Miracle-dz/UniFAR-FTUs huggingface dataset:
Are global hotspots of endemic richness shaped by plate tectonics?

Singular regions of the globe harbour a disproportionally large fraction of extant biodiversity. Spatial biodiversity gradients are frequently associated to extant ecological conditions using statistical models, but more rarely to paleo-environmental conditions, especially beyond the Quaternary. On one hand the role of plate tectonics in shaping the extant diversity of lineages is supported by numerous phylogenetic and fossil evidences, and on the other hand the spatial variation of biodiversity across the globe is rarely associated to geodynamic variables. In this study, we propose that plate tectonics explain the current location of hotspots of endemic richness across the globe. As an illustration, we used paleogeographies in a model, which quantifies through time and for each cell the potential dispersal across disconnected habitat patches. Rare events of dispersal across dynamic straits of unsuitable habitats allows species colonisation and that a subsequent absence of gene flow could lead to in-situ speciation. We evaluated whether this process could pinpoint the locations of hotspots of endemic richness computed from the ranges of 181,603 species across 14 taxonomic groups. The significant congruence between the regions highlighted by the model and the endemic richness provides evidences of the contribution of plate tectonics in shaping global biodiversity gradients. Places with high tectonic complexity, predominantly located at the confluence of major lithospheric plates such as the Mediterranean basin, Central America, Madagascar and South East Asia likely provided favourable circumstances for allopatric speciation and the emergence of new species across straits. While our illustration supports the role of plate tectonics, accounting for deep time geological events in spatial models of extant biodiversity is not straightforward. Future research should develop quantitative spatial models of biodiversity including the dynamic of ancient habitats.
A Heuristic Genetic Algorithm for Independent Task Scheduling

This research tackles genetic algorithm techniques in scheduling independent tasks for multiprocessor by proposed heuristic genetic algorithm resulting from combining two classical list heuristics of scheduling independent tasks, in order to gaining an optimal scheduling with the least period of time (schedule length). The researcher proved is more efficient than using a separate algorithm of the two list scheduling algorithms.
Quantitative strain imaging and elasticity reconstruction

Ultrasound (US) based tissue elasticity imaging introduces a new challenging inverse problem measurements of internal tissue motion induced by a small external compression and the knowledge of corresponding force and/or displacement boundary conditions. On this basis, the problem can be stated as determine the elasticity distribution that best accounts for the observed internal displacements. Here, using computer simulation of the elasticity equations and an echographic image formation model, the authors outline the basic principles of this new imaging modality.
Cupids: increasing information system security through the use of dedicated co-processing

Most past and present intrusion detection systems architectures assume a uniprocessor environment or do not explicitly make use of multiple processors when they exist. Yet, especially in the server world, multiple processor machines are commonplace; and with the advent of technologies such as Intel and ANID's multi-core or Hyperthreading technologies, commodity computers are likely to have multiple processors. This research explores how explicitly dividing the system into production and security components and running the components in parallel on different processors can improve the effectiveness of the security system. The production component contains all user tasks and most of the operating system while the security component contains security monitoring and validating tasks and the parts of the O/S that pertain to security. We demonstrate that under some circumstances this architecture allows intrusion detection systems to use monitoring models with higher fidelity, particularly with regard to the timeliness of detection, and will also increase system robustness in the face of some types of attacks. Empirical results with a prototype co-processing intrusion detection system (Cu-PIDS) architecture support the feasibility of this approach. The construction of the prototype allowed us to demonstrate the implementation costs of the architecture are reasonable. Experimentation using fine-grained protection of real-world applications resulted in about a fifteen percent slowdown white demonstrating CuPIDS' ability to quickly detect and respond to illegitimate behavior.
Feedback linearization based adaptive friction compensation for a sandwich nonlinear system

Control strategies are developed for a sandwich nonlinear system with joint flexibility, damping and friction. Ideal feedback linearization matching conditions are defined for the case when the system parameters are known. Adaptive feedback linearization is employed to get asymptotically exact cancellation for the uncertainty inherent in the knowledge of the given system parameters. Friction is estimated by a model and the linearizing control input is modified with the addition of a friction compensating term.
A Hybrid Approach for Encrypting Data on Cloud to prevent DoS Attacks

Any technology cannot be said perfect until it is free from any vulnerability. So whenever a new technology is introduced the security is the first feature that is countable. There are many famous technologies that are used for online data storage, accessing the data from any location and provide the online use of any software. Cloud computing is the same technology that provides the online data storage and the most important feature that it provides software on lease facility. If large data storage feature took into consideration then it must be said that if a user wants to store the data on cloud then the security of that data must be the first requirement of the user. In this paper an integrated approach is introduced to encrypt and decrypt the data before sending on cloud by using the two different techniques. And the performance analysis is done on the basis of different parameters to achieve the better performance and security.
Key issues review: evolution on rugged adaptive landscapes

Adaptive landscapes represent a mapping between genotype and fitness. Rugged adaptive landscapes contain two or more adaptive peaks: allele combinations with higher fitness than any of their neighbors in the genetic space. How do populations evolve on such rugged landscapes? Evolutionary biologists have struggled with this question since it was first introduced in the 1930s by Sewall Wright. Discoveries in the fields of genetics and biochemistry inspired various mathematical models of adaptive landscapes. The development of landscape models led to numerous theoretical studies analyzing evolution on rugged landscapes under different biological conditions. The large body of theoretical work suggests that adaptive landscapes are major determinants of the progress and outcome of evolutionary processes. Recent technological advances in molecular biology and microbiology allow experimenters to measure adaptive values of large sets of allele combinations and construct empirical adaptive landscapes for the first time. Such empirical landscapes have already been generated in bacteria, yeast, viruses, and fungi, and are contributing to new insights about evolution on adaptive landscapes. In this Key Issues Review we will: (i) introduce the concept of adaptive landscapes; (ii) review the major theoretical studies of evolution on rugged landscapes; (iii) review some of the recently obtained empirical adaptive landscapes; (iv) discuss recent mathematical and statistical analyses motivated by empirical adaptive landscapes, as well as provide the reader with instructions and source code to implement simulations of evolution on adaptive landscapes; and (v) discuss possible future directions for this exciting field.
Why concatenation fails in the anomaly zone

Genome-scale sequencing has been of great benefit in recovering species trees, but has not provided final answers. Despite the rapid accumulation of molecular sequences, resolving short and deep branches of the tree of life has remained a challenge, and has prompted the development of new strategies that can make the best use of available data. One such strategy – the concatenation of gene alignments – can be successful when coupled with many tree estimation methods, but has also been shown to fail when there are high levels of incomplete lineage sorting. Here, we focus on the failure of likelihood-based methods in retrieving a rooted, asymmetric four-taxon species tree from concatenated data when the species tree is in or near the anomaly zone – a region of parameter space where the most common gene tree does not match the species tree because of incomplete lineage sorting. First, we use coalescent theory to prove that most informative sites will support the species tree in the anomaly zone, and that as a consequence maximum-parsimony succeeds in recovering the species tree from concatenated data. We further show that maximum-likelihood tree estimation from concatenated data fails both inside and outside the anomaly zone, and that this failure is unconnected to the frequency of the most common gene tree. We provide support for a hypothesis that likelihood-based methods fail in and near the anomaly zone because discordant sites on the species tree have a lower likelihood than those that are discordant on alternative topologies. Our results confirm and extend previous reports of the failure and success of likelihood- and parsimony-based methods, and highlight avenues for future work improving the performance of methods aimed at recovering species tree.
Comparison of linear predictive analysis methods for ANN-based speaker identification

This paper studies the parametrization of speech using linear predictive (LP) analysis and its application to speaker identification. The task of speaker classification is realized using multilayer perceptron. The system is evaluated on speaker set for speaker identification. The system is also tested with cepstral and reflection coefficients, and the results obtained are compared.
In Vivo Immune Responses of Cross-Linked Electrospun Tilapia Collagen Membrane.

Collagen has been used extensively in tissue engineering applications. However, the source of collagen has been primarily bovine and porcine. In view of the potential risk of zoonotic diseases and religious constraints associated with bovine and porcine collagen, fish collagen was examined as an alternative. The aim of this study is to use tilapia fish collagen to develop a cross-linked electrospun membrane to be used as a barrier membrane in guided bone regeneration. As there is limited data available on the cytotoxicity and immunogenicity of cross-linked tilapia collagen, in vitro and in vivo tests were performed to evaluate this in comparison to the commercially available Bio-Gide® membrane. In this study, collagen was extracted and purified from tilapia skin and electrospun into a nanofibrous membrane. The resultant membrane was cross-linked to obtain a cross-linked electrospun tilapia collagen (CETC) membrane, which was characterized by scanning electron microscopy (SEM), differential scanning calorimetry (DSC), degradation studies, cytotoxicity studies, and cell proliferation studies. The membranes were also implanted subcutaneously in rats and the host immune responses were examined. The DSC data showed that cross-linking increased the denaturation temperature of tilapia collagen to 58.3°C ± 1.4°C. The in vitro tests showed that CETC exhibited no cytotoxicity toward murine fibroblast L929 cells, and culture of murine preosteoblast MC3T3-E1 cells demonstrated better proliferation on CETC as compared to Bio-Gide. When implanted in rats, CETC caused a higher production of interleukin IL-6 at early time points as compared to Bio-Gide, but there was no long-term inflammatory responses after the acute inflammation phase. This finding was supported with histology data, which clearly illustrated that CETC has a decreased inflammatory response comparable to the benchmark control group. In all, this study demonstrated the viability for the use of CETC as a tissue engineering scaffold and provides an insight on the in vivo immune responses toward xenogenic collagen scaffolds.
Convolutional Neural Network for Sentence Classification

The goal of a Knowledge Base–supported Question Answering (KB-supported QA) system is to answer a query natural language by obtaining the answer from a knowledge database, which stores knowledge in the form of (entity, relation, value) triples. QA systems understand questions by extracting entity and relation pairs. This thesis aims at recognizing the relation candidates inside a question. We define a multi-label classification problem for this challenging task. Based on the word2vec representation of words, we propose two convolutional neural networks (CNNs) to solve the multi-label classification problem, namely Parallel CNN and Deep CNN. The Parallel CNN contains four parallel convolutional layers while Deep CNN contains two serial convolutional layers. The convolutional layers of both the models capture local semantic features. A max over time pooling layer is placed on the top of the last convolutional layer to select global semantic features. Fully connected layers with dropout are used to summarize the features. Our experiments show that these two models outperform the traditional Support Vector Classification (SVC)–based method by a large margin. Furthermore, we observe that Deep CNN has better performance than Parallel CNN, indicating that the deep structure enables much stronger semantic learning capacity than the wide but shallow network.
Determination of antimicrobial activity of two macro algae extracts

Bu calismada, Ulva rigida ve Gracilaria verrucosa makroalglerinden elde edilen etanol ozutlerinin antimikrobiyal aktivitesi incelenmistir. U. rigida ve G. verrucosa makroalgleri Inciralti (Izmir, Turkiye)sahilinden toplanmistir.Laboratuarda ornekler ilk once musluk suyu ile daha sonra saf su ile yikanarak temizlenmis ve 40 °C’de 24 saat sure ile kurutulmustur. Kurutulan ve toz haline getirilen ornekler (10 g) amber renkli erlene tartilmis ve uzerine 200 ml %95’lik etanol eklenmistir. Bu karisimlar calkalamali su banyosunda, farkli ekstraksiyon sicakliklarinda (30 °C, 45 °C ve 60 °C) 30 dakika sure ile ekstrakte edilmistir. Bu ozutler filtre edildikten sonra doner buharlastirici kullanilarak cozgen uzaklastirilmistir. Farkli sicakliklarda U. rigida ve G. verrucosa makroalglerinden saglanan etanol ozutlerinin kagit disk difuzyon agar metodu kullanilarak 6 bakteri ( Bacillus subtilis , Staphylococcus aureus , Enterococcus faecalis , Listeria monocytogenes , Escherichia coli ve Pseudomonas aeruginosa ) ve 2 mantar ( Aspergillus brasiliensis ve Candida albicans ) icin antibakteriyel ve antifungal aktiviteleri in-vitro olarak degerlendirilmistir. Test edilen tum ozutlerin A. brasiliensis haric tum bakteri ve mantarlara karsi antimikrobiyal etkiye sahip oldugu tespit edilmistir.
On the design of compliant-based micro-motion manipulators with a nanometer range resolution

In the last decades, there has been an increasing demand in the field of micromanipulation with high precision requirement. This motivated the development of a class of new devices, micro-motion manipulators or macromanipulators. This paper concerns some issues on designing a high-precision micromanipulator, which is based on "compliant mechanism" concept. The design rules for this kind of micromanipulators in terms of material, geometry, flexure hinges, actuators, motion and fabrication, are proposed in an imperative way. Based on these rules, the practical realization for the design of two compliant-based macromanipulators is described. The results of this paper are very useful for the design of compliant-based macro-motion systems.
Trianthema portulacastrum L.- the noxious weed and its control

Horse purslane (Trianthema portulacastrum Linn.) of family Aizoacae is native to South Africa and has been reported to be present in India, Pakistan, Tropical America, West Asia, Sri Lanka and Africa. It has become noxious due to substantial yield reduction on account of competition in several cultivated crops. The aim of this review is to provide general information about the physiology, distribution, ill effects, and management of horse purslane. Various methods has been tried to control this weed, but no single method would be adequate to manage horse purslane, and there is a need to integrate various management options. Successful management of this weed can only be achieved by an integrated approach with biological control as the key element.
CoGe LoadExp+: A web-based suite that integrates next-gen sequencing data analysis workflows and visualization

To make genomic and epigenomic analyses more widely available to the biological research community, we have created LoadExp+, a suite of bioinformatics workflows integrated with the web-based comparative genomics platform, CoGe. LoadExp+ allows users to perform transcriptomic (RNA-seq), epigenomic (BS-seq), chromatin-binding (ChIP-seq), variant identification (SNPs), and population genetics analyses against any genome in CoGe, including genomes integrated by users themselves. Through LoadExp+’s integration with CoGe’s existing features, all analyses are available for visualization and additional downstream processing, and are available for export to CyVerse’s data management and analysis platforms. LoadExp+ provides easy-to-use functionality to manage genomics and epigenomics data throughout its entire lifecycle and facilitates greater accessibility of genomics analyses to researchers of all skill levels. LoadExp+ can be accessed at https://genomevolution.org.
Development and Analysis of Gull Inspired UAV Flapping Wing

Unmanned Aerial Vehicles (UAVs) are the aircraft which are controlled remotely or autonomously. They can be characterized on the basis of type of wings used, namely fixed, flapping and rotary wing UAVs. They can be used for various military and civil applications. Present study is focused on flapping wing UAVs. Natural fliers are the master of flapping flight and can be taken as inspiration for developing an efficient flapping UAV model. In this study a flapping wing system, inspired from Black Headed Gull, is developed and tested for its kinematic and aerodynamic characteristics. Like the original biological structure, the developed model has a shoulder joint, an elbow joint, and a wrist joint. Laser displacement sensor and digital image correlation setups were used for kinematic testing. The aerodynamic analysis was carried out using six component force balance in wind tunnel at different wind speeds and angle of attacks. It was found that the wing performed flapping motion similar to the gull with independent control of each joint. Also, the effect of each joint was observed on the lift, thrust and moments generated by the model during flight. It was observed that the developed model showed similar properties as compared to its biological inspiration.
Predicting Coexistence in Species with Continuous Ontogenetic Niche Shifts and Competitive Asymmetry

A longstanding problem in ecology is whether structured life cycles impede or facilitate coexistence between species. Theory based on populations with two discrete stages in the life-cycle indicates that coexistence requires at least one species to shift its niche between stages and that each species is a better competitor in one of the niches. However, in many cases, niche shifts are associated with changes in an underlying continuous trait like organism size and we have few predictions for how the conditions for coexistence are affected by this type of ontogenetic dynamics. Here we develop a framework for analyzing species coexistence based on Integral Projection Models (IPMs) that incorporates continuous ontogenetic changes in both the resource niche and competitive ability. We parameterize the model using experimental data from Trinidadian guppies and make predictions about how niche shifts and competitive symmetries allow or prevent species coexistence. Overall, our results show that the effects of competition on fitness depend upon trait-mediated niche-separation, trait-mediated competitive asymmetry in the part of the niche that is shared across body sizes, and the sensitivity of fitness to body size. When all three conditions are considered, we find multiple ecological and evolutionary routes to coexistence. When both species can shift their niche with increasing body size and competition for resources among the species and sizes is symmetric, then the species that shifts its niche to a greater degree with ontogeny will competitively exclude the other species. When competitive ability increases with increasing body size, then the two species can coexist when the better competitor shifts its niche with body size to a lesser degree than the weaker competitior. This region of coexistence shrinks as the better competitor increasingly shifts its niche with increasing size. When both species shift their niches with size, but each is a better competitor on resources used by smaller or larger individuals, then the model predicts an alternative stable state over some range of niche shifts. We discuss how our results provide new insights into species coexistence and the evolutionary consequences of size-structured interspecific competition.
Functional regulatory evolution outside of the minimal even-skipped stripe 2 enhancer

Transcriptional enhancers are regions of DNA that drive precise patterns of gene expression. Although many studies have elucidated how individual enhancers can evolve, most of this work has focused on what are called ‘minimal’ enhancers, the smallest DNA regions that drive expression that approximates an aspect of native gene expression. Here, we explore how the Drosophila erecta even-skipped (eve) locus has evolved by testing its activity in the divergent D. melanogaster genome. We found, as has been reported previously, that the D. erecta eve stripe 2 enhancer (eveS2) fails to drive appreciable expression in D. melanogaster. However, we found that a large transgene carrying the entire D. erecta eve locus drives normal eve expression, including in stripe 2. We performed a functional dissection of the region upstream of the D. erecta eveS2 region and found multiple Zelda motifs that are required for normal expression. Our results illustrate how sequences outside of minimal enhancer regions can evolve functionally through mechanisms other than changes in transcription factor-binding sites that drive patterning. Summary: Analysis of sequences upstream of the eve minimal enhancer region in multiple Drosophila species demonstrates functional evolution via mechanisms other than changes in transcription factor-binding sites.