Miracle-dz/UniFAR-FTUs huggingface dataset:
Attentional Control Theory in Childhood: Enhanced Attentional Capture by Non-Emotional and Emotional Distractors in Anxiety and Depression

Attentional control theory (ACT) proposes that anxiety is associated with executive functioning deficits. The theory has been widely investigated in adults. The current study tested whether symptoms of childhood anxiety and depression were associated with experimentally measured attentional control in the context of non-emotional and emotional stimuli. Sixty-one children (mean age = 9.23 years, range = 8.39–10.41) reported their trait anxiety and depression symptoms and completed three visual search tasks. The tasks used a variant of an irrelevant singleton paradigm and measured attentional capture by task-irrelevant non-emotional (color) and emotional (facial expressions) distractors. Significant attentional capture by both non-emotional and emotional distractors was observed, and was significantly correlated with trait anxiety and symptoms of depression. The strength of relationship between attentional capture and the symptoms did not differ significantly for non-emotional and emotional distractors. The results suggest that symptoms of childhood anxiety and depression are associated with poorer attentional control both in the presence of emotional and non-emotional stimuli, supporting ACT in younger populations. This attentional deficit in the context of non-emotional information might be as central to childhood internalizing symptoms as attentional biases often observed on tasks investigating processing of emotional stimuli.
Resting and exercise haemodynamics in relation to six‐minute walk test in patients with heart failure and preserved ejection fraction

Patients with heart failure and preserved ejection fraction (HFpEF) are characterized by functional impairment and an abnormal haemodynamic response to exercise. The six‐minute walk test (6MWT) serves as a standardized test for functional capacity quantification in heart failure patients, and is associated with cardiovascular outcomes. However, as the association between 6MWT and haemodynamic parameters during rest and exercise in HFpEF patients is unknown, we sought to elucidate this relationship.
Genome-Wide Identification, Phylogenetic and Expression Analyses of the Ubiquitin-Conjugating Enzyme Gene Family in Maize

Background Ubiquitination is a post-translation modification where ubiquitin is attached to a substrate. Ubiquitin-conjugating enzymes (E2s) play a major role in the ubiquitin transfer pathway, as well as a variety of functions in plant biological processes. To date, no genome-wide characterization of this gene family has been conducted in maize (Zea mays). Methodology/Principal Findings In the present study, a total of 75 putative ZmUBC genes have been identified and located in the maize genome. Phylogenetic analysis revealed that ZmUBC proteins could be divided into 15 subfamilies, which include 13 ubiquitin-conjugating enzymes (ZmE2s) and two independent ubiquitin-conjugating enzyme variant (UEV) groups. The predicted ZmUBC genes were distributed across 10 chromosomes at different densities. In addition, analysis of exon-intron junctions and sequence motifs in each candidate gene has revealed high levels of conservation within and between phylogenetic groups. Tissue expression analysis indicated that most ZmUBC genes were expressed in at least one of the tissues, indicating that these are involved in various physiological and developmental processes in maize. Moreover, expression profile analyses of ZmUBC genes under different stress treatments (4°C, 20% PEG6000, and 200 mM NaCl) and various expression patterns indicated that these may play crucial roles in the response of plants to stress. Conclusions Genome-wide identification, chromosome organization, gene structure, evolutionary and expression analyses of ZmUBC genes have facilitated in the characterization of this gene family, as well as determined its potential involvement in growth, development, and stress responses. This study provides valuable information for better understanding the classification and putative functions of the UBC-encoding genes of maize.
State-feedback ℋ∞ control for stochastic time-delay nonlinear systems with state and disturbance-dependent noise

This article focuses on the state-feedback ℋ∞ control problem for the stochastic nonlinear systems with state and disturbance-dependent noise and time-varying state delays. Based on the maxmin optimisation approach, both the delay-independent and the delay-dependent Hamilton–Jacobi-inequalities (HJIs) are developed for synthesising the state-feedback ℋ∞ controller for a general type of stochastic nonlinear systems. It is shown that the resulting control system achieves stochastic stability in probability and the prescribed disturbance attenuation level. For a class of stochastic affine nonlinear systems, the delay-independent as well as delay-dependent matrix-valued inequalities are proposed; the resulting control system satisfies global asymptotic stability in the mean-square sense and the required disturbance attenuation level. By modelling the nonlinearities as uncertainties in corresponding stochastic time-delay systems, the sufficient conditions in terms of a linear matrix inequality (LMI) and a bilinear matrix inequality (BMI) are derived to facilitate the design of the state-feedback ℋ∞ controller. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed methods.
Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

Surface albedo is one of the key controlling geophysical parameters in the surface energy budget studies, and its temporal and spatial variation is closely related to the global climate change and regional weather system due to the albedo feedback mechanism. As an efficient tool for monitoring the surfaces of the Earth, remote sensing is widely used for deriving long-term surface broadband albedo with various geostationary and polar-orbit satellite platforms in recent decades. Moreover, the algorithms for estimating surface broadband albedo from satellite observations, including narrow-to-broadband conversions, bidirectional reflectance distribution function (BRDF) angular modeling, direct-estimation algorithm and the algorithms for estimating albedo from geostationary satellite data, are developed and improved. In this paper, we present a comprehensive literature review on algorithms and products for mapping surface broadband albedo with satellite observations and provide a discussion of different algorithms and products in a historical perspective based on citation analysis of the published literature. This paper shows that the observation technologies and accuracy requirement of applications are important, and long-term, global fully-covered (including land, ocean, and sea-ice surfaces), gap-free, surface broadband albedo products with higher spatial and temporal resolution are required for climate change, surface energy budget, and hydrological studies.
Hybrid BFO and PSO Swarm Intelligence Approach for Biometric Feature Optimization

Nature-inspired novel swarm intelligence algorithms have gained more proliferation due to a variety of applications and uses in optimization of complex problems and selection of discriminatory sets of features to classify huge datasets during the past few decades. Feature selection is an efficient and useful pre-processing technique for solving classification problems in computer vision, data mining and pattern recognition. The major challenges of solving the feature selection problems lay in swarm intelligence algorithms which are capable of handling the vast number of feature sets from involved databases. In biometric based recognition systems, face recognition is a non-intrusive approach to identify individuals based on their discriminatory sets of facial feature vectors. In this paper, the authors tend to propose a unique novel hybrid based on Bacterial Foraging Optimization BFO and Particle swarm optimization PSO approach for the selection of best facial feature vectors that enhance the identification accuracy of the individual recognition because concerned facial info will contain useless and redundant face expression. The proposed hybrid approach mitigates irrelevant facial features in the feature space and selects the relevant set of features from the facial feature space. The proposed feature selection approach presents promising experimental results with respect to the number of facial feature subsets. The identification accuracies are superior to other approaches from the literature.
Desynchronization induced by time-varying network

The synchronous dynamics of an array of excitable oscillators, coupled via a generic graph, is studied. Non-homogeneous perturbations can grow and destroy synchrony, via a self-consistent instability which is solely instigated by the intrinsic network dynamics. By acting on the characteristic time-scale of the network modulation, one can make the examined system to behave as its (partially) averaged analogue. This result is formally obtained by proving an extended version of the averaging theorem, which allows for partial averages to be carried out. As a byproduct of the analysis, oscillation death is reported to follow the onset of the network-driven instability.
Correcting quantum channels by measuring the environment

The corrected capacity of a quantum channel is defined as the best one-shot capacity that can be obtained by measuring the environment and using the result to correct the output of the channel. It is shown that (i) all qubit channels have corrected capacity log 2, (ii) a product of N qubit channels has corrected capacity N log 2, and (iii) all channels have corrected capacity at least log 2. The question is posed of finding the channel with smallest corrected capacity in any dimension d.
Visual animal biometrics: survey

Visual animal biometrics is an emerging research discipline in computer vision, pattern recognition and cognitive science. It is a promising research field that encourages new development of quantified algorithms and methodologies for representing, detection of visible features, phenotypic appearances of species, individuals and recognition of morphological and animal biometric characteristics. Furthermore, it also assists the study of animal trajectory and behaviours analysis of species. Currently, real-world applications of visual animal biometric systems are gaining more proliferation due to a variety of applications and use, enhancement of quantity and quality of the collection of extensive ecological data and processing. However, to advance visual animal biometrics will require integration of methodologies among the scientific disciplines involved. Such valuable efforts will be worthwhile due to the enormous perspective of this approach rests with the formal abstraction of phenomics, to build well-developed interfaces between different organisational levels of life. This study provides a comprehensive survey of visual animal biometric systems and recognition approaches for various species and individual animal based on their morphological image pattern and biometric characteristics. This comprehensive review paper encourages the multidisciplinary researchers, scientists, biologists and different research communities to design the better platforms for the development of efficient algorithms and learning models to solve the massive data processing, classification and identification of different species related problems.
In Vivo Fate Imaging of Intracerebral Stem Cell Grafts in Mouse Brain

We generated transgenic human neural stem cells (hNSCs) stably expressing the reporter genes Luciferase for bioluminescence imaging (BLI) and GFP for fluorescence imaging, for multimodal imaging investigations. These transgenic hNSCs were further labeled with a clinically approved perfluoropolyether to perform parallel 19F MRI studies. In vitro validation demonstrated normal cell proliferation and differentiation of the transgenic and additionally labeled hNSCs, closely the same as the wild type cell line, making them suitable for in vivo application. Labeled and unlabeled transgenic hNSCs were implanted into the striatum of mouse brain. The time profile of their cell fate after intracerebral grafting was monitored during nine days following implantation with our multimodal imaging approach, assessing both functional and anatomical condition. The 19F MRI demarcated the graft location and permitted to estimate the cell number in the graft. BLI showed a pronounce cell loss during this monitoring period, indicated by the decrease of the viability signal. The in vivo obtained cell fate results were further validated and confirmed by immunohistochemistry. We could show that the surviving cells of the graft continued to differentiate into early neurons, while the severe cell loss could be explained by an inflammatory reaction to the graft, showing the graft being surrounded by activated microglia and macrophages. These results are different from earlier cell survival studies of our group where we had implanted the identical cells into the same mouse strain but in the cortex and not in the striatum. The cortical transplanted cells did not show any loss in viability but only pronounced and continuous neuronal differentiation.
Study of Malformin C, a Fungal Source Cyclic Pentapeptide, as an Anti-Cancer Drug

Malformin C, a fungal cyclic pentapeptide, has been claimed to have anti-cancer potential, but no in vivo study was available to substantiate this property. Therefore, we conducted in vitro and in vivo experiments to investigate its anti-cancer effects and toxicity. Our studies showed Malformin C inhibited Colon 38 and HCT 116 cell growth dose-dependently with an IC50 of 0.27±0. 07μM and 0.18±0. 023μM respectively. This inhibition was explicated by Malformin C’s effect on G2/M arrest. Moreover, we observed up-regulated expression of phospho-histone H2A.X, p53, cleaved CASPASE 3 and LC3 after Malformin C treatment, while the apoptosis assay indicated an increased population of necrotic and late apoptotic cells. In vivo, the pathological study exhibited the acute toxicity of Malformin C at lethal dosage in BDF1 mice might be caused by an acute yet subtle inflammatory response, consistent with elevated IL-6 in the plasma cytokine assay. Further anti-tumor and toxicity experiments proved that 0.3mg/kg injected weekly was the best therapeutic dosage of Malformin C in Colon 38 xenografted BDF1 mice, whereas 0.1mg/kg every other day showed no effect with higher resistance, and 0.9mg/kg per week either led to fatal toxicity in seven-week old mice or displayed no advantage over 0.3mg/kg group in nine-week old mice. Overall, we conclude that Malformin C arrests Colon 38 cells in G2/M phase and induces multiple forms of cell death through necrosis, apoptosis and autophagy. Malformin C has potent cell growth inhibition activity, but the therapeutic index is too low to be an anti-cancer drug.
RNA Sequencing Revealed Numerous Polyketide Synthase Genes in the Harmful Dinoflagellate Karenia mikimotoi

The dinoflagellate Karenia mikimotoi forms blooms in the coastal waters of temperate regions and occasionally causes massive fish and invertebrate mortality. This study aimed to elucidate the toxic effect of K. mikimotoi on marine organisms by using the genomics approach; RNA-sequence libraries were constructed, and data were analyzed to identify toxin-related genes. Next-generation sequencing produced 153,406 transcript contigs from the axenic culture of K. mikimotoi. BLASTX analysis against all assembled contigs revealed that 208 contigs were polyketide synthase (PKS) sequences. Thus, K. mikimotoi was thought to have several genes encoding PKS metabolites and to likely produce toxin-like polyketide molecules. Of all the sequences, approximately 30 encoded eight PKS genes, which were remarkably similar to those of Karenia brevis. Our phylogenetic analyses showed that these genes belonged to a new group of PKS type-I genes. Phylogenetic and active domain analyses showed that the amino acid sequence of four among eight Karenia PKS genes was not similar to any of the reported PKS genes. These PKS genes might possibly be associated with the synthesis of polyketide toxins produced by Karenia species. Further, a homology search revealed 10 contigs that were similar to a toxin gene responsible for the synthesis of saxitoxin (sxtA) in the toxic dinoflagellate Alexandrium fundyense. These contigs encoded A1–A3 domains of sxtA genes. Thus, this study identified some transcripts in K. mikimotoi that might be associated with several putative toxin-related genes. The findings of this study might help understand the mechanism of toxicity of K. mikimotoi and other dinoflagellates.
Investigating Tissue Optical Properties and Texture Descriptors of the Retina in Patients with Multiple Sclerosis

Purpose To assess the differences in texture descriptors and optical properties of retinal tissue layers in patients with multiple sclerosis (MS) and to evaluate their usefulness in the detection of neurodegenerative changes using optical coherence tomography (OCT) image segmentation. Patients and Methods 38 patients with MS were examined using Stratus OCT. The raw macular OCT data were exported and processed using OCTRIMA software. The enrolled eyes were divided into two groups, based on the presence of optic neuritis (ON) in the history (MSON+ group, n = 36 and MSON- group, n = 31). Data of 29 eyes of 24 healthy subjects (H) were used as controls. A total of seven intraretinal layers were segmented and thickness as well as optical parameters such as contrast, fractal dimension, layer index and total reflectance were measured. Mixed-model ANOVA analysis was used for statistical comparisons. Results Significant thinning of the retinal nerve fiber layer (RNFL), ganglion cell/inner plexiform layer complex (GCL+IPL) and ganglion cell complex (GCC, RNFL+GCL+IPL) was observed between study groups in all comparisons. Significant difference was found in contrast in the RNFL, GCL+IPL, GCC, inner nuclear layer (INL) and outer plexiform layer when comparing MSON+ to the other groups. Higher fractal dimension values were observed in GCL+IPL and INL layers when comparing H vs. MSON+ groups. A significant difference was found in layer index in the RNFL, GCL+IPL and GCC layers in all comparisons. A significant difference was observed in total reflectance in the RNFL, GCL+IPL and GCC layers between the three examination groups. Conclusion Texture and optical properties of the retinal tissue undergo pronounced changes in MS even without optic neuritis. Our results may help to further improve the diagnostic efficacy of OCT in MS and neurodegeneration.
Evaluation of potential Spanish text markers on social posts as features for polarity classification

This work describes the identification and evaluation process of potential text markers for sentiment analysis. Evaluation of the markers and its use as part of the feature extraction process from plain text that is needed for sentiment analysis is presented. Evaluation of text marker obtained as a result of systematic analysis from a corpus over a second one allowed us to identify that emphasized positive words are strong indicators for positive text. The second corpus allowed us to evaluate the relation between the polarity of emphasized words and the text they appear in. Evaluation of the markers for polarity detection task in combination with a polarized dictionary produced polarity classification average precision of 56% using only three markers. This are promising results compared to the top 69% obtained using more features and specialized dictionaries for the same task.
Migratory behaviour predicts greater parasite diversity in ungulates

Long-distance animal movements can increase exposure to diverse parasites, but can also reduce infection risk through escape from contaminated habitats or culling of infected individuals. These mechanisms have been demonstrated within and between populations in single-host/single-parasite interactions, but how long-distance movement behaviours shape parasite diversity and prevalence across host taxa is largely unknown. Using a comparative approach, we analyse the parasite communities of 93 migratory, nomadic and resident ungulate species. We find that migrants have higher parasite species richness than residents or nomads, even after considering other factors known to influence parasite diversity, such as body size and host geographical range area. Further analyses support a novel ‘environmental tracking' hypothesis, whereby migration allows parasites to experience environments favourable to transmission year-round. In addition, the social aggregation and large group sizes that facilitate migration might increase infection risk for migrants. By contrast, we find little support for previously proposed hypotheses, including migratory escape and culling, in explaining the relationship between host movement and parasitism in mammals at this cross-species scale. Our findings, which support mechanistic links between long-distance movement and increased parasite richness at the species level, could help predict the effects of future environmental change on parasitism in migratory animals.
Movement Duration, Fitts's Law, and an Infinite-Horizon Optimal Feedback Control Model for Biological Motor Systems

Optimization models explain many aspects of biological goal-directed movements. However, most such models use a finite-horizon formulation, which requires a prefixed movement duration to define a cost function and solve the optimization problem. To predict movement duration, these models have to be run multiple times with different prefixed durations until an appropriate duration is found by trial and error. The constrained minimum time model directly predicts movement duration; however, it does not consider sensory feedback and is thus applicable only to open-loop movements. To address these problems, we analyzed and simulated an infinite-horizon optimal feedback control model, with linear plants, that contains both control-dependent and control-independent noise and optimizes steady-state accuracy and energetic costs per unit time. The model applies the steady-state estimator and controller continuously to guide an effector to, and keep it at, target position. As such, it integrates movement control and posture maintenance without artificially dividing them with a precise, prefixed time boundary. Movement pace is determined by the model parameters, and the duration is an emergent property with trial-to-trial variability. By considering the mean duration, we derived both the log and power forms of Fitts's law as different approximations of the model. Moreover, the model reproduces typically observed velocity profiles and occasional transient overshoots. For unbiased sensory feedback, the effector reaches the target without bias, in contrast to finite-horizon models that systematically undershoot target when energetic cost is considered. Finally, the model does not involve backward and forward sweeps in time, its stability is easily checked, and the same solution applies to movements of different initial conditions and distances. We argue that biological systems could use steady-state solutions as default control mechanisms and might seek additional optimization of transient costs when justified or demanded by task or context.