Miracle-dz/UniFAR-FTUs huggingface dataset:
The influence of operating loads on the state of stress and strain in selected load-bearing elements of a tower-type headgear structure / Wpływ obciążeń eksploatacyjnych na stan naprężenia oraz przemieszczenia wybranych elementów nośnych konstrukcji basztowej wieży szybowych

The headgear structure allows the conveyance to be moved over the shaft top to the loading (unloading) point, at the same time it keeps in place the rope pulleys while tower-type headgear structures also accommodate the entire winder installations. The headgear is where the final stage of the hoisting installation is located and where the surface transport systems begin. These aspects strongly impact the actual shape of the tower, its height and in some cases determine the design of the entire winding gear. In order that all the headgear functions should be provided, it is required that the ultimate state conditions should be maintained throughout its entire service life. In order to assess the critical service conditions, the computation procedure should be applied based on design loads and fatigue endurance parameters. The computations of characteristic loads acting on the headgear structure use the developed model of the system based on the dynamic analysis carried out for a specific case: a hoisting installation operated in one of the underground collieries inPoland. The maximal and minimal loads acting on a Koepe pulley and those required for the system operation are determined accordingly. The laws of dynamics provide a background for finding the forces and moments of forces acting in the components of the driving system (including the electric motors and pulley blocks) for the specified loading of the Koepe pulley. Underlying the numerical FEM model of the tower-type headgear structure are the technical specifications of the analysed object and FEM calculations followed by endurance analysis to find the state of stress in structural elements of the headgear under the typical service conditions. The results help in assessing how the design of the hoisting installation should impact on safety features of load-bearing elements in the headgear structure.
Why Do Countries Adopt Constitutional Review?

In recent decades, there has been a wide-ranging global movement towards constitutional review. This development poses important puzzles of political economy: Why would self-interested governments willingly constrain themselves by constitutional means? What explains the global shift toward judicial supremacy? Though different theories have been proposed, none have been systematically tested against each other using quantitative empirical methods. In this article, we utilize a unique new dataset on constitutional review for 204 countries for the period 1781–2011 to test various theories that explain the adoption of constitutional review. Using a fixed-effects spatial lag model, we find substantial evidence that the adoption of constitutional review is driven by domestic electoral politics. By contrast, we find no general evidence that constitutional review adoption results from ideational factors, federalism, or international norm diffusion. (JEL: K00, K19, K49)
Best Predictor of Cloud Computing Usage among Various Constructs

Abstract This study aimed to analyse the determinants of Cloud computing adoption and use among high school learners. The research question that followed was; which is the best predictor of Cloud computing usage given a set of determinants? The study involved 116 respondents using simple random sampling. The results revealed that performance expectancy was the strongest predictor of the intention to adopt Cloud computing when compared to other constructs. There was a strong positive correlation of r = +0.989 between ‘the use of Internet for learning purposes in enhancing the effectiveness of learning’ and ‘being taught in their studies through Internet devices’. These findings suggest that Cloud computing adoption and application may be enhanced through educating teachers and learners on the potential benefits of this mode of communication in improving the accessibility and dissemination of scholarly content.
Comparison of Amplitude-Based and Phase-Based Methods for Speed Tracking in Application to Wind Turbines

Focus of the vibration expert community shifts more and more to wards diagnosing machines subjected to varying rotational speeds and loads. Such machines require order analysis for proper fault detection a nd identification. In many cases phase markers (tachometers, encoders, etc) are used to help performing t he resampl ing of the vibration signals to remove the speed fl uctuations and smearing from the spectrum (order tracking). However, not all machines have the facil ity to install speed tracking sensors, due to desig n or cost reasons, and the signal itself has to then b e used to extract this information. This paper is f ocused on the problem of speed tracking in wind turbines, which represent typical situations for speed and load variation. T he basic design of a wind turbine is presented. Two main typ es of speed control i . e. stall and pitch control are presented,. The authors have investigated two methods of speed tracking, using information from the signal (withou t relying on a speed signal). One method is based on extracti ng a reference signal to use as a tachometer, whi le the other is phase-based (phase demodulation). Both methods are presented and applied to the vibration data from real wind turbines. The results are compared with each o ther and with the actual speed data.
A Dynamic Weighted Method on Learning User Preference Profile

Recommender Systems usually store personal preference profiles, many items in the profiles can be represented by numerical attributes. However, the initial profile of each user is incomplete and imprecise. One important problem in the development of these systems is how to learn the user preferences, and how to update the profiles dynamically. This paper presents an approach to learn user preferences over numeric attributes by analyzing the interactions between users and RS. More specifically, there are two contributions in this paper: 1) a learning approach to measure the influence of over-ranked items through analysis of user feedbacks; 2) a weighing algorithm to calculate weight of different attributes by analyzing user selections. These two approaches are integrated into a traditional model for updating user preference profiles dynamically. Extensive simulations and results show that both approaches are more effective than existing approaches.
Development of a decision support tool: preliminary analysis to improve field data collection in Kathiraveli Village, Sri Lanka

This paper focuses specifically on the development of a water balance model that will support agricultural decision making for the irrigation field and water supply tanks. The study based on an irrigation system within Kathiraveli, an isolated war affected village in north-eastern Sri Lanka. The irrigation system is used to deliver water to approximately 100 farmers. Estimates or measurements of water availability at the start of the cultivation period are able to be combined with estimates of likely future inflows based on previous rainfall to determine optimum crop selection and crop area allocation. The model consists of three modules: a crop water requirement calculator, a water tank balance model, and a model which simulates the storage in the permanent wetland attached to the irrigation tank. Due to limited budgets and timeframes to obtain input data, a careful balance between accuracy, complexity and cost needed to be reached to ensure that the model can be accurate for its intended use. To do this the model was ran initially under baseline conditions. A sensitivity analysis was then performed to assess the importance of major variables; the outcomes of this study was used to prioritise the collection of field data.
Obstacle Filtering Algorithm for Control of an Autonomous Road Vehicle in Public Highway Traffic

This paper presents an obstacle filtering algorithm that mimics human driver-like grouping of objects within a model predictive control scheme for an autonomous road vehicle. In the algorithm, a time to collision criteria is first used as risk assessment indicator to filter the potentially dangerous obstacle object vehicles in the proximity of the autonomously controlled vehicle. Then, the filtered object vehicles with overlapping elliptical collision areas put into groups. A hyper elliptical boundary is regenerated to define an extended collision area for the group. To minimize conservatism, the parameters for the tightest hyper ellipse are determined by solving an optimization problem. By excluding undesired local minimums for the planning problem, the grouping alleviates limitations that arise from the limited prediction horizons used in the model predictive control. The computational details of the proposed algorithm as well as its performance are illustrated using simulations of an autonomously controlled vehicle in public highway traffic scenarios involving multiple other vehicles.
Numerical analysis of a turbulent flow in a channel provided with transversal waved baffles

This article presents a computational analysis of the turbulent flow of air in a pipe of rectangular section provided with two waved fins sequentially arranged in the top and the bottom of the channel wall. The governing equations, based on the k-e model with low Reynolds number used to describe the turbulence phenomena, are solved by the finite volume method. The velocity and pressure terms of momentum equations are solved by the SIMPLEC algorithm. The profiles of axial velocity, the velocity fields and the drag coefficient were obtained and presented for all the geometry considered and for selected sections, namely, upstream, downstream, and between two waved baffles. This contribution lead to results which were analyzed by the use of the solid, plane baffles, waved and inclined with active degrees of 0° up to 45° with a step equal to 15° and directed towards the left. Over the range of the study, the undulation of the baffles induced with an improvement on the skin friction of about 9.91% in the case of a = 15°, more than 16% in the other cases, and concerning the pressure loss, the undulation of the baffles was insured improvements starter from 10,43% in all cases compared with the baffles of plane form.
Structural analysis of thin film silicon PV modules by means of large area laser beam induced current measurements

The spatial variation of key properties of large area silicon thin film PV modules is investigated using a Laser Beam Induced Current (LBIC) system. The system produces a very detailed current mapping of devices, allowing the identification of spatially varying structural defects of photovoltaic modules. It allows for efficient defect detection as well as investigations of localised performance variation. In this paper, the results are shown for large area single junction amorphous silicon modules from different manufacturers that have been installed outdoors for more than two years. Several defects are identified as probable sources of poor performance and low efficiency of some devices. Some of the major contributions to these defects are likely to occur during the production process while some are developed during outdoor exposure.
Impact of Data Characteristics on Feature Selection Techniques Performance

Abstract Feature selection is a step in knowledge discovery in databases which takes away most of the time of the entire process. Therefore, the effective implementation of feature selection significantly improves the overall process. This paper suggests examining data characteristics before applying feature selection and hypothesize that data characteristics significantly affect feature selection techniques performance. Our experimental comparison of five previously used feature selection techniques reveals significant difference in feature selection techniques performance when dealing with data sets of different characteristics
Variation in cell volume and community composition of bacteria in response to temperature

Although temperature is a key parameter controlling the activity and growth of all microorganisms, information about how water temperature may structure the bacterioplankton community is not consistent. We examined the relationship between temperature and the community composition, cell volume, and morphology of marine bacterioplankton in 4 continuous cultures harbouring multispecies communities. All 4 cultures were maintained at a turnover time of 0.04 h(-1) but at different temperatures of 10, 15, 20, and 25 degrees C. Denaturing gradient gel electrophoresis analyses showed that the community composition shifted in response to temperature. Cell volumes were determined from digital photomicrographs using an image analysis program, which also allowed the identification of 3 morphological types of bacteria: cocci-, rod-, and vibrio-shaped bacteria. Mean bacterial cell volume decreased with increasing temperature, e.g., by 39% when the temperature was increased from 10 degrees C to 20 degrees C. When the temperature increased, the bacterial morphology also shifted from dominance by rod- and vibrio-shaped bacteria to dominance by coccoid bacteria. The results clearly indicate the potential role of temperature in driving the community succession of bacterioplankton and in selecting for smaller cells at higher temperatures.
Biodiversity for multifunctional grasslands: equal productivity in high-diversity low-input and low-diversity high-input systems

Abstract. Modern grassland management seeks to provide many ecosystem services and experimental studies in resource-poor grasslands have shown a positive relationship between plant species richness and a variety of ecosystem functions. Thus, increasing species richness might help to enhance multifunctionality in managed grasslands if the relationship between species richness and ecosystem functioning is equally valid in high-input grassland systems. We tested the relative effects of low-input to high-input management intensities and low to high plant species richness. Using a combination of mowing frequencies (1, 2 or 4 cuts per season) and fertilisation levels (0, 100 and 200 kg N ha−1 a−1), we studied the productivity of 78 experimental grassland communities of increasing plant species richness (1, 2, 4, 8 or 16 species with 1 to 4 functional groups) in two successive years. Our results showed that in both years higher diversity was more effective in increasing productivity than higher management intensity: the 16-species mixtures had a surplus of 449 g m−2 y−1 in 2006 and 492 g m−2 y−1 in 2007 over the monoculture yields whereas the high-input management resulted in only 315 g m−2 y−1 higher productivity in 2006 and 440 g m−2 y−1 in 2007 than the low-input management. In addition, high-diversity low-input grassland communities had similar productivity as low-diversity high-input communities. The slopes of the biodiversity – productivity relationships significantly increased with increasing levels of management intensity in both years. We conclude that the biological mechanisms leading to enhanced biomass production in diverse grassland communities are as effective for productivity as a combination of several agricultural measures. Our results demonstrate that high-diversity low-input grassland communities provide not only a high diversity of plants and other organisms, but also ensure high forage yields, thus granting the basis for multifunctional managed grasslands.
Comparison of Decomposition Rates of Beech (Fagus orientalis Lipsky) and Spruce (Picea orientalis (L.) Link) Litter in Pure and Mixed Stands of Both Species in Artvin, Turkey

The decomposition of spruce, beech and mixed litters of spruce and beech was investigated over 3.5 years in beech, spruce and mixed (beech/spruce) stands using less than 1.5 mm mesh litter bags. Initially, carbon, nitrogen, lignin and cellulose concentrations, and C:N and lignin:N ratios were determined in beech and spruce litters. For all sampling intervals, mixed litters showed higher decay rates than individual beech and spruce litters in both pure stands and mixed stands. Spruce decomposed more rapidly than beech, and initial lignin concentration explained most of the variation in decomposition rates between beech and spruce. However, differences in decomposition rates between beech and spruce were most pronounced in the mixed stand, while they were intermediate in the beech stand and least pronounced in the spruce stand. This shows that adverse environmental conditions, mostly associated with a lower pH content of the soil under spruce stands, retard decomposition processes and individual litters appear to be more sensitive to this retardation than mixed litters. The results also indicate that abiotic and microbial factors in mixed stands could be better than those in pure stands of spruce and beech. Therefore, the establishment of mixed beech and spruce stands can counteract detrimental processes in decomposition associated with spruce monocultures.
Species composition and forest structure explain the temperature sensitivity patterns of productivity in temperate forests

Abstract. Rising temperatures due to climate change influence the wood production of forests. Observations show that some temperate forests increase their productivity, whereas others reduce their productivity. This study focuses on how species composition and forest structure properties influence the temperature sensitivity of aboveground wood production (AWP). It further investigates which forests will increase their productivity the most with rising temperatures. We described forest structure by leaf area index, forest height and tree height heterogeneity. Species composition was described by a functional diversity index (Rao's Q ) and a species distribution index ( ΩAWP ). ΩAWP quantified how well species are distributed over the different forest layers with regard to AWP. We analysed 370 170 forest stands generated with a forest gap model. These forest stands covered a wide range of possible forest types. For each stand, we estimated annual aboveground wood production and performed a climate sensitivity analysis based on 320 different climate time series (of 1-year length). The scenarios differed in mean annual temperature and annual temperature amplitude. Temperature sensitivity of wood production was quantified as the relative change in productivity resulting from a 1 ∘ C rise in mean annual temperature or annual temperature amplitude. Increasing ΩAWP positively influenced both temperature sensitivity indices of forest, whereas forest height showed a bell-shaped relationship with both indices. Further, we found forests in each successional stage that are positively affected by temperature rise. For such forests, large ΩAWP values were important. In the case of young forests, low functional diversity and small tree height heterogeneity were associated with a positive effect of temperature on wood production. During later successional stages, higher species diversity and larger tree height heterogeneity were an advantage. To achieve such a development, one could plant below the closed canopy of even-aged, pioneer trees a climax-species-rich understorey that will build the canopy of the mature forest. This study highlights that forest structure and species composition are both relevant for understanding the temperature sensitivity of wood production.
An Analysis of Microbial Involvement in Biospeleogenesis Within Lechuguilla Cave System

Caves are geologic systems, shaped by inorganic chemical processes (speleogenesis). Nonetheless, there is increasing evidence that biological processes also play a role in the origin and development of caves (biospeleogenesis). In order to examine the role that microorganisms may play in secondary passage enlargement we collected samples from Lechuguilla Cave, a deep cave system that is largely shielded from human impact. Samples were collected from areas where rock corrosion was obvious. In order to determine if microorganisms were involved with the observed corrosion, we used scanning electron microscopy (SEM) to identify apparent microbial pitting of the rock surface. To establish the identity of the organisms responsible for this pitting, pure cultures of 15 bacterial isolates were obtained. PCR amplification was then utilized in order to obtain the 16S small ribosomal RNA gene sequence of each. These DNA sequences were then assembled using Geneious, followed by alignment of the DNA sequences using the SILVA sequence aligner and ARB program. Aligned sequences were used to create a phylogenetic tree using the RAxML Blackbox software, and the robustness was tested with bootstrapping. This tree allowed us to identify the isolates as Brevibacterium, Citricoccus, Kocuria, Micrococcus, and Rothia. To determine if microorganisms within these genera were responsible for the calcite dissolution observed in the environment, they were each incubated for 36 days with a calcite crystal. These crystals were then visually inspected to look for evidence of calcite dissolution. Our results suggest that microorganisms isolated from the cave environment are capable of calcite dissolution, suggesting that such species may play a role in secondary speleogenetic processes.
Electronic transport and doping mechanisms in Cu(In,Ga)Se₂ thin film solar cells

Photovoltaics (PV), the direct conversion of sunlight into electricity, is an environmentally friendly approach without safety issues for the general public to substitute the energy sources based on fossil fuels and nuclear power. The PV devices based on a Cu(In,Ga)Se2 (CIGS) absorber layer show very high potential for cost-effective energy conversion because only a very thin layer of a few μm is required to absorb the sunlight and high efficiencies above 20% were already achieved with lab scale devices. Moreover, the CIGS solar cells can be produced with a low temperature (< 500◦C) process which enables roll-to-roll manufacturing on flexible polyimide substrate. It is believed that these cost-effective production techniques can further reduce the price of solar modules as well as their energy payback time in the future. While CIGS solar cells produced at high substrate temperature (≈ 600◦C) have already crossed 20% efficiency, low temperature grown devices reached only around 16%. Even if the production costs of low temperature grown CIGS devices are lower such a pronounced difference in efficiency is not acceptable from an industrial point of view because the device efficiency directly translates into production capacity and cost per Watt of the solar module. In this thesis several aspects of the electronic transport which limit the efficiency of low temperature grown CIGS solar cells are investigated and strategies to overcome them are developed. The first part of this thesis concerns the CIGS growth process itself. It is found that due to the reduced temperature during the deposition process a pronounced compositional gradient forms. Because the CIGS composition has a strong influence on the optical and electronic properties of the material this compositional variation induces a band gap grading. By temperature dependent current density-voltage (J-V) measurements