Miracle-dz/UniFAR-FTUs huggingface dataset:
Forced turbulent fountain flow behaviour

Numerical simulations of turbulent fountain flow are used to investigate the important energy and mass transfer mechanisms present in the forced fountain flow regime, which has been reported to exist at Froude numbers (Fr) greater than 3. The flow is equivalent to a negatively buoyant jet with three flow streams, the inner upflow (IF), the outer downflow (OF) and the surrounding ambient fluid (AF). Simulation results are presented for Fr = 4 and 7 at Reynolds number Re = 3350. The mean fountain penetration height scales with the previously reported relation Zm/R0 = 2.46Fr, where R0 is the source radius, but the assumptions behind analytical derivations of the relation are not supported by the present results. The results suggest that the OF may be relatively well described by the dynamics of a pure line plume surrounding the IF but with higher entrainment owing to the unsteady pulsing behaviour of the flow entering the OF from the IF. The length scale for a pure plume appears to apply at Fr = 7 in the OF and a degree of self-similarity exists. Comparisons with previous results suggest the IF is not fully developed at Fr = 7 and entrainment into the IF from the OF may not occur until Fr > 15.
Femtosecond laser induced nanocone structure and simultaneous crystallization of 1.6 µm amorphous silicon thin film for photovoltaic application

In this paper, we have demonstrated the crystallization and simultaneous formation of the nanocone structure on the 1.6 µm thick amorphous silicon (a-Si) film using a one-step femtosecond laser annealing approach. The a-Si layer is crystallized after the annealing process, as confirmed from their Raman spectra. Meanwhile, the conical structures with diameters ranging from 160 nm to 1.4 µm are formed upon laser beam irradiation at different fluences, as deduced from scanning electron microscope and atomic force microscope characterization. The highest absorption is achieved when the sample is irradiated with a laser fluence of 588 mJ cm−2. The developed process has potential applications in the fabrication of high efficiency and low cost Si thin-film solar cells. Moreover, the physics and mechanism involved in the laser annealing process are also discussed.
Surface Photometry of Dwarf Elliptical Galaxies in the Virgo Cluster

On presente les resultats de la photometrie photographique de surface de 69 galaxies elliptiques naines de la region centrale de l'amas Virgo, faite a l'aide de deux plaques obtenues dans la bande B avec le telescope de 2,5 m de l'observatoire de Las Campanas. On a obtenu les profils de luminosite, ainsi que divers parametres photometriques
Repetition and Confirmation of Messages Received by Ear and by Eye

A rating method was used to obtain operating characteristics for 60 heterogeneous words. A single message was heard in noise, or seen briefly in a tachistoscope. It was repeated until it had been assigned to the highest accuracy category (“confirmed”) or sent a maximum of six trials. The comparisons showed that it matters little whether reception is by eye or by ear. Whether within a trial or over successive repetitions, accuracy of reception is a direct function of the confidence rating and is relatively independent of the intelligibility level. Neither do the accuracy of reception or the distributions of rating categories change markedly over trials. Although no direct test was made, it appears that accuracy of reception is not lessened by the task of rating. Both visual and auditory data are fitted reasonably well by predictions made from a simple stochastic model based on the assumptions that (1) intelligibility, (2) probability of a correct acceptance, and (3) probability of an incorrect acceptance remain constant over successive repetitions. The model fits the visual better than the auditory data, as might be expected, since conditions of reception are more homogeneous over trials for vision than for audition.
Effect of two seeding rates on yield and yield components of winter and spring faba bean

ABSTRACT In Central European cropping systems, there is increasing interest in winter faba bean (Vicia faba L. minor), which is traditionally used as a spring crop. But limited knowledge on yield and yield formation and optimum seeding rate exist. Therefore, the purpose of this assessment was to compare soil coverage, yield and yield components of two winter faba bean varieties (Diva and Hiverna) with a spring faba bean (Alexia) with two seeding rates (SR), 25 versus 50 germinable seeds m−2 (S), in a two-year field experiment under Pannonian climate conditions in eastern Austria. Both winter faba bean varieties produced a high grain yield with 25 S, whereas that of Alexia tended to be higher with 50 S. The grain yield of Diva and Hiverna was with 25 S and that of Diva also with 50 S higher than that of Alexia. The higher SR caused in winter faba beans a higher intraspecific competition resulting in less stems plant−1. Pod density of Alexia was higher with 50 S compared to 25 S, while grains pod−1 and thousand kernel weight of all three varieties were not affected by SR. Results show that winter faba bean can be sown in Central Europe with lower seeding rates compared to spring faba bean without suffering a grain yield loss.
Hyperspectral image classification using meta-heuristics and artificial neural network

Abstract Hyperspectral images usually comprise several continuous spectral bands that represent the category of similar objects or material within the captured scene. These high-dimensional data structures have a high level of correlation and possess unique information that can be used for precise image classification. The precise selection of useful features from these high dimensional band information is very important to reduce the challenge of hyper spectral image classification approaches. Nowadays, metaheuristic algorithms are immensely utilized as a promising tool for hyperspectral image classification. In the present research work, hyperspectral images are classified with the various combinations of meta-heuristic approaches and the neural network including the mostly used Cuckoo Search (CS) optimization algorithm to resolve the global optimization search problems considering the improvement needed in image classification. Further, the strength of CS is improved using the integration of the Genetic Algorithm (GA) fitness function within the CS. The feature selection is performed by the hybrid CS and GA algorithm and the optimized features are then fed to ANN for training and classification. The paper has shown a comparative analysis of various meta heuristics techniques with ANN on parameters like kappa coefficient, Class accuracy and overall Accuracy and the designed algorithms are tested on the Indian Pines dataset. The proposed CS and GA with ANN outperformed the two already existing works with an overall average accuracy of 97.30% and a kappa coefficient of 0.9760.
The effect of financial development on economic growth and income distribution: an empirical evidence from lower-middle and upper-middle-income countries

ABSTRACT Financial development and its relationships with economic growth and income inequality have recently received considerable attention. The present study investigates the relationships between financial development and (i) economic growth, using data from 44 countries; (ii) economic inequality, using data from 42 middle-income countries. Estimates are obtained through a panel Autoregressive Distributed Lag (ARDL) model for a period of 23 years (1995-2018). Results reveal that financial development contributes to economic growth in both groups of countries in the long run. However, the contribution financial development makes to economic growth is more noticeable in the case of upper-middle income countries. Additionally, Granger causality test based on Vector Error Correction (VEC) showed two-way Granger causality between financial development and economic growth. Findings disclosed an inverted U-shaped association between financial development and income inequality for both lower-middle income and upper-middle income countries. This study can aid policymakers in designing policies that can strengthen financial systems, thereby enhancing economic growth and reducing income inequality.
Assessment of the spatial variability of selected soil chemical properties using geostatistical analysis in the north-western highlands of Ethiopia

ABSTRACT The aim of this research was to evaluate the status of selected soil chemical properties and to explore their spatial variability in various agroecosystems (AEs) of Choke Mountain, northwestern highlands of Ethiopia. A total of 74 geo-referenced composite surface (0-30 cm) soil samples were collected from representative farm lands. Soil chemical properties were analyzed following standard procedures. In addition, semi-variogram model was applied to estimate the spatial variability of soil properties. The results showed that soil chemical properties are below their threshold values in all agroecosystems and soil groups. The value of soil pH ranged from 4.3 to 6.8; Exchangeable acidity ranged from 0.124 to 0.180 cmol (+) kg−1; EC ranged from 0.02 to 0.19 dS m−1; OC ranged from 0.7 to 3.8%; TN ranged from 0.11 to 0.27%; Exchangeable potassium from 0.29 to 2.0 cmol (+) kg−1and CEC from 22 to 56 cmol (+)kg−1. The results also revealed that soil pH, exchangeable acidity, electrical conductivity, and exchangeable potassium showed strong spatial dependence whereas SOC and TN had moderate spatial dependence. The results indicated that soil quality is deteriorating. Hence, crop, soil and site-specific soil management strategies, primarily focusing on improving the content of SOM and addressing the problems of soil acidity are suggested to improve the soil conditions.
The number of bound states for a discrete Schrödinger operator on , lattices

We consider the discrete Schrödinger operator in in the case of a potential with negative part in an appropriate ℓσ-space (decays with an appropriate rate). We present a discrete analog of the method of Li and Yau (1983 Commun. Math. Phys. 88 309–18), proving an explicit upper estimate on the number of bound states , which is independent of the dimension of the lattice. This is a major difference with the continuous counterpart estimate, which is not valid when N = 1, 2. As a consequence, a dimension-independent smallness criterion for the existence of bound states is derived in contrast to the continuous case as well as to the discrete case of vanishing potential. A short comment is made on possible applications of the results to the study of the dynamics of some particular spatially discrete nonlinear systems.
Using in silico perturbational approach to identify critical areas in schizophrenia

Schizophrenia is a debilitating neuropsychiatric disorder whose underlying correlates remain unclear despite decades of neuroimaging investigation. One contentious topic concerns the role of global signal fluctuations and how they affect more focal functional changes. Moreover, it has been difficult to pinpoint causal mechanisms of circuit disruption. Here we analysed resting-state fMRI data from 47 schizophrenia patients and 118 age-matched healthy controls and used dynamical analyses to investigate how global fluctuations and other functional metastable states are affected by this disorder. We then used in-silico perturbation of a whole-brain model to identify critical areas involved in the disease. We found that brain dynamics in the schizophrenic group were characterised by an increased probability of globally coherent states and reduced recurrence of a substate dominated by coupled activity in the default mode and limbic networks. Perturbing a set of temporoparietal sensory and associative areas in a model of the healthy brain reproduced global pathological dynamics. Healthy brain dynamics were instead restored by perturbing a set of medial fronto-temporal and cingulate regions in the model of pathology. These results highlight the relevance of global signal alterations in schizophrenia and identify a set of vulnerable areas involved in determining a shift in brain state.
Non-specific vs specific DNA binding free energetics of a transcription factor domain protein for target search and recognition

Transcription factor (TF) proteins regulate gene expression by binding to specific sites on the genome. In the facilitated diffusion model, an optimized search process is achieved by the TF protein alternating between 3D diffusion in the bulk and 1D diffusion along DNA. While undergoing 1D diffusion, the protein can switch from a search mode for fast diffusion along non-specific DNA to a recognition mode for stable binding to specific DNA. It was recently noticed that for a small TF domain protein, re-orientations on DNA other than conformational changes happen between the non-specific and specific DNA binding. We here conducted all-atom molecular dynamics simulations with steering forces to reveal the protein-DNA binding free energetics, with a difference between the non-specific and specific binding about 10 kBT, confirming that the search and recognition modes are distinguished only by protein orientations on the DNA. As the binding free energy difference differs from that being estimated from experimental measurements about 4-5 kBT on 15-bp DNA constructs, we hypothesize that the discrepancy comes from DNA sequences flanking the 6-bp central binding sites impacting on the dissociation kinetics measurements. The hypothesis is supported by a simplified spherical protein-DNA model along with stochastic simulations and kinetic modeling.
R-mode oscillations in uniformly rotating stars

R-mode (or quasi-toroidal mode) oscillations in uniformly and slowly rotating stars have been investigated. Perturbations of the gravitational potential have been included. Applying an adiabatic analysis to a polytrope of index n = 3 (GAMMA/sub 1/ = 5/3), we confirm that gravitational potential perturbations are small for r modes in most cases. A nonadiabatic analysis of oscillations with l = Vertical Bar m Vertical Bar is applied to the models of massive zero-age main-sequence stars are stable whereas r modes in the ZZ Ceti model appear to be overstable. However, the neglect of coupling between oscillations and convection might be important for the latter stars because regions of excitation coincide with convection zones.
Profile-Wise Analysis: A profile likelihood-based workflow for identifiability analysis, estimation, and prediction with mechanistic mathematical models

Interpreting data using mechanistic mathematical models provides a foundation for discovery and decision-making in all areas of science and engineering. Developing mechanistic insight by combining mathematical models and experimental data is especially critical in mathematical biology as new data and new types of data are collected and reported. Key steps in using mechanistic mathematical models to interpret data include: (i) identifiability analysis; (ii) parameter estimation; and (iii) model prediction. Here we present a systematic, computationally-efficient workflow we call Profile-Wise Analysis (PWA) that addresses all three steps in a unified way. Recently-developed methods for constructing ‘profile-wise’ prediction intervals enable this workflow and provide the central linkage between different workflow components. These methods propagate profile-likelihood-based confidence sets for model parameters to predictions in a way that isolates how different parameter combinations affect model predictions. We show how to extend these profile-wise prediction intervals to two-dimensional interest parameters. We then demonstrate how to combine profile-wise prediction confidence sets to give an overall prediction confidence set that approximates the full likelihood-based prediction confidence set well. Our three case studies illustrate practical aspects of the workflow, focusing on ordinary differential equation (ODE) mechanistic models with both Gaussian and non-Gaussian noise models. While the case studies focus on ODE-based models, the workflow applies to other classes of mathematical models, including partial differential equations and simulation-based stochastic models. Open-source software on GitHub can be used to replicate the case studies.
Automated genome mining predicts combinatorial diversity and taxonomic distribution of peptide metallophore structures

Microbial competition for trace metals shapes their communities and interactions with humans and plants. Many bacteria scavenge trace metals with metallophores, small molecules that chelate environmental metal ions and transport them back into the cell. Our incomplete knowledge of metallophores diversity stymies our ability to fight infectious diseases and harness beneficial microbiome interactions. The majority of known metallophores are non-ribosomal peptides (NRPs), which feature metal-chelating moieties rarely found in other classes of natural products. NRP metallophore production may be predicted by genome mining, where genomes are scanned for homologs of known biosynthetic gene clusters (BGCs). However, accurately detecting NRP metallophore biosynthesis currently requires expert manual inspection. Here, we introduce automated identification of NRP metallophore BGCs through a comprehensive detection algorithm, newly implemented in antiSMASH. Custom-designed profile hidden Markov models detect genes encoding the biosynthesis of most known NRP metallophore chelating moieties (2,3-dihydroxybenzoate, hydroxamates, salicylate, β-hydroxyamino acids, graminine, Dmaq, and the pyoverdine chromophore), achieving 97% precision and 78% recall against manual curation. We leveraged the algorithm, in combination with transporter gene detection, to detect NRP metallophore BGCs in 15,562 representative bacterial genomes and predict that 25% of all non-ribosomal peptide synthetases encode metallophore production. BiG-SCAPE clustering of 2,562 NRP metallophore BGCs revealed that significant diversity remains unexplored, including new combinations of chelating groups. Additionally, we find that Cyanobacteria are severely understudied and should be the focus of more metallophore isolation efforts. The inclusion of NRP metallophore detection in antiSMASH version 7 will aid non-expert researchers and facilitate large-scale investigations into metallophore biology.
Hiding data in colour palette images with hybrid strategies

Abstract In this paper, we propose a data embedding scheme for embedding secret data into colour palette images by using a hybrid combining pixel prediction, clustering and dissimilar pair concepts. To maintain better image quality, a predefined threshold is defined and a luminance sorted algorithm is used to perform clustering and select similar colours from the colour palette for data embedding. Experimental results confirm that our proposed scheme can successfully enhance hiding capacity while maintaining a satisfactory image quality of the stego-image.
Perceptual awareness is gradual in temporal and dichotomous in fronto-parietal cortices

Two major issues in consciousness research concern the measuring methods that determine perceptual unawareness and whether consciousness is a gradual or an ‘all-or-nothing’ phenomenon. This 7T fMRI study addresses both questions using a continuous flash suppression paradigm with an emotional recognition task (fear vs neutral bodies) in combination with the perceptual awareness scale. Behaviorally, recognition sensitivity increased linearly with increased stimuli awareness and was at chance level during perceptual unawareness. Threat expressions triggered a slower heart rate than neutral ones during ‘almost clear’ experience of the stimulus, indicating freezing behavior. The activity in occipital, temporal, parietal and frontal regions as well as in amygdala increased with increased stimulus awareness while the activity in early visual areas showed the opposite pattern. The relationship between temporal area activity and perceptual awareness was better characterized by a gradual model while the activity in fronto-parietal areas by a dichotomous model, suggesting different roles in conscious processing. Interestingly, no evidence of non-conscious processing was found in amygdala as well as no significant effect of emotion, in disagreement with the functions long ascribed to this subcortical structure.
Can we improve our ability to interpret ectotherm thermal tolerance?

Thermal tolerances, such as critical temperatures, are important indices for understanding an organism’s vulnerability to changing environmental temperature. Differences in thermal tolerance over ontogeny may generate a ‘thermal bottleneck’ that sets the climate vulnerability for organisms with complex life cycles. However, a species’ microhabitat preference and methodological differences among studies can generate confounding variation in thermal tolerance that may mask trends in large-scale comparative studies and may hinder our ability to assess climate change vulnerability within and among species. Here, we evaluated two approaches to resolving ontogenetic and environmental drivers of thermal tolerance and methodological variation: mathematical standardisation of thermal tolerance and classifying microhabitat preferences. Using phylogenetically informed, multi-level models with a global dataset of upper critical temperatures from 438 Anuran species, we found ontogenetic trends in thermal tolerance were similar across microhabitat preferences and standardising critical temperatures against common methodological variation had little impact on our conclusions. Our results suggested thermal bottlenecks are not strongly present in Anurans but instead, implied strong developmental or genetic conservatism of thermal tolerance within families and ecotypes. We discussed considerations for resolving confounding variation to interpret thermal tolerance at a macrophysiological scale.
Abbreviated title : Frontoparietal task-switching dissociations after TMS

Preparatory control in task-switching has been suggested to rely upon a set of distributed regions within a frontoparietal network, with frontal and parietal cortical areas cooperating to implement switch-specific preparation processes. Although recent causal evidences using transcranial magnetic stimulation (TMS) have generally supported this model, alternative evidences from both functional neuroimaging and neurophysiological studies have questioned the switch-specific role of both frontal and parietal cortices. The aim of the present study was to clarify the role of prefrontal and parietal areas supporting preparatory cognitive control in task-switching. Within this purpose, an fMRI study during task-switching performance was conducted to identify the specific brain areas involved in preparatory control during performance of a task-switching paradigm. Then, TMS was applied over the specific coordinates previously identified through fMRI, that is, the anterior portion of the inferior frontal junction (aIFJ) and the intraparietal sulcus (IPS). Results revealed that TMS over the aIFJ disrupted performance in both switch and repeat trails in terms of delayed responses as compared to Sham condition. In contrast, TMS over the IPS selectively interfered performance in switch trials. These findings support a multicomponent model of executive control with the aIFJ being involved in more general switch-unspecific process such as the episodic retrieval of goals, and the IPS being related to the implementation of switch-specific preparation mechanisms for activating stimulus-response mappings. The results help conciliating preceding evidences about the role of a frontoparietal network during task-switching, and support current models about a hierarchical organization within prefrontal cortex.