Miracle-dz/UniFAR-FTUs huggingface dataset:
Personalized Image Aesthetics Assessment via Meta-Learning With Bilevel Gradient Optimization

Typical image aesthetics assessment (IAA) is modeled for the generic aesthetics perceived by an “average” user. However, such generic aesthetics models neglect the fact that users’ aesthetic preferences vary significantly depending on their unique preferences. Therefore, it is essential to tackle the issue for personalized IAA (PIAA). Since PIAA is a typical small sample learning (SSL) problem, existing PIAA models are usually built by fine-tuning the well-established generic IAA (GIAA) models, which are regarded as prior knowledge. Nevertheless, this kind of prior knowledge based on “average aesthetics” fails to incarnate the aesthetic diversity of different people. In order to learn the shared prior knowledge when different people judge aesthetics, that is, learn how people judge image aesthetics, we propose a PIAA method based on meta-learning with bilevel gradient optimization (BLG-PIAA), which is trained using individual aesthetic data directly and generalizes to unknown users quickly. The proposed approach consists of two phases: 1) meta-training and 2) meta-testing. In meta-training, the aesthetics assessment of each user is regarded as a task, and the training set of each task is divided into two sets: 1) support set and 2) query set. Unlike traditional methods that train a GIAA model based on average aesthetics, we train an aesthetic meta-learner model by bilevel gradient updating from the support set to the query set using many users’ PIAA tasks. In meta-testing, the aesthetic meta-learner model is fine-tuned using a small amount of aesthetic data of a target user to obtain the PIAA model. The experimental results show that the proposed method outperforms the state-of-the-art PIAA metrics, and the learned prior model of BLG-PIAA can be quickly adapted to unseen PIAA tasks.
Fipa cattle in the southwestern highlands of Tanzania: molecular characterization

This study aimed at characterising the genetic diversity of two Fipa cattle populations (Sumbawanga and Nkasi) of South-Western Tanzania, and establishing their genetic relationships with the other indigenous cattle strains (Tarime, Iringa red and Ankole) and Friesian cattle found in the area. The genetic diversity was analysed using 30 microsatellite markers. All the markers used were highly polymorphic. The Nkasi Fipa cattle exhibited the highest mean number of alleles (7.31) and mean genetic diversity (0.732) per locus, followed by Sumbawanga Fipa cattle with 7.10 mean number of alleles and 0.725 mean genetic diversity per locus, with the latter population having a very low mean inbreeding coefficient (F IS = 0.027). Three percent of the genetic diversity was due to differences among indigenous strains while the rest was due to differences among individuals within the strains. Small genetic distances (D A) were observed between Sumbawanga Fipa and Nkasi Fipa (0.032), Tarime (0.073), Iringa red (0.076) and Ankole cattle (0.086). As expected, the largest genetic distances were observed between the Friesian and all indigenous strains since this breed has a quite distinct genetic origin. In the assignment test, the proportion of animals from each group correctly assigned to their source population ranged from 55.3 percent (for Nkasi Fipa) to 100 percent (for Friesian). Despite the low genetic differentiation and genetic indistinctiveness of the Sumbawanga Fipa population from the other indigenous strains, its high genetic diversity, very low inbreeding coefficient and a threat emanating from population admixture with other indigenous strains underscore the importance of establishing appropriate conservation and management strategies for it.
Kernelizing the Hitting Set Problem in Linear Sequential and Constant Parallel Time

We analyze a reduction rule for computing kernels for the hitting set problem: In a hypergraph, the link of a set c of vertices consists of all edges that are supersets of c. We call such a set critical if its link has certain easy-to-check size properties. The rule states that the link of a critical c can be replaced by c. It is known that a simple linear-time algorithm for computing hitting set kernels (number of edges) at most k^d (k is the hitting set size, d is the maximum edge size) can be derived from this rule. We parallelize this algorithm and obtain the first AC⁰ kernel algorithm that outputs polynomial-size kernels. Previously, such algorithms were not even known for artificial problems. An interesting application of our methods lies in traditional, non-parameterized approximation theory: Our results imply that uniform AC⁰-circuits can compute a hitting set whose size is polynomial in the size of an optimal hitting set.
Abundant Symmetry-Breaking Solutions of the Nonlocal Alice-Bob Benjamin-Ono System

The Benjamin–Ono equation is a useful model to describe the long internal gravity waves in deep stratified fluids. In this paper, the nonlocal Alice–Bob Benjamin–Ono system is induced via the parity and time-reversal symmetry reduction. By introducing an extended Bäcklund transformation, the symmetry-breaking soliton, breather, and lump solutions for this system are obtained through the derived Hirota bilinear form. By taking suitable constants in the involved ansatz functions, abundant fascinating symmetry-breaking structures of the related explicit solutions are shown.
Disturbance Observer-Based Continuous Finite-Time Sliding Mode Control against Matched and Mismatched Disturbances

In this paper, we propose the disturbance observer-based continuous finite-time sliding mode controller (DOBCSMC) for input-affine nonlinear systems in which additive matched and mismatched disturbances exist. The objective is to show the robustness and disturbance attenuation performance of the closed-loop system with the proposed DOBCSMC subjected to general classes of matched and mismatched disturbances. The proposed DOBCSMC consists of three main features: (i) the nonlinear finite-time disturbance observer to obtain a fast and accurate estimation of matched and mismatched disturbances, (ii) the nonlinear sliding surface to ensure high precision in the steady-state phase of the controlled output, and (iii) the continuous supertwisting algorithm to guarantee finite-time convergence of the controlled output and reduce the chattering under the effect of matched and mismatched disturbances. It should be noted that the existing approaches cannot handle time-varying mismatched disturbances and/or cannot guarantee faster finite-time stability of the controlled output. We prove that the closed-loop system with the DOBCSMC guarantees both finite-time reachability to the sliding surface and finite-time stability of the controlled output to the origin. Various simulations are performed to demonstrate the effectiveness of the proposed DOBCSMC. In particular, the simulation results show that the DOBCSMC guarantees faster convergence of the closed-loop system to the origin, higher precision of the controlled output, and better robustness performance against various classes of (time-varying) matched and mismatched disturbances, compared with the existing approaches.
FY07 LDRD Final Report Comparative Analysis of Genome Composition with Respect to Genotype-to-Phenotype Mapping and Metabolic Capability

Given the glut of sequence data, comparative genomics methods are essential to efficiently leverage existing knowledge. However, most current approaches are limited to comparisons between closely related species. We study a large collection of bacterial genomes at the level of gene content rather than precise sequence similarity, allowing us to take advantage of sequence data from even remotely related species. By linking genome content to phenotypic traits across hundreds of fully sequenced microorganisms, we intend to elucidate genotype-to-phenotype mapping, with particular emphasis on metabolic processes. Our modeling tools to decompose the genome composition include non-negative matrix factorization, linear and logit models, class association rule mining, support vector machines, and other machine learning techniques, validated against published data. The patterns we discover in gene composition across the spectrum of bacterial genomes will increase understanding of which genes, gene classes, pathways, etc. are associated with or required for specific bacterial phenotypes, as well as yielding computational predictions of function for many unknown genes. Based on a list of genes in a newly sequenced genome (or even an unassembled environmental "shotgun" sequence), we expect to predict the metabolic processes, and how the organisms fits into its environment, which will give us insight on modifying or exploiting the organism(s) in question. Such a predictive capability for genotype-to-phenotype mapping is crucial for analyzing the flood of new sequence data.
The Effect of Cultural Procedures on the Attachment of Bacteria to Chicken Breast Meat

Various bacterial strains were cultured in a laboratory medium, on chicken breast meat or derived from faeces of orally infected chicks. Suspensions of these bacterial cultures were brought in contact with chicken breast meat. The way in which the bacteria were cultured had little influence on the number of bacteria which attached to the chicken breast meat surface or on as the strength of attachment (i.e. the easiness of removal of attached bacteria). Only bacteria from the faeces of freshly infected chicks (24 h after inoculation) attached in higher numbers (more than one log10 unit) and these were less easy to remove.
Engineered Extracellular Vesicles/Exosomes as a New Tool against Neurodegenerative Diseases

Neurodegenerative diseases are commonly generated by intracellular accumulation of misfolded/aggregated mutated proteins. These abnormal protein aggregates impair the functions of mitochondria and induce oxidative stress, thereby resulting in neuronal cell death. In turn, neuronal damage induces chronic inflammation and neurodegeneration. Thus, reducing/eliminating these abnormal protein aggregates is a priority for any anti-neurodegenerative therapeutic approach. Although several antibodies against mutated neuronal proteins have been already developed, how to efficiently deliver them inside the target cells remains an unmet issue. Extracellular vesicles/exosomes incorporating intrabodies against the pathogenic products would be a tool for innovative therapeutic approaches. In this review/perspective article, we identify and describe the major molecular targets associated with neurodegenerative diseases, as well as the antibodies already developed against them. Finally, we propose a novel targeting strategy based on the endogenous engineering of extracellular vesicles/exosomes constitutively released by cells of the central nervous system.
Roost-site selection and roosting ecology of forest-dwelling bats in southern British Columbia

We used radiotelemetry to examine the roost-site preferences of four species of tree-roosting bats (Eptesicus fuscus, Lasionycteris noctivagans, Myotis evotis, and M. volans) in southern British Columbia, Canada, by radio-tracking bats to their day roosts. We found a total of 21 roost trees: 14 roosts were beneath loose bark, 5 were in cavities excavated by woodpeckers, and 2 were in natural cavities. Entrance height increased with tree height, but roost entrances tended to be situated below the level of the canopy. Of the 22 tree and site variables examined, only 3 significantly discriminated between roost trees and available trees: tree height, distance to the nearest available tree, and percent canopy closure. Bats preferred tall trees associated with low percent canopy closure and a short distance to the nearest available tree. Bats roosted in western white pine, and to a lesser extent ponderosa pine and western larch, in intermediate stages of decay more often than would be expected at random. Bats s.
Prostate‐specific membrane antigen expression in melanoma metastases

Prostate‐specific membrane antigen (PSMA) is a prostatic epithelial protein that is used as a radiotracer (68Ga‐PSMA‐11) for prostate cancer staging. PSMA‐PET/CT (positron emission tomography/computed tomography) performed for prostate cancer has been observed to detect melanoma metastases. The aim of this study was to investigate the performance of PSMA immunohistochemistry on resected melanoma metastases to explore its use as a diagnostic imaging biomarker for melanoma.
Multiparameter Flow Cytometry Assay for Analysis of Nitrosative Stress Status in Human Spermatozoa

Male infertility is an increasing health problem, and oxidative/nitrosative stress plays an important role in the etiology of this condition. Nitrosative stress due to excessive levels of reactive nitrogen species (RNS) is associated with impaired male fertility. Flow cytometry may be a useful tool for semen evaluation, but the availability of multiparameter assays for analysis of sperm quality is limited. The present study standardized a multiparameter flow cytometry analysis for nitrosative stress status in human spermatozoa in a single assay. A suitable multicolor fluorochrome panel was designed and consisted of fluorescein‐boronate to detect peroxynitrite, a highly RNS, propidium iodide to analyze viability, tetramethylrhodamine methyl ester perchlorate to detect mitochondrial membrane potential (MMP) and monobromobimane to analyze thiol oxidation. Proper positive and negative controls for each fluorochrome were used to establish the technique, and sperm cells of different qualities and spermatozoa subjected to cryopreservation were analyzed. The results showed that the controls clearly discriminated between the high and low fluorescence intensities for each fluorochrome. The analysis of sperm cells of different quality demonstrated that the assay properly detected differences in all parameters analyzed according to sperm quality. The results may be reported as the mean fluorescence intensity of each fluorochrome and the percentage of cells exhibiting different characteristics. In conclusion, a protocol was standardized to analyze nitrosative stress status, including peroxynitrite production, viability, MMP, and thiol oxidation, in a single analysis using flow cytometry. This protocol may be applied to research approaches and clinical andrology to improve the evaluation of sperm quality and provide a promising tool to increase the use of clinical flow cytometry. © 2020 International Society for Advancement of Cytometry
Comparison of air temperature measured in a vineyard canopy and at a standard weather station

The complex environment within a crop canopy leads to a high variability of the air temperature within the canopy, and, therefore, air temperature measured at a weather station (WS) does not represent the internal energy within a crop. The objectives of this study were to quantify the difference between the air temperature measured at a standard WS and the air temperature within a six-year-old vineyard (cv. Chardonnay) and to determine the degree of uncertainty associated with the assumption that there is no difference between the two temperatures when air temperature is used as input in grapevine models. Thermistors and thermocouples were installed within the vine canopy at heights of 0.5 m and 1.2 m above the soil surface and immediately adjacent to the berry clusters. In the middle of the clusters sensors were installed to determine the temperature of the air surrounding the clusters facing east and west. The data were recorded within the canopy from December 2015 to June 2017 as well as at the standard WS that was installed close to the vineyard (410 m). Significant differences were found between the air temperatures measured at the WS and those within the vineyard during the summer when the average daily minimum air temperature within the canopy was 1.2°C less than at the WS and the average daily maximum air temperature in the canopy was 2.0°C higher than at the WS. The mean maximum air temperature measured in the clusters facing east was 1.5°C higher and west 4.0°C higher than the temperature measured at the WS. Therefore, models that assume that air temperature measured at a weather station is similar to air temperature measured in the vineyard canopy could have greater uncertainty than models that consider the temperature within the canopy.
XenoNet: Inference and Likelihood of Intermediate Metabolite Formation

Drug metabolism is a common cause of adverse drug reactions. Drug molecules can be metabolized into reactive metabolites, which can conjugate to biomolecules, like protein and DNA, in a process termed bioactivation. To mitigate adverse reactions caused by bioactivation, both experimental and computational screening assays are utilized. Experimental assays for assessing the formation of reactive metabolites are low-throughput and expensive to perform, so they are often reserved until later stages of the drug development pipeline when the drug candidate-pools are already significantly narrowed. In contrast, computational methods are high-throughput and cheap to perform to screen thousands to millions of compounds for potentially toxic molecules during the early stages of the drug development pipeline. Commonly used computational methods focus on detecting and structurally characterizing reactive metabolite-biomolecule adducts or predicting sites on a drug molecule that are liable to form reactive metabolites. However, such methods are often only concerned with the structure of the initial drug molecule or of the adduct formed when a biomolecule conjugates to a reactive metabolite. Thus, these methods are likely to miss intermediate metabolites that may lead to subsequent reactive metabolite formation. To address these shortcomings, we create XenoNet, a metabolic network predictor that can take a pair of a substrate and a target product as input and (1) enumerate pathways, or sequences of intermediate metabolite structures, between the pair, and (2) compute the likelihood of those pathways and intermediate metabolites. We validate XenoNet on a large, chemically-diverse data set of 17,054 metabolic networks built from a literature-derived reaction database. Each metabolic network has a defined substrate molecule that has been experimentally observed to undergo metabolism into a defined product metabolite. XenoNet can predict experimentally observed pathways and intermediate metabolites linking the input substrate and product pair with a recall of 88% and 46%, respectively. Using likelihood scoring, XenoNet also achieves a top-one pathway and intermediate metabolites accuracy of 93.6% and 51.9%, respectively. We further validate XenoNet against prior methods for metabolite prediction. XenoNet significantly outperforms all prior methods across multiple metrics. XenoNet will be available at https://swami.wustl. edu/xenonet.
Management of lithium dosing around delivery: An observational study

Recommendations on lithium dosing around delivery vary, with several guidelines suggesting that lithium should be discontinued prior to delivery. We aimed to evaluate the validity of these recommendations by investigating 1) maternal lithium blood level changes following delivery, and 2) the association between neonatal lithium blood levels at delivery and neonatal outcomes.
Four parameters of the wound response of loblolly and shortleaf pines to inoculation with the blue-staining fungus associated with the southern pine beetle

The wound response of loblolly, Pinus taeda L. , and shortleaf, P. echinata Mill. , pine was examined for 14 days following wounding and inoculation of the trees with Ceratocystis minor (Hedgecock) Hunt, a fungal associate of the southern pine beetle, Dendroctonus frontalis Zimmermann. Lesion length increased at a constant rate during June, while during July there was an initially rapid lesion formation followed by a leveling off for both tree species. Lesion enlargement occurred faster from days 2 through 7 in July for both species, and at the end of the 14-day study periods, the loblolly pines had a longer average lesion length than did the shortleaf pines during both months. During June, there was an initial increase in resin flow rate followed by a decrease in resin flow rate for several days and then an increased resin flow rate to levels similar to or above the rate measured prior to wounding. During July, the initial increase in resin flow rate following inoculation was not observed. Average soluble-.
Evidence that Olisthodiscus luteus is a member of the Chrysophyceae

Abstract The biochemical and ultrastructural features of Olisthodiscus luteus Carter are compared to those of the five classes of algae which have chloroplasts that are enclosed by chloroplast ER and possess girdle lamellae and a peripheral ring-shaped nucleoid. It is concluded that O. luteus belongs to the Chrysophyceae. Particular attention is paid to the question of whether Olisthodiscus might belong to the Chloromonadophyceae, but several important differences between the chloromonads and O. luteus are noted. For example, the carotenoid pigments of Olisthodiscus are similar to those of the Chrysophyceae and very different from those so far observed in the Chloromonadophyceae. Also Olisthodiscus is not divided into endoplasmic and ectoplasmic regions as all chloromonad cells are, nor does Olisthodiscus possess the characteristic chloromonad rhizostyle. Mitosis in Olisthodiscus is typically Chrysophyceall with an open spindle, whereas in mitotic cells of chloromonads the spindle is closed.
Stable Fibroblast Growth Factor 2 Dimers with High Pro-Survival and Mitogenic Potential

Fibroblast growth factor 2 (FGF2) is a heparin-binding growth factor with broad mitogenic and cell survival activities. Its effector functions are induced upon the formation of 2:2 FGF2:FGFR1 tetrameric complex. To facilitate receptor activation, and therefore, to improve the FGF2 biological properties, we preorganized dimeric ligand by a covalent linkage of two FGF2 molecules. Mutations of the FGF2 WT protein were designed to obtain variants with a single surface-exposed reactive cysteine for the chemical conjugation via maleimide-thiol reaction with bis-functionalized linear PEG linkers. We developed eight FGF2 dimers of defined topology, differing in mutual orientation of individual FGF2 molecules. The engineered proteins remained functional in terms of FGFR downstream signaling activation and were characterized by the increased stability, mitogenic potential and anti-apoptotic activity, as well as induced greater migration responses in normal fibroblasts, as compared to FGF2 monomer. Importantly, biological activity of the dimers was much less dependent on the external heparin administration. Moreover, some dimeric FGF2 variants internalized more efficiently into FGFR overexpressing cancer cells. In summary, in the current work, we showed that preorganization of dimeric FGF2 ligand increased the stability of the growth factor, and therefore, enhanced its biological activity.