Miracle-dz/UniFAR-FTUs huggingface dataset:
Robot Visual Servoing Using Discontinuous Control

This work presents different proposals to deal with common problems in robot visual servoing based on the application of discontinuous control methods. The feasibility and effectiveness of the proposed approaches are substantiated by simulation results and real experiments using a 6R industrial manipulator. The main contributions are: - Geometric invariance using sliding mode control (Chapter 3): the defined higher-order invariance is used by the proposed approaches to tackle problems in visual servoing. Proofs of invariance condition are presented. - Fulfillment of constraints in visual servoing (Chapter 4): the proposal uses sliding mode methods to satisfy mechanical and visual constraints in visual servoing, while a secondary task is considered to properly track the target object. The main advantages of the proposed approach are: low computational cost, robustness and fully utilization of the allowed space for the constraints. - Robust auto tool change for industrial robots using visual servoing (Chapter 4): visual servoing and the proposed method for constraints fulfillment are applied to an automated solution for tool changing in industrial robots. The robustness of the proposed method is due to the control law of the visual servoing, which uses the information acquired by the vision system to close a feedback control loop. Furthermore, sliding mode control is simultaneously used in a prioritized level to satisfy the aforementioned constraints. Thus, the global control accurately places the tool in the warehouse, but satisfying the robot constraints. - Sliding mode controller for reference tracking (Chapter 5): an approach based on sliding mode control is proposed for reference tracking in robot visual servoing using industrial robot manipulators. The novelty of the proposal is the introduction of a sliding mode controller that uses a high-order discontinuous control signal, i.e., joint accelerations or joint jerks, in order to obtain a smoother behavior and ensure the robot system stability, which is demonstrated with a theoretical proof. - PWM and PFM for visual servoing in fully decoupled approaches (Chapter 6): discontinuous control based on pulse width and pulse frequency modulation is proposed for fully decoupled position based visual servoing approaches, in order to get the same convergence time for camera translation and rotation. Moreover, other results obtained in visual servoing applications are also described.
Global change effects on plant communities are magnified by time and the number of global change factors imposed

Significance Accurate prediction of community responses to global change drivers (GCDs) is critical given the effects of biodiversity on ecosystem services. There is consensus that human activities are driving species extinctions at the global scale, but debate remains over whether GCDs are systematically altering local communities worldwide. Across 105 experiments that included over 400 experimental manipulations, we found evidence for a lagged response of herbaceous plant communities to GCDs caused by shifts in the identities and relative abundances of species, often without a corresponding difference in species richness. These results provide evidence that community responses are pervasive across a wide variety of GCDs on long-term temporal scales and that these responses increase in strength when multiple GCDs are simultaneously imposed. Global change drivers (GCDs) are expected to alter community structure and consequently, the services that ecosystems provide. Yet, few experimental investigations have examined effects of GCDs on plant community structure across multiple ecosystem types, and those that do exist present conflicting patterns. In an unprecedented global synthesis of over 100 experiments that manipulated factors linked to GCDs, we show that herbaceous plant community responses depend on experimental manipulation length and number of factors manipulated. We found that plant communities are fairly resistant to experimentally manipulated GCDs in the short term (<10 y). In contrast, long-term (≥10 y) experiments show increasing community divergence of treatments from control conditions. Surprisingly, these community responses occurred with similar frequency across the GCD types manipulated in our database. However, community responses were more common when 3 or more GCDs were simultaneously manipulated, suggesting the emergence of additive or synergistic effects of multiple drivers, particularly over long time periods. In half of the cases, GCD manipulations caused a difference in community composition without a corresponding species richness difference, indicating that species reordering or replacement is an important mechanism of community responses to GCDs and should be given greater consideration when examining consequences of GCDs for the biodiversity–ecosystem function relationship. Human activities are currently driving unparalleled global changes worldwide. Our analyses provide the most comprehensive evidence to date that these human activities may have widespread impacts on plant community composition globally, which will increase in frequency over time and be greater in areas where communities face multiple GCDs simultaneously.
Pengaruh Store Atmosphere Terhadap Keputusan Pembelian Di Gramedia Manado

Store atmosphere is an atmosphere that refers to the physical characteristics of exterior buildings and interior spaces, which shape the store image and bring in customers. This study aims to determine the effect of store atmosphere on consumer purchasing decisions at Gramedia Manado Sam Ratulangi. The problem in this study is the problem of parking where when going to Gramedia is less comfortable, jammed and narrow, there is a lack of sanitary hygiene, and sometimes changes in shelves and location marks make consumers confused. The type of research used in this study is descriptive quantitative research, using questionnaires and using a Likert scale. The population is all Gramedia Sam Ratulangi Manado consumers whose population size is unknown. Samples taken amounted to 80 respondents using probability sampling method that is by simple random sampling technique. The statistical analysis used in this study is a simple regression analysis using SPSS 25 for windows. The results of this study indicate that store atmosphere has a positive and significant effect on purchasing decisions. The amount of store atmosphere influence on purchasing decisions is 54.7% and 45.3% is influenced by other factors not examined in this study such as product quality, price, promotion and store associate factors that were not examined in this study.
Modelling effects of land-use and climate changes on catchment streamflow, sediment and nutrient loads by means of alternative and integrated models

Urbanization poses a challenge to sustainable catchment management worldwide. This study compares streamflows and nutrient loads in the urbanized Torrens catchment in South Australia at present and future urbanization levels, and addresses possible mitigation of urbanization effects by means of the control measures: river bank stabilization, buffer strip expansion, and wetland construction. A scenario analysis by means of the Soil and Water Assessment Tool (SWAT) based on the anticipated urban population density growth in the Torrens catchment over the next 30 years predicted a remarkable increase of streamflow and Total Phosphorous loads but decreased Total Nitrogen loads. In contrast, minor changes of model outputs were predicted under the present urbanization scenario, i.e. urban area expansion on the grassland. Scenarios of three feasible control measures demonstrated best results for expanding buffer zone to sustain stream water quality. The construction of wetlands along the Torrens River resulted in the reduction of catchment runoff, but only slight decreases in TN and TP loads. Overall, the results of this study suggested that combining the three best management practices by the adaptive development of buffer zones, wetlands and stabilized river banks might help to control efficiently the increased run-off and TP loads by the projected urbanization of the River Torrens catchment.
Introduction to the Special Issue: Ice on Ceres

Ceres is the largest body in the asteroid belt, and the most water‐rich inner solar system body after Earth. Its exploration by the Dawn spacecraft has been long anticipated, in large part because it was expected to be an ice‐rich world. A variety of ice‐ and volatile‐related physical processes were expected to occur on Ceres, including possible cryovolcanism. A major goal of the Dawn mission at Ceres was to understand the abundance, distribution, and phase partitioning of water in the subsurface. Coordinated investigations of subsurface ice during the Dawn mission benefited from the decades‐long effort to inventory and characterize subsurface ice on Mars. Specifically, morphological analysis was leveraged to bridge a length‐scale gap between geophysical remote sensing data sets that provide quantitative constraints on the abundance of subsurface ice at very shallow depths (<1 m; neutron spectroscopy) and data sets that provide quantitative constraints on composition at much longer length scales (tens of kilometers; gravity science). This morphological analysis underscores that Ceres shares geophysical characteristics with terrestrial planets, icy moons, comets, and asteroids, and blurs some of the conventional boundaries between these terms. Grappling with this ambiguity stands to benefit investigations of interior evolution and volatile‐related processes on all solid planetary bodies.
Nonconscious goal pursuit and the surmounting of physical and social obstacles

The ability to overcome obstacles is widely regarded as a sign of motivation. Building oil recent research on nonconscious goal pursuit, two experiments are presented that test whether activating the goal of helping outside people's awareness by exposure to social stereotypes causes them to overcome physical and social obstacles. Experiment I established that although overall participants were less inclined to pick up a tissue that was accidentally dropped on the floor by the experimenter when this tissue was dirty instead of clean, they were able to overcome their aversion toward picking up the physical object when they were primed with the mental representation of a social group (e.g., nurse) containing the goal of helping. Results were replicated ill Experiment 2, in which participants had to overcome a social obstacle by providing feedback to a student of a negatively evaluated ethnic minority group, and explanations in terms of demand characteristics and mood were excluded. Implications for the literature on nonconscious goal pursuit are briefly discussed. Copyright 2008 John Wiley & Sons, Ltd.
Evaluation and Comparison of Random Forest and A-LSTM Networks for Large-scale Winter Wheat Identification

Machine learning comprises a group of powerful state-of-the-art techniques for land cover classification and cropland identification. In this paper, we proposed and evaluated two models based on random forest (RF) and attention-based long short-term memory (A-LSTM) networks that can learn directly from the raw surface reflectance of remote sensing (RS) images for large-scale winter wheat identification in Huanghuaihai Region (North-Central China). We used a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images over one growing season and the corresponding winter wheat distribution map for the experiments. Each training sample was derived from the raw surface reflectance of MODIS time-series images. Both models achieved state-of-the-art performance in identifying winter wheat, and the F1 scores of RF and A-LSTM were 0.72 and 0.71, respectively. We also analyzed the impact of the pixel-mixing effect. Training with pure-mixed-pixel samples (the training set consists of pure and mixed cells and thus retains the original distribution of data) was more precise than training with only pure-pixel samples (the entire pixel area belongs to one class). We also analyzed the variable importance along the temporal series, and the data acquired in March or April contributed more than the data acquired at other times. Both models could predict winter wheat coverage in past years or in other regions with similar winter wheat growing seasons. The experiments in this paper showed the effectiveness and significance of our methods.
Impact‐Induced Porosity and Microfracturing at the Chicxulub Impact Structure

Porosity and its distribution in impact craters has an important effect on the petrophysical properties of impactites: seismic wave speeds and reflectivity, rock permeability, strength, and density. These properties are important for the identification of potential craters and the understanding of the process and consequences of cratering. The Chicxulub impact structure, recently drilled by the joint International Ocean Discovery Program and International Continental scientific Drilling Program Expedition 364, provides a unique opportunity to compare direct observations of impactites with geophysical observations and models. Here, we combine small‐scale petrographic and petrophysical measurements with larger‐scale geophysical measurements and numerical simulations of the Chicxulub impact structure. Our aim is to assess the cause of unusually high porosities within the Chicxulub peak ring and the capability of numerical impact simulations to predict the gravity signature and the distribution and texture of porosity within craters. We show that high porosities within the Chicxulub peak ring are primarily caused by shock‐induced microfracturing. These fractures have preferred orientations, which can be predicted by considering the orientations of principal stresses during shock, and subsequent deformation during peak ring formation. Our results demonstrate that numerical impact simulations, implementing the Dynamic Collapse Model of peak ring formation, can accurately predict the distribution and orientation of impact‐induced microfractures in large craters, which plays an important role in the geophysical signature of impact structures.
Nonlinear Effects of Electron‐Electron Collisions on ISR Temperature Measurements

Incoherent scatter radars (ISR) estimate the electron and ion temperatures in the ionosphere by fitting measured spectra of ion‐acoustic waves to forward models. For radars looking at aspect angles within 5° off perpendicular to the Earth's magnetic field, the magnetic field constrains electron movement and Coulomb collisions add an additional source of damping that narrows the spectra. Fitting the collisionally narrowed spectra to collisionless forward models leads to errors or underestimates of the plasma temperatures. This paper presents the first fully kinetic particle‐in‐cell (PIC) simulations of ISR spectra with collisional damping by velocity‐dependent electron‐electron and electron‐ion collisions. For aspect angles between 0.5° and 2° off perpendicular, the damping effects of electron‐ion and electron‐electron collisions in the PIC simulations are the same and the resulting spectra are narrower than what current theories and models predict. For aspect angles larger than 3° away from perpendicular, the simulations with electron‐ion collisions match collisionless ISR theory well, but spectra with electron‐electron collisions are narrower than theory predicts at aspect angles as large as 5° away from perpendicular. At aspect angles less than 5° the PIC simulations produce narrower spectra than previous simulations using single‐particle displacement statistics that include both electron‐ion and electron‐electron collisions. The narrowing of spectra by electron‐electron collisions in the PIC code between 3° and 5° away from perpendicular is currently neglected when fitting measured spectra from the Jicamarca and Millstone Hill radars, leading to underestimates of electron temperatures by as much as 25% at small aspect angles.
Effect of Calcium Humate, Nitrogen Fertilizer Rates and Irrigation Regime on Soil Chemical Properties and Faba Bean Productivity

A field experiment was conducted at Malawi Agric. Res. Station, Minia Governorate, Egypt during two successive winter seasons of 2014/2015 and 2015/2016 to study the effect of calcium humate (Ca-H), as organic soil conditioner, and nitrogen fertilizer rate under irrigation regime on soil chemical properties and faba bean productivity. The experiment was designed in a split plot design with three replicates, the main plots were occupied by three irrigation regimes: Farmer irrigation (I1), irrigation requirement with 100% WR (I2) and irrigation 75% WR(I3) while sub-plots consists of four treatments (control, 100% N(recommended dose) , Ca-Humate (40 Lfed) and 75% N + Ca-Humate (40 Lfed). Results showed that seasonal water consumptive use increased by increasing available soil moisture as a result of increasing applied water, in general, in both growth seasons. The greatest values of seasonal consumptive use was recorded under farmer practice while the lowest value was recorded under irrigation treatment 75% WR (I3). Also, the interaction effect between irrigation regime and N rates in combination with Ca-H data show that the highest water use efficiency is 1.00 kg seeds/mwater consumption was obtained by irrigation at 75% WR combined with 75% N+Ca-H at second season. The lowest water use efficiency is 0.30 kg seeds/m water consumption was obtained by control treatment under farmer practice. Results revealed that mean values of different irrigation regimes had significantly increased growth characters of faba bean crop (yield, biological yields, 100 seed, plant height, number of branches, number of pods) were observed with I2 (100% WR ) followed by I1 (farmer practices) and I3 (75% WR ), respectively. Applied Ca-H individually or in combination with mineral nitrogen fertilizer were significantlyincreased growth characters of faba bean (yield, biological yield, 100 seed, plant height, number of branches, number of pods) as compared to control treatment. The superior treatmentis75%N+Ca-H at 12 irrigation levels (100% WR). In addition, data reveal that I2 irrigation treatment with 75% N+Ca-H was significantly increased macronutrients total content in (straw and seeds), protein content and protein yield in faba bean crop as compared to control treatment at two successive seasons. On the other hand, chemical soil parameters (pH and EC values) were slightly affected with all applied treatments and increased gradually by decreasing irrigation water. The maximum increased was observed with I2 and applied 75%N+ Ca-H treatment. On the other hand, OM value was decreased with I3 more than I1 and I2, as well as, it was increased by applied calcium hamates application.In conclusion, the application of Ca-H in combination with mineral nitrogen fertilizers was enhanced faba bean crop production and increased NPK content, protein content and protein yield along with improved soil chemical properties under irrigation regimes. Also, Ca-H can be saved about 25% from nitrogen fertilizer dose under low amount of irrigation water.
Coexisting Discrete Bodies of Rhyolite and Punctuated Volcanism Characterize Yellowstone's Post‐Lava Creek Tuff Caldera Evolution

Ion‐microprobe 206Pb/238U geochronology and trace element geochemistry of the unpolished rims and sectioned interiors of zircons from Yellowstone caldera's oldest post‐caldera lavas provide insight into the magmatic system during the prelude and aftermath of the caldera‐forming Lava Creek supereruption. The post‐caldera lavas compose the Upper Basin Member of the Plateau Rhyolite and fall into two groups based on zircon crystallization age: early lavas with zircon ages between ~750 and 550 ka and late lavas with zircon ages between ~350 and 250 ka. Zircons from the early‐erupted East Biscuit Basin flow yield U‐Pb dates and trace element compositions, which when considered with the Pb isotopic compositions of their coexisting feldspars and pyroxenes, point to an isotopically distinct parental melt present during crystallization of the Lava Creek magma but untapped by the supereruption. Distinct zircon crystallization ages and Pb‐isotope compositions of major minerals between the early and late Upper Basin Member groups suggest contrasting sources in the magma reservoir. As proxies for melt evolution, the zircons indicate that Yellowstone's post‐caldera rhyolites became more evolved between mid‐ to late‐Pleistocene time, during the same interval that melting of hydrothermally altered wall rock and recharge by new silicic magmas changed in their relative roles. The results from this study indicate that discrete and ephemeral bodies of silicic magma, at times within a mush dominated reservoir and including during the prelude to the Lava Creek eruption, have characterized Yellowstone's subvolcanic reservoir.
An investigation into the treatment and modelling of Municipal Solid Waste Incineration (MSWI) Air Pollution Control (APC) residues

Air Pollution Control (APC) residues from Municipal Solid Waste Incineration (MSWI) is considered a problematic hazardous waste, with no current viable reuse, within the UK. Therefore, it is often treated before being deposited into a landfill. This research explores a number of novel techniques to mitigate the hazardous properties of this waste by investigating thermal treatment and cold bonding. Thermal treatment was investigated to manufacture inert Light Weight Aggregate (LWA) by sintering APC residues with clay. The addition of 20% APC residue produced the highest fracture strength of 5.78MPa. Treatment through cold bonding was achieved using the geopolymerisation process. The developed material achieved a compressive strength of approximately 2.35 MPa. The data from the APC residues based geopolymer experimentation was used to develop a machine learning model to predict the compressive strength of the geopolymer. In addition, it was observed through a comprehensive literature review, that complexities arising due to significant variations in the composition of the residue, makes it very difficult to produce a commercially stable product. Therefore, the research tackles this problem by developing an Artificial Neural Network (ANN) model to identify and classify different types of residues/ashes based on their chemical composition as determined by X-ray Fluorescence (XRF) spectroscopy. Overall this research showed that machine learning could be very beneficial to this field to determine the capabilities for various reuse applications for ash waste.