Miracle-dz/UniFAR-FTUs huggingface dataset:
How low can you go? – Extending downwards the limits of plastic deformation in pyrite

Abstract Understanding the deformation mechanisms that may operate in pyrite (FeS2) across a range of P-T conditions is important in deciphering the history of deformed ore deposits. Pyrite has frequently been considered a hard mineral, which deforms by cataclastic flow or diffusive processes, if at all, at temperatures <425°C. However, utilizing SEM-based orientation-contrast (OC) imaging and electron-backscatter diffraction (EBSD) techniques, plastic deformation can now be readily identified within pyrite grains. In this study, a series of pyrite-rich polymetallic ore deposits, deformed at low temperature metamorphic conditions (∼200-420°C), have been investigated. Results indicate that pyrite grains in all the ore deposits preserve internal lattice 'distortion' or ‘bending’ and therefore plastic deformation mechanisms have operated. Many pyrite grains in the ore deposits also contain low-angle (∼2°) sub-grain boundaries or ‘dislocation walls’, indicating that both dislocation glide and creep have been the dominant deformation mechanisms at peak metamorphic conditions within the pyrite grains. These results suggest that the brittle-ductile transition in pyrite occurs at temperatures potentially as low as ∼200°C, far lower than implied from previous studies or the current pyrite deformation-mechanism map.
CASIA-SURF: A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing

Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face antispoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects (≤ 170) and modalities (≤ 2), which hinder the further development of the academic community. To facilitate future face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIASURF, which is the largest publicly available dataset for face anti-spoofing both in terms of subjects and visual modalities. Specifically, it consists of 1, 000 subjects with 21, 000 videos and each sample has 3 modalities (i.e., RGB, Depth and IR). Associated with this dataset, we also provide concrete measurement set, evaluation protocol and training/validation/testing subsets, developing a new benchmark for face anti-spoofing. Moreover, we present a new multimodal fusion method as a strong baseline, which performs feature re-weighting to select the more informative channel features while suppressing less useful ones for each modal. Extensive experiments have been conducted on the proposed dataset to verify its significance and generalization capability.
Organizational context, supplier management practices and supplier performance

Purpose – This paper aims to examine the relationships among supplier management practices, organizational context and supplier performance. The contexts selected for supplier management practices are economics transactional practices and high involvement work practices (HIWP); while power asymmetry and competition intensity are considered within the organizational context.Design/methodology/approach – A questionnaire survey was conducted on a multinational semiconductor company. A two‐phase statistical analysis, which comprised phase one (reliability and factor analysis), and phase two (hierarchical multiple regression analysis), was used to analyze the data.Findings – The study provides empirical evidence to support the conceptual and prescriptive statements in the literature regarding the impact of supplier management practices and the dynamics between organizational context and supplier management towards supplier performance. The results show that high involvement work practices (HIWP) mediate the im.
Broadcast, relay and feedback in Gaussian channels

Network information theory explores the fundamental data transport limits over communication networks. Broadcasting and relaying are two natural models arising in communication contexts where multiple users share a common communication medium. Number of relay and broadcasting models are considered in this thesis. We first collect the existing methodologies of communication over a discrete memoryless relay channel. A new communication strategy over this channel is also proposed, which achieves the same data-rates as the best known schemes in literature, incurring a lower delay at the same time. We then consider the Gaussian broadcast channel (GBC), and show that its capacity region is enlarged by the availability of feedback, even if the feedback is from only one of the receivers. We further show a low complexity, explicit capacity achieving strategy over a GBC with degraded receivers. A combination of relay and broadcast models, called the relay-broadcast channel (RBC) is analyzed next. Achievable regions are proposed for different RBC scenarios. For the Gaussian version of an RBC, we characterize the complete capacity region when the receivers are degraded with respect to the relay. The final part of this thesis investigates communication over fading channels. We propose upper bounds for non-coherent, as well as lower bounds for coherent communication over a MIMO fading channel.
Polynomial size proofs of the propositional pigeonhole principle

Abstract Cook and Reckhow defined a propositional formulation of the pigeonhole principle. This paper shows that there are Frege proofs of this propositional pigeonhole principle of polynomial size. This together with a result of Haken gives another proof of Urquhart's theorem that Frege systems have an exponential speedup over resolution. We also discuss connections to provability in theories of bounded arithmetic.
Requirements for MPLS Transport Profile (MPLS-TP) Shared Mesh Protection

This document presents the basic network objectives for the behavior of Shared Mesh Protection (SMP) that are not based on control-plane support. This document provides an expansion of the basic requirements presented in RFC 5654 ("Requirements of an MPLS Transport Profile") and RFC 6372 ("MPLS Transport Profile (MPLS-TP) Survivability Framework"). This document provides requirements for any mechanism that would be used to implement SMP for MPLS-TP data paths, in networks that delegate protection switch coordination to the data plane.
Robust Stabilization of T–S Fuzzy Stochastic Descriptor Systems via Integral Sliding Modes

This paper addresses the robust stabilization problem for T–S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi–Sugeno (T–S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T–S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.
Who will share Fake-News on Twitter? Psycholinguistic cues in online post histories discriminate Between actors in the misinformation ecosystem

The spread of misinformation or fake-news is a global concern that undermines progress on issues such as protecting democracy and public health. Past research aiming to combat its spread has largely focused on identifying its semantic content and media outlets publishing such news. In contrast, we aim to identify individuals who are more likely to share fake-news by studying the language of actors in the fake-news ecosystem (such as fake-news sharers, fact-check sharers and random twitter users), and creating a linguistic proﬁle of them. Fake-news sharers and fact-check sharers use signiﬁcantly more high-arousal negative emotions in their language, but fake-news sharers express more existentially-based needs than other actors. Incorporating psycholinguistic cues as inferred from their tweets into a model of socio-demographic predictors considerably improves classiﬁcation accuracy of fake-news sharers. The ﬁnding that fake-news sharers differ in important ways from other actors in the fake-news ecosystem (such as in their existential needs), but are also similar to them in other ways (such as in their anger levels), highlights the importance of studying the entire fake-news ecosystem to increase accuracy in identiﬁcation and prediction. Our approach can help mitigate fake-news sharing by enabling platforms to pre-emptively screen potential fake-news sharers’ posts.
On the half-slope and straight-slope methods of basement depth determination

Although a great variety of interpretation techniques for basement depth determination has been developed during the past two or three decades, the half‐slope and straight‐slope methods are still popular due to their simplicity and general reliability in manual interpretation and are widely used in oil exploration work (Nettleton, 1976). The half‐slope and straight‐slope rules are derived for a particular set of geologic/geophysical conditions and care should be taken in applying them in a more general way. For example, the half‐slope method of Peters (1949) was derived for magnetic anomalies over vertical dikes with vertical polarization. The straight‐slope method uses the horizontal projection of the straight‐line part of the steepest gradient at the inflection point on the anomaly curve as the depth estimator. This rule is purely empirical because mathematically there is no straightline part on the anomaly curve. Vacquier et al. (1951) made an exhaustive study of the straight‐slope method and presented.
The MediaMill TRECVID 2006 Semantic Video Search Engine

In this paper we describe our TRECVID 2006 experiments. The MediaMill team participated in two tasks: concept detection and search. For concept detection we use the MediaMill Challenge as experimental platform. The MediaMill Challenge divides the generic video indexing problem into a visual-only, textual-only, early fusion, late fusion, and combined analysis experiment. We provide a baseline implementation for each experiment together with baseline results, which we made available to the TRECVID community. The Challenge package was downloaded more than 80 times and we anticipate that it has been used by several teams for their 2006 submission. Our Challenge experiments focus specifically on visual-only analysis of video (run id: B MM). We extract image features, on global, regional, and keypoint level, which we combine with various supervised learners. A late fusion approach of visual-only analysis methods using geometric mean was our most successful run. With this run we conquer the Challenge baseline by more than 50%. Our concept detection experiments have resulted in the best score for three concepts: i.e. desert, flag us, and charts. What is more, using LSCOM annotations, our visual-only approach generalizes well to a set of 491 concept detectors. To handle such a large thesaurus in retrieval, an engine is developed which automatically selects a set of relevant concept detectors based on text matching and ontology querying. The suggestion engine is evaluated as part of the automatic search task (run id: A-MM) and forms the entry point for our interactive search experiments (run id: A-MM). Here we experiment with query by object matching and two browsers for interactive exploration: the CrossBrowser and the novel RotorBrowser. It was found that the RotorBrowser is able to produce the same results as the CrossBrowser, but with less user interaction. Similar to previous years our best interactive search runs yield top performance, ranking 2nd and 6th overall. Again a lot has been learned during this year's TRECVID campaign, we highlight the most important lessons at the end of this paper.
A novel ontology matching approach using key concepts

Purpose – Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched. Design/methodology/approach – Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson’s.
Quantum Spatially-Coupled Codes

Spatially-coupled (SC) codes is a class of convolutional LDPC codes that has been well investigated in classical coding theory thanks to their high performance and compatibility with low-latency decoders. We describe toric codes as quantum counterparts of classical two-dimensional spatially-coupled (2D-SC) codes, and introduce quantum spatially-coupled (QSC) codes as a generalization. We use the convolutional structure to represent the parity check matrix of a 2D-SC code as a polynomial in two indeterminates, and derive an algebraic condition that is both necessary and sufﬁcient for a 2D-SC code to be a stabilizer code. This algebraic framework facilitates the construction of new code families. While not the focus of this paper, we note that small memory facilitates physical connectivity of qubits, and it enables local encoding and low-latency windowed decoding. In this paper, we use the algebraic framework to optimize short cycles in the Tanner graph of 2D-SC HGP codes that arise from short cycles in either component code. While prior work focuses on QLDPC codes with rate less than 1/10, we construct 2D-SC HGP codes with small memory, higher rates (about 1/3), and superior thresholds.
Contained Neural Style Transfer for Decorated Logo Generation

Making decorated logos requires image editing skills, without sufficient skills, it could be a time-consuming task. While there are many on-line web services to make new logos, they have limited designs and duplicates can be made. We propose using neural style transfer with clip art and text for the creation of new and genuine logos. We introduce a new loss function based on distance transform of the input image, which allows the preservation of the silhouettes of text and objects. The proposed method contains style transfer to only a designated area. We demonstrate the characteristics of proposed method. Finally, we show the results of logo generation with various input images.
Stratigraphy and depositional history of the Apollo 17 drill core

Lithologic abundances obtained from modal analyses of a continuous string of polished thin sections indicate that the Apollo 17 deep drill core can be divided into three main zones: An upper zone (0-19 cm depth) characterized by high abundances of agglutinates (30%) and a high ratio of mare to non-mare lithic fragments (less than 0.8); a coarse-grained layer (24-56 cm) rich in fragments of high-Ti mare basalts and mineral fragments derived from them, and poor in agglutinates (6%); and a lower zone (56-285 cm) characterized by variable but generally high agglutinate abundances (25%) and a low ratio of mare to nonmare lithic fragments (0.6). Using observations of the geology of the landing site, the principles of cratering dynamics, and the vast amount of data collected on the core, the following depositional history for the section of regolith sampled by the Apollo 17 drill core: was devised.
Design of obstacle detection and avoidance system for Guanay II AUV

This paper presents the design of an obstacle avoidance algorithm for Guanay II AUV. The obstacle detection system disposes a SONAR and its use guarantees the safety in navigation of AUV. Obstacle avoidance is performed based on a fuzzy reactive architecture for different forward speeds of the vehicle. The simulation results obtained through the implementation of the algorithms designed in Matlab validate the designs.
DensE: An Enhanced Non-Abelian Group Representation for Knowledge Graph Embedding

Capturing the composition patterns of relations is a vital task in knowledge graph completion. It also serves as a fundamental step towards multi-hop reasoning over learned knowledge. Previously, rotation-based translational methods, e.g., RotatE, have been developed to model composite relations using the product of a series of complex-valued diagonal matrices. However, RotatE makes several oversimplified assumptions on the composition patterns, forcing the relations to be commutative, independent from entities and fixed in scale. To tackle this problem, we have developed a novel knowledge graph embedding method, named DensE, to provide sufficient modeling capacity for complex composition patterns. In particular, our method decomposes each relation into an SO(3) group-based rotation operator and a scaling operator in the three dimensional (3-D) Euclidean space. The advantages of our method are twofold: (1) For composite relations, the corresponding diagonal relation matrices can be non-commutative and related with entity embeddings; (2) It extends the concept of RotatE to a more expressive setting with lower model complexity and preserves the direct geometrical interpretations, which reveals how relations with distinct patterns (i.e., symmetry/anti-symmetry, inversion and composition) are modeled. Experimental results on multiple benchmark knowledge graphs show that DensE outperforms the current state-of-the-art models for missing link prediction, especially on composite relations.
DP-SEP! Differentially Private Stochastic Expectation Propagation

We are interested in privatizing an approximate posterior inference algorithm called Expectation Propagation (EP). EP approximates the posterior by iteratively reﬁning approximations to the local likelihoods, and is known to provide better posterior uncertainties than those by variational inference (VI). However, using EP for large-scale datasets imposes a challenge in terms of memory requirements as it needs to maintain each of the local approximates in memory. To overcome this problem, stochastic expectation propagation (SEP) was proposed, which only considers a unique local factor that captures the average eﬀect of each likelihood term to the posterior and reﬁnes it in a way analogous to EP. In terms of privacy, SEP is more tractable than EP because at each reﬁning step of a factor, the remaining factors are ﬁxed to the same value and do not depend on other datapoints as in EP, which makes the sensitivity analysis tractable. We provide a theoretical analysis of the privacy-accuracy trade-oﬀ in the posterior estimates under diﬀerentially private stochastic expectation propagation (DP-SEP). Furthermore, we demonstrate the performance of our DP-SEP algorithm evaluated on both synthetic and real-world datasets in terms of the quality of posterior estimates at diﬀerent levels of guaranteed privacy.
Urban green infrastructure

Urban green infrastructure is a network of green spaces, water and other natural features within urban areas. A green infrastructure approach uses natural processes to deliver multiple functions, such as reducing the risk of flooding and cooling high urban temperatures. This POSTnote summarises research evidence of the effectiveness of green infrastructure, and challenges to its implementation. Overview 80% of people in the UK live in urban areas. Green space has decreased in many cities in recent decades. This reduction poses risks to human health and natural systems that may increase with climate change. Urban green infrastructure can help to mitigate these risks. Green infrastructure can often provide the same functions as conventional infrastructure, such as water management and flood risk alleviation, with other benefits for health and biodiversity. However, these benefits are not always well quantified. Constraints on green infrastructure provision include a lack of understanding of natural systems and their associated benefits, a lack of strategic green infrastructure plans and a lack of co-ordination within local authorities.
Scan-chain optimization algorithms for multiple scan-paths

This paper presents an algorithm framework for the scan-chain optimization problem in multiple-scan design methodology. It also presents algorithms we propose based on the framework; these are the first algorithms ever proposed for multiple-scan designing. Experiments using actual design data show that, for ten scan-paths, our algorithms achieved a 90% reduction in scan-test time at the expense of a 7% total scan-path length increase as compared with the length of a single optimized scan-path.
Probabilistic n-Choose-k Models for Classification and Ranking

In categorical data there is often structure in the number of variables that take on each label. For example, the total number of objects in an image and the number of highly relevant documents per query in web search both tend to follow a structured distribution. In this paper, we study a probabilistic model that explicitly includes a prior distribution over such counts, along with a count-conditional likelihood that defines probabilities over all subsets of a given size. When labels are binary and the prior over counts is a Poisson-Binomial distribution, a standard logistic regression model is recovered, but for other count distributions, such priors induce global dependencies and combinatorics that appear to complicate learning and inference. However, we demonstrate that simple, efficient learning procedures can be derived for more general forms of this model. We illustrate the utility of the formulation by exploring applications to multi-object classification, learning to rank, and top-K classification.
Verification, validation, and accreditation

This paper presents guidelines for conducting verification, validation, and accreditation (VV&A) of M&S applications. Fifteen guiding principles are introduced to help the researchers, practitioners and managers better comprehend what VV&A is all about. The VV&A activities are described in two M&S life cycles. Applicability of 77 V&V techniques is shown for the major stages of the two M&S life cycles. A methodology for accreditation of M&S applications is briefly introduced.
Learning the Principle of Least Action with Reinforcement Learning

It is attractive to learn physics via machine learning because physics describes our complicated real-world both elegantly and economically, with simple laws of physics to govern the evolution of complex states. In the case of classical mechanics, nature favors the object to move along the path according to the time integral of the Lagrangian, called the action S . We consider setting the reward/penalty as a function of S , so the agent could learn the physical trajectory of particles in various kinds of environments with reinforcement learning (RL). In this work, we veriﬁed the idea by using a Q-Learning based algorithm on learning how light propagates in materials with different refraction indices, and show that the agent could recover the minimal-time path equivalent to the solu-tion obtained by Snell’s law or Fermat’s Principle. The success sheds light on the possibility of further applications for combining RL and physics.