A fast and memory-efficient calculation of theoretical isotope patterns is crucial for the routine interpretation of mass spectrometric data. For high-resolution experiments, calculations must procure the exact masses and probabilities of relevant isotopologues over a wide range of polyisotopic compounds, while pruning low-probable ones. Here, a novel albeit simple treelike structure is introduced to swiftly derive sets of relevant subisotopologues for each element in a molecule, which are then combined to the isotopologues of the full molecule. In contrast to existing approaches, transitions via single replacements of the most abundant isotope per element are used in separable tree branches to derive subisotopologues from each other. Moreover, the underlying transition trees prevent redundant replacements and permit the detection of the most probable isotopologue in a first phase. A relative threshold can then be exploited in a second parallelized phase for a precise prepruning of large fractions of the remaining subisotopologues. The gain in performance from such early pruning and the lower variation in the distortion of simulated data with use of relative rather than absolute thresholds were validated in a large-scale benchmark simulation, unprecedentedly comprising several thousand molecular formulas. Both the algorithm and a wealth of related features are freely available as R-package enviPat and as a user-friendly Web interface.

HighlightsWe modelled the surface water salinity in the Baltic from the 1960s to 2100.We studied possible changes in distribution areas of predominant plant, invertebrate and fish species.The results suggest a critical shift in the salinity range 5–7, which is a bottleneck for both marine and freshwater species distribution and diversity.This foreseen salinity change is likely to have large impacts on marine ecology, it́s monitoring, modelling as well as fisheries.

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This special issue includes eight original works that detail the further developments of ELMs in theories, applications, and hardware implementation. In "Representational Learning with ELMs for Big Data," Liyanaarachchi Lekamalage Chamara Kasun, Hongming Zhou, Guang-Bin Huang, and Chi Man Vong propose using the ELM as an auto-encoder for learning feature representations using singular values. In "A Secure and Practical Mechanism for Outsourcing ELMs in Cloud Computing," Jiarun Lin, Jianping Yin, Zhiping Cai, Qiang Liu, Kuan Li, and Victor C.M. Leung propose a method for handling large data applications by outsourcing to the cloud that would dramatically reduce ELM training time. In "ELM-Guided Memetic Computation for Vehicle Routing," Liang Feng, Yew-Soon Ong, and Meng-Hiot Lim consider the ELM as an engine for automating the encapsulation of knowledge memes from past problem-solving experiences. In "ELMVIS: A Nonlinear Visualization Technique Using Random Permutations and ELMs," Anton Akusok, Amaury Lendasse, Rui Nian, and Yoan Miche propose an ELM method for data visualization based on random permutations to map original data and their corresponding visualization points. In "Combining ELMs with Random Projections," Paolo Gastaldo, Rodolfo Zunino, Erik Cambria, and Sergio Decherchi analyze the relationships between ELM feature-mapping schemas and the paradigm of random projections. In "Reduced ELMs for Causal Relation Extraction from Unstructured Text," Xuefeng Yang and Kezhi Mao propose combining ELMs with neuron selection to optimize the neural network architecture and improve the ELM ensemble's computational efficiency. In "A System for Signature Verification Based on Horizontal and Vertical Components in Hand Gestures," Beom-Seok Oh, Jehyoung Jeon, Kar-Ann Toh, Andrew Beng Jin Teoh, and Jaihie Kim propose a novel paradigm for hand signature biometry- for touchless applications without the need for handheld devices. Finally, in "An Adaptive and Iterative Online Sequential ELM-Based Multi-Degree-of-Freedom Gesture Recognition System," Hanchao Yu, Yiqiang Chen, Junfa Liu, and Guang-Bin Huang propose an online sequential ELM-based efficient gesture recognition algorithm for touchless human-machine interaction

The nitrous oxide emissions of the Viikinmäki wastewater treatment plant were measured in a 12 month online monitoring campaign. The measurements, which were conducted with a continuous gas analyzer, covered all of the unit operations of the advanced wastewater-treatment process. The relation between the nitrous oxide emissions and certain process parameters, such as the wastewater temperature, influent biological oxygen demand, and ammonium nitrogen load, was investigated by applying online data obtained from the process-control system at 1 min intervals. Although seasonal variations in the measured nitrous oxide emissions were remarkable, the measurement data indicated no clear relationship between these emissions and seasonal changes in the wastewater temperature. The diurnal variations of the nitrous oxide emissions did, however, strongly correlate with the alternation of the influent biological oxygen demand and ammonium nitrogen load to the aerated zones of the activated sludge process. Overall, the annual nitrous oxide emissions of 168 g/PE/year and the emission factor of 1.9% of the influent nitrogen load are in the high range of values reported in the literature but in very good agreement with the results of other long-term online monitoring campaigns implemented at full-scale wastewater-treatment plants.

Muscle ischemic preconditioning (IP) has been found to improve exercise performance in laboratory tests. This investigation aims at verifying whether performance is improved by IP during self-paced exercise (SPE) in the field. 11 well-trained male runners performed 3 randomly assigned 5 000 m self-paced running tests on an outdoor track. One was the reference (RT) test, while the others were performed following muscle IP (IPT) and a control sham test (ST). Average speeds were measured during each test. Mean values in oxygen uptake (VO2), aerobic energy cost (AEC) during race and post-race blood lactate (BLa) were gathered. Data showed that none of the studied variables were affected by IPT or ST with respect to the RT test. Average speeds were 4.63±0.31, 4.62±0.31 and 4.60±0.25 m·s(-1) for the RT, the ST and the IPT tests, respectively. Moreover, there was no difference among tests in speed reached during each lap. VO2 was 3.5±0.69, 3.74±0.85 and 3.62±1.19 l·min(-1). AEC was 1.04±0.15, 1.08±0.1 and 1.09±0.15 kcal·kg(-1)·km(-1). Finally, post-race BLa levels reached 12.85±3.54, 11.88±4.74 and 12.82±3.6 mmol·l(-1). These findings indicate that performance during SPE is not ameliorated by ischemic preconditioning, thereby indicating that IP is not suitable as an ergogenic aid.

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