This paper presents a mobile outdoor augmented reality application that enables a realistic three-dimensional on-site visualization of planned wind turbines in their surroundings. For this purpose, the requirements for such an application are presented, which were obtained from the discussion with representatives of the relevant target groups. In addition, the essential aspects of the graphical user interface and the technical concept (architecture) as well as the implementation and evaluation of the application are presented.
South East European countries are pursuing their way towards EU accession which involves the adoption of EU laws, standards, and policy approaches. This process of policy alignment faces a local institutional environment marked by existing institutional asymmetries between formal and informal institutions, often based on institutional voids. In this article, we examine the conditions for introducing the EU’s smart specialization approach to a context marked by institutional voids and asymmetries. We understand the institutional environment of South East European countries as low-coordination economies marked by low degrees of cooperation and trust. In such an environment, a participatory policymaking approach such as smart specialization can serve to mitigate institutional asymmetries but is likely to face major challenges, leading to an institutional smart specialization paradox that is exacerbated by the absence of an ex-ante conditionality. To explore these challenges, we examine institutional voids and asymmetries relevant for innovation policy in Bosnia and Herzegovina, based on a series of interviews with firms and intermediary organizations and an inductive research design inspired by grounded theory. Drawing on the results, we offer conclusions and policy recommendations for the upcoming introduction of smart specialization to Bosnia and Herzegovina and other EU enlargement countries.
This article analyses differences in sustainability performances across supplier groups in the automotive industry using a multiple regression approach. The supplier sustainability performance is proxied by the self-assessment questionnaire (SAQ), a document-based assessment tool widely used in the automotive industry. The supplier groups are divided according to their headcount, business category and the region suppliers are located in. The analysis shows that the sustainability performance increases significantly with a supplier’s headcount. Furthermore, it shows that manufacturing suppliers perform significantly better compared to service providers. While there exist regional performance differences, the development stage of a country is found to be only a small significant factor influencing suppliers’ sustainability performances. Our results suggest OEM requirements in their assessments to be a major driver for supplier sustainability performance and that further analysis of regional factors is necessary.
The actin cortex of an animal cell is a thin polymeric layer attached to the inner side of the plasma membrane. It plays a key role in shape regulation and pattern formation on the cellular and tissue scale and, in particular, generates the contractile ring during cell division. Experimental studies showed that the cortex is fluid-like but highly viscous on long time scales with a mechanics that is sensitively regulated by active and passive cross-linker molecules that tune active stress and shear viscosity. Here, we use an established minimal model of active surface dynamics of the cell cortex supplemented with the experimentally motivated feature of mechanosensitivity in cross-linker binding dynamics. Performing linear stability analysis and computer simulations, we show that cross-linker mechanosensitivity significantly enhances the versatility of pattern formation and enables self-organized formation of contractile rings. Furthermore, we address the scenario of concentration-dependent shear viscosities as a way to stabilize ring-like patterns and constriction in the mid-plane of the active surface.
This paper presents two experiments measuring the impact of a virtual nose on simulator sickness and game experience in two virtual reality games. The pilot study contrasts a design implementation from the sensorial conflict theory (habituation) to one design suggestion from the rest-frame hypothesis (virtual nose). Habituation contributed significantly to the reduction of simulator sickness while the low fidelity prototype of the virtual nose did not. The main study presents an improved nose model and investigated the impact of awareness toward the virtual nose. The improved nose indicated that the usage of a virtual nose reduces simulator sickness while it does not affect the game experience. Further results showed no significant impact of the rest-frame’s awareness, neither on simulator sickness nor on the game experience. In sum, the outcome of the study supports the thesis that a rest-frame in form of a stable virtual nose can be used in demanding virtual reality applications to reduce simulator sickness while not affecting the game experience.
View Video Presentation: https://doi.org/10.2514/6.2022-4135.vid The implementation of a novel, cost-effective PVDF piezo-film sensor array for unsteady wall-pressure measurements in supersonic flows is introduced. With this type of technique, multiple local pointwise measurements can be taken simultaneously from a single thin foil without disturbing the flow field. The paper presents a detailed explanation of the design of the sensor array and of its signal conditioning system. The sensor array is tested in a turbulent incident shockwave/boundary layer interaction (SBLI) at Mach 2 and validated through favorable comparison with a classical Kulite piezoresistive transducer. The results of unsteady wall-pressure measurements also show good agreement with other SBLI studies already presented in the literature.
The program FITTER, which has been used successfully for many years to analyze the hyperfine structure in atomic and ionic spectra, has been extended. Confidence intervals for all adjusted parameters are now calculated, adding essential information to the results. A brief overview of the theoretical basics of hyperfine structure is given, the calculation of the confidence intervals is presented and the application is discussed using an example.
Breast diseases are a group of diseases that appear in different forms. An entire group of these diseases is breast cancer. This disease is one of the most important and common diseases in women. A machine learning system has been trained to identify specific patterns using an algorithm in a machine learning system to diagnose breast cancer. Therefore, designing a feature extraction method is essential to decrease the computation time. In this article, a two-dimensional contourlet is utilized as the input image based on the Breast Cancer Ultrasound Dataset. The sub-banded contourlet coefficients are modeled using the time-dependent model. The features of the time-dependent model are considered the leading property vector. The extracted features are applied separately to determine breast cancer classes based on classification methods. The classification is performed for the diagnosis of tumor types. We used the time-dependent approach to feature contourlet sub-bands from three groups of benign, malignant, and health control test samples. The final feature of 1200 ultrasound images used in three categories is trained based on k-nearest neighbor, support vector machine, decision tree, random forest, and linear discrimination analysis approaches, and the results are recorded. The decision tree results show that the method’s sensitivity is 87.8%, 92.0%, and 87.0% for normal, benign, and malignant, respectively. The presented feature extraction method is compatible with the decision tree approach for this problem. Based on the results, the decision tree architecture with the highest accuracy is the more accurate and compatible method for diagnosing breast cancer using ultrasound images.
Since direct oral anticoagulants (DOAC) are administered frequently to an elderly, co-morbid population, medical emergencies including trauma, acute bleeding or organ failure are not uncommon. In these situations, the type, dosage or the time of last intake of anticoagulants is often unknown and single substance analysis by functional tests is only possible if the substance contained in the sample is known. A reliable and validated toxicology screen of DOAC and argatroban would be helpful inform not only attending physicians in the emergency department but also law enforcement and courts of justice. After precipitation with acetone, HPLC separation was achieved on a Phenomenex Luna Pentafluorophenyl Colum using acetonitrile–water (90:10, v/v) as mobile phase system. Detection was performed using a 3200 Q Trap mass spectrometer (AB Sciex). For analysis MRM Scans (MS/MS) with positive ionization were chosen. The method was validated for blank serum as the matrix of choice. Limits of detection are between 0.5 and 1.0 ng/mL, limits of quantification are between 1.9 and 3.6 ng/mL and recoveries are above 60%. The applicability of the method was demonstrated by the determination of DOAC in body fluids from forensic cases and in therapeutic drug monitoring. The rapid simultaneous detection and quantification of apixaban, argatroban, dabigatran etexilate, dabigatran, edoxaban and rivaroxaban in body fluids by HPLC–MS/MS closes an important gap in emergency toxicology.
Klassische Betondeckungsmessgeräte geraten bei Betondeckungen von mehr als 6 bis 7 cm und bei Objekten hinter oberflächennaher Bewehrung an ihre Grenzen. In diesem Beitrag wird für tiefere Objekte primär auf Ultraschall eingegangen und zunächst dessen Einsatzbereich von Radar abgegrenzt. Während die „Betondeckung“ mit max. 6 bis 7 cm nur für die Dauerhaftigkeit von Beton eine Rolle spielt, werden Radar und Ultraschallecho zur Ermittlung der „Einbautiefe“ von Hüllrohren und Bewehrung in deutlich größeren Tiefen verwendet, deren Kenntnis primär für den Nachweis der Standsicherheit von Konstruktionen notwendig ist (ZfPStatik). Dabei entscheiden Prüfaufgabe und Randbedingungen, welches Verfahren zum Einsatz kommt. Durch systematische Untersuchungen an Betonbauteilen und der Variation von Verlegedichte der Bewehrung an der Oberfläche, Einbautiefe, Stababstand der zu detektierenden Bewehrung und deren Durchmesser werden Leistungsfähigkeit und Grenzen von Ultraschall in Echo‐Anordnung (Sender und Empfänger eines Arrays auf einer Seite des Bauteils) hinsichtlich der Detektierbarkeit von Hüllrohren und Bewehrungsstäben aufgezeigt und die Genauigkeit der Messung der Einbautiefe ermittelt. Diese Erkenntnisse zu Ultraschall werden abschließend im Vergleich zur Leistungsfähigkeit von Radar und magnetisch induktiven Verfahren eingeordnet, die bereits in vorangegangenen Beiträgen behandelt wurden. Durch die zusammenfassende Betrachtung am Ende dieses Beitrags soll es dem Anwender erleichtert werden, das für seine Prüfaufgabe und Randbedingungen am besten geeignete Verfahren auszuwählen und realistische Erwartungen an die erzielbaren Ergebnisse zu stellen. Detection of tendon ducts and rebars and the accuracy of the measured concrete cover using ultrasonic echo Classical covermeters come to their limits when the concrete cover exceeds 6 to 7 cm or beneath a mesh. Concrete cover measurement with these devices is performed up to 6 to 7 cm and is only of interest for durability. Concrete cover in greater depth is performed with Radar and Ultrasonic Echo with the focus on stability of structures (NDT‐SC, static calculations). The decision of the appropriate method depends on the boundary conditions, given by the spacing of the rebars near the surface, the depth, diameter and spacing of the objects to be detected. These parameters have been varied systematically in different concrete members to quantify the accuracy as well as strength and limitations especially for Ultrasonic Echo. The obtained results will be set in the context of Radar and magnetic methods with results of former publications. This will help the operator to make the best decision to find the appropriate method according to his testing task or boundary conditions.
The d-dimensional weighted region shortest path problem asks for finding a shortest path between two given points s and t in a d-dimensional polyhedral structure consisting of polyhedral cells having individual positive weights. It is a generalization of the d-dimensional unweighted (Euclidean) shortest path problem for polyhedral structures. In the unweighted (Euclidean) setting, a shortest path visits, due to cell convexity, each polyhedral cell at most once. Surprisingly, this is no longer true for the weighted setting, which is a strong motivation for studying the complexity of weighted shortest paths in polyhedral structures. Previously, Ω(n2), respectively Ω(n3) lower bounds on the maximum number of cell crossings for weighted shortest paths in 2-dimensional, respectively 3-dimensional polyhedral structures have been obtained. In this paper, a new lower bound of Ω(nd) is derived on the maximum number of cell crossings a weighted shortest path could take in d-dimensional polyhedral structures consisting of a linear number of O(n) polyhedral cells and cell faces. This new result is a generalization and sharpening of the formerly known lower bounds and has been a long-standing open problem for the general d-dimensional case.
For research as well as policymakers aiming at fostering multilevel transitions toward sustainability, there is a clear need to better understand the transformative role and relevance of startups as newcomers in the market. The existing typologies of sustainable entrepreneurship and green startups have been derived from theory and are conceptual or anecdotal in nature. The lack of validity and generalizability is a major research gap, as the existing typologies do not provide a sufficient basis for policy decisions on how to promote which type of entrepreneurship to effectively support specific transition policies. Against this backdrop, we investigate the research question: Does the transformation orientation differ among startups, and if so, how can they be clustered as basis for sustainability transition policy? Based on a sample of 1674 startups and cluster analysis, the paper makes three important contributions: First, we provide a differentiated perspective and empirical data on the transformation orientation of newcomers. Second, we provide an empirically founded taxonomy of the transformative orientation of startups and contribute to theory-building of transformative entrepreneurship. Third, we test the assumption inherent in most existing frameworks that there exists a high-potential subgroup of startups. Our results confirm the existence of a clearly distinguishable subgroup with a particularly high transformation orientation, which we label as "sustainability transformers." In terms of transition strategies, policymakers can build on our findings to adjust public funds and support programs in favor of specific subgroups such as sustainability transformers.
The spectra emitted by a thulium hollow-cathode discharge lamp with argon or neon as inert gases have been recorded with a Bruker IFS 125 HR Fourier Transform spectrometer in the visible wavelength region from 400 nm to 700 nm. The paper presents the investigation of the hyperfine-structure splitting of 50 spectral lines of neutral thulium. As a result, the magnetic dipole hyperfine structure constant A for 20 fine structure levels of Tm I have been determined for the first time.
In this study, we investigated the hyperfine structure of 43 spectral lines of atomic thulium. We analyzed Fourier-transform spectra in the wavelength range from 700 nm to 2250 nm, which corresponds to the wavenumber range from 14300 cm⁻¹ to 4440 cm⁻¹, respectively. The excited thulium atoms were generated in a hollow-cathode lamp. As a result of this investigation, the magnetic-dipole hyperfine constant A of 17 fine structure levels have been determined experimentally, 14 of them for the first time. The magnetic-dipole hyperfine constant values of the three remaining levels, reported in the literature, differed significantly from the results of our determination.
Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses. This study presents the results of the second round of the Critical Assessment of Metagenome Interpretation challenges (CAMI II), which is a community-driven effort for comprehensively benchmarking tools for metagenomics data analysis.
In the present study, two pretreatment methods (thermal pretreatment and biological pre-hydrolysis) were suggested for food waste (FW) with the aim to enhance biomass conversion and biogas production by anaerobic. The effects of thermal pretreatment (TP), including TP at 60°C and 80°C for 60 min, and TP at 100°C, 120°C and 140°C for 30 min, well as biological pre-hydrolysis (BPH) at 37°C, 55°C, 37°C followed by 55°C and 55°C followed by 37°C for 40 hour on anaerobic digestion performance of FW were evaluated in batch tests. Results were compared with untreated FW. The BPH and TP caused an increase in the soluble chemical oxygen demand and hydrolysis efficiency. The methane yield (MY) increased from 371.17 ml CH4/g VS for untreated FW to 471.95 ml CH4/ g VS. The maximal MY was recorded for BPH at 37°C for 20 h followed by 55°C for 20 h. The pretreatments increased the biogas production rate and reduced the lag phase. The most influential variables on the methane yield were investigated using three statistical methods: Principal component analysis, Mutual Information and R-squared. The results allowed a good modeling of the methane yield and minimized the overfitting effect. For reproduction and solid contribution to the field, we have attached to our article all the necessary material to reproduce the same statistical work as in the paper body.
Expert interviews can provide interesting data for the use in qualitative comparative analysis (OCA) to investigate complex social phenomena. To guide the challenging task of data calibration from qualitative data sets, techniques have already been suggested for the transformation of qualitative data into fuzzy sets. The current article follows existing guidelines and extends them with a system for indicator-based data calibration of expert interviews. While the underlying data set is confidential due to its corporate setting, in this article the analysis of the data is made transparent and hence reproducible for potential follow-up studies. First, the process of data collection is described, and the final data sample is characterized. Consequently, a system for indicator-based data calibration is presented and the calibration results for the empirical sample are provided in form of the set membership of cases and truth tables. • Data collection from expert interviews is described for a configurational setting • A combined indicator-based system is used for the calibration of qualitative data
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