Sampling Rate Research Articles

Establishment and Application of a Rapid Detection Method of Cyprinid Herpesvirus 2 (CyHV-2) in Aquacultural Waters by Using a Novel One-Pot RAA-CRISPR/Cas12a Combined With Fe-Iron Flocculation Technology.

Cyprinid herpesvirus 2 (CyHV-2) poses a substantial global threat to goldfish (Carassius auratus) and crucian carp (Carassius carassius). Despite the development of several sensitive molecular diagnostic techniques, there is an ongoing demand for alternative visualisation platforms to streamline the workflow, enhance safety profiles, and improve accessibility for end-users. In this study, we have integrated recombinase-aided amplification (RAA) technology with the CRISPR/Cas12a system to establish a rapid diagnostic system for CyHV-2, termed one-pot RAA-CRISPR/Cas12a. This method enables the results of detection within 60 min. The RAA-CRISPR/Cas12a platform is capable of detecting as few as 10 copies of CyHV-2 per reaction cycle without exhibiting cross-reactivity with other pathogens. The positive detection rate in clinical samples exceeds that of conventional PCR approaches, underscoring its high precision. Furthermore, the method could be used in conjunction with iron flocculation for the concentration and detection of viruses within aquaculture settings. This approach minimises the dissection of aquatic organisms, thereby maximising animal welfare and bolstering detection efficiency. Collectively, our findings validate the RAA-CRISPR/Cas12a method as a robust, specific, confirmatory, user-friendly and promising approach for on-site diagnosis of CyHV-2.

Differential Measurement of Involuntary Breathing Movements

Free divers are known to experience a physiological response during extreme breath holding, causing involuntary breathing movements (IBMs). To investigate these movements, a low-cost multi-core ESP32-Pico microcontroller prototype was developed to measure IBMs during a static breath hold. This novel device, called the bioSense, uses a differential measurement between two accelerometers placed on the sternum and the xiphoid process to acquire breathing-related movements. Sensor placement allowed for data acquisition that was posture- and body-shape-agnostic. Sensor placement was also designed to be as non-intrusive as possible and precisely capture breathing movements at configurable sampling rates. Measurements from the device were sent over WiFi to be accessed on a password-protected webserver and backed up to a micro-secure digital (microSD) card. This device was used in a pilot study, where it captured the various phases of breathing experienced by recreational free divers alongside a force plate measurement system for comparison.

Edible Bird’s Nest (EBN) Ameliorates the Effects of Indomethacin (IMC)-Induced Embryo Implantation Dysfunction in Rats

IMC has been reported to influence embryo implantation negatively in animals including rats. While EBN has been known to have a potential protective effect against reproductive toxicity, there is limited study on the effect of EBN on IMC toxicity in reproduction. This study aimed to ascertain whether pretreatment with a natural substance, Edible Bird’s Nest (EBN), will reduce IMC-induced toxicity in pregnant rats. Thirty Sprague-Dawley rats divided into five equal groups were treated with EBN and IMC as follows: G1 = Control, G2 = IMC (4.33 mg/kg), G3 = IMC + EBN (4.33 mg/kg + 60 mg/kg), G4 = IMC + EBN (4.33 mg/kg + 90 mg/kg), and G5 = IMC + EBN (4.33 mg/kg +120 mg/kg). EBN was administered once daily for 8 weeks while IMC was injected subcutaneously. On day 8 after mating, all rats were sacrificed for blood sampling and embryo implantation rate (EIR) assessment; the uterine tissues were also subjected to immunohistochemical and histological analyses. G5 recorded significantly higher EIR, fertility index, and expression of epidermal growth factor receptor (EGFR) in the uterine section, across stroma cells, the glandular epithelium, and the luminal epithelium compared to control and other groups. IMC-induced inflammatory alterations, endometrial atrophy, vacuolar degeneration, and atrophy were not detected in uterine tissue sections in G4 and G5, with the latter group demonstrating the highest EIR with protective effects on uterine tissues. Thus, EBN supplementation might be of great benefit in guarding the fertility of individuals who depend on IMC for the treatment of chronic inflammatory illness.

Self-supervised constrained super-resolution fast coded spectral imaging system

Current coded aperture spectral imaging techniques suffer from slow imaging speeds and poor image quality at low sampling rates. To address these issues, we propose a self-supervised constrained super-resolution fast coded spectral imaging system by combining a physical process of spectral imaging with image fusion super-resolution techniques. We constructed a discrete cosine transform spectrometer (DCTS) and successfully acquired low-resolution hyperspectral images (LR-HSI) and high-resolution multispectral images (HR-MSI). In order to enhance the resolution of hyperspectral images, we designed a self-supervised spectral image super-resolution network based on the physical process of spectral imaging: SSAM-Unet. This network successfully reconstructs the HR-HSI by fusing the LR-HSI with the HR-MSI. We verified the performance and generalization ability of this method through extensive experiments. Experimental results show that our proposed method can achieve good imaging results at very low sampling rates.

Dynamic land-plant carbon sources in marine sediments inferred from ancient DNA

Terrigenous organic matter in marine sediments is considered a significant long-term carbon sink, yet our knowledge regarding its source taxa is severely limited. Here, we leverage land-plant ancient DNA from six globally distributed marine sediment cores covering the Last Glacial–Holocene transition as a proxy for the share, burial rate, preservation, and composition of terrigenous organic matter. We show that the spatial and temporal plant composition as revealed by sedimentary ancient DNA records reflects mainly the vegetation dynamics of nearby continents as revealed by comparison with pollen from land archives. However, we also find indications of a global north-to-south translocation of sedimentary ancient DNA. We also find that plant sedimentary ancient DNA has a higher burial rate in samples from the Late Glacial, which is characterized by high runoff and mineral load. This study provides an approach to understanding the global linkages between the terrestrial and marine carbon cycle, highlighting the need for further research to quantify the processes of DNA preservation and dispersal in marine sediments.

Systematic evaluation of sampling rate influences and variability in POCIS using meta-analysis and quantitative structure property relationship (QSPR).

Despite the significant benefits of aquatic passive sampling (low detection limits and time-weighted average concentrations), the use of passive samplers is impeded by uncertainties, particularly concerning the accuracy of sampling rates. This study employed a systematic evaluation approach based on the combination of meta-analysis and quantitative structure-property relationships (QSPR) models to address these issues. A comprehensive meta-analysis based on extensive data from 298 studies on the Polar Organic Chemical Integrative Sampler (POCIS) identified essential configuration parameters, including the receiving phase (type, mass) and the diffusion-limiting membrane (type, thickness, pore size), as key factors influencing uptake kinetic parameters. The incomplete availability of these details across studies potentially impacts data reproducibility and comparability. The subsequent meta-regression and subgroup analysis were performed to reveal the most significant factors contributing to sampling rate variability and inter-study heterogeneity. The flow rate and octanol-water partitioning (Kow or pH-dependent Dow) were identified from all environmental factors and chemical properties. Furthermore, the impact of chemical properties on the sampling rates of POCIS was predicted by Quantitative Structure-Property Relationship (QSPR) models using 2D descriptors and random forest regression. The analysis highlighted that the electrotopological state and molecular mass are the most important chemical properties influencing the sampling rate. This study systematically unraveled the most important impact factors on reliable estimates of passive sampling rates, and these causes of uncertainty should be further considered in aquatic monitoring and assessment with passive samplers.

Accelerated model-based T1, T2* and proton density mapping using a Bayesian approach with automatic hyperparameter estimation.

To achieve automatic hyperparameter estimation for the model-based recovery of quantitative MR maps from undersampled data, we propose a Bayesian formulation that incorporates the signal model and sparse priors among multiple image contrasts. We introduce a novel approximate message passing framework "AMP-PE" that enables the automatic and simultaneous recovery of hyperparameters and quantitative maps. We employed the variable-flip-angle method to acquire multi-echo measurements using gradient echo sequence. We explored undersampling schemes to incorporate complementary sampling patterns across different flip angles and echo times. We further compared AMP-PE with conventional compressed sensing approaches such as the -norm minimization, PICS and other model-based approaches such as GraSP, MOBA. Compared to conventional compressed sensing approaches such as the -norm minimization and PICS, AMP-PE achieved superior reconstruction performance with lower errors in mapping and comparable performance in and proton density mappings. When compared to other model-based approaches including GraSP and MOBA, AMP-PE exhibited greater robustness and outperformed GraSP in reconstruction error. AMP-PE offers faster speed than MOBA. AMP-PE performed better than MOBA at higher sampling rates and worse than MOBA at a lower sampling rate. Notably, AMP-PE eliminates the need for hyperparameter tuning, which is a requisite for all the other approaches. AMP-PE offers the benefits of model-based recovery with the additional key advantage of automatic hyperparameter estimation. It works adeptly in situations where ground-truth is difficult to obtain and in clinical environments where it is desirable to automatically adapt hyperparameters to individual protocol, scanner and patient.

Achieving synergistic improvement on wear performance of D3 cold-work steel by modifying the number and order of deep cryogenic and tempering treatments

ABSTRACT This study concentrates on the effects of several tempering processes both before and after the deep cryogenic process on the microstructural, hardness, and tribological characteristics of D3-type steel. The treatment contains hardening at 950 °C for 40 min, tempering at 250 °C for 2 h, and deep cryogenic treatment at -196 °C for 18 h. A ball-on-disc wear tester conducts wear tests against the Al2O3 ball under a load providing 1.9 GPa Hertzian contact pressure, simulating severe wear conditions. Double Tempering-Cryogenic Treatment-Double Tempering (DTCDT) was the best heat treatment combination. There was a substantial decrease in wear rate in DTCDT samples by up to 80.3% owing to their homogeneously distributed finer carbide formation.

Analysis of Timely Follow-Up in the Evaluation of Postmenopausal Bleeding

OBJECTIVE: To characterize guideline-adherent follow-up in patients evaluated with transvaginal ultrasonography (TVUS) for postmenopausal bleeding. METHODS: We conducted a retrospective study of patients with an intact uterus and postmenopausal bleeding who presented to a single academic institution and underwent TVUS between January 2013 and December 2022. Primary outcome measures were prompt follow-up, defined as receipt of endometrial sampling within 3 months of a finding of thickened or inadequately visualized endometrium, diagnosis of endometrial cancer, cancer stage at diagnosis, and rates of tissue sampling. Associations between sociodemographic variables and prompt follow-up were assessed. A Pareto analysis was performed to describe reasons for lack of prompt follow-up. RESULTS: Of 1,671 patients with thickened endometrium, 307 (18.4%) did not receive prompt follow-up; of 389 patients with inadequately visualized endometrium, 128 (33.0%) did not receive prompt follow-up. Sociodemographic variables were not associated with prompt follow-up. Clinician-related factors, including misinterpretation of ultrasound results, accounted for 46.1% of delayed or absent follow-up for thickened endometrium and 58.4% of inadequately visualized endometrium. The rates of diagnosing endometrial cancer within 1 year were similar after findings of thickened endometrium (8.8%; 95% CI, 7.5–10.3%) compared with inadequately visualized (7.7%; 95% CI, 5.3–10.9%) endometrium. CONCLUSION: Clinician misinterpretation of TVUS performed for postmenopausal bleeding was the most common reason for delayed or absent follow-up. Given observed suboptimal rates of prompt follow-up after findings of thickened or inadequately visualized endometrium on ultrasonography and similar rates of an eventual cancer diagnosis in these cohorts, efforts should be focused on clinician understanding of ultrasonographic endometrial evaluation. To simplify the diagnostic process and reduce the risk of missing a cancer diagnosis, universal endometrial sampling for patients with postmenopausal bleeding could be considered.

TR(Acking) Individuals Down: Exploring the Effect of Temporal Resolution in Resting-State Functional MRI Fingerprinting.

Functional brain fingerprinting has emerged as an influential tool to quantify reliability in neuroimaging studies and to identify cognitive biomarkers in both healthy and clinical populations. Recent studies have revealed that brain fingerprints reside in the timescale-specific functional connectivity of particular brain regions. However, the impact of the acquisition's temporal resolution on fingerprinting remains unclear. In this study, we examine for the first time the reliability of functional fingerprinting derived from resting-state functional MRI (rs-fMRI) with different whole-brain temporal resolutions (TR = 0.5, 0.7, 1, 2, and 3 s) in a cohort of 20 healthy volunteers. Our findings indicate that subject identifiability within a fixed TR is successful across different temporal resolutions, with the highest identifiability observed at TR 0.5 and 3 s (TR(s)/identifiability(%): 0.5/64; 0.7/47; 1/44; 2/44; 3/56). We discuss this observation in terms of protocol-specific effects of physiological noise aliasing. We further show that, irrespective of TR, associative brain areas make an higher contribution to subject identifiability (functional connections with highest mean ICC: within subcortical network [SUB; ICC = 0.0387], within default mode network [DMN; ICC = 0.0058]; between DMN and somato-motor [SM] network [ICC = 0.0013]; between ventral attention network [VA] and DMN [ICC = 0.0008]; between VA and SM [ICC = 0.0007]), whereas sensory-motor regions become more influential when integrating data from different TRs (functional connections with highest mean ICC: within fronto-parietal network [ICC = 0.382], within dorsal attention network [DA; ICC = 0.373]; within SUB [ICC = 0.367]; between visual network [VIS] and DA [ICC = 0.362]; within VIS [ICC = 0.358]). We conclude that functional connectivity fingerprinting derived from rs-fMRI holds significant potential for multicentric studies also employing protocols with different temporal resolutions. However, it remains crucial to consider fMRI signal's sampling rate differences in subject identifiability between data samples, in order to improve reliability and generalizability of both whole-brain and specific functional networks' results. These findings contribute to a better understanding of the practical application of functional connectivity fingerprinting, and its implications for future neuroimaging research.

A POCIS-based approach for the monitoring of pharmaceuticals in wastewater treatment plants: Calibration and deployment challenges.

The impact of pharmaceuticals in aquatic environments requires complementary monitoring techniques to the more conventional grab sampling approach for an improved sample representativity. This study explores the application of Polar Organic Chemical Integrative Samplers (POCIS) in the analysis of a wide range of pharmaceutical residues in wastewater effluent, highlighting its advantages over grab sampling. Passive sampling techniques, extending sampling duration several days or weeks, provide continuous and representative data, improving the punctual nature of grab sampling. Despite their advantages, achieving quantitative results remains a challenge. Calibration through precise determination of sampling rates (RS) is recommended to convert the accumulated contaminant mass on the adsorbent to water concentrations. In the present work, 78 pharmaceuticals were preselected for stability suitability for POCIS passive sampling. RS were experimentally determined for 49 stable compounds: 33 of them had not been previously reported and most the other 16 agree with previous published literature. These RS were used to determine the concentration of pharmaceuticals in a wastewater treatment plant (WWTP) near to Barcelona, Spain over 3 weeks. High concentrations of 1,7-dimethylxanthine (2897 ng L-1), 4-acetamidoantipyrine (191 ng L-1), acetaminophen (165 ng L-1) and rasagiline (152 ng L-1) were found. This study examines POCIS deployment strategies, calibration, and analysis methods for 49 pharmaceutical compounds in an WWTP effluent. This research establishes a robust methodology for quantitative passive sampling of pharmaceuticals in aquatic environments, providing critical insights for more accurate monitoring of pharmaceuticals of environmental concern.

Passive measurements of marine seismic reflection surveys using Ocean Observatories Initiative hydrophones.

The Ocean Observatories Initiative (OOI) provides continuous monitoring of acoustic fields at various locations in the northeast Pacific Ocean, among other types of data. The effects of marine seismic reflection surveys on the ambient soundscape in the vicinity of these hydrophones can be quantified by looking at OOI hydrophone data in conjunction with cruise documentation. Two seismic reflection surveys, MGL1905 and MGL2104, and measurements on three hydrophones at varying depths with 64 kHz sampling rates are considered. The seismic air guns are exhibited to raise the mean ambient sound by up to 30 dB over several one-third octave bands, where the impact varies significantly as a function of range, depth, and other factors. Effects can be observed hundreds of kilometers from the air gun arrays, and shots may be frequent enough that the ambient sound does not return to its pre-cruise background levels between shots. Although range is strongly correlated with these effects, metrics, such as sound exposure level or sound pressure level, can easily vary by 10 dB or more at the same range.

Experimental DMD Analysis of Combustion Modes and Instabilities in a Scramjet Combustor

The combustion characteristics of a gaseous hydrogen fueled scramjet combustor were experimentally investigated through single-shot micro-pulse detonation engine (μPDE) operations across a range of fuel injection pressures and corresponding equivalence ratios. This study utilized a lab-scale direct-connect scramjet combustor integrated with a μPDE, designed to simulate flight conditions at Mach numbers between 4.0 and 5.0 at altitudes of 20 to 25 km. Static wall pressure was measured using 16 pressure probes from the isolator to the scramjet combustor at a sampling rate of 500 Hz. Additionally, Z-fold type Schlieren and flame luminosity were captured using a high-speed camera in a test section equipped with a quartz visualization window. Experiments were conducted under five conditions with equivalence ratios ranging from 0.10 to 0.55, each performed three times to ensure repeatability. Fast Fourier transform (FFT) and dynamic mode decomposition (DMD) analyses were applied to the pressure and image data obtained. Although auto-ignition was not achieved in all cases, combustion persisted while fuel was injected following the single-shot μPDE ignition. This allowed for the identification of distinct combustion modes according to equivalence ratio, by observing the dominant flame types and the shock structure within the flow of the combustor. These combustion modes showed different types of instability.

Ghadeer-speech-crowd-corpus: Speech dataset.

The availability of raw data is a considerable challenge across most branches of science. In the absence of data, neither experiments can be conducted nor development can be undertaken. Despite their importance, raw data are still lacking across many scientific fields. A literature survey conducted at the beginning of our study indicated a significant lack of Arabic speech datasets. Therefore, this study aims to address this problem by proposing a new Arabic and English dataset called Ghadeer-Speech-Crowd-Corpus. This dataset was designed to target more than one branch of speech-processing applications, such as crowd speaker identification, speech synthesis (text-to-speech), and speech recognition (speech-to-text). Speech samples were recorded over three months from 210 Iraqi Arab citizens living in different parts of Iraq and included more than one accent. The proposed dataset was fully balanced with respect to sex and recordings (same number of Arabic and English recordings). Additionally, it is a mono dataset and contains 15,626 audio samples recorded at a sampling rate of 44,100 Hz, 16-bit depth, and bit rate of 705.6 kb/s. The recordings were conducted at the Academy for Media Training of the College of Media, University of Baghdad.

Vision transformer based cut interruption detection and prediction of laser fusion cutting from monitored melt pool images

Incomplete cuts during laser fusion cutting result in a closed kerf, preventing the workpiece from detaching from the sheet and resulting in rework or rejection. We demonstrate the approach of a vision transformer, used for image classification, to detect cut interruption during laser fusion cutting in steel and aluminum. With events impending an incomplete cut in steel, we attempt to predict cut interruption before they even occur. To build a data set for training, cutting experiments are carried out with a 4 kW fiber laser, forcing incomplete cuts by varying the process parameters such as laser power and feed rate. The thermal radiation from the process zone during the cutting process is captured with a size of 256 × 256 px2 at sample rates of 20 × 103 fps. The kerf is recorded with a spectral sensitivity between 400 and 700 nm, without external illumination, which enables the melt to be observed in the range of the visual spectrum. The vision transformer model, which is used for image classification, splits the image into patches, linearly embedded with an added position embedding, and fed to a standard transformer encoder. For training the model, a set of images was labeled for the respective classes of a complete, incomplete, and impending incomplete cut. With the trained model, incomplete cuts in steel and aluminum can then be recognized and impending incomplete cuts in steel can be predicted in advance.

The effects of self-explanation on game-based learning: Evidence from eye-tracking analyses

The purpose of this study was to examine the effect of self-explanation prompts on game performance using eye-tracking techniques. We adopted an experimental design for the study. A total of 40 4th graders participated and were randomly assigned to either the experimental or control group. While the experimental group played a computer game with self-explanation prompts, the control group played the same game without any prompts. A Tobii 4C eye tracker with a sampling rate of 90 Hz was used to record the eye movements of the participants while they were playing the game. A pre-test and post-test were used to assess the participants’ understanding of the target concepts of the game before and after their game-playing, respectively. The results indicated an interaction effect between self-explanation and prior knowledge on the learning outcomes. Regarding the participants with lower-level prior knowledge, the experimental group gained significantly better scores on the posttest than the control group. In contrast, with respect to the participants with higher-level prior knowledge, the self-explanation prompts did not demonstrate a positive effect on the experimental group. Moreover, the results of the lag sequential analysis provide solid evidence of the differences in visual transitional patterns between the participants with different levels of prior knowledge while they were reacting to the self-explanation prompts. These results could account for the different learning outcomes achieved by the participants with different levels of prior knowledge in the experimental group.

Soil carbon and wood decay models in Nigeria’s Niger Delta environment

Decaying of wood is a major factor in modelling global carbon emissions and their effect on climate change. When not properly considered, trees used in urban greening have been observed to cause hazards and do a disservice in terms of carbon storage due to their degradation. This degradation process is aided by species properties and climatic and biological factors, but the quantitative characteristics of this process on commonly used avenue trees in Nigeria are scarce. The decay rate of wood-block samples of six commonly used avenue trees (Azadirachta indica, Gmelina arborea, Delonix regia, Casuarina equisetifolia, Musanga cecropiodes, and Ficus elastica), as well as soil carbon changes beneath the wood blocks, were monitored under natural varying climatic conditions (Soil temperature, air temperature, relative humidity) and incidence of termite attack over a period of 16 weeks. Soil and air temperature showed a quadratic trend with decay rate, with p-values less than 0.05 and 0.10, respectively, while density and incidence of termite attack were negatively linear (p<0.05) and positively linear (p<0.01), respectively. Among the species, D. regia had the highest coefficient for predicting decay rate. Soil depth and wood density were significant predictors of soil carbon accumulation from decaying wood samples. Soil temperature and other climatic variables of a region should be considered for various tree planting and management projects to discourage the selection of trees with a high decay rate and carbon loss in the area, such as D. regia.

A Compact Time Domain Diffuse Optical Tomography System for Cortical Neuroimaging

Abstract Recent years have witnessed a rise in research utilizing neuroimaging for precision neuromedicine, but clinical translation has been hindered by scalability and cost. Time Domain functional Near Infrared Spectroscopy (TD-fNIRS), the gold standard of optical neuroimaging techniques, offers a unique opportunity in this domain since it provides superior depth sensitivity and enables resolution of absolute properties unlike its continuous wave counterparts. However, current TD systems have limited commercial availability, slow sampling rates, and sparse head coverage. Our team has overcome the technical challenges involved in developing a whole-head time-domain diffuse optical tomography (TD-DOT) system. Here, we present the system characterization results using standardized protocols and compare them to the state-of-the-art. Furthermore, we showcase the system performance in retrieving cortical activation maps during standard hemodynamic, sensory, and motor tasks. A combination of the system performance, signal quality, and ease-of-use can enable future studies aimed at investigating TD-DOT clinical applications.

Hybrid low-complexity baud-rate sampling and adaptive equalization technique for 400 G/800 G coherent metropolitan area networks

Baud-rate sampling and adaptive equalization (BSAE) techniques digitize and adaptively equalize received optical signals at the baud-rate and thus can concurrently reduce ADC and equalization power consumption compared with oversampling and fractionally-spaced adaptive equalization (OFAE) techniques operating at a higher sampling rate. Although suitable for short-reach intensity modulation-direct detection (IM-DD) based access networks or intra-datacenter networks, the BSAE techniques are generally regarded as not suitable for metropolitan area networks (MANs), owing to their limited capability to compensate for the large chromatic dispersion (CD) and in-phase/quadrature (IQ) skew distortions encountered in MANs. This constraint renders them inferior to the OFAE techniques able to compensate for arbitrary CD and IQ skew distortions. In this paper, we propose a BSAE technique combining a baud-rate frequency and time domain hybrid adaptive equalizer (AEQ) and Nyquist filtering for dynamic 400 G/800 G coherent MANs. Numerical simulations and experiments show that the BSAE technique can overcome the limitations and compensate for large CD and IQ skew distortions encountered in 400 G/800 G coherent MANs with spans up to 120 km. Furthermore, compared with the current state-of-the-art BSAE and OFAE techniques, the proposed BSAE technique can reduce the equalization computation complexity by about 40% and 80%, respectively, while maintaining a superior performance as the OFAE techniques. These merits make it a highly attractive solution for the dynamic 400 G/800 G coherent MANs.

Self-rerouting sensor network for electronic skin resilient to severe damage

We propose a network architecture for electronic skin with an extensive sensor array—crucial for enabling robots to perceive their environment and interact effectively with humans. Fault tolerance is essential for electronic skins on robot exteriors. Although self-healing electronic skins targeting minor damages are studied using material-based approaches, substantial damages such as severe cuts necessitate re-establishing communication pathways, traditionally performed with high-functionality microprocessor sensor nodes. However, this method is costly, increases latency, and boosts power usage, limiting scalability for large, nuanced sensation-mimicking sensor arrays. Our proposed system features sensor nodes consisting of only a few dozen logic circuits, enabling them to autonomously reconstruct reading pathways. These nodes can adapt to topological changes within the sensor network caused by disconnections and reconnections. Testing confirms rapid reading times of only a few microseconds and power consumption of 1.88 μW/node at a 1 kHz sampling rate. This advancement significantly boosts robots’ collaborative potential with humans.