Selecting electrical billing attributes: big data preprocessing improvements

The attribute selection is a very relevant activity of data preprocessing when discovering knowledge on databases. Its main objective is to eliminate irrelevant and/or redundant attributes to obtain computationally treatable issues, without affecting the quality of the solution. Various techniques are proposed, mainly from two approaches: wrapper and ranking. This article evaluates a novel approach proposed by Bradley and Mangasarian (Machine learning ICML. Morgan Kaufmann, Sn Fco, CA, pp. 82–90, 1998 [1]) which uses concave programming for minimizing the classification error and the number of attributes required to perform the task. The technique is evaluated using the electric service billing database in Colombia. The results are compared against traditional techniques for evaluating: attribute reduction, processing time, discovered knowledge size, and solution quality

Insular Celtic population structure and genomic footprints of migration

Previous studies of the genetic landscape of Ireland have suggested homogeneity, with population substructure undetectable using single-marker methods. Here we have harnessed the haplotype-based method fineSTRUCTURE in an Irish genome-wide SNP dataset, identifying 23 discrete genetic clusters which segregate with geographical provenance. Cluster diversity is pronounced in the west of Ireland but reduced in the east where older structure has been eroded by historical migrations. Accordingly, when populations from the neighbouring island of Britain are included, a west-east cline of Celtic-British ancestry is revealed along with a particularly striking correlation between haplotypes and geography across both islands. A strong relationship is revealed between subsets of Northern Irish and Scottish populations, where discordant genetic and geographic affinities reflect major migrations in recent centuries. Additionally, Irish genetic proximity of all Scottish samples likely reflects older strata of communication across the narrowest inter-island crossing. Using GLOBETROTTER we detected Irish admixture signals from Britain and Europe and estimated dates for events consistent with the historical migrations of the Norse-Vikings, the Anglo-Normans and the British Plantations. The influence of the former is greater than previously estimated from Y chromosome haplotypes. In all, we paint a new picture of the genetic landscape of Ireland, revealing structure which should be considered in the design of studies examining rare genetic variation and its association with traits

Soccer Team Vectors

In this work we present STEVE - Soccer TEam VEctors, a principled approach for learning real valued vectors for soccer teams where similar teams are close to each other in the resulting vector space. STEVE only relies on freely available information about the matches teams played in the past. These vectors can serve as input to various machine learning tasks. Evaluating on the task of team market value estimation, STEVE outperforms all its competitors. Moreover, we use STEVE for similarity search and to rank soccer teams.Comment: 11 pages, 1 figure; This paper was presented at the 6th Workshop on Machine Learning and Data Mining for Sports Analytics at ECML/PKDD 2019, W\"urzburg, Germany, 201

Morphological characteristics of motor neurons do not determine their relative susceptibility to degeneration in a mouse model of severe spinal muscular atrophy

Spinal muscular atrophy (SMA) is a leading genetic cause of infant mortality, resulting primarily from the degeneration and loss of lower motor neurons. Studies using mouse models of SMA have revealed widespread heterogeneity in the susceptibility of individual motor neurons to neurodegeneration, but the underlying reasons remain unclear. Data from related motor neuron diseases, such as amyotrophic lateral sclerosis (ALS), suggest that morphological properties of motor neurons may regulate susceptibility: in ALS larger motor units innervating fast-twitch muscles degenerate first. We therefore set out to determine whether intrinsic morphological characteristics of motor neurons influenced their relative vulnerability to SMA. Motor neuron vulnerability was mapped across 10 muscle groups in SMA mice. Neither the position of the muscle in the body, nor the fibre type of the muscle innervated, influenced susceptibility. Morphological properties of vulnerable and disease-resistant motor neurons were then determined from single motor units reconstructed in Thy.1-YFP-H mice. None of the parameters we investigated in healthy young adult mice - including motor unit size, motor unit arbor length, branching patterns, motor endplate size, developmental pruning and numbers of terminal Schwann cells at neuromuscular junctions - correlated with vulnerability. We conclude that morphological characteristics of motor neurons are not a major determinant of disease-susceptibility in SMA, in stark contrast to related forms of motor neuron disease such as ALS. This suggests that subtle molecular differences between motor neurons, or extrinsic factors arising from other cell types, are more likely to determine relative susceptibility in SMA

Predicting short-term electricity demand through artificial neural network

Forecasting the consumption of electric power on a daily basis allows considerable money savings for the supplying companies, by reducing the expenses in generation and operation. Therefore, the cost of forecasting errors can be of such magnitude that many studies have focused on minimizing the forecasting error, which makes this topic as an integral part of planning in many companies of various kinds and sizes, ranging from generation, transmission, and distribution to consumption, by requiring reliable forecasting systems

A dynastic elite in monumental Neolithic society

The nature and distribution of political power in Europe during the Neolithic era remains poorly understood. During this period, many societies began to invest heavily in building monuments, which suggests an increase in social organization. The scale and sophistication of megalithic architecture along the Atlantic seaboard, culminating in the great passage tomb complexes, is particularly impressive. Although co-operative ideology has often been emphasised as a driver of megalith construction, the human expenditure required to erect the largest monuments has led some researchers to emphasize hierarchy—of which the most extreme case is a small elite marshalling the labour of the masses. Here we present evidence that a social stratum of this type was established during the Neolithic period in Ireland. We sampled 44 whole genomes, among which we identify the adult son of a first-degree incestuous union from remains that were discovered within the most elaborate recess of the Newgrange passage tomb. Socially sanctioned matings of this nature are very rare, and are documented almost exclusively among politico-religious elites—specifically within polygynous and patrilineal royal families that are headed by god-kings. We identify relatives of this individual within two other major complexes of passage tombs 150 km to the west of Newgrange, as well as dietary differences and fine-scale haplotypic structure (which is unprecedented in resolution for a prehistoric population) between passage tomb samples and the larger dataset, which together imply hierarchy. This elite emerged against a backdrop of rapid maritime colonization that displaced a unique Mesolithic isolate population, although we also detected rare Irish hunter-gatherer introgression within the Neolithic population

Web-based guided insulin self-titration in patients with type 2 diabetes: the Di@log study. Design of a cluster randomised controlled trial [TC1316]

<p>Abstract</p> <p>Background</p> <p>Many patients with type 2 diabetes (T2DM) are not able to reach the glycaemic target level of HbA1c < 7.0%, and therefore are at increased risk of developing severe complications. Transition to insulin therapy is one of the obstacles in diabetes management, because of barriers of both patient and health care providers. Patient empowerment, a patient-centred approach, is vital for improving diabetes management. We developed a web-based self-management programme for insulin titration in T2DM patients. The aim of our study is to investigate if this internet programme helps to improve glycaemic control more effectively than usual care.</p> <p>Methods/Design</p> <p>T2DM patients (n = 248), aged 35–75 years, with an HbA1c ≥ 7.0%, eligible for treatment with insulin and able to use the internet will be selected from general practices in two different regions in the Netherlands. Cluster randomisation will be performed at the level of general practices. Patients in the intervention group will use a self-developed internet programme to assist them in self-titrating insulin. The control group will receive usual care.</p> <p>Primary outcome is the difference in change in HbA1c between intervention and control group. Secondary outcome measures are quality of life, treatment satisfaction, diabetes self-efficacy and frequency of hypoglycaemic episodes. Results will be analysed according to the intention-to-treat principle.</p> <p>Discussion</p> <p>An internet intervention supporting self-titration of insulin therapy in T2DM patients is an innovative patient-centred intervention. The programme provides guided self-monitoring and evaluation of health and self-care behaviours through tailored feedback on input of glucose values. This is expected to result in a better performance of self-titration of insulin and consequently in the improvement of glycaemic control. The patient will be enabled to 'discover and use his or her own ability to gain mastery over his/her diabetes' and therefore patient empowerment will increase. Based on the self-regulation theory of Leventhal, we hypothesize that additional benefits will be achieved in terms of increases in treatment satisfaction, quality of life and self-efficacy.</p> <p>Trial registration</p> <p>Dutch Trial Register TC1316.</p

Pelagic connectivity of European sea bass between spawning and nursery grounds

The sea bass stock around the UK (northern stock) has declined rapidly over the past decade, likely due to a combination of both overfishing and low recruitment. Understanding mechanisms that drive the number of young reaching nursery grounds is important for explaining observed recruitment variability and therefore developing effective management strategies. An individual-based model (IBM) has been developed here to investigate factors affecting sea bass settlement on nursery grounds for the northern stock. Simulations considered seven years with varying environmental conditions and year class strength, and outputs were compared to empirical data from monitoring of nursery areas in the UK and Ireland. The IBM includes hydrodynamics to simulate the drift of eggs and larvae, temperature-dependent growth and mortality, and behavior affecting position in the water column. Comparison between the model and ICES assessment abundance of age class zero fish showed similar temporal variability, but with higher recruitment predicted for 2018, and a lower peak recruitment in 1997. The model reproduced general patterns of interannual variability for the Thames estuary, but performed less well for some other regions. Further investigation is needed to understand differences between modelled supply and observations, as these could be due to uncertainties in reproducing the physical environment (e.g., currents, temperature) or biology (e.g., spawning, behavior, mortality), as well as uncertainty in recruitment derived from stock assessments or data collected from nursery grounds. Nevertheless, the model provides a useful demonstration of connectivity between spawning and nursery grounds, showing spawning regions that are likely to have greatest influence on recruitment in different estuaries, and how these may vary interannually. For example, sources from western Channel and Celtic Sea can supply larvae to many areas, leading to connectivity across the Channel and Celtic Sea, and into the Irish Sea. However, other regions may depend on more local areas. For example, with the Solent estuary dependent on sources within the Channel each year. With the temperature-dependence on growth, and therefore duration of the pelagic stage, results show the potential influence of spawning timing, in relation to ocean temperatures, for connectivity between spawning and nursery grounds.</jats:p

The population genomics of archaeological transition in west Iberia: Investigation of ancient substructure using imputation and haplotype-based methods

We analyse new genomic data (0.05–2.95x) from 14 ancient individuals from Portugal distributed from the Middle Neolithic (4200–3500 BC) to the Middle Bronze Age (1740–1430 BC) and impute genomewide diploid genotypes in these together with published ancient Eurasians. While discontinuity is evident in the transition to agriculture across the region, sensitive haplotype-based analyses suggest a significant degree of local hunter-gatherer contribution to later Iberian Neolithic populations. A more subtle genetic influx is also apparent in the Bronze Age, detectable from analyses including haplotype sharing with both ancient and modern genomes, D-statistics and Y-chromosome lineages. However, the limited nature of this introgression contrasts with the major Steppe migration turnovers within third Millennium northern Europe and echoes the survival of non-Indo-European language in Iberia. Changes in genomic estimates of individual height across Europe are also associated with these major cultural transitions, and ancestral components continue to correlate with modern differences in stature