18 resultados para Processing-speed


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The apolipoprotein (APOE) epsilon4 allele is a genetic risk factor for the development of Alzheimer's disease (AD). It has also been associated with vascular dementia (VaD) in some but not all studies. Previous studies have examined the role of APOE in predicting performance on cognitive tests in both demented and non-demented populations. In cognitively intact individuals, statistically significant group differences between APOE epsilon4 carriers and non-carriers have been demonstrated for several cognitive domains. In AD studies of the impact of APOE epsilon4 on cognition have been conflicting while no previous study has assessed cognition and impact of APOE epsilon4 in VaD. In this study we investigated the impact of APOE epsilon4 on performance in neuropsychological tests including information processing speed in patients with mild-moderate AD and VaD. We incorporated both computerized and pen and paper tests to ensure a sensitive method of assessing cognition. 109 patients participated in the study (VaD=41, AD=68). Neurocognitive performance of 44 epsilon4 present AD patients was compared to 24 epsilon4absent patients and performance of 23 epsilon4 present VaD patients was compared to 18 epsilon4 absent patients. There was evidence that APOE epsilon4 conferred a risk of poorer cognitive functioning in both patient groups. In the AD group presence of epsilon4 conferred a negative impact on some measures of speed of information processing and immediate recall while in the VaD group epsilon4 present patients had evidence of poorer accuracy on tasks such as choice reaction time and spatial working memory. In AD and VaD groups epsilon4 present patients showed impairment in selective attention. These findings provide further support of the negative impact of the epsilon4 allele in cognition.

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This integrative review presents a novel hypothesis as a basis for integrating two evolutionary viewpoints on the origins of human cognition and communication, the sexual selection of human mental capacities, and the social brain hypothesis. This new account suggests that mind-reading social skills increased reproductive success and consequently became targets for sexual selection. The hypothesis proposes that human communication has three purposes: displaying mind-reading abilities, aligning and maintaining representational parity between individuals to enable displays, and the exchange of propositional information. Intelligence, creativity, language, and humor are mental fitness indicators that signal an individual’s quality to potential mates, rivals, and allies. Five features central to the proposed display mechanism unify these indicators, the relational combination of concepts, large conceptual knowledge networks, processing speed, contextualization, and receiver knowledge. Sufficient between-mind alignment of conceptual networks allows displays based upon within-mind conceptual mappings. Creative displays communicate previously unnoticed relational connections and novel conceptual combinations demonstrating an ability to read a receiver’s mind. Displays are costly signals of mate quality with costs incurred in the developmental production of the neural apparatus required to engage in complex displays and opportunity costs incurred through time spent acquiring cultural knowledge. Displays that are fast, novel, spontaneous, contextual, topical, and relevant are hard-to-fake for lower quality individuals. Successful displays result in elevated social status and increased mating options. The review addresses literatures on costly signaling, sexual selection, mental fitness indicators, and the social brain hypothesis; drawing implications for nonverbal and verbal communication.

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A practically viable multi-biometric recognition system should not only be stable, robust and accurate but should also adhere to real-time processing speed and memory constraints. This study proposes a cascaded classifier-based framework for use in biometric recognition systems. The proposed framework utilises a set of weak classifiers to reduce the enrolled users' dataset to a small list of candidate users. This list is then used by a strong classifier set as the final stage of the cascade to formulate the decision. At each stage, the candidate list is generated by a Mahalanobis distance-based match score quality measure. One of the key features of the authors framework is that each classifier in the ensemble can be designed to use a different modality thus providing the advantages of a truly multimodal biometric recognition system. In addition, it is one of the first truly multimodal cascaded classifier-based approaches for biometric recognition. The performance of the proposed system is evaluated both for single and multimodalities to demonstrate the effectiveness of the approach.

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Background

It is estimated that up to 75% of cancer survivors may experience cognitive impairment as a result of cancer treatment and given the increasing size of the cancer survivor population, the number of affected people is set to rise considerably in coming years. There is a need, therefore, to identify effective, non-pharmacological interventions for maintaining cognitive function or ameliorating cognitive impairment among people with a previous cancer diagnosis.
Objectives

To evaluate the cognitive effects, non-cognitive effects, duration and safety of non-pharmacological interventions among cancer patients targeted at maintaining cognitive function or ameliorating cognitive impairment as a result of cancer or receipt of systemic cancer treatment (i.e. chemotherapy or hormonal therapies in isolation or combination with other treatments).
Search methods

We searched the Cochrane Centre Register of Controlled Trials (CENTRAL), MEDLINE, Embase, PUBMED, Cumulative Index of Nursing and Allied Health Literature (CINAHL) and PsycINFO databases. We also searched registries of ongoing trials and grey literature including theses, dissertations and conference proceedings. Searches were conducted for articles published from 1980 to 29 September 2015.
Selection criteria

Randomised controlled trials (RCTs) of non-pharmacological interventions to improve cognitive impairment or to maintain cognitive functioning among survivors of adult-onset cancers who have completed systemic cancer therapy (in isolation or combination with other treatments) were eligible. Studies among individuals continuing to receive hormonal therapy were included. We excluded interventions targeted at cancer survivors with central nervous system (CNS) tumours or metastases, non-melanoma skin cancer or those who had received cranial radiation or, were from nursing or care home settings. Language restrictions were not applied.
Data collection and analysis

Author pairs independently screened, selected, extracted data and rated the risk of bias of studies. We were unable to conduct planned meta-analyses due to heterogeneity in the type of interventions and outcomes, with the exception of compensatory strategy training interventions for which we pooled data for mental and physical well-being outcomes. We report a narrative synthesis of intervention effectiveness for other outcomes.
Main results

Five RCTs describing six interventions (comprising a total of 235 participants) met the eligibility criteria for the review. Two trials of computer-assisted cognitive training interventions (n = 100), two of compensatory strategy training interventions (n = 95), one of meditation (n = 47) and one of physical activity intervention (n = 19) were identified. Each study focused on breast cancer survivors. All five studies were rated as having a high risk of bias. Data for our primary outcome of interest, cognitive function were not amenable to being pooled statistically. Cognitive training demonstrated beneficial effects on objectively assessed cognitive function (including processing speed, executive functions, cognitive flexibility, language, delayed- and immediate- memory), subjectively reported cognitive function and mental well-being. Compensatory strategy training demonstrated improvements on objectively assessed delayed-, immediate- and verbal-memory, self-reported cognitive function and spiritual quality of life (QoL). The meta-analyses of two RCTs (95 participants) did not show a beneficial effect from compensatory strategy training on physical well-being immediately (standardised mean difference (SMD) 0.12, 95% confidence interval (CI) -0.59 to 0.83; I2= 67%) or two months post-intervention (SMD - 0.21, 95% CI -0.89 to 0.47; I2 = 63%) or on mental well-being two months post-intervention (SMD -0.38, 95% CI -1.10 to 0.34; I2 = 67%). Lower mental well-being immediately post-intervention appeared to be observed in patients who received compensatory strategy training compared to wait-list controls (SMD -0.57, 95% CI -0.98 to -0.16; I2 = 0%). We assessed the assembled studies using GRADE for physical and mental health outcomes and this evidence was rated to be low quality and, therefore findings should be interpreted with caution. Evidence for physical activity and meditation interventions on cognitive outcomes is unclear.
Authors' conclusions

Overall, the, albeit low-quality evidence may be interpreted to suggest that non-pharmacological interventions may have the potential to reduce the risk of, or ameliorate, cognitive impairment following systemic cancer treatment. Larger, multi-site studies including an appropriate, active attentional control group, as well as consideration of functional outcomes (e.g. activities of daily living) are required in order to come to firmer conclusions about the benefits or otherwise of this intervention approach. There is also a need to conduct research into cognitive impairment among cancer patient groups other than women with breast cancer.

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‘Temporally urgent’ reactions are extremely rapid, spatially precise movements that are evoked following discrete stimuli. The involvement of primary motor cortex (M1) and its relationship to stimulus intensity in such reactions is not well understood. Continuous theta burst stimulation (cTBS) suppresses focal regions of the cortex and can assess the involvement of motor cortex in speed of processing. The primary objective of this study was to explore the involvement of M1 in speed of processing with respect to stimulus intensity. Thirteen healthy young adults participated in this experiment. Behavioral testing consisted of a simple button press using the index finger following median nerve stimulation of the opposite limb, at either high or low stimulus intensity. Reaction time was measured by the onset of electromyographic activity from the first dorsal interosseous (FDI) muscle of each limb. Participants completed a 30 min bout of behavioral testing prior to, and 15 min following, the delivery of cTBS to the motor cortical representation of the right FDI. The effect of cTBS on motor cortex was measured by recording the average of 30 motor evoked potentials (MEPs) just prior to, and 5 min following, cTBS. Paired t-tests revealed that, of thirteen participants, five demonstrated a significant attenuation, three demonstrated a significant facilitation and five demonstrated no significant change in MEP amplitude following cTBS. Of the group that demonstrated attenuated MEPs, there was a biologically significant interaction between stimulus intensity and effect of cTBS on reaction time and amplitude of muscle activation. This study demonstrates the variability of potential outcomes associated with the use of cTBS and further study on the mechanisms that underscore the methodology is required. Importantly, changes in motor cortical excitability may be an important determinant of speed of processing following high intensity stimulation.

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Using a speed-matching task, we measured the speed tuning of the dynamic motion aftereVect (MAE). The results of our Wrst experiment, in which we co-varied dot speed in the adaptation and test stimuli, revealed a speed tuning function. We sought to tease apart what contribution, if any, the test stimulus makes towards the observed speed tuning. This was examined by independently manipulating dot speed in the adaptation and test stimuli, and measuring the eVect this had on the perceived speed of the dynamic MAE. The results revealed that the speed tuning of the dynamic MAE is determined, not by the speed of the adaptation stimulus, but by the local motion characteristics of the dynamic test stimulus. The role of the test stimulus in determining the perceived speed of the dynamic MAE was conWrmed by showing that, if one uses a test stimulus containing two sources of local speed information, observers report seeing a transparent MAE; this is despite the fact that adaptation is induced using a single-speed stimulus. Thus while the adaptation stimulus necessarily determines perceived direction of the dynamic MAE, its perceived speed is determined by the test stimulus. This dissociation of speed and direction supports the notion that the processing of these two visual attributes may be partially independent.

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A variation of the least means squares (LMS) algorithm, called the delayed LMS (DLMS) algorithm is an ideally suited to achieve highly pipelined, adaptive digital filter implementations. The paper presents an efficient method of determining the delays in the DLMS filter and then transferring these delays using retiming in order to achieve fully pipelined circuit architectures for FPGA implementation. The method has been used to derive a series of retimed delayed LMS (RDLMS) architectures, which considerable reduce the number of delays and convergence time and give superior performance in terms of throughput rate when compared to previous work. Three circuit architectures and three hardware shared versions are presented which have been implemented using the Virtex-II FPGA technology resulting in a throughout rate of 182 Msample/s.

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BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

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The fabrication and performance of the first bit-level systolic correlator array is described. The application of systolic array concepts at the bit level provides a simple and extremely powerful method for implementing high-performance digital processing functions. The resulting structure is highly regular, facilitating yield enhancement through fault-tolerant redundancy techniques and therefore ideally suited to implementation as a VLSI chip. The CMOS/SOS chip operates at 35 MHz, is fully cascadable and exhibits 64-stage correlation for 1-bit reference and 4-bit data. 7 refs.

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Melt viscosity is one of the main factors affecting product quality in extrusion processes particularly with regard to recycled polymers. However, due to wide variability in the physical properties of recycled feedstock, it is difficult to maintain the melt viscosity during extrusion of polymer blends and obtain good quality product without generating scrap. This research investigates the application of ultrasound and temperature control in an automatic extruder controller, which has ability to maintain constant melt viscosity from variable recycled polymer feedstock during extrusion processing. An ultrasonic modulation system has been developed and fitted to the extruder prior to the die to convey ultrasonic energy from a high power ultrasonic generator to the polymer melt. Two separate control loops have been developed to run simultaneously in one controller: the first loop controls the ultrasonic energy or temperature to maintain constant die pressure, the second loop is used to control extruder screw speed to maintain constant throughput at the extruder die. Time response and energy consumption of the control methods in real-time experiments are also investigated and reported this paper.

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Graphene, due to its outstanding properties, has become the topic of much research activity in recent years. Much of that work has been on a laboratory scale however, if we are to introduce graphene into real product applications it is necessary to examine how the material behaves under industrial processing conditions. In this paper the melt processing of polyamide 6/graphene nanoplatelet composites via twin screw extrusion is investigated and structure–property relationships are examined for mechanical and electrical properties. Graphene nanoplatelets (GNPs) with two aspect ratios (700 and 1000) were used in order to examine the influence of particle dimensions on composite properties. It was found that the introduction of GNPs had a nucleating effect on polyamide 6 (PA6) crystallization and substantially increased crystallinity by up to 120% for a 20% loading in PA6. A small increase in crystallinity was observed when extruder screw speed increased from 50 rpm to 200 rpm which could be attributed to better dispersion and more nucleation sites for crystallization. A maximum enhancement of 412% in Young's modulus was achieved at 20 wt% loading of GNPs. This is the highest reported enhancement in modulus achieved to date for a melt mixed thermoplastic/GNPs composite. A further result of importance here is that the modulus continued to increase as the loading of GNPs increased even at 20 wt% loading and results are in excellent agreement with theoretical predictions for modulus enhancement. Electrical percolation was achieved between 10–15 wt% loading for both aspect ratios of GNPs with an increase in conductivity of approximately 6 orders of magnitude compared to the unfilled PA6.

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In this paper, the processing and characterization of Polyamide 6 (PA6) / graphite nanoplatelets
(GNPs) composites is reported. PA6/GNPs composites were prepared by melt-mixing using an
industrial, co-rotating, intermeshing, twin-screw extruder. A bespoke screw configuration was used
that was designed in-house to enhance nanoparticle dispersion into a polymer matrix. The effects of
GNPs type (xGnP® M-5 and xGnP® C-500), GNPs content, and extruder screw speed on the bulk
properties of the PA6/GNPs nanocomposites were investigated. Results show a considerable
improvement in the thermal and mechanical properties of PA6/GNPs composites, as compared with
the unfilled PA6 polymer. An increase in crystallinity (%Xc) with increasing GNPs content, and a
change in shape of the crystallization exotherms (broadening) and melting endotherms, both suggest a
change in the crystal type and perfection. An increase in tensile modulus of as much as 376% and
412% was observed for PA6/M-5 xGnP® and PA6/C-500 xGnP® composites, respectively, at filler
contents of 20wt%. The enhancement of Young’s modulus and yield stress can be attributed to the
reinforcing effect of GNPs and their uniform dispersion in the PA6 matrix. The rheological response
of the composite resembles that of a ‘pseudo-solid’, rather than a molten liquid, and analysis of the
rheological data indicates that a percolation threshold was reached at GNPs contents of between 10–
15wt%. The electrical conductivity of the composite also increased with increasing GNPs content,
with an addition of 15wt% GNPs resulting in a 6 order-of-magnitude increase in conductivity. The
electrical percolation thresholds of all composites were between 10–15wt%.

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The aim of this article was to construct a T–ϕ phase diagram for a model drug (FD) and amorphous polymer (Eudragit® EPO) and to use this information to understand the impact of how temperature–composition coordinates influenced the final properties of the extrudate. Defining process boundaries and understanding drug solubility in polymeric carriers is of utmost importance and will help in the successful manufacture of new delivery platforms for BCS class II drugs. Physically mixed felodipine (FD)–Eudragit® EPO (EPO) binary mixtures with pre-determined weight fractions were analysed using DSC to measure the endset of melting and glass transition temperature. Extrudates of 10 wt% FD–EPO were processed using temperatures (110°C, 126°C, 140°C and 150°C) selected from the temperature–composition (T–ϕ) phase diagrams and processing screw speed of 20, 100 and 200rpm. Extrudates were characterised using powder X-ray diffraction (PXRD), optical, polarised light and Raman microscopy. To ensure formation of a binary amorphous drug dispersion (ADD) at a specific composition, HME processing temperatures should at least be equal to, or exceed, the corresponding temperature value on the liquid–solid curve in a F–H T–ϕ phase diagram. If extruded between the spinodal and liquid–solid curve, the lack of thermodynamic forces to attain complete drug amorphisation may be compensated for through the use of an increased screw speed. Constructing F–H T–ϕ phase diagrams are valuable not only in the understanding drug–polymer miscibility behaviour but also in rationalising the selection of important processing parameters for HME to ensure miscibility of drug and polymer.

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Flow processing is a fundamental element of stateful traffic classification and it has been recognized as an essential factor for delivering today’s application-aware network operations and security services. The basic function within a flow processing engine is to search and maintain a flow table, create new flow entries if no entry matches and associate each entry with flow states and actions for future queries. Network state information on a per-flow basis must be managed in an efficient way to enable Ethernet frame transmissions at 40 Gbit/s (Gbps) and 100 Gbps in the near future. This paper presents a hardware solution of flow state management for implementing large-scale flow tables on popular computer memories using DDR3 SDRAMs. Working with a dedicated flow lookup table at over 90 million lookups per second, the proposed system is able to manage 512-bit state information at run time.