Miracle-dz/UniFAR-FTUs huggingface dataset:
’ s repository of research publications and other research outputs Quantum-Inspired Interactive Networks for Conversational Sentiment Analysis . Conference or Workshop Item

Conversational sentiment analysis is an emerging, yet challenging Artificial Intelligence (AI) subtask. It aims to discover the affective state of each participant in a conversation. There exists a wealth of interaction information that affects the sentiment of speakers. However, the existing sentiment analysis approaches are insufficient in dealing with this task due to ignoring the interactions and dependency relationships between utterances. In this paper, we aim to address this issue by modeling intrautterance and inter-utterance interaction dynamics. We propose an approach called quantum-inspired interactive networks (QIN), which leverages the mathematical formalism of quantum theory (QT) and the long short term memory (LSTM) network, to learn such interaction dynamics. Specifically, a density matrix based convolutional neural network (DM-CNN) is proposed to capture the interactions within each utterance (i.e., the correlations between words), and a strong-weak influence model inspired by quantum measurement theory is developed to learn the interactions between adjacent utterances (i.e., how one speaker influences another). Extensive experiments are conducted on the MELD and IEMOCAP datasets. The experimental results demonstrate the effectiveness of the QIN model.
CLINICAL AND HISTOLOGICAL EVALUATION OF GINGIVAL HEALING AFTER GINGIVECTOMY AND LOW-LEVEL LASER THERAPY

Background: Low-level laser therapy (LLLT) may induce morphological and cellular processes, which are involved in wound healing. Thus, increasing interest in the matter of LLLT is based on its ability to provide minimally invasive and painless treatments for the patient as well as increasing his comfort following surgery. Objective: The purpose of this study was to assess the clinical and histological effect of LLLT on healing of gingiva after gingivectomy. Methods: Twenty patients with inflammatory gingival enlargement on their maxillary or mandibular anterior region were included in this study. Patients were divided randomly into two groups (Test group=ten patients) after gingivectomy a diode laser (660 nm) was applied to the wound area immediately post-surgery (day 1) and at days 3, 5 post-surgery. The control group (ten patients) did not receive laser irradiation. Healing was evaluated clinically using Healing score and Visual analogue scale VAS. For histological evaluation, mucosal defect measuring 2 mm in diameter and 0.2 mm in wall thickness was created into the hard palate of eighteen male Dawley rats. For the test group (9 rats) LLLT was applied with the same settings and intervals used in the clinical part of the study, while for the control group (9 rats) no laser irradiation was applied. Results: The laser-treated group had significant improvement regarding the healing score at 5, 7 and 14 days p.s. , and significant improvement in VAS score was observed at day 3 and 5 p.s. , than the control group. The histological sections revealed a thin layer of epithelium covering the wound after 4 days in the test group in contrast to the control group. Also, complete epithelization of the wound area with keratin formation and revascularization after 7 days was observed in the test group. Conclusion: LLLT can be used as an effective adjunctive treatment following gingivectomy procedure to promote healing of oral mucosa.
Encounters with common warthogs along the B 1 highway in north-central Namibia

Introduction Common warthog (Phacochoerus africanus) occur throughout Namibia except the far south, southeast, arid west (i.e., Namib Desert), and the densely populated north­central communal areas. Their Namibian conservation and legal status lists warthog as “secure and huntable game” (Griffin & Coetzee, 2005). Although seemingly ubiquitous, often alongside major roads where they are viewed as a nuisance to drivers, little has been published regarding their local ecology and/or numbers. During 2013, Namibia experienced a widespread drought with warthog lured to road verges with better grazing. Their numbers seemed astounding at times – e.g. 391 individuals on a 146 km stretch of the B1 highway between Okahandja and Otjiwarongo in central Namibia on 7 October 2013 between 17h00 and 19h00 (this study). Mean average annual rainfall for this area varies from 300 mm in the south (Okahandja area) to 450 mm in the north (Otjiwarongo area) mainly between January and April. Coefficient of variation in rainfall of 30­40% (Mendelsohn et al., 2002) mainly between January and April. During the 2012/2013 rainy season these areas received between 100­200 mm. Whilst travelling this route for other purposes, I kept note of warthog numbers along this section of the B1 Highway, including anthropomorphic activities potentially affecting warthog distribution. This note highlights some of these findings and although not attempted as a formal scientific study it does raise interesting questions.
ISTA-A : Conceptual model using indicators selected by systems hinking for adaptation strategies in a changing climate : Case study in gro-ecosystems

Adapting our ecosystems to climate change for sustainable management requires an understanding of three broad interconnected systems: ecosystems, climate systems and adaptive management and planning systems. Multiple factors shape adaptive responses to a changing climate because of the complexities and multi-disciplinary nature of these three systems. In this study, the conceptual model CISTA-A (CISTA for Agro-ecosystems) is developed using Indicators that are identified as using a Systems Thinking approach to Adaptation. CISTA addresses questions concerning “how to adapt” our ecosystems to climate change and has three or more layers: A base (element) layer has abiotic/biotic information (e.g. ecological, agro-hydrological, and meteorological data). One or more components (intermediate) layer(s) have ecological, agro-hydrological, and climatological indicators (e.g. length of the growing season and growing degree days) that affect the ecosystem. Indicators are identified and estimated from an element layer.
Scalable distributed video coding based on block SW-SPIHT

Nowadays, distributed source coding (DSC) and distributed video coding (DVC) have been receiving more and more attention due to the distinct contributions to the easy encoding. At the same time, with more new requirements coming forth in the current network communication, the scalability of bit stream has been a new focus in the real applications. A scalable DVC scheme is presented without requiring layered coding in which the main attributions of DVC, namely the capabilities of easy encoding and robustness, are inherited remarkably and the property of scalability is also integrated simultaneously. Based on the block Slepian-Wolf set partitioning in hierarchical trees (SW-SPIHT), the Wyner-Ziv frames are encoded to get the scalable bit stream. In addition, the binary motion searching is explored at the decoder with the help of a rate-variable 'hash' from the encoder to improve the performance of the whole system. The final experimental results show that our system has higher peak signal-to-noise ratio (PSNR) than the pixel-domain DVC at the high bit rate. What is more, the scalability in signal-to-noise ratio (SNR) is also achieved satisfactorily.
A framework for lexical representation

In this paper we present a unicationbased lexical platform designed for highly inected languages like Roman ones. A formalism is proposed for encoding a lemmabased lexical source well suited for linguistic generalizations. From this source we automatically generate an allomorph indexed dictionary adequate for eficient processing. A set of software tools have been implemented around this formalism access libraries morphological processors etc.
Orbits of Hipparcos metal-poor stars with well-defined spectroscopic abundances.

Orbital characteristics of 80 HIPPARCOS mildly metal-poor stars are derived assuming a Galactic model slightly modified from that of Ostriker and Caldwell (1979). A comparison with other works is performed and a relationship between the dynamical properties of the stars and their well-determined spectroscopic abundances is investigated.
Real-time face recognition

This report describes practical aspects of implementing and evaluating real-time face recognition biometric system. We propose a modular face recognition pipeline consisting of individual modules that deal with specific tasks, such are face detection, face landmarks detection, face pose orientation, feature extraction and template comparison. We describe each of those components and provide overview of available solutions and how they can be incorporated to the recognition pipeline and further tailored to our needs.
Value Relevant Information Beyond Analysts ’ Forecasts : The Role of Growth Potential and Bankruptcy Risk

This paper explores the value relevant information beyond analysts’ forecasts in residual income dynamics and equity valuation. More specifically, we incorporate Growth Potential (GP) and Bankruptcy Risk (BK) into the residual income dynamics beyond analysts’ forecasts. Among the various proxies, we find the Present Value of Growth Potential (PVGO) of Kester (1984) and the Loss Given Default (LGD) of Merton (1974) best capture GP and BK effects. We demonstrate that GP and BK provide additional information content beyond lagged residual income and analysts’ forecasts in the residual income dynamics. Moreover, incorporating GP and BK in residual income dynamic beyond analysts’ forecasts reveals superiority in equity valuation in terms of forecast accuracy and explainability. The subsample analysis shows that the improvement of this model is mainly reflected in the high potential growth subsample and high financial risk subsample, in line with growth potential and bankruptcy risk theories. JEL classification: M40, M41, G14
Object detection algorithm based on the video stream for complex environment

Due to the complexity of the environment and the diversity of the goal itself in the visual system, the technology of object detection has brought great difficulties. The practical experience shows that the technology of object detection is far from mature in the general sense and there are still certain gaps away from practical application. In this paper, for solving these problems of complex background and lighting mutation of the fixed monitoring scenes, a moving object detection algorithm based on the video stream is proposed and can be applied to the complex of indoor and outdoor environments. The convergence rate is improved by improved Gaussian mixture model. Taken into account the interference of light mutation and combined with the advantage of frame-difference method, the system detection capability for fast moving target is improved. Morphological method is used for noise processing of motion region, while remedying the generated hole during object detection. Experimental results show that the algorithm can complete detecting under the light mutation quickly and accurately and has a strong robustness.
Impacts of Major Freshwater Ions on the Acute Toxicity and Chemical Behavior of Silver Nanoparticles

iv Acknowledgements . v List of Tables . viii List of Figures . ix Introduction . 1 Methods . 11 Experiment Design . 11 Biotic Ligand Model . 13 AgNP Synthesis . 14 Toxicity Testing . 15 UV-Vis . 16 ICP-MS . 17 Results . 21 AgNP Batch . 21 Toxicity . 28 Biotic Ligand Model . 32 UV-Vis . 35 ICP-MS . 41 Discussion . 46 Toxicity . 46 UV-Vis . 48 ICP-MS . 50
PerceivedKnowledgeandPriorities and Needs amongVeterinaryMedicine Faculty

Training for health professions typically does not include preparation for meeting the teaching, research, and scholarship responsibilities that a veterinarian assuming an academic faculty position will need. To address this matter, well-executed research on veterinary faculty is needed. This study reports survey findings from faculty at a southeastern United States veterinary school that measured the relationship between knowledge and priorities for further training, level of satisfaction with current faculty development opportunities and mentoring, and perceptions of what additional training/resources that might advance careers. Overall, 57% (n = 75) of the faculty participated. Agreement between knowledge and indicated priority was measured using McNemar’s test for paired binary data and Fisher’s exact test. There were significant differences between participants’ ratings of their knowledge needs and priorities on almost all items. Slightly less than two thirds rated the mentoring as fair or poor. Also, participants reported several unmet needs that were essential to their development including training, support, learning how to write grant proposals, garnering funded research grants, and time. The findings provide information about the development needs of this faculty and hold implications for guiding change in the preparation of veterinary medical professionals who anticipate seeking positions in academia.
The effect of experiential learning on attitude and willingness to insulin therapy in patients with type 2 diabetes

In this study we are designing to evaluate the influences of experimental learning theory towards the treatment attitudes and willingness of insulin usage in type 2 diabetic patients who treated with insulin. This is a quasi-experimental study. A total of 400 patients with type 2 diabetes without insulin injections’ history were enrolled in this study by convenience sampling and were equally divided into experiential learning group (ELG) and control group (CG) according to their admission time. The CG received routine health education, while the ELG received the diabetes and insulin injection education based on the experiential learning theory. Using questionnaire survey to collect patients’ general information, the attitudes towards insulin injection, the incidence of psychological resistance to insulin and the willing score of insulin injectionat baseline and 3 months after hospital discharge. After intervention, the insulin treatment attitude scores in both groups showed a decline, and the scores in ELG was significantly lower than CG (x2=4.600, P=0.000). The incidence of psychological insulin resistance in ELG showed a significantly decline than CG (x2=20.135, P=0.000). Both groups showed a rising in willing score of insulin injection, and those in ELG was significantly higher than those of CG (x2=172.612, P=0.000). The intervention based on experiential learning theory can improve insulin treatment attitudes, reduce the incidence of psychological resistance to insulin and improve the willingness of insulin injection in patients with type 2 diabetes.
RUSSE ’ 2018 : A SHARED TASK ON WORD SENSE INDUCTION FOR THE RUSSIAN LANGUAGE

The paper describes the results of the first shared task on word sense induction (WSI) for the Russian language. While similar shared tasks were conducted in the past for some Romance and Germanic languages, we explore the performance of sense induction and disambiguation methods for a Slavic language that shares many features with other Slavic languages, such as rich morphology and virtually free word order. The participants were asked to group contexts of a given word in accordance with its senses which were not provided beforehand. For instance, given a word “bank” and a set of contexts for this word, e.g. “bank is a financial institution that accepts deposits” and “river bank is a slope beside a body of water”, a participant was asked to cluster such contexts into unknown in advance number of clusters corresponding to, in this case, the “company” and the “area” senses of the word “bank”. For the purpose of this evaluation campaign, we developed three new evaluation datasets based on sense inventories that have different sense granularity. The contexts in these datasets were sampled from texts of Wikipedia, the academic corpus of Russian, and an explanatory dictionary of Russian. Overall, 18 teams participated in the competition submitting 383 models. Multiple teams managed to substantially outperform competitive stateof-the-art baselines from the previous years based on sense embeddings.
A Probabilistic Model for Ranking Entities to Mentions

Entity linking (EL) is the task of mapping name mentions in web text to their entities in a knowledge base. Most of earlier EL work in the knowledge based approach is usually formulated as a ranking problem, either by (i) non-collective approaches with supervised models, or (ii) collective approaches by leveraging global topical coherence which means semantic relations between entities through graph-based approaches. For the mapping process, we can regard it as selecting an entity to its mention by combining these two methods. In this paper, we propose a probabilistic model that ranks related entities to name mentions where ranking is customized by using three types of data: popularity knowledge of the entity, context similarity between mentions and the entity, and semantic relations between mapping entities. Specifically, we first propose an EL model utilizing global topical coherence that means semantic relations between entities, as well as using local mention-to-entity compatibility, to improve recall and precision. The key benefit of our model comes from 1) combination of two methods to provide customized ranking for mentions, 2) the model is efficient by directly modeling the global semantic coherence between the entities and the document.
A THEORETICAL STUDY OF THE IMPACT OF BIOMASS-BURNING CCN ON THE DYNAMICS OF DEEP CONVECTIVE CLOUDS WITH MIXED PHASE

Clouds are important components of the climate system as they affect the Earth's albedo and they participate in the hydrological cycle. One of the largest uncertainties in climate modeling is related to the parameterization of convective processes and, in particular, the question of how anthropogenic emissions may affect the different types of clouds is still open. Most research has been devoted to warm stratocumulus clouds, and only recently some studies incorporate changes in cirrus and mixed phase clouds. Emissions of gases and particles during biomass burning may affect the microphysics and dynamics of clouds developing near and downwind of said emissions, and some studies have suggested that precipitation may be inhibited (Ramanathan et al, 2001). Nevertheless, there have not been many studies that explore the effect that cloud condensation nuclei (CCN) originated by biomass burning may have on deep convective clouds, in which the ice phase is dominant. In this study we have introduced changes in the parameterization of the autoconversion and accretion processes in a 3-dimensional numerical model to represent the increased ambient CCN and evaluate the dynamical response and the evolution and magnitude of precipitation.
ANNUAL CYCLE OF THE SOUTH AMERICAN MONSOON SYSTEM

The South America monsoon system plays an important role on the precipitation and circulation regimes over the continent. Over several areas of the monsoon region there is a quick increase of precipitation during spring (SON) and a reduction in March and April. The austral summer, DJF, is the rainy season in these areas, with maximum observed precipitation (Paegle et al., 2002). The monsoon onset and duration affect several economic and social activities, as agriculture planning and management of hydrological resources. Although the South American continent does not present a classical typical wind monsoon characteristic, like in Asia or India, several studies have indicated monsoon features over South America. Removing the annual mean of the low level wind, it is possible to identify the wind reversion, as shown by Zhou and Lau (1998). The seasonal cycle has a strong contrast between summer and winter, discussed in several studies, as Rao et al. (1996), Gan et al. (2004). The rainy season in central and southeastern South America regions are closely linked to the monsoon lifecycle. The initial phase of the South America Monsoon System (SAMS) occurs during SH spring (sep-nov), when there is a migration of the convection from the extreme NW South America towards central Amazonia. This migration has been associated with the intense atmospheric heating from the surface (Nogués-Peagle et al. 2002). The SAMS reach the maximum intensity during the SH summer, when there is a change in the atmospheric circulation and maximum precipitation over central Amazonia and Southeastern Brazil, associated with the Bolivia High, South Atlantic/Northeast Upper Level Cyclonic Vortice, and South Atlantic Convergence Zone (SACZ), (Grimm, 2005). The onset and demise of the rainy season over these regions have been analyzed using OLR, precipitation and wind components (Kousky, 1988; Marengo et al., 2001; Gan et al., 2004, Zhou and Lau, 1998). Fasullo and Webster (2003) used
TRP Channels Mediated Pathological Ca2+-Handling and Spontaneous Ectopy

Ion channel biology offers great opportunity in identifying and learning about cardiac pathophysiology mechanisms. The discovery of transient receptor potential (TRP) channels is an add-on to the opportunity. Interacting with numerous signaling pathways, being activated multimodally, and having prescribed signatures underlining acute hemodynamic control and cardiac remodeling, TRP channels regulate cardiac pathophysiology. Impaired Ca2+-handling cause contractile abnormality. Modulation of intracellular Ca2+ concentration ([Ca2+]i) is a major part of Ca2+-handling processes in cardiac pathophysiology. TRP channels including TRPM4 regulate [Ca2+]i, Ca2+-handling and cardiac contractility. The channels modulate flux of divalent cations, such as Ca2+ during Ca2+-handling and cardiac contractility. Seminal works implicate TRPM4 and TRPC families in intracellular Ca2+ homeostasis. Defective Ca2+-homeostasis through TRP channels interaction with Ca2+-dependent regulatory proteins such as sodium calcium exchanger (NCX) results in abnormal Ca2+ handling, contractile dysfunction and in spontaneous ectopy. This review provides insight into TRP channels mediated pathological Ca2+-handling and spontaneous ectopy.