Bitext alignment: building and evaluating a bilingual corpus and translation memory of academic course descriptions

Following the internationalization of contemporary higher education, academic institutions based in non-English speaking countries are increasingly urged to produce contents in English to address international prospective students and personnel, as well as to increase their attractiveness. The demand for English translations in the institutional academic domain is consequently increasing at a rate exceeding the capacity of the translation profession. Resources for assisting non-native authors and translators in the production of appropriate texts in L2 are therefore required in order to help academic institutions and professionals streamline their translation workload. Some of these resources include: (i) parallel corpora to train machine translation systems and multilingual authoring tools; and (ii) translation memories for computer-aided tools. The purpose of this study is to create and evaluate reference resources like the ones mentioned in (i) and (ii) through the automatic sentence alignment of a large set of Italian and English as a Lingua Franca (ELF) institutional academic texts given as equivalent but not necessarily parallel (i.e. translated). In this framework, a set of aligning algorithms and alignment tools is examined in order to identify the most profitable one(s) in terms of accuracy and time- and cost-effectiveness. In order to determine the text pairs to align, a sample is selected according to document length similarity (characters) and subsequently evaluated in terms of extent of noisiness/parallelism, alignment accuracy and content leverageability. The results of these analyses serve as the basis for the creation of an aligned bilingual corpus of academic course descriptions, which is eventually used to create a translation memory in TMX format.

THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS

The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the principles of neural science provide an instance of how biological processes may inspire novel methods in mathematical modeling and engineering. The application ofmathematical models towards understanding neural signals and systems represents a vibrant field of research that has spanned over half a century. During this period, multiple approaches to neuronal modeling have been adopted, and each approach is adept at elucidating a specific aspect of nervous system function. Thus while bio-physical models have strived to comprehend the dynamics of actual physical processes occurring within a nerve cell, the phenomenological approach has conceived models that relate the ionic properties of nerve cells to transitions in neural activity. Further-more, the field of neural networks has endeavored to explore how distributed parallel processing systems may become capable of storing memory. Through this project, we strive to explore how some of the insights gained from biophysical neuronal modeling may be incorporated within the field of neural net-works. We specifically study the capabilities of a simple neural model, the Resonate-and-Fire (RAF) neuron, whose derivation is inspired by biophysical neural modeling. While reflecting further biological plausibility, the RAF neuron is also analytically tractable, and thus may be implemented within neural networks. In the following thesis, we provide a brief overview of the different approaches that have been adopted towards comprehending the properties of nerve cells, along with the framework under which our specific neuron model relates to the field of neuronal modeling. Subsequently, we explore some of the time-dependent neurocomputational capabilities of the RAF neuron, and we utilize the model to classify logic gates, and solve the classic XOR problem. Finally we explore how the resonate-and-fire neuron may be implemented within neural networks, and how such a network could be adapted through the temporal backpropagation algorithm.

Maternal and Postweaning High-Fat Diets Disturb Hippocampal Gene Expression, Learning, and Memory Function

We tested the hypothesis that excess saturated fat consumption during pregnancy, lactation, and/or postweaning alters the expression of genes mediating hippocampal synaptic efficacy and impairs spatial learning and memory in adulthood. Dams were fed control chow or a diet high in saturated fat before mating, during pregnancy, and into lactation. Offspring were weaned to either standard chow or a diet high in saturated fat. The Morris Water Maze was used to evaluate spatial learning and memory. Open field testing was used to evaluate motor activity. Hippocampal gene expression in adult males was measured using RT-PCR and ELISA. Offspring from high fat-fed dams took longer, swam farther, and faster to try and find the hidden platform during the 5-day learning period. Control offspring consuming standard chow spent the most time in memory quadrant during the probe test. Offspring from high fat-fed dams consuming excess saturated fat spent the least. The levels of mRNA and protein for brain-derived neurotrophic factor and activity-regulated cytoskeletal-associated protein were significantly decreased by maternal diet effects. Nerve growth factor mRNA and protein levels were significantly reduced in response to both maternal and postweaning high-fat diets. Expression levels for the N-methyl-D-aspartate receptor (NMDA) receptor subunit NR2B as well as synaptophysin were significantly decreased in response to both maternal and postweaning diets. Synaptotagmin was significantly increased in offspring from high fat-fed dams. These data support the hypothesis that exposure to excess saturated fat during hippocampal development is associated with complex patterns of gene expression and deficits in learning and memory.

Developmental changes of BOLD signal correlations with global human EEG power and synchronization during working memory

In humans, theta band (5-7 Hz) power typically increases when performing cognitively demanding working memory (WM) tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent) signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-)dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and synchronization and that these opposite correlations with different distributions undergo similar and significant neuronal developments with brain maturation.

Memory of childbirth in the second year: the long-term effect of a negative birth experience and its modulation by the perceived intranatal relationship with caregivers

OBJECTIVE: To assess the memory of various subdimensions of the birth experience in the second year postpartum, and to identify women in the first weeks postpartum at risk of developing a long-term negative memory. DESIGN, METHOD, OUTCOME MEASURES: New mothers' birth experience (BE) was assessed 48-96 hours postpartum (T1) by means of the SIL-Ger and the BBCI (perception of intranatal relationships); early postnatal adjustment (week 3 pp: T1(bis)) was also assessed. Then, four subgroups of women were defined by means of a cluster-analysis, integrating the T1/T1(bis) variables. To evaluate the memory of the BE, the SIL-Ger was again applied in the second year after childbirth (T2). First, the ratings of the SIL-Ger dimensions of T1 were compared to those at T2 in the whole sample. Then, the four subgroups were compared with respect to their ratings of the birth experience at T2 (correlations, ANOVAs and t-tests). RESULTS: In general, fulfillment, emotional adaptation, physical discomfort, and anxiety improve spontaneously over the first year postpartum, whereas in negative emotional experience, control, and time-going-slowly no shift over time is observed. However, women with a negative overall birth experience and a low level of perceived intranatal relationship at T1 run a high risk of retaining a negative memory in all of the seven subdimensions of the birth experience. CONCLUSIONS: Women at risk of developing a negative long-term memory of the BE can be identified at the time of early postpartum, when the overall birth experience and the perceived intranatal relationship are taken into account.

Self-Reported Memory Symptoms with Coronary Artery Disease: A Prospective of CABG Patients and Nonsurgical Controls

Background. Subjective memory complaints are common after coronary artery bypass grafting (CABG), but previous studies have concluded that such symptoms are more closely associated with depressed mood than objective cognitive dysfunction. We compared the incidence of self-reported memory symptoms at 3 and 12 months after CABG with that of a control group of patients with comparable risk factors for coronary artery disease but without surgery. Methods. Patients undergoing CABG (n = 140) and a demographically similar nonsurgical control group with coronary artery disease (n = 92) were followed prospectively at 3 and 12 months. At each follow-up time, participants were asked about changes since the previous evaluation in areas of memory, calculations, reading, and personality. A Functional Status Questionnaire (FSQ) and self-report measure of symptoms of depression (CES-D) were also completed. Results. The frequency of self-reported changes in memory, personality, and reading at 3 months was significantly higher among CABG patients than among nonsurgical controls. By contrast, there were no differences in the frequency of self-reported symptoms relating to calculations or overall rating of functional status. After adjusting for a measure of depression (CES-D rating score), the risk for self-reported memory changes remained nearly 5 times higher among the CABG patients than control subjects. The relative risk of developing new self-reported memory symptoms between 3 and 12 months was 2.5 times higher among CABG patients than among nonsurgical controls (CI 1.24 – 5.02), and the overall prevalence of memory symptoms at 12 months was also higher among CABG patients (39%) than controls (14%). Conclusions. The frequency of self-reported memory symptoms 3 and 12 months after baseline is significantly higher among CABG patients than control patients with comparable risk factors for coronary and cerebrovascular disease. These differences could not be accounted for by symptoms of depression. The self-reported cognitive symptoms appear to be relatively specific for memory, and may reflect aspects of memory functioning that are not captured by traditional measures of new verbal learning and memory. The etiology of these self-reported memory symptoms remains unclear, but our findings as well as those of others, may implicate factors other than cardiopulmonary bypass itself.

Low awareness of transient ischemic attacks and risk factors of stroke in a Swiss urban community

BACKGROUND AND PURPOSE: Time delays from stroke onset to arrival at the hospital are the main obstacles for widespread use of thrombolysis. In order to decrease the delays, educational campaigns try to inform the general public how to act optimally in case of stroke. To determine the content of such a campaign, we assessed the stroke knowledge in our population. METHODS: The stroke knowledge was studied by means of a closed-ended questionnaire. 422 randomly chosen inhabitants of Bern, Switzerland, were interviewed. RESULTS: The knowledge of stroke warning signs (WS) was classified as good in 64.7%. A good knowledge of stroke risk factors (RF) was noted in 6.4%. 4.2% knew both the WS and the RF of stroke indicating a very good global knowledge of stroke. Only 8.3% recognized TIA as symptoms of stroke resolving within 24 hours, and only 2.8% identified TIA as a disease requiring immediate medical help. In multivariate analysis being a woman, advancing age, and having an afflicted relative were associated with a good knowledge of WS (p = 0.048, p < 0.001 and p = 0.043). Good knowledge of RF was related to university education (p < 0.001). The good knowledge of TIA did not depend on age, sex, level of education or having an afflicted relative. CONCLUSIONS: The study brings to light relevant deficits of stroke knowledge in our population. A small number of participants could recognize TIA as stroke related symptoms resolving completely within 24 hours. Only a third of the surveyed persons would seek immediate medical help in case of TIA. The information obtained will be used in the development of future educational campaigns.

Reducing main memory access latency through SDRAM address mapping techniques and access reordering mechanisms

As the performance gap between microprocessors and memory continues to increase, main memory accesses result in long latencies which become a factor limiting system performance. Previous studies show that main memory access streams contain significant localities and SDRAM devices provide parallelism through multiple banks and channels. These locality and parallelism have not been exploited thoroughly by conventional memory controllers. In this thesis, SDRAM address mapping techniques and memory access reordering mechanisms are studied and applied to memory controller design with the goal of reducing observed main memory access latency. The proposed bit-reversal address mapping attempts to distribute main memory accesses evenly in the SDRAM address space to enable bank parallelism. As memory accesses to unique banks are interleaved, the access latencies are partially hidden and therefore reduced. With the consideration of cache conflict misses, bit-reversal address mapping is able to direct potential row conflicts to different banks, further improving the performance. The proposed burst scheduling is a novel access reordering mechanism, which creates bursts by clustering accesses directed to the same rows of the same banks. Subjected to a threshold, reads are allowed to preempt writes and qualified writes are piggybacked at the end of the bursts. A sophisticated access scheduler selects accesses based on priorities and interleaves accesses to maximize the SDRAM data bus utilization. Consequentially burst scheduling reduces row conflict rate, increasing and exploiting the available row locality. Using a revised SimpleScalar and M5 simulator, both techniques are evaluated and compared with existing academic and industrial solutions. With SPEC CPU2000 benchmarks, bit-reversal reduces the execution time by 14% on average over traditional page interleaving address mapping. Burst scheduling also achieves a 15% reduction in execution time over conventional bank in order scheduling. Working constructively together, bit-reversal and burst scheduling successfully achieve a 19% speedup across simulated benchmarks.

Impact of working memory training on memory performance in old-old adults

Memory impairments constitute an increasing objective and subjective problem with advancing age. The aim of the present study was to investigate the impact of working memory training on memory performance. The authors trained a sample of 80-year-old adults twice weekly over a time period of 3 months. Participants were tested on 4 different memory measures before, immediately after, and 1 year after training completion. The authors found overall increased memory performance in the experimental group compared to an active control group immediately after training completion. This increase was especially pronounced in visual working memory performance and, to a smaller degree, also in visual episodic memory. No group differences were found 1 year after training completion. The results indicate that even in old?old adults, brain plasticity is strong enough to result in transfer effects, that is, performance increases in tasks that were not trained during the intervention.

Memory resource balancing for virtualized computing

Virtualization has become a common abstraction layer in modern data centers. By multiplexing hardware resources into multiple virtual machines (VMs) and thus enabling several operating systems to run on the same physical platform simultaneously, it can effectively reduce power consumption and building size or improve security by isolating VMs. In a virtualized system, memory resource management plays a critical role in achieving high resource utilization and performance. Insufficient memory allocation to a VM will degrade its performance dramatically. On the contrary, over-allocation causes waste of memory resources. Meanwhile, a VM’s memory demand may vary significantly. As a result, effective memory resource management calls for a dynamic memory balancer, which, ideally, can adjust memory allocation in a timely manner for each VM based on their current memory demand and thus achieve the best memory utilization and the optimal overall performance. In order to estimate the memory demand of each VM and to arbitrate possible memory resource contention, a widely proposed approach is to construct an LRU-based miss ratio curve (MRC), which provides not only the current working set size (WSS) but also the correlation between performance and the target memory allocation size. Unfortunately, the cost of constructing an MRC is nontrivial. In this dissertation, we first present a low overhead LRU-based memory demand tracking scheme, which includes three orthogonal optimizations: AVL-based LRU organization, dynamic hot set sizing and intermittent memory tracking. Our evaluation results show that, for the whole SPEC CPU 2006 benchmark suite, after applying the three optimizing techniques, the mean overhead of MRC construction is lowered from 173% to only 2%. Based on current WSS, we then predict its trend in the near future and take different strategies for different prediction results. When there is a sufficient amount of physical memory on the host, it locally balances its memory resource for the VMs. Once the local memory resource is insufficient and the memory pressure is predicted to sustain for a sufficiently long time, a relatively expensive solution, VM live migration, is used to move one or more VMs from the hot host to other host(s). Finally, for transient memory pressure, a remote cache is used to alleviate the temporary performance penalty. Our experimental results show that this design achieves 49% center-wide speedup.

Visual vector inversion during memory antisaccades--a TMS study

In the memory antisaccade task, subjects are instructed to look at an imaginary point precisely at the opposite side of a peripheral visual stimulus presented short time previously. To perform this task accurately, the visual vector, i.e., the distance between a central fixation point and the peripheral stimulus, must be inverted from one visual hemifield to the other. Recent data in humans and monkeys suggest that the posterior parietal cortex (PPC) might be critically involved in the process of visual vector inversion. In the present study, we investigated the temporal dynamics of visual vector inversion in the human PPC by using transcranial magnetic stimulation (TMS). In six healthy subjects, single pulse TMS was applied over the right PPC during a memory antisaccade task at four different time intervals: 100 ms, 217 ms, 333 ms, or 450 ms after target onset. The results indicate that for rightward antisaccades, i.e., when the visual target was presented in the left screen-half, TMS had a significant effect on saccade gain when applied 100 ms after target onset, but not later. For leftward antisaccades, i.e., when the visual target was presented in the right screen-half, a significant TMS effect on gain was found for the 333 ms and 450 ms conditions, but not for the earlier ones. This double dissociation of saccade gain suggests that the initial process of vector inversion can be disrupted 100 ms after onset of the visual stimulus and that TMS interfered with motor saccade planning based on an inversed vector signal at 333 ms and 450 ms after stimulus onset.

Using transcranial magnetic stimulation to probe decision-making and memory

Decision-making and memory are fundamental processes for successful human behaviour. For eye movements, the frontal eye fields (FEF), the supplementary eye fields (SEF), the dorsolateral prefrontal cortex (DLPFC), the ventrolateral frontal cortex and the anterior cingulum are important for these cognitive processes. The online approach of transcranial magnetic stimulation (TMS), i.e., the application of magnetic pulses during planning and performance of saccades, allows interfering specifically with information processing of the stimulated region at a very specific time interval (chronometry of cortical processing). The paper presents studies, which showed the different roles of the FEF and DLPFC in antisaccade control. The critical time interval of DLPFC control seems to be before target onset since TMS significantly increased the percentage of antisaccade errors at that time interval. The FEF seems to be important for the triggering of correct antisaccades. Bilateral stimulation of the DLPFC could demonstrate parallel information-processing transfer in spatial working memory during memory-guided saccades.

Practical Object-Oriented Back-in-Time Debugging

Back-in-time debuggers are extremely useful tools for identifying the causes of bugs, as they allow us to inspect the past states of objects no longer present in the current execution stack. Unfortunately the "omniscient" approaches that try to remember all previous states are impractical because they either consume too much space or they are far too slow. Several approaches rely on heuristics to limit these penalties, but they ultimately end up throwing out too much relevant information. In this paper we propose a practical approach to back-in-time debugging that attempts to keep track of only the relevant past data. In contrast to other approaches, we keep object history information together with the regular objects in the application memory. Although seemingly counter-intuitive, this approach has the effect that past data that is not reachable from current application objects (and hence, no longer relevant) is automatically garbage collected. In this paper we describe the technical details of our approach, and we present benchmarks that demonstrate that memory consumption stays within practical bounds. Furthermore since our approach works at the virtual machine level, the performance penalty is significantly better than with other approaches.

Linking brain connectivity across different time scales with electroencephalogram, functional magnetic resonance imaging, and diffusion tensor imaging

Structural and functional connectivity are intrinsic properties of the human brain and represent the amount of cognitive capacities of individual subjects. These connections are modulated due to development, learning, and disease. Momentary adaptations in functional connectivity alter the structural connections, which in turn affect the functional connectivity. Thus, structural and functional connectivity interact on a broad timescale. In this study, we aimed to explore distinct measures of connectivity assessed by functional magnetic resonance imaging and diffusion tensor imaging and their association to the dominant electroencephalogram oscillatory property at rest: the individual alpha frequency (IAF). We found that in 21 healthy young subjects, small intraindividual temporal IAF fluctuations were correlated to increased blood oxygenation level-dependent signal in brain areas associated to working memory functions and to the modulation of attention. These areas colocalized with functionally connected networks supporting the respective functions. Furthermore, subjects with higher IAF show increased fractional anisotropy values in fascicles connecting the above-mentioned areas and networks. Hence, due to a multimodal approach a consistent functionally and structurally connected network related to IAF was observed.