Miracle-dz/UniFAR-FTUs huggingface dataset:
From collocations and patterns to constructions – an introduction

Linguistic usage patterns are not just coincidental phenomena on the textual surface but constitute a fundamental constructional principle of language. At the same time, however, linguistic patterns are highly idiosyncratic in the sense that they tend to be item-specific and unpredictable, thus defying all attempts at capturing them by general abstract rules. A range of linguistic approaches inspired by surprisingly different background assumptions and aims have acknowledged these insights and tried to come up with ways of emphasizing the importance of linguistic repetitiveness and regularity while doing justice to unpredictability and item-specificity. Their efforts are epitomized in the terms enshrined in the title of the present volume, whose aim is to provide a multifaceted view of Constructions, Collocation and Patterns. What all of these approaches share, in addition to their interest in recurrent patterns, is a strong commitment to the value of usage, be it in the wider sense of usage as an empirical basis for sound linguistic analysis and description or in the narrower sense of usage as constituting the basis for the emergence and consolidation of linguistic knowledge. The first and presumably oldest (though to some perhaps not the most obvious) tradition takes the perspective of foreign language linguistics. Any reflection upon what is important in the learning – and, consequently, also in the teaching – of a foreign language will have to take into account the crucial role of conventionalized but unpredictable collocations. Any attempt by a learner to achieve some kind of near-nativeness will have to include facts of language such as the fact that it is lay or set the table in English, but Tisch decken in German, and mettre la table in French. 1 It is thus not at all surprising that foreign language linguistics has resulted in extensive research on collocations and how they can best be taught and learnt. In fact, the very origin of the term collocation can be traced back to the Second Interim Report on English Collocations by Harold E. Palmer published in 1933 (Cowie 2009: 391-393, Stubbs 2009). Secondly, while the phenomenon of collocation concerns the associations between lexical items, verb complementation or valency patterns present learners with the same kind of difficulty, since a similar element of unpredictability can be observed in this area in that you can say Sie erklärte
Notes on Carex (Cyperaceae) from China (IX): three new species of section Mitratae s.l.

﻿Abstract Carexsect.Mitratae s.l. was established by Kükenthal in 1909 and can be distinguished from the closely related sections in having nutlets frequently discoid-annulate at the apex and a persistent style base. Based on field surveys and specimen examination, three new species of sect. Mitratae are described and illustrated here. Carexfatsuaniana was collected from Yunnan and differs from C.truncatigluma in having the utricles nearly glabrous, the nutlets with a ca. 0.5 mm long beak at the apex, the staminate spikes cylindrical, 5–7.5 cm long, 4–5 mm wide, and the pistillate glumes acuminate at the apex. Carexdamingshanica was collected from Guangxi and differs from C.breviscapa and C.rhynchachaenium in having 3 or 4 spikes, the lateral spikes cylindrical, the pistillate glumes, utricles and nutlets all shorter than in the other two species. Carexradicalispicula was collected from Sichuan and differs from C.truncatirostris in having the staminate spikes clavate, 1.5–2 mm wide, the pistillate glumes pale yellow-white, 3–3.2 mm long, acuminate or short-awned at the apex, and the nutlets with 3 angles shallowly constricted at the middle.
Construction of a Continuous SL(3, R) Action on 4-Sphere

Soit Φ o : SO(3)×M 3 (R)→M 3 )r) l'action de SO(3) sur l'espace vectoriel M 3 (R) de toutes les matrices de degre 3, defini par Φ o (A,X)=AXA −1 pour ACSO(3) et X∈M 3 (R). Soient V et S(V) le sous-espace lineaire de M 3 (R) constitue de matrices symetriques de trace O et sa sphere unite. Soit Φ: so)3)×S(V)→S(V) l'action restreinte de Φ o . On montre que l'action SO(3) de Φ sur S(V) s'etend a l'action continue SL(3;R) de Ψ sur S(V)
The Usability of Hidden Functional Elements in Mobile User Interfaces

: The trend of maximizing mobile screen real estate by hiding user interface features has been in use for some time. However, there is a lack of empirical knowledge concerning the real usability issues of using this strategy. In this paper, we present novel and statistically significant evidence to suggest that hiding user interface elements decreases usability in terms of performance and user experience. We conducted a within-users experiment comparing identical user interfaces, where the only differences between them were that one version hid the user interface elements and the other version had all the user interface elements visible to the user. We recorded task times, errors and user satisfaction for a series of tasks. We also discuss our results in light of existing user interface design guidelines and show that our results are in harmony with existing guidelines.
The kinematics of the reduced velocity gradient tensor in a fully developed turbulent free shear flow

Abstract This paper examines the kinematic behaviour of the reduced velocity gradient tensor (VGT), $\tilde{\unicode[STIX]{x1D608}}_{ij}$ , which is defined as a $2\times 2$ block, from a single interrogation plane, of the full VGT $\unicode[STIX]{x1D608}_{ij}=\partial u_{i}/\partial x_{j}$ . Direct numerical simulation data from the fully developed turbulent region of a nominally two-dimensional mixing layer are used in order to examine the extent to which information on the full VGT can be derived from the reduced VGT. It is shown that the reduced VGT is able to reveal significantly more information about regions of the flow in which strain rate is dominant over rotation. It is thus possible to use the assumptions of homogeneity and isotropy to place bounds on the first two statistical moments (and their covariance) of the eigenvalues of the reduced strain-rate tensor (the symmetric part of the reduced VGT) which in turn relate to the turbulent strain rates. These bounds are shown to be dependent upon the kurtosis of $\partial u_{1}/\partial x_{1}$ and another variable defined from the constituents of the reduced VGT. The kurtosis is observed to be minimised on the centreline of the mixing layer and thus tighter bounds are possible at the centre of the mixing layer than at the periphery. Nevertheless, these bounds are observed to hold for the entirety of the mixing layer, despite departures from local isotropy. The interrogation plane from which the reduced VGT is formed is observed not to affect the joint probability density functions (p.d.f.s) between the strain-rate eigenvalues and the reduced strain-rate eigenvalues despite the fact that this shear flow has a significant mean shear in the cross-stream direction. Further, it is found that the projection of the eigenframe of the strain-rate tensor onto the interrogation plane of the reduced VGT is also independent of the plane that is chosen, validating the approach of bounding the full VGT using the assumption of local isotropy.
Ancestral Radiation of Paenungulate Mammals (Paenungulatomorpha)—New Evidence from the Paleocene of Morocco

ABSTRACT Reported here is the discovery of a new mammal from the middle Paleocene of the Ouled Abdoun phosphate basin, Morocco. Hadrogeneios phosphaticus, gen. et sp. nov., is described based on dental and gnathic specimens. Comparative dental anatomy and CT scan observations support stem relationships to paenungulates. The cladistic analysis relates Hadrogeneios to paenungulatomorphs, especially based on the shared morphotypic condition of a dilambdodont ectoloph linked to inflated stylar cusps. Within the Paenungulatomorpha, Hadrogeneios is plesiomorphic not only with respect to crown paenungulates, but also to Abdounodus and Ocepeia, making it the basalmost known paenungulatomorph. Hadrogeneios, on the other hand, displays a peculiarly specialized mandibular symphyseal region (mentum), which is enlarged and raised high above the cheek teeth, and bears at its apex small incisors that are innervated and vascularized by a peculiar long and thin dorsal canaliculus. This is tentatively interpreted as a plier-like dental apparatus specialized for enhanced oral gripping function of the food, with increasing grip strength or enhanced grip precision. A composite reconstruction of the lower jaw of Hadrogeneios phosphaticus, based on 3D modeling from CT scans, is provided. Hadrogeneios, Abdounodus, and Ocepeia, all from the same Ouled Abdoun Paleocene phosphate levels, are the very rare witnesses of the first evolution and diversification of the endemic African ungulates phylogenetically preceding the modern paenungulate orders.
Theory and applications of weak signal non-linear detection method for incipient fault diagnosis of mechanical equipments

The basic theory and mathematic model of parallel stochastic resonance(PSR),chaotic oscillator and difference resonance were expounded.The correlation analysis was applied to extract the same components from the output of difference SR in the PSR,thereby reduce the dependence on the system parameters.When the chaotic oscillator changing from chaos state to large-scale periodic state,the Hu moment invariant will have a distinct change.So the Hu moment invariant can be used to automatically quantify the phase state of chaotic oscillator.The linear relationship between the phase diagram size and signal amplitude is presented to make up for the shortage that differential oscillator can't detect the signal amplitude.Applying the three nonlinear methods to the fault diagnosis of mechanical equipments,the weak feature information of incipient fault was successfully extracted.
Exploring the Power of Frequent Neighborhood Patterns on Edge Weight Estimation

Since links on social networks model a mixture of many factors, such as acquaintances and friends, the problem of link strength prediction arises: given a social tie e = (u, v) in a social network, how strong the tie e is? Previous work tackles this problem mainly by node profile-based methods, i.e., utilizing users’ profile information. However, some networks do not have node profiles. In this thesis, we study a novel problem of exploring the power of frequent neighborhood patterns on edge weight estimation. Given a labeled graph, we estimate its edge weights by applying its structural information as features. We develop an efficient pattern-growth based mining algorithm to mine frequent neighborhood patterns as features to estimate edge weights. Our experimental results on two real datasets show the efficiency of our method and the effectiveness of the frequent neighborhood pattern based features.
Speculative hybrids: Investigating the generation of conceptual architectural forms through the use of 3D generative adversarial networks

The process of architectural design aims at solving complex problems that have loosely defined formulations, no explicit basis for terminating the problem-solving activity, and where no ideal solution can be achieved. This means that design problems, as wicked problems, sit in a space between incompleteness and precision. Applying digital tools in general and artificial intelligence in particular to design problems will then mediate solution spaces between incompleteness and precision. In this paper, we present a study where we employed machine learning algorithms to generate conceptual architectural forms for site-specific regulations. We created an annotated dataset of single-family homes and used it to train a 3D Generative Adversarial Network that generated annotated point clouds complying with site constraints. Then, we presented the framework to 23 practitioners of architecture in an attempt to understand whether this framework could be a useful tool for early-stage design. We make a three-fold contribution: First, we share an annotated dataset of architecturally relevant 3D point clouds of single-family homes. Next, we present and share the code for a framework and the results from training the 3D generative neural network. Finally, we discuss machine learning and creative work, including how practitioners feel about the emergence of these tools as mediators between incompleteness and precision in architectural design.
High-Order Markov Random Fields for Low-Level Vision

Low-level vision is a fundamental area of computer vision that is concerned with the analysis of digital images at the pixel level and the computation of other dense, pixel-based representations of scenes such as depth and motion. Many of the algorithms and models in low-level vision rely on a representation of prior knowledge about images or other dense scene representations. In the case of images, this prior knowledge represents our a-priori belief in observing a particular image among all conceivable images. Such prior knowledge can be supplied in a variety of different ways; a wide range of low-level vision techniques represent the prior belief using Markov random fields (MRFs). MRFs are a compact and efficient probabilistic representation, and are particularly appropriate for spatially arranged data, such as the pixels in an image. Markov random fields have a long history in low-level computer vision; their representational power, however, has often been limited by restricting them to very local spatial structures. This dissertation introduces a novel, expressive Markov random field model for representing prior knowledge in low-level vision, for example about images and image motion (optical flow). This high-order MRF model, called Fields of Experts (FoE), represents interactions over larger spatial neighborhoods compared to many previous MRF models. Learning the parameters of large MRF models from training data, as well as inferring the quantity of interest (e. g., the noise-free image) are known to be very challenging, both algorithmically and computationally. This is even more so in models that represent complex spatial interactions and have many parameters, such as the FoE model. This dissertation describes machine learning techniques that enable approximate learning and inference with these models. The core thesis developed in this work is that these high-order Markov random fields are more powerful models for representing prior knowledge in low-level vision than previous MRF models, and that they lead to competitive algorithms for varied problems such as image denoising and the estimation of image motion.
The local labour market effects of earthquakes

ABSTRACT Using a balanced panel of local labour market areas (LLMAs) and adopting a new difference-in-differences approach with multiple time periods and multiple groups, this paper assesses the causal effects on local labour market outcomes of the earthquakes that occurred in Italy in 2009, 2012 and 2016. The results show a strong heterogeneity: the 2009 event had significant negative and persistent impacts on the employment rate of the LLMAs involved, while there were no adverse effects for the LLMAs affected by the earthquakes in 2012 and 2016. We also extend the analysis at the industry level in order to highlight the sectoral shifts that typically characterise the aftermath of these natural disasters.
The Goal Setting Challenge App: Promoting Self-Determination Through Technology

Promoting student self-determination is recognized as the best practice in secondary transition planning. Few self-determination interventions have utilized technology to provide individualized learning opportunities. The Goal Setting Challenge (GSC) App was developed to provide a technology-based instructional approach to support developing self-determination. The purpose of this single-case study was to evaluate the impact of the GSC App on self-determination knowledge outcomes for students with disabilities and explore the feasibility of students’ use of the App in transition planning over an academic semester. Results were significantly impacted due to the COVID-19 pandemic; however, this created opportunities to explore feasibility during in-person instruction and the unprecedented shift to remote learning. Findings suggest mixed results related to outcomes for student use and feasibility but suggest the possibility of the App providing a student-friendly means for engaging in self-determination instruction during in-person and remote instruction. Limitations and implications for future research and practice are discussed.
The Effects of Alcohol Intoxication and Withdrawal on Hypothalamic Neurohormones and Extrahypothalamic Neurotransmitters

The aim of the present study was to determine the effects of alcohol intoxication and withdrawal on hypothalamic neurohormones such as corticotropin-releasing factor (CRF) and arginine vasopressin (AVP), and extrahypothalamic neurotransmitters such as striatal dopamine (DA), amygdalar gamma aminobutyric acid (GABA), and hippocampal glutamate (GLU). In addition, the participation of the two CRF receptors, CRF1 and CRF2, was investigated. For this purpose, male Wistar rats were exposed to repeated intraperitoneal (ip) administration of alcohol every 12 h, for 4 days and then for 1 day of alcohol abstinence. On the fifth or sixth day, intracerebroventricular (icv) administration of selective CRF1 antagonist antalarmin or selective CRF2 antagonist astressin2B was performed. After 30 min, the expression and concentration of hypothalamic CRF and AVP, the concentration of plasma adrenocorticotropic hormone (ACTH) and corticosterone (CORT), and the release of striatal DA, amygdalar GABA, and hippocampal GLU were measured. Our results indicate that the neuroendocrine changes induced by alcohol intoxication and withdrawal are mediated by CRF1, not CRF2, except for the changes in hypothalamic AVP, which are not mediated by CRF receptors.
Mechatronic Design of Two-Jaw Pleating End-Effector for Large-Scale Carbon Fibre Reinforced Polymer Manufacturing

Large-scale composite manufacturing processes, particularly vacuum injection moulding, are often hampered by expensive labour costs and low-levels of automation. The current process of manufacturing carbon fibre reinforced polymers (CFRP) for airplane fuselage workpieces requires experienced workers to spend hours manually placing, pleating and migrating multiple layers of fabrics in order to produce the desired composite part. A promising solution is to utilize robot platforms as assistants to alleviate the physical demands of the tasks. In this paper, we present the design and evaluate the performance of our novel Vacuum Infusion Moulding End-Effector (VIMEE) prototype in the pleating procedure of a simulated CFRP manufacturing vacuum bagging process, where our gripper system performs pleat loading, height detection and migration tasks. Experimental results show successful manipulation of nylon pleats by our mechatronic systems design. These results are promising, demonstrating our VIMEE design's potential value in vacuum injection moulding.
Multiscale Self-Attention Architecture in Temporal Neural Network for Nonintrusive Load Monitoring

Nonintrusive load monitoring (NILM) constitutes a significant function of the smart grid in the future. The purpose is to ameliorate the consumption and supply of electricity by disaggregating the total load to the appliance-level load without intrusive monitoring. Recently, energy disaggregation is improved with the emergence of deep learning, but the imbalanced datasets and long sequences bring multiple difficulties to model training. The distribution of ON/OFF states and the limitation of the model lead to massive false-positive samples and undetected events. To tackle these problems, we proposed a multiscale self-attention network (MSANet) to utilize the global temporal correlation and local sequential features. Specifically, the dilated window self-attention mechanism is proposed to compute the local attention, and the multibranch structure is to exploit sequential features of different scales. Furthermore, the embedding of global temporal information is introduced to improve global contextual awareness, and subtask networks are designed for different tasks, respectively, to alleviate the effect of imbalance. The proposed model is evaluated on the reference energy disaggregation dataset (REDD) and U.K.-domestic appliance-level electricity (DALE) dataset and shows outstanding performance on the mean absolute error (MAE) and $F1$ score compared with baseline algorithms.
The use of an autologous platelet-rich fibrin (PRF) membrane for the treatment of deep corneal ulcers in dogs

The aim of this study was to evaluate the clinical efficacy of a platelet-rich fibrin (PRF) membrane, which is considered to be a new alternative surgical method in the treatment of vision-threatening corneal ulcers in dogs. Fourteen dogs (17 eyes) of various breeds and ages with deep corneal ulcers were treated surgically with a PRF membrane transplantation. The corneal ulcer of all the patients was closed with an autologous platelet-rich fibrin membrane. In the first 10 days after the operation, it was observed that the fibrin membrane partially melted, and corneal epithelialization and granulation tissue occurred in and around the ulcer area due to the graft material. Pain was significantly relieved, and conjunctival inflammation was noticeably improved. From the 20th day after the surgery, the granulation tissue was gradually cleaned. It was determined that all the eyes had vision. The most common complications after surgery were corneal pigmentation and fibrosis of varying severity. The use of autologous fibrin membranes is a safe and effective surgical alternative for the closure and healing of corneal ulcers. Our findings show that the autologous platelet-rich fibrin membrane is useful and effective in treating canine corneal deep ulcers.
Vehicle Logo Recognition Using Spatial Structure Correlation and YOLO-T

The vehicle logo contains the vehicle’s identity information, so vehicle logo detection (VLD) technology has extremely important significance. Although the VLD field has been studied for many years, the detection task is still difficult due to the small size of the vehicle logo and the background interference problem. To solve these problems, this paper proposes a method of VLD based on the YOLO-T model and the correlation of the vehicle space structure. Aiming at the small size of the vehicle logo, we propose a vehicle logo detection network called YOLO-T. It integrates multiple receptive fields and establishes a multi-scale detection structure suitable for VLD tasks. In addition, we design an effective pre-training strategy to improve the detection accuracy of YOLO-T. Aiming at the background interference, we use the position correlation between the vehicle lights and the vehicle logo to extract the region of interest of the vehicle logo. This measure not only reduces the search area but also weakens the background interference. We have labeled a new vehicle logo dataset named LOGO-17, which contains 17 different categories of vehicle logos. The experimental results show that our proposed method achieves high detection accuracy and outperforms the existing vehicle logo detection methods.