Miracle-dz/UniFAR-FTUs huggingface dataset:
Preschool in Three Cultures Revisited: China, Japan, and the United States.

Published twenty years ago, the original "Preschool in Three Cultures" was a landmark in the study of education: a profoundly enlightening exploration of the different ways preschoolers are taught in China, Japan, and the United States. Here, lead author Joseph Tobin - along with new collaborators Yeh Hsueh and Mayumi Karasawa - revisits his original research to discover how two decades of globalization and sweeping social transformation have affected the way these three cultures educate and care for their youngest pupils. Putting their subjects' responses into historical perspective, Tobin, Hsueh, and Karasawa analyze the pressures put on schools to evolve and to stay the same, discuss how the teachers adapt to these demands, and examine the patterns and processes of continuity and change in each country. "Preschool in Three Cultures Revisited" artfully and insightfully illustrates the surprising, illuminating, and at times entertaining experiences of four-year-olds - and their teachers - on both sides of the Pacific.
Automatic map updating by fusion of multispectral images in the Dempster-Shafer framework

In this article, we present a strategy to report in an automatic way significant changes on a map by fusion of recent images in various spectral bands. We focus on industrial scenes where changes concern objects like man-made structures and water areas. The approach is a two-stage processing. The first one concerns the detection of cartographic objects that do not exist anymore. The second one concerns the detection of new objects by a multispectral classification of the images. For configurations of partial overlapping between map and images, it is difficult or even impossible to formalize the approach suggested within a probabilistic framework. Thus, the Dempster-Shafer theory is shown as a more suitable formalism in view of the available information, and we present several solutions. Experimental results are presented.
Optimal Control of Elliptic Equations with Pointwise Constraints on the Gradient of the State in Nonsmooth Polygonal Domains

This article is concerned with optimal control problems subject to a second order elliptic PDE and additional pointwise constraints on the gradient of the state. In particular, the existence of solutions on nonsmooth polygonal or polyhedral domains is analyzed. In this situation the solution operator for the PDE does not provide enough regularity to state the pointwise constraint for any right-hand side due to the appearance of singularities associated to the corners, edges, and vertices of the domain. Further, necessary optimality conditions for the solution of the optimization problem in two and three space dimensions are derived. However, in the three-dimensional case certain critical angles along the edges of the domain have to be circumvented in the derivation of the optimality conditions. Finally, the derived optimality conditions are utilized to deduce additional regularity for the control variable.
Photolysis and radiolysis of water ice on outer solar system bodies

In this paper the available laboratory data on photolysis and radiolysis of water ice are summarized for the purpose of interpreting remote sensing data for the icy satellites. The relevance of these data to the objects in the outer solar system is then discussed. It is pointed out that the dominant species seen in laboratory spectra can differ from that seen on icy objects in space because of the low ion and UV fluxes and the relatively long annealing times in space. In the absence of contaminants, O2 is a relatively stable, photoresistant product which forms more efficiently with increasing temperature. O2 can accumulate in voids in which O3 is then formed by photolysis. In regions with temperatures always <100 K the absorption band seen in laboratory spectra at 0.28 μm, associated with trapped OH, as well as bands (<0.25 μm) associated with HO2 and H2O2 can produce a general reddening below ∼0.4 μm. This will contribute to the icy satellite reflectance spectra, as well as the reflectance spectra of more distant solar system objects. The stability of these species (O2, H2O2, HO2, OH) is enhanced by the preferential loss of H2, which also affects the D/H ratio in the surface. It is also shown that the luminescence produced by plasma bombardment might be observable by spacecraft on the nightside of certain satellites.
Fancy Man Launches Zippo at WNUT 2020 Shared Task-1: A Bert Case Model for Wet Lab Entity Extraction

Automatic or semi-automatic conversion of protocols specifying steps in performing a lab procedure into machine-readable format benefits biological research a lot. These noisy, dense, and domain-specific lab protocols processing draws more and more interests with the development of deep learning. This paper presents our teamwork on WNUT 2020 shared task-1: wet lab entity extract, that we conducted studies in several models, including a BiLSTM CRF model and a Bert case model which can be used to complete wet lab entity extraction. And we mainly discussed the performance differences of Bert case under different situations such as transformers versions, case sensitivity that may don’t get enough attention before.
The AT-rich tract of the SV40 ori core: negative synergism and specific recognition by single stranded and duplex DNA binding proteins

The SV40 origin of replication comprises a run of thymine and adenine residues. Integrity of this AT-rich sequence is known to be essential for replication. We set out to study whether or not these elements can work synergistically to sustain replication. Quite surprisingly, additional copies of the AT stretch linked to a functional SV40 ori core dramatically reduce its replication in Cosl cells, probably by creating some physical block. Interestingly, the same inhibiting effect can be observed with the addition in cis of the yeast ARS consensus, which is homologous to the SV40 AT stretch. This modulation is possibly due to the action of cellular factors that recognize either of the two sequences. In fact, we demonstrate the existence of factor(s) in Cosl crude nuclear extracts that in vitro can specifically bind to either of them. Moreover, we show that these sequence-specific factor(s) (MW about 50 kDa), named SOAP, recognize both single (T-rich strand) and double stranded forms of the AT tracts. Binding to single stranded AT stretches can be specifically inhibited by the corresponding duplex form, but not vice versa.
Distributed Multi-Robot Task Allocation Through Vacancy Chains

Existing task allocation algorithms generally do not consider the effects of task interaction, such as interference, but instead assume that tasks are independent. That assumption is often violated in multi-agent systems, e.g., in the case of cooperative mobile robots, where interaction effects can have a critical impact on performance. Modeling the effects of the interactions within a multi-robot system, the {\em group dynamics}, is difficult due to their complexity. The same complexity also makes it difficult to program, by hand, optimal solutions to multi-robot task allocation (MRTA) problems. We formalize the concept of group dynamics in the traditional framework of scheduling and show that task allocation in multi-agent systems with significant performance effects from the group dynamics is an $\mathcal NP$-complete problem. We then present a simplified model of task allocation in multi-agent systems based on {\em vacancy chains}. A vacancy chain is a resource distribution process commonly found in nature. Its simplicity and robustness inspired us to use it as a basis for a new model of task allocation with a related MRTA algorithm, both are presented in this article. The new algorithm is sensitive to interaction dynamics without involving the full complexity of the problem. The algorithm uses distributed reinforcement learning to make interference-sensitive estimates of task utilities and relies on stigmergy to produce optimal allocations. We validate our simplified model by demonstrating, in simulation, that the predicted allocations are produced by our algorithm. We also present experimental evidence that the algorithm can handle heterogeneous groups of agents where individual performance levels may differ. Abstract
Observability in Inertial Parameter Identification

We present an algorithm to characterize the space of identifiable inertial parameters in system identification of an articulated robot. This problem has been considered in the literature for decades; however, existing methods suffer from common drawbacks. Methods either rely on symbolic techniques that do not scale, or rely on numerical techniques that are sensitive to the choice of an input motion. The contribution of this work is to propose a recursive algorithm for this problem that requires only the structural parameters of a mechanism as its input. This Recursive Parameter Nullspace Algorithm (RPNA) can be applied to general open-chain kinematic trees, and does not rely on symbolic techniques. Drawing on the exponential parameterization of rigid-body kinematics, classical linear controllability and observability results can be directly applied to inertial parameter identifiability. The high-level operation of the RPNA is based on a key observation -- undetectable changes in inertial parameters can be interpreted as sequences of inertial transfers across the joints. This observation can be applied recursively, and lends an overall complexity of O(N) to determine the minimal parameters for a system of N bodies. Matlab source code for the new algorithm is provided.
The Occurrence and Effect of Sulfate Reduction and Sulfide Oxidation on Coastal Limestone Dissolution in Yucatan Cenotes

Dissolution of carbonate minerals in the coastal halocline is taking place in the karst terrain along the northeastern coast of the Yucatan Peninsula. The dissolution is being accelerated in cenotes (sinkholes) where sulfate reduction and oxidation of the produced sulfide is occurring. Hydrogen-sulfide concentrations ranged from 0.06 to 4 mmolal within the halocline in two sinkholes. Relative to concentrations expected by conservative mixing, fluids with high hydrogen-sulfide concentrations were correlated with low sulfate concentrations, high alkalinities, low pH values, and heavy sulfur isotope values for sulfate. Hydrogen-sulfide concentrations were less than those predicted from sulfate reduction, calculated from deficiencies in measured sulfate concentrations, indicating mobility and loss of aqueous sulfide. Fluids with low hydrogen-sulfide concentrations were correlated with very high calcium concentrations, high strontium and sulfate concentrations, slightly elevated alkalinities, low pH values, and sea-water sulfur isotope values for sulfate. Gypsum dissolution is supported by the sulfur isotopes as the major process producing high sulfate concentrations. However, oxidation of aqueous sulfide to sulfuric acid, resulting in carbonate-mineral dissolution is needed to explain the calcium concentrations, low pH values, and only slightly elevated alkalinities. The halocline may trap hydrogen sulfide that has been stripped from the underlying anoxic salt water. The halocline can act as a stable, physical boundary, holding some of the hydrogen sulfide until it is oxidized back to sulfuric acid through interaction with the overlying, oxygenated fresh water or through the activity of sulfide-oxidizing bacteria.
The pattern of Lapita settlement in Fiji

At continental and oceanic geographic scales radiocarbon chronologies are important for calibrating the expansion of prehistoric populations, and understanding the type of dispersal process. In Fiji where the colonisation phase was relatively brief — within two standard deviations of most C14 dates — there are significant differences between Lapita sites and material culture suites. To investigate this variability three models of intra-archipelagic dispersal are reviewed against four categories of archaeological data to examine the pattern of settlement in the scattered Fiji Islands. Initial colonisation was probably restricted to west Fiji and may represent an inter-archipelago hiatus in Lapita expansion eastward. East Fiji was settled later during a second phase of systematic colonisation that centered on Lakeba and took in the small non-continental islands of the Lau Group.
Text Conditional Alt-Text Generation for Twitter Images

In this work we present an approach for generating alternative text (or alt-text) descriptions for images shared on social media, specifically Twitter. This task is more than just a special case of image captioning, as alt-text is both more literally descriptive and context-specific. Also critically, images posted to Twitter are often accompanied by user-written text that despite not necessarily describing the image may provide useful context that if properly lever-aged can be informative – e.g. the tweet may name an uncommon object in the image that the model has not previously seen. We address this with a CLIP prefix model that extracts an embedding of the image and passes it to a mapping network that outputs a short sequence in word embedding space, or a “prefix”, to which we also concatenate the text from the tweet itself. This lets the model condition on both visual and textual information from the post. The combined multimodal prefix is then fed as a prompt to a pretrained language model which autore-gressively completes the sequence to generate the alt-text. While prior work has used similar methods for captioning, ours is the first to our knowledge that incorporates textual information from the associated social media post into the prefix as well, and we further demonstrate through ablations that utility of these two information sources stacks. We put forward a new dataset scraped from Twitter and evaluate on it across a variety of automated metrics as well as human evaluation, and show that our approach of conditioning on both tweet text and visual information significantly outperforms prior work.
Electronic markets and service delivery: requisite competencies for virtual environments

Electronic markets have a short but dynamic history. How an electronic market can be successfully developed remains in dispute. There is a clear need to better understand the nature of electronic markets themselves and, in particular, to review important developments in their conceptualisation. To enable a deeper understanding of these issues, we decided to restrict our investigation to electronic markets in the agricultural export sector. Agribusiness is a natural early adopter of digital marketplaces because of the industry’s traditional reliance on markets and current take-up of global supply chain management (Wilkins, Swatman and Castleman, 2002). We review two portals from this sector that aimed to simplify access to regulatory documentation. The earlier implementation had its funding withdrawn after one year, whilst the more recently established portal is rapidly becoming a showcase project for the stakeholders. We use a composite theory based on Bijker (1995) and Nowotny et al (2001) to establish a framework for analysing our data. We also refer to a body of literature characterising intangible services and their design and its implications for emarket implementations. Our findings indicate that governance style is in fact closely related to the success or failure of specific sites. We also found support for earlier research indicating that expectations and understanding of electronic markets are still evolving.
SPACE RESECTION : FAILURE CASES

It is well known that there exists a “danger cylinder” for space resection, analogous to the “danger circle” in the plane, on which the resection is unstable. This paper shows how the existence of this surface may be detected and draws attention to the way in which the instability differs from that in the plane. Resume L'existence du cylindre dit “de danger” est bien connue dans la theorie de relevement dans l'espace. Si le centre de projection se trouve sur ce cylindre la solution du probleme est indefinie. Cette communication expose la base mathematique du probleme et met en evidence les differences entre le probleme dans l'espace et le probleme analogue dans le plan.
An Interactive Algorithm for Image Smoothing and Segmentation

This work introduces an interactive algorithm for image smoothing and segmentation. A non-linear partial differential equation is employed to smooth the image while preserving contours. The segmentation is a region-growing and merging process initiated around image minima (seeds), which are automatically detected, labeled and eventually merged. The user places one marker per region of interest. Accurate and fast segmentation results can be achieved for gray and color images using this simple method.
On the Importance of the Significant Slope in Empirical Wind-Wave Studies

Abstract The significant slope of a random wave field is found to be an important parameter in empirical wind-wave studies. This significant slope Ss is defined as Ss = (ζ2)½/λ0, with ζ2 as the mean-square surface elevation and λ0 as the wavelength corresponding to the waves at the peak of the spectrum. With this parameter, the relationship between Ẽ and n is reduced to an identity expressing a pure geometric measure of the sea state, because Ẽn4 = (2πSs)2. By applying the significant slope as a parameter explicitly, we proposed that the traditional empirical formulas relating the nondimensional energy Ẽ, fetch x and frequency n be combined into a single unified relationship as Ẽn/x = (9/40)Ss9/4. This unified empirical formula governs the wind-wave data equally as well in the field as in the laboratory.
Trend-cycle Approach to Estimate Changes in Southern Canada’s Water Yield

Quantifying how Canada’s water yield has changed over time is an important component of the water accounts maintained by Statistics Canada. This study evaluates the movement in the series of annual water yield estimates for Southern Canada from 1971 to 2004. We estimated the movement in the series using a trend-cycle approach and found that water yield for Southern Canada has generally decreased over the period of observation.
CSI: A Hybrid Deep Model for Fake News

In the recent political climate, the topic of fake news has drawn aaention both from the public and the academic communities. Such misinformation has been cited to have a strong impact on public opinion, presenting the opportunity for malicious manipulation. Detecting fake news is an important, yet challenging problem since it is ooen diicult for humans to distinguish misinformation. However , there have been three generally agreed upon characteristics of fake news: the text, the response received, and the source users promoting it. Existing work has largely focused on tailoring solutions to a particular characteristic, but the complexity of the fake news epidemic limited their success and generality. In this work, we propose a model that combines all three characteristics for a more accurate and automated prediction. Speciically, we incorporate the behavior of both parties, users and articles, and the group behavior of users who propagate fake news. Motivated by the three characteristics, we propose a model called CSI, which is composed of three modules: Capture, Score, and Integrate. e rst module uses a Recurrent Neural Network (RNN) to capture the temporal paaern of user activity that occurred with a given article, and the second captures the behavior of users over time. e two are then integrated with the third module to classify an article as fake or not. rough experimental analysis on real-world data, we demonstrate that CSI achieves higher accuracy than existing models. Further, we show that each module captures relevant behavioral information both on users and articles with respect to the propagation of fake news.
A spectral-spatial fusion model for robust blood pulse waveform extraction in photoplethysmographic imaging

Photoplethysmographic imaging is a camera-based solution for non-contact cardiovascular monitoring from a distance. This technology enables monitoring in situations where contact-based devices may be problematic or infeasible, such as ambulatory, sleep, and multi-individual monitoring. However, extracting the blood pulse waveform signal is challenging due to the unknown mixture of relevant (pulsatile) and irrelevant pixels in the scene. Here, we design and implement a signal fusion framework, FusionPPG, for extracting a blood pulse waveform signal with strong temporal fidelity from a scene without requiring anatomical priors (e.g., facial tracking). The extraction problem is posed as a Bayesian least squares fusion problem, and solved using a novel probabilistic pulsatility model that incorporates both physiologically derived spectral and spatial waveform priors to identify pulsatility characteristics in the scene. Experimental results show statistically significantly improvements compared to the FaceMeanPPG method ($p<0.001$) and DistancePPG ($p<0.001$) methods. Heart rates predicted using FusionPPG correlated strongly with ground truth measurements ($r^2=0.9952$). FusionPPG was the only method able to assess cardiac arrhythmia via temporal analysis.
Maintaining Plasticity in Deep Continual Learning

Modern deep-learning systems are specialized to problem settings in which training occurs once and then never again, as opposed to continual-learning settings in which training occurs continually. If deep-learning systems are applied in a continual learning setting, then it is well known that they may fail catastrophically to remember earlier examples. More fundamental, but less well known, is that they may also lose their ability to adapt to new data, a phenomenon called loss of plasticity . We show loss of plasticity using the MNIST and ImageNet datasets repurposed for continual learning as sequences of tasks. In ImageNet, binary classification performance dropped from 89% correct on an early task down to 77%, or to about the level of a linear network, on the 2000th task. Such loss of plasticity occurred with a wide range of deep network architectures, optimizers, and activation functions, and was not eased by batch normalization or dropout. In our experiments, loss of plasticity was correlated with the proliferation of dead units, with very large weights, and more generally with a loss of unit diversity. Loss of plasticity was substantially eased by L 2 -regularization, particularly when combined with weight perturbation (Shrink and Perturb). We show that plasticity can be fully maintained by a new algorithm—called continual backpropagation —which is just like conventional backpropagation except that a small fraction of less-used units are reinitialized after each example. This continual injection of diversity appears to maintain plasticity indefinitely. 1
Generic e-Removal and Input e-Normalization Algorithms for Weighted Transducers

We present a new generic ∊-removal algorithm for weighted automata and transducers defined over a semiring. The algorithm can be used with any semiring covered by our framework and works with any queue discipline adopted. It can be used in particular in the case of unweighted automata and transducers and weighted automata and transducers defined over the tropical semiring. It is based on a general shortest-distance algorithm that we briefly describe. We give a full description of the algorithm including its pseudocode and its running time complexity, discuss the more efficient case of acyclic automata, an on-the-fly implementation of the algorithm and an approximation algorithm in the case of the semirings not covered by our framework. We illustrate the use of the algorithm with several semirings. We also describe an input ∊-normalization algorithm for weighted transducers based on the general shortest-distance algorithm. The algorithm, which works with all semirings covered by our framework, admits an on-the-fly implementation.