Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Multiobjective Optimal Operation Strategy for Wind-Photovoltaic-Hydro Complementary Power System

To address the problems of wind and solar generation volatility and lose of wind and photovoltaic resources, on the basis of the complementary property of wind-solar-water, the topology structure of the wind-solar-water synergy power generation system is constructed. Taking the minimum grid fluctuation index, the minimum wind-photovoltaic-hydro discard rate and the greatest economic effectiveness of the power station as the goal functions and considering various constraints of the wind, photovoltaic, and hydrostation units, a triobjective optimization running model of the wind-photovoltaic-water synergy system is established. Meanwhile, this essay suggests an IMOSSA on the basis of tent chaotic sequence and random wandering strategy to settle the described triobjective optimization issue. Taking Hubei Pankou as an example for simulation analysis, after choosing the best scheme, IMOSSA compared with MOSSA, MOGWO, and NSGA-II, the volatility of sunny days is reduced by 12.39%, 19.5%, and 36.71%, respectively; the wind-photovoltaic abandonment rate is reduced by 11.17%, 22.5%, and 38.03%, respectively, while in the rainy days the volatility is reduced by 8.09%, 18.34%, and 47.03%, respectively; the wind-photovoltaic abandonment rate is reduced by 14.84%, 16.86%, and 40%, respectively. Therefore, it is possible to demonstrate the validity of the proposed three-objective model and the efficiency of the IMOSSA in solving the issue. The efficiency of the optimization operation approach suggested in this research is confirmed by the case study, providing a new idea for the large-scale consumption of new energy in high-proportion hydropower grids.
Biogas Recovery from Refinery Oily Sludge by Co-Digestion Followed by Sustainable Approach for Recycling the Residual Digestate in Concrete Mixes

This study investigated the potential of biogas recovery from refinery oily sludge (ROS) inoculated with animals’ manure by co-digestion of in lab-scale biodigesters at mesophilic conditions. Cow dung (CD), cattle manure (CM), and poultry manure (PM) were utilized as co-substrates. The biogas production from the co-digestion process exceeds its production from uninoculated ROS by approximately 67.5, 22.13 and 21.6% for PM, CM, and CD, respectively. Kinetics of the co-digestion process was well described by the modified Gompertz model. The pre dicted and experimental values of biogas production were well fitted with R 2 > 0.96, suggesting favorable condi tions of the digestion process. New approach for recycling the residual digestate to replace freshwater in concrete mixes was carried out. Results of examining the mechanical properties of the residual digestate-modified concrete mixes demonstrated a potential sustainable approach for the disposal of residual digestate in concrete mixes.
The role of human resources practices and branding in the hotel industry in Dubai

Abstract Given the need for qualitative research on human resource (HR) practices, this study explores and demonstrates the interrelated HR practices around motivating, engaging, and retaining employees. It employs in-depth interviews to explore such practices adopted by 4- and 5- star hotels in Dubai. The findings reveal that HR practices are classified within employer branding and internal branding and directed toward hotel and destination brand image enhancement. This study offers destination managers with HR practices that contribute to enhancing the hotel and the destination brand.
Positive solutions of nonlinear elliptic boundary value problems

This dissertation focuses on the study of positive steady states to classes of nonlinear reaction diffusion (elliptic) systems on bounded domains as well as on exterior domains with Dirichlet boundary conditions. In particular, we study such systems in the challenging case when the reaction terms are negative at the origin, referred in the literature as semipositone problems. For the last 30 years, study of elliptic partial differential equations with semipositone structure has flourished not only for the semilinear case but also for quasilinear case. Here we establish several results that directly contribute to and enhance the literature of semipositone problems. In particular, we discuss existence, non-existence and multiplicity results for classes of superlinear as well as sublinear systems. We establish our results via the method of sub-super solutions, degree theory arguments, a priori bounds and energy analysis.
Unveiling the Hot Molecular Core in the Ultracompact \hii Region with Extended Emission G12.21--0.10

We present a multiwavelength study of the cometary \hii region G12.21--0.10 using the VLA and OVRO. Both radio continuum (0.3, 0.7, 2 and 3.6~cm) and spectral lines of H41$\alpha$, $^{13}$CS(2$-$1) \& (1$-$0), and NH$_{\rm 3}$(2,2) \& (4,4) observations are included. We find two 3~mm continuum peaks toward G12.21--0.10, one of them is spatially coincident with the UC~H~II region, while the other coincides spatially with a molecular clump. We also find that the 0.7, 2 and 3.6~cm continuum and H41$\alpha$ line are only detected toward the UC~H~II region, while the $^{13}$CS, and NH$_{\rm 3}$ is spatially associated with the molecular clump. Based on the morphology, kinetic temperature ($\sim$86~K), volumetric density ($\sim$1.5$\times$10$^6$~cm$^{-3}$) and linear size ($\sim$0.22~pc) of the molecular clump, we suggest this source is consistent with a hot molecular core.
Infrared Spectroscopy of Symbiotic Stars. IV. V2116 Ophiuchi/GX 1+4, The Neutron Star Symbiotic

We have computed, using 17 infrared radial velocities, the first set of orbital elements for the M giant in the symbiotic binary V2116 Ophiuchi. The giant's companion is a neutron star, the bright X-ray source GX 1+4. We rule out the previously proposed period of 304 days and instead find an orbital period of 1161 days, by far the longest of any known X-ray binary. The orbit has a modest eccentricity of 0.10, with an orbital circularization time of ≲5 × 106 yr. The large mass function of the orbit significantly restricts the mass of the M giant. Adopting a neutron star mass of 1.35 M☉, the maximum mass of the M giant is 1.22 M☉, making it the less massive star. Spectrum synthesis analysis of several infrared spectral regions results in slightly subsolar abundances for most metals. Carbon and nitrogen are in the expected ratio resulting from the red-giant first dredge-up phase. The lack of 17O suggests that the M giant has a mass less than 1.3 M☉, consistent with our maximum mass. The surface gravity and maximum mass of the M giant result in a radius of 103 R☉, much smaller than its estimated Roche lobe radius. Thus, the mass loss of the red giant is via a stellar wind. These properties argue that the M giant is near the tip of the first-ascent giant branch. Although the M-giant companion to the neutron star has a mass similar to the late-type star in low-mass X-ray binaries, its near-solar abundances and apparent runaway velocity are not fully consistent with the properties of this class of stars. Thus, in many ways this symbiotic X-ray binary system is unique, and various scenarios for its possible evolution are discussed.
Possibilistic simulation of quantum circuits by classical circuits

In a recent breakthrough, Bravyi, Gosset and Konig (BGK) [Science, 2018] proved that a family of shallow quantum circuits cannot be simulated by shallow classical circuits. In our paper, we first formalise their notion of simulation, which we call possibilistic simulation. We then construct classical circuits, using {NOT, AND, OR} gates of fan-in $\leq 2$, that can simulate any given quantum circuit with Clifford+$T$ gates. Our constructions give log-depth classical circuits that solve the Hidden Linear Function problem defined by BGK, matching their classical lower bound. More importantly, our constructions imply that the constant-vs-log circuit depth separation achieved by BGK is the largest achievable for simulating quantum circuits, like theirs, with Clifford+$T$ gates.
Drift-Kinetic Simulations of Neoclassical Transport

A new ! f Eulerian kinetic code NEO-GK has been developed for numerical studies of neoclassical transport. NEO-GK serves a dual role: in addition to its practical value as a tool for high-accuracy neoclassical calculations, NEO-GK also functions as a stepping-stone (together with our nonlinear GK code GYRO) toward a full-F gyrokinetic code which integrates neoclassical transport and microturbulence. NEO-GK is based on a hierarchy of equations derived by expanding the fundamental drift-kinetic equation in powers of "*, the ratio of the ion gyroradius to the system size. Thus, unlike NCLASS [1], NEO-GK represents a first-principles calculation of the neoclassical transport coefficients (particle flux, heat flux, bootstrap current, poloidal rotation, etc.) directly from the particle distribution function. NEO-GK extends previous numerical studies by including the self-consistent coupling of electrons and multiple ion species and the calculation of the first-order electrostatic potential via coupling with the Poisson equation. Fully general geometry is included, using either a full numerical equilibrium or the Miller local parameterized equilibrium model [2]. For benchmarking, comparisons of the second-order transport coefficients with various analytical theories are presented. Three model collision operators are compared in NEO-GK: the full HirshmanSigmar operator [3], which includes pitch-angle scattering dynamics and energy diffusion, and the reduced Hirshman-Sigmar operator [4] and the Connor model [5], both of which consist of just the sum of pitch angle scattering and momentum-restoring terms. For all three models, the ambipolar relation #s Zs $s=0, which can only be maintained with complete cross-species collisional coupling, is confirmed. With the full Hirshman-Sigmar collision operator, we confirm that the widely used Chang-Hinton analytical model [6] overestimates the ion energy flux in the intermediate aspect ratio regime. Agreement with the more accurate Taguchi banana regime model [7] is shown for validation. The reduced HirshmanSigmar operator and the Connor model are found to consistently underestimate the ion energy flux in all collisionality regimes. Through comparisons with simulations using an adiabatic electron model, the effects of kinetic electron dynamics on the ion transport coefficients are specifically identified. The effects of heavy impurity ions are also explored and limitations of multi-species collisionally-interpolated analytical theories are discussed. Furthermore, parameterized studies of the effects of shaping are performed using the Miller model. Results using DIII-D experimental profiles are also presented. Finally, finite orbit width effects are studied via solution of the third and fourth-order drift-kinetic equations. Neoclassical transport near the magnetic axis is explored and the implications of non-local transport on the validity of the ! f formulation are discussed.
Response to Reviewer #2 of our manuscript entitled Coastal extreme sea levels in the Caribbean Sea induced by tropical cyclones submitted to Natural Hazards and Earth System Sciences .

In their manuscript “Coastal extreme sea levels in the Caribbean Sea induced by tropical cyclones,” the authors Mart´ın et al. use a new database of synthetic tropical cyclones as forcing to simulations of wind waves and storm surges in the Caribbean Sea. It is shown that the wind waves and storm surges vary significantly at coasts around the basin, due to differences in storm evolution, local bathymetry, and other characteristics. The manuscript is generally well-written. It is manuscript To this reviewer, there are two critical flaws in this study. First, the validation is inconsistent with the rest of the study and is inconclusive about the quality of the model predictions. The two validation storms are represented by data-assimilated atmospheric products, whereas the synthetic storms are constructed from a simple parametric model. And the two validation storms are (apparently) not described by sufficient observations of wind waves and coastal sea levels, so it is not possible to validate the model predictions for these storms. Without a validation, it is not possible to trust the later predictions for the synthetic storms – this is recognized by the authors, who note an insufficient nearshore resolution and possible boundary effects as reasons for poor predictions of wind waves and storm surge, respectively. The validation should be expanded to investigate these and other potential problems, either by validating against all available observations for these storms, or by selecting other storms with useful observations. Second, the findings are not necessarily novel, and it is not clear what is the contribution to our scientific understanding. Previous studies have investigated storm-induced hazards in the Caribbean Sea and elsewhere, and they have characterized the wind waves and storm surge that is possible along their coastlines, as well as the relative roles of atmospheric pressures, winds, and waves as drivers. What are the gaps in those previous studies, not in number of storms considered, but in understanding of coastal processes? How will this study help to fill those gaps? As-is, the study is impressive in the amount of computations that have been performed, but it is lacking in
Towards Practical Multi-key TFHE: Parallelizable, Key-Compatible, Quasi-linear Complexity

Multi-key homomorphic encryption is a generalized notion of homomorphic encryption supporting arbitrary computation on cipher-texts, possibly encrypted under different keys. In this paper, we revisit the work of Chen, Chillotti and Song (ASIACRYPT 2019) and present yet another multi-key variant of the TFHE scheme. The previous construction by Chen et al. involves a blind rotation procedure where the complexity of each iteration gradually increases as it continuously operates on ciphertexts under different keys. Hence, the complexity of gate bootstrapping grows quadratically with respect to the number of associated keys. Our scheme is based on a new blind rotation algorithm which consists of two separate phases. We first split a given multi-key ciphertext into several single-key ciphertexts, take each of them as input to the blind rotation procedure, and obtain accumulators corresponding to individual keys. Then, we merge these single-key accumulators into a single multi-key accumulator. In particular, we develop a novel homomorphic operation between single-key and multi-key ciphertexts to instantiate our pipeline. Therefore, our construction achieves an almost linear time complexity since the gate bootstrapping is dominated by the first phase of blind rotation which requires only independent single-key operations. It also enjoys with great advantages of parallelizability and key-compatibility. Weimplementthe proposed scheme and provide its performance benchmark. For example, our experiment of 16-key gate bootstrapping demonstrates about 4.75x speedup without parallelization, and 55.53x speedup with parallelization over prior work.
How far can the error estimation problem in data assimilation be closed by collocated data?

Accurate specification of error statistics required for data assimilation remains an ongoing challenge, partly because their estimation is an ill-posed problem that requires statistical assumptions. Even with the common assumption that background and observation errors are uncorrelated, the problem remains underdetermined. One natural question that could arise is: Can the increasing amount of overlapping observations or other datasets help to reduce the total number of statistical assumptions, or do they introduce more statistical unknowns? In order to answer this question, this paper provides a conceptual 5 view on the statistical error estimation problem for multiple collocated datasets, including a generalized mathematical formulation, an exemplary demonstration with synthetic data as well as a formulation of the minimal and optimal conditions to solve the problem. It is demonstrated that the required number of statistical assumptions increases linearly with the number of datasets. However the number of error statistics that can be estimated increases quadratically, allowing for an estimation of an increasing number of error cross-statistics between datasets for more than three datasets. The presented optimal estimation of 10 full error covariance and cross-covariance matrices between dataset does not accumulate uncertainties of assumptions among estimations of subsequent error statistics.
Higher order sliding mode inspired nonlinear discrete-time observer (cid:73)

This work proposes a design scheme for arbitrary order discrete-time sliding mode observers for input-aﬃne nonlinear systems. The dynamics of the estimation errors are represented in a pseudo-linear form, where the coeﬃcients of the characteristic polynomial comprise the nonlinearities of the algorithm. The design process is reduced to a state-dependent eigenvalue placement procedure. Moreover, two diﬀerent discrete-time eigenvalue mappings are proposed. As basis for the eigenvalue mappings serves a modiﬁed version of the continuous-time uniform robust exact diﬀerentiator. Due on the chosen eigenvalue mapping the proposed algorithm does not suﬀer from discretization chattering. Global asymptotic stability of the estimation errors for observers of order 2 and 3 is proven and the method to prove stability for higher order observers is demonstrated. The performance of a 3-rd order observer is illustrated in simulation. Simulation studies indicate that proposed discrete-time observer might posses an upper bound of its convergence time independent of the initial conditions.
Strategies for conservative and non-conservative monotone remapping on the sphere

Abstract. Monotonicity is an important property of remapping operators for coupled weather and climate models. However, it is often challenging to design highly accurate operators that avoid the generation of new extrema or keep a remapped field between physically prescribed bounds. To that end, this paper explores several traditional and novel approaches for both conservative and non-conservative monotone remapping on the sphere. The accuracy and effectiveness of these algorithms are evaluated in the context of several different real and idealized fields and meshes.
Bayesian calibration of a flood simulator using binary flood extent observations

Abstract. Computational simulators of complex physical processes, such as inundations, require a robust characterization of the uncertainties involved to be useful for flood hazard and risk analysis. While flood extent data, as obtained from synthetic aperture radar (SAR) imagery, have become widely available, no methodologies have been implemented that can consistently assimilate this information source into fully probabilistic estimations of the model parameters, model structural deficiencies, and model predictions. This paper proposes a fully Bayesian framework to calibrate a 2D physics-based inundation model using a single observation of flood extent, explicitly including uncertainty in the floodplain and channel roughness parameters, simulator structural deficiencies, and observation errors. The proposed approach is compared to the current state-of-practice generalized likelihood uncertainty estimation (GLUE) framework for calibration and with a simpler Bayesian model. We found that discrepancies between the computational simulator output and the flood extent observation are spatially correlated, and calibration models that do not account for this, such as GLUE, may consistently mispredict flooding over large regions. The added structural deficiency term succeeds in capturing and correcting for this spatial behavior, improving the rate of correctly predicted pixels. We also found that binary data do not have information on the magnitude of the observed process (e.g., flood depths), raising issues in the identifiability of the roughness parameters, and the additive terms of structural deficiency and observation errors. The proposed methodology, while computationally challenging, is proven to perform better than existing techniques. It also has the potential to consistently combine observed flood extent data with other data such as sensor information and crowdsourced data, something which is not currently possible using GLUE calibration framework.
Advanced Graphics and Image Processing —

This section explains how to render a light field for a novel view position using a parametrization with a focal plane. The method is explained on a rather high level in [1]. These notes are meant to provide a practical guide on how to perform the required calculations and in particular how to find a homographic transformation between the virtual and array cameras. The scenario and selected symbols are illustrated in Figure 1. We want to render our light field ”as seen” by camera K. We have N images captured by N cameras in the array (only 4 shown in the figure), all of which have their apertures on the camera array plane C. We further assume that our array cameras are pin-hole cameras to simplify the explanation. The novel view is rendered assuming focal plane F . The focal plane has a similar function as the focus distance in a regular camera: objects on the focal plane will be rendered sharp, while objects that and in front or behind that plane will appear blurry (in practice they will appear ghosted because of the limited number of cameras). The focal plane F does not need to be parallel to the camera plane; it can be titled, unlike in a traditional camera with a regular lens. Because we have a limited number of cameras, we need to use reconstruction functions A0, . , A1 (only two shown) for each camera. The functions shown contain the weights in the range 0-1 that are used to interpolate between two neighboring views. To intuitively understand how light field rendering is performed, imagine the following hypothetical scenario. Each camera in the array captures the
Rapport de Mi-Parcours Well-quasi-orderings and Database Driven Systems

This thesis takes places at the crossroad of several (cid:3001)(cid:2989)elds of computer science: combinatorics (through well-quasi-orderings), topology (through Nœtherian spaces), and logic (through Finite Model Theory). Ideally, onewouldstudydatabaserelatedproblemsthroughthelensoflogic,andprovidecombinatorialargumentsfor theirresolutionusingthetheoryofwell-quasi-orderings.However,well-quasi-orderingsarenotwell-suitedto describelogicalproperties,andFiniteModelTheoryismorepronetode(cid:3001)(cid:2989)ningtopologies.Asagluebetween thesetworealms,Nœtheriantopologies,theanalogueofwell-quasi-orderingsinthetopologicalsetting,allows toamorceadialoguebetweentheseclassicalorder-theoreticresultsand(cid:3001)(cid:2989)nitemodeltheory. Aparticularinstanceofthisinterplay,studiedinthisthesis,isthewidevarietyofpreservationtheorems, relatingsyntacticfragmentsofFirstOrderLogic(e.g.unionsofconjunctivequeries)tosemanticfragments ofFirstOrderLogic(e.g.queriespreservedunderextensions). Thereexistsaplethoraofsuchpreservation theoremsinclassicalmodeltheorybutmostofthemfailinthe(cid:3001)(cid:2989)nite.Astheclassicalproofscruciallyrely onthecompactnesstheoremof(cid:3001)(cid:2989)rstorderlogic,thisisa(cid:3001)(cid:2989)ttingplacetostudytheinterplaybetween(cid:3001)(cid:2989)nite modeltheoryandnotionsofcompactnessintopologicalspaces.Our(cid:3001)(cid:2989)rstcontributionistostudypreservation theoremsthroughthelensoftopologyvia“topologicalpreservationtheorems”,or,moreformally,logically presentedpre-spectralspaces,wherethetopologicalsettingisidealtodescribealgebraicpropertiesofthose theorems.However,thistopologicaldescriptionshasitslimitsandweprovidedawayto“decouple”topology