Working memory load improves early stages of independent visual processing.

Increasing evidence suggests that working memory and perceptual processes are dynamically interrelated due to modulating activity in overlapping brain networks. However, the direct influence of working memory on the spatio-temporal brain dynamics of behaviorally relevant intervening information remains unclear. To investigate this issue, subjects performed a visual proximity grid perception task under three different visual-spatial working memory (VSWM) load conditions. VSWM load was manipulated by asking subjects to memorize the spatial locations of 6 or 3 disks. The grid was always presented between the encoding and recognition of the disk pattern. As a baseline condition, grid stimuli were presented without a VSWM context. VSWM load altered both perceptual performance and neural networks active during intervening grid encoding. Participants performed faster and more accurately on a challenging perceptual task under high VSWM load as compared to the low load and the baseline condition. Visual evoked potential (VEP) analyses identified changes in the configuration of the underlying sources in one particular period occurring 160-190 ms post-stimulus onset. Source analyses further showed an occipito-parietal down-regulation concurrent to the increased involvement of temporal and frontal resources in the high VSWM context. Together, these data suggest that cognitive control mechanisms supporting working memory may selectively enhance concurrent visual processing related to an independent goal. More broadly, our findings are in line with theoretical models implicating the engagement of frontal regions in synchronizing and optimizing mnemonic and perceptual resources towards multiple goals.

Glutamine and antioxidants in the critically ill patient: a post hoc analysis of a large-scale randomized trial.

BACKGROUND: The recent large randomized controlled trial of glutamine and antioxidant supplementation suggested that high-dose glutamine is associated with increased mortality in critically ill patients with multiorgan failure. The objectives of the present analyses were to reevaluate the effect of supplementation after controlling for baseline covariates and to identify potentially important subgroup effects. MATERIALS AND METHODS: This study was a post hoc analysis of a prospective factorial 2 × 2 randomized trial conducted in 40 intensive care units in North America and Europe. In total, 1223 mechanically ventilated adult patients with multiorgan failure were randomized to receive glutamine, antioxidants, both glutamine and antioxidants, or placebo administered separate from artificial nutrition. We compared each of the 3 active treatment arms (glutamine alone, antioxidants alone, and glutamine + antioxidants) with placebo on 28-day mortality. Post hoc, treatment effects were examined within subgroups defined by baseline patient characteristics. Logistic regression was used to estimate treatment effects within subgroups after adjustment for baseline covariates and to identify treatment-by-subgroup interactions (effect modification). RESULTS: The 28-day mortality rates in the placebo, glutamine, antioxidant, and combination arms were 25%, 32%, 29%, and 33%, respectively. After adjusting for prespecified baseline covariates, the adjusted odds ratio of 28-day mortality vs placebo was 1.5 (95% confidence interval, 1.0-2.1, P = .05), 1.2 (0.8-1.8, P = .40), and 1.4 (0.9-2.0, P = .09) for glutamine, antioxidant, and glutamine plus antioxidant arms, respectively. In the post hoc subgroup analysis, both glutamine and antioxidants appeared most harmful in patients with baseline renal dysfunction. No subgroups suggested reduced mortality with supplements. CONCLUSIONS: After adjustment for baseline covariates, early provision of high-dose glutamine administered separately from artificial nutrition was not beneficial and may be associated with increased mortality in critically ill patients with multiorgan failure. For both glutamine and antioxidants, the greatest potential for harm was observed in patients with multiorgan failure that included renal dysfunction upon study enrollment.

Conditioning of multiple-point statistics facies simulations to tomographic images

Geophysical tomography captures the spatial distribution of the underlying geophysical property at a relatively high resolution, but the tomographic images tend to be blurred representations of reality and generally fail to reproduce sharp interfaces. Such models may cause significant bias when taken as a basis for predictive flow and transport modeling and are unsuitable for uncertainty assessment. We present a methodology in which tomograms are used to condition multiple-point statistics (MPS) simulations. A large set of geologically reasonable facies realizations and their corresponding synthetically calculated cross-hole radar tomograms are used as a training image. The training image is scanned with a direct sampling algorithm for patterns in the conditioning tomogram, while accounting for the spatially varying resolution of the tomograms. In a post-processing step, only those conditional simulations that predicted the radar traveltimes within the expected data error levels are accepted. The methodology is demonstrated on a two-facies example featuring channels and an aquifer analog of alluvial sedimentary structures with five facies. For both cases, MPS simulations exhibit the sharp interfaces and the geological patterns found in the training image. Compared to unconditioned MPS simulations, the uncertainty in transport predictions is markedly decreased for simulations conditioned to tomograms. As an improvement to other approaches relying on classical smoothness-constrained geophysical tomography, the proposed method allows for: (1) reproduction of sharp interfaces, (2) incorporation of realistic geological constraints and (3) generation of multiple realizations that enables uncertainty assessment.

Patients' satisfaction with community treatment: a pilot cross-sectional survey adopting multiple perspectives.

ACCESSIBLE SUMMARY: Patients' satisfaction is scarcely studied within the context of community treatment for adolescents. Thus, this study adopts a multiple perspective on patients' satisfaction (including service users as well as staff members). The results highlighted that all informants (patients, foster carers in foster homes and professional caregivers from community treatment teams) perceived the patients to be satisfied, with foster carers reporting the highest patient satisfaction rate. Considering the patient satisfaction rate from multiple perspectives provides complementary understandings. Clinical outcomes and, specifically, a reduction in emotional difficulties were related to patient's satisfaction, but only from the patients' perspective. ABSTRACT: Community treatment (CT) teams in Switzerland provide care to patients who are unable to use regular child and adolescent mental health services (i.e. inpatient and outpatients facilities). No study has considered patients' self-rated satisfaction alongside with staff members' perspectives on patient satisfaction. Thus, adopting a cross-sectional survey design, we collected patients' satisfaction using the Client Satisfaction Questionnaire (CSQ-8), rated by multiple informants (patients, foster carers in foster homes and professional caregivers from CT teams). Professional caregivers assessed clinical outcomes using the Health of the Nation Outcome Scale for Children and Adolescents. The results indicated that all informants were satisfied with the community treatment teams. The satisfaction scores were not correlated across informants; however, the alleviation of emotional symptoms was correlated with patients' satisfaction. This study indicated that the use of a combined approach including the views of service users and professionals gives important complementary information. Finally, in our sample, lower emotional symptoms were linked to enhanced patient satisfaction. This study demonstrated the importance of considering multiple perspectives to obtain the most accurate picture of patients' satisfaction. Second, focusing on the reduction of emotional symptoms might lead to a higher degree of patients' satisfaction.

Patients' satisfaction with community treatment: a pilot cross-sectional survey adopting multiple perspectives.

ACCESSIBLE SUMMARY: Patients' satisfaction is scarcely studied within the context of community treatment for adolescents. Thus, this study adopts a multiple perspective on patients' satisfaction (including service users as well as staff members). The results highlighted that all informants (patients, foster carers in foster homes and professional caregivers from community treatment teams) perceived the patients to be satisfied, with foster carers reporting the highest patient satisfaction rate. Considering the patient satisfaction rate from multiple perspectives provides complementary understandings. Clinical outcomes and, specifically, a reduction in emotional difficulties were related to patient's satisfaction, but only from the patients' perspective. ABSTRACT: Community treatment (CT) teams in Switzerland provide care to patients who are unable to use regular child and adolescent mental health services (i.e. inpatient and outpatients facilities). No study has considered patients' self-rated satisfaction alongside with staff members' perspectives on patient satisfaction. Thus, adopting a cross-sectional survey design, we collected patients' satisfaction using the Client Satisfaction Questionnaire (CSQ-8), rated by multiple informants (patients, foster carers in foster homes and professional caregivers from CT teams). Professional caregivers assessed clinical outcomes using the Health of the Nation Outcome Scale for Children and Adolescents. The results indicated that all informants were satisfied with the community treatment teams. The satisfaction scores were not correlated across informants; however, the alleviation of emotional symptoms was correlated with patients' satisfaction. This study indicated that the use of a combined approach including the views of service users and professionals gives important complementary information. Finally, in our sample, lower emotional symptoms were linked to enhanced patient satisfaction. This study demonstrated the importance of considering multiple perspectives to obtain the most accurate picture of patients' satisfaction. Second, focusing on the reduction of emotional symptoms might lead to a higher degree of patients' satisfaction.

Accelerated Microstructure Imaging via Convex Optimisation for regions with multiple fibres (AMICOx)

This paper reviews and extends our previous work to enable fast axonal diameter mapping from diffusion MRI data in the presence of multiple fibre populations within a voxel. Most of the existing mi-crostructure imaging techniques use non-linear algorithms to fit their data models and consequently, they are computationally expensive and usually slow. Moreover, most of them assume a single axon orientation while numerous regions of the brain actually present more complex configurations, e.g. fiber crossing. We present a flexible framework, based on convex optimisation, that enables fast and accurate reconstructions of the microstructure organisation, not limited to areas where the white matter is coherently oriented. We show through numerical simulations the ability of our method to correctly estimate the microstructure features (mean axon diameter and intra-cellular volume fraction) in crossing regions.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images.

OBJECTIVE: The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. METHODS: Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. RESULTS: A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). CONCLUSION: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. ADVANCES IN KNOWLEDGE: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality.

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Local map update for large scale SLAM

A technique for simultaneous localisation and mapping (SLAM) for large scale scenarios is presented. This solution is based on the use of independent submaps of a limited size to map large areas. In addition, a global stochastic map, containing the links between adjacent submaps, is built. The information in both levels is corrected every time a loop is closed: local maps are updated with the information from overlapping maps, and the global stochastic map is optimised by means of constrained minimisation

Turbulent shallow-water model for orographic subgrid-scale perturbations

A parallel pseudo-spectral method for the simulation in distributed memory computers of the shallow-water equations in primitive form was developed and used on the study of turbulent shallow-waters LES models for orographic subgrid-scale perturbations. The main characteristics of the code are: momentum equations integrated in time using an accurate pseudo-spectral technique; Eulerian treatment of advective terms; and parallelization of the code based on a domain decomposition technique. The parallel pseudo-spectral code is efficient on various architectures. It gives high performance onvector computers and good speedup on distributed memory systems. The code is being used for the study of the interaction mechanisms in shallow-water ows with regular as well as random orography with a prescribed spectrum of elevations. Simulations show the evolution of small scale vortical motions from the interaction of the large scale flow and the small-scale orographic perturbations. These interactions transfer energy from the large-scale motions to the small (usually unresolved) scales. The possibility of including the parametrization of this effects in turbulent LES subgrid-stress models for the shallow-water equations is addressed.

QUALITY OF PROCESSING TOMATO FRUITS IN COMPETITION WITH Solanum americanum

ABSTRACT Five experiments were conducted to evaluate the hypothesis that Solanum americanum density and time of coexistence affect the quality of processing tomato fruit. The tomato crop was established using either the direct drilling or the transplanting technique. The factors evaluated consisted of weed density (from 0 up to 6 plants m-2) and time of weed interference (early bloom stage, full flowering stage, fruit filling, and harvest time). The effects of competition on tomato fruit quality were analysed using a multiple model. Tomato variables evaluated included industrial fruit types (which depended on ripeness and disease infection) and soluble solids level(obrix). Tomato fruit quality is dependent on the factors tested. Under low densities (< 6 plants m-2) of S. americanum there was a small impact on the quality of the tomato fruits. The percentage of grade A (mature fruit with red color and without pathogen infection) tomato fruits is the variable most affect by the independent variables. The impact of these independent variables on the percentage of grade C (green and/or with more than 15% disease infection) tomato yield was of smaller magnitude and in an inverse trend as the observed for grade A. The level of soluble solids was influenced by the weed interference on only two experiments, but the impact was of small magnitude. The impact of the results on current and future crop management practices is discussed.

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Developing purchase invoice processing through workflow automation

The aim of this master’s thesis is to research and analyze how purchase invoice processing can be automated and streamlined in a system renewal project. The impacts of workflow automation on invoice handling are studied by means of time, cost and quality aspects. Purchase invoice processing has a lot of potential for automation because of its labor-intensive and repetitive nature. As a case study combining both qualitative and quantitative methods, the topic is approached from a business process management point of view. The current process was first explored through interviews and workshop meetings to create a holistic understanding of the process at hand. Requirements for process streamlining were then researched focusing on specified vendors and their purchase invoices, which helped to identify the critical factors for successful invoice automation. To optimize the flow from invoice receipt to approval for payment, the invoice receiving process was outsourced and the automation functionalities of the new system utilized in invoice handling. The quality of invoice data and the need of simple structured purchase order (PO) invoices were emphasized in the system testing phase. Hence, consolidated invoices containing references to multiple PO or blanket release numbers should be simplified in order to use automated PO matching. With non-PO invoices, it is important to receive the buyer reference details in an applicable invoice data field so that automation rules could be created to route invoices to a review and approval flow. In the beginning of the project, invoice processing was seen ineffective both time- and cost-wise, and it required a lot of manual labor to carry out all tasks. In accordance with testing results, it was estimated that over half of the invoices could be automated within a year after system implementation. Processing times could be reduced remarkably, which would then result savings up to 40 % in annual processing costs. Due to several advancements in the purchase invoice process, business process quality could also be perceived as improved.

Restless leg syndrome, sleep quality and fatigue in multiple sclerosis patients

We have tested the hypothesis that restless leg syndrome (RLS) is related to quality of sleep, fatigue and clinical disability in multiple sclerosis (MS). The diagnosis of RLS used the four minimum criteria defined by the International Restless Legs Syndrome Study Group. Fatigue was assessed by the Fatigue Severity Scale (FSS >27), quality of sleep by the Pittsburgh Sleep Quality Index (PSQI >6), excessive daytime sleepiness by the Epworth Sleepiness Scale (ESS >10) and clinical disability by the Expanded Disability Status Scale (EDSS). Forty-four patients (32 women) aged 14 to 64 years (43 ± 14) with disease from 0.4 to 23 years (6.7 ± 5.9) were evaluated. Thirty-five were classified as relapsing-remitting, 5 as primary progressive and 4 as secondary progressive. EDSS varied from 0 to 8.0 (3.6 ± 2.0). RLS was detected in 12 cases (27%). Patients with RLS presented greater disability (P = 0.01), poorer sleep (P = 0.02) and greater levels of fatigue (P = 0.03). Impaired sleep was present in 23 (52%) and excessive daytime sleepiness in 3 cases (6.8%). Fatigue was present in 32 subjects (73%) and was associated with clinical disability (P = 0.000) and sleep quality (P = 0.002). Age, gender, disease duration, MS pattern, excessive daytime sleepiness and the presence of upper motor neuron signs were not associated with the presence of RLS. Fatigue was best explained by clinical disability and poor sleep quality. Awareness of RLS among health care professionals may contribute to improvement in MS management.

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.