The influence of holes in the mechanical properties of EWT solar cells

EWT back contact solar cells are manufactured from very thin silicon wafers. These wafers are drilled by means of a laser process creating a matrix of tiny holes with a density of approximately 125 holes per square centimeter. Their influence in the stiffness and mechanical strength has been studied. To this end, both wafers with and without holes have been tested with the ring on ring test. Numerical simulations of the tests have been carried out through the Finite Element Method taking into account the non-linearities present in the tests. It's shown that one may use coarse meshes without holes to simulate the test and after that sub models are used for the estimation of the stress concentration around the holes

OPTIMIZING THE DENSITY OF HOLES OF EWT SOLAR CELLS TAKING INTO CONSIDERATION MECHANICAL ASPECTS

ABSTRACT: EWT solar cells start from drilled wafers with approximately 100 holes/cm 2 . These holes act as stress concentrators leading to a reduction in the mechanical strength of this type of wafers. The viability of cells with higher density of holes has been studied. To this end, sets of wafers with different density of holes have been characterized. The ring on ring test has been employed and FE models have been developed to simulate the test. The statistical evaluation permits to draw conclusions about the reduction of the strength depending on the density of holes. Moreover, the stress concentration around the holes has been studied by means of the FE method employing the sub-modeling technique. The maximum principal stress of EWT wafers with twice the density of holes of commercial ones is almost the same. However, the mutual interaction between the stress concentration effects around neighboring holes is only observed for wafers with a density of 200 holes/cm 2

Assessing the potential distribution of insect pests: case studies on large pine weevil (Hylobius abietis L) and horse-chestnut leaf miner (Cameraria ohridella) under present and future climate conditions in European forests†

Forest insect pests represent a serious threat to European forests and their negative effects could be exacerbated by climate change. This paper illustrates how species distribution modelling integrated with host tree species distribution data can be used to assess forest vulnerability to this threat. Two case studies are used: large pine weevil (Hylobius abietis L) and horse-chestnut leaf miner (Cameraria ohridella Deschka & Dimic) both at pan-European level. The proposed approach integrates information from different sources. Occurrence data of insect pests were collected from the Global Biodiversity Information Facility (GBIF), climatic variables for present climate and future scenarios were sourced, respectively, from WorldClim and from the Research Program on Climate Change, Agriculture and Food Security (CCAFS), and distributional data of host tree species were obtained from the European Forest Data Centre (EFDAC), within the Forest Information System for Europe (FISE). The potential habitat of the target pests was calculated using the machine learning algorithm of Maxent model. On the one hand, the results highlight the potential of species distribution modelling as a valuable tool for decision makers. On the other hand, they stress how this approach can be limited by poor pest data availability, emphasizing the need to establish a harmonised open European database of geo-referenced insect pest distribution data. Evaluation de la repartition potentielle des insectes nuisibles: etudes de cas sur le grand charancon du pin (Hylobius abietis L.) et sur la mineuse du marronnier (Cameraria ohridella) dans les conditions climatiques actuelles et futures dans les forets europeennes Les insectes nuisibles des forets representent une menace serieuse pour les forets europeennes et leurs effets negatifs pourraient etre aggraves par le changement climatique. Cet article illustre l'utilisation de la modelisation de la repartition des especes, integree aux donnees de repartition des arbres-hotes, pour evaluer la vulnerabilite des forets a cette menace. Deux etudes de cas sont utilisees, toutes deux au niveau paneuropeen, pour le grand charancon du pin (Hylobius abietis L.) et la mineuse du marronnier (Cameraria ohridella Deschka & Dimic). L'approche proposee utilise des informations de differentes sources. Les donnees sur la presence des insectes nuisibles proviennent du service mondial d'information sur la biodiversite ('Global Biodiversity Information Facility', GBIF), les variables climatiques pour le climat actuel et des scenarios futurs ont ete obtenues, respectivement, a partir de WorldClim et du Programme de recherche sur le changement climatique, l'agriculture et la securite alimentaire (CCAFS), et les donnees sur la repartition des arbres-hotes ont ete obtenues aupres du Centre europeen de donnees sur les forets (EFDAC), qui fait partie du systeme d'information forestiere pour l'Europe ('Forest Information System for Europe', FISE). L'habitat potentiel des ravageurs etudies a ete calcule en utilisant l'algorithme d'apprentissage automatique du modele Maxent. D'une part, les resultats indiquent que la modelisation de la repartition des especes peut devenir un outil precieux pour les decideurs. D'autre part, ils indiquent que cette approche peut etre limitee par le manque de donnees sur les organismes nuisibles, renforcant ainsi la necessite de creer une base de donnees europeenne harmonisee et ouverte pour les donnees geo-referencees sur la repartition des insectes nuisibles. Oцeнкa пoтeнциaльнoгo pacпpocтpaнeния вpeдныx нaceкoмыx нa пpимepe бoльшoгo cocнoвoгo дoлгoнocикa (Hylobius abietis L) и лиcтoвoгo минёpa кoнcкoгo кaштaнa (Cameraria ohridella) пpи cyщecтвyющиx и бyдyщиx климaтичecкиx ycлoвияx в eвpoпeйcкиx лeca

Model Ensembles of Ecosystem Services Fill Global Certainty and Capacity Gaps

Sustaining ecosystem services (ES) critical to human wellbeing is hindered by many practitioners lacking access to ES models (‘the capacity gap’) or knowledge of the accuracy of available models (‘the certainty gap’), especially in the world’s poorer regions. We developed ensembles of multiple models at an unprecedented global scale for five ES of high policy relevance. Ensembles were 2-14% more accurate than individual models. Ensemble accuracy was not correlated with proxies for research capacity – indicating accuracy is distributed equitably across the globe and that countries less able to research ES suffer no accuracy penalty. By making these ES ensembles and associated accuracy estimates freely available, we provide globally consistent ES information that can support policy and decision making in regions with low data availability or low capacity for implementing complex ES models. Thus, we hope to reduce the capacity and certainty gaps impeding local to global-scale movement towards ES sustainability

Laser Cooling of Optically Trapped Molecules

Calcium monofluoride (CaF) molecules are loaded into an optical dipole trap (ODT) and subsequently laser cooled within the trap. Starting with magneto-optical trapping, we sub-Doppler cool CaF and then load $150(30)$ CaF molecules into an ODT. Enhanced loading by a factor of five is obtained when sub-Doppler cooling light and trapping light are on simultaneously. For trapped molecules, we directly observe efficient sub-Doppler cooling to a temperature of $60(5)$ $\mu\text{K}$. The trapped molecular density of $8(2)\times10^7$ cm$^{-3}$ is an order of magnitude greater than in the initial sub-Doppler cooled sample. The trap lifetime of 750(40) ms is dominated by background gas collisions.Comment: 5 pages, 5 figure

XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP

Predictive business process monitoring (PBPM) is a class of techniques designed to predict behaviour, such as next activities, in running traces. PBPM techniques aim to improve process performance by providing predictions to process analysts, supporting them in their decision making. However, the PBPM techniques` limited predictive quality was considered as the essential obstacle for establishing such techniques in practice. With the use of deep neural networks (DNNs), the techniques` predictive quality could be improved for tasks like the next activity prediction. While DNNs achieve a promising predictive quality, they still lack comprehensibility due to their hierarchical approach of learning representations. Nevertheless, process analysts need to comprehend the cause of a prediction to identify intervention mechanisms that might affect the decision making to secure process performance. In this paper, we propose XNAP, the first explainable, DNN-based PBPM technique for the next activity prediction. XNAP integrates a layer-wise relevance propagation method from the field of explainable artificial intelligence to make predictions of a long short-term memory DNN explainable by providing relevance values for activities. We show the benefit of our approach through two real-life event logs

EU-wide methodology to map and assess ecosystem condition

The EU Biodiversity Strategy for 2030 calls for developing an EU-wide methodology to map, assess and achieve good condition of ecosystems, so they can deliver benefits to society through the provision of ecosystem services. The EU-wide methodology presented in this report addresses this methodological gap. The EU-wide methodology has adopted the System of Environmental Economic Accounting - Ecosystem Accounting (SEEA EA) as reference framework. The SEEA EA is an integrated framework for organizing biophysical information about ecosystems, adopted as a global statistical standard by the United Nations. The SEEA EA is also the reference framework under the proposal for the amendment of Regulation (EU) No 691/2011 on European environmental economic accounts. Building on previous work done within the MAES initiative, the EU-wide methodology presents useful insights to operationalise the SEEA EA at EU level by integrating different EU data streams in a consistent way with this global statistical standard to consistently map and assess ecosystem condition in the EU across all ecosystem types. The adoption of the SEEA EA framework offers the flexibility to integrate different data flows, leveraging the use of available EU data, such as data reported by MS under EU legislation and EU geospatial data. The EU-wide methodology. The implementation of the EU-wide methodology, making use of available data, will provide the scientific knowledge base to support a range of policies and legal instruments

Molecules cooled below the Doppler limit

The ability to cool atoms below the Doppler limit -- the minimum temperature reachable by Doppler cooling -- has been essential to most experiments with quantum degenerate gases, optical lattices and atomic fountains, among many other applications. A broad set of new applications await ultracold molecules, and the extension of laser cooling to molecules has begun. A molecular magneto-optical trap has been demonstrated, where molecules approached the Doppler limit. However, the sub-Doppler temperatures required for most applications have not yet been reached. Here we cool molecules to 50 uK, well below the Doppler limit, using a three-dimensional optical molasses. These ultracold molecules could be loaded into optical tweezers to trap arbitrary arrays for quantum simulation, launched into a molecular fountain for testing fundamental physics, and used to study ultracold collisions and ultracold chemistry

Mapping and Assessment of forest Ecosystem and Their Services. Applications and guidance for decision making in the framework of MAES

The aim of this report is to illustrate by means of a series of case studies the implementation of mapping and assessment of forest ecosystem services in different contexts and geographical levels. Methodological aspects, data issues, approaches, limitations, gaps and further steps for improvement are analysed for providing good practices and decision making guidance. The EU initiative on Mapping and Assessment of Ecosystems and their Services (MAES), with the support of all Member States, contributes to improve the knowledge on ecosytem services. MAES is one of the building-block initiatives supporting the EU Biodiversity Strategy to 2000

A multi-component flood risk assessment in the Maresme coast (NW Mediterranean)

Coastal regions are the areas most threatened by natural hazards, with floods being the most frequent and significant threat in terms of their induced impacts, and therefore, any management scheme requires their evaluation. In coastal areas, flooding is a hazard associated with various processes acting at different scales: coastal storms, flash floods, and sea level rise (SLR). In order to address the problem as a whole, this study presents a methodology to undertake a preliminary integrated risk assessment that determines the magnitude of the different flood processes (flash flood, marine storm, SLR) and their associated consequences, taking into account their temporal and spatial scales. The risk is quantified using specific indicators to assess the magnitude of the hazard (for each component) and the consequences in a common scale. This allows for a robust comparison of the spatial risk distribution along the coast in order to identify both the areas at greatest risk and the risk components that have the greatest impact. This methodology is applied on the Maresme coast (NW Mediterranean, Spain), which can be considered representative of developed areas of the Spanish Mediterranean coast. The results obtained characterise this coastline as an area of relatively low overall risk, although some hot spots have been identified with high-risk values, with flash flooding being the principal risk process