Miracle-dz/UniFAR-FTUs huggingface dataset:
A Deep Learning Approach to Network Intrusion Detection Using Deep Autoencoder

The security of computer networks is critical for network intrusion detection systems (NIDS). However, concerns exist about the suitability and sustainable development of current approaches in light of modern networks. Such concerns are particularly related to increasing levels of human interaction required and decreased detection accuracy. These concerns are also highlighted. This post presents a modern intrusion prevention deep learning methodology. For unattended function instruction, we clarify our proposed Symmetric Deep Autoencoder (SDAE). Also, we are proposing our latest deep research classification model developed with stacked SDAEs. The classification proposed by the Network Security Laboratory-Knowledge Discovery in Databases (NSL-KDD) and Canadian Institute for Cybersecurity -Intrusion Detection System (CICIDS 2017) data sets was implemented in Tensor Flow, a Graphics Procedure Unit (GPU) enabled and evaluated. We implemented and tested our experiment with different batch sizes using Adam optimizer. Promising findings from our model have been achieved so far, which demonstrates improvements over current solutions and the subsequent improvement for use in advanced NIDS.
proposta metodológica para o estudo da sincronização da fala em interação com a semântica

This work presents a methodological proposal to make viable the observation of synchronized speech and its relations with the semantic level of a sentence uttered when two people read out loud the same text. We will present the theoretical and methodological basis for the preliminary study. The central question of this study refers to the interaction between a physical and concrete level of language, the speech, and a higher and abstract level, the semantics, formulated as: to what extent the task of synchronized speech can be interfered by the violation of semantic expectancy? Synchronized speech is characterized as a type of speech where two people read the same text at the same time, which is easily and rapidly achieved. The violation of semantic expectancy refers to words that occurs out of context and, therefore, can be found odd in relation to the meaning of the sentence or text. In this preliminary study, we used two types of texts (narrative and expository) and two experimental conditions (original and altered), generating five different texts. We bring here the results of one pair of speakers. We didn’t observe any significative differences between the experimental conditions; however, we highlight the difference, in gross values, between the versions of the narrative text. This preliminary and exploratory study has allowed, on one hand, to corroborate the idea that speakers synchronize very well, due to the entrainment and interaction between them, and on the other hand, to indicate the next steps to be taken regarding the methodology.
Metabolic modulation predicts heart failure tests performance

Cardiopulmonary testing (CPET) and biomarkers such as NT-proBNP, Galectin-3, and C-reactive protein (CRP) have shown great promise for characterizing the heart failure (HF) phenotypes. However, the underlying metabolic changes that cause, predict and accompany changes in these parameters are not well known. In depth knowledge of these metabolic changes has the ability to provide new insights towards the clinical management of HF as well as providing better biomarkers for the assessment of disease progression and measurement of success from clinical interventions. To address this knowledge gap, we undertook a deep metabolomic and lipidomic phenotyping of a cohort of HF patients and utilized Multiple Regression Analysis (MRA) to identify associations between the patient’s plasma metabolome and the lipidome to parameters of CPET and the above mentioned HF biomarkers (HFBio). A total of 49 subjects were submitted to CPET and HFBio evaluation with deep metabolomic and lipidomic profiling of the plasma. Stepwise MRA and Standard Least Squares methods were used to determine models of best fit. Metabolic Pathway Analysis was utilized to detect what metabolites were over-represented and significantly enriched, and Metabolite Set Enrichment Analysis was used to explore preexisting biological knowledge from studies of human metabolism. The study cohort was predominantly males of African American decent, presenting a high frequency of diabetes, hyperlipidemia, and hypertension with a low mean left ventricular ejection fraction and a high left ventricular end-diastolic and end-systolic volume. VE/VCO2 and Peak VO2 (CV=0.07 and 0.08, respectively) showed the best metabolic predictive model for test performance, while CRP and NT-ProBNP (CV=0.31 and 0.29, respectively) were the least fitted models. Aminoacyl-tRNA and amino acid biosynthesis, amino acid metabolism, nitrogen metabolism, pantothenate and CoA biosynthesis, sphingolipid and glycerolipid metabolism, fatty acid biosynthesis, glutathione metabolism, and pentose phosphate pathway (PPP) were revealed to be the most relevant pathways. Principal related diseases were brain dysfunction and enzyme deficiencies associated with lactic acidosis. Considering the modulations in HF poor test performance, our results indicate an overall profile of oxidative stress, lactic acidosis, and metabolic syndrome coupled with mitochondria dysfunction. Overall, the insights resulting from this study’s MRA coincides with what has previously been discussed in parts in existing literature thereby confirming the validity of our findings while at the same time thoroughly characterizing the metabolic underpinning of CPET and HFBio results.
Bike-sharing: the good, the bad, and the future

Due to the dilemma of bike-sharing concerning its benefits and drawbacks, and its unclear future, we focused on a mixed-methods approach to analyze this public discussion through posts or “tweets” from the social media channel Twitter. We collected around 12,000 tweets in English around the world related to bike-sharing for a period of about six months. We considered two approaches, including topic clustering and sentiment analysis in tweets including: a) bike-sharing related terms and b) “future” and bike-sharing related terms. Strongly positive tweets promote bike-sharing and its benefits such as being convenient, well-performing, and sustainable. Additionally, there is a tendency to write that public, electric, and dockless are better, together with scooters. In contrast, the complaints on bike-sharing focused on inequity, rentals and safety issues, critique on authorities and laws, and poor performance especially of dockless Asian bike-sharing start-ups with low-quality bikes. Around 50% of the tweets that included the terms “future” and “bike–sharing” stated that bike-sharing is going to be part of the future of mobility as an electric dockless version together with other shared modes. The hesitant statements towards bike-sharing being part of the future referred mainly to the systems with poor bikes’ quality. Politicians and stakeholders can use this information to enhance bike-sharing or consider the implementation of certain types of bike-sharing in their cities. To the best of the authors’ knowledge, this study would be one of the first that analysis the public discussion on social media about a transportation system and its future using a mixed-methods approach. Future studies should aim at identifying and comparing the public opinion of different emerging transportation technologies.
ROV vs trawling approaches in the study of benthic communities: the case of Pennatula rubra (Cnidaria: Pennatulacea)

Megabenthic soft bottom communities of trawlable grounds have been studied since the first few decades of the last century, thanks to trawl fishing technologies. Despite providing an extensive amount of presence data, trawling cannot be considered reliable from a quantitative point of view, frequently giving only weak information about sessile species density, large and small-scale distribution and main habitat features. The recent development of visual technologies on remotely operated vehicles (ROVs) can give a more accurate approach for the study of mega-epibenthic communities. The present study reports the application of both ROV imaging and trawling approaches for the study of a large aggregation (i.e. field) of the red sea pen Pennatula rubra in the Ionian Sea. Density, biomass and population structure were studied in the same population of P. rubra. The density assessed by ROV was significantly higher than that estimated with a three-year series of trawling surveys. Trawling gear efficiency in the removal of P. rubra was low overall. Incidental mortality can be very high due to damage to those specimens that encounter the trawl net but are not directly captured. However, sampling of several colonies by trawling was necessary to establish biometric correlations to estimates of size and biomass from ROV imaging. Trawling catch abundance/biomass data could be useful to identify areas of higher concentration of sea pens, while ROV imaging can be used to monitor these fields in a non-destructive manner that would be consistent with protection measures.
University of Birmingham Understanding visual attention with RAGNAROC

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On the importance of fine‐scale sampling in detecting alpha taxonomic diversity among saproxylic invertebrates: A velvet worm (Onychophora: Opisthopatus amaxhosa) template

The phylogeography and social structure of the narrow endemic velvet worm species Opisthopatus amaxhosa were investigated by conducting fine‐scale sampling in its distribution range in the Eastern Cape province of South Africa. In addition, and as part of larger grant on forest biodiversity, Opisthopatus specimens sampled at localities not included during a recent evaluation of the genus were included in a new phylogeny. A total of 89 specimens from 18 sample localities were collected at three forest patches for O. amaxhosa samples, while an additional six Opisthopatus sample localities were included. For O. amaxhosa, we sequenced the COI locus for all specimens, while a subset of specimens was sequenced for two nuclear loci, 18S rRNA and the fushi tarazu intron (FTz). Phylogenetic analyses using maximum likelihood and Bayesian inferences of the latter species revealed the presence of two highly divergent clades, characterised by marked uncorrected sequence divergence values. In addition, these two clades did not share any maternal haplotypes, were characterised by high FST values and fixed nuclear difference for the 18S rRNA locus, while the FTz intron was genetically invariant. Furthermore, the application of scanning electron microscopy between the two genetically divergent clades also revealed the presence of fixed ventral and dorsal scale numbers. Collectively, this provides evidence for a novel species that is present at a fine scale. Divergence time estimations suggest that the two clades diverged during the late and early Pleistocene with climatic cycling potentially causal to the fragmentation. The social structure was male‐biased, and samples from the same logs were not always genetically identical. At the broader scale, the inclusion of new specimens within Opisthopatus revealed no novel lineages. Fine‐scale sampling appears more important to detect alpha taxonomic diversity compared to broadscale sampling.
Meiotic viral attenuation through an ancestral apoptotic pathway

Significance A hypothesis for the paradoxical evolution of programmed cell death posits that suicide mechanisms were co-opted from processes that were originally pro-survival. Here we show that meiotically programmed mitochondrial release of the Endonuclease G (EndoG) homolog Nuc1 occurs during sporulation in budding yeast. While EndoG release is implicated in animal cell apoptotic death, we find that Nuc1 release is pro-survival, protecting spores from the detrimental consequences of unrestrained viral expression. The programmed release of apoptogenic proteins from mitochondria is a core event of apoptosis, although ancestral roles of this phenomenon are not known. In mammals, one such apoptogenic protein is Endonuclease G (EndoG), a conserved mitochondrial nuclease that fragments the DNA of dying cells. In this work, we show that budding yeast executes meiotically programmed mitochondrial release of an EndoG homolog, Nuc1, during sporulation. In contrast to EndoG’s ostensible pro-death function during apoptosis, Nuc1 mitochondrial release is pro-survival, attenuating the cytosolic L-A and Killer double-stranded RNA mycoviruses and protecting meiotic progeny from the catastrophic consequences of their derepression. The protective viral attenuation role of this pathway illuminates a primordial role for mitochondrial release of EndoG, and perhaps of apoptosis itself.
Pertumbuhan dan Hasil Gandum pada Berbagai Kerapatan Populasi dan Dosis Pemupukan Urea

Efforts to produce wheat in Indonesia need to be supported by the availability of cultivation technology suitable for agro-climate conditions in Indonesia, including the use of proper population density and fertilization dosages, which are fundamental for obtaining maximum yields. This study was aimed to determine ideal population density and dosage of urea for optimum grain yield of wheat in Lombok Island. The experiment carried out at Aik Bukak, Central Lombok at elevation of 400 m asl, to observe the growth and yield of two varieties of wheat, Nias and Gladius, with 4 plant population densities (133, 160, 200, and 250 plants m-2) and 3 dosages of urea fertilization, 200, 300, and 400 kg ha-1. Data from this study indicated that Lombok Island has the potential for growing wheat with quite dense population density of 250 plants m-2. This density yielded higher, 1.74 tons ha-2, due to the increased number of kernel per unit area without reducing individual kernel weight. The use of urea 300 kg ha-1 exhibited the best growth and yielded 1.32 tons ha-2.Keywords: fertilization, population density, wheat varieties
Simulation Studies of Cyanide-Caused Cardiac Toxicity

Abstract : A series of computer studies showing the effect of cyanide (CN) on the electrophysiology of cardiac tissue is presented. A mathematical model of the electrophysiology of cardiac tissue, with initial and boundary conditions based on experimental data from studies using CN as metabolic blockers from the literature, was used to simulate changes in the electrical activity of the heart. Emphasis was on the modulation of ion concentrations in the cells, changes in current magnitudes, and the activation of currents that are dormant under normal circumstances. These calculations showed for the first time: (1) disturbance of the energy homeostasis and ion concentrations in cardiac tissue due to CN results in the reversal of the direction from the normal and change in magnitudes of cellular membrane currents. These, in turn, change the morphology of the action potential and the electrocardiogram (ECG). This is the initial step leading to ventricular fibrillation, the usual endpoint in the effect of CN on the heart. (2) CN causes cell swelling and hemorrhaging in cardiac tissue. Cell swelling activates chloride membrane currents affecting homeostasis of the tissue. These effects were shown to be important for the electrical state of the CN-affected tissue and were included for the first time in a model of CN-affected cardiac tissue. (3) The calculations reproduced aspects of the changes in an ECG of a subject under the effect of a lethal dose of CN. (4) The obtained results suggest and define the characteristics required of a pharmacological intervention needed to overcome or reverse CN poisoning, of vital importance for development of therapeutics for force protection. Primarily, such intervention needs to reduce the calcium overload of the cardiac cell, restore the depolarizing sodium current, and alleviate the accumulation of potassium ions exterior to the cell.
Geometrically Driven Underground Camera Modeling and Calibration With Coplanarity Constraints for a Boom-Type Roadheader

The conventional calibration methods based on a perspective camera model are not suitable for the underground camera with two-layer glasses, which is specially designed for explosion proof and dust removal in a coal mine. Underground camera modeling and calibration algorithms are urgently needed to improve the precision and reliability of underground visual measurement systems. This article presents a novel geometrically driven underground camera calibration algorithm for a boom-type roadheader. The underground camera model is established under coplanarity constraints, considering explicitly the impact of refraction triggered by the two-layer glasses and deriving the geometrical relationship of equivalent collinearity equations. On this basis, we perform parameters calibration based on a geometrically driven calibration model, which are 2D–2D correspondences between the image points and object coordinates of the planar target. A hybrid Levenberg–Marqurdt (LM) and particle swarm optimization (PSO) algorithm is further proposed in terms of the dynamic combination of the LM and PSO, which optimizes the underground camera calibration results by minimizing the error of the nonlinear underground camera model. The experimental results demonstrate that the pose errors caused by the two-layer glass refraction are well corrected by the proposed method. The accuracy of the cutting-head pose estimation has increased by 55.73%, meeting the requirements of underground excavations.
Throughput Analysis of NOMA-ALOHA

This paper considers from the perspective of MAC layer, a throughput maximization problem of NOMA-ALOHA, ALOHA implemented over NOMA (non-orthogonal multiple access), that can decode simultaneously transmitted multiple packets via successive interference cancellation (SIC) if each of the multiple packets has a different power level from those of others. We start with a throughput optimization problem for two power levels and extend it to a problem for a general number of power levels. For the case of two power levels, we find upper and lower bounds of the maximum throughput and suggest a practical sub-optimal transmission probability whose throughput is close to the maximum. The maximum throughput of NOMA-ALOHA is at least 1.774 times higher than that of traditional slotted ALOHA in our numerical example. We extend the optimization problem into a general one with arbitrary number of power levels. We numerically analyze the performance through a relaxed problem of the original one with high complexity. Our numerical analysis shows that the maximum throughput of NOMA-ALOHA with three power levels is 2.33 times higher than simple ALOHA’s maximum throughput and that adding one power level to NOMA-ALOHA with two power levels enhances throughput at least by more than 28 percent.
Hematopoiesis of a Healthy Supercentenarian is Dominated by One Myeloid-Biased Stem Cell Clone for at least 9 Years

SUMMARY Background : The number of Hematopoietic Stem Cell (HSC) clones that actively contribute to human hematopoiesis and the dynamics of those clones are matters of debate. Methods : We investigated the somatic mutation load of the peripheral blood cells of a healthy female supercentenarian over the course of nine years and inferred the HSC clonal architecture by clustering these mutations based on their Variant Allele Frequencies (VAFs). We also assessed the presence of these mutations in lymphoid and myeloid cells sorted with Fluorescence-Activated Cell Sorting (FACS). Results : We detected 912 putative somatic blood mutations with deep whole genome sequencing and validated 307 of these putative somatic mutations to be true somatic mutations with amplicon sequencing. All 307 confirmed mutations were present in her peripheral blood for at least nine years, and they could be detected in all FACS-sorted immune cell types. Subclonal analysis suggested that the mutations represent one clone of HSCs with 4 subclones, which in total populated almost 70% of the peripheral blood cell compartment. The VAFs in the different cell types indicated that this clone generated almost 90% of the myeloid cells and only 8% of the B cells and 11% of the T cells. Conclusion : Our findings suggest that one HSC clone and its subclones dominated the white blood cell production of this supercentenarian during at least nine years. This clone and its subclones were stable over time and myeloid-biased.
Empirically-Derived Synthetic Populations to Overcome Small Sample Sizes

Overfitting is a problem often encountered when developing multivariate predictive models with limited data. The objective of this work is to present a method to generate a synthetic population (SP) from a sparse seed dataset that has a similar multivariate structure to aid in model building. We used a multivariate kernel density estimation approach with an unconstrained bandwidth to generate SPs with data at the individual level. A matched case-control study (n=180 pairs) was used as the seed dataset. Cases and controls were considered as two subpopulations and analyzed separately. We included four continuous measures and one categorical variable for each subject. Bandwidth matrices were determined with differential evolution (DE) optimization based on covariance comparisons. Similarity between the seed dataset with datasets selected randomly from SPs were compared under the hypothesis that the structure should be similar. To evaluate similarity, we compared PCA score distributions and residuals summarized with the distance to the model in X-space (DModX). SPs were generated for both case and control groups. The probability of selecting seed replicas when constructing synthetic sample datasets randomly was minute. Within group, both PCA scores and residuals were similar across seed and synthetic samples; covariance comparisons also indicated the structure was similar. Feasibility of a new SP generation methodology was presented. This approach produced synthetic data at the patient level indistinguishable from the seed data. The methodology coupled kernel density estimation with DE optimization and deployed novel similarity metrics derived from PCA. The use of synthetic samples may be useful to mitigate overfitting in initial model building exercises. To further develop this approach into a research tool for model building, additional evaluation with increased dimensionality is required.