Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Comparative In Silico Analysis of the RNA Helicase Gene Family in Zea mays and Glycine max: A Comparison with Arabidopsis and Oryza sativa

RNA helicases are enzymes that are thought to unwind double-stranded RNA molecules in an energy-dependent fashion through the hydrolysis of NTP. RNA helicases are associated with all processes involving RNA molecules, including nuclear transcription, editing, splicing, ribosome biogenesis, RNA export, and organelle gene expression. The involvement of RNA helicase in response to stress and in plant growth and development has been reported previously. While their importance in Arabidopsis and Oryza sativa has been partially studied, the function of RNA helicase proteins is poorly understood in Zea mays and Glycine max. In this study, we identified a total of RNA helicase genes in Arabidopsis and other crop species genome by genome-wide comparative in silico analysis. We classified the RNA helicase genes into three subfamilies according to the structural features of the motif II region, such as DEAD-box, DEAH-box and DExD/H-box, and different species showed different patterns of alternative splicing. Secondly, chromosome location analysis showed that the RNA helicase protein genes were distributed across all chromosomes with different densities in the four species. Thirdly, phylogenetic tree analyses identified the relevant homologs of DEAD-box, DEAH-box and DExD/H-box RNA helicase proteins in each of the four species. Fourthly, microarray expression data showed that many of these predicted RNA helicase genes were expressed in different developmental stages and different tissues under normal growth conditions. Finally, real-time quantitative PCR analysis showed that the expression levels of 10 genes in Arabidopsis and 13 genes in Zea mays were in close agreement with the microarray expression data. To our knowledge, this is the first report of a comparative genome-wide analysis of the RNA helicase gene family in Arabidopsis, Oryza sativa, Zea mays and Glycine max. This study provides valuable information for understanding the classification and putative functions of the RNA helicase gene family in crop growth and development.
Early Land Plants Today (ELPT): How many liverwort species are there?

Estimates of extant liverwort species range from 4,500 to 9,000, with estimates in the past decade converging on 5,000 to 6,000. Potential problems and pitfalls of deriving species estimates are addressed, including binomial accumulation, the impact of synonymy, taxonomic inflation, the impact of unrevised species-rich genera, species concepts and cryptic species. We present a revised mean estimate of 7,500 for the number of liverwort species based on estimating rates of synonymy in a sample of recently monographed and revised taxa. This estimate does not include infraspecific names and may underestimate global diversity as a result. We also present a databased estimate of about 8,500 species derived from the Early Land Plants Today data set. We argue higher estimates are supported by: 1) the number of published species has not reached a plateau and new species continue to be discovered; 2) not all regions have been thoroughly explored and with equal intensity, with survey effort being historically biased toward northern temperate regions; 3) synonymy rates are not uniform across taxonomic groups; 4) novel discovery of species outpaces new species derived from elevation in rank (taxonomic inflation); and 5) species numbers are not necessarily distorted by large unrevised genera. A standardized global worldwide liverwort checklist with strong community participation coupled with the critical need for ongoing monographs and revisions, will aid in arriving at a clearer estimates of liverwort diversity. We promote and encourage interest in the topic using an evidence-based approach and quantitative data.
Public watermarks and resistance to tampering

Public watermarks allow embedded signals to be extracted from audio and video content for a variety of purposes. One application is for copyright control, where it is envisaged that digital video recorders will not permit the recording of content that is watermarked as "never copy". In such a scenario, it is important that the watermark survive both normal signal transformations and attempts to remove the watermark so that an illegal copy can be made. In this paper, we discuss to what extent a public watermark can be resistant to tampering and describe a variety of possible
Happy feelings: examining music in the service environment

Purpose The purpose of this paper is to examine the psychological influence that the presence of music has on consumers’ evaluations of the service environment. Specifically, it investigates how emotion regulation processes and the impact of emotions/mood are linked to consumers’ evaluation of service and product quality. Design/methodology/approach An exploratory study was conducted using industry professionals in order to garner insight about the value of music and its benefits in the service environment. A field experiment was then conducted to test hypotheses. Findings Industry professionals offer implicit theories about the value of music. Specifically, they propose that music can be used to help customers regulate emotions and improve mood, enhance the customer experience and help in attracting new consumer segments. Results from the field experiment found that those exposed to music were likely to improve mood, express more favorable evaluations of the service and product quality of the establishment, as well as exhibit stronger intentions to continue to patronize the establishment. Practical implications Using live music in the service environment can be beneficial to organizations by improving customers’ emotional/psychological status as well as their evaluation of the consumption experience. Originality/value This research contributes to the existing literature by demonstrating how emotion regulation processes and the impact of emotions/mood are linked to consumers’ evaluation of service and product quality. Also, support for mood congruency judgment is found. Participants in the field study who had been exposed to music indicated that they made efforts to improve their mood and subsequently had more favorable judgments of service and product quality.
Are Chinese Technologies A Mode Of Entry For Firms In Developing Countries? The Case of Furniture Manufacturing in Kenya

Kenya has started to rely significantly on technologies developed in developing countries particularly China rather than those from advanced countries such as the United Kingdom, Germany and Japan. Using data from furniture manufacturing firms in Kenya, the paper compares the investment cost and the scale characteristics of the technologies (machines and equipment) from China with those from advanced countries and Kenya. By examining the characteristics of the firms that have invested in technologies from various sources, the paper concludes that the technologies from China and Kenya have lessened entry barrier (specifically high capital cost) for new firms, compared to advanced country technologies. Chinese technology appears to serve as an entry mode more than the Kenyan technology. In terms of barriers to entry, therefore Chinese and Kenyan technologies appear to be more appropriate for Kenya (and more generally developing countries) than advanced country technology
On the Newly Discovered Canes Venatici II dSph Galaxy

We report on the detection of variable stars in the Canes Venatici II (CVn II) dwarf spheroidal galaxy, a new satellite of the Milky Way recently discovered by the Sloan Digital Sky Survey. We also present a V, B − V color-magnitude diagram that reaches V ∼ 25.5 mag, showing the galaxy’s main-sequence turnoff at V ∼ 24.5 mag and revealing several candidate blue straggler stars. Two RR Lyrae stars have been identified within the half-light radius of CVn II, a fundamental-mode variable (RRab) with period Pab = 0.743 days, and a first-overtone (RRc) RR Lyrae star with Pc = 0.358 days. The rather long periods of these variables along with their position on the period-amplitude diagram support an Oosterhoff type II classification for CVn II. The average apparent magnitude of the RR Lyrae stars, ⟨ V⟩ = 21.48 ± 0.02 mag, is used to obtain a precision distance modulus of μ0 = 21.02 ± 0.06 mag and a corresponding distance of 160+ 4−5 kpc, for an adopted reddening E(B − V) = 0.015 mag.
Spectral Angle Sensitive Forest: A solution for fast hyperspectral matching

This paper proposed a type of data structure, Spectral Angle Sensitive Forest (SASF), which was designed for indexing and matching Hyperspectral data with spectral angle metric at low computational cost. In this paper, we theoretically and experimentally proved that this new method outperformed the traditional data structure (such as Vantage Point Tree) used for high dimensional dataset, and overcome the problem of Locality Sensitive Hashing algorithm that the query data could not get matching results in certain probability. By adjusting a few parameters, SASF is convenient for users to choose between matching speed and matching accuracy in the applications.
Motivating Students To Access Support Services In Higher Education: A Self-Determination Theory Perspective

Helping students with their academic and personal problems is a priority for higher education institutions. However, students may not seek support for the challenges they face. Self-determination theory frames this resistance to access services in terms of motivation. Students who are experiencing problems are not motivated to address them because they feel incapable, incompetent and isolated. In response to this, self-determination theory would advocate a support service that offers choice, skill-based problem solving and a collaborative approach. This forms the basis of a proposed comparative study to explore whether these aspects of motivation correlate with engagement in student support services at the University of Lincoln. Qualitative and quantitative data will be gathered from undergraduate students, in various disciplines, to explore the barriers to support engagement. The study is planned to run from September 2018 to June 2019.
An Efficient Bit-Parallel Multi-Patterns Word Searching Algorithm through Splitting the Text

Word matching problem is to find all the occurrences of a pattern P[0…m-1] in the text T[0…n-1], where P neither contains any white space nor preceded and followed by space. In the multi-patterns word matching problem, all the occurrences of multiple word P0, P1, P2 …Pr-1, (r≥1) in the given text T are to be reported. In the present discussion, we assume that all the patterns have equal size m and our text T is offline. We further assume that m ≤ w, where w is the word length of computer used. Ibrahiem et al. in 2008 have proposed an algorithm (WSA) for solving the word matching problem for single pattern by splitting the offline text into number of tables in the preprocessing phase. The main drawback of this algorithm was: after splitting the text into a number of tables, they search each occurrence of the pattern by the brute force manner in each table. In this paper, we extend this algorithm for multi-patterns word matching by using the technique of bit-parallel proposed by Baeza Yates, 1992. In this technique, after splitting the text into number of tables, we apply the shift-or algorithm to find the words of same length in the text T. The set of r multiple patterns is being handled by using the concept of classes of characters. This extended algorithm is called as multi-patterns word searching algorithm (MPWSA). Experimental results show that MPWSA algorithm is much faster than the previously proposed WSA algorithm.
HyperMAMBO-X64: Using Virtualization to Support High-Performance Transparent Binary Translation

Current computer architectures --- ARM, MIPS, PowerPC, SPARC, x86 --- have evolved from a 32-bit architecture to a 64-bit one. Computer architects often consider whether it could be possible to eliminate hardware support for a subset of the instruction set as to reduce hardware complexity, which could improve performance, reduce power usage and accelerate processor development. This paper considers the scenario where we want to eliminate 32-bit hardware support from the ARMv8 architecture. Dynamic binary translation can be used for this purpose and generally comes in one of two forms: application-level translators that translate a single user mode process on top of a native operating system, and system-level translators that translate an entire operating system and all its processes. Application-level translators can have good performance but is not totally transparent; system-level translators may be 100% compatible but performance suffers. HyperMAMBO-X64 uses a new approach that gets the best of both worlds, being able to run the translator as an application under the hypervisor but still react to the behavior of guest operating systems. It works with complete transparency with regards to the virtualized system whilst delivering performance close to that provided by hardware execution. A key factor in the low overhead of HyperMAMBO-X64 is its deep integration with the virtualization and memory management features of ARMv8. These are exploited to support caching of translations across multiple address spaces while ensuring that translated code remains consistent with the source instructions it is based on. We show how these attributes are achieved without sacrificing either performance or accuracy.
Antenna selection: A novel approach to improve energy efficiency in massive MIMO systems

Due to take advantage of large number of antennas, massive MIMO systems are able to serve high data rates. On the other hand, using more antennas will rise the hardware power consumption and therefore total power consumption. So, a trade-off between data rate and power consumption is made which can be reflected well in Energy-Efficiency parameter. Considering hardware power consumption results to more realistic model. In this paper, a model for Energy-Efficiency by taking hardware power consumption into account is introduced and then, an antenna selection algorithm is presented to improve Energy-Efficiency. As dimensions of system is high, this algorithm is designed simple. Next, different selection scenario will be investigated and at the end an optimization for a special case will be represented. Our simulations results show significant improvement in Energy-Efficiency for antenna selection case using proposed method.
Routing decisions with recycle and handling reliability options in distribution network using genetic algorithm

Routing decision is an essential element to the efficiency of a distribution network as its configuration determines the flow of different products via various transition points. Traditionally, factors, such as cost and distance, will usually be considered. However, different handling reliability and the ability of recycling wastes, packaging materials for example, in some transition points could affect the performance of the network. The objective of this paper is to propose a genetic algorithm to determine the flow and route of products in a distribution network. It simultaneously considers various factors such as cost, distance, the handling reliability, and recycling ability in different transition point. A numerical example is presented to illustrate the conflicts between the different factors to the performance of the distribution network under study, and thus how the proposed algorithm can handle the trade-off in such a multi-criterion decision making problem.
Time-based localization for asynchronous wireless sensor networks

In this paper, we propose time-based localization approaches for asynchronous wireless sensor networks (WSNs), where not only clock skews but also clock offsets are present at all nodes. We first propose a joint synchronization and localization approach using the two-way ranging (TWR) protocol. Furthermore, a novel ranging protocol, namely asymmetric trip ranging (ATR), is employed and a two-step joint synchronization and localization approach is developed. As a result, we achieve efficient closed-form least-squares (LS) estimators. We compare these two proposed approaches. Moreover, simulation results corroborate the efficiency of our time-based localization schemes.
Combining Graph and Machine Learning Methods to Analyze Differences in Functional Connectivity Across Sex

In this work we combine machine learning methods and graph theoretical analysis to investigate gender associated differences in resting state brain network connectivity. The set of all correlations computed from the fMRI resting state data is used as input features for classification. Two ensemble learning methods are used to perform the detection of the set of discriminative edges between groups (males vs. females) of brain networks: 1) Random Forest and 2) an ensemble method based on least angle shrinkage and selection operator (lasso) regressors. Permutation testing is used not only to assess significance of classification accuracy but also to evaluate significance of feature selection. Finally, these methods are applied to data downloaded from the Connectome Project website. Our results suggest that gender differences in brain function may be related to sexually dimorphic regional connectivity between specific critical nodes via gender-discriminative edges.
Simplified representation for 3D point cloud data

3D data representation becomes more popular, but the enormous points make the model reconstruction and the object recognition difficult. A simplification algorithm for 3D point cloud data integrating both the feature parameter and uniform spherical sampling is presented. At first, we define a feature parameter which includes the average distance parameter and the normal included angle parameter between the point and its neighboring points and point curvature parameter. Then we calculate the density of 3D point cloud data and define it as the feature threshold. We distinguish the feature from the non-feature points by comparing the feature parameter and the threshold. Then we simplify the non-feature points by uniform spherical sampling. The non-feature sampling result and the feature points will be used as the final simplification result. The experimental results demonstrate that our new approach might retain the sharp information of the 3D point cloud data.
Numerical methods for Stackelberg-Nash equilibrium calculation with favorable and unfavorable followers

Regularized versions of the rdquoProjectional Gradient Techniquerdquo and the ldquoExtraproximal Methodrdquo are suggested to be applied for finding Stackelberg-Nash equilibrium in a multi-participant static game. A comparative between these methods is shown. There exist two levels of hierarchy in decision making: the first one consists of a leader decision and the second one is formed by the decisions of (N - 1)-followers. The followers react to the leaderpsilas announced strategy by playing according to the Nash equilibrium concept among themselves selecting those of equilibriums which is most favorable or unfavorable for the leader. The convergence of the suggested procedure is analyzed. Simulation results illustrate the feasibility of this method.
A Lightweight Encryption and Secure Protocol for Smartphone Cloud

User data on mobile devices are always transferred into Cloud for flexible and location-independent access to services and resources. The issues of data security and privacy data have been often reverted to contractual partners and trusted third parties. As a matter of fact, to project data, data encryption and user authentication are fundamental requirements between the mobile devices and the Cloud before a data transfer. However, due to limited resources of the smartphones and the unawareness of security from users, data encryption has been the last priority in mobile devices, and the authentication between two entities always depends on a trusted third party. In this paper, we propose a lightweight encryption algorithm and a security handshaking protocol for use specifically between in mobile devices and in Cloud, with the intent of securing data on the user side before it is migrated to cloud storages. The proposed cryptographic scheme and security protocol make use of unique device specific identifiers and user supplied credentials. It aims to achieve a usersoriented approach for Smartphone Cloud. Through experiments, we demonstrated that the proposed cryptographic scheme requires less power consumption on mobile devices.
Adenocarcinoma Model Cancer Cell Motility-inhibitory Protein in the Dunning Updated Version

Cell HUMÂ¡lii\ has been associated with metastatic ability in the Dunning R3327 rat prostatic adenocarcinoma model. Cancer cell motility pro moters but not inhibitors have been described by many investigators. Serum-containing and serum-free media conditioned by the nonmotile, nonmetastatic G Dunning subline inhibited the motility of the highlymotile, highly metastatic MAT-LyLu subline. Motility inhibition by the G subline-conditioned serum-free media was lost upon heating to I()()"< and by treatment with trypsin. The motility inhibitory protein(s) had a molecular weight exceeding 50,000 as determined by diafiltration. G subline-conditioned RPMI 1640 contained several proteins with molec ular weights of between approximately 53,000 and 116,000 when ana lyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. One of these bands may represent the first inhibitor of cancer cell motility identified.
AN EVOLUTIONARY ALGORITHM FOR LINEAR SYSTEMS IDENTIFICATION EDMARY ALTAMIRANDA

This paper presents a systems identification method, for discrete time linear systems, based on an evolutionary approach, which allows achieving the selection of a suitable structure and the parameters estimation, using non conventional objective functions. This algorithm incorporates parametric crossover and parametric mutation along a weighted gradient direction [1]. The performance of the proposed method is illustrated with computer simulations using ARX model structures, where parameters, model dynamical order and input-output delay values are estimated. Key-Words: System identification, Discrete time systems, Regression models, Evolutionary computation.