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Cyber-physical systems (CPS) have shaped the discussion about Industry 4.0 (I4.0) for some time. To ensure the competitiveness of manufacturing enterprises the vision for the future figures out cyber-physical production systems (CPPS) as a core component of a modern factory. Adaptability and coping with complexity are (among others) potentials of this new generation of production management. The successful transformation of this theoretical construct into practical implementation can only take place with regard to the conditions characterizing the context of a factory. The subject of this contribution is a concept that takes up the brownfield character and describes a solution for extending existing (legacy) systems with CPS capabilities.
There is an increasing interest in fusing data from heterogeneous sources. Combining data sources increases the utility of existing datasets, generating new information and creating services of higher quality. A central issue in working with heterogeneous sources is data migration: In order to share and process data in different engines, resource intensive and complex movements and transformations between computing engines, services, and stores are necessary.
Muses is a distributed, high-performance data migration engine that is able to interconnect distributed data stores by forwarding, transforming, repartitioning, or broadcasting data among distributed engines' instances in a resource-, cost-, and performance-adaptive manner. As such, it performs seamless information sharing across all participating resources in a standard, modular manner. We show an overall improvement of 30 % for pipelining jobs across multiple engines, even when we count the overhead of Muses in the execution time. This performance gain implies that Muses can be used to optimise large pipelines that leverage multiple engines.
We study those nonlinear partial differential equations which appear as Euler-Lagrange equations of variational problems. On defining weak boundary values of solutions to such equations we initiate the theory of Lagrangian boundary value problems in spaces of appropriate smoothness. We also analyse if the concept of mapping degree of current importance applies to Lagrangian problems.
Compound natural hazards likeEl Ninoevents cause high damage to society, which to manage requires reliable risk assessments. Damage modelling is a prerequisite for quantitative risk estimations, yet many procedures still rely on expert knowledge, and empirical studies investigating damage from compound natural hazards hardly exist. A nationwide building survey in Peru after theEl Ninoevent 2017 - which caused intense rainfall, ponding water, flash floods and landslides - enables us to apply data-mining methods for statistical groundwork, using explanatory features generated from remote sensing products and open data. We separate regions of different dominant characteristics through unsupervised clustering, and investigate feature importance rankings for classifying damage via supervised machine learning. Besides the expected effect of precipitation, the classification algorithms select the topographic wetness index as most important feature, especially in low elevation areas. The slope length and steepness factor ranks high for mountains and canyons. Partial dependence plots further hint at amplified vulnerability in rural areas. An example of an empirical damage probability map, developed with a random forest model, is provided to demonstrate the technical feasibility.
Children's participation in legal proceedings affecting them personally has been gaining importance. So far, a primary research concern has been how children experience their participation in court proceedings. However, little is known about the child's voice itself: Are children able to clearly express their wishes, and if so, what do they say in child protection cases? In this study, we extracted information about children's statements from court file data of 220 child protection cases in Germany. We found 182 children were asked about their wishes. The majority of the statements found came either from reports of the guardians ad litem or from judicial records of the child hearings. Using content analysis, three main aspects of the statements were extracted: wishes concerning main place of residence, wishes about whom to have or not contact with, and children granting decision-making authority to someone else. Children's main focus was on their parents, but others (e.g., relatives and foster care providers) were also mentioned. Intercoder agreement was substantial. Making sure that child hearings are as informative as possible is in the child's best interest. Therefore, the categories developed herein might help professionals to ask questions more precisely relevant to the child.
Technological advancements are giving rise to the fourth industrial revolution - Industry 4.0 -characterized by the mass employment of smart objects in highly reconfigurable and thoroughly connected industrialproduct-service systems. The purpose of this paper is to propose a theory-based knowledgedynamics model in the smart grid scenario that would provide a holistic view on the knowledge-based interactions among smart objects, humans, and other actors as an underlyingmechanism of value co-creation in Industry 4.0. A multi-loop and three-layer - physical, virtual, and interface - model of knowledge dynamics is developedby building on the concept of ba - an enabling space for interactions and theemergence of knowledge. The model depicts how big data analytics are just one component inunlocking the value of big data, whereas the tacit engagement of humans-in-the-loop - theirsense-making and decision-making - is needed for insights to be evoked fromanalytics reports and customer needs to be met.
Flood loss data collection and modeling are not standardized, and previous work has indicated that losses from different flood types (e.g., riverine and groundwater) may follow different driving forces. However, different flood types may occur within a single flood event, which is known as a compound flood event. Therefore, we aimed to identify statistical similarities between loss-driving factors across flood types and test whether the corresponding losses should be modeled separately. In this study, we used empirical data from 4,418 respondents from four survey campaigns studying households in Germany that experienced flooding. These surveys sought to investigate several features of the impact process (hazard, socioeconomic, preparedness, and building characteristics, as well as flood type). While the level of most of these features differed across flood type subsamples (e.g., degree of preparedness), they did so in a nonregular pattern. A variable selection process indicates that besides hazard and building characteristics, information on property-level preparedness was also selected as a relevant predictor of the loss ratio. These variables represent information, which is rarely adopted in loss modeling. Models shall be refined with further data collection and other statistical methods. To save costs, data collection efforts should be steered toward the most relevant predictors to enhance data availability and increase the statistical power of results. Understanding that losses from different flood types are driven by different factors is a crucial step toward targeted data collection and model development and will finally clarify conditions that allow us to transfer loss models in space and time. <br /> Key Points <br /> Survey data of flood-affected households show different concurrent flood types, undermining the use of a single-flood-type loss model Thirteen variables addressing flood hazard, the building, and property level preparedness are significant predictors of the building loss ratio Flood type-specific models show varying significance across the predictor variables, indicating a hindrance to model transferability
We present the results from Chandra X-ray observations, and near- and mid-infrared analysis, using VISTA/VVV and Spitzer/GLIMPSE catalogs, of the high-mass star-forming region IRAS 16562-3959, which contains a candidate for a high-mass protostar. We detected 249 X-ray sources within the ACIS-I field of view. The majority of the X-ray sources have low count rates (<0.638 cts/ks) and hard X-ray spectra. The search for YSOs in the region using VISTA/VVV and Spitzer/GLIMPSE catalogs resulted in a total of 636 YSOs, with 74 Class I and 562 Class II YSOs. The search for near- and mid-infrared counterparts of the X-ray sources led to a total of 165 VISTA/VVV counterparts, and a total of 151 Spitzer/GLIMPSE counterparts. The infrared analysis of the X-ray counterparts allowed us to identify an extra 91 Class III YSOs associated with the region. We conclude that a total of 727 YSOs are associated with the region, with 74 Class I, 562 Class II, and 91 Class III YSOs. We also found that the region is composed of 16 subclusters. In the vicinity of the high-mass protostar, the stellar distribution has a core-halo structure. The subcluster containing the high-mass protostar is the densest and the youngest in the region, and the high-mass protostar is located at its center. The YSOs in this cluster appear to be substantially older than the high-mass protostar.
We study the Cauchy problem for a nonlinear elliptic equation with data on a piece S of the boundary surface partial derivative X. By the Cauchy problem is meant any boundary value problem for an unknown function u in a domain X with the property that the data on S, if combined with the differential equations in X, allows one to determine all derivatives of u on S by means of functional equations. In the case of real analytic data of the Cauchy problem, the existence of a local solution near S is guaranteed by the Cauchy-Kovalevskaya theorem. We discuss a variational setting of the Cauchy problem which always possesses a generalized solution.
Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI<18.5 kg/m(2)) or obese (BMI30 kg/m(2)) categories, while the highest quartile of ABSI separated 18-39% of the individuals within each BMI category, which had 22-55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.
Abiotic stresses cause oxidative damage in plants. Here, we demonstrate that foliar application of an extract from the seaweed Ascophyllum nodosum, SuperFifty (SF), largely prevents paraquat (PQ)-induced oxidative stress in Arabidopsis thaliana. While PQ-stressed plants develop necrotic lesions, plants pre-treated with SF (i.e., primed plants) were unaffected by PQ. Transcriptome analysis revealed induction of reactive oxygen species (ROS) marker genes, genes involved in ROS-induced programmed cell death, and autophagy-related genes after PQ treatment. These changes did not occur in PQ-stressed plants primed with SF. In contrast, upregulation of several carbohydrate metabolism genes, growth, and hormone signaling as well as antioxidant-related genes were specific to SF-primed plants. Metabolomic analyses revealed accumulation of the stress-protective metabolite maltose and the tricarboxylic acid cycle intermediates fumarate and malate in SF-primed plants. Lipidome analysis indicated that those lipids associated with oxidative stress-induced cell death and chloroplast degradation, such as triacylglycerols (TAGs), declined upon SF priming. Our study demonstrated that SF confers tolerance to PQ-induced oxidative stress in A. thaliana, an effect achieved by modulating a range of processes at the transcriptomic, metabolic, and lipid levels.
"Left" and "right" coordinates control our spatial behavior and even influence abstract thoughts. For number concepts, horizontal spatial-numerical associations (SNAs) have been widely documented: we associate few with left and many with right. Importantly, increments are universally coded on the right side even in preverbal humans and nonhuman animals, thus questioning the fundamental role of directional cultural habits, such as reading or finger counting. Here, we propose a biological, nonnumerical mechanism for the origin of SNAs on the basis of asymmetric tuning of animal brains for different spatial frequencies (SFs). The resulting selective visual processing predicts both universal SNAs and their context-dependence. We support our proposal by analyzing the stimuli used to document SNAs in newborns for their SF content. As predicted, the SFs contained in visual patterns with few versus many elements preferentially engage right versus left brain hemispheres, respectively, thus predicting left-versus rightward behavioral biases. Our "brain's asymmetric frequency tuning" hypothesis explains the perceptual origin of horizontal SNAs for nonsymbolic visual numerosities and might be extensible to the auditory domain.
The estimation of a log-concave density on R is a canonical problem in the area of shape-constrained nonparametric inference. We present a Bayesian nonparametric approach to this problem based on an exponentiated Dirichlet process mixture prior and show that the posterior distribution converges to the log-concave truth at the (near-) minimax rate in Hellinger distance. Our proof proceeds by establishing a general contraction result based on the log-concave maximum likelihood estimator that prevents the need for further metric entropy calculations. We further present computationally more feasible approximations and both an empirical and hierarchical Bayes approach. All priors are illustrated numerically via simulations.
Prenylated flavanones were obtained from ortho-allyloxy chalcones through a one-pot sequence of Claisen rearrangement and 6-endo-trig cyclization, followed by olefin cross metathesis of the intermediate allyl flavanones with 2-methyl-2-butene. The synthetic utility of this route is illustrated for the synthesis of several naturally occurring prenyl flavanones.
(40)A/Ar-39 step-heating of mica and amphibole megacrysts from hauyne-bearing olivine melilitite scoria/tephra from the Zelezna hurka yielded a 435 +/- 108 ka isotope correlation age for phlogopite and a more imprecise 1.55 Ma total gas age of the kaersutite megacryst. The amphibole megacrysts may constitute the first, and the younger phlogopite megacrysts the later phase of mafic, hydrous melilitic magma crystallization. It cannot be ruled out that the amphibole megacrysts are petrogenetically unrelated to tephra and phlogopite megacrysts and were derived from mantle xenoliths or disaggregated older, deep crustal pegmatites. This is in line both with the rarity of amphibole at Zelezna hurka and with the observed signs of magmatic resorption at the edges of amphibole crystals.
Ground-penetrating radar (GPR) is an established geophysical tool to explore a wide range of near-surface environments. Today, the use of synthetic GPR data is largely limited to 2D because 3D modeling is computationally more expensive. In fact, only recent developments of modeling tools and powerful hardware allow for a time-efficient computation of extensive 3D data sets. Thus, 3D subsurface models and resulting GPR data sets, which are of great interest to develop and evaluate novel approaches in data analysis and interpretation, have not been made publicly available up to now. <br /> We use a published hydrofacies data set of an aquifer-analog study within fluvio-glacial deposits to infer a realistic 3D porosity model showing heterogeneities at multiple spatial scales. Assuming fresh-water saturated sediments, we generate synthetic 3D GPR data across this model using novel GPU-acceleration included in the open-source software gprMax. We present a numerical approach to examine 3D wave-propagation effects in modeled GPR data. Using the results of this examination study, we conduct a spatial model decomposition to enable a computationally efficient 3D simulation of a typical GPR reflection data set across the entire model surface. We process the resulting GPR data set using a standard 3D structural imaging sequence and compare the results to selected input data to demonstrate the feasibility and potential of the presented modeling studies. We conclude on conceivable applications of our 3D GPR reflection data set and the underlying porosity model, which are both publicly available and, thus, can support future methodological developments in GPR and other near-surface geophysical techniques.
Monolithic perovskite silicon tandem solar cells can overcome the theoretical efficiency limit of silicon solar cells. This requires an optimum bandgap, high quantum efficiency, and high stability of the perovskite. Herein, a silicon heterojunction bottom cell is combined with a perovskite top cell, with an optimum bandgap of 1.68 eV in planar p-i-n tandem configuration. A methylammonium-free FA(0.75)Cs(0.25)Pb(I0.8Br0.2)(3) perovskite with high Cs content is investigated for improved stability. A 10% molarity increase to 1.1 m of the perovskite precursor solution results in approximate to 75 nm thicker absorber layers and 0.7 mA cm(-2) higher short-circuit current density. With the optimized absorber, tandem devices reach a high fill factor of 80% and up to 25.1% certified efficiency. The unencapsulated tandem device shows an efficiency improvement of 2.3% (absolute) over 5 months, showing the robustness of the absorber against degradation. Moreover, a photoluminescence quantum yield analysis reveals that with adapted charge transport materials and surface passivation, along with improved antireflection measures, the high bandgap perovskite absorber has the potential for 30% tandem efficiency in the near future.
Herein, we represent cation-responsive fluorescent probes for the divalent cations Zn2+, Mg2+ and Ca2+, which show cation-induced fluorescence enhancements (FE) in water. The Zn2+-responsive probes Zn1, Zn2, Zn3 and Zn4 are based on o-aminoanisole-N,N-diacetic acid (AADA) derivatives and show in the presence of Zn2+ FE factors of 11.4, 13.9, 6.1 and 8.2, respectively. Most of all, Zn1 and Zn2 show higher Zn2+ induced FE than the regioisomeric triazole linked fluorescent probes Zn3 and Zn4, respectively. In this set, ZN2 is the most suitable probe to detect extracellular Zn2+ levels. For the Mg2+-responsive fluorescent probes Mg1, Mg2 and Mg3 based on o-aminophenol-N,N,O-triacetic acid (APTRA) derivatives, we also found that the regioisomeric linkage influences the fluorescence responds towards Mg2+ (Mg1+100 mM Mg2+ (FEF=13.2) and Mg3+100 mM Mg2+ (FEF=2.1)). Mg2 shows the highest Mg2+-induced FE by a factor of 25.7 and an appropriate K-d value of 3 mM to measure intracellular Mg2+ levels. Further, the Ca2+-responsive fluorescent probes Ca1 and Ca2 equipped with a 1,2-bis(o-aminophenoxy)ethane-N,N,N',N'-tetraacetic acid (BAPTA) derivative show high Ca2+-induced FEs (Ca1 (FEF=22.1) and Ca2 (FEF=23.0)). Herein, only Ca1 (K-d=313 nM) is a suitable Ca2+ fluorescent indicator to determine intracellular Ca2+ levels.
We present novel experimental evidence on the availability and the status of exhaustivity inferences with focus partitioning in German, English, and Hungarian. Results suggest that German and English focus-background clefts and Hungarian focus share important properties, (É. Kiss 1998, 1999; Szabolcsi 1994; Percus 1997; Onea & Beaver 2009). Those constructions are anaphoric devices triggering an existence presupposition. EXH-inferences are not obligatory in such constructions in English, German, or Hungarian, against some previous literature (Percus 1997; Büring & Križ 2013; É. Kiss 1998), but in line with pragmatic analyses of EXH-inferences in clefts (Horn 1981, 2016; Pollard & Yasavul 2016). The cross-linguistic differences in the distribution of EXH-inferences are attributed to properties of the Hungarian number marking system.