHM arrangement, it is shown that specimen topography can be measured with an accuracy, defined as the axial standard deviation, reduced to at least 0.9 nm. Indeed, it is reported that averaging each of the two wavefronts recorded with real-time dual-wavelength DHM can provide up to 30% spatial noise reduction for the given configuration, thanks to their non-correlated nature. ©2008 COPYRIGHT SPIE

Pharmaceutical and Industrial Traits in Genetically Modified Crops: Co-existence with Conventional Agriculture, August 2006

This paper discusses the implications of using genetically modified crops to biomanufacture pharmaceuticals and industrial compounds from the perspective of their co-existence with conventional agriculture. Such plant-made pharmaceuticals and plantmade industrial products rely on exciting scientific and technological breakthroughs and promise new opportunities for the agricultural sector, but they also entail novel risks. The management of the externalities and of the possible unintended economic effects that arise in this context is critical and poses difficult questions for regulators.

Inherently self-calibrating non-Cartesian parallel imaging.

The use of self-calibrating techniques in parallel magnetic resonance imaging eliminates the need for coil sensitivity calibration scans and avoids potential mismatches between calibration scans and subsequent accelerated acquisitions (e.g., as a result of patient motion). Most examples of self-calibrating Cartesian parallel imaging techniques have required the use of modified k-space trajectories that are densely sampled at the center and more sparsely sampled in the periphery. However, spiral and radial trajectories offer inherent self-calibrating characteristics because of their densely sampled center. At no additional cost in acquisition time and with no modification in scanning protocols, in vivo coil sensitivity maps may be extracted from the densely sampled central region of k-space. This work demonstrates the feasibility of self-calibrated spiral and radial parallel imaging using a previously described iterative non-Cartesian sensitivity encoding algorithm.

A polynomial algorithm for special case of the one-machine scheduling problem with time-lags

The standard one-machine scheduling problem consists in schedulinga set of jobs in one machine which can handle only one job at atime, minimizing the maximum lateness. Each job is available forprocessing at its release date, requires a known processing timeand after finishing the processing, it is delivery after a certaintime. There also can exists precedence constraints between pairsof jobs, requiring that the first jobs must be completed beforethe second job can start. An extension of this problem consistsin assigning a time interval between the processing of the jobsassociated with the precedence constrains, known by finish-starttime-lags. In presence of this constraints, the problem is NP-hardeven if preemption is allowed. In this work, we consider a specialcase of the one-machine preemption scheduling problem with time-lags, where the time-lags have a chain form, and propose apolynomial algorithm to solve it. The algorithm consist in apolynomial number of calls of the preemption version of the LongestTail Heuristic. One of the applicability of the method is to obtainlower bounds for NP-hard one-machine and job-shop schedulingproblems. We present some computational results of thisapplication, followed by some conclusions.

Multiparametric brainstem segmentation using a modified multivariate mixture of Gaussians

The human brainstem is a densely packed, complex but highly organised structure. It not only serves as a conduit for long projecting axons conveying motor and sensory information, but also is the location of multiple primary nuclei that control or modulate a vast array of functions, including homeostasis, consciousness, locomotion, and reflexive and emotive behaviours. Despite its importance, both in understanding normal brain function as well as neurodegenerative processes, it remains a sparsely studied structure in the neuroimaging literature. In part, this is due to the difficulties in imaging the internal architecture of the brainstem in vivo in a reliable and repeatable fashion. A modified multivariate mixture of Gaussians (mmMoG) was applied to the problem of multichannel tissue segmentation. By using quantitative magnetisation transfer and proton density maps acquired at 3 T with 0.8 mm isotropic resolution, tissue probability maps for four distinct tissue classes within the human brainstem were created. These were compared against an ex vivo fixated human brain, imaged at 0.5 mm, with excellent anatomical correspondence. These probability maps were used within SPM8 to create accurate individual subject segmentations, which were then used for further quantitative analysis. As an example, brainstem asymmetries were assessed across 34 right-handed individuals using voxel based morphometry (VBM) and tensor based morphometry (TBM), demonstrating highly significant differences within localised regions that corresponded to motor and vocalisation networks. This method may have important implications for future research into MRI biomarkers of pre-clinical neurodegenerative diseases such as Parkinson's disease.

The role of role uncertainty in modified dictator games

We compare behavior in modified dictator games with and without role uncertainty. Subjectschoose between a selfish action, a costly surplus creating action (altruistic behavior) and acostly surplus destroying action (spiteful behavior). While costly surplus creating actions are themost frequent under role uncertainty (64%), selfish actions become the most frequent withoutrole uncertainty (69%). Also, the frequency of surplus destroying choices is negligible with roleuncertainty (1%) but not so without it (11%). A classification of subjects into four differenttypes of interdependent preferences (Selfish, Social Welfare maximizing, Inequity Averse andCompetitive) shows that the use of role uncertainty overestimates the prevalence of SocialWelfare maximizing preferences in the subject population (from 74% with role uncertainty to21% without it) and underestimates Selfish and Inequity Averse preferences. An additionaltreatment, in which subjects undertake an understanding test before participating in theexperiment with role uncertainty, shows that the vast majority of subjects (93%) correctlyunderstand the payoff mechanism with role uncertainty, but yet surplus creating actions weremost frequent. Our results warn against the use of role uncertainty in experiments that aim tomeasure the prevalence of interdependent preferences.

On the efficiency and sensitivity of a pyramidal classification algorithm

In this paper we propose a Pyramidal Classification Algorithm,which together with an appropriate aggregation index producesan indexed pseudo-hierarchy (in the strict sense) withoutinversions nor crossings. The computer implementation of thealgorithm makes it possible to carry out some simulation testsby Monte Carlo methods in order to study the efficiency andsensitivity of the pyramidal methods of the Maximum, Minimumand UPGMA. The results shown in this paper may help to choosebetween the three classification methods proposed, in order toobtain the classification that best fits the original structureof the population, provided we have an a priori informationconcerning this structure.