Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying wildlife‐watching ecotourism intensity on an endangered marine vertebrate

Here, we show how seasonal changes in animal density drive strategic shifts in the activities of wildlife‐watching operators. These shifts result in high viewing intensity when animal densities are low, highlighting the need for modifications to existing wildlife‐watching guidelines. We used the endangered loggerhead sea turtle Caretta caretta as a model species that exhibits staggered departure from an important breeding area (Zakynthos, Greece, Mediterranean) over a 2‐month period (July to August) when tourism is at a peak, to investigate changes in wildlife‐watching strategies, zoning effectiveness and voluntary guideline compliance over time. We used a combination of direct land‐based observations, global positioning system tracking (of wildlife‐watching vessels and turtles) and models. The modelled number of turtles present in the breeding area decreased from > 200 in July to < 50 in August, while the intensity of turtle‐viewing increased from a mean 1.5 to 6.1 wildlife‐watching vessels per turtle‐viewing event (i.e. concurrent and consecutive vessels observing a single turtle) over the same period, respectively. During this period, the wildlife‐watching strategy changed and compliance to guidelines reduced (exacerbated by recreational vessels). However, wildlife‐watching activity was limited to a highly restricted 0.95‐km2 nearshore area, overlapping with just 9.5% of the core habitat area used by turtles. Our results have broad implications (whale watching etc.) by showing the importance of taking the number of animals available for viewing into consideration when assessing wildlife‐watching activity and when designing viewing guidelines, particularly for populations where numbers noticeably fluctuate.
Structural analysis of network models in tetrapod skulls

Background Ever since classic anatomists like George Cuvier, Geoffroy St. Hilaire, or Richard Owen laid down the fundamental principles of comparative anatomy in the 19th century, connections among anatomical parts have been essential for the recognition of biological homologies. However, few studies have addressed the possibility of implementing an adequate methodological tool to use connections among parts to unveil problems in morphology; although Woodger, Rashevsky, Riedl, and, more recently, Rasskin-Gutman pointed in this direction. In the last decades Network Theory has been developed as a novel conceptual and methodological framework to deal with the relational properties that emerge due to connections between parts in any organized system (e.g., robustness, self-organization, and modularity). Network analysis was readily applied to a wide range of complex biological systems, such as gene regulatory pathways, brain neuronal systems, or ecological communities. However, a seemingly natural arena to use this mathematical tool such as comparative anatomy has never been systematically studied using current network analysis tools.
DYNAMICS OF STAR-DISK INTERACTION PROCESSES IN YOUNG, LOW-MASS STARS AS SEEN FROM SPACE

High-precision time series photometry provides a unique window into the dynamics of the inner disk regions (< 1 AU) around young stars (< 5-10 Myr), at spatial scales hardly accessible via direct imaging techniques. In this review, we discuss the breakthrough brought in by space-based missions in our understanding of the physics and characteristic timescales of variability of protoplanetary disks in connection with their host stars. Our review is based on several young clusters and star-forming regions monitored with the CoRoT (NGC 2264) and Kepler/K2 (ρ Ophiuchus, Upper Scorpius) satellites. These regions virtually cover every stage of the disk lifetimes. In each region, hundreds of young, low-mass stars with disks were monitored nearly continuously for 30 to 80 days. The precision and homogeneity of such space-borne data allowed us to identify several distinct classes of young star-disk variables: spotted, quasi-periodic, stochastic, bursters, and dippers. The intrinsic timescales of variability that pertain to each light-curve class are indicative of the characteristic timescales of interaction between the stars and their inner disks, which are in turn related to the dynamical evolution of inner disk structures. The observed photometric behaviors can be associated with at least two distinct paradigms of star-disk interaction: an unstable regime, with erratic flux variations that trace intense and short-lived bursts of mass accretion onto the star, and a stable regime, with ordered accretion streams from the inner disk onto the star. These distinct scenarios may be related to different stages of the inner disk evolution, in an interplay with external and environmental conditions.
Corn Stover to Sustain Soil Organic Carbon Further Constrains Biomass Supply

Sustainable aboveground crop biomass harvest estimates for cellulosic ethanol production, to date, have been limited by the need for residue to control erosion. Recently, estimates of the amount of corn (Zea mays L.) stover needed to maintain soil carbon, which is responsible for favorable soil properties, were reported (5.25-12.50 Mg ha 1). These estimates indicate stover needed to maintain soil organic carbon, and thus productivity, are a greater constraint to environmentally sustainable cellulosic feedstock harvest than that needed to control water and wind erosion. An extensive effort is needed to develop advanced cropping systems that greatly expand biomass production to sustainably supply cellulosic feedstock without undermining crop and soil productivity.
Trajectories, bifurcations, and pseudo-time in large clinical datasets: applications to myocardial infarction and diabetes data

Abstract Background Large observational clinical datasets are becoming increasingly available for mining associations between various disease traits and administered therapy. These datasets can be considered as representations of the landscape of all possible disease conditions, in which a concrete disease state develops through stereotypical routes, characterized by “points of no return" and “final states" (such as lethal or recovery states). Extracting this information directly from the data remains challenging, especially in the case of synchronic (with a short-term follow-up) observations. Results Here we suggest a semi-supervised methodology for the analysis of large clinical datasets, characterized by mixed data types and missing values, through modeling the geometrical data structure as a bouquet of bifurcating clinical trajectories. The methodology is based on application of elastic principal graphs, which can address simultaneously the tasks of dimensionality reduction, data visualization, clustering, feature selection, and quantifying the geodesic distances (pseudo-time) in partially ordered sequences of observations. The methodology allows a patient to be positioned on a particular clinical trajectory (pathological scenario) and the degree of progression along it to be characterized with a qualitative estimate of the uncertainty of the prognosis. We developed a tool ClinTrajan for clinical trajectory analysis implemented in the Python programming language. We test the methodology in 2 large publicly available datasets: myocardial infarction complications and readmission of diabetic patients data. Conclusions Our pseudo-time quantification-based approach makes it possible to apply the methods developed for dynamical disease phenotyping and illness trajectory analysis (diachronic data analysis) to synchronic observational data.
From pre-turbulent flows to fully developed turbulence

SUMMARY: In colloquial speech the term “turbulence” means any flow with complicated temporal and spatial dynamics. In contrast, the properties of these flows are supposed to be described by models which are based on the assumption of a precise and very well defined setting. This paper is an attempt to review the fundamentals of turbulence theory, with emphasis on non-fully developed turbulence.
GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research

Protein-ligand docking is an in silico tool used to screen potential drug compounds for their ability to bind to a given protein receptor within a drug-discovery campaign. Experimental drug screening is expensive and time consuming, and it is desirable to carry out large scale docking calculations in a high-throughput manner to narrow the experimental search space. Few of the existing computational docking tools were designed with high performance computing in mind. Therefore, optimizations to maximize use of high-performance computational resources available at leadership-class computing facilities enables these facilities to be leveraged for drug discovery. Here we present the porting, optimization, and validation of the AutoDock-GPU program for the Summit supercomputer, and its application to initial compound screening efforts to target proteins of the SARS-CoV-2 virus responsible for the current COVID-19 pandemic.
Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling

To accelerate kernel methods, we propose a near input sparsity time algorithm for sampling the high-dimensional feature space implicitly defined by a kernel transformation. Our main contribution is an importance sampling method for subsampling the feature space of a degree $q$ tensoring of data points in almost input sparsity time, improving the recent oblivious sketching method of (Ahle et al., 2020) by a factor of $q^{5/2}/\epsilon^2$. This leads to a subspace embedding for the polynomial kernel, as well as the Gaussian kernel, with a target dimension that is only linearly dependent on the statistical dimension of the kernel and in time which is only linearly dependent on the sparsity of the input dataset. We show how our subspace embedding bounds imply new statistical guarantees for kernel ridge regression. Furthermore, we empirically show that in large-scale regression tasks, our algorithm outperforms state-of-the-art kernel approximation methods.
Towards an Understanding of Residual Networks Using Neural Tangent Hierarchy (NTH)

Gradient descent yields zero training loss in polynomial time for deep neural networks despite non-convex nature of the objective function. The behavior of network in the infinite width limit trained by gradient descent can be described by the Neural Tangent Kernel (NTK) introduced in \cite{Jacot2018Neural}. In this paper, we study dynamics of the NTK for finite width Deep Residual Network (ResNet) using the neural tangent hierarchy (NTH) proposed in \cite{Huang2019Dynamics}. For a ResNet with smooth and Lipschitz activation function, we reduce the requirement on the layer width $m$ with respect to the number of training samples $n$ from quartic to cubic. Our analysis suggests strongly that the particular skip-connection structure of ResNet is the main reason for its triumph over fully-connected network.
Aphyllophoraceous wood-inhabiting fungi on Quercus spp. in Italy

species of 92 genera of aphyllophoraceous fungi growing on Pinus spp. in Italy are reported. Dacryobolus karstenii, Hypochnicium cremicolor and Trechispora kavinioides are reported as new to Italy. Antrodia citrina has previously been described as a new species from this substrata while many species have to be considered rare or infrequent in
Poinsettia Cultivars Differ in Their Response to Molybdenum Deficiency

nutrition Abstract. Six cultivars of poinsettia (Euphorbia pulcherrima Willd. ex Kl.) were grown in unlimed growth medium consisting of equal volumes of sphagnum peat and perlite. Plants received fertilizer solutions supplying Mo at either 0.0 mg·liter -1 (-Mo) or 1.0 mg·liter -1 (+Mo). In the -Mo treatment, moderate to severe symptoms of Mo defi- ciency (marginal and interveinal chlorosis, marginal necrosis, and downward curling of the margins) developed on the middle-aged and some recently matured leaves of 'Annette Hegg Brilliant Diamond' and 'Eckespoint Lilo', while some interveinal chlo- rosis occurred on the same leaves of 'Gutbier V-17 Angelika'. No symptoms appeared on 'Gross Supjibi', 'Peace Regal Velvet', and 'Peace Noel'. All cultivars were symp- tomless in the + Mo treatment. In the -Mo treatment, upper, recently matured leaves of the symptomatic cultivars and two of three symptomless cultivars had Mo concen- trations at or near the critical level for deficiency; however, nitrate reductase enzyme activity was higher and NO3-N was lower in the leaves of symptomless cultivars than of symptomatic cultivars.
A Free Viewpoint Portrait Generator with Dynamic Styling

Generating portrait images from a single latent space facing the problem of entangled attributes, making it difficult to explicitly adjust the generation on specific attributes, e.g., contour and viewpoint control or dynamic styling. Therefore, we propose to decompose the generation space into two subspaces: geometric and texture space. We first encode portrait scans with a semantic occupancy field (SOF), which represents semantic-embedded geometry structure and output free-viewpoint semantic segmentation maps. Then we design a semantic instance wised(SIW) StyleGAN to regionally styling the segmentation map. We capture 664 3D portrait scans for our SOF training and use real capture photos(FFHQ and CelebA-HQ) for SIW StyleGAN training. Adequate experiments show that our representations enable appearance consistent shape, pose, regional styles controlling, achieve state-of-the-art results, and generalize well in various application scenarios.
With Wronskian through the Looking Glass

In the work of Mukhin and Varchenko from 2002 there was introduced a Wronskian map from the variety of full flags in a finite dimensional vector space into a product of projective spaces. We establish a precise relationship between this map and the Plucker map. This allows us to recover the result of Varchenko and Wright saying that the polynomials appearing in the image of the Wronsky map are the initial values of the tau-functions for the Kadomtsev-Petviashvili hierarchy.
BIOLOGICAL ASPECTS OF ANTIFEEDANTS

Certain chemicals of plant origin may inhibit food intake in phytophagous insects. Such antifeedants act at low concentrations and are perceived by specialized deterrent receptors or by their modifying effect on normal chemosensory input. In some cases habituation to the presence of antifeedants occurs. When we want to find more chemicals which fulfill all requirements of true and effective antifeedants more research on plant chemistry and insect behaviour is needed. Large scale application only becomes feasible when a number of biological as well as technical problems will be solved.
Discovery of the Optical Afterglow and Host Galaxy of Short GRB 181123B at z = 1.754: Implications for Delay Time Distributions

We present the discovery of the optical afterglow and host galaxy of the Swift short-duration gamma-ray burst (SGRB) GRB 181123B. Observations with Gemini-North starting ≈9.1 hr after the burst reveal a faint optical afterglow with i ≈ 25.1 mag at an angular offset of 0. ″59 ± 0. ″16 from its host galaxy. Using grizYJHK observations, we measure a photometric redshift of the host galaxy of . From a combination of Gemini and Keck spectroscopy of the host galaxy spanning 4500–18000 Å, we detect a single emission line at 13390 Å, inferred as Hβ at z = 1.754 ± 0.001 and corroborating the photometric redshift. The host galaxy properties of GRB 181123B are typical of those of other SGRB hosts, with an inferred stellar mass of ≈9.1 × 109 M⊙, a mass-weighted age of ≈0.9 Gyr, and an optical luminosity of ≈0.9L*. At z = 1.754, GRB 181123B is the most distant secure SGRB with an optical afterglow detection and one of only three at z > 1.5. Motivated by a growing number of high-z SGRBs, we explore the effects of a missing z > 1.5 SGRB population among the current Swift sample on delay time distribution (DTD) models. We find that lognormal models with mean delay times of ≈4–6 Gyr are consistent with the observed distribution but can be ruled out to 95% confidence, with an additional ≈one to five Swift SGRBs recovered at z > 1.5. In contrast, power-law models with ∝t−1 are consistent with the redshift distribution and can accommodate up to ≈30 SGRBs at these redshifts. Under this model, we predict that ≈1/3 of the current Swift population of SGRBs is at z > 1. The future discovery or recovery of existing high-z SGRBs will provide significant discriminating power on their DTDs and thus their formation channels.
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion

Conversational recommender systems (CRS) aim to recommend high-quality items to users through interactive conversations. Although several efforts have been made for CRS, two major issues still remain to be solved. First, the conversation data itself lacks of sufficient contextual information for accurately understanding users' preference. Second, there is a semantic gap between natural language expression and item-level user preference. To address these issues, we incorporate both word-oriented and entity-oriented knowledge graphs~(KG) to enhance the data representations in CRSs, and adopt Mutual Information Maximization to align the word-level and entity-level semantic spaces. Based on the aligned semantic representations, we further develop a KG-enhanced recommender component for making accurate recommendations, and a KG-enhanced dialog component that can generate informative keywords or entities in the response text. Extensive experiments have demonstrated the effectiveness of our approach in yielding better performance on both recommendation and conversation tasks.
Dynamique de l’activation de la transcription d’un gène

Expression de l’information genetique Au sein d’un organisme, une information genetique identique conduit a l’elaboration de phenotypes cellulaires differents, ce qu’expliquent l’activation et/ou la repression selectives d’un repertoire de genes. Ces evenements moleculaires permettent egalement la reponse appropriee de la cellule a une variation locale des concentrations en hormones. La transcription requiert la presence de l’ARN polymerase II (Pol II), recrutee au niveau du promoteur du gene sous l’influence de la liaison d’un ou de plusieurs facteurs de transcription dits enhancer sur des sequences cis precises. Cet enhancer va provoquer la mise en place du complexe de pre-initiation (CPI) au niveau du site d’initiation de la transcription. Le CPI inclut la Pol II inactive ainsi que les six complexes TFIIA, B, C, D, E et F [1]. D’autres complexes proteiques composes de plusieurs sous-unites, les TRAP/DRIP/Mediator (TRAP pour thyroid receptor-associated protein complex, DRIP pour vitamin D receptor interacting proteins), etablissent un pont entre le CPI et l’activateur et permettent la transition entre le CPI et un complexe Pol II competent pour la transcription. Cette transition est due a la phosphorylation de la sous-unite Rbp1 (ou extension carboxy-terminale) de la Pol II qui permet un echange des proteines de type Mediator pour des proteines specifiques (de type Elongator) de la Pol II active. Chromatine et dynamique d’activation de la transcription d’un gene Au sein de la chromatine, l’ADN est compacte par les histones sous forme de nucleosomes. L’initiation de la transcription d’un gene se deroule donc in vivo dans un contexte tres restrictif, car cette structure compacte est physiquement peu propice a la liaison des complexes proteiques de haut poids moleculaire formant le CPI. Au niveau du promoteur, la plasticite de la chromatine requise pour l’initiation de la transcription est assuree par le recrutement et l’assemblage de complexes proteiques specifiques [2]. Ces evenements impliquent soit des proteines de type SWI/SNF qui alterent l’organisation spatiale des nucleosomes en presence d’ATP, soit des proteines qui, en modifiant les lysines et les arginines des histones tails par acetylation (activite HAT, histone acetyltransferase) ou methylation (HMT, histone methyltransferase), vont affaiblir les liaisons physiques entre les histones et l’ADN [3]. Il y a deja maintenant pres de 20 ans, s’est pose la question de la cinetique de ces evenements: les complexes recrutes au niveau d’un promoteur sont-ils deja preformes ou bien s’assemblent-ils sur le promoteur, et dans quel ordre ?
Measuring the psychological drivers of participation in collective action to address violence against women in Mumbai, India

Background: A growing number of global health interventions involve community members in activism to prevent violence against women (VAW), but the psychological drivers of participation are presently ill-understood. We developed a new scale for measuring three proposed drivers of participation in collective action to address VAW in the context of urban informal settlements in Mumbai, India: perceived legitimacy, perceived efficacy, and collective action norms. Methods: We did a household survey of 1307 men, 1331 women, and 4 trans persons. We checked for 1) social desirability bias by comparing responses to self-administered and face-to-face interviews, 2) acquiescence bias by comparing responses to positive and negatively worded items on the same construct, 3) factor structure using confirmatory factor analysis, and 4) convergent validity by examining associations between construct scores and participation in groups to address VAW and intent to intervene in case of VAW. Results: Of the ten items, seven showed less than five percentage point difference in agreement rates between self-administered and face-to-face conditions. Correlations between opposite worded items on the same construct were negative (p<0.05), while correlations between similarly worded items were positive (p<0.001). A hierarchical factor structure showed adequate fit (Tucker-Lewis index, 0.919; root mean square error of approximation, 0.036; weighted root mean square residual, 1.949). Comparison of multi-group models across gender, education, caste, and marital status showed little evidence against measurement invariance. Perceived legitimacy, efficacy and collective action norms all predicted participation in groups to address VAW and intent to intervene in case of VAW, even after adjusting for social capital (p<0.05). Conclusion: This is the first study to operationalize a measure of the psychological drivers of participation in collective action to address VAW in a low- and middle-income context. Our novel scale may provide insight into modifiable beliefs and attitudes community mobilisation interventions can address to inspire activism in similar low-resource contexts.
A POTENTIAL STALK-BORER INSECTICIDE MANAGEMENT PROGRAM THAT ENHANCES BIOLOGICAL CONTROL

An extensive search and evaluation for narrow-range, minimum-risk insecticides to control the sugarcane borer, Diatraea saccharalis (F.), involved research with the Rohm and Haas new class of insecticides, the molting-accelerator compounds (ecdysone agonists). Tebufenozide (Confirmo) showed an extremely positive fit for integrated pest management use in the Louisiana sugarcane industry, which has had a history of insecticide environmentally related problems with fish and wildlife. To assess if tebufenozide could be integrated into an effective sugarcane-borer management program, studies evaluated the effects on parasitoids and predators, assessing direct mortality in comparison to cessation of feeding, determining critical exposure time, and assessing impact on various life stages influencing length of control period. By the time of permanent labeling of tebufenozide for D. saccharalis control on sugarcane in the US, more than 70% of sugarcane insecticide used with temporary labels of this compound.