Miracle-dz/UniFAR-FTUs huggingface dataset:
Enriching scientific publications with semantically related data

Linked Open Data (LOD) and semantic technologies present an enormous potential for a variety of applications. LOD cloud is changing shape in a permanent way with the continuous addition of new datasets. This raises new possibilities for usage and affects the creation of applications on top of these data for various purposes. The purpose of this paper is to describe the use of LOD and semantic technologies to allow content and search results enrichment for digital libraries, with an emphasis to EconBiz case study. The main challenge for achieving this, present the process of contextualization of scientific publications with semantically related data. More specifically we describe the process of creating a profile of publication from the content that is available in a semantic web representation. This would allow detection and alignment of similar publications from different areas, author details, co-authors relativeness, events, organizations, etc. This is claimed to affect significantly the perspective of what should be of digital libraries in the future.
Distributed stochastic routing optimization using expander graph theory

In this paper, we propose a novel algorithm for distributed and decentralized stochastic routing to optimize the convergence rate and the resilience of routing. More precisely, the novelty of our method is the provision of a stochastic routing technique which greatly improves the spectral gap of the routing matrix, as compared to existing methods. We define a novel measure of effective expansion capability of a node, which we use to maximize the spectral gap of the stochastic routing matrix. Simulation results demonstrate that our proposed routing method significantly improves the convergence rate and resilience of routing compared to other existing methods.
Evolution of Relative Synonymous Codon Usage in Human Immunodeficiency Virus Type 1

Mutation in Human Immunodeficiency Virus type-1 (HIV-1) is extremely rapid, a consequence of a low-fidelity viral reverse transcription process. The envelope gene has been shown to accumulate substitutions at a rate of approximately 1% per year and can frequently spend a long time in the host (approximately 10 years). The relative synonymous codon usage (RSCU) in HIV-1 is known to be different from that of the human host. However, by reengineering the protein coding sequences of HIV-1 to reflect the RSCU patterns observed in humans, a large increase in protein expression is observed. It is reasonable to suggest that within a host there may be a selective drive for change in the RSCU of HIV-1 towards human RSCU. To test this hypothesis we analyzed HIV-1 partial envelope sequences from eight patients sampled serially in time. For each sequence, an RSCU table was constructed. Sequences were labelled as "early" or "late" depending on whether they were sampled before or after the mid-point of the study. Using the RSCU values as descriptor variables, a Principal Components Analysis (PCA) was performed. The first three components clearly discriminated between early and late sequences. We also constructed pooled groupwise RSCU tables for early and late sequences. The viral RSCU values of each of the groups were correlated with human RSCU. If there is selection for host-adaptation in RSCU, we expect that "late" viral RSCUs would tend to be more highly correlated with human RSCU than "early" viral RSCUs. In fact, tests of significance suggest that this is the case. However, closer examination of the data revealed that the apparent trend towards human RSCU can be attributed to the homogenization of the codon usage by mutation pressure rather than host adaptation.
Multi-Bernoulli based track-before-detect with road constraints

The random set based multi-Bernoulli filter is applied to a challenging low signal to noise track before detect scenario. Specifically we use the variant of the multi-Bernoulli filter that processes raw image observations. We add an additional layer of track management logic to output trajectories rather than point estimates. The tracker also exploits additional road map information by integrating the roads into the filtering likelihood. We show that this approach of using the image observation MeMBer filter with track management and road constrained model can yield an effective tracker for track before detect scenarios.
New Organizational Forms can Emerge when CSCW systems are Implemented in the Swedish Social Insurance Board

The CSCW technology enables a flexible design of the organisation compared with the old technology. New organisation forms emerge that are flexible, boundless and process-oriented. In this article a case study is presented of the development and test of a prototype in Lotus Notes for dealing with social insurance matters within the Swedish Social Insurance Board. The focus of the case study is on integration of work organisation aspects into the development process of CSCW systems. The design of the technology and the organisation could affect the work organisation of the individual as well as efficiency and quality aspects. Scenarios are proposed as a technique for discussion and design of the future work organisation of CSCW systems.
Predição temporal de links baseada na evolução de tríades

Nowadays, with the development of artiﬁcial intelligence and the need to study virtual social networks, the importance of the analysis of such networks has grown. There are many problems that arise when studying these networks, including the Link Prediction problem in a social network, a task associated with Social Network Analysis. The current state-of-the-art on Link Predictionseekstoﬁndahiddenpatterninthenetwork,includingstructuralpatterns,similarities and statistical characteristics and evolving to more complex models, like temporal patterns. This work aims to create a new temporal method, called Temporal Link Prediction based on Triads Evolution, which provides a more satisfactory and efﬁcient solution for the Link Prediction problem. To achieve this goal, a new temporal data model, the Triad Transition Tensor, was created and used as a source to compute temporal forecasting statistic models based on time series. This method was conceived from a wide analysis of the state-of-the-art of the Link Predictionmethodsandidentifyingit’sadvantagesandlimitations. Theresultsinthisworkshow that, compared to other methods found in related works, there was a considerable improvement in the quality of the predictions when using the proposed method.
Priority control based on website categories in edge computing

Modern websites consist of many rich objects dynamically produced by servers and client terminals at diverse locations. To deliver dynamic objects efficiently, edge computing in which objects are dynamically generated and delivered to client terminals on edge servers located at edge nodes will be effective. It is anticipated that the effectiveness of edge computing depends on the geographical pattern of object deployment, and the tendency of geographical distribution of objects is different among website categories, e.g., Sports and News, so it seems effective to prioritize website categories for edge computing. In this paper, we first propose a platform for measuring the geographical tendency of object deployment in each website category. We then propose to differentiate the caching priority in edge computing among website categories based on the measured deployment pattern of objects. Through the experience of accessing about 1,000 of the most popular websites from 12 locations worldwide using PlanetLab, we clarify that we can improve the reduction ratio of web response time by about 20% by carefully differentiating caching priority among website categories.
Advancements in web accessibility evaluation methods: how far are we?

Achieving web accessibility has become a global aim nowadays, especially with the significant inclusion of the Internet in our daily lives. There exist different accessibility evaluation methods that support web developers and designers during websites' development life cycle, and each has different benefits and drawbacks. However, many studies show that there is a continued lack of equality between disabled and non-disabled people in benefitting from the web, especially with the prolonged growth of web development standards and techniques, which raises a demand for continuous improvement in web accessibility evaluation methods in order to gain reliable results. Given this demand, our paper investigates the advancements in web accessibility evaluation methods for the past five years (2011-2015). The results reveal a lack of significant evolution of these evaluation methods. Based on our findings, more efforts are required for enhancing accessibility evaluation techniques in order to achieve better web accessibility.
BLUE: A bipedal robot with variable stiffness and damping

Exploiting variable impedance for dynamic tasks such as walking is both challenging and topical - research progress in this area impacts not only autonomous, bipedal mobility but also prosthetics and exoskeletons. In this work, we present the design, construction and preliminary testing of a planar bipedal robot with joints capable of physically varying both their stiffness and damping independently - the first of its kind. A wide variety of candidate variable stiffness and damping actuator designs are investigated. Informed by human biophysics and locomotion studies, we design an appropriate (heterogenous) impedance modulation mechanism that fits the necessary torque and stiffness range and rate requirements at each joint while ensuring the right form factor. In addition to hip, knee and ankle, the constructed robot is also equipped with a three part compliant foot modelled on human morphology. We describe in detail the hardware construction and the communication and control interfaces. We also present a full physics based dynamic simulation which matches the hardware closely. Finally, we test impedance modulation response characteristics and a basic walking gait realised through a simple movement controller, both in simulation and on the real hardware.
A new approach for target motion analysis with signal time delay

A new approach is proposed in this paper for the problem of the target motion analysis (TMA) with signal propagation time delay. This problem is an unobservable tracking problem in which the acoustic signal transmits with time delay. We present an intelligent range parameterized unscented Kalman filter (IRPUKF) algorithm to estimate the state of the nonlinear unobservable tracking system and propose a recursive model parameter online adjustment method to deal with the time delay in signal propagation. In a simulation of tracking target using a maneuvering acoustic sensor with signal time delay case study, the effectiveness and efficiency of the proposed algorithm is testified to perform better, compared with the range parameterized extended Kalman filter (RPEKF) algorithm.
A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.
Glassy transition and aging in a model without disorder.

We study the off-equilibrium relaxational dynamics of the Amit-Roginsky $\phi^3$ field theory, for which the mode coupling approximation is exact. We show that complex phenomena such as aging and ergodicity breaking are present at low temperature, similarly to what is found in long range spin glasses. This is a generalization of mode coupling theory of the structural glass transition to off-equilibrium situations.
The impact of interactive manipulation on the recognition of objects

A new application for VR has emerged: product development, in which several stakeholders (from engineers to end users) use the same VR for development and communicate purposes. Various characteristics among these stakeholders vary considerably, which imposes potential constraints to the VR. The current paper discusses the influence of three types of exploration of objects (i.e., none, passive, active) on one of these characteristics: the ability to form mental representations or visuo-spatial ability (VSA). Through an experiment we found that all users benefit from exploring objects. Moreover, people with low VSA (e.g., end users) benefit from an interactive exploration of objects opposed to people with a medium or high VSA (e.g. engineers), who are not sensitive for the type of exploration. Hence, for VR environments in which multiple stakeholders participate (e.g. for product development), differences among their cognitive abilities (e.g., VSA) have to be taken into account to enable an efficient usage of VR.
Effectiveness of the 2010 and 2011 Southern Hemisphere trivalent inactivated influenza vaccines against hospitalization with influenza-associated acute respiratory infection among Thai adults aged ≥50 years

Inactivated influenza vaccine (IIV) effectiveness has been evaluated among older adults in high‐income countries, but data on IIV effectiveness in low‐ and middle‐income countries remain sparse. We conducted a test‐negative case–control analysis to estimate 2010 and 2011 trivalent IIV effectiveness against hospitalization with influenza‐associated acute respiratory infection (ARI) among persons aged ≥50 years in rural Thailand.
Case for Cooperative Cloud Intermediaries for Small and Medium-Sized EnterprisesA

Cloud computing is a new and increasingly popular form of IT outsourcing. It implies that a cloud service provider offers very standardized abstract IT services which are accessed by a user over the Internet. While cloud services are supposed to be very beneficial for small and medium-sized enterprises, the adoption of such services has been low in this group, among other reasons because of high complexity of the cloud market and trust concerns. This paper motivates the notion of cooperative cloud intermediaries as a solution for these concerns by building on well-known concepts: transaction cost theory, agency theory, the notion of intermediaries in electronic markets and the cooperative paradigm. We derive our solution in detail and show its viability in theory.
IGCEGA: A Novel Heuristic Approach for Personalisation of Cold Start Problem

IGCEGA, an acronym for Information Gain Clustering through Elitizt Genetic Algorithm, is a novel heuristic used in Recommender System (RS) for solving personalization problems. In comparison with IGCGA (Information Gain Clustering through Genetic Algorithm), IGCEGA is not associated with the inherent problem of increasing the possibility of losing good solution during the crossover phase, which translates into increasing the guarantee of converging to a global minima and consequently, enhancing the accuracy of the recommendation. Besides, IGCEGA using the technique of global minima still resolves the problem associated with IGCN (Information Gain through Clustered Neighbor), which traps the algorithm in local clustering centroids. Although this problem was alleviated by IGCGA, IGCEGA solves the problem even better because IGCEGA assumes the lowest Mean Absolute Error (MAE), the evaluation matrix used in this work. Results of the experimentation of the various heuristics / techniques in RS used in personalization for cold start problems -- for instance Popularity, Entropy, IGCN, IGCGA - showed that IGCEGA is associated with the lowest MAE, therefore, best clustering, which in turn results into best recommendation.
On the semantics of epistemic description logics . (Extended Abstract)

The modal description logic AEA:/C both constitutes a promising framework for reasoning about actions and allows for the formalization of several non-first-order aspects of KR systems based on DLs. However, other nonmonotonic features of DL-based KR systems, in particular role and concept closure inside the knowledge base, lack an intuitive formalization in this modal framework. To overcome these difficulties, we propose a modification of the semantics for . A£CIC, which consists in allowing selective minimization of primitive concepts and roles, thus providing for a correct formalization of the notion of role and concept closure.
Development and validation of an HPLC method for stability evaluation of nystatin

A liquid chromatography method for evaluating the stability of Nystatin (Nys) in an ointment was developed and validated, since the traditional pharmacopeial microbiological methods are unable to indicate stability. The stress experiments showed that Nys was found to significantly degrade in alkaline and acidic conditions and also under oxidative stress. Lower levels of degradation were detected under heat and with the sample exposed to Xenon light. Resolutions higher than 2 for Nys and degradation products (DP) chromatographic peaks were achieved by using an Inerstil ODS-3 column, isocratic elution with methanol:water and UV detection at 305 nm. The system was found to be linear over a range of 102 to 310 IU mL-1 and proved precise, since the RSD(%) was 0.24% for the six replicates tested. The method also exhibited good levels of recovery (from 98.24% to 100.74%). Therefore, the validation fulfilled pharmacopeial requirements and the procedure was found to be reliable, precise, accurate and selective for determination of Nys and its degradation products.
The Basolateral Amygdala Responds Robustly to Social 10 Calls : Response Characteristics of Single Unit Activity

35 Vocalizations emitted within a social context can trigger call-specific changes in the 36 emotional and physiological/autonomic state of the receiver. The amygdala is implicated in 37 mediating these changes, but its role in call perception remains relatively unexplored. We 38 examined call and pitch selectivity of single neurons within the basolateral amygdala (BLA) by 39 recording spiking activity in response to five pitch-variants of each of 14 species-specific calls 40 presented to awake, head-restrained mustached bats, Pteronotus parnellii. A response-wise 41 analysis across neurons revealed 7 types of temporal response patterns based on the timing 42 and duration of spiking. Roughly half of the responses to different call types were significantly 43 affected by changes in their pitch. A neuron-wise analysis revealed that about 12% (8/69) of 44 the neurons preferred the same pitch across all call types. 93% (93/100) of neurons were 45 excited by at least one call type and 76% exhibited either complete or transient suppression to 46 one or more call types. The majority of neurons preferred fewer than half of the 14 different 47 simple-syllabic calls. A call-wise analysis of spiking activity revealed that call types signaling 48 either threat or fear most consistently evoked increases in the spike rate. In contrast, calls 49 emitted during appeasement tended to evoke spike suppression. Our data suggest that BLA 50 neurons participate in the processing of multiple call types and exhibit a rich variety of 51 temporal response patterns that are neither neuron nor call-specific.
True Zero-Training Brain-Computer Interfacing – An Online Study

Despite several approaches to realize subject-to-subject transfer of pre-trained classifiers, the full performance of a Brain-Computer Interface (BCI) for a novel user can only be reached by presenting the BCI system with data from the novel user. In typical state-of-the-art BCI systems with a supervised classifier, the labeled data is collected during a calibration recording, in which the user is asked to perform a specific task. Based on the known labels of this recording, the BCI's classifier can learn to decode the individual's brain signals. Unfortunately, this calibration recording consumes valuable time. Furthermore, it is unproductive with respect to the final BCI application, e.g. text entry. Therefore, the calibration period must be reduced to a minimum, which is especially important for patients with a limited concentration ability. The main contribution of this manuscript is an online study on unsupervised learning in an auditory event-related potential (ERP) paradigm. Our results demonstrate that the calibration recording can be bypassed by utilizing an unsupervised trained classifier, that is initialized randomly and updated during usage. Initially, the unsupervised classifier tends to make decoding mistakes, as the classifier might not have seen enough data to build a reliable model. Using a constant re-analysis of the previously spelled symbols, these initially misspelled symbols can be rectified posthoc when the classifier has learned to decode the signals. We compare the spelling performance of our unsupervised approach and of the unsupervised posthoc approach to the standard supervised calibration-based dogma for n = 10 healthy users. To assess the learning behavior of our approach, it is unsupervised trained from scratch three times per user. Even with the relatively low SNR of an auditory ERP paradigm, the results show that after a limited number of trials (30 trials), the unsupervised approach performs comparably to a classic supervised model.
Shoe-integrated sensor system for wireless gait analysis and real-time feedback

We are developing a sensor system for use in clinical gait analysis. This research involves the development of an on-shoe device that can be used for continuous and real-time monitoring of gait. This paper presents the design of an instrumented insole and a removable instrumented shoe attachment. Transmission of the data is in real-time and wireless, providing information about the three-dimensional motion, position, and pressure distribution of the foot. Using pattern recognition and numerical analysis of the calibrated sensor outputs, algorithms will be developed to analyze the data in real-time. Results will be validated by comparison to results from a commercial optical gait analysis system at the Massachusetts General Hospital (MGH) Biomoti on Lab.