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Karst remote sensing ecological index KRSEI for monitoring ecological quality in Southwest China
Photoperiodic flowering regulators are required for nitrogen-dependent flowering delay in rice under long-day condition
Impaired antibody responses to heterologous ChAdOx1 nCoV-19 and BNT162b2 vaccination in individuals with type 2 diabetes
Reply to: Altered effort and deconditioning are not valid explanations of myalgic encephalomyelitis/chronic fatigue syndrome
Single-nucleus transcriptome profiling provides insights into the pathophysiology of OSA-related renal injury
Local microwave sensing of excitons and their electrical environment
Recurrent issues with deep neural network models of visual recognition
Abstract Object recognition requires flexible and robust information processing, especially in view of the challenges posed by naturalistic visual settings. The ventral stream in visual cortex is provided with this robustness by its recurrent connectivity. Recurrent deep neural networks (DNNs) have recently emerged as promising models of the ventral stream, surpassing feedforward DNNs in the ability to account for brain representations. In this study, we asked whether recurrent DNNs could also better account for human behaviour during visual recognition. We assembled a stimulus set that includes manipulations that are often associated with recurrent processing in the literature, like occlusion, partial viewing, clutter, and spatial phase scrambling. We obtained a benchmark dataset from human participants performing a categorisation task on this stimulus set. By applying a wide range of model architectures to the same task, we uncovered a nuanced relationship between recurrence, model size, and performance. First, results show that increases in performance were most strongly linked to increases in model size, with architecture seemingly not playing a role, even for more challenging manipulations. Second, we found larger models to be more consistent with humans on which manipulations they found more difficult, regardless of model architecture. Finally, we found a negative effect of size in matching human confusion matrices in recurrent but not feedforward DNNs. Contrary to previous assumptions, our findings challenge the notion that recurrent models are better models of human recognition behaviour than feedforward models, and emphasise the complexity of incorporating recurrence into computational models.
Global hidden material flows triggered by China’s vehicle supply chain far exceed eventual material use
Differences and fingerprints of ESBL-producing E. coli from chicken faeces
Structure-function relationship of the GH168 fucanase reveals an unusual enzyme recognition mechanism for sulfated polysaccharide
Childhood visual impairment in Qassim region of Saudi Arabia prevalence causes and risk factors
Efficient active hydrogen delivery for drug-free radiation enteritis therapy in mice
Determination of yield losses against sheath rot caused by Sarocladium oryzae in rice varieties with differential resistance
Abstract Sheath rot (Sarocladium oryzae) of rice causes significant grain yield losses, warranting integrated, cost effective and eco-friendly management. With limited availability of highly resistant varieties, combining resistant / moderately resistant varieties with judicious and need based application of fungicides is a practical alternative. However, scarce information is available on the extent of yield losses in varieties with varied levels of resistance. This study evaluated yield losses in terms of 1000 grain weight (TGW) in rice varieties with varying resistance levels to sheath rot under protected conditions using fungicide azoxystrobin (11%) + tebuconazole (13.8%). It was observed that the differences in disease severity, AUDPC values and TGW loss were mainly attributed to the interaction effects among the treatment i.e. fungicide sprayed (protected) and fungicide non-sprayed (unprotected) treatment, and varieties & between varieties and years (P < 0.001). Plots with fungicidal application had a mean disease severity of 5.60% compared to 25.46% in untreated plots. Protected plots had a mean TGW of 24.80 g compared with 20.59 g in unprotected plots, reflecting a significant differences . Fungicide applications resulted in reduction of mean disease severity of 100, 74.03–97.57, 69.62–80.92, and 72.29–73.95% in resistant, moderately resistant, susceptible and highly susceptible varieties, respectively. A strong positive correlation was observed between disease severity and TGW loss during the cropping season 2019, 2020 and pooled data. The grain yield was enhanced, and crop loss models indicated good fitness with excellent predictive validity for estimating sheath rot impacts. As the first systematic assessment in northern region of India to systematically assess the impact of rice sheath rot. Its findings provide crucial insights into the interaction between fungicide treatments, varietal resistance, and disease dynamics, paving the way for more informed and effective management strategies in the region.
Seed structure and phosphorylation in the fuzzy coat impact tau seeding competency
Abstract Tau misfolding into β-sheet–rich filaments and subsequent recruitment of monomeric tau are central to Alzheimer’s disease (AD) pathogenesis. While cryo-EM has resolved the conformation of the AD tau core, the structural features conferring biological activity remain unclear. Here, we investigated how tau filament core structure and post-translational modifications influence seeding capacity in neurons and mice. Our findings show that although filament structure impacts seeding, the AD tau core alone is insufficient to fully replicate AD tau’s biological activity. The unstructured fuzzy coat, particularly phosphorylation within this region, is essential for full seeding competence. Importantly, recombinant tau filaments bearing twelve phospho-mimetic residues (PAD12 tau) and adopting the AD fold recapitulate the seeding activity of native AD tau. These results demonstrate that tau filament pathogenicity arises from the combined contributions of both the ordered core structure and post-translational modifications within the fuzzy coat, providing critical insights into mechanisms underlying tau-driven neurodegeneration.
Validating a remote saliva collection tool for genomic analyses in free ranging dogs
Abstract Saliva is a well-established source of DNA for various applications due to its non-invasive collection and its provision of high-quality DNA. However, its use in wild and free-ranging animal research remains limited due to challenges in collection without direct animal handling. In this study, we developed and evaluated a hands-off saliva collection method designed for free-ranging domestic dogs (FRDs), serving as a model for non-invasive genetic sampling of wildlife. Our method utilized a funnel paired with a commercially available Performagene kit (DNA Genotek, Canada), presented to the dog in the presence of an operator. The dog was free to approach and interact with the apparatus, depositing saliva while trying to reach bait. We compared DNA yield and genotyping success from samples using this hands-off method with those collected via the manufacturer’s recommended method. We collected 461 saliva samples from 326 FRDs, performing 750 DNA extractions. Samples collected by hand yielded significantly higher DNA concentrations after the first extraction attempt (mean = 46.3 ng/µL) than those collected using the hands-off method (mean = 32.2 ng/µL). Despite lower DNA concentrations, genotyping success did not significantly differ between methods, demonstrating that the hands-off method can yield DNA suitable for genomic analyses. The hands-off saliva collection method is a viable alternative to invasive sampling, addressing ethical concerns and enabling genomic studies in wild animals. Furthermore, our method mitigates sampling bias toward bold individuals, a common limitation in behavioral and genetic studies of free-ranging animals. With minor adaptations, this method could be applied across various species, including more elusive ones, contributing to conservation genetics and behavioral ecology research.
Generation, transmission, and conversion of orbital torque by an antiferromagnetic insulator
Abstract Electrical control of magnetization in nanoscale devices can be significantly improved through the efficient generation of orbital currents and their conversion into spin currents. In nonmagnetic/ferromagnetic bilayers, this conversion produces a torque on the magnetization, enabling magnetization switching and dynamic manipulation. While previous studies focus on metallic ferromagnets, we demonstrate a large orbital torque and enhanced orbital-to-spin conversion by an antiferromagnetic insulating CoO layer. Measurements in CuOx/CoO/Co trilayers show that inserting CoO reverses the torque’s sign and triples its magnitude compared to CuOx/Co. This behaviour stems from the inverted oxygen gradient at the CuOx/CoO interface and CoO’s high orbital multiplicity, which favours the transmission of orbital momenta and efficient orbital-to-spin conversion. At low temperatures, the onset of antiferromagnetic order induces a further many-fold increase of the torque, which we attribute to the efficient excitation and propagation of spin-orbit excitons induced by magnetic coupling. Comparative measurements of CuOx/NiO/Co and CuOx/MnO/Co trilayers show that the torque efficiency scales with the orbital momentum of the Co2+, Ni2+, and Mn2+ ions in the antiferromagnet. These results reveal that antiferromagnetic insulators like CoO provide highly effective orbital-to-spin transduction, combining orbital torque and exchange bias functionalities to improve the performance of spintronic devices.
Mechanical response and energy dissipation law of double-fractured sandstone under dynamic load
Abstract To study the dynamic mechanical response and energy dissipation law of fractured sandstone, an SHPB device combined with a high-speed camera system was used to carry out impact compression tests with seven rock bridge angle specimens. The dynamic strength characteristics of fractured sandstone and the crack initiation stress at the fracture tip was explored. The fractal characteristics of debris were quantitatively described, and the relationship between energy dissipation and fractal dimension and average debris size was analyzed. In addition, a significant rate effect between rock angle and dynamic load was observed with peak stress degradation value of the sample been significantly affected by the rock angle. The results show that the strain value of peak stress increases first and then decreases with rock angle increase; the peak stress values of the intact specimen show a sensitive change characteristic, and the prefabricated fractures significantly weaken the peak stress. The maximum and minimum rock angles are 0°and 90°, respectively. Under low dynamic load and small rock bridge angle, cracks are single and dispersed; under high dynamic load and large rock bridge angle, crack types are diverse, showing a composite failure of shear and tension. Dynamic load and rock bridge angle have a significant impact on the stress and deterioration performance of the samples, especially under higher dynamic load and larger rock bridge angle, where the stress deterioration of the samples is more pronounced. The crack initiation stress at the fracture tip decreases with rock angle increase and is lower than the peak stress. There are significant differences in the initiation time of cracks (damage velocity) at the fracture tip. The damage velocity is significantly affected by dynamic load; there is a significant rate effect between the incident energy and the reflected energy and the dynamic load. The energy dissipation rate and fractal dimension increase with dynamic load; the energy dissipation rate has an opposite relationship with the exponential curve of fractal dimension and average fragment size, and the 60° specimen shows more sensitive fractal variation characteristics.