Simple Integration Research Articles

Boolean Computation in Single-Transistor Neuron.

Brain neurons exhibit far more sophisticated and powerful information-processing capabilities than the simple integrators commonly modeled in neuromorphic computing. A biological neuron can in fact efficiently perform Boolean algebra, including linear nonseparable operations. Traditional logic circuits require more than a dozen transistors combined as NOT, AND, and OR gates to implement XOR. Lacking biological competency, artificial neural networks require multilayered solutions to exercise XOR operation. Here, it is shown that a single-transistor neuron, harnessing the intrinsic ambipolarity of graphene and ionic filamentary dynamics, can enable in situ reconfigurable multiple Boolean operations from linear separable to linear nonseparable in an ultra-compact design. By leveraging the spatiotemporal integration of inputs, bio-realistic spiking-dependent Boolean computation is fully realized, rivaling the efficiency of a human brain. Furthermore, a soft-XOR-based neural network via algorithm-hardware co-design, showcasing substantial performance improvement, is demonstrated. These results demonstrate how the artificial neuron, in the ultra-compact form of a single transistor, may function as a powerful platform for Boolean operations. These findings are anticipated to be a starting point for implementing more sophisticated computations at the individual transistor neuron level, leading to super-scalable neural networks for resource-efficient brain-inspired information processing.

Flexible electronic-photonic 3D integration from ultrathin polymer chiplets

Integrating flexible electronics and photonics can create revolutionary technologies, but combining these components on a single polymer device has been difficult, particularly for high-volume manufacturing. Here, we present a robust chiplet-level heterogeneous integration of polymer-based circuits (CHIP), where ultrathin polymer electronic and optoelectronic chiplets are vertically bonded at room temperature and shaped into application-specific forms with monolithic Input/Output (I/O). This process was used to develop a flexible 3D integrated optrode with high-density microelectrodes for electrical recording, micro light-emitting diodes (μLEDs) for optogenetic stimulation, temperature sensors for bio-safe operations, and shielding designs to prevent optoelectronic artifacts. CHIP enables simple, high-yield, and scalable 3D integration, double-sided area utilization, and miniaturization of connection I/O. Systematic characterization demonstrated the scheme’s success and also identified frequency-dependent origins of optoelectronic artifacts. We envision CHIP being applied to numerous polymer-based devices for a wide range of applications.

Synergistic effects of MXene support and cobalt salts in dye-sensitized photocatalytic hydrogen generation

This study introduces an approach to photocatalytic hydrogen production through a dye-sensitized photocatalytic system employing MXene (Ti3C2Tx) and a non-noble cobalt metal catalyst. It was demonstrated that simple integration of eosin Y, Ti3C2Tx and cobalt salt (CoSO4) significantly enhances the photocatalytic hydrogen evolution, outperforming the corresponding system that does not include Ti3C2Tx. The key to this enhanced performance lies in the unique properties of MXene material, which facilitates effective electron transfer and acts as a support for dye and catalyst. The successful well-dispersed decoration of small (2–3 nm) cobalt-based nanoparticles on the Ti3C2Tx sheet via in situ photodeposition was confirmed by transmission electron microscopy (TEM) and X-ray Photoelectron Spectroscopy (XPS). The optimal hydrogen production rates were achieved with a Co to Ti3C2Tx mass ratio of 15%. This optimized interaction results in a hydrogen evolution rate of 40.1 mmol h−1 g−1 and an apparent quantum efficiency (AQE) of 35.4% at 505 nm. These findings highlight the potential of Ti3C2Tx as a versatile component in photocatalytic systems, particularly effective when paired with economically viable, earth-abundant catalysts like cobalt.

Sparse-spike seismic inversion with semismooth newton algorithm solver

Seismic prospecting has been widely used in the exploration and development of underground geological resources, such as mineral products (e.x., coal, uranium deposit), oil and gas, groundwater, and so forth. Seismic impedance is a physical characteristic parameter of underground formation, which can be used in lithologic classification, rock characterization, stratigraphic correlation, and further mineral reservoir prediction, reserve estimation, and so forth. To estimate impedance from seismic data, one must perform reflectivity series inversion first. Under a simple exponential integration transformation, the reflectivity series can give the final estimated impedance. Sparse-spike seismic inversion is the most common method to obtain reflectivity series with high resolution. It adopts a sparse regularization to impose sparsity on reflectivity series. From sparse reflectivity series, the final estimated impedance has blocky features to make formation interfaces and geological edges precise, which is very important to accurately delineate the distribution range of mineral resources. The development of sparse-spike seismic inversion is still facing major challenges of fast optimization algorithms in real-life application, especially for massive seismic data in 3D case. Semismooth Newton algorithm (SNA), which is a second order mehtod and has super-linear, even quadratic convergence rate, is used to solve sparse-spike seismic inversion. The proposed algorithm has been compared with common used algorithms through a synthetic seismic trace and a 3D real seismic data volume. The results show that the proposed algorithm has faster convergence rate and fewer computation time. It provides a new effective algorithm to solve sparse-spike seismic inversion.

Simplified conservative discretization of the Cahn-Hilliard-Navier-Stokes equations

In this paper we construct a novel discretization of the Cahn-Hilliard equation coupled with the Navier-Stokes equations. The Cahn-Hilliard equation models the separation of a binary mixture. We construct a very simple time integration scheme for simulating the Cahn-Hilliard equation, which is based on splitting the fourth-order equation into two second-order Helmholtz equations. We combine the Cahn-Hilliard equation with the Navier-Stokes equations to simulate phase separation in a two-phase fluid flow in two dimensions. The scheme conserves mass and momentum and exhibits consistency between mass and momentum, allowing it to be used with large density ratios. We introduce a novel discretization of the surface tension force from the phase-field variable that has finite support around the transition region. The model has a parameter that allows it to transition from a smoothed continuum surface force to a fully sharp interface formulation. We show that our method achieves second-order accuracy, and we compare our method to previous work in a variety of experiments.

Proximity ligation-based sequencing for the identification of human papillomavirus genomic integration sites in formalin-fixed paraffin embedded oropharyngeal squamous cell carcinomas.

Human papillomavirus (HPV) infections are an increasing cause of oropharyngeal squamous cell carcinomas (OPSCC). Integration of the viral genome into the host genome is suggested to affect carcinogenesis, however, the correlation with OPSCC patient prognosis is still unclear. Research on HPV integration is hampered by current integration detection technologies and their unsuitability for formalin-fixed paraffin-embedded (FFPE) tissues. This study aims to develop and validate a novel targeted proximity-ligation based sequencing method (targeted locus amplification/capture [TLA/TLC]) for HPV integration detection in cell lines and FFPE OPSCCs. For the identification of HPV integrations, TLA/TLC was applied to 7 cell lines and 27 FFPE OPSCCs. Following preprocessing steps, a polymerase chain reaction (PCR)-based HPV enrichment was performed on the cell lines and a capture-based HPV enrichment was performed on the FFPE tissues before paired-end sequencing. TLA was able to sequence up to hundreds of kb around the target, detecting exact HPV integration loci, structural variants, and chromosomal rearrangements. In all cell lines, one or more integration sites were identified, in accordance with detection of integrated papillomavirus sequences PCR data and the literature. TLC detected integrated HPV in 15/27 FFPE OPSCCs and identified simple and complex integration patterns. In general, TLA/TLC confirmed PCR data and detected additional integration sites. In conclusion TLA/TLC reliably and robustly detects HPV integration in cell lines and FFPE OPSCCs, enabling large, population-based studies on the clinical relevance of HPV integration. Furthermore, this approach might be valuable for clonality assessment of HPV-related tumors in clinical diagnostics.

The nucleus accumbens shell: a neural hub at the interface of homeostatic and hedonic feeding.

Feeding behavior is a complex physiological process regulated by the interplay between homeostatic and hedonic feeding circuits. Among the neural structures involved, the nucleus accumbens (NAc) has emerged as a pivotal region at the interface of these two circuits. The NAc comprises distinct subregions and in this review, we focus mainly on the NAc shell (NAcSh). Homeostatic feeding circuits, primarily found in the hypothalamus, ensure the organism's balance in energy and nutrient requirements. These circuits monitor peripheral signals, such as insulin, leptin, and ghrelin, and modulate satiety and hunger states. The NAcSh receives input from these homeostatic circuits, integrating information regarding the organism's metabolic needs. Conversely, so-called hedonic feeding circuits involve all other non-hunger and -satiety processes, i.e., the sensory information, associative learning, reward, motivation and pleasure associated with food consumption. The NAcSh is interconnected with hedonics-related structures like the ventral tegmental area and prefrontal cortex and plays a key role in encoding hedonic information related to palatable food seeking or consumption. In sum, the NAcSh acts as a crucial hub in feeding behavior, integrating signals from both homeostatic and hedonic circuits, to facilitate behavioral output via its downstream projections. Moreover, the NAcSh's involvement extends beyond simple integration, as it directly impacts actions related to food consumption. In this review, we first focus on delineating the inputs targeting the NAcSh; we then present NAcSh output projections to downstream structures. Finally we discuss how the NAcSh regulates feeding behavior and can be seen as a neural hub integrating homeostatic and hedonic feeding signals, via a functionally diverse set of projection neuron subpopulations.

Extended legality of curved boundary integral method

The angular spectrum method is an efficient approach for synthesizing electromagnetic beams from planar electric field distributions. The electric field definition is restricted to a plane, which can introduce inaccuracy when applying the synthesized beam to curved surface features. The angular spectrum method can also be interpreted as a pure source method defining the field symmetrically with respect to the creation plane. Recently, we generalized that symmetric field method to arbitrary source distributions, which are valid at any point on compact, regular surface Ω in R3. We call this approach the Curved Boundary Integral method. The electromagnetic fields synthesized with this method satisfy the Helmholtz equation and are adjusted via amplitude and phase at the desired surface. The fields are obtained as a relatively simple integral. However, restrictions on where in space the synthesized field is valid were included in the mathematical proof length to avoid obscuring the main points. These restrictions can be significant depending on the shape and degree of curvature of surface Ω. In this article, we remove these restrictions so that the integral representation of the electromagnetic beam becomes valid at all points r∈R3∖Ω, with a minor restriction. Its modification can work even on Ω. We demonstrate the importance of this extended legality with a source field parametrized into the torus surface. The electromagnetic radiation of this structure would not be valid at any point in space without this extension. Finally, we show that by changing the order of integration, the field singularity at each source point is eliminated.

Numerical integration in the virtual element method with the scaled boundary cubature scheme

AbstractThe virtual element method (VEM) is a stabilized Galerkin method on meshes that consist of arbitrary (convex and nonconvex) polygonal and polyhedral elements. A crucial ingredient in the implementation of low‐ and high‐order VEM is the numerical integration of monomials and nonpolynomial functions over such elements. In this article, we apply the recently proposed scaled boundary cubature (SBC) scheme to compute the weak form integrals in various virtual element formulations over polygonal and polyhedral meshes. In doing so, we demonstrate the flexibility of the approach and the accuracy that it delivers on a broad suite of boundary‐value problems in 2D and 3D over polytopes with affine faces as well as on elements with curved boundaries. In addition, the use of the SBC scheme is exemplified in an enriched Poisson formulation of the VEM in which weakly singular functions are required to be integrated. This study establishes the SBC method as a simple, accurate and efficient integration scheme for use in the VEM.

Enhanced Ferromagnetism and Tunable Magnetic Anisotropy in a van der Waals Ferromagnet.

2D van der Waals (vdW) magnets have recently emerged as a promising material system for spintronic device innovations due to their intriguing phenomena in the reduced dimension and simple integration of magnetic heterostructures without the restriction of lattice matching. However, it is still challenging to realize Curie temperature far above room temperature and controllable magnetic anisotropy for spintronics application in 2D vdW magnetic materials. In this work, the pressure-tuned dome-like ferromagnetic-paramagnetic phase diagram in an iron-based 2D layered ferromagnet Fe3GaTe2 is reported. Continuously tunable magnetic anisotropy from out-of-plane to in-plane direction is achieved via the application of pressure. Such behavior is attributed to the competition between intralayer and interlayer exchange interactions and enhanced DOS near the Fermi level. The study presents the prominent properties of pressure-engineered 2D ferromagnetic materials, which can be used in the next-generation spintronic devices.

Parameterization of Physiologically Based Biopharmaceutics Models: Workshop Summary Report.

This Article shares the proceedings from the August 29th, 2023 (day 1) workshop "Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives". The focus of the day was on model parametrization; regulatory authorities from Canada, the USA, Sweden, Belgium, and Norway presented their views on PBBM case studies submitted by industry members of the IQ consortium. The presentations shared key questions raised by regulators during the mock exercise, regarding the PBBM input parameters and their justification. These presentations also shed light on the regulatory assessment processes, content, and format requirements for future PBBM regulatory submissions. In addition, the day 1 breakout presentations and discussions gave the opportunity to share best practices around key questions faced by scientists when parametrizing PBBMs. Key questions included measurement and integration of drug substance solubility for crystalline vs amorphous drugs; impact of excipients on apparent drug solubility/supersaturation; modeling of acid-base reactions at the surface of the dissolving drug; choice of dissolution methods according to the formulation and drug properties with a view to predict the in vivo performance; mechanistic modeling of in vitro product dissolution data to predict in vivo dissolution for various patient populations/species; best practices for characterization of drug precipitation from simple or complex formulations and integration of the data in PBBM; incorporation of drug permeability into PBBM for various routes of uptake and prediction of permeability along the GI tract.

Tuning Surface Adhesion Using Grayscale Electron-beam Lithography.

Surface texturing of manufactured products tailors their properties, such as friction, adhesion, biocompatibility, or fluid interactions. However, advancements in this area are largely the result of trial-and-effort testing and generally lack a science-guided framework for determining the surface topography that will optimize performance. The present investigation explores grayscale electron-beam lithography as a means to create multiscale surface patterns to control surface performance. Here, we created and characterized a set of surface textures on a silicon wafer; the textures were superpositions of sine waves of varying wavelengths and amplitudes. First, the multiscale topography of the patterned surface was characterized, using profilometry and atomic force microscopy, to understand its fidelity to the designed-in pattern. The results of this analysis demonstrated how grayscale lithography accurately controlled the lateral size of features but was less precise on the vertical height of the surface, and also introduced inherent roughness below the scale of patterning. Second, a micromechanical tester was used to characterize the adhesion of the surfaces with large-scale polished silicon spheres. The results showed that adhesion could be tailored, with significant contribution from all of the designed-in length scales of topography. The strength of adhesion did not correlate with conventional roughness parameters but could be accurately modeled using simple numerical integration. Taken together, this investigation demonstrates the promise and challenges of grayscale e-beam lithography with multiscale patterns as a method for the tailoring of surface performance.

Composite polymer films with semiconductor nanocrystals for organic electronics and optoelectronics

Organic materials and, in particular, polymer films enhanced with certain nanocrystals have a potential for wide application in electronics and optoelectronics due to their organic flexibility, lightweight, simple integration, affordable manufacturing cost, and low environmental impact of their production. The purpose of this research is to investigate the electrical properties of polymer-based composite films containing Cd1–xCuxS nanocrystals in order to determine their prospects for use as conductive layers in organic electronics and optoelectronics. The paper contains a detailed description of the synthesis method of hybrid nanocomposite films based on peroxide reactive copolymer (PRC) with Cd1–xCuxS nanocrystals. The defect structure of the films is studied by analyzing the photoluminescence spectra. Current-voltage characteristics of the films with different Cd and Cu contents in the Cd1–xCuxS nanocrystals embedded into the polymer matrix, deposited on glass substrates are measured in the dark and under light illumination. The film conductivity is found to increase with the Cu content in the Cd1–xCuxS nanocrystals. The carrier transport corresponds to the Ohm law at low voltages and the space charge limited current (SCLC) or Poole–Frenkel mechanisms at higher ones. The conductivity of the polymer-based hybrid nanocomposite films has a weak dependence on the intensity of light illumination. The explanation of the obtained experimental results is proposed.

Strong‐Motion Broadband Displacements From Collocated Ocean‐Bottom Pressure Gauges and Seismometers

AbstractDense and broad‐coverage ocean‐bottom observation networks enable us to obtain near‐fault displacement records associated with an offshore earthquake. However, simple integration of ocean‐bottom strong‐motion acceleration records leads to physically unrealistic displacement records. Here we propose a new method using a Kalman filter to estimate coseismic displacement waveforms using the collocated ocean‐bottom seismometers and pressure gauges. First, we evaluate our method using synthetic records and then apply it to an offshore Mw 6.0 event that generated a small tsunami. In both the synthetic and real cases, our method successfully estimates reasonable displacement waveforms. Additionally, we show that the computed waveforms improve the results of the finite fault modeling process. In other words, the proposed method will be useful for estimating the details of the rupture mechanism of offshore earthquakes as a complement to onshore observations.

Prototype Alat Pengaman Sepeda Motor Berbasis Arduino Uno Terintegrasi GPS, Notifikasi dan Kontrol Melalui SMS

Motorbike theft is increasing, causing concern and losses for vehicle owners. Preventing motorbike theft can be done by creating a prototype of an innovative motorbike safety device based on Arduino Uno which integrates global positioning system (GPS) technology, notifications and distance control via short message service (SMS). This tool uses Arduino Uno as the main control brain, with a NEO-6M GPS module to obtain accurate location information. The SIM800L V2 GSM cellular communications module is integrated to transmit location data and receive commands via SMS. Passive infrared (PIR) sensors for movement detection are also implemented to detect and respond to theft attempts. The system can provide notifications to motorbike owners via SMS messages when suspicious events occur, such as unwanted movements or attempted theft. Users can control certain functions such as turning off the vehicle using a relay as an electrical breaker in the vehicle. Tests are carried out to ask about location, notification response speed and general security of the tool. Testing the tool was carried out in several steps, firstly testing the SIM 800L function to see the cellphone's access speed in receiving signals, secondly testing the GPS NEO-6M to see the speed of accessing map sending, thirdly testing when the motorbike was moved to a certain point. This will see how fast the tool is designed to send signals via SMS. Based on tests carried out, this tool provides a fast response in the range of 8 to 80 seconds. Test results show that this tool can provide an effective handheld and innovative solution to improve motorbike safety through the advantage of simple but efficient technological integration.

Waveguide-integrated van der Waals heterostructure photodetector on a lithium niobate on insulator platform.

Lithium niobate (LN) photonics has gained significant interest for their distinct material properties. However, achieving monolithically integrated photodetectors on lithium niobate on an insulator (LNOI) platform for communication wavelengths remains a challenge due to the large bandgap and extremely low electrical conductivity of LN material. A two-dimensional (2D) material photodetector is an ideal solution for LNOI photonics with a strong light-matter interaction and simple integration technique. In this work, a van der Waals heterostructure photodiode composed of a p-type black phosphorus layer and an n-type MoS2 layer is successfully demonstrated for photodetection at communication wavelengths on a LNOI platform. The LNOI waveguide-integrated BP-MoS2 photodetector exhibits a dark current as low as 0.21 nA and an on/off ratio exceeding 200 under zero voltage bias with an incident power of 13.93 µW. A responsivity as high as 1.46 A/W is achieved at -1 V bias with a reasonable dark current around 2.33 µA. With the advantages of high responsivity, low dark current, and simple fabrication process, it is promising for the monolithically integrated photodetector application for LNOI photonic platforms at communication wavelengths.

Multimodal Transformer Model Using Time-Series Data to Classify Winter Road Surface Conditions.

This paper proposes a multimodal Transformer model that uses time-series data to detect and predict winter road surface conditions. For detecting or predicting road surface conditions, the previous approach focuses on the cooperative use of multiple modalities as inputs, e.g., images captured by fixed-point cameras (road surface images) and auxiliary data related to road surface conditions under simple modality integration. Although such an approach achieves performance improvement compared to the method using only images or auxiliary data, there is a demand for further consideration of the way to integrate heterogeneous modalities. The proposed method realizes a more effective modality integration using a cross-attention mechanism and time-series processing. Concretely, when integrating multiple modalities, feature compensation through mutual complementation between modalities is realized through a feature integration technique based on a cross-attention mechanism, and the representational ability of the integrated features is enhanced. In addition, by introducing time-series processing for the input data across several timesteps, it is possible to consider the temporal changes in the road surface conditions. Experiments are conducted for both detection and prediction tasks using data corresponding to the current winter condition and data corresponding to a few hours after the current winter condition, respectively. The experimental results verify the effectiveness of the proposed method for both tasks. In addition to the construction of the classification model for winter road surface conditions, we first attempt to visualize the classification results, especially the prediction results, through the image style transfer model as supplemental extended experiments on image generation at the end of the paper.

Operando Battery Monitoring: Lab‐on‐Fiber Electrochemical Sensing Technologies

AbstractSuccess in the development of next‐generation rechargeable batteries is attained by achieving low cost, high energy density, and long cycling life. Battery optimization is challenging due to the complicated processes involving material selection and optimal utilization of cell components. Battery performance and status during the charging/discharging cycle depend on the complicated interdependence of battery design and operational parameters. Monitoring techniques must be able to detangle the hidden high‐value information, including states of charge, health estimations, and operational guidance, as well as provide non‐electrochemical early failure indicators. Fiber–optic battery monitoring methods, which are advantageous because of their low cost, compactness, remote sensing capabilities, and simple integration without interfering with internal chemistry, are recently reported. The convergence of fiber optic technology and smart battery platforms promises to revolutionize the industry. The introduction of electrochemical lab‐on‐fiber sensing technology to continuously operando monitor the performance, health, and safety status of batteries will promote more reliable energy storage systems. This review highlights recent advancements in, and associated benefits of, electrochemical fiber grating battery sensing. This powerful sensing technology's potential to make possible the next generation of sustainable energy storage, and discuss future directions for improving battery sustainability is showcased.

Development and comprehensive evaluation of a dual-port textile UWB MIMO antenna for biomedical use

In this paper, a textile two-port multi-input multi-output (MIMO) half-circle antenna with corrugated borders is designed and fully analyzed for nearfield ultra-wideband biomedical diagnostic applications. The orthogonal polarization technique is introduced for mutual coupling reduction, signal quality, and imaging accuracy improvement. A low pass filter with significant out-of-band rejection is inserted between the two MIMO structural elements to improve the isolation from element to element. For simple system integration, A 50 ohms feed coplanar waveguide is suggested for each element. The entire antenna is constructed using textile materials, with the radiating element composed of conductor fabric. The substrate, on the other hand, is crafted from cotton material which possesses a relative permittivity of and a tan δ value of 0.025. The size of each antenna element has low-profile dimensions of 40 × 40 × 0.3 mm3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${mm}^{3}$$\\end{document}. The measured results obtained demonstrate an extremely broad bandwidth extends from 2.5 GHz to 12 GHz. Omnidirectional radiation pattern is obtained, with 6 dBi maximum gain and 96% efficiency. In order to ensure flexibility, a range of bending conditions were analyzed, and the durability was assessed through wash ability testing. Safety was confirmed by measuring the specific absorption rate. Furthermore, time domain and MIMO performance assessments were performed to ensure its suitability for imaging systems.

Instance redistribution-based label integration for crowdsourcing

Crowdsourcing provides an inexpensive solution to employ crowd workers labeling instances, and hence each instance is labeled with a multiple noisy label set instead of its true label. Label integration aims to infer a true label from its multiple noisy label set. However, existing fine-tuned methods increase the model complexity while enhancing the performance of label integration. Therefore, it is a challenge to search for a simple but efficient label integration method. Meeting this challenge, this paper proposes instance redistribution-based label integration (IRLI), a novel method for label integration. Firstly, from the label view, we estimate the probability of an instance belonging to each class based on its multiple noisy label set and obtain a multiple noisy label distribution vector. Secondly, from the attribute view, we reestimate the probability of an instance belonging to each class based on its attribute set and obtain an instance redistribution vector. Finally, we combine the multiple noisy label distribution vector and the instance redistribution vector of each instance to infer its integrated label. Comprehensive experimental results on both simulated and real-world crowdsourced datasets validate the superiority of IRLI.