Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation Performance and Case Study of Extreme Events in Northwest China Using the BCC-CSM2 Model

The BCC-CSM2 model is the second generation of the Beijing Climate Center Climate System Model developed by the National Center of China Meteorological Administration. Using the outputs of two versions of the BCC-CSM2 model with different resolutions, namely: BCC-CSM2-MR and BCC-CSM2-HR, their performance in simulating the climate characteristics of Northwest China was compared. The BCC-CSM2-HR had a better ability to simulate the detailed distribution of the average temperature and precipitation in Northwest China, and could delineate the influence of the topography in detail. The extreme events in Northwest China were evaluated further using the BCC-CSM2-HR and the observation data from China Meteorological Data Center. The BCC-CSM2-HR provided a good simulation of the spatial distribution of extreme climate events in Northwest China, and the spatial distribution of TXx, TNx, TXn, and TNn in Northwest China show closer proximity to the observation than that of TX90p, TN90p, TX10p, and TN10p, even in the case of extreme heavy precipitation. This case study of the extreme weather events showed that the BCC-CSM2-HR model had the best simulation performance for extreme high temperature events in Northwest China, followed by extreme low temperature events, and had the worst simulation ability for extreme precipitation events.
Active fixation as an efficient coding strategy for neuromorphic vision

Contrary to a photographer, who puts a great effort in keeping the lens still, eyes insistently move even during fixation. This benefits signal decorrelation, which underlies an efficient encoding of visual information. Yet, camera motion is not sufficient alone; it must be coupled with a sensor specifically selective to temporal changes. Indeed, motion induced on standard imagers only results in burring effects. Neuromorphic sensors represent a valuable solution. Here we characterize the response of an event-based camera equipped with fixational eye movements (FEMs) on both synthetic and natural images. Our analyses prove that the system starts an early stage of redundancy suppression, as a precursor of subsequent whitening processes on the amplitude spectrum. This does not come at the price of corrupting structural information contained in local spatial phase across oriented axes. Isotropy of FEMs ensures proper representations of image features without introducing biases towards specific contrast orientations.
Psychological Motivation of Athletes’ Physical Training Based on Deep Learning Model

In the field of sports training, two methods of physical and psychological monitoring are usually used to monitor the training process. Physiological index monitoring can objectively reflect the physical function of athletes, and there are many monitoring constraints. Psychological indicators can subjectively reflect the athlete’s own state, and the monitoring is simple and easy. This paper mainly used the subjective perception of effort (RPE) and the profile of mood state (POMS) scales to track and monitor 20 nonprofessional athletes in a university track and field team. Based on the change of the same training volume, the change law and relationship between RPE and POMS, and the change law and relationship between RPE, POMS, heart rate, and blood pressure were analyzed. Finally, it was concluded that the athletes are feeling more and more about the amount of training, and the minimum value P < 0.01 showed a very significant difference, reflecting that the increase of training volume has a significant impact on the t-test value. The training volume has an impact on both the positive and negative dimensions of POMS, but the negative dimension reflects the training volume more clearly. There was a linear relationship between RPE and POMS subscales. RPE was not significantly correlated with positive emotions but positively correlated with negative emotions and TMD. The change trend was the same and the RPE grade increases; the blood pressure and systolic blood pressure also increased accordingly, and vice versa. The POMS negative dimension and TMD were the same as changes in blood pressure increase or decrease, and TMD was not related to heart rate. Scientific training has a large impact on the training of nonprofessional athletes, and whether the training volume is reasonable or not directly affects the qualitative change of athletes’ physical functions. Therefore, it is particularly important to monitor the physiological and psychological indicators of nonprofessional athletes. The improvement of sports performance is the goal, and the improvement of physical function is the guarantee.
Progress Report Religion and old age

The interconnections between religion and old age are complex; the more so given that the concept of age itself has – for a large part of human history – been determined by religious understandings of life. In traditional societies, religion played a crucial part in structuring the transitions between one stage of the life and the next and in deﬁning maturity and fulﬁlment. And up to a point it still does: in Western societies at the turn of the millennium the association of religious rituals with key moments in the life course – birth, adolescence, marriage and above all death – remains widespread. Such interconnections change over time, however; they also vary from place to place. A second diﬃculty lies on the deﬁnition of religion. Deﬁnitions vary along a continuum from the substantive – with a strong emphasis on the presence of or belief in some sort of supernatural, to the functional – with a much more inclusive framework. And even within substantive deﬁnitions, there is a tension between the traditional faith communities (the world religions) and new forms of religious life, many of which exist as cultural rather than structural phenomena. This paper will look ﬁrst at sources which associate religious belief and practice with age, examining (a) material from surveys of practice and opinion, (b) case studies, and (c) comparative ethnographies. The second part of the paper uses a more theoretical perspective to reﬂect about the changing nature of the life course and the place of religion within this.
Measuring Factual Consistency of Abstractive Summaries

Recent abstractive summarization systems fail 001 to generate factual consistent – faithful – sum-002 maries, which heavily limits their practical ap-003 plication. Commonly, these models tend to 004 mix concepts from the source or hallucinate 005 new content, completely ignoring the source. 006 Addressing the faithfulness problem is perhaps 007 the most critical challenge for current abstrac-008 tive summarization systems. First automatic 009 faithfulness metrics were proposed, but we ar-010 gue that existing methods do not yet utilize 011 all "machinery" that this ﬁeld has to offer 012 and introduce new approaches to assess fac-013 tual correctness. We evaluate existing and our 014 proposed methods by correlating them with 015 human judgements and ﬁnd that BERTScore 016 works well. Next, we conduct a data analy-017 sis, which reveals common problems, ways to 018 further improve the metrics and indicates that 019 combining multiple metrics is promising. Fi-020 nally, we exploit faithfulness metrics in pre-021 and post-processing steps to decrease factual 022 errors made by state-of-the-art summarization 023 systems. We ﬁnd that simple techniques like 024 ﬁltering training data and re-ranking generated 025 summaries can increase the faithfulness by a 026 substantial margin. 027
Design of 8T SRAM using 14nm FINFET Technology

: FinFETs are superior to CMOS because of their low power consumption and ability to function at low voltage. The power consumption of today's digital systems has grown due to an exponential increase in transistor count. Furthermore, due to short channel effects, the performance of typical CMOS devices degrades at lower technology nodes. In sub-14 nm technology, FinFETs have greater control over a gate and outperform CMOS designs. FinFET devices feature a greater Ion current and better extensibility than typical CMOS devices. The quasi planar FinFET structure's simple production technique drew a lot of attention. Static leakage current is decreased by up to 90%, and it is more compact. Because of its area of performance, reduced leakage power, intra-die variability
Spiralling out of control: 3D hydrodynamical modelling of the colliding winds in $\eta\thinspace$Carinae

Three dimensional (3D) adaptive-mesh refinement (AMR) hydrodynamical simulations of the wind-wind collision between the enigmatic super-massive star \etacar and its mysterious companion star are presented which include radiative driving of the stellar winds, gravity, optically-thin radiative cooling, and orbital motion. Simulations with static stars with a periastron passage separation reveal that the preshock companion star's wind speed is sufficiently reduced that radiative cooling in the postshock gas becomes important, permitting the runaway growth of non-linear thin shell (NTSI) instabilities which massively distort the WCR. However, large-scale simulations which include the orbital motion of the stars, show that orbital motion reduces the impact of radiative inhibition, and thus increases the acquired preshock velocities. As such, the postshock gas temperature and cooling time see a commensurate increase, and sufficient gas pressure is preserved to stabilize the WCR against catastrophic instability growth. We then compute synthetic X-ray spectra and lightcurves and find that, compared to previous models, the X-ray spectra agree much better with {\it XMM-Newton} observations just prior to periastron. The narrow width of the 2009 X-ray minimum can also be reproduced. However, the models fail to reproduce the extended X-ray mimimum from previous cycles. We conclude that the key to explaining the extended X-ray minimum is the rate of cooling of the companion star's postshock wind. If cooling is rapid then powerful NTSIs will heavily disrupt the WCR. Radiative inhibition of the companion star's preshock wind, albeit with a stronger radiation-wind coupling than explored in this work, could be an effective trigger.
Growth in the development of health and fitness mobile apps amid COVID-19 pandemic

Objectives Technology in the form of mobile apps has played an essential role in facilitating, tracking, and maintaining health and fitness activities during the pandemic. When countries opted for partial or complete lockdowns to contain the spread of the coronavirus disease 2019 virus, it led to people working on their health and fitness-related activities from their homes, just as they continued working from home. This paper aims to quantify the impact of coronavirus disease 2019 on the development of health and fitness mobile apps. Specifically, we compute the effect of coronavirus disease 2019 on the growth of different sub-categories of health and fitness apps. Methods We scraped data about a population of 78,890 health and fitness apps from the iOS App Store. First, categories of health and fitness apps are identified using text analysis on the descriptions of apps. Second, the rise in the development of new apps is analyzed. To quantify the impact of coronavirus disease 2019 on the growth of the health and fitness apps, multiple time-series forecasting models are created for different categories of health and fitness apps. Results The text analysis identified twelve different types of health and fitness apps on the app market. Our models estimated that the number of health and fitness apps on the iOS app market exceeded the expected growth by 29.9% after the pandemic. The results of all categories of health and fitness are discussed in the paper. Conclusions Our analysis found significant growth in the development of new health and fitness apps after the pandemic outbreak. The post hoc study of the population of health and fitness apps presented the current state of this particular area of the app market. In addition, it provided potential growth areas in app markets where there are fewer apps.
Intelligent Interactive Control via Haptic E‐skin for Human–Robot Interaction and Collaboration

Human–robot interaction and collaboration are emerging as critical and necessary technologies as robots become more commonplace in our lives. Haptic perception and intelligent control are essential to ensure safe and dexterous interactions between humans and robots. Traditional interaction methods using robot proprioceptors rely on robot dynamic models that complicate robotic controls and narrow their adaptabilities. Herein, an intelligent interactive control method is proposed based on a generalized virtual spring‐damping force‐touch mechanism using haptic e‐skin, which converts contact forces and contact positions on the e‐skin to generalized forces for implementing robot compliance controls of multidimensional movements. By touching the e‐skin mounted on a robot arm, a human can readily manipulate the robot arm, achieving flexible movement and rotation. An intelligent architecture of human–robot‐in‐the‐loop is proposed to accomplish versatile interactive and collaborative actions. A task learning is demonstrated for a robot from human, that is, a human teaches a robot how to pick up, carry, and place an object into a box by hand‐by‐hand teaching, which shows promising prospects in intelligent robot applications.
A Review of Hyperhidrosis Treatment Methods

Context: Hyperhidrosis is known to cause numerous individual and social problems with sweating more than the body’s physiological needs. Researchers have discussed the causes of this disease so far; however, factors such as heredity, nervous system defects, infections, and drugs have been introduced as the causes. Evidence Acquisition: Firstly, 127 articles were identified from different databases. After categorizing and removing duplicate papers and reviewing the abstracts and full texts, we selected 50 articles to review and include in this study. Results: Hyperhidrosis is a burdening disorder leading to physical and social problems. Hyperhidrosis patients are not able to efficiently use specific tools such as metallic and electronic devices. Limitations of this disorder show great concern about the performance of military personnel, too. Therapeutic methods such as topical antiperspirants, anticholinergic drugs, surgery, and Botox injections are the therapeutic measures used to treat this disease; each of these treatments is prescribed at different stages of the disease, and the effect of each is observed. Topical treatment is at the forefront of treatment methods for this disease, followed by oral anticholinergic drugs. Iontophoresis is one of the methods considered in the treatment of hyperhidrosis. Besides surgery, Botox injection is one of the effective methods in treating this disease, especially in the palm. Conclusions: This review presents standard treatment methods used in treating hyperhidrosis with particular attention to iontophoresis as an engineering solution to solve health problems. Based on the severity of sweating and the region of hyperhidrosis incidents, there are different solutions to treat hyperhidrosis. Topical and anticholinergic therapies are the most common treatment options. However, there are other more effective treatment methods, such as iontophoresis and Botox delivery. Iontophoresis is effective and has a long-term effect on preventing sweating with fewer side effects. Suction curettage surgery is an invasive method to treat patients with hyperhidrosis.
The VIMOS Ultra Deep Survey first data release: Spectra and spectroscopic redshifts of 698 objects up to zspec ~ 6 in CANDELS

This paper describes the first data release (DR1) of the VIMOS Ultra Deep Survey (VUDS). The VUDS-DR1 is the release of all low-resolution spectroscopic data obtained in 276.9 arcmin^2 of the CANDELS-COSMOS and CANDELS-ECDFS survey areas, including accurate spectroscopic redshifts zspec and individual spectra obtained with VIMOS on the ESO-VLT. A total of 698 objects have a measured redshift, with 677 galaxies, two type-I AGN, and a small number of 19 contaminating stars. The targets of the spectroscopic survey are selected primarily on the basis of their photometric redshifts to ensure a broad population coverage. About 500 galaxies have z_(spec) > 2, 48 of which have z_(spec) > 4; the highest reliable redshifts reach beyond z_(spec) = 6. This data set approximately doubles the number of galaxies with spectroscopic redshifts at z > 3 in these fields. We discuss the general properties of the VUDS–DR1 sample in terms of the spectroscopic redshift distribution, the distribution of Lyman-α equivalent widths, and physical properties including stellar masses M_⋆ and star formation rates derived from spectral energy distribution fitting with the knowledge of z_(spec). We highlight the properties of the most massive star-forming galaxies, noting the wide range in spectral properties, with Lyman-α in emission or in absorption, and in imaging properties with compact, multi-component, or pair morphologies. We present the catalogue database and data products. All VUDS-DR1 data are publicly available and can be retrieved from a dedicated query-based database. Future VUDS data releases will follow this VUDS-DR1 to give access to the spectra and associated measurement of ~8000 objects in the full ~1 square degree of the VUDS survey.
Development of 5G LDPC Experimental Kit

In this work, we develop the 5G LDPC experimental kit to demonstrate the encoding processes of LDPC codes in 5G new radio. The experimental kit consists of a graphical user interface (GUI) and an FPGA development board. Any parameters defined in the 5G new radio can be configured and their encoding results are presented in the GUI. We also develop the 5G LDPC encoder as the software module integrated within the GUI. The user can select the software or hardware for the 5G LDPC encoder. The experimental kit is simple to use and no need any complicated setups. We believe that the experimental kit would be useful to anyone interested in the LDPC 5G NR standard.
Evidence for nonlinear resonant mode coupling in the β Cephei star HD 180642 (V1449 Aquilae) from CoRoT photometry

Context. We present the CoRoT light curve of the β Cep star HD 180642, assembled during the first long run of the space mission, as well as archival single-band photometry. Aims. Our goal is to analyse the detailed behaviour present in the light curve and interpret it in terms of excited-mode frequencies. Methods. After describing the noise properties in detail, we use various time series analyses and fitting techniques to model the CoRoT light curve, for various physical assumptions. We apply statistical goodness-of-fit criteria that allow us to select the most appropriate physical model fit to the data. Results. We conclude that the light-curve model based on nonlinear resonant frequency and phase locking provides the best representation of the data. Interpretation of the residuals is dependent on the chosen physical model used to prewhiten the data. Conclusions. Our observational results constitute a fruitful starting point for detailed seismic stellar modelling of this large-amplitude and evolved β Cep star.
Model selection for the binary latent block model

The latent block model is a mixture model that can be used to deal with the simultaneous clustering of rows and columns of an observed numerical matrix, known as co-clustering. For this mixture model unfortunately, neither the likelihood, nor the EM algorithm are numerically tractable, due to the dependence of the rows and columns into the label joint distribution conditionally to the observations. Several approaches can be considered to compute approximated solutions, for the maximum likelihood estimator as well as for the likelihood itself. The comparison of a determinist approach using a variational principle with a stochastic approach using a MCMC algorithm is first discussed and applied in the context of binary data. These results are then used to build and compute ICL and BIC criteria for model selection. Numerical experiments show the interest of this approach in model selection and data reduction.
Empirical determination of the integrated red giant and horizontal branch stellar mass-loss in ω Centauri

We herein determine the average integrated mass-loss from stars belonging to the dominant metal-poor population ([Fe/H] ∼−1.7) of the Galactic globular cluster ω Centauri (NGC 5139) during their red giant and horizontal branch (HB) evolution. Masses are empirically calculated from spectroscopic measurements of surface gravity and photometric measurements of temperature and luminosity. Systematic uncertainties prevent an absolute measurement of masses at a phase of evolution. However, the relative masses of early asymptotic giant branch (AGB) stars and central red giant branch (RGB) stars can be measured, and used to derive the mass-loss between these two phases. This can then be used as a physical check of models of HB stars. For ω Centauri, the average difference is found to be 26 ± 4 per cent. Assuming initial and final masses of 0.83 and 0.53 M⊙, we determine that 0.21 ± 0.03 M⊙ is lost on the RGB and 0.09 ±∼0.05 M⊙ is lost on the AGB. The implied HB stellar mass of 0.62 ± 0.04 M⊙ is commensurate with literature determinations of the masses of the cluster’s HB stars. The accuracy of this measurement can be improved through better selection of stars and spectral coverage, and applied to other clusters where HB models do not currently agree.
CrossDet++: Growing Crossline Representation for Object Detection

In object detection, precise object representation is a key factor to successfully classify and locate objects of an image. Existing methods usually use rectangular anchor boxes or a set of points to represent objects. However, these methods either introduce background noise or miss the continuous appearance information inside the object, and thus cause incorrect detection results. In this paper, we propose a novel anchor-free object detection network, called CrossDet++, which uses a set of growing crosslines along horizontal and vertical axes as object representations. An object can be flexibly represented as crosslines in different combinations, which inspires us to select the expressive crossline to effectively reduce the interference of noise. Meanwhile, the crossline representation takes into account the continuous adjacent object information, which is useful to enhance the discriminability of object features and find the object boundaries. Based on the learned crosslines, we propose an axis-query crossline growing module to adaptively capture features of crosslines and query surrounding pixels related to the line features for subsequent growing of crosslines. Their growing offsets and scales can be supervised by a decoupled regression mechanism, which limits the regression target to a specific direction for decreasing the optimization difficulty. During the training, we design a semantic-guided label assignment to emphasize the importance of crossline targets with higher semantic richness, further improving the detection performance. The experiment results demonstrate the effectiveness of our proposed method. Code can be available at: https://github.com/QiuHeqian/CrossDet.