Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of Factor Mixture Models as a Function of Model Size, Covariate Effects, and Class-Specific Parameters

Abstract Factor mixture models are designed for the analysis of multivariate data obtained from a population consisting of distinct latent classes. A common factor model is assumed to hold within each of the latent classes. Factor mixture modeling involves obtaining estimates of the model parameters, and may also be used to assign subjects to their most likely latent class. This simulation study investigates aspects of model performance such as parameter coverage and correct class membership assignment and focuses on covariate effects, model size, and class-specific versus class-invariant parameters. When fitting true models, parameter coverage is good for most parameters even for the smallest class separation investigated in this study (0.5 SD between 2 classes). The same holds for convergence rates. Correct class assignment is unsatisfactory for the small class separation without covariates, but improves dramatically with increasing separation, covariate effects, or both. Model performance is not influenced by the differences in model size investigated here. Class-specific parameters may improve some aspects of model performance but negatively affect other aspects.
Impedance spectroscopy study of hybrid photovoltaic supercapacitors

The integration of energy-harvesting and storage in a single device is considered to be one of the most demanding technologies for future wireless sensors. Photovoltaic supercapacitors are among promising solutions with the dual properties of photoelectric and electrochemical charge storage. In order to improve the efficiency in hybrid photovoltaic supercapacitors, most research has focused on studying electrode materials. In this work, we have studied the effect of polyaniline (PANI) concentration in a composite gel-based electrolyte on the impedance of the device. The photovoltaic supercapacitors were fabricated in a two-electrode configuration combining a titanium dioxide (TiO2) coated on fluorine-doped tin oxide (FTO) glass as the working electrode, a multi-walled carbon nanotube (MWCNT) porous electrode as the counter electrode, and a composite gel-based electrolyte. The composite gel was made of polyvinyl alcohol (PVA), hydrochloric acid (HCl), ammonium persulfate (APS), and different concentrations of aniline (ANI). The impedance study of the gel with 0.5 mM concentration of PANI showed a two-stage charge storage mechanism associated to the double-layer at the electrode-electrolyte interface and a pseudo-capacitive charge storage mechanism in the bulk of the electrolyte. The absorption spectrum of the synthesized gel shows a strong absorption peak near 780 nm confirming the formation of the emeraldine salt of PANI in the gel. The current results are inspiring the research for optimizing the composite material to improve both energy harvesting and the charge storage stability in photovoltaic supercapacitors.
Metabolomic signature of the maternal microbiota in the fetus

The maternal microbiota affects the development of the offspring by microbial metabolites translocating to the fetus. We investigated samples of placenta, fetal intestine and brain from germ-free (GF) and specific pathogen free (SPF) mouse dams by non-targeted metabolic profiling. One hundred one annotated metabolites and altogether 3680 molecular features were present in significantly different amounts in the placenta and/or fetal organs of GF and SPF mice. The concentrations of more than half of the annotated and differentially expressed metabolites were lower in the GF organs, suggesting their microbial origin or a metabolic response of the host to the presence of gut microbiota. The clearest separation was observed in the placenta. Metabolites that were detected in lower amounts in the fetal organs in the GF mice included 5-aminovaleric acid betaine, trimethylamine N-oxide, catechol-O-sulphate, hippuric and pipecolic acid. Derivatives of the amino acid tryptophan, such as kynurenine, 3-indolepropionic acid and hydroxyindoleacetic acid, were also decreased in the absence of microbiota. Several metabolites had higher levels in the GF mice. These could be precursors of microbial metabolites or indicators of host metabolic response to the absence of gut microbiota. Ninety-nine molecular features were only detected in the SPF mice, suggesting the existence of yet unidentified microbially modified metabolites that potentially influence fetal development.
Assessments of S-NPP and N20 VIIRS DNB and M bands calibration stability and consistency using a homogeneous ground target

The S-NPP and N20 VIIRS Day-Night band (DNB) and M bands top-of-atmosphere (TOA) radiance and reflectance are calculated and a kernel-driven Bidirectional Reflectance Distribution Function (BRDF) correction model is used to correct the surface and atmosphere combined BRDF influence. Due to degradation in the DNB modulated Relative Spectral Response (RSR), the S-NPP VIIRS observed TOA DNB reflectance indicates a decrease of 1.89% and the SCIAMACHY spectra derived TOA DNB reflectance has a decrease of 1.63% for the past 8.5 years. The N20 VIIRS TOA DNB reflectance decreased 0.50% in the past 2.5 years. The DNB radiance is also compared with the integral of the M bands radiance from M4, M5, and M7. The fitting trends of DNB to the integral of M bands ratios indicate a 0.48% decrease for S-NPP VIIRS and 0.14% increase for N20 VIIRS. The N20 VIIRS DNB to integral M bands ratios are closer to 1 than the S-NPP VIIRS data. The BRDF corrected reflectance comparisons show that the N20 VIIRS data is slightly lower than those of S-NPP VIIRS. The averages of the linear fit values of the N20 to S-NPP VIIRS from 2018 to 2020 June are - 1.97%, -4.99%, -3.36%, and -0.85% for M4, M5, M7, and DNB, respectively. Our results indicate that the S-NPP and N20 VIIRS DNB and M bands calibration have been stable. The cross-sensor differences in DNB and M bands are generally consistent with other independent studies using similar and different approaches.
The Huntingtin-interacting protein SETD2/HYPB is an actin lysine methyltransferase

SETD2 regulates actin dynamics and cell migration via methylation of actin at Lys68 in a cellular complex containing Huntingtin. The methyltransferase SET domain–containing 2 (SETD2) was originally identified as Huntingtin (HTT) yeast partner B. However, a SETD2 function associated with the HTT scaffolding protein has not been elucidated, and no linkage between HTT and methylation has yet been uncovered. Here, we show that SETD2 is an actin methyltransferase that trimethylates lysine-68 (ActK68me3) in cells via its interaction with HTT and the actin-binding adapter HIP1R. ActK68me3 localizes primarily to the insoluble F-actin cytoskeleton in cells and regulates actin polymerization/depolymerization dynamics. Disruption of the SETD2-HTT-HIP1R axis inhibits actin methylation, causes defects in actin polymerization, and impairs cell migration. Together, these data identify SETD2 as a previously unknown HTT effector regulating methylation and polymerization of actin filaments and provide new avenues for understanding how defects in SETD2 and HTT drive disease via aberrant cytoskeletal methylation.
Breeding biology and mating system of Brown Accentors Prunella fulvescens on the Tibet Plateau

ABSTRACT Capsule: The mating system of the Brown Accentor Prunella fulvescens in the high altitudes of the Tibeta plateau is mainly monogamous but polyandry was recording in 9.7% of breeding groups. Aims: To describe the poorly known breeding biology of Brown Accentors in the high-altitude environment of the northeastern Tibet plateau. Methods: Individually colour-ringed birds were observed during two breeding seasons. Biometrics were recorded for breeders, and reproductive variables were quantified. Results: Brown Accentors were territorial during the breeding season and were resident year-round. Most groups (90.3%, n = 31 groups) were socially monogamous and the remainder (9.7%) were polyandrous, with two males sharing a female’s territory. Mean group size was 2.1 adults and the population adult sex ratio was 52% male. The birds raised a single brood during the breeding season. Nests were invariably located in Sea Buckthorn Hippophae rhamnoides. Eggs were laid between late June and late July, and mean clutch size was 3.4 ± 0.6 (SD) eggs. Incubation was undertaken by the female and lasted 12.9 ± 0.9 (SD) days. Both sexes provisioned young in the nest for 13.9 ± 1.2 (SD) days. Females provided significantly more feeding visits than did males. Brood size at estimated fledging dates averaged 2.2 ± 0.7 (SD) nestlings. Forty-five per cent of nesting attempts (n = 37) fledged at least one nestling. Conclusions: Like other species in the family Prunellidae, the Brown Accentor exhibits remarkable variation in its mating system.
Susceptibility of Midge and Mosquito Vectors to SARS-CoV-2

Abstract SARS-CoV-2 is a recently emerged, highly contagious virus and the cause of the current COVID-19 pandemic. It is a zoonotic virus, although its animal origin is not clear yet. Person-to-person transmission occurs by inhalation of infected droplets and aerosols, or by direct contact with contaminated fomites. Arthropods transmit numerous viral, parasitic, and bacterial diseases; however, the potential role of arthropods in SARS-CoV-2 transmission is not fully understood. Thus far, a few studies have demonstrated that SARS-CoV-2 replication is not supported in cells from certain insect species nor in certain species of mosquitoes after intrathoracic inoculation. In this study, we expanded the work of SARS-CoV-2 susceptibility to biting insects after ingesting a SARS-CoV-2-infected bloodmeal. Species tested included Culicoides sonorensis (Wirth & Jones) (Diptera: Ceratopogonidae) biting midges, as well as Culex tarsalis (Coquillett) and Culex quinquefasciatus (Say) mosquitoes (Diptera: Culicidae), all known biological vectors for numerous RNA viruses. Arthropods were allowed to feed on SARS-CoV-2-spiked blood and at a time point postinfection analyzed for the presence of viral RNA and infectious virus. Additionally, cell lines derived from C. sonorensis (W8a), Aedes aegypti (Linnaeus) (Diptera: Culicidae) (C6/36), Cx. quinquefasciatus (HSU), and Cx. tarsalis (CxTrR2) were tested for SARS-CoV-2 susceptibility. Our results indicate that none of the biting insects, nor the insect cell lines evaluated support SARS-CoV-2 replication, suggesting that these species are unable to be biological vectors of SARS-CoV-2.
Discovery of a Novel Mtdna Sequence in the Eastern Buzzard (Buteo Japonicus) in Japan

Abstract. In recent years, several phylogenetic studies on the genus Buteo have been conducted. However, little is known about the lineage of the Eastern Buzzard (Buteo japonicus). We sequenced 919-bp fragments of mtDNA from 45 Eastern Buzzards from Japan and compared them with the sequences of the genus Buteo registered in the DDBJ/EMBL/GenBank databases. ND6 and pseudo control region phylogenetic analyses were performed on 15 and 35 specimens in the database, respectively. All 45 Eastern Buzzards from Japan possessed the same novel sequence in the ND6 gene, which differed in four base pairs from sequences previously reported for the Eastern Buzzard from continental Asia. Phylogenetic analysis of the ND6 gene showed that Japanese birds with the novel sequence did not form a clade with those from continental Asia with the previously reported sequences; instead, the continental Eastern Buzzard formed a clade with Himalayan Buzzards (Buteo refectus). A phylogenetic tree constructed using pseudo control region sequences showed that Eastern Buzzards were divided into two groups: one containing the Himalayan Buzzard, and one containing birds with the novel sequence. Our results suggested that the novel sequence revealed in this study is a geographic variant that may represent the “true” Eastern Buzzard, and that the previously reported sequence (from continental Asia) is that of the Himalayan Buzzard. We suggest that it is necessary to examine the habitats and characteristics of Eastern and Himalayan Buzzards in eastern Eurasia to more accurately classify these birds.
Effects of chitin degradation products N-acetylglucosamine and N,Nʹ-diacetylchitobiose on chitinase activity and bacterial community structure in an incubated upland soil

ABSTRACT Chitin, which is the polymer of N-acetylglucosamine (GlcNAc) linked by β1,4 glycoside bonds, has been reported as a soil amendment to mitigate plant soil diseases, increasing the population of chitin-degrading bacteria, and chitinolytic enzymatic activity in the soil. In some chitin-degrading bacteria, whose chitinolytic systems have been intensively studied, the chitin degradation product N,Nʹ-diacetylchitobiose {(GlcNAc)2} induces expression of genes for chitinases whereas GlcNAc does not. To evaluate the effects of these mono- and disaccharides on the population and activity of chitinolytic bacteria in soil, we investigated the chitinolytic enzyme activity and bacterial community structure in an incubated upland soil supplemented with GlcNAc or (GlcNAc)2. The added GlcNAc and (GlcNAc)2 (2 mg g−1) were consumed within 1 d when incubated at 25°C. Chitinase activity was induced by (GlcNAc)2 and chitin after 1-d and 7-d incubation, respectively, but not by GlcNAc. N-acetylglucosaminidase (GlcNAcase) activity was induced by GlcNAc but was lower than those by (GlcNAc)2 and chitin. Amplicon sequencing analysis targeting 16S rRNA genes demonstrated that both GlcNAc and (GlcNAc)2 significantly increased the rate of the order Bacillales, but the compositions of Bacillales differed from each other: the family Planococcaceae significantly increased in either GlcNAc- or (GlcNAc)2-added soil, but the genera Bacillus and Paenibacillus were increased mainly by GlcNAc and (GlcNAc)2, respectively. The family Streptomycetaceae of the order Actinomycetales was significantly increased by (GlcNAc)2 and chitin, but GlcNAc did not. Thus, GlcNAc and (GlcNAc)2, which were promptly consumed in the incubated soil, indicated partly similar but distinctive effects on chitinolytic enzyme activity and bacterial communities. Both aminosugars increased GlcNAcase activity and the population size of Planococcaceae. GlcNAc increased Bacillus. Chitinase activity and the populations of Paenibacillus and Streptomycetaceae, a number of strains of which are known as potent chitin-degraders, were increased by (GlcNAc)2, but not by GlcNAc.
Automatic analysis of breast thermograms by convolutional neural networks

Temperature patterns of the breast measured using infrared thermography have been used to detect changes in blood perfusion that can occur due to inflammation, angiogenesis, or other pathological causes. In this work, 94 thermograms of patients with suspected breast cancer were analyzed using an automatic classification method, based on a convolutional neural network. In particular, our approach uses a deep convolutional neural network (CNN) with transfer learning to automatically classify thermograms into two different tasks: normal and abnormal thermograms, and malign and benign lesions. Class Activation Mapping is used to show how the network can focus on the affected areas without having received this information. Several measurements were carried out to validate the performance of the network in each task and these results suggest that deep convolutional neural networks with transfer learning are able to detect thermal anomalies in thermograms with sensitivity similar to that of a human expert, even in cohorts with a low prevalence of breast cancer.
Cross-codec encoding optimizations for video transcoding

A video on demand (VOD) server generates multiple video output qualities (bit rates), resolutions and codecs to best video quality for all viewers’ internet connection. While each codec optimizes tools and does computation-quality tradeoff there isn't much work to exploit computation reduction across codecs. In this work, we propose some methods to achieve this. Specifically, we use VP9 mode decision to reduce the computational requirements of AV1 encoding.
Fast transform type selection using conditional Laplace distribution based rate estimation

Selecting among multiple transform kernels to code prediction residuals is widely used for better compression efficiency. Conventionally, the encoder performs trials of each transform to estimate the rate-distortion (R-D) cost. However, such an exhaustive approach suffers from a significant increase of complexity. In this paper, a novel rate estimation approach is proposed to by-pass the entropy coding process for each transform type using the conditional Laplace distribution model. The proposed method estimates the Laplace distribution parameter by the context inferred by the quantization level and finds the expected rate of the coefficients for transform type selection. Furthermore, a greedy search algorithm for separable transforms is also presented to further accelerate the process. Experimental results show that the transform type selection scheme using the proposed rate estimation method achieves high accuracy and provides a satisfactory speed-performance trade-off.
Recognition of objects based on deep learning in an RPAS

A combination between research lines of robotics and artificial intelligence and using computer vision, this consists of using robotic systems that can recognize and understand images and scenes, generally integrate the Areas: detection of objects image recognition and Image Generation Object detection is sophisticated and more in robotics due to countless applications that can develop through image processing. This article shows the implementation of the NVIDIA® Jetson development card in a remote control unmanned aerial system (RPAS) for object recognition, based on focal loss. Hence, it is a challenge to obtain results, which it faces to develop it will show in the expected final solution.
Identification of a unique ZIP transporter involved in zinc uptake via the arbuscular mycorrhizal fungal pathway

Low soil zinc (Zn) availability is a limiting factor for crop yield, and increasing Zn content is a major target for the biofortification of major crops. Arbuscular mycorrhizal (AM) fungi associate with the roots of most terrestrial plant species and improve the host plant’s growth and nutrition through the mycorrhizal pathway of nutrient uptake. Although the physiology of Zn uptake through the mycorrhizal pathway is well established, the identity of the molecular components responsible for Zn transport in the mycorrhizal pathway are unknown. RNA-seq analysis identified the putative Zn transporter gene MtZIP14 by its marked up-regulation in Medicago truncatula roots when colonised by the AM fungus Rhizophagus irregularis under varying soil Zn supply. Expression of GFP-tagged MtZIP14 in roots revealed that it is exclusively localised to the site of plant-fungal nutrient exchange in cortical cells, the peri-arbuscular membrane. Expression of MtZIP14 in a yeast mutant lacking Zn transport function restored growth under low Zn availability. M. truncatula MtZIP14 loss-of-function mutants had reduced shoot biomass compared to the wild-type when colonised by AM fungi and grown under low Zn. Vesicular and arbuscular colonisation, but not hyphal colonisation, were also lower in mtzip14 mutant plants. Based on these results we propose that MtZIP14 plays a key role in the transport of Zn from AM fungus to plant across the peri-arbuscular membrane, and MtZIP14 function is crucial to plant competitiveness in a low Zn soil. Significance statement Majority of crop plant species associate with arbuscular mycorrhizal fungi, which can increase plant nutrient uptake. Improving our knowledge of how Zn is taken up in mycorrhizal plants will lead to improved plant and human Zn nutrition outcomes. Here, we report a novel plant transporter with a major role in Zn nutrition of mycorrhizal plants. MtZIP14 is involved in Zn transport, is exclusively localised to the specialised plant-fungal interface in roots, and impairment of MtZIP14 gene function results in negative impacts on both plant growth and Zn nutrition.
Self-Tracking Health Over Time: From the Use of Instagram to Perform Optimal Health to the Protective Shield of the Digital Detox

Instagram and self-tracking technologies enable multiple ways to perform and represent the body and health. No research has yet explored how self-tracking technologies and self-representations of health identity on social media, in particular Instagram, influence health “sharing” online and individual health management offline. To enable a thorough investigation of how self-tracking mediations of identity construction work in practice, through a textual and thematic analysis of empirical ethnographic data from online content, reflexive diaries and semi-structured interviews with 14 participants, this research examines the use of these converged technologies to share health-related data on Instagram in the performance of optimal health identities. Participants identified pressures that arose from this continual performative identity of being a healthy role model under persistent self- and community surveillance, which also led to the development of powerful compulsions to use these technologies to document and share many aspects of health and lifestyle. Over time, the participants attempted to disengage and detox either temporarily or permanently from Instagram, to enable a protective shield from the pervasive, normalized surveillance and community practices. Most interestingly, even when they removed these technologies and platforms from their daily lives, participants still felt neglectful to their devices, to themselves, and to their communities online in their abstinence and resistance to perform optimal health practices.
Comparative studies of the fluorescence spectroscopy and dynamics of mCerulean3 and mTurquoise2.1 as donors in FRET pairing with mCitrine

We investigated the donor effects (mCerulean3 versus mTurquoise2.1) on the spectroscopy and dynamics of mCerulean3-linker-mCitrine constructs using integrated fluorescence spectroscopy methods. Here, mCerulean3 (a cyan fluorescent protein) and mCitrine (a yellow fluorescent protein) act as Förster resonance energy transfer (FRET) pair, separated by flexible linker region. We hypothesize that the construct with mTurquoise2.1 would have many advantages as a donor, which include a higher FRET efficiency as compared with the mCerulean3 due to the enhanced spectral overlap with mCitrine. To test this hypothesis, we used steady-state spectroscopy, time-resolved fluorescence, and fluorescence correlation spectroscopy of both mCerulean3-linker-mCitrine and mTurquoise2.1-linker-mCitrine to investigate the donor effect on the FRET efficiency and translational diffusion as a means for developing a rational design for hetero-FRET constructs for environmental sensing.