Miracle-dz/UniFAR-FTUs huggingface dataset:
A Riemannian approach to trace norm regularized low-rank tensor completion

One of the popular approaches for low-rank tensor completion is to use the {\it latent trace norm} regularization. However, most existing works in this direction learn a sparse combination of tensors. In this work, we fill this gap by proposing a variant of the latent trace norm that helps in learning a non-sparse combination of tensors. We develop a dual framework for solving the proposed low-rank tensor completion problem. In this framework, we first show a novel characterization of the solution space with an interesting factorization of the optimal solution. This allows to propose two scalable optimization formulations. The problems are shown to lie on a Cartesian product of Riemannian spectrahedron manifolds. We exploit the versatile Riemannian optimization framework for proposing computationally efficient trust region algorithms. The experiments illustrate the efficacy of the proposed algorithms on several real-world datasets across applications.
Therapeutic potential of curcumin and its nanoformulations for treating oral cancer

The global incidence of oral cancer has steadily increased in recent years and is associated with high morbidity and mortality. Oral cancer is the most common cancer in the head and neck region, and is predominantly of epithelial origin (i.e. squamous cell carcinoma). Oral cancer treatment modalities mainly include surgery with or without radiotherapy and chemotherapy. Though proven effective, chemotherapy has significant adverse effects with possibilities of tumor resistance to anticancer drugs and recurrence. Thus, there is an imperative need to identify suitable anticancer therapies that are highly precise with minimal side effects and to make oral cancer treatment effective and safer. Among the available adjuvant therapies is curcumin, a plant polyphenol isolated from the rhizome of the turmeric plant Curcuma longa. Curcumin has been demonstrated to have anti-infectious, antioxidant, anti-inflammatory, and anticarcinogenic properties. Curcumin has poor bioavailability, which has been overcome by its various analogues and nanoformulations, such as nanoparticles, liposome complexes, micelles, and phospholipid complexes. Studies have shown that the anticancer effects of curcumin are mediated by its action on multiple molecular targets, including activator protein 1, protein kinase B (Akt), nuclear factor κ-light-chain-enhancer of activated B cells, mitogen-activated protein kinase, epidermal growth factor receptor (EGFR) expression, and EGFR downstream signaling pathways. These targets play important roles in oral cancer pathogenesis, thereby making curcumin a promising adjuvant treatment modality. This review aims to summarize the different novel formulations of curcumin and their role in the treatment of oral cancer.
Study on Students’ Engagement of Different Writing Levels in the Process of Peer Feedback of English Writing in the Junior High School

Within peer feedback, the act of involving students uploading their first drafts of English essays as writers, offering written comments as feedback givers, back-evaluating the helpfulness of peer responses as feedback receivers, and revising previous work as suggested. Research investigating features and development trajectories of engagement from the perspective of feedback givers is still in its infancy. Based on the requirements of the peer feedback task and in the context of teaching English writing in junior schools, this paper uses the survey research method to investigate the learning engagement of Chinese junior high school students in peer feedback and its dynamic changes.
A radial basis function neural network approach to filtering stochastic wind speed data

Various types of control methods are utilized in wind turbines to obtain the optimal amount of power from wind. The turbine dynamics are required in said methods, and the wind speed is a critical component of the analysis. However, the stochastic nature of wind means that wind speed sensor signals are noisy. This paper proposes the utilization of a radial basis function neural network (RBFNN) based filter to process the signal, by training the network with a simulated wind signal. The network is differentiated from a traditional filter in that the number of neurons and the “learning rate” of the network dictate the properties of the filtered signal. The information flow in the network consists of the signal to be processed as the input, the which is then used as an argument in a radial basis function (which determines the “distance” of each value in the input from a particular preset point), and then it multiplied by a weight. The learning rate is obtained from a novel equation that is proposed in the paper. The results showed that the proposed scheme has versatility in terms of noise removal and signal smoothing, and if required, can viably match performance with a Butterworth filter. Furthermore, live training and adaptability also serve as advantages over a classic filter. Three “modes” of processing the signal are determined based on choosing certain ranges of values for parameters which comprise the RBFNN (number of neurons used and learning rate), and the control designer can choose which one to implement based on performance requirements.
A hybrid finite element / finite difference time domain technique for modelling the acoustics of surfaces within a medium

The paper will explore the interaction of vibrating structures with an acoustic medium such as air by the hybridisation of a time integrated sparse node finite element based technique with the finite difference time domain method. In this paper the technique will be employed to model frequency dependant reflection and absorption of surfaces though it could have wider application in modelling sound generation from forced structure vibration. The results of virtual impedance tube and frequency sweep experiments will demonstrate the technique's potential for modelling architectural surfaces and resonant absorbers.
Development of efficient meshless methods for free surface flows

The aim of this thesis is to develop an SPH method free of post formulation corrections with application to the classical Dam-break problem. The analysis has been focused on the weakly compressible smoothed particle hydrodynamics (SPH) formulation of the fluid flow. The discretization and implementation of classical Euler equations has been revised in order to avoid artificial and unphysical corrections commonly used in literature. Many other tools are also used to improve accuracy and performance features, such as a new Kernel Theory to achieve the lowest error and a higher order adaptive time integrator. The results obtained are encouraging either from the physical reliability or the performance time. The obtained simulations are fully comparable with the other already existing in literature, as well as the running time being very promising as it is of order of few hours in a single CPU machine.
On the Measurement Problem and the EPR Paradox

After a polarization measurement with photons in singlet state we know for certain the photons were in the measured state prior to measurement. Photons in singlet state do therefore not exhibit action at a distance. The EPR paradox with entangled photons has been challenged. It was also shown why quantum mechanics infringes Bells inequality.
Temperature-dependent properties of CoFeB/MgO thin films: Experiments versus simulations

CoFeB/MgO heterostructures are a promising candidate for an integral component of spintronic devices due to their high magnetic anisotropy, low Gilbert damping, and excellent magnetoresistive properties. Here, we present experimental measurements and atomistic simulations of the temperature and CoFeB thickness dependence of spontaneous magnetization and magnetic anisotropy in CoFeB/MgO ultrathin films. We find that the thermal fluctuations are different between the bulk and interface magnetizations, and that the interfacial anisotropy originates from a two-site anisotropic exchange interaction. These effects lead to a complex temperature and thickness dependence of the magnetic properties critical to device operation and stability at elevated temperatures.
ANALISIS KINERJA KEUANGAN PERUSAHAAN YANG TERDAFTAR DI BEI PADA MASA PANDEMI COVID-19

The purpose of this study was to analyze differences in the financial performance of companies listed on the Indonesia Stock Exchange before and during the Covid-19 pandemic through solvency ratios and profitability ratios. Covid-19 has caused the Indonesian econo- my to grow negatively. This has had a major impact on the compa- ny's financial performance, because the company experienced a decline in revenue due to policies made due to the Covid-19 pandemic. Thus, in order to survive in the midst of the Covid-19 pandemic, companies listed on the Indonesia Stock Exchange must begin to rise to compete in gaining competitive advantage and superior financial performance. The sample in this study is all sectors of companies listed on the Indonesia Stock Exchange, except the financial sector. The analytical technique used is the Paired-Sample T-test with the help of the STATA program. The results of this study indicate that there are differences in the solvency ratio when measured using the time interest earned ratio. However, the solvency ratio shows no difference when measured using the debt ratio and cash coverage ratio. While the profitability ratio shows that there are differences in the company's financial performance between before and during the Covid-19 pandemic.
Model Predictive Control for Field Excitation of Synchronous Generators

This paper describes a Model Predictive Control (MPC) system for voltage control through ﬁeld excitation of hydroelectric generating units. An attractive feature of MPC is its capability to handle Multiple Input, Multiple Output (MIMO) systems and nonlinear systems taking constraints into account. The system under study is a power system based on detailed models from Matlab’s SimPowerSystems TM and parametrized according to the Nordic model from the Norwegian Transmission System Operator (TSO), Statnett. The primary role of the ﬁeld excitation control system is to quickly respond to voltage disturbances occurring in the power system. The control system is tested for both ﬁrst-swing transient stability and long term voltage stability.
CARINA Project: Visual Perception Systems Applied for Autonomous Vehicles and Advanced Driver Assistance Systems (ADAS)

Autonomous mobile robots use computational techniques of great complexity so that to allow navigation in various types of dynamic environments, avoiding collisions with obstacles and always seeking to optimize the best route, ultimately enabling them to operate in a safe and precise manner. In order for navigation at this level to be possible, a variety of computer vision and intelligent sensing techniques are used. The potential of an intelligent computer vision system to detect and predict the actions of dynamic agents on the streets is applied to increase traffic safety with intelligent robotic vehicles. In this paper we present a systematic review of computer vision models for the detection and tracking of obstacles in traffic environments. Specifically, we cover works involving 2D and 3D (stereo vision) data fusion for both internal and external perception, as well as current trends regarding efficient model design and temporally-aware architectures. We provide a thorough discussion on the main positive and negative points of the state-of-the-art in Visual Robotic Attention, as well as share our experience and contributions in applying visual perception for external obstacle detection and tracking, and internal (driver) monitoring. The results presented should serve as a compilation of the history of visual perception for autonomous mobile robots (specifically, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles), thus providing the reader with a comprehensive basis on both the main contributions and the state-of-the-art in the field.
Magnetic fluid deformable mirror based wavefront sensorless adaptive optics systems

Magnetic fluid deformable mirror (MFDM) is a new type of wavefront corrector that features large deformation strokes, smooth continuous mirror surface, low manufacturing cost, and easy scalability. Considering the idea of taking full advantages of the MFDM’s stroke strengths and the limitations of the adaptive optics (AO) system with the wavefront sensor, this paper proposes a MFDM based wavefront sensorless adaptive optics system. In order to make the MFDM produce desired deformation to eliminate unknown aberrations, this paper introduces the stochastic parallel gradient descent (SPGD) algorithm in the control system. Experimental results show that this SPGD algorithm can effectively control the MFDM to compensate for the unknown aberration in a parallel laser beam so that a perfect focused spot is produced on the CCD image.
A 500-kHz ZVS Class-E Type DC–DC Converter With Two Anti-Series mosfets Topology

Power converters powered by batteries have been widely used in many applications, such as outdoor emergency lighting, electric motorcycle charger, unmanned aerial vehicle supply, and so on. This article presents a 500-kHz zero-voltage switching (ZVS) Class-E type dc–dc converter with two anti-series mosfets used for battery-powered applications. The low-side mosfet is adopted as the main switch to realize the working operation of traditional Class-E resonant converter, while the high-side anti-series mosfet is used to implement the regulation of the converter output voltage based on pulsewidth modulation. Both active switches are ZVS operated so that a high efficiency can be achieved. By changing the high-side mosfet duty cycle, the ac voltage of the resonant tank is also changed to regulate the output voltage consequently. The control method is simple, and the operating frequency is constant, which is beneficial for the design of the resonant components. A 100-W prototype is built to verify the validity of the proposed control method for which a 94.85% efficiency has been achieved.
Novel Synthesis of Generalized Strongly Coupled Resonator Triplet Filters With Complex Reflection Zeros

Complex reflection zeros (CRZs) are introduced into generalized strongly coupled resonator triplet (GSCRT) filter synthesis for the first time to reliably eliminate negative couplings, thus facilitating physical implementation. CRZs bring more flexibility in synthesis and can be preassigned and regulated as needed to guarantee nonnegative couplings in different topologies and achieve varying electrical performance. Besides, CRZs bring the advantage of self-suppressed spikes, which can save extra band-stop modules in the system. To provide useful guidelines for designers, the selection of suitable CRZs is discussed in detail. With the introduced CRZs, the responses of GSCRT filters feature nonideal “in-between” performance, which shows a tradeoff between electrical performance and physical realization. Also, a comparison between the performance of GSCRT filters, extracted-zero, and path filters is given, which aims to help designers choose the most suitable configuration in practical use. Finally, the good measurement results of an anti-interference satellite filter have strongly validated the proposed theories.
Fragmented Subjects in Jonathan Franzen’s The Corrections: A Critique of Globalization

This paper argues that globalization results in producing fragmented self which contradicts its original promise of bringing about happiness and coherent personality as such. In other words, the study illustrates the paradox between the integrating promises and disintegrating effects of globalization and consumer culture in post-industrial America. Analyzing Jonathan Franzen’s The Corrections, this study explores the dissociation in the life of the characters and the society they represent. The notion of globalization and generation gap brought by this phenomenon, the illusion that the drugs can cure depression and anxiety, passion over the financial market correction, question over sexuality and gender roles are some areas causing disorder in the life of the characters. This research is based on the cultural criticism of theories on globalization. Globalization is a multi-disciplinary phenomenon. So, to support the cultural aspect of globalization, I have, on and off, brought classical theory of macroeconomics that supports promises of globalization, and the concept of ‘supply chain’ to explain how those promises have been shattered.
Transient stability analysis based on the state‐plane trajectory and the relative kinetic energy change rate

Due to the widespread application of the wide area measurement system in power systems, it has become feasible to identify the transient stability of a power system on-line. A real-time transient stability identification method combining state-plane trajectory and relative kinetic energy is proposed. First, the correlation between the minimum value of the state-plane trajectory and the system stability is analysed in a single-machine infinite system. On this basis, the relationship between the concavity–convexity of the trajectory and the transient stability is discussed in detail. Second, the calculation of the transient energy is introduced to analyse the energy transformation and a sub-criterion is presented. The comprehensive application of trajectory characteristics and energy criteria can accurately determine the transient stability of all of the units, which is of great practical significance for accurately cutting off the unstable units when system faults occur. A simulation analysis with the IEEE New England 10-machine 39-bus system verified the correctness and effectiveness of the proposed method.
3D reconstruction algorithm for cone-beam differential phase contrast computed tomography

Differential phase contrast computed tomography (DPC-CT) is a novel x-ray inspection method. It reconstructs the refraction index decrement rather than the attenuation coefficient, and can subsequently be applied to inspect weakly absorbing samples. Recently, DPC-CT is implemented, using conventional x-ray tube instead of synchrotron radiation source. In this paper, the reconstruction problem for cone-beam DPC-CT was studied. Some mathematical assumptions were made and a FDK-type algorithm was applied to reconstruct the refractive index decrement distribution of the samples directly from phase contrast projection images. Despite the approximation of our algorithm, it has great features for simplicity of computation and for relatively small errors. The efficacy and shortcoming of the algorithm is presented by its application to a mathematical phantom.
The Impact of Bilingualism on Cognitive Reserve as a Protectant Against Cognitive Decline

Cognitive decline exists on a spectrum, ranging from mild cognitive impairment to dementia. These two diagnoses encompass a group of symptoms rooted in the progressive decline of cognitive function, impairing aspects like memory, decision-making, language use, and locomotion. This review centers upon the premise of cognitive reserve, an intangible measure of the brain’s resilience and capacity to compensate for damage, and its relationship with the preservation of cognitive function later in life. Bilingualism constitutes one of many contributing factors to a higher cognitive reserve; however, this term fails to reflect the unique linguistic profile intrinsic to every individual—including whether a second language was acquired during childhood or later in life. Therefore, a distinction between “acquired” and “lifelong” bilingualism is made. Through the analysis of task-based and neuroimaging data, this review article elucidates the impact both forms of bilingualism have on cognitive reserve as a protectant against cognitive decline, revealing that resultant neuroprotective advantage is most salient when both languages are used regularly, in diverse environments, and in an active manner. These practices are observed in both acquired and lifelong bilinguals to varying degrees, which are contextualized and explored in detail within the review.
What is the alternative to the Alexander–Orbach relation?

The Alexander–Orbach (AO) relation dw = 2df/ds connecting the fractal dimension of a random walk’s (RW) trajectory dw or the exponent of anomalous diffusion α = 2/dw on a fractal structure with the fractal and spectral dimension of the structure itself plays a key role in discussion of dynamical properties of complex systems including living cells and single biomolecules. This relation however does not hold universally and breaks down for some structures like diffusion limited aggregates and Eden trees. We show that the alternative to the AO relation is the explicit dependence of the coefficient of the anomalous diffusion on the system’s size, i.e. the absence of its thermodynamical limit. The prerequisite for its breakdown is the dependence of the local structure of possible steps of the RW on the system’s size. The discussion is illustrated by the examples of diffusion on a Koch curve (AO-conform) and on a Cantor dust (violating AO relation).
Applying a hybrid particle swarm optimization_Tabu search algorithm to a facility location case in Jakarta

Abstract The hierarchical facility location problem (HFLP) is defined as determining the location of facilities in such a way that high-level facilities can serve the facilities in low-level efficiently. In this paper, a mixed integer programming model for the HFLP with the flow capacity constraint is proposed. An approach hybrided PSO and Tabu search (TS) (HPSO-TS) is proposed to solve the HFLP. The objective is to minimize overall demand-weighted distance travel, facility operating costs, and flow assignment costs. This method transforms PSO particles representing various dimensions of the attributes into a Tabu priority list and then constructs the assignment networks. The performance of the proposed algorithm is compared with branch-and-bound algorithm, a genetic algorithm, and classical PSO. Numerical results show that the performance of the proposed algorithm is better than those with exact methods when solving such problems. Finally, the proposed algorithm is applied to solve a case company in Jakarta.
High-Accuracy Localization and Calibration for 5-DoF Indoor Magnetic Positioning Systems

Magnetic local positioning systems are a well-suited candidate for reliable indoor positioning systems, as they are robust against blocking by dielectric materials like walls or people. The system presented in this paper is implemented with a one-axis magnetic transmitter and several three-axis field sensors connected to a complete sensor network. Unfortunately, the performance of the system is severely impaired by field sensor nonidealities such as magnetic coupling of the sensor coils, coil misalignment, field sensor rotation, and unsynchronized sampling. In this paper, the overall field sensor impairments and an additive Gaussian noise model superposing the magnetic field are mathematically described. Then, a novel calibration scheme for the overall field sensor nonidealities is presented. Furthermore, a statistically optimal localization procedure coping with the field sensor nonidealities is developed. The proposed novel localization and calibration algorithms are demonstrated in a common office environment with a size of 7 m <inline-formula> <tex-math notation="LaTeX">${\times }\,\,5$ </tex-math></inline-formula> m <inline-formula> <tex-math notation="LaTeX">${\times }$ </tex-math></inline-formula> 3 m. Thereby, the calibration impressively reduces the position root-mean-square error (RMSE) from 46.8 to 10.6 cm and the angle RMSE from 24.8° to 6.1°.