Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrusion Detection System (IDS) and Their Types

Over the last two decades, computer and network security has become a main issue, especially with the increase number of intruders and hackers, therefore systems were designed to detect and prevent intruders. This chapter per the authors investigated the most important design approaches, by mainly focusing on their collecting, analysis, responding capabilities and types of current IDS products. For the collecting capability, there were two main approaches, namely host- and network-based IDSs. Therefore, a combination of the two approaches in a hybrid implementation is ideal, as it will offer the highest level of protection at all levels of system functions. The analysis capability of an IDS can be characterised by the misuse and anomaly detection approaches. Therefore, a combination of the two approaches should improve the analysis capability of an IDS i.e. hybrid of misuse and anomaly detection.
Retrospective analysis of 2015–2017 wintertime PM2.5 in China: response to emission regulations and the role of meteorology

Abstract. To better characterize anthropogenic emission-relevant aerosol species, the Gridpoint Statistical Interpolation (GSI) and Weather Research and Forecasting with Chemistry (WRF/Chem) data assimilation system was updated from the GOCART aerosol scheme to the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) 4-bin (MOSAIC-4BIN) aerosol scheme. Three years (2015–2017) of wintertime (January) surface PM2.5 (fine particulate matter with an aerodynamic diameter smaller than 2.5 µm) observations from more than 1600 sites were assimilated hourly using the updated three-dimensional variational (3DVAR) system. In the control experiment (without assimilation) using Multi-resolution Emission Inventory for China 2010 (MEIC_2010) emissions, the modeled January averaged PM2.5 concentrations were severely overestimated in the Sichuan Basin, central China, the Yangtze River Delta and the Pearl River Delta by 98–134, 46–101, 32–59 and 19–60 µg m−3, respectively, indicating that the emissions for 2010 are not appropriate for 2015–2017, as strict emission control strategies were implemented in recent years. Meanwhile, underestimations of 11–12, 53–96 and 22–40 µg m−3 were observed in northeastern China, Xinjiang and the Energy Golden Triangle, respectively. The assimilation experiment significantly reduced both high and low biases to within ±5 µg m−3. The observations and the reanalysis data from the assimilation experiment were used to investigate the year-to-year changes and the driving factors. The role of emissions was obtained by subtracting the meteorological impacts (by control experiments) from the total combined differences (by assimilation experiments). The results show a reduction in PM2.5 of approximately 15 µg m−3 for the month of January from 2015 to 2016 in the North China Plain (NCP), but meteorology played the dominant role (contributing a reduction of approximately 12 µg m−3). The change (for January) from 2016 to 2017 in NCP was different; meteorology caused an increase in PM2.5 of approximately 23 µg m−3, while emission control measures caused a decrease of 8 µg m−3, and the combined effects still showed a PM2.5 increase for that region. The analysis confirmed that emission control strategies were indeed implemented and emissions were reduced in both years. Using a data assimilation approach, this study helps identify the reasons why emission control strategies may or may not have an immediately visible impact. There are still large uncertainties in this approach, especially the inaccurate emission inputs, and neglecting aerosol–meteorology feedbacks in the model can generate large uncertainties in the analysis as well.
Modelo de simulación del crecimiento y desarrollo de la papa criolla

En aras de contribuir al desarrollo tecnologico del sistema productivo de la papa criolla, se desarrollo la presente investigacion cuyo objetivo fue adaptar el paradigma fuente demanda a los procesos de captura y asignacion de nutrientes para simular el crecimiento y desarrollo de la planta de papa criolla. Se presenta el proceso de formulacion, parametrizacion y evaluacion de un modelo demografico basado en la fisiologia de la papa criolla Solanum phureja cv. Criolla Colombia; Se incluyeron dos variables climaticas, temperatura y radiacion solar para simular los procesos de fotosintesis, respiracion, asignacion selectiva y acumulacion de biomasa. Se compararon los resultados de la simulacion con datos de campo independientes a los que fueron empleados para parametrizar el modelo y se encontro un adecuado ajuste en cuanto al crecimiento de raices, tallos, hojas, estolones y tuberculos.
The effect of noise on segmental and prosodic timing in speech production

The present investigation examined the effects of noise on prosodic and segmental timing in speech production, focusing on preboundary lengthening, pausing, speaking rate and trends in segmental duration. Preboundary lengthening was examined using normalized duration measurements. Four subjects participated in this study. Each read syntactically ambiguous sentences to a listener under conditions of quiet and multitalker babble. These sentences were then labeled by listeners according to a seven-point scale of perceived boundary strength (or break index). Each break index corresponded to a level of prosodic phrasing proposed in the literature. In general, speakers were highly individualistic in the ways they altered the segmental components of speech in noise. Three of four subjects decreased their rates of speaking in noise to varying degrees. The greatest changes in segmental durations were observed in vowels and sonorants. Changes in consonant durations were more subject specific. Both the distribution and durations of pauses were characterized by a large degree of intersubject variability. The number of pauses tended to increase with increasing perceptual boundary strength, and pauses at the larger phrase boundaries were significantly longer than those at lower levels of phrasing. Preboundary lengthening was found to increase rapidly across three lower levels of phrasing, while almost no differences were observed between the two highest levels of phrasing across both speaking conditions. This suggests that preboundary lengthening is an important perceptual cue to the lower levels of phrasing, which are marked by few other phonetic cues. The effect of noise on overall timing relationships between prosodic constituents was minimal. The degree of preboundary lengthening remained relatively constant across speaking conditions for all four subjects participating in the experiment. It is proposed that speakers try to maintain prosodic timing relationships in order to preserve speech intelligibility in noise.
Software Module Fault Prediction using Convolutional Neural Network with Feature Selection

Software plays a significant role in technological and economic development due to its utmost importance in day to day activities. A sequence of rigorous activities under certain constraints is followed to come up with reliable software. Various measures are taken during the process of software development to ensure high quality software. One such method is software module fault prediction for quality assurance to discover defects in the software prior to testing. It aids in predicting the software module faults earlier in the development of the software which predicts fault prone modules so that these can be given special attention to avoid any future risk which eventually curbs the testing along with maintenance cost and effort. The literature survey uncovers many findings that had never been focused like dimensionality reduction and feature selection based on individual feature importance which leads to increase in time complexity and chances of false information. This paper addresses these issues and proposes a supervised machine learning based software module fault prediction technique by implementing Convolutional Neural Network (CNN) as classifier model. Feature selection methods used are InfoGain and Correlation. The results obtained are compared with the existing method HySOM (SOM Clustering with Artificial Neural Network Classification) by considering three different feature sets (Fifteen features, Eighteen features and Twenty one features) of PC1 dataset from NASA. The comparative analysis is performed on the basis of accuracy, precision, recall and F1-measure. The results clearly show better performance of the proposed CNN based technique than HySOM. This paper will contribute towards improvement of quality assurance models utilized for software fault prediction by automating this process using machine learning which enhances True Positive Rate and reduces the detection error. This in turn will help project managers, testers and developers to locate and keep track of fault prone modules so that final software is more accurate, consistent and reliable without consuming much of the testing and maintenance resources
Isotropization of a Rotating and Longitudinally Expanding ϕ4 Scalar System

We study numerically the evolution of an expanding system of scalar fields. The initial configuration is non-isotropic and rotating. We calculate the energy–momentum tensor and angular momentum vector of the system. We compare the time scales associated with the isotropization of the transverse and longitudinal pressures, and the decay of the initial angular momentum. We show that even a fairly large initial angular momentum decays significantly faster than the pressure anisotropy.
Research on the application of the improved genetic algorithm in the electroencephalogram-based mental workload evaluation for miners

Electroencephalogram is the electrical phenomena in the cerebral cortex or the scalp surface due to the electrophysiological activity of brain cells. Electroencephalogram has great theoretical and practical significance in measuring mental workload of people. More precise electroencephalographic is a precondition to study mental workload of miners. In this article, based on the actual situation of the electroencephalographic measurement of miners, the particle swarm optimization is introduced to improve the standard genetic algorithm, and put forward a combined method integrating the genetic algorithm with particle swarm optimization for achieving electroencephalogram-based measures of miners' mental workload. Moreover, the MATLAB simulation platform is used for simulation testing. Testing results prove the effectiveness of the combined method.
Perfil de imunoglobulinas, cura clínica e bacteriológica após diferentes tratamentos para a mastite clínica bovina

RESUMO O presente estudo objetivou avaliar o perfil das Ig durante os diferentes tratamentos de vacas com mastite clínica. Para isso, 30 vacas com mastite clínica em um quarto mamário foram utilizadas e divididas em três grupos. O primeiro grupo foi composto por 10 animais submetidos ao tratamento combinado com infusão intramamária de 8,5mg de sulfato de cefquinoma após cada ordenha, totalizando três aplicações e administração intramuscular de 2,5mg/kg de enrofloxacina por três dias. O segundo grupo foi composto por 10 animais submetidos ao tratamento intramamário, com infusão intramamária de 8,5mg de sulfato de cefquinoma, após cada ordenha, totalizando três aplicações. O terceiro grupo foi composto por 10 animais submetidos ao tratamento sistêmico, com 2,5mg/kg de enrofloxacina, durante três dias. As amostras de leite foram coletadas de todos os animais antes dos tratamentos (momento 0), no segundo (momento 1), no quinto (momento 2) e no 12º dia (momento 3) após o término dos tratamentos. Estas foram submetidas à contagem de células somáticas, ao California Mastitis Test (CMT), ao exame bacteriológico e à quantificação das IgG1, IgG2, IgA e IgM. O tratamento combinado foi mais eficaz e precoce na taxa de cura clínica, na redução dos escores de CMT e da contagem de células somáticas. Além disso, os resultados do presente estudo demonstraram que as concentrações lácteas das diferentes classes de Ig, apesar de sua importância biológica, não estão relacionadas ao prognóstico da mastite clínica bovina, ou seja, não podem ser consideradas marcadores robustos associados à cura clínica e/ou bacteriológica da infecção intramamária.
Functional and morphological evolution in gymnosperms: A portrait of implicated gene families

Gymnosperms diverged from their sister plant clade of flowering plants 300 Mya. Morphological and functional divergence between the two major seed plant clades involved significant changes in their reproductive biology, water‐conducting systems, secondary metabolism, stress defense mechanisms, and small RNA‐mediated epigenetic silencing. The relatively recent sequencing of several gymnosperm genomes and the development of new genomic resources have enabled whole‐genome comparisons within gymnosperms, and between angiosperms and gymnosperms. In this paper, we aim to understand how genes and gene families have contributed to the major functional and morphological differences in gymnosperms, and how this information can be used for applied breeding and biotechnology. In addition, we have analyzed the angiosperm versus gymnosperm evolution of the pleiotropic drug resistance (PDR) gene family with a wide range of functionalities in plants' interaction with their environment including defense mechanisms. Some of the genes reviewed here are newly studied members of gene families that hold potential for biotechnological applications related to commercial and pharmacological value. Some members of conifer gene families can also be exploited for their potential in phytoremediation applications.
Hydrodynamic changes due to coastal reclamation activities in Daya Bay

Based on the geometry and surface in Daya Bay, we artificially divided the reclamation projects into three periods to analyze the influences and changes on hydrodynamic conditions as a result of the reclamation projects. Three periods of tidal current fields, tidal prisms, and water exchange capacity are simulated by the Finite-Volume, primitive equation Community Ocean Model and the characteristics and trends of hydrodynamics in Daya Bay are discussed. The combination of observation and simulation in this paper gives a good description on the tidal dynamic system in Daya Bay. As indicated by model results, the tidal current velocity in the Bay totally decreases after numerous activities associated with reclamation construction. The decreasing current velocity region is mainly distributed near the Xiachong and Gangkou chain islands. The current velocity in 2015 decreases by approximately 5 cm s−1 compared with velocities before 2000. Future reclamation activities will exacerbate these decreasing current velocity trends in some regions. Compared with 2015, the tidal prism has significantly decreased by 1.3622 × 107 m3 due to planned reclamation. The half-water exchange times for Daya Bay in 2015 and after planned reclamation are 178.9 and 177.4 days, respectively. The water exchange capacity in Fanhe Harbor is weaker than other water fields throughout Daya Bay.
Message-Based Routing in Mobile Networks

Mobile phones and PDAs can be utilized as ad-hoc mobile messaging communication devices for near field communication by using Bluetooth technology and mobile ad-hoc networks (MANET). Until now known MANET concepts rely on stationary networks. Liability and stability of the connection in near field communication-based networks are pivotal ans require sophisticated and complex mechanisms. However, these mechanisms often do not reflect the application’s particularities such as memory or interface restrictions This contribution provides an approach for an ad-hoc messaging network (AMNET), which uses simple store-and-forward message passing to spread data asynchronously. This approach focuses primarily on application-specific needs that can be covered by simple message passing mechanisms. In this paper, we will describe a network based on the AMNET approach. Results are derived by scenario analysis to provide insights into speeding up the network setup process and enable the use of AMNETs even with a limited number of participants by introducing a hybrid infrastructure and by adding mobile nodes.
Maximal Sequential Patterns: A Tool for Quantitative Semantic in Text Analysis

This chapter introduces maximal sequential patterns, how to extract them, and some applications of maximal sequential patterns for document processing and web content mining. The main objective of this chapter is showing that maximal sequential patterns preserve document semantic, and therefore they could be a good alternative to the word and n-gram models. First, this chapter introduces the problem of maximal sequential pattern mining when the data are sequential chains of words. After, it defines several basic concepts and the problem of maximal sequential pattern mining in text documents. Then, it presents two algorithms proposed by the authors of this chapter for efficiently finding maximal sequential patterns in text documents. Additionally, it describes the use of maximal sequential patterns as a quantitative semantic tool for solving different problems related to document processing and web content mining. Finally, it shows some future research directions and conclusions. DOI: 10.4018/978-1-60960-881-1.ch010
Understanding the emergence of bacterial pathogens in novel hosts

Our understanding of the ecological and evolutionary context of novel infections is largely based on viral diseases, even though bacterial pathogens may display key differences in the processes underlying their emergence. For instance, host-shift speciation, in which the jump of a pathogen into a novel host species is followed by the specialization on that host and the loss of infectivity of previous host(s), is commonly observed in viruses, but less often in bacteria. Here, we suggest that the extent to which pathogens evolve host generalism or specialism following a jump into a novel host will depend on their level of adaptation to dealing with different environments, their rates of molecular evolution and their ability to recombine. We then explore these hypotheses using a formal model and show that the high levels of phenotypic plasticity, low rates of evolution and the ability to recombine typical of bacterial pathogens should reduce their propensity to specialize on novel hosts. Novel bacterial infections may therefore be more likely to result in transient spillovers or increased host ranges than in host shifts. Finally, consistent with our predictions, we show that, in two unusual cases of contemporary bacterial host shifts, the bacterial pathogens both have small genomes and rapid rates of substitution. Further tests are required across a greater number of emerging pathogens to assess the validity of our hypotheses. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.
A comparative analysis of the organic and inorganic carbon content of Halimeda and Penicillus (Chlorophyta, Bryopsidales) in a coastal subtropical lagoon

Abstract Standing stocks of the calcifying algae, Halimeda and Penicillus, have remained stable over the 10 years surveyed (2007–2017) in Florida Bay (USA), a subtropical lagoon. The maximum contribution of calcium carbonate (CaCO3; 779.75 g m−2) was lower compared to tropical lagoons. Halimeda was more abundant and had higher inorganic:organic carbon ratios compared to Penicillus. The abundance of Penicillus varied across the surveyed sites, Sprigger Bank, Bob Allen Keys, and Duck Key, while its inorganic:organic carbon ratios did not vary significantly. Our long-term study provides a critical baseline that can help understand fluctuations in carbonate sediment production by calcareous algae in subtropical coastal waters.
Finding the global semantic representation in GAN through Frechet Mean

The ideally disentangled latent space in GAN involves the global representation of latent space with semantic attribute coordinates. In other words, considering that this disentangled latent space is a vector space, there exists the global semantic basis where each basis component describes one attribute of generated images. In this paper, we propose an unsupervised method for finding this global semantic basis in the intermediate latent space in GANs. This semantic basis represents sample-independent meaningful perturbations that change the same semantic attribute of an image on the entire latent space. The proposed global basis, called Fr\'echet basis, is derived by introducing Fr\'echet mean to the local semantic perturbations in a latent space. Fr\'echet basis is discovered in two stages. First, the global semantic subspace is discovered by the Fr\'echet mean in the Grassmannian manifold of the local semantic subspaces. Second, Fr\'echet basis is found by optimizing a basis of the semantic subspace via the Fr\'echet mean in the Special Orthogonal Group. Experimental results demonstrate that Fr\'echet basis provides better semantic factorization and robustness compared to the previous methods. Moreover, we suggest the basis refinement scheme for the previous methods. The quantitative experiments show that the refined basis achieves better semantic factorization while constrained on the same semantic subspace given by the previous method.
Genetic Variability and Heritability among Sugarcane Genotypes in Plant Crop for Some Agronomic Traits under Tropical Dry Climate of Ferké, Ivory Coast

Aims: The study aimed to determine the best performing cane genotypes among 29 clones tested under sprinkler irrigation, in comparison with a check variety (R579). Study Design: The experimental design used was a randomized complete block (RCB) with 30 cane genotypes in three replications. Every plot consisted of two dual rows of five meters with 0.5 and 1.90 m of inter-row spacing, i.e. 19 m² per plot and about 600 m² for the whole experiment. Place and Duration of Study: It was carried out on a commercial sugarcane plantation of Ferké 2 located in the northern part of the country, over 10 months as a late season crop from late May 2018 to late March 2019. Methodology: Over each micro-plot, data were collected at harvest from both dual rows consisted of millable stalk number/ha, cane yield, juice quality traits (sucrose, purity, and recoverable sucrose), fiber content, and damaged internodes by stem borer Eldana saccharina. Results: Based on sugar yields, seven cane genotypes were equivalent to the check variety R579 which gave 17.6 t/ha. Their yield performances ranged from 12.2 to 15.4 t of sugar/ha and from 134.2 to 160.8 t of cane/ha compared to 176.0 t/ha for the check. Higher heritability values ranging from 52 to 85% were observed in traits like sugar yield, juice purity, juice sucrose, recoverable sucrose, sucrose percent, fiber content and stem borer infestations. Differences between PCV and GCV for most traits were small, indicating high prospects for genetic progress through selection under conditions of this study. Conclusions: Findings obtained need to be confirmed over the 2019-20 cropping season in first ratoon crop to determine promising cane genotypes for the advanced selection stage.