In addition to the development and research of battery-driven vehicles, a high research effort in the field of hydrogen technology can currently be observed. Various research and strategy initiatives relating to hydrogen are being initiated and pursued with considerable commitment worldwide. A significant expansion of the hydrogen filling station network is also being sought in Germany. In the course of designing a hydrogen refuelling station, the paradigms of thermal management must be taken into account in addition to a large number of different environmental and life phase-induced influencing factors. The interactions between influencing factors, requirements and the system architecture result in a multitude of possible refuelling station concepts, which can hardly be surveyed or managed from an organisational point of view. This publication introduces a method for the development of descriptive requirement collectives, which is applied to hydrogen refuelling stations in the framework of THEWA, but can also be adapted for other technical systems. The requirement collective is the first core element of the THEWA tool chain that enables a requirement-oriented and fast design of hydrogen refuelling stations.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

R-MAT (for Recursive MATrix) is a simple, widely used model for generating graphs with a power law degree distribution, a small diameter, and communitys structure. It is particularly attractive for generating very large graphs because edges can be generated independently by an arbitrary number of processors. However, current R-MAT generators need time logarithmic in the number of nodes for generating an edge— constant time for generating one bit at a time for node IDs of the connected nodes. We achieve constant time per edge by precomputing pieces of node IDs of logarithmic length. Using an alias table data structure, these pieces can then be sampled in constant time. This simple technique leads to practical improvements by an order of magnitude. This further pushes the limits of attainable graph size and makes generation overhead negligible in most situations.

This research communication addresses the hypothesis that Southeast dairy producers' self-reported bulk tank somatic cell count (BTSCC) was associated with producers' response to three statements (1) ‘a troublesome thing about mastitis is the worries it causes me,’ (2) ‘a troublesome thing about mastitis is that cows suffer,’ and (3) ‘my broad goals include taking good care of my cows and heifers.’ Surveys were mailed to producers in Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, and Virginia (29% response rate, N = 596; final analysis N = 574), as part of a larger survey to assess Southeastern dairy producers' opinions related to BTSCC. Surveys contained 34 binomial (n = 9), Likert scale (n = 7), and descriptive (n = 18) statements targeted at producer self-assessment of herd records, management practices, and BTSCC. Statements 1 and 2 were assessed on a 5-point Likert scale from ‘strongly disagree’ to ‘strongly agree.’ Statement 3 was assessed on a 5-point Likert scale from ‘very unimportant’ to ‘very important.’ Reported mean BTSCC for all participants was 254 500 cells/ml. Separate univariable logistic regressions using generalized linear mixed models (SAS 9.4, Cary, NC, USA) with a random effect of farm, were performed to determine if BTSCC was associated with probability for a producer's response to statements. If BTSCC was significant, forward manual addition was performed until no additional variables were significant (P ≤ 0.05), but included BTSCC, regardless of significance. Bulk tank somatic cell count was associated with ‘a troublesome thing about mastitis is the worries it causes me,’ but not with Statements 2 or 3. This demonstrates that >75% of Southeastern dairy producers are concerned with animal care and cow suffering, regardless of BTSCC. Understanding Southeast producers' emphasis on cow care is necessary to create targeted management tools for herds with elevated BTSCC.

The Upper Cretaceous Kanguk Formation of the Sverdrup Basin, Canadian Arctic Islands, contains numerous diagenetically altered volcanic ash layers (bentonites). Eleven bentonites were sampled from an outcrop section on Ellesmere Island for U–Pb zircon secondary ion mass spectrometry dating and whole-rock geochemical analysis. Two distinct types of bentonite are identified from the geochemical data. Relatively thick (0.1 to 5 m) peralkaline rhyolitic to trachytic bentonites erupted in an intraplate tectonic setting. These occur throughout the upper Turonian to lower Campanian (c. 92–83 Ma) outcrop section and are likely associated with the alkaline phase of the High Arctic Large Igneous Province. Two thinner (<5 cm) subalkaline dacitic to rhyolitic bentonites of late Turonian to early Coniacian age (c. 90–88 Ma) are also identified. The geochemistry of these bentonites is consistent with derivation from volcanoes within an active continental margin tectonic setting. The lack of nearby potential sources of subalkaline magmatism, together with the thinner bed thickness of the subalkaline bentonites and the small size of zircon phenocrysts therein (typically 50–80 μm in length) are consistent with a more distal source area. The zircon U–Pb age and whole-rock geochemistry of these two subalkaline bentonites correlate with an interval of intense volcanism in the Okhotsk–Chukotka Volcanic Belt, Russia. It is proposed that during late Turonian to early Coniacian times intense volcanism within the Okhotsk–Chukotka Volcanic Belt resulted in widespread volcanic ash dispersal across Arctic Alaska and Canada, reaching as far east as the Sverdrup Basin, more than 3000 km away.

Physical activity (PA) may be therapeutic for people with severe mental illness (SMI) who generally have low PA and experience numerous life style-related medical complications. We conducted a meta-review of PA interventions and their impact on health outcomes for people with SMI, including schizophrenia-spectrum disorders, major depressive disorder (MDD) and bipolar disorder. We searched major electronic databases until January 2018 for systematic reviews with/without meta-analysis that investigated PA for any SMI. We rated the quality of studies with the AMSTAR tool, grading the quality of evidence, and identifying gaps, future research needs and clinical practice recommendations. For MDD, consistent evidence indicated that PA can improve depressive symptoms versus control conditions, with effects comparable to those of antidepressants and psychotherapy. PA can also improve cardiorespiratory fitness and quality of life in people with MDD, although the impact on physical health outcomes was limited. There were no differences in adverse events versus control conditions. For MDD, larger effect sizes were seen when PA was delivered at moderate-vigorous intensity and supervised by an exercise specialist. For schizophrenia-spectrum disorders, evidence indicates that aerobic PA can reduce psychiatric symptoms, improves cognition and various subdomains, cardiorespiratory fitness, whilst evidence for the impact on anthropometric measures was inconsistent. There was a paucity of studies investigating PA in bipolar disorder, precluding any definitive recommendations. No cost effectiveness analyses in any SMI condition were identified. We make multiple recommendations to fill existing research gaps and increase the use of PA in routine clinical care aimed at improving psychiatric and medical outcomes.

Chip-package interaction (CPI) and the related thermomechanical stress in microchips increase the risk of failure in on-chip interconnect stacks, caused by delamination along Cu/dielectrics interfaces (adhesive failure) and fracture in dielectrics (cohesive failure). High-resolution transmission X-ray microscopy (TXM) is a unique technique to image crack propagation in on-chip interconnect stacks. The visualization of crack evolution in Cu/low-k Backend-of-Line (BEoL) structures is demonstrated using an experimental setup which combines high-resolution X-ray imaging with mechanical loading. The application of an indenter manipulator at the TXM beamline of the synchrotron radiation source BESSY II provides an unprecedented level of details on the fracture behavior of microchips. This in-situ experiment allows to identify the weakest layers and interfaces and to evaluate the robustness of the BEoL stack against CPI.