Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of fluctuating soundscapes in shaping the emotional geographies of individuals living with Ménière’s disease

Abstract The potential for everyday soundscapes to evoke diverse emotions amongst different cultural and acoustic communities is increasingly recognised within the literature. However, few studies have examined how these soundscapes can shift with the onset and progression of specific hearing impairments. This paper explores such shifts, drawing on a series of in-depth narrative interviews conducted in the south west of England with individuals diagnosed with Ménière’s disease; a long-term progressive vestibular disorder characterised by episodes of vertigo, tinnitus, sensorineural hearing loss and, for some people, hyperacusis (high sensitivity to sudden irregular sounds). Located in the subfield of ‘emotional geographies’, the paper discusses how participants were forced to connect with and attune to previously unremarkable aspects of their everyday soundscapes in ways that were both emotionally and socially challenging. Four aspects of participants’ embodied, emotional soundscapes are critically explored: hearing life in ‘2D’; corporeal and environmental ‘sonic intruders’; corporeal sound ‘symbols’; and seeking to regain a semblance of control through soundscape (re)-negotiations. Such insights are important to inform conscious acoustic design efforts that respect the ‘ears and voice’ of people living with varying levels of auditory sensitivity, rather than urban and community planning policies that continue to prioritise vision and transit.
An extensive math query language

Math search is a new area of research with many enabling technologies but also many challenges. Some of the enabling technologies include XML, XPath, XQuery, and MathML. Some of the challenges involve enabling search systems to recognize mathematical symbols and structures. Several math search projects have made considerable progress in meeting those challenges. One of the remaining challenges is the creation and implementation of a math query language that enables the general users to express their information needs intuitively yet precisely. This paper will present such a language and detail its features. The new math query language offers an alternative way to describe mathematical expressions that is more consistent and less ambiguous than conventional mathematical notation. In addition, the language goes beyond the Boolean and proximity query syntax found in standard text search systems. It defines a powerful set of wildcards that are deemed important for math search. These wildcards provide for more precise structural search and multi-levels of abstractions.
THE SAR MEASUREMENT OF OCEAN WAVES : WAVE SESSION WHITEPAPER

Remote sensing techniques enable the measurement of ocean wave fields with both high resolution and large coverage. As the acquisition of active radar data is independent of daylight and cloud conditions, these data are therefore believed to be most suited for operational use at weather centers and governmental agencies, as well as for many ongoing scientific investigations. In the present overview paper the determination of sea state parameters from radar images together with some results from the operational use at weather centers are given. Synthetic aperture radar (SAR) yields high resolution two dimensional images of the radar backscatter properties of the sea surface and can thus be used to measure wind fields and sea state from space. The determination of ocean wave spectra from SAR image spectra is sensitive to various imaging effects due to sea surface features, spatial variation of wind speed, rain, current and motion of the sea surface. Thus, measuring ocean wave parameters is related to most of the other measurements of marine parameters described in this volume. In this paper an overview of the SAR satellite missions is given, as well as a description of the basic techniques to measure ocean waves by SAR and validation against wave model results and other space borne and in situ measurements. The full two dimensional SAR image spectrum provides information on the directional ocean wave spectrum. This can be used to determine expectation values of, e.g. , significant wave height, mean wavelength and direction in order to improve the wave model prediction. In addition information can be gathered from the radar images directly such as individual wave height, crest length and groupiness of the ocean waves. Thus, the distribution of maximum wave height can be investigated globally, or wave refraction and diffraction in coastal areas can be studied in detail. Fig. 1: 10 x 15 km cutout from a SEASAT SAR image acquired on 20 Aug 1978 at the Portuguese coast showing swell refraction, wave breaking and internal waves. In the following an overview of ocean wave measurements from space are given, the papers presented in the wave session are put into the general context and applications for weather prediction, ship routing, oil and shipbuilding industry and ship classifying societies are discussed. A general overview on theory and measurement of directional wave spectra, including a special chapter on remote sensing of directional ocean wave spectra together with an extensive literature list is given in the
HE ROLE OF CONTRAST IN THE DISTRIBUTIONAL RESTRICTIONS ON J APANESE PALATALIZED

Phonemes or sequences of phonemes can be subject to distributional restrictions. Certain phonological forms in a language appear freely in some contexts but never, or very rarely, in others. Recent studies have shown that the notion of contrast and perceptual distinctiveness plays an important role in such distributional restrictions (Flemming 1995, Gallagher 2010, Padgett 2001 to name a few). From this point of view, grammar disfavors not the phonological forms that are absent from the inventory but rather perceptually indistinct contrasts that they would give rise to. This paper points out previously unnoticed skewed distributional patterns of Japanese palatalized consonants and claims that they are another instance of restrictions that are grounded on perceptual distinctiveness. The first goal of the study is to give a full analysis of the limited distribution of Japanese palatalized consonants. The second goal is to provide empirical evidence that some, if not all, distributional restrictions should be analyzed in terms of constraints on contrasts.
Targeted p120-Catenin Ablation Disrupts Dental Enamel Development

Dental enamel development occurs in stages. The ameloblast cell layer is adjacent to, and is responsible for, enamel formation. When rodent pre-ameloblasts become tall columnar secretory-stage ameloblasts, they secrete enamel matrix proteins, and the ameloblasts start moving in rows that slide by one another. This movement is necessary to form the characteristic decussating enamel prism pattern. Thus, a dynamic system of intercellular interactions is required for proper enamel development. Cadherins are components of the adherens junction (AJ), and they span the cell membrane to mediate attachment to adjacent cells. p120 stabilizes cadherins by preventing their internalization and degradation. So, we asked if p120-mediated cadherin stability is important for dental enamel formation. Targeted p120 ablation in the mouse enamel organ had a striking effect. Secretory stage ameloblasts detached from surrounding tissues, lost polarity, flattened, and ameloblast E- and N-cadherin expression became undetectable by immunostaining. The enamel itself was poorly mineralized and appeared to be composed of a thin layer of merged spheres that abraded from the tooth. Significantly, p120 mosaic mouse teeth were capable of forming normal enamel demonstrating that the enamel defects were not a secondary effect of p120 ablation. Surprisingly, blood-filled sinusoids developed in random locations around the developing teeth. This has not been observed in other p120-ablated tissues and may be due to altered p120-mediated cell signaling. These data reveal a critical role for p120 in tooth and dental enamel development and are consistent with p120 directing the attachment and detachment of the secretory stage ameloblasts as they move in rows.
Examplers based image fusion features for face recognition

Examplers of a face are formed from multiple gallery images of a person and are used in the process of classification of a test image. We incorporate such examplers in forming a biologically inspired local binary decisions on similarity based face recognition method. As opposed to single model approaches such as face averages the exampler based approach results in higher recognition accu- racies and stability. Using multiple training samples per person, the method shows the following recognition accuracies: 99.0% on AR, 99.5% on FERET, 99.5% on ORL, 99.3% on EYALE, 100.0% on YALE and 100.0% on CALTECH face databases. In addition to face recognition, the method also detects the natural variability in the face images which can find application in automatic tagging of face images.
Disaster at a University: A Case Study in Information Security

To this end, we present a case that addresses a data breach at a university caused by lax security policies and includes an element of social engineering. The data breach at the university resulted in a number of students’ losing personally identifiable information. The resulting aftermath placed a significant financial burden on the university as it was not prepared to handle an information security disaster. This case can be used as a pedagogical tool as it uniquely captured a data breach in a university setting. Readers of the case will identify that at the management level the case raised a number of issues regarding the security culture at the university and management of security function. The case also highlights the issues of lack of training and access control.
The Selective Interaction between Silica Nanoparticles and Enzymes from Molecular Dynamics Simulations

Nanoscale particles have become promising materials in many fields, such as cancer therapeutics, diagnosis, imaging, drug delivery, catalysis, as well as biosensors. In order to stimulate and facilitate these applications, there is an urgent need for the understanding of the interaction mode between the nano-particles and proteins. In this study, we investigate the orientation and adsorption between several enzymes (cytochrome c, RNase A, lysozyme) and 4 nm/11 nm silica nanoparticles (SNPs) by using molecular dynamics (MD) simulation. Our results show that three enzymes are adsorbed onto the surfaces of both 4 nm and 11 nm SNPs during our MD simulations and the small SNPs induce greater structural stabilization. The active site of cytochrome c is far away from the surface of 4 nm SNPs, while it is adsorbed onto the surface of 11 nm SNPs. We also explore the influences of different groups (-OH, -COOH, -NH2 and CH3) coated onto silica nanoparticles, which show significantly different impacts. Our molecular dynamics results indicate the selective interaction between silicon nanoparticles and enzymes, which is consistent with experimental results. Our study provides useful guides for designing/modifying nanomaterials to interact with proteins for their bio-applications.
An online trajectory planning method for visually guided assisted reaching through a rehabilitation robot

Several manipulators or exoskeleton are characterized by having a concave workspace in the operational space due to mechanical limits. This article proposes an online trajectory planning method for performing visually guided assisted reaching through a rehabilitation robotic exoskeleton, the L-Exos, in its concave workspace. To evalute the proposed methodology in a rehabilitation application, we set-up a computer vision based system that can automatically identify target objects in the workspace and generate a robot assisted movement to reach them through the L-Exos.
Iodine Deficiency in Pregnancy: The Effect on Neurodevelopment in the Child

Iodine is an integral part of the thyroid hormones, thyroxine (T4) and tri-iodothyronine (T3), necessary for normal growth and development. An adequate supply of cerebral T3, generated in the fetal brain from maternal free T4 (fT4), is needed by the fetus for thyroid hormone dependent neurodevelopment, which begins in the second half of the first trimester of pregnancy. Around the beginning of the second trimester the fetal thyroid also begins to produce hormones but the reserves of the fetal gland are low, thus maternal thyroid hormones contribute to total fetal thyroid hormone concentrations until birth. In order for pregnant women to produce enough thyroid hormones to meet both her own and her baby’s requirements, a 50% increase in iodine intake is recommended. A lack of iodine in the diet may result in the mother becoming iodine deficient, and subsequently the fetus. In iodine deficiency, hypothyroxinemia (i.e., low maternal fT4) results in damage to the developing brain, which is further aggravated by hypothyroidism in the fetus. The most serious consequence of iodine deficiency is cretinism, characterised by profound mental retardation. There is unequivocal evidence that severe iodine deficiency in pregnancy impairs brain development in the child. However, only two intervention trials have assessed neurodevelopment in children of moderately iodine deficient mothers finding improved neurodevelopment in children of mothers supplemented earlier rather than later in pregnancy; both studies were not randomised and were uncontrolled. Thus, there is a need for well-designed trials to determine the effect of iodine supplementation in moderate to mildly iodine deficient pregnant women on neurodevelopment in the child.
How to put archaeological geometric data into context? Representing mining history research with CIDOC CRM and extensions

A wealth of information on cultural heritage coming from archaeological investigations exists in the form of geometric information. Here we want to question how this geometric information relates back to the reality it was intended to document. Building upon the CIDOC CRM - an ontology to represent data for cultural heritage - we apply CRMgeo, an extension to the CIDOC CRM that treats space always in combination with time which is essential to archaeological investigations. Interdisciplinary research on mining sites in Austria within the project HIMAT serves as the field of application for showing our proposal how to put geometries into context. From the various research conducted in the course of HIMAT we selected prospection activities, archaeological excavations, survey and dendrochronological analysis for a prototypical modelling. We want to show how such a modelling may help to answer practical research questions like reconstructing the spatial organisation of the metallurgical production chain.
A Population Dynamics Model for Data Streaming over P2P Networks

Data streaming (DS) over Peer-to-Peer (P2P) networks has been intensively studied in recent years and there have been various schemes proposed already. To evaluate these schemes, either measurement in experimental implementations, or simulation and theoretical analysis have been used. The former is inadequate as data are collected from different experiments, while the latter lacks a proper theoretical dynamics model. Our research aims at providing a general theoretical model to evaluate DS over P2P systems and analyze their dynamic behaviors. In this paper, with the analysis and abstraction of the characteristics of peers and their organization in DS over P2P, we propose a general population dynamics model for DS over P2P with fixed population. The model depicts the dynamic distribution of peers as a closed Markov queuing network. In particular, the model is scheme-independent and can be used with various schemes. Through theoretical analysis, we prove the model has equilibrium and only one closed-form solution. Besides, we verify the model through simulations, and show that it is a helpful analytical tool with a case study.
Super-reflection and cloaking based on zero index metamaterial

A zero index metamaterial (ZIM) can be utilized to block wave (super-reflection) or conceal objects completely (cloaking). The “super-reflection” device can be realized by a Mu zero (Epsilon zero) metamaterial with a perfect electric (magnetic) conductor inclusion of arbitrary shape and size for a transverse electric (magnetic) incident wave. In contrast, a Mu zero (Epsilon zero) metamaterial with a perfect magnetic (electric) conductor inclusion for a transverse electric (magnetic) incident wave can be used to conceal objects of arbitrary shape. The underlying physics here is determined by the intrinsic properties of the ZIM.
Automated discrimination of gait patterns based on sEMG recognition using neural networks

A set of schemes for automated discrimination of gait patterns based on recognition of surface electromyogram (sEMG) of human lower limbs is proposed to classify 3 different terrains and 6 different movement patterns. To compare the recognition performance of different classifiers, Back Propagation Neural Networks (BPNNs) and Process Neural Networks (PNNs) are deployed to discriminate gait patterns under different conditions. To obtain the discrete inputs to BPNNs, time-frequency parameters, wavelet variance and matrix singularity values are separately considered as the feature vector. Since PNNs can deal with time-varying functions without signal discretion or feature extraction, sEMG signal after filtering is directly fed to the neural networks to discriminate different gaits. To improve the learning efficiency and accuracy, partial swarm optimization (PSO) is used to obtain the weight parameters of PNNs. Simulations were conducted to validate the efficiencies and recognition accuracies of different neural classifiers. PNNs show good adaptability and robustness and have great potential in the application of bio-electrical signal processing.
Software-defined open architecture for front- and backhaul in 5G mobile networks

New software-defined open network concepts are proposed in this paper to enable an efficient implementation of front- and backhaul solutions for future 5G mobile networks. Main requirements for 5G front- and backhaul are derived and then related to the open network architecture enabling multiple operators to share the same physical infrastructure. The value of software-defined networking (SDN) is particularly outlined therefore. For the use of SDN in the fronthaul, CPRI over Ethernet (CoE) is proposed as a new transport protocol. In the backhaul, distributed security can be implemented using SDN where direct links are confined inside the access domain, as opposed to the current centralized security solution including also the transport domain. In this way, low latency can be realized e.g. for machine-type communications. As the benefits for fixed-mobile convergence are evident, SDN should be enabled increasingly in the access domain.
Generic Transfer for General Spin Groups

We prove Langlands functoriality for the generic spectrum of general spin groups (both odd and even). Contrary to other recent instances of functoriality, our resulting automorphic representations on the general linear group are not self-dual. Together with cases of classical groups, this completes the list of cases of split reductive groups whose L-groups have classical derived groups. The important transfer from GSp4 to GL4 follows from our result as a special case.
Cost-priority cognizant regression testing

Any change in software requires all the test cases, developed earlier, to be re-executed. This is done to make sure that the changes have not affected the proper working of the software. Since it is usually impossible to re-run all the test cases, the number of test cases, to be reexecuted, must be reduced. Prioritization, reduction and selection are the three techniques used to accomplish the same. The basis of the prioritization of test cases can be the time of execution or the cost. A test case suite has many test cases. The sequence of test cases in a suite also plays a part in evaluating the effectiveness of a suite. Both cost and priority should be taken into account to determine the order of test suites. This work proposes a fitness function, which depends on both factors. This fitness function would decide the priority of the test cases. Since it is an optimization problem, Genetic Algorithms have been used to accomplish the task. In order to verify the technique, the test data of four testing cycles of a professional Enterprise Resource Planning System has been used.
Classification Strategies for Image Classification in Genetic Programming

This paper describes an approach to the use of genetic programming for multi-class image recognition problems. In this approach, the terminal set is constructed with image pixel statistics, the function set consists of arithmetic and conditional operators, and the fitness function is based on classification accuracy in the training set. Rather than using fixed static thresholds as boundaries to distinguish between different classes, this approach introduces two dynamic methods of classification, namely centred dynamic range selection and slotted dynamic range selection, based on the returned value of an evolved genetic program where the boundaries between different classes can be dynamically determined during the evolutionary process. The two dynamic methods are applied to five image datasets of classification problems of increasing difficulty and are compared with the commonly used static range selection method. The results suggest that, while the static boundary selection method works well on relatively easy binary or tertiary image classification problems with class labels arranged in the natural order, the two dynamic range selection methods outperform the static method for more difficult, multiple class problems.
Measuring mass-loss rates from Galactic satellites

Number count profiles of many Galactic and some extra-galactic satellite systems show evidence for associated stars beyond the cut-off in density that is identified as the point of tidal limitation (e.g. Irwin & Hatzidimitriou 1995, Grillmair et al. 1995). These “extra-tidal” stars are assumed to be debris lost from the satellite due to heating or stripping by the Galactic tidal field or (in the case of globular clusters) evaporation of stars over the tidal boundary. In this contribution we present a method for using these features to measure the mass loss rate from the satellite, and test it on the results of numerical simulations of satellite disruption. A more detailed discussion of all aspects of this work can be found in (1998).
Decisions From Experience and Statistical Probabilities: Why They Trigger Different Choices Than a Priori Probabilities

The distinction between risk and uncertainty is deeply entrenched in psychologists' and economists' thinking. Knight ([1921]), to whom it is frequently attributed, however, went beyond this dichotomy. Within the domain of risk, he set apart a priori and statistical probabilities, a distinction that maps onto that between decisions from description and experience, respectively. We argue this distinction is important because risky choices based on a priori (described) and statistical (experienced) probabilities can substantially diverge. To understand why, we examine various possible contributing factors to the description-experience gap. We find that payoff variability and memory limitations play only a small role in the emergence of the gap. In contrast, the presence of rare events and their representation as either natural frequencies in decisions from experience or single-event probabilities in decisions from description appear relevant for the gap.