Space Mapping Research Articles

In Situ X-Ray Study During Thermal Cycle Treatment Combined with Complementary Ex Situ Investigation of InGaN Quantum Wells.

In situ X-ray reciprocal space mapping was performed during the interval heating and cooling of InGaN/GaN quantum wells (QWs) grown via metal-organic vapor phase epitaxy (MOVPE). Our detailed in situ X-ray analysis enabled us to track changes in the peak intensities and radial and angular broadenings of the reflection. By simulating the radial diffraction profiles recorded during the thermal cycle treatment, we demonstrate the presence of indium concentration distributions (ICDs) in the different QWs of the heterostructure (1. QW, bottom, 2. QW, middle, and 3. QW, upper). During the heating process, we found that the homogenization of the QWs occurred in the temperature range of 850 °C to 920 °C, manifesting in a reduction in ICDs in the QWs. Furthermore, there is a critical temperature (T = 940 °C) at which the mean value of the indium concentration starts to decrease below 15% in 1. QW, indicating the initiation of decomposition in 1. QW. Moreover, further heating up to 1000 °C results in extended diffuse scattering along the angular direction of the diffraction spot, confirming the propagation of the decomposition and the formation of trapezoidal objects, which contain voids and amorphous materials (In-Ga). Heating InGaN QWs up to T = 1000 °C led to a simultaneous decrease in the indium content and ICDs. During the cooling phase, there was no significant variation in the indium concentrations in the different QWs but rather an increase in the defect area, which contributes to the amplification of diffuse scattering. A comparison of ex situ complementary high-resolution transmission microscopy (Ex-HRTEM) measurements performed at room temperature before and after the thermal cycle treatment provides proof of the formation of four different types of defects in the QWs, which result from the decomposition of 1. QW during the heating phase. This, in turn, has strongly influenced the intensity of the photoluminescence emission spectra without any detectable shift in the emission wavelength λMQWs.

Fixed Point Results for Contractive Mappings in F-metric Space

Fixed Point Results for Contractive Mappings in F-metric Space

Solving split equality fixed point problem of generalized demimetric mapping and certain optimization problem via dynamic step-size technique

In this article, we study the split equality problem of certain optimization problem in real Hilbert spaces. We propose a new viscosity iterative algorithm for approximating solution for finite families of split equality variational inequality and split equality fixed point problems of generalized demi metric mapping in real Hilbert spaces. Using our iterative method, we establish a strong convergence result for finding a common element for finite families of variational inequality and fixed point problems of generalized demimetric mapping. We present some consequences and application to the convex minimization problem to validate our main result. Our result complements and generalizes some related results in literature.

Regularities of the theory of quasi-geodesic mappings of special parabolic spaces

We study quasi-geodesic mappings (QGM) of generalized-recurrent-parabolic spaces f: (Vn, gij, Fih) → (V'n, g'ij, Fih). QGM can be of two types: general and canonical. This article examines the QGM of the general type. Earlier, we considered the fundamental questions of the theory of QGM of generalized-recurrent-parabolic spaces. We proved theorems that allow for any generalized-recurrent-parabolic space (Vn, gij, Fih) to either find all spaces (V'n, g'_{ij}, Fih) on which Vn admits QGM of the general form, or prove that there are no such spaces. In this article, we constructed a Γ-transformation that makes it possible to obtain from a pair of generalized-recurrent-parabolic spaces that are in a quasi-geodesic mapping, an infinite sequence of pairs of other generalized-recurrent-parabolic spaces, which are also in a quasi-geodesic mapping.

Common fixed-point theorems on complex partial b- metric space

In this paper, we establish some unique common fixed-point theorems for two pairs of weakly compatible mappings in complex partial b-metric space which generalize and improves several well- known common fixed point results in partial b-metric space.

Infrared photoresponse of GeSiSn p-i-n photodiodes based on quantum dots, quantum wells, pseudomorphic and relaxed layers.

Structural and photoelectric properties of p-i-n photodiodes based on GeSiSn/Si multiple quantum dots both on Si and silicon-on-insulator (SOI) substrates were investigated. Elastic strained state of grown films was demonstrated by x-ray diffractometry. Annealing of p-i-n structures before the mesa fabrication can improve the ideality factor of current-voltage characteristics. The lowest dark current density of p-i-n photodiodes based on quantum dots at the reverse bias of 1 V reaches the value of 0.8 mA/cm2. The cutoff wavelength shifts to the long-wavelength region with the Sn content increase. Maximum cutoff wavelength value is found to be 2.6 μm. Moreover, multilayer periodic structures with GeSiSn/Ge quantum wells and GeSiSn relaxed layers on Ge substrates were obtained. Reciprocal space maps were used to study the strained state of GeSiSn layers. The optimal growth parameters were determined to obtain slightly relaxed GeSiSn layers. Designed p-i-n photodiodes based on these structures demonstrated the minimal dark current density of 0.7 mA/cm2 and the cutoff wavelength of about 2μm.

Benzoxazinone Derivatives as Antiplatelet: Synthesis, Molecular Docking, and Bleeding Time Evaluation

Background The recurrence of atherosclerosis is still a global problem. Unfortunately, the drugs currently being used are reported to have resistance. Purpose To prevent the recurrence of atherosclerosis disease, this study developed benzoxazinone derivatives as an antiplatelet agent: 2-phenyl-3,1-benzoxazine-4-one (BZ1) and 2-(4′-chlorophenyl)-3,1-benzoxazin-4-one (BZ2). Methods The target compounds were synthesized through acyl nucleophilic substitution from acyl chloride and anthranilic acid using a base catalyst in triethylamine. This compound was then given to mice at three different doses to perform bleeding-time and clotting-time tests, using acetosal as a comparison. In silico, the binding energy between the test compound and the cyclooxygenase 1 enzyme was tested using Molegro Virtual Docker version 5.5 (MVD 5.5). The pharmacokinetic parameters were predicted using pharmacokinetics and chemistry through space mapping (pkCSM). Results The synthesis provided 83% yield. The biological assay at a dose of 20 mg/kg body weight (BW) BZ1 showed a higher bleeding time (361 s) than acetosal (324 s), whereas BZ2 was lower (179 s). The molecular analysis revealed that the compound had higher activity than aspirin. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) showed that the compound posed high intestinal absorption. Conclusion This research concluded that both of the synthesized compounds have the potential and prospective to be developed as antiplatelet agents.

Infrared photoresponse of GeSiSn p-i-n photodiodes based on quantum dots, quantum wells, pseudomorphic and relaxed layers.

Structural and photoelectric properties of p-i-n photodiodes based on GeSiSn/Si multiple quantum dots both on Si and silicon-on-insulator (SOI) substrates were investigated. Elastic strained state of grown films was demonstrated by x-ray diffractometry. Annealing of p-i-n structures before the mesa fabrication can improve the ideality factor of current-voltage characteristics. The lowest dark current density of p-i-n photodiodes based on quantum dots at the reverse bias of 1 V reaches the value of 0.8 mA/cm2. The cutoff wavelength shifts to the long-wavelength region with the Sn content increase. Maximum cutoff wavelength value is found to be 2.6 μm. Moreover, multilayer periodic structures with GeSiSn/Ge quantum wells and GeSiSn relaxed layers on Ge substrates were obtained. Reciprocal space maps were used to study the strained state of GeSiSn layers. The optimal growth parameters were determined to obtain slightly relaxed GeSiSn layers. Designed p-i-n photodiodes based on these structures demonstrated the minimal dark current density of 0.7 mA/cm2 and the cutoff wavelength of about 2μm.

Ecological portraits: Mapping functional spectra and space characteristics of birds in China

Ecological portraits: Mapping functional spectra and space characteristics of birds in China

Activation Function-Assisted Objective Space Mapping to Enhance Evolutionary Algorithms for Large-Scale Many-Objective Optimization

Activation Function-Assisted Objective Space Mapping to Enhance Evolutionary Algorithms for Large-Scale Many-Objective Optimization

Normalizing flow-based latent space mapping for implicit pattern authentication on mobile devices

In numerous mobile device applications, safeguarding user privacy through authentication is of paramount importance. Traditional methods employ information-matching-based systems, wherein users authenticate themselves using preset passwords. However, such systems pose a challenge in maintaining privacy if the password is compromised. This study introduces a behavior-based authentication approach that capitalizes on implicit patterns generated by individual users’ device usage habits during password entry on mobile devices, complementing information-based authentication. To optimize this feature, we develop a user-specific latent space mapping framework utilizing a normalizing flow and train a one-class classification machine learning model based on the latent space to enhance authentication performance. Upon applying the proposed methodology to data from 1,000 mobile banking service users, we observed a significant improvement in authentication performance. The integrated error decreased from 21.42% to 9.48%, and the equal error rate reduced from 27.84% to 16.3% compared to the method solely employing a machine learning model in the data space without implementing latent space mapping.

Cognitive space mapping and its neural mechanisms

Cognitive space mapping and its neural mechanisms

“Memes as the Gusle of the 21st Century”: An Analysis of Memes About Gusle, Gusle Players and Gusle Practices on the Internet

Memes are nowadays both a simple digital form and one of the most prevalent, widely shared contents in the field of creative freedom and digital culture, observed in this case as part of the so-called “Cyber Folk Art”. This paper aims to analyze Internet memes about the gusle (one-stringed instrument) and gusle players, primarily found on social networks such as Instagram and Facebook or obtained via Google searches. Based on the collected (internet) sources and materials, different levels of identification, symbolism, communication and stereotypes, which already emerge as the first associations with gusle practices, can be discerned. The cultural and social contexts will be included in the analysis and interpretation of memes, i.e. comprehensive performances and depictions of ethnic, national, musical and personal foundations of certain historical and public figures from the political and gusle music world will be interpreted through memes – a combination of image, text, and/or videos. As is the case with other genres of Internet memes and musical genres and styles, the creation of content based on social needs, the writing of social space into musical space and vice versa, as well as the mapping of a symbolic space and stereotypes are evident in the presented and analyzed memes. It can be said that memes about gusle and gusle players, i.e. gusle practices, represent a kind of simplified form of communication in terms of the use of stereotypes and symbolism that indicate different levels of identification, which is the topic with potential for further and more detailed research.

An Inertial Subgradient Extragradient Method for Efficiently Solving Fixed-Point and Equilibrium Problems in Infinite Families of Demimetric Mappings

The primary objective of this article is to enhance the convergence rate of the extragradient method through the careful selection of inertial parameters and the design of a self-adaptive stepsize scheme. We propose an improved version of the extragradient method for approximating a common solution to pseudomonotone equilibrium and fixed-point problems that involve an infinite family of demimetric mappings in real Hilbert spaces. We establish that the iterative sequences generated by our proposed algorithms converge strongly under suitable conditions. These results substantiate the effectiveness of our approach in achieving convergence, marking a significant advancement in the extragradient method. Furthermore, we present several numerical tests to illustrate the practical efficiency of the proposed method, comparing these results with those from established methods to demonstrate the improved convergence rates and solution accuracy achieved through our approach.

On Existence of Fixed Points for Multivalued Contractive Type Mappings in Quasi-Metric Spaces

We present fixed point results for multivalued contractive type mappings via Q-function on quasi-metric spaces. Our main results supported with example. Consequently, our results either improve or generalize several known results of metric fixed point theory.

Generalized Wardowski type contractive mappings in b-metric spaces and some fixed point results with applications in optimization problem and modeling biological ecosystem.

In the realm of b-metric spaces, this study introduces a novel generalized Wardowski-type quasi-contraction, denoted as β-(θ, ϑ). We begin by applying this new contraction to derive standard fixed point results. Subsequently, we establish the existence of a generalized quasi-contraction of the Wardowski type, thereby validating the robustness of our findings. Specifically, we utilize Nadler's work to model biological ecosystems and apply our results to solve an optimization problem. To illustrate the practical implications and effectiveness of our approach, we provide a comparative analysis between our results and those of Nadler. This comprehensive study underscores the significance and utility of our generalized contraction in both theoretical and applied contexts.

Precise Tuning of Flexoelectricity in SrTiO3 by Ion Irradiation.

Flexoelectric coefficient is a tetradic and its introduction enables centrosymmetric materials to exhibit piezoelectricity. However, the flexoelectric paradigm currently lacks a strategy to effectively tune the strain gradient for optimal electro-mechanical coupling. This study proposes a quantized collision model accessible through ionic irradiation technology to explore the flexoelectricity and precisely modulate the strain gradient. The lattice strain is introduced in SrTiO3 (STO) single crystals and tuned broadly by irradiation with ions of He+, C+, and P+ at dose of 1×1014 and 2×1015 ioncm-2, respectively. Under C+ ion irradiation at a dose of 2×1015 ioncm-2, thin-film X-ray diffraction reveals a strain gradient up to ≈0.65% nm-1. The resulted polarization is found to orient out-of-plane, as observed through X-ray reciprocal space mapping and high-angle annular dark field scanning transmission electron microscopy. Piezoresponse force microscopy characterization reveals that the electric-induced out-of-plane polarization reversal emerges at room temperature, corresponding to a stain gradient ≈0.05% nm-1 in STO's flexoelectric response. This study demonstrates that ion irradiation is an effective strategy for precisely tuning the flexoelectric properties.

Reciprocal space mapping of ZnMgY face-centred icosahedral quasicrystals

The reciprocal lattice of face-centred icosahedral ZnMgY quasicrystals was investigated using X-ray diffractometry. A large-scale planar cut of the reciprocal ZnMgY lattice was recorded making use of a PIXcel area detector. The θ-2θ scans along the C5, C3 and C2 symmetry axes revealed numerous diffraction peaks with a large dynamical range of about 106. Low structure-factor diffraction peaks, corresponding to large complementary reciprocal lattice vectors g┴ up to g┴a = 24 (where a is the quasilattice constant), were observed, indicating a high structural quality of ZnMgY quasicrystals. A static linear phason strain was detected in one of the five investigated ZnMgY samples.

Some Results in Fixed Point Theorem using Weakly Compatible Mappings in Neutrosophic Metric Spaces

Neutrosophic metric space was introduced by Kirisci and Simsek in 2020. In this paper, the author introduced the concept of coupled fixed point, coupled coincidence point, common coupled fixed point. To define the above concept two mappings are used also, we prove some common fixed point using compatible and weakly compatible mappings in Neutrosophic metric space.

Towards Lightweight Super-Resolution With Dual Regression Learning.

Deep neural networks have exhibited remarkable performance in image super-resolution (SR) tasks by learning a mapping from low-resolution (LR) images to high-resolution (HR) images. However, the SR problem is typically an ill-posed problem and existing methods would come with several limitations. First, the possible mapping space of SR can be extremely large since there may exist many different HR images that can be super-resolved from the same LR image. As a result, it is hard to directly learn a promising SR mapping from such a large space. Second, it is often inevitable to develop very large models with extremely high computational cost to yield promising SR performance. In practice, one can use model compression techniques to obtain compact models by reducing model redundancy. Nevertheless, it is hard for existing model compression methods to accurately identify the redundant components due to the extremely large SR mapping space. To alleviate the first challenge, we propose a dual regression learning scheme to reduce the space of possible SR mappings. Specifically, in addition to the mapping from LR to HR images, we learn an additional dual regression mapping to estimate the downsampling kernel and reconstruct LR images. In this way, the dual mapping acts as a constraint to reduce the space of possible mappings. To address the second challenge, we propose a dual regression compression (DRC) method to reduce model redundancy in both layer-level and channel-level based on channel pruning. Specifically, we first develop a channel number search method that minimizes the dual regression loss to determine the redundancy of each layer. Given the searched channel numbers, we further exploit the dual regression manner to evaluate the importance of channels and prune the redundant ones. Extensive experiments show the effectiveness of our method in obtaining accurate and efficient SR models.