Social and content hybrid image recommender system for mobile social networks

One of the advantages of social networks is the possibility to socialize and personalize the content created or shared by the users. In mobile social networks, where the devices have limited capabilities in terms of screen size and computing power, Multimedia Recommender Systems help to present the most relevant content to the users, depending on their tastes, relationships and profile. Previous recommender systems are not able to cope with the uncertainty of automated tagging and are knowledge domain dependant. In addition, the instantiation of a recommender in this domain should cope with problems arising from the collaborative filtering inherent nature (cold start, banana problem, large number of users to run, etc.). The solution presented in this paper addresses the abovementioned problems by proposing a hybrid image recommender system, which combines collaborative filtering (social techniques) with content-based techniques, leaving the user the liberty to give these processes a personal weight. It takes into account aesthetics and the formal characteristics of the images to overcome the problems of current techniques, improving the performance of existing systems to create a mobile social networks recommender with a high degree of adaptation to any kind of user.

Recubrimientos autolubricantes cuasicristalinos tipo composite depositados mediante proyección térmica para aplicaciones espaciales y de alta temperatura

Los recubrimientos lubricantes sólidos son requeridos para reducir la fricción y prevenir el desgaste en componentes que operan a altas temperaturas o en vacío (vehículos espaciales, industria química, motores diésel, turbinas aeronáuticas y de generación de energía…). Los lubricantes líquidos pierden sus características cuando las condiciones de presión, temperatura o ambientales son severas (oxidación, inestabilidad térmica, volatilidad,…), por ejemplo los aceites minerales convencionales se descomponen a temperaturas próximas a 200 ºC. Por tanto, la única manera de poder conseguir una adecuada lubricación a temperaturas extremas es por medio de sólidos, que cada vez más, se aplican en forma de recubrimientos. Estos recubrimientos podrían ser empleados en componentes de vehículos espaciales reutilizables, donde se pueden alcanzar, en la reentrada en la atmósfera, temperaturas de 700 ºC (bisagras, rodamientos, articulaciones y zonas de sellado en las superficies de control, y rodamientos de las turbobombas y las cajas de engranajes). Dichos recubrimientos también deberían ser capaces de proporcionar una lubricación efectiva a bajas temperaturas para las operaciones en tierra, para las operaciones de arranque en frío, incluso en el espacio. El conjunto de requisitos que tendrían que satisfacer las capas tribológicas relacionadas con estas condiciones extremas es muy diverso, lo que hace que el concepto de capas tipo composite (aquéllas constituidas por varios componentes) sea, en principio, muy adecuado para estas aplicaciones. Recubrimientos composite proyectados térmicamente constituidos por una matriz dura y conteniendo lubricantes sólidos pueden ser una buena solución desde el punto de vista tribológico. El “Lewis Research Centre” de la NASA ha estado desarrollando recubrimientos autolubricantes tipo composite, constituidos por la combinación de materiales duros como el carburo de cromo, junto con lubricantes sólidos como plata o la eutéctica de fluoruros de calcio y bario, en una matriz de NiCr, para su uso en aplicaciones terrestres a alta temperatura. Estos recubrimientos han sido aplicados mediante proyección térmica, siendo denominados como series PS100, PS200, PS300 y PS400, reduciendo de forma significativa el coeficiente de fricción y mejorando la resistencia al desgaste en un amplio margen de temperaturas. Otra nueva familia de materiales con comportamiento tribológico prometedor son las aleaciones cuasicristalinas (QC). Presentan características muy atractivas: alta dureza, baja fricción, alto límite elástico de compresión... Son muy frágiles como materiales másicos, por lo que se intentan aplicar en forma de recubrimientos. Se pueden depositar mediante proyección térmica. Algunos de estos materiales cuasicristalinos, como AlCoFeCr, poseen coeficientes de dilatación próximos al de los materiales metálicos, alta estabilidad térmica, baja conductividad térmica y una elevada resistencia a la oxidación y a la corrosión en caliente. En esta tesis se han desarrollado recubrimientos tipo composite conteniendo cuasicristales como componente antidesgaste, NiCr como componente tenaz, y Ag y la eutéctica de BaF2-CaF2, como lubricantes sólidos. Estos recubrimientos han sido depositados con diferentes composiciones (denominadas TH100, TH103, TH200, TH400, TH600…) mediante distintos procesos de proyección térmica: plasma en aire (PS), plasma en baja presión (LPPS) y combustión a alta velocidad (HVOF). Los recubrimientos se han generado sobre el sustrato X-750, una superaleación base níquel, endurecible por precipitación, con muy buena resistencia mecánica y a la oxidación hasta temperaturas de 870 ºC y, además, es empleada en aplicaciones aeroespaciales e industriales. Los recubrimientos han sido caracterizados microestructuralmente en INTA (Instituto Nacional de Técnica Aeroespacial), mediante SEM-EDS (Scanning Electronic Microscopy-Energy Dispersive Spectroscopy) y XRD (X-Ray Diffraction), y tribológicamente mediante medidas de microdureza y ensayos en tribómetro POD (Pin On Disc) para determinar los coeficientes de fricción y de desgaste. Los recubrimientos han sido ensayados tribológicamente a alta temperatura en INTA y en vacío en AMTTARC (Aerospace and Space Materials Technology Testhouse – Austrian Research Centres), en Seibersdorf (Austria). Se ha estudiado la influencia de la carga normal aplicada, la velocidad lineal y el material del pin. De entre las diferentes series de recubrimientos cuasicristalinos tipo composite desarrolladas, dos de ellas, TH100 y TH103 han presentado una excelente calidad microestructural (baja porosidad, distribución uniforme de fases…) y se han mostrado como excelentes recubrimientos antidesgaste. Sin embargo, estas capas presentan un pobre comportamiento como autolubricantes a temperatura ambiente, aunque mejoran mucho a alta temperatura o en vacío. Los resultados del trabajo presentado en esta tesis han proporcionado nuevo conocimiento respecto al comportamiento tribológico de recubrimientos autolubricantes cuasicristalinos tipo composite depositados por proyección térmica. Sin embargo, dichos resultados, aunque son muy prometedores, no han puesto de manifiesto el adecuado comportamiento autolubricante que se pretendía y, además, como ocurre en cualquier trabajo de investigación, durante el desarrollo del mismo siempre aparecen nuevas dudas por resolver. Se proponen nuevas líneas de trabajo futuro que complementen los resultados obtenidos y que puedan encaminar hacia la obtención de un recubrimiento que mejore su comportamiento autolubricante. ABSTRACT Solid lubricant coatings are required to reduce friction and prevent wear in components that operate at high temperatures or under vacuum (space vehicles, chemical industry, diesel engines, power generation turbines and aeronautical turbines, for instance). In these cases neither greases nor liquid lubricants can be employed and the only practicable approach to lubrication in such conditions is by means of solids. These are increasingly applied in the form of coatings which should exhibit low shear strength, whilst maintaining their chemical stability at extremes temperatures and in the space environment. In the space field, these coatings would be employed in re-usable space plane applications, such as elevon hinges, where temperatures of 700 ºC are reached during re-entry into the Earth’s atmosphere. These coatings should also be capable of providing effective lubrication at lower temperatures since “cold start” operation may be necessary, even in the space environment. The diverse and sometimes conflictive requirements in high temperature and space-related tribological coatings make the concept of composite coatings highly suitable for these applications. Thermal-sprayed composites containing solid lubricants in a hard matrix perform well tribologically. NASA‘s Lewis Research Centre had developed self-lubricating composite coatings for terrestrial use, comprising hard materials like chromium carbide as well as solid lubricant additives such as silver and BaF2-CaF2 eutectic on a Ni-Cr matrix. These coatings series, named PS100, PS200, PS300 and PS400, are applied by thermal spray and significantly reduce friction coefficients, improving wear resistance over a wide temperature range. Quasicrystalline alloys (QC) constitute a new family of materials with promising tribological behaviour. Some QC materials exhibit a combination of adequate antifriction properties: low friction coefficient, high hardness and high yield strength under compression, and can be easily produced as coatings on top of metallic and non-metallic materials. Among these QC alloys, AlCoFeCr has high hardness (700 HV0.1), a thermal expansion coefficient close to that of metals, high thermal stability, low thermal conductivity and good oxidation and hot corrosion resistance. However most QC materials have the disadvantage of being very brittle. In order to take advantage of the excellent tribological properties of QCs, thick composite lubricant coatings were prepared containing them as the hard phase for wear resistance, Ag and BaF2-CaF2 eutectic as lubricating materials and NiCr as the tough component. These coatings were deposited in different composition mixtures (named TH100, TH103, TH200, TH400, TH600…) by different thermal spray processes: air plasma spray (PS), low pressure plasma spray (LPPS) and high velocity oxy-fuel (HVOF), on X-750 substrates. X-750 is an age-hardenable nickel-base superalloy with very good strength and a good resistance to oxidising combustion gas environments at temperatures up to about 870 ºC and it is widely used in aerospace and industrial applications. Coatings have been characterized microstructurally, at INTA (National Institute for Aerospace Technology), by means of SEM-EDS (Scanning Electronic Microscopy- Energy Dispersive Spectroscopy) and XRD (X-Ray Diffraction), and tribologically by microhardness measurements and pin-on-disc testing to determine friction coefficients as well as wear resistance. The coatings were tested tribologically at high temperature at INTA and under vacuum at AMTT-ARC (Aerospace and Space Materials Technology Testhouse – Austrian Research Centres), in Seibersdorf (Austria). Different loads, linear speeds and pin materials were studied. TH100 and TH103 QC alloy matrix composite coatings were deposited by HVOF with excellent microstructural quality (low porosity, uniform phase distribution) and showed to be excellent wear resistant coatings. However these QC alloy matrix composite coatings are poor as a self-lubricant at room temperature but much better at high temperature or in vacuum. The results from the work performed within the scope of this thesis have provided new knowledge concerning the tribological behavior of self-lubricating quasicrystalline composite coatings deposited by thermal spraying. Although these results are very promising, they have not shown an adequate self-lubricating behavior as was intended, and also, as in any research, the results have in addition raised new questions. Future work is suggested to complement the results of this thesis in order to improve the selflubricating behaviour of the coatings.

Uma abordagem baseada em filtragem colaborativa integrada a mapas de saliência para a recomendação de imagens

Nowadays, the amount of customers using sites for shopping is greatly increasing, mainly due to the easiness and rapidity of this way of consumption. The sites, differently from physical stores, can make anything available to customers. In this context, Recommender Systems (RS) have become indispensable to help consumers to find products that may possibly pleasant or be useful to them. These systems often use techniques of Collaborating Filtering (CF), whose main underlying idea is that products are recommended to a given user based on purchase information and evaluations of past, by a group of users similar to the user who is requesting recommendation. One of the main challenges faced by such a technique is the need of the user to provide some information about her preferences on products in order to get further recommendations from the system. When there are items that do not have ratings or that possess quite few ratings available, the recommender system performs poorly. This problem is known as new item cold-start. In this paper, we propose to investigate in what extent information on visual attention can help to produce more accurate recommendation models. We present a new CF strategy, called IKB-MS, that uses visual attention to characterize images and alleviate the new item cold-start problem. In order to validate this strategy, we created a clothing image database and we use three algorithms well known for the extraction of visual attention these images. An extensive set of experiments shows that our approach is efficient and outperforms state-of-the-art CF RS.

Collaborative Filtering with Data Classification : A Combined Approach to Hotel Recommendation Systems

Recommendation systems aim to help users make decisions more efficiently. The most widely used method in recommendation systems is collaborative filtering, of which, a critical step is to analyze a user's preferences and make recommendations of products or services based on similarity analysis with other users' ratings. However, collaborative filtering is less usable for recommendation facing the "cold start" problem, i.e. few comments being given to products or services. To tackle this problem, we propose an improved method that combines collaborative filtering and data classification. We use hotel recommendation data to test the proposed method. The accuracy of the recommendation is determined by the rankings. Evaluations regarding the accuracies of Top-3 and Top-10 recommendation lists using the 10-fold cross-validation method and ROC curves are conducted. The results show that the Top-3 hotel recommendation list proposed by the combined method has the superiority of the recommendation performance than the Top-10 list under the cold start condition in most of the times.

The role of context in image annotation and recommendation

With the rise of smart phones, lifelogging devices (e.g. Google Glass) and popularity of image sharing websites (e.g. Flickr), users are capturing and sharing every aspect of their life online producing a wealth of visual content. Of these uploaded images, the majority are poorly annotated or exist in complete semantic isolation making the process of building retrieval systems difficult as one must firstly understand the meaning of an image in order to retrieve it. To alleviate this problem, many image sharing websites offer manual annotation tools which allow the user to “tag” their photos, however, these techniques are laborious and as a result have been poorly adopted; Sigurbjörnsson and van Zwol (2008) showed that 64% of images uploaded to Flickr are annotated with < 4 tags. Due to this, an entire body of research has focused on the automatic annotation of images (Hanbury, 2008; Smeulders et al., 2000; Zhang et al., 2012a) where one attempts to bridge the semantic gap between an image’s appearance and meaning e.g. the objects present. Despite two decades of research the semantic gap still largely exists and as a result automatic annotation models often offer unsatisfactory performance for industrial implementation. Further, these techniques can only annotate what they see, thus ignoring the “bigger picture” surrounding an image (e.g. its location, the event, the people present etc). Much work has therefore focused on building photo tag recommendation (PTR) methods which aid the user in the annotation process by suggesting tags related to those already present. These works have mainly focused on computing relationships between tags based on historical images e.g. that NY and timessquare co-exist in many images and are therefore highly correlated. However, tags are inherently noisy, sparse and ill-defined often resulting in poor PTR accuracy e.g. does NY refer to New York or New Year? This thesis proposes the exploitation of an image’s context which, unlike textual evidences, is always present, in order to alleviate this ambiguity in the tag recommendation process. Specifically we exploit the “what, who, where, when and how” of the image capture process in order to complement textual evidences in various photo tag recommendation and retrieval scenarios. In part II, we combine text, content-based (e.g. # of faces present) and contextual (e.g. day-of-the-week taken) signals for tag recommendation purposes, achieving up to a 75% improvement to precision@5 in comparison to a text-only TF-IDF baseline. We then consider external knowledge sources (i.e. Wikipedia & Twitter) as an alternative to (slower moving) Flickr in order to build recommendation models on, showing that similar accuracy could be achieved on these faster moving, yet entirely textual, datasets. In part II, we also highlight the merits of diversifying tag recommendation lists before discussing at length various problems with existing automatic image annotation and photo tag recommendation evaluation collections. In part III, we propose three new image retrieval scenarios, namely “visual event summarisation”, “image popularity prediction” and “lifelog summarisation”. In the first scenario, we attempt to produce a rank of relevant and diverse images for various news events by (i) removing irrelevant images such memes and visual duplicates (ii) before semantically clustering images based on the tweets in which they were originally posted. Using this approach, we were able to achieve over 50% precision for images in the top 5 ranks. In the second retrieval scenario, we show that by combining contextual and content-based features from images, we are able to predict if it will become “popular” (or not) with 74% accuracy, using an SVM classifier. Finally, in chapter 9 we employ blur detection and perceptual-hash clustering in order to remove noisy images from lifelogs, before combining visual and geo-temporal signals in order to capture a user’s “key moments” within their day. We believe that the results of this thesis show an important step towards building effective image retrieval models when there lacks sufficient textual content (i.e. a cold start).

COMPARATIVE ANALYSIS OF EFFICIENCY AND OPERATING CHARACTERISTICS OF AUTOMOTIVE POWERTRAIN ARCHITECTURES THROUGH CHASSIS DYNAMOMETER TESTING

The thesis "COMPARATIVE ANALYSIS OF EFFICIENCY AND OPERATING CHARACTERISTICS OF AUTOMOTIVE POWERTRAIN ARCHITECTURES THROUGH CHASSIS DYNAMOMETER TESTING" was completed through a collaborative partnership between Michigan Technological University and Argonne National Laboratory under a contractual agreement titled "Advanced Vehicle Characterization at Argonne National Laboratory". The goal of this project was to investigate, understand and document the performance and operational strategy of several modern passenger vehicles of various architectures. The vehicles were chosen to represent several popular engine and transmission architectures and were instrumented to allow for data collection to facilitate comparative analysis. In order to ensure repeatability and reliability during testing, each vehicle was tested over a series of identical drive cycles in a controlled environment utilizing a vehicle chassis dynamometer. Where possible, instrumentation was preserved between vehicles to ensure robust data collection. The efficiency and fuel economy performance of the vehicles was studied. In addition, the powertrain utilization strategies, significant energy loss sources, tailpipe emissions, combustion characteristics, and cold start behavior were also explored in detail. It was concluded that each vehicle realizes different strengths and suffers from different limitations in the course of their attempts to maximize efficiency and fuel economy. In addition, it was observed that each vehicle regardless of architecture exhibits significant energy losses and difficulties in cold start operation that can be further improved with advancing technology. It is clear that advanced engine technologies and driveline technologies are complimentary aspects of vehicle design that must be utilized together for best efficiency improvements. Finally, it was concluded that advanced technology vehicles do not come without associated cost; the complexity of the powertrains and lifecycle costs must be considered to understand the full impact of advanced vehicle technology.

Development of a Predictive Control Function for a Plug-in Hybrid Electric Vehicle with Electrically-heated Catalyst

This master thesis work is focused on the development of a predictive EHC control function for a diesel plug-in hybrid electric vehicle equipped with a EURO 7 compliant exhaust aftertreatment system (EATS), with the purpose of showing the advantages provided by the implementation of a predictive control strategy with respect to a rule-based one. A preliminary step will be the definition of an accurate powertrain and EATS physical model, starting from already existing and validated applications. Then, a rule-based control strategy managing the torque split between the electric motor (EM) and the internal combustion engine (ICE) will be developed and calibrated, with the main target of limiting tailpipe NOx emission by taking into account EM and ICE operating conditions together with EATS conversion efficiency. The information available from vehicle connectivity will be used to reconstruct the future driving scenario, also referred to as electronic horizon (eHorizon), and in particular to predict ICE first start. Based on this knowledge, an EATS pre-heating phase can be planned to avoid low pollutant conversion efficiencies, thus preventing high NOx emission due to engine cold start. Consequently, the final NOx emission over the complete driving cycle will be strongly reduced, allowing to comply with the limits potentially set by the incoming EURO 7 regulation. Moreover, given the same NOx emission target, the gain achieved thanks to the implementation of an EHC predictive control function will allow to consider a simplified EATS layout, thus reducing the related manufacturing cost. The promising results achieved in terms of NOx emission reduction show the effectiveness of the application of a predictive control strategy focused on EATS thermal management and highlight the potential of a complete integration and parallel development of involved vehicle physical systems, control software and connectivity data management.

Non-invasive prenatal diagnosis of multiple endocrine neoplasia type 2A using COLD-PCR combined with HRM genotyping analysis from maternal serum.

The multiple endocrine neoplasia type 2A (MEN2A) is a monogenic disorder characterized by an autosomal dominant pattern of inheritance which is characterized by high risk of medullary thyroid carcinoma in all mutation carriers. Although this disorder is classified as a rare disease, the patients affected have a low life quality and a very expensive and continuous treatment. At present, MEN2A is diagnosed by gene sequencing after birth, thus trying to start an early treatment and by reduction of morbidity and mortality. We first evaluated the presence of MEN2A mutation (C634Y) in serum of 25 patients, previously diagnosed by sequencing in peripheral blood leucocytes, using HRM genotyping analysis. In a second step, we used a COLD-PCR approach followed by HRM genotyping analysis for non-invasive prenatal diagnosis of a pregnant woman carrying a fetus with a C634Y mutation. HRM analysis revealed differences in melting curve shapes that correlated with patients diagnosed for MEN2A by gene sequencing analysis with 100% accuracy. Moreover, the pregnant woman carrying the fetus with the C634Y mutation revealed a melting curve shape in agreement with the positive controls in the COLD-PCR study. The mutation was confirmed by sequencing of the COLD-PCR amplification product. In conclusion, we have established a HRM analysis in serum samples as a new primary diagnosis method suitable for the detection of C634Y mutations in MEN2A patients. Simultaneously, we have applied the increase of sensitivity of COLD-PCR assay approach combined with HRM analysis for the non-invasive prenatal diagnosis of C634Y fetal mutations using pregnant women serum.

Prominent use of distal 5’ transcription start sites and discovery of a large number of additional exons in ENCODE regions

This report presents systematic empirical annotation of transcript products from 399 annotated protein-coding loci across the 1% of the human genome targeted by the Encyclopedia of DNA elements (ENCODE) pilot project using a combination of 5' rapid amplification of cDNA ends (RACE) and high-density resolution tiling arrays. We identified previously unannotated and often tissue- or cell-line-specific transcribed fragments (RACEfrags), both 5' distal to the annotated 5' terminus and internal to the annotated gene bounds for the vast majority (81.5%) of the tested genes. Half of the distal RACEfrags span large segments of genomic sequences away from the main portion of the coding transcript and often overlap with the upstream-annotated gene(s). Notably, at least 20% of the resultant novel transcripts have changes in their open reading frames (ORFs), most of them fusing ORFs of adjacent transcripts. A significant fraction of distal RACEfrags show expression levels comparable to those of known exons of the same locus, suggesting that they are not part of very minority splice forms. These results have significant implications concerning (1) our current understanding of the architecture of protein-coding genes; (2) our views on locations of regulatory regions in the genome; and (3) the interpretation of sequence polymorphisms mapping to regions hitherto considered to be "noncoding," ultimately relating to the identification of disease-related sequence alterations.

Are cold winters in Europe associated with low solar activity?

Solar activity during the current sunspot minimum has fallen to levels unknown since the start of the 20th century. The Maunder minimum (about 1650–1700) was a prolonged episode of low solar activity which coincided with more severe winters in the United Kingdom and continental Europe. Motivated by recent relatively cold winters in the UK, we investigate the possible connection with solar activity. We identify regionally anomalous cold winters by detrending the Central England temperature (CET) record using reconstructions of the northern hemisphere mean temperature. We show that cold winter excursions from the hemispheric trend occur more commonly in the UK during low solar activity, consistent with the solar influence on the occurrence of persistent blocking events in the eastern Atlantic. We stress that this is a regional and seasonal effect relating to European winters and not a global effect. Average solar activity has declined rapidly since 1985 and cosmogenic isotopes suggest an 8% chance of a return to Maunder minimum conditions within the next 50 years (Lockwood 2010 Proc. R. Soc. A 466 303–29): the results presented here indicate that, despite hemispheric warming, the UK and Europe could experience more cold winters than during recent decades.

The solar influence on the probability of relatively cold UK winters in the future

Recent research has suggested that relatively cold UK winters are more common when solar activity is low (Lockwood et al 2010 Environ. Res. Lett. 5 024001). Solar activity during the current sunspot minimum has fallen to levels unknown since the start of the 20th century (Lockwood 2010 Proc. R. Soc. A 466 303–29) and records of past solar variations inferred from cosmogenic isotopes (Abreu et al 2008 Geophys. Res. Lett. 35 L20109) and geomagnetic activity data (Lockwood et al 2009 Astrophys. J. 700 937–44) suggest that the current grand solar maximum is coming to an end and hence that solar activity can be expected to continue to decline. Combining cosmogenic isotope data with the long record of temperatures measured in central England, we estimate how solar change could influence the probability in the future of further UK winters that are cold, relative to the hemispheric mean temperature, if all other factors remain constant. Global warming is taken into account only through the detrending using mean hemispheric temperatures. We show that some predictive skill may be obtained by including the solar effect.

Using seasonal hindcasts to understand the origin of the equatorial cold tongue bias in CGCMs and its impact on ENSO

The cold equatorial SST bias in the tropical Pacific that is persistent in many coupled OAGCMs severely impacts the fidelity of the simulated climate and variability in this key region, such as the ENSO phenomenon. The classical bias analysis in these models usually concentrates on multi-decadal to centennial time series needed to obtain statistically robust features. Yet, this strategy cannot fully explain how the models errors were generated in the first place. Here, we use seasonal re-forecasts (hindcasts) to track back the origin of this cold bias. As such hindcasts are initialized close to observations, the transient drift leading to the cold bias can be analyzed to distinguish pre-existing errors from errors responding to initial ones. A time sequence of processes involved in the advent of the final mean state errors can then be proposed. We apply this strategy to the ENSEMBLES-FP6 project multi-model hindcasts of the last decades. Four of the five AOGCMs develop a persistent equatorial cold tongue bias within a few months. The associated systematic errors are first assessed separately for the warm and cold ENSO phases. We find that the models are able to reproduce either El Niño or La Niña close to observations, but not both. ENSO composites then show that the spurious equatorial cooling is maximum for El Niño years for the February and August start dates. For these events and at this time of the year, zonal wind errors in the equatorial Pacific are present from the beginning of the simulation and are hypothesized to be at the origin of the equatorial cold bias, generating too strong upwelling conditions. The systematic underestimation of the mixed layer depth in several models can also amplify the growth of the SST bias. The seminal role of these zonal wind errors is further demonstrated by carrying out ocean-only experiments forced by the AOCGCMs daily 10-meter wind. In a case study, we show that for several models, this forcing is sufficient to reproduce the main SST error patterns seen after 1 month in the AOCGCM hindcasts.

Isotopic signature of specific biomarkers derived from anaerobic methanotrophic archaea (ANME groups) and sulphate-reducing bacteria (SRB) at different cold seep provinces

Anaerobic methane-oxidizing microbial communities in sediments at cold methane seeps are important factors in controlling methane emission to the ocean and atmosphere. Here, we investigated the distribution and carbon isotopic signature of specific biomarkers derived from anaerobic methanotrophic archaea (ANME groups) and sulphate-reducing bacteria (SRB) responsible for the anaerobic oxidation of methane (AOM) at different cold seep provinces of Hydrate Ridge, Cascadia margin. The special focus was on their relation to in situ cell abundances and methane turnover. In general, maxima in biomarker abundances and minima in carbon isotope signatures correlated with maxima in AOM and sulphate reduction as well as with consortium biomass. We found ANME-2a/DSS aggregates associated with high abundances of sn-2,3-di-O-isoprenoidal glycerol ethers (archaeol, sn-2-hydroxyarchaeol) and specific bacterial fatty acids (C16:1omega5c, cyC17:0omega5,6) as well as with high methane fluxes (Beggiatoa site). The low to medium flux site (Calyptogena field) was dominated by ANME-2c/DSS aggregates and contained less of both compound classes but more of AOM-related glycerol dialkyl glycerol tetraethers (GDGTs). ANME-1 archaea dominated deeper sediment horizons at the Calyptogena field where sn-1,2-di-O-alkyl glycerol ethers (DAGEs), archaeol, methyl-branched fatty acids (ai-C15:0, i-C16:0, ai-C17:0), and diagnostic GDGTs were prevailing. AOM-specific bacterial and archaeal biomarkers in these sediment strata generally revealed very similar d13C-values of around -100 per mill. In ANME-2-dominated sediment sections, archaeal biomarkers were even more 13C-depleted (down to -120 per mill), whereas bacterial biomarkers were found to be likewise 13C-depleted as in ANME-1-dominated sediment layers (d13C: -100 per mill). The zero flux site (Acharax field), containing only a few numbers of ANME-2/DSS aggregates, however, provided no specific biomarker pattern. Deeper sediment sections (below 20 cm sediment depth) from Beggiatoa covered areas which included solid layers of methane gas hydrates contained ANME-2/DSS typical biomarkers showing subsurface peaks combined with negative shifts in carbon isotopic compositions. The maxima were detected just above the hydrate layers, indicating that methane stored in the hydrates may be available for the microbial community. The observed variations in biomarker abundances and 13C-depletions are indicative of multiple environmental and physiological factors selecting for different AOM consortia (ANME-2a/DSS, ANME-2c/DSS, ANME-1) along horizontal and vertical gradients of cold seep settings.

Mats of psychrophilic thiotrophic bacteria associated with cold seeps of the Barents Sea

This study focused on the bacterial diversity associated with microbial mats of deep-sea cold seeps at the Norwegian continental margin. Study sites included the Storegga and Nyegga areas as well as the Håkon Mosby mud volcano, where the mats occurred at temperatures permanently close to the freezing point of seawater. Two visually different mat types, i.e. small gray mats and extensive white mats, were studied with the aim to determine the identity of the mat-forming sulfide oxidizers, and to investigate which environmental factors (e.g. sulfate reduction and methane oxidation rates) shown here could explain the observed diversity. Sequence data have been submitted to the EMBL database under accession No. FR847864-FR847887 (giant sulfur bacteria), No. FR827864 (Menez Gwen filament; see Supplementary Material) and No. FR875365-FR877509 (except FR875905; remaining partial sequences).