Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of grape seed extract on the bond strength and durability of resin-dentin interface

Abstract To investigate the effect of grape seed extract (GSE) on the bond strength and durability of the resin-dentin interface using a two-step etch-and-rinse (E&R) and a universal adhesive (UA) system. Additionally the effect of dry and wet bonding on the interface created by UA was evaluated. The effect of GSE on the morphology, nanoleakage expression (NE) and bond strength of the resin-dentin interface was evaluated by scanning electron microscopy (SEM) evaluation, interfacial NE and micro-tensile bond strength (μ-TBS) testing respectively. Dentin surfaces of sound molars were exposed, acid-etched, and treated with cross-linking pre-conditioners followed by application of adhesive, light-cured, and built up with restorative composite in an incremental manner. After the restored teeth were left for 24 h in distilled water for polymerisation, dentin beams were sectioned for μ-TBS testing and dentin slabs for SEM and NE. Pre-treatment with GSE did not significantly alter the μ-TBS and NE of any adhesives compared to their respective controls at 24 h and 1 year. Significant decrease in μ-TBS and significant increase in NE after 1 year of storage compared to 24 h results is observed. SEM evaluation showed good hybrid layer formation at 24 h but shows a degraded appearance after 1 year especially with wet bonding technique. Pre-treatment of acid-etched dentin with 6.5% GSE w/v for 1 min, before the application of the adhesive did not significantly improve the bond strength and durability of the resin-dentin interface created by the two-step E&R adhesive and UA. Dry bonding technique for UA seemed more effective.
Identification of Defense Compounds in Barbarea vulgaris against the Herbivore Phyllotreta nemorum by an Ecometabolomic Approach1[W]

Winter cress (Barbarea vulgaris) is resistant to a range of insect species. Some B. vulgaris genotypes are resistant, whereas others are susceptible, to herbivory by flea beetle larvae (Phyllotreta nemorum). Metabolites involved in resistance to herbivory by flea beetles were identified using an ecometabolomic approach. An F2 population representing the whole range from full susceptibility to full resistance to flea beetle larvae was generated by a cross between a susceptible and a resistant B. vulgaris plant. This F2 offspring was evaluated with a bioassay measuring the ability of susceptible flea beetle larvae to survive on each plant. Metabolites that correlated negatively with larvae survival were identified through correlation, cluster, and principal component analyses. Two main clusters of metabolites that correlate negatively with larvae survival were identified. Principal component analysis grouped resistant and susceptible plants as well as correlated metabolites. Known saponins, such as hederagenin cellobioside and oleanolic acid cellobioside, as well as two other saponins correlated significantly with plant resistance. This study shows the potential of metabolomics to identify bioactive compounds involved in plant defense.
Theoretical Models for Learning from Multiple, Heterogenous and Strategic Agents

With the advent of internet enabled hand-held mobile devices, there is a proliferation of user generated data. Often there is a wealth of useful knowledge embedded within this data and machine learning techniques can be used to extract the information. However, as much of this data is user generated, it suffers from subjectivity. Any machine learning techniques used in this context should address the subjectivity in a principled way. We broadly study three problems in the context of learning from multiple agents, (1) Multi-label classification (2) Active Linear Regression (3) Sponsored Search Auctions.
Image moments-based velocity estimation of UAVs in GPS denied environments

This paper proposes a new method for quadrotor translational velocity estimation using only onboard sensing and without any prior knowledge on the geometry of the scene. Image moments extracted from the onboard camera images, together with onboard IMU data, are exploited in an Unscented Kalman filter (UKF). Differently with respect to the literature approaches, the proposed method is independent from the scale factor when considering a planar visual object. The estimation algorithm, in addition of involving matrices of constant size, does not require a well-textured environment, but can rather operate with few visual features. This makes it computationally-cheap, thus appealing for onboard applications. Experiments on a flying real quadrotor are carried out in a GPS-denied and poorly-textured environment in order to verify the validity of the proposed approach as well as its robustness to measurement noises and errors.
“ I like work : I can sit and look at it for hours ” Type clash vs . plausibility in covert event recovery

A range of event-subcategorizing verbs can combine with entity-denoting nouns, like begin the newspaper. The interpretation of such sentences typically involves the recovery of covert events (CE) which are not realized on the surface, as in begin reading the newspaper. We report on an ongoing study that scrutinizes two assumptions made by traditional accounts: (a) that the triggering of CEs can be ascribed to the object’s ontological type; and (b), that one or two CEs can be retrieved for each noun. Preliminary evidence against both assumptions is presented.
Spaceborne lidar calibration from cirrus and molecular backscatter returns

In order to make optimal quantitative use of multiwavelength spaceborne lidar data it is essential that the lidar be well calibrated. Due to system gain/efficiency changes that can be expected to occur during the course of a shuttle or satellite mission, it is essential to employ a calibration approach that can be implemented on-orbit, preferably repeatable at least a few times per orbit. For wavelengths less than about 550 nm, in situ calibration can be accomplished via normalization to high altitude, nearly molecular scattering regions. However, for longer wavelengths beyond about 800 nm, particularly the popular Nd:YAG fundamental wavelength at 1064 nm, the Rayleigh normalization approach becomes questionable due to both an inherently weaker signal and a stronger, variable and somewhat unknown aerosol scattering contribution. For lidars operating at both longer and shorter wavelengths, a viable approach is to retrieve the longer wavelength calibrations ratioed to the shorter wavelength calibrations via comparisons of spectral backscatter from known/quantifiable scatterers. Cirrus clouds are good for this purpose because they occur at high altitudes with significant frequency and provide strong, nearly spectrally flat backscatter. This paper presents the cirrus spectral backscatter ratio calibration approach, including results obtained from case studies of lidar data collected during the LITE shuttle mission. Attention is focused on developing a simple, autonomous approach applicable to satellite lidar missions such as PICASO-CENA.
SemCCM: course and competence management in learning management systems using semantic web technologies

The knowledge embedded into the Learning Management Systems (LMSs) contains great potential, but currently is not utilized well enough because the learning content is mainly tailored for human understanding and not for computer processing. The courses in the LMSs cover certain set of topics that are usually exposed through a few general keywords and areas. In this paper the SemCCM system that utilizes the state of the art Semantic Web tools, methods and datasets for automatic semantic annotation of LMS courses is presented. The SemCCM system complements the LMSs through extraction and ranking of the relevant DBpedia resources for each of the courses, and uses their Wikipedia categories for more general area determination. The extracted DBpedia resources, together with their categories represent the specific topics covered by the courses and provide more accurate course retrieval. Together with the users' completed courses, the extracted DBpedia resources are used for determination of the users' competencies. The SemCCM system presents the analysis results to the end users in several different perspectives, enabling semantically enhanced course and user search, graph based course and competence overview, as well as user comparison.
Interpretable Probabilistic Divisive Clustering of Large Node-Attributed Networks

Social network analysis is an important set of techniques that are used in many different areas. One such area is intelligence and law enforcement where social network analysis is used to study various kinds of networks. One of the problems with social networks that are extracted from social media is that easily becomes very large and as a consequence difficult to analyze. Therefore, there is a need for techniques that can divide a large network into smaller communities that are more feasible to analyze. Existing community detection algorithms usually only focus on creating communities based on the underlying networks structure and therefore it can be hard to interpret the meaning of communities.In this work, we present two methods for community detection that allows a user to detect communities with an underlying meaning not only based on the relations in the network but also on attributes of the nodes. Our methods use iterative approaches that allow the user to define meaningful properties and are applicable on large social networks with attributed nodes.
Run the GAMUT: a comprehensive approach to evaluating game-theoretic algorithms

We present GAMUT^1, a suite of game generators designed for testing game-theoretic algorithms. We explain why such a generator is necessary, offer a way of visualizing relationships between the sets of games supported by GAMUT, and give an overview of GAMUTýs architecture. We highlight the importance of using comprehensive test data by benchmarking existing algorithms. We show surprisingly large variation in algorithm performance across different sets of games for two widely-studied problems: computing Nash equilibria and multiagent learning in repeated games.
Some concepts and methods of information granule diffusion

When a set of information granules is incomplete to represent an object A, it seems that we could employ the information diffusion techniques to change the granules into fuzzy granulations for filling the gaps with respect to a scarcity. In this paper, we suggest the concept of information granule diffusion, and give the 1-dimension linear diffusion model and normal diffusion model. We give two examples in engineering to show that the methods of information granule diffusion would play a pivotal role in the processing of incomplete, uncertain, vague information.
Automatic parameters selection for SVM based on GA

Motivated by the fact that automatic parameter selection for support vector machines (SVM) is an important issue in order to make the SVM practically useful against the commonly used leave-one-out (loo) method, which has complex calculation and time consuming. An effective strategy for automatic parameter selection for SVM is proposed by using the genetic algorithm (GA) in this paper. Simulation results of the practice data model demonstrate the effectiveness and high efficiency of the proposed approach.
PDAF: Proactive Distributed Authentication Framework for Regional Network

We are designing a regional network for New Generation Network (NWGN), which is a future network vision. Regional network needs strong security protections to enable it to be robust under various attacks, such as impersonation attack, replay attack, and illegal modification. To disable these attacks, we identify the design requirements and then propose a proactive and distributed authentication framework (PDAF), where a novel entity called regional network key server (RNKS) is introduced for ID/key generation in this network. By the proposed PDAF, the automatic trustworthy registration, distributed access authentication, handover authentication and mutual authentication can be achieved by end devices, and meanwhile trustworthy information dissemination and transmission can be realized for networking devices without involving trust third parties (TTPs).
Preventing Schizophrenia and Psychotic Behaviour: Definitions and Methodological Issues

Although schizophrenia onset usually occurs in late adolescence or early adulthood, much research shows that its seeds are planted early in life and that eventual onset occurs at the end of a neurodevelopmental process leading to aberrant brain functioning. This idea, along with the fact that current therapies are far from fully effective, suggests that preventive treatments may be needed to achieve an ideal outcome for schizophrenia patients and those predisposed to the disorder. In this article, we review the methodological challenges that must be overcome before effective preventive interventions can be created. Prevention studies will need to define the target population. This requires the identification of risk factors that will be useful in selecting at-risk people for preventive treatment. We review currently identified risk factors for schizophrenia: genes, psychosocial factors, pregnancy and delivery complications, and viruses. We also review 3 different types of prevention programs: universal, indicated, and selective. For schizophrenia, we distinguish prevention programs that target prodromal cases and those that target the disorder's premorbid precursors. Although those targeting prodromal cases provide a useful framework for early treatment of the disorder, studies of premorbid individuals are needed to design a truly preventive treatment.
Febuxostat for management of tumor lysis syndrome including its effects on levels of purine metabolites in patients with hematological malignancies - a single institution's, pharmacokinetic and pilot prospective study.

BACKGROUND/AIM Tumor lysis syndrome (TLS) is a life-threatening oncological emergency, and control of serum uric acid level (S-UA) is most important. In this single-institution, short-term and pilot prospective study, the efficacy of a new xanthine oxidase inhibitor, febuxostat, as an alternative to conventional allopurinol, including its effects on hypoxanthine and xanthine, was evaluated in 10 consecutive patients with hematological malignancies at intermediate risk for TLS. PATIENTS AND METHODS Febuxostat at 40 mg (n=7) or 60 mg (n=3) daily was administered according to renal function, and induction chemotherapy was started within 24 h. The primary end-point was the reduction of S-UA to ≤ 7.5 mg/dl by day 5. RESULTS The median S-UA at base-line was 8.0 mg/dl (range=3.2-10.6 mg/dl). The median S-UA on day 5 after chemotherapy was 3.3 mg/dl (range=1.1-5.8 mg/dl) (p<0.0001, by paired t-test), indicating successful control of S-UA during chemotherapy. All patients achieved S-UA ≤ 7.5 mg/dl. A simultaneous decrease in serum creatinine and increase in estimated glomerular filtration rate were seen. Serum hypoxanthine and xanthine levels (as the consequence of inhibition of xanthine oxidase) were elevated along with the decrease in S-UA. Xanthine level was elevated higher compared to hypoxanthine level and reached the level reported to cause xanthine nephropathy, but no advance of renal impairment was observed. Serum febuxostat concentrations at 2 h after administration were 891.8 ± 285.0 ng/ml (mean ± SE) for the 40-mg dose and 770.6 ± 242.7 ng/ml for the 60-mg dose (p=0.80, unpaired t-test), showing no accumulation in patients with renal impairment. No febuxostat-related adverse reactions were noted. No patients experienced progressive TLS. CONCLUSION Febuxostat is promising for the management of TLS of an intermediate-risk patient and further observation and reevaluation regarding xanthine nephropathy should be performed.
Invariant Surface EMG Feature Against Varying Contraction Level for Myoelectric Control Based on Muscle Coordination

Variations in muscle contraction effort have a substantial impact on performance of pattern recognition based myoelectric control. Though incorporating changes into training phase could decrease the effect, the training time would be increased and the clinical viability would be limited. The modulation of force relies on the coordination of multiple muscles, which provides a possibility to classify motions with different forces without adding extra training samples. This study explores the property of muscle coordination in the frequency domain and found that the orientation of muscle activation pattern vector of the frequency band is similar for the same motion with different force levels. Two novel features based on discrete Fourier transform and muscle coordination were proposed subsequently, and the classification accuracy was increased by around 11% compared to the traditional time domain feature sets when classifying nine classes of motions with three different force levels. Further analysis found that both features decreased the difference among different forces of the same motion p <; 0.005) and maintained the distance among different motions p > 0.1). This study also provided a potential way for simultaneous classification of hand motions and forces without training at all force levels.
Audio-visual speaker identification using the CUAVE database

The freely available nature of the CUAVE database allows it to provide a valuable platform to form benchmarks and compare research. This paper shows that the CUAVE database can successfully be used to test speaker identifications systems, with performance comparable to existing systems implemented on other databases. Additionally, this research shows that the optimal configuration for decisionfusion of an audio-visual speaker identification system relies heavily on the video modality in all but clean speech conditions.
Denoising and deconvolution in nuclear medicine

Nuclear medicine imaging is an excellent diagnostic tool because it does not only show the anatomy of an organ or body part, but also the function of the organ. This additional functional information allows nuclear medicine to diagnose certain diseases much sooner that other medical examinations which provide mainly anatomic information. One of the major sources of error in nuclear medicine images is Poisson noise which hinders image analysis and interpretation. Moreover, we are facing the problem of removing the effect of the observation mechanism from the images. This paper presents a new restoration method where denoising and deconvolution are coupled in a multiresolution frame. The performances are illustrated with phantom images.
Performance Analysis of Cognitive Radio based WRAN over Rayleigh Fading Channel with Alamouti-STBC 2X1, 2X2&2X4 Multiplexing

Bit error rate (BER) is the fundamental parameter to access the quality of any wireless communication. The good quality (low BER) of transmission over less SNR value is always a topic of research. However the BER can be reduced by increasing the SNR, the high value of SNR for wireless communication is limited by available transmitted power & large distance. It is observed that different modulation techniques struggles neck to neck for getting low BER, at lesser value of SNR but still with the slight change in BER the quality of transmission changes many folds. In this work we are evaluating the BER performance of cognitive radio based IEEE 802.22 WRAN with ALAMOUTI-STBC multiplexing over Rayleigh fading channel using BPSK & QPSK modulation in MATLAB environment.
Stoichiometry and Affinity of Thioflavin T Binding to Sup35p Amyloid Fibrils

In this work two modes of binding of the fluorescent probe thioflavin T to yeast prion protein Sup35p amyloid fibrils were revealed by absorption spectrometry of solutions prepared by equilibrium microdialysis. These binding modes exhibited significant differences in binding affinity and stoichiometry. Moreover, the absorption spectrum and the molar extinction coefficient of the dye bound in each mode were determined. The fluorescence quantum yield of the dye bound in each mode was determined via a spectrofluorimetric study of the same solutions in which the recorded fluorescence intensity was corrected for the primary inner filter effect. As previously predicted, the existence of one of the detected binding modes may be due to the incorporation of the dye into the grooves along the fiber axis perpendicular to the β-sheets of the fibrils. It was assumed that the second type of binding with higher affinity may be due to the existence of ThT binding sites that are localized to areas where amyloid fibrils are clustered.
Morphology, tensile properties, and fracture toughness of epoxy/Al2O3 nanocomposites

Epoxy/Al 2 O 3 nanocomposites were prepared using an epoxy resin, diglycidyl ether of bisphenol A, and cured with a polyoxypropylene diamine (Jeffamine D-400). Transmission electron microscopy and wide angle X-ray diffraction were employed to reveal the morphology of epoxy/Al 2 O 3 nanocomposites. Dynamic mechanical analysis results showed that the storage modulus and the glass transition temperature (Tg) of epoxy were improved. Tensile strength and Young's modulus also increased with increasing Al 2 O 3 loading. Fracture toughness, as indicated by the stress intensity factor, K Q , was determined using single edge notch bending method, and 40% increase in K Q was observed with only 2 vol % Al 2 O 3 . Scanning electron microscopy study of fracture surface showed a rather smooth and flat morphology for neat epoxy. However, massive plastic deformation was observed for epoxy/Al 2 O 3 nanocomposites, leading to the significant increase in fracture toughness. The influence of spherical Al 2 O 3 nanoparticles on thermophysical properties of epoxy was discussed and compared with that of sheet-like nanoclays.
Segmentation Method for NaXi Pictograph Character Recognition

NaXi pictograph, which is the only hieroglyph in use is important for researching into the evolution of the character. The research on the recognition of printed NaXi pictograph characters is now just beginning. The major problem with machine printed NaXi pictograph character segmentation is the shape of the letter depending on its location in the word. In this paper, a machine printed NaXi pictograph character segmentation algorithm, which is based on the windows backtracking histogram and some thresholds, is presented. To establish two sample databases of NaXi pictograph text images, and use three thresholds methods separately to make the binarization processing about images. After the testing, Ostu’s algorithm is more suitable for the binarization processing about NaXi pictograph images. For this sample database, we separately employ the projection algorithm and windows backtracking algorithm for segmentation, and the experimental results show that the windows backtracking algorithm in this paper is better than the projection algorithm.
Robust Offline Signature Verification Based on Polygon Matching Technique

— Biometrics verification has become a hot subject in recent years because the need to prevent unauthorized accesses to all kinds of e-data. A handwritten signature, being a behavior biometrics, is well accepted socially and legally as a convenient mean of authorization and identification. This paper presents the approach for extraction of Global and Textural feature required for verification. This method takes care of skill, simple and random forgeries. The objective of the work is to reduce the two vital parameters False Acceptance Rate (FAR) and False Rejection Rate (FRR) normally used in any signature verification scheme. The signature reflects both the direction change pattern of the sequence and smoothness of the signature that are efficient for signature verification. The user introduces into the computer the scanned images, modifies their quality by image enhancement and noise reduction techniques, to be followed by feature extraction and finally verifies the authenticity of the signature. The paper discusses the different stages of the process including: image pre-processing, feature extraction and verification.