Miracle-dz/UniFAR-FTUs huggingface dataset:
RFID TAG GROUP RECOGNITION BASED ON MOTION BLUR ESTIMATION AND YOLOv2 IMPROVED WITH THE GAUSSIAN ALGORITHM

Eﬀective recognition of tags in the dynamic measurement system would signiﬁcantly improve the reading performance of the tag group, but the blurred outline and appearance of tag images captured in motion seriously limit the eﬀectiveness of the existing tag group recognition. Thus, this paper proposes passive tag group recognition in the dynamic environment based on motion blur estimation and improved YOLOv2. Firstly, blur angles are estimated with a Gabor ﬁlter, and blur lengths are estimated through nonlinear modelling of a Generalized Regression Neural Network (GRNN). Secondly, tag recognition based on YOLOv2 improved by a Gaussian algorithm is proposed. The features of the tag group are analyzed by the Gaussian algorithm, the region of interest of the dynamic tag is eﬀectively framed, and the tag foreground is extracted; Secondly, the data set of tag groups are trained by the end-to-end YOLOv2 algorithm for secondary screening and recognition, and ﬁnally the speciﬁc locations of tags are framed to meet the eﬀective identiﬁcation of tag groups in diﬀerent scenes. A considerable number of experiments illustrate that the fusion algorithm can signiﬁcantly improve recognition accuracy. Combined with the reading distance, the research presented in this paper can more accurately optimize the three-dimensional structure of the tag group, improve the reading performance of the tag group, and avoid the interference and collision of tags in the communication channel. Compared with the previous template matching algorithm, the tag group recognition ability put forward in this paper is improved by at least 13.9%, and its reading performance is improved by at least 6.2% as shown in many experiments.
On the Power of Regular and Permutation Branching Programs

We give new upper and lower bounds on the power of several restricted classes of arbitrary-order read-once branching programs (ROBPs) and standard-order ROBPs (SOBPs) that have received significant attention in the literature on pseudorandomness for space-bounded computation. Regular SOBPs of length n and width ⌊ w ( n +1) / 2 ⌋ can exactly simulate general SOBPs of length n and width w , and moreover an n/ 2 − o ( n ) blow-up in width is necessary for such a simulation. Our result extends and simplifies prior average-case simulations (Reingold, Trevisan, and Vadhan (STOC 2006), Bogdanov, Hoza, Prakriya, and Pyne (CCC 2022)), in particular implying that weighted pseudorandom generators (Braverman, Cohen, and Garg (SICOMP 2020)) for regular SOBPs of width poly( n ) or larger automatically extend to general SOBPs. Furthermore, our simulation also extends to general (even read-many) oblivious branching programs. There exist natural functions computable by regular SOBPs of constant width that are average-case hard for permutation SOBPs of exponential width. Indeed, we show that Inner-Product mod 2 is average-case hard for arbitrary-order permutation ROBPs of exponential width. There exist functions computable by constant-width arbitrary-order permutation ROBPs that are worst-case hard for exponential-width SOBPs. Read-twice permutation branching programs of subexponential width can simulate polynomial-width arbitrary-order ROBPs.
An overview of reciprocal L1‐regularization for high dimensional regression data

High dimensional data plays a key role in the modern statistical analysis. A common objective for the high dimensional data analysis is to perform model selection, and penalized likelihood method is one of the most popular approaches. Typical penalty functions are usually symmetric about 0, continuous and nondecreasing in (0, ∞). In this review article, we will focus on a special type of penalty function, the so call reciprocal Lasso (rLasso) penalty. The rLasso penalty functions are decreasing in (0, ∞), discontinuous at 0, and converge to infinity when the coefficients approach zero. Although uncommon, this choice of penalty is intuitively appealing if one seeks a parsimonious model fitting. In this article, we will provide an overview for the motivation, theory, and computational challenges of this rLasso penalty, and we will also compare the theoretical properties and empirical performance of rLasso with other popular penalty choices. WIREs Comput Stat 2018, 10:e1416. doi: 10.1002/wics.1416
Peripheral Vision Transformers – Supplementary Materials –

In this supplementary material, we provide additional results and analyses of the proposed method, and implementation details. In Sec. A, we provide a complete derivation on the peripheral initialization introduced in Sec. 3.1 of our main paper. In Sec. B, we present additional details on peripheral region classification presented in Sec 4.1. In Sec. C, we prove that an Multi-head Peripheral Attention (MPA) in two extreme cases of semi-dynamic attention and position bias injection is in turn convolution and multi-head self-attnetion layers respectively. In Sec. D, we provide in-depth analyses of inner workings of PerViT and recent baselines of [18, 24] both quantitatively and qualitatively. In Sec. E and F, we provide network layouts of different model sizes, training hyperparameters, and implementation details. We conclude this paper with a short discussion on potential impacts of our work in Sec. G.
S3C: Semi-Supervised VQA Natural Language Explanation via Self-Critical Learning

VQA Natural Language Explanation (VQA-NLE) task aims to explain the decision-making process of VQA models in natural language. Unlike traditional attention or gradient analysis, free-text rationales can be easier to understand and gain users' trust. Existing methods mostly use post-hoc or selfrationalization models to obtain a plausible explanation. However, these frameworks are bottle-necked by the following challenges: 1) the reasoning process cannot be faithfully responded to and suffer from the problem of logical inconsistency. 2) Human-annotated explanations are expensive and time-consuming to collect. In this paper, we propose a new Semi-Supervised VQA-NLE via Self-Critical Learning (S3C), which evaluates the candidate explanations by answering rewards to improve the logical consistency between answers and rationales. With a semi-supervised learning framework, the S3C can benefit from a tremendous amount of samples without human-annotated explanations. A large number of automatic measures and human evaluations all show the effectiveness of our method. Meanwhile, the framework achieves a new state-of-the-art performance on the two VQA-NLE datasets.
Supplementary Material for the Paper: Class Relationship Embedded Learning for Source-Free Unsupervised Domain Adaptation

Numerous UDA methods have explored the prediction space to enhance feature learning [6, 28, 38], while most of them only focus on the intra-class relationship. Some methods [18, 24] propose to utilize the inter-class term, but their primary objective is to suppress it and produce more confident predictions. It is implemented by directly minimizing the inter-class term [18] or resorting to adversarial training between two classifiers [24]. Different from them, we use the source prior class similarity as coefficient for the interclass term instead of a fixed value. It is beneficial to accurately represent the similarity between two samples. The experimental results show that our method can surpass them even without source supervision during target training. In SFUDA, class relationships can be implicitly learned through pseudo labeling [14, 25] or prediction consistency of neighborhoods [52–54]. CAiDA [8] focus on multisource-free domain adaptation, and propose to preserve the consistency of the interclass relationship by aligning soft label distributions across domains. It relies on multiple source
Group Identity in Public Deliberation

I argue that different argumentative practices require participants to categorize themselves in different modes. Accordingly, I distinguish four types of argumentation: rational argumentation, intergroup argumentation, intragroup argumentation, and, finally, personal argumentation. An inescapable implication of my approach to deliberation is that deliberation presupposes the self-categorization of participants in the same ingroup. Deliberation does not require, however, the group to antecede the deliberation process, and a distinctive feature of successful public deliberation is its capacity to produce social identification with the deliberative group. Thus, identity negotiation is an important part of deliberative processes.
Millennial and orbital-scale variability in a 54 000-year record of total air content from the South Pole ice core

Abstract. The total air content (TAC) of polar ice cores has long been considered a potential proxy for past ice sheet elevation. Recent work, however, has shown that a variety of other factors also influence this parameter. In this paper we present a high-resolution TAC record from the South Pole ice core (SPC14) covering the last 54 000 years and discuss the implications of the data for interpreting TAC from ice cores. The SPC14 TAC record shows multiple features of interest, including (1) long-term orbital-scale variability, (2) millennial-scale variability in the Holocene and last glacial period, and (3) a period of stability from 35 to 25 ka. The longer, orbital-scale variations in TAC are highly correlated with integrated summer insolation (ISI), corroborating the potential of TAC to provide an independent dating tool via orbital tuning. Large millennial-scale variability in TAC during the last glacial period is positively correlated with past accumulation rate reconstructions as well as δ15N-N2, a firn thickness proxy. These TAC variations are too large to be controlled by direct effects of temperature and too rapid to be tied to elevation changes. We propose that grain size metamorphism near the firn surface explains these changes. We note, however, that at sites with different climate histories than the South Pole, TAC variations may be dominated by other processes. Our observations of millennial-scale variations in TAC show a different relationship with accumulation rate than observed at sites in Greenland.
Regenerative block-bootstrap confidence intervals for the extremal index

This paper is devoted to show how the regenerative block-bootstrap methodology (RBB), proved asymptotically valid in the case of sample means and U-statistics based on data drawn from a regenerative arkov chain X = {Xn}n in Bertail and Clemencon (2005, 2006b), may be successfully extended for onstructing confidence intervals for the extremal index of instantaneous functions {f(Xn)}n. Precisely, this boils down to applying the RBB procedure to the regenerative blocks estimator proposed in Bertail et al. (2007) for measuring the clustering tendency of high threshold exceedances. Asymptotic normality of this estimator is established, together with the asymptotic validity of the bootstrap distribution estimate, under mild stochastic stability assumptions. Eventually, a preliminary numerical experiment is presented, with the aim to empirically evaluate the capacity of the RBB for building accurate confidence intervals for the extremal index of the waiting process related to a M/M/1 queue.
Simulation of marine stratocumulus using the super-droplet method: Numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.0

The super-droplet method (SDM) is a Lagrangian particle-based numerical scheme for cloud microphysics. In this work, a series of simulations based on the DYCOMS-II (RF02) setup with different horizontal and vertical resolutions are conducted to explore the grid convergence of the SDM simulations of marine stratocumulus. The results are compared with the double-moment bulk scheme (SN14) and model intercomparison project (MIP) results. In general, all SDM and SN14 15 variables show a good agreement with the MIP results and have similar grid size dependencies. The stratocumulus simulation is more sensitive to the vertical resolution than to the horizontal resolution. The vertical grid length DZ << 2.5 m is necessary for both SDM and SN14. The horizontal grid length DX < 12.5 m is necessary for the SDM simulations. DX ≤ 25 m is sufficient for SN14. We also assess the numerical convergence with respect to the super-droplet (SD) numbers. The simulations are well converged when the SD number concentration (SDNC) is larger than 16 SDs/cell. Our results indicate that the SD number per
Influence of Social Media Usage on the Academic Performance of Arabic Students in Tertiary Institutions in Katsina State, Nigeria

This study investigated the influence of social media usage on the academic performance of Arabic students in tertiary institutions of Katsina state. The investigation was carried out with a researcher designed questionnaire. A total of 248 students were selected using Stratified random sampling technique. Data collected were analyzed with the Statistical Package for the Social Sciences (SPSS), IBM version 26. Statistical procedure adopted included descriptive statistics. The Chi-square was used to determine the extent of association at the fixed alpha level of 0.05. Findings revealed that WhatsApp, Facebook, Tiktok, Instagram, Telegram, Twitter and Linkedin in order of hierarchy were the social media being used by the students. It was found that Arabic students accessed their social media at anytime, anywhere but with more emphasis on during free time and when at home and that social media are generally used for academic, social connections, news and other information such as trending gist, clothing style, music among others. Use of WhatsApp and Facebook were found to manifest addictiveness among the students. Students were of the view that social media improve on their academic performance. Use of social media except Facebook was not significantly associated with students’ gender but use of Facebook was found to be significantly associated with students’ gender. Indulgence in use of social media was found to be associated with a number of challenges which included unsolicited information often encountered in the internet, among others. It was recommended, among others that since it was reported that Social media has positive influence on Arabic student’ academic performance, Curriculum development stakeholders should include Social media as part of the strategies for the implementation of the Nigeria’s educational curriculum.
River flow in the near future: a global perspective in the context of a high-emission climate change scenario

There is high confidence that global warming intensifies all components of the global water cycle. Our goal is to investigate the possible effects of the global warming on river flows worldwide in the coming decades. We conducted 18 global hydrological simulations to assess how the river flows are expected to change in the near future (2015-2050) compared to the recent past (1950-2014). The simulations are forced by runoff from HighResMIP-CMIP6 GCMs, which assume a high-emission scenario for the projections. The assessment includes estimating the signal-to-noise (S/N) ratio and the time of emergence 5 (ToE) of all the rivers in the world, with further evaluation of those presenting significant departures from their historic mean flow. Consistent with the water cycle intensification, the hydrological simulations project a clear positive global river discharge trend from ∼ 2000, that emerges beyond the levels of natural variability and becomes ‘unfamiliar’ by 2017 and ‘unusual’ by 2033. This climate change signal is dominated by strong increases in flows of rivers originating in central Africa, east Russia, Alaska and Greenland. African rivers project most future annual cycles above the climatological annual cycle, with the largest 10 differences occurring during peak flows. Recent unprecedent floods in the Republic of Congo, D.R. C. , Nigeria, and Chad high-light the potential catastrophic consequences of these changes in metropolitan areas. However, the positive trend of Lake Chad tributaries may aid its recovery from the strong reduction observed since the 1970s. Lastly, the projected Nile streamflow rise reinforces the need for collaboration in dam management. The simulated and observed extra release of freshwater into the Arctic Ocean produces a freshening of the ocean, potentially impacting the global ocean overturning circulation. It is concerning 15 that several important rivers are projected to exceed their natural variability. However, the hydrological predictions assume a very high baseline emission scenario and should be interpreted as an upper limit for decision-making.
Multi-Modality Imaging in Aortic Stenosis an EACVI Clinical Consensus Document.

In this EACVI clinical scientific update, we will explore the current use of multi-modality imaging in the diagnosis, risk-stratification and follow-up of patients with aortic stenosis, with a particular focus on recent developments and future directions. Echocardiography is and will likely remain the key method of diagnosis and surveillance of aortic stenosis providing detailed assessments of valve haemodynamics and the cardiac remodelling response. CT is already widely used in the planning of transcutaneous aortic valve implantation. We anticipate its increased use as an anatomical adjudicator to clarify disease severity in patients with discordant echocardiographic measurements. CT calcium scoring is currently used for this purpose, however contrast computed tomography techniques are emerging that allow identification of both calcific and fibrotic valve thickening. Additionally, improved assessments of myocardial decompensation with echocardiography, cardiac magnetic resonance and computed tomography will become more commonplace in our routine assessment of aortic stenosis. Underpinning all of this will be widespread application of artificial intelligence. In combination we believe this new era of multi-modality imaging in aortic stenosis will improve the diagnosis, follow-up and timing of intervention in aortic stenosis as well as potentially accelerate the development of the novel pharmacological treatments required for this disease.
Analysis of weak labels for sound event tagging

—Weak labels are a recurring problem in the context of ambient sound analysis. While multiple methods using neural networks have been proposed to address it, limited attention has been given to the analysis of the problem to have a better understanding of it. Many of these methods seem to improve detection or tagging performance, but they have been evaluated in scenarios where other problems such as unreliable labels, over-lapping sound events, or class unbalance also occur. Therefore, it is difﬁcult to conclude whether the observed improvement is due to solving the problem of weak labels or not. In this article, we provide for the ﬁrst time a detailed analysis of the impact of weak labels independently of other problems on a sound event tagging system. We show that, in order to limit the negative impact of weak labels on the performance, the training clips must be at least as long as the test clips and longer training clip durations have a minor impact. We also show that good temporal aggregation can help to reduce this impact at test time and provide insight on the annotation granularity needed depending on the targeted scenario.
Diel and seasonal methane dynamics in the shallow and 1 turbulent Wadden Sea 2

The Wadden Sea is a coastal system fringing the land-sea borders of Denmark, Germany, and the 15 Netherlands. The Wadden Sea is extremely productive and influenced by strong variations in physical and 16 biological forcing factors that act on time scales of hours to seasons. Productive coastal seas are known to dominate 17 the ocean’s methane emission to the atmosphere, but knowledge on controls and temporal variations of methane 18 dynamics in these vastly dynamic systems are scarce. Here we address this knowledge gap by measuring methane 19 inventories and methanotrophic activity at a temporal resolution of two hours over a time period of two days, 20 repeatedly during four successive seasons in the central Dutch Wadden Sea. We found that methane dynamics 21 varied between colder and warmer seasons, with generally higher water column methane concentrations and 22 methanotrophic activity in the warmer seasons. Efflux of methane to the atmosphere was, on the other hand, lower 23 in the warmer seasons because of lower wind speeds. On a diel scale, tides controlled methanotrophic activity, 24 which increased ~ 40 % at low tide compared to high tide. We estimate that methane oxidizing bacteria reduce the 25 methane budget of the Dutch Wadden Sea by only 2 %, while ~ 1/3 escapes to the atmosphere and ~ 2/3 are flushed 26 out into the open North Sea at ebb tide. Our findings indicate that tides play a key role in controlling methane 27 dynamics and methanotrophic activity and highlight the importance of high resolution and repeated sampling 28 strategies to resolve methane dynamics in fast-changing coastal systems.
Mussel squeeze: dissolved oxygen and temperature can “squeeze” zebra mussels out of invaded reservoirs

Zebra mussels ( Dreissena polymorpha ) are an aquatic invasive species that cause extensive economic and ecological impacts and are a management priority in areas outside of their native range. Survivorship and distribution of zebra mussels within a waterbody are thought to be influenced by temperature and dissolved oxygen conditions, but detailed information to confirm the importance of these environmental controls is necessary to inform management efforts. We measured planktonic zebra mussel veliger density and adult survivorship in San Justo Reservoir in central California to determine distribution and timing of spawning in relation to temperature and dissolved oxygen throughout winter, spring, and summer. We found seasonal patterns in adult survivorship, with high mortality late in the summer and higher than expected survivorship during the spring when dissolved oxygen concentrations were approximately 1 mg/L. Veliger abundance peaked several meters above the thermocline from June to August. Dissolved oxygen concentrations limited veliger distribution, with few to no veligers collected in the anoxic hypolimnion. Veliger settlement out of the water column appears to be possible in San Justo Reservoir at any time of year. A better understanding of how veligers, juveniles, and adult mussels respond to fluctuating dissolved oxygen and temperature conditions will further knowledge of timing and duration of water drawdowns or other control methods for managing this harmful invasive species