Miracle-dz/UniFAR-FTUs huggingface dataset:
Motivation to transfer learning to multiple contexts

To stay up-to-date in contemporary information intensive societies it is important to be able to effectively and efficiently find, evaluate, process and present required information. In educational contexts training in these so-called information literacy competences is mainly the domain of institutional libraries. Essential to education is the long-term transfer of learning, that is the application of newly acquired competencies also outside the training environment. Research learns that this often takes place sparsely, leading to what is called a Transfer Paradox. The aim of this study is to develop a practical instrument for instructional designers to measure the influence of a set of key variables on the learner's motivation to transfer learning to the wider educational and the work context. Two hundred and thirty-four students of the Open University of the Netherlands doing an information literacy course filled out a questionnaire before entering the course. Data was analyzed using factor analyses and hierarchical multiple regression analysis. Results show that the opportunity to apply new learning and sanctions from supervisors are two important factors that influence the learner's motivation to transfer learning in both the study and the work context already before the course has started.
An Approximate Model for Predicting the Specific Yield Under Periodic Water Table Oscillations

Predicting specific yield for a given aquifer remains a great challenge due to its dynamic characteristics, especially under periodic (e.g., seasonal and diurnal) groundwater level fluctuations. In this study, a dimensionless period of groundwater level fluctuations, which depends on the saturated hydraulic conductivity, the length of the groundwater level fluctuation period, and the soil water retention properties, is first introduced. Then, the relationship between the predicted specific yield and the dimensionless period of groundwater level fluctuations is defined based on the theory of variably saturated flow. The proposed approximate formula is tested by series of simulations of variably saturated flow within homogeneous and isotropic porous media with the Hydrus‐1D program. The results of numerical experiments demonstrate an invariant relationship between the predicted specific yield and the dimensionless period for a wide range of changes in the dimensionless period of groundwater level oscillations. Furthermore, the sensitivity analysis of the dependence of the predicted specific yield on the van Genuchten parameters indicates the applicability of estimating the specific yield via van Genuchten parameters, which can be predicted by the soil texture classes for a given length of the oscillation period and a known saturated hydraulic conductivity in the zone of groundwater level fluctuations. The proposed model can be used for predicting the dynamics of the specific yield under seasonal or diurnal groundwater level fluctuations.
Robot hand and robot

The invention relates to a robot hand and a robot. A robot hand and a robot according to an embodiment include supporting units. The supporting units are arranged on a base and contact the peripheral border of a board to grip the board. At least one of the supporting units rotates while abutting on the peripheral border of the board.
Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach

The deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), though algorithms typically have limited transferability in space and time due to variability in water constituent compositions, mixtures, and inherent optical properties. This study used in situ spectral reflectances and their first derivatives to compare empirical algorithms for estimating TSS using hyperspectral and multispectral data. These algorithms were applied to imagery collected by NASA’s Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over coastal Louisiana, USA, and validated with a multiyear in situ dataset. The best performing models were then applied to independent spectroscopic data collected in the Peace–Athabasca Delta, Canada, and the San Francisco Bay–Delta Estuary, USA, to assess their robustness and transferability. A derivative-based partial least squares regression (PLSR) model applied to simulated AVIRIS-NG data showed the most accurate TSS retrievals (R2 = 0.83) in these contrasting deltaic environments. These results highlight the potential for a more broadly applicable generalized algorithm employing imaging spectroscopy for estimating suspended solids.
Pan-European data sets of coastal flood probability of occurrence under present and future climate

GIS-compatible files containing data related to the probablity of coastal floods occurring in Europe under present and future climate. Includes gridded (GeoTIFF) datasets of coastal flood extents (in two variants, with or without flood protection) and water depths. Additionally includes extreme water level and storm surge heights estimates in ESRI Shapefile format. Based upon SMHI-RCA4-EC-EARTH regional climate simulation (EURO-CORDEX)
A Novel Automated Wind Chiller Hybrid Cooling System for a Cold Storage Room Application

This paper presents a novel automated wind chiller hybrid cooling system applied to a cold storage room. The objective of the new hybrid system is to utilize less electricity from the grid by using a wind chiller setup. The dimensions and cooling load of a typical cold storage room was defined based on the requirements of the Philippine environment. Various cold storage parameters were listed and calculated to fully define the typical cold storage room. An automation system was designed using ladder logic programming to identify the usage of the wind chiller in hybrid with a conventional electric cooling system. The rotational speed of the wind chiller was the primary parameter in accessing the usage of the wind chiller or the electrical cooling system. The automation included lubrication to ensure optimal wind chiller rotation. Equipment for automation implementation were suggested in the study. Simulations showed that the proposed program can control the utilization of wind chiller or the electrical cooling system for optimal performance. Results show that a potential savings of USD 4,860 can be achieved in a year. 
Exploiting multi-level deep features via joint sparse representation with application to SAR target recognition

ABSTRACT In order to improve synthetic aperture radar (SAR) target recognition performance, this paper proposes a novel method using multi-level deep features. The multi-level deep features are learned by the convolutional neural network (CNN), which are capable of describing the target characteristics from different aspects. In order to make full use of the discrimination contained in the multi-level deep features, the joint sparse representation (JSR) is used as the basic classifier, which performs the multi-task learning to jointly classify the multi-level deep features. It could not only represent each feature properly but also consider the correlations between different levels of features. Based on the solutions from JSR, the target label is classified as the training class with the minimum reconstruction error. By fully exploiting the discriminative information contained in the multi-level deep features, the proposed method could effectively enhance SAR target recognition performance. The moving and stationary target acquisition and recognition (MSTAR) dataset is employed in the experiments. The results show that the proposed method could achieve a significantly high recognition rate of 99.38% for classifying 10 classes of targets under the standard operating condition (SOC), which is higher than those from some reference methods drawn from current literatures. Under different types of extended operating conditions (EOCs), the overall performance of the proposed method keeps superior over the reference methods. In addition, the outlier rejection capability of the proposed method is also better than the compared methods. All these experimental results validate the high effectiveness of the proposed method.
Drought‐Net rainfall shelters did not cause nondrought effects on photosynthesis for California central coast plants

Rainfall interception shelters are frequently used to study the ecological consequences of drought. One common shelter design employs V‐shaped plastic troughs spaced on a supporting frame to intercept rainfall. Shading, reflection, and infrared radiation may alter the radiative environment under shelters in ways independent of their intended effect on soil moisture. We measured microclimate and several photosynthetic variables for watered, potted plants under rain‐out shelters and in open‐air, unsheltered plots. We tested whether the shelter infrastructure altered aboveground micrometeorology and photosynthesis for watered, potted plants of native Californian species: Elymus glaucus, Eriogonum latifolium, Mimulus aurantiacus, and Morella californica. We quantified the effects on photosynthesis in terms of light harvesting by photosystem II (PSII) and leaf‐level gas exchange on open‐air and shelter plots, the quantum yield of PSII for darkened leaves, dark respiration, and nocturnal stomatal conductance. The rain‐out shelter reduced daily integrated photosynthetically active radiation by 20%. Air temperature, leaf temperature, and leaf‐to‐air vapour pressure difference were not different under shelters compared with controls during the day. Likewise, there were no effects of shelters on net CO2 assimilation, stomatal conductance to water vapour (gs), internal leaf (CO2), or electron transport rate through PSII during the daytime. At night, Tair was 0.6°C higher under shelters, but there were no effects on dark respiration or stomatal conductance. Despite some differences in micrometeorology under rain‐out shelters compared with open‐air plots, there were little or no aboveground nondrought effects of the shelters on leaf‐level photosynthesis for watered, potted plants of these California native plant species.
Instant Uml

From the Publisher: UML is the Unified Modeling Language, produced in response to the call for a standard notation for the OO application design. UML is a synthesis of Booch, OMT, and OOSE methods. This book is an introduction to the object modeling approach as well as a tutorial in the UML notation and usage. The focus is object oriented modeling: user requirements, analysis, and definition.
Improving Energy Efficiency of Android Devices by Preventing Redundant Frame Generation

Managing the power consumption of display-related components in mobile devices is difficult because of performance degradation. Therefore, eliminating hidden workloads, such as redundant frames, is preferable, as it directly reduces power without affecting the user experience. Our preliminary study shows that the default launcher of the Android Open Source Project (AOSP) and popular applications, such as Instagram and Pinterest, generate redundant frames. In this paper, we propose a scheme to optimize the power consumption of the smartphone's display-related components by preventing redundant frames generation. By analyzing the frame-generation process, we observe that redundant frame generation is possible in the current Android framework. We then propose a scheme that recognizes and prevents redundant frame generation before actual frame generation (i.e., frame rendering in the GPU). The proposed scheme utilizes a display list, which was introduced in recent Android smartphones for efficient frame generation. We implemented the proposed scheme on Nexus smartphones. On the Nexus 5, the proposed solution reduced the energy of the AOSP default launcher, Instagram, and Pinterest by 40, 35.4, and 39.6 percent, respectively. Furthermore, the experimental results with a general usage scenario showed that our scheme prevented about 35 percent of redundant frame generation with a false-positive rate of 1.8 percent.
User-Adaptive A Posteriori Restoration for Incorrectly Segmented Utterances in Spoken Dialogue Systems

Ideally, the users of spoken dialogue systems should be able to speak at their own tempo. Thus, the systems needs to interpret utterances from various users correctly, even when the utterances contain pauses. In response to this issue, we propose an approach based on a posteriori restoration for incorrectly segmented utterances. A crucial part of this approach is to determine whether restoration is required. We use a classiﬁcation-based approach, adapted to each user. We focus on each user’s dialogue tempo, which can be obtained during the dialogue, and determine the correlation between each user’s tempo and the appropriate thresholds for classiﬁcation. A linear regression function used to convert the tempos into thresholds is also derived. Experimental results show that the proposed user adaptation approach applied to two restoration classiﬁcation methods, thresholding and decision trees, improves classiﬁcation accuracies by 3.0% and 7.4%, respectively, in cross validation.
Electromagnetic articulography (EMA) for real-time feedback application: computational techniques

Abstract The application of state-of-the-art signal processing often differs between offline and online real-time application domains. Offline processing techniques may be used to accurately reduce signal noise and spot errors before analysis. However, without the global signal information available to offline processes, such techniques can be difficult to reproduce in online real-time applications. This paper presented methods that were developed to support a state-of-the-art computer-based speech therapy system. These methods included online head correction and low-pass filtering and aimed to reproduce offline processing data quality when using a real-time clinical feedback application. The adequacy of these methods was evaluated relative to the offline processing ‘gold’ standard and in a context of computing a specific kinematic parameter (i.e. articulatory working space). The results showed that the online real-time output values were highly correlated with the offline manually-processed values.
Detection of a Climate Change Signal in Extreme Heat, Heat Stress, and Cold in Europe From Observations

In the last two decades Europe experienced a series of high‐impact heat extremes. We here assess observed trends in temperature extremes at ECA&D stations in Europe. We demonstrate that on average across Europe the number of days with extreme heat and heat stress has more than tripled and hot extremes have warmed by 2.3 °C from 1950–2018. Over Central Europe, the warming exceeds the corresponding summer mean warming by 50%. Days with extreme cold temperatures have decreased by a factor of 2–3 and warmed by more than 3 °C, regionally substantially more than winter mean temperatures. Cold and hot extremes have warmed at about 94% of stations, a climate change signal that cannot be explained by internal variability. The clearest climate change signal can be detected in maximum heat stress. EURO‐CORDEX RCMs broadly capture observed trends but the majority underestimates the warming of hot extremes and overestimates the warming of cold extremes.
Biogenic New Particle Formation: Field Observations and Chamber Experiments

New particle formation (NPF) is an atmospheric phenomenon, observed in many environments globally, and it contributes to a major fraction of the global aerosol number budget thereby affecting both climate and human health. In this thesis, we investigate the mechanisms behind NPF in the boreal forest environment and analyze the long-term behavior of the variables associated with the occurrence of this phenomenon. In order to improve the classification of atmospheric NPF events, especially when considering the increasing number of measurement campaigns and stations, we developed an automatic framework to classify NPF events based on the 2–4 nm ion and 7–25 nm aerosol particle concentrations in the atmosphere. This approach categorizes days into four defined classes: Regional NPF events, transported NPF events, ion bursts and non-events. For regional NPF events, the approach additionally determined the precise period (start and end-time) during which the event occurred. We show that, in the boreal forest, NPF events tend to occur under clear sky conditions with low condensation sinks and moderate temperatures. Using chamber simulations, we further investigated the mechanisms of new particle formation and growth in the boreal forest environment. While sulfuric acid is known to be the driver of NPF, we found that pure biogenic NPF is possible in the absence of sulfuric acid, and that the nucleation is mediated by dimers of highly oxygenated monoterpene oxidation products. We also found that anthropogenic vapors, such as NOx, attenuate the particle formation and growth by modifying the chemical composition of highly oxygenated molecules (HOMs) necessary for nucleation and growth. In the present-day-time atmosphere, we found that highly oxygenated molecules (HOMs) govern ioninduced new particle formation in the boreal forest when the ratio of biogenic HOMs to H2SO4 is greater than 30. Our results show that non-nitrate HOM dimers mediate ion-induced nucleation not only during daytime but also during night-time. In the absence of H2SO4, we observed pure biogenic ion-induced clustering mediated by non-nitrate HOM dimers and trimers; however, these clusters did not grow past 6 nm due to insufficient photochemistry needed for producing condensable vapors that would ensure cluster survival.
Biodiesel Production from Mutton Waste Fat – A Short Review

Article history: Received 27 April 2019 Accepted 21 May 2019 Available online 15 July 2019 Currently, the world is facing an immense threat from pollution and global warming. Fossil fuels are limited, and they are considered as non-renewable source of energy. Crude oil reserves are consumed at large scale with respective passing year. If the consumption rate is increased, it may cause ruination and irreplaceable damage to the environment. It now poses a great threat to mankind and to our planet earth. Renewable source of energy is revolutionary in this modern era. Biofuels are one of the most promising alternatives to conventional sources of fuel. Biodiesel is an eco-friendly, non-toxic green fuel that reduces the use of fossil fuel and helps combat climate change. Biodiesel can be produced through transesterification of waste animal fats into fatty acid methyl esters. India is the second largest producer of goat-based meat in the world. Currently, there is so much of waste fat being generated from meat processing plants and dumped in open grounds. It is hazardous waste and causes environmental pollution. The process of converting waste fat to biodiesel will reduce the dumping of waste fat. It can act as a major technique in fighting menace of pollution and helps in better waste management.
Subseismic to Seismic Slip in Smectite Clay Nanofoliation

Smectite clays are the main constituent of slipping zones found in subduction zone faults at shallow depth (e.g., <1‐km depth in the Japan Trench) and in the decollements of large landslides (e.g., 1963 landslide, Vajont, Italy). Therefore, deformation processes in smectite clays may control the mechanical behavior from slow creep to fast accelerations and slip during earthquakes and landslides. Here, we use (1) laboratory experiments to investigate the mechanical behavior of partly water‐saturated smectite‐rich gouges sheared from subseismic to seismic slip rates V and (2) nanoscale microscopy to study the gouge fabric. At all slip rates, deformation localizes in volumes of the gouge layer that contain a “nanofoliation” consisting of anastomosing smectite crystals. “Seismic” nanofoliations produced at V = 0.01, 0.1, and 1.3 m/s are similar to “subseismic” nanofoliations obtained at V = 10−5 m/s. This similarity suggests that frictional slip along water‐lubricated smectite grain boundaries and basal planes may occur from subseismic to seismic slip rates in natural smectite‐rich faults. Thus, if water is available along smectite grain boundaries and basal planes, nanofoliations can develop from slow to fast slip rates. Still, when nanofoliations are found highly localized in a volume, they can be diagnostic of slip that occurred at rates equal or larger than 0.01 m/s. In such a case, they could be markers of past seismic events when found in natural fault rocks.
Vulnerability of a Northeast Mediterranean Island to Soil Loss. Can Grazing Management Mitigate Erosion?

Grazing management practices can be erosion abatement actions for lowering soil loss and the subsequent sediment pollution of surface water bodies. Process-based Geographic Information Systems models provide the opportunity to identify critical areas and hence better target such actions across the landscape. This study implemented the SWAT (Soil Water Assessment Tool) hydrologic and catchment management model to estimate the soil loss vulnerability of the nearly pristine but highly erodible Greek island of Samothraki in the North Aegean Sea, with a typical Mediterranean climate and steep topography. Model parameterization and evaluation were carried out by taking advantage of previous modeling experience on areas with data limitations. Inter-annual and intra-annual soil loss variability and the most critical areas (subbasins) of soil loss to waters were adequately identified and grazing management scenarios, including livestock reductions by 50% and 100%, grazing period reduction, and a combination of them, were formulated and applied to investigate the degree to which soil loss could be reduced. The annual reduction results varied between scenarios in the range of 10% to 25% for the entire island, and in wider ranges for its individual subbasins, showing a high potential for reducing the vulnerability of the most pressured ones. However, due to the high importance of the natural factors of rainfall and land slopes, the erosion vulnerability of the island overall could be significantly altered only if grazing management was integrated within a vegetation regeneration plan that included reforestation.
Bulk updates and cache sensitivity in search trees

OF DOCTORAL DISSERTATION HELSINKI UNIVERSITY OF TECHNOLOGY P.O. Box 1000, FI-02015 TKK http://www.tkk. fi/ Author Riku Saikkonen Name of the dissertation Bulk Updates and Cache Sensitivity in Search Trees Manuscript submitted 09.04. 2009 Manuscript revised 15.08. 2009 Date of the defence 04.09. 2009 £ Monograph ¤ Article dissertation (summary + original articles) Faculty Faculty of Information and Natural Sciences Department Department of Computer Science and Engineering Field of research Software Systems Opponent(s) Prof. Peter Widmayer Supervisor Prof. Eljas Soisalon-Soininen Instructor Prof. Eljas Soisalon-Soininen
Using a Simulation-Based Learning Environment for Teaching and Learning about Complexity in Public Policy Decision Making

Abstract Public leaders and managers today are being challenged by unprecedented, complex problems. Tackling “wicked problems” requires a new way of thinking, and new methods and tools for building models that realistically account for social and natural phenomena, gather and structure convincing evidence, and predict policy outcomes accurately. To prepare future and current public decision makers for a rapidly changing, complex world, we suggest a multidimensional framework of complexity in public policy settings that encompasses both analytic and socially constructed complexity, and introduce a simulation-based learning environment (SBLE) in which the power of traditional learning environments is augmented by a computer simulation model. In this study, we report on our experimental attempt to teach students in the MPA classroom about complexity by creating and implementing a SBLE with a U. S. Gulf Coast disaster preparedness case.