Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel Pathway Dense Video Captioning With Deformable Transformer

Dense video captioning is a very challenging task because it requires a high-level understanding of the video story, as well as pinpointing details such as objects and motions for a consistent and fluent description of the video. Many existing solutions divide this problem into two sub-tasks, event detection and captioning, and solve them sequentially (“localize-then-describe” or reverse). Consequently, the final outcome is highly dependent on the performance of the preceding modules. In this paper, we decompose this sequential approach by proposing a parallel pathway dense video captioning framework that localizes and describes events simultaneously without any bottlenecks. We introduce a representation organization network at the branching point of the parallel pathway to organize the encoded video feature by considering the entire storyline. Then, an event localizer focuses to localize events without any event proposal generation network, a sentence generator describes events while considering the fluency and coherency of sentences. Our method has several advantages over existing work: (i) the final output does not depend on the output of the preceding modules, (ii) it improves existing parallel decoding methods by relieving the bottleneck of information. We evaluate the performance of PPVC on large-scale benchmark datasets, the ActivityNet Captions, and YouCook2. PPVC not only outperforms existing algorithms on the majority of metrics but also improves on both datasets by 5.4% and 4.9% compared to the state-of-the-art parallel decoding method.
A Direct Feedback FVF LDO for High Precision FMCW Radar Sensors in 65-nm CMOS Technology

A direct feedback flipped voltage follower (FVF) LDO for a high-precision frequency-modulated continuous-wave (FMCW) radar is presented. To minimize the effect of the power supply ripple on the FMCW radar sensor’s resolution, a folded cascode error amplifier (EA) was connected to the outer loop of the FVF to increase the open-loop gain. The direct feedback structure enhances the PSRR while minimizing the power supply ripple path and not compromising a transient response. The flipped voltage follower with a super source follower forms a fast feedback loop. The stability and parameter variation sensitivity of the multi-loop FVF LDO were analyzed through the state matrix decomposition. We implemented the FVF LDO in TSMC 65 nm CMOS technology. The fabricated FVF LDO supplied a maximum load current of 20 mA with a 1.2 V power supply. The proposed FVF LDO achieved a full-spectrum PSR with a low-frequency PSRR of 66 dB, unity-gain bandwidth of 469 MHz, and 20 ns transient settling time with a load current step from 1 mA to 20 mA.
Cost-effectiveness of volunteer and contract ground-based shooting of sambar deer in Australia

ABSTRACT Context Introduced sambar deer (Cervus unicolor) are increasing in south-eastern Australia, and both volunteer and contract ground-based shooters are being used by management agencies to control their undesirable impacts. However, little is known about the effectiveness and costs of volunteer and contract shooters for controlling deer populations in Australia. Aim We evaluated the effectiveness and costs of volunteer and contract ground-based shooters for controlling sambar deer and their impacts in a 5-year management program conducted in and around alpine peatlands in Alpine National Park, Victoria. Methods Ground-based shooting operations were organised in two blocks. Within each block, four ~4200-ha management units were delimited, of which two were randomly assigned as treatment (ground-based shooting) and two as non-treatment (no organised ground-based shooting). In the treatment units, ground-based shooting was conducted using either volunteers or contractors. Each shooting team recorded their effort and the numbers of deer seen and shot, and used a GPS to record their track log and the time and locations of deer shot. Key costs were recorded for both shooter types. Key results The catch per unit effort of contract shooters was four times greater than that of volunteer shooters. Both shooter types were most effective during the first half of the night and prior to sunrise, and when using a vehicle with a spotlight or walking with thermal-vision equipment. During the day, the use of gundogs to indicate deer significantly increased the success rate of volunteer shooters. Both volunteer and contract shooters used roads and tracks to move in the landscape, but contractors covered more ground than did volunteers. After accounting for key operational costs, the cost per deer killed was 10.1% higher for contract than volunteer shooters. Conclusions The effectiveness of ground-based shooters is increased by operating at night using vehicles, spotlights and thermal-vision equipment. Contract shooters kill sambar deer at a faster rate, but are slightly more expensive per deer killed, than are volunteer shooters. Implications Ground-based shooting is likely to be most effective when conducted at night with thermal-vision equipment, and in areas with a high density of roads and tracks.
Study of Charged Current Neutral Pion Production in the T2K Near Detector

T2K is a long-baseline neutrino oscillation experiment based at the J-PARC research facility in eastern Japan. The main systematic uncertainties dominating the neutrino oscillation analyses for T2K are related to the beam flux, cross-section and final state interaction uncertainties. Within this thesis, a first attempt is made to develop an analysis to reconstruct charged-current single neutral-pion interactions within the tracking detector region of the T2K near detector. The analysis presented is divided into six topologies and produces a selection efficiency, over all the event topologies of interest, of 9.6% with 12.1% purity. When considering the most effective selection topology, labelled FGD2DsDs, an efficiency of 9.4% with purity of 22.6% is achieved. This leads to a FGD2DsDs Monte-Carlo prediction of 58.5 ± 3.5 (stat.) ± 15.4 (syst.) events being selected across the T2K Run 2, Run 3 and Run 4 data taking periods, with a total of 58 events being selected within the real data. With further development in the future, it is expected that the presented analysis will contribute towards the data samples used to constrain the T2K experiment oscillation analysis and lead to a CC1pi0 final state cross-section measurement.
A Hybrid Method Combining Genetic and Nelder-Mead Algorithms for the Interpretation of Electrochemical Impedance Data - Application to Proton Exchange Membrane Fuel Cells

Electrochemical Impedance Spectroscopy (EIS) is a technique commonly used for characterizing electrochemical systems such as fuel cells, supercapacitors or batteries [1]–[3]. Modeling of the experimental results is mostly done under the form of equivalent electrical circuits (EEC) aiming to represent the charge and mass transport phenomena and electrochemical reactions occurring at the material scale inside the individual components of the electrical components, such as resistors, capacitances, etc. It is necessary to use a numerical solver to estimate the values of the model parameters starting from experimental data. Traditional methods use deterministic algorithms, which makes the results highly dependent on the initial values chosen as starting points. Obtaining reliable and consistent results even requires sometimes to analyze separately the low, intermediate and high frequencies regions of the impedance spectra [4], [5]. In this work, we propose to use a hybrid method combining a genetic algorithm (GA) with a deterministic Nelder-Mead (NM) algorithm. The GA is used for a first estimate because of the main advantages it offers as a global optimization method: it does not require initial values for parameter estimation and is also robust and well adapted for problems with -possibly-multiple solutions. However, GA are well known to require many iterations and are therefore rather slow when some of the optimization parameters are-even partially-correlated [6]. This is the reason why the GA was combined with a NM algorithm to accelerate convergence. Both types of algorithms were taken from MATLAB standard libraries. This hybrid GA-NM method is used mainly to interpret the data measured on Proton Exchange Membrane Fuel Cells (PEMFC), which are generally modeled with Randlestype circuits or Transmission Line Models [7], depending on the shape of the spectra at high frequencies. Such EEC include at least 5 and sometimes up to 12 parameters. The results show that the combined GA-NM method converges toward satisfying solutions in most of the cases, with low least-square residuals, including when the range of parameter values is unknown and/or when the sensitivity of some of them is low.
Machine Learning approach for detecting mental health on Twitter using chrome extension

Social media is used by people to communicate with friends and to share information, such as their feelings and moods. This enables companies to better understand how people think, feel, and act when communicating on various online platforms by analysing emotional data from social networks. People don't seek expert assistance because they are unwilling to do so. Additionally, many people who were kept inside their houses due of the Covid 19 pandemic decided to vent themselves on social media. We intend to create and develop a Chrome plugin that will instantly evaluate the user's tweet in order to solve this issue. Our technology would assess their posts using a machine learning model, then query them. The system will decide whether a user needs professional help based on how they respond to the questions.
Role of STAT3 and NRF2 in Tumors: Potential Targets for Antitumor Therapy

Signal transducer and activator of transcription 3 (STAT3) and nuclear factor erythroid-derived 2-like 2 (NRF2, also known as NFE2L2), are two of the most complicated transcription regulators, which participate in a variety of physiological processes. Numerous studies have shown that they are overactivated in multiple types of tumors. Interestingly, STAT3 and NRF2 can also interact with each other to regulate tumor progression. Hence, these two important transcription factors are considered key targets for developing a new class of antitumor drugs. This review summarizes the pivotal roles of the two transcription regulators and their interactions in the tumor microenvironment to identify potential antitumor drug targets and, ultimately, improve patients’ health and survival.
Modelling and Simulation of solidification processes in polymer melt flows

This work deals with the modelling and simulation of solidification processes in polymer melt flows. Two models describing the latent heat and the rheological behaviour were implemented in a finite volume code. The models are empirical and their parameters are identified using experimental results obtained from investigations with a rotational rheometer and a differential scanning calorimetry. First results of the simulation of a solidifying channel flow are shown. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Changes in the distribution of bryophytes in a highly urbanised region in Western Europe (Flanders, Belgium): a species-traits analysis

ABSTRACT Introduction In densely populated, highly industrialised regions such as Flanders (northern Belgium), species are under significant environmental pressures arising from air pollution, land use changes, and climate change, which affect distribution patterns and species abundance. Methods We compared bryophyte distribution data for 1980–1999 and 2000–2019. Species traits data were analysed to detect general trends in changes in occupancy for different species of moss and liverwort. Key results Species occupancy increased for epiphytic species of both mosses and liverworts. Liverwort species growing on dead, decorticated wood declined, whereas the number of mosses growing on this substrate increased. Liverworts decreased in all terrestrial habitats except artificial stones and other rocky substrates. Occupancy increased for mosses growing on peat substrates and on hard natural rocks. Changes in occupancy among groups of taxa classified according to Ellenberg values showed that liverworts of wet or moist habitats declined compared with those of dry habitats. Liverworts of warmer regions increased; however, for those characteristic of cold climates, there was no significant change. Conclusions Improvements in air quality, particularly due to reduced SO2 and NOx emissions, has allowed epiphytic bryophyte species numbers to recover. Among terrestrial species, there has been a decline in the number of liverwort species especially, and particularly those adapted to wet, cold conditions. This is probably due to longer and more frequent drought periods during summer, coupled with rising ambient temperatures. Larger, more robust wetlands and forests could be created to mitigate against this decline, these habitats being very fragmented in Flanders.
Fractional Stochastic Gradient Algorithm for Time-Delayed Models With Piece-Wise Linear Input Using Self-Organizing Maps Method

Although stochastic gradient algorithm can identify linear systems with high efficiency. It is inefficient for nonlinear systems for the difficulty in the step-size designing. To overcome this dilemma, this paper proposes a fractional stochastic gradient algorithm for systems with piece-wise linear input. First, the nonlinear system is transformed into a polynomial nonlinear model, then the parameters and time-delay are estimated iteratively based on the fractional stochastic gradient algorithm and self-organizing maps method. In addition, to increase the convergence rates of the fractional stochastic gradient algorithm, a multi-innovation fractional stochastic gradient algorithm is developed. Convergence analysis and simulation examples are introduced to show the effectiveness of the proposed algorithms.
Design of an Acoustical Imaging Operator Based on the Singular Value Decomposition Method

A new imaging operator has been developed for acoustical imaging using a 2ch m-sequence encoding array transducer. The new imaging operator has the ability to correct the poor orthogonal property of a transfer matrix. Moreover, images with many image points have been reconstructed by the new imaging operator. The new imaging operator has been composed on the basis of the singular-value decomposition (SVD) of the transfer matrix in the frequency domain. Characteristics of the new imaging operator are discussed by simulating the two-dimensional point spread functions (2-D PSFs). An image with a high dynamic range was obtained for a single object on the sampling image points by the method. Moreover, the method was able to reconstruct the image of the existing object outside the sampling image points.
3,3-Disubstituted 1-acylthioureas as ionophores for Pb(II)-ion selective electrodes: physical and chemical characterization of the sensing membranes

Abstract Solid-state Pb(II) ion selective electrodes were developed, which are based on 3,3-disubstituted 1-acylthioureas as ionophores and use PVC membranes. 1-Benzoyl, 1-(2-furoyl), 3,3-diethyl and 3,3-diphenyl were the substituent groups on the thioureide core. The analytical parameters for the constructed electrodes were studied. The electrodes based on 3,3-diethyl substituted thiourea derivatives showed better analytical response to Pb(II) ions with suitable sensitivity and an average lifetime of more than 30 days. Cu(II), Hg(II) and Ag(I) ions were interfering species during Pb(II) detection. Scanning electron microscopy and atomic force microscopy micrographs of the activated sensing membranes revealed morphological changes, which have been associated with the performance of the sensors. The studies have suggested that the detection of few large size particles or aggregates at the membrane surface are responsible for inadequate functioning of the prepared electrodes. This pattern was mainly observed for the sensing membranes based on 3,3-diphenyl groups as substituents and is related to unfavorable steric and electronic factors. Furthermore, X-ray photoelectron spectroscopy profiles S2p and Pb4f supported chemically the analytical response displayed for the four membrane systems. The X-ray photoelectron spectroscopy results combined with scanning electron microscopy and atomic force microscopy studies shed light on the working mechanism of the studied electrodes. Graphical Abstract
Dispositional Awe Positively Predicts Prosocial Tendencies: The Multiple Mediation Effects of Connectedness and Empathy

Awe is an emotion frequently experienced by individuals in different cultures. When individuals experience awe, they would feel a sense of connectedness to other people or nature arises, and shift their attention to the outside world, which would increase empathy for others in need and, in turn, improve their prosocial tendencies. To test this proposal, we applied a cross-sectional study using a questionnaire survey to collect a sample of 1545 (Nfemale = 988) in Asia, aged between 16 and 71 years old (M = 22.81, SD = 7.80). The Structural Equation Model and bootstrapping method were used to test the mediation effects of connectedness and empathy between awe and prosocial tendency. Results showed that dispositional awe positively predicted a prosocial tendency, which could be partially explained by the multiple mediation effects of connectedness and empathy, after controlling for the effect of the small self. The findings deepen researchers’ understanding of the underlying mechanisms of the relationship between awe and prosociality and have practical implications for cultivating awe and prosocial behavior.
GamiTool: Supporting Instructors in the Gamification of MOOCs

Reward-based gamification strategies are proposed as a promising technique to increase student engagement in Massive Open Online Courses (MOOCs), following its success in other small-scale educational settings. However, these strategies imply a number of orchestration tasks (e.g., design, management) that are usually carried out by instructors, and which may hinder their use and adoption. Furthermore, some MOOC distinctive features (e.g., scale, 24/7 availability, etc.) have considerable implications on how these gamification strategies are orchestrated, resulting in an unmanageable instructors’ workload in cases of manual operation. Therefore, an eventual adoption of gamification in MOOCs calls for automatic systems capable of decreasing the additional workload of instructors. The limitations identified in the current solutions (e.g., non-usable graphical interfaces, inflexible gamification designs) led us to propose and develop a new gamification system named GamiTool. An evaluation with 19 MOOC instructors and gamification designers showed the high design expressiveness, usability and potential for adoption of GamiTool. Hence, GamiTool can be used by instructors to improve students’ engagement, and also, by researchers to keep understanding the effects of gamification in MOOC settings.
Emission based attenuation correction of PET images of the thorax

Reports investigations on a method for obtaining an emission based attenuation correction of PET studies specifically in the thorax. The following components of the method were evaluated: body contour determination, lung contour estimation using a lung atlas, refinement of the lung contour using the consistency conditions and additional refinement of the attenuation map using a coupled iterative algorithm to alternately update both the emission and transmission distributions. Body contours could be determined with a high degree of accuracy, but the lung contours could not. The consistency conditions (up to and including the second order) did not provide a substantial improvement to the initial lung contour estimate. The coupled reconstruction algorithm also did not converge to an acceptable solution. It is concluded that these techniques are insufficient for generating an attenuation correction based solely on emission data.
Wavelets and Dilation Equations: A Brief Introduction

Wavelets are new families of basis functions that yield the representation $f(x) = \sum {b_{jk} W(2^j x - k)} $. Their construction begins with the solution $\phi (x)$ to a dilation equation with coefficients $c_k $. Then W comes from $\phi $, and the basis comes by translation and dilation of W. It is shown in Part 1 how conditions on the $c_k $ lead to approximation properties and orthogonality properties of the wavelets. Part 2 describes the recursive algorithms (also based on the $c_k $) that decompose and reconstruct f. The object of wavelets is to localize as far as possible in both time and frequency, with efficient algorithms
Bias in meta‐analysis due to outcome variable selection within studies

Although bias in meta‐analysis arising from selective publication has been studied, within‐study selection has received little attention. Chronic diseases often have several possible outcome variables. Methods based on the size of the effect allow results from studies with different outcomes to be combined. However, the possibility of selective reporting of outcomes must be considered. The effect of selective reporting on estimates of the size of the effect and significance levels is presented, and sensitivity analyses are suggested. Substantial publication bias could arise from multiple testing of outcomes in a study, followed by selective reporting. Two meta‐analyses, on anthelminth therapy and a treatment for incontinence, are reassessed allowing for within‐study selection, as it is clear that more outcomes had been measured than were reported. The sensitivity analyses show that the robustness of the anthelminth results is dependent on what assumption one makes about the reporting strategy for the largest trial. The possible influence of correlation between within‐child measurements was such that the conclusions could easily be reversed. The effect of a mild assumption on within‐trial selection alone could alter general recommendations about the treatment for incontinence.
An extended cyclic plasticity model at finite deformations describing the Bauschinger effect and ratchetting behaviour

1 Department of Applied Mechanics and Engineering, Southwest Jiaotong University, Chengdu, 610031, China * Corresponding author: Guozhengkang@126.com Abstract A popular cyclic plasticity model at small deformations is extended to finite deformations for describing the Bauschinger effect and ratchetting behaviour by considering the combined isotropic and kinematic hardening rules. The model is based on the multiplicative decomposition of deformation gradient into elastic and inelastic parts. Following, a further multiplicative decomposition of inelastic part of deformation gradient into energetic and dissipative parts is adopted to extend the popular Ohno-Karim nonlinear kinematic hardening rule. Finally, numerical examples are carried out to validate the proposed model under strain controlled and stress controlled cyclic loadings.