A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: superindividual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

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RATIONALE: While severe asthma affects approximately 5% of all individuals with asthma, this small minority of individuals accounts for a large proportion of the asthma-related costs. Greater understanding of the pathophysiology of asthma combined with the emergence of novel biologic therapies for severe asthma supported the need for a thorough review of the diagnosis, investigation, phenotyping, and management of severe asthma. OBJECTIVES: We aimed to propose a practical approach to distinguish uncontrolled asthma due to inadequate asthma management from severe asthma despite optimal asthma management. Moreover, based on emerging scientific evidence, we sought to provide guidance for characterizing individuals with severe asthma and considering a phenotype-specific management. We also aimed to review other novel new potential therapeutic approaches. METHODS: We systematically reviewed the relevant literature focusing on randomized controlled trials and when available, systematic reviews of randomized controlled trials. The proposed key messages, based on scientific evidence and expert opinion, were agreed upon by unanimous consensus. MAIN RESULTS: We defined severe asthma and outlined its significant impact from the societal and patient perspectives. We outlined a practical approach to distinguish severe from uncontrolled but not severe asthma, based on stepwise investigation and management of potential reasons for uncontrolled asthma. After reviewing the current evidence we concluded that: 1) Several biomarkers (e.g. sputum or blood eosinophil count, total IgE, or FeNO) can help identify potential responders to new therapeutic options; 2) Tiotropium may be considered as an add-on therapy for individuals 12 years of age and over with severe asthma uncontrolled despite combination ICS/LABA therapy; 3) The chronic use of macrolides may decrease asthma exacerbations in individuals 18 years of age and over with severe asthma independent of their inflammatory profile; 4) Children aged 6 years and older and adults who are sensitized to at least one relevant perennial allergen and who remain poorly controlled asthmatics despite high dose ICS and a second controller can benefit from the addition of anti-IgE therapy to reduce asthma exacerbations; due to the known risk of side effects associated with high-dose ICS in children, omalizumab should also be considered in children and adolescents who repeatedly exacerbate or have poor control when therapy is stepped down from high-dose to moderate-dose ICS and at least one other controller; 5) Anti-IL5 therapies may be considered for adults 18 years of age and over with severe eosinophilic asthma who experience recurrent asthma exacerbations in spite of high doses of ICS in addition to at least one other controller; and 6) Although bronchial thermoplasty has shown a decrease in asthma exacerbations in one study, its role in the treatment of severe asthma remains uncertain. CONCLUSIONS: After reviewing existing and emerging therapies for severe asthma, we developed ke...

484625. than from PVC (54±55% of DM) or bagasse (51± 58% of DM). It is concluded that substrate type has a strong effect on periphyton productivity and composition, and on ®sh productivity. Good ®sh production was achieved without feed inputs. More research is needed to study the economic viability of periphyton-based systems in the context of Indian aquaculture.

We introduce a novel constitutive model for growing soft biological tissue and study its performance in two characteristic cases of mechanically-induced wall thickening of the heart. We adopt the concept of an incompatible growth configuration introducing the multiplicative decomposition of the deformation gradient into an elastic and a growth part. The key feature of the model is the definition of the evolution equation for the growth tensor which we motivate by pressure-overload induced sarcomerogenesis. In response to the deposition of sarcomere units on the molecular level, the individual heart muscle cells increase in diameter, and the wall of the heart becomes progressively thicker. We present the underlying constitutive equations and their algorithmic implementation within an implicit nonlinear finite element framework. To demonstrate the features of the proposed approach, we study two classical growth phenomena in the heart: left and right ventricular wall thickening in response to systemic and pulmonary hypertension.