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Abstract Mimicking the human eye’s ability to autonomously adapt to diverse and mixed illumination conditions remains a fundamental challenge in artificial vision systems. Although substantial progress has been made in materials and device engineering, current adaptive vision architectures still depend heavily on complex circuitry or algorithms and are typically restricted to uniform illumination owing to the strong intensity-dependence of photosensitivity. Here, this work presents a highly adaptive TiO₂/PEDOT:PSS photomemristor that leverages the tunable conductivity of PEDOT:PSS together with the optoelectronic response of TiO₂. The photothermal effect dynamically modulates the water absorption/desorption equilibrium in PEDOT:PSS, enabling reversible suppression or enhancement of photosensitivity under bright or dim illumination, respectively. By combining with artificial neural networks (ANNs), the artificial vision system based on TiO₂/PEDOT:PSS photomemristor arrays achieves a high accuracy of 91.3% in image recognition under mixed-light conditions—without the need for complex circuitry or algorithms. This work may establish a new approach for designing autonomous, efficient, and high-performance neuromorphic vision systems to advance the development of autonomous driving and humanoid robots. 

Facing constant challenges from various pathogens and pests, plants have evolved different strategies to defend themselves both locally and systemically. A global change in RNA metabolism is one of the necessary steps to mount a long-lasting immunity against present and future invasions.Arabidopsisserine/arginine-rich 45 (SR45) is an evolutionarily conserved RNA-binding protein that regulates multiple steps of RNA metabolism. Our prior study suggested that SR45 acts as a negative regulator of plant immunity. To better understand the molecular mechanism for SR45’s defense role, we examined the metabolic profile in both Col-0 andsr45-1. The results showed a significant accumulation of pipecolic acid (Pip), salicylic acid (SA), and other potential defense compounds insr45-1, indicating an increased systemic immunity. Thesr45–1mutant exhibited an elevated resistance to a wide range of biotrophic pathogen species and insensitivity to Pip, SA, and pathogen pretreatment. Between the two alternatively spliced isoforms, SR45.1 and SR45.2, SR45.1 seemed to be the culprit for the observed immune suppression. Upon examination of the transcriptome profile between Col-0 andsr45-1under either mock orPseudomonas syringae PmaDG3 challenge, we identified 1,125 genes as SR45-suppressed andPmaDG3-induced. Genes that function in SA biosynthesis and systemic acquired resistance were overrepresented, including those coding for WRKY, receptor-like kinases (RLKs), receptor-like proteins (RLPs), protein kinases, and TIR-NBS-LRR proteins. In addition, we identified significant alternative splicing activity in a list of genes due to eithersr45–1alone or bothsr45–1andPmaDG3 challenge. Among them, we characterized the effect of alternative splicing in two candidates,CBRLK1andSRF1. Interestingly, alternative splicing in both exhibited a switch between RLPs and RLKs in the predicted protein products. Overexpressing theirsr45–1dominant isoform in Col-0 led to a partial increase in immunity, suggesting the involvement of both alternative splicing events in SR45-conferred immune suppression. In summary, we hypothesize that SR45 regulates a subset of immune genes at either transcriptional or co-transcriptional pre-mRNA splicing levels to confer its function in systemic immune suppression. 

Self-assembly of amphiphilic molecules is an important phenomenon attracting a broad range of research. In this work, we study the self-assembly of KTOF4 sphere–rod amphiphilic molecules in mixed water–dioxane solvents. The molecules are of a T-shaped geometry, comprised of a hydrophilic spherical Keggin-type cluster attached by a flexible bridge to the center of a hydrophobic rod-like oligodialkylfluorene (OF), which consists of four OF units. Transmission electron microscopy (TEM) uncovers self-assembled spherical structures of KTOF4 in dilute solutions. These spheres are filled with smectic-like layers of KTOF4 separated by layers of the solution. There are two types of layer packings: (i) concentric spheres and (ii) flat layers. The concentric spheres form when the dioxane volume fraction in the solution is 35–50 vol%. The flat layers are formed when the dioxane volume fraction is either below (20 and 30 vol%.) or above (55 and 60 vol%.) the indicated range. The layered structures show no in-plane orientational order and thus resemble thermotropic smectic A liquid crystals and their lyotropic analogs. The layered packings reveal edge and screw dislocations. Evaporation of the solvent produces a bulk birefringent liquid crystal phase with textures resembling the ones of uniaxial nematic liquid crystals. These findings demonstrate that sphere–rod molecules produce a variety of self-assembled structures that are controlled by the solvent properties. 

Abstract The concentration of dopamine (DA) and tyrosine (Tyr) reflects the condition of patients with Parkinson's disease, whereas moderate paracetamol (PA) can help relieve their pain. Therefore, real‐time measurements of these bioanalytes have important clinical implications for patients with Parkinson's disease. However, previous sensors suffer from either limited sensitivity or complex fabrication and integration processes. This work introduces a simple and cost‐effective method to prepare high‐quality, flexible titanium dioxide (TiO₂) thin films with highly reactive (001)‐facets. The as‐fabricated TiO₂film supported by a carbon cloth electrode (i.e., TiO₂–CC) allows excellent electrochemical specificity and sensitivity to DA (1.390 µA µM⁻¹ cm⁻²), Tyr (0.126 µA µM⁻¹ cm⁻²), and PA (0.0841 µA µM⁻¹ cm⁻²). More importantly, accurate DA concentration in varied pH conditions can be obtained by decoupling them within a single differential pulse voltammetry measurement without additional sensing units. The TiO₂–CC electrochemical sensor can be integrated into a smart diaper to detect the trace amount of DA or an integrated skin‐interfaced patch with microfluidic sampling and wireless transmission units for real‐time detection of the sweat Try and PA concentration. The wearable sensor based on TiO₂–CC prepared by facile manufacturing methods holds great potential in the daily health monitoring and care of patients with neurological disorders. 

Abstract Skin‐interfaced high‐sensitive biosensing systems to detect electrophysiological and biochemical signals have shown great potential in personal health monitoring and disease management. However, the integration of 3D porous nanostructures for improved sensitivity and various functional composites for signal transduction/processing/transmission often relies on different materials and complex fabrication processes, leading to weak interfaces prone to failure upon fatigue or mechanical deformations. The integrated system also needs additional adhesive to strongly conform to the human skin, which can also cause irritation, alignment issues, and motion artifacts. This work introduces a skin‐attachable, reprogrammable, multifunctional, adhesive device patch fabricated by simple and low‐cost laser scribing of an adhesive composite with polyimide powders and amine‐based ethoxylated polyethylenimine dispersed in the silicone elastomer. The obtained laser‐induced graphene in the adhesive composite can be further selectively functionalized with conductive nanomaterials or enzymes for enhanced electrical conductivity or selective sensing of various sweat biomarkers. The possible combination of the sensors for real‐time biofluid analysis and electrophysiological signal monitoring with RF energy harvesting and communication promises a standalone stretchable adhesive device platform based on the same material system and fabrication process. 

Adopting FPGA as an accelerator in datacenters is becoming mainstream for customized computing, but the fact that FPGAs are hard to program creates a steep learning curve for software programmers. Even with the help of high-level synthesis (HLS) , accelerator designers still have to manually perform code reconstruction and cumbersome parameter tuning to achieve optimal performance. While many learning models have been leveraged by existing work to automate the design of efficient accelerators, the unpredictability of modern HLS tools becomes a major obstacle for them to maintain high accuracy. To address this problem, we propose an automated DSE framework— AutoDSE —that leverages a bottleneck-guided coordinate optimizer to systematically find a better design point. AutoDSE detects the bottleneck of the design in each step and focuses on high-impact parameters to overcome it. The experimental results show that AutoDSE is able to identify the design point that achieves, on the geometric mean, 19.9× speedup over one CPU core for MachSuite and Rodinia benchmarks. Compared to the manually optimized HLS vision kernels in Xilinx Vitis libraries, AutoDSE can reduce their optimization pragmas by 26.38× while achieving similar performance. With less than one optimization pragma per design on average, we are making progress towards democratizing customizable computing by enabling software programmers to design efficient FPGA accelerators.