Species richness-environment relationships of European arthropods at two spatial grains : habitats and countries

We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area

Introducing the comfort performance gap in new educational buildings: a case study

Providing adequate indoor environmental quality is crucial in educational settings. In this paper, we implemented and tested a framework that collects occupant feedback and investigated correlations between teachers comfort and the operational characteristics of an Austrian school building in September and October 2022. Initial results show that the measured average temperatures (23.1 t-25.1 deg C) in all rooms are on the upper limit of various recommendations, such as comfort guidelines for building operation or workplace regulations. This assessment is in line with the feedback we received from the teachers. A literature review demonstrated that childrens comfort temperatures are lower compared to adults. Hence, it is reasonable to conclude that indoor temperatures during the survey period were inadequate for the pupils either, even without direct feedback. An analysis of the CO2 measurements showed that, during school hours, approximately 20% of all measurement values were above 1000 ppm, with 2% above 1500 ppm. CO2 levels above 1000 ppm are considered hygienically critical, with the latest research proposing to lower the limits below 800 ppm to ensure a healthy and effective learning environment. While we only assessed the challenges of providing a healthy indoor environment for an educational building in Austria, our literature review shows similar challenges and research efforts worldwide. Our analysis demonstrates the need for adapting design requirements, especially for school buildings, acknowledging the different comfort needs of adults and children and the importance of high indoor air quality for providing an optimum learning environment. Future research should focus on testing adapted indoor environmental quality requirements for schools, especially in urban areas, and how to integrate real-time occupant feedback in the heating, ventilation and air conditioning systems

Generalizable Temperature Nowcasting with Physics-Constrained RNNs for Predictive Maintenance of Wind Turbine Components

Machine learning plays an important role in the operation of current wind energy production systems. One central application is predictive maintenance to increase efficiency and lower electricity costs by reducing downtimes. Integrating physics-based knowledge in neural networks to enforce their physical plausibilty is a promising method to improve current approaches, but incomplete system information often impedes their application in real world scenarios. We describe a simple and efficient way for physics-constrained deep learning-based predictive maintenance for wind turbine gearbox bearings with partial system knowledge. The approach is based on temperature nowcasting constrained by physics, where unknown system coefficients are treated as learnable neural network parameters. Results show improved generalization performance to unseen environments compared to a baseline neural network, which is especially important in low data scenarios often encountered in real-world applications.Comment: Published at ICLR 2024 Tackling Climate Change with Machine Learning Worksho

Comparison of Functionalized Lithium Dihydrobis(azolyl)borates with Their Corresponding Azolates as Environmentally Friendly Red Pyrotechnic Coloring Agents

The recent awareness of the impact of strontium on health has stimulated research efforts on lithium‐based red pyrotechnic colorants. We have previously shown lithium dihydrobis(azolyl)borates to be promising candidates due to their favorable adjustment to a reductive and low‐temperature flame atmosphere. These compounds are assumed to be sufficiently stable only if the pKa values of the heterocycles are between 5 and 20. Apart from their acidities, functionalization of 1H‐tetrazole and 1H‐pyrazole with nitro or amino groups, respectively, tailors the oxygen balances of the resulting Lewis acid base adducts to enhance the fuel‐rich flame environment or to make them oxidizing agents. This work determines whether the lithium salts of dihydrobis(3‐nitropyrazol‐1‐yl)borate and dihydrobis(5‐aminotetrazol‐1‐yl)borate are suitable replacements for strontium‐containing color imparters. Furthermore, the influence of potentially green‐light‐producing boron is evaluated by comparing the emissions of the lithium borates and the corresponding lithium azolates

IoT Middleware Platforms for Smart Energy Systems: An Empirical Expert Survey

Middleware platforms are key technology in any Internet of Things (IoT) system, considering their role in managing the intermediary communications between devices and applications. In the energy sector, it has been shown that IoT devices enable the integration of all network assets to one large distributed system. This comes with significant benefits, such as improving energy efficiency, boosting the generation of renewable energy, reducing maintenance costs and increasing comfort. Various existing IoT middlware solutions encounter several problems that limit their performance, such as vendor locks. Hence, this paper presents a literature review and an expert survey on IoT middleware platforms in energy systems, in order to provide a set of tools and functionalities to be supported by any future efficient, flexible and interoperable IoT middleware considering the market needs. The analysis of the results shows that experts currently use the IoT middleware mainly to deploy services such as visualization, monitoring and benchmarking of energy consumption, and energy optimization is considered as a future application to target. Likewise, non-functional requirements, such as security and privacy, play vital roles in the IoT platforms’ performances

Transport and recombination through weakly coupled localized spin pairs in semiconductors during coherent spin excitation

Semi-analytical predictions for the transients of spin-dependent transport and recombination rates through localized states in semiconductors during coherent electron spin excitation are made for the case of weakly spin-coupled charge carrier ensembles. The results show that the on-resonant Rabi frequency of electrically or optically detected spin-oscillation doubles abruptly as the strength of the resonant microwave field gamma B_1 exceeds the Larmor frequency separation within the pair of charge carrier states between which the transport or recombination transition takes place. For the case of a Larmor frequency separation of the order of gamma B_1 and arbitrary excitation frequencies, the charge carrier pairs exhibit four different nutation frequencies. From the calculations, a simple set of equations for the prediction of these frequencies is derived

The Impact of Scientific Management Principles on Food Hub

Food hubs have seen substantial growth in the past few decades but the overall operational efficiency and effectiveness is a concern for the managers of these facilities. The experiment designed consisted of 60 participants divided into four treatment groups that simulated tasks completed at food hubs. The experiment designed was a 2x2 factorial design and each treatment group had five teams with three members. The treatment groups had all combinations of the two independent variables ‘training’ and ‘process improvement’ and the impact these factors made on time to pack (TP), time to stack (TS), number of errors while stacking (ES), and number of errors while packing (EP) were investigated. The results show that for TS, TP, and ES, both training and process improvement significantly increased the food hub’s efficiency. For EP, process improvement significantly reduced errors while training had less impact

Incidence of brain injuries in a large cohort of very preterm and extremely preterm infants at term-equivalent age: results of a single tertiary neonatal care center over 10 years

OBJECTIVES Cerebral magnetic resonance imaging (cMRI) at term-equivalent age (TEA) can detect brain injury (BI) associated with adverse neurological outcomes in preterm infants. This study aimed to assess BI incidences in a large, consecutive cohort of preterm infants born < 32 weeks of gestation, the comparison between very (VPT, ≥ 28 + 0 to < 32 + 0 weeks of gestation) and extremely preterm infants (EPT, < 28 + 0 weeks of gestation) and across weeks of gestation. METHODS We retrospectively analyzed cMRIs at TEA of VPT and EPT infants born at a large tertiary center (2009-2018). We recorded and compared the incidences of BI, severe BI, intraventricular hemorrhage (IVH), periventricular hemorrhagic infarction (PVHI), cerebellar hemorrhage (CBH), cystic periventricular leukomalacia (cPVL), and punctate white matter lesions (PWML) between VPTs, EPTs, and across weeks of gestation. RESULTS We included 507 preterm infants (VPT, 335/507 (66.1%); EPT, 172/507 (33.9%); mean gestational age (GA), 28 + 2 weeks (SD 2 + 2 weeks); male, 52.1%). BIs were found in 48.3% of the preterm infants (severe BI, 12.0%) and increased with decreasing GA. IVH, PVHI, CBH, cPVL, and PWML were seen in 16.8%, 0.8%, 10.5%, 3.4%, and 18.1%, respectively. EPT vs. VPT infants suffered more frequently from BI (59.3% vs. 42.7%, p < 0.001), severe BI (18.6% vs. 8.7%, p = 0.001), IVH (31.9% vs. 9.0%, p < 0.001), and CBH (18.0% vs. 6.6%, p < 0.001). CONCLUSION Brain injuries are common cMRI findings among preterm infants with a higher incidence of EPT compared to VPT infants. These results may serve as reference values for clinical management and research. CLINICAL RELEVANCE STATEMENT Our results with regard to gestational age might provide valuable clinical insights, serving as a key reference for parental advice, structured follow-up planning, and enhancing research and management within the Neonatal Intensive Care Unit. KEY POINTS Brain injury is a common cMRI finding in preterm infants seen in 48.3% individuals. • Extremely preterm compared to very preterm infants have higher brain injury incidences driven by brain injuries such as intraventricular and cerebellar hemorrhage. • Reference incidence values are crucial for parental advice and structured follow-up planning