Fast algorithm for border bases of Artinian Gorenstein algebras

Given a multi-index sequence $$\sigma$$, we present a new efficient algorithm to compute generators of the linear recurrence relations between the terms of $$\sigma$$. We transform this problem into an algebraic one, by identifying multi-index sequences, multivariate formal power series and linear functionals on the ring of multivariate polynomials. In this setting, the recurrence relations are the elements of the kerne l$I$\sigma of the Hankel operator $H$\sigma associated to $$\sigma$$. We describe the correspondence between multi-index sequences with a Hankel operator of finite rank and Artinian Gorenstein Algebras. We show how the algebraic structure of the Artinian Gorenstein algebra $A$\sigma$$associated to the sequence$$\sigma yields the structure of the terms $\sigma\alpha$for all$$\alpha$ $\in$ N n$. This structure is explicitly given by a border basis of$A$\sigma$$, which is presented as a quotient of the polynomial ring$K[x 1 ,. .. , xn$] by the kernel$I$\sigma$$of the Hankel operator$H$\sigma$$. The algorithm provides generators of$I$\sigma$$constituting a border basis, pairwise orthogonal bases of$A$\sigma$$ and the tables of multiplication by the variables in these bases. It is an extension of Berlekamp-Massey-Sakata (BMS) algorithm, with improved complexity bounds. We present applications of the method to different problems such as the decomposition of functions into weighted sums of exponential functions, sparse interpolation, fast decoding of algebraic codes, computing the vanishing ideal of points, and tensor decomposition. Some benchmarks illustrate the practical behavior of the algorithm

Persuading consumers to reduce their consumption of electricity in the home

Previous work has identified that providing real time feedback or interventions to consumers can persuade consumers to change behaviour and reduce domestic electricity consumption. However, little work has investigated what exactly those feedback mechanisms should be. Most past work is based on an in-home display unit, possibly complemented by lower tariffs and delayed use of non-essential home appliances such as washing machines. In this paper we focus on four methods for real time feedback on domestic energy use, developed to gauge the impact on energy consumption in homes. Their feasibility had been tested using an experimental setup of 24 households collecting minute-by-minute electricity consumption data readings over a period of 18 months. Initial results are mixed, and point to the difficulties of sustaining a reduction in energy consumption, i.e. persuading consumers to change their behaviour. Some of the methods we used exploit small group social dynamics whereby people want to conform to social norms within groups they identify with. It may be that a variety of feedback mechanisms and interventions are needed in order to sustain user interest

Potential impact of multiple interventions on HIV incidence in a hyperendemic region in Western Kenya : a modelling study

Background: Multiple prevention interventions, including early antiretroviral therapy initiation, may reduce HIV incidence in hyperendemic settings. Our aim was to predict the short-term impact of various single and combined interventions on HIV spreading in the adult population of Ndhiwa subcounty (Nyanza Province, Kenya). Methods: A mathematical model was used with data on adults (15-59 years) from the Ndhiwa HIV Impact in Population Survey to compare the impacts on HIV prevalence, HIV incidence rate, and population viral load suppression of various interventions. These interventions included: improving the cascade of care (use of three guidelines), increasing voluntary medical male circumcision (VMMC), and implementing pre-exposure prophylaxis (PrEP) use among HIV-uninfected women. Results: After four years, improving separately the cascade of care under the WHO 2013 guidelines and under the treat-all strategy would reduce the overall HIV incidence rate by 46 and 58 %, respectively, vs. the baseline rate, and by 35 and 49 %, respectively, vs. the implementation of the current Kenyan guidelines. With conservative and optimistic scenarios, VMMC and PrEP would reduce the HIV incidence rate by 15-25 % and 22-28 % vs. the baseline, respectively. Combining the WHO 2013 guidelines with VMMC would reduce the HIV incidence rate by 35-56 % and combining the treat-all strategy with VMMC would reduce it by 49-65 %. Combining the WHO 2013 guidelines, VMMC, and PrEP would reduce the HIV incidence rate by 46-67 %. Conclusions: The impacts of the WHO 2013 guidelines and the treat-all strategy were relatively close; their implementation is desirable to reduce HIV spread. Combining several strategies is promising in adult populations of hyperendemic areas but requires regular, reliable, and costly monitoring

Influence of arrays errors on the performances of radar adaptive antenna processing

The purpose of ibis chapter is to present some results concerning the impact of array errors residuals, after calibration of the antenna, on the performances of adoptive array processing in radar applications . Adoptive array processing is a means for detecting targets in presence of jammers, e.g. in presence of spatially coloured noise. The processing concept is recalled, and indexes of performance examined. Some models of array errors are presented concerning for instance, complex gains différences, or transfert function différences, from channel to channel . Two examples illustrate the influence of the various types of error on the processing performancesL'objet de ce chapitre est de présenter quelques élements d'analyse relatifs à l'influence des imperfections de calibration d'antenne sur les performances de traitements de formation de voies adaptives en radar. Ce type de traitement est mis en place pour détecter les cibles en présence de brouillage, ce qui se traduit par une coloration spatiale du bruit de réception. On rappelle dans un premier temps les caractéristiques générales des traitements considérés et les critères de performances examiné

Hyperspectral imaging for phenotyping plant drought stress and nitrogen interactions using multivariate modelling and machine learning techniques in wh

Accurate detection of drought stress in plants is essential for water use efficiency and agricultural output. Hyperspectral imaging (HSI) provides a non-invasive method in plant phenotyping, allowing the long-term monitoring of plant health due to sensitivity to subtle changes in leaf constituents. The broad spectral range of HSI enables the development of different vegetation indices (VIs) to analyze plant trait responses to multiple stresses, such as the combination of nutrient and drought stresses. However, known VIs may underperform when subjected to multiple stresses. This study presents new VIs in tandem with machine learning models to identify drought stress in wheat plants under varying nitrogen (N) levels. A pot wheat experiment was set up in the glasshouse with four treatments: well-watered high-N (WWHN), well-watered low-N (WWLN), drought-stress high-N (DSHN) and drought-stress low-N (DSLN). In addition to ensuring that plants were watered according to the experiment design, photosynthetic rate (Pn) and stomatal conductance (gs) (which are used to assess plant drought stress) were taken regularly, serving as the ground truth data for this study. The proposed VIs, together with known VIs, were used to train three classification models: support vector machines (SVM), random forest (RF), and deep neural networks (DNN) to classify plants based on their drought status. The proposed VIs achieved more than 0.94 accuracy across all models, and their performance further increased when combined with known VIs. The combined VIs were used to train three regression models to predict the stomatal conductance and photosynthetic rates of plants. The random forest regression model performed best, suggesting that it could be used as a stand-alone tool to forecast gs and Pn and track drought stress in wheat. This study shows that combining hyperspectral data with machine learning can effectively monitor and predict drought stress in crops, especially in varying nitrogen condition

Analysis of Safety from a Human Clinical Trial with Pterostilbene

Objectives. The purpose of this trial was to evaluate the safety of long-term pterostilbene administration in humans. Methodology. The trial was a prospective, randomized, double-blind placebo-controlled intervention trial enrolling patients with hypercholesterolemia (defined as a baseline total cholesterol ≥200 mg/dL and/or baseline low-density lipoprotein cholesterol ≥100 mg/dL). Eighty subjects were divided equally into one of four groups: (1) pterostilbene 125 mg twice daily, (2) pterostilbene 50 mg twice daily, (3) pterostilbene 50 mg + grape extract (GE) 100 mg twice daily, and (4) matching placebo twice daily for 6–8 weeks. Safety markers included biochemical and subjective measures. Linear mixed models were used to estimate primary safety measure treatment effects. Results. The majority of patients completed the trial (91.3%). The average age was 54 years. The majority of patients were females (71%) and Caucasians (70%). There were no adverse drug reactions (ADRs) on hepatic, renal, or glucose markers based on biochemical analysis. There were no statistically significant self-reported or major ADRs. Conclusion. Pterostilbene is generally safe for use in humans up to 250 mg/day

Genetic diversity in nitrogen fertilizer responses and N gas emission in modern wheat

Crops assimilate nitrogen (N) as ammonium via the glutamine synthetase/glutamate synthase (GS/GOGAT) pathway which is of central importance for N uptake and potentially represents a bottle neck for N fertilizer-use efficiency. The aim of this study was to assess whether genetic diversity for N-assimilation capacity exists in wheat and could be exploited for breeding. Wheat plants rapidly, within 6h, responded to N application with an increase in GS activity. This was not accompanied by an increase in GS gene transcript abundance and a comparison of GS1 and GS2 protein models revealed a high degree of sequence conservation. N responsiveness amongst ten wheat varieties was assessed by measuring GS enzyme activity, leaf tissue ammonium, and by a leaf-disc assay as a proxy for apoplastic ammonia. Based on these data, a high-GS group showing an overall positive response to N could be distinguished from an inefficient, low-GS group. Subsequent gas emission measurements confirmed plant ammonia emission in response to N application and also revealed emission of N2O when N was provided as nitrate, which is in agreement with our current understanding that N2O is a by-product of nitrate reduction. Taken together, the data suggest that there is scope for improving N assimilation capacity in wheat and that further investigations into the regulation and role of GS-GOGAT in NH3 emission is justified. Likewise, emission of the climate gas N2O needs to be reduced, and future research should focus on assessing the nitrate reductase pathway in wheat and explore fertilizer management options

On Embeddability of Buses in Point Sets

Set membership of points in the plane can be visualized by connecting corresponding points via graphical features, like paths, trees, polygons, ellipses. In this paper we study the \emph{bus embeddability problem} (BEP): given a set of colored points we ask whether there exists a planar realization with one horizontal straight-line segment per color, called bus, such that all points with the same color are connected with vertical line segments to their bus. We present an ILP and an FPT algorithm for the general problem. For restricted versions of this problem, such as when the relative order of buses is predefined, or when a bus must be placed above all its points, we provide efficient algorithms. We show that another restricted version of the problem can be solved using 2-stack pushall sorting. On the negative side we prove the NP-completeness of a special case of BEP.Comment: 19 pages, 9 figures, conference version at GD 201

Pterostilbene on Metabolic Parameters: A Randomized, Double-Blind, and Placebo-Controlled Trial

Introduction. The purpose of this trial was to evaluate the effect of pterostilbene on metabolic parameters. Methods. A prospective, randomized, double-blind, and placebo-controlled study that enrolled 80 patients with a total cholesterol ≥200 mg/dL and/or LDL≥100 mg/dL. Subjects were divided into four groups: (1) pterostilbene 125 mg twice daily; (2) pterostilbene 50 mg twice daily; (3) pterostilbene 50 mg + grape extract (GE) 100 mg twice daily; (4) matching placebo twice daily for 6–8 weeks. Endpoints included lipids, blood pressure, and weight. Linear mixed models were used to examine and compare changes in parameters over time. Models were adjusted for age, gender, and race. Results. LDL increased with pterostilbene monotherapy (17.1 mg/dL; P=0.001) which was not seen with GE combination (P=0.47). Presence of a baseline cholesterol medication appeared to attenuate LDL effects. Both systolic (−7.8 mmHg; P<0.01) and diastolic blood pressure (−7.3 mmHg; P<0.001) were reduced with high dose pterostilbene. Patients not on cholesterol medication (n=51) exhibited minor weight loss with pterostilbene (−0.62 kg/m2; P=0.012). Conclusion. Pterostilbene increases LDL and reduces blood pressure in adults. This trial is registered with Clinicaltrials.gov NCT01267227

Epidemiology of paraneoplastic neurologic syndromes and autoimmune encephalitides in France

OBJECTIVE: To determine the observed and expected incidence rates of paraneoplastic neurologic syndromes (PNSs) and autoimmune encephalitides (AEs) diagnosed in France between 2016 and 2018, we conducted a population-based epidemiologic study. METHODS: Observed incidence rates were stratified by sex, age groups, region of care, year of diagnosis, and disease subgroups. National expected incidence rates were calculated based on rates obtained in the area directly adjacent to the Reference Center using a mixed Poisson model and compared with observed incidence rates. RESULTS: Six hundred thirty-two patients with definite PNS or AE met the inclusion criteria. The observed incidence rate of definite PNS and AE in France was 3.2 per million person-years (CI95%: 2.9-3.4) compared with an expected incidence rate of 7.1 per million person-years (CI95%: 3.9-11.4). The national observed incidence rate for the antibody-positive AE subgroup increased from 1.4 per million person-years (CI95%: 1.2-1.7) in 2016 to 2.1 per million person-years (CI95%: 1.7-2.4) in 2018, thus surpassing the incidence rate of classical PNS (1.2 per million person-years [CI95%: 1.0-1.5]) of 2018. CONCLUSIONS: There was a significant widespread year-to-year increase in the incidence of diagnoses registered with the Reference Center for all subgroups of PNS and AE studied. The national observed incidence rate is likely underestimated due to underdiagnosis and underreporting