Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical study of correlations in the fitness landscapes of combinatorial optimization problems

One of the most common problem-solving heuristics is by analogy. For a given problem, a solver can be viewed as a strategic walk on its fitness landscape. Thus if a solver works for one problem, it is anticipated that it will be effective for problems within the same category whose fitness landscapes essentially share structural similarity with each other. However, due to the black-box nature, it is far from trivial to infer such similarity in real-world scenarios. To bridge this gap, this paper proposes two alternative approaches to empirically investigate the potential existence of structural similarity among different fitness landscapes. Specifically, we pick up three classic combinatorial optimization problems to constitute the benchmark set. We apply a local optima network construction routine to build a coarse-grained model to represent the fitness landscapes of different problems at various dimensions. Thereafter, we apply a graph embedding method, to empirically investigate the potential existence of correlations with respect to different local optima networks. From our empirical results, we are exciting to find some evidence of the existence of similarity not only for a given problem with various dimensions but also across different problems.
Combining clustering and classification algorithms for automatic bot detection: a case study on posts about COVID-19

In the last decade, there has been a great insertion of bots in several social media. Among the potentially harmful effects of these software agents, there are: the spread of computer viruses and different internet scams, and the spread of fake news, with emphasis on political-electoral and public health-related news. This work presents a new approach for bots’ detection on Twitter, combining the use of feature selection, clustering, and classification algorithms. The proposed approach was compared with more conventional ones (for example, without the use of clustering) and the premise used in this work proved to be true: the use of clustering, together with the features selection, allowed the production of better classification models in order to identify not only the bots who have an activity profile considered non-human (extremely active on Twitter) but also other bots whose profiles are more similar to humans’ ones. The best results of automatic detection of bots reached an overall accuracy of 96.8% and F1 score equal to 0.622. As an additional advantage, these values were achieved by decision-tree models, which can be considered explainable artificial intelligence models.
Predicting soft robot's locomotion fitness

Organisms with different body morphology and movement dynamics have distinct abilities to move through the environment. Despite such truism, there is a lack of general principles that predict which shapes and dynamics make the organisms more fit to move. Studying a minimal yet embodied soft robot model under the influence of gravity, we find three features that predict robot locomotion fitness: (1) A larger body is better. (2) Two-point contact with the ground is better than one-point contact. (3) Out-of-phase oscillating body parts increase locomotion fitness. These design principles can guide the selection rules for evolutionary algorithms to obtain robots with higher locomotion fitness.
Automatic Story Generation

Computational generation of stories is a subfield of computational creativity where artificial intelligence and psychology intersect to teach computers how to mimic humans’ creativity. It helps generate many stories with minimum effort and customize the stories for the users’ education and entertainment needs. Although the automatic generation of stories started to receive attention many decades ago, advances in this field to date are less than expected and suffer from many limitations. This survey presents an extensive study of research in the area of non-interactive textual story generation, as well as covering resources, corpora, and evaluation methods that have been used in those studies. It also shed light on factors of story interestingness.
Selecting between evolutionary and classical algorithms for the CVRP using machine learning: optimization of vehicle routing problems

Solutions for NP-hard problems are often obtained using heuristics that yield results relatively quickly, at some cost to the objective. Many different heuristics are usually available for the same problem type, and the solution quality of a heuristic may depend on characteristics of the instance being solved. This paper explores the use of machine learning to predict the best heuristic for solving Capacitated Vehicle Routing Problems (CVRPs). A set of 23 features related to the CVRP were identified from the literature. A large set of CVRP instances were generated across the feature space, and solved using four heuristics including a genetic algorithm and a novel self-organizing map. A neural network was trained to predict the best performing heuristic for a given problem instance. The model correctly selected the best heuristic for 79% of the CVRP test instances, while the single best heuristic was dominant for only 50% of the test instances.
Direct numerical simulation of a supercritical hydrothermal flame in a turbulent jet

Abstract The aim of this study is to establish a fundamental understanding of the flame structure and autoignition characteristics of supercritical hydrothermal flames in three-dimensional shear-driven turbulence. The study involves direct numerical simulation of a non-premixed flame (with fuel comprising a mixture of 10 % $\textrm {H}_2$ and 90 % $\textrm {H}_2\textrm {O}$ in terms of mole fraction) at 25.0 MPa in a slot jet; detailed reaction mechanism and multispecies real-fluid properties are considered in the simulation. Qualitative transient inspection revealed that the flame undergoes a three-stage development process in the streamwise direction: sparse autoignition kernels in the upstream region, intense ignitions and establishment of a continuous flame surface in the middle region, and massive flamelets in the downstream region. Ignition kernels primarily form in the interior of large-scale shear-driven vortices featuring a low scalar dissipation rate. Probability density function (p.d.f.) analysis further confirmed that these kernels mainly form in the premixed combustion mode and on the fuel-lean side, in contrast to the authors’ previous findings concerning autoignition in a two-dimensional mixing layer. Analysis of the preignition chemistry indicator (i.e. $\textrm {H}_2\textrm {O}_{2}$ radicals) revealed that although the fuel-rich condition has a shorter homogeneous autoignition delay time, it does not exhibit any remarkable preignition chemistry or intense heat release in the upstream or middle regions because of its large-scale flow structure. A volume rendering of the dimensionless Damköhler number ($Da$) reveals the distribution of autoignition spots and propagating flames. The joint p.d. f. of the mixture fraction and $Da$ reveals the transition from sparse ignition to intense ignition and, finally, to flame propagation.
A Distributed Network for Multimodal Experiential Representation of Concepts

Neuroimaging, neuropsychological, and psychophysical evidence indicate that concept retrieval selectively engages specific sensory and motor brain systems involved in the acquisition of the retrieved concept. However, it remains unclear which supramodal cortical regions contribute to this process and what kind of information they represent. Here, we used representational similarity analysis of two large fMRI datasets with a searchlight approach to generate a detailed map of human brain regions where the semantic similarity structure across individual lexical concepts can be reliably detected. We hypothesized that heteromodal cortical areas typically associated with the default mode network encode multimodal experiential information about concepts, consistent with their proposed role as cortical integration hubs. In two studies involving different sets of concepts and different participants (both sexes), we found a distributed, bihemispheric network engaged in concept representation, composed of high-level association areas in the anterior, lateral, and ventral temporal lobe; inferior parietal lobule; posterior cingulate gyrus and precuneus; and medial, dorsal, ventrolateral, and orbital prefrontal cortex. In both studies, a multimodal model combining sensory, motor, affective, and other types of experiential information explained significant variance in the neural similarity structure observed in these regions that was not explained by unimodal experiential models or by distributional semantics (i.e., word2vec similarity). These results indicate that during concept retrieval, lexical concepts are represented across a vast expanse of high-level cortical regions, especially in the areas that make up the default mode network, and that these regions encode multimodal experiential information. SIGNIFICANCE STATEMENT Conceptual knowledge includes information acquired through various modalities of experience, such as visual, auditory, tactile, and emotional information. We investigated which brain regions encode mental representations that combine information from multiple modalities when participants think about the meaning of a word. We found that such representations are encoded across a widely distributed network of cortical areas in both hemispheres, including temporal, parietal, limbic, and prefrontal association areas. Several areas not traditionally associated with semantic cognition were also implicated. Our results indicate that the retrieval of conceptual knowledge during word comprehension relies on a much larger portion of the cerebral cortex than previously thought and that multimodal experiential information is represented throughout the entire network.
Downregulation of WT1 transcription factor gene expression is required to promote myocardial fate

During cardiac development, cells from the precardiac mesoderm fuse to form the primordial heart tube, which then grows by addition of further progenitors to the venous and arterial poles. In the zebrafish, wilms tumor 1 transcription factor a (wt1a) and b (wt1b) are expressed in the pericardial mesoderm at the venous pole of the forming heart tube. The pericardial mesoderm forms a single layered mesothelial sheet that contributes to further the growth of the myocardium, and forms the proepicardium. Proepicardial cells are subsequently transferred to the myocardial surface and give rise to the epicardium, the outer layer covering the myocardium in the adult heart. wt1a/b expression is downregulated during the transition from pericardium to myocardium, but remains high in proepicardial cells. Here we show that sustained wt1 expression impaired cardiomyocyte maturation including sarcomere assembly, ultimately affecting heart morphology and cardiac function. ATAC-seq data analysis of cardiomyocytes overexpressing wt1 revealed that chromatin regions associated with myocardial differentiation genes remain closed upon wt1b overexpression in cardiomyocytes, suggesting that wt1 represses a myocardial differentiation program. Indeed, a subset of wt1a/b-expressing cardiomyocytes changed their cell adhesion properties, delaminated from the myocardial epithelium, and upregulated the expression of epicardial genes, as confirmed by in vivo imaging. Thus, we conclude that wt1 acts as a break for cardiomyocyte differentiation by repressing chromatin opening at specific genomic loci and that sustained ectopic expression of wt1 in cardiomyocytes can lead to their transformation into epicardial cells.
A Newcastle disease virus-vector expressing a prefusion-stabilized spike protein of SARS-CoV-2 induces protective immune responses against prototype virus and variants of concern in mice and hamsters

Rapid development of coronavirus disease 2019 (COVID-19) vaccines and expedited authorization for use and approval has been proven beneficial to mitigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread and given hope in this desperate situation. It is believed that sufficient supplies and equitable allocations of vaccines are necessary to limit the global impact of the COVID-19 pandemic and the emergence of additional variants of concern. We have developed a COVID-19 vaccine based on Newcastle disease virus (NDV) that can be manufactured at high yields in embryonated eggs. Here we provide evidence that the NDV vector expressing an optimized spike antigen (NDV-HXP-S), upgraded from our previous construct, is a versatile vaccine that can be used live or inactivated to induce strong antibody responses and to also cross-neutralize variants of concern. The immunity conferred by NDV-HXP-S effectively counteracts SARS-CoV-2 infection in mice and hamsters. It is noteworthy that vaccine lots produced by existing egg-based influenza virus vaccine manufacturers in Vietnam, Thailand and Brazil exhibited excellent immunogenicity and efficacy in hamsters, demonstrating that NDV-HXP-S vaccines can be quickly produced at large-scale to meet global demands.
Algorithms for the discovery of cis-eQTL signals in woody species: the vine (Vitis vinifera L.) as a study model

Expression quantitative trait loci (eQTLs), are associations between genetic variants, such as Single Nucleotide Polymorphisms (SNPs), and gene expression. eQTLs are an important tool to understand the genetics of gene expression of complex phenotypes. eQTLs analysis are common in human studies and in model species such as mice, rats and yeast but are very scarce in wood crop species such as fruit trees or grapevines. In this study a comprehensive bioinformatic pipeline has been carried out using genomics and expression data from 10 genotypes of grape, which has been used as model species. As a result of this study a total of 10,618 genetic variants that regulate gene expression levels of 525 genes were detected. A 78% of them, 411, received a functional annotation from UniProtKB or DAVID, between the annotated protein-coding genes are Germin-like proteins (GLPs), auxin-regulatory factors, GRFS, ANK_REP_REGION domain-containing protein, Kinesin motor domain-containing protein or RPP13like protein 2(LOC100852873). This new inventory of cis eQTLs influencing gene expression during the ripening of fruits of Vitis vinifera L. will be an important resource for future research to understand the mechanistic basis for variation in gene regulation in this species. In the future, this methodology may be applied to other woody species, once the necessary databases are generated.
SARS-CoV-2 genome sequencing with Oxford Nanopore Technology and Rapid PCR Barcoding in Bolivia

SARS-CoV-2 genomic surveillance has Illumina technology as the golden standard. However, Oxford Nanopore Technology (ONT) provides significant improvements in accessibility, turnaround time and portability. Characteristics that gives developing countries the opportunity to perform genome surveillance. The most used protocol to sequence SARS-CoV-2 with ONT is an amplicon-sequencing protocol provided by the ARTIC Network which requires DNA ligation. Ligation reagents can be difficult to obtain in countries like Bolivia. Thus, here we provide an alternative for library preparation using the rapid PCR barcoding kit (ONT). We mapped more than 3.9 million sequence reads that allowed us to sequence twelve SARS-CoV-2 genomes from three different Bolivian cities. The average sequencing depth was 324X and the average genome length was 29527 bp. Thus, we could cover in average a 98,7% of the reference genome. The twelve genomes were successfully assigned to four different nextstrain clades (20A, 20B, 20E and 20G) and we could observe two main lineages of SARS-CoV-2 circulating in Bolivia. Therefore, this alternative library preparation for SARS-CoV-2 genome sequencing is effective to identify SARS-CoV-2 variants with high accuracy and without the need of DNA ligation. Hence, providing another tool to perform SARS-CoV-2 genome surveillance in developing countries.
TAF8 regions important for TFIID lobe B assembly, or for TAF2 interactions, are required for embryonic stem cell survival

The human general transcription factor TFIID is composed of the TATA-binding protein (TBP) and 13 TBP-associated factors (TAFs). In eukaryotic cells, TFIID is thought to nucleate RNA polymerase II (Pol II) preinitiation complex formation on all protein coding gene promoters and thus, be crucial for Pol II transcription. TFIID is composed of three lobes, named A, B and C. Structural studies showed that TAF8 forms a histone fold pair with TAF10 in lobe B and participates in connecting lobe B to lobe C. In the present study, we have investigated the requirement of the different regions of TAF8 for in vitro TFIID assembly, and the importance of certain TAF8 regions for mouse embryonic stem cell (ESC) viability. We have identified a TAF8 region, different from the histone fold domain of TAF8, important for assembling with the 5TAF core complex in lobe B, and four regions of TAF8 each individually required for interacting with TAF2 in lobe C. Moreover, we show that the 5TAF coreinteracting TAF8 domain, and the proline rich domain of TAF8 that interacts with TAF2, are both required for mouse embryonic stem cell survival. Thus, our study demonstrates that distinct TAF8 regions involved in connecting lobe B to lobe C are crucial for TFIID function and consequent ESC survival.
Evolutionary History of DNA Methylation Related Genes in Bivalvia: New Insights From Mytilus galloprovincialis

DNA methylation is an essential epigenetic mechanism influencing gene expression in all organisms. In metazoans, the pattern of DNA methylation changes during embryogenesis and adult life. Consequently, differentiated cells develop a stable and unique DNA methylation pattern that finely regulates mRNA transcription during development and determines tissue-specific gene expression. Currently, DNA methylation remains poorly investigated in mollusks and completely unexplored in Mytilus galloprovincialis. To shed light on this process in this ecologically and economically important bivalve, we screened its genome, detecting sequences homologous to DNA methyltransferases (DNMTs), methyl-CpG-binding domain (MBD) proteins and Ten-eleven translocation methylcytosine dioxygenase (TET) previously described in other organisms. We characterized the gene architecture and protein domains of the mussel sequences and studied their phylogenetic relationships with the ortholog sequences from other bivalve species. We then comparatively investigated their expression levels across different adult tissues in mussel and other bivalves, using previously published transcriptome datasets. This study provides the first insights on DNA methylation regulators in M. galloprovincialis, which may provide fundamental information to better understand the complex role played by this mechanism in regulating genome activity in bivalves.
Open-Source Code-Based Tidal Modeling of Tropical and Temperate Waters

Tidal energy is the most reliable and predictable form of renewable energy capable of ensuring energy security in coastal regions of the world. Many developing countries are prone to energy self-sufficiency due to a lack of tidal data, expensive commercial tidal modeling tools, and program codes. In the present study, an open-source finite element code along with available open-source data was used to predict the tidal resource potential of sites in both temperate and coastal waters. This paper also investigates the suitability of open-source code towards accurate tidal resource prediction and provides a comparative study on tidal resource prediction of sites in both temperate and coastal waters. Based on knowledge gained from tidal experts all around the globe, the straits of the Alderney race were selected as a temperate water site because of their high tidal flow conditions and high tidal energy resource potential. Singapore was selected as a tropical water site because of its low tidal flow conditions and lack of open-source tidal resource data in the tropical belt. From the results, temperate waters such as Alderney Race experience high tidal velocity in the range of 3.5–4.5 m/s with an average power density of about 15 kW/m2 in comparison with tropical waters such as Singapore that experiences tidal velocity in the range of 1–1.5 m/s with an average power density of about 1.5 kW/m2. The thrusting force behind the coastal dynamics is mainly due to tides, their interactions, and changes in seabed topography. The seabed roughness profile creates a drag force on the flow on the velocity field. Lack of understanding of the effects of seabed friction on tidal modeling might reduce the accuracy of the model prediction. Thus, the present study also focuses on the effects of seabed roughness on tidal prediction of Alderney race straits using the open-source finite element-based 2-dimensional depth average ocean model. It can be found that an increase in seabed friction reduces the flow velocity and thus the average power density of the location due to its major energy dissipating phenomenon for the energetic ocean flow.
Efficacy, Safety and Tolerability of a New 10% Intravenous Immunoglobulin for the Treatment of Primary Immunodeficiencies

We report here the results of a phase 3 study to assess the efficacy, safety, and tolerability of GC5107, a new 10% liquid intravenous immunoglobulin (IVIG) in preventing serious bacterial infections in patients with primary immunodeficiency (ClinicalTrials.gov: NCT02783482). Over a 12-month study period, 49 patients aged 3 to 70 years with a confirmed diagnosis of primary immunodeficiency received GC5107 at doses ranging from 319 to 881 mg/kg body weight every 21 or 28 days, according to their previous IVIG maintenance therapy. A total of 667 infusions of GC5107 were administered comprising a total of 45.86 patient-years of treatment. A single acute serious bacterial infection occurred during the study, resulting in an incidence of 0.02 events per patient-year (upper 99% one-sided confidence interval limit: 0.21), meeting the prespecified primary efficacy endpoint. The mean incidence of infections other than acute serious bacterial infections was 2.9 infections per patient-year. Efficacy was also demonstrated by the low mean annualized rate of hospitalizations due to infection (0.1 day) and the mean annualized duration of hospitalizations (0.1 day). The mean rate of intravenous and oral antibiotic use was 0.1 day and 13.2 days, respectively. There was a mean of 7.1 days of missed work, school, or daycare days. The proportion of infusions with temporally associated adverse events (TAAEs) occurring during or within 72 hours after GC5107 infusion was 0.24 (upper 95% one-sided confidence interval limit: 0.31), meeting the pre-specified primary safety endpoint. Overall, 149 of 667 infusions (22%) were associated with TAAEs. The most common TAAE was headache, reported by 49% of patients. More than 98% (731/743) of all adverse events that occurred throughout the 12-month study period were mild or moderate. More than 98% of infusions were completed without discontinuation, interruption or rate reduction. There were no treatment-emergent serious adverse events related to GC5107 or study discontinuations due to an adverse event. Overall, pharmacokinetic parameters for GC5107 were within the range of those reported in studies of other marketed IVIG products. Results of the present study demonstrate that GC5107 is an effective, safe and well-tolerated treatment for patients with primary immunodeficiency.