Miracle-dz/UniFAR-FTUs huggingface dataset:
Encoded C4 homologue enzymes genes function under abiotic stresses in C3 plant

ABSTRACT Plant organisms assimilate CO2 through the photosynthetic pathway, which facilitates in the synthesis of sugar for plant development. As environmental elements including water level, CO2 concentration, temperature and soil characteristics change, the plants may recruit series of genes to help adapt the hostile environments and challenges. C4 photosynthesis plants are an excellent example of plant evolutionary adaptation to diverse condition. Compared with C3 photosynthesis plants, C4 photosynthesis plants have altered leaf anatomy and new metabolism for CO2 capture, with multiple related enzymes such as phosphoenolpyruvate carboxylase (PEPCase), pyruvate orthophosphate dikinase (PPDK), NAD(P)-malic enzyme (NAD(P)-ME), NAD(P) – malate dehydrogenase (NAD(P)-MDH) and carbonic anhydrases (CA), identified to participate in the carbon concentrating mechanism (CCM) pathway. Recently, great achievements about C4 CCM-related genes have been made in the dissection of C3 plant development processes involving various stresses. In this review, we describe the functions of C4 CCM-related homologous genes in carbon and nitrogen metabolism in C3 plants. We further summarize C4 CCM-related homologous genes’ functions in response to stresses in C3 plants. The understanding of C4 CCM-related genes’ function in response to abiotic stress in plant is important to modify the crop plants for climate diversification.
Weaning period and growth patterns of captive Sunda pangolin (Manis javanica) cubs

This study tracked and recorded the weight changes of 13 captive Sunda pangolin cubs from lactation to maturity to explored the appropriate weaning time and reveal the rules of its weight growth. SPSS 25.0 was used to build a cubic equation model to fit the body weight change rules of 4 individuals who nonvoluntarily ingested artificial feed (NIAF) at 127 days after birth and 5 individuals who voluntarily ingested artificial feed (VIAF) at 86–108 days after birth. The body weight of NIAF cubs aged 0–120 days and VIAF cubs aged 0–150 days were estimated according to the fitting model. An independent sample T-test was performed on the mean body weight of the two groups during the late lactation period. The results showed that at 105 days after birth, the body weight of the VIAF group was significantly higher than that of the NIAF group (P = 0.049), and the body weight of the VIAF group was extremely significantly higher than that of the NIAF group at 114 days (P = 0.008); The peak cumulative body weight of the NIAF cubs during lactation appeared around 130 days of age (n = 3); The mortality rate was 66.7% (n = 3) after about 150 days if the feed was continuously consumed nonvoluntarily. It was concluded that the milk secretion period of the mother is about 0–5 months after giving birth; the weaning period of the cubs should be 4–5 months after birth. If the cubs don’t follow the mother to eat artificial feed for 3 months after birth, it can start be induced with artificial diet which adds termites, and the time point cannot be later than 130 days, otherwise it is not conducive to the survival of the cubs; When sexually mature, the body length and body weight of female cubs account for about 84% and 60% of the adult, respectively; the body maturity and body weight of female cubs tend to be stable about 15.3 months and 16.4 months, respectively. Finally, a special needle-shaped nipples and nursing patterns of female Sunda pangolins were also recorded in this study. These findings play an important role in guiding the nursing of captive Sunda pangolin cubs and other pangolin cubs. It is expected to improve the survival rate of the cubs by exploring the appropriate weaning time and the rules of weight growth. By scientifically planning the reproductive cycle of the female Sunda pangolins, our goal is to expand the population size and eventually release to the wild, meanwhile improving knowledge of this critically endangered species.
Predictive Model for Quality of Life in Patients With Heart Failure

Background Although many studies have been conducted to examine predictors of quality of life (QoL), little information exists on the real-world application of Rector's conceptual model for QoL related to heart failure (HF). Objectives In this study, we aimed to examine a hypothetical model of QoL based on Rector's conceptual model for QoL in relation to HF and the existing literature on patients with HF. Methods Using a cross-sectional survey, 165 patients with HF were recruited from an outpatient clinic in Korea. Data were collected based on Rector's model constructs, such as cardiac function, symptoms, functional limitation, depression, distress, and QoL. Left ventricular ejection fraction for cardiac function was measured using echocardiography. Results Functional limitation, depression, and distress, but not symptoms, had a direct effect on QoL (all Ps < .001). Cardiac function and symptoms directly affected functional limitation (β = 0.186, P = .004, and β = −0.488, P = < .001, respectively), whereas cardiac function, symptoms, and depression affected QoL through functional limitation and distress. Conclusions These results confirm that the Rector's model is suitable for predicting QoL in patients with HF. These findings have potential to guide and inform intervention programs designed to alleviate symptoms in patients with HF, enhance their physical functioning, and moderate their psychological distress with the ultimate goal of improving their QoL.
Prevalence and characterization of middle ear effusion in 55 brachycephalic dogs.

OBJECTIVE Multiple, breeding-related malformations of the skull of brachycephalic dogs are well-known. Whereas the eye-catching deformities of the nose that lead to dramatic respiratory problems are obvious, changes of the middle ear are often an incidental finding on CT examinations and usually clinically inapparent. The objectives of this work were to investigate the prevalence and characteristics of middle ear effusion in brachycephalic dog breeds presented for multilevel surgery of upper airway obstructions. MATERIAL AND METHODS Brachycephalic dogs with incidental middle ear effusion detected on CT scans obtained prior to surgical treatment of brachycephalic airway syndrome were prospectively enrolled. A perendoscopic tympanocentesis followed by macroscopic description, microscopic cytology and bacteriological analysis of the fluid was performed. RESULTS Prevalence of middle ear effusion in all dogs presented to the department during the study period was 55/170 (32 %) in 86 middle ears. The only breeds suffering from MEE were French Bulldogs (FB) with a prevalence of 35/66 (53 %) and Pugs with a prevalence of 20/79 (25 %). Tympanocentesis was performed in 80 ears. In the majority of cases the effusion was either mucoid or serous, with a honey-like or ochre colour.Bacteriology was available for 76 ears and tested positive in 34 (45 %) cases. Cytology was performed in 73 ears and revealed all effusions to contain inflammatory cells with a high concentration in 23 (31.5 %) cases. CONCLUSIONS AND CLINICAL RELEVANCE Brachycephalic dogs presented for surgical treatment of brachycephalic airway syndrome have a high prevalence of incidental middle ear effusions. Cytological findings differ from previously reported analyses of effusions in Cavalier King Charles spaniels with clinical symptoms of primary secretory otitis media, where usually cell-free effusions are found. A study comparing effusions of brachycephalic dogs with vestibular disease to those found as an incidental condition is warranted.
Mapless Navigation of a Hybrid Aerial Underwater Vehicle with Deep Reinforcement Learning Through Environmental Generalization

Previous works showed that Deep-RL can be applied to perform mapless navigation, including the medium transition of Hybrid Unmanned Aerial Underwater Vehicles (HUAUVs). This paper presents new approaches based on the state-of-the-art actor-critic algorithms to address the navigation and medium transition problems for a HUAUV. We show that a double critic Deep-RL with Recurrent Neural Networks improves the navigation performance of HUAUVs using solely range data and relative localization. Our Deep-RL approaches achieved better navigation and transitioning capabilities with a solid generalization of learning through distinct simulated scenarios, outperforming previous approaches.
Small Transformers Compute Universal Metric Embeddings

We study representations of data from an arbitrary metric space $\mathcal{X}$ in the space of univariate Gaussian mixtures with a transport metric (Delon and Desolneux 2020). We derive embedding guarantees for feature maps implemented by small neural networks called \emph{probabilistic transformers}. Our guarantees are of memorization type: we prove that a probabilistic transformer of depth about $n\log(n)$ and width about $n^2$ can bi-H\"{o}lder embed any $n$-point dataset from $\mathcal{X}$ with low metric distortion, thus avoiding the curse of dimensionality. We further derive probabilistic bi-Lipschitz guarantees, which trade off the amount of distortion and the probability that a randomly chosen pair of points embeds with that distortion. If $\mathcal{X}$'s geometry is sufficiently regular, we obtain stronger, bi-Lipschitz guarantees for all points in the dataset. As applications, we derive neural embedding guarantees for datasets from Riemannian manifolds, metric trees, and certain types of combinatorial graphs. When instead embedding into multivariate Gaussian mixtures, we show that probabilistic transformers can compute bi-H\"{o}lder embeddings with arbitrarily small distortion.
NAAP-440 Dataset and Baseline for Network Architecture Accuracy Prediction

Network architecture search (NAS) has become a common approach to developing and discovering new neural architectures for different target platforms and purposes. However, scanning the search space is comprised of long training processes of many candidate architectures, which is costly in terms of computational resources and time. Regression algorithms are a common tool to predicting a candidate architecture’s accuracy, which can dramatically accelerate the search procedure. We aim at proposing a new baseline that will support the development of regression algorithms that can predict an architecture’s accuracy just from its scheme, or by only training it for a minimal number of epochs. Therefore, we introduce the NAAP-440 dataset of 440 neural architectures, which were trained on CIFAR10 using a ﬁxed recipe. Our experiments indicate that by using off-the-shelf regression algorithms and running up to 10% of the training process, not only is it possible to predict an architecture’s accuracy rather precisely, but that the values predicted for the architectures also maintain their accuracy order with a minimal number of monotonicity violations. This approach may serve as a powerful tool for accelerating NAS-based studies and thus dramatically increase their efﬁciency. The dataset 1 and code used in the study 2 have been made public.
A Silent Revolution in Fundamental Astrophysics

Arbitrariness in the zeropoint of bolometric corrections is a paradigm that is nearly a century old and leads to two more paradigms. “Bolometric corrections must always be negative,” and “the bolometric magnitude of a star ought to be brighter than its V magnitude”. Both were considered valid before the IAU 2015 General Assembly Resolution B2, a revolutionary document that supersedes all three aforementioned paradigms. The purpose of this article is to initiate new insight into and a new understanding of the fundamental astrophysics and present new capabilities to obtain standard and more accurate stellar luminosities and gain more from accurate observations in the era after Gaia. The accuracy gained will aid in advancing stellar structure and evolution theories and also Galactic and extragalactic research, observational cosmology, and searches for dark matter and dark energy.
Revisiting Neural Scaling Laws in Language and Vision

The remarkable progress in deep learning in recent years is largely driven by improvements in scale, where bigger models are trained on larger datasets for longer schedules. To predict the benefit of scale empirically, we argue for a more rigorous methodology based on the extrapolation loss, instead of reporting the best-fitting (interpolating) parameters. We then present a recipe for estimating scaling law parameters reliably from learning curves. We demonstrate that it extrapolates more accurately than previous methods in a wide range of architecture families across several domains, including image classification, neural machine translation (NMT) and language modeling, in addition to tasks from the BIG-Bench evaluation benchmark. Finally, we release a benchmark dataset comprising of 90 evaluation tasks to facilitate research in this domain.
Eigenpolytope Universality and Graphical Designs

We show that the eigenpolytopes of graphs are universal in the sense that every polytope, up to affine equivalence, appears as the eigenpolytope of some positively weighted graph. We next extend the theory of graphical designs, which are quadrature rules for graphs, to positively weighted graphs. Through Gale duality for polytopes, we show a bijection between graphical designs and the faces of eigenpolytopes. This bijection proves the existence of graphical designs with positive quadrature weights, and upper bounds the size of a minimal graphical design. Connecting this bijection with the universality of eigenpolytopes, we establish three complexity results: it is strongly NP-complete to determine if there is a graphical design smaller than the mentioned upper bound, it is NP-hard to find a smallest graphical design, and it is #P-complete to count the number of minimal graphical designs.
Salinomycin biosynthesis reversely regulates the β‐oxidation pathway in Streptomyces albus by carrying a 3‐hydroxyacyl‐CoA dehydrogenase gene in its biosynthetic gene cluster

Streptomyces is well known for synthesis of many biologically active secondary metabolites, such as polyketides and non‐ribosomal peptides. Understanding the coupling mechanisms of primary and secondary metabolism can help develop strategies to improve secondary metabolite production in Streptomyces. In this work, Streptomyces albus ZD11, an oil‐preferring industrial Streptomyces strain, was proved to have a remarkable capability to generate abundant acyl‐CoA precursors for salinomycin biosynthesis with the aid of its enhanced β‐oxidation pathway. It was found that the salinomycin biosynthetic gene cluster contains a predicted 3‐hydroxyacyl‐CoA dehydrogenase (FadB3), which is the third enzyme of β‐oxidation cycle. Deletion of fadB3 significantly reduced the production of salinomycin. A variety of experimental evidences showed that FadB3 was mainly involved in the β‐oxidation pathway rather than ethylmalonyl‐CoA biosynthesis and played a very important role in regulating the rate of β‐oxidation in S. albus ZD11. Our findings elucidate an interesting coupling mechanism by which a PKS biosynthetic gene cluster could regulate the β‐oxidation pathway by carrying β‐oxidation genes, enabling Streptomyces to efficiently synthesize target polyketides and economically utilize environmental nutrients.
European beech dieback after premature leaf senescence during the 2018 drought in northern Switzerland

Abstract During the particularly severe hot summer drought in 2018, widespread premature leaf senescence was observed in several broadleaved tree species in Central Europe, particularly in European beech (Fagus sylvatica L.). For beech, it is yet unknown whether the drought evoked a decline towards tree mortality or whether trees can recover in the longer term. In this study, we monitored crown dieback, tree mortality and secondary drought damage symptoms in 963 initially live beech trees that exhibited either premature or normal leaf senescence in 2018 in three regions in northern Switzerland from 2018 to 2021. We related the observed damage to multiple climate‐ and stand‐related parameters. Cumulative tree mortality continuously increased up to 7.2% and 1.3% in 2021 for trees with premature and normal leaf senescence in 2018, respectively. Mean crown dieback in surviving trees peaked at 29.2% in 2020 and 8.1% in 2019 for trees with premature and normal leaf senescence, respectively. Thereafter, trees showed first signs of recovery. Crown damage was more pronounced and recovery was slower for trees that showed premature leaf senescence in 2018, for trees growing on drier sites, and for larger trees. The presence of bleeding cankers peaked at 24.6% in 2019 and 10.7% in 2020 for trees with premature and normal leaf senescence, respectively. The presence of bark beetle holes peaked at 22.8% and 14.8% in 2021 for trees with premature and normal leaf senescence, respectively. Both secondary damage symptoms occurred more frequently in trees that had higher proportions of crown dieback and/or showed premature senescence in 2018. Our findings demonstrate context‐specific differences in beech mortality and recovery reflecting the importance of regional and local climate and soil conditions. Adapting management to increase forest resilience is gaining importance, given the expected further beech decline on dry sites in northern Switzerland.
Kähler–Einstein metrics, canonical random
 point processes and birational geometry

In the present paper and the companion paper [8] a probabilistic (statistical mechanical) approach to the study of canonical metrics and measures on a complex algebraic variety X is introduced. On any such variety with positive Kodaira dimension a canonical (birationally invariant) random point processes is defined and shown to converge in probability towards a canonical deterministic measure on X, coinciding with the canonical measure of Song-Tian and Tsuji. The proof is based on new large deviation principle for Gibbs measures with singular Hamiltonians which relies on an asymptotic submean inequality in large dimensions, proved in a companion paper. In the case of a variety X of general type we obtain as a corollary that the (possibly singular) K\"ahler-Einstein metric on X with negative Ricci curvature is the limit of a canonical sequence of quasi-explicit Bergman type metrics. In the opposite setting of a Fano variety X we relate the canonical point processes to a new notion of stability, that we call Gibbs stability, which admits a natural algebro-geometric formulation and which we conjecture is equivalent to the existence of a K\"ahler-Einstein metric on X and hence to K-stability as in the Yau-Tian-Donaldson conjecture.
Social Media Perceptions and Internet Verification Skills Associated With Human Papillomavirus Vaccine Decision-Making Among Parents of Children and Adolescents: Cross-sectional Survey

Background Human Papillomavirus (HPV) vaccination is recommended for children aged 11-12 years in the United States. One factor that may contribute to low national HPV vaccine uptake is parental exposure to misinformation on social media. Objective This study aimed to examine the association between parents’ perceptions of the HPV vaccine information on social media and internet verification strategies used with the HPV vaccine decision-making stage for their child. Methods Parents of children and adolescents aged 9-17 years were recruited for a cross-sectional survey in North Texas (n=1192) and classified into 3 groups: children and adolescents who (1) were vaccinated, (2) unvaccinated and did not want the vaccine, and (3) unvaccinated and wanted the vaccine. Multinomial logistic regression models were estimated to identify factors associated with the HPV vaccine decision-making stage with children and adolescents who were vaccinated as the referent group. Results Of the 1192 respondents, 44.7% (n=533) had an HPV-vaccinated child, 38.8% (n=463) had an unvaccinated child and did not want the vaccine, and 16.4% (n=196) had an unvaccinated child and wanted the vaccine. Respondents were less likely to be “undecided/not wanting the vaccine” if they agreed that HPV information on social media is credible (adjusted odds ratio [aOR] 0.40, 95% CI 0.26-0.60; P=.001), disagreed that social media makes them question the HPV vaccine (aOR 0.22, 95% CI 0.15-0.33; P<.001), or had a higher internet verification score (aOR 0.74, 95% CI 0.62-0.88; P<.001). Conclusions Interventions that promote web-based health literacy skills are needed so parents can protect their families from misinformation and make informed health care decisions.
High‐Throughput Neurite Outgrowth Assay Using GFP‐Labeled iPSC‐Derived Neurons

The potential neurotoxicity from an increasing number of drugs and untested environmental chemicals creates a need to develop reliable and efficient in vitro methods for identifying chemicals that may adversely affect the nervous system. An important process in neurodevelopment is neurite outgrowth, which can be affected by developmental neurotoxicity. Currently, neurite outgrowth assays rely mainly on staining, which requires multiple sample processing steps, particularly washing steps, that may introduce variation and limit throughput. Here, we describe a neurite outgrowth assay that uses induced pluripotent stem cell (iPSC)–derived human cortical glutamatergic neurons and/or spinal motor neurons labeled with green fluorescent protein (GFP) to test compounds in a high‐content and high‐throughput format. This method enables live and time‐lapse imaging of GFP‐labeled neurons using an assay plate that is continuously imaged at multiple times after chemical treatment. In this article, we describe how to thaw frozen GFP‐labeled neurons, culture them, treat them with a compound of interest, and analyze neurite outgrowth using a high‐content imaging platform. In this assay, GFP‐labeled iPSC‐derived human neurons represent a promising tool for identifying and prioritizing compounds with potential developmental neurotoxicity for further hazard characterization. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
The ubiquity of variations of Hodge structure

Solar energy collector assembly including a solar energy collector in an enclosed space housing with bottom closure member secured by a snap-fit spring channel and low thermal conductivity mating projection therefor, a collector member securing means comprising a plurality of stiff low thermal conductivity wire retainers and top cover securing and sealing means comprising a seal and clamp engaging the top cover just inward of its periphery, to prevent intrusion of condensate in the enclosed space of the housing.