Miracle-dz/UniFAR-FTUs huggingface dataset:
Metal-Enhanced Near-Infrared Fluorescence by Micropatterned Gold Nanocages

In metal-enhanced fluorescence (MEF), the localized surface plasmon resonances of metallic nanostructures amplify the absorption of excitation light and assist in radiating the consequent fluorescence of nearby molecules to the far-field. This effect is at the base of various technologies that have strong impact on fields such as optics, medical diagnostics, and biotechnology. Among possible emission bands, those in the near-infrared (NIR) are particularly intriguing and widely used in proteomics and genomics due to its noninvasive character for biomolecules, living cells, and tissues, which greatly motivates the development of effective and, eventually, multifunctional NIR-MEF platforms. Here, we demonstrate NIR-MEF substrates based on Au nanocages micropatterned with a tight spatial control. The dependence of the fluorescence enhancement on the distance between the nanocage and the radiating dipoles is investigated experimentally and modeled by taking into account the local electric field enhancement and the modified radiation and absorption rates of the emitting molecules. At a distance around 80 nm, a maximum enhancement up to 2–7 times with respect to the emission from pristine dyes (in the region 660–740 nm) is estimated for films and electrospun nanofibers. Due to their chemical stability, finely tunable plasmon resonances, and large light absorption cross sections, Au nanocages are ideal NIR-MEF agents. When these properties are integrated with the hollow interior and controllable surface porosity, it is feasible to develop a nanoscale system for targeted drug delivery with the diagnostic information encoded in the fluorophore.
Deposition and transport of linezolid mediated by a synthetic surfactant Synsurf® within a pressurized metered dose inhaler: a Calu-3 model

Background Previous studies in our laboratory demonstrated that a synthetic peptide containing lung surfactant enhances the permeability of chemical compounds through bronchial epithelium. The purpose of this study was to test two formulations of Synsurf® combined with linezolid as respirable compounds using a pressurized metered dose inhaler (pMDI). Methods Aerosolization efficiency of the surfactant-drug microparticles onto Calu-3 monolayers as an air interface culture was analyzed using a Next Generation Impactor™. Results The delivered particles and drug dose showed a high dependency from the preparation that was aerosolized. Scanning electron microscopy imaging allowed for visualization of the deposited particles, establishing them as liposomal-type structures (diameter 500 nm to 2 μm) with filamentous features. Conclusion The different surfactant drug combinations allow for an evaluation of the significance of the experimental model system, as well as assessment of the formulations providing a possible noninvasive, site-specific, delivery model via pMDI.
Distinct myocardial lineages break atrial symmetry during cardiogenesis in zebrafish

The ultimate formation of a four-chambered heart allowing the separation of the pulmonary and systemic circuits was key for the evolutionary success of tetrapods. Complex processes of cell diversification and tissue morphogenesis allow the left and right cardiac compartments to become distinct but remain poorly understood. Here, we describe an unexpected laterality in the single zebrafish atrium analogous to that of the two atria in amniotes, including mammals. This laterality appears to derive from an embryonic antero-posterior asymmetry revealed by the expression of the transcription factor gene meis2b. In adult zebrafish hearts, meis2b expression is restricted to the left side of the atrium where it controls the expression of pitx2c, a regulator of left atrial identity in mammals. Altogether, our studies suggest that the multi-chambered atrium in amniotes arose from a molecular blueprint present before the evolutionary emergence of cardiac septation and provide insights into the establishment of atrial asymmetry.
Interactive exploration of healthcare queries

Healthcare related queries are a treasure trove of information about the information needs of domain users, be they patients or doctors. However, unlike general queries, in order to make the most out of the information therein, such queries have to be processed within a medical terminology annotation pipeline. We show how this has been done in the context of the KConnect project and demonstrate an interactive query log exploration interface that allows data analysts and search engineers to better understand their users and design a better search experience.
Medical Entity Corpus with PICO elements and Sentiment Analysis

In this paper, we present our process to establish a PICO and a sentiment annotated corpus of clinical trial publications. PICO stands for Population, Intervention, Comparison and Outcome — these four classes can be used for more advanced and speciﬁc search queries. For example, a physician can determine how well a drug works only in the subgroup of children. Additionally to the PICO extraction, we conducted a sentiment annotation, where the sentiment refers to whether the conclusion of a trial was positive, negative or neutral. We created both corpora with the help of medical experts and non-experts as annotators.
Teachers’ beliefs about emotions in the classroom : relations to teacher characteristics and implementation of a social-emotional learning program

The aim of this descriptive study was to examine teachers’ beliefs about emotions in the classroom and factors related to these beliefs, namely teacher background characteristics and the implementation of an emotion-focused social-emotional learning (SEL) program – the Roots of Empathy (ROE). Participants included 58 elementary school teachers from a Western Canadian city (n = 40) and the Isle of Man (n = 18) who hosted the ROE program or comprised the control group. Participants completed self-report measures assessing emotion beliefs (Bonds, Expressiveness, Instruction/Modeling, Protect, and Display/Control), background characteristics (grade level taught and years of teaching experience), and ROE program implementation (number of subject areas and frequency). Results indicated grade level taught (primary versus intermediate) and years of teaching experience were significantly related to some emotion beliefs dimensions. Instruction/Modeling beliefs were significantly higher for experienced teachers than novice teachers. Protect beliefs were significantly higher for primary grade teachers than intermediate grade teachers. Display/Control beliefs were significantly higher for intermediate grade teachers than primary grade teachers. Particular emotion beliefs were also significantly associated with teachers’ reports of ROE program implementation. Teachers’ Expressiveness beliefs were positively correlated with the frequency with which they implemented activities. Teachers’ Protect beliefs were negatively correlated with, and Display/Control beliefs were positively correlated with, the number of subject areas in and frequency with which implementation occurred. These findings support and extend research investigating teacherrelated factors associated with implementation. Suggestions concerning the need for SEL training and support are made to enhance the effectiveness of emotion-focused SEL programs.
A robust speech enhancement method based on microphone array

In this paper, a robust noise suppression algorithm is introduced by combining beamforming technique and multiband spectral subtraction. Robust speech enhancement algorithms are critical to improving the performance of speech recognition systems. Basic spectral subtraction performs effectively for suppressing additive stationary noise received from a single microphone, but it will also introduce musical noise into our enhanced signal. In order to resolve this shortcoming, the proposed algorithm in this paper improves the existing spectral subtraction algorithm with a microphone array to suppress its residual musical noise. Results show that, the proposed algorithm works effectively on reducing both background noise and musical noise.
Survey on Privacy Preserving and Data Security Techniques

: In day to day life cloud computing is most promising and widely used technology. As it provides infrastructure, platform and software as a service, it is used in almost all area of computing. We use cloud for data storage, data processing and computing purpose. In return we pay to cloud for using its resources. Here user is not sure whether his data is in safe hands as well as his identity is reveled with his data. In this Survey paper we enlist all the research carried out related to data security and users privacy preserving techniques in detail. Finally we proposed system which provides data ownership privacy using token generation for each user, each session and data security using RSA.
Plastin 1 widens stereocilia by transforming actin filament packing from hexagonal to liquid

Stereocilia of the inner ear’s sensory hair cells are filled with a paracrystalline array of parallel actin filaments. Krey et al. show that the actin cross-linker plastin-1 is needed for random liquid packing of actin filaments and final stereocilia diameter.
The reverse remodeling response to sacubitril/valsartan therapy in heart failure with reduced ejection fraction

BACKGROUND Major classes of medical therapy for heart failure with reduced ejection fraction (HFrEF) induce reverse remodeling. The revere remodeling response to sacubitril/valsartan remains unstudied. METHODS We performed a single-center, prospective assessor-blinded study to determine the reverse remodeling response of sacubitril/valsartan therapy in HFrEF patients with a class I indication (New York heart Association [NYHA]-class II-IV, Left ventricular ejection fraction [LVEF] < 35%, optimal dose with Renin-Angiotensin-System-Blocker [RAS-blocker]). Doses of sacubitril/valsartan were optimized to individual tolerance. Echocardiographic images were assessed offline by 2 investigators blinded to both the clinical data and timing of echocardiograms. RESULTS One-hundred-twenty-five HFrEF patients (66 ± 10 years) were prospectively included. The amount of RAS-blocker before and after switch to sacubitril/valsartan was similar(P = .290), indicating individual optimal dosing of sacubitril/valsartan. Over a median(IQR) follow-up of 118(77-160) days after initiation of sacubitril/valsartan, LVEF improved (29.6 ± 6% vs 34.8 ± 6%; P < .001) and Left ventricular end-systolic (LVESV) and end-diastolic volume (LVEDV) decreased (LVESV; 147 ± 57 mL vs 129 ± 55 mL; P < .001 and LVEDV; 206 ± 71 mL vs197 ± 72 mL; P = .027). Volumetric remodeling was associated with a reduction in the degree of mitral regurgitation (1.59 ± 1.0 vs 1.11 ± 0.8; P < .001; [scale from 0-4]). Metrics of diastolic function improved; including a drop in the E/A-wave ratio (1.75 ± 1.13 vs 1.38 ± 0.88; P = .002) and diastolic filling time (% of cycle length) prolonged (48 ± 9% vs 52 ± 1%; P = .005). The percent of patients with a restrictive mitral filling pattern dropped from 47% to 23% (P = .004). A dose-dependent effect was noted for changes in LVEF (P < .001) and LVESV (P = .031), with higher doses of sacubitril/valsartan leading to more reverse remodeling. CONCLUSION Switching therapy in eligible HFrEF patients from a RAS-blocker to sacubitril/valsartan induces beneficial reverse remodeling of both metrics of systolic as diastolic function.
PoPF: A Consensus Algorithm for JCLedger

JointCloud is a new generation of cloud computing model which facilitates developers to customize cloud services. JCLedger is a blockchain based distributed ledger for JointCloud computing which can make cloud resources exchange more reliable and convenient, and it is the combination of JointCloud and BlockChain. One of the most important elements for creating JCLedger is the consensus algorithm. PoW (Proof of Work) is the consensus algorithm for Bitcoin, which is proved to be quite safe but needs much computing power. The original PoW is not suitable for JCLedger because the identities of participants are not equal in computing power, which may lead to accounting monopoly, and the throughput cannot satisfy the requirement of the massive and high-frequency transactions in JointCloud. In this paper, we propose a PoW based consensus algorithm called Proof of Participation and Fees (PoPF), which can save much computing power and handled transactions more efficiently for JCLedger. In our design, only the candidates have the opportunities for mining and the candidates are chosen according to the ranking which is determined by two factors: the times of the participant to be the accountant and the fees the participant has paid. The difficulty for candidates of solving the PoW hash puzzle is different (the higher ranking means easier for mining). The simulation experiment shows that the distribution of accountants is well-balanced, that is to say, the unequal computing power of participants in JointCloud is shielded, and all the users who have enough contribution in JCLedger will have the opportunities to be accountants.
On the Vector Representation of Utterances in Dialogue Context

In recent years, the representation of words as vectors in a vector space, also known as word embeddings, has achieved a high degree of attention in the research community and the beneﬁts of such a representation can be seen in the numerous applications that utilise it. In this work, we introduce dialogue vector models, a new language resource that represents dialogue utterances in vector space and captures the semantic meaning of those utterances in the dialogue context. We examine how the word vector approach can be applied to utterances in a dialogue to generate a meaningful representation of them in vector space. Utilising existing dialogue corpora and word vector models, we create dialogue vector models and show that they capture relevant semantic information by comparing them to manually annotated dialogue acts. Furthermore, we discuss potential areas of application for dialogue vector models, such as dialogue act annotation, learning of dialogue strategies, intent detection and paraphrasing.
Multisource Transfer Double DQN Based on Actor Learning

Deep reinforcement learning (RL) comprehensively uses the psychological mechanisms of “trial and error” and “reward and punishment” in RL as well as powerful feature expression and nonlinear mapping in deep learning. Currently, it plays an essential role in the fields of artificial intelligence and machine learning. Since an RL agent needs to constantly interact with its surroundings, the deep Q network (DQN) is inevitably faced with the need to learn numerous network parameters, which results in low learning efficiency. In this paper, a multisource transfer double DQN (MTDDQN) based on actor learning is proposed. The transfer learning technique is integrated with deep RL to make the RL agent collect, summarize, and transfer action knowledge, including policy mimic and feature regression, to the training of related tasks. There exists action overestimation in DQN, i.e., the lower probability limit of action corresponding to the maximum Q value is nonzero. Therefore, the transfer network is trained by using double DQN to eliminate the error accumulation caused by action overestimation. In addition, to avoid negative transfer, i.e., to ensure strong correlations between source and target tasks, a multisource transfer learning mechanism is applied. The Atari2600 game is tested on the arcade learning environment platform to evaluate the feasibility and performance of MTDDQN by comparing it with some mainstream approaches, such as DQN and double DQN. Experiments prove that MTDDQN achieves not only human-like actor learning transfer capability, but also the desired learning efficiency and testing accuracy on target task.
Radix Ilicis Pubescentis total flavonoids ameliorates neuronal damage and reduces lesion extent in a mouse model of transient ischemic attack

Flavonoids are a major component in the traditional Chinese medicine Radix Ilicis Pubescentis. Previous studies have shown that the administration of Radix Ilicis Pubescentis total flavonoids is protective in cerebral ischemia. However, to our knowledge, no studies have examined whether the total flavonoids extracted from Radix Ilicis Pubescentis prevent or ameliorate neuronal damage following transient ischemic attacks. Therefore, Radix Ilicis Pubescentis total flavonoids question and the potential underlying mechanisms. Thus, beginning 3 days before the induction of a mouse model of transient ischemic attack using tert-butyl hydroperoxide injections, mice were intragastrically administered 0.3, 0.15, or 0.075 g/kg of Radix Ilicis Pubescentis total flavonoids daily for 10 days. The results of spectrophotometric analyses demonstrated that Radix Ilicis Pubescentis total flavonoids enhanced oxygen free radical scavenging and reduced pathological alterations in the brain. Hematoxylin-eosin staining results showed that Radix Ilicis Pubescentis total flavonoids reduced hippocampal neuronal damage and cerebral vascular injury in this mouse model of transient ischemic attack. These results suggest that the antioxidant effects of Radix Ilicis Pubescentis total flavonoids alleviate the damage to brain tissue caused by transient ischemic attack.
ESCRITO - An NLP-Enhanced Educational Scoring Toolkit

We propose E SCRITO , a toolkit for scoring student writings using NLP techniques that addresses two main user groups: teachers and NLP researchers. Teachers can use a high-level API in the teacher mode to assemble scoring pipelines easily. NLP researchers can use the developer mode to access a low-level API, which not only makes available a number of pre-implemented components, but also allows the user to integrate their own readers, preprocessing components, or feature extractors. In this way, the toolkit provides a ready-made testbed for applying the latest developments from NLP areas like text similarity, paraphrase detection, textual entailment, and argument mining within the highly challenging task of educational scoring and feedback. At the same time, it allows teachers to apply cutting-edge technology in the classroom.
Frameworkbasiertes Augmented Reality-Lernszenario in der Kfz-Ausbildung(Framework-Based Augmented Reality Learning Scenario in Automotive Education)

Training in the automotive industry is characterized by a close integration of theory and practice. With current augmented reality technology, a learning scenario was designed to provide context-based support to the learner in the field of view by holographic insertions while assembling a real gearbox. In addition, by implementing a framework for the creation of learning scenarios, access for experts in the respective knowledge domain is facilitated. Despite the increased complexity of this medium and the technologies involved, the effort to realize new learning scenarios with this software should only slightly increase compared to conventional teaching methods. Carsten Ullrich, Martin Wessner (Eds.): Proceedings of DeLFI and GMW Workshops 2017 Chemnitz, Germany, September 5, 2017 Frameworkbasiertes Augmented Reality-Lernszenario in der Kfz-Ausbildung Gregor Tallig, Raphael Zender, Mario Runge Abstract: Die Ausbildung in der Automobil-Industrie zeichnet sich durch eine enge Verzahnung von Theorie und Praxis aus. Im Zuge der Verwendung aktueller Augmented-Reality-Technologie wird ein Lernszenario konzipiert, das eine kontextbasierte Unterstützung des Lernenden bei einer realen Getriebemontage im Sichtfeld durch holografische Einblendungen ermöglicht. Darüber hinaus wird durch die Implementierung eines Frameworks zur Erstellung von Lernszenarien der Zugang für Experten der jeweiligen Wissensdomäne geebnet. Trotz der bei diesem Medium erhöhten Komplexität der verwendeten Technologien soll so der Aufwand zur Realisierung neuer Lernszenarien im Vergleich zu herkömmlichen Lehrmethoden nur geringfügig steigen. Die Ausbildung in der Automobil-Industrie zeichnet sich durch eine enge Verzahnung von Theorie und Praxis aus. Im Zuge der Verwendung aktueller Augmented-Reality-Technologie wird ein Lernszenario konzipiert, das eine kontextbasierte Unterstützung des Lernenden bei einer realen Getriebemontage im Sichtfeld durch holografische Einblendungen ermöglicht. Darüber hinaus wird durch die Implementierung eines Frameworks zur Erstellung von Lernszenarien der Zugang für Experten der jeweiligen Wissensdomäne geebnet. Trotz der bei diesem Medium erhöhten Komplexität der verwendeten Technologien soll so der Aufwand zur Realisierung neuer Lernszenarien im Vergleich zu herkömmlichen Lehrmethoden nur geringfügig steigen.
Improving Crowdsourcing-Based Annotation of Japanese Discourse Relations

Although discourse parsing is an important and fundamental task in natural language processing, few languages have corpora annotated with discourse relations and if any, they are small in size. Creating a new corpus of discourse relations by hand is costly and time-consuming. To cope with this problem, Kawahara et al. (2014) constructed a Japanese corpus with discourse annotations through crowdsourcing. However, they did not evaluate the quality of the annotation. In this paper, we evaluate the quality of the annotation using expert annotations. We ﬁnd out that crowdsourcing-based annotation still leaves much room for improvement. Based on the error analysis, we propose improvement techniques based on language tests. We re-annotated the corpus with discourse annotations using the improvement techniques, and achieved approximately 3% improvement in F-measure. We will make re-annotated data publicly available.
EFFECT OF CELL RATIO ON CHONDROGENESIS OF CO-CULTURED HUMAN ADIPOSE-DERIVED STEM CELLS AND NASAL CHONDROCYTES IN ALGINATE HYDROGEL

The field of stem-cell-based tissue engineering has grown steadily in recent years. The fundamental aim of tissue engineering is to recapitulate key features of development or tissue repair to either promote tissue formation ex vivo or improve tissue regeneration in vivo for the replacement of malfunction or defective tissues/organs (1). In articular cartilage, a cell-based therapy termed autologous chondrocytes implantation (ACI) involves harvesting a specimen from a non-weight bearing region. This tends to be detrimental to the healthy cartilage surrounding the donor site (2-4). It has been proposed that chondrocytes from nonarticular cartilage sources can be used to overcome this issue (5). Septum cartilage is an attractive source of hyaline cartilage and able to be used for repairing articular cartilage defects by the ability to adapt to the knee joint environment (6). Nasal septum cartilage can be easily harvested with minimal morbidity through septoplasty procedure because the donor site is exposed to low physical force (7). However, chondrocytes tend to lose their cartilaginous phenotype after a large degree of in vitro expansion (6). Human adipose-derived stem cells; Nasal chondrocytes; Cell ratio; Chondrogenesis; Co-culture system; Alginate gel ABSTRACT