Miracle-dz/UniFAR-FTUs huggingface dataset:
Características psicométricas del ECR-R (Experiences in Close Relationships-Revised) en población ecuatoriana

El objetivo del presente estudio fue analizar las características psicométricas de la escala Experiences in Close Relationships-Revised (ECR-R) en jóvenes adultos ecuatorianos. Los participantes fueron 641 estudiantes universitarios de 20 a 25 años, provenientes de dos instituciones de educación superior de Quito, a quienes se les aplicó la prueba. Mediante la técnica de Análisis Factorial Confirmatorio se verificó que los resultados encontrados se ajustaban al modelo peruano del ECR-R. Por tanto, la versión ecuatoriana quedó conformada por los 27 ítems de la versión peruana, los cuales corresponden a las dos dimensiones originales de la escala: Ansiedad y Evitación, esta última constituida por dos factores, uno de ítems directos y otro de ítems inversos. Se encontró una confiabilidad adecuada de los factores de Ansiedad (α = .91; ω = .91), Evitación inversa (α = .90; ω = .89) y Evitación directa (α = .72; ω = .83).
Analysis of the light and radial velocity curves of transiting extra-solar planets

Abstract Several approaches have been followed for the analysis of the light curves of transiting extra-solar planets. From simple approximate algorithms and synthetic models to semi-analytical complete solutions. The different alternatives are discussed with their strengths and weaknesses. Analytical expressions can also provide a deeper insight into the main system parameters from the measurement of a few strategic points describing the shape of the light curve.
Fear of Cancer Recurrence in Patients with Sarcoma in the United Kingdom

Simple Summary After a cancer diagnosis, the fear that it could come back is one of the most difficult negative emotions to manage. Sarcoma is a rare cancer of connective tissue affecting soft tissue and bone that has a high rate of recurrence and metastases. It can present itself in any age group from childhood to older adulthood. The experience of fear of cancer recurrence has not yet been explored in-depth among those with sarcoma. We, therefore, conducted an online survey to identify the prevalence of fear of cancer recurrence and factors that may be associated with it. A total of 229 people with sarcoma submitted responses, and the majority expressed interest in receiving support for fear of cancer recurrence. Overall, fear of cancer recurrence levels was found to be higher than those reported by patients with most other types of cancer. Emotional distress and being able to manage emotions were associated with fear of cancer recurrence. Abstract Fear of cancer recurrence (FCR) is a persistent concern among those living with cancer and is associated with a variety of negative psychosocial outcomes. However, people with sarcoma have been underrepresented within this area of research. We aimed to determine the prevalence of FCR experienced by people with sarcoma in the United Kingdom and explore factors that may predict FCR, such as the perceived impact of cancer and psychological flexibility. Participants (n = 229) with soft tissue (n = 167), bone (n = 25), and gastrointestinal stromal tumours (n = 33) completed an online survey including the self-reported measures of FCR, the perceived physical and psychological impact of cancer and psychological flexibility, and demographic information. Data were analysed using ANOVA and multiple regression modelling. Mean FCR scores (M = 91.4; SD = 26.5) were higher than those reported in meta-analytic data inclusive of all cancer types (M = 65.2; SD = 28.2). Interest in receiving support for FCR was also high (70%). Significant factors associated with FCR included cognitive and emotional distress and psychological flexibility, but not perceptions of the physical impact of cancer (R2 = 0.56). The negative association between psychological flexibility and FCR suggests the potential benefit of intervention approaches which foster psychological flexibility, such as acceptance and commitment therapy.
Expected color variations of the gravitationally microlensed QSO 2237 + 0305

Typical light curves and the corresponding color curves are shown for the present model of QSO 2237 + 0305 A, the image that has been reported to vary. Probabilities are presented for color changes of certain amplitudes as functions of the observed magnitude changes for different intervals between the two observational epochs, different source sizes, and different source size ratios. It may be possible to find the ratio of the continuum source sizes in the two color bands, once a color change correlated with a continuum change is found.
Basiacuong tradition on social science learning in elementary school

Basiacuong tradition has a lot of meaning and is needed by researchers to inherit and study it for students. It is based on the essentialism philosophy including the main function of preservation and transmission of human tradition’s basic element. This study is carried out using qualitative, interpretive, literature review methods on the Basiacuong tradition based on essentialism philosophy. The study result indicates that there are systematical phases in applying the Basiacuong tradition in essentialism that shows the values transmitted to the students. Every phase in the Basiacuong tradition contains the rules of terminology transmission in terms of Pitatah Pititih, which contains moral values. The cultural values in the Basicuong tradition will be a concept to direct young generations or the students either in being behaved or acted in society, which can determine which one the good or bad one is in the social environment where the students are. The values in this tradition, Basiacuong, can be internalized and applied the moral values in Social Science learning for students. The presence of cultural integration or local wisdom in Social Science learning at school will produce the students’ moral values.
A Reinforcement Learning Based Grammatical Inference Algorithm Using Block-Based Delta Inverse Strategy

A resurgent interest for grammatical inference aka automaton learning has emerged in several intriguing areas of computer sciences such as machine learning, software engineering, robotics and internet of things. An automaton learning algorithm commonly uses queries to learn the regular grammar of a Deterministic Finite Automaton (DFA). These queries are posed to a Minimum Adequate Teacher (MAT) by the learner (Learning Algorithm). The membership and equivalence queries which the learning algorithm may pose, are often capable of having their answers provided by the MAT. The three main categories of learning algorithms are incremental, sequential, and complete learning algorithms. In the presence of a MAT, the time complexity of existing DFA learning algorithms is polynomial. Therefore, in some applications these algorithms may fail to learn the system. In this study, we have reduced the time complexity of DFA learning from polynomial to logarithmic form. For this, we propose an efficient complete DFA learning algorithm; the Block based DFA Learning through Inverse Query (BDLIQ) using block based delta inverse strategy, which is based on the idea of inverse queries that John Hopcroft introduced for state minimization of a DFA. The BDLIQ algorithm possess $O(\vert \Sigma \vert N.log N)$ complexity when a MAT is available. The MAT is also made capable of responding to inverse queries. We provide theoretical and empirical analysis of the proposed algorithm. Results show that our suggested approach for complete learning; BDLIQ algorithm, is more efficient than the ID algorithm in terms of time complexity.
Chloride, Sodium and Calcium Intake Are Associated with Mortality and Follow-Up Kidney Function in Critically Ill Patients Receiving Continuous Veno-Venous Hemodialysis—A Retrospective Study

Background: Studies on the association between solute, nutrition and fluid intakes and mortality and later kidney function in critically ill acute kidney injury (AKI) patients receiving continuous veno-venous hemodialysis (CVVHD) are scarce. Methods: Altogether, 471 consecutive critically ill AKI patients receiving CVVHD in the research intensive care unit (ICU) were recruited in this single-center, retrospective study. Results: The median age was 66 (58–74) years, and 138 (29.3%) were female. The 90-day and one-year mortalities were 221 (46.9%) and 251 (53.3%), respectively. After adjusting for age, sex, Acute Physiology and Chronic Health Evaluation II (APACHE) score, coronary artery disease, immunosuppression, ICU care duration, mechanical ventilation requirement, vasopressor requirement and study time period, the cumulative daily intake of potassium, chloride, sodium, phosphate, calcium, glucose, lipids and water was associated with one-year mortality in separate multivariable cox proportional hazards models. In a sensitivity analysis excluding patients who died within the first three days of ICU care, the daily intake of chloride (hazard ratio (HR) 1.001, confidence interval (CI) 95% 1.000–1.003, p = 0.032), sodium (HR 1.001, CI 95% 1.000–1.002, p = 0.031) and calcium (HR 1.129, CI 95% 1.025–1.243, p = 0.014) remained independently associated with mortality within one-year in the respective, similarly adjusted multivariable cox analyses. The cumulative daily intake of chloride, sodium, calcium and water was independently associated with the estimated glomerular filtration rate (eGFR) at 90 days follow-up in separate substantially adjusted multivariable cox proportional hazards models. Conclusion: The cumulative daily intake of chloride, sodium and calcium is associated with mortality and daily chloride, sodium, calcium and water intake is associated with follow-up eGFR in critically ill patients with CVVHD-treated AKI.
The impact of latent‐heat release on the hadley circulation

Non‐reversible latent‐heat release is introduced into a model of the zonally symmetric Hadley circulation. Including latent‐heat release does not increase the strength of the circulation when the heating is centred off the equator, in contrast with other studies. However, latent‐heat release does result in a reduction of the meridional extent of the ascent. The assumptions and simplifications made are discussed and compared with those in other simple models of the role of latent‐heat release in the low‐latitude axisymmetric circulation.
Building Height Reconstruction Based on Propagator and Generalized Maximum Entropy-TomoSAR

In recent years, the synthetic aperture radar tomography (TomoSAR) technique is becoming an increasingly hot research topic in the 3-D reconstruction of the structure of urban buildings. The robustness of the many advanced nonparametric spectral estimation methods in use is based on a high number of observations. This letter aims to evaluate the ability of the five nonparametric estimator techniques, including propagator, generalized maximum entropy (GME), minimum norm (MN), singular value decomposition (SVD), and Capon in the separation of scattering contributions with a small number of SAR images. The performance comparison of the employed algorithms is carried out on the simulated and real datasets. The study results show that the novel high-resolution propagator and GME estimators, respectively, based on the partitioning and extrapolation of the covariance matrix, can discriminate the number of scatterers in one azimuth-range resolution and satisfactorily prevent the appearance of undesirable sidelobes. The experimental results on real SAR images acquired by the TerraSAR-X satellite show the proposed propagator spectral estimation can significantly improve the 3-D building reconstruction in the urban environment. Also, the estimated height of the scatters using the propagator technique is similar to the data obtained from ground observations.
Research on Image Edge Detection Algorithm Based on CORDIC

Image edge extraction is the foundation of high-level image processing. In view of the characteristics of large amount of square root algorithm and difficult hardware implementation in traditional Canny edge detection, the CORDIC algorithm is proposed in this paper, and the square root operation is completed by shifting, adding and subtracting, and multiplying. According to the experiment, under the premise of limited resources on FPGA, the image edge extraction can be completed in real time by this method, which opens up a new idea for real-time image processing.
Double OptconNet architecture based facial expression recognition in video processing

ABSTRACT A Double optimization based convolution network model is introduced in the proposed video based facial expression recognition framework. The proposed model comprises U-shaped network, Residual-Network architecture, and Coot optimization. Before performing expression recognition, the input video is subjected to pre-processing, and face detection is performed over the extracted frames using the viola jones algorithm. The U-shaped network has the advantage of improving the processing speed of the convolution network, whereas the residual network can reduce the error that occurs during the frame encoding and gradient dissipation avoidance. Due to this merit, these two networks are combined and introduced in the proposed framework for facial expression recognition. The experimental evaluation is performed using a matrix laboratory tool over the three datasets: Affectiva-MIT Facial Expression Dataset, BAUM-1s and Real-world affective faces database. The comparative analysis shows that the proposed network has attained an efficient recognition rate than other existing network architecture.
MEMS Gyroscope Drift Performance Enhancement using Single Axis Rotation Modulation Technique

MEMS Gyroscope has an increasing use in recent years as it is a central part of localization systems. Varying drift is considered one of the major MEMS gyroscope error sources, as it limits the usage of the gyroscope to short periods only. So in the paper, we apply the continuous rotation modulation technique (CRMT) to the ADIS16334 MEMS gyroscope to reduce the drift of the sensor. The experimental results prove that the application of CRMT has yielded a significant enhancement of the sensors’ roll and pitch angle drift by 37x and 8x, respectively. This performance enhancement enables the dependence on the sensor for an extended period.
Effective haptic feedback type for robot-mediated material discrimination depending on target properties

Haptic feedback enables material perception via remote robotics. Both force and vibration information are essential for haptic feedback, and it is important to understand their applicability in different situations. In this study, the relationship between the effective type of haptic feedback and target properties in robot-mediated material discrimination was investigated. A remote-control system including a force presentation device and a wearable vibrotactile display was constructed. In the first experiment, the discrimination performance of material hardness was compared between two types of feedback, force and hybrid (vibrotactile and force) conditions. The results show that both feedback systems allow statistically-significant discrimination of the stimuli, and a significant difference in correct-answer rates between the two feedback conditions was not observed. This indicates that the force system was effective for hardness discrimination, and that there was no superimposed effect of the hybrid system. In the second experiment, the discrimination performance of material roughness was compared between three types of feedback (force, vibrotactile, and hybrid). The results indicate that the rate of correct responses for hybrid feedback condition are significantly higher than those for the force condition. This suggests that hybrid feedback is effective for roughness discrimination. Therefore, the effective type of feedback depends on the properties of target materials, and the superimposed effect of hybrid feedback was only observed in roughness discrimination. These findings play an important role in selecting the best feedback method for a given situation or constructing multiple feedback methods that achieve high discrimination performance.
An investigation of the topology and structure of constant-α force-free fields

Coronal field structures corresponding to specified normal fields on the photosphere are investigated using a force- free model. The force-free parameter is insufficient to determine the field uniquely, and so a second parameter representing the contribution of the complementary Green's function is included. For isolated loops represented by a single source-sink pair, the influence of the two parameters on field structure is comparable. Effects on the topology (as measured by field line connectivity) of multiple source configurations are also found to be comparable. It is notable that some configurations are more stable than others to variation of either parameter. The results of this study are compared with previous magnetic charge topology studies involving only the force-free parameter.
STS1 and STS2 Phosphatase Inhibitor Baicalein Enhances the Expansion of Hematopoietic and Progenitor Stem Cells and Alleviates 5-Fluorouracil-Induced Myelosuppression

STS1 and STS2, as the protein phosphatases that dephosphorylate FLT3 and cKIT, negatively regulate the self-renewal and differentiation of hematopoietic stem and progenitor cells (HSPCs). To obtain the small molecule inhibitors of STS1/STS2 phosphatase activity used to expand HSPCs both in vitro and in vivo, we establish an in vitro phosphatase assay using the recombinant proteins of the STS1/STS2 histidine phosphatase (HP) domain, by which we screened out baicalein (BC) as one of the effective inhibitors targeting STS1 and STS2. Then, we further demonstrate the direct binding of BC with STS1/STS2 using molecular docking and capillary electrophoresis and verify that BC can restore the phosphorylation of FLT3 and cKIT from STS1/STS2 inhibition. In a short-term in vitro culture, BC promotes profound expansion and enhances the colony-forming capacity of both human and mouse HSPCs along with the elevation of phospho-FLT3 and phospho-cKIT levels. Likewise, in vivo administration with BC significantly increases the proportions of short-term hematopoietic stem cells (ST-HSCs), multipotent progenitors (MPPs) and especially long-term HSCs (LT-HSCs) in healthy mouse bone marrow and increases the numbers of colony-forming units (CFU) formed by HSPCs as well. More importantly, pre-administration of BC significantly enhances the survival of mice with lethal 5-fluorouracil (5-FU) injection due to the alleviation of 5-FU-induced myelosuppression, as evidenced by the recovery of bone marrow histologic injury, the increased proportions of LT-HSCs, ST-HSCs and MPPs, and enhanced colony-forming capacity. Collectively, our study not only suggests BC as one of the small molecule candidates to stimulate HSPC expansion both in vitro and in vivo when needed in either physiologic or pathologic conditions, but also supports STS1/STS2 as potential therapeutic drug targets for HSPC expansion and hematopoietic injury recovery.
A Novel Ni/WOX/W Resistive Random Access Memory with Excellent Retention and Low Switching Current

The behavior of WOX resistive random access memory (ReRAM) is a strong function of the top electrode material, which controls the conduction mechanism and the forming process. When using a top electrode with low work function, the current conduction is limited by space charges. On the other hand, the mechanism becomes thermionic emission for devices with a high work function top electrode. These (thermionic) devices are also found to have higher initial resistance, reduced forming current, and larger resistance window. Based on these insights and considering the compatibility to complementary metal–oxide–semiconductor (CMOS) process, we proposed to use Ni as the top electrode for high performance WOX ReRAM devices. The new Ni/WOX/W device can be switched at a low current density less than 8×105 A/cm2, with RESET/SET resistance ratio greater than 100, and extremely good data retention of more than 300 years at 85 °C.
MVAD: monocular vision-based autonomous driving distance perception system

In recent years, with the development of social economy and the unprecedented development of computer hardware computing power, artificial intelligence technology has developed rapidly, the era of big computing has come, and breakthroughs in deep learning algorithms have brought new opportunities for human-computer interaction and autonomous vehicles. Autonomous driving is divided into three parts: perception, planning and control. The perception part is the most widely used technical field of computer vision, and the camera, as one of the indispensable sensors in intelligent driving vehicles, provides important image information for self-driving vehicle systems. The automatic driving system can obtain the location and distance information of various vehicles and pedestrians appearing in front of the car, providing accurate road information for drivers, avoiding traffic accidents, reducing casualties and property losses. This paper studies the object detection task and depth estimation task based on monocular vision in the visual distance perception system of autonomous driving. The emergence of deep learning has promoted the rapid development of the field of computer vision, and the application of deep convolutional neural networks has enabled vision-based object detection and depth estimation. The estimation accuracy has been greatly improved, but the computational load of the deep convolutional neural network is very large. Since the automatic driving system needs to control the car in real time, it requires the visual perception algorithm to run in real time, and the on-board computing platform of the self-driving car is required. It belongs to the mobile computing platform, and its computing power is very limited. Therefore, this paper designs a multi-task deep convolutional neural network to detect the targets appearing in the field of view of the autonomous vehicle in real time based on monocular images, and obtain the front The distance between the target vehicle or person and the camera of the vehicle appears.
Programming in Martin-Lo¨f's type theory: an introduction

Part 1 Polymorphic sets: the semantics of the judgement forms general rules enumeration sets Cartesian product of a family of sets equality sets natural numbers lists cartesian product of two sets disjoint union of two sets disjoint union of a family of sets the set of small sets (the first universe) well-orderings general trees. Part 2 Subsets: subsets in the basic set theory the subset theory. Part 3 Monomorphic sets: types defining sets in terms of types. Part 4 Examples: some small examples program derivation specification of abstract data types.
Improved Adaptive Terminal Sliding-Mode Reaching Law for Speed Control of TPMLSM With Disturbance Observer

This paper investigates the speed regulation issue of the tubular permanent magnet linear synchronous motor (TPMLSM) control system based on sliding-mode control (SMC) and disturbance compensation technology. By introducing the terminal attractor on the basis of exponential reaching law, an improved adaptive terminal sliding-mode reaching law (IATSMRL) is proposed to ensure the state variables of the control system to reach their equilibrium points quickly and suppress the chattering effectively. Based on the IATSMRL, the sliding-mode speed controller is designed to improve the dynamic performance of the TPMLSM control system. To further compensate the lumped disturbance in the TPMLSM control system, the paper utilizes an extended sliding-mode disturbance observer (ESMDO) to obtain the estimated lumped disturbance. Then an anti-disturbance sliding-mode speed controller is designed to strengthen the disturbance rejection capability of the TPMLSM control system and further improve the dynamic performance. The stability of the controller is proved by the Lyapunov stability theory. Comprehensive simulation and experimental results have been carried out to demonstrate the superiority of the proposed method.