Miracle-dz/UniFAR-FTUs huggingface dataset:
Intercalated cushion cells within the cardiac outflow tract are derived from the myocardial troponin T type 2 (Tnnt2) Cre lineage

Background: The origin of the intercalated cushions that develop into the anterior cusp of the pulmonary valve (PV) and the noncoronary cusp of the aortic valve (AV) is not well understood. Results: Cre transgenes in combination with the Rosa TdTomato‐EGFP reporter were used to generate three‐dimensional lineage mapping of AV and PV cusps during intercalated cushion development. Tie2‐Cre;EGFP was used to mark endothelial‐derived mesenchymal cells, Wnt1‐Cre;EGFP for cardiac neural crest and cardiac Troponin T (Tnnt2)Cre;EGFP, for myocardial lineage. The highest percentage of intercalated cushion cells at embryonic day (E) 12.5 was Tnnt2‐Cre; EGFP positive; 68.0% for the PV and 50.0% AV. Neither Tnnt2 mRNA nor Tnnt2‐Cre protein was expressed in the intercalated cushions; and the Tnnt2‐Cre lineage intercalated cushion cells were also positive for the mesenchymal markers Sox9 and versican. Tnnt2‐Cre lineage was present within the forming intercalated cushions from E11.5 and was present in the intercalated cushion derived PV and AV cusps and localized to the fibrosa layer at postnatal day 0. Conclusions: Intercalated cushions of the developing outflow tract are populated with Tnnt2‐Cre derived cells, a Cre reporter previously used for tracing and excision of myocardial cells and not previously associated with mesenchymal cells. Developmental Dynamics 247:1005‐1017, 2018. © 2018 Wiley Periodicals, Inc.
EVALUATION OF THE ZYGOMATIC BUTTRESS AS A DONOR SITE FOR RIDGE AUGMENTATION PRIOR TO IMPLANT INSERTION IN THE ESTHETIC ZONE

INTRODUCTION: Traumatic loss of teeth in the esthetic zone commonly results in significant loss of buccal bone. This leads to reducedesthetics, problems with phonetics and reduction in function. Single tooth replacement has become an indication for implant-based restoration.In case of lack of bone volume the need of surgical reconstruction of the alveolar ridge is warranted. Several bone grafting techniques havebeen described to ensure sufficient bone volume for implantation.OBJECTIVES: Evaluation of using the zygomatic buttress as an intraoral bone harvesting donor site for pre-implant grafting.MATERIALS AND METHODS: Twelve patients were selected with limited alveolar ridge defect in the esthetic zone that needs bone graftingprocedure prior to dental implants. Patients were treated using a 2-stage technique where bone blocks harvested from the zygomatic buttressregion were placed as onlay grafts and fixed with osteosynthesis micro screws. After 4 months of healing, screws were removed for implantplacementRESULTS: Harvesting of 12 bone blocks were performed for all patients indicating a success rate of 100% for the zygomatic buttress area asa donor site. Final rehabilitation with dental implants was possible in 11 of 12 patients, yielding a success rate of 91.6%. Three patients (25%)had postoperative complications at the donor site and one patient (8.3%) at the recipient site. The mean value of bone width pre-operativelywas 3.64 ± . 48 mm which increased to 5.47 ± . 57 mm post-operatively, the increase in mean value of bone width was statistically significant(p < 0.001). CONCLUSIONS: Harvesting of intraoral bone blocks from the zygomatic buttress region is an effective and safe method to treat localizedalveolar ridge defect before implant placement.KEYWORDS: Zygomatic buttress, autogenous bone graft, dental implant, esthetic zone.
A review: Face recognition techniques for differentiate similar faces and twin faces

Facial Recognition Technology is a challenging area in the pattern recognition and computer vision.lot of research is completed in face recognition system. But still we need to enhance the facial recognition system due the poor performance and under practical conditions. This facial recognition technology is used to identify the authorized person mainly for security purpose. In this facial recognition technology its having challenging aspects like similar faces, twins, same person with different ages etc. This paper focus on techniques and algorithm to differentiate the similar faces and identical twins.
Theory of electron, phonon and spin transport in nanoscale quantum devices

At the level of fundamental science, it was recently demonstrated that molecular wires can mediate long-range phase-coherent tunnelling with remarkably low attenuation over a few nanometre even at room temperature. Furthermore, a large mean free path has been observed in graphene and other graphene-like two-dimensional materials. These create the possibility of using quantum and phonon interference to engineer electron and phonon transport through nanoscale junctions for a wide range of applications such as molecular switches, sensors, piezoelectricity, thermoelectricity and thermal management. To understand transport properties of such devices, it is crucial to calculate their electronic and phononic transmission coefficients. The aim of this tutorial article is to outline the basic theoretical concepts and review the state-of-the-art theoretical and mathematical techniques needed to treat electron, phonon and spin transport in nanoscale molecular junctions. This helps not only to explain new phenomenon observed experimentally but also provides a vital design tool to develop novel nanoscale quantum devices.
A generalized hybrid multilevel inverter with reduced number of switches

This paper demonstrates about a novel multilevel inverter (MLI) structure designed with reduced number of switches that can be worked in both symmetric as well as asymmetric DC link voltages. Also, the proposed model can be extended to a generalized n level inverter. The carrier based, Level shifted PWM (LS-PWM) technique is used to generate the gate pulses of the proposed inverter. The proposed MLI is simulated using the MATLAB/SIMULINK platform and verified by the experimental results. The simulation results of a specimen seven level symmetrical inverter as well for a nine-level asymmetrical inverter is presented in the paper. The corresponding experimental results are also presented for the different modulation index.
Data security in cloud

Cloud computing is moving increasingly to a destination with no return: the consolidation is an essential tool for the future existence of the internet world. Cloud computing is used as private, hybrid cloud, big data analytics and backup. Today the trend followed is to store the databases and software's in cloud environment. The services are taken whenever required. Without installing software's in systems users can go to cloud where already software is available and make use of it similarly for storing data also. Security is the main aspect now for the confidential data what we store in cloud. The methodology followed is, to collect resource/data, store data in the cloud, data processing by giving access to fetch the resource to user IP, checking hacker's information and admin responding by restricting respective IP. The restricted IP user can never access the resources anymore. Big data security in cloud, results in tracking unauthorized users (hackers) who try to access the resources. Admin have the special privilege to block the hackers machine by disabling IP address of respective machine. In this current work the data is stored in the server in encrypted fashion and only the admin is given the writes to decrypt the data. If an unauthorized user is trying to access any file or data from the cloud the admin can block the users IP address from accessing the data so that the security for data will be given.
Sampling Clustering

We propose an efficient linear-time graph-based divisive cluster analysis approach called Sampling Clustering. It constructs a lite informative dendrogram by recursively dividing a graph into subgraphs. In each recursive call, a graph is sampled first with a set of vertices being removed to disconnect latent clusters, then condensed by adding edges to the remaining vertices to avoid graph fragmentation caused by vertex removals. We also present some sampling and condensing methods and discuss the effectiveness in this paper. Our implementations run in linear time and achieve outstanding performance on various types of datasets. Experimental results show that they outperform state-of-the-art clustering algorithms with significantly less computing resource requirements.
Online least angle regression algorithm for sparse system identification

Traditional least mean square algorithm based system identifications schemes are not effective in identifying sparse systems and a few sparse adaptive algorithms have been developed recently to overcome this limitation. Least angle regression (LARS) algorithm, which has recently emerged as an effective model selection approach, has found applications in sparse coding and sparse signal recovery. LARS has been shown to provide very fast convergence in sparse signal recovery tasks. The offline learning nature of the LARS algorithm prevents the direct use of the algorithm for online sparse system identification. With an objective to utilize the fast convergence offered by LARS algorithm, an online sparse system identification method based on LARS is developed in this letter. The new scheme has been shown to provide improved convergence behaviour over conventional sparse system identification methods.
Cover time and mixing time of random walks on dynamic graphs

The application of simple random walks on graphs is a powerful tool that is useful in many algorithmic settings such as network exploration, sampling, information spreading, and distributed computing. This is due to the reliance of a simple random walk on only local data, its negligible memory requirements, and its distributed nature. It is well known that for static graphs the cover time, that is, the expected time to visit every node of the graph, and the mixing time, that is, the time to sample a node according to the stationary distribution, are at most polynomial relative to the size of the graph. Motivated by real world networks, such as peer‐to‐peer and wireless networks, the conference version of this paper was the first to study random walks on arbitrary dynamic networks. We study the most general model in which an oblivious adversary is permitted to change the graph after every step of the random walk. In contrast to static graphs, and somewhat counter‐intuitively, we show that there are adversary strategies that force the expected cover time and the mixing time of the simple random walk on dynamic graphs to be exponentially long, even when at each time step the network is well connected and rapidly mixing. To resolve this, we propose a simple strategy, the lazy random walk, which guarantees, under minor conditions, polynomial cover time and polynomial mixing time regardless of the changes made by the adversary.
Effect of a School-Based Intervention on Parents' Nutrition and Exercise Knowledge, Attitudes, and Behaviors

Background Parents exert a significant effect on children's eating behaviors and physical activity levels, so it is imperative to find successful obesity prevention programs that target whole families in underserved communities. Purpose To investigate the effects of a Coordinated School Health Program (CSHP) on parents in the program over a 2-year period. Methods Parents of kindergarteners (n = 277) in 7 schools participating in a CSHP that served an underserved, predominantly minority community were surveyed at 3 time points regarding their nutrition and physical activity knowledge, attitudes, and behaviors (KABs). Results after years 1 and 2 were compared with pre-intervention results using t tests. Effects of socioeconomic variables were investigated using multivariate linear regression. Results Reported unhealthy behaviors were lower at the end of both year 1 (P = .03) and year 2 (P = .04). Numerous factors were associated with changes in KABs in the parents, including parental gender. Discussion A CSHP may have lasting effects on parental behaviors in an underserved, predominantly minority community. Translation to Health Education Practice Future studies should assess the effects of CSHPs in other populations and which factors most significantly affect parental attitude and behavioral changes so that program content may be tailored accordingly.
IPv 6 Convergence for IoT Cyber – Physical Systems

We describe the evolution of the IoT towards a heterogeneous multitopology network subject to dynamic change and volatility yet still capable of secure and dependable operation. As part of this evolution, we outline the key changes in wireless communications technologies and heterogeneous networking that have arisen during the development of the IoT. We briefly outline the emerging area of cyber–physical systems, and associated technical challenges. We then describe how IP convergence can be viewed as the narrow waist connecting endpoint devices and fieldbus devices with applications and services in new Industry 4.0, and cyber–physical system use cases. We outline how a protocol-packing approach can be used for encapsulating LoRaWAN frames with IEEE 802.15. 4 and IEEE 802.11 frames. Extending this, we propose a method for ultracompressed IPv6 signaling, and detail how this can be achieved in an example low-power wide-area technology, namely LoRaWAN. To support our proposed approach, we provide real-world analyses where IPv6 commands undergo a process of ultracompression and are then conveyed to a LoRaWAN endpoint. We find that IPv6 command ultracompression can potentially support command packet sizes that are over 20x smaller than the reported worst-case maximum protocol data unit size of 81 bytes.
Detection of repackaged Android applications based on Apps Permissions

Android developer develops applications and stores it in Google play market to earn profits. Some developers may repackage other's application (Free apps available in Android market) with their names or include various advertisements and add some malicious code to the apps and upload them to the application market for their profit. Similarly, attackers may also include malicious code into the original application in order to gain access the mobile devices to retrieve the personal information of the user, send SMS messages to premium rate numbers etc. Many detection methods have been used to find these repackaged applications available in various markets but they are not so effective to analyze the unknown applications. An efficient method is essential to reduce the number of features, decrease the classification error and the processing time. Repacked apps are identified by comparing the permissions of original and repacked apps. In this paper, a method is proposed to detect a repackaged application by using mutual information and chi square for selecting features and evaluating using random forest classifier. The performance of the classifier is compared with SVM, NB, Decision Tree and KNN.
Technological Advancements in Echocardiographic Assessment of Thoracic Aortic Dilatation: Head to Head Comparison Among Multidetector Computed Tomography, 2-Dimensional, and 3-Dimensional Echocardiography Measurements

Purpose: The aim of this study was to evaluate the feasibility and accuracy of 2-dimensional (2D) and 3-dimensional (3D) transthoracic echocardiography (2DTTE, 3DTTE) versus multidetector computed tomography (MDCT) in patients with ascending aortic (AA) dilation. Materials and Methods: Fifty consecutive patients with AA dilation were evaluated by 2DTTE, X-plane (XP) 3DTTE, and MDCT. Aorta diameters were measured at aortic annulus, aortic root (SIN), sinotubular junction, AA, aortic arch before the prebrachiocephalic artery (PRE), and before left subclavian artery (INTRA). Leading edge-to-leading edge (L-L) and inner-to-inner (I-I) measurements were compared with MDCT data. Results: Feasibility, quality of imaging, and accuracy was high with all echocardiographic methods. Specifically for MDCT maximum SIN diameter, the best correlation and agreement was obtained using XP maximum diameter at 3DTTE (MDCT: 44.8±7.4 mm vs. XP: 44.4±7.4 mm; r=0.975; bias=−0.4 mm). The same was true for AA maximum diameter at MDCT (MDCT: 46.6±8.1 mm vs. XP: 47.5±8.1 mm; r=0.991; bias=0.1 mm). For aortic arch the best correlation and agreement with MDCT were as follows: 2DTTE L-L diameter for arch PRE (MDCT: 37.9±5.3 mm vs. TTE: 36.6±4.5 mm; r=0.927; bias=−0.9 mm) and MDCT minimum diameter with XP minimum diameter for arch INTRA (MDCT: 28.2±5.0 mm vs. TTE 28.8±4.7 mm; r=0.939; bias=−0.3 mm). Conclusion: In patients with aortic dilatation or aneurysm, new techniques (mainly 2D-3D probes allowing XP views) facilitate accuracy of aortic measurements at different sites of the vessel and allow standardization of analysis to better compare with MDCT.
Experimental Analysis of Distributed Graph Systems

This paper evaluates eight parallel graph processing systems: Hadoop, HaLoop, Vertica, Giraph, GraphLab (PowerGraph), Blogel, Flink Gelly, and GraphX (SPARK) over four very large datasets (Twitter, World Road Network, UK 200705, and ClueWeb) using four workloads (PageRank, WCC, SSSP and K-hop). The main objective is to perform an independent scale-out study by experimentally analyzing the performance, usability, and scalability (using up to 128 machines) of these systems. In addition to performance results, we discuss our experiences in using these systems and suggest some system tuning heuristics that lead to better performance.
Latent Dirichlet Allocation and POS Tags Based Method for External Plagiarism Detection: LDA and POS Tags Based Plagiarism Detection

In﻿this﻿article﻿we﻿present﻿a﻿new﻿semantic﻿and﻿syntactic-based﻿method﻿for﻿external﻿plagiarism﻿detection. ﻿ In﻿the﻿proposed﻿approach,﻿latent﻿dirichlet﻿allocation﻿(LDA)﻿and﻿parts﻿of﻿speech﻿(POS)﻿tags﻿are﻿used﻿ together﻿ to﻿detect﻿plagiarism﻿between﻿ the﻿sample﻿and﻿a﻿number﻿of﻿ source﻿documents. ﻿The﻿basic﻿ hypothesis﻿is﻿that﻿considering﻿semantic﻿and﻿syntactic﻿information﻿between﻿two﻿text﻿documents﻿may﻿ improve﻿the﻿performance﻿of﻿the﻿plagiarism﻿detection﻿task. ﻿Our﻿method﻿is﻿based﻿on﻿two﻿steps,﻿naming,﻿ which﻿is﻿a﻿pre-processing﻿where﻿we﻿detect﻿the﻿topics﻿from﻿the﻿sentences﻿in﻿documents﻿using﻿the﻿LDA﻿ and﻿convert﻿each﻿sentence﻿in﻿POS﻿tags﻿array;﻿then﻿a﻿post﻿processing﻿step﻿where﻿the﻿suspicious﻿cases﻿ are﻿verified﻿purely﻿on﻿the﻿basis﻿of﻿semantic﻿rules. ﻿For﻿two﻿types﻿of﻿external﻿plagiarism﻿(copy﻿and﻿ random﻿obfuscation),﻿we﻿empirically﻿compare﻿our﻿approach﻿to﻿the﻿state-of-the-art﻿N-gram﻿based﻿and﻿ stop-word﻿N-gram﻿based﻿methods﻿and﻿observe﻿significant﻿improvements. KEyWORDS External Plagiarism Detection, Latent Dirichlet Allocation (LDA), POS Tags, Topic Semantics
The fishery for California market squid (Loligo opalescens) (Cephalopoda: Myopsida from 1981 through 2003

The California market squid (Loligo opalescens) has been harvested since the 1860s and it has become the largest fishery in California in terms of tonnage and dollars since 1993. The fishery began in Monterey Bay and then shifted to southern California, where effort has increased steadily since 1983. The California Department of Fish and Game (CDFG) collects information on landings of squid, including tonnage,location, and date of capture. We compared landings data gathered by CDFG with sea surface temperature(SST), upwelling index (UI), the southern oscillation index (SOI), and their respective anomalies. We found that the squid fishery in Monterey Bay expends twice the effort of that in southern California. Squid landings decreased substantially following large El Nino events in 1982−83 and 1997−98, but not following the smaller El Nino events of 1987 and 1992. Spectral analysis revealed autocorrelation at annual and 4.5-year intervals (similar to the time period between El Nino cycles). But this analysis did not reveal any fortnightly or monthly spawning peaks, thus squid spawning did not correlate with tides. A paralarvae density index (PDI) for February correlated well with catch per unit of effort (CPUE) for the following November recruitment of adults to the spawning grounds. This stock– recruitment analysis was significant for 2000−03 (CPUE=8.42+0.41PDI, adjusted coefficient of determination,r2=0.978, P=0.0074). Surveys of squid paralarvae explained 97.8% of the variance for catches of adult squid nine months later. The regression of CPUE on PDI could be used to manage the fishery. Catch limits for the fishery could be set on the basis of paralarvae abundance surveyed nine months earlier.
Abnormal behaviour detection at traffic junctions using Lucas Kanade and Harris Corner detector

Image processing has played a vital role in every aspect of human life. Video surveillance has reached a major out through by the application of advanced image processing and frame modeling techniques. Video surveillance is the most recent issue regarding community security and welfare. Detection of behavior of moving objects in video streams is a vital aspect. In this article, automatic real-time object's behavior detection is implemented using Lucas Kanade and Harris Corner based approach. The velocity of moving element is reported and their association with anomalous activity is also an inseparable part of this art. This work can be used to develop a surveillance system of static camera and robotic automation visual systems. Whenever a new object comes in the camera frame, the system uses the concepts of frame based processing using Lucas Kanade approach incorporated with Harris Corner Detector. In this work, an investigation is carried out to define the optimum value of velocity parameters for declaring a behavior as anomalous. Moreover, it is analyzed that proposed algorithm for video behaviour detection at traffic points perform well but its accuracy can be further enhanced using three dimensional imaging and mapping of moving elements in a hyperspace.
The DEBS 2018 Grand Challenge

The ACM DEBS 2018 Grand Challenge is the eighth in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the 2018 Grand Challenge is on the application of machine learning to spatio-temporal streaming data. The goal of the challenge is to make the naval transportation industry more reliable by providing predictions for vessels' destinations and arrival times. This paper describes the specifics of the data streams and queries that define the DEBS 2018 Grand Challenge. It also describes the benchmarking platform that supports testing of corresponding solutions.
siRNAs Targeting Growth Factor Receptor and Anti-Apoptotic Genes Synergistically Kill Breast Cancer Cells through Inhibition of MAPK and PI-3 Kinase Pathways

Breast cancer, the second leading cause of female deaths worldwide, is usually treated with cytotoxic drugs, accompanied by adverse side-effects, development of chemoresistance and relapse of disease condition. Survival and proliferation of the cancer cells are greatly empowered by over-expression or over-activation of growth factor receptors and anti-apoptotic factors. Identification of these key players that cross-talk to each other, and subsequently, knockdown with their respective siRNAs in a synchronous manner could be a promising approach to precisely treat the cancer. Since siRNAs demonstrate limited cell permeability and unfavorable pharmacokinetic behaviors, pH-sensitive nanoparticles of carbonate apatite were employed to efficiently carry the siRNAs in vitro and in vivo. By delivering selective siRNAs against the mRNA transcripts of the growth factor receptors, such as ER, ERBB2 (HER2), EGFR and IGFR, and anti-apoptotic protein, such as BCL2 in human (MCF-7 and MDA-MB-231) and murine (4T1) breast cancer cell lines, we found that ESR1 along with BCL-2, or with ERBB2 and EGFR critically contributes to the growth/survival of the cancer cells by activating the MAPK and PI-3 kinase pathways. Furthermore, intravenous delivery of the selected siRNAs aiming to suppress the expression of ER/BCL2 and ER/ERBB2/EGFR groups of proteins led to a significant retardation in tumor growth in a 4T1-induced syngeneic mouse model.