Communication, Information, Médias

Click-through rates are still the de facto measure of Internet advertising effectiveness. Unfortunately, click-through rates have plummeted. This decline prompts two critical questions: (1) Why do banner ads seem to be ineffective and (2) what can advertisers do to improve their effectiveness? To address these questions, we utilized an eye-tracking device to investigate online surfers’ attention to online advertising. Then we conducted a large-scale survey of Internet users’ recall, recognition, and awareness of banner advertising. Our research suggests that the reason why click-through rates are low is that surfers actually avoid looking at banner ads during their online activities. This implies that the larger part of a surfer's processing of banners will probably be done at the pre-attentive level. If such is the case, click-through rate is an ineffective measure of banner ad performance. Our research also shows that banner ads do have an impact on traditional memory-based measure of effectiveness. Thus, we claim that advertisers should rely more on traditional brand equity measures such as brand awareness and advertising recall. Using such measures, we show that repetition affects unaided advertising recall, brand recognition, and brand awareness and that a banner's message influences both aided advertising recall and brand recognition.

This study investigates the performances of four major global Leaf Area Index (LAI) products at 1/11.2° spatial sampling and a monthly time step: ECOCLIMAP climatology, GLOBCARBON (from SPOT/VEGETATION and ATSR/AATSR), CYCLOPES (from SPOT/VEGETATION) and MODIS Collection 4 (main algorithm, from MODIS/TERRA). These products were intercompared during the 2001–2003 period over the BELMANIP network of sites. Their uncertainty was assessed by comparison with 56 LAI reference maps derived from ground measurements. CYCLOPES and MODIS depict realistic spatial variations at continental scale, while ECOCLIMAP poorly captures surface spatial heterogeneity, and GLOBCARBON tends to display erratic variations. ECOCLIMAP and GLOBCARBON show the highest frequency of successful retrievals while MODIS and CYCLOPES retrievals are frequently missing in winter over northern latitudes and over the equatorial belt. CYCLOPES and MODIS describe consistent temporal profiles over most vegetation types, while ECOCLIMAP does not show any interannual variations, and GLOBCARBON can exhibit temporal instability during the growing season over forests. The CYCLOPES, MODIS, and GLOBCARBON LAI values agree better over croplands and grasslands than over forests, where differences in vegetation structure representation between algorithms and surface reflectance uncertainties lead to substantial discrepancies between products. CYCLOPES does not reach high enough LAI values to properly characterize forests. In contrast, the other products have sufficient dynamic range of LAI to describe the global variability of LAI. Overall, CYCLOPES is the most similar product to the LAI reference maps. However, more accurate ground measurements and better representation of the global and seasonal variability of vegetation are required to refine this result.

The Globcover initiative comprises the development and demonstration of a service that in first instance produces a global land cover map for year 2005/2006. Globcover uses MERIS fine resolution (300 m) mode data acquired between mid 2005 and mid 2006 and, for maximum user benefit, the thematic legend is compatible with the UN land cover classification system (LCCS). This new product updates and complements the other existing comparable global products, such as the global land cover map at 1 km resolution for the year 2000 (GLC2000) produced by JRC. It is expected to improve such previous global product, in particular because of the finer spatial resolution. The Globcover project is an initiative of ESA in cooperation with an international network of partner including EEA, FAO, GOFC-GOLD, IGBP, JRC and UNEP.

BACKGROUND AND OBJECTIVE: Machine learning and deep learning models are very powerful in predicting the presence of a disease. To achieve good predictions, those models require a certain amount of data to train on, whereas this amount i) is generally limited and difficult to obtain; and, ii) increases with the complexity of the interactions between the outcome (disease presence) and the model variables. This study compares the ways training dataset size and interactions affect the performance of those prediction models. METHODS: To compare the two influences, several datasets were simulated that differed in the number of observations and the complexity of the interactions between the variables and the outcome. A few logistic regressions and neural networks were trained on the simulated datasets and their performance evaluated by cross-validation and compared using accuracy, F1 score, and AUC metrics. RESULTS: Models trained on simulated datasets without interactions provided good results: AUC close to 0.80 with either logistic regression or neural networks. Models trained on simulated dataset with order 2 interactions led also to AUCs close to 0.80 with either logistic regression or neural networks. Models trained on simulated datasets with order 4 interactions led to AUC close to 0.80 with neural networks and 0.85 with penalized logistic regressions. Whatever the interaction order, increasing the dataset size did not significantly affect model performance, especially that of machine learning models. CONCLUSION: Machine learning models were the less influenced by the dataset size but needed interaction terms to achieve good performance, whereas deep learning models could achieve good performance without interaction terms. Conclusively, with the considered scenarios, well-specified machine learning models outperformed deep learning models.

BACKGROUND: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. METHODS: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. RESULTS: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10(-11)), cholesterol transport (P = 2.96 × 10(-9)), and proteasome-ubiquitin activity (P = 1.34 × 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05). CONCLUSIONS: The immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.

Fluctuating prey populations and their effects on avian predator population dynamics have been studied particularly at high latitudes, where prey populations, especially microtines, are known to be cyclic; raptors show both numerical and functional responses to variations in their prey. In this paper, we investigate the response of a migratory raptor (Montagu's Harrier, Circus pygargus) to variations in abundance of its main prey (common vole, Microtus arvalis) in France. We document multiannual fluctuation in the abundance of common voles. The numerical response of Montagu's Harrier to this variable food supply was studied using breeding parameters (breeding density, breeding phenology, and various measures of breeding success). Breeding density and mean clutch size were strongly correlated with spring vole abundance, whereas mean brood size at fledging was correlated positively with summer vole abundance. The mechanism involved in the numerical response of Montagu's Harrier indicates that dispersal and colonization by yearlings may be more important than natality per se. Pellets collected between 1986 and 1997 were used to determine the functional response of Montagu's Harrier to variations in vole abundance. In terms of biomass, Montagu's Harrier diet consisted mainly of voles (33.7–86.6%, between 1986 and 1997). Vole biomass in pellets was closely related to vole abundance estimated by trapping. A type II functional response was detected, with satiation at high prey density, as the shapes of many relationships between breeding parameters and vole abundance were more curvilinear than linear. Our results fit the pattern of relationships between predators and cyclic prey found in Fennoscandia, in which specialist predators show a strong numerical response, although at such a temperate latitude, a more pronounced functional response might have been expected.

The Convention on Biological Diversity (CBD) aims at the conservation of all three levels of biodiversity, that is, ecosystems, species and genes. Genetic diversity represents evolutionary potential and is important for ecosystem functioning. Unfortunately, genetic diversity in natural populations is hardly considered in conservation strategies because it is difficult to measure and has been hypothesised to co-vary with species richness. This means that species richness is taken as a surrogate of genetic diversity in conservation planning, though their relationship has not been properly evaluated. We tested whether the genetic and species levels of biodiversity co-vary, using a large-scale and multi-species approach. We chose the high-mountain flora of the Alps and the Carpathians as study systems and demonstrate that species richness and genetic diversity are not correlated. Species richness thus cannot act as a surrogate for genetic diversity. Our results have important consequences for implementing the CBD when designing conservation strategies.

This paper presents a novel supervised convolutional neural network architecture, "DUCK-Net", capable of effectively learning and generalizing from small amounts of medical images to perform accurate segmentation tasks. Our model utilizes an encoder-decoder structure with a residual downsampling mechanism and a custom convolutional block to capture and process image information at multiple resolutions in the encoder segment. We employ data augmentation techniques to enrich the training set, thus increasing our model's performance. While our architecture is versatile and applicable to various segmentation tasks, in this study, we demonstrate its capabilities specifically for polyp segmentation in colonoscopy images. We evaluate the performance of our method on several popular benchmark datasets for polyp segmentation, Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB, and ETIS-LARIBPOLYPDB showing that it achieves state-of-the-art results in terms of mean Dice coefficient, Jaccard index, Precision, Recall, and Accuracy. Our approach demonstrates strong generalization capabilities, achieving excellent performance even with limited training data.

<h3>ABSTRACT</h3> This article provides empirical evidence of a model for effectiveness of event marketing and illustrates the application of the model. The model is founded on research within sponsorship, advertising effectiveness, and the latest research on emotional responses within consumer behavior and neuropsychological theory. The model is formulated as a structural equation model with latent variables. Based on a golf tournament as the event activity for the well-known Danish corporate brand B&amp;O, it is demonstrated how the model and measurement system can estimate the impact of the event on brand attitude as well as buying intention. It gives a better understanding of how an event influences the perception of a brand in the minds of the customers. Hereby the model can give directions for how an event should be designed to create positive brand attitude and buying intention.

The need for orientation is the most prominent contingent condition for agenda-setting effects. It provides a psychological explanation for why people engage in information seeking and why some people are susceptible to agenda-setting effects while others are not. The purpose of this paper is to present the development and empirical validation of a three-dimensional scale of need for orientation. Based on a review of previous measures, three dimensions of need for orientation are posited: The need for orientation towards issues, the need for orientation towards facts and the need for orientation towards journalistic evaluations. In a first step, the model is tested on a representative sample applying confirmatory factor analysis. After some modifications, the model is finally validated on another, independent sample. A series of studies demonstrate the psychometric properties of the measure and its construct validity with respect to related constructs. The theoretical utility of the construct and the measure of need for orientation are discussed.

Frontotemporal dementia (FTD) refers to a disease spectrum including the behavioral variant FTD (bvFTD), primary progressive aphasia (PPA), progressive supranuclear palsy/corticobasal degeneration syndrome (PSP/CBDS), and FTD with amyotrophic lateral sclerosis (FTD-ALS). A GGGGCC expansion in C9ORF72 is a major cause of FTD and ALS. C9ORF72 was analyzed in 833 bvFTD, FTD-ALS, PPA, and PSP/CBDS probands; 202 patients from 151 families carried an expansion. C9ORF72 expansions were much more frequent in the large subgroup of patients with familial FTD-ALS (65.9%) than in those with pure FTD (12.8%); they were even more frequent than in familial pure ALS, according to estimated frequencies in the literature (23-50%). The frequency of carriers in non-familial FTD-ALS (12.7%) indicates that C9ORF72 should be analyzed even when family history is negative. Mutations were detected in 6.8% of PPA patients, and in 3.2% of patients with a clinical phenotype of PSP, thus enlarging the phenotype spectrum of C9ORF72. Onset was later in C9ORF72 (57.4 years, 95%CI: 55.9-56.1) than in MAPT patients (46.8, 95%CI: 43.0-50.6; p = 0.00001) and the same as in PGRN patients (59.6 years; 95%CI: 57.6-61.7; p = 0.4). ALS was more frequent in C9ORF72 than in MAPT and PGRN patients; onset before age 50 and parkinsonism were indicative of MAPT mutations, whereas hallucinations were indicative of PGRN mutations; prioritization of genetic testing is thus possible. Penetrance was age- and gender-dependent: by age 50, 78% of male carriers were symptomatic, but only 52% of females. This can also guide genetic testing and counseling. A flowchart for genetic testing is thus proposed.

Ultramafic vertisols cover large areas in Albania and offer opportunities for phytomining. We undertook a field experiment with native Alyssum murale on two representative Vertisols at a distance of 20 km from each other (Pojskë and Domosdovë, Albania), to test the effect of planting density (transplanted seedlings) on a phytomining cropping system. Both areas were cleared in late summer 2012 and then ploughed and the soils were characterised. At Domosdovë, an area of 0.5 ha was planted with local native seedlings at a density of six plants per square metre in September 2012. Spontaneous plants that had germinated in Spring 2012 were left to grow without any competition from other plants on a second 0.1-ha plot at Domosdovë. All plots were weeded manually in the autumn of 2012 and spring of 2013. Individual plants occupied ~1 m2 at maturity. At Pojskë, an area of 0.3 ha was also planted in September 2012 with local native seedlings of A. murale at a density of four plants per square metre. Plants grown at initial densities of four and six plants per square metre did not fully cover the ground; gaps were filled in naturally by a second spontaneous generation of A. murale seedlings (recruits) that had germinated in Autumn 2012. Other weeds were eliminated with herbicides. At Domosdovë, at densities of one and six plants and at Pojskë of four plants per square metre, the biomass yield was 10, 5 and 10 t ha–1, respectively. Concentration of phytoextracted nickel was 77, 41 and 112 kg ha–1. We suggest that a density of four plants per square metre is suitable for phytoextraction with native populations of A. murale. A. murale can be a weed itself and lower the nickel phytoextraction yield. Plants responded differently in their native environment than in previous field trials in North America.

ABSTRACT It is increasingly recognised that land degradation monitoring and assessment can benefit from incorporating multiple sources of knowledge, using a variety of methods at different scales, including the perspectives of researchers, land managers and other stakeholders. However, the knowledge and methods required to achieve this are often dispersed across individuals and organisations at different levels and locations. Appropriate knowledge management mechanisms are therefore required to more efficiently harness these different sources of knowledge and facilitate their broader dissemination and application. This paper examines what knowledge is, how it is generated and explores how it may be stored, transferred and exchanged between knowledge producers and users before it is applied to monitor and assess land degradation at the local scale. It suggests that knowledge management can also benefit from the development of mechanisms that promote changes in understanding and efficient means of accessing and/or brokering knowledge. Broadly, these processes for knowledge management can (i) help identify and share good practices and build capacity for land degradation monitoring at different scales and in different contexts and (ii) create knowledge networks to share lessons learned and monitoring data among and between different stakeholders, scales and locations. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Au sein des sociétés capitalistes avancées, la question de l’appropriation des technologies numériques d’information et de communication (TNIC) s’impose comme une problématique centrale. Si le facteur technique n’est pas une préoccupation majeure de la raison sociologique contemporaine, les sciences sociales peuvent néanmoins se prévaloir d’un nombre très important de travaux conduits ces trente dernières années sur les usages de l’informatique connectée, tant dans la sphère domestique que dans les espaces professionnels. Réunissant les contributions de dix chercheurs réputés, cet ouvrage n’a pas pour objectif de proposer une dissertation théorique mais, dans une démarche résolument polyphonique, d’offrir un ensemble de travaux pertinents et originaux.

The GlobCover project has developed a service dedicated to the generation of multiyear global land cover maps at 300-m spatial resolution using as its main source of data the full-resolution full-swath (300 m) data (FRS) acquired by the MERIS sensor on-board the ENVISAT satellite. As multiple single daily orbits have to be combined in one single data set, an accurate relative and absolute geolocation of GlobCover orthorectified products is required and needs to be assessed. We describe in this paper the main steps of the orthorectification pre-processing chain as well as the validation methodology and geometric performance assessments. Final results are very satisfactory with an absolute geolocation error of 77-m rms and a relative geolocation error of 51-m rms.

The new robot named light puncture robot (LPR), has an original compact body-supported architecture, which is naturally able to follow the patient's body surface respiratory movements for abdominal and thoracic percutaneous procedures, which is compatible with CT, open MRI, and closed MRI. It is entirely made of plastic and uses MR-compatible pneumatic actuators powered by compressed air. It is localized via an image-based control using a localization device that is totally integrated to the robot. The physician is also included in the control loop, since he/she selects the target and the entry point and supervises the whole process.

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The prototype of a communicating underclothe for medical remote monitoring was realized. It delivers physiological information on the subject (Cardiac Frequency, Breathing Frequency, surface and mid-temperature) as well as the environment and activity parameters (ambient temperature, fall detection). It also enables the automatic data transfer on event, with the localization of the subject.

L’observation des champs de recherche sur la question de la « médiatisation » conduit à un double constat : la tendance à la simple juxtaposition des approches, l’insuffisante prise en compte de la dimension discursive dans l’analyse de la médiatisation comme construction sociale. La remise en questions de la notion, dans le cadre d’une approche constructiviste, amène les auteurs à proposer la notion de « discursivité sociale » comme ensemble de formes et de contenus et comme processus en co-construction permanente. Les implications d’une telle notion sont envisagées notamment dans l’analyse des « problèmes (configurés comme) publics » en en pointant, en particulier, les implications méthodologiques et épistémologiques.

BACKGROUND: The Alzheimer's Disease Assessment Scale (ADAS) was designed as a rating scale for the severity of dysfunction in the cognitive and non-cognitive behaviours that are characteristic of persons with Alzheimer's disease. Its subscale, the ADAS-cog, is a cognitive testing instrument most widely used to measure the impact of the disease. However, the ADAS-cog takes more than 45 min to administer and requires a qualified clinical psychologist as the rater. A more comprehensive rating battery is therefore required. In the present study, we developed a computerized test battery named the Touch Panel-type Dementia Assessment Scale (TDAS), which was intended to substitute for the ADAS-Cog, and was specifically designed to rate cognitive dysfunction quickly and without the need of a specialist rater. METHODS: The hardware for the TDAS comprises a 14-inch touch panel display and computer devices built into one case. The TDAS runs on Windows OS and was bundled with a custom program made with reference to the ADAS-cog. Participants in the present study were 34 patients with Alzheimer's disease. Each participant was administered the ADAS-cog and the TDAS. The test scores for each patient were compared to determine whether the severity of cognitive dysfunction of the patients could be rated equally as well by both tests. RESULTS: Pearson's correlation coefficient showed a significant correlation between the total scores (r= 0.69, P < 0.01) on the two scales for each patient. The Kendall coefficients of concordance obtained for the three corresponding pairs of tasks (word recognition, orientation, and naming object and fingers) showed the three TDAS tasks can rate symptoms of cognitive decline equally as well as the corresponding items on the ADAS-cog. CONCLUSIONS: The TDAS appears to be a sensitive and comprehensive assessment battery for rating the symptoms of Alzheimer's disease, and can be substituted for the ADAS-cog.