Diurnal changes in reflectance factor due to Sun-row direction interactions

Over a two year period, data were collected regarding the canopies of soybeans grown in rows in planter boxes placed on a turntable in an effort to investigate changes in the spectral reflectance factor related to row direction, Sun direction, soil background, and crop development stage. Results demonstrate that the direction of rows in a soybean canopy can affect the reflectance factor of the canopy by as much as 230%. The results for the red spectral region tend to support the validity of canopy reflectance models; results for the infrared region do not

Generalizing with perceptrons in case of structured phase- and pattern-spaces

We investigate the influence of different kinds of structure on the learning behaviour of a perceptron performing a classification task defined by a teacher rule. The underlying pattern distribution is permitted to have spatial correlations. The prior distribution for the teacher coupling vectors itself is assumed to be nonuniform. Thus classification tasks of quite different difficulty are included. As learning algorithms we discuss Hebbian learning, Gibbs learning, and Bayesian learning with different priors, using methods from statistics and the replica formalism. We find that the Hebb rule is quite sensitive to the structure of the actual learning problem, failing asymptotically in most cases. Contrarily, the behaviour of the more sophisticated methods of Gibbs and Bayes learning is influenced by the spatial correlations only in an intermediate regime of $\alpha$, where $\alpha$ specifies the size of the training set. Concerning the Bayesian case we show, how enhanced prior knowledge improves the performance.Comment: LaTeX, 32 pages with eps-figs, accepted by J Phys

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

Background and Objectives 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson’s disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer’s disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory. Methods We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories. Results The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman’s rho =0.62, P=0.004). Conclusion In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages

A lattice gas model of II-VI(001) semiconductor surfaces

We introduce an anisotropic two-dimensional lattice gas model of metal terminated II-IV(001) seminconductor surfaces. Important properties of this class of materials are represented by effective NN and NNN interactions, which result in the competition of two vacancy structures on the surface. We demonstrate that the experimentally observed c(2x2)-(2x1) transition of the CdTe(001) surface can be understood as a phase transition in thermal equilbrium. The model is studied by means of transfer matrix and Monte Carlo techniques. The analysis shows that the small energy difference of the competing reconstructions determines to a large extent the nature of the different phases. Possible implications for further experimental research are discussed.Comment: 7 pages, 2 figure

Action on the social determinants for advancing health equity in the time of COVID-19: perspectives of actors engaged in a WHO Special Initiative.

Since the 2008 publication of the reports of the Commission on Social Determinants of Health and its nine knowledge networks, substantial research has been undertaken to document and describe health inequities. The COVID-19 pandemic has underscored the need for a deeper understanding of, and broader action on, the social determinants of health. Building on this unique and critical opportunity, the World Health Organization is steering a multi-country Initiative to reduce health inequities through an action-learning process in 'Pathfinder' countries. The Initiative aims to develop replicable and reliable models and practices that can be adopted by WHO offices and UN staff to address the social determinants of health to advance health equity. This paper provides an overview of the Initiative by describing its broad theory of change and work undertaken in three regions and six Pathfinder countries in its first year-and-a-half. Participants engaged in the Initiative describe results of early country dialogues and promising entry points for implementation that involve model, network and capacity building. The insights communicated through this note from the field will be of interest for others aiming to advance health equity through taking action on the social determinants of health, in particular as regards structural determinants

Action on the social determinants for advancing health equity in the time of COVID-19: perspectives of actors engaged in a WHO Special Initiative

Since the 2008 publication of the reports of the Commission on Social Determinants of Health and its nine knowledge networks, substantial research has been undertaken to document and describe health inequities. The COVID-19 pandemic has underscored the need for a deeper understanding of, and broader action on, the social determinants of health. Building on this unique and critical opportunity, the World Health Organization is steering a multi-country Initiative to reduce health inequities through an action-learning process in ‘Pathfinder’ countries. The Initiative aims to develop replicable and reliable models and practices that can be adopted by WHO offices and UN staff to address the social determinants of health to advance health equity. This paper provides an overview of the Initiative by describing its broad theory of change and work undertaken in three regions and six Pathfinder countries in its first year-and-a-half. Participants engaged in the Initiative describe results of early country dialogues and promising entry points for implementation that involve model, network and capacity building. The insights communicated through this note from the field will be of interest for others aiming to advance health equity through taking action on the social determinants of health, in particular as regards structural determinants

Exploring Quaker organising to consider the possibilities for relational leadership

This paper develops the perspective of ‘relational leadership’ by exploring dynamics of influence within Quaker organising. The theory of relational leadership is drawn upon as it is connected with more sustainable and equitable ways of organising. A Quaker context is studied as it is conducive for understanding possibilities for relational leadership because there is no formal hierarchy. By applying three aspects of a relational leadership perspective (mutual influence process [1], momentary [2] and socially co-constructed [3]) to a thematic analysis of interview data, understanding is developed about the potential dynamics of influence and leadership in non-hierarchical organising. Two contributions to relational leadership theory are offered. Firstly, the paper shows a need for greater critical attention to appreciate the potential subtleties and tensions involved in influencing dynamics in non-hierarchical organising; and, secondly, assumptions about the continuous potential for fluidity of influencing are challenged

The role of biases in on-line learning of two-layer networks

The influence of biases on the learning dynamics of a two-layer neural network, a normalized soft-committee machine, is studied for on-line gradient descent learning. Within a statistical mechanics framework, numerical studies show that the inclusion of adjustable biases dramatically alters the learning dynamics found previously. The symmetric phase which has often been predominant in the original model all but disappears for a non-degenerate bias task. The extended model furthermore exhibits a much richer dynamical behavior, e.g. attractive suboptimal symmetric phases even for realizable cases and noiseless data

Remaking Africa's informal economies: youth, entrepreneurship and the promise of inclusion at the bottom of the pyramid

In recent years, the quest for 'inclusive markets' that incorporate Africa's youth has become a key focus of national and international development efforts, with so-called bottom of the pyramid (BoP) initiatives increasingly seen as a way to draw the continent's poor into new networks of global capitalism. SSA has become a fertile frontier for such systems, as capital sets its sights on the continents vast 'under-served' informal economies, harnessing the entrepreneurial mettle of youth to create new markets for a range of products, from solar lanterns and shampoo to cook stoves and sanitary pads. Drawing on ethnographic research with youth entrepreneurs, we trace the prcesses of individual and collective 'transformation' that the mission of (self-) empowerment through entrepreneurship seeks to bring about. We argue that, while such systems are meant to bring those below the poverty line above it, the 'line' is reified and reinforced through a range of discursive and strategic practices that actively construct and embed distinctions between the past and the future, valuable and valueless, and the idle and productive in Africa's informal economies