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ZusammenfassungZum sogenannten Mittelbau zählen Doktoranden und Doktorandinnen, Postdocs, Nachwuchsgruppenleiter und -leiterinnen, Junior- und Tenure-Track-Professoren und -Professorinnen. Insbesondere Promovierende sowie Postdoktoranden und Postdoktorandinnen sind, noch mehr als früher, von den komplexen strukturellen und finanziellen Problematiken des Wissenschafts- und Lehrbetriebs betroffen, und das in vielerlei Hinsicht über Fächer hinweg. Der Flaschenhals auf dem Weg zur Professur oder einer anderweitig verstetigten Forschungs- oder Lehrstelle führt in der akademischen Karriere zu prekären Beschäftigungsverhältnissen. Die schwierige Vereinbarkeit von Familie und akademischer Karriere erzeugt eine zusätzliche Benachteiligung, insbesondere von Wissenschaftlerinnen. Mangelnde Qualitätssicherung sowie fehlende zuverlässige und vertrauenswürdige Prozesse erschweren die Aufdeckung und Aufarbeitung von Konflikten während der Promotionsphase und der Zeit des Postdoktorats. Der Beirat des wissenschaftlichen Nachwuchses (GI-WiN) der Gesellschaft für Informatik e. V. (GI) fordert und empfiehlt in einem Positionspapier (https://doi.org/10.1007/s00287-020-01250-x) mehrere Maßnahmen zur Stabilisierung von Karriere- und Beschäftigungssituation des Mittelbaus. Der vorliegende Artikel fasst die Ergebnisse einer Umfrage zur Ergänzung und empirischen Untermauerung dieser Empfehlungen zusammen. Die vorliegende Umfrage wurde mit dem Anspruch erhoben, Daten aus allen Fachbereichen – nicht nur der Informatik – zu sammeln. In den Ergebnissen zeigte sich, dass diesen vielfältigen Herausforderungen begegnet werden muss, die in Nicht-MINT-Fächern und MINT-Fächern ähnlich empfunden werden. Die Schaffung von unbefristeten Stellen für die Phase nach der Promotion wurde im Rahmen der Umfrage als besonders wünschenswert angesehen. Vorgeschlagen wurde auch die Abschaffung von Lehrstühlen und die Einführung einer Departmentstruktur. Des Weiteren wurde die Trennung von Begutachtung und Betreuung vor allem bei der Promotion angeregt. Die letzten 2 Jahre im Zeichen der COVID-19-Pandemie waren für einen großen Teil der Betroffenen von fehlendem fachlichen Austausch und sowohl beruflichen als auch privaten Zusatzbelastungen geprägt. Diese Ergebnisse können über die genannten Fachbereiche hinaus eine Entscheidungsgrundlage für eine gerechtere Wissenschaftspolitik liefern und bessere Arbeits- und Karrierebedingungen für den wissenschaftlichen Nachwuchs erwirken.

ZusammenfassungDie nekrotisierende Fasziitis (NF) ist eine schwerwiegende Infektion, die sich entlang der Faszien auf das subkutane Fett und die darüber liegenden Weichteile, die Haut und schließlich die Muskulatur ausbreitet und unbehandelt schnell zu septischem Schock und Tod führt. Um eine massive systemische Ausbreitung des infektiösen Prozesses zu vermeiden, ist schon bei Verdacht ein sofortiges und umfassendes radikales chirurgisches Debridement des nekrotischen Gewebes erforderlich, ergänzt durch eine kalkulierte intravenöse antibiotische Therapie. Die Mortalität ist trotzdem mit 20–40 % anhaltend hoch. Aufgrund des Fehlens spezifischer klinischer Merkmale im Anfangsstadium der Krankheit wird sie häufig unterschätzt oder mit einem lokalen Infekt oder Abszess verwechselt. In 85–100 % der Fälle kommt es zu einer verspäteten Diagnose mit dem Verstreichen kostbarer Zeit.Das Ziel dieser Übersichtsarbeit ist es, die für die Diagnose relevanten klinischen und laborchemischen Parameter sowie die wesentlichen therapeutischen Schritte zusammenzufassen.

Industry 4.0, big data, predictive analytics, and robotics are leading to a paradigm shift on the shop floor of industrial production. However, complex, cognitive tasks are also subject of change, due to the development of artificial intelligence (AI). Smart assistants are finding their way into the world of knowledge work and require cooperation with humans. Here, trust is an essential factor that determines the success of human-AI cooperation. Within this article, an analysis within production management identifies possible antecedent variables on trust in AI and evaluates these due to interaction scenarios with AI. The results of this research are five antecedents for human trust in AI within production management. From these results, preliminary design guidelines are derived for a socially sustainable human-AI interaction in future production management systems.

In various oncological conditions, complications correlate with diminished prognosis, however literature on soft tissue sarcomas is limited and inconclusive. The aim of this study was to assess risk factors and the oncologic impact of wound complications in primary extremity soft-tissue sarcomas.Patients with primary extremity soft tissue sarcomas without dissemination and with clear surgical margins (R0) were analyzed. Groups with and without wound complications were compared by univariate and multivariable analysis to identify risk factors. Uni- and multivariable analysis of factors associated with local recurrence free survival (LRFS), metastasis free survival (MFS) and disease specific survival (DSS) were performed.682 patients were included in the study, wound complications occurred in 94 patients (13.7%) within 90 days. Age, ASA-stage, high tumor size and grade, tumor location in the foot, neoadjuvant radiation therapy and operation time represented independent risk factors for wound complications. Patients with wound complications had a significantly worse estimated 5-year LRFS of 49.4 ± 6% versus 78.3 ± 2.1% and 5-year DSS of 77.9 ± 5.4% versus 89.1 ± 1.6%. Wound complications could be identified as an independent risk factor for worse LRFS (HR 2.68[CI 1.83-3.93], p 0.001) and DSS (HR 1.79[CI 1.01-3.16], p = 0.046).Wound complications after soft tissue sarcomas of the extremities are associated with worse local oncological outcome and survival. Patients with high risk of wound complications should be identified and strategies implemented to reduce surgical complications and possibly improve oncologic prognosis.

Abstract Impaired bone homeostasis caused by osteomyelitis provokes serious variations in the bone remodeling process, thereby involving multiple inflammatory cytokines to activate bone healing. We have previously established a mouse model for post-traumatic osteomyelitis and studied bone regeneration after sufficient debridement. Moreover, we could further characterize the postinfectious inflammatory state of bony defects after debridement with elevated osteoclasts and decreased bone formation despite the absence of bacteria. In this study, we investigated the positive effects of Wnt-pathway modulation on bone regeneration in our previous established mouse model. This was achieved by local application of Wnt3a, a recombinant activator of the canonical Wnt-pathway. Application of Wnt3a could enhance new bone formation, which was verified by histological and μ-CT analysis. Moreover, histology and western blots revealed enhanced osteoblastogenesis and downregulated osteoclasts in a RANKL-dependent manner. Further analysis of Wnt-pathway showed downregulation after bone infections were reconstituted by application of Wnt3a. Interestingly, Wnt-inhibitory proteins Dickkopf 1 (DKK1), sclerostin, and secreted frizzled protein 1 (sFRP1) were upregulated simultaneously to Wnt-pathway activation, indicating a negative feedback for active form of Beta-catenin. In this study, we could demonstrate enhanced bone formation in defects caused by post-traumatic osteomyelitis after Wnt3a application. Key messages Osteomyelitis decreases bone regeneration Wnt3a restores bone healing after infection Canonical Wnt-pathway activation with negative feedback

BACKGROUND: Chronic inflammation is a hallmark among patients with cystic fibrosis (CF). We explored whether mutation-induced (F508del) misfolding of the cystic fibrosis transmembrane conductance regulator (CFTR), and/or secondary colonization with opportunistic pathogens, activate tissue remodeling and innate immune response drivers. METHODS: Using RNA-seq to interrogate global gene expression profiles, we analyzed stress response signaling cascades in primary human bronchial epithelia (HBE) and intestinal organoids. RESULTS: Primary HBE acquired from CF patients with advanced disease and prolonged exposure to pathogenic microorganisms display a clear molecular signature of activated tissue remodeling pathways, unfolded protein response (UPR), and chronic inflammation. Furthermore, CFTR misfolding induces inflammatory signaling cascades in F508del patient-derived organoids from both the distal small intestine and colon. CONCLUSION: Despite the small patient cohort size, this proof-of-principle study supports the use of RNA-seq as a means to both identify CF-specific signaling profiles in various tissues and evaluate disease heterogeneity. Our global transcriptomic data is a useful resource for the CF research community for analyzing other gene expression sets influencing CF disease signature but also transcriptionally contributing to CF heterogeneity.

Artificial intelligence (AI) gains importance in many domains and may soon be transferred decision-making responsibilities in production management from production managers. For the future, it will be vital to identify each entity’s domain of decision-making superiority. Therefore, this paper proposes and applies a model to assess AI performance in contrast to human decision-making. Relying on reinforcement learning and item response theory, the approach describes a minimum viable setup for AI systems to identify opportunities for AI systems in manufacturing. The model is based on operative production management decisions (job-shop scheduling) and validated through a series of academic scheduling instances.

Lifecycle extensions of production resources provide major leverage to the improvement of resource sustainability. This paper presents the results of a systematic literature review on technological fundamentals of intelligent maintenance and remanufacturing approaches as well as affiliated business models. In total, 3,368 paper were identified of which 35 were synthesized. Key findings are that less research activities focus on intelligent remanufacturing than on intelligent maintenance. Moreover, integrated decision frameworks for Prescriptive Maintenance are rare. Beyond that, identified maintenance approaches – most of them focusing on the energy sector – aim at avoiding machine breakdowns rather than ensuring a certain performance level.

ZUSAMMENFASSUNGEin 3-wöchiger Aufenthalt in einer Rehabilitationsklinik für Stoffwechselerkrankungen ermöglicht vieles, was ambulant nicht geschehen würde. Befreit von den Alltagsroutinen wie Arbeit und Haushalt, wird der Mensch aufnahmebereit für Neues. Motivationsaufbau und Selbstermächtigung verstärken sein gesundheitsförderliches Verhalten. Viele stellen ihre Bewegungs- und Ernährungsgewohnheiten sogar erfolgreich lebenslang um. Einigen Menschen ist dies jedoch nicht möglich. Hier geraten die Ärzte und Berater an ihre Grenzen, wenn der Patient zum wiederholten Male mit schlechtem HbA1c-Wert und unverändert adipös in der Reha auftaucht. Austherapiert und bedrohlich, hilft die 5. Wiederholung? Spätestens jetzt muss neben der klassisch medizinischen Behandlung auch der Behandlungskontext und die individuelle Bedeutungsreaktion Beachtung finden. Als Psychologin im Team greife ich nun auf den lösungsfokussierten Ansatz von De Jong und Berg zurück, um neben den zu erforschenden Schwierigkeiten die Freude auf die Zukunft zu wecken.

In this brief, the calculation of the signal behavior and the achievable signal-to-quantization-noise ratio of continuous-time (CT) incremental sigma–delta (I-SD) analog-to-digital converters (ADCs) is described. The presented method allows for the analysis of I-SD ADCs in frequency domain, including the specific non-idealities of the CT modulator. In the state-of-the-art, it is described that the omission of the preceding sample-and-hold for the I-SD ADC alters the transfer characteristic compared to a Nyquist-rate converter. So far, for CT I-SD ADCs this behavior is only investigated via simulations. In this brief, the model of a discrete-time I-SD ADC is generalized and adapted for the CT case. This allows to analytically obtain the signal and noise transfer function of the I-SD ADC in frequency domain in combination with arbitrary reconstruction filters due to the utilization of the lifting method in a fast and accurate way.

In a successive-approximation-register (SAR) ADC, comparator noise is often one of the dominant error sources. In this brief, the relation between the input referred noise of a comparator and its resulting noise in an SAR ADC is presented. A scaling factor less than unity is found when the comparator noise is referred back to the ADC input. When the comparator contains both thermal and flicker noise, the noise profile is maintained when referred back to the ADC input; however, due to aliasing caused by sampling, the flicker noise corner at the ADC output is pushed toward lower frequencies compared with the flicker noise corner frequency of the comparator. The results are analytically derived and proven by simulation and measurement.

This paper presents a dynamic power reduction technique for incremental $\Delta \Sigma $ (I- $\Delta \Sigma $ ) modulators. The technique makes use of the unequal weighting of the digital reconstruction filter. The underlying idea is that the input signal samples are not equally weighted in the higher order reconstruction filter. Thus, it is possible to increase the non-idealities of the I- $\Delta \Sigma $ modulator during the runtime of a single Nyquist conversion, thereby saving power. This principal idea is verified by an example design, where the input-referred noise of the first integrator is dynamically increased, which allows for improved efficiency. The proposed technique is readily applicable to every state-of-the-art I- $\Delta \Sigma $ modulator. Furthermore, it is shown that this property can also be used to switch a single-bit digital-to-analog converter (DAC) into a multibit DAC during runtime, thereby greatly improving the achievable signal-to-quantization-noise ratio (SQNR) without suffering from the DAC non-linearity. The prototype I- $\Delta \Sigma $ modulator is manufactured in a 180-nm CMOS technology and achieves a dynamic range/SNDR = 91.5/86.6 dB for a sampling rate of 200 kS/s while consuming l.l mW from a 3-V supply, while the dynamic power reduction method accounts for 30% power savings.

What is the relation between ethical reflection and moral behavior? Does professional reflection on ethical issues positively impact moral behaviors? To address these questions, Schwitzgebel and Ru...

Journal of modelling in management (2018). doi:10.1108/JM2-02-2018-0016, Published by Emerald, Bradford

Background: Body image research deals a lot with awareness of the body as an entity. Studies that consider individual anatomical aspects and place them in an intercultural context are rarely present. Methods: For this purpose, general data, body perception and judgment of body images from 2163 (48% female and 52% male) participants from Germany, Nigeria, the USA and Japan were evaluated as part of a survey. Results: There were clear differences in the personal body image of the participants’ own buttocks, the buttocks as a beauty ideal and the way in which dissatisfaction was dealt with in different countries. In addition to sexual well-being (importance score: 0.405 a.u.), the country of origin (0.353), media consumption (0.042) and one’s own weight (0.069) were also identified as influencing factors for satisfaction with one’s own buttocks. A clear evolution could be derived regarding a WHR (waist-to-hip ratio) of well below 0.7, which was consistently favored by the participants but also propagated by influencers through images (p < 0.001). In this context, participants who indicated celebrities as role models for the buttocks showed a correspondingly high level of dissatisfaction with their own buttocks (R = −0.207, p < 0.001, ρ = −0.218). Conclusion: Overall, a highly significant correlation was shown between the consumption frequency of Instagram, TikTok and pornography with the negative perception of women’s own buttocks.

Throughout many present studies dealing with multi-modal fusion, decisions are synchronously forced for fixed time segments across all modalities. Varying success is reported, sometimes performance is worse than unimodal classification. Our goal is the synergistic exploitation of multimodality whilst implementing a real-time system for affect recognition in a naturalistic setting. Therefore we present a categorization of possible fusion strategies for affect recognition on continuous time frames of complete recording sessions and we evaluate multiple implementations from resulting categories. These involve conventional fusion strategies as well as novel approaches that incorporate the asynchronous nature of observed modalities. Some of the latter algorithms consider temporal alignments between modalities and observed frames by applying asynchronous neural networks that use memory blocks to model temporal dependencies. Others use an indirect approach that introduces events as an intermediate layer to accumulate evidence for the target class through all modalities. Recognition results gained on a naturalistic conversational corpus show a drop in recognition accuracy when moving from unimodal classification to synchronous multimodal fusion. However, with our proposed asynchronous and event-based fusion techniques we are able to raise the recognition system's accuracy by 7.83 percent compared to video analysis and 13.71 percent in comparison to common fusion strategies.

In the United States, approximately one third of the energy end-use is from the industry which makes the industrial sector ranked number one in terms of energy consumption. One way to lower the energy consumption and to enhance the energy efficiency in the industry is to combine intelligent linkage of energy consumer, distribution, storage, and energy supply. In this paper, the research is focused on the study of these combinations leading to a smart industrial consumer which can interact in a “smart grid” system. This model-based study considers the energy supply of a plastic processing company, the processing machines as well as the factory hall including a HVAC system. The energy flows of all technologies are linked and interdependent. Different energy efficiency measures are integrated, and an innovative flexible high-temperature system is introduced. The complex energy flows are shown and the end and primary energy demand as well as the CO2 emissions are determined. The plastic processing industry mainly uses electric power for their facilities. To obtain flexibility in using machines from many different energy sources such as combined heat and power plant (CHP), heat by the burning of natural gas, or electrical grid, the electrical heating method is changed to thermal oil heating in many production machines. The study shows the energy saving potential for a typical manufacturing company located in three different locations in Germany, Canada and the USA. Based on the results of the study, the end energy demand increases due to thermal losses. Besides the primary energy demand can be reduced up to 34 percent through a flexible use of different energy sources. Furthermore, a high degree of flexibility can be achieved.

PurposeCopy-number variants (CNVs) are generally interpreted by linking the effects of gene dosage with phenotypes. The clinical interpretation of noncoding CNVs remains challenging. We investigated the percentage of disease-associated CNVs in patients with congenital limb malformations that affect noncoding cis-regulatory sequences versus genes sensitive to gene dosage effects.MethodsWe applied high-resolution copy-number analysis to 340 unrelated individuals with isolated limb malformation. To investigate novel candidate CNVs, we re-engineered human CNVs in mice using clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing.ResultsOf the individuals studied, 10% harbored CNVs segregating with the phenotype in the affected families. We identified 31 CNVs previously associated with congenital limb malformations and four novel candidate CNVs. Most of the disease-associated CNVs (57%) affected the noncoding cis-regulatory genome, while only 43% included a known disease gene and were likely to result from gene dosage effects. In transgenic mice harboring four novel candidate CNVs, we observed altered gene expression in all cases, indicating that the CNVs had a regulatory effect either by changing the enhancer dosage or altering the topological associating domain architecture of the genome.ConclusionOur findings suggest that CNVs affecting noncoding regulatory elements are a major cause of congenital limb malformations.

The impact of transient tropospheric forcing on the deep vertical mountain-wave propagation is investigated by a unique combination of in situ and remote sensing observations and numerical modeling. The temporal evolution of the upstream low-level wind follows approximately a [Formula: see text] shape and was controlled by a migrating trough and connected fronts. Our case study reveals the importance of the time-varying propagation conditions in the upper troposphere and lower stratosphere (UTLS). Upper-tropospheric stability, the wind profile, and the tropopause strength affected the observed and simulated wave response in the UTLS. Leg-integrated along-track momentum fluxes ([Formula: see text]) and amplitudes of vertical displacements of air parcels in the UTLS reached up to 130 kN m−1 and 1500 m, respectively. Their maxima were phase shifted to the maximum low-level forcing by ≈8 h. Small-scale waves ([Formula: see text] km) were continuously forced, and their flux values depended on wave attenuation by breaking and reflection in the UTLS region. Only maximum flow over the envelope of the mountain range favored the excitation of longer waves that propagated deeply into the mesosphere. Their long propagation time caused a retarded enhancement of observed mesospheric gravity wave activity about 12–15 h after their observation in the UTLS. For the UTLS, we further compared observed and simulated [Formula: see text] with fluxes of 2D quasi-steady runs. UTLS momentum fluxes seem to be reproducible by individual quasi-steady 2D runs, except for the flux enhancement during the early decelerating forcing phase.

False-positive assay readouts caused by badly behaving compounds-frequent hitters, pan-assay interference compounds (PAINS), aggregators, and others-continue to pose a major challenge to experimental screening. There are only a few in silico methods that allow the prediction of such problematic compounds. We report the development of Hit Dexter, two extremely randomized trees classifiers for the prediction of compounds likely to trigger positive assay readouts either by true promiscuity or by assay interference. The models were trained on a well-prepared dataset extracted from the PubChem Bioassay database, consisting of approximately 311 000 compounds tested for activity on at least 50 proteins. Hit Dexter reached MCC and AUC values of up to 0.67 and 0.96 on an independent test set, respectively. The models are expected to be of high value, in particular to medicinal chemists and biochemists who can use Hit Dexter to identify compounds for which extra caution should be exercised with positive assay readouts. Hit Dexter is available as a free web service at http://hitdexter.zbh. uni-hamburg.de.

Introduction The optimal therapy for deep burn wounds is based on the principle of rapid necrectomy and coverage in order to achieve healing that is as scar-free as possible. The available infrastructure and the patient’s condition represent limitations. With enzymatic debridement, selective bedside debridement can now be performed, however the optimal cover after enzymatic debridement has not been elucidated to date. In this study we compare superficial dermal and deep dermal wounds, which are either covered with lactic acid membrane, piscine skin, or split-thickness skin graft. To validate our approach the healed burn wounds were examined for objective (elasticity, water content, sebum, wound healing) and subjective skin quality as part of our standard follow-up care. Methods In this study, 12 patients who had received piscine skin, lactic acid membrane, or split-thickness skin graft after enzymatic debridement were retrospectively examined objectively and subjectively for scar quality as part of follow-up care 12 months after the accident. The wound healing process was also documented. Results Acceleration of wound healing was observed with the application of piscine skin vs split-thickness skin graft or lactic acid membrane. Skin elasticity was comparable to that of split-thickness skin graft but significantly better than lactic acid membrane. The sebum production in wounds treated with piscine skin was higher compared to lactic acid membrane covered wounds. The water storage capacity in the piscine skin treated wounds was also significantly higher than in lactic acid membrane or split-thickness skin graft treated wounds. Using the POSAS score, an improvement in elasticity, thickness, pigmentation, and relief was shown in piscine skin treated wounds, as well as a reduction in pain and itching, compared to split-thickness skin graft or lactic acid membrane. Conclusions The use of intact piscine skin immediately following enzymatic debridement in burn wounds results in faster wound healing and better patient outcomes compared to split-thickness skin graft or lactic acid membrane.

The papers in this special issue contribute significantly to the discussion about translanguaging and pursue the critical discussion of multilingual practices while building on earlier work in urban sociolinguistics (Rampton 1995;Jørgensen 2008, inter alia), globalization (Blommaert 2010, inter alia), and on the research about language teaching and the multilingual subject (Kramsch 2009). The concept translanguaging glosses a contemporary linguistic reality, shaped by migration, mobility, and media in the conurbations of the 20th and 21st century and increasingly spreading out to the rest of the societies.

This postscript discusses the contributions of the four articles in this issue to the field and positions them in relation to other studies in recent CA research on L2. The articles focus on the two arenas for L2 learning: the classroom and the lifeworld of learners. These arenas are widely different from each other and equally so within with respect to organization and participation frameworks and the social practices deployed; but the interactional problems that participants confront inside and outside of the classroom partially overlap. Learning and teaching objects (or ‘learnables’) are brought into being by the participants through their joint actions, at particular moments in the ongoing activity, be it in a classroom or a situation in the lifeworld. The four articles re‐specify standard SLA concepts in interactional terms: attention and noticing (Kunitz, 2018, this issue), corrective feedback (Majlesi, 2018, this issue), negotiation of/for meaning (Eskildsen, 2018, this issue), and corrections and metalinguistic explanations (Theodorsdottir, 2018, this issue). Their re‐specification adds value to these concepts because it furnishes them with a publicly visible interactional grounding and shows in each case how linguistic items become objects for reflexive linguistic practices by the participants. [ABSTRACT FROM AUTHOR]

Airborne coherent Doppler wind lidar measurements, acquired during the Gravity Wave Life-Cycle (GW-LCYCLE) I field campaign performed from 2 to 14 December 2013 in Kiruna, Sweden, are used to investigate internal gravity waves (GWs) induced by flow across the Scandinavian Mountains. Vertical wind speed is derived from lidar measurements with a mean bias of less than 0.05 m s−1 and a standard deviation of 0.2 m s−1 by correcting horizontal wind projections onto the line-of-sight direction by means of ECMWF wind data. The horizontal wind speed and direction are retrieved from lidar measurements by applying a velocity–azimuth display scan and a spectral accumulation technique, leading to a horizontal resolution of about 9 km along the flight track and a vertical resolution of 100 m, respectively. Both vertical and horizontal wind measurements are valuable for characterizing GW properties as demonstrated by means of a flight performed on 13 December 2013 acquired during weather conditions favorable for orographic GW excitation. Wavelet power spectra of the vertical wind speed indicate that the horizontal GW wavelengths lay mainly between 10 and 30 km and that the GW amplitude above the mountain ridge decreases with increasing altitude. Additionally, the perturbations of the horizontal wind speed are analyzed, showing horizontal wavelengths in the excitation region of 100–125 km with upwind-tilted wave fronts. By means of elevation power spectra, it is revealed that vertical wind power spectra are dominated by the short-wave elevation part, whereas horizontal wind perturbations are dominated by the long-wave part.

Element partitioning is a key geochemical process. While partition coefficients between phases including melts have been measured in many experimental studies, new insight into the mechanisms of partitioning may be obtained by relating partitioning to melt structure. Here, we address this problem by exploring an ab initio molecular dynamics simulation approach. Combined with the thermodynamic integration method, these simulations provide a unique way to predict simultaneously thermodynamic properties related to element partitioning and information about the molecular structure of the melt. Thus, it should be possible not only to predict the partitioning of elements, but also to provide an explanation for this behavior based on atomic structures of the coexisting phases. Using this approach, we derive from first-principles the Ni partition coefficient between a metal and a silicate melt at 2500 K and ambient pressure, which is at least in qualitative agreement with experiment. Structural analysis of various (Mg,Fe,Ni) 2 SiO 4 silicate and (Fe,Ni) metal melts reveals that the Ni partitioning is mainly determined by its structural environment in the silicate melt, whereas the coordination environments of Ni and Fe are almost indistinguishable in the metal melt. Possible strategies to improve the predictive power of the proposed approach are discussed.

To understand the behavior of rare earth elements (REE) in magmatic systems it is important to characterize in a systematic way their incorporation into silicate melts and glasses. Here, we study the structural environment of the REE Y and La in four aluminosilicate glasses and melts with varying REE content, using a combined simulation and diffraction approach. Glasses are investigated by X-ray and neutron diffraction as well as classical molecular dynamics simulations using two different polarizable ion potentials. Structure models of the corresponding melts are derived from classical and first-principles molecular dynamics simulations. We discuss the effect of temperature on coordination numbers and rationalize the structural changes in response to variations in melt/glass composition in terms of cation field strengths. We find robust evidence that REE and Al coordination numbers decrease with increasing REE content in the investigated melts and glasses. Comparing the two classical potentials, one of them is able to reproduce features of the experimental structure factors with a mixture of corner- and edge-sharing Al-O/REE-O polyhedra, whereas the other potential predicts corner-sharing Al-O/REE-O polyhedra only.

Manufacturing companies face rising pressure due to increased competition. Traditionally, companies have merely concentrated on offering impeccable, cost-efficient products. Today, however, flexibility and on-time delivery are additional requirements to satisfy the customers. At the same time, disruptions in production, especially in low-volume assembly, still frequently occur, leading to economic losses and delayed customer deliveries. The approach proposed in this paper strives for improving the disruption situation in low-volume assemblies. A detailed disruption management methodology has been developed, aiming at realizing an efficient reduction of disruptions, while at the same time considering the specific characteristics of low-volume assembly. The methodology is supported by a catalog of pre-emptive measures. These measures are known to reduce the disruptions’ occurrence or to diminish their consequences. In general, the approach pursues the basic idea to implement particularly those measures, which have the best cost-benefit-ratio. Based on the analysis of the cost-benefit-ratio of each measure, the developed methodology aims at improving the disruption situation in assembly and thus providing a high on-time delivery rate. The usability of the methodology for the low-volume assembly context has been confirmed by assembly experts on the basis of an application of the methodology in an exemplary case study.

Two mountain wave events, which occurred over northern Scandinavia in December 2013 are analysed by means of airborne observations and global and mesoscale numerical simulations with horizontal mesh sizes of 16, 7.2, 2.4 and 0.8 km. During both events westerly cross-mountain flow induced upward-propagating mountain waves with different wave characteristics due to differing atmospheric background conditions. While wave breaking occurred at altitudes between 25 and 30 km during the first event due to weak stratospheric winds, waves propagated to altitudes above 30 km and interfacial waves formed in the troposphere at a stratospheric intrusion layer during the second event. Global and mesoscale simulations with 16 and 7.2 km grid sizes were not able to simulate the amplitudes and wavelengths of the mountain waves correctly due to unresolved mountain peaks. In simulations with 2.4 and 0.8 km horizontal resolution, mountain waves with horizontal wavelengths larger than 15 km were resolved, but exhibited too small amplitudes and too high energy and momentum fluxes. Simulated fluxes could be reduced by either increasing the vertical model grid resolution or by enhancing turbulent diffusion in the model, which is comparable to an improved representation of small-scale nonlinear wave effects.

We analyze a large-amplitude mountain wave event, which was observed by a ground-based lidar above New Zealand between 31 July and 1 August 2014. Besides the lidar observations, European Centre for Medium-Range Weather Forecasts (ECMWF) data, satellite observations, and ray tracing simulations are utilized in this study. It is found that the propagation of mountain waves into the middle atmosphere is influenced by two different processes at different stages of the event. At the beginning of the event, instabilities in a weak wind layer cause wave breaking in the lower stratosphere. During the course of the event the mountain waves propagate to higher altitudes and are refracted southward toward the polar night jet due to the strong meridional shear of the zonal wind. As the waves propagate out of the observational volume, the ground-based lidar observes no mountain waves in the mesosphere. Ray tracing simulations indicate that the mountain waves propagated to mesospheric altitudes south of New Zealand where the polar night jet advected the waves eastward. These results underline the importance of considering horizontal propagation of gravity waves, e.g., when analyzing locally confined observations of gravity waves.

The unbundling of formerly vertically integrated utilities in liberalized electricity markets led to a coordination problem between investments in the regulated electricity grid and investments into new power generation. At the same time investments into new generation capacities based on weather dependent renewable energy sources such as wind and solar energy are increasingly subsidized with different support schemes. Against this backdrop this article analyzes the locational choice of private wind power investors under different support schemes and the implications on grid investments. I find that investors do not choose system optimal locations in feed-in tariff schemes, feed-in premium schemes and subsidy systems with direct capacity payments. Consequently, inefficiencies arise if transmission investment follows wind power investment. A benevolent transmission operator can implement the first-best solution by anticipatory investment behavior, which is however only applicable under perfect regulation. Alternatively a location dependent network charge for wind power producers can directly influence investment decisions and internalize the grid integration costs of wind power generation.

An ear recognition system represents a powerful tool in forensic applications. Even in case the facial characteristic of a suspect is partly or fully covered an image of the outer ear may suffice to reveal a subject's identity. In forensic scenarios imagery may stem from surveillance cameras of environments where image compression is common practice to overcome limitations of storage or transmission capacities. Yet, the impact of severe image compression on ear recognition has remained undocumented. In this work the authors analyse the influence of different state-of-the-art image compression standards on ear detection and ear recognition algorithms. Evaluations conducted on an uncompressed ear database are considered with respect to different stages in the processing chain of an ear recognition system where compression may be applied, representing the most relevant forensic scenarios. Experimental results are discussed in detail highlighting the potential and limitations of automated ear recognition in presence of image compression.

The enactment of the Energy Concept by the German Government in 2010 set ambitious targets for the future energy transition in Germany. The most prominent goals include a greenhouse gas (GHG) emission reduction of the economy and an increase in the share of renewable energy in the whole energy sector. Since the long run effects of these policy measures are hard to assess, science-based policy evaluation methods are needed to identify weak points and areas with a need for action. This paper presents the results of the German Energy Reference Forecast with a focus on the electricity sector. It is based on an investment and dispatch model for the European electricity sector over the planning horizon of the ‘Energiewende’ up to 2050, with an emphasis on the time period up to 2030. We find that almost all targets of the German ‘Energiewende’ are not reached, for the case in which no further measures are undertaken. In particular reductions in GHG emissions fall short to the target value. Contrary to the negative results, e.g., regarding GHG-emissions as well as gross electricity consumption, generation from renewable energy sources will exceed the policy's target value.