Miracle-dz/UniFAR-FTUs huggingface dataset:
Animal Disease Event Recognition and Classication

Monitoring epidemic crises, caused by rapid spread of infec- tious animal diseases, can be facilitated by the plethora of information about disease-related events that is available online. Therefore, the abil- ity to use this information to perform domain-specic entity recognition and event-related sentence classication, which in turn can support time and space visualization of automatically extracted events, is highly desir- able. Towards this goal, we present a rule-based approach to the problem of extracting animal disease-related events from web documents. Our ap- proach relies on the recognition of structured entity tuples, consisting of attributes, which describe events related to animal diseases. The event attributes that we consider include animal diseases, dates, species and geo-referenced locations. We perform disease names and species recog- nition using an automatically-constructed ontology, dates are extracted using regular expressions, while location are extracted using a condi- tional random elds tool. The extracted events are further classied as conrmed or suspected based on semantic features, obtained from the e.g., GoogleSets 1 and WordNet 2 . Our preliminary results demonstrate the feasibility of the proposed approach.
Applying Formal Approach to Core Asset Instantiation in Product Line Engineering

As an effective reuse approach, product line engineering (PLE) is used to develop a number of applications by instantiating a reusable core asset. Current research works mostly center on domain engineering, it is yet to define how to instantiate core assets systematically and to validate the instantiation process. We believe that formal specifications have a great potential in defining detailed and precise instantiation process. In this paper, we first define the key elements of core assets, and show how to formally specify core assets Object-Z. Then, we present rules for defining the instantiation process and relevant constraints. Using the proposed formal framework, the task of instantiating core assets can be carried out precisely and correctly, yielding high quality software development.
Structural insights into the effects of 2′-5′ linkages on the RNA duplex

Significance The nonenzymatic replication of RNA is thought to have been a critical step in the emergence of simple cellular life from prebiotic chemistry. However, the chemical copying of RNA templates generates product strands that contain 2′-5′ backbone linkages and normal 3′-5′ linkages. Our recent finding that RNAs with such mixed backbones can still fold into functional structures raised the question of how RNA accommodates the presence of 2′-5′ linkages. Here we use X-ray crystallography and molecular dynamics simulations to reveal how 3′-5′–linked RNA duplexes accommodate interspersed 2′-5′ linkages. The diminished thermal and chemical stability of such RNA duplexes reflects local structural changes, but compensatory changes result in a global RNA duplex structure with relatively minor alterations. The mixture of 2′-5′ and 3′-5′ linkages generated during the nonenzymatic replication of RNA has long been regarded as a central problem for the origin of the RNA world. However, we recently observed that both a ribozyme and an RNA aptamer retain considerable functionality in the presence of prebiotically plausible levels of linkage heterogeneity. To better understand the RNA structure and function in the presence of backbone linkage heterogeneity, we obtained high-resolution X-ray crystal structures of a native 10-mer RNA duplex (1.32 Å) and two variants: one containing one 2′-5′ linkage per strand (1.55 Å) and one containing three such linkages per strand (1.20 Å). We found that RNA duplexes adjust their local structures to accommodate the perturbation caused by 2′-5′ linkages, with the flanking nucleotides buffering the disruptive effects of the isomeric linkage and resulting in a minimally altered global structure. Although most 2′-linked sugars were in the expected 2′-endo conformation, some were partially or fully in the 3′-endo conformation, suggesting that the energy difference between these conformations was relatively small. Our structural and molecular dynamic studies also provide insight into the diminished thermal and chemical stability of the duplex state associated with the presence of 2′-5′ linkages. Our results contribute to the view that a low level of 2′-5′ substitution would not have been fatal in an early RNA world and may in contrast have been helpful for both the emergence of nonenzymatic RNA replication and the early evolution of functional RNAs.
Affect in Embodied Pedagogical Agents

Over the past decade, computer games and other interactive technologies have shown great potential when used in innovative ways to enhance learning. It is now known that learning is associated not only with cognitive ability but also with affect. The incorporation of affective embodied pedagogical agents (EPAs) in computer programs for learning can significantly influence learner beliefs and efficacy. However, there have been a number of criticisms and contradictory empirical findings calling into question earlier results and theoretical claims on the effectiveness of using EPAs. Therefore, this paper reviewed studies that evaluated the effectiveness of affect in EPAs in a computer-based learning environment (CLE). The statistical meta-analytic review (k = 30, n = 2,150) found that the use of affect in EPAs has a significant and moderate impact (r = .35) on students’ learning motivation and a relatively smaller impact on knowledge retention (r = .29) and knowledge transfer (r = .26). The effect sizes of the three outcome variables in this review are stronger compared with previous meta-analysis on the impact of the embodiment level of EPAs, indicating that the use of affect is more desirable and effective in CLEs. Finally, implications for both designers and researchers of using affective EPAs in CLEs are discussed.
Blind source separation of convolutive audio using an adaptive stereo basis

We consider the problem of convolutive blind source separation of audio mixtures. We propose an Adaptive Stereo Basis (ASB) method based on learning a set of basis vectors pairs fromthe time-domain stereomixtures. The basis vector pairs are clustered using estimated directions of arrival (DOAs) such that each basis vector pair is associated with one source. The ASB method is compared with the DUET algorithm on convolutive speech mixtures at different reverberation times and noise levels.
Removals of estrone and 17β-estradiol by microalgae cultivation: kinetics and removal mechanisms

ABSTRACT Occurrence of estrone (E1) and 17β-estradiol (E2) in the environment has attracted the public attention since E1 and E2 cause estrogenicity in aquatic microorganisms. Microalgae cultivation in wastewater is considered as an economical practice since microalgae can be used for not only pollutant removals, but also as energy resources. This research aims to investigate the removals of E1 and E2 in synthetic wastewater by microalgae (i.e. Chlorella vulgaris and Scenedesmus obliquus). At the steady state, S. obliquus removed E1 and E2 by 91% and 99%, respectively. C. vulgaris removed E1 and E2 by 52% and 99%, respectively. Interestingly, the occurrence of E1 was observed when E2 was degraded by microalgae. The predominant mechanism for E1 and E2 removals was biodegradation, followed by adsorption. The adsorption kinetic and isotherm for both E1 and E2 can be described by the pseudo-second-order and Freundlich model. The addition of E1 and E2 resulted in a higher lipid content of microalgae by 1–9%.
Prediction of Protein Function Using Common-Neighbors in Protein-Protein Interaction Networks

The recent high-throughput bio-techniques have provided us large-scale protein-protein interaction data through systematic identification of physical and genetic interactions among all proteins in an organism. Several previous studies have shown that using protein-protein interaction networks to predict protein function is a big step toward full understanding of the mechanisms of cells. However, the protein-protein interaction data derived from high-throughput experiments are typically very noisy, which presents great challenges to the existing methods. In this paper, we propose a novel common-neighbor-based model and a Bayesian framework to predict protein function on the basis of the small-world property of the protein-protein interaction network. We tested our approach on five data sets from various sources. The experimental results have shown that our approach has a better performance than several representative methods in terms of both precision and recall. In addition, our method is particularly effective to handle the high false-positive and false-negative rates in protein-protein interaction data
The nature of nursing practice in rural and remote areas of Greenland

Background The Greenlandic Healthcare Reform (2010) required improved quality of services for health promotion, prevention of infectious and lifestyle diseases, family nursing and evidence-based clinical nursing. Aim To investigate current nursing practice in Greenland and to identify whether it meets the requirements of healthcare reform. Design This ethnographic study utilised documentary analysis, participant observation and qualitative interviewing carried out in remote areas of Greenland during 2011–2012. Eight registered nurses, four women and four men, aged between 35 and 55, participated in this study. Four were working at healthcare centres in towns and four were working at nursing stations in villages. The nurses were educated in Greenland or a Nordic country and had been practicing nursing for at least 2 years in an Arctic region. They were observed for 1–5 days, and subsequently interviewed. Interviews included in-depth questioning, based on emerging outcomes from observation. Interviews were recorded and transcribed; they were analysed within a phenomenological–hermeneutic approach. Results Nurses in rural and remote areas navigate their health promotion and preventive work with conflict between health strategies and everyday realities, where unpredictable tasks often lead to prioritisation of urgent, acute work. There is interaction between personal and professional skills. Everyday life is characterised by opportunities and challenges in the grey areas, namely nursing, medical and social work. Conclusion The nature of nursing practice in rural and remote Greenland is characterised by a high degree of variability and complexity, with a requirement for a wide range of knowledge and skills. Nurses need to be better prepared with regard to acute medical care, preventive care, social work, humanistic approaches and information technology to implement the ideology of health strategies.
Inorganic Carbon Limitation and Light Control the Expression of Transcripts Related to the CO2-Concentrating Mechanism in the Cyanobacterium Synechocystis sp. Strain PCC68031

The cyanobacterium Synechocystis sp. strain PCC6803 possesses three modes of inorganic carbon (Ci) uptake that are inducible under Ci stress and that dramatically enhance the efficiency of the CO2-concentrating mechanism (CCM). The effects of Ci limitation on the mRNA transcript abundance of these inducible uptake systems and on the physiological expression of the CCM were investigated in detail in this cyanobacterium. Transcript abundance was assessed with semiquantitative and real-time reverse transcriptase-polymerase chain reaction techniques. Cells aerated with CO2-free air for 30 min in the light, but not in the dark, depleted the total [Ci] to near zero levels. Under these conditions, the full physiological expression of the CCM was apparent within 2 h. Transcripts for the three inducible Ci uptake systems,ndhF3, sbtA, and cmpA, showed near-maximal abundance at 15 min under Ci limitation. The transcriptional regulators, cmpR andndhR, were more moderately expressed, whereas therbcLXS and ccmK-N operons andndhF4/ndhD4/chpX and ccaAgenes were insensitive to the low-Ci treatment. The combined requirement of low Ci and light for the expression of several CCM-related transcripts was examined using real-time reverse transcriptase-polymerase chain reaction. CmpA,ndhF3, and sbtA were strongly expressed in the light, but not in the dark, under low-Ci conditions. We could find no evidence for induction of these or other CCM-related genes by a high-light treatment under high-CO2 conditions. This provided evidence that high-light stress alone could not trigger the expression of CCM-related transcripts in Synechocystissp. PCC6803. Potential signals triggering induction of the high-affinity state of the CCM are discussed.
The Molecular Detection and Clinical Significance of ALK Rearrangement in Selected Advanced Non-Small Cell Lung Cancer: ALK Expression Provides Insights into ALK Targeted Therapy

Background This study aimed to elucidate clinical significance of anaplastic lymphoma kinase (ALK) rearrangement in selected advanced non-small cell lung cancer (NSCLC), to compare the application of different ALK detection methods, and especially evaluate a possible association between ALK expression and clinical outcomes in crizotinib-treated patients. Methods ALK status was assessed by fluorescent in situ hybridization (FISH), immunohistochemistry (IHC) and quantitative RT-PCR (qRT-PCR) in 173 selected advanced NSCLC patients. Clinicopathologic data, genotype status and survival outcomes were analyzed. Moreover, the association of ALK expression with clinical outcomes was evaluated in ALK FISH-positive crizotinib-treated patients including two patients with concurrent epidermal growth factor receptor (EGFR) mutation. Results The positivity detection rate of ALK rearrangement by FISH, IHC and qRT-PCR was 35.5% (59/166), 35.7% (61/171), and 27.9% (34/122), respectively. ALK rearrangement was observed predominantly in young patients, never or light smokers, and adenocarcinomas, especially with signet ring cell features and poor differentiation. Median progression-free survival (PFS) of crizotinib-treated patients was 7.6 months. The overall survival (OS) of these patients was longer compared with that of crizotinib-naive or wild-type cohorts, but there was no significant difference in OS compared with patients with EGFR mutation. ALK expression did not associate with PFS; but, when ALK expression was analyzed as a dichotomous variable, moderate and strong ALK expression had a decreased risk of death (P = 0.026). The two patients with concomitant EGFR and ALK alterations showed difference in ALK expression, response to EGFR and ALK inhibitors, and overall survival. Conclusions Selective enrichment according to clinicopathologic features in NSCLC patients could highly improve the positivity detection rate of ALK rearrangement for ALK-targeted therapy. IHC could provide more clues for clinical trial design and therapeutic strategies for ALK-positive NSCLC patients including patients with double genetic aberration of ALK and EGFR.
Multirobot Belief Fusion for Mapping and Tracking with Unreliable Sensors

We present an approach for mapping and tracking with multiple sensors that is robust to false-positives and falsenegatives. Sequential observations are first passed through the Improbability Filter to exclude false-positives, combined into a single joint observation, and finally fed to the Kalman filter to update the prior joint belief. Modifications to the Kalman update equations eliminate biases introduced by using both filters in succession; similar dual-filter techniques ignore bias or address it in an ad-hoc, unprincipled fashion. We apply the framework to the domain of robot soccer; in simulation, our algorithm, which we call the Comprehensive Kalman filter or CKF, far outperforms the standard Kalman filter when applied to landmark mapping in the presence of false-positives and false-negatives. CKF achieves convergence even with sensors of false-positive rates up to 50%.
DETECTION OF AFFECTIVE PATTERNS IN PHYSIOLOGICAL SIGNALS TOWARDS IMPROVING AUTOMATIC EMOTION RECOGNITION

In this chapter, we investigate the potential of physiological signals as reliable channels for emotion recognition. All essential stages of an automatic recognition system are discussed, from the recording of a physiological dataset to a feature-based multiclass classiﬁcation. In order to collect a physiological dataset from multiple subjects, we developed a musical induction method, without any deliberate lab setting. Four-channel biosensors were used to measure electromyogram, electrocardiogram, skin conductivity, and respiration changes. A wide range of physiological features from various analysis domains is proposed to ﬁnd the best emotion-relevant features and correlate them with emotional states. The best features extracted are speciﬁed in detail and their eﬀectiveness is proven by classiﬁ-cation results. Classiﬁcation of four musical emotions (positive/high arousal, negative/high arousal, negative/low arousal, positive/low arousal) is performed by using an extended linear discriminant analysis (pLDA). Furthermore, by exploiting a dichotomic property of the 2D emotion model, we develop a novel scheme of emotion-speciﬁc multilevel dichotomous classiﬁcation (EMDC) and compare its performance with direct multiclass classiﬁcation using the pLDA.
Proteome Analysis of Plant-Virus Interactome

Known host-parasite molecular interactions are widespread among parasite families, but these interactions have to be particularly large considering that viruses generally encode few proteins. Although some particular virus-host interactions are well described, no global study has yet shown multiple and simultaneous interactions in a host-parasite biological system. To prove that these multiple interactions occur in biological conditions, the complexes formed by a plant virus (rice yellow mottle virus) and the proteins of its natural host (rice) were extracted and purified from infected tissue sample. Remarkably mass spectrometry permitted the identification of a large number of proteins from the complexes that are involved in different functions not encoded by the virus but probably essential for its biological life cycle. This recruiting of proteins was strongly confirmed by the repetition of experiments using different pairs of virus-host and the use of high salt concentration to extract the complexes. We mainly identified proteins involved in plant defense, metabolism, translation, and protein synthesis and some proteins involved in transport. This study demonstrates that viruses are able to recruit many proteins from their hosts to ensure their development. Among different pairs of virus-host, similar protein functions were identified suggesting a particular importance of these proteins for viruses. The identification of particular paralog proteins among multigenic families suggests the high specificity of the recruiting for some protein functions.
On combining gamification theory and ABET criteria for teaching and learning engineering

The main contribution of this paper is the introduction of a continuous improvement cycle for devising teaching scenarios and conducting learning experiences in engineering. The proposed cycle consists of seven steps on which gamification theory and ABET criteria are combined. It arose from the adaptation of a gamification design framework, commonly used in industry, into the specific context of high quality education in engineering. It is formulated at high level. Consequently, it should be useful for practitioners having different requirements and expectations. A developed practice, following the proposed cycle, is presented, discussed and evaluated. In particular, the proposal is applied and exemplified, in a scenario for teaching introductory concepts of computer programming in a first-year course. A digital game was used within a gamified learning experience, as a teaching tool. However, the learning process does not rely solely on the use of the game by itself. Moreover, the devised scenario has a purpose beyond edutainment: contributing to achievement of student outcomes, under a continuous improvement approach, according to ABET. A quantitative and qualitative evaluation of the developed practice was performed. A positive impact on students' emotional engagement and behavior was observed as a result of the evaluation process.
An algorithm for multipath computation using distance-vectors with predecessor information

Routing algorithms in the IP Internet provide a single path between each source-destination pair and where more than one path is provided, they are paths of equal length. Single-path routing is inherently slow in responding to congestion and temporary traffic bursts; multiple paths are better suited to handle congestion. Also the paths provided in RIP and OSPF are not free of loops during times of network transition, which can be debilitating to network performance. We present a distributed routing algorithm for computing multiple paths that need not have equal length between each source-destination pair in a computer network such that they are loop-free at every instant - in steady state as well as during network transitions. The algorithm is scalable to large networks as it uses only one-hop synchronization which is unlike diffusing computations that require internodal synchronization spanning multiple hops. The safety and liveness properties of the algorithm are proven and its complexity is analyzed.
A neural network model for the prediction of musical emotions

This chapter presents a novel methodology to analyse the dynamics of emotional responses to music in terms of computational representations of perceptual processes (psychoacoustic features) and self-perception of physiological activation (peripheral feedback). The approach consists of a computational investigation of musical emotions based on spatio-temporal neural networks sensitive to structural aspects of music. We present two computational studies based on connectionist network models that predict human subjective feelings of emotion. The first study uses six basic psychoacoustic dimensions extracted from the music pieces as predictors of the emotional response. The second computational study evaluates the additional contribution of physiological arousal to the subjective feeling of emotion. Both studies are backed up by experimental data. A detailed analysis of the simulation models' results demonstrates that a significant part of the listener's affective response can be predicted from a set of psychoacoustic features of sound tempo, loudness, multiplicity (texture), power spectrum centroid (mean pitch), sharpness (timbre) and mean STFT flux (pitch variation) and one physiological cue, heart rate. This work provides a new methodology to the field of music and emotion research based on combinations of computational and experimental work, which aid the analysis of emotional responses to music, while offering a platform for the abstract representation of those complex relationships.