Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-delay tradeoffs in a linear sequence of relay channels

In this paper, we aim at characterizing the gain induced by using relay channels in a linear network under both capacity constraint and realistic energy model. We express a general model based on a convex optimization problem. Then, we use numerical tools to obtain results on the outer and inner bounds of the capacity of the full and half duplex relay channel. We then further this study with more complex networks based on relay channels, especially networks formed by a linear chain of nodes. We describe the Pareto optimal solutions of the minimization problem with respect to the consumed energy and latency in such a linear network. From the simple case of the linear multi-hop network, we study the gains when implementing a linear chain of relay channels and compare these results to the simpler multi-hop transmission.
Global Motions in the Nucleosome Explored Using a Coarse-Grained Model

The nucleosome is the basic compacting unit of chromatin, a complex structure that enables DNA to ﬁt in the eucaryotic cell nucleus. Because many biological processes require free DNA as a substrate, the nucleosome has to undergo conformational transitions to allow the DNA target sites to be exposed. To obtain insight into the global dynamics of the nucleosome, microsecond timescale coarse-grained molecular dynamics is performed. Here we report a principal component analysis (PCA) realised on a 5 µ s coarse-grained molecular dynamics trajectory to identify the global motions obtained in the nucleosome.
Biophysical Origins of Consciousness

Introduction Recent studies [1-4] of EPR (Einstein-Podolsky-Rosen)generated [5] entangled proton qubit-pairs demonstrate that Grover’s [6] enzyme quantum-readers quantify quantum informational content embodied within entangled proton qubits of rat and human genomic systems [7]. Double-helical DNA is replicated into a “metastable” keto-amino state; so, metastable hydrogen bonded amino (-NH2) genome protons encounter quantum uncertainty limits [1,2], / 2 x x p ∆ ∆ ≥ │ ħ . The resulting quantum mechanical proton proton interaction introduces probabilities of EPR-arrangements, keto-amino-(entanglement) → enol-imine, yielding “qubit-pairs” of entangled enol and imine protons (Figures 1 & 2). Reactions yielding EPR-generated entangled proton qubit-pairs are observed [1,2] as ́ ,́ * * G C G C G C G C − → − − → − and * * A T A T − → − A. (Bold italics ́ ,́* * ,* * G C G C A T − − − denote necessity of Hilbert space to describe dynamics of embedded entangled proton qubit-pairs; see Figures 1 & 2 for notation).
Software structure design for a haptic-based medical examination system

This paper presents a novel approach to software structure design of a haptic-based medical examination simulator. The proposed software is implemented in a fully object-oriented structure that provides real-time interaction with a PHANToM/spl trade/ haptic device, as a diagnostic tool for medical experts. The software allows radiology experts to visualize, display and interact with the graphical model of a patient's pre-scanned organ or tissue. The expert is also able to re-slice through pre-registered model data sets and view the 2D reslice images in different modalities simultaneously. The haptic interface guarantees position correspondence between the operator's hand and a virtual probe. Thus the simulated procedure emulates actual examinations condition in clinic. Our preliminary human factors study at Kingston General Hospital with radiology residents have demonstrated the significant potential of the developed software for scientific and commercial applications.
The Application of Data Mining to Explore Association Rules between Metabolic Syndrome and Lifestyles

This study used an efficient data mining algorithm, called DCIP (the data cutting and inner product method), to explore association rules between the lifestyles of factory workers in Taiwan and the metabolic syndrome. A total of 1,216 workers in four companies completed a lifestyle questionnaire. Results of the questionnaire survey were integrated into the workers' health examination reports to form an attribute database of the metabolic syndrome. Among the association rules derived by DCIP, 80% of those on the list of the top 15 highest support counts are corroborated by medical literature or by healthcare professionals. These findings prove that data mining is a valid and effective research method, and that larger sample sizes will likely produce more accurate associations connecting the metabolic syndrome to specific lifestyles. The rules already verified can serve as a reference guide for the health management of factory workers. The remaining 20%, while still lacking hard evidence, provide fertile ground for future research.
Efficient Lattice-based Authenticated Encryption: A Practice-Oriented Provable Security Approach

Lattice-based cryptography has been received significant attention in the past decade. It has attractive properties such as being a major post-quantum cryptography candidate, enjoying worst-case to average-case security reductions, and being supported by efficient implementations. In recent years, lattice-based schemes have achieved enough maturity to become interesting also for the industry. Additionally, authenticated encryption (AE) is another important topic in the community of cryptography. In this paper, considering two above-mentioned subjects, we propose three lattice-based AEs with an acceptable practical efficiency. These schemes are provably secure assuming the hardness of elementary lattice problems. That is in contrast to the other practical provably-secure AEs, which are based on the hardness assumption of another cryptographic primitive, such as AES. Moreover, we analyze the exact security of these schemes in the paradigm of practice-oriented provable security, while the security proofs of almost all previous lattice-based schemes are asymptotic. The implementation results show that one of the proposed schemes becomes even faster than an AES-256-GCM implementation to encrypt messages of length 64 bytes or longer. Particularly, for a 1500-byte message, this scheme is 34% faster than AES-256-GCM.
Robust speech recognition under noisy environments based on selection of multiple noise suppression methods

Summary form only given. To achieve high recognition performance for a wide variety of noise and for a wide range of signal-to-noise ratio, this paper presents the integration of four noise reduction algorithms: spectral subtraction with smoothing of time direction; temporal domain SVD-based speech enhancement; GMM-based speech estimation; and KLT-based comb-filtering. In this paper, we investigated the optimal suppression method for each noise condition, and then also developed the method of choosing the optimal method automatically for unknown noise. Recognition results on the AURORA-2J task show the effectiveness of our proposed method.
The Assessment Methods of Laryngeal Muscle Activity in Muscle Tension Dysphonia: A Review

The purpose of this paper is to review the methods used for the assessment of muscular tension dysphonia (MTD). The MTD is a functional voice disorder associated with abnormal laryngeal muscle activity. Various assessment methods are available in the literature to evaluate the laryngeal hyperfunction. The case history, laryngoscopy, and palpation are clinical methods for the assessment of patients with MTD. Radiography and surface electromyography (EMG) are objective methods to provide physiological information about MTD. Recent studies show that surface EMG can be an effective tool for assessing muscular tension in MTD.
Maximum Stable Throughput of Network-Coded Multiple Broadcast Sessions for WirelessTandem Random Access Networks

This paper presents an analytical study of the stable throughput for multiple broadcast sessions in a multi-hop wireless tandem network with random access. Intermediate nodes leverage on the broadcast nature of wireless medium access to perform inter-session network coding among different flows. This problem is challenging due to the interaction among nodes, and has been addressed so far only in the saturated mode where all nodes always have packet to send, which results in infinite packet delay. In this paper, we provide a novel model based on multi-class queueing networks to investigate the problem in unsaturated mode. We devise a theoretical framework for computing maximum stable throughput of network coding for a slotted ALOHA-based random access system. Using our formulation, we compare the performance of network coding and traditional routing. Our results show that network coding leads to high throughput gain over traditional routing. We also define a new metric, network unbalance ratio (NUR), that indicates the unbalance status of the utilization factors at different nodes. We show that although the throughput gain of the network coding compared to the traditional routing decreases when the number of nodes tends to infinity, NUR of the former outperforms the latter. We carry out simulations to confirm our theoretical analysis.
Gender differences in adult numeracy skills: what is the role of education?

ABSTRACT Previous research suggests that as societies empower women educationally, gender differences in numeracy skills will decline. Using direct measures of 56,142 adults’ numeracy skills from the Programme for International Assessment for Adult Competencies (PIAAC), this article studies whether this claim is evidenced across 20 Organisation for Economic Co-operation and Development (OECD) countries. Results show that in many countries, as education has equalised over generations, gender differences in adult numeracy skills have indeed declined. However, women’s advances in education have not always been matched by a reduction in the gender difference in adult numeracy. Contrary to expectations, gender differences in fields of study in further and higher education cannot systematically explain gender differences in adult numeracy. This suggests that to achieve gender equality in numeracy skills, societies must do more than empower women educationally. More research is needed on the educational policies, contextual, and life course factors contributing to gender differences in adult numeracy in post-industrial societies.
Visualisation of Cache Coherence Bottlenecks in Shared Memory Multiprocessor Applications

Shared memory multiprocessors are becoming more and more important but one major problem is how to keep the processor caches coherent. Many diff erent solutions to this problem exist and the performance of a given program depends largely on the access pattern observed to shared data, the sharing behaviour. We discuss in this paper how to characterise and visualise sharing behaviour. In terms of cache coherence the degree of sharing, the access mode and the temporal granularity are found to be essential in order to describe and understand sharing behaviour. The sharing behaviour can be measured by simulation and visualised in asharing profile diagram. We use an unblocked matrix multiplication and two diff erent ways of parallelising a blocked matrix multipl ication algorithm to illustrate the problems involved and how the sharing profil e can aid in choosing the right algorithm.
1998 HUB-4 INFORMATION EXTRACTION EVALUATION

This paper documents the Information Extraction Named-Entity Evaluation (IE-NE), one of the new spokes added to the DARPA-sponsored 1998 Hub-4 Broadcast News Evaluation. This paper discusses the information extraction task as posed for the 1998 Broadcast News Evaluation. This paper reviews the evaluation metrics, the scoring process, and the test corpus that was used for the evaluation. Finally, this paper reviews the results of the first running of a Hub-4 IE-NE Evaluation. The Baseline IE-NE evaluation, in which BBN’s IdentiFinder was run on the primary system transcripts submitted for the Hub-4 Broadcast News evaluation, found that the transcripts generated by LIMSI’s automatic speech recognition system produced the "highest" F-measure score (82.39). In the Quasi IE-NE evaluation, where sites ran their own NEtaggers on a set of three baseline recognizer transcripts, the SRI developed tagger achieved the highest F-measure score for baseline recognizers 1 & 3, while the BBN developed tagger achieved the highest score for baseline recognizer 2. In the Full IE-NE evaluation, where sites implemented their own NE-tagger on the their own automatic speech recognizer transcripts, BBN achieved the highest overall F-measure score of 82.22.
Causal Structure and Hierarchies of Models

Economics prefers complete explanations: general over partial equilibrium, microfoundational over aggregate. Similarly, probabilistic accounts of causation frequently prefer greater detail to less as in typical resolutions of Simpson's paradox. Strategies of causal refinement equally aim to distinguish direct from indirect causes. Yet, there are countervailing practices in economics. Representative-agent models aim to capture economic motivation but not to reduce the level of aggregation. Small structural vector-autoregression and dynamic stochastic general-equilibrium models are practically preferred to larger ones. The distinction between exogenous and endogenous variables suggests partitioning the world into distinct subsystems. The tension in these practices is addressed within a structural account of causation inspired by the work of Herbert Simon's, which defines cause with reference to complete systems adapted to deal with incomplete systems and piecemeal evidence. The focus is on understanding the constraints that a structural account of causation places on the freedom to model complex or lower-order systems as simpler or higher-order systems and on to what degree piecemeal evidence can be incorporated into a structural account.
The MatchNMingle Dataset: A Novel Multi-Sensor Resource for the Analysis of Social Interactions and Group Dynamics In-the-Wild During Free-Standing Conversations and Speed Dates

We present MatchNMingle, a novel multimodal/multisensor dataset for the analysis of free-standing conversational groups and speed-dates in-the-wild. MatchNMingle leverages the use of wearable devices and overhead cameras to record social interactions of 92 people during real-life speed-dates, followed by a cocktail party. To our knowledge, MatchNMingle has the largest number of participants, longest recording time and largest set of manual annotations for social actions available in this context in a real-life scenario. It consists of 2 hours of data from wearable acceleration, binary proximity, video, audio, personality surveys, frontal pictures and speed-date responses. Participants’ positions and group formations were manually annotated; as were social actions (eg. speaking, hand gesture) for 30 minutes at 20 FPS making it the first dataset to incorporate the annotation of such cues in this context. We present an empirical analysis of the performance of crowdsourcing workers against trained annotators in simple and complex annotation tasks, founding that although efficient for simple tasks, using crowdsourcing workers for more complex tasks like social action annotation led to additional overhead and poor inter-annotator agreement compared to trained annotators (differences up to 0.4 in Fleiss’ Kappa coefficients). We also provide example experiments of how MatchNMingle can be used.
EasyTrack - Orchestrating Large-scale Mobile User Experimental Studies (poster)

In recent years, large-scale data collection has become crucial in Human-Computer Interaction (HCI) research. With a sharp climb of the amount of data being gathered due to an increasing number of mobile and wearable devices, real-time maintenance of Data Quality (DQ) of data-collection campaigns has already become an overwhelming task, especially in large-scale experiments. This paper proposes EasyTrack, a platform that collects large-scale data in an automatized manners. We describe how our proposed solution detects and tackles issues in data collection campaigns in an automated manner.
Towards a Smart Sustainable City Roadmap

This workshop of the CAP4CITY (Erasmus+ Strengthening Governance Capacity for Smart Sustainable Cities) project is to promote and stimulate the discussion and networking in the area of Digital Government. Smart Sustainable Cities and related concepts of Digital, Intelligent and Smart Cities represent a progression of how cities around the world apply digital technology to serve their populations, pursue sustainable socio-economic development, and transform themselves in the process, and require strong capacity for public governance in the digital world. In order to identify the gaps concerning missing knowledge and training needs in this area we propose to validate a Smart Sustainable Cities roadmap through a scenario-building approach.
Exploiting Similarity Information in Reinforcement Learning - Similarity Models for Multi-Armed Bandits and MDPs

This paper considers reinforcement learning problems with additional similarity information. We start with the simple setting of multi-armed bandits in which the learner knows for each arm its color, where it is assumed that arms of the same color have close mean rewards. An algorithm is presented that shows that this color information can be used to improve the dependency of online regret bounds on the number of arms. Further, we discuss to what extent this approach can be extended to the more general case of Markov decision processes. For the simplest case where the same color for actions means similar rewards and identical transition probabilities, an algorithm and a corresponding online regret bound are given. For the general case where transition probabilities of same-colored actions imply only close but not necessarily identical transition probabilities we give upper and lower bounds on the error by action aggregation with respect to the color information. These bounds also imply that the general case is far more difficult to handle.
Enhancing Access to Situational Vocabulary by Leveraging Geographic Context.

Users of augmentative and alternative communication (AAC) aids could benefit from novel methods for accelerating access to contextually relevant vocabulary. This paper describes our initial efforts toward improving access to situational vocabulary through the use of geographic context to predict vocabulary. A corpus of spoken data produced by one able-bodied male speaker across various locations was collected and used to mine location-specific vocabulary clusters. We describe the data mining algorithm and illustrate how context-driven vocabulary organization and prediction can be integrated into an iconic communication system. Correlations between user and algorithmgenerated vocabulary patterns highlight discrepancies between actual versus perceived frequency statistics. Thus, device customization may be achieved through a hybrid humanalgorithmic approach to vocabulary selection. Endowing the communication aid with knowledge about the user’s location-specific vocabulary patterns may help to balance the burden of communication between the system and the user to yield substantial gains in accessing situationally appropriate vocabulary which may in turn accelerate communication rate.
Microneedle Array Design Determines the Induction of Protective Memory CD8+ T Cell Responses Induced by a Recombinant Live Malaria Vaccine in Mice

Background Vaccine delivery into the skin has received renewed interest due to ease of access to the immune system and microvasculature, however the stratum corneum (SC), must be breached for successful vaccination. This has been achieved by removing the SC by abrasion or scarification or by delivering the vaccine intradermally (ID) with traditional needle-and-syringes or with long microneedle devices. Microneedle patch-based transdermal vaccine studies have predominantly focused on antibody induction by inactivated or subunit vaccines. Here, our principal aim is to determine if the design of a microneedle patch affects the CD8+ T cell responses to a malaria antigen induced by a live vaccine. Methodology and Findings Recombinant modified vaccinia virus Ankara (MVA) expressing a malaria antigen was percutaneously administered to mice using a range of silicon microneedle patches, termed ImmuPatch, that differed in microneedle height, density, patch area and total pore volume. We demonstrate that microneedle arrays that have small total pore volumes induce a significantly greater proportion of central memory T cells that vigorously expand to secondary immunization. Microneedle-mediated vaccine priming induced significantly greater T cell immunity post-boost and equivalent protection against malaria challenge compared to ID vaccination. Notably, unlike ID administration, ImmuPatch-mediated vaccination did not induce inflammatory responses at the site of immunization or in draining lymph nodes. Conclusions/Significance This study demonstrates that the design of microneedle patches significantly influences the magnitude and memory of vaccine-induced CD8+ T cell responses and can be optimised for the induction of desired immune responses. Furthermore, ImmuPatch-mediated delivery may be of benefit to reducing unwanted vaccine reactogenicity. In addition to the advantages of low cost and lack of pain, the development of optimised microneedle array designs for the induction of T cell responses by live vaccines aids the development of solutions to current obstacles of immunization programmes.
Effect of continuous and interval exercise training on the PETCO2 response during a graded exercise test in patients with coronary artery disease

OBJECTIVE: The purpose of this study was to evaluate the following: 1) the effects of continuous exercise training and interval exercise training on the end-tidal carbon dioxide pressure (PETCO2) response during a graded exercise test in patients with coronary artery disease; and 2) the effects of exercise training modalities on the association between PETCO2 at the ventilatory anaerobic threshold (VAT) and indicators of ventilatory efficiency and cardiorespiratory fitness in patients with coronary artery disease. METHODS: Thirty-seven patients (59.7±1.7 years) with coronary artery disease were randomly divided into two groups: continuous exercise training (n = 20) and interval exercise training (n = 17). All patients performed a graded exercise test with respiratory gas analysis before and after three months of the exercise training program to determine the VAT, respiratory compensation point (RCP) and peak oxygen consumption. RESULTS: After the interventions, both groups exhibited increased cardiorespiratory fitness. Indeed, the continuous exercise and interval exercise training groups demonstrated increases in both ventilatory efficiency and PETCO2 values at VAT, RCP, and peak of exercise. Significant associations were observed in both groups: 1) continuous exercise training (PETCO2VAT and cardiorespiratory fitness r = 0.49; PETCO2VAT and ventilatory efficiency r = -0.80) and 2) interval exercise training (PETCO2VAT and cardiorespiratory fitness r = 0.39; PETCO2VAT and ventilatory efficiency r = -0.45). CONCLUSIONS: Both exercise training modalities showed similar increases in PETCO2 levels during a graded exercise test in patients with coronary artery disease, which may be associated with an improvement in ventilatory efficiency and cardiorespiratory fitness.