Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary multi-objective concurrent maximisation of process tolerances

Concurrent tolerancing which simultaneously optimises process tolerance based on constraints of both dimensional and geometrical tolerances (DGTs), and process accuracy with multi-objective functions is tedious to solve by a conventional optimisation technique like a linear programming approach. Concurrent tolerancing becomes an optimisation problem to determine optimum allotment of the process tolerances under the design function constraints. Optimum solution for this advanced tolerance design problem is difficult to obtain using traditional optimisation techniques. The proposed algorithms (elitist non-dominated sorting genetic algorithm (NSGA-II) and multi-objective differential evolution (MODE)) significantly outperform the previous algorithms for obtaining the optimum solution. The average fitness factor method and the normalised weighting objective function method are used to select the best optimal solution from Pareto optimal fronts. Two multi-objective performance measures namely solution spread measure and ratio of non-dominated individuals are used to evaluate the strength of the Pareto optimal fronts. Two more multi-objective performance measures namely optimiser overhead and algorithm effort are used to find the computational effort of the NSGA-II and MODE algorithms. Comparison of the results establishes that the proposed algorithms are superior to the algorithms in the literature.
Electroluminescence of 2,4-bis(4-(2′-thiophene-yl)phenyl)thiophene in organic light-emitting field-effect transistors

We succeeded in observing electroluminescence (EL) of 2,4-bis(4-(2′-thiophene-yl)phenyl)thio-phene (TPTPT) as an active layer in an organic field-effect transistor (OFET). In particular, an OFET with a short channel of dSD=0. 8μm demonstrated higher EL efficiency than one with a much longer channel (dSD=9.8μm). We observed a maximum EL quantum efficiency (ηmax) of 6.4×10−3% in the short-channel-length device at an applied source-drain voltage of Vd=−100V and a gate voltage of Vg=−40V. From the OFET characteristics, although the TPTPT layer demonstrated typical p-type operation, the occurrence of EL clearly indicated simultaneous hole and electron injection from the source and drain electronics, respectively, under high Vd and Vg.
Low-Light Raw Video Denoising With a High-Quality Realistic Motion Dataset

Recently, supervised deep-learning methods have shown their effectiveness on raw video denoising in low-light. However, existing training datasets have specific drawbacks, e.g., inaccurate noise modeling in synthetic datasets, simple motion created by hand or fixed motion, and limited-quality ground truth caused by the beam splitter in real captured datasets. These defects significantly decline the performance of network when tackling real low-light video sequences, where noise distribution and motion patterns are extremely complex. In this paper, we collect a raw video denoising dataset in low-light with complex motion and high-quality ground truth, overcoming the drawbacks of previous datasets. Specifically, we capture 210 paired videos, each containing short/long exposure pairs of real video frames with dynamic objects and diverse scenes displayed on a high-end monitor. Besides, since spatial self-similarity has been extensively utilized in image tasks, harnessing this property for network design is more crucial for video denoising as temporal redundancy. To effectively exploit the intrinsic temporal-spatial self-similarity of complex motion in real videos, we propose a new Transformer-based network, which can effectively combine the locality of convolution with the long-range modeling ability of 3D temporal-spatial self-attention. Extensive experiments verify the value of our dataset and the effectiveness of our method on various metrics.
A general and effective way for evaluating the integrals with various orders of singularity in the direct boundary element method

A general and efficient technique is developed for the evaluation of the integrals with various orders of singularity, such as occur in the three-dimensional boundary element method (BEM). Generalized (extended) triangle, tetrahedron polar co-ordinate mappings together with two conditions are used to remove the singularity of the integrals, and to evaluate the corresponding non-singular ones in a new numerical space. Triangle and tetrahedron polar co-ordinates in Reference 1 are proved to be a special case of the generalized ones in this paper. With the developed idea, boundary element results converge rapidly towards the analytical solutions for the strongly singular integrals evaluated directly, and the analytical solutions can be gained in principle, even when employing higher order, triangular boundary elements and tetrahedral cells. The generality and practicability of the method are demonstrated in the case of higher order elements, discontinuous elements and large engineering problems.
A statistical image resolution enhancement approach for mixed-resolution video

Many scalable video compression techniques utilise a mixed-resolution scheme, which down-samples some frames at the encoder to produce reduced-resolution frames while keeping resolutions of other frames unchanged as full resolutions, in order to achieve higher compression gain. Image enlargement technique is required at the decoder to recover the original full-resolution frames for this mixed-resolution video system set-up. This article proposes a Bayesian approach to enlarge the reduced-resolution frame via its maximum a-posterior estimation, using the information from the observed reduced-resolution frame, plus more detailed information extracted from available neighbouring frames in full resolution. Experiments are conducted to justify that the proposed approach outperforms a few conventional approaches.
3D22MX: Performance Subjective Evaluation of 3D/Stereoscopic Image Processing and Analysis

This work is divided into three parts: (i) a methodology developed for building a 3D/ stereoscopic database, called 3D22MX, (ii) a software tool designed for degradation of 3D/stereoscopic images, and (iii) a psychophysical experiment carried out for a specific type of noise. The novelty of this work is to integrate these three parts precisely to provide not only professionals who design algorithms to estimate three-dimensional image quality but also those who wish to generate new image databases. For the development of the 3D/stereoscopic database, 15 indoor images and 5 outdoor ones were spatial-calibrated and lighted for different types of scenarios. Criteria calibration is different for indoor images with respect to outdoor images. The software tool to degrade 3D/stereoscopic images is designed from MatLab programming language since images captured in the first part are calculated for achieving several image degradation. Our program has ten different types of noises for degradation, such as white Gauss impulse, localvar, spatial correlation, salt & pepper, speckle, blur, contrast, jpeg, and j2k. Due to each type of noise containing up to five levels of degradation, in this proposal, a database of 20 images is required to design a tool for degrading and generating three-dimensional images ranging from all types of noise to yield psychophysical. Finally, there are applied specific criteria to carry out some psychophysical experiments with 3D/stereoscopic images. Moreover, we analyzed the methodology used to qualify and apply images to the j2k noise, explaining every degradation level for this noise.
Others’ Facial Expressions Influence Individuals Making Choices and Processing Feedback: The Event-Related Potential and Behavioral Evidence

To date, several studies have found the effect of facial expressions on trust decision, using the event-related potentials (ERPs). However, little is known about the neural mechanism underlying the modulation effect of facial expressions on making choices and subsequent outcome evaluation. In the present study, using an ERP technique, we investigated how the neural process of making choices and subsequent outcome evaluation were influenced by others’ facial expressions for the first time. Specifically, participants played a modified version of the Trust Game, in which they watched a photo of the trustee before making choices. Critically, trustees’ faces differed regarding emotional types (i.e., happy, neutral, or angry) and gender (i.e., female or male). Behaviorally, an interaction between expressions and gender was observed on investment rates. On the neural level, the N2 and P3 amplitudes were modulated by facial expressions in the making-choice stage. Additionally, the feedback-related P3 was also modulated by facial expressions. The present study proved the effect of facial expressions on making choices and subsequent outcome evaluation.
Autonomous robot navigation based on the evolutionary multi-objective optimization of potential fields

This article presents the application of a new multi-objective evolutionary algorithm called RankMOEA to determine the optimal parameters of an artificial potential field for autonomous navigation of a mobile robot. Autonomous robot navigation is posed as a multi-objective optimization problem with three objectives: minimization of the distance to the goal, maximization of the distance between the robot and the nearest obstacle, and maximization of the distance travelled on each field configuration. Two decision makers were implemented using objective reduction and discrimination in performance trade-off. The performance of RankMOEA is compared with NSGA-II and SPEA2, including both decision makers. Simulation experiments using three different obstacle configurations and 10 different routes were performed using the proposed methodology. RankMOEA clearly outperformed NSGA-II and SPEA2. The robustness of this approach was evaluated with the simulation of different sensor masks and sensor noise. The scheme reported was also combined with the wavefront-propagation algorithm for global path planning.
Quantum entropies of nonprobabilistic matrices

Von Neumann defined the informational entropy of a density matrix ρ by the expression S(ρ)=−tr(ρ ln ρ). [J. Von Neumann, Die Mathematischen Grundlagen der Quantummechanik (Springer‐Verlag, Berlin, 1932)]. Here, starting from the definitions of Shannon entropy and of Renyi entropy of random variables, and using some (reasonable) rules of inference, two expressions are obtained for the quantum entropy of a given square (deterministic) matrix, irrespective of any probabilistic framework and/or any randomization technique. These definitions apply directly to linear operators on Hilbert spaces even when they are not of positive trace class, and they contain Von Neumann entropy as a special case. These new measures of uncertainty could provide new approaches to some problems related to structure complexity.
Adult hippocampal neurogenesis and social behavioural deficits in the R451C Neuroligin3 mouse model of autism are reverted by the antidepressant fluoxetine

Neuron generation persists throughout life in the hippocampus but is altered in animal models of neurological and neuropsychiatric diseases, suggesting that disease‐associated decline in cognitive and emotional hippocampal‐dependent behaviours might be functionally linked with dysregulation of postnatal neurogenesis. Depletion of the adult neural stem/progenitor cell (NSPCs) pool and neurogenic decline have been recently described in mice expressing synaptic susceptibility genes associated with autism spectrum disorder (ASDs). To gain further insight into mechanisms regulating neurogenesis in mice carrying mutations in synaptic genes related to monogenic ASDs, we used the R451C Neuroligin3 knock‐in (Nlgn3 KI) mouse, which is characterized by structural brain abnormalities, deficits in synaptic functions and reduced sociability. We show that the number of adult‐born neurons, but not the size of the NSPC pool, was reduced in the ventral dentate gyrus in knock‐in mice. Notably, this neurogenic decline was rescued by daily injecting mice with 10 mg/Kg of the antidepressant fluoxetine for 20 consecutive days. Sustained treatment also improved KI mice's sociability and increased the number of c‐Fos active adult‐born neurons, compared with vehicle‐injected KI mice. Our study uncovers neurogenesis‐mediated alterations in the brain of R451C KI mouse, showing that the R451C Nlgn3 mutation leads to lasting, albeit pharmacologically reversible, changes in the brain, affecting neuron formation in the adult hippocampus. Our results suggest that fluoxetine can ameliorate social behaviour in KI mice, at least in part, by rescuing adult hippocampal neurogenesis, which may be relevant for the pharmacological treatment of ASDs.
The use of optical fibers to enhance the laser generation of ultrasonic waves

It is shown that optical fibers offer a convenient way to control, both spatially and temporally, the laser light used to generate ultrasound in a solid. Proper phasing between the acoustic signals received at the transducer can enhance the ultrasonic signal in a particular direction. The principle is validated experimentally, with two optical fibers guiding the light emitted by a cw argon‐ion laser.
TURKISH VALIDITY AND RELIABILITY OF COVID-19 STRESS SCALES (CSS)

Objective: It is considered that evaluation of the stress level, in crisis situations, will provide a valuable source of the crisis intervention. The aim of the study was to test the Turkish validity and reliability of the COVID-19 Stress Scales. Method: This methodological study was conducted between December 2020 and January 2021 with 841 nursing students and online. The data collection form included socio-demographical characteristics of the participants, COVID-19 Stress Scales, Perceived Stress Scale, Scale of Fear of COVID-19, and Scale of Coronavirus Phobia. Translations and intercultural adaptation process were used for the Turkish version of the COVID-19 Stress Scales. Content, construct and criterion validity analyzes were performed for the validity of the Scale. Internal consistency and intra-class correlation coefficients values were calculated for the reliability of the scale. Results: The mean age of the participants was 23.63±8.5. The Content Validity Index of the COVID-19 Stress Scales was calculated as 0.98. According to suggestions of the experts, the subscale of "xenophobia" was excluded from the scale. In Confirmatory Factor Analysis, fit indices were calculated at acceptable levels and good fits. The five factors were reported in the original study of the scale, was confirmed in the Turkish version. The Cronbach's α value was 0.94 for the scale total. Strong and positive correlations was found between the test and retest scores of the total scale (ICC=0.799; p=0.001). Conclusion: COVID-19 Stress Scales with 30 items and five subscales was a valid and reliable measurement tool for Turkish society.
Influence of Food Density on Digestive Enzyme Activities in Newly Hatched Larvae of the Spiny Lobster, Panulirus ornatus

ABSTRACT There is considerable interest in developing hatchery techniques for the tropical spiny lobster, Panulirus ornatus. Although some progress has been made toward identifying effective foods and feeding protocols for this species, the density at which food is first provided to larvae varies greatly in practice. This study examined relationships between food density and the activities of major digestive enzymes in P. ornatus to evaluate larval feeding protocols from a nutrient utilization perspective. Specifically, activities of α-amylase, nonspecific esterase, and trypsin-like protease were quantified to determine the response of newly hatched larvae of P. ornatus to provision of Artemia nauplii at three different densities. Results showed that food density significantly (P < 0.01) influenced α-amylase and nonspecific esterase activities during the first 24 h of feeding, but had minimal effect (P ≥ 0.09) on trypsin-like protease activities. Based on enzyme activities, there is no advantage to increasing food densities above 2.5 Artemia mL–1, but when food density decreased to 0.5 Artemia mL–1, the availability of dietary nutrients became limiting. An optimal density at which to provide Artemia nauplii to newly hatched larvae of P. ornatus is likely between 0.5 and 2.5 Artemia mL–1. The comparative analyses of enzyme activities presented in this study represents an innovative approach to identify potentially excessive or insufficient food densities quickly (within 24 h) for larval crustaceans.
Bolt Positioning Detection Based on Improved YOLOv5 for Bridge Structural Health Monitoring

To improve the stability of the bridge structure, we detect bolts in the bridge which cause the symmetry failure of the bridge center. For data acquisition, bolts are small-scale objects under complex background in images, and their feature expression ability is limited. Due to those questions, we propose a new bolt positioning detection based on improved YOLOv5 for bridge structural health monitoring. This paper makes three major contributions. Firstly, according to the calibration anchor boxes of bolts, the size and proportion parameters of the initial anchor boxes are optimized by K-means++ clustering algorithm to solve the initial clustering problem of anchor boxes in object detection. Second, the hypercolumn (HC) technique fuses the low-level global features of the trunk and the high-level local features of three different scales to solve the problem of the inefficient distribution of anchors and insufficient extraction of classification features. In this way, we improve the detection accuracy and speed of bolt detection. Finally, we establish a dataset of bridge bolts through network collection and public datasets, including 1494 images. We compare and verify the new method in the collected bolt dataset. The experimental results show that the precision (P) of the improved YOLOv5x is up to 87.3%, and the average precision (AP) is up to 86.3%, which are 6.5% and 5.9% higher than the original YOLOv5x, respectively.
Masers in GLIMPSE Extended Green Objects (EGOs)

Abstract Large-scale Spitzer surveys of the Galactic plane have yielded a new diagnostic for massive young stellar objects (MYSOs) that are actively accreting and driving outflows: extended emission in the IRAC 4.5 μm band, believed to trace shocked molecular gas. Maser studies of these extended 4.5 μm sources (called EGOs, Extended Green Objects, for the common coding of 3-color IRAC images) have been and remain crucial for understanding the nature of EGOs. High detection rates in VLA CH3OH maser surveys provided the first proof that EGOs were indeed MYSOs driving outflows; our recent Nobeyama 45-m survey of northern EGOs shows that the majority are associated with H2O masers. Maser studies of EGOs also provide important constraints for the longstanding goal of a maser evolutionary sequence for MYSOs, particularly in combination with high resolution (sub)mm data. New SMA results show that Class I methanol masers can be excited by both young (hot core) and evolved (ultracompact HII region) sources within the same massive star-forming region.
Luminosity performance studies of the compact linear collider with intra-train feedback system at the interaction point

To achieve the design luminosity at future linear colliders, control of beam stability at the sub-nanometre level at the interaction point will be necessary. Any source of beam motion which results in relative vertical offsets of the two beams at the interaction point may significantly reduce the luminosity from the nominal value. Beam-based intra-train feedback systems located in the interaction region are foreseen to correct the relative beam-beam offset and thus to steer the two beams into collision. These feedback systems must be capable of acting within the bunch train. In addition, these feedback systems might considerably help to relax the tight stability tolerances required for the final doublet magnets. For the Compact Linear Collider (CLIC), the extremely short nominal bunch spacing (0.5 ns) and very short nominal pulse duration (156 ns) make the intra-train feedback implementation technically very challenging. In this paper the conceptual design of an intra-train feedback system for the CLIC interaction point is described. Results of luminosity performance simulations are presented and discussed for different scenarios of ground motion. We also show how the intra-train feedback system can help to relax the very tight tolerances of the vertical vibration on the CLIC final doublet quadrupoles.
Air Flow and Particle Trajectories around Aircraft Fuselages. I: Theory

Abstract A potential-flow sink-source technique is used to model the flows around fuselage shapes. It is shown that the flow in any plane can be approximated reasonably well using an axisymmetric model of similar shape and that at a few fuselage radii from the nose the flow is determined principally by the size of the fuselage radius. Departures from the free-stream velocity are typically less than 10% and vary as the inverse square of the scaled distance from the nose. Analyses of water drop trajectories around three different aircraft shapes show that two of the more important features of the trajectories, the width of the shadow zone and the concentration enhancement factors, can be described quite generally in terms of a scaled fuselage radius and a parameter similar to the Stokes number. Thus the maximum width of the shadow zone is shown to be about one-fifth of the fuselage radius and occurs for a combination of particle size and aircraft speed for which the modified Stokes parameter has a value of .
Virtualized Network Graph Design and Embedding Model to Minimize Provisioning Cost

The provisioning cost of a virtualized network (VN) depends on several factors, including the numbers of virtual routers (VRs) and virtual links (VLs), mapping of them on a substrate infrastructure, and routing of data traffic. An existing model, known as the virtual network embedding (VNE) model, determines the embedding of given VN graphs into the substrate infrastructure. When the resource allocation model of the VNE problem is adopted to a single-entity scenario, where a single entity fulfills the roles of both a service provider and an infrastructure provider, an issue of increased costs of VNs and access paths arise. This paper proposes a model for virtualized network graph design and embedding (VNDE) for the single-entity scenario. The VNDE model determines the number of VRs and a VN graph for each request in conjunction with embedding. The VNDE model also determines access paths that connect customer premises and VRs. We formulate the VNDE model as an integer linear programming (ILP) problem. We develop heuristic algorithms for the cases where the ILP problem cannot be solved in practical time. We evaluate the performance of the VNDE model on several networks, including an actual Japanese academic backbone network. Numerical results show that the proposed model designs suitable VN graphs and embeds them according to the volume of traffic demands and access path cost. Compared with the benchmark model, which is based on a classic VNE approach, the proposed model reduces the provisioning cost at most 28.7% in our examined scenarios.