Miracle-dz/UniFAR-FTUs huggingface dataset:
The Cultural Self-Construals and the Romantic Relationship Experiences of Turkish Young Adults

ABSTRACT The capacity to form and maintain committed romantic relationships is a key aspect of young adulthood. Yet, little is known about the role of cultural factors, in particular cultural self-construal, and their links to romantic relationships. The goal of the current study was to examine the cultural concepts of autonomous and related self-construal as defined by Kağıtçıbaşı’s Family Change Theory and their association with the quality and satisfaction of non-marital romantic relationships. The sample included 621 Turkish young adults (74.4% female, 83.7% undergraduate students, ages 18–25) who were currently in an exclusive and heterosexual romantic relationship for at least three months. Participants completed informed consent and a 15-minute online survey through Qualtrics. Hierarchical linear regression analysis indicated that autonomy self-construal was positively associated with relationship quality and satisfaction, while relatedness self-construal was linked to relationship quality but not satisfaction. Additionally, high levels of commitment significantly predicted better relationship outcomes. The findings suggest a need to explore cultural self-construal and relationship outcomes across cultures.
Fuzzy clustering of EEE components for space industry

One of the most important problems of the space industry is obtaining reliable methods of automatic grouping (clustering) of specialized EEE components for using in space systems. The main purpose of automatic grouping of EEE components on a set different parameters is the most legible splitting group of EEE components into several homogeneous production batches produced from a single bath of raw materials. The Expectation Maximization algorithm first time applied for the classification of EEE components.
Management of Congestion in Distribution Networks Utilizing Demand Side Management and Reinforcement Learning

The high penetration of distributed energy resources and heavy flexible loads, such as electric vehicles, has changed the operating conditions of the distribution network. In particular, the adoption of green energy innovations has caused an increase in electricity consumption. Such an increase can result in thermal overloading due to power flow exceeding a network asset's transfer capability, possibly damaging devices such as distribution transformers and feeders. It is very challenging to design a congestion management scheme given the uncertainty of flexible loads consumption and electricity prices. Obtaining stochastic models for such loads may not be easily available in practice. In this article, a deep deterministic policy gradient (DDPG) reinforcement learning (RL) scheme is proposed to alleviate congestion. DDPG RL is a model free technique that does not require explicit probabilistic models of the controllable loads to determine the change in electricity prices needed, in the form of tariffs and/or subsidies. The DDPG RL technique is compared with the existing model-based congestion management scheme using an IEEE 33 bus system and the results obtained demonstrate the out performance of the proposed technique in terms of the electricity cost and peak-to-average ratio of the load profiles.
Perspectival Logic of Acceptance and Rejection

This paper aims at developing a logical theory of perspectival epistemic attitudes. After presenting a standard framework for modeling acceptance, where the epistemic space of an agent coincides with a unique epistemic cell, more complex systems are introduced, which are characterized by the existence of many connected epistemic cells, and diﬀerent possible attitudes towards a proposition, both positive and negative, are discussed. In doing that, we also propose some interesting ways in which the systems can be interpreted on well known epistemological standpoints.
Ultrasensitive and High-Speed Ga2O3 Solar-Blind Photodetection Based on Defect Engineering

Oxygen vacancy (VO) defects are ubiquitous in oxide semiconductors and usually served as charge carriers recombination centers to depress the device performance. Herein, a surface VO defect compensation engineering is conducted to modulate the VO and improve the device performance of <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> film via oxygen-plasma treatment. As a result, the photodetectors (PD) based on 30 min oxygen-plasma treated Gallium oxide (Ga<sub>2</sub>O<sub>3</sub>) film not only exhibit record-low dark current of 5 fA, over three orders of magnitude times higher responsivity rejection ratio (<inline-formula> <tex-math notation="LaTeX">${R}_{{250}}/{R}_{{400}}{)}$ </tex-math></inline-formula>, and faster rise and decay speed than the untreated device but also the oxygen-plasma-treated PDs exhibits exceptional sensitivity to detect extremely weak UV signals (<inline-formula> <tex-math notation="LaTeX">$0.1 \mu \text{W}$ </tex-math></inline-formula>/cm<inline-formula> <tex-math notation="LaTeX">$^{{2}}{)}$ </tex-math></inline-formula> with a photo-to-dark current ratio of <inline-formula> <tex-math notation="LaTeX">$\sim 10^{{4}}$ </tex-math></inline-formula>. Also, it is discovered that the device based on oxygen plasma has excellent photoelectric stabilities. The defect engineering with surface plasma treatment offers an efficient strategy for the high performance of Ga<sub>2</sub>O<sub>3</sub> film devices.
Nonintrusive Uncertainty Quantification in the Simulation of Steel Reheating Using Polynomial Chaos Expansion

Uncertainty quantification (UQ) is deemed critical in steel reheating simulations due to the significant input uncertainties arising when defining steel surface properties and atmospheric furnace conditions. In order to conduct UQ, the study utilizes polynomial chaos expansion, which has been found to significantly curtail the computational effort needed to obtain reliable convergent statistics for the model of interest. Results from a comprehensive UQ analysis of a walking‐beam reheat furnace simulated using Tata Steel's reheat furnace control model, online slab temperature calculation, are presented. Slab temperature evolution and oxide scale growth are chosen as the study's QoIs. The analysis reveals that at the earlier stages of reheating, the majority of the output variance in slab temperature can be traced back exclusively to the emissivity of the slab surface, and the majority of the output variance in oxide scale growth is traced back to the combination of slab's surface emissivity and the initial scale thickness found on steel products prior to reheating. However, as the steel product advances toward the furnace's discharge end, inputs related to oxide scale growth become increasingly important, ultimately becoming the most influential input parameters, although the dynamics of this transition differ between the QoIs.
Access to long-term optical memories using photon echoes retrieved from electron spins in semiconductor quantum wells

We use spontaneous (two-pulse) and stimulated (three-pulse) photon echoes for studying the coherent evolution of optically excited ensemble of trions which are localized in semiconductor CdTe/CdMgTe quantum well. Application of transverse magnetic field leads to the Larmor precession of the resident electron spins, which shuffles optically induced polarization between optically accessible and inaccessible states. This results in several spectacular phenomena. First, magnetic field induces oscillations of spontaneous photon echo amplitude. Second, in three-pulse excitation scheme, the photon echo decay is extended by several orders of magnitude. In this study, short-lived optical excitation which is created by the first pulse is coherently transferred into a long-lived electron spin state using the second optical pulse. This coherent spin state of electron ensemble persists much longer than any optical excitation in the system, preserving information on initial optical field, which can be retrieved as a photon echo by means of third optical pulse.
Multi-objective optimization for AGV energy efficient scheduling problem with customer satisfaction

In recent years, it has been gradually recognized that efficient scheduling of automated guided vehicles (AGVs) can help companies find the balance between energy consumption and workstation satisfaction. Therefore, the energy consumption of AGVs for the manufacturing environment and the AGV energy efficient scheduling problem with customer satisfaction (AGVEESC) in a flexible manufacturing system are investigated. A new multi-objective non-linear programming model is developed to minimize energy consumption while maximizing workstation satisfaction by optimizing the pick-up and delivery processes of the AGV for material handling. Through the introduction of auxiliary variables, the model is linearized. Then, an interactive fuzzy programming approach is developed to obtain a compromise solution by constructing a membership function for two conflicting objectives. The experimental results show that a good level of energy consumption and workstation satisfaction can be achieved through the proposed model and algorithm.
General Version of Gauss-type Proximal Point Method and Its Uniform Convergence Analysis for Metrically Regular Mappings

We study the uniform convergence of the general version of Gauss-type proximal point algorithm (GG-PPA), introduced by Alom et al. [Alom et al. (2016)], for solving the parametric generalized equations y ∈ T (x), where T : X ⇒ 2 is a set-valued mapping with locally closed graph, y is a parameter, and X and Y are Banach spaces. In particular, we establish the uniform convergence of the GG-PPA by considering a sequence of Lipschitz continuous functions gk : X → Y with gk(0) = 0 and positive Lipschitz constants λk in the sense that it is stable under small perturbations when T is metrically regular at a given point. In addition, we give a numerical example to justify the uniform convergence of the GG-PPA.
Multiple Analysis of Remarks of Elderly and Disabled People by Text Mining

: This paper describes a method to analyze needs from the remarks of elderly and disabled people by using two text mining systems, which are the concept graph system and matrix search system. First, we collected 2,409 remarks about products and services from 19 people. Next, we transformed remarks with meaningful content into an evaluation record with ten aspects, and made 680 evaluation records. The two text mining systems analyze evaluation records in which an input keyword is used in a manner similar to search engines. The concept graph system visualizes a hierarchy of feature words in the records. We can understand important words and their relations in the records before we read the records. The matrix search system displays a matrix of the distribution of clustering from two aspects of the records. We can understand the relation of two aspects in the records by combining various aspects. The two systems achieve multiple and dialogical analysis of evaluation records. Therefore, the systems enable us to examine various problems that we choose to target. In experiments, we made an analysis of the records by combining the results of the two text mining systems.
Investigating the Mechanism of Scutellariae barbata Herba in the Treatment of Gastric Cancer by Network Pharmacology and Molecular Docking

Gastric cancer is one of the most common gastrointestinal tumors, annually accounting for about 10 % of all diagnosed cancers and cancer mortalities worldwide. Scutellariae barbata Herba is one of the most commonly used Chinese medicines to treat gastric cancer. Although numerous experiments have been conducted to decipher the mechanism of Scutellariae barbata Herba, it has not been fully elucidated. Therefore, we constructed a pharmacological and molecular docking network to understand the mechanism of action of Scutellariae barbata Herba. The active components and targets of Scutellariae barbata Herba were screened with traditional Chinese medicine systems pharmacology. Gastric cancer related targets were screened using online mendelian inheritance in man and GeneCards Suite database platforms. The intersection target genes of Scutellariae barbata Herba and gastric cancer were retrieved by R software. The Cytoscape software was utilized to draw a drug-compound gene-disease visualization network diagram. The string online analysis platform was incorporated to construct the target-protein interaction network for screening the core targets. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were performed on the core targets. PyMoL and other software were utilized to verify the molecular docking between the key active components of Scutellariae barbata Herba and the key targets. Our results elucidate the active components, associated targets, biological processes and signaling pathways of Scutellariae barbata Herba during gastric cancer treatment. This study deepens our understanding of the potential role of Scutellariae barbata Herba in gastric cancer and provides novel ideas for treating gastric cancer using Scutellariae barbata Herba.
Spontaneous emission intensity and anisotropy of quantum dot films in proximity to nanoscale photonic–plasmonic templates

We discuss results on spontaneous emission intensity and lifetime anisotropy of cadmium selenide quantum dot monolayer films placed in close proximity to a porous block copolymer based photonic–plasmonic two dimensional array. The porous block copolymer cylinders can be filled with metal nanoparticles and the concentration of these nanoparticles is varied to control both the photoluminescence intensity and lifetime of a layer of quantum dots placed above the template. Significant emission enhancement is achieved even for the quantum dot layer whose core lies about 1 nm above the template surface. Interestingly, polarised decay lifetime analysis indicates considerable emission anisotropy, as well for these quantum dots. Our results thus demonstrates how such hybrid optical materials can be created with controlled optical properties and suggests extension of this method to other novel two dimensional materials in combination with the photonic–plasmonic template.
Searches for the Anomalous Photon Polarisation in Radiative B Decays at LHCb

This thesis is exploring the measurements of the photon polarisation in radiative $B$ decays at LHCb, which are mediated through $b\to s\gamma$ transitions. To ensure optimal physics performance, procedures to align the LHCb detector and to monitor the alignment quality over time are presented. Using data corresponding to an integrated luminosity of $3 \text{fb}^{-1}$, collected in the year of 2011 at the centre-of-energy $\sqrt{s} = 7$ TeV and the year of 2012 at $\sqrt{s} = 8$ TeV in proton-proton collisions, the photon polarisation parameter $A^\Delta$, which is related to the ratio of right- over left-handed photon polarisation amplitudes in $b\to s\gamma$ transitions, is measured by performing an untagged time-dependent analysis of more than $4000$ $B_s^0\to \phi\gamma$ decays. From an unbinned simultaneous fit to the $B_s^0\to\phi\gamma$ and the control channel $B^0\to{K^*}^0\gamma$ data samples, a value of $A^\Delta = -0.98^{ +0.46}_{ -0.52}\text{(stat.)}^{ +0.23}_{ -0.20}\text{(syst.)}$ is measured. This result is compatible with the SM expectation of $A^\Delta_\text{SM} = 0.047^{ +0.029}_{ -0.025}$, within two standard deviations. Furthermore, a study of the feasibility of measuring the photon polarisation in $B^+\to\phi K^+ \gamma$ decays is performed. Background from $B^+\to K^+K^+K^-\pi^0$ decays form the main experimental difficulty for the selection of signal candidates when the calorimetric photons are used for decay reconstruction, but fitting the $\gamma/\pi^0$ separation variable can disentangle effectively the signal from these backgrounds. About $1400$ signal $B^+\to \phi K^+ \gamma$ decay candidates are reconstructed. No clear evidence of resonances in the $\phi K^+$-system is found, thus, the chance of measuring the photon polarisation in this decay is slim. When using converted photons, their good momentum resolution allows the $B$ mass to act as a good discriminating variable to separate signal from $B^+\to K^+K^+K^-\pi^0$ decays. In this case, $53\pm17$ signal candidates are found, where the uncertainty is purely statistical. This result is consistent with the expected number of signal events when correcting the yield obtained from calorimetric photons with the photon conversion rate, the reconstruction efficiency and the $K^+K^-$ mass range. In addition, the direct $CP$ asymmetry in the $B^+\to \phi K^+ \gamma$ decay amplitudes is measured to be $A_{CP} (B^+\to \phi K^+ \gamma) = (1.6\pm2.1\text{(stat.)}\pm0.7\text{(syst.)})%$. This value is consistent with the SM prediction of $-(0.1-1)%$.
Improved deep face identification with multi-class pairwise discriminant loss

A novel method to extract discriminative deep feature representations of facial images for face identification is presented. A new ‘multi-class pairwise discriminant loss’ is devised and incorporated it into the general deep convolutional neural network learning framework in a novel way, leading to highly discriminative deep face features. The method shows significant improvement over existing deep feature extraction techniques relying on softmax or triplet loss. Moreover, the method achieves a level of accuracy on the widely used identification protocols, which are better and comparable results than other state-of-the-art methods.
Migration and Socio-Cultural Adaptation of Bugis Ethnic Migrants in Palu City

The aims of this study were 1) to find out about the migration process of the Bugis ethnic group to Palu City, to explain the driving factors in the area of ​​origin of South Sulawesi, the pull factors in the destination area of ​​Palu City as well as the inhibiting factors and barriers to migrating to Palu City. 2) Knowing about social interactions and socio-cultural adaptations of the Bugis ethnic in Palu City. The method used is a qualitative approach involving 8 informants. The results showed that: Migration of the Bugis Ethnic to Palu City was motivated by economic factors due to limited job opportunities and increasingly competitive life along with population growth in the area of ​​origin of South Sulawesi. The factor of "siri" cultural values, past conflicts and political upheavals also contributed to the migration of the Bugis Ethnic to Palu City. The swift flow of migration of the Bugis Ethnic to Palu City has an impact on social relations, both associative and dissociative which automatically forces Bugis migrants to be more adaptive to the surrounding social environment, therefore, the cultural values ​​possessed by the Bugis Ethnic are internalized in his life is expected to become a social glue in social interaction in the overseas area of ​​Palu City.
Shooting Posture Correction System Based on Deep Learning

: In view of the lack of effective guidance when people practice shooting posture at home, I designed this model. By importing the video captured by the camera into the model, the model will track the athletes' shoulder, elbow, wrist and other key points in the video, and then calculate the bending Angle of the elbow, and finally judge whether the athletes' shooting posture is standard. The experiment proves that this model has reached the expected goal.
Learning color names using least-squares probabilistic classifiers

Color name is one of the important features for computer vision. Many existing methods proposed to classify colors into a small number of color names. In this paper, we propose an alternative method with the goal to improve the accuracy for assigning a color name to an object in the given image. We here use the least-squares probabilistic classifiers (LSPC) with the local scaling parameters for solving this task. The benefit of the LSPC is that its solution can be computed analytically so that the obtained solution is global optimum, while the local scaling parameters play an important role to deal with the data including clusters with different local statistics as appeared in the real-world data. To deal with this task, the LSPC is learned to assign a color name to each pixel with the highest of the class-posterior density distribution. Then, the estimations of the class-posterior density distributions are utilized to compute the scores for predicting a color name to the given object. Lastly, the color name with the highest score is chosen as a predicted color name for that object. The experimental results on the eBay data set show the improvements over previously proposedmethods.
Numerical Solution of Time-Fractional Order Telegraph Equation by Bernstein Polynomials Operational Matrices

We present a new method to solve time-fractional order telegraph equation (TFOTE) by using Bernstein polynomials. By implementation of Bernstein polynomials operational matrices of fractional differential on TFOTE, we reduce the original problem to a linear system of algebraic equations. Also, we prove the convergence analysis. In order to show the efficiency of the proposed method, we present two numerical examples.
Additive manufacturing of promising heterostructure for biomedical applications

As a new generation of materials/structures, heterostructure is characterized by heterogeneous zones with dramatically different mechanical, physical or chemical properties. This endows heterostructure with unique interfaces, robust architectures, and synergistic effects, making it a promising option as advanced biomaterials for the highly variable anatomy and complex functionalities of individual patients. However, the main challenges of developing heterostructure lie in the control of crystal/phase evolution and the distribution/fraction of components and structures. In recent years, additive manufacturing techniques have attracted increasing attention in developing heterostructure due to the unique flexibility in tailored structures and synthetic multimaterials. This review focuses on the additive manufacturing of heterostructure for biomedical applications. The structural features and functional mechanisms of heterostructure are summarized. The typical material systems of heterostructure, mainly including metals, polymers, ceramics, and their composites, are presented. And the resulting synergistic effects on multiple properties are also systematically discussed in terms of mechanical, biocompatible, biodegradable, antibacterial, biosensitive and magnetostrictive properties. Next, this work outlines the research progress of additive manufacturing employed in developing heterostructure from the aspects of advantages, processes, properties, and applications. This review also highlights the prospective utilization of heterostructure in biomedical fields, with particular attention to bioscaffolds, vasculatures, biosensors and biodetections. Finally, future research directions and breakthroughs of heterostructure are prospected with focus on their more prospective applications in infection prevention and drug delivery.
Geometric construction of the action for pure supergravity coupled to Wess-Zumino multiplets

In this article we build "step-by-step" the complete Lagrangian relative to the coupling of the scalar multiplets, or Wess-Zumino multiplets, with the action of pure D = 4, N = 1 supergravity. We follow the so-called "geometric approach", i.e. using the concepts of supersymmetry, superspace, rheonomic principle and considering all fields as superforms in superspace.