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Abstract We present room-temperature measurements of magnon spin diffusion in epitaxial ferrimagnetic insulator MgAl 0.5 Fe 1.5 O 4 (MAFO) thin films near zero applied magnetic field where the sample forms a multi-domain state. Due to a weak uniaxial magnetic anisotropy, the domains are separated primarily by 180° domain walls. We find, surprisingly, that the presence of the domain walls has very little effect on the spin diffusion – nonlocal spin transport signals in the multi-domain state retain at least 95% of the maximum signal strength measured for the spatially-uniform magnetic state, over distances at least five times the typical domain size. This result is in conflict with simple models of interactions between magnons and static domain walls, which predict that the spin polarization carried by the magnons reverses upon passage through a 180° domain wall. 

Although humic substances are the principal ingredients in processed humic products, there has been no practical way to determine if a material is humified, allowing fake products to be used by farmers instead of genuine humic substances.

To develop a test method using conventional laboratory techniques to determine if a material is humified.

A neutralized extract is prepared using the standardized extraction protocols specified in ISO 19822:2018(E). A portion of the extract is used to determine the concentration of dissolved organic matter on an ash-free basis. A portion of the remaining neutralized extract is diluted to a concentration of 30 mg/kg of dissolved organic matter and transferred to a quartz UV cuvette for ultraviolet-visible (UV-Vis) spectroscopy. UV-Vis absorbance is recorded over a wavelength range of 220–500 nm at 5 nm intervals. The absorbance data are normalized by conversion to scaled absorbance, which is compared to a reference scaled absorbance spectral curve for humic substances to determine if the tested material is humic or non-humic.

This method was able to differentiate legitimate humic substances from non-humic adulterants in a multiple-laboratory validation study (P ≤ 0.05).

This method can differentiate humic from non-humic substances in materials intended to be used as ingredients in commercial humic products or for research.

This method uses common laboratory procedures and equipment.

 

Digital biosensing assays demonstrate remarkable advantages over conventional biosensing systems because of their ability to achieve single-molecule detection and absolute quantification. Unlike traditional low-abundance biomarking screening, digital-based biosensing systems reduce sample volumes significantly to the fL-nL level, which vastly reduces overall reagent consumption, improves reaction time and throughput, and enables high sensitivity and single target detection. This review presents the current technology for compartmentalizing reactions and their applications in detecting proteins and nucleic acids. We also analyze existing challenges and future opportunities associated with digital biosensing and research opportunities for developing integrated digital biosensing systems. 

Laser spectroscopy of the^229mTh nuclear clock transition is necessary for the future construction of a nuclear-based optical clock. Precision laser sources with broad spectral coverage in the vacuum ultraviolet are needed for this task. Here, we present a tunable vacuum-ultraviolet frequency comb based on cavity-enhanced seventh-harmonic generation. Its tunable spectrum covers the current uncertainty range of the^229mTh nuclear clock transition.

 

Spiking Neural Networks (SNNs) are brain- inspired computing models incorporating unique temporal dynamics and event-driven processing. Rich dynamics in both space and time offer great challenges and opportunities for efficient processing of sparse spatiotemporal data compared with conventional artificial neural networks (ANNs). Specifically, the additional overheads for handling the added temporal dimension limit the computational capabilities of neuromorphic accelerators. Iterative processing at every time-point with sparse inputs in a temporally sequential manner not only degrades the utilization of the systolic array but also intensifies data movement.In this work, we propose a novel technique and architecture that significantly improve utilization and data movement while efficiently handling temporal sparsity of SNNs on systolic arrays. Unlike time-sequential processing in conventional SNN accelerators, we pack multiple time points into a single time window (TW) and process the computations induced by active synaptic inputs falling under several TWs in parallel, leading to the proposed parallel time batching. It allows weight reuse across multiple time points and enhances the utilization of the systolic array with reduced idling of processing elements, overcoming the irregularity of sparse firing activities. We optimize the granularity of time-domain processing, i.e., the TW size, which significantly impacts the data reuse and utilization. We further boost the utilization efficiency by simultaneously scheduling non-overlapping sparse spiking activities onto the array. The proposed architectures offer a unifying solution for general spiking neural networks with commonly exhibited temporal sparsity, a key challenge in hardware acceleration, delivering 248X energy-delay product (EDP) improvement on average compared to an SNN baseline for accelerating various networks. Compared to ANN based accelerators, our approach improves EDP by 47X on the CIFAR10 dataset. 

ABSTRACT One of the most promising tools for the control of fungal plant diseases is spray‐induced gene silencing (SIGS). In SIGS, small interfering RNA (siRNA) or double‐stranded RNA (dsRNA) targeting essential or virulence‐related pathogen genes are exogenously applied to plants and postharvest products to trigger RNA interference (RNAi) of the targeted genes, inhibiting fungal growth and disease. However, SIGS is limited by the unstable nature of RNA under environmental conditions. The use of layered double hydroxide or clay particles as carriers to deliver biologically active dsRNA, a formulation termed BioClay™, can enhance RNA durability on plants, prolonging its activity against pathogens. Here, we demonstrate that dsRNA delivered as BioClay can prolong protection against Botrytis cinerea , a major plant fungal pathogen, on tomato leaves and fruit and on mature chickpea plants. BioClay increased the protection window from 1 to 3 weeks on tomato leaves and from 5 to 10 days on tomato fruits, when compared with naked dsRNA. In flowering chickpea plants, BioClay provided prolonged protection for up to 4 weeks, covering the critical period of poding, whereas naked dsRNA provided limited protection. This research represents a major step forward for the adoption of SIGS as an eco‐friendly alternative to traditional fungicides.