Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimentelle Untersuchungen zur mitwirkenden Breite für Querkraft von einfeldrigen Fahrbahnplatten

Die Anforderungen an Brückenbauwerke haben sich in den vergangenen Jahren infolge der steigenden Verkehrszahlen deutlich erhöht. Gleichzeitig hat sich mit der Umstellung der Normen der rechnerische Querkraftwiderstand von Bauteilen ohne Querkraftbewehrung verringert. Als Folge lässt sich für Brückenbauwerke im Bestand mit Fahrbahnplatten ohne Querkraftbewehrung nach derzeitigen technischen Regeln oft keine ausreichende Querkrafttragfähigkeit nachweisen. Daher wurde im Rahmen eines von der Bundesanstalt für Straßenwesen (BASt) geförderten Forschungsvorhabens das Querkrafttragverhalten von Fahrbahnplatten aus Stahlbeton genauer analysiert. Der vorliegende Aufsatz beschreibt die Ergebnisse der experimentellen Untersuchungen zur maßgebenden Lastverteilungsbreite für Radlasten bei einfeldrigen, gelenkig gelagerten Platten ohne Querkraftbewehrung.
Self-amplitude modulation in PSK coherent optical transmission systems

Self-amplitude modulation due to group velocity dispersion (chromatic dispersion of an optical fiber) in phase-shift keying (PSK) coherent optical transmission systems is presented. It may place a serious limitation on performance of such systems by limiting the maximum transmission distance attainable at a given bit rate. The maximum transmission distance for any prescribed degree of self-amplitude modulation is derived for PSK coherent systems. The result shows that the distance over which appreciable amplitude modulation is impressed on a phase-modulated signal is considerably less than the dispersion-limited transmission distance for intensity modulated direct detection systems.
A sampling method for the objective thinning of IASI channels

There is a vast amount of information about the current state of the atmosphere from instruments measuring the top of the atmosphere radiances on board satellites. One example is the IASI (Infrared Atmospheric Sounding Interferometer) instrument which measures radiances emitted from the Earth’s atmosphere and surface in 8461 channels. In many cases it is difficult to transmit, store and assimilate such a large amount of data. A practical solution to this has been to select a subset of a few hundred channels based on those which contain the most useful information. Different measures of information content for objective channel selection have been suggested for application to variational data assimilation. These include mutual information and the degrees of freedom for signal. To date, the calculation of these measures of information content have been based on the linear theory which is at the heart of operational variational data assimilation. However the retrieval of information about the atmosphere from the satellite radiances can be highly non-linear. Here we look at a sampling method for calculating the mutual information which is free from assumptions about the linearity of the relationship between the observed radiances and the state variables. How this new estimate of information content can be used in channel selection is addressed, with particular attention given to the efficiency of the new method.
Fabrication of silicon-silicide-on-insulator substrates using wafer bonding and layer-cutting techniques

A novel single-crystalline Si/poly-CoSi/sub 2//SiO/sub 2//Sub-Si structure has been successfully formed by silicon wafer bonding and hydrogen implantation induced layer cutting techniques. The hydrogen implanted silicon wafer were deposited by a thin Co and Si films subsequently and was brought into contact with an. During the oxidized silicon wafer at room temperature. During the subsequent annealing, the hydrogen-implanted wafer was split along the projected range, leaving a thin Si film and the above deposited films on the oxidized wafer to form a multi-layer structure. The following annealing procedure not only increases the bond strength, but also employs solid state reaction of the deposited Co to form a buried poly-crystalline CoSi/sub 2/ layer with a resistivity of about 160 /spl mu//spl Omega//spl middot/cm.
Turbine Tip and Shroud Heat Transfer and Loading: Part B — Comparisons Between Prediction and Experiment Including Unsteady Effects

Flowfield predictions in the tip regions of turbine blades have recently increased in fidelity, but additional data and greater collaboration between numerical and physical experimenters is required to make further improvements. This is particularly true as one moves to experiments and predictions of the full annulus, rotating conditions found in actual turbomachines. Toward this end, a recent set of experimental measurements obtained in a single-stage high pressure turbine at the US Air Force Turbine Research Facility (TRF) was complemented with true predictions of the tip flowfield undertaken at Pratt & Whitney. The TRF is a full scale rotating rig that operates at flow conditions that are non-dimensionally consistent with the true turbine environment. Both heat transfer and surface pressure measurements were obtained on the tip of the blade, along the shroud, and at 96.5% of the blade span providing significantly detailed information on the flowfield in the tip region. The experimental data was obtained at frequencies up to 100 kHz so that multiple data samples per vane and/or blade passing event were recorded. These measurements were complemented and extended with 3-D, Reynolds-Averaged Navier-Stokes (RANS) predictions that together revealed the true flow pattern and the overall heat load to the airfoil. Because of the greater spatial resolution of the predictions, they also revealed additional flowfield physics that was not captured by the experiment. Both steady state and time-resolved comparisons were then made between the predictions and the data to reveal the complex nature of the flowfield in the turbine tip-gap region. These comparisons will help to elucidate the fundamental physics involved in this highly complicated region of the turbine.Copyright © 2003 by ASME
Modular Extensions of Security Monitors for Web APIs: The DOM API Case Study

Client-side JavaScript programs often interact with the web page on which they are included, as well as the browser itself, through APIs such as the DOM API, the XMLHttpRequest API, and the W3C Geolocation API. The continuous emergence and heterogeneity of different APIs renders the problem of reasoning precisely about JavaScript security particularly challenging. To tackle this problem, we propose a methodology for extending sound JavaScript information ﬂow monitors. This methodology allows us to verify whether a monitor complies with the proposed noninterference property in a modular way. Thus, proving that a monitor is noninterferent after extending it with a new API only requires the proof that the API is itself noninterferent. We show how to extend an information ﬂow monitor-inlining compiler so that it takes into account the invocation of arbitrary APIs and we provide an implementation of such a compiler. Using the proposed methodology, we present a group of monitor extensions for handling a fragment of the DOM Core Level 1 API for which we have studied information leaks not explored in previous work.
Chaetoceros turingii sp. nov. (Bacillariophyceae): morphological and molecular description of a new species from the Gulf of Naples, Italy

In the present study we describe and illustrate a new species in the genus Chaetoceros, C. turingii sp. nov., from the Gulf of Naples, Italy. Colonies have a brush-like appearance due to the apparent randomness in seta orientation. The defi ning feature of this species is the regular pattern of narrow ridges on the exterior of the terminal valve face, which is visible in electron microscopy. In addition, a petallike collar is present at the base of each intercalary seta. Its nuclear-encoded 18S rDNA and partial 28S rDNA sequences were resolved in a clade with C. anastomosans, C. dayaensis, C. cf. vixvisibilis as well as with three other Chaetoceros species still in need of description. The new species is compared with morphologically similar species, and their diff erences are discussed.
Multi-domain and Explainable Prediction of Changes in Web Vocabularies

Web vocabularies (WV) have become a fundamental tool for structuring Web data: over 10 million sites use structured data formats and ontologies to markup content. Maintaining these vocabularies and keeping up with their changes are manual tasks with very limited automated support, impacting both publishers and users. Existing work shows that machine learning can be used to reliably predict vocabulary changes, but on specific domains (e.g. biomedicine) and with limited explanations on the impact of changes (e.g. their type, frequency, etc.). In this paper, we describe a framework that uses various supervised learning models to learn and predict changes in versioned vocabularies, independent of their domain. Using well-established results in ontology evolution we extract domain-agnostic and human-interpretable features and explain their influence on change predictability. Applying our method on 139 WV from 9 different domains, we find that ontology structural and instance data, the number of versions, and the release frequency highly correlate with predictability of change. These results can pave the way towards integrating predictive models into knowledge engineering practices and methods.
IMPACTS OF FINANCIAL EDUCATION ON THE REDUCTION OF ECONOMIC VULNERABILITY OF LOW INCOME ELDERLY IMPACTOS DA EDUCAÇÃO FINANCEIRA NA REDUÇÃO DA VULNERABILIDADE ECONÔMICA DE IDOSOS DE BAIXA RENDA

This paper reports the implementation and evaluation of the financial education program for adults "I and my retirement organizing the financial life" and its effects on the reduction of the economic vulnerability of low income elderly in Palmas TO. The evaluation method used was the Propensity Score Matching with Differences in Differences econometric model considering the effects of the program on the financial health of the elderly. The results pointed to the positive effect of the program in all dimensions surveyed: monthly income spent on food, health, housing, water and electricity; savings (72%); ability to make financial decisions (14%); debt knowledge (30%) and reduction of overdue accounts after intervention (50%).
21.2: A Low‐Voltage P‐type Poly‐Si Integrated Driving Circuits for Active Matrix Display

A low power poly‐Si gate and data driver circuits employing p‐type low temperature poly‐Si (LTPS) TFTs are proposed and verified by simulation and measurement. We have designed a 5V driven p‐type level‐shifter and it achieves a wide range output of ∼8∼10V. A new p‐type latch employing complementary clock compensation is proposed and the latch stores the low voltage (5V) data bits (D and D') without an output voltage loss. A simple and new source‐follower type poly‐Si analog buffer with fast charging is also designed and measured. P‐type poly‐Si fully integrated circuits on glass substrates may provide cost benefits and improve panel reliability.
Collapsed Form Simulation of Styles of Different Structures under Earthquake Based on ANSYS/LS-DYNA

In this paper, different types of steel frame structure under earthquake are adopted as the analyzed object of structural collapse. Seismic waves can be applyed into the structure in form of dynamic acceleration in ANSYS/LS-DYNA. The whole process of earthquake effects on the structure is simulated truly. It is helpful to realize and understand the failure mechanism and space mechanism of the different forms of steel frame structures. This paper can also provide a reference for reinforcement and maintenance of structure and a basis of anti-seism design of structure.
PWM control using a modified triangular signal

The proposed analog-based modified PWM control scheme for the DC-AC inverter can eliminate the low order harmonic components caused by the nonconstant DC voltage source. A simple high-power factor full-bridge rectifier with the valley-fill filter is selected to realize the nonconstant DC voltage source. The development of a modified triangular signal for the PWM control is introduced in this paper. The performance of the proposed modified PWM control scheme is verified by using computer simulation and experimental results.
Combined Effect of Three-Dimensional Contact Load and Thermal Gradients on the Cracking Performance of Heavy-Duty Asphalt Pavements

Top-down cracking is well recognized as a major distress for heavy-duty asphalt pavements, yet the mechanism is not fully understood. Studies have indicated that nonuniform tire–pavement contact stress may play a significant role in the initiation of top-down cracking, and thermal stress caused by the temperature gradient may contribute to the initiation and development of top-down cracking. These relevant factors were evaluated with a sophisticated three-dimensional viscoelastic finite element model that was developed for studying the cracking performance of heavy-duty flexible pavements under combined three-dimensional tire–pavement contact stress and thermal stress induced by the temperature gradient. It was found that the stress distribution in asphalt concrete layers continuously changed as the pavement was loaded because of the rheological behavior of the asphalt concrete. Significant maximum principal tensile stresses are present at the tire edge at the asphalt concrete surface, which may result in an accumulation of dissipated creep strain energy over time (or with a cumulative number of loads) and may eventually lead to crack initiation. Additionally, near-surface pavement responses associated with top-down cracking under three-dimensional tire–pavement contact pressure are found to be more severe than those from uniform contact pressure. In a comparison with pavements without thermal effect, the negative temperature gradient increases the potential for top-down cracking, and the positive temperature gradient increases the potential for bottom-up cracking. The study provides insight into crack mechanisms, which may improve current heavy-duty asphalt pavement design procedures.
A Machine Learning approach to enhance indoor thermal comfort in a changing climate

This paper presents an alternative workflow for thermal comfort prediction. By using the leverage of Data Science & AI in combination with the power of computational design, the proposed methodology exploits the extensive comfort data provided by the ASHRAE Global Thermal Comfort Database II to generate more customised comfort prediction models. These models consider additional, often significant input parameters like location and specific building characteristics. Results from an early case study indicate that such an approach has the potential for more accurate comfort predictions that eventually lead to more efficient and comfortable buildings.
CFD-based surrogate modelling of urban wind farms using artificial neural networks: double rotor arrangements

Extensive characterization studies are required to identify optimal wind farm layouts and achieve high power density, i.e., power per land area. Performing such studies using experimental or high-fidelity numerical methods can be timely and computationally expensive. To alleviate this obstacle, surrogate models can be developed to mimic the behavior of the simulation/experiment. In this paper, a shallow feed-forward artificial neural network (ANN) surrogate model is developed. The Levenberg-Marquardt algorithm is used to train a model with 3 layers and 10 hidden nodes. The model correlates the arrangement of a double-rotor vertical axis wind turbine array, as the fundamental generating cell of the wind farm, with its overall power performance. The inputs are the relative distance (R) and angle (®) between the rotors, and the output is the overall power coefficient of the array. In total, 96 CFD-simulated arrangements are used as data points to train, validate and test the model. The trained model has a mean square error of 2.10 × 10-5 and R-squared of 0.99, indicating its accuracy and generalizability. The average and maximum errors are 3% and 10%, respectively. The employed method can be expanded to accommodate more rotors towards optimal urban wind farm layout design.
Using Machine Learning to estimate the technical potential of shallow ground-source heat pumps with thermal interference

The increasing use of ground-source heat pumps (GSHPs) for heating and cooling of buildings raises questions regarding the technical potential of GSHPs and their impact on the temperature in the shallow subsurface. In this paper, we develop a method using Machine Learning to estimate the technical potential of shallow GSHPs, which enables such an estimation for Switzerland with limited data and computational resources. A training dataset is constructed based on meteorological and geological data across Switzerland. We analyse correlations and the importance of each of the input data for estimating the GSHP potential and compare different input feature sets and Machine Learning models. The Random Forest algorithm, trained on the full dataset, provides the best performance to estimate the GSHP potential. The resulting model yields an R2 score of 0.95 for the annual energy potential, 0.86 for the heat extraction rate, and 0.82 for the potential number of boreholes per GSHP system.
Parametric design of an additively manufactured building facade for bespoke response to solar radiation

The building construction industry is adapting Additive Manufacturing (AM) and robotic fabrication techniques to, among other efficiency and cost benefits, reduce the lifecycle Green House Gas (GHG) emissions of new buildings. This research aims to fabricate a low- GHG emission façade by encoding environmental performance using a combination of material selection, AM techniques, and bespoke geometry. This paper presents the design methodology, specifically the response to solar radiation (i.e. shading and daylight transmission). The key contribution of this publication is establishing the digital fabrication process of AM facades: beginning with performative parametric design, using empirical Bi-directional Scattering Distribution Function (BSDF) data of AM thermoplastic elements for daylight simulation to assess performance, and finally optimising the topology for a specific context (location and orientation).
Artificial Intelligence for Detecting Indoor Visual Discomfort from Facial Analysis of Building Occupants

Glare is a common local visual discomfort that is difficult to identify with conventional light sensors. This article presents an artificial intelligence algorithm that detects subjective local glare discomfort from the image analysis of the video footage of an office occupant’s face. The occupant’s face is directly used as a visual comfort sensor. Results show that it can recognize glare discomfort with around 90% accuracy. This algorithm can thus be at the basis of an efficient feedback control system to regulate shading devices in an office building.
Satellite imagery to select a sample of rooftops for a PV installation project in Jeddah, Saudi Arabia

A region-based convolutional neural network image segmentation approach (Mask R-CNN) was applied to identification of flat rooftops from satellite imagery in the city of Jeddah in Saudi Arabia. The model was trained on a small sample of rooftops (202) digitized from a 0.5 m resolution image (covering 0.21 km2) and then was applied to an independent area 4.5 km away. The precision and recall of the model were 0.98 and 0.96 respectively in terms of identifying rooftops in the independent area. A spatially stratified sample of rooftops was drawn from those identified by the model and the median roof area of the sample was not significantly different from the area as a whole. The results, although at a small scale, demonstrate the effectiveness of this approach for selecting buildings with appropriate rooftops for solar photovoltaic (PV) installation, in the context of closely spaced flat-roofed buildings, without requiring cadastral mapping or LIDAR datasets.
Pinpointing suitable 'direct service' volunteers

Volunteering managers are challenged with finding individuals who are interested in performing a broad range of volunteering roles, which could include for example, board members, accountants and gardeners. This study extends the work of Heidrich (1990) by demonstrating that by splitting the segment of “direct service” volunteers into specific functions, groups of individuals with distinct lifestyle characteristics can be identified. Theoretically, the implication is that considering volunteering as a generic entity is of limited use, and that heterogeneity of volunteering functions must be accounted for. Practically, the contribution lies in providing insight to volunteer managers about to the importance of developing customised marketing campaigns to attract volunteers for specific functions, the interests of whom match the volunteering organisation’s recruitment needs. Publication Details Randle, M. J. & Dolnicar, S. (2008). Pinpointing suitable 'direct service' volunteers. In D. Spanjaard, S. Denize & N. Sharma (Eds.), Australian and New Zealand Marketing Academy Conference (pp. 1-6). Sydney: Australian & New Zealand Marketing Academy. This conference paper is available at Research Online: http://ro.uow. edu.au/commpapers/715 Pinpointing Suitable “Direct Service” Volunteers Melanie Randle and Sara Dolnicar, University of Wollongong
A Predictive Rolling Contact Fatigue Crack Growth Model: Onset of Branching, Direction, and Growth—Role of Dry and Lubricated Conditions on Crack Patterns

Complex crack networks are initiated in rails under Rolling Contact Fatigue. This paper attempts to model the RCF crack propagation with a particular emphasis on the branching conditions and the parameters that play a role on them. The numerical tool proposed rests on the combination of the author’s RCF model, Hourlier and Pineau’s criterion for the branch prediction and experimental data and the corresponding models for fatigue crack extension that are derived from a Joint European project. Parametric studies on the influence of (i) residual stresses, (ii) both interfacial crack and wheel/rail contact frictional effects, (iii) neighboring crack are conducted to reach a better understanding of the RC crack propagation behavior and more particularly the branch conditions, i.e., the length of the primary crack prior to branch formation and the branch direction.
Local scalable description of global characteristics of various on-chip asymmetrically octagonal inductors

We present a parametric investigation of various groups of on-chip asymmetrically octagonal inductors on silicon substrates. The inductors have different numbers of turns, strip widths, spacings, outer dimensions, and inner radii. Using two-port S parameters measured by a deembedding technique, we derive some local scalable formulas for extrapolating Q factor, resonance frequency, inductance, overlapping, and oxide capacitances of these octagonal inductors with different geometries. The effects of all geometric parameters on Q factor and so forth are explored, analyzed, and compared with each other in detail.