Miracle-dz/UniFAR-FTUs huggingface dataset:
Second‐order defeaturing error estimation for multiple boundary features

A posteriori estimation of defeaturing error, that is, engineering analysis error caused by defeaturing, remains a key challenge in computer‐aided design/computer‐aided engineering integration; indeed, it is essential if analysis based on automatic simplification of the geometry of a complex design is to be reliable. Previous work has mainly focused on removing a single, negative, internal design feature (i.e. a void within the model's interior); effects of removal of multiple features are found by simple summation. In this paper, we give a second‐order defeaturing error estimator that can handle multiple boundary features, either positive or negative (cutouts or additions on the model's boundary). This is the first such method to take into account interactions between different features. (Removing internal holes in 2D or through holes in 3D will change the model's topology and is not addressed here.) The proposed estimator is also the first to handle positive features without heuristics. Our approach uses second‐order shape sensitivity, on the basis of reformulating defeaturing as a shape transformation process. The reference model used for sensitivity computation is carefully chosen, as is the associated shape variation velocity, to ensure efficient computation and simple sensitivity expressions. Mixed partial derivatives in a second‐order Taylor expansion are used to account for interaction between features. The advantages of our approach are demonstrated using various numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.
New Adaptive Image Quality Assessment Based on Distortion Classification

This paper proposes a new adaptive image quality assessment (AIQA) method, which is based on distortion classifying. AIQA contains two parts, distortion classification and image quality assessment. Firstly, we analysis characteristics of the original and distorted images, including the distribution of wavelet coefficient, the ratio of edge energy and inner energy of the differential image block, we divide distorted images into White Noise distortion, JPEG compression distortion and fuzzy distortion. To evaluate the quality of first two type distortion images, we use pixel based structure similarity metric and DCT based structural similarity metric respectively. For those blurriness pictures, we present a new wavelet-based structure similarity algorithm. According to the experimental results, AIQA takes the advantages of different structural similarity metrics, and it’s able to simulate the human visual perception effectively. Copyright © 2014 IFSA Publishing, S. L.
An Exploration into Technological Capabilities Among Early Stage Indian Product Based Telecom Start-Ups

New technology based start-ups play a very important role in developing the economy of a country. In India, telecom sector has seen unprecedented growth over the last decade and this has led to emergence of several telecom related start-ups. However, product based B2B start-ups are rare and existing ones have to undergo several challenges in commercializing. Surprisingly not much research work has been undertaken in identifying capabilities among early stage start-ups although the early phase represents a very crucial phase for product based firms and has been known to determine the success or failure for start-ups. Present study explores the technological capabilities that enable commercialization among such early stage start-ups by adopting a multiple case (four independent cases) based inductive methodology with Indian telecom start-ups as the context. We have identified architectural design, algorithmic implementation and product adaptation as components of technological capability of such start-ups. We further drill in to each of the sub-components of the technological capabilities to unearth their antecedents and peculiarities in telecom product company context. As a result we also present a classification scheme for studying the product architecture in the telecom context. We analyze and point out differences in technological capability among telecom start-ups vis-a-vis established firms in the sector .
Transarterial radioembolization using yttrium-90 microspheres in the treatment of hepatocellular carcinoma: a review on clinical utility and developments

A selective intra-arterial liver injection using yttrium-90-loaded microspheres as sources for internal radiation therapy is a form of transarterial radioembolization (TARE). Current data from the literature suggest that TARE is effective in hepatocellular carcinoma (HCC) and is associated with a low rate of adverse events; however, they are all based on retrospective series or non-controlled prospective studies, since randomized controlled trials comparing the other liver-directed therapies for intermediate and locally advanced stages HCC are still ongoing. The available data show that TARE provides similar or even better survival rates. TARE is very well tolerated and has a low rate of complications; these complications do not result from the embolic effects but mainly from the unintended irradiation to non-target tissue, including the liver parenchyma. The complications can be further reduced by accurate patient selection and a strict pre-treatment evaluation, including dosimetry and assessment of the vascular anatomy. First-line TARE is best indicated for intermediate-stage patients (according to the Barcelona Clinic Liver Cancer [BCLC] staging classification) who are poor candidates for transarterial chemoembolization or patients having locally advanced disease with segmental or lobar branch portal vein thrombosis. Moreover, data are emerging regarding the use of TARE in patients classified slightly above the criteria for liver transplantation with the purpose of downstaging them. TARE can also be applied as a second-line treatment in patients progressing to transarterial chemoembolization or sorafenib; a large number of Phase II/III trials are in progress in order to evaluate the best association with systemic therapies. Given the complexity of a correct treatment algorithm for potential TARE candidates and the need for clinical guidance, a comprehensive review was carried out analyzing both the best selection criteria of patients who really benefit from TARE and the new advances of this therapy which add significant value to the therapeutic weaponry against HCC.
The Helping Behavior Helps Lighten Physical Burden

ABSTRACT It is often believed that helping behaviors benefit the recipients at the expense of the performers. However, we propose that costly helping behaviors could alleviate feelings of physical burden experienced by the performers. In support of the proposal, we found in five studies that both imaginary and real helping behaviors led the performers to perceive physically challenging tasks as less demanding (Studies 1, 2, 3, 5), such as perceiving a steep mountain road as less steep (Study 2), a heavy carton as lighter (Study 4), and a long path as shorter (Study 5). These results challenge the conventional wisdom that helping behaviors always come at the cost of the helper and corroborate a growing body of literature showing that helping others could benefit the performer.
Network data mining: methods and techniques for discovering deep linkage between attributes

Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of 'emergent' patterns and trends in the linkage. It complements conventional data mining methods, which assume the independence between the attributes and the independence between the values of these attributes. These techniques typically flag, alert or alarm instances or events that could represent anomalous behaviour or irregularities because of a match with pre-defined patterns or rules. They serve as 'exception detection' methods where the rules or definitions of what might constitute an exception are able to be known and specified ahead of time. Many problems are suited to this approach. Many problems however, especially those of a more complex nature, are not well suited. The rules or definitions simply cannot be specified. For example, in the analysis of transaction data there are no known suspicious transactions. This chapter presents a human-centred network data mining methodology that addresses the issues of depicting implicit relationships between data attributes and/or specific values of these attributes. A case study from the area of security illustrates the application of the methodology and corresponding data mining techniques. The chapter argues that for many problems, a 'discovery' phase in the investigative process based on visualisation and human cognition is a logical precedent to, and complement of, more automated 'exception detection' phases.
A computationally affordable implementation of an asymptotically optimal BSS algorithm for ar sources

The second-order blind identification (SOBI) algorithm for separation of stationary sources was proved to be useful in many biomedical applications. This paper revisits the weights-adjusted variant of SOBI, known as WASOBI, which is asymptotically optimal (in separating Gaussian parametric processes), yet prohibitively computationally demanding for more than 2-3 sources. A computationally feasible implementation of the algorithm is proposed, which has a complexity not much higher than SOBI. Excluding the estimation of the correlation matrices, the post-processing complexity of SOBI is O(d4M), where d is the number of the signal components and M is the number of covariance matrices involved. The additional complexity of our proposed implementation of WASOBI is O(d6 + d3M3) operations However, for WASOBI, the number M of the matrices can be significantly lower than that of SOBI without compromising performance. WASOBI is shown to significantly outperform SOBI in simulation, and can be applied, eg. , in the processing o low density EEG signals.
Energy consumption balancing in wireless sensors networks

The management of energy in wireless sensors networks (wsn) is the main factor that can influence the lifespan of the network. To reduce the energy consumption, the transmission of data between sensor nodes must be reduced in order to preserve the remaining energy in every node. The nodes closest to the sink are critical nodes, they perform far more tasks than other nodes in wsn and consume a big amount of energy. Therefore, the resources of these nodes determine the lifetime of the whole network. To reduce the network traffic overhead and prolong the lifespan of the network we propose a new energy balancing architecture based on hexagonal clusters. In addition, the use of a mobile agent for each and every cluster and several sinks for the whole network can solve the problem of uneven energy consumption of both inter- and intra-cluster environments.
A Block Cipher Basing Upon a Revisit to the Feistel Approach and the Modular Arithmetic Inverse of a Key Matrix

In this paper, we have developed a block cipher by using the modular arithmetic inverse of a key matrix. The key matrix is generated by taking the key in the form of twenty-eight numbers, wherein each number is represented in terms of seven binary bits. The encryption is carried out by using the key matrix containing binary bits. The decryption is performed by using the modular arithmetic inverse of the matrix.
On-line signature verification based on template matching approach and support vector data description

Automatic on-line signature verification is an intriguing intellectual challenge with wide attention and practical applications. To solve the difficulty of how to choose the verification threshold in signature verification, we present a novel method based on template matching approach and support vector data description (SVDD) in this paper. Investigates the details of the method and examines the validation of features extracted from 3-axis force of pen-tip to writing tablet. The effectiveness of the proposed solution is demonstrated by the experiment.
Effect of apical clearing technique on the treatment outcome of teeth with asymptomatic apical periodontitis: A randomized clinical trial

Aim: This study aims to compare the periapical healing of teeth with asymptomatic apical periodontitis treated either by conventional apical preparation (CAP) or apical clearing technique (ACT). Materials and Methods: T wenty subjects with bilateral nonvital similar teeth exhibiting comparable periapical index (PAI) score were enrolled and randomly allocated. Group I (CAP, n = 20): Apical preparation three sizes greater (master apical file [MAF]) than the first binding file at the established working length. Group II (ACT, n = 20): Apical preparation three sizes greater than the MAF that was followed by dry reaming. Root canal therapy was accomplished in single-visit for all the teeth. They were pursued radiographically at 3, 6, 9 and 12 months. Pre- and post-treatment PAI scores were compared. To ascertain the proportion of healed teeth between the two groups, McNemar Chi-square test was applied. Results: At 3, 6, and 9 months' time interval the proportion of healed teeth for Group II (ACT) was greater in comparison to Group I (CAP) (P < 0.05). However, at 12 months follow-up period this difference was not significant (P = 0.08). Conclusion: ACT enhanced the healing kinetics. However, the long-term (12 months) radiographic outcome was similar for either technique.
Information infrastructure in action

Since the introduction of computers in the middle of the twentieth century, the potential of information technology (IT) to transform organisations has been a constant subject of analysis for both organisation studies and information systems research. Each new generation of technology and every major technological innovation has been followed by strong alleges that organisations, businesses and society in general, would have to be radically and fundamentally transformed to take account of the opportunities opened by the innovations in technological capabilities. The opportunities of change in the organisation of work activities predicted in association with these new technologies have conventionally been discussed in the light of different views on technology, associated with new perspectives on organisation design and management. A very similar debate characterises the dispute about the role of information infrastructures in supporting economic activities in contemporary society. As a consequence of their diffusion, information infrastructures have in fact gained increased attention in the area of information systems research. As a result of the increased diffusion of information technologies in organisation and in society the level of interdependences among single information systems is escalating so that today it is very difficult to think about independent information systems rather than information infrastructures (Hanseth, 2004b). Such information infrastructures are in fact characterised by the interplay in the intricacy of the set of interconnected hardware, software, and procedural configurations deployed to support and enact pre-determined paths of behaviour in organisations and among users. This chapter aims to contribute to this area of research by questioning the nature of information infrastructures to better understand how to design, deploy and manage them. In doing so, it discusses how the traditional distinction between technology and organisation and the analyses based on this assumption are not sufficient to explain the problem associated with information infrastructure design, deployment, and management. This study of information infrastructures focuses on the interplay between technologies and the organisations using them. This interplay is regarded as the main force that shapes information infrastructures and hence the most important fact to be considered to understand the complexity of these structures.
HOS2 and HDA1 Encode Histone Deacetylases with Opposing Roles in Candida albicans Morphogenesis

Epigenetic mechanisms regulate the expression of virulence traits in diverse pathogens, including protozoan and fungi. In the human fungal pathogen Candida albicans, virulence traits such as antifungal resistance, white-opaque switching, and adhesion to lung cells are regulated by histone deacetylases (HDACs). However, the role of HDACs in the regulation of the yeast-hyphal morphogenetic transitions, a critical virulence attribute of C. albicans, remains poorly explored. In this study, we wished to determine the relevance of other HDACs on C. albicans morphogenesis. We generated mutants in the HDACs HOS1, HOS2, RPD31, and HDA1 and determined their ability to filament in response to different environmental stimuli. We found that while HOS1 and RPD31 have no or a more limited role in morphogenesis, the HDACs HOS2 and HDA1 have opposite roles in the regulation of hyphal formation. Our results demonstrate an important role for HDACs on the regulation of yeast-hyphal transitions in the human pathogen C. albicans.
Searchlight: Enabling Integrated Search and Exploration over Large Multidimensional Data

We present a new system, called Searchlight, that uniquely integrates constraint solving and data management techniques. It allows Constraint Programming (CP) machinery to run efficiently inside a DBMS without the need to extract, transform and move the data. This marriage concurrently offers the rich expressiveness and efficiency of constraint-based search and optimization provided by modern CP solvers, and the ability of DBMSs to store and query data at scale, resulting in an enriched functionality that can effectively support both data- and search-intensive applications. As such, Searchlight is the first system to support generic search, exploration and mining over large multi-dimensional data collections, going beyond point algorithms designed for point search and mining tasks. Searchlight makes the following scientific contributions: • Constraint solvers as first-class citizens Instead of treating solver logic as a black-box, Searchlight provides native support, incorporating the necessary APIs for its specification and transparent execution as part of query plans, as well as novel algorithms for its optimized execution and parallelization. • Speculative solving Existing solvers assume that the entire data set is main-memory resident. Searchlight uses an innovative two stage Solve-Validate approach that allows it to operate speculatively yet safely on main-memory synopses, quickly producing candidate search results that can later be efficiently validated on real data. • Computation and I/O load balancing As CP solver logic can be computationally expensive, executing it on large search and data spaces requires novel CPU-I/O balancing approaches when performing search distribution. We built a prototype implementation of Searchlight on Google's Or-Tools, an open-source suite of operations research tools, and the array DBMS SciDB. Extensive experimental results show that Searchlight often performs orders of magnitude faster than the next best approach (SciDB-only or CP-solver-only) in terms of end response time and time to first result.
Targeting the insulin growth factor-1 receptor with fluorescent antibodies enables high resolution imaging of human pancreatic cancer in orthotopic mouse models

The goal of the present study was to determine whether insulin-like growth factor-1 receptor (IGF-1R) antibodies, conjugated with bright fluorophores, could enable visualization of pancreatic cancer in orthotopic nude mouse models. IGF-1R antibody (clone 24-31) was conjugated with 550 nm or 650 nm fluorophores. Western blotting confirmed the expression of IGF-1R in Panc-1, BxPC3, and MIAPaCa-2 human pancreatic cancer cell lines. Labeling with fluorophore-conjugated IGF-1R antibody demonstrated fluorescent foci on the membrane of the pancreatic cancer cells. Subcutaneous Panc-1, BxPC-3, and MIA PaCa-2 tumors became fluorescent after intravenous administration of fluorescent IGF-1R antibodies. Orthotopically-transplanted BxPC-3 tumors became fluorescent with the conjugated IGF-1R antibodies, and were easily visible with intravital imaging. Gross and microscopic ex vivo imaging of resected pancreatic tumor and normal pancreas confirmed that fluorescence indeed came from the membrane of cancer cells, and it was stronger from the tumor than the normal tissue. The present study demonstrates that fluorophore-conjugated IGF-1R antibodies can visualize pancreatic cancer and it can be used with various imaging devices such as endoscopy and laparoscopy for diagnosis and fluorescence-guided surgery.
Protein-network modeling of prostate cancer gene signatures reveals essential pathways in disease recurrence

Objective Uncovering the dominant molecular deregulation among the multitude of pathways implicated in aggressive prostate cancer is essential to intelligently developing targeted therapies. Paradoxically, published prostate cancer gene expression signatures of poor prognosis share little overlap and thus do not reveal shared mechanisms. The authors hypothesize that, by analyzing gene signatures with quantitative models of protein–protein interactions, key pathways will be elucidated and shown to be shared. Design The authors statistically prioritized common interactors between established cancer genes and genes from each prostate cancer signature of poor prognosis independently via a previously validated single protein analysis of network (SPAN) methodology. Additionally, they computationally identified pathways among the aggregated interactors across signatures and validated them using a similarity metric and patient survival. Measurement Using an information-theoretic metric, the authors assessed the mechanistic similarity of the interactor signature. Its prognostic ability was assessed in an independent cohort of 198 patients with high-Gleason prostate cancer using Kaplan–Meier analysis. Results Of the 13 prostate cancer signatures that were evaluated, eight interacted significantly with established cancer genes (false discovery rate <5%) and generated a 42-gene interactor signature that showed the highest mechanistic similarity (p<0.0001). Via parameter-free unsupervised classification, the interactor signature dichotomized the independent prostate cancer cohort with a significant survival difference (p=0.009). Interpretation of the network not only recapitulated phosphatidylinositol-3 kinase/NF-κB signaling, but also highlighted less well established relevant pathways such as the Janus kinase 2 cascade. Conclusions SPAN methodolgy provides a robust means of abstracting disparate prostate cancer gene expression signatures into clinically useful, prioritized pathways as well as useful mechanistic pathways.
A robust predominant-F0 estimation method for real-time detection of melody and bass lines in CD recordings

This paper describes a robust method for estimating the fundamental frequency (F0) of melody and bass lines in monaural real-world musical audio signals containing sounds of various instruments. Most previous F0-estimation methods had great difficulty dealing with such complex audio signals because they were designed to deal with mixtures of only a few sounds. To make it possible to estimate the F0 of the melody and bass lines, we propose a predominant-F0 estimation method called PreFEst that does not rely on the F0's unreliable frequency component and obtains the most predominant F0 supported by harmonics within an intentionally limited frequency range. It evaluates the relative dominance of every possible F0 by using the expectation-maximization algorithm and considers the temporal continuity of F0s by using a multiple-agent architecture. Experimental results show that our real-time system can detect the melody and bass lines in audio signals sampled from commercially distributed compact discs.