Generating unconstrained two-dimensional non-guillotine cutting patterns by a Recursive Partitioning Algorithm

In this study, a dynamic programming approach to deal with the unconstrained two-dimensional non-guillotine cutting problem is presented. The method extends the recently introduced recursive partitioning approach for the manufacturer's pallet loading problem. The approach involves two phases and uses bounds based on unconstrained two-staged and non-staged guillotine cutting. The method is able to find the optimal cutting pattern of a large number of pro blem instances of moderate sizes known in the literature and a counterexample for which the approach fails to find known optimal solutions was not found. For the instances that the required computer runtime is excessive, the approach is combined with simple heuristics to reduce its running time. Detailed numerical experiments show the reliability of the method. Journal of the Operational Research Society (2012) 63, 183-200. doi: 10.1057/jors.2011.6 Published online 17 August 2011

Generating multiple random exams using mathematica package and LATEX

[EN]In the framework of the European Higher Education Area, the assessment has been one of the most important aspects considered. In the Spanish Universities, one of the main differences with regard to the previous system is the incorporation of the continuous assessment to the evaluation process that is understood in several ways depending on the Universities, the courses and the lecturers. Focus on our context, a course of Mathematics of the first academic year in the Faculty of Business Administration at the University of Las Palmas de Gran Canaria (Spain), the continuous assessment has brought the preparation of a large amount of different tests to evaluate the students enrolled in it, therefore the incorporation of new tools and skills in order to make the teaching–learning process easier and more dynamic has become a need mainly in those degrees with a large number of students as the case we consider here. In this work we provide an efficient and effective way to elaborate random multiple-choice examina tion tests (although essay exams are also possible) by using Mathematica package and LATEXin order to make easier to the lectures the preparation of a large number of mid-term tests for a large number of students.

Markov Constraints for Generating Texts with Style

This thesis addresses the issue of generating texts in the style of an existing author, that also satisfy structural constraints imposed by the genre of the text. Although Markov processes are known to be suitable for representing style, they are difficult to control in order to satisfy non-local properties, such as structural constraints, that require long distance modeling. The framework of Constrained Markov Processes allows to precisely generate texts that are consistent with a corpus, while being controllable in terms of rhymes and meter. Controlled Markov processes consist in reformulating Markov processes in the context of constraint satisfaction. The thesis describes how to represent stylistic and structural properties in terms of constraints in this framework and how this approach can be used for the generation of lyrics in the style of 60 differents authors An evaluation of the desctibed method is provided by comparing it to both pure Markov and pure constraint-based approaches. Finally the thesis describes the implementation of an augmented text editor, called Perec. Perec is intended to improve creativity, by helping the user to write lyrics and poetry, exploiting the techniques presented so far.

Generating vegetation-spectra as a basis for global monitoring of annual vegetation cycles using DOAS satellite observations

Vegetation-cycles are of general interest for many applications. Be it for harvest-predictions, global monitoring of climate-change or as input to atmospheric models.rnrnCommon Vegetation Indices use the fact that for vegetation the difference between Red and Near Infrared reflection is higher than in any other material on Earth’s surface. This gives a very high degree of confidence for vegetation-detection.rnrnThe spectrally resolving data from the GOME and SCIAMACHY satellite-instrumentsrnprovide the chance to analyse finer spectral features throughout the Red and Near Infrared spectrum using Differential Optical Absorption Spectroscopy (DOAS). Although originally developed to retrieve information on atmospheric trace gases, we use it to gain information on vegetation. Another advantage is that this method automatically corrects for changes in the atmosphere. This renders the vegetation-information easily comparable over long time-spans.rnThe first results using previously available reference spectra were encouraging, but also indicated substantial limitations of the available reflectance spectra of vegetation. This was the motivation to create new and more suitable vegetation reference spectra within this thesis.rnThe set of reference spectra obtained is unique in its extent and also with respect to its spectral resolution and the quality of the spectral calibration. For the first time, this allowed a comprehensive investigation of the high-frequency spectral structures of vegetation reflectance and of their dependence on the viewing geometry.rnrnThe results indicate that high-frequency reflectance from vegetation is very complex and highly variable. While this is an interesting finding in itself, it also complicates the application of the obtained reference spectra to the spectral analysis of satellite observations.rnrnThe new set of vegetation reference spectra created in this thesis opens new perspectives for research. Besides refined satellite analyses, these spectra might also be used for applications on other platforms such as aircraft. First promising studies have been presented in this thesis, but the full potential for the remote sensing of vegetation from satellite (or aircraft) could bernfurther exploited in future studies.

Synthetic-echo time postprocessing technique for generating images with variable T2-weighted contrast: diagnosis of meniscal and cartilage abnormalities of the knee

To assess the feasibility and accuracy of a synthetic-echo time (TE) magnetic resonance (MR) postprocessing technique for the diagnostic evaluation of abnormalities of menisci and articular cartilage in the knee.

500 ml of blood loss does not decrease non-invasive tissue oxygen saturation (StO2) as measured by near infrared spectroscopy - A hypothesis generating pilot study in healthy adult women

Background The goal when resuscitating trauma patients is to achieve adequate tissue perfusion. One parameter of tissue perfusion is tissue oxygen saturation (StO2), as measured by near infrared spectroscopy. Using a commercially available device, we investigated whether clinically relevant blood loss of 500 ml in healthy volunteers can be detected by changes in StO2 after a standardized ischemic event. Methods We performed occlusion of the brachial artery for 3 minutes in 20 healthy female blood donors before and after blood donation. StO2 and total oxygenated tissue hemoglobin (O2Hb) were measured continuously at the thenar eminence. 10 healthy volunteers were assessed in the same way, to examine whether repeated vascular occlusion without blood donation exhibits time dependent effects. Results Blood donation caused a substantial decrease in systolic blood pressure, but did not affect resting StO2 and O2Hb values. No changes were measured in the blood donor group in the reaction to the vascular occlusion test, but in the control group there was an increase in the O2Hb rate of recovery during the reperfusion phase. Conclusion StO2 measured at the thenar eminence seems to be insensitive to blood loss of 500 ml in this setting. Probably blood loss greater than this might lead to detectable changes guiding the treating physician. The exact cut off for detectable changes and the time effect on repeated vascular occlusion tests should be explored further. Until now no such data exist.

Equality of P-partition Generating Functions

To every partially ordered set (poset), one can associate a generating function, known as the P-partition generating function. We find necessary conditions and sufficient conditions for two posets to have the same P-partition generating function. We define the notion of a jump sequence for a labeled poset and show that having equal jumpsequences is a necessary condition for generating function equality. We also develop multiple ways of modifying posets that preserve generating function equality. Finally, we are able to give a complete classification of equalities among partially ordered setswith exactly two linear extensions.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

Dystrophic cardiomyopathy: amplification of cellular damage by Ca2+ signalling and reactive oxygen species-generating pathways

AIMS: Cardiac myopathies are the second leading cause of death in patients with Duchenne and Becker muscular dystrophy, the two most common and severe forms of a disabling striated muscle disease. Although the genetic defect has been identified as mutations of the dystrophin gene, very little is known about the molecular and cellular events leading to progressive cardiac muscle damage. Dystrophin is a protein linking the cytoskeleton to a complex of transmembrane proteins that interact with the extracellular matrix. The fragility of the cell membrane resulting from the lack of dystrophin is thought to cause an excessive susceptibility to mechanical stress. Here, we examined cellular mechanisms linking the initial membrane damage to the dysfunction of dystrophic heart. METHODS AND RESULTS: Cardiac ventricular myocytes were enzymatically isolated from 5- to 9-month-old dystrophic mdx and wild-type (WT) mice. Cells were exposed to mechanical stress, applied as osmotic shock. Stress-induced cytosolic and mitochondrial Ca(2+) signals, production of reactive oxygen species (ROS), and mitochondrial membrane potential were monitored with confocal microscopy and fluorescent indicators. Pharmacological tools were used to scavenge ROS and to identify their possible sources. Osmotic shock triggered excessive cytosolic Ca(2+) signals, often lasting for several minutes, in 82% of mdx cells. In contrast, only 47% of the WT cardiomyocytes responded with transient and moderate intracellular Ca(2+) signals. On average, the reaction was 6-fold larger in mdx cells. Removal of extracellular Ca(2+) abolished these responses, implicating Ca(2+) influx as a trigger for abnormal Ca(2+) signalling. Our further experiments revealed that osmotic stress in mdx cells produced an increase in ROS production and mitochondrial Ca(2+) overload. The latter was followed by collapse of the mitochondrial membrane potential, an early sign of cell death. CONCLUSION: Overall, our findings reveal that excessive intracellular Ca(2+) signals and ROS generation link the initial sarcolemmal injury to mitochondrial dysfunctions. The latter possibly contribute to the loss of functional cardiac myocytes and heart failure in dystrophy. Understanding the sequence of events of dystrophic cell damage and the deleterious amplification systems involved, including several positive feed-back loops, may allow for a rational development of novel therapeutic strategies.

GENERATING PLANS IN CONCURRENT, PROBABILISTIC, OVER-SUBSCRIBED DOMAINS

Planning in realistic domains typically involves reasoning under uncertainty, operating under time and resource constraints, and finding the optimal subset of goals to work on. Creating optimal plans that consider all of these features is a computationally complex, challenging problem. This dissertation develops an AO* search based planner named CPOAO* (Concurrent, Probabilistic, Over-subscription AO*) which incorporates durative actions, time and resource constraints, concurrent execution, over-subscribed goals, and probabilistic actions. To handle concurrent actions, action combinations rather than individual actions are taken as plan steps. Plan optimization is explored by adding two novel aspects to plans. First, parallel steps that serve the same goal are used to increase the plan’s probability of success. Traditionally, only parallel steps that serve different goals are used to reduce plan execution time. Second, actions that are executing but are no longer useful can be terminated to save resources and time. Conventional planners assume that all actions that were started will be carried out to completion. To reduce the size of the search space, several domain independent heuristic functions and pruning techniques were developed. The key ideas are to exploit dominance relations for candidate action sets and to develop relaxed planning graphs to estimate the expected rewards of states. This thesis contributes (1) an AO* based planner to generate parallel plans, (2) domain independent heuristics to increase planner efficiency, and (3) the ability to execute redundant actions and to terminate useless actions to increase plan efficiency.

PyGirl Generating Whole-System VMs from high-level models using PyPy

Virtual machines emulating hardware devices are generally implemented in low-level languages and using a low-level style for performance reasons. This trend results in largely difficult to understand, difficult to extend and unmaintainable systems. As new general techniques for virtual machines arise, it gets harder to incorporate or test these techniques because of early design and optimization decisions. In this paper we show how such decisions can be postponed to later phases by separating virtual machine implementation issues from the high-level machine-specific model. We construct compact models of whole-system VMs in a high-level language, which exclude all low-level implementation details. We use the pluggable translation toolchain PyPy to translate those models to executables. During the translation process, the toolchain reintroduces the VM implementation and optimization details for specific target platforms. As a case study we implement an executable model of a hardware gaming device. We show that our approach to VM building increases understandability, maintainability and extendability while preserving performance.

PyGirl: Generating Whole-System VMs from High-Level Prototypes Using PyPy

Virtual machines (VMs) emulating hardware devices are generally implemented in low-level languages for performance reasons. This results in unmaintainable systems that are difficult to understand. In this paper we report on our experience using the PyPy toolchain to improve the portability and reduce the complexity of whole-system VM implementations. As a case study we implement a VM prototype for a Nintendo Game Boy, called PyGirl, in which the high-level model is separated from low-level VM implementation issues. We shed light on the process of refactoring from a low-level VM implementation in Java to a high-level model in RPython. We show that our whole-system VM written with PyPy is significantly less complex than standard implementations, without substantial loss in performance.