Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Outsourced Proofs of Retrievability Enabling Auditing Migration for Remote Storage Security

Remote data auditing service is important for mobile clients to guarantee the intactness of their outsourced data stored at cloud side. To relieve mobile client from the nonnegligible burden incurred by performing the frequent data auditing, more and more literatures propose that the execution of such data auditing should be migrated from mobile client to third-party auditor (TPA). However, existing public auditing schemes always assume that TPA is reliable, which is the potential risk for outsourced data security. Although Outsourced Proofs of Retrievability (OPOR) have been proposed to further protect against the malicious TPA and collusion among any two entities, the original OPOR scheme applies only to the static data, which is the limitation that should be solved for enabling data dynamics. In this paper, we design a novel authenticated data structure called bv23Tree, which enables client to batch-verify the indices and values of any number of appointed leaves all at once for efficiency. By utilizing bv23Tree and a hierarchical storage structure, we present the first solution for Dynamic OPOR (DOPOR), which extends the OPOR model to support dynamic updates of the outsourced data. Extensive security and performance analyses show the reliability and effectiveness of our proposed scheme.
Domestication of Smartphones Among Adolescents in Brunei Darussalam

This article describes how smartphones have converged into multifunctional personal devices. Smartphones are equipped with features such as Internet access, cameras (pictures and videos) and MP3 players. While a majority of previous research investigated the use and effects of mobile phones and young people, these studies focused on the Western context. A qualitative research method was used to investigate the research questions. Specifically, focus groups and in-depth interviews were used to collect data. Nevertheless, while a growing number of studies has investigated mobile phone use by teenagers in non-western countries, there is little research on smartphone uses and their implications to teenagers in an Islamic context. This article examines the uses of smartphones by, and their implications to, Bruneian teenagers. The research seeks to map and understand the complex forces that influence and challenge the socio-cultural values and religious beliefs of teenagers in a non-Western, Malay, Islamic society such as Brunei.
A Novel Mach-Zehnder Interferometer Using Eccentric-Core Fiber Design for Optical Coherence Tomography

A novel Mach-Zehnder interferometer using eccentric-core fiber (ECF) design for optical coherence tomography (OCT) is proposed and demonstrated. Instead of the commercial single-mode fiber (SMF), the ECF is used as one interference arm of the implementation. Because of the offset location of the eccentric core, it is sensitive to directional bending and the optical path difference (OPD) of two interference arms can be adjusted with high precision. The birefringence of ECF is calculated and experimentally measured, which demonstrates the polarization sensitivity of the ECF proposed in the paper is similar to that of SMF. Such a structure can replace the reference optical delay line to form an all-fiber passive device. A mirror is used as a sample for analyzing the ECF bending responses of the system. Besides, four pieces of overlapping glass slides as sample are experimentally measured as well.
A Low Storage Room Requirement Framework for Distributed Ledger in Blockchain

Traditional centralized commerce on the Internet relies on trusted third parties to process electronic payments. It suffers from the weakness of the trust-based model. A pure decentralized mechanism called blockchain tackles the above problem and has become a hot research area. However, since each node in a blockchain system needs to store all transactions of the other nodes, as time continues, the storage room required to store the entire blockchain will be huge. Therefore, the current storage mechanism needs to be revised to cater to the rapidly increasing need for storage. Network coded (NC) distributed storage (DS) can significantly reduce the required storage room. This paper proposes a NC-DS framework to store the blockchain and proposes corresponding solutions to apply the NC-DS to the blockchain systems. Analysis shows that the proposed scheme achieves significant improvement in saving storage room.
Judicial Deference and Executive Control Over Administrative Agencies

Do judges defer to executives with increased institutional control over the executive branch? Administrative agencies play a key role in the policy implementation process. Executives could view aggressive judicial review of executive branch activity as a threat to executive power and negatively respond to perceived judicial intrusions. Governors across the country possess varying amounts of institutional authority over the agencies that comprise their states’ executive branches. For example, in many states, executive branch officials are elected by the public or appointed by someone other than the governor. Increased fragmentation increases the difficulty of centralized management and decreases gubernatorial influence over the executive branch. I examine whether state supreme courts defer more to agencies in states where governors have more formal control over the executive branch. I find that state supreme courts are more likely to rule in favor of state administrative agencies in states where the governor has increased appointment power and increased power to review agency rulemaking.
Melatonin-stimulated biosynthesis of anti-microbial ZnONPs by enhancing bio-reductive prospective in callus cultures of Catharanthus roseus var. Alba

Abstract Melatonin as plant growth regulator induces differential effects on metabolites that are responsible for reduction, capping and stabilization of zinc oxide nanoparticles. Phytochemical analysis of callus cultures was performed and results were compared with callus cultures supplemented with other plant growth regulators (α-napthalene acetic acid, 2,4-dichlorophenoxy acetic acid and thidiazuron). Highest total phenolic and flavonoid content [42.23 mg of gallic acid equivalent (GAE) g−1 DW and 36.4 mg of (quercetin equivalent) g−1 DW, respectively] were recorded at melatonin (1.0 µM) + NAA (13.5 µM). ZnONPs were synthesized from NAA (13.5 µM) and melatonin (1.0 µM) + NAA (13.5 µM)-induced calli extracts separately and characterized via X-ray diffraction, Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). FTIR analysis confirmed the presence of phenolics and flavonoids that were mainly found responsible for reduction and capping of ZnONPs. SEM analysis showed triangular shaped ZnONPs synthesized from melatonin + NAA callus extract and these NPs were more dispersed as compared to the spherical-agglomerates of ZnONPs synthesized from NAA-mediated callus extract. Melatonin + NAA callus extract-mediated ZnONPs (having smaller size) were more potent against multiple drug resistant bacterial strains, e.g. Bacillus subtilis, Escherichia coli and Pseudomonas aeruginosa by producing zone of inhibitions 17 ± 0.76 mm,10 ± 0.57 mm and 13 ± 0.54 mm, respectively.
A Note on Kumaraswamy Exponentiated Rayleigh distribution

In this paper, a new four parameter continuous distribution, called the Kumaraswamy Rayleigh (KW-ER) distribution is proposed and studied. Some mathematical properties are presented and discussed, these properties involve expansions for the cumulative and density functions, skewness and kurtosis based on the quantile function and explicit expressions for the moments and generating function. The density function of the order statistics and obtain their moments are provided. An explicit expression for Renyi entropy is obtained. The method of maximum likelihood is used for estimating the distribution parameters and the observed information matrix is derived. A data set is used to illustrate the application of the new distribution.
Minimal length scales for the existence of local temperature

We review a recent approach to determine the minimal spatial length scales on which local temperature exists. After mentioning an experiment where such considerations are of relevance, we first discuss the precise definition of the existence of local temperature and its physical relevance. The approach to calculate the length scales in question considers homogenous chains of particles with nearest-neighbour interactions. The entire chain is assumed to be in a thermal equilibrium state and it is analysed when such an equilibrium state at the same time exists for a local part of it. The result yields estimates for real materials, the liability of which is discussed in the sequel. We finally consider a possibility to detect the existence or non-existence of a local thermal state in experiment.
Cognitive status and incident disability in older Mexican Americans: findings from the Hispanic established population for the epidemiological study of the elderly.

OBJECTIVE To determine the effects of baseline cognitive function on incidence of disability in activities of daily living (ADL) in initially non-disabled Mexican-American elderly over a 7-year period. DESIGN A prospective cohort study. SETTING Southwestern United States: Texas, California, Arizona, New Mexico, and Colorado. PARTICIPANTS A population-based sample of Mexican Americans aged 65 and over who completed the Mini-Mental State Examination (MMSE) and other relevant variables at baseline. The sample at baseline consisted of 2731 subjects, of which 2431 were non-ADL disabled. MEASUREMENTS In-home interviews in 1993-94, 1995-96, 1998-99, and 2000-2001 assessed sociodemographic variables, selected medical conditions (stroke, cancer, diabetes, arthritis, and hip fracture), cognitive function, depressive symptomatology, and ADLs. RESULTS In a Cox proportional regression analysis, a significant relationship was evident between MMSE score at baseline and risk of incident ADL disability over a 7-year period. Among non-disabled subjects at baseline, the hazard ratio of any new ADL limitation was 1.58 (95% CI, 1.18-2.12) for those with impaired cognition (MMSE score 0-21), 1.38 (95% CI, 1.04-1.82) for low normal cognition (MMSE score 22-24), and 1.30 (95% CI, 1.02-1.66) for normal cognition (MMSE score 25-28) when compared to subjects with high-normal cognition (MMSE score 29-30), adjusting for sociodemographic variables, presence of selected medical conditions and depressive symptoms at baseline. Similar results were also found when MMSE score was used as a continuous variable. Among non-disabled subjects at baseline, each unit increase in MMSE score decreased the risk of onset of any ADL limitation over a 7-year follow-up period, controlling for relevant variables at baseline (HR=0.97; 95% CI, 0.95-0.99). CONCLUSION Low MMSE score was associated with increased risk for incident ADL disability over a 7-year period in older Mexican Americans. Given the social, economic, and health impact of cognitive impairment, these findings suggest a need to develop effective intervention programs that delay or prevent the onset of cognitive and ADL disability in the elderly.
A Neural Network Model for Part-Of-Speech Tagging of Social Media Texts

In this paper, we propose a neural network model for Part-Of-Speech (POS) tagging of User-Generated Content (UGC) such as Twitter, Facebook and Web forums. The proposed model is end-to-end and uses both character and word level representations. Character level representations are learned during the training of the model through a Convolutional Neural Network (CNN). For word level representations, we combine several pre-trainned embeddings (Word2Vec, FastText and GloVe). To deal with the issue of the poor availability of annotated social media data, we have implemented a Transfer Learning (TL) approach. We demonstrate the validity and genericity of our model on a POS tagging task by conducting our experiments on ﬁve social media languages (English, German, French, Italian and Spanish).
Semantic Relatedness of Wikipedia Concepts – Benchmark Data and a Working Solution

Wikipedia is a very popular source of encyclopedic knowledge which provides highly reliable articles in a variety of domains. This richness and popularity created a strong motivation among NLP researchers to develop relatedness measures between Wikipedia concepts. In this paper, we introduce WORD (Wikipedia Oriented Relatedness Dataset), a new type of concept relatedness dataset, composed of 19,276 pairs of Wikipedia concepts. This is the ﬁrst human annotated dataset of Wikipedia concepts, whose purpose is twofold. On the one hand, it can serve as a benchmark for evaluating concept-relatedness methods. On the other hand, it can be used as supervised data for developing new models for concept relatedness prediction. Among the advantages of this dataset compared to its term-relatedness counterparts, are its built-in disambiguation solution, and its richness with meaningful multi-word terms. Based on this benchmark we develop a new tool, named WORT (Wikipedia Oriented Relatedness Tool), for measuring the level of relatedness between pairs of concepts. We show that the relatedness predictions of WORT outperform state of the art methods.
Optimal ℓ2-ℓ∞ filtering for Markovian jump repeated scalar nonlinear systems

This work studies the optimal ℓ<sub>2</sub>-ℓ<sub>∞</sub> filter design problem for discrete-time Markovian jump repeated scalar nonlinear systems. The design focus is full- and reduced-order filters which guarantee the filtering error system to be stochastically stable with a prescribed weighted ℓ<sub>2</sub>-ℓ<sub>∞</sub> performance. Firstly, both the mode dependent Lyapunov function approach and the positive definite diagonally dominant Lyapunov function technique are employed to establish a sufficient condition that guarantees the Markovian jump repeated scalar nonlinear system to be stochastically stable with an induced ℓ<sub>2</sub>-ℓ<sub>∞</sub> disturbance attenuation performance. Secondly, the corresponding full-order filter design is transformed into a convex optimization problem, which can be efficiently handled using standard numerical algorithms. Finally, a numerical example is presented to show the effectiveness of the proposed design.
Electrical Characterization of the Self-Heating Effect in Oxide Semiconductor Thin-Film Transistors Using Pulse-Based Measurements

The self-heating effect (SHE) in top-gate In–Ga–Zn–O (IGZO) thin-film transistors (TFTs) was examined systematically using short electrical pulse measurement methods. The temperature dependence of the pulse measurements of IGZO TFTs revealed a significant increase in temperature during the measurements, suggesting that conventional measurements can overestimate the device performance significantly. The effective temperature was introduced and extracted for IGZO TFTs at various heating powers and ambient temperatures. The short sampling time was determined to be a key in characterizing the intrinsic device properties that are not influenced by the SHE. The cooling behavior after self-heating was also examined using multipulse measurements. Because heating and cooling are significant even in a very short time, it is essential to consider the operation condition of the devices when characterizing TFTs to estimate the precise performance and reliability in a real operation.
Backup Anomaly Identification with R and Hadoop

In recent years “big data” has become something of a buzzword in business, computer science, information studies, information systems, statistics, and many other fields. As technology continues to advance, we constantly generate an ever-increasing amount of data. This growth does not differentiate between individuals and businesses, private or public sectors, institutions of learning and commercial entities. It is nigh universal and therefore warrants further study. Increasingly larger scale applications are generating an unprecedented amount of data. In order to exploit data mining techniques on collected backup job metadata, we integrate a big data analytics platform with the existing enterprise backup architecture. We build a scalable data mining platform to store, process, and perform advanced data mining techniques on the overall data set. We leverage open source tools to reduce the overall cost while preserving flexibility.
Wideband circular polarizer based on twisted double-layer spiral planar structure

A wideband circular polarizer constructed by using 2×2 array metallic planar spiral structure is proposed. The top and bottom spiral structures are patterned with certain twisted angles with respect to each other along xoy directions. A new class of structure is presented that transmit the incident linearly polarized wave into a circularly polarized wave at microwave frequencies. The impinged wave is converted into a right-handed circularly polarized (RHCP) wave from 14.42 GHz–16.12 GHz. The accumulative axial ratio of Txx, Txy 10% is obtained for circular polarization. Results show that proposed structure possesses substantially good performances, in terms of transmission efficiency and axial ratio bandwidth. The simulated surface current distributions illustrate transformation behavior for linear and circular polarizations. The proposed structure could be useful to design optical devices and polarization control devices.
Analyzing the Performance of Supply Chain using Topsis

The paper seeks to evaluate various attributes of Supply chain by means of some facts and figures and with the help of AHP and Topsis finally the performance index are calculated which provides a better picture of the various parameters their effect on the supply chain mathematically. Thus it provides a benchmark for a process and the managers to evaluate the performance and thus the efficacy with which it is performing by evaluating the effectiveness of the supply chain with the help of various parameters which are associated while performance is measured. A proper amalgamation of diverse factors such as financial, non-financial factors was taken into consideration by surveying including diverse variety of resources so available.
Auto-hMDS: Automatic Construction of a Large Heterogeneous Multilingual Multi-Document Summarization Corpus

Automatic text summarization is a challenging natural language processing (NLP) task which has been researched for several decades. The available datasets for multi-document summarization (MDS) are, however, rather small and usually focused on the newswire genre. Nowadays, machine learning methods are applied to more and more NLP problems such as machine translation, question answering, and single-document summarization. Modern machine learning methods such as neural networks require large training datasets which are available for the three tasks but not yet for MDS. This lack of training data limits the development of machine learning methods for MDS. In this work, we automatically generate a large heterogeneous multilingual multi-document summarization corpus. The key idea is to use Wikipedia articles as summaries and to automatically search for appropriate source documents. We created a corpus with 7,316 topics in English and German, which has variing summary lengths and variing number of source documents. More information about the corpus can be found at the corpus GitHub page at https://github.com/AIPHES/auto-hMDS .
Frequent Implication of Multistress-Tolerant Campylobacter jejuni in Human Infections

Campylobacter jejuni, a major cause of bacterial foodborne illnesses, is considered highly susceptible to environmental stresses. In this study, we extensively investigated the stress tolerance of 121 clinical strains of C. jejuni against 5 stress conditions (aerobic stress, disinfectant exposure, freeze-thaw, heat treatment, and osmotic stress) that this pathogenic bacterium might encounter during foodborne transmission to humans. In contrast to our current perception about high stress sensitivity of C. jejuni, a number of clinical strains of C. jejuni were highly tolerant to multiple stresses. We performed population genetics analysis by using comparative genomic fingerprinting and showed that multistress-tolerant strains of C. jejuni constituted distinct clades. The comparative genomic fingerprinting subtypes belonging to multistress-tolerant clades were more frequently implicated in human infections than those in stress-sensitive clades. We identified unique stress-tolerant C. jejuni clones and showed the role of stress tolerance in human campylobacteriosis.
Two unconditionally implied parameters and volatility smiles and skews

The study examines estimation of parameters of diffusion market models from historical data. The standard definition of implied volatility for these models presents its value as an implicit function of several parameters, including the risk-free interest rate. In reality, the risk free interest rate is unknown and needs to be forecasted, because the option price depends on its future curve. Therefore, the standard implied volatility is conditional: it depends on the future values of the risk free rate. Two implied parameters are studied: the implied volatility and the implied average cumulative risk free interest rate. They can be found unconditionally from a system of two equations. It was found that very simple models with random volatilities (for instance, with two point distributions) generate various volatility smiles and skews with this approach.
A Discrete-Event Object-Oriented Modeling Environment For Sawmill Simulation

The paper presents a simulation modeling environment developed for sawmill design and analysis in the forest products industry. The design facilitates flexibility in modeling different sawmill configurations and production scenarios. The system represents a library of objects developed in an object-oriented framework. These include structures required to develop simulation models, to execute discrete event simulation, and for system-user interface.
Biochemical characterization of purified mammalian ARL13B protein indicates that it is an atypical GTPase and ARL3 guanine nucleotide exchange factor (GEF)

Primary cilia play central roles in signaling during metazoan development. Several key regulators of ciliogenesis and ciliary signaling are mutated in humans, resulting in a number of ciliopathies, including Joubert syndrome (JS). ARL13B is a ciliary GTPase with at least three missense mutations identified in JS patients. ARL13B is a member of the ADP ribosylation factor family of regulatory GTPases, but is atypical in having a non-homologous, C-terminal domain of ∼20 kDa and at least one key residue difference in the consensus GTP-binding motifs. For these reasons, and to establish a solid biochemical basis on which to begin to model its actions in cells and animals, we developed preparations of purified, recombinant, murine Arl13b protein. We report results from assays for solution-based nucleotide binding, intrinsic and GTPase-activating protein-stimulated GTPase, and ARL3 guanine nucleotide exchange factor activities. Biochemical analyses of three human missense mutations found in JS and of two consensus GTPase motifs reinforce the atypical properties of this regulatory GTPase. We also discovered that murine Arl13b is a substrate for casein kinase 2, a contaminant in our preparation from human embryonic kidney cells. This activity, and the ability of casein kinase 2 to use GTP as a phosphate donor, may be a source of differences between our data and previously published results. These results provide a solid framework for further research into ARL13B on which to develop models for the actions of this clinically important cell regulator.