To overcome limitations in the applications of existing SNP arrays in cotton genotyping and genomic selection (GS), we developed a liquid-phase SNP array, CottonSNP10K, for genomics-assisted breeding in cotton. Based on the high-quality reference genome of modern upland cotton cultivar NDM8, CottonSNP10K achieves precise probe design, and its marker system innovatively integrates the modern breeding genetic background, incorporating not only 13 agronomic traits associated loci (including fiber quality and yield-traits and stress resistance) identified via genome-wide association studies (GWAS), but also six exogenous gene markers targeting traits such as high lint percentage, herbicide resistance and insect resistance. The chip incorporates genome-wide background SNPs to ensure comprehensive genetic coverage, resulting in a final design comprising 11,159 SNPs, including 3,981 functionally trait-associated markers with 1,743 annotated genes and 7,178 genome-wide background markers. Through rigorous applications across diverse cotton accessions, CottonSNP10K performed exceptionally technical robustness with call rates > 99% and genotype concordance rates > 99%. The array can effectively support precisely marker-assisted selection (MAS) for agronomic traits and high-resolution breeding population analysis, and markedly enhance GS predictive accuracy for agronomically important traits using prediction models that we established. This integrated approach provides a high-throughput precision tool for parent germplasm characterization and breeding line selection in cotton, enabling reliable identification of elite germplasm and advancement of genomics-assisted breeding.
High-performance broadband photodetector arrays are pivotal for sensing, imaging and optical communication technologies, yet scalable materials that simultaneously offer broadband photoresponse coverage, fast response speed and uniform device performance remain elusive. Here, we present a 3×5 photodetector array based on few-layer MoTe2 grown via chemical vapor deposition (CVD) method. The MoTe2 photodetector exhibits a stable photoresponse ranging from ultraviolet to near-infrared regions. The device features a responsivity (R) of 3.82 mA/W, an external quantum efficiency (EQE) of 1.17% and a detectivity (D*) of 1.62×107 Jones under 405 nm illumination (5.04 mW/cm2) at Vds = 2 V and Vgs = 0 V. The response time and recovery time remain on the millisecond scale throughout the entire photoresponse coverage. This work provides a feasible route toward the construction of high-performance broadband photodetector arrays using single material alone.
Edge artificial intelligence (AI) and embodied vision call for compact, fast, and energy-efficient hardware that integrates sensing, linear analog computation, and nonlinear activation, while flexibly reallocating these functions as workloads change. However, in-sensor computing (ISC) and in-memory computing (IMC) platforms still implement activation with external peripherals and use fixed functional partitions, which break the analog signal path and restrict system reconfigurability. Here, we report a reconfigurable ferroelectric transistor (Fe-FET) array in which polarization-programmed local fields enable junction-barrier engineering in ambipolar tungsten diselenide (WSe2) channel. This junction-barrier engineering mechanism co-programs photoresponsivity, multilevel conductance, and tunable nonlinear transport within the same device, allowing each Fe-FET cell to be reassigned among weighted sensing (ISC), linear accumulation (IMC), and hardware-native activation. The array therefore functions as a uniform pool of physical units whose roles and spatial partitions can be dynamically allocated to match task demands without changing the hardware platform. Using this role-reconfigurable platform, we implement an end-to-end analog neuromorphic vision system in which broadband sensing, linear computation, and nonlinear activation are executed natively on the same Fe-FET platform. These results establish a task-adaptive and energy-efficient route toward scalable neuromorphic vision hardware for edge intelligence.
This paper proposes the dual functional microwave sensor with high gain array antenna using loaded U-resonator and asymmetric T-junction. The microwave sensor is designed to operate at fr = 2.11 GHz while the array antenna operates at fr = 2.84 GHz which is integrated using asymmetric T-junction based on microstrip line. The performance of the sensor is observed based on the frequency shift of S21 for solid material characterization with a permittivity range of 1-9.8 while for the antenna is observed based on the parameters S11, bandwidth, gain and radiation pattern. From the measurement results, the antenna and sensor have high performance and have independent characteristics with high isolation of ≤ -40 dB to work concurrently. Moreover, the antenna has performance of S11 ≤ -10 dB, Fractional Bandwidth (FBW) 2.11% and gain of 6.03 dBi at fr = 2.84 GHz. The sensors operating at fr = 2.11 GHz has a performance of ∆F of 0.4 GHz, FDR of 0.061 GHz / ∆εr, normalized sensitivity (NS) of 2.21% and accuracy of 99.38%. Therefore, this work can be recommended for application in industries such as material quality control, pharmaceuticals and biomedical as a solution for real-time measurement processes integrated with wireless communications.
Two-dimensional (2D) organic-inorganic van der Waals heterojunctions (vdWHs) are promising for integrated optoelectronics, but scalable fabrication of highly crystalline heterostructures with clean interfaces remains challenging. Here, we report centimeter-scale organic-inorganic vdWHs assembled by combining wet transfer of monolayer graphene with air-liquid interfacial growth of single-crystal C6-DPA. The resulting C6-DPA/graphene phototransistor exhibits broadband photodetection from 365 to 808 nm at room temperature, delivering a responsivity of 1.06 × 106 A W-1, a detectivity of 8.42 × 1015 Jones, and rise/decay times of 7.81/52.3 ms under 450 nm illumination. Large-area phototransistor arrays fabricated from a single heterojunction show excellent uniformity, near-unity yield, and high-contrast imaging capability. This work establishes a scalable route to large-area, highly crystalline organic-inorganic vdWHs and highlights their potential for high-performance integrated optoelectronic systems.
This study proposes a strategy to simultaneously improve conductance uniformity and data retention characteristics by introducing the incremental step pulse with verify algorithm (ISPVA) technique and hydrogen (H2) annealing into a non-filamentary TiN/Ti/HfO2/TiOx/TiN resistive switching memory device. The high Schottky barrier formed at the Ti/HfO2 interface induces asymmetric electron injection and limits reverse current flow, resulting in a rectifying ratio of approximately 1442. This self-rectifying characteristic provides an intrinsic advantage in suppressing sneak currents in crossbar arrays. The ISPVA technique improves the linearity and uniformity of conductance modulation, enabling the implementation of up to 6-bit multilevel states within a few-µA current range. In addition, H2 annealing stabilized conduction by forming hydrogen bonds with oxygen vacancies in the oxide layer and suppressing oxygen ion-vacancy recombination. As a result, data retention over 104 s and endurance exceeding 104 cycles were achieved even under a low energy consumption of 36.3 pJ. Furthermore, the experimentally obtained long-term potentiation and depression characteristics were implemented in a Transformer-based keyword spotting (KWS) model, achieving a recognition accuracy of 92.5%. These results suggest that the proposed device enables controlled analog conductance modulation with improved stability, showing its potential for Transformer-based neuromorphic computing applications.
Biological vision systems tightly couple spectral sensing with temporal integration to extract task-relevant information with minimal data movement. In contrast, conventional optoelectronic vision hardware typically separates photodetection from electronic computation, incurring substantial latency and energy costs. Optical neural networks can alleviate this bottleneck, but many implementations are difficult to scale. Here, we propose a bio-inspired optoelectronic inference architecture based on a Fabry-Perot microcavity-integrated MoS2 photodetector array, in which sensing, weighting, and accumulation are unified within each pixel. Cavity-engineered wavelength selectivity encodes neural-network weights in the spectral domain, while the finite carrier lifetime of MoS2 enables analog temporal accumulation without external memory. The system achieves test accuracies of 99.6%, 94.8% and 94.0% on MNIST, CIFAR-10 and the Free Spoken Digit Dataset, respectively. Post-training optical Hessian pruning further reduces optical complexity while maintaining robustness. This architecture provides a compact route toward wavelength-aware in-sensor neuromorphic inference.
Ensuring food safety necessitates rapid, non-destructive, and reliable monitoring strategies, among which colorimetric sensor arrays (CSAs), based on analyte-induced color changes, have emerged as cost-effective tools for real-time food quality monitoring. Recent advances in sensing materials, fabrication strategies, and colorimetric mechanisms have expanded the analytical capability of CSAs, particularly through integration with machine learning. Automated feature extraction, pattern recognition, and predictive modeling significantly improve sensitivity, specificity, and classification accuracy, enabling more reliable food freshness assessment. Both traditional algorithms and deep learning models have been applied to CSA data analysis, supporting their implementation in portable, smartphone-based, and embedded sensing platforms. However, practical deployment is still limited by sensor degradation, environmental variability, response inconsistency, and the lack of standardized imaging and evaluation protocols. Future efforts should prioritize adaptive and lightweight algorithms, standardized data workflows, multimodal sensing systems, and sustainable, high-stability materials to enhance robustness, reproducibility, and industrial applicability.
Calix[4]pyrroles with unsubstituted meso-positions were synthesized by precipitating the products from reaction mixtures. The introduction of meso-spiroadamantyl subunits resulted in the scrambling of oligopyrrole intermediates during [2 + 2] condensation reactions. This process afforded a combination of cis- and trans-arranged isomers, as well as significant spectroscopic modifications arising from close contacts between the adjacent π-planes by the bulky adamantyl groups attached to the meso-positions in a spiro configuration.
This study aimed to improve intracortical microelectrode array implantation sites for grasp-related motor decoding by integrating anatomical, functional, and vascular imaging with preoperative 3D modeling. A participant with C5 tetraplegia underwent anatomical MRI, diffusion-weighted imaging, and task-based fMRI to identify grasp-related cortical regions while avoiding vasculature and speech-critical areas. Quicktome software was used to refine target selection by integrating structural connectivity and functional activation data. A 3D-printed skull and cortical model enabled preoperative planning, including craniotomy and electrode positioning simulations. Electrode placement was validated postoperatively using neural data collected from the implanted arrays during attempted movements of the arm and hand. Functional imaging identified distinct grasp-related activation in anterior intraparietal area (AIP), ventral premotor cortex (PMv), and inferior frontal gyrus (IFG). Putative AIP was selected based on its strong connectivity with motor cortex and distinct functional activation. Subregions 6v and 6r of PMv, which exhibited robust grasp-related activity and were surgically accessible, were chosen over the posterior IFG region, which extended into a sulcus making implantation difficult. Postoperatively, the arrays enabled high-fidelity decoding of arm/hand movements, achieving a combined classification accuracy of 96%. This study presents a multi-modal approach for improving intracortical electrode placement by combining MRI-based anatomical mapping, fMRI-guided functional localization, connectivity information, and 3D surgical modeling. These findings demonstrate an effective method for identifying surgically feasible grasp network implant locations in a paralyzed individual. This is an essential step toward brain-machine interfaces that enable individuals with spinal cord injury to control devices using grasp-related brain activity.
The growing demand for energy- and area-efficient computing in edge devices has highlighted the limitations of conventional von Neumann architectures, which suffer from the memory bottleneck due to frequent data transfer between logic and memory units. Processing-in-memory (PIM) has emerged as a promising solution, and among its approaches, stateful logic enables computation directly within memory arrays using simple voltage pulses. To realize this concept, we demonstrate the stateful logic functionality using selector-only-memory (SOM) device based on Sn-doped GeSeTe (SGST). The device reveals a distinctive switching behavior, where the direction of threshold switching can be reversibly tuned by adjusting the external series resistance. This behavior originates from RC delay effects, which induce a residual opposite-polarity voltage during the falling edge of the input pulse. Utilizing this property, we implement various stateful logic operations-including IMPLY, NAND, NOR, AND, and OR-directly within the SOM array. Furthermore, a half-adder circuit is experimentally realized, confirming the scalability of the approach. The low off-state current and reconfigurable switching behavior make the SOM device highly suitable for dense and low-power logic-in-memory architectures, particularly in large-scale arrays for edge computing. This work will provide a new direction for designing stateful logic devices with both structural simplicity and functional versatility.
Staphylococcus aureus is a major human commensal and pathogen, with the Panton-Valentine leukocidin (PVL) genes being associated with increased virulence. Rapid detection and molecular typing of such isolates are essential for effective epidemiological surveillance and infection control. Studies from Lithuania indicate that PVL is relatively common among S. aureus isolates, but detailed molecular typing data are still lacking. Clinical S. aureus isolates were collected from two hospitals in Vilnius in 2018-2019 and 2024, and from healthy volunteers between 2012 and 2020. Isolates were screened for PVL genes using real-time PCR. In addition, positive isolates harvested directly from the agar plate were tested for PVL production using an experimental lateral flow assay (LFA). Positive isolates were characterised using DNA-microarrays that facilitated the detection of resistance markers and virulence genes including PVL as well as an assignment to clonal complexes, strains and SCCmec types. Epidemiologically relevant isolates were subjected to whole-genome sequencing using Oxford nanopore technology. Out of 1296 S. aureus isolates, 124 yielded PVL-positive PCR results. 100 isolates were available for genotyping. Two PCR-positive isolates were negative by array and LFA, but PVL detection by DNA-microarray and lateral flow test (LF) showed complete concordance. Among PVL-positive isolates, 61.2% were methicillin-resistant S. aureus (MRSA). The most common PVL-MRSA strain (n = 43) was a Clonal Complex (CC) 8 MRSA that resembled the North American "USA300" strain but that lacked the arginine catabolic mobile element (ACME). This suggested an outbreak in one of the participating hospitals. Other common strains were PVL-positive CC30-MSSA, CC121-MSSA and CC8-MRSA-[IV+ACME] "USA300", while other lineages were represented by single isolates only. Whole-genome sequencing of two ACME-negative CC8-MRSA-IV isolates and of one local "USA300" isolate, as well as a comparison to international reference sequences, showed a very high degree of similarity in core genome and prophage content. The dominant PVL-MRSA strains were "USA300", indicating a possible importation from North America, and a locally emerged variant of "USA300" that lost the ACME-associated genes of its SCCmec element. These findings suggest that real-time PVL detection is essential for outbreak prevention. Given its clinical relevance, routine PVL screening -via PCR or lateral flow assays-in routine diagnostics should be seriously considered and surveillance of PVL-MRSA is urgently recommended.
The rapid development of multispectral detection technology urgently requires the simultaneous suppression of microwave and infrared (IR) signatures. However, conventional strategies suffer from limited functional integration, complex structures, and poor scalability in achieving synergistic control of radar cross section (RCS) and IR radiation characteristics. Herein, we propose a chaotic paradigm combined with a multi-scale strategy to address radar-IR-optical multispectral stealth by using a single-layer coding indium tin oxide (ITO) platform. This architecture covers millimeter-scale representative elements, centimeter-scale phase-coded subarrays, and decimeter-scale meta-arrays, with a direct correlation established between chaotic initial conditions and microwave/IR responses theoretically. Specifically, chaotic coding, a deterministic pseudo-random coding method, is adopted to construct a meta-array inspired by sensitivity of chaotic systems to initial conditions. Tuning chaotic initial parameters enables controllable spatial IR emissivity modulation while preserving broadband intrinsic microwave diffusion due to the multi-wavevector mechanism. For verification, a proof-of-concept metadevice is fabricated, and experimental results manifested a broadband RCS reduction over 10 dB within X/Ku bands (8 ~ 18 GHz) for incident angles up to 45°, with a low IR emissivity below 0.3 and a high optical transmittance of 71.2%. Featuring ultrathin profile (3.35 mm, ~ 0.09 λL), light weight, optical transparency, and facile fabrication, our strategy offers a promising avenue for multi-scale multispectral stealth applications.
Meteorites are classified as either non-carbonaceous or carbonaceous, representing bodies that are likely to have formed in the inner or outer Solar System, respectively. Despite its location in the inner Solar System, the Earth is thought to contain either minor (~6%) or substantial amounts (~40%) of outer Solar System material. However, because neither interpretation leverages variations among multiple isotopic systems simultaneously, Earth's provenance remains equivocal. Here we examine variations in ten nucleosynthetic isotope anomalies among planets and meteorite parent bodies to show that the linear extension of an array defined by non-carbonaceous bodies in any two isotopic anomalies always intersects the observed isotopic composition of the bulk silicate Earth to within 1 standard deviation. The Earth therefore formed exclusively from inner Solar System material whose composition did not vary over the course of accretion and was, on average, unlike that of any chondrite. Extension of the non-carbonaceous array yields isotopic compositions for Mercury and Venus that are more extreme than for Earth, implying a spatial or temporal gradient during the formation of the terrestrial planets.
Acoustic beamforming is widely used for source localization and line-of-bearing determination. Although many different beamforming techniques have been formulated, atmospheric turbulence effects on acoustic arrays are usually ignored in both their theoretical formulation and practical implementation. As a result, the performance of conventional beamformers, formulated for a non-turbulent atmosphere, degrades in the presence of wind velocity and temperature fluctuations, which cause fluctuations in the received signal amplitude and phase. This article presents a mathematical framework in which the amplitude and phase fluctuations are effectively suppressed from the signals allowing application of any beamforming technique and mitigating its performance degradation in a turbulent atmosphere. The framework is constrained to a single source and by the monochromatic plane wave approximation. Application of such an approach to an experiment revealed that the phase and amplitude fluctuations with spatial scales smaller than the array aperture are successfully suppressed, but the larger fluctuations (resulting in wavefront random tilt) remain and cause errors in the line of bearing estimates.
Electrically evoked compound action potentials (ECAPs) represent summation of action potentials generated by neurons of the auditory nerve in response to electrical stimulation. The slope of the ECAP amplitude growth function (AGF) reflects responsiveness or survival of neurons proximal to the stimulating electrode. Goals of the present study were to characterize the magnitude of the AGF slope by electrode site and over time in a cohort of pediatric CI users and measure the degree of correlation of slopes with auditory assessment results. 23 CI users participated in the study, ranging in age from 3 to 12 years. All implanted with 31.5 mm electrode array, full insertion. ECAP AGF slopes measured with all active electrodes intra-operatively, device switch-on, 3-, 6-, 9-, and 12-months post switch-on. Auditory assessments administered at 3-, 6-, 9-, and 12-months post-implantation. Analysis performed by electrode as well as intracochlear electrode site (basal, middle, and apical). AGF slopes significantly increased according to a basal-to-apical gradient. Slopes were more than twice as large at the apical-most electrode compared to the basal-most (43.1 vs. 20.3 µV/nC). AGF slopes stimulated from basal electrodes significantly increased over time, while those stimulated from apical electrodes significantly decreased over time. No statistically significant correlations were observed between AGF slopes and the test results of any auditory assessment at any timepoint. Observations demonstrate AGF slopes vary substantially, both across the array and over time. No significant associations were observed between AGF slopes and auditory perception skills in this cohort. Due to our relatively small sample size and the heterogeneity of the data, no definitive conclusions regarding these associations can be made here.
Accurately monitoring carcinogenic volatile aromatic hydrocarbons (BTXs) is crucial for assessing air-qualities and danger-classes in specific occasions, However, it remains challenging to conduct highly selective identification of them in complex environments. Here, we have developed a gas-shunting strategy by installing function-reversal ZnO materials into Ir-WO3 supports to diminish interference-gas responses and guide special aromatic hydrocarbons sensing. We find that ZnO materials can serve as reactively sacrificial sites for small-molecule H2S and CO and induce main aromatic hydrocarbons reactants into Ir-WO3 supports. This gas-shunting route guarantees highly-selective aromatic hydrocarbons sensing even in dual/ternary gas mixtures. Through integrating functional-opposite sensors into a system, the final sensing arrays achieve 100% classification accuracy for 10 single gases and 75 multi-compose gases with low training costs. In addition, we also show an autonomic "cruise-detection" system by equipping sensor arrays into robotic dog to accurately identify complex gases. Our findings emphasize sensors designs with selective features and may broaden integrated sensing-system analysis in complex environment.
High design-to-fabrication consistency is critical for microneedle (MN) arrays, as geometric fidelity directly governs mechanical and drug delivery performance. Traditional process control, relying on static models such as the Jacobs working curve and the reciprocity law, inadequately captures nonlinear polymerization kinetics, leading to defects like warping and distortion. To address this, we developed a photopolymerization kinetic framework that decouples exposure intensity from duration and incorporates dynamic light attenuation and polymerization progression into a multiscale finite element analysis via a custom UMAT subroutine. The results reveal that extreme exposure duration or intensity is deleterious, as the former induces over-curing and shrinkage, whereas the latter results in heterogeneous polymerization and warpage. Importantly, the simulation identifies a critical stress-minimization regime where slicing thickness (30 μm) aligns with the material's optical penetration depth (Dp ≈ 29.3 μm). Guided by this model, we fabricated gradient MN arrays with a tip precision of 12.8 μm, approaching the optical diffraction limit (10 μm) and representing a 68% accuracy improvement over conventional methods. This work provides a quantitatively driven methodology for defect-free manufacturing of complex microstructures, shifting fabrication from empirical iteration to model-guided precision.
Tissue engineering has shown great potential for manufacturing tissue replacements and developing physiologically relevant tissue models. However, conventional tissue engineering strategies often face challenges in fabricating tissues simultaneously incorporating controlled cellular and extracellular matrix (ECM) architectures. Here, we introduce Acoustic Tweezers-Assisted Biomaterial Molding in Petri Dishes (TAMP), enabling tissue fabrication with controlled cellular and ECM architectures in Petri dishes, specifically, producing constructs with customized ECM geometries and various internal cellular architectures, including parallel elongated cell bundles, arrays of interconnected cell spheroids, and lattice-like cellular networks. TAMP leverages a portable acoustic array that delivers standing waves into a Petri dish or a polydimethylsiloxane (PDMS) mold, thereby enabling a unique "dual-control" mechanism. The acoustic field arranges internal cells into parallel line-like and lattice-like patterns, while the PDMS mold defines the overall ECM geometry. Our approach was demonstrated by arranging micro-objects into various patterns within different-shaped molds and fabricating glioma tissues with various unique internal cellular architectures, including parallel elongated glioma tissue bundles, lattice-like glioma tissue networks, and chains of interconnected glioma spheroids. We anticipate the TAMP technique will lead to portable, easy-to-operate tools for engineering tissues with controlled cellular and ECM architectures for biomedical research, disease modeling, and drug testing.
Long-term stability of sensor arrays remains a major limitation for the practical implementation of electronic nose systems in non-invasive analysis of volatile organic compounds (VOCs) and differentiation of oncological status. Changes in the physicochemical properties of sensing layers during prolonged operation may alter diagnostic parameters and compromise classification consistency. This study evaluated the long-term stability of diagnostically significant parameters obtained from skin gas-profile analysis using a quantum dot-based electronic nose. An eight-sensor piezoelectric electronic nose array based on cadmium sulfide quantum dots with various modifiers was used for skin gas-profile analysis of volunteers and cancer patients. Pair sensitivity parameters (Ai/j) and kinetic sorption parameters derived from chronofrequency responses were assessed by comparing measurements obtained during the pilot study and after two years of sensor operation. Pair sensitivity parameters demonstrated substantial susceptibility to long-term surface degradation and environmental variability, particularly humidity, resulting in pronounced classification drift. In contrast, kinetic sorption parameters exhibited higher temporal stability and lower sensitivity to operating conditions. A correction strategy based on systematic changes in kinetic parameters was developed and applied to compensate for sensor aging effects. The proposed approach reduced classification drift. These findings indicate that correction of long-term sensor drift may help extend the operational lifetime of quantum dot-based electronic nose systems, while kinetic parameters may provide more stable analytical indicators for gas-profile analysis.