Miracle-dz/UniFAR-FTUs huggingface dataset:
Turtle Shell Impression in a Coprolite from South Carolina, USA

ABSTRACT Coprolites (fossilized feces) can preserve a wide range of biogenic components. A mold of a hatchling turtle partial shell (carapace) referable to Taphrosphys sulcatus is here identified within a coprolite from Clapp Creek in Kingstree, Williamsburg County, South Carolina, USA. The specimen is the first-known coprolite to preserve a vertebrate body impression. The small size of the turtle shell coupled with the fact that it shows signs of breakage indicates that the turtle was ingested and that the impression was made while the feces were still within the body of the predator. The detailed impression could only have survived the act of defecation if the section of bony carapace was voided concurrently and remained bonded with the feces until the latter lithified. Exceptionally, the surface texture of the scutes is preserved, including its finely pitted embryonic texture and a narrow perimeter of hatchling scute texture. The very small size of the shell represented by the impression makes it a suitable size for swallowing by any one of several large predators known from this locality. The coprolite was collected from a lag deposit containing a temporally mixed vertebrate assemblage (Cretaceous, Paleocene and Plio-Pleistocene). The genus Taphrosphys is known from both sides of the Cretaceous–Paleogene (K–Pg) boundary so, based on the size of the coprolite and the locally-known predators, the juvenile turtle could have been ingested by a mosasaur, a crocodylian, or a theropod dinosaur. Unlike mosasaurs and theropod dinosaurs, crocodylian stomachs have extremely high acid content that almost always dissolves bone. Therefore, the likely predator of this turtle was a mosasaur or a (non-avian or avian) theropod dinosaur.
AI-powered Covert Botnet Command and Control on OSNs

Botnet is one of the major threats to computer security. In previous botnet command and control (C&C) scenarios using online social networks (OSNs), methods for finding botmasters (e.g. ids, links, DGAs, etc.) are hardcoded into bots. Once a bot is reverse engineered, botmaster is exposed. Meanwhile, abnormal contents from explicit commands may expose botmaster and raise anomalies on OSNs. To overcome these deficiencies, we propose an AI-powered covert C&C channel. On leverage of neural networks, bots can find botmasters by avatars, which are converted into feature vectors. Commands are embedded into normal contents (e.g. tweets, comments, etc.) using text data augmentation and hash collision. Experiment on Twitter shows that the command-embedded contents can be generated efficiently, and bots can find botmaster and obtain commands accurately. By demonstrating how AI may help promote a covert communication on OSNs, this work provides a new perspective on botnet detection and confrontation.
Impacts of artificial nighttime light on moths and their food plants

42 Introduction . 43 Material & Methods . 44 Study area and lighting . 44 Lights alone or in competition . 44 Statistical analyses . 45 Results . 47 Discussion. 48 Acknowledgements . 50 References . 50 Figures . 53 Appendices 2 . 58 Supplementary methodology . 61 References . 61 Chapter 3: LED lighting and the attraction of moths: do families respond differently? 62 Abstract . 62 Introduction . 63 Materials and methods . 65. 62 Introduction . 63 Materials and methods . 65 Study area and lighting . 65 Statistical analyses . 66
Atmosphere: A Framework for Contextual Awareness

This article enhances existing approaches to present-day asynchronous awareness concepts by providing the means to explicitly represent and mediate contextual information. The resulting concept of contextual awareness takes different notions of the term context into account. Following a human-centered approach, the proposed methods serve as mediators for context between persons rather than automatically detecting context. Based on this variant of awareness, the atmosphere framework is introduced to provide mechanisms to deal with the problem of workload in tandem with contextual information. Atmosphere provides a highly tailorable structure and interface to deal with a wide variance of user and organizational requirements. The article closes with the description of a partial implementation of the framework and its evaluation.
Please Scroll down for Article the Quarterly Journal of Experimental Psychology Observed Attention Allocation Processes in Category Learning

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BIOINFORMATICS ORIGINAL PAPER

Motivation: Time course gene expression experiments are performed to study time-varying changes in mRNA levels of thousands of genes. Statistical methods from functional data analysis (FDA) have recently gained popularity for modelling and exploring such time courses. Each temporal proﬁle is treated as the realization of a smooth function of time, or curve, and the inferred curve becomes the basic unit of statistical analysis. The task of identifying genes with differential temporal proﬁles then consists of detecting statistically signiﬁcant differences between curves, where such differences are commonly quantiﬁed by computing the area between the curves or the l 2 distance. Results: We propose a general test statistic for detecting differences between gene curves, which only depends on a suitably chosen distance measure between them. The test makes use of a distance-based variance decomposition and generalizes traditional MANOVA tests commonly used for vectorial observations. We also introduce the visual l 2 distance, which is shown to capture shape-related differences in gene curves and is robust against time shifts, which would otherwise inﬂate the traditional l 2 distance. Other shape-related distances, such as the curvature, may carry biological signiﬁcance. We have assessed the comparative performance of the test on realistically simulated datasets and applied it to human immune cell responses to bacterial infection over time.
Cs 598csc: Combinatorial Optimization

1 Total Dual Integrality Recall that if A is TUM and b, c are integral vectors, then max{cx : Ax ≤ b} and min{yb : y ≥ 0, yA = c} are attained by integral vectors x and y whenever the optima exist and are finite. This gives rise to a variety of min-max results, for example we derived König’s theorem on bipartite graphs. There are many examples where we have integral polyhedra defined by a system Ax ≤ b but A is not TUM; the polyhedron is integral only for some specific b. We may still ask for the following. Given any c, consider the maximization problem max{cx : Ax ≤ b}; is it the case that the dual minimization problem min{yb : y ≥ 0, yA = c} has an integral optimal solution (whenever a finite optimum exists)? This motivates the following definition: Definition 1 A rational system of inequalities Ax ≤ b is totally dual integral (TDI) if, for all integral c, min{yb : y ≥ 0, yA = c} is attained by an integral vector y∗ whenever the optimum exists and is finite. Remark 2 If A is TUM, Ax ≤ b is TDI for all b.
On Computing Maximal Independent Sets of Hypergraphs in Parallel

Whether or not the problem of finding maximal independent sets (MIS) in hypergraphs is in (R)NC is one of the fundamental problems in the theory of parallel computing. Essentially, the challenge is to design (randomized) algorithms in which the number of processors used is polynomial and the (expected) runtime is polylogarithmic in the size of the input. Unlike the well-understood case of MIS in graphs, for the hypergraph problem, our knowledge is quite limited despite considerable work. It is known that the problem is in RNC when the edges of the hypergraph have constant size. For general hypergraphs with n vertices and m edges, the fastest previously known algorithm works in time O(√n) with poly(m,n) processors. In this article, we give an EREW PRAM randomized algorithm that works in time no(1) with O(n + mlog n) processors on general hypergraphs satisfying m ≤ no(1) log log n/log log log n. We also give an EREW PRAM deterministic algorithm that runs in time nε on a graph with m ≤ n1/δ edges, for any constants δ, ε; the number of processors is polynomial in m, n for a fixed choice of δ, ε. Our algorithms are based on a sampling idea that reduces the dimension of the hypergraph and employs the algorithm for constant dimension hypergraphs as a subroutine.
Model-checking Distributed Applications with GRAS

In this paper, we present our work to add a model-checker to the GRAS framework. This tool provides a development environment allowing debug real applications within the simulator before deploying them on real platforms. We discuss the main di culties to integrate such a model-checker, and present our approach to solve them, as well as a prototype implementation. Key-words: model-checking, distributed systems, simulation ∗ Cristian.Rosa@loria.fr Nancy University / LORIA † Martin.Quinson@loria.fr Nancy University / LORIA ‡ Stephan.Merz@loria.fr INRIA Nancy-Grand Est / LORIA in ria -0 03 78 37 4, v er si on 2 15 J ul 2 01 0 Model-checking des Applications Distribuées avec
CIRCUITRY OF THE CEREBELLAR CORTEX

the structure’s performance such as locomotion, vestibular-occular refl ex (VOR), eye blink conditioning (Boyden et al., 2004; De Zeeuw and Yeo, 2005) and fear conditioning (Scelfo et al., 2008); 3, precise cell-type specifi c targeting, permitting interventional analysis of the circuit (e.g. Oberdick et al., 1990; Smeyne et al., 1995; Bahn et al., 1997; Barski et al., 2000; Aller et al., 2003; Wulff et al., 2007, 2009; Gajendran et al., 2009; Nakanishi, 2009); 4, techniques that enable specifi c cerebellar cell types to be reversibly modulated on a fast time scale in vivo (e.g. Tervo and Karpova, 2007; Wulff et al., 2007; Luo et al., 2008; Arenkiel and Ehlers, 2009). These techniques allow dynamic analysis of individual circuit components and how they relate to, or produce behaviour. Here we discuss our work on how two precise interventions within the circuit, one a permanent ablation of inhibitory synaptic input onto Purkinje cells, the other a selective fast reversible augmentation of the same inhibitory input have given complimentary insights into the function of molecular layer interneuron (MLI)-Purkinje cell synapses. Both strategies involved the same protein, the γ2 subunit of the GABA A receptor (Pritchett et al., 1989).
From products to processes: Academic events to foster interdisciplinary and iterative dialogue in a changing climate

In the context of climate change, both climate researchers and decision makers deal with uncertainties, but these uncertainties differ in fundamental ways. They stem from different sources, cover different temporal and spatial scales, might or might not be reducible or quantifiable, and are generally difficult to characterize and communicate. Hence, a mutual understanding between current and future climate researchers and decision makers must evolve for adaptation strategies and planning to progress. Iterative two‐way dialogue can help to improve the decision making process by bridging current top‐down and bottom‐up approaches. One way to cultivate such interactions is by providing venues for these actors to interact and exchange on the uncertainties they face. We use a workshop‐seminar series involving academic researchers, students, and decision makers as an opportunity to put this idea into practice and evaluate it. Seminars, case studies, and a round table allowed participants to reflect upon and experiment with uncertainties. An opinion survey conducted before and after the workshop‐seminar series allowed us to qualitatively evaluate its influence on the participants. We find that the event stimulated new perspectives on research products and communication processes, and we suggest that similar events may ultimately contribute to the midterm goal of improving support for decision making in a changing climate. Therefore, we recommend integrating bridging events into university curriculum to foster interdisciplinary and iterative dialogue among researchers, decision makers, and students.
Channel-Adaptive ADC and TDC for 28 Gb/s PAM-4 Digital Receiver

A low-power channel-adaptive 28 Gb/s PAM-4 receiver is presented utilizing a predictive analog-to-digital converter (ADC), a successive-approximation-register (SAR) time-to-digital converter (TDC), and a feed-forward equalizer (FFE) in the digital domain. The variable-resolution flash ADC takes advantage of the channel inter-symbol interference (ISI) and can achieve 5.5 bits resolution utilizing only 16 comparators. By reusing the comparators, the ADC can provide a programmable resolution from 2 to 5.5 bits consuming 40 to 90 mW, respectively. The SAR-TDC generates 5 bits timing information that includes 2 bits ISI and 3 bits timing error to achieve a low-latency and low-jitter timing recovery. Subsequently, a three-to-eight programmable tap FFE is used to equalize up to 30-dB loss achieving bit error rate lower than 10−8. FFE is implemented in a field-programmable gate array, and the first three taps are realized in a look-up table (LUT). An offline higher resolution ADC is used to generate the pre-computed values for the LUT. Measured power consumption is 130 mW (excluding digital signal processing) from a 1.2-V power supply with active chip area of 0.2025 mm2 in 65-nm technology. Due to programmability on the both ADC resolution and the number of FFE taps according to the channel loss, the receiver enables energy efficiency according to loss compensation.
Comparing high dimensional partitions with the Coclustering Adjusted Rand Index

The popular Adjusted Rand Index (ARI) is extended to the task of simultaneous clustering of the rows and columns of a given matrix. This new index called Coclustering Adjusted Rand Index (CARI) remains convenient and competitive facing other indices. Indeed, partitions with high numbers of clusters can be considered and it does not require any convention when the numbers of clusters in partitions are different. Experiments on simulated partitions are presented and the performance of this index to measure the agreement between two pairs of partitions is assessed. Comparison with other indices is discussed.
The Institute for Integrating Statistics in Decision Sciences

In this paper, we discuss issues that arise in the analysis of call center arrivals that are mostly linked to individual ads. More specifically, we consider the case where there is no complete linkage between the calls and the advertisements that led to the calls. The ability to model and infer such latent call arrival sources is important from a marketing as well as an operations point of view since knowledge of the linkage improves forecasting performance of the model. We pose this as a missing data problem and develop a data augmentation algorithm for the Bayesian analysis. We implement the proposed algorithm to simulated and actual call center arrival data and discuss its performance.
MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES

We derive a new representation for a function as a linear combination of local correlation kernels at optimal sparse locations and discuss its relation to PCA, regularization, sparsity principles and Support Vector Machines. We also discuss its Bayesian interpretation and justi cation. We rst review previous results for the approximation of a function from discrete data (Girosi, 1998) in the context of Vapnik's feature space and dual representation (Vapnik, 1995). We apply them to show 1) that a standard regularization functional with a stabilizer de ned in terms of the correlation function induces a regression function in the span of the feature space of classical Principal Components and 2) that there exist a dual representations of the regression function in terms of a regularization network with a kernel equal to a generalized correlation function. We then describe the main observation of the paper: the dual representation in terms of the correlation function can be sparsi ed using the Support Vector Machines (Vapnik, 1982) technique and this operation is equivalent to sparsify a large dictionary of basis functions adapted to the task, using a variation of Basis Pursuit De-Noising (Chen, Donoho and Saunders, 1995; see also related work by Donahue and Geiger, 1994; Olshausen and Field, 1995; Lewicki and Sejnowski, 1998). In all cases { regularization, SVM and BPD { we show that a bayesian approach justi es the choice of the the correlation function as kernel. In addition to extending the close relations between regularization, Support Vector Machines and sparsity, our work also illuminates and formalizes the LFA concept of Penev and Atick (1996). We discuss the relation between our results, which are about regression, and the di erent problem of pattern classi cation. Copyright c Massachusetts Institute of Technology, 1998 This report describes research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences and at the Arti cial Intelligence Laboratory at the Massachusetts Institute of Technology. This research is sponsored by a grant from the National Science Foundation under contract ASC-9217041 (this award includes funds from ARPA provided under the HPCC program) and by MURI grant N00014-95-1-0600. Additional support is provided by Eastman Kodak Company, Daimler-Benz, Siemens Corporate Research, Inc. and AT&T.
Indian summer monsoon: Extreme events, historical changes, and role of anthropogenic forcings

The South Asian summer monsoon is a complex coupled human‐natural system that poses unique challenges for understanding its evolution alongside increasing anthropogenic activities. Rapid and substantial changes in land‐use, land‐management and industrial activities over the subcontinent, and warming in the Indian Ocean, have influenced the South Asian summer monsoon. These might continue to be significant drivers in the near‐term along with rising global greenhouse gas emissions. Deciphering the region's vulnerability to climate change requires an understanding of how these anthropogenic activities, acting on a range of spatial scales, have shaped the monsoon spatially and temporally. This review summarizes historical changes in monsoon rainfall characteristics, associated mechanisms, and the role of anthropogenic forcings, focusing on subseasonal variability and extreme events. Several studies have found intensified subseasonal extremes across parts of India and an increase in spatial variability of rainfall despite an overall weakening of seasonal rainfall in the monsoon core. However, understanding these changes remains challenging because of uncertainties in observations and climate models. The mechanisms and relative influences of various anthropogenic activities, particularly on subseasonal extremes, remain relatively underexplored. Large biases in the representation of relevant processes in global climate models limit the ability to attribute historical changes and make reliable projections. Nevertheless, recent advances in modeling these processes using higher‐resolution modeling frameworks provide new tools to investigate the Indian summer monsoon's response to various anthropogenic forcings. There is an urgent need to understand how these forcings interact to shape climate variability and change in this vulnerable region.
PRISMACLOUD - Privacy and Security Maintaining Services in the Cloud

from a series that will keep you updated about our research activities, project results and events. It is being sent out to members of the “User and Advisory Board” (UAB) directly as well as interested people who registered for it on our homepage where it is also available for download. This first issue contains a short overview of the project, a summary of first achievements as well as highlights from our participation in events and networking activities with other projects. Call: H2020-ICT-2014-1 Topic: ICT-32-2014 Type of Action: RIA Partners: 16 Duration: 42 months Start Date: 01.02. 2015 Estimated Project Cost: ~8.5 M Requested EU Contribution: ~8.0 M Grant Agreement No: 644962 Coordinator: AIT Austrian Institute
A new distance between shapes 2 . 1 . Optimal conformal map between genus zero surfaces

In this paper, we propose a new approach for computing a distance between two shapes embedded in three-dimensional space. We take as input a pair of triangulated genus zero surfaces that are topologically equivalent to spheres with no holes or handles, and construct a discrete conformal map f between the surfaces. The conformal map is chosen to minimize a symmetric deformation energy Esd( f ) which we introduce. This measures the distance of f from an isometry, i.e. a non-distorting correspondence. We show that the energy of the minimizing map gives a well-behaved metric on the space of genus zero surfaces. In contrast to most methods in this field, our approach does not rely on any assignment of landmarks on the two surfaces. We illustrate applications of our approach to geometric morphometrics using three datasets representing the bones and teeth of primates. Experiments on these datasets show that our approach performs remarkably well both in shape recognition and in identifying evolutionary patterns, with success rates similar to, and in some cases better than, those obtained by expert observers.
Learning a Generalized Physical Face Model From Data

Physically-based simulation is a powerful approach for 3D facial animation as the resulting deformations are governed by physical constraints, allowing to easily resolve self-collisions, respond to external forces and perform realistic anatomy edits. Today's methods are data-driven, where the actuations for finite elements are inferred from captured skin geometry. Unfortunately, these approaches have not been widely adopted due to the complexity of initializing the material space and learning the deformation model for each character separately, which often requires a skilled artist followed by lengthy network training. In this work, we aim to make physics-based facial animation more accessible by proposing a generalized physical face model that we learn from a large 3D face dataset in a simulation-free manner. Once trained, our model can be quickly fit to any unseen identity and produce a ready-to-animate physical face model automatically. Fitting is as easy as providing a single 3D face scan, or even a single face image. After fitting, we offer intuitive animation controls, as well as the ability to retarget animations across characters. All the while, the resulting animations allow for physical effects like collision avoidance, gravity, paralysis, bone reshaping and more.