Leaf diversity influences in-stream litter decomposition through effects on shredders

1. The functioning of many aquatic ecosystems is controlled by surrounding terrestrial ecosystems. In a view of growing interest in linking biodiversity to ecosystem-level processes, we examined whether and how leaf diversity influences litter decomposition and consumers in streams. 2. We tested experimentally the hypothesis that the effects of leaf diversity on decomposition are determined by the responses of leaf consumers to resource–habitat heterogeneity. Leaves from three common riparian trees, beech (Fagus sylvatica), hazel (Corylus avellana) and ash (Fraxinus excelsior), were exposed alone and in all possible mixtures of two and three species in a stream. We analysed individual leaf species for decomposition rate, microbial respiration and mycelial biomass, and we determined the species composition, abundance and biomass of shredders in leaf bags. 3. We found that the decomposition of the fastest decomposing leaves (hazel and ash) was substantially stimulated (up to twofold higher than single species leaf packs) in mixtures containing beech leaves, which are refractory. In contrast, the decomposition of beech leaves was not affected by leaf mixing. Such species-specific behaviour of leaves in species mixtures has been overlooked in previous studies that examined the overall decompo- sition of litter mixtures. 4. The effects of leaf diversity on decomposition varied with the abundance and biomass of shredders but not with microbial parameters. Beech leaves alone were less attractive to shredders than leaf packs made of hazel, ash or any mixture of species. Moreover, the presence of beech leaves in mixtures led to higher shredder abundance and biomass than we had expected from data from single species exposed alone. Lastly, we found that early instars of the caddisfly Potamophylax (the dominant shredder in terms of biomass) almost exclusively used the toughest material (i.e. beech leaves) to construct their cases. 5. Leaf pack heterogeneity may have altered shredder-mediated decomposition. Shredders colonising diverse leaf packs benefited from the stable substratum provided by beech leaves, whereas ash and hazel leaves were primarily used as food. Thus, our findings provide strong evidence for an intimate linkage between the diversity of riparian vegetation and aquatic communities

Role of radiography, MRI and FDG-PET/CT in diagnosing, staging and therapeutical evaluation of patients with multiple myeloma

Multiple myeloma is a malignant B-cell neoplasm that involves the skeleton in approximately 80% of the patients. With an average age of 60 years and a 5-years survival of nearly 45% Brenner et al. (Blood 111:2516–2520, 35) the onset is to be classified as occurring still early in life while the disease can be very aggressive and debilitating. In the last decades, several new imaging techniques were introduced. The aim of this review is to compare the different techniques such as radiographic survey, multidetector computed tomography (MDCT), whole-body magnetic resonance imaging (WB-MRI), fluorodeoxyglucose positron emission tomography- (FDG-PET) with or without computed tomography (CT), and 99mTc-methoxyisobutylisonitrile (99mTc-MIBI) scintigraphy. We conclude that both FDG-PET in combination with low-dose CT and whole-body MRI are more sensitive than skeleton X-ray in screening and diagnosing multiple myeloma. WB-MRI allows assessment of bone marrow involvement but cannot detect bone destruction, which might result in overstaging. Moreover, WB-MRI is less suitable in assessing response to therapy than FDG-PET. The combination of PET with low-dose CT can replace the golden standard, conventional skeletal survey. In the clinical practise, this will result in upstaging, due to the higher sensitivity

Strange Particle Production in pp Collisions at sqrt(s) = 0.9 and 7 TeV

Peer reviewe

Impact of etcd deployment on Kubernetes, Istio, and application performance

This experience article describes lessons learned as we conducted experiments in a Kubernetes-based environment, the most notable of which was that the performance of both the Kubernetes control plane and the deployed application depends strongly and in unexpected ways on the performance of the etcd database. The article contains (a) detailed descriptions of how networking with and without Istio works in Kubernetes, based on the Flannel Container Networking Interface (CNI) provider in VXLAN mode with IP Virtual Server (IPVS)-backed Kubernetes Services, (b) a comprehensive discussion about how to conduct load and performance testing using a closed-loop workload generator, and (c) an open source experiment framework useful for executing experiments in a shared cloud environment and exploring the resulting data. It also shows that statistical analysis may reveal the data resulting from such experiments to be misleading even when careful preparations are made, and that nondeterministic behavior stemming from etcd can affect both the platform as a whole and the deployed application. Finally, it is demonstrated that using high-performance backing storage for etcd can reduce the occurrence of such nondeterministic behaviors by a statistically significant (P < .05) margin. The implication of this experience article is that systems researchers studying the performance of applications deployed on Kubernetes cannot simply consider their specific application to be under test. Instead, the particularities of the underlying Kubernetes and cloud platform must be taken into account, in particular because their performance can impact that of etcd

An osmotic computing infrastructure for urban pollution monitoring

Urban pollution control systems suffer from the presence of fixed stations in a greater number than mobile monitoring devices. Data gathered from such stations provide detailed and reliable information, thanks to equipment quality and effective measuring protocols, but these sampled data are gathered from very limited areas and through discontinuous monitoring campaigns. Fortunately, the spread of technologies for mobility has fostered the development of new approaches like mobile crowdsensing (MCS), increasing the chances of using mobile devices, even personal ones, as suitable sensors for the urban monitoring scenario. Nevertheless, one of the open challenges is the management of integrated heterogeneous data flows, differing in terms of typology, technical specifications (eg, transmission protocols), and semantics. The osmotic computing paradigm aims at creating an abstract level between mobile devices/Internet-of-Things devices and a cloud platform, which enables opportunistic filtering and the addition of metadata for improving the data processing flow. This work focuses on the design and development of a middleware that integrates data coming from mobile and Internet-of-Things devices specifically deployed in urban contexts using the osmotic computing paradigm. Moreover, a component of the osmotic membrane has been developed for security management