Miracle-dz/UniFAR-FTUs huggingface dataset:
A Reusable Solar-Electric Orbit Transfer Service

This report describes a commercial service for geosynchronous orbit transfer that is composed of a reusable solar-electric orbit transfer vehicle and infrastructure to store and transfer propellant on-orbit. The service is characterized as being able to transport 4-12 metric ton payloads to orbits in cis-Lunar space, specifically geosynchronous orbit. The service includes an orbit transfer vehicle composed of commercially available Hall-effect thrusters and solar arrays. The vehicle is sized to achieve a mission rate that provides a theoretical operating profit for a business. As the required power is on the scale of hundreds of kilowatts, an on-orbit assembly sequence is proposed to assemble such a vehicle. A scheme for in-orbit propellant resupply is introduced, centered around the approach of tank replacement and leveraging high performance launch vehicles to spread costs of propellant launch over several missions. The orbit transfer mission is assessed with trajectory analysis using an Edelbaum-Alfano control law. The analysis trades off required propellant mass and time of flight for several classes of vehicles optimized for power-plant mass and payload. Trajectories are simulated in four different eclipse seasons for year 2020 and the impact of eclipse on the mission is assessed. Payload mass up to 20 metric tons is also considered. The service improves on standard geosynchronous transfer orbits by delivering payload direct to geosynchronous inclination, which provides benefit to the payload client. The claim is made that the low mass requirement using electric propulsion and long-term storability of its propellants enables the service to be developed and operated commercially with resupply of propellant from Earth.
Changing climate and implications for water use in the Hetao Basin, Yellow River, China

Abstract. Balancing water allocations in river basins between upstream irrigated agriculture and downstream cities, industry and environments is a global challenge. The effects of changing allocations are exemplified in the arid Hetao Irrigation District on the Yellow River, one of China's three largest irrigation districts. Amongst the many challenges there, the impact of changing climate on future irrigation water demand is an underlying concern. In this paper we analyse trends in local climate data from the late 1950s and consider the implications for irrigation in the Basin. Since 1958, daily minimum temperatures, Tmin in the Basin have increased at three times the rate of daily maximum temperatures, Tmax . Despite this, there has been no significant increases in annual precipitation, P or pan evaporation, Epan . The difference between the increasing trends in Tmax and Tmin means that the average annual diurnal temperature range, DTR, has decreased very significantly, part of a global phenomenon. Hargreaves empirical approach is used to estimate changes in both incoming solar radiation, Rs , and potential evaporation, ET 0 . Changes in estimated ET 0 correlated well with changes in measured pan evaporation, Epan . Paradoxically, the estimated decreasing trend in Rs does not correspond to a significant decreasing trend in Epan . Implications of changing climate on water use and soil salinity in the Basin are discussed.
Genetic diversity analysis of six cultured populations of Macrobrachium rosenbergii using microsatellite markers

We compared the genetic diversity and structure of cultivated population of Macrobrachium rosenbergii collected from different areas in China and Thailand by microsatellite analysis. Twelve fluorescently labeled primers were used to amplify microsatellite DNA from three Guangdong cultivated populations( GD1,GD2 and GD3),one Jiangsu cultivated population( JS) in China and two cultivated populations in Thailand( TG1 and TG2). The results show that the detected microsatellite loci possessed high polymorphism( PIC = 0. 853 ~0. 941). All the populations analyzed displayed high genetic diversity( He= 0. 848 ~ 0. 896). Genetic differentiation index( Fst) and AMOVA analysis reveal that the genetic differentiation within populations was relatively low( Fst 0. 15). About 5. 27% genetic variation was derived from inter-populations,while 94. 73% variation was derived from intra-population. Nei's genetic distance indicates that the genetic distance between JS and GD2 population was the lowest( 0. 160 8),while that between the GD1 population and TG2 population was the highest( 0. 695 8). Phylogenetic analysis displays that these six M. rosenbergii populations could be divided into two groups.GD1,GD2,GD3 and JS populations were clustered together as one group and TG1 population was clustered with the TG2 population as another group. The results demonstrate that the analyzed cultivated M. rosenbergii populations maintained relatively high genetic diversity,and there was low kinship between China and Thailand populations.
Measuring Switching Costs in the Italian Residential Electricity Market

Residential electricity markets in European countries are still characterized by low consumer engagement, especially where regulated and liberalized markets coexist. Using an original dataset on 2015–2018 prices for the Italian electricity market, augmented with the number of residential consumers, we study the presence and magnitude of switching costs—i.e., time-based and cognitive-based costs on consumers changing providers—in the liberalized market. We find that switching from the incumbent involves high costs—almost as high as the yearly energy expenditure—while switching from competitors is less expensive. We also carry out two counterfactual analyses. In the first, we show that consumers would have incurred lower average switching costs over the years had the market been less concentrated. In the second, we simulate how switching costs could evolve once regulated prices are phased out, and the market is fully liberalized.
A Survey on Quantitative Assessment of the Quality of Tone-Mapped Images using TMQI-LI

- Even though the knowledge of tone mapping is continuously developing, many unanswered questions and hypotheses still remain to be solved. On that account, we are quite far away from having an accurate computational model for the compression of high dynamic range images to low dynamic ones. It is; therefore; of particular importance and necessity to conduct experimental subjective evaluations of the computational approaches that incorporate various tone mapping operators to judge and validate them properly. Moreover, the evaluations give us a deeper insight into the inquired area and, besides the evaluation of existing methods they can lead to proposals of new ones. The goal of Image Quality Assessment (IQA) is to computationally predict human perceptions of image quality. In order to improve the quality of the image two factors are considered, they are structural fidelity and statistical naturalness. Then the proposed iterative algorithms are used, so as to improve the quality of the image. Numerical and subjective experiments make evident that the proposed algorithm consistently produces better quality tone mapped images even when the initial images of the iteration are created by the most competitive TMOs.
Constraints on localized CMB structure from multichannel, broadband SKS-coda analysis

In recent years, a wide range of geophysical results have offered evidence that Earth’s lowermost mantle is characterized by strong lateral variations in material properties. Among the structures of particular interest are intermittent ultra-low velocity zones (ULVZ’s), located directly above the CMB, which have been originally inferred from the distortion of teleseismic SPdKS phases. ULVZ’s have been modelled as layers with sharp boundaries and seismic velocity reductions ≥10%, and interpreted as regions of partial melt. In this study, we further constrain local ULVZ structure beneath North America by signal processing and waveform modelling of the SKS-coda recorded at broadband seismic arrays. Secondary phases in the SKS-coda are effectively isolated by eigenimage processing. Residual (i.e. SKS-less) data sections from various western Pacific events display clear SPdKS arrivals, followed by a secondary phase whose timing and slowness are consistent with CMB origins. One-dimensional modelling of these phases by reflectivity and generalized ray synthetics favours an asymmetric model, with ULVZ present at only one of the CMB-intercepts. The preferred ULVZ is characterized by reductions in P and S velocities of 18% and 50%, respectively, and a diffuse upper boundary. These characteristics are interpreted in the context of local production and gravitational sinking of dense (i.e., iron rich) partial melt above the CMB. We postulate that a gradational ULVZ beneath North America may mark a lateral transition domain between regions of mantle upwelling, where more uniform ULVZ’s exist, and regions of downwelling, where ULVZ’s are either nonexistent or imperceptibly thin.
MOUNT BAKER BASALT MINERAL TEXTURES AND CHEMISTRY: PROBES INTO MAGMA RESERVOIR PROCESSES

PROBES INTO MAGMA RESERVOIR PROCESSES Maria Vasin Advisor: Sue DeBari April 2017 – June 2018 ABSTRACT The purpose of this study is to investigate the magmatic journey of two basaltic lava flows from Mount Baker from mantle melting to eruption. This investigation involves semi-quantitative analysis of phenocryst zoning and disequilbrium textures which are likely to reflect open-system processes. The Park Butter flow was found to involve just one (or two possible but unlikely) mafic magma injection causing zoning and eruption. The Lake Shannon flow was found to involve felsic magma travel through cumulates, mixing of felsic and mafic magmas, and finally a mafic injection into this mixed chamber causing eruption. Both the Park Butte and Lake Shannon flows were found to show strong evidence of diequilibrium textures.
Hand-held X-ray fluorescence (hXRF) measurements as a useful tool in the environmental and mining sector – Comparative measurements and effects of water content

In this article, direct hXRF measurements on zinc-, arsenicand lead-containing tailing material, which has been investigated with regard to its potential for re-mining, will be presented. Measurements on the original moist field material will be compared to measurements on dry material. In general, the evaluation of the hXRF data for the tailing material shows a good relative replication of the element contents determined (chemical analysis). This was not compulsory for such a heterogeneous material. In humid sediments, however, there are considerably large fluctuations in the element concentration.
A HYBRID ALGORITHM TO ENHANCE IMAGE CONTRAST BASED ON DHE AND IHE

: Image processing is a system which is utilized to upgrade crude pictures which are gotten from cameras, sensors set on satellites and air make. The Image processing strategies, picture upgrade procedures are completely utilized as a piece of the field of medical imaging, particularly Magnetic Resonance Imaging (MRI). Contrast material is utilized to see MRI images clearly. The primary capacity of image enhancement is to discover concealed part in a picture and to upgrade the low contrast picture. The nature of picture shows signs of improvement by contrast control. A very well known performance for contrast upgrade is histogram equalization (HE). Histogram equalization procedure enhances the contrast of the pictures. There are different histogram equalization methods however the greater part of them is time-consuming and there is a need to present new procedure with less time utilization. The current systems are mostly implemented for the grey level images, lack behind contrast adjustment, not function admirably with colored pictures and all the more testing is required to generalized the picture. The examination here manages the picture upgrade utilizing histogram equalization out to beat the current restrictions. Color and profundity data will be utilized to solve color image improvement. Different image histogram parameters, for example, blurriness, noise, least square factor, contrast of a picture are assessed. The approach gives better contrast of a picture. The outcomes are thought about utilizing a histogram equalization graph which demonstrates that the proposed strategy is appropriate for image contrast and upgrade for better picture quality applications.
COMPLETION OF SPARSE AND PARTIAL POINT CLOUDS OF VEHICLES USING A NOVEL END-TO-END NETWORK

Abstract. Completing the 3D shape of vehicles from real scan data, which aims to estimate the complete geometry of vehicles from partial inputs, acts as a role in the field of remote sensing and autonomous driving. With the recent popularity of deep learning, plenty of data-driven methods have been proposed. However, most of them usually require additional information as prior knowledge for the input, for example, semantic labels and symmetry assumptions. In this paper, we design a novel and end-to-end network, termed as S2U-Net, to achieve the completion of 3D shapes of vehicles from the partial and sparse point clouds. Our network includes two modules of the encoder and the generator. The encoder is designed to extract the global feature of the incomplete and sparse point cloud while the generator is designed to produce fine-grained and dense completion. Specially, we adopt an upsampling strategy to output a more uniform point cloud. Experimental results in the KITTI dataset illustrate our method achieves better performance than the state-of-arts in terms of distribution uniformity and completion quality. Specifically, we improve the translation accuracy by 50.8% and rotation accuracy by 40.6% evaluating completed results with a point cloud registration task.
MULTIREGRESSION DYNAMIC MODELS IN GROUP ANALYSIS

Connectivity studies of the brain are usually based on functional Magnetic Resonance Imaging (fMRI) experiments involving many subjects. These studies need to take into account not only the interaction between areas of a single brain but also the differences amongst those subjects. This work uses the group-structure (GS) approach applied to Multiregression Dynamic Model (MDM), as defined in Costa et al. (2019), to study the information flow of the brain. The GS approach consists of grouping subjects according to the similarities in their graph structures. For this, firstly the process of learning network is done twice: a) for each subject individually and b) for each pairwise of subjects under the constraints of both individuals have the same graphical structure but the connectivity strength may be different. To search over networks we have used an efficient search-and-score method called as MDM-IP algorithm (Costa et al., 2015) which is based on the gobnilp system (Cussens, 2011; Bartlett and Cussens, 2013) and the scores were defined as the joint log predictive likelihood (LPL) calculated as
Data‐driven robust extended computer‐aided harmonic power flow analysis

The surge in the uptake of harmonic producing loads in 21st-century smart distribution networks has necessitated that robust data-driven approaches for harmonic assessment be developed. Moreover, there exists abundant harmonic data which can be leveraged on for the construction of this harmonic assessment tool. This is the objective of this study. Large volumes of time-stamped data acquired from a practical distribution network in Edmonton, Canada, have been used to construct a time-dependent cross-coupled harmonic model that has been combined with a formulated iterative time-dependent robust extended computer-aided harmonic power flows. The constructed harmonic power flow formulation also considered the constraints relating to the power conservation principle at the fundamental frequency. Practical network conditions including untransposed lines, load unbalance and skin effects of conductors have been thoroughly modelled. The proposed method has been applied to practical radial and weakly meshed medium voltage distribution networks and it demonstrated robustness to initialisation of the iterative procedure. Moreover, findings from this detailed data-driven technique reveal that harmonic impacts in the distribution networks depend on the quantum of harmonic levels, type of network and location of the harmonic sources.
The influence of radiation on cloud-surface feedback mechanisms using Large Eddy Simulation

A broken cloud layer, such as shallow cumulus, cast shadows on the surface and change the radiation budget at the surface. A large eddy simulation is used to investigate these cloud-shadow effects. Including the shadows of shallow cumulus clouds in a simulation leads to a decrease in the net radiation, the surface heat fluxes and results in a lower buoyancy flux in the boundary layer. This causes clouds to die out. When looking at the difference between a homogeneously and heterogeneously spread radiation budget significant differences were observed. Two simulations were done; one where the net radiation depended on the presence of a cloud above (heterogeneous) and one where the net radiation in columns with and without clouds were averaged and spread out over the entire domain (homogeneous). In this case the heterogeneity of the radiation budget caused a decrease in the surface heat fluxes below the clouds and an increase of the surface heat fluxes in the non-cloudy parts. In addition, a decrease in the liquid water content was observed. The cloud cover did not change significantly, but the clouds themselves had a lower liquid water mixing ratio and were thinner. Heterogeneity also had a negative effect on the cloud activity, lifetime and size. These findings may be important in cloud parameterizations in global circulation models.
Chemolithotrophic sulfide oxidizers in mine environment

Microbial communities in waste rock waters from Mine A were compared to process water sample microbial communities from Mines B and C, with special attention to microbes active in sulfur and iron cycling. It turned out that in Mine A waste rock waters, neutrophilic, psychrotolerant proteobacteria represented the majority of sulfur oxidizers while in Mine B and C process samples, acidophilic sulfur oxidizers dominated. Data presented in this paper emphasize the interaction between environmental conditions and microbial clusters.
FACULTATIVE SELF-POLLINATION IN ISLAND IRISES

-Blue flag (Irzs versicolor) is an insect-pollinated clonal plant found in wet habitats throughout northeastern North America. Our study of an isolated population on Kent Island, New Brunswick, showed that blue flag was self-compatible. Moreover, we found no evidence of inbreeding depression. Although individual flowers were protandrous, the timing of male and female phases and the precise behavior of flowers depended upon whether the flowers had been pollinated. Naturally pollinated or hand-pollinated flowers closed their stigmas shortly after pollination, making them no longer receptive. Flowers from which pollinators had been excluded prolonged the period during which stigmas were open and reflexed downwards, increasing the likelihood that they could come into contact with their own anthers or petals onto which pollen had fallen. In the absence of insects, plants growing in exposed habitats apparently took advantage of wind to achieve pollination. Hand-pollination experiments showed no evidence of inbreeding depression. Fruit set, capsule size and the number of seeds per capsule did not depend on whether pollen came from the same flower, the same clone, the same population or different populations. Facultative autonomous self-pollination may be advantageous whenever pollination and outcrossing are unlikely, as in inbred populations, in small or clonal populations, or in populations where insect pollinators are scarce, ineffective or constrained by harsh environmental conditions.
A Hybrid Partitioning Strategy for Distributed FCA

Several parallel and distributed FCA algorithms have been proposed to speedup the discovery of concepts. Some require the context to be replicated on all machines while others partition the context horizontally across diﬀerent machines. The former suﬀers from memory bottlenecks for large contexts as every machine retains the entire context in memory. The latter approaches are based on Map-Reduce paradigm wherein to compute a valid concept requires all-all communication be-tween diﬀerent machines, incurring huge communication overheads. It has been shown that DFS (Depth-First-Search) based approaches can exploit database reduction strategy for concept sub-tree exploration. This signiﬁcantly decreases the cost of closure computation in the concept sub-tree and results in higher speedup. The existing Map-Reduce based approaches cannot use DFS exploration strategy. In this paper, we propose a hybrid partitioning strategy for distributed FCA that uses horizontal partitioning for groups of low support attributes and vertical partitioning for high support attributes. This not only alleviates memory bottlenecks but also minimizes communication overheads. For vertically partitioned sub-context, inter-machine communication is only required for concepts below a certain support threshold. We further minimize the communication cost by using group-id based auxiliary structure. This hybrid partitioning also allows DFS based concept exploration, thereby making it more scalable and eﬃcient.
Analysis of Available Selection Techniques and Recommendation for Memetic Algorithm and its Application to TSP

: In this article, different types of selection techniques have considered for the study. The method of selecting the appropriate chromosome in the genetic algorithm is called selection operation. So, it can be a part of the matting cycle. The genetic and memetic algorithm is probabilistic and randomized. Both of these algorithms fall into the evolutionary algorithm group. These algorithms work on the principle of natural selection used by Charles Darwin. This algorithm can be applied to various problems of optimization, such as scheduling, routing, Travelling salesman problems, and combinatorial problems. Such two algorithms performance depends on their operators, such as selection techniques, crossover operators, mutation operators, and their probability rates. This research mainly focuses on studying and evaluating the selection techniques. Genetic algorithm is implemented for the combinatorial problem i.e process scheduling problem. In the extend research memetic algorithm can be implemented for other combinatorial problem i.e TSP. The computation time of the algorithm with respect to the selection techniques are analyzed. Compared to the existing selection operator, steady state selection technique shows better results.
The majestic edge coloring and the majestic 2-tone edge coloring of some cycle related graphs

An edge coloring of a graph G is called a majestic edge coloring if there is the induced proper vertex coloring. If the colors of edges of the G graph have 2-elements sets and the G graph has induced proper vertex coloring then an edge coloring of the G graph is called the majestic 2-tone coloring. The majestic and the majestic 2-tone chromatic indices for some cycle related graphs which are wheel graph, gear graph, helm graph, web graph, and friendship graph are computed.