Miracle-dz/UniFAR-FTUs huggingface dataset:
LASER DIODE DISTANCE MEASURING INTERFEROMETER - METROLOGICAL PROPERTIES

A novel laser diode based length measuring interferometer for scientific and industrial metrology is presented. Wavelength the stabilization system applied in the interferometer is based on the optical wedge interferometer. Main components of the interferometer such as: laser diode stabilization assembly, photodetection system, measuring software, air parameters compensator and base optical assemblies are described. Metrological properties of the device such as resolution, measuring range, repeatability and accuracy are characterized.
Prevention of Alveolar Osteitis following Third Molar Surgery

Alveolar osteitis (AO) is one of the most common complications after third molar surgery. Various risk factors has been determined as the etiology of AO. In addition, different preventive measures with promising outcome have been provided by researchers. The aim of the present review is to provide the most recent preventive measures to reduce the risk of developing AO following third molar surgery.
Making Virtue Out of Necessity: Managing the Citrus Waste Supply Chain for Bioeconomy Applications

The efficient use of agricultural wastes and by-products, which essentially transforms waste materials into value-added products, is considered as pivotal for an effective bioeconomy strategy for the rural development. Within this scope, citrus waste management represents a major issue for citrus processors. However, it also represents a potentially unexploited resource for rural sustainable development. This study focuses on analyzing the current management of citrus waste in South Italy, and on identifying the determinants and barriers that may affect an entrepreneur’s choice in the destination of citrus waste. This study investigates the preferences of citrus processors regarding the contract characteristics necessary to take part in a co-investment scheme. Both analyses are preliminary steps in designing an innovative and sustainable citrus by-product supply chain. Results show that the distance between the citrus processors and the citrus by-products plant is one of the main criteria for choosing alternative valorization pathways. Moreover, guaranteed capital, a short duration of the contract, and reduced risk are contract scheme characteristics that improve entrepreneurs’ willingness to co-invest in the development of a citrus waste multifunctional plant. The overall applied approach can be extended to other contexts for designing new and innovative by-product supply chains, thereby enhancing the implementation of bioeconomy strategies.
Understanding the connections between intimate partner domestic violence and mental health within the European context : implications for innovative practice

This material has been published in Dailogue in Praxis: A Social Work International Journal, by the Interuniversity Centre, Dubrovnik, Croatia. Content in the UH Research Archive is made available for personal research, educational, and non-commercial purposes only. Unless otherwise stated, all content is protected by copyright, and in the absence of an open license, permissions for further re-use should be sought from the publisher, the author, or other copyright holder.
Bias corrections of GOSAT SWIR XCO2 and XCH4 with TCCON data and their evaluation using aircraft measurement data

Abstract. We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.
Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence‐only data for 50 species in five different regions, to test whether: (1) a 10‐fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.
Order of Entry and Performance of Multinational Corporations in an Emerging Market: A Contingent Resource Perspective

Drawing on the resource-based view, this study examines the contingency effects of industry- and firm-level variables on the first-mover advantages and effective follower strategies in an emerging-market context. Using hierarchical regressions, the authors analyze a large data set of foreign investors in China. Contingency models that include the interactions of entry order with the moderating variables have better fit of the data than the main-effect models. Industry growth and competition, firm size, entry mode, resource commitment, and marketing intensity have significant moderating effects on first-mover advantages. After the authors correct for multicollinearity bias using ridge regression, it seems that pioneers still enjoy a small advantage in market share but not in profitability, indicating a trade-off between the two. Furthermore, followers may augment performance by increasing resource commitment and marketing intensity. These findings have significant implications for entry-order strategies and for improving foreign direct investment performance in foreign markets; they also suggest meaningful directions for further research.
Matter wave transport and Anderson localization in anisotropic three-dimensional disorder

We study quantum transport of matter waves in anisotropic three-dimensional disorder. First, we show that structured correlations can induce rich effects, such as anisotropic suppression of the white-noise limit and inversion of the transport anisotropy. Second, we show that the localization threshold (mobility edge) is strongly affected by a disorder-induced shift of the energy states, which we calculate. Our work is directly relevant to ultracold-matter waves in optical disorder, and implications on recent experiments are discussed. It also offers scope for further studies of anisotropy effects in other systems with controlled disorder, where counterparts of the discussed effects can be expected.
GMAP: A Generic Methodology for Agile Product Line Engineering

Agile Product Line Engineering (APLE) is a relatively novel approach that has emerged as the result of the combination of two successful software development approaches: Software Product Line Engineering and Agile Software Development. The main goal of this combined approach is to cover the weaknesses of each of these two approaches while maximizing the advantages of both. We propose the Generic Methodology for Agile Product Line Engineering (GMAP), which can be instantiated to produce a bespoke, concrete methodology for any specific project situation. GMAP is generic in that its process covers the main activities of existing APLE methodologies, while refraining from enforcing any specific and concrete method or technique for performing the activities. GMAP has been produced by studying existing APLE methodologies, identifying their strengths and weaknesses, abstracting them into a high-level framework, and finally instantiating this abstract framework so as to address the shortcomings of existing methodologies. Keywords—Software Development Methodology; Software Product Line; Agile Method; Agile Product Line Engineering.
Chemodiversity of a Scots pine stand and implications for terpene air concentrations

Abstract. Atmospheric chemistry in background areas is strongly influenced by natural vegetation. Coniferous forests are known to produce large quantities of volatile vapors, especially terpenes. These compounds are reactive in the atmosphere, and contribute to the formation and growth of atmospheric new particles. Our aim was to analyze the variability of mono- and sesquiterpene emissions between Scots pine trees, in order to clarify the potential errors caused by using emission data obtained from only a few trees in atmospheric chemistry models. We also aimed at testing if stand history and seed origin has an influence on the chemotypic diversity. The inherited, chemotypic variability in mono- and sesquiterpene emission was studied in a seemingly homogeneous 48 yr-old stand in Southern Finland, where two areas differing in their stand regeneration history could be distinguished. Sampling was conducted in August 2009. Terpene concentrations in the air had been measured at the same site for seven years prior to branch sampling for chemotypes. Two main compounds, α-pinene and Δ3-carene formed together 40–97% of the monoterpene proportions in both the branch emissions and in the air concentrations. The data showed a bimodal distribution in emission composition, in particular in Δ3-carene emission within the studied population. 10% of the trees emitted mainly α-pinene and no Δ3-carene at all, whereas 20% of the trees where characterized as high Δ3-carene emitters (Δ3-carene forming >80% of total emitted monoterpene spectrum). An intermediate group of trees emitted equal amounts of both α-pinene and Δ3-carene. The emission pattern of trees at the area established using seeding as the artificial regeneration method differed from the naturally regenerated or planted trees, being mainly high Δ3-carene emitters. Some differences were also seen in e.g. camphene and limonene emissions between chemotypes, but sesquiterpene emissions did not differ significantly between trees. The atmospheric concentrations at the site were found to reflect the species and/or chemodiversity rather than the emissions measured from any single tree, and were strongly dominated by α-pinene. We also tested the effect of chemodiversity on modeled monoterpene concentrations at the site and found out that since it significantly influences the distributions and hence the chemical reactions in the atmosphere, it should be taken into account in atmospheric modeling.
Non-intrusive model reduction of static parametric non-linear systems and application to global optimization and uncertainty quantification

A methodology for non-intrusive parametric model reduction is presented as an extension of the basic method introduced by Renganathan et. al. (2018). Specifically, we extend the method for static systems with parametric geometry (that deforms the mesh), in addition to parametric boundary conditions. The main idea is to first perform a transformation on the governing equations such that it is lifted to a higher dimensional but linear under-determined system. This enables one to extract the system matrices easily compared to that of the original non-linear system. The under-determined system is closed with a set of unique non-linear constraints upon which the model reduction is performed. The methodology is validated on the subsonic and transonic inviscid flow past the NACA0012 and the RAE2822 airfoils. We further demonstrate the utility of the approach by applying it to two common problems in the many-query context namely, gradient-free global optimization and parametric uncertainty quantification with Monte-Carlo sampling. Overall, the methodology is shown to achieve accuracy upto 5\% and computational speed-up of 2-3 orders of magnitude as that of the full-order model.
Measuring retirement savings adequacy: developing a multi-pillar approach in the Netherlands

The Dutch pension system is highly ranked on adequacy. These rankings, however, are based on fictitious replacement rates for median income earners. This paper investigates whether the Dutch pension adequacy is still high when we take into account the resources that people really accumulate, using a large administrative data set. A comprehensive approach is followed: not only public and private pension rights, but also private savings and housing wealth are taken into account. Summed over all age- and socioeconomic groups we find a median gross replacement rate of 83% and a net replacement rate of 101%. At retirement age, 31% of all households face a gross replacement rate that is lower than 70% of current income. Public and occupational pensions each account for more than 35% of total pension annuities. Private non-housing assets account for 14% and imputed rental income from net housing wealth accounts for about 10%. Some vulnerable groups, such as the self-employed, have below average replacement rates. Results are fairly similar to results found in the UK, indicating that we should be careful in evaluating the adequacy of pensions systems on the basis of fictitious replacement rates.
On Observing Contracts: Deontic Contracts Meet Smart Contracts

Smart contracts have been proposed as executable implementations enforcing real-life contracts. Unfortunately, the semantic gap between these allows for the smart contract to diverge from its intended deontic behaviour. In this paper we show how a deontic contract can be used for real-time monitoring of smart contracts specifically and request-based interactive systems in general, allowing for the identification of any violations. The deontic logic of actions we present takes into account the possibility of action failure (which we can observe in smart contracts), allowing us to consider novel monitorable semantics for deontic norms. For example, taking a rights-based view of permissions allows us to detect the violation of a permission when a permitted action is not allowed to succeed. A case study is presented showing this approach in action for Ethereum smart contracts.
Application of Recursive Least Squares to Efficient Blunder Detection in Linear Models

In many geodetic applications a large number of observations are being measured to estimate the unknown parameters. The unbiasedness property of the estimated paramete rs is only ensured if there is no bias (e.g. systematic effect) or falsifying observations, which are also known as outliers. One of the most important steps towards obtaining a coherent analysis for the parameter estimation is the detection and elimination of outliers, which may appear to be inconsistent with the remainder of the observations or the model. Outlier detection is thus a primary step in many geodetic applications. There are various methods in handling the outlying observations among which a sequential data snooping procedure, known as Detection, Identification and Adaptation (DIA) algorithm, is employed in the present contribution. An efficient data snooping procedure is based on the Baarda's theory in which blunders are detected element-wise and the model is adopted in an iterative manner. This method may become computationally expensive when there exists a large number of blunders in the observations. An attempt is made to optimize this commonly used method for outlier detection. The optimization is performed to improve the computational time and complexity of the conventional method. An equivalent formulation is thus presented in order to simplify the elimination of outliers from an estimation set-up in a linear model. The method becomes more efficient when there is a large number of model parameters involved in the inversion. In the conventional method this leads to a large normal matrix to be inverted in a consecutive manner. Based on the recursive least squares method, the normal matrix inversion is avoided in the presented algorithm. The accuracy and performance of the proposed formulation is validated based on the results of two real data sets. The application of this formulation has no numerical impact on the final result and it is identical to the conventional outlier elimination. The method is also tested in a simulation case to investigate the accuracy of the outlier detection method in critical cases when large amount of the data is contaminated. In the application considered, it is shown that the proposed algorithm is faster than the conventional method by at least a factor of 3. The method becomes faster when the number of observations and parameters increases.
Challenges in Magnetic Resonance Imaging and Vocal Tract Modeling

The development of two and three-dimensional magnetic resonance imaging (MRI) opened new options for a better understanding of speech production; in particular, for the articulation process, comparing with other imaging techniques, such as x-rays. Several MRI studies have been carried out considering different languages, but concerning European Portuguese the available information is far from being completely achieved. Recently, the knowledge gained with the application of deformable models in magnetic resonance images towards the automatic study of the vocal tract, has allowed an  Email: smr@estsp.ipp. pt / sandra.rua@eu.ipp. pt Sandra M. Rua Ventura, Maria João M. Vasconcelos et al. 2 enhanced identification and description of the articulatory mechanism and its organs. Our aim is to extract and evaluate the main characteristics of the movements of vocal tract during European Portuguese speech production to achieve speaker-specific articulatory assessment from MRI. For this, we used active shape and active appearance models to identify, i.e. to segment, and simulate the vocal tract’s shape in MR images and concluded that both are suitable for such tasks being the later more proficient. The findings obtained are believed to be useful for speech rehabilitation and simulation purposes, namely to recognize and simulate the compensatory movements of the articulators during speech production. Therefore, this chapter gains particular interest within the communities of speech study and rehabilitation, medical imaging and bioengineering. It is organized as follows: the introduction section starts with a literature review concerning the use, application and challenges of MRI in speech production study, in particular for speech articulation. In addition, image analysis techniques based on deformable templates, more specifically by using geometrical shapes driven by parameterized functions, are introduced. In the second section, the adopted methodology of MRI acquisition and data assessment are described. Based on this image analysis approach, in the results section the key aspects of articulatory movements during the production of relevant European Portuguese speech sounds are addressed. In the final section of this chapter, conclusions are presented and further suggestions for future work are indicated.
Effect of Fumaric Acid on Methane Production, Rumen Fermentation and Digestibility of Cattle Fed Roughage Alone

Four Holstein steers fed with Sorghum silage were used to examine the effect of fumaric acid supplementation (20g/kg. diet dry matter (DM)) on methane production, rumen fermentation, blood metabolism and feed digestibility. The protozoal population in the rumen was unaffected by fumaric acid supplementation. The postprandial ruminal concentration of ammonia-N decreased, and that of total volatile fatty acids tended to be higher with fumaric acid supplementation. The proportion of ruminal acetic acid was unaffected, but that of propionic acid increased and that of butyric acid decreased by fumaric acid. The postprandial blood plasma concentration of glucose was increased, whereas that of urea-N was decreased by fumaric acid. The plasma concentration of most of free amino acids was unaffected. Daily methane production decreased by 23.0% and carbon dioxide production decreased by 20.5% with fumaric acid supplementation. Apparent digestibility of dry matter and of neutral detergent fiber were not influenced by fumaric acid. These results indicated that fumaric acid was converted to propionic acid by rumen microorganisms, and that methane production from the rumen was reduced without lowering the ability to digest dietary fiber. However, some dietary conditions that alter the effectiveness of fumaric acid and the long term effect remain to be examined.
Wirkung von Fahrerassistenz auf der Führungsebene in Abhängigkeit der Modalität und des Automatisierungsgrades

Es wird auf Basis einer systemergonomischen Betrachtung der Fahraufgabe der Bedarf an Fahrerassistenz abgeleitet und anschliesend aufbauend auf Gesetzmasigkeiten aus der Ergonomie und der Automatisierungstechnik, eine Interaktionsmetapher zur Langs- und Querfuhrungsunterstutzung abgeleitet, bei der Fahrer und Assistenzsystem als kooperative Partner zusammenwirken. Diese wird in verschiedenen Auspragungen im Fahrsimulator umgesetzt und in mehreren Versuchsreihen zunachst partiell verfeinert und durch zwei abschliesende Experimente summativ evaluiert. Es zeigt sich ein sehr positiver Einfluss der Assistenz auf die Verkehrssicherheit und das Fahrerverhalten.