Miracle-dz/UniFAR-FTUs huggingface dataset:
Overlap-Save FBMC Receivers

Future communication systems are foreseen to support several services with different requirements. Waveform designs based on filter-bank multi-carrier with offset quadrature amplitude modulation (FBMC/OQAM) can offer interesting advantages in this context, such as low out-of-band power leakage and high spectral efficiency due to the lack of guard intervals. However, downsides of FBMC/OQAM with respect to a typical orthogonal frequency-division multiplexing (OFDM) solution include higher latency, higher complexity and difficulties in adapting some existing OFDM techniques such as MIMO Alamouti. To address these issues, novel FBMC receivers suitable for short prototype filters are proposed. Based on the Overlap-Save algorithm, the proposed receivers improve error-rate performance on multipath channels and support asynchronous communication. We show that complexity can be further reduced by efficiently processing blocks of FBMC symbols jointly, and that user mobility support can be traded off for additional complexity reductions in a flexible way through polynomial decomposition of the equalizer stage. Finally, we show that a block-Alamouti scheme can be applied, and we propose a MIMO equalizer with improved error-rate performance on time-varying channels, compared to the typical FBMC block-Alamouti equalizer.
View Synthesis-based Distributed Light Field Compression

Light field imaging is becoming a key technology, which provides users with a realistic visual experience through the capability of dynamic viewpoint shifting. This ability comes at the cost of capturing huge amounts of information, leaving the problem of compression and transmission a challenge. The encoder complexity is the key to achieve efficient coding in conventional light field coding schemes, where a complicated prediction process is essentially used at the encoder side to exploit the redundancy present in the light field image. We employ Distributed Source Coding (DSC) for light field images, which can extensively lift the computational requirement from the encoding side at the expense of increased computational complexity at the decoder side. The efficiency of DSC is heavily dependent on the quality of side information at the decoder. Therefore, we propose to leverage a learning-based view synthesis method, which takes into account the light field structure to generate high-quality side information. We compare our approach to Distributed Video Coding and Distributed Multi-view Video Coding schemes adapted to the light field framework and relevant standard-based approach, and demonstrate that the proposed view synthesis-based approach can achieve similar performance, while substantially reducing the number of key views to be transmitted.
Green Extraction of Polyphenols from Olive Leaves using Ired-Irrad® as a Pretreatment

Maximization of polyphenols recovery from olive leaves by conventional water bath extraction was investigated using infrared irradiation as a pretreatment. A multivariate study enabled us to define the best experimental parameters for polyphenol extraction: 1:20 (w/v) for the solid to liquid ratio; $60 ^{\circ}\mathrm {C}$ and 75% ethanol/water. Untreated and infrared pretreated leaves were then subjected to the conventional extraction of polyphenols using the abovementioned conditions. A significant increase in both polyphenol yields and antiradical activities were shown subsequently to the infrared pretreatment of the leaves. This study concluded that IR pretreatment intensified the polyphenols extraction by varying different operative parameters such as temperature and IR exposure time.
Nomenclatural Notes on Anoles (Sauria: Polychridae): Stability over Priority

In the course of our recent studies relating to the taxonomy of anoline lizards (Guyer and Savage, 1987; Savage and Guyer, 1989; hereafter cited simply as 1987 and 1989) we have discovered several nomenclatural problems that require elucidation. As a matter of convenience they are treated in chronological order based upon the first published use of the name. In this account the abbreviation ICZN refers to the
Distribution and physiological characterization of cyanobacteria isolated from arid zones of Rajasthan

Soil samples were collected from selected arid zones of Rajasthan, India, namely Achrol, Jaiselmer, Manwar and Pokharan. Studies conducted on the distribution indicated their ubiquitious occurrence and predominant presence of Nostoc species. Unialgal non-heterocystous forms namely Phormidium and Oscillatoria and heterocystous forms like Nostoc, Anabaena, Calothrix, Westiellopsis and Chlorogloeopsis were isolated and purified. These isolates were characterized for chlorophyll content, specific metabolite content and nitrogen fixing ability. Phormidium species showed maximum chlorophyll accumulation in comparison to heterocystous forms. Anabaena sphaerica exhibited maximum level of soluble proteins. Non-heterocystous forms, like Phormidium and Oscillatoria, also accumulated high levels of soluble proteins. Heterocystous forms namely Nostoc, Anabaena and Westiellopis were more efficient to synthesize carbohydrates in comparison to nonheterocytstous forms. Anabaena sphaerica, an isolate from Achrol, showed highest nitrogenase activity. Calothrix species isolated from Manwar and Pokharan region showed remarkable potential for nitrogen fixation, although these were poor in terms of chlorophyll accumulation and soluble protein content.
AI Meta-Learners and Extra-Trees Algorithm for the Detection of Phishing Websites

Phishing is a type of social web-engineering attack in cyberspace where criminals steal valuable data or information from insensitive or uninformed users of the internet. Existing countermeasures in the form of anti-phishing software and computational methods for detecting phishing activities have proven to be effective. However, new methods are deployed by hackers to thwart these countermeasures. Due to the evolving nature of phishing attacks, the need for novel and efficient countermeasures becomes crucial as the effect of phishing attacks are often fatal and disastrous. Artificial Intelligence (AI) schemes have been the cornerstone of modern countermeasures used for mitigating phishing attacks. AI-based phishing countermeasures or methods possess their shortcomings particularly the high false alarm rate and the inability to interpret how most phishing methods perform their function. This study proposed four (4) meta-learner models (AdaBoost-Extra Tree (ABET), Bagging – Extra tree (BET), Rotation Forest – Extra Tree (RoFBET) and LogitBoost-Extra Tree (LBET)) developed using the extra-tree base classifier. The proposed AI-based meta-learners were fitted on phishing website datasets (currently with the newest features) and their performances were evaluated. The models achieved a detection accuracy not lower than 97% with a drastically low false-positive rate of not more 0.028. In addition, the proposed models outperform existing ML-based models in phishing attack detection. Hence, we recommend the adoption of meta-learners when building phishing attack detection models.
Defensive Behavior and Display of the Leaf-Mimicking Katydid Pterochroza ocellata (L.) (Orthoptera: Tettigoniidae: Pseudophyllinae: Pterochrozini)

The leaf-mimicking katydid Pterochroza ocellata resembles a dead or diseased leaf when at rest. When disturbed, this katydid elicits a threatening eyespot display, presenting visual elements similar to those found on an avian face. Behavioral components of this display are described and quantified. The threatening display was found to vary in duration, and in several cases was followed by escape behavior and the resumption of a cryptic attitude differing from the initial resting posture. Both male and female P. ocellata have the same primary defenses (camouflage/leaf resemblance) and secondary defenses (eyespots/threatening display) (KEY WORDS: mimicry, eyespots, camouflage, defensive behavior, threatening display, Orthoptera, Tettigoniidae, Pseudophyllinae, Pterochrozini)
Survival rates required to sustain bear populations

A simple approximation to the Lotka equations permits using various combinations of population dynamics parameters to determine adult female survival rates needed to sustain a constant population level under various conditions suggested by observed data on grizzly (Ursus arctos) and polar bears (U. maritimus). The approximation should be useful in evaluating more complex models. Some data on polar bears were used to illustrate a method for estimating the ratio of early survival rates to that for adults. Such a ratio may be useful in establishing appropriate combinations of subadult and total adult survivorship for sustained population levels
Analysis of VHR Image Classification by Single and Ensemble of Classifiers

Given the wide variety of image classifiers available nowadays, some questions remain about the accuracy and processing time of Very High Resolution (VHR) images. Another question concerns the use of a Single or Ensemble Classifiers. Of course, the main factor to consider is the quality of the classified image, but computational cost is also important, especially in applications that require real-time processing. Given this scenario, this paper aims to relate the accuracy of seven single classifiers and the ensemble of the same classifiers with the processing time. In this paper the ensemble of classifiers had the best results in terms of accuracy, however, it comes to processing time, the decision tree had the best performance.
Philopatry. nest-site tenacity, and mate fidelity of Semipalmated Plovers

Philopatry, nest-site tenacity, and mate fidelity were examined in a population of Semipalmated Plovers Charadrius semipalmatus breeding near Churchill, Manitoba, Canada from 1992 to 1997. Natal philopatry was low (7 of 445 (1.57%) hatchlings returned to the study area to breed) and no difference in sex of recruits was detected. Adult males returned at a significantly higher rate (58.9%) than adult females (41.2%). For both sexes, but more strongly for females, success in the previous year resulted in higher return rates in the subsequent year. Of pairs that returned, 41.6% divorced. Females that divorced or changed mates through death or disappearance of a partner between breeding seasons were significantly less site tenacious than females that reunited and also less so than males of any pairing status. Females that experienced breeding failure and changed mates in the subsequent breeding season moved farther than successful females that changed mates. In only one of four years did reunited pairs nest earlier and have greater hatching success than novel pairs. After divorce new mates of females did not differ significantly in morphological or plumage characteristics from old mates, nor did they possess territories with greater visibility, or territories nearer to water. After divorce new mates of males were significantly smaller than old mates. Our return rates underestimate survivorship in females because both the probability of return and site tenacity of females are strongly influenced by their previous success.
Detecting Center Pivots In Matopiba Using Hough Transform And Web Time Series Service

In the last decades, the Brazilian Cerrado biome has undergone major transformations due to the expansion of the agricultural frontier. The region called MATOPIBA acronym for states Maranhão, Tocantins, Piauí, and Bahia can be considered very attractive for agricultural expansion. The Cerrado predominates in the MATOPIBA region (91% of the area), also having small areas of the Amazon and Caatinga biomes to the northeast and east, respectively. In this work, we will present a study to identify center pivot irrigation systems in the MATOPIBA region using remote sensing images from Landsat-8 satellite. The methodology is based on the use of robust edge detection techniques such as Canny, Circular Hough Transform (CHT) and time series extraction through the Moderate Resolution Imaging Spectroradiometer (MODIS) product MOD13Q1 which has two vegetation indices NDVI and EVI. These time series will be used to filter the detected circles, seeking to eliminate the circles that do not correspond to center pivots. Our approach detected 80% of the center pivots mapped by the Brazilian National Water Agency (ANA) used as a knowledge base. The states with better detection were Piauí and Bahia that showed the accuracy of 90% and 85% respectively, Maranhão obtained 57% and Tocantins 41%.
Diversity of phlorotannin profiles among sargassasacean species affecting variation and abundance of epiphytes

In general, epiphytes have detrimental effects on the growth of their basiphytes due to competition for light and nutrients. Therefore, basiphyte species must expend energy suppressing epiphytes. Some studies suggest that phlorotannins, i.e. brown algal polyphenols, prevent colonization by epiphytes, whereas others question their allelopathic function because there is not necessarily a negative correlation between epiphyte abundance and the phlorotannin content of the basiphyte algae. Various phlorotannin components are found in brown algal species, thus we hypothesized that the antifouling activities of polyphenolic compounds may differ and that the analysis of phlorotannin profiles could be useful for estimating their ecological functions. We surveyed the epiphyte richness in the apical portions of 373 thalli from 15 sargassacean species, demonstrating that the variation and abundance of epiphyte species differed remarkably among the basiphyte species. However, there was a weak negative correlation between the density and total phlorotannin content of the basiphyte algae in only one of the 18 epiphyte species. The interspecific differences in the phlorotannin profile were characterized by quantitative 1H nuclear magnetic resonance spectroscopy (qNMR), and four major groups were categorized based on cluster and principal component analyses of polyphenolic signals in the qNMR spectra. The epiphyte Neosiphonia harveyi was more abundant on Sargassum hemiphyllum, S. patens and S. piluliferum than on other basiphyte species, and these three species were similar according to the cluster analysis. These results suggest that some phlorotannin components may be more effective for antifouling; thus interspecific differences in the phlorotannin profile could affect the variation and abundance of epiphytes.
State estimation for parabolic PDE system with moving boundary utilizing mobile sensor networks with missing measurements

This paper considers the estimation for parabolic PDE systems with moving boundaries. To improve the estimation performance of the system, mobile sensors with missing measurements are used to provide the measurement information. Using abstract evolution equation of parabolic PDE system and Lyapunov stability arguments, a state estimator is designed to estimate the states of the system. Meanwhile, a stable control law for each of the mobile sensors, which is greatly affected by the moving boundary and the packet dropout rate, is presented while taking account of the dynamics of sensor movements. Simulation results show that the proposed estimators and mobile policies are effective.
Multitemporal Spectral Analysis for Algae Detection in an Eutrophic Lake using Sentinel 2 Images

Eutrophication is characterized by excessive plant and algal growth due to the increased of organic matter, carbon dioxide and nutrients in water body. Although eutrophication naturally occurs over centuries as lakes age, human activities have accelerated it processes and caused dramatic changes to the aquatic ecosystems including elevated algae blooms and risk for hypoxia as well as degradation in the quality of drinking water and fisheries. Monitoring eutrophic processes is therefore highly important to human health and to the aquatic environment. However, the spatial and seasonal distribution of the phenomena and its dynamic are difficult to be resolved using conventional methods as water sampling or sparse acquisition of remote sensing data. This research work proposes a methodology that takes advantage of the high temporal resolution of Sentinel-2 (S2) for monitoring eutrophic reservoir. Specifically, it uses large temporal series of S2 images and advanced temporal unmixing model to estimate the abundance of [Chl-a] and algae species in San Roque reservoir, Argentina, in the period August 2016 to August 2019. The spatial patterns and the temporal tendencies of these aquatic indicators, that have a direct link to Eutrophication, were analysed and evaluated using in situ data in order to assess their contribution to the local water management.
Parametric Study of a Cathode-Less Radio Frequency Thruster

A cathode-less radio frequency (RF) thruster is a plasma-based system for space propulsion. It consists on a source for plasma generation driven by an RF antenna and a magnetic nozzle for the acceleration of the exhausted plasma stream. A parametric analysis has been conducted in order to evaluate the influence of some key design parameters on the performances of such a thruster. Specifically, the intensity and the topology of the magneto-static field, along with the antenna geometry have been varied. Their influence has been assessed on the plasma parameter profiles within the source (i.e., electron density, electron temperature, and power deposition), the antenna properties (i.e., impedance and current distribution), and the propulsive performances (i.e., thrust and specific impulse). The results presented in this work have been obtained with the validated code 3D-VIRTUS. The latter solves self-consistently both the electro-magnetic wave propagation and the plasma transport within a source driven by a RF antenna. An analytical model has been subsequently employed in order to solve the plasma dynamics in the plume and, in turn, to estimate the propulsive performances.
HMTL: Heterogeneous Modality Transfer Learning for Audio-Visual Sentiment Analysis

Multimodal sentiment analysis is an extended approach to traditional language-based sentiment analysis, which uses other relevant modality data. Multimodal sentiment analysis usually applies visual, textual, and acoustic representations for sentiment prediction. Recently, various data fusion methodologies have been proposed for multimodal sentiment analysis. In most cases, textual modality plays a major role, and visual and acoustic modalities are used as auxiliary sources for multimodal sentiment analysis. However, in general multimedia such as video, text transcripts of an individual’s speech are not provided. Research on an audio-visual sentiment analysis methodology that does not depend on text modality is essential for multimodal sentiment analysis in real-world industrial applications. Therefore, it is important to improve audio-visual sentiment analysis because it currently exhibits lower performance than multimodal sentiment analysis, including text modality. In this paper, we propose heterogeneous modality transfer learning (HMTL) to utilize the knowledge of aligned text data as a source modality in transfer learning to improve audio-visual sentiment analysis performance. Our approach uses a decoder and adversarial learning techniques to reduce the gap between the source and target modalities in the embedded space for multimodal representation. Our proposed methodology experimentally outperformed recent unimodal and bimodal audio-visual sentiment analysis achievements.
A weighted AMMI algorithm to study genotype-by-environment interaction and QTL-by-environment interaction

Genotype-by-environment (G × E) interaction (GEI) and quantitative trait locus (QTL)-by-environment interaction (QEI) are common phenomena in multiple-environment trials and represent a major challenge to breeders. The additive main effects and multiplicative interaction (AMMI) model is a widely used tool for the analysis of multiple-environment trials, where the data are represented by a two-way table of G × E means. For complete tables, least squares estimation for the AMMI model is equivalent to fitting an additive two-way ANOVA model for the main effects and applying a singular value decomposition to the interaction residuals, thereby implicitly assuming equal weights for all G × E means. However, multiple-environment data with strong GEI are often also characterized by strong heterogeneous error variation. To improve the performance of the AMMI model in the latter situation, we introduce a generalized estimation scheme, the weighted AMMI or W-AMMI algorithm. This algorithm is useful for studying GEI and QEI. For QEI, the W-AMMI algorithm can be used to create predicted values per environment that are subjected to QTL analysis. We compare the performance of this combined W-AMMI and QTL mapping strategy to direct QTL mapping on G × E means and to QTL mapping on AMMI-predicted values, again with QTL analyses for individual environments. Finally, we compare the W-AMMI QTL mapping strategy, with a multi-environment mixed model QTL mapping approach. Two data sets are used: (i) data from a simulated pepper (Capsicum annuum L.) back cross population using a crop growth model to relate genotypes to phenotypes in a nonlinear way, and (ii) the doubled-haploid Steptoe × Morex barley (Hordeum vulgare L.) population. The QTL analyses on the W-AMMI-predicted values outperformed the QTL analyses on the G × E means and on the AMMI-predicted values, and were very similar to the mixed model QTL mapping approach with regard to the number and location of the true positive QTLs detected, especially for QTLs associated with the interaction and for environments with higher error variance. W-AMMI analysis for GEI and QEI provides an easy-to-use and robust tool with wide applicability.
Studies of Natural Populations of Mus. vi. Sizes of Populations Inhabiting Corn Cribs in Southwestern Ontario

Theoretical studies concerned with genetic variability in natural populations have generally considered genetically effective population sizes ( N e ) of 104 or greater. This study shows that N e in some highly polymorphic populations such as those of the house mouse, Mus musculus , may be considerably smaller. The mouse populations considered inhabit corn cribs in southwestern Ontario and are polymorphic at a number of loci. They are ideal for this work because the entire population can be collected over a short period of time, and because the various cribs provide replicas of the same general microhabitat. The mean population sizes were 14.4 and 54.4 in the winter and summer, respectively. No correlation was observed between population size and crib size. N e , based on the mean numbers of mice observed in the winter and summer collections and the assumption that all mice are reproductively active, was approximately 20. This could be as high as 70 in some populations and as low as 10 in others. To determine factors that might affect population size, data were collected on 16 environmental variables. Stepwise multiple regression analysis indicated that four environmental variables, compass orientation of a crib ( P < 0.001), number of predators ( P < 0.01), distance from an east-west line ( P < 0.01), and distance from a north-south line ( P < 0.05) were significantly associated with population size. Based on the male:female ratio in the summer populations, only one crib appeared to be fully utilized by the mice. In this exception, a crib with a high population density, a deficiency of males suggested competition for territory.