Predicting conversion to dementia in a memory clinic: A standard clinical approach compared with an empirically defined clustering method (latent profile analysis) for mild cognitive impairment subtyping

Introduction
Mild cognitive impairment (MCI) has clinical value in its ability to predict later dementia. A better understanding of cognitive profiles can further help delineate who is most at risk of conversion to dementia. We aimed to (1) examine to what extent the usual MCI subtyping using core criteria corresponds to empirically defined clusters of patients (latent profile analysis [LPA] of continuous neuropsychological data) and (2) compare the two methods of subtyping memory clinic participants in their prediction of conversion to dementia.

Methods
Memory clinic participants (MCI, n = 139) and age-matched controls (n = 98) were recruited. Participants had a full cognitive assessment, and results were grouped (1) according to traditional MCI subtypes and (2) using LPA. MCI participants were followed over approximately 2 years after their initial assessment to monitor for conversion to dementia.

Results
Groups were well matched for age and education. Controls performed significantly better than MCI participants on all cognitive measures. With the traditional analysis, most MCI participants were in the amnestic multidomain subgroup (46.8%) and this group was most at risk of conversion to dementia (63%). From the LPA, a three-profile solution fit the data best. Profile 3 was the largest group (40.3%), the most cognitively impaired, and most at risk of conversion to dementia (68% of the group).

Discussion
LPA provides a useful adjunct in delineating MCI participants most at risk of conversion to dementia and adds confidence to standard categories of clinical inference.

On the statistical memory architecture exploration and optimization

The worsening of process variations and the consequent increased spreads in circuit performance and consumed power hinder the satisfaction of the targeted budgets and lead to yield loss. Corner based design and adoption of design guardbands might limit the yield loss. However, in many cases such methods may not be able to capture the real effects which might be way better than the predicted ones leading to increasingly pessimistic designs. The situation is even more severe in memories which consist of substantially different individual building blocks, further complicating the accurate analysis of the impact of variations at the architecture level leaving many potential issues uncovered and opportunities unexploited. In this paper, we develop a framework for capturing non-trivial statistical interactions among all the components of a memory/cache. The developed tool is able to find the optimum memory/cache configuration under various constraints allowing the designers to make the right choices early in the design cycle and consequently improve performance, energy, and especially yield. Our, results indicate that the consideration of the architectural interactions between the memory components allow to relax the pessimistic access times that are predicted by existing techniques.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

Evidence of syntactic working memory usage in MEG data

While reading times are often used to measure working memory load, frequency effects (such as surprisal or n-gram frequencies) also have strong confounding effects on reading times. This work uses a naturalistic audio corpus with magnetoencephalographic (MEG) annotations to measure working memory load during sentence processing. Alpha oscillations in posterior regions of the brain have been found to correlate with working memory load in non-linguistic tasks (Jensen et al., 2002), and the present study extends these findings to working memory load caused by syntactic center embeddings. Moreover, this work finds that frequency effects in naturally-occurring stimuli do not significantly contribute to neural oscillations in any frequency band, which suggests that many modeling claims could be tested on this sort of data even without controlling for frequency effects.

Historical Dialogue and Memory in Policing Change: the Case of the Police in Northern Ireland

This paper explores the complex relationship between organisational change and historical dialogue in transitional societies. Using the policing reform process in Northern Ireland as an example, the paper does three things: the first is to explore the ways in which policing changes were understood within the policing organisation and ‘community’ itself. The second is to make use of a processual approach, privileging the interactions of context, process and time within the analysis. Thirdly, it considers this perspective through the relatively new lens of ‘historical dialogue’: understood here as a conversation and an oscillation between the past, present and future through reflections on individual and collective memory. Through this analysis, we consider how members’ understandings of a difficult past (and their roles in it) facilitated and/or impeded the organisations change process. Drawing on a range of interviews with previous and current members of the organisation, this paper sheds new light on how institutions deal with and understand the past as they experience organisational change within the a wider societal transition from conflict to non-violence.

Memory-centric VDF Graph Transformations for Practical FPGA Implementation

Realising memory intensive applications such as image and video processing on FPGA requires creation of complex, multi-level memory hierarchies to achieve real-time performance; however commerical High Level Synthesis tools are unable to automatically derive such structures and hence are unable to meet the demanding bandwidth and capacity constraints of these applications. Current approaches to solving this problem can only derive either single-level memory structures or very deep, highly inefficient hierarchies, leading in either case to one or more of high implementation cost and low performance. This paper presents an enhancement to an existing MC-HLS synthesis approach which solves this problem; it exploits and eliminates data duplication at multiple levels levels of the generated hierarchy, leading to a reduction in the number of levels and ultimately higher performance, lower cost implementations. When applied to synthesis of C-based Motion Estimation, Matrix Multiplication and Sobel Edge Detection applications, this enables reductions in Block RAM and Look Up Table (LUT) cost of up to 25%, whilst simultaneously increasing throughput.

Wounded Spaces: When Planning Degraded Cairo’s Urban Memory

This paper examines the position of planning practices operated under precise guidelines for displaying modernity. Cultivating the spatial qualities of Cairo since the 1970s has unveiled centralised ideologies and systems of governance and economic incentives. I present a discussion of the wounds that result from the inadequate upgrading ventures in Cairo, which I argue, created scars as enduring evidence of unattainable planning methods and processes that undermined its locales. In this process, the paper focuses on the consequences of eviction rather than the planning methods in one of the city’s traditional districts. Empirical work is based on interdisciplinary research, public media reports and archival maps that document actions and procedures put in place to alter the visual, urban, and demographic characteristics of Cairo’s older neighbourhoods against a backdrop of decay to shift towards a global spectacular. The paper builds a conversation about the power and fate these spaces were subject to during hostile transformations that ended with their being disused. Their existence became associated with sores on the souls of its ex-inhabitants, as outward signs of inward scars showcasing a lack of equality and social justice in a context where it was much needed.

Remembering 1916: The Easter Rising, the Somme and the Politics of Memory in Ireland

The year 1916 witnessed two events that would profoundly shape both
politics and commemoration in Ireland over the course of the following
century. Although the Easter Rising and the Battle of the Somme were
important historical events in their own right, their significance also lay
in how they came to be understood as iconic moments in the emergence
of Northern Ireland and the Irish Republic. Adopting an interdisciplinary
approach drawing on history, politics, anthropology and cultural
studies, this volume explores how the memory of these two foundational
events has been constructed, mythologised and revised over the course
of the past century. The aim is not merely to understand how the Rising
and Somme came to exert a central place in how the past is viewed in
Ireland, but to explore wider questions about the relationship between
history, commemoration and memory.

Following instructions in a virtual school: Does working memory play a role?

Accumulating evidence that working memory supports the ability to follow instructions has so far been restricted to experimental paradigms that have greatly simplified the practical demands of performing actions to instructions in everyday tasks. The aim of the present study was to investigate whether working memory is involved in maintaining information over the longer periods of time that are more typical of everyday situations that require performing instructions to command. Forty-two children 7–11 years of age completed assessments of working memory, a real-world following-instructions task employing 3-D objects, and two new computerized instruction-following tasks involving navigation around a virtual school to complete a sequence of practical spoken commands. One task involved performing actions in a single classroom, and the other, performing actions in multiple locations in a virtual school building. Verbal working memory was closely linked with all three following-instructions paradigms, but with greater association to the virtual than to the real-world tasks. These results indicate that verbal working memory plays a key role in following instructions over extended periods of activity.

Perceptual learning of acoustic noise generates memory-evoked potentials

Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.

Heat Activated Prestressing of Shape Memory Alloys for Active Confinement of Concrete Sections

This paper presents the results from the experimental investigation on heat activated prestressing of Shape Memory Alloy (SMA) wires for active confinement of concrete sections. Active confinement of concrete is found to be much more effective than passive confinement which becomes effective only when the concrete starts to dilate. Active confinement achieved using conventional prestressing techniques often faces many obstacles due to practical limitations. A class of smart materials that has recently drawn attention in civil engineering is the super elastic SMA which has the ability to undergo reversible hysteretic shape change known as the shape memory effect. The shape memory effect of SMAs can be utilized to develop a convenient prestressing technique for active confinement of concrete sections.
In this study a series of experimental tests are conducted to study Heat Activated Prestress (HAP) in SMAs. Three different types of tests are conducted with different loading protocol to determine parameters such as HAP, residual strain after heating and range of strain that can be used for effective active confinement after HAP. Test results show a maximum HAP of about 500 MPa can be achieved after heating and approximately 450MPa is retained at 25oC in specimens pre-strained by 6%. A substantial amount of strain recovery upon unloading and after heating the SMA wires is recorded. About 2.5% elastic strain recovery upon unloading from 6% strain level is observed. In the specimen pre-strained by 6%, a total of 4% strain is recovered when unloaded after heating. A strain range of 3% is found available for effective confinement after HAP. Test results demonstrate that SMAs have unique features that can be intelligently employed in many civil engineering applications including active confinement of concrete sections.

Corrosion Fatigue Behaviour of Laser-welded Shape Memory NiTi Wires in a Simulated Body Fluid

Corrosion fatigue is a fracture process as a consequence of synergistic interactions between the material structure, corrosive environment and cyclic loads/strains. It is difficult to be detected and can cause unexpected failure of engineering components in use. This study reveals a comparison of corrosion fatigue behaviour of laser-welded and bare NiTi wires using bending rotation fatigue (BRF) test coupled with a specifically-designed corrosion cell. The testing medium was Hanks’ solution (simulated body fluid) at 37.5 oC. Electrochemical impedance spectroscopic (EIS) measurement was carried out to monitor the change of corrosion resistance of sample during the BRF test at different periods of time. Experiments indicate that the laser-welded NiTi wire would be more susceptible to the corrosion fatigue attack than the bare NiTi wire. This study can serve as a benchmark for the product designers and engineers to understand the corrosion fatigue behaviour of the NiTi laser weld joint and determine the fatigue life safety factor for NiTi medical devices/implants involving laser welding in the fabrication process.

Energy Optimization of Memory Intensive Parallel Workloads

Energy consumption is an important concern in modern multicore processors. The energy consumed by a multicore processor during the execution of an application can be minimized by tuning the hardware state utilizing knobs such as frequency, voltage etc. The existing theoretical work on energy minimization using Global DVFS (Dynamic Voltage and Frequency Scaling), despite being thorough, ignores the time and the energy consumed by the CPU on memory accesses and the dynamic energy consumed by the idle cores. This article presents an analytical energy-performance model for parallel workloads that accounts for the time and the energy consumed by the CPU chip on memory accesses in addition to the time and energy consumed by the CPU on CPU instructions. In addition, the model we present also accounts for the dynamic energy consumed by the idle cores. The existing work on global DVFS for parallel workloads shows that using a single frequency for the entire duration of a parallel application is not energy optimal and that varying the frequency according to the changes in the parallelism of the workload can save energy. We present an analytical framework around our energy-performance model to predict the operating frequencies (that depend upon the amount of parallelism) for global DVFS that minimize the overall CPU energy consumption. We show how the optimal frequencies in our model differ from the optimal frequencies in a model that does not account for memory accesses. We further show how the memory intensity of an application affects the optimal frequencies.