Miracle-dz/UniFAR-FTUs huggingface dataset:
LGCNet: Feature Enhancement and Consistency Learning Based on Local and Global Coherence Network for Correspondence Selection

Correspondence selection, a crucial step in many computer vision tasks, aims to distinguish between inliers and outliers from putative correspondences. The coherence of correspondences is often used for predicting inlier probability, but it is difficult for neural networks to extract coherence contexts based only on quadruple coordinates. To overcome this difficulty, we propose enhancing the preliminary features using local and global handcrafted coherent characteristics before model learning, which strengthens the discrimination of each correspondence and guides the model to prune obvious outliers. Furthermore, to fully utilize local information, neighbors are searched in coordinate space as well as feature space. These two kinds of neighbors provide complementary and plentiful contexts for inlier probability prediction. Finally, a novel neighbor representation and a fusion architecture are proposed to retain detailed features. Experiments demonstrate that our method achieves state-of-the-art performance on relative camera pose estimation and correspondence selection metrics on the outdoor YFCC100M [1] and the indoor SUN3D [2] datasets.
STEV: Stretchable Triboelectric E-skin enabled Proprioceptive Vibration Sensing for Soft Robot

Vibration perception is essential for robotic sensing and dynamic control. Nevertheless, due to the rigorous demand for sensor conformability and stretchability, enabling soft robots with proprioceptive vibration sensing remains challenging. This paper proposes a novel liquid metal-based stretchable e-skin via a kirigami-inspired design to enable soft robot proprioceptive vibration sensing. The e-skin is fabricated into 0.1mm ultrathin thickness, ensuring its negligible influence on the overall stiffness of the soft robot. Moreover, the working mechanism of the e-skin is based on the ubiquitous triboelectrification effect, which transduces mechanical stimuli without external power supply. To demonstrate the practicability of the e-skin, we built a soft gripper consisting of three soft robotic fingers with proprioceptive vibration sensing. Our experiment shows that the gripper can accurately distinguish the grain category (six grains with the same mass, 99.9% accuracy) and the packaging quality (100% accuracy) by simply shaking the gripped bottle. In summary, a soft robotic proprioceptive vibration sensing solution is proposed; it helps soft robots to have a more comprehensive awareness of their self-state and may inspire further research on soft robotics.
Diagnosis of Alzheimer’s disease and Mild Cognitive Impairment using Rethinking and Deep Neural Networks

The early diagnosis of Alzheimer’s Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), are important for doctors to treat patients as soon as possible. In this paper we focus exclusively on the use of EEG for the Machine Learning based diagnosis of MCI and AD. The choice of EEG is made because this modality is relatively inexpensive, non-invasive and easily available even outside the clinical environment. Unlike the majority of ML algorithms for AD diagnosis which treat EEG as an 1-D signal we propose a 2-D approach. We first split the EEG channel signals into fixed length segments and then we reshape them into 2-D images used to train a powerful VGG-16 deep Convolutional Neural Network model. In order to improve the performance of the VGG-16 model and avoid overfitting, we employed a powerful pruning method called Rethinking.We study two experimental tasks: (a) classifying segments into AD/MCI or Health Control (HC) categories (b) classifying subjects (patients and healthy individuals) into the same categories. Our results showed that the proposed method can be used as a tool to diagnose AD at early stages with accuracy over 98.8.
Subspace Method for Generalized Controller Synthesis: An Artificial Potential Field Motion Planning Approach

This paper integrates concepts from the frequency domain control methods, state space control and robot motion planning to produce a flexible control synthesis approach that is applicable to a wide class of dynamical systems. The method views a system's frequency response as a trajectory in the complex plane that is evolving under the influence of an artificial force to satisfy a geometric stability-performance criterion. A nonlinear subspace approach is used to translate these forces into an equivalent state space dynamical system that governs the dynamics of the parameters of the compensator used to generate the control signal. The design method places no restrictions on the order of the compensator or geometry of the frequency domain criterion. The approach is developed and a proof of its ability to converge, if a solution exists, to the tuning parameters set that satisfies the desired conditions is provided. The paper provides a set of design examples to demonstrate its applicability to different types of linear, nonlinear, SISO and MIMO systems.
Super-resolution Localization of Moving Target Based on Improved Compressive Sensing Algorithm

Aiming at the localization problem of moving targets in two-dimensional planar scenes, this paper proposes an improved compressive sensing algorithm for the super-resolution localization of moving targets. Firstly, a multi-target location model is presented in a moving scene according to the detection principle of frequency-modulated continuous wave radar (FMCW) and the fast Fourier transform (FFT) method. Then, considering the data characteristics of the IF signal group, the multiple target location problem is transformed into optimization problems such as sparse signal recovery and reconstruction by adopting compressive sensing theory (CS). A free-grid compressive sensing algorithm is also designed to avoid grid mismatch and improve positioning accuracy. On this basis, the particle swarm optimization (PSO) algorithm is applied to optimize the target’s direction of arrival information (DOA), further reducing the algorithm’s complexity and ensuring the solution’s existence and optimization. Finally, the numerical simulation results show that the proposed algorithm has high positioning accuracy and good real-time performance, which can achieve cooperative super-resolution positioning for multiple moving targets.
Scintillation recording and playback in free-space optical links

Abstract. The performance of a free-space optical (FSO) communication system is strongly affected by optical scintillation. Scintillation fades can cause errors when the power on a detector falls below its noise floor while surges can overload a detector. The very long time scale of scintillation compared to a typical bit in an FSO link means that error-correcting protocols designed for fiber optic links are inappropriate for FSO links. Comparing the performance effects of different components, such as photodetectors or protocols, such as forward error correction, in the field is difficult because conditions are constantly changing. On the other hand, laboratory-based turbulence simulators may not really simulate the effects of long-range propagation through the atmosphere. We have investigated a different approach. Scintillation has been measured during field tests using FSO terminals by sending a continuous wave beam through the atmosphere. A high dynamic range photodetector was digitized at a 5-KHz rate and files of the intensity variations were saved. Many hours of scintillation data under different environmental conditions and at different sites have been combined into a library of data. A fiber-optic-based scintillation playback system was then used in the laboratory to test modems and protocols with the recorded irradiance files. This enabled comparisons using the same atmospheric conditions allowing optimization of such parameters as detector dynamic range. It also allowed comparison and optimization of different error correcting protocols.
Inclusive Leadership and Workplace Deviant Behavior: The Role of Organizational Ethics climate and Moral Disengagement

In order to investigate the potential relationship between inclusive leadership and workplace deviant behavior of employees, and the boundary conditions of the influence of inclusive leadership on workplace deviant behavior of employees, managers and their direct subordinates were investigated. The results show that inclusive leadership is positively correlated with moral disengagement and workplace deviant behavior. The organizational ethical climate is lower, the stronger the positive effect of inclusive leadership on moral disengagement and workplace deviant behavior.
Numerical study of the Bessel beams carrying optical vortices propagating in turbulent atmosphere

In this paper, the aperture averaged scintillations of the Bessel beams carrying optical vortices propagating in turbulent atmosphere are evaluated. The multistep form of the propagation algorithm and a numerical phase screen simulation method are applied to the calculations of the aperture averaged scintillation. The results show that the Bessel beam with more topological charges delivers the smaller scintillation. The relation between the aperture averaged scintillation and the size of the beams is investigated. The effect of inner and outer scales of turbulence on the scintillations of the Bessel beams is also studied. These results may be useful in long-distance optical communications in free space or in turbulent atmosphere.
Closedness of convex sets in Orlicz spaces with applications to dual representation of risk measures

Let $(\Phi,\Psi)$ be a conjugate pair of Orlicz functions. A set in the Orlicz space $L^\Phi$ is said to be order closed if it is closed with respect to dominated convergence of sequences of functions. A well known problem arising from the theory of risk measures in financial mathematics asks whether order closedness of a convex set in $L^\Phi$ characterizes closedness with respect to the topology $\sigma(L^\Phi,L^\Psi)$. (See [26, p.3585].) In this paper, we show that for a norm bounded convex set in $L^\Phi$, order closedness and $\sigma(L^\Phi,L^\Psi)$-closedness are indeed equivalent. In general, however, coincidence of order closedness and $\sigma(L^\Phi,L^\Psi)$-closedness of convex sets in $L^\Phi$ is equivalent to the validity of the Krein-Smulian Theorem for the topology $\sigma(L^\Phi,L^\Psi)$; that is, a convex set is $\sigma(L^\Phi,L^\Psi)$-closed if and only if it is closed with respect to the bounded-$\sigma(L^\Phi,L^\Psi)$ topology. As a result, we show that order closedness and $\sigma(L^\Phi,L^\Psi)$-closedness of convex sets in $L^\Phi$ are equivalent if and only if either $\Phi$ or $\Psi$ satisfies the $\Delta_2$-condition. Using this, we prove the surprising result that: \emph{If (and only if) $\Phi$ and $\Psi$ both fail the $\Delta_2$-condition, then there exists a coherent risk measure on $L^\Phi$ that has the Fatou property but fails the Fenchel-Moreau dual representation with respect to the dual pair $(L^\Phi, L^\Psi)$}. A similar analysis is carried out for the dual pair of Orlicz hearts $(H^\Phi,H^\Psi)$.
Predicting Pilot-in-training Success and Persistence in a United States University

Commercial pilot numbers have been on a decline since 2009, while in parallel, pilot demands continue to rise. In order to close the gap, airlines and companies need a steady stream of pilots-in-training who have successfully graduated. However, collegiate flight training programs have had issues with low retention and low success rates of pilots-in-training. The need to understand how to retain students within collegiate flight programs and increase success rates is vital to fill the gaps present within the aviation industry. Past studies have investigated predictive factors for pilots-in-training graduation persistence and the time it takes to graduate yielding similar findings. Many factors have been identified as related to pilot-in-training success and persistence, the most common being high school GPA and cost. However, suggestions have been presented as variables of interest to examine for future studies, such as the effect of different types of flight postponements. The research study conducted expanded the knowledge regarding variables that predict or contribute to pilot-in-training success in a collegiate aviation flight degree program, examining graduation persistence and time to graduate. An archival data of 262 pilot-in-training students were used to explore the relationship between the 19 predictors, graduation persistence, and time to graduate. Several variables had significant relationships with both Time to Graduate and Persistence Before Dropout, including Age, Number of Transfer Credits, Class Load, and Pass Rates in Aeronautics Classes. Additionally, Time to Graduate had a significant relationship with Academic Success in Aeronautics Classes and Maintenance Postponements per Semester. Persistence Before Dropout had a significant relationship with Instructor Changes, Instructor Postponements, and Weather Postponements.
Teacher Educators’ Culturally Sustaining Pedagogy and Activism in Practice: A Multi-Institutional Collaborative Self-Study

Rooted in critical pedagogy and situated learning theory, this collaborative self-study examined how six teacher educators from different institutions worked to improve their culturally sustaining pedagogy (CSP) and activism practice. Data sources included participants’ weekly journals, critical friends’ feedback, and field notes and audio-video recordings of virtual meetings. Through constant-comparative analysis, three major themes emerged: we engaged in recursive cycles of (re)conceptualizations of CSP and activism, our evolving conceptualizations (re)shaped our practice, and we built a communal responsibility-a deep seated commitment to the success of all group members. This study suggests collaborative critical reflection on CSP and activism is beneficial to practitioners, including teacher educators.
CHALLENGING SOME CONTEMPORARY VIEWS OF CORONAL MASS EJECTIONS. II. THE CASE FOR ABSENT FILAMENTS

When a coronal mass ejection (CME) appears in a coronagraph it often exhibits three parts. This “classic” three-part configuration consists of a bright leading edge, a dark circular- or teardrop-shaped cavity, and a bright core within the cavity. It is generally accepted that these are manifestations of coronal plasma pileup, the driving magnetic flux rope, and the associated eruptive filament, respectively. The latter has become accepted by the community since coronagraph CMEs have been commonly associated with eruptive filaments for over 40 years. In this second part of our series challenging views on CMEs, we present the case that the inner core of the three-part coronagraph CME may not be, and in the most common cases is not, a filament. We present our case in the form of four exhibits showing that most of the CMEs in a broad survey are not associated with an eruptive filament at the Sun, and that the cores of those CMEs that are filament-associated do not geometrically resemble or consist of material from the associated filament. We conclude with a discussion on the possible causes of the bright CME core and what happens to the filament material postlaunch. We discuss how the CME core could arise spontaneously from the eruption of a flux rope from the Sun, or could be the result of a mathematical caustic produced by the geometric projection of a twisted flux rope.
The Effect of Breast Massage Training on Self-Efficacy and Perceived Stress of Prim Parous Women: A Clinical Trial Study

Background: Breastfeeding is a highly efficacious, health-promoting activity that prevents many disorders and diseases. Successful breastfeeding depends on various maternal physiological and psychological factors, among which breastfeeding self-efficacy is an adjustable framework. This study investigates the effect of breast massage training on self-efficacy and perceived stress in primiparous women. Materials and Methods: This study is a clinical trial study on 132 eligible primiparous mothers referred to Bahar Hospital from August 15, 2019, to December 15, 2020. The women were randomly divided into intervention and control groups. The massage was performed in the intervention group before breastfeeding. The data were collected using a standard breastfeeding self-efficacy questionnaire and the Sheldon Perceived Standard Questionnaire. Data were entered into SPSS 18 and analyzed using descriptive statistics, Chi-square, and analysis of variance. Results: The results of this study showed that the mean (SD) breastfeeding self-efficacy in the breast massage training group with direct midwife involvement was 61.63 (9.21), higher than the one in the control group 51.51 (11.62). In addition, perceived stress was 19.81 in the intervention group and 24.84 in the control group, which was also statistically significant. Conclusions: Due to the increase in self-efficacy scores and decrease in stress scores after breast massage, this method can improve breastfeeding performance in women. Therefore, educational strategies should be developed in this area.
External oblique muscle plane blocks in combination with modified thoracoabdominal nerves block through perichondrial approach for analgesia in abdominal surgery: A case report

The costal and lateral external oblique muscle plane (EXOP) blocks anesthetize the lateral cutaneous branches, whereas the modified thoracoabdominal nerves block through perichondrial approach (M-TAPA) anesthetizes the anterior branches of the thoracoabdominal nerves. Herein, we report two cases of successful perioperative pain management with the combination of these blocks: case 1 was a 67-year-old man who underwent open cholecystectomy and case 2 was a 38-year-old woman who underwent emergency laparoscopic surgery for strangulation ileus. Both patients were administered the costal and/or lateral EXOP blocks along with bilateral M-TAPA for perioperative analgesia. A pin-prick test performed 1 h after surgery revealed that the cutaneous sensory block covered all areas of the abdominal surgical field. Combined use of these blocks can be a new local analgesic strategy for abdominal surgery.
The logic and linguistic model for automatic extraction of collocation similarity

The article discusses the process of automatic identification of collocation similarity. The semantic analysis is one of the most advanced as well as the most difficult NLP task. The main problem of semantic processing is the determination of polysemy and synonymy of linguistic units. In addition, the task becomes complicated in case of word collocations. The paper suggests a logical and linguistic model for automatic determining semantic similarity between colocations in Ukraine and English languages. The proposed model formalizes semantic equivalence of collocations by means of semantic and grammatical characteristics of collocates. The basic idea of this approach is that morphological, syntactic and semantic characteristics of lexical units are to be taken into account for the identification of collocation similarity. Basic mathematical means of our model are logical-algebraic equations of the finite predicates algebra. Verb-noun and noun-adjective collocations in Ukrainian and English languages consist of words belonged to main parts of speech. These collocations are examined in the model. The model allows extracting semantically equivalent collocations from semi-structured and non-structured texts. Implementations of the model will allow to automatically recognize semantically equivalent collocations. Usage of the model allows increasing the effectiveness of natural language processing tasks such as information extraction, ontology generation, sentiment analysis and some others.
The Effect of an Educational Intervention Based on Protection Motivation Theory on Pregnant Women’s Knowledge and Self-Protection Regarding COVID-19. An Intervention Study

Background: COVID-19 infection endangers pregnant women and newborns. Infection prevention measures are available and easy to apply, but the problem is the application continuity. Empowering pregnant women to increase their intention for self-protection is very important. This study explores the effect of educational intervention based on the Protection Motivation Theory (PMT) on pregnant women's knowledge and self-protection regarding COVID-19. Materials and Methods: A randomized, controlled trial was conducted at the Obstetrics and Gynecology outpatient clinic at El Shatby Hospital, Alexandria governorate/Egypt, from November 2020 to May 2021. The study included a convenient sample of 163 pregnant women using the randomization block technique. A self-reported questionnaire was used for data collection. For the intervention group, the PMT-based education included need assessment, planning, implementation, and evaluation. Two months later, a reevaluation was done. Results: ANCOVA showed a significant improvement in the intervention group's knowledge (F1 = 8.56, p < 0.001) when taking the pretest as a reference. The effect size shows that 25.8% of the intervention group's knowledge improvement and 58.80% of the difference between the two groups were due to intervention. ANCOVA showed a significant improvement in the intervention group's PMT constructs when taking the pretest or group as a reference (p <0.001). The effect size shows that 56.10% of the intervention group's total PMT constructs improvement and 89.60% of the differences between the two groups were due to the intervention. Conclusions: PMT-based intervention is effective in improving pregnant women's knowledge and self-protection intention regarding COVID-19. PMT is recommended to tailor educational intervention for pregnant women.
Collaborative Tasks in Immersive Virtual Reality Increase Learning

: Advances in immersive virtual reality (IVR) are creating more computer-supported collaborative learning environments, but there is little research explicating how collaboration in IVR impacts learning. We ran a quasi-experimental study with 80 participants targeting ocean literacy learning, varying the manner in which participants interacted in IVR to investigate how the design of collaborative IVR experiences influences learning. Results are discussed through the lens of collaborative cognitive learning theory. Participants that collaborated to actively build a new environment in IVR scored higher for learning than participants who only watched an instructional guide’s avatar, or participants who watched the guide’s avatar and subsequently discussed what they learned while in IVR. Moreover, feeling negative emotions, feeling active in the environment, and feeling bonded to the group members negatively correlated with learning. Results shed light on the mechanisms behind how collaborative tasks in IVR can support learning.