Miracle-dz/UniFAR-FTUs huggingface dataset:
Three Organic/Inorganic Nanolayers on Flexible Foam Allow Retaining Superior Flame Retardancy Performance Upon Mechanical Compression Cycles

The water-based deposition of flame retardant coatings on flexible polyurethane foams has attracted great interest among scientific community due to the great performances associated with this technology. Unfortunately, this approach results inefficient as it requires a high number of steps in order to achieve the desired properties. In this paper, we report the production of flame retardant foams by means of the simple deposition of only three nanoparticles containing layers. The composition and order of the deposited layer has been designed in order to provide specific flame retardant actions, targeting delayed release of polymer decomposition products to the gas phase, dilution of these flammable products with water and intumescent barrier formation. The morphology of the coated foams after the adsorption of each layer has been investigated by scanning electron microscopy, demonstrating the ability of each adsorbed layer to completely wrap the complex 3D structure of the foam. This three layers based coating produces a protective exoskeleton that is capable of self-extinguishing the flame in standard flammability tests, leaving the foam almost unaffected (final residue 98%). In forced combustion tests by cone calorimetry, treated foams showed considerably reduced combustion rates, with reduced peak of heat release rate (-50%) as well as consistent reduction in the smoke optical density (-51%) and the total smoke release (-34%). In addition, treated foams have been demonstrated to maintain the ability to self-extinguish the flame as well as reduced combustion rates and smoke production even after being subjected to 100 compression cycles.
Social Tobacco Warnings Can Influence Implicit Associations and Explicit Cognitions

Previous research showed that fear-inducing graphic warning labels can lead to cognitive dissonance and defensive responses. Less threatening, social-related warning labels do not elicit these defensive responses, making them more effective in preventing smoking in adults. Given that smoking numbers are still too high among youngsters, it is crucial to investigate how warning labels should be designed to prevent teenagers from starting smoking in the first place. In two studies, we investigated whether comparable effects of social-related warning labels could be observed in a group of teenagers (14–17 years) who are not yet legally allowed to smoke. In addition, we tried to replicate earlier findings with smoking and non-smoking adults. Participants were presented with either health warning labels, social warning labels, or no warning labels. Subsequently, their explicit cognitions (i.e., risk perception, attitude toward smoking) and their implicit associations of smoking with healthiness/unhealthiness (Study 1a and Study 1b) and with positivity/negativity (Study 2a and Study 2b) were assessed. Results showed that in both studies, adult smokers had a higher risk perception and a more positive attitude toward smoking than adult non-smokers. Additionally, social warning labels lead to stronger implicit associations between smoking and negativity in Study 2 in the adult groups. In the teenage group, social warning labels lead to more positive attitudes than health warning labels in Study 2. No further effects on risk perception or implicit associations were found in the teenage group. Possible explanations are discussed.
Learning from Multi-annotator Data

In the field of sentiment analysis and emotion detection in social media, or other tasks such as text classification involving supervised learning, researchers rely more heavily on large and accurate labelled training datasets. However, obtaining large-scale labelled datasets is time-consuming and high-quality labelled datasets are expensive and scarce. To deal with these problems, online crowdsourcing systems provide us an efficient way to accelerate the process of collecting training data via distributing the enormous tasks to various annotators to help create large amounts of labelled data at an affordable cost. Nowadays, these crowdsourcing platforms are heavily needed in dealing with social media text, since the social network platforms (e.g., Twitter) generate huge amounts of data in textual form everyday. However, people from different social and knowledge backgrounds have different views on various texts, which may lead to noisy labels. The existing noisy label aggregation/refinement algorithms mostly focus on aggregating labels from noisy annotations, which would not guarantee their effectiveness on the subsequent classification/ranking tasks. In this article, we propose a noise-aware classification framework that integrates the steps of noisy label aggregation and classification. The aggregated noisy crowd labels are fed into a classifier for training, while the predicted labels are employed as feedback for adjusting the parameters at the label aggregating stage. The classification framework is suitable for directly running on crowdsourcing datasets and applies to various kinds of classification algorithms. The feedback strategy makes it possible for us to find optimal parameters instead of using known data for parameter selection. Simulation experiments demonstrate that our method provide significant label aggregation performance for both binary and multiple classification tasks under various noisy environments. Experimenting on real-world data validates the feasibility of our framework in real noise data and helps us verify the reasonableness of the simulated experiment settings.
The Establishment of Weak Ecological Microexpressions Recognition Test (WEMERT): An Extension on EMERT

The JACBART (Japanese and Caucasian Brief Affect Recognition Test) microexpression recognition test only examines facial expressions under the neutral expression background and the ecological validity is not high. The EMERT (Ecological MicroExpressions Recognition Test) microexpression recognition test examined six microexpressions under seven backgrounds but does not detect the intensity of expressions. In the current study, a weak ecological microexpression recognition test was established to examine the recognition features of six weak microexpressions in all seven high intensity basic expressions. The results found: (1) the test had good retest reliability, criterion validity and ecological validity; and (2) the reliability and validity tests revealed a lot of characteristics of weak microexpression recognition. There were training effects in some weak microexpression recognition. Weak microexpression recognition was generally positively related to the microexpression recognition of JACBART but were generally negatively related to approximate common expressions. The backgrounds main effects in all weak microexpressions were significant and pairwise comparisons show there were a wide range of differences between weak microexpressions under different backgrounds. The standard deviations, of the accuracy of weak microexpressions in different backgrounds, were used to define the fluctuations of the weak microexpression recognition and we found that weak microexpression recognition had many fluctuations. (3) Personality openness and its subdimensions (O1, O2, O3, and O5) were generally positively related to some weak microexpression recognition, except O1, which was significantly negatively related to surprise under neutrality. O1 was positively related to the standard deviation of the weak anger microexpression recognition accuracies and O6 was negatively related to the standard deviation of the weak happiness microexpression recognition accuracies in the first measurement.
A 72.4-dB SNDR 92-dB SFDR Blocker Tolerant CT  $\Delta\Sigma$  Modulator With Inherent DWA

This brief presents the design and implementation of a new blocker tolerant wideband continuous-time delta-sigma modulator. Using a customized digital integrator with inherent data-weighted averaging at the back-end of the modulator, the power consumption of the quantizer is reduced while the speed of operation is increased. Additionally, by using a single amplifier biquad structure in the loop filter, the number of op-amps is reduced, thus reducing the analog power consumption. Also, the modulator robustness to the out-of-band blocker is improved by increasing the number of levels in the digital integrator and feedback DACs. The out-of-band blocker tolerance is improved by 3 dB compared to a conventional CIFF-B delta-sigma modulator with a minimal increase in the power consumption. The proposed architecture has been implemented in a 65-nm CMOS technology and operates at a 250 MHz sampling frequency. It achieves 73.5 dB SNR, 72.4 dB SNDR, and 92 dB SFDR over a 7-MHz bandwidth and a Walden figure-of-merit of 341 fJ/conversion.
Research on Customer Marketing Acceptance for Future Automatic Driving—A Case Study in China City

This paper investigates the acceptance of intelligent driving vehicles in the Chinese market using Guangzhou City as an example and a field questionnaire investigation based on the innovation diffusion theory. First, we tested the reliability and validity of 2530 effective questionnaires in 2018. Second, the cognition, expectations, technical concerns, and prospective expectations data of consumers with respect to intelligent driving vehicles are analyzed statistically. Finally, T-test and Pearson’s correlation analysis is carried out on the intelligent driving vehicle performance parameters and the respondents’ basic information. The research shows that consumers are more focused on the developmental prospects of intelligent driving vehicles and express concerns about their technological safety. Furthermore, the acceptance of intelligent driving cars depends on age, the higher the expectation, the sooner to buy an intelligent, and so on. Ninety percentage of the respondents are willing to purchase intelligent driving vehicles and are willing to pay extra money to buy them. This result will provide an objective reference for the government to issue supporting policies and laws regarding intelligent driving vehicles, and it is useful to help the enterprises to adjust their research and developmental directions for intelligent driving vehicles.
Poisson Reconstruction-Based Fusion of Infrared and Visible Images via Saliency Detection

Saliency-based methods have been widely used in the fusion of infrared (IR) and visible (VIS) images, which can highlight the salient object region and preserve the detailed background information simultaneously. However, most existing methods ignore the salient information in the VIS image or they fail to highlight the boundaries of objects, which makes the final saliency map incomplete and the edges of the object blurred. To address the above-mentioned issues, we propose a novel IR and VIS images’ fusion algorithm based on the Poisson reconstruction and saliency detection using the Dempster–Shafer (DS) theory. In detail, we mix the gradient using a mask map derived from the saliency map, which could avoid low contrast and halo effects in the results. Besides, both the intensity saliency of the IR image and the structural saliency of all source images are considered by DS to suppress some noise in the IR image. Thus, we could obtain smooth object contours and enhance the edge information of the salient region. Moreover, we also propose a novel probability mass function to calculate the probabilistic map in the process of applying DS to decrease the error from manually assigning the prior probability. Finally, the extensive qualitative and quantitative experiments have demonstrated the advantages and effectiveness of our method compared with other nine state-of-the-art IR and VIS image fusion methods.
Self-Interest Induces Counter- Empathy at the Late Stage of Empathic Responses to Others’ Economic Payoffs

Previous studies have found that individuals exhibit empathic responses when others are treated unfairly. However, there remains a lack of clarity over the extent to which self-interest regulates these empathic responses, and in identifying which component of empathy is more likely to be affected. To investigate these issues, an experiment was designed based on a money distribution task with two conditions [observation condition (OC) vs. participation condition (PC)], and carried out using scalp-recorded event-related potentials (ERPs). Behavioral data showed that the participants’ empathic responses were consistent with their coplayers’ emotional expressions in the OC, whereas they were inconsistent with the coplayers’ expressions in the PC. The electrophysiological data showed that the neural encoding of facial expressions (reflected in the N170) was not affected by self-interest. However, the late stage of empathic responses (LPP) showed a decline when participants’ self-interest was involved. Disadvantageous inequality and relatively fair distribution to others elicited a more pronounced feedback-related negativity (FRN) than advantageous inequality distribution in both the OC and PC. As the late stage of empathic responses is also indexed by the LPP amplitude, these results indicate that the participants were more concerned for their own outcomes than for others’ benefits when self-interest was involved, which reduced their empathy toward their coplayers at the late stage of empathic responses.
Interrogation System With Automatic Recognition and Delay Correction Functions of Fiber Bragg Gratings by Pulse Modulation With Wavelength-Swept Laser

We propose an interrogation-system with automatic recognition and delay correction functions of fiber Bragg gratings (FBGs) by pulse modulation with a wavelength-swept laser. By pulse-modulating the light of a wavelength-swept laser, light with an arbitrary wavelength bandwidth can be extracted as the pulsed light. In the automatic recognition function of FBGs, the pulsed light is sequentially controlled to match the wavelength bandwidth of each FBG. This recognition method enables the selection and detection of a reflection signal from a single FBG. Therefore, reflection signals from multiple FBGs can be recognized individually. When multiple FBGs are installed at long distances, the reflection signal of each FBG is affected by the propagation time (delay). In the interrogation system with the wavelength-swept laser, the delay lowers the measurement accuracy. Therefore, a delay correction function using bidirectional sweeping of the wavelength-swept laser is used. The wavelength-swept laser using Fourier domain mode locking (FDML) is driven at a sweep frequency of 50.7 kHz with a sweep bandwidth of ~60 nm. This study demonstrates that pulse-modulated FDML laser can automatically recognize reflection signals from multiple FBGs installed at arbitrary long distances. When the recognition process is complete, the interrogation system can perform real-time measurement with a time resolution of $9.9~\mu \text{s}$ , without being affected by delay that occurs when installing at a long distance.
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition

This article takes a problem-oriented perspective and presents a comprehensive review of transfer-learning methods, both shallow and deep, for cross-dataset visual recognition. Specifically, it categorises the cross-dataset recognition into 17 problems based on a set of carefully chosen data and label attributes. Such a problem-oriented taxonomy has allowed us to examine how different transfer-learning approaches tackle each problem and how well each problem has been researched to date. The comprehensive problem-oriented review of the advances in transfer learning with respect to the problem has not only revealed the challenges in transfer learning for visual recognition but also the problems (e.g., 8 of the 17 problems) that have been scarcely studied. This survey not only presents an up-to-date technical review for researchers but also a systematic approach and a reference for a machine-learning practitioner to categorise a real problem and to look up for a possible solution accordingly.
Integrated Latch Placement and Cloning for Timing Optimization

This article presents an algorithm for integrated timing-driven latch placement and cloning. Given a circuit placement, the proposed algorithm relocates some latches while circuit timing is improved. Some latches are replicated to further improve the timing; the number of replicated latches along with their locations are automatically determined. After latch cloning, each of the replicated latches is set to drive a subset of the fanouts that have been driven by the original single latch. The proposed algorithm is then extended such that relocation and cloning are applied to some latches together with their neighbor logic gates. Experimental results demonstrate that the worst negative slack and the total negative slack are improved by 24% and 59%, respectively, on average of test circuits. The negative impacts on circuit area and power consumption are both marginal, at 0.7% and 1.9% respectively.
Adaptation and Validation of the Perceived Control in Unemployment Scale

Perceived control plays an important role in the understanding of people's experiences with unemployment and reemployment. Yet, no scale has been designed specifically to measure people's perceived control in an unemployment situation. In the current study, using two independent samples with 1,009 and 831 unemployed people in France and Luxembourg, respectively, we created and tested a three-dimensional Perceived Control in Unemployment Scale that was based on Levenson's (1973, 1981) theory. An exploratory factor analysis (Study 1) and a confirmatory factor analysis (Study 2) showed that the data were consistent with the theoretically postulated three-factor model. In addition, we established convergent and discriminant validity with several adaptive and non-adaptive dimensions in two independent samples of 141 unemployed people and 384 recently unemployed people in Luxembourg (Studies 3 and 4, respectively). Perceived control did not change over a period of 6 months of unemployment, yet the three types of perceived control measured at the beginning of unemployment predicted employment status 6 months later. Unemployed people with perceptions of internal control or control from powerful others found jobs more quickly, whereas the perception that chance was the controlling factor predicted longer unemployment.
Design and Multi-Abstraction-Level Evaluation of a NoC Router for Mixed-Criticality Real-Time Systems

A Mixed Criticality System (MCS) combines real-time software tasks with different criticality levels. In a MCS, the criticality level specifies the level of assurance against system failure. For high-critical flows of messages, it is imperative to meet deadlines; otherwise, the whole system might fail, leading to catastrophic results, like loss of life or serious damage to the environment. In contrast, low-critical flows may tolerate some delays. Furthermore, in MCS, flow performances such as the Worst Case Communication Time (WCCT) may vary depending on the criticality level of the applications. Then execution platforms must provide different operating modes for applications with different levels of criticality. To conclude, in Network-On-Chip (NoC), sharing resources between communication flows can lead to unpredictable latencies and subsequently turns the implementation of MCS in many-core architectures challenging. In this article, we propose and evaluate a new NoC router to support MCS based on an accurate WCCT analysis for high-critical flows. The proposed router, called Double Arbiter and Switching router (DAS), jointly uses Wormhole and Store And Forward communication techniques for low- and high-critical flows, respectively. It ensures that high-critical flows meet their deadlines while maximizing the bandwidth remaining for the low-critical flows. We also propose a new method for high-critical communication time analysis, applied to Store And Forward switching mode with virtual channels. For low-critical flows communication time analysis, we adapt an existing wormhole communication time analysis with share policy to our context. The second contribution of this article is a multi-abstraction-level evaluation of DAS. We evaluate the communication time of flows, the system mode change, the cost, and four properties of DAS. Simulations with a cycle-accurate SystemC NoC simulator show that, with a 15% network use rate, the communication delay of high-critical flows is reduced by 80% while communication delay of low-critical flow is increased by 18% compared to solutions based on routers with multiple virtual channels. For 10% of network interferences, using system mode change, DAS reduces the high-critical communication delays about 66%. We synthesize our router with a 28nm SOI technology and show that the size overhead is limited of 2.5% compared to the solution based on virtual channel router. Finally, we applied model checking verification techniques to automatically prove several DAS properties required by critical systems designers.
Angiosperm-Wide and Family-Level Analyses of AP2/ERF Genes Reveal Differential Retention and Sequence Divergence After Whole-Genome Duplication

Plants are immobile and often face stressful environmental conditions, prompting the evolution of genes regulating environmental responses. Such evolution is achieved largely through gene duplication and subsequent divergence. One of the most important gene families involved in regulating plant environmental responses and development is the AP2/ERF superfamily; however, the evolutionary history of these genes is unclear across angiosperms and in major angiosperm families adapted to various ecological niches. Specifically, the impact on gene copy number of whole-genome duplication events occurring around the time of the origins of several plant families is unknown. Here, we present the first angiosperm-wide comparative study of AP2/ERF genes, identifying 75 Angiosperm OrthoGroups (AOGs), each derived from an ancestral angiosperm gene copy. Among these AOGs, 21 retain duplicates with increased copy number in many angiosperm lineages, while the remaining 54 AOGs tend to maintain low copy number. Further analyses of multiple species in the Brassicaceae family indicated that family-specific duplicates experienced differential selective pressures in coding regions, with some paralogs showing signs of positive selection. Further, cis regulatory elements also exhibit extensive divergence between duplicates in Arabidopsis. Moreover, comparison of expression levels suggested that AP2/ERF genes with frequently retained duplicates are enriched for broad expression patterns, offering increased opportunities for functional diversification via changes in expression patterns, and providing a mechanism for repeated duplicate retention in some AOGs. Our results represent the most comprehensive evolutionary history of the AP2/ERF gene family, and support the hypothesis that AP2/ERF genes with broader expression patterns are more likely to be retained as duplicates than those with narrower expression profiles, which could lead to a higher chance of duplicate gene subfunctionalization. The greater tendency of some AOGs to retain duplicates, allowing expression and functional divergence, may facilitate the evolution of complex signaling networks in response to new environmental conditions.