Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution Grid Optimal Power Flow (D-OPF): Modeling, Analysis, and Benchmarking

In the power distribution systems, optimal power flow (D-OPF) is formulated as a non-convex and non-linear programming (NLP) problem. Convex relaxation and linear approximation models have been increasingly adopted to achieve computational efficiency for D-OPF. Despite the benefits of scalability and global optimality, each method is based on certain assumptions, performs differently, and may lead to solutions that are physically not meaningful. In this context, this work numerically evaluates the relative performance of second-order cone programming (SOCP), semi-definite programming (SDP), and linear programming (LP) formulations of D-OPF in terms of their feasibility, optimality, and scalability with respect to NLP-based formulations. We also compare the bus injection (in bus voltage and current variables) and branch flow (in active and reactive power flow variables) based on NLP formulations. The performance is evaluated using small (123-node), medium (730-node), and large (2522-node) sized distribution feeders. Case studies, which are backed up by visualization of the analytical models for the solution space to the extent possible, show that (1) the feasibility and exactness of relaxed D-OPF formulations depend upon the problem type, (2) some NLP formulations are computationally more tractable than others, (3) different NLP formulations can converge to different local solutions, and (4) the approximate linear model may underestimate or overestimate the cost function (depending upon the problem type) and may lead to AC-infeasible solutions.
Finite-Time Model-Based Event-Triggered Implementation of Hybrid Controllers

In this paper, we implement model-based event-triggered control on a hybrid controller by exploiting finite-time attractivity of the sensor dynamics. We provide conditions for the following properties of the closed-loop system: 1) asymptotic stability of a compact set; 2) no Zeno solutions; 3) robustness against small perturbations. The proposed implementation is demonstrated by applying it on top of an event-triggered controller.
Instabilité elliptique sous champ magnétique

: We present a theoretical, experimental and numerical approach of the dynamics of the elliptical instability in a rotating conducting fluid when a magnetic field is imposed along the rotation axis. We show that the growth rate of the instability and the square of the amplitude of the induced field decrease linearly with the square of the applied field. A particularly rich non-linear dynamics is highlighted. Finally, the possibility of a dynamo by elliptical instability is discussed.
A learning-based synthesis approach of reward asynchronous probabilistic games against the linear temporal logic winning condition

The traditional synthesis problem is usually solved by constructing a system that fulfills given specifications. The system is constantly interacting with the environment and is opposed to the environment. The problem can be further regarded as solving a two-player game (the system and its environment). Meanwhile, stochastic games are often used to model reactive processes. With the development of the intelligent industry, these theories are extensively used in robot patrolling, intelligent logistics, and intelligent transportation. However, it is still challenging to find a practically feasible synthesis algorithm and generate the optimal system according to the existing research. Thus, it is desirable to design an incentive mechanism to motivate the system to fulfill given specifications. This work studies the learning-based approach for strategy synthesis of reward asynchronous probabilistic games against linear temporal logic (LTL) specifications in a probabilistic environment. An asynchronous reward mechanism is proposed to motivate players to gain maximized rewards by their positions and choose actions. Based on this mechanism, the techniques of the learning theory can be applied to transform the synthesis problem into the problem of computing the expected rewards. Then, it is proven that the reinforcement learning algorithm provides the optimal strategies that maximize the expected cumulative reward of the satisfaction of an LTL specification asymptotically. Finally, our techniques are implemented, and their effectiveness is illustrated by two case studies of robot patrolling and autonomous driving.
Simultaneous Advertiser Profit and Ad Platform Revenue Maximization in Programmatic Advertising via Feedback Control

The majority of online advertising is served through real-time bidding, and advertising campaigns are often defined as optimization problems. This paper deals with simultaneous advertiser profit and ad platform revenue maximization subject to multiple advertiser performance constraints and is an extension to the work published in [1]. The optimal bidding mechanism is derived for a large family of advertising problems; and it is shown how the solution can be implemented as three separate subsystems dealing with impression valuation, campaign control, and bid shading optimization, respectively. Feedback control is a critical aspect of the solution and makes the optimization scalable and adaptive. A proof of concept control system is proposed and simulated to demonstrate the impact of trading advertiser profit for ad platform revenue.
A Bin-by-Bin Calibration with Neural Network for FPGA-Based Tapped-Delay-Line Time-to-Digital Converter

The method of implementing TDC with FPGA carry chain is widely used, but the delay time of each TDC bin is greatly affected by the changes of operating temperature. At present, the commonly used methods can’t well fit the changing trend of each delay bin in long delay line under the influence of complex temperature changes. In this paper, a neural network calibration module based on MLP is proposed, in which 128 delay time data of delay line and corresponding temperature data transmitted to the host computer are used as training samples to establish MLP. When working, the delay time of each TDC bin can be given independently by knowing current temperature condition. Through experiments, the compensation of network calibration module on temperature changes is verified, and the network can be transplanted to different types of FPGA chips and run under various temperature changes. The TDC have a precision of 34ps.
Switching of optical vortices in nonlinear annular couplers

We suggest an annular waveguide coupler for switching the angular momentum of light. We study linear and nonlinear coupling of both power and momentum of an optical vortex beam launched into one of the ring cores, and demonstrate that the switching takes place well below the collapse threshold. The switching is more effective for the inner-ring excitation since it triggers more sharply and for the lower power enough to avoid the beam azimuthal instability.
Reference Model for the Development of a Learning Management System with an Integrated Voice Assistant for the Optimization of the Teaching Process of a Foreign Language for People with Visual Impairment

Visually impaired people experience different accessibility barriers when they want to learn a second language through virtual classes. In addition to this, Screen Readers often have a high learning curve, plus they are not optimized for reading different languages at the same time. For this reason, it was decided to design the model of a Learning Management System (LMS) with a minimalist and accessible design and with an integrated voice assistant. As a result, it was obtained that the proposed solution was more efficient and effective in providing support to the process of teaching foreign languages in contrast to the methodology currently used.
A mixed-integer MPC with polyhedral potential field cost for obstacle avoidance

This work pertains to the use of polyhedral potential fields which take into account the obstacles’ shape through their associated sum function. As contributions, we extend the polyhedral sum function notion to the multi-obstacle case and show that the polyhedral support of its piecewise affine representation comes from an associated hyperplane arrangement. We exploit the obtained combinatorial structure to provide equivalent mixed-integer representations and model a repulsive potential term for subsequent use in a Model Predictive Control (MPC) formulation. The advantages are related to a decrease in the computational complexity and a coherent description of the repulsive potential, regardless of the cluttered environment’s complexity.
Quality Evaluation Method for Chest X-Ray Images using the Reference Patterns

Chest X-Ray image quality evaluation relies on clinicians' judgment with clinical guidelines and expertise. Recently, the deep learning model for disease diagnosis has been made using X-ray image datasets. In this case, the quality of the image, which is the training model's input, determines the diagnostic model's performance. However, there are cost and time limitations to relying solely on the evaluation of clinicians for the massive amount of images. Therefore, there is a need to automatically evaluate the checklist of a given guideline and select a high-quality image. This paper generates a high-quality pattern from the chest X-ray image, and the difference between pixels from the target image is imaged. It is a method of evaluating quality with a CNN-based model by patterning the pixel value distribution of the generated image. The proposed method shows that it is possible to evaluate multiple integrated items, not a single evaluation item. In addition, to confirm the effectiveness of the proposed model, data composed by refining only randomly configured data and high-quality data without applying quality evaluation were applied to the Nodule Diagnostics Model. As a result of the experiment, model performance improved by 19% accuracy and 21% AUC when training with high-quality data.
Codon Usage Bias and Cluster Analysis of the MMP-2 and MMP-9 Genes in Seven Mammals

Matrix metalloproteinase (MMP)-2 and MMP-9 are a family of Zn2+ and Ca2+-dependent gelatinase MMPs that regulate muscle development and disease treatment, and they are highly conservative during biological evolution. Despite increasing knowledge of MMP genes, their evolutionary mechanism for functional adaption remains unclear. Moreover, analysis of codon usage bias (CUB) is reliable to understand evolutionary associations. However, the distribution of CUB of MMP-2 and MMP-9 genes in mammals has not been revealed clearly. Multiple analytical software was used to study the genetic evolution, phylogeny, and codon usage pattern of these two genes in seven species of mammals. Results showed that the MMP-2 and MMP-9 genes have CUB. By comparing the content of synonymous codon bases amongst seven mammals, we found that MMP-2 and MMP-9 were low-expression genes in mammals with high codon conservation, and their third codon preferred the G/C base. RSCU analysis revealed that these two genes preferred codons encoding delicious amino acids. Analysing what factors influence CUB showed that the third base distributors of these two genes were C/A and C/T, and GC3S had a wide distribution range on the ENC plot reference curve under no selection or mutational pressure. Thus, mutational pressure is an important factor in CUB. This study revealed the usage characteristics of the MMP-2 and MMP-9 gene codons in different mammals and provided basic data for further study towards enhancing meat flavour, treating muscle disease, and optimizing codons.
Anisotropic thermal expansion effects in layered n-Alkyl carboxylic acid – bipyridyl cocrystals

ABSTRACT Cocrystallisation of butanoic acid (BA), pentanoic acid (PA), and eicosanoic acid (EA) with 4,4’-azopyridine (azp) and trans-1,2-bis(4-pyridyl)ethylene (bpe) results in 2:1 lamellar cocrystals. All cocrystals display the OH···Npyridyl seven-membered ring supramolecular synthon however, each cocrystal responds differently upon heating. Positive thermal expansion (PTE) occurs along the c-axis due to π···π stacking in the isostructural BA cocrystals, while the PA cocrystals are not isostructural and display a mixture of anti and gauche conformations of the acid chains because of the length mismatch with the coformer. PA2·azp displays negative thermal expansion (NTE) of the intrasynthon C···O hydrogen bond. The two EA cocrystals both display c-axis elongation on warming due to the expansion of the distance between the alkyl chains. The expansion by more than 1 Å in EA2·azp is highly anisotropic, however, there is much less c-axis expansion in EA2·bpe. Graphical Abstract
Numerical simulations of shock-cloud interactions

This Thesis presents numerical simulations of shocks interacting with regions containing multiple individual clouds. Firstly, the hydrodynamic interaction is presented. It is the first study to include 100s of clouds in a clumpy region which `mass-load' the flow. The 'mass-loading' reduces the Mach number of the shock and leads to the formation of a dense shell. In cases in which the `mass-loading' is sufficient the flow slows enough that the shock degenerates into a wave. The shock does not decelerate below a minimum velocity determined by properties of the region. Despite the turbulence generated behind the shock, the initial mass loss from the clouds is weaker. Nevertheless, the shell is found to regulate the cloud lifetimes such that all clouds are destroyed in similar time. The one exception occurs when a few high density clouds are distributed among lower density ones. Secondly, 2D adiabatic magnetohydrodynamic simulations of a shock interacting with groups of two or three cylindrical clouds are presented. We find (i) some clouds are stretched along their field lines, whereas others are confined by their field lines; (ii) upstream clouds may accelerate past downstream clouds; (iii) clouds may also change their relative positions transverse to the direction of shock propagation as they `slingshot' past each other; (iv) downstream clouds may be offered some protection from the oncoming flow as a result of being in the lee of an upstream cloud; (v) the cycle of cloud compression and re-expansion is generally weaker when there are nearby neighbouring clouds. This small-scale study helps to interpret the behaviour of systems with 100s of clouds. Infinitely wide regions can be interpreted via interactions between individual clouds, but in regions of finite width shocks driven from the sides of the region have different field-flow orientations - individual clouds can experience evolving field morphology.
User Evaluation of UbiQuitous Access Learning (UQAL) Portal: Measuring User Experience

—The goal of user experience (UX) research in human-computer interaction is to understand how humans interact with technology. This paper aimed to evaluate the interface and user experience of UbiQuitous Access Learning Portal (UQAL) and make recommendations for the system interface. UQAL Portal is an e-learning web portal that teaches a targeted group of users how to start a business or an online business using an e-learning portal. The portal will be used to search for business-related information, among other things. The User Experience Questionnaire (UEQ) is used to evaluate user experience. The interface is evaluated using a heuristic evaluation technique based on Nielsen’s ten heuristics. According to the UEQ results, the average score for each aspect in 30 UQAL users is: Attractiveness aspect: 1.77; Perspicuity aspect: 2.20; Efficiency aspect: 2.30; Dependability aspect: 1.73; Stimulation aspect: 0.63; and Novelty aspect: 1.27. A comparison of the average score in the dataset product of UEQ Data Analysis Tool revealed that the Perspicuity, Efficiency, and Dependability aspects of UQAL belonged to the Excellent category. The Attractiveness and Novelty aspects could be categorized as Good, and its stimulation could be categorized as Below Average. Four evaluators participate in the heuristic evaluation, which tests all user categories in UQAL. The findings of this study can be used as a suggestion and reference for UQAL Portal improvement.
Evidence for a self-organized growth in granular Co/Al2O3 multilayers

By sequential deposition of thin layers of cobalt and alumina by sputtering, we have fabricated granular multilayers consisting of successive planes of nanosized cobalt clusters separated by alumina along the growth direction. Combining grazing-incidence small-angle x-ray scattering and transmission electron microscopy experiments, we show that, in a given range of thickness, the vertical arrangement of clusters from plane to plane is not random but shows a topology-induced self-organization.
The Fractalkine‐CX3CR1 Axis Regulates Non‐inflammatory Osteoclastogenesis by Enhancing Precursor Cell Survival

The chemokine fractalkine (FKN) is produced by various cell types, including osteoblasts and endothelial cells in bone tissue, and signals through a sole receptor, CX3CR1, which is expressed on monocytes/macrophages, including osteoclast precursors (OCPs). However, the direct effects of FKN signaling on osteoclast lineage cells under homeostatic noninflammatory conditions remain unclear. Here, we report that FKN regulates mouse OCP survival and primes OCPs for subsequent osteoclast differentiation. Wild‐type but not CX3CR1‐deficient OCPs grown on immobilized FKN showed enhanced osteoclast formation following receptor activator of NF‐κB ligand (RANKL) stimulation, with increased expression of osteoclast differentiation markers. Interestingly, the growth of OCPs on immobilized FKN increased the expression of Cx3cr1 and Tnfrsf11a (Rank) transcripts, but following RANKL stimulation, OCPs rapidly downregulated Cx3cr1 expression. Consistently, anti‐FKN monoclonal antibody (mAb) treatment attenuated RANKL‐induced osteoclast formation on immobilized FKN before, but not during, RANKL stimulation. CX3CR1 and RANK proteins were highly expressed on bone marrow‐derived CD11bhigh CD115+ OCPs. Growth on immobilized FKN prior to RANKL stimulation also increased CD11bhigh CD115+ OCP number and their survival and differentiation potential. In a RANKL‐based mouse model of bone loss, anti‐FKN mAb pretreatment significantly inhibited RANKL‐dependent bone loss. Thus, blocking the FKN‐CX3CR1 axis could represent a therapeutic option in noninflammatory bone loss diseases. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
Nonequilibrium Phase Transition in Non-Local and Nonlinear Diffusion Model

We present the results of analytical and numerical studies of a one-dimensional nonlocal and nonlinear diffusion equation describing non-equilibrium processes ranging from aggregation phenomena to cooperation of individuals. We study a dynamical phase transition that is obtained on tuning the initial conditions and demonstrate universality and characterize the critical behavior. The critical state is shown to be reached in a self-organized manner on dynamically evolving the diffusion equation subjected to a mirror symmmetry transformation.
SOURCE: Towards Solar-Uncertainty-Aware E-Taxi Coordination under Dynamic Passenger Mobility

As more fuel-based vehicles are replaced by electric vehicles (EVs) for providing transportation services in cities, e.g., electric taxi or bus fleets, solar-powered charging stations have been progressively deployed in the cities to provide charging services for EV fleets. The emerging solar-powered charging stations bring opportunities for EV fleets to reduce charging cost and carbon footprint by utilizing cheap and environment-friendly solar energy. The uncertainty and dynamics of solar power, however, raise challenges in making full use of solar power on time for EV fleets, e.g., e-taxis, while at the same time serving passengers efficiently. In this work, we design SOURCE, a solar-uncertainty-aware coordination algorithm for e-taxis under spatial-temporal dynamics of uncertain solar energy and passenger mobility. We evaluate our solution with a comprehensive dataset for an existing e-taxi system and charging infrastructures including 726 e-taxis, 7,228 regular fuel taxis, 37 working charging stations, and 62,100 collected taxi trips per day. Our data-driven evaluation shows that our solution significantly improves the usage rate of solar power by 17.6% with similar passenger waiting time compared to the solution that co-optimizes service quality and usage of solar power without considering the solar power uncertainty.
Load Balancing in Software-Defined Data Centre With Fat Tree Architecture

Software-defined data centres have emerged as an automated and virtualized platform for the management of networked computer servers in providing services to organizations and customers. Given the fast increase in demand by different applications on storage, the challenge is to keep up with performance requirements by avoiding bottlenecks in the network. Some examples of these applications are Google Drive, YouTube, and Megaupload. Data centre systems are intended to fulfill the information transmission request of tightly interrelated hosts with the network topology and routing devices playing a part in influencing the latency and other network performances. At present, the fat-tree network is among the most generally utilized topologies for data centre systems. As traffic demand increases in the data centres, the traffic load needs to be shared between servers and inevitably load balancing is required. In software-defined data centres with software-defined networks, the key to load balancing is in the form of smart congestion-conscious routing. It is an important element in promoting the accessibility and adaptability that further prompts to accomplish a minimal reaction application time. This paper reviews load balancing techniques in software-defined data centres with the fat-tree architecture. Load balancing techniques have become smarter and more effective over the years with reductions on overhead statistical collection and improvement in the quality of service. Nevertheless, focus on optimal energy usage is another dimension that can be investigated in promoting green computing.
On the application of spinors to the problems of celestial mechanics

Since Newton, the stumbling-block in celestial me­ chanics has been the three-body problem. Only restricted cases have yielded solutions. This paper describes a new tool for solving the perturbation problem--"spinors," a vec­ torial concept (in the complex plane) originally used in atomic physics but now applied to celestial mechanics. The two-body problem is discussed and two devices a r e intro­ duced: "pseudo-time" and the Levi-CivitL transformations. Then spinors a r e shown to make possible the extension of these transformations to three dimensions. Perturbation problems a r e discussed; notably a body moving around the sun and being acted on by the orbital motion of a major planet.
Transient Stability Analysis of Grid-Following VSCs Considering Voltage-Dependent Current Injection During Fault Ride-Through

This article analyzes the transient stability of grid-following voltage source converters (GFL-VSCs) considering the voltage-dependent current injection (VDCI) dynamics during fault ride-through (FRT). The dynamic interaction between the VDCI and the phase-locked loop (PLL) under the weak grid is revealed to provide insight for their impact on system transient stability. The condition of existence of equilibrium points (EPs) of VSC-grid system during grid faults is first investigated by using a static model considering the VDCI. Then, a dynamic model is developed to characterize the capability of VSC in converging to the EPs during grid faults. It is revealed that the K-factor, which determines the characteristic of the VDCI, has a crucial impact on the transient stability of the system. Finally, case studies based on electromagnetic transient (EMT) simulation and experiment are given to validate the theoretical findings.