Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitochondrial E3 ubiquitin ligase MARCH5 controls mitochondrial fission and cell sensitivity to stress-induced apoptosis through regulation of MiD49 protein

The data presented support a critical role for MARCH5 in the regulation of mitochondrial fission and cell viability. Through ubiquitin- and proteasome-dependent degradation of MiD49, MARCH5 acts as a negative regulator of mitochondrial fission and thereby initiates a mechanism that affords the cell protection from stress-induced apoptosis.
Document frequency and term specificity

Document frequency is used in various applications in Information Retrieval and other related fields. An assumption frequently made is that the document frequency represents a level of the term's specificity. However, empirical results to support this assumption are limited. Therefore, a large-scale experiment was carried out, using multiple corpora, to gain further insight into the relationship between the document frequency and term specificity. The results show that the assumption holds only at the very specific levels that cover the majority of vocabulary. The results also show that a larger corpus is more accurate at estimating the specificity. However, the co-occurrence information is shown to be effective for improving the accuracy when only a small corpus is available.
Performance Evaluation of Beamforming Algorithm with Jacket Matrix Based Eigenvalue Decomposition

In this paper, we have evaluated the performance of Beam forming algorithm for uncoded signal with and without Jacket Matrix based eigenvalue decomposition. First, the channel matrix has been converted to the Jacket form according to the Jacket matrix transformation and the eigenvalue is calculated. Eigenvalues are used to calculate the weight matrix. Finally, weight matrix is used for transmit signal with adaptive white Gaussian noise. The experimental result shows that the jacket matrix based eigenvalue decomposition performs better than normal decomposition.
BlogMiner: Web Blog Mining Application for Classification of Movie Reviews

With the increasing use of Web 2.0 platforms such as Web Blogs, discussion forums, Wikis, and various other types of social media, people began to share their experiences and opinions about products or services on the World Wide Web. Web Blogs have thus become an important source of information. In turn, great interest in blog mining has arisen, specifically due to its potential applications, such as in opinion or review search engine applications the ability to collect and analyze data. In this study, we introduce an architecture, implementation, and evaluation of a Web blog mining application, called the BlogMiner, which extracts and classifies people’s opinions and emotions (or sentiment) from the contents of weblogs about movie reviews.
A Fast and Robust Method for Visualizing Separation Line Features

The visualization of a three-dimensional viscous flow around an embedded object is typically based on the analysis of its wall shear stress. This vector field defined over the object body exhibits structures that are key to the qualitative evaluation of the surrounding flow. Open separation and attachment lines are of essential interest in aerodynamics due to their adverse effects on the object motion and their implication in vortex genesis. The paper presents a new method for the efficient analysis and visualization of separation and attachment lines on polyhedral surfaces in threespace. It combines local prediction and global feature extraction to yield a scheme that is both efficient and accurate. In particular, it does not suffer from the restrictions induced by assumptions of local linearity and is able to detect features where existing techniques fail. The algorithm is built upon an efficient streamline integration scheme on polyhedral surfaces. The latter is also employed to develop a variation of the LIC scheme. Results are proposed on CFD data sets that demonstrate the ability of the new technique to precisely identify and depict interesting structures in practical applications.
A study of the effect of emotional state upon text-independent speaker identification

In this paper we evaluate the effect of the emotional state of a speaker when text-independent speaker identification is performed. The spectral features used for speaker recognition are the Mel-frequency cepstral coefficients, while for the training of the speaker models and testing the system the Gaussian Mixture Models are employed. The tests are performed on the Berlin emotional speech database which contains 10 different speakers recorded in different emotional situations: happy, angry, fear, bored, sad and neutral. The results show an important influence of the emotional state upon text-independent speaker identification. In the end we try to give a possible solution to this problem.
Promoting Patriarchy or Dual Equality? Multiculturalism and the Immigrant Household Division of Labor

ABSTRACT In this article, we provide the first empirical analysis of the relationship between multicultural immigration policy and gender inequality within immigrant communities. A fierce sociological debate pits those who identify multiculturalism as a key obstacle to gender equality among immigrant families against those who believe multiculturalism and gender egalitarianism are “dual-equality projects. ” At the core of this debate are differences over the extent to which multiculturalism impedes or promotes the transmission of gender egalitarianism from host societies to immigrant communities. To adjudicate between these two perspectives, we examine whether microfoundations of the household division of labor—relative resources, time availability, and gender ideology—reduce the share of women’s labor to a greater or lesser degree in multicultural countries. We find multiculturalism increases the egalitarian effects of microfoundations among immigrant households. Both symbolic and material forms of multiculturalism contribute to its moderating effect, but immigrant women benefit the most in countries with both types of multiculturalist policies. In highly multicultural countries, rising incomes, greater employment, and more egalitarian gender ideologies can produce dramatic reductions in housework for immigrant women. We conclude by specifying the conditions where multiculturalism reduce inequalities between immigrants and natives, and within immigrant communities.
Coalition calculation in a dynamic agent environment

We consider a dynamic market-place of self-interested agents with differing capabilities. A task to be completed is proposed to the agent population. An agent attempts to form a coalition of agents to perform the task. Before proposing a coalition, the agent must determine the optimal set of agents with whom to enter into a coalition for this task; we refer to this activity as coalition calculation. To determine the optimal coalition, the agent must have a means of calculating the value of any given coalition. Multiple metrics (cost, time, quality etc.) determine the true value of a coalition. However, because of conflicting metrics, differing metric importance and the tendency of metric importance to vary over time, it is difficult to obtain a true valuation of a given coalition. Previous work has not addressed these issues. We present a solution based on the adaptation of a multi-objective optimization evolutionary algorithm. In order to obtain a true valuation of any coalition, we use the concept of Pareto dominance coupled with a distance weighting algorithm. We determine the Pareto optimal set of coalitions and then use an instance-based learning algorithm to select the optimal coalition. We show through empirical evaluation that the proposed technique is capable of eliciting metric importance and adapting to metric variation over time.
Description and Evaluation of Elasticity Strategies for Business Processes in the Cloud

More and more companies are currently migrating business processes to the Cloud in order to handle customer service in an efficient and cost effective way. Cloud Computing's elasticity and flexibility in service delivery makes it an ideal solution for companies to deal with highly variable service demands and uncertain financial environment to ensure the required QoS while using resources and reduce their expenses. Elasticity management is witnessing a lot of attention from IT community as a pivotal issue for finding the right tradeoffs between QoS levels and operational costs by working on developing novel methods and mechanisms. However, controlling business process elasticity and defining non-trivial elasticity strategies are challenging issues. In this paper, we propose an elasticity strategy description language, called Strat. It is defined as an extensible Domain-Specific Language to allow business process holders to describe elasticity strategies that are evaluated using our formal evaluation framework. Given a usage behavior and a business process, the evaluation consists in providing a set of plots that allows the analysis and the comparison of strategies. Our contributions and developments provide Cloud tenants with facilities to choose elasticity strategies that fit to their business processes and usage behaviors.
Further simplified servers assisted threshold RSA signature

Server assisted threshold signatures provide a user with controllability for activating his private signing function in a certain enhanced way. In this paper, we present a simple, efficient and adaptively secure server assisted threshold RSA signature protocol. The proposed protocol is claimed to be correct, consistent and t − 1 unforgeability. As a separate contribution we prove that it is also secure in the universal composability framework. The proposed scheme reduces large amounts of modular exponential computations and communications. It can be applied to the mobile agent system, regardless what the environment it interacts with.
Invited SIG - participation and HCI: why involve people in design?

Participation is of high relevance to the CHI Design community. Participatory work has been performed with very different intentions: to democratize the design process; to better inform the design of new systems; to engage the public in the construction of their own futures; or simply to appease funding commitments. Whilst this increased attention has lead to a large amount of methodological innovation, very little effort has been spent reflecting on why various participatory approaches should, or should not be, used and how we can assess their impacts on the design process and products. This invited SIG will bring together invited experts who have explored participation to different degrees within their past work to provoke group and plenary audience discussion. The aim of this SIG is to provide an opportunity for discussion and reflection on how and why participative methods are used in HCI research and practice.
Scan test of die logic in 3D ICs using TSV probing

Pre-bond testing of TSVs and die logic is a significant challenge and a potential roadblock for 3D integration. BIST solutions introduce considerable die area overhead. Oversized probe pads on TSVs to provide pre-bond test access limit both test bandwidth and TSV density. This paper presents a solution to these problems, allowing a probe card to contact TSVs without the need for probe pads, enabling both TSV and pre-bond scan test. Two possible pre-bond scan test configurations are shown - they provide varying degrees of test parallelism. HSPICE simulations are performed on a logic-on-logic 3D benchmark. Results show that the ratio of the number of probe needles available for test access to the number of pre-bond scan chains determines which pre-bond scan configuration results in the shortest test time. Maximum pre-bond scan-in and scan-out shift-clock speeds are determined for dies in a benchmark 3D design. These clock speeds show that pre-bond scan test can be performed quickly, at a speed that is comparable to scan testing of packaged dies. The maximum clock speed can also be tuned by changing the drive strength of the probe and on-die drivers of the TSV network. Estimates are also provided for peak and average power consumption during pre-bond scan test. On-die area overhead for the proposed method is estimated to be between 1.0% and 2.2% for three dies in the 3D stack.
Shallow Discourse Parsing Using Distributed Argument Representations and Bayesian Optimization

This paper describes the Georgia Tech team's approach to the CoNLL-2016 supplementary evaluation on discourse relation sense classification. We use long short-term memories (LSTM) to induce distributed representations of each argument, and then combine these representations with surface features in a neural network. The architecture of the neural network is determined by Bayesian hyperparameter search.
High-Throughput Screening for N-Type Calcium Channel Blockers Using a Scintillation Proximity Assay

N-type calcium channels located on presynaptic nerve terminals regulate neurotransmitter release, including that from the spinal terminations of primary afferent nociceptors. Accordingly, N-type calcium channel blockers may have clinical utility as analgesic drugs. A selective N-type calcium channel inhibitor, ziconotide (Prialt), is a neuroactive peptide recently marketed as a novel nonopioid treatment for severe chronic pain. To develop a small-molecule N-type calcium channel blocker, the authors developed a 96-well plate high-throughput screening scintillation proximity assay (SPA) for N-type calcium channel blockers using [125I]-labeled ω-conotoxin GVIA as a channel-specific ligand. Assay reagents were handled using Caliper’s Allegro automation system, and bound ligands were detected using a PerkinElmer TopCount. Using this assay, more than 150,000 compounds were screened at 10 μM and approximately 340 compounds were identified as hits, exhibiting at least 40% inhibition of [125I]GVIA binding. This is the 1st demonstration of the use of [125I]-labeled peptides with SPA beads to provide a binding assay for the evaluation of ligand binding to calcium channels. This assay could be a useful tool for drug discovery.
Duality between foveatization and multiscale local spectrum estimation

In this work we demonstrate the relationship existing between two important issues in vision: multi-scale local spectrum analysis, and log-polar foveatization. We show that, when applying a continuous set of self-similar (rotated and scaled) band-pass filters to estimate the local spectrum at a given point of attention of the image, the inverse Fourier transform of this local spectrum is a log- polar foveated version of the original image at that position. Both the local spectrum and its associated foveated image can be obtained through log-polar warping of the spectral/spatial domain followed by a conventional invariant low-pass filtering and the corresponding inverse warping. Furthermore, the low-pass filters in the warped space and frequency domains are mirror versions of each other. Thus, filters with mirror symmetry under the log- polar warping are self-dual, and make the foveatization process commute with the Fourier transform. Nevertheless, in order to implement a fovea that can be easily moved across the image, it is preferable to use a fixed bank of steerable filters, instead of applying log-polar warpings with different centers. Using low-pass scalable filters we have implemented a real-time moving fovea. We believe that a dual finite spatial/spectral local representation of images could be a very powerful tool for many visual tasks, which could benefit from a dual explicit representation in space and spatial frequency, as well as from the rotation and scale invariance naturally achieved in both domains.
Iconicity correlated with vowel harmony in Korean ideophones

This paper aims to establish connections between the following phenomena pertaining to Korean ideophonic vowel harmony: A set of vowel patterns classified (phonologically) as ‘harmonic,’ ‘neutral,’ and ‘disharmonic’; a set of ideophones classified (semantically) as onomatopoeic vs. cross-modal; and a set of form-meaning mappings classified (semiotically) as higher vs. lower in iconicity. Onomatopoeic ideophones represent sounds in the external world by linguistic sounds. To do so effectively requires taking whatever phonological and phonotactic liberties are needed. This predicts that (a) onomatopoeic ideophones will show great diversity in harmony patterns and, in contrast, (b) cross-modal ideophones that capture sensory imagery by using more abstract iconic mappings (Dingemanse et al., 2016) will have more ‘room’ to conform to vowel harmony. To test these hypotheses, the distribution of harmony patterns in onomatopoeic vs. cross-modal ideophones was examined, using a written corpus of Korean ideophonic stems. The results supported the hypotheses by revealing that onomatopoeic ideophones are skewed toward a larger proportion of disharmonic forms compared to cross-modal ideophones.
The updated Vocabulary Levels Test

The Vocabulary Levels Test (Nation, 1983; Schmitt, Schmitt, & Clapham, 2001) indicates the word frequency level that should be used to select words for learning. The present study involves the development and validation of two new forms of the test. The new forms consist of five levels measuring knowledge of vocabulary at the 1000, 2000, 3000, 4000, and 5000 levels. Items for the tests were sourced from Nation’s (2012) BNC/COCA word lists. The research involved first identifying quality items using the data from 1,463 test takers to create two equivalent forms, and then evaluating the forms with the data from a further 250 test takers. This study also makes an initial attempt to validate the new forms using Messick’s (1989, 1995) validity framework.
Calculation of functions on the RF-channel for IoT

We consider the calculation of mathematical functions at the time of wireless superimposition of data sequences in IoT environments. IoT devices will be heavily resource limited, possibly parasitic or passive powered nodes. Although restricted in their computational capabilities, such nodes draw on a virtually unlimited power source. We exploit this property by trading computational load for communication load. In particular, we present a communication scheme by which mathematical computations can be executed at the time of wireless transmission. This transmission scheme enables the execution of complex computations by a network of resource restricted, cooperating nodes at a computational load below the operation's computational complexity. We derive the scheme analytically, explore its feasibility for dense networks in mathematical simulations and demonstrate its practicability in a case study with 15 nodes.
Fluorescent magnetic particle inspection device based on digital image processing

Fluorescent magnetic particle inspection is widely applied in industry production, however; traditional ways are manual and depend on individuals' experience, which can also cause damage to workers' eyes. An automatic fluorescent magnetic particle inspection device is presented in this paper. A series of image processing methods have been investigated, which are put into a combination for detecting flaws in images automatically. And we propose a wavelet-based Canny operator to extract outlines of flaws in images, which is more effective than common Canny operator, and could constrain noises at a reasonable level. Results suggest that this novel automatic inspection device offers a low labor intensity but more effective way for flaw detection work, and image processing methods proposed in this paper are feasible.
Secure Communication in Stochastic Wireless Networks—Part II: Maximum Rate and Collusion

In Part I of this paper, we introduced the intrinsically secure communications graph (iS-graph)-a random graph which describes the connections that can be established with strong secrecy over a large-scale network, in the presence of eavesdroppers. We focused on the local connectivity of the iS-graph, and proposed techniques to improve it. In this second part, we characterize the maximum secrecy rate (MSR) that can be achieved between a node and its neighbors. We then consider the scenario where the eavesdroppers are allowed to collude, i.e., exchange and combine information. We quantify exactly how eavesdropper collusion degrades the secrecy properties of the network, in comparison to a noncolluding scenario. Our analysis helps clarify how the presence of eavesdroppers can jeopardize the success of wireless physical-layer security.
Being different, teaching difference : challenges and possibilities for non-heterosexual men in elementary school teaching

This inquiry brought together the experiences of six male teachers working in NYC schools who identify as either gay, queer or bisexual. Drawing primarily on interviews, which addressed topics such as personal history, educational philosophy and classroom practices, I examined the contextual and cultural factors involved in being "out" as a queer, gay or bisexual teacher and the importance of teaching with an eye towards gender and sexual diversity (GSD). Focusing on the decision to be out, discussion and exploration of GSD in the classroom, and the hidden curriculum of gender performance, I was able to explore the complex and thorny issues surrounding this social justice mission. The purpose of this study was to obtain rich qualitative data to create a portrait of these teachers, each with unique backgrounds and opinions about the challenges or responsibilities of working with young children.
Applying Naive Bayes Classification to Google Play Apps Categorization

There are over one million apps on Google Play Store and over half a million publishers. Having such a huge number of apps and developers can pose a challenge to app users and new publishers on the store. Discovering apps can be challenging if apps are not correctly published in the right category, and, in turn, reduce earnings for app developers. Additionally, with over 41 categories on Google Play Store, deciding on the right category to publish an app can be challenging for developers due to the number of categories they have to choose from. Machine Learning has been very useful, especially in classification problems such sentiment analysis, document classification and spam detection. These strategies can also be applied to app categorization on Google Play Store to suggest appropriate categories for app publishers using details from their application. In this project, we built two variations of the Naive Bayes classifier using open metadata from top developer apps on Google Play Store in other to classify new apps on the store. These classifiers are then evaluated using various evaluation methods and their results compared against each other. The results show that the Naive Bayes algorithm performs well for our classification problem and can potentially automate app categorization for Android app publishers on Google Play Store